ATF3 Expression in the corpus luteum: possible role in luteal regression
Technology Transfer Automated Retrieval System (TEKTRAN)
The present study investigated the induction and possible role of activating transcription factor 3 (ATF3) in the corpus luteum. Postpubertal cattle were treated at midcycle with prostaglandin F2alpha(PGF) for 0–4 hours. Luteal tissue was processed for immunohistochemistry, in situ hybridization, an...
Fang, Ling; Gu, Caiyun; Liu, Xinyu; Xie, Jiabin; Hou, Zhiguo; Tian, Meng; Yin, Jia; Li, Aizhu; Li, Yubo
2017-01-01
Primary dysmenorrhea (PD) is a common gynecological disorder which, while not life-threatening, severely affects the quality of life of women. Most patients with PD suffer ovarian hormone imbalances caused by uterine contraction, which results in dysmenorrhea. PD patients may also suffer from increases in estrogen levels caused by increased levels of prostaglandin synthesis and release during luteal regression and early menstruation. Although PD pathogenesis has been previously reported on, these studies only examined the menstrual period and neglected the importance of the luteal regression stage. Therefore, the present study used urine metabolomics to examine changes in endogenous substances and detect urine biomarkers for PD during luteal regression. Ultra performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry was used to create metabolomic profiles for 36 patients with PD and 27 healthy controls. Principal component analysis and partial least squares discriminate analysis were used to investigate the metabolic alterations associated with PD. Ten biomarkers for PD were identified, including ornithine, dihydrocortisol, histidine, citrulline, sphinganine, phytosphingosine, progesterone, 17-hydroxyprogesterone, androstenedione, and 15-keto-prostaglandin F2α. The specificity and sensitivity of these biomarkers was assessed based on the area under the curve of receiver operator characteristic curves, which can be used to distinguish patients with PD from healthy controls. These results provide novel targets for the treatment of PD. PMID:28098892
Luteal blood flow and luteal function
Takasaki, Akihisa; Tamura, Hiroshi; Taniguchi, Ken; Asada, Hiromi; Taketani, Toshiaki; Matsuoka, Aki; Yamagata, Yoshiaki; Shimamura, Katsunori; Morioka, Hitoshi; Sugino, Norihiro
2009-01-01
Background Blood flow in the corpus luteum (CL) is associated with luteal function. The present study was undertaken to investigate whether luteal function can be improved by increasing CL blood flow in women with luteal phase defect (LFD). Methods Blood flow impedance in the CL was measured by transvaginal color-pulsed-Doppler-ultrasonography and was expressed as a resistance index (RI). The patients with both LFD [serum progesterone (P) concentrations < 10 ng/ml during mid-luteal phase] and high CL-RI (≥ 0.51) were given vitamin-E (600 mg/day, n = 18), L-arginine (6 g/day, n = 14) as a potential nitric oxide donor, melatonin (3 mg/day, n = 13) as an antioxidant, or HCG (2,000 IU/day, n = 10) during the subsequent menstrual cycle. Results In the control group (n = 11), who received no medication to increase CL blood flow, only one patient (9%) improved in CL-RI and 2 patients (18%) improved in serum P. Vitamin-E improved CL-RI in 15 patients (83%) and improved serum P in 12 patients (67%). L-arginine improved CL-RI in all the patients (100%) and improved serum P in 10 patients (71%). HCG improved CL-RI in all the patients (100%) and improved serum P in 9 patients (90%). Melatonin had no significant effect. Conclusion Vitamin-E or L-arginine treatment improved luteal function by decreasing CL blood flow impedance. CL blood flow is a critical factor for luteal function. PMID:19144154
Mifepristone for luteal phase contraception.
Croxatto, Horacio B
2003-12-01
The concept of luteal phase contraception and the use of mifepristone in clinical trials, which allows for testing of its validity, as well as clinical pharmacological research designed to understand its mode of action, are reviewed. Early luteal phase administration has a variety of morphological, physiological and biochemical effects on the endometrium that are likely to interfere with embryonic-endometrial interactions. In fact, specifically designed pilot clinical trials as well as data derived from emergency contraception studies indicate that early luteal phase administration of mifepristone is highly effective in preventing pregnancy, with minimal disturbance of hormonal parameters or menstrual cyclicity. Mid and late luteal phase administration of mifepristone at doses above 25 mg are highly effective in inducing endometrial bleeding in nonconceptional cycles. However, administration of mifepristone within the period between implantation and expected menses fails to induce bleeding in a significant proportion of cases, and furthermore the bleeding induced does not insure the termination of pregnancy. While the data suggest there is potential for a once-a-month contraceptive pill, it is likely that no molecule endowed with partial agonistic properties, like mifepristone, will completely and reliably suppress the essential functions of progesterone in order to achieve contraceptive efficacy comparable to that of modern contraceptive methods.
Emerging roles of immune cells in luteal angiogenesis.
Shirasuna, Koumei; Shimizu, Takashi; Matsui, Motozumi; Miyamoto, Akio
2013-01-01
In the mammalian ovary, the corpus luteum (CL) is a unique transient endocrine organ displaying rapid angiogenesis and time-dependent accumulation of immune cells. The CL closely resembles 'transitory tumours', and the rate of luteal growth equals that of the fastest growing tumours. Recently, attention has focused on multiple roles of immune cells in luteal function, not only in luteolysis (CL disruption by immune responses involving T lymphocytes and macrophages), but also in CL development (CL remodelling by different immune responses involving neutrophils and macrophages). Neutrophils and macrophages regulate angiogenesis, lymphangiogenesis, and steroidogenesis by releasing cytokines in the CL. In addition, functional polarisation of neutrophils (proinflammatory N1 vs anti-inflammatory N2) and macrophages (proinflammatory M1 vs anti-inflammatory M2) has been demonstrated. This new concept concurs with the phenomenon of immune function within the luteal microenvironment: active development of the CL infiltrating anti-inflammatory N2 and M2 versus luteal regression together with proinflammatory N1 and M1. Conversely, excessive angiogenic factors and leucocyte infiltration result in indefinite disordered tumour development. However, the negative feedback regulator vasohibin-1 in the CL prevents excessive tumour-like vasculogenesis, suggesting that CL development has well coordinated time-dependent mechanisms. In this review, we discuss the physiological roles of immune cells involved in innate immunity (e.g. neutrophils and macrophages) in the local regulation of CL development with a primary focus on the cow.
Transforming growth factor Beta 1 stimulates profibrotic activities of luteal fibroblasts in cows.
Maroni, Dulce; Davis, John S
2012-11-01
Luteolysis is characterized by angioregression, luteal cell apoptosis, and remodeling of the extracellular matrix characterized by deposition of collagen 1. Transforming growth factor beta 1 (TGFB1) is a potent mediator of wound healing and fibrotic processes through stimulation of the synthesis of extracellular matrix components. We hypothesized that TGFB1 stimulates profibrotic activities of luteal fibroblasts. We examined the actions of TGFB1 on luteal fibroblast proliferation, extracellular matrix production, floating gel contraction, and chemotaxis. Fibroblasts were isolated from the bovine corpus luteum. Western blot analysis showed that luteal fibroblasts expressed collagen 1 and prolyl 4-hydroxylase but did not express markers of endothelial or steroidogenic cells. Treatment of fibroblasts with TGFB1 stimulated the phosphorylation of SMAD2 and SMAD3. [(3)H]thymidine incorporation studies showed that TGFB1 caused concentration-dependent reductions in DNA synthesis in luteal fibroblasts and significantly (P < 0.05) reduced the proliferative effect of FGF2 and fetal calf serum. However, TGFB1 did not reduce the viability of luteal fibroblasts. Treatment of luteal fibroblasts with TGFB1 induced the expression of laminin, collagen 1, and matrix metalloproteinase 1 as determined by Western blot analysis and gelatin zymography of conditioned medium. TGFB1 increased the chemotaxis of luteal fibroblasts toward fibronectin in a transwell system. Furthermore, TGFB1 increased the fibroblast-mediated contraction of floating bovine collagen 1 gels. These results suggest that TGFB1 contributes to the structural regression of the corpus luteum by stimulating luteal fibroblasts to remodel and contract the extracellular matrix.
Thompson, I M; Ozawa, M; Bubolz, J W; Yang, Q; Dahl, G E
2011-05-01
In the present study, we performed quantitative reverse-transcription PCR (qPCR) to examine changes in gene expression of prolactin receptor (long form: l-PRLR; short form: s-PRLR) and 20α-hydroxysteroid dehydrogenase (20α-HSD; EC 1.1.1.149) in the bovine corpus luteum (CL) throughout the estrous cycle and pregnancy. Western blotting was used to determine protein abundance. Bovine CL were collected and luteal stages (n = 6/stage) were classified by macroscopic observation as early (d 1 to 4 after ovulation), mid (d 5 to 10), late (d 11 to 17), and regressing (d 18 to 20). A CL of pregnancy (n = 6) was determined by the presence of conceptus (d 28 to term). The mRNA for both forms of PRLR were expressed at all the luteal stages. Expression of s-PRLR and l-PRLR mRNA was less (P < 0.01) during early and regressing luteal stages compared with mid and late stages. Expression of s-PRLR mRNA in CL of pregnancy was greater (P < 0.01) than early, mid, and regressing CL and did not differ from late luteal stage expression. A greater (P < 0.01) expression of l-PRLR mRNA was observed in pregnant vs. early and regressing CL. In addition, qPCR showed the presence of 20α-HSD mRNA during all luteal stages of the estrous cycle, with the greatest (P < 0.01) expression observed in the regressing luteal stage. Western blotting revealed protein abundance of both PRLR isoforms during all luteal stages and pregnancy, with a predominance of the s-PRLR protein. Densitometry analysis indicated that protein abundances of s-PRLR were greater (P < 0.05) than l-PRLR during early, mid, and late luteal stages and did not differ during the regressing luteal stage. Protein abundances of 20α-HSD were least (P < 0.05) during the early luteal stage. In conclusion, results of the current study suggest a possible involvement of PRLR, especially s-PRLR, in the regulation of progesterone secretion and metabolism during the bovine estrous cycle and pregnancy.
Evaluation of bovine luteal blood flow by using color Doppler ultrasonography.
Lüttgenau, J; Bollwein, H
2014-04-01
Since luteal vascularization plays a decisive role for the function of the corpus luteum (CL), the investigation of luteal blood flow (LBF) might give valuable information about the physiology and patho-physiology of the CL. To quantify LBF, usually Power mode color Doppler ultrasonography is used. This method detects the number of red blood cells moving through the vessels and shows them as color pixels on the B-mode image of the CL. The area of color pixels is measured with computer-assisted image analysis software and is used as a semiquantitative parameter for the assessment of LBF. Although Power mode is superior for the evaluation of LBF compared to conventional color Doppler ultrasonography, which detects the velocity of blood cells, it is still not sufficiently sensitive to detect the blood flow in the small vessels in the center of the bovine CL. Therefore, blood flow can only be measured in the bigger luteal vessels in the outer edge of the CL. Color Doppler ultrasonographic studies of the bovine estrous cycle have shown that plasma progesterone (P4) concentration can be more reliably predicted by LBF than by luteal size (LS), especially during the CL regression. During the midluteal phase, cows with low P4 level showed smaller CL, but LBF, related to LS, did not differ between cows with low and high P4 levels. In contrast to non-pregnant cows, a significant rise in LBF was observed three weeks after insemination in pregnant cows. However, LBF was not useful for an early pregnancy diagnosis due to high LBF variation among cows. When the effects of an acute systemic inflammation and exogenous hormones on the CL are examined, the LBF determination is more sensitive than LS assessment. In conclusion, color Doppler ultrasonography of the bovine CL provides additional information on luteal function compared to measurements of LS and plasma P4, but its value as a parameter concerning assessment of fertility in cows has to be clarified.
Effects of testosterone and 5alpha-dihydrotestosterone on luteal lifespan in dairy heifers.
Silvia, W J; Jacobs, A L; Hayes, S H
1989-11-01
Endogenous concentrations of testosterone increase approximately 7 d prior to estrus in cattle and goats. Inhibition of testosterone synthesis results in a delay of luteal regression in both species. The purpose of this experiment was to determine if treatment with testosterone or 5alpha-dihydrotestosterone (DHT), 2 to 6 d prior to the endogenous rise in testosterone, would result in premature luteal regression. Sixteen heifers were randomly assigned to one of three treatment groups: 1) Control (n = 6); 2) testosterone (100 mug, n = 5); or 3) DHT (100 mug, n = 5). Each heifer received a single injection of the appropriate steriod on Day 8, 9, 10, 11 or 12 post estrus. Jugular venous blood samples were collected at frequent intervals for 24 h to quantify testosterone, and then daily for 14 d to quantify progesterone. Concentrations of testosterone increased within 15 min of injection of testosterone, and reached a maximum at 30 min. Concentrations were maintained at > 2 ng/ml throughout the first 24 h after injection. Based on concentrations of progesterone, neither androgen had any effect on the lifespan of the corpus luteum or the level of luteal function.
Treatment of luteal phase defects in assisted reproduction.
Muñoz, Elkin; Taboas, Esther; Portela, Susana; Aguilar, Jesús; Fernandez, Iria; Muñoz, Luis; Bosch, Ernesto
2013-07-01
Abnormal luteal function is a common issue in assisted reproduction techniques associated with ovarian stimulation probably due to low levels of LH in the middle and in the late luteal phase. This defect seems to be associated with supraphysiological steroid levels at the end of follicular phase. The luteal phase insufficiency has not got a diagnostic test which has proven reliable in a clinical setting. Luteal phase after ovarian stimulation becomes shorter and insufficient, resulting in lower pregnancy rates. Luteal phase support with progesterone or hCG improves pregnancy outcomes and no differences are found among different routes of administration. However, hCG increases the risk of ovarian hyperstimulation syndrome. In relation to the length of luteal support, the day of starting it remains controversial and it does not seem necessary to continue once a pregnancy has been established. After GnRHa triggering ovulation, intensive luteal support or hCG bolus can overcome the defect in luteal phase, but more studies are needed to show the LH utility as support.
Transcriptomes of bovine ovarian follicular and luteal cells
Technology Transfer Automated Retrieval System (TEKTRAN)
RNA expression analysis was performed on four somatic ovarian cell types using a gene array panel: the granulosa cells (GCs) and theca cells (TCs) of the dominant follicle and the large luteal cells (LLCs) and small luteal cells (SLCs) of the corpus luteum. The normalized linear microarray data was ...
Carnaby, Kim; Painer, Johanna; Söderberg, Arne; Gavier-Widèn, Dolores; Göritz, Frank; Dehnhard, Martin; Jewgenow, Katarina
2012-10-01
Lynx presents a unique sexual cycle with persistent corpora lutea (CLs) and elevated serum progesterone (P₄) throughout parturition and lactation. In other mammals, CLs normally disintegrate after parturition, therefore the aim of our study was to characterise the annual life cycle of lynx CLs. Ovaries from Eurasian lynxes were obtained from the National Veterinary Institute in Sweden, where tissues from killed lynx were stored at -20 °C. Ovaries from 66 animals were weighed; each corpus luteum was segmented for histology and hormone analysis. Ovary and CLs weights were constant throughout the year, peaking during pregnancy. In non-pregnant lynxes, the seasonal level of intraluteal steroids was steady for P₄ (3.2±1.9 s.d. μg/g, n=53) and total oestrogens (18.3±15.5 s.d. ng/g, n=53). Within histology slides, structurally intact luteal cells were found throughout the year with the highest incidence in March/April; evidence of luteal regression was predominantly found in post-breeding season. Ovaries from pregnant animals contained two types of CLs. Group A was bigger in size with large luteal cells (P₄, 72.3±65.4 s.d. μg/g; oestrogen, 454.0±52.4 s.d. ng/g). In contrast, group B were smaller, with greater luteal regression and lower steroid concentrations (P₄, 8.3±2.9 s.d. μg/g; oestrogen, 31.5±20.4 s.d. ng/g). Our results suggest that structural luteolysis proceeds throughout the year and into next breeding cycle, resulting in two CLs types on the same ovary.
Isolation and functional aspects of free luteal cells
Luborsky, J.L.; Berhrman, H.R.
1985-01-01
Methods of luteal cell isolation employ enzymatic treatment of luteal tissue with collagenase and deoxyribonuclease. Additional enzymes such as hyaluronidase or Pronase are also used in some instances. Isolated luteal cells retain the morphological characteristics of steroid secreting cells after isolation. They contain mitochondria, variable amounts of lipid droplets, and an extensive smooth endoplasmic reticulum. Isolated luteal cells have been used in numerous studies to examine the regulation of steriodogenesis by luteinizing hormone (LH). LH receptor binding studies were employed to quantitate specific properties of hormone-receptor interaction in relation to cellular function. Binding of (/sup 125/I)LH to bovine luteal cells and membranes was compared and it was concluded that the enzymatic treatment used to isolate cells did not change the LH receptor binding kinetics.
Wiles, Jessica R.; Katchko, Robin A.; Benavides, Elizabeth A.; O’Gorman, Chad W.; Escudero, Jean M.; Keisler, Duane H.; Stanko, Randy L.; Garcia, Michelle R.
2014-01-01
Fibroblast growth factor 2 (FGF2), angiopoietin 1 (Ang1), and vascular endothelial growth factor (VEGF) are angiogenic factors implicated in the vascular development of the corpus luteum (CL). Each factor is regulated or influenced by leptin in non-ovarian tissues. Moreover, leptin and its receptor, ObRb, have been identified in luteal tissue throughout the luteal phase. Therefore, leptin is hypothesized to influence luteal vasculature through the regulation of FGF2, Ang1, and VEGF. Multiparous, cycling crossbred female goats (does) were allocated to early (n=12), mid (n=8), and late (n=11) stages of the luteal phase for CL collection. Luteal tissue was harvested and either snap frozen in liquid N2, paraffin embedded, or cultured with leptin (0, 10−12, 10−11, 10−10, 10−9, 10−8 M). Tissue was analyzed for FGF2, Ang1, VEGF, ObRb, and leptin expression. Angiopoietin 1, FGF2, VEGF expression was higher (P≤0.001) in the mid-luteal stage than the early stage. Expression decreased (P≤0.001) during the late luteal stage with the exception of VEGF, which remained elevated. In contrast, leptin and ObRb were lowest (P≤0.003) during the mid-luteal stage compared to the early and late stages. All factors were detected in and/or around vessels in early stage tissue compared to mid and late stages. Leptin stimulated (P≤0.02) Ang1, FGF2, and VEGF expression only in early stage luteal cultures. Collectively, these data provide evidence that leptin may be involved in the luteal angiogenic process during the early stage of CL formation. PMID:24962614
The bovine luteal histological composition: a topographic point of view.
Cools, S; Van den Broeck, W; De Vliegher, S; Piepers, S; Opsomer, G
2013-04-01
High-yielding dairy cows are struggling with a high incidence of embryonic loss, among others caused by an insufficient peripheral progesterone concentration which for its part might be associated with an impaired luteal progesterone production. This impaired capacity to produce progesterone might be reflected in the histology of the gland. The aim of the present pilot study was the assessment of the variation in cell density within a bovine luteal gland (LG), to examine whether it is possible to analyse histologically the functionality of the gland based on one single tissue sample. Six LGs (stage II or III) were harvested out of just as many healthy cows at the slaughterhouse. The luteal cell density was assessed by calculating the nuclear density (ND) of the different luteal cell types on haematoxylin-eosin-stained histological sections from a number of topographic regions evenly spread throughout the glands, to give an overview of the pattern of cellular distribution within the whole gland. Cells were differentiated into 'large luteal cells', 'small luteal cells' and 'non-steroidogenic cells'. Results show that the cellular density, within a tissue sample is not significantly influenced by its location in relation to the gland's equatorial plane. However, the position with respect to the polar axis of the gland has a decisive effect, as the ND is significantly higher (p < 0.05) in the peripheral regions (outer zone) when compared with the central regions (inner zone) of the gland, and this counts for all three cell types.
The effect of metritis on luteal function in dairy cows
2013-01-01
Background Disturbed uterine involution impairs ovarian function in the first weeks after calving. This study analyzed the long-term effect of metritis on luteal function of 47 lactating Holstein-Friesian cows during the first four postpartum estrous cycles. Cows with abnormal uterine enlargement and malodorous lochia were classified as having metritis (group M, n = 18), and all others were considered healthy (group H, n = 29). Luteal size was measured once between days 9 and 13 of the first (group H, n = 11; group M, n = 12), second (group H, n = 23; group M, n = 18) and fourth (group H, n = 11; group M, n = 7) postpartum luteal phases. Serum progesterone concentration was measured at the same time. Sixteen cows (group H, n = 9; group M, n = 7) underwent transvaginal luteal biopsy for gene expression analysis of steroidogenic regulatory proteins during the second and fourth cycles. Cows with persistence of the corpus luteum (CL) underwent determination of luteal size, luteal biopsy and serum progesterone measurement once between days 29 and 33, followed by prostaglandin treatment to induce luteolysis. The same procedures were repeated once between days 9 and 13 of the induced cycle. Results The cows in group M had smaller first-cycle CLs than the cows in group H (p = 0.04), but progesterone concentrations did not differ between groups. Luteal size, progesterone concentration and gene expression did not differ between the two groups during the second and fourth cycles. Compared with healthy cows (10%), there was a trend (p = 0.07) toward a higher prevalence of persistent CLs in cows with metritis (33%). Persistent CLs were limited to the first cycle. Persistent CLs and the induced cyclic CLs did not differ with regard to the variables investigated. Conclusions An effect of metritis on luteal activity was apparent in the first postpartum estrous cycle. However, after the first postpartum cycle, no differences occurred
Notch Signaling Pathway Regulates Progesterone Secretion in Murine Luteal Cells.
Wang, Jing; Liu, Shuangmei; Peng, Lichao; Dong, Qiming; Bao, Riqiang; Lv, Qiulan; Tang, Min; Hu, Chuan; Li, Gang; Liang, Shangdong; Zhang, Chunping
2015-10-01
Notch signaling is an evolutionarily conserved pathway, which involves in various cell life activities. Other studies and our report showed that the Notch signaling plays very important role in follicle development in mammalian ovaries. In luteal cells, Notch ligand, delta-like ligand 4, is involved in normal luteal vasculature. In this study, murine luteal cells were cultured in vitro and treated with Notch signaling inhibitors, L-658,458 and N-[N-(3,5-difluorophenacetyl)-l-alanyl]-S-phenylglycinet-butyl ester (DAPT). We found that L-658,458 and DAPT treatment decrease basal and human chorionic gonadotropin (hCG)-stimulated progesterone secretion. On the contrary, overexpression of intracellular domain of Notch3 increased basal and hCG-stimulated progesterone secretion. Further studies demonstrated that Notch signaling regulated the expression of steroidogenic acute regulatory protein and CYP11A, 2 key enzymes for progesterone synthesis. In conclusion, Notch signaling plays important role in regulating progesterone secretion in murine luteal cells.
A novel physiological culture system that mimics luteal angiogenesis.
Robinson, R S; Hammond, A J; Mann, G E; Hunter, M G
2008-03-01
Luteal inadequacy is a major cause of poor embryo development and infertility. Angiogenesis, the formation of new blood vessels, is an essential process underpinning corpus luteum (CL) development and progesterone production. Thus, understanding the factors that regulate angiogenesis during this critical time is essential for the development of novel strategies to alleviate luteal inadequacy and infertility. This study demonstrates the development of a physiologically relevant primary culture system that mimics luteal angiogenesis. This system incorporates all luteal cell types (e.g. endothelial, steroidogenic cells, fibroblasts and pericytes). Using this approach, endothelial cells, identified by the specific marker von Willebrand factor (VWF), start to form clusters on day 2, which then proliferate and develop thread-like structures. After 9 days in culture, these tubule-like structures lengthen, thicken and form highly organized intricate networks resembling a capillary bed. Development of the vasculature was promoted by coating wells with fibronectin, as determined by image analysis (P<0.001). Progesterone production increased with time and was stimulated by LH re-enforcing the physiological relevance of the model in mimicking in vivo luteal function. LH also increased the area stained positively for VWF by twofold (P<0.05). Development of this endothelial cell network was stimulated by fibroblast growth factor 2 and vascular endothelial growth factor A, which increased total area of VWF positive staining on day 9, both independently (three- to fourfold; P<0.01) and in combination (tenfold; P<0.001). In conclusion, the successful development of endothelial cell networks in vitro provides a new opportunity to elucidate the physiological control of the angiogenic process in the developing CL.
Involvement of Mst1 in tumor necrosis factor-{alpha}-induced apoptosis of endothelial cells
Ohtsubo, Hideki; Ichiki, Toshihiro Imayama, Ikuyo; Ono, Hiroki; Fukuyama, Kae; Hashiguchi, Yasuko; Sadoshima, Junichi; Sunagawa, Kenji
2008-03-07
Mammalian sterile 20-kinase 1 (Mst1), a member of the sterile-20 family protein kinase, plays an important role in the induction of apoptosis. However, little is know about the physiological activator of Mst1 and the role of Mst1 in endothelial cells (ECs). We examined whether Mst1 is involved in the tumor necrosis factor (TNF)-{alpha}-induced apoptosis of ECs. Western blot analysis revealed that TNF-{alpha} induced activation of caspase 3 and Mst1 in a time- and dose-dependent manner. TNF-{alpha}-induced Mst1 activation is almost completely prevented by pretreatment with Z-DEVD-FMK, a caspase 3 inhibitor. Nuclear staining with Hoechst 33258 and fluorescence-activated cell sorting of propidium iodide-stained cells showed that TNF-{alpha} induced apoptosis of EC. Diphenyleneiodonium, an inhibitor of NADPH oxidase, and N-acetylcysteine, a potent antioxidant, also inhibited TNF-{alpha}-induced activation of Mst1 and caspase 3, as well as apoptosis. Knockdown of Mst1 expression by short interfering RNA attenuated TNF-{alpha}-induced apoptosis but not cleavage of caspase 3. These results suggest that Mst1 plays an important role in the induction of TNF-{alpha}-induced apoptosis of EC. However, positive feedback mechanism between Mst1 and caspase 3, which was shown in the previous studies, was not observed. Inhibition of Mst1 function may be beneficial for maintaining the endothelial integrity and inhibition of atherogenesis.
Love, Richard R.; Hossain, Syed Mozammel; Hussain, Md. Margub; Mostafa, Mohammad Golam; Laudico, Adriano V.; Siguan, Stephen Sixto S.; Adebamowo, Clement; Sun, Jing-zhong; Fei, Fei; Shao, Zhi-Ming; Yunjiang, Liu; Akram Hussain, Syed Md.; Zhang, Baoning; Lin, Cheng; Panigaro, Sonar; Walta, Fardiana; Chuan, Jiang Hong; Mirasol-Lumague, Maria Rica; Yip, Cheng-Har; Navarro, Narciso S.; Huang, Chiun-sheng; Lu, Yen-shen; Ferdousy, Tahmina; Salim, Reza; Akhter, Chameli; Nahar, Shamsun; Uy, Gemma; Young, Gregory S.; Hade, Erinn M.; Jarjoura, David
2016-01-01
Purpose In premenopausal women with metastatic hormone receptor positive breast cancer, hormonal therapy is the first line therapy. GnRH + tamoxifen therapies have been found to be more effective. The pattern of recurrence risk over time after primary surgery suggests that peri-operative factors impact recurrence. Secondary analyses of an adjuvant trial suggested that the luteal phase timing of surgical oophorectomy in the menstrual cycle simultaneous with primary breast surgery favorably influenced long-term outcomes. Methods 249 premenopausal women with incurable or metastatic hormone receptor positive breast cancer entered a trial in which they were randomized to historical mid-luteal or mid-follicular phase surgical oophorectomy followed by oral tamoxifen treatment. Kaplan-Meier methods, the log-rank test, and multivariable Cox regression models were used to assess overall and progression free survival in the two randomized groups and by hormone confirmed menstrual cycle phase. Results Overall survival (OS) and progression-free survival were not demonstrated to be different in the two randomized groups. In a secondary analysis, OS appeared worse in luteal phase surgery patients with progesterone levels of <2ng/ml (anovulatory patients) (adjusted hazard ratio 1.46, 95% CI: 0.89–2.41, p=0.14) compared to patients in luteal phase with progesterone 2ng/ml or higher. Median overall survival was 2.0 years (95% CI: 1.7 – 2.3) and OS at 4 years was 26%. Conclusions The history-based timing of surgical oophorectomy in the menstrual cycle did not influence outcomes in this trial of metastatic patients. ClinicalTrials.gov number NCT 00293540 PMID:27107325
Vallcaneras, Sandra S; Casais, Marilina; Anzulovich, Ana C; Delgado, Silvia M; Sosa, Zulema; Telleria, Carlos M; Rastrilla, Ana M
2011-07-01
Androstenedione can affect luteal function via a neural pathway in the late pregnant rat. Here, we investigate whether androstenedione is capable of opposing to regression of pregnancy corpus luteum that occurs after parturition, indirectly, from the coeliac ganglion. Thus, androstenedione was added into the ganglionar compartment of an ex vivo coeliac ganglion-superior ovarian nerve-ovary system isolated from non-lactating rats on day 4 postpartum. At the end of incubation, we measured the abundance of progesterone, androstenedione and oestradiol released into the ovarian compartment. Luteal mRNA expression and activity of progesterone synthesis and degradation enzymes, 3β-hydroxysteroid-dehydrogenase (3β-HSD) and 20α-hydroxysteroid-dehydrogenase (20α-HSD), respectively, as well as the aromatase, Bcl-2, Bax, Fas and FasL transcript levels, were also determined. Additionally, we measured the ovarian release of norepinephrine, nitric oxide and luteal inducible nitric oxide synthase (iNOS) mRNA expression. The presence of androstenedione in the ganglion compartment significantly increased the release of ovarian progesterone, androstenedione and oestradiol without modifying 3β-HSD and 20α-HSD activities or mRNA expression. The ovarian release of oestradiol in response to the presence of androstenedione in the ganglion compartment declined with time of incubation in accord with a reduction in the aromatase mRNA expression. Androstenedione added to the ganglion compartment decreased FasL mRNA expression, without affecting luteal Bcl-2, Bax and Fas transcript levels; also increased the release of norepinephrine, decreased the release of nitric oxide and increased iNOS mRNA. In summary, on day 4 after parturition, androstenedione can mediate a luteotropic effect acting at the coeliac ganglion and transmitting to the ovary a signaling via a neural pathway in association with increased release of norepinephrine, decreased nitric oxide release, and decreased expression
Kowalewski, Mariusz Pawel; Beceriklisoy, Hakki Bülent; Aslan, Selim; Agaoglu, Ali Reha; Hoffmann, Bernd
2009-11-01
In nonpregnant and pregnant dogs the corpora lutea (CL) are the only source of progesterone (P4) which shows an almost identical secretion pattern until the rapid decrease of P4 prior to parturition. For the nonpregnant dog clear evidence has been obtained that physiological luteal regression is devoid of a functional role of the PGF2alpha-system and seems to depend on the provision of StAR. Yet in pregnant dogs the rapid prepartal luteal regression, coinciding with an increase of PGF2alpha, may be indicative for different regulatory mechanisms. To assess this situation and by applying semi-quantitative Real Time (Taq Man) RT-PCR, expression patterns were determined for the following factors in CL of pregnant and prepartal dogs and of mid-pregnant dogs treated with the antiprogestin Aglepristone: cyclooxygenase 2 (Cox2), prostaglandin E2 synthase (PGES), prostaglandin F2alpha synthase (PGFS), its receptors (EP2, EP4 an FP), the steroidogenic acute regulatory protein (StAR), 3beta-hydroxysteroid-dehydrogenase (3betaHSD) and the progesterone receptor (PR). Peripheral plasma P4 concentrations were determined by RIA. CL were collected via ovariohysterectomy from pregnant bitches (n=3-5) on days 8-12 (Group 1, pre-implantation period), days 18-25 (Group 2, post-implantation period), days 35-40 (Group 3, mid-gestation period) and during the prepartal progesterone decline (Group 4). Additionally, CL were obtained from groups of 5 mid-pregnant dogs (days 40-45) 24h, respectively 72h after the second treatment with Aglepristone. Expression of Cox2 and PGES was highest during the pre-implantation period, that of PGFS and FP during the post-implantation period. EP4 and EP2 revealed a constant expression pattern throughout pregnancy with a prepartal upregulation of EP2. 3betaHSD and StAR decreased significantly from the pre-implatation period to prepartal luteolysis, it was matched by the course of P4 concentrations. Expression of the PR was higher during mid-gestation and
Endocrine disruptors and human corpus luteum: in vitro effects of phenols on luteal cells function.
Romani, Federica; Tropea, Anna; Scarinci, Elisa; Dello Russo, Cinzia; Lisi, Lucia; Catino, Stefania; Lanzone, Antonio; Apa, Rosanna
2013-01-01
Endocrine disruptors are well known to impair fertility. The aim of the present study was to investigate the effects of bisphenol A (BPA) and nonylphenol (p-NP) on human luteal function in vitro. In particular, in luteal cells isolated from 21 human corpora lutea progesterone, prostaglandin (PG) F2α, PGE2 and vascular endothelial growth factor (VEGF) release, as well as VEGF expression were evaluated. BPA and p-NP negatively affected both luteal steroidogenesis and luteotrophic/ luteolytic factors balance, without influencing VEGF mRNA expression. Actually, BPA and p-NP impaired human luteal cells function in vitro, underlining the already suggested correlation between phenols and reproductive failure.
Webley, G E; Michael, A E; Abayasekara, D R E
2010-04-01
To address the potential luteolytic role for prostaglandin F(2 alpha) (PGF(2 alpha)) in the corpus luteum of the common marmoset monkey (Callithrix jacchus), the ability of marmoset luteal cells, maintained in monolayer culture, to produce PGF(2 alpha) was determined in vitro in the presence and absence of human chorionic gonadotrophin (hCG) and other established pharmacological modulators of PGF(2 alpha) synthesis. We also assessed the effects of the PGF(2 alpha) analogue, cloprostenol, on progesterone output from luteal cells isolated in the early luteal phase versus the mid-luteal phase (days 3 and 14 post ovulation, respectively). Cloprostenol had no effect on progesterone output from luteal cells isolated on day 3 of the luteal phase, whereas it significantly inhibited both basal and hCG-stimulated progesterone synthesis by day 14 luteal cells during the culture period 48-72 h (P<0.001). Intra-luteal PGF(2 alpha) concentrations were 5-fold higher in luteal cells isolated in the early luteal phase than in mid-luteal phase cells (16.5+/-3.5 versus 3.5+/-0.6 pmol/10(5) cells). While PGF(2 alpha) production was unaffected by hCG in vitro, it was decreased by indomethacin (1000 ng/ml) (P<0.05) and stimulated by the calcium ionophore A23187 (10 micromol/l) (P<0.05) in luteal cells from both stages of the luteal phase. Phospholipase A(2) did not influence PGF(2 alpha) production by day 3 luteal cells whereas at 10 IU/ml, it significantly stimulated PGF(2 alpha) production by day 14 luteal cells (P<0.05). Hence, the timing of luteolysis in the common marmoset monkey appears to involve changes in both the luteal cell response to and production of PGF(2 alpha).
Embryo transfer and luteal support in natural cycles.
Vlaisavljevic, Veljko
2007-06-01
Embryo transfer policy and luteal supplementation was reviewed, comparing literature data and the results from the Maribor IVF Centre. A retrospective analysis of 1024 cycles in patients undergoing IVF, intracytoplasmic sperm injection (ICSI) or testicular sperm aspiration in unstimulated cycles was carried out using four different approaches for cycle monitoring. This showed that the most successful protocol for monitoring was administration of human chorionic gonadotrophin (HCG) when serum oestradiol was >0.49 nmol/l and follicle diameter was at least 15 mm. The implantation rate per transferred embryo was higher when a blastocyst was transferred (42.8%) rather than a day-2 embryo (23.5%) in the same monitoring protocol. Analysis of the influence of patient age on the success of oocyte retrieval, oocyte fertilization, embryo transfer rate and delivery rate demonstrates that patient age does not influence the rate of positive oocyte retrieval or fertilization rate as much as it influences pregnancy rate per embryo transfer. The delivery rate per cycle was dramatically influenced by age in patients over 38 years. There is no clear evidence in the literature as to whether luteal phase support is necessary in natural cycles for IVF/ICSI. Comparing the data, a higher pregnancy rate was observed if HCG was administered after embryo transfer.
Jukic, Anne Marie; Calafat, Antonia M.; McConnaughey, D. Robert; Longnecker, Matthew P.; Hoppin, Jane A.; Weinberg, Clarice R.; Wilcox, Allen J.; Baird, Donna D.; Calafat, Antonia M.; McConnaughey, D. Robert; Longnecker, Matthew P.; Hoppin, Jane A.; Weinberg, Clarice R.; Wilcox, Allen J.; Baird, Donna D.
2015-01-01
Background Certain phthalates and bisphenol A (BPA) show reproductive effects in animal studies and potentially affect human ovulation, conception, and pregnancy loss. Objectives We investigated these chemicals in relation to follicular- and luteal-phase lengths, time to pregnancy, and early pregnancy loss (within 6 weeks of the last menstrual period) among women attempting pregnancy. Methods Women discontinuing contraception provided daily first-morning urine specimens and recorded days with vaginal bleeding for up to 6 months. Specimens had previously been analyzed for estrogen and progesterone metabolites and human chorionic gonadotropin. A total of 221 participants contributed 706 menstrual cycles. We measured 11 phthalate metabolites and BPA in pooled urine from three specimens spaced throughout each menstrual cycle. We analyzed associations between chemical concentrations and outcomes using linear mixed models for follicular- and luteal-phase lengths, discrete-time fecundability models for time to pregnancy, and logistic regression for early pregnancy loss. Results Higher concentrations of monocarboxyoctyl phthalate (MCOP) were associated with shorter luteal phase [2nd tertile vs. 1st tertile: –0.5 days (95% CI: –0.9, –0.1), 3rd vs. 1st: –0.4 days (95% CI: –0.8, 0.01), p = 0.04]. BPA was also associated with shorter luteal phase [2nd vs. 1st: –0.8 days (95% CI: –1.2, –0.4), 3rd vs. 1st: –0.4 days (95% CI: –0.8, 0.02), p = 0.001]. Conclusions BPA and MCOP (or its precursors) were associated with shorter luteal phase. Menstrual cycle–specific estimates of urinary BPA and phthalate metabolites were not associated with detrimental alterations in follicular-phase length, time to pregnancy, or early pregnancy loss, and in fact, DEHP [di(2-ethylhexyl) phthalate] metabolites {MEOHP [mono(2-ethyl-5-oxohexyl) phthalate] and ΣDEHP} were associated with reduced early loss. These findings should be confirmed in future human studies. Citation Jukic
Hossain, M; Okubo, Y; Horie, S; Sekiguchi, M
1996-01-01
We examined the hypothesis that one of the pro-inflammatory cytokines, tumour necrosis factor-alpha (TNF-alpha), could induce expression of the adhesion molecule CD4 on human eosinophils. We further examined the effector function of CD4 and the mechanisms regulating CD4 expression. Human eosinophils were cultured with various concentrations of recombinant human TNF-alpha (rhTNF-alpha) with or without various drugs for 24 hr. After culture, eosinophils were stained for CD4 using a monoclonal antibody and then analysed by flow cytometry. Eosinophil-derived neurotoxin (EDN) release as eosinophil degranulation was examined by cross-linking of CD4 on eosinophils. The rhTNF-alpha induced CD4 expression on human eosinophils in a dose- and time-dependent fashion; rhTNF-alpha-induced CD4 expression was significantly inhibited by 10(-6) M cycloheximide, 10(-8) M dexamethasone, or 10(-6) M herbimycin A. Recombinant human interferon-gamma inhibited rhTNF-alpha-induced CD4 expression in a dose-dependent manner. However, cross-linking of CD4 on eosinophils did not evoke EDN release, suggesting that newly expressed CD4 molecules on human eosinophils do not play any role in triggering degranulation. Our data indicate that TNF-alpha-induced CD4 expression on human eosinophils is dependent on protein synthesis and may be dependent on tyrosine kinase activity. PMID:8690465
Anti-inflammatory effect of resveratrol on TNF-{alpha}-induced MCP-1 expression in adipocytes
Zhu Jian; Yong Wei; Wu Xiaohong; Yu Ying; Lv Jinghuan; Liu Cuiping; Mao Xiaodong; Zhu Yunxia; Xu Kuanfeng; Han Xiao Liu Chao
2008-05-02
Chronic low-grade inflammation characterized by adipose tissue macrophage accumulation and abnormal cytokine production is a key feature of obesity and type 2 diabetes. Adipose-tissue-derived monocyte chemoattractant protein (MCP)-1, induced by cytokines, has been shown to play an essential role in the early events during macrophage infiltration into adipose tissue. In this study we investigated the effects of resveratrol upon both tumor necrosis factor (TNF)-{alpha}-induced MCP-1 gene expression and its underlying signaling pathways in 3T3-L1 adipoctyes. Resveratrol was found to inhibit TNF-{alpha}-induced MCP-1 secretion and gene transcription, as well as promoter activity, which based on down-regulation of TNF-{alpha}-induced MCP-1 transcription. Nuclear factor (NF)-{kappa}B was determined to play a major role in the TNF-{alpha}-induced MCP-1 expression. Further analysis showed that resveratrol inhibited DNA binding activity of the NF-{kappa}B complex and subsequently suppressed NF-{kappa}B transcriptional activity in TNF-{alpha}-stimulated cells. Finally, the inhibition of MCP-1 may represent a novel mechanism of resveratrol in preventing obesity-related pathologies.
Hypertonic saline attenuates TNF-alpha-induced NF-kappaB activation in pulmonary epithelial cells.
Nydam, Trevor L; Moore, Ernest E; McIntyre, Robert C; Wright, Franklin L; Gamboni-Robertson, Fabia; Eckels, Phillip C; Banerjee, Anirban
2009-05-01
Resuscitation with hypertonic saline (HTS) attenuates acute lung injury (ALI) and modulates postinjury hyperinflammation. TNF-alpha-stimulated pulmonary epithelium is a major contributor to hemorrhage-induced ALI. We hypothesized that HTS would inhibit TNF-alpha-induced nuclear factor (NF)-kappaB proinflammatory signaling in pulmonary epithelial cells. Therefore, we pretreated human pulmonary epithelial cells (A549) with hypertonic medium (180 mM NaCl) for 30 min, followed by TNF-alpha stimulation (10 ng/mL). Key regulatory steps and protein concentrations in this pathway were assessed for significant alterations. Hypertonic saline significantly reduced TNF-alpha-induced intercellular adhesion molecule 1 levels and NF-kappaB nuclear localization. The mechanism is attenuated phosphorylation and delayed degradation of IkappaB alpha. Hypertonic saline did not alter TNF-alpha-induced p38 mitogen-activated protein kinase phosphorylation or constitutive vascular endothelial growth factor expression, suggesting that the observed inhibition is not a generalized suppression of protein phosphorylation or cellular function. These results show that HTS inhibits TNF-alpha-induced NF-kappaB activation in the pulmonary epithelium and, further, our understanding of its beneficial effects in hemorrhage-induced ALI.
Evaluation of models to induce low progesterone during the early luteal phase in cattle.
Beltman, M E; Roche, J F; Lonergan, P; Forde, N; Crowe, M A
2009-10-15
Two experiments were designed to evaluate models for generation of low circulating progesterone concentrations during early pregnancy in cattle. In Experiment 1, 17 crossbred heifers (Bos taurus) were assigned to either prostaglandin F(2alpha) (PGF(2alpha)) administration on Days 3, 3.5, and 4 (PG3; n=9) or to control (n=8). Blood samples were collected from heifers from Days 1 to 9 for progesterone assay. Progesterone concentrations were decreased (P<0.03) between 18 and 48h after first PGF(2alpha) treatment in heifers assigned to PG3 compared with that of controls. In Experiment 2, 39 crossbred heifers detected in estrus were inseminated (Day 0) and assigned to either (1) PGF(2alpha) administration on Days 3, 3.5, and 4 (PG3; n=10), (2) PGF(2alpha) administration on Days 3, 3.5, 4, and 4.5 (PG4; n=10), (3) Progesterone Releasing Intravaginal Device (PRID) insertion on Day 4.5 with PGF(2alpha) administration on Days 5 and 6 (PRID+PGF(2alpha); n=10), or (4) control (n=9). Blood samples were collected daily until Day 15, and conceptus survival rate was determined at slaughter on Day 16. Progesterone concentrations during the sampling period in the PG3 and PG4 groups did not differ but were less than that of controls (P<0.01). After an initial peak, progesterone concentrations in the PRID+PGF(2alpha) group were similar to that of controls. More heifers in the PG4 group (6 of 10) had complete luteal regression than did those in the PG3 group (3 of 10). Conceptus survival rate on Day 16 did not differ between groups. There was a significant correlation between progesterone concentration on Days 5 and 6 and conceptus size on Day 16. In summary, treatment with PGF(2alpha) on Days 3, 3.5, and 4 postestrus appeared to provide the best model to induce reduced circulating progesterone concentrations during the early luteal phase in cattle.
Zhong, Xia; Li, Xiaonan; Liu, Fuli; Tan, Hui; Shang, Deya
2012-08-24
Highlights: Black-Right-Pointing-Pointer Omentin inhibited TNF-{alpha}-induced adhesion of THP-1 cells to HUVECs. Black-Right-Pointing-Pointer Omentin reduces expression of ICAM-1 and VCAM-1 induced by TNF-{alpha} in HUVECs. Black-Right-Pointing-Pointer Omentin inhibits TNF-{alpha}-induced ERK and NF-{kappa}B activation in HUVECs. Black-Right-Pointing-Pointer Omentin supreeses TNF-{alpha}-induced expression of ICAM-1 and VCAM-1 via ERK/NF-{kappa}B pathway. -- Abstract: In the present study, we investigated whether omentin affected the expression of intracellular adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1) in tumor necrosis factor-{alpha} (TNF-{alpha}) induced human umbilical vein endothelial cells (HUVECs). Our data showed that omentin decreased TNF-{alpha}-induced expression of ICAM-1 and VCAM-1 in HUVECs. In addition, omentin inhibited TNF-{alpha}-induced adhesion of THP-1 cells to HUVECs. Further, we found that omentin inhibited TNF-{alpha}-activated signal pathway of nuclear factor-{kappa}B (NF-{kappa}B) by preventing NF-{kappa}B inhibitory protein (I{kappa}B{alpha}) degradation and NF-{kappa}B/DNA binding activity. Omentin pretreatment significantly inhibited TNF-{alpha}-induced ERK activity and ERK phosphorylation in HUVECs. Pretreatment with PD98059 suppressed TNF-{alpha}-induced NF-{kappa}B activity. Omentin, NF-kB inhibitor (BAY11-7082) and ERK inhibitor (PD98059) reduced the up-regulation of ICAM-1 and VCAM-1 induced by TNF-{alpha}. These results suggest that omentin may inhibit TNF-{alpha}-induced expression of adhesion molecules in endothelial cells via blocking ERK/NF-{kappa}B pathway.
Patel, K R
1975-01-01
In six patients with extrinsic bronchial asthma the inhalation of prostaglandin (PG) F2 alpha in a small dosage produced significant bronchoconstriction, whereas PGE2 produced bronchodilatation. In these patients cholinergic blockade with atropine partially inhibited the PGF2 alpha-induced bronchoconstriction, but the alpha-receptor-blocking drug thymoxamine and sodium cromoglycate did not. These results suggest that the effect of PGF2 alpha is mediated through cholinergic receptors in the airways, and this effect is grossly exaggerated in asthma. The failure to inhibit PGF2 alpha-induced bronchoconstriction with sodium cromoglycate and the observation of an inhibitory effect of sodium cromoglycate in both allergic and exercise asthma suggest that locally formed PGF2 alpha may not be the main factor in the pathogenesis of bronchial asthma. PMID:124195
Oh, G S; Pae, H O; Chung, H T; Kwon, J W; Lee, J H; Kwon, T O; Kwon, S Y; Chon, B H; Yun, Young Gab
2004-05-01
Sesquiterpene lactones have raised considerable interest because of their ability to block the activation of nuclear transcription factor-kappaB (NF-kappaB). NF-kappaB plays an important role in the resistance of cancer cells to the induction of apoptosis by anticancer drugs and tumor necrosis factor-alpha (TNF-alpha). Pharmacological inhibition of NF-kappaB offers the promise of enhancing the efficacy of anticancer therapies. Here, we demonstrate that dehydrocostus lactone (DL), the major sesquiterpene lactone isolated from the roots of Saussurea lappa, inhibits NF-kappaB activation by preventing TNF-alpha-induced degradation and phosphorylation of its inhibitory protein I-kappaB alpha in human leukemia HL-60 cells and that DL renders HL-60 cells susceptible to TNF-alpha-induced apoptosis by enhancing caspase-8 and caspase-3 activities.
Kim, Soon Ok; Markosyan, Nune; Pepe, Gerald J.; Duffy, Diane M.
2015-01-01
Prostaglandin F2α (PGF2α) has been proposed as a functional luteolysin in primates. However, administration of PGF2α or prostaglandin synthesis inhibitors in vivo both initiate luteolysis. These contradictory findings may reflect changes in PGF2α receptors (PTGFR) or responsiveness to PGF2α at a critical point during the life span of the corpus luteum. The current study addressed this question using ovarian cells and tissues from female cynomolgus monkeys and luteinizing granulosa cells from healthy women undergoing follicle aspiration. PTGFRs were present in the cytoplasm of monkey granulosa cells, while PTGFRs were localized to the perinuclear region of large, granulosa-derived monkey luteal cells by mid-late luteal phase. A PTGFR agonist decreased progesterone production by luteal cells obtained at mid-late and late luteal phases but did not decrease progesterone production by granulosa or luteal cells from younger corpora lutea. These findings are consistent with a role for perinuclear PTGFRs in functional luteolysis. This concept was explored using human luteinizing granulosa cells maintained in vitro as a model for luteal cell differentiation. In these cells, PTGFRs relocated from the cytoplasm to the perinuclear area in an estrogen- and estrogen receptor-dependent manner. Similar to our findings with monkey luteal cells, human luteinizing granulosa cells with perinuclear PTGFRs responded to a PTGFR agonist with decreased progesterone production. These data support the concept that PTGFR stimulation promotes functional luteolysis only when PTGFRs are located in the perinuclear region. Estrogen receptor-mediated relocation of PTGFRs within luteal cells may be a necessary step in the initiation of luteolysis in primates. PMID:25687410
Dietary factors and luteal phase deficiency in healthy eumenorrheic women
Andrews, Mary A.; Schliep, Karen C.; Wactawski-Wende, Jean; Stanford, Joseph B.; Zarek, Shvetha M.; Radin, Rose G.; Sjaarda, Lindsey A.; Perkins, Neil J.; Kalwerisky, Robyn A.; Hammoud, Ahmad O.; Mumford, Sunni L.
2015-01-01
STUDY QUESTION Are prospectively assessed dietary factors, including overall diet quality, macronutrients and micronutrients, associated with luteal phase deficiency (LPD) in healthy reproductive aged women with regular menstrual cycles? SUMMARY ANSWER Mediterranean Diet Score (MDS), fiber and isoflavone intake were positively associated with LPD while selenium was negatively associated with LPD after adjusting for age, percentage body fat and total energy intake. WHAT IS KNOWN ALREADY LPD may increase the risk of infertility and early miscarriage. Prior research has shown positive associations between LPD and low energy availability, either through high dietary restraint alone or in conjunction with high energy expenditure via exercise, but few studies with adequate sample sizes have been conducted investigating dietary factors and LPD among healthy, eumenorrheic women. STUDY DESIGN, SIZE, DURATION The BioCycle Study (2005–2007) prospectively enrolled 259 women from Western New York state, USA, and followed them for one (n = 9) or two (n = 250) menstrual cycles. PARTICIPANTS/MATERIALS, SETTING, METHODS Women aged 18–44 years, with self-reported BMI between 18 and 35 kg/m2 and cycle lengths between 21 and 35 days, were included in the study. Participants completed baseline questionnaires, four 24-h dietary recalls per cycle and daily diaries capturing vigorous exercise, perceived stress and sleep; they also provided up to eight fasting serum samples during clinic visits timed to specific phases of the menstrual cycle using a fertility monitor. Cycles were included for this analysis if the peak serum luteal progesterone was >1 ng/ml and a urine or serum LH surge was detected. Associations between prospectively assessed diet quality, macronutrients and micronutrients and LPD (defined as luteal duration <10 days) were evaluated using generalized linear models adjusting for age, percentage body fat and total energy intake. MAIN RESULTS AND THE ROLE OF CHANCE LPD
Effects of beta-carotene and vitamin A on bovine luteal function
Graves-Hoagland, R.L.
1987-01-01
Initially, the direct effects of B-carotene and vitamin A on progesterone (P4) production were studied by exposing dispersed luteal cells to these compounds in vitro. There were no positive relationships between P4 and B-carotene or vitamin A. However, a negative, and perhaps toxic, effect of a large dose of B-carotene on P4 reproduction was noted. A positive relationship between plasma B-carotene and percent change of P4 in the medium of dispersed luteal cells was demonstrated when these plasma metabolites were measured in slaughterhouse cows from which CL were obtained for incubation. This relationship was only present during the winter when plasma levels of B-carotene and vitamin A were considerably lower. Preliminary investigations into the mechanism of action of B-carotene and/or vitamin A were initiated. Luteal tissue ribonucleic acid (RNA), deoxyribonucleic acid (DNA), the RNA to DNA ratio and total protein concentration were measured to study the influence of plasma levels of B-carotene and vitamin A on the protein synthetic capacity of luteal tissue. There were no relationships detected, however, RNA concentration and the RNA to DNA ratio of luteal tissue were greater during the summer. The percent binding of radiolabeled vitamin A was greater in the nuclear than in the cytoplasmic component of the luteal cell.
Tsou, Tsui-Chun; Yeh, Szu Ching; Tsai, Feng-Yuan; Chen, Jein-Wen; Chiang, Huai-Chih
2007-06-01
We investigated the regulatory role of glutathione in tumor necrosis factor-alpha (TNF-alpha)-induced vascular endothelial dysfunction as evaluated by using vascular endothelial adhesion molecule expression and monocyte-endothelial monolayer binding. Since TNF-alpha induces various biological effects on vascular cells, TNF-alpha dosage could be a determinant factor directing vascular cells into different biological fates. Based on the adhesion molecule expression patterns responding to different TNF-alpha concentrations, we adopted the lower TNF-alpha (0.2 ng/ml) to rule out the possible involvement of other TNF-alpha-induced biological effects. Inhibition of glutathione synthesis by l-buthionine-(S,R)-sulfoximine (BSO) resulted in down-regulations of the TNF-alpha-induced adhesion molecule expression and monocyte-endothelial monolayer binding. BSO attenuated the TNF-alpha-induced nuclear factor-kappaB (NF-kappaB) activation, however, with no detectable effect on AP-1 and its related mitogen-activated protein kinases (MAPKs). Deletion of an AP-1 binding site in intercellular adhesion molecule-1 (ICAM-1) promoter totally abolished its constitutive promoter activity and its responsiveness to TNF-alpha. Inhibition of ERK, JNK, or NF-kappaB attenuates TNF-alpha-induced ICAM-1 promoter activation and monocyte-endothelial monolayer binding. Our study indicates that TNF-alpha induces adhesion molecule expression and monocyte-endothelial monolayer binding mainly via activation of NF-kappaB in a glutathione-sensitive manner. We also demonstrated that intracellular glutathione does not modulate the activation of MAPKs and/or their downstream AP-1 induced by lower TNF-alpha. Although AP-1 activation by the lower TNF-alpha was not detected in our systems, we could not rule out the possible involvement of transiently activated MAPKs/AP-1 in the regulation of TNF-alpha-induced adhesion molecule expression.
Clinostat rotation induces apoptosis in luteal cells of the pregnant rat
NASA Technical Reports Server (NTRS)
Yang, Hyunwon; Bhat, Ganapathy K.; Sridaran, Rajagopala
2002-01-01
Recent studies have shown that microgravity induces changes at the cellular level, including apoptosis. However, it is unknown whether microgravity affects luteal cell function. This study was performed to assess whether microgravity conditions generated by clinostat rotation induce apoptosis and affect steroidogenesis by luteal cells. Luteal cells isolated from the corpora lutea of Day 8 pregnant rats were placed in equal numbers in slide flasks (chamber slides). One slide flask was placed in the clinostat and the other served as a stationary control. At 48 h in the clinostat, whereas the levels of progesterone and total cellular protein decreased, the number of shrunken cells increased. To determine whether apoptosis occurred in shrunken cells, Comet and TUNEL assays were performed. At 48 h, the percentage of apoptotic cells in the clinostat increased compared with that in the control. To investigate how the microgravity conditions induce apoptosis, the active mitochondria in luteal cells were detected with JC-1 dye. Cells in the control consisted of many active mitochondria, which were evenly distributed throughout the cell. In contrast, cells in the clinostat displayed fewer active mitochondria, which were distributed either to the outer edge of the cell or around the nucleus. These results suggest that mitochondrial dysfunction induced by clinostat rotation could lead to apoptosis in luteal cells and suppression of progesterone production.
Mid-luteal estradiol levels of poor/good responders and intracytoplasmic sperm injection
Rehman, Rehana; Tariq, Sundus; Tariq, Saba; Hashmi, Faisal; Baig, Mukhtiar
2017-01-01
Objective: To assess mid-luteal estradiol (E2) levels in poor and good responders and determine its effect on the outcome after intracytoplasmic sperm injection (ICSI). Methods: The current study was carried out in females who underwent ICSI from June 2011 to September 2013 in “Islamabad Clinic Serving Infertile Couples”. They were categorized into good and poor responders on the basis of female age ≤40 years, basal follicle stimulating hormone ≤12 mIU/ml, and antral follicle count >5, respectively. Their mid-luteal E2 measured on the day of embryo transfer was stratified into groups (A-E) on the basis of 20th, 40th, 60th and 80th percentile values. The outcome was categorized into non-pregnant with beta human chorionic Gonadotrophin (hCG) 5-25 m IU/ml, and clinical pregnancy with beta hCG>25 m IU/ml. Results: The conception rate was 12% (63/513) in poor responders and 72% (237/329) in good responders respectively. The mid-luteal E2 levels were higher in conception as compared to non-conception cycles (p<0.001) in good and poor responders. Conclusion: Maximum pregnancies in poor and good responders (53% and 98% respectively) with mid-luteal E2 levels above 80th percentiles confirm the role of the increase in mid-luteal E2 for augmentation in conception rate of females after ICSI. PMID:28367196
Stimulation of LH, FSH, and luteal blood flow by GnRH during the luteal phase in mares.
Castro, T; Oliveira, F A; Siddiqui, M A R; Baldrighi, J M; Wolf, C A; Ginther, O J
2016-03-01
A study was performed on the effect of a single dose per mare of 0 (n = 9), 100 (n = 8), or 300 (n = 9) of GnRH on Day 10 (Day 0 = ovulation) on concentrations of LH, FSH, and progesterone (P4) and blood flow to the CL ovary. Hormone concentration and blood flow measurements were performed at hours 0 (hour of treatment), 0.25, 0.5, 1, 2, 3, 4, and 6. Blood flow was assessed by spectral Doppler ultrasonography for resistance to blood flow in an ovarian artery before entry into the CL ovary. The percentage of the CL with color Doppler signals of blood flow was estimated from videotapes of real-time color Doppler imaging by an operator who was unaware of mare identity, hour, or treatment dose. Concentrations of LH and FSH increased (P < 0.05) at hour 0.25 and decreased (P < 0.05) over hours 1 to 6; P4 concentration was not altered by treatment. Blood flow resistance decreased between hours 0 and 1, but the decrease was greater (P < 0.05) for the 100-μg dose than for the 300-μg dose. The percentage of CL with blood flow signals increased (P < 0.05) between hours 0 and 1 with no significant difference between the 100- and 300-μg doses. The results supported the hypothesis that GnRH increases LH concentration, vascular perfusion of the CL ovary, and CL blood flow during the luteal phase; however, P4 concentration was not affected.
Role of nitric oxide in PGF2 alpha-induced ocular hyperemia.
Astin, M; Stjernschantz, J; Selén, G
1994-10-01
The effect of nitric oxide synthase inhibition on prostaglandin F2 alpha (PGF2 alpha)-induced ocular hyperemia in the rabbit has been studied. PGF2 alpha was administered topically as the isopropyl ester (PGF2 alpha-IE) unilaterally, with the other eye serving as a control. The regional blood flow in the eye was determined with radioactively-labelled microspheres in conscious animals. Synthesis of nitric oxide (NO) was blocked by L-NMMA (200 mg kg-1 b.w., i.v.). PGF2 alpha-IE induced marked hyperemia of the surface structures of the eye (conjunctiva, eye lids, nictitating membrane, anterior sclera), as well as increased blood flow of the anterior uvea. L-NMMA blocked the hyperemia of the surface structures but not completely the increase in blood flow of the anterior uvea. PhXA41 (13,14-dihydro-17-phenyl-18,19,20-trinor-PGF2 alpha-isopropyl ester), a selective prostaglandin FP-receptor agonist, had no significant effect on the ocular blood flow. These results indicate that PGF2 alpha causes surface hyperemia of the eye by activating nitric oxide synthase, but this mechanism seems to be only partly involved in the increase in blood flow of the ciliary processes and the iris. The PGF2 alpha-induced ocular hyperemia is unlikely to be mediated by FP receptors.
The {alpha}-induced thick-target {gamma}-ray yield from light elements
Heaton, R.K. |
1994-10-01
The {alpha}-induced thick-target {gamma}-ray yield from light elements has been measured in the energy range 5.6 MeV {le} E{sub {alpha}} {le} 10 MeV. The {gamma}-ray yield for > 2.1 MeV from thick targets of beryllium, boron nitride, sodium fluoride, magnesium, aluminum and silicon were measured using the {alpha}-particle beam from the Lawrence Berkeley Laboratories 88 in. cyclotron. The elemental yields from this experiment were used to construct the {alpha}-induced direct production {gamma}-ray spectrum from materials in the SNO detector, a large volume ultra-low background neutrino detector located in the Creighton mine near Sudbury, Canada. This background source was an order of magnitude lower than predicted by previous calculations. These measurements are in good agreement with theoretical calculations of this spectrum based on a statistical nuclear model of the reaction, with the gross high energy spectrum structure being reproduced to within a factor of two. Detailed comparison of experimental and theoretical excitation population distribution of several residual nuclei indicate the same level of agreement within experimental uncertainties.
The HPV-16 E7 oncogene sensitizes malignant cells to IFN-alpha-induced apoptosis
Wang, Yisong
2005-10-01
Interferons (IFNs) exert antitumor effects in several human malignancies, but their mechanism of action is unclear. There is a great variability in sensitivity to IFN treatment depending on both tumor type and the individual patient. The reason for this variable sensitivity is not known. The fact that several IFN-induced anticellular effects are exerted through modulation of proto-oncogenes and tumor suppressor genes may indicate that the malignant genotype may be decisive in the cell's sensitivity to IFN. To determine if a deregulated oncogene could alter the cellular response to IFN, a mouse lymphoma cell line (J3D) was stably transfected with the viral human papillomavirus-16 (HPV-16) E7 oncogene. The E7-transfected cells and their respective mock-transfected sister clones were treated with IFN-{alpha} and examined for possible IFN-induced anticellular effects. We found that the E7-transfected clones were greatly sensitized to IFN-{alpha}-induced apoptosis compared with their mock-transfected counterparts. Induction of apoptosis in the transfected cells correlated with the ability of IFN to activate parts of the proapoptotic machinery specifically in these cells, including activation of caspases and the proapoptotic protein Bak. In summary, our data suggest that transfection of malignant cells with the E7 oncogene can sensitize them to IFN-{alpha}-induced apoptosis. This demonstrates that an oncogenic event may alter the cellular sensitivity to IFN and might also have implications for treatment of HPV related diseases with IFN.
Colour Doppler Ultrasonography as a Tool to Assess Luteal Function in Santa Inês Ewes.
Figueira, L M; Fonseca, J F; Arashiro, Ekn; Souza-Fabjan, Jmg; Ribeiro, Acs; Oba, E; Viana, Jhm; Brandão, F Z
2015-08-01
The aim of this study was to evaluate luteal dynamics in the Santa Inês ewes using colour Doppler (CD) ultrasonography. Oestrus was synchronized in nulliparous females (n = 18), and subsequently, they were only teased (n = 6) or teased and mated (n = 12). Blood samples were collected daily for plasma progesterone (P4 ) concentrations. Ultrasonographic images of corpora lutea (CL) in CD mode were obtained for further analysis in its largest diameter. The CD mode allowed an early sequential monitoring of CL that was visualized by the first time 0.77 ± 0.62 days after ovulation, with luteal area 29.68 ± 13.21 mm(2) . During the luteogenesis, a progressive increase was observed, followed by a plateau of luteal area, vascularization area and plasma concentrations of P4 reaching maximum values in D11 (124.0 ± 38.0 mm(2) , 52.78 ± 24.08 mm(2) and 11.23 ± 4.89 ng/ml, respectively). In the luteolysis, the plasma concentrations of P4 decreased sharply, whereas luteal and vascularization area gradually. The vascularization area was positively correlated with plasma concentrations of P4 during the luteogenesis (r = 0.22) and luteolysis (r = 0.48). The luteal dynamics of Santa Inês ewes showed patterns similar to those observed in other sheep breeds studied. The CD ultrasonography has the potential to be used as a tool to assess luteal function in sheep.
Doblinger, Jakob; Cometti, Barbara; Trevisan, Silvia; Griesinger, Georg
2016-01-01
Objective To summarize efficacy and safety data on a new progesterone compound which is available for subcutaneous administration as compared to vaginally administered progesterone for luteal phase support in patients undergoing IVF treatment. Design Data from two randomized phase III trials (07EU/Prg06 and 07USA/Prg05) performed according to GCP standards with a total sample size of 1435 per-protocol patients were meta-analyzed on an individual patient data level. Setting University affiliated reproductive medicine unit. Patients Subcutaneous progesterone was administered to a total of 714 subjects and vaginal progesterone was administered to a total of 721 subjects who underwent fresh embryo transfer after ovarian stimulation followed by IVF or ICSI. The subjects were between 18 and 42 years old and had a BMI <30kg/m2. Interventions Subcutaneous progesterone 25 mg daily vs. either progesterone vaginal gel 90 mg daily (07EU/Prg06) or 100 mg intravaginal twice a day (07USA/Prg05) for luteal phase support in IVF patients. Main outcome measures Ongoing pregnancy rate beyond 10 gestational weeks, live birth rate and OHSS risk. Results The administration of subcutaneous progesterone versus intra-vaginal progesterone had no impact on ongoing pregnancy likelihood (OR = 0.865, 95% CI 0.694 to 1.077; P = n.s.), live birth likelihood (OR = 0.889, 95% CI 0.714 to 1.106; P = n.s.) or OHSS risk (OR = 0.995, 95% CI 0.565 to 1.754; P = n.s.) in regression analyses accounting for clustering of patients within trials, while adjusting for important confounders. Only female age and number of oocytes retrieved were significant predictors of live birth likelihood and OHSS risk. Conclusion No statistical significant or clinical significant differences exist between subcutaneous and vaginal progesterone for luteal phase support. PMID:26991890
2012-01-01
Background Management of established severe OHSS requires prolonged hospitalization, occasionally in intensive care units, accompanied by multiple ascites punctures, correction of intravascular fluid volume and electrolyte imbalance. The aim of the present study was to evaluate whether it is feasible to manage women with severe OHSS as outpatients by treating them with GnRH antagonists in the luteal phase. Methods This is a single-centre, prospective, observational, cohort study. Forty patients diagnosed with severe OHSS, five days post oocyte retrieval, were managed as outpatients after administration of GnRH antagonist (0.25 mg) daily from days 5 to 8 post oocyte retrieval, combined with cryopreservation of all embryos. The primary outcome measure was the proportion of patients with severe OHSS, in whom outpatient management was not feasible. Results 11.3% (95% CI 8.3%-15.0%) of patients (40/353) developed severe early OHSS. None of the 40 patients required hospitalization following luteal antagonist administration and embryo cryopreservation. Ovarian volume, ascites, hematocrit, WBC, serum oestradiol and progesterone decreased significantly (P < 0.001) by the end of the monitoring period, indicating rapid resolution of severe OHSS. Conclusions The current study suggests, for the first time, that successful outpatient management of severe OHSS with antagonist treatment in the luteal phase is feasible and is associated with rapid regression of the syndrome, challenging the dogma of inpatient management. The proposed management is a flexible approach that minimizes unnecessary embryo transfer cancellations in the majority (88.7%) of high risk for OHSS patients. PMID:22938051
Kim, Hyeon Ho; Lee, Youngae; Eun, Hee Chul Chung, Jin Ho
2008-04-04
Eicosapentaenoic acid (EPA) is an omega-3 ({omega}-3) polyunsaturated fatty acid (PUFA), which has anti-inflammatory and anti-cancer properties. Some reports have demonstrated that EPA inhibits NF-{kappa}B activation induced by tumor necrosis factor (TNF)-{alpha} or lipopolysaccharide (LPS) in various cells. However, its detailed mode of action is unclear. In this report, we investigated whether EPA inhibits the expression of TNF-{alpha}-induced matrix metalloproteinases (MMP)-9 in human immortalized keratinocytes (HaCaT). TNF-{alpha} induced MMP-9 expression by NF-{kappa}B-dependent pathway. Pretreatment of EPA inhibited TNF-{alpha}-induced MMP-9 expression and p65 phosphorylation. However, EPA could not affect I{kappa}B-{alpha} phosphorylation, nuclear translocation of p65, and DNA binding activity of NF-{kappa}B. EPA inhibited TNF-{alpha}-induced p65 phosphorylation through p38 and Akt inhibition and this inhibition was IKK{alpha}-dependent event. Taken together, we demonstrate that EPA inhibits TNF-{alpha}-induced MMP-9 expression through inhibition of p38 and Akt activation.
Wathen, N C; Perry, L; Lilford, R J; Chard, T
1984-01-01
Single serum progesterone determinations were made in 79 apparently normal women with a regular menstrual cycle. A normal range (40 subjects) was derived from the concentrations in the follicular phase and used to define an "anovular" range for luteal phase values (nine out of 39 subjects). The remaining luteal phase values were used to construct an "ovular" range for the luteal phase and, within this range, to define a group of values (less than the 20th centile) which could be described as a "defective luteal phase." The cut off limits between ovular and anovular and between normal and defective luteal phases were respectively two and four times the follicular phase median. It is proposed that the numerical findings of this study may be used as a rule of thumb for defining normality and abnormality from a single serum progesterone determination. PMID:6418326
Kim, Hyung Gyun; Kim, Ji Young; Hwang, Yong Pil; Lee, Kyung Jin; Lee, Kwang Youl; Kim, Dong Hee; Kim, Dong Hyun; Jeong, Hye Gwang . E-mail: hgjeong@chosun.ac.kr
2006-12-15
Endothelial cells produce adhesion molecules after being stimulated with various inflammatory cytokines. These adhesion molecules play an important role in the development of atherogenesis. Recent studies have highlighted the chemoprotective and anti-inflammatory effects of kahweol, a coffee-specific diterpene. This study examined the effects of kahweol on the cytokine-induced monocyte/human endothelial cell interaction, which is a crucial early event in atherogenesis. Kahweol inhibited the adhesion of TNF{alpha}-induced monocytes to endothelial cells and suppressed the TNF{alpha}-induced protein and mRNA expression of the cell adhesion molecules, VCAM-1 and ICAM-1. Furthermore, kahweol inhibited the TNF{alpha}-induced JAK2-PI3K/Akt-NF-{kappa}B activation pathway in these cells. Overall, kahweol has anti-inflammatory and anti-atherosclerotic activities, which occurs partly by down-regulating the pathway that affects the expression and interaction of the cell adhesion molecules on endothelial cells.
NASA Astrophysics Data System (ADS)
Grégoire, G.
2014-12-01
The logistic regression originally is intended to explain the relationship between the probability of an event and a set of covariables. The model's coefficients can be interpreted via the odds and odds ratio, which are presented in introduction of the chapter. The observations are possibly got individually, then we speak of binary logistic regression. When they are grouped, the logistic regression is said binomial. In our presentation we mainly focus on the binary case. For statistical inference the main tool is the maximum likelihood methodology: we present the Wald, Rao and likelihoods ratio results and their use to compare nested models. The problems we intend to deal with are essentially the same as in multiple linear regression: testing global effect, individual effect, selection of variables to build a model, measure of the fitness of the model, prediction of new values… . The methods are demonstrated on data sets using R. Finally we briefly consider the binomial case and the situation where we are interested in several events, that is the polytomous (multinomial) logistic regression and the particular case of ordinal logistic regression.
EFFECTS OF BROMODICHLOROMETHANE (BDCM) ON EX VIVO LUTEAL FUNCTION IN THE F344 RAT
EFFECTS OF BROMODICHLOROMETHANE (BDCM) ON EX VIVO LUTEAL FUNCTION IN THE PREGNANT F344 RAT.
S. R. Bielmeier1, A. S. Murr2, D. S. Best2, J. M. Goldman2, and M. G. Narotsky2
1 Curriculum in Toxicology, Univ. of North Carolina, Chapel Hill, NC, USA
2 Reproductive T...
EFFECTS OF BROMODICHLOROMETHANE (BDCM) ON EX VIVO LUTEAL FUNCTION IN THE PREGNANT F344 RAT
EFFECTS OF BROMODICHLOROMETHANE (BDCM) ON EX VIVO LUTEAL FUNCTION IN THE PREGNANT F344 RAT.
S. R. Bielmeier1, A. S. Murr2, D. S. Best2, J. M. Goldman2, and M. G. Narotsky2
1 Curriculum in Toxicology, Univ. of North Carolina, Chapel Hill, NC, USA
2 Reproductive T...
Effects of IL8 and immune cells on the regulation of luteal progesterone secretion
Technology Transfer Automated Retrieval System (TEKTRAN)
Recent studies suggest that chemokines may mediate the luteolytic action of PGF2a (PGF). Our objective was to identify chemokines induced by PGF in vivo and to determine the effects of IL8 on specific luteal cell types in vitro. Midcycle cows were injected with saline or PGF, ovaries were removed ...
A controlled study of light therapy in women with late luteal phase dysphoric disorder.
Lam, R W; Carter, D; Misri, S; Kuan, A J; Yatham, L N; Zis, A P
1999-06-30
Previous studies suggest that light therapy, as used to treat seasonal affective disorder, may be beneficial for pre-menstrual depressive disorders. We conducted a six-menstrual cycle randomized, double-blind, counter-balanced, crossover study of dim vs. bright light therapy in women with late luteal phase dysphoric disorder (LLPDD). Fourteen women who met DSM-III-R criteria for LLPDD completed two menstrual cycles of prospective baseline monitoring of pre-menstrual symptoms, followed by two cycles of each treatment. During the 2-week luteal phase of each treatment cycle, patients were randomized to receive 30 min of evening light therapy using: (1) 10000 lx cool-white fluorescent light (active condition); or (2) 500 lx red fluorescent light (placebo condition), administered by a light box at their homes. After two menstrual cycles of treatment, patients were immediately crossed over to the other condition for another two cycles. Outcome measures were assessed at the mid-follicular and luteal phases of each cycle. Results showed that the active bright white light condition significantly reduced depression and pre-menstrual tension scores during the symptomatic luteal phase, compared to baseline, while the placebo dim red light condition did not. These results suggest that bright light therapy is an effective treatment for LLPDD.
EFFECTS OF BROMODICHLOROMETHANE (BDCM) ON EX VIVO LUTEAL FUNCTION IN THE F344 RAT DURING PREGNANCY
Effects of Bromodichloromethane (BDCM) on Ex Vivo Luteal Function In the Pregnant F344 Rat
Susan R. Bielmeier1, Ashley S. Murr2, Deborah S. Best2, Jerome M. Goldman2, and Michael G. Narotsky2
1Curriculum in Toxicology, Univ. of North Carolina, Chapel Hill, NC 27599,...
Natural Micronized Progesterone Sustained Release (SR) and Luteal Phase: Role Redefined!!
Malik, Sonia
2016-01-01
Role of progesterone in reproductive medicine is evolving with its suggested clinical role for the hormonal and nonhormonal actions in reproductive medicine. The main function of progesterone is to induce ‘secretory’ changes in endometrium that is further complimented by its immunomodulatory and anti-inflammatory actions. It positively modulates PIBF, NK cells and HOXA 10 genes for better implantation. MHRA recommends Serum Progesterone levels ≥14ng/ml in the mid-luteal phase for supporting pregnancy adequately. Oral Natural Micronized Progesterone SR formulation represents a therapeutic advance in this direction offering ‘therapeutic compliance’ with oral formulation while avoiding the local side effects related to long-term patient compliance in reproductive disorders. The formulation offers round the clock efficiency and efficacy with single dose administration thereby improving patient convenience and compliance. This formulation has been marketed globally since 1986 utilizing the well validated drug delivery system involving Methylcellulose base. The clinical utility of this formulation is further suggested especially in various conditions related with luteal phase insufficiency and Bad obstetric history (BOH) or luteal phase support in ART. The level of evidence has been quite robust with several clinical studies including Prescription Event Monitoring and Investigator initiated studies supporting the clinical role of oral NMP SR formulation especially in ‘Real world’ clinic settings for Luteal phase insufficiency that may be physiological or iatrogenic. PMID:27042538
Cao, Li Hua; Lee, Yun Jung; Kang, Dae Gill; Kim, Jin Sook; Lee, Ho Sub
2009-01-01
Pro-inflammatory cytokines induce the injury of endothelial cells in response to increases of adhesion molecules, leading to vascular inflammation and the development of atherosclerosis. In this study, we evaluated an ethanol extract of Zanthoxylum schinifolium (EZS) to determine if it inhibits the expressions of cellular adhesion molecules in human umbilical vein endothelial cells (HUVEC). When pretreatment of HUVEC with EZS, EZS suppressed the expression levels of cell adhesion molecules such as vascular cell adhesion molecule-1 (VCAM-1), intercellular adhesion molecule-1 (ICAM-), and E-selectin induced by TNF-alpha. The adhesion of HL-60 cells to TNF-alpha-induced endothelial cells was decreased significantly in a concentration-dependent manner. Furthermore, TNF-alpha-induced MCP-1 and IL-8 mRNA expression levels were also attenuated by pretreatment with EZS. In addition, EZS suppressed TNF-alpha-induced production of reactive oxygen species (ROS). EZS inhibited NF-kappaB activation and IkappaB-alpha phosphorylation induced by TNF-alpha, subsequent degradation of IkappaB-alpha. Finally, EZS inhibited TNF-alpha-induced p38 MAPK and c-Jun N-terminal kinase (JNK) phosphorylation. Taken together, these results demonstrate that EZS suppresses vascular inflammatory process, which may be closely related to the inhibition of ROS, JNK, p38 MAPK and NF-kappaB activation in HUVEC.
Fish meal supplementation increases bovine plasma and luteal tissue omega-3 fatty acid composition.
White, N R; Burns, P D; Cheatham, R D; Romero, R M; Nozykowski, J P; Bruemmer, J E; Engle, T E
2012-03-01
The objective of this experiment was to determine if dietary inclusion of fish meal would increase plasma and luteal tissue concentrations of eicosapentaenoic and docosahexaenoic acids. Seventeen nonlactating Angus cows (2 to 8 yr of age) were housed in individual pens and fed a corn silage-based diet for approximately 60 d. Diets were supplemented with fish meal at 5% DMI (a rich source of eicosapentaenoic acid and docosahexaenoic acid; n = 9 cows) or corn gluten meal at 6% DMI (n = 8 cows). Body weights and jugular blood samples were collected immediately before the initiation of supplementation and every 7 d thereafter for 56 d to monitor plasma n-3 fatty acid composition and BW. Estrous cycles were synchronized using 2 injections of PGF(2α) administered at 14-d intervals. The ovary bearing the corpus luteum was surgically removed at midcycle (between d 10 and 12) after estrus synchronization, which corresponded to approximately d 60 of supplementation. The ovary was transported to the laboratory, and approximately 1.5 g of luteal tissue was stored at -80°C until analyzed for n-3 fatty acid content. Initial and ending BW did not differ (P > 0.10) between cows supplemented with fish meal and those with corn gluten meal. Plasma eicosapentaenoic acid was greater (P < 0.05) beginning at d 7 of supplementation and docosahexaenoic was greater (P < 0.05) beginning at d 14 of supplementation for cows receiving fish meal. Luteal tissue collected from fish meal-supplemented cows had greater (P < 0.05) luteal n-3 fatty acids and reduced (P < 0.05) arachidonic acid and n-6 to n-3 ratio as compared with tissue obtained from cows supplemented with corn gluten meal. Our data show that fish meal supplementation increases luteal n-3 fatty acid content and reduces available arachidonic acid content, the precursor for PGF(2α). The increase in luteal n-3 fatty acids may reduce PGF(2α) intraluteal synthesis after breeding resulting in increased fertility in cattle.
Influence of Reproductive Aging of the Cow on Luteal Function and Period 1 mRNA Expression
Technology Transfer Automated Retrieval System (TEKTRAN)
In rodents, disruption of the circadian clock genes results in increased incidence of anovulation, irregular estrous cycles, decreased luteal function, and accelerated reproductive ageing. In cattle, reproductive ageing is associated with decreased numbers of follicles in the ovary, decreased lutea...
DNA-binding activity of TNF-{alpha} inducing protein from Helicobacter pylori
Kuzuhara, T. Suganuma, M.; Oka, K.; Fujiki, H.
2007-11-03
Tumor necrosis factor-{alpha} (TNF-{alpha}) inducing protein (Tip{alpha}) is a carcinogenic factor secreted from Helicobacter pylori (H. pylori), mediated through both enhanced expression of TNF-{alpha} and chemokine genes and activation of nuclear factor-{kappa}B. Since Tip{alpha} enters gastric cancer cells, the Tip{alpha} binding molecules in the cells should be investigated. The direct DNA-binding activity of Tip{alpha} was observed by pull down assay using single- and double-stranded genomic DNA cellulose. The surface plasmon resonance assay, indicating an association between Tip{alpha} and DNA, revealed that the affinity of Tip{alpha} for (dGdC)10 is 2400 times stronger than that of del-Tip{alpha}, an inactive Tip{alpha}. This suggests a strong correlation between DNA-binding activity and carcinogenic activity of Tip{alpha}. And the DNA-binding activity of Tip{alpha} was first demonstrated with a molecule secreted from H. pylori.
Interferon alpha-inducible protein 6 regulates NRASQ61K-induced melanomagenesis and growth
Gupta, Romi; Forloni, Matteo; Bisserier, Malik; Dogra, Shaillay Kumar; Yang, Qiaohong; Wajapeyee, Narendra
2016-01-01
Mutations in the NRAS oncogene are present in up to 20% of melanoma. Here, we show that interferon alpha-inducible protein 6 (IFI6) is necessary for NRASQ61K-induced transformation and melanoma growth. IFI6 was transcriptionally upregulated by NRASQ61K, and knockdown of IFI6 resulted in DNA replication stress due to dysregulated DNA replication via E2F2. This stress consequentially inhibited cellular transformation and melanoma growth via senescence or apoptosis induction depending on the RB and p53 pathway status of the cells. NRAS-mutant melanoma were significantly more resistant to the cytotoxic effects of DNA replication stress-inducing drugs, and knockdown of IFI6 increased sensitivity to these drugs. Pharmacological inhibition of IFI6 expression by the MEK inhibitor trametinib, when combined with DNA replication stress-inducing drugs, blocked NRAS-mutant melanoma growth. Collectively, we demonstrate that IFI6, via E2F2 regulates DNA replication and melanoma development and growth, and this pathway can be pharmacologically targeted to inhibit NRAS-mutant melanoma. DOI: http://dx.doi.org/10.7554/eLife.16432.001 PMID:27608486
1994-01-01
Tumor necrosis factor (TNF) alpha, a potent inhibitor of endothelial cell growth in vitro, is angiogenic in vivo. Therefore, it was suggested that the angiogenic properties of this agent might be consequent to the production of secondary mediators. Since TNF-alpha stimulates the synthesis of platelet-activating factor (PAF) by monocytes and endothelial cells, we investigated the possible involvement of PAF in the angiogenic effect of TNF-alpha. Angiogenesis was studied in a murine model in which Matrigel was used as a vehicle for the delivery of mediators. In this model the angiogenesis induced by TNF-alpha was shown to be inhibited by WEB 2170, a specific PAF receptor antagonist. Moreover, in mice injected with TNF-alpha, PAF was detected within the Matrigel, 6 and 24 h after TNF-alpha injection. The synthesis of PAF within the Matrigel was concomitant with the early migration of endothelial cells and infiltration of monocytes. No infiltration of lymphocytes or polymorphonuclear leukocytes was observed. Synthetic PAF as well as PAF extracted and purified from mice challenged with TNF-alpha induced a rapid angiogenic response, inhibited by WEB 2170. These results suggest that the angiogenic effect of TNF-alpha is, at least in part, mediated by PAF synthesized from monocytes and/or endothelial cells infiltrating the Matrigel plug. PMID:7516414
Fusion protein of CDR mimetic peptide with Fc inhibit TNF-alpha induced cytotoxicity.
Qin, Weisong; Feng, Jiannan; Li, Yan; Lin, Zhou; Shen, Beifen
2006-02-01
The variable regions of antibodies play central roles in the binding with antigens. Based on the model of a tumour necrosis factor-alpha (TNF-alpha) neutralizing monoclonal antibody (named as Z12) with TNF-alpha, heavy chain CDR2 (HCDR2) and light chain CDR3 (LCDR3) of Z12 were found to be the most responsible to bind with TNF-alpha. A mimetic peptide (PT) was designed based on the sequence derived from HCDR2 and LCDR3. Fusion protein PT-Fc was constructed by linking PT with Fc of human IgG1 through a flexible linker (GGGGGS). The primary structural characteristics of Fc and PT-Fc were analyzed, including the flexibility, hydrophilicity and epitopes. It was demonstrated that PT and Fc in the fusion protein possessed bio-function properly and non-interfering with each other. Furthermore, PT-Fc was expressed in Escherichia coli by fusion with thioredoxin (Trx). After trx-PT-Fc was cleaved with recombinant enterokinase, PT-Fc was obtained. The results of in vitro cytotoxic assays showed that both PT and PT-Fc could efficiently inhibit TNF-alpha induced apoptosis on L929 cells. At the same micromole concentration, the inhibition activity of PT-Fc was significantly higher than PT.
Roth, Lauren W.; Allshouse, Amanda A.; Bradshaw-Pierce, Erica L.; Lesh, Jennifer; Chosich, Justin; Kohrt, Wendy; Bradford, Andrew P.; Polotsky, Alex J.; Santoro, Nanette
2014-01-01
Summary Objectives Female obesity is a state of relative hypogonadotrophic hypogonadism. The aim of this study is to examine gonadotrophin secretion and response to GnRH in the luteal phase of the menstrual cycle and to investigate the pharmacodynamics and pharmacokinetics of endogenous and exogenous LH in obese women. Design Participants underwent a luteal phase frequent blood sampling study. Endogenous LH pulsatility was observed, gonadotrophin releasing hormone (GnRH) was given in 2 weight based doses, and GnRH antagonist was administered followed by recombinant LH. Patients Regularly menstruating obese (n=10) and normal weight (n=10) women Measurements Endogenous hypothalamic-pituitary function (as measured by LH pulsatility), pituitary sensitivity (GnRH induced LH secretion), pharmacodynamics of endogenous LH, and pharmacokinetics of exogenous LH were compared between the obese and normal weight groups. Results There were no statistically significant differences in endogenous LH pulsatility or pituitary responses to two weight-based doses of GnRH between the obese and normal weight women. There were no differences in the pharmacodynamics of endogenous LH or the pharmacokinetics of exogenous LH between the groups. FSH dynamics did not differ between the groups throughout the study. Conclusions The relative hypogonadotrophic hypogonadism of obesity cannot be explained by differences in LH and FSH luteal phase dynamics or differences in endogenous LH pharmacodynamics or exogenous LH pharmacokinetics. Clinical trial registration number NCT01457703, www.clinicaltrials.gov PMID:24576183
N-acetylcysteine impairs survival of luteal cells through mitochondrial dysfunction.
Löhrke, Berthold; Xu, Jinxian; Weitzel, Joachim M; Krüger, Burkhard; Goldammer, Tom; Viergutz, Torsten
2010-04-01
N-acetylcysteine (NAC) is known as an antioxidant and used for mucus viscosity reduction. However, this drug prevents or induces cell death depending on the cell type. The response of steroidogenic luteal cells to NAC is unknown. Our data shows that NAC can behave as an antioxidant or prooxidant in dependency on the concentration and mitochondrial energization. NAC elevated the flowcytometric-measured portion of hypodiploid (dying) cells. This rise was completely abolished by aurintricarboxylic acid, an inhibitor of topoisomerase II. NAC increased the secretion of nitric oxide and cellular nitrotyrosine. An image analysis indicated that cells pretreated with NAC and loaded with DHR showed a fluorescent structure probably elicited by the oxidative product of DHR, rhodamine 123 that sequesters mitochondrially. Pretreating luteal cells with NAC or adding NAC directly to mitochondrial fractions followed by assessing the mitochondrial transmembrane potential difference (Deltapsi) by the JC-1 technique demonstrated a marked decrease in Deltapsi. A protonophore restored Deltapsi and rotenone (an inhibitor of respiratory chain complex I) inhibited mitochondrial recovering. Thus, in steroidogenic luteal cells from healthy mature corpus luteum, NAC impairs cellular survival by interfering with mitochondrial metabolism. The protonophore-induced recovering of NAC-provoked decrease in Deltapsi indicates that an ATP synthase-favored route of H(+) re-entry to the matrix is essentially switched off by NAC while other respiratory chain complexes remain intact. These data may be important for therapeutic timing of treatments with NAC. (c) 2010 International Society for Advancement of Cytometry.
Luteal phase HCG support for unexplained recurrent pregnancy loss - a low hanging fruit?
Fox, Chelsea; Azores-Gococo, Denise; Swart, Linda; Holoch, Kristin; Savaris, Ricardo F; Likes, Creighton E; Miller, Paul B; Forstein, David A; Lessey, Bruce A
2017-03-01
Recurrent pregnancy loss (RPL) is defined by two or more failed pregnancies and accounts for only 1-5% of pregnancy failures. Treatment options for unexplained RPL (uRPL) are limited. Previous studies suggest a link between delayed implantation and pregnancy loss. Based on this, a timely signal for rescue of the corpus luteum (CL) using human chorionic gonadotrophin (HCG) could improve outcomes in women with uRPL. This retrospective cohort study included 98 subjects with uRPL: 45 underwent 135 monitored cycles without HCG support; and 53 underwent 142 cycles with a single mid-luteal HCG injection. Based on Log-rank Mantel-Cox survival curves, miscarriage rate and time to pregnancy decreased in the HCG group (P = 0.0005). Women receiving luteal HCG support had an increased chance of an ongoing pregnancy compared with those not receiving it (RR = 2.4; 95% CI 1.4-3.6; number need to treat (NNT) = 7; 95% CI 4-18). Subjects receiving HCG support had a significant absolute risk reduction (ARR) of miscarriage (P < 0.001; ARR = 11.5%; 95% CI 3.6-19.5; NNT = 9(5-27). These data suggest restoration of synchrony and CL support improves outcomes in women with RPL. Further randomized controlled trials of luteal-phase HCG in women with RPL appears warranted.
Lovick, Thelma A; Guapo, Vinicius G; Anselmo-Franci, Janete A; Loureiro, Camila M; Faleiros, Maria Clara M; Del Ben, Cristina M; Brandão, Marcus L
2017-01-01
There is a consensus that the development of premenstrual dysphoric states is related to cyclical change in gonadal hormone secretion during the menstrual cycle. However, results from studies seeking to link symptom severity to luteal phase progesterone concentration have been equivocal. In the present study we evaluated not only the absolute concentrations of progesterone but also the kinetics of the change in progesterone concentration in relation to development of premenstrual symptoms during the last 10days of the luteal phase in a population of 46 healthy young adult Brazilian women aged 18-39 years, mean 26.5±6.7years. In participants who developed symptoms of premenstrual distress, daily saliva progesterone concentration remained stable during most of the mid-late luteal phase, before declining sharply during the last 3days prior to onset of menstruation. In contrast, progesterone concentration in asymptomatic women underwent a gradual decline over the last 8days prior to menstruation. Neither maximum nor minimum concentrations of progesterone in the two groups were related to the appearance or severity of premenstrual symptoms. We propose that individual differences in the kinetics of progesterone secretion and/or metabolism may confer differential susceptibility to the development of premenstrual syndrome.
Meng, Charles Q; Zheng, X Sharon; Ni, Liming; Ye, Zhihong; Simpson, Jacob E; Worsencroft, Kimberly J; Hotema, Martha R; Weingarten, M David; Skudlarek, Jason W; Gilmore, Joshua M; Hoong, Lee K; Hill, Russell R; Marino, Elaine M; Suen, Ki-Ling; Kunsch, Charles; Wasserman, Martin A; Sikorski, James A
2004-03-22
Novel chalcone derivatives have been discovered as potent inhibitors of TNF-alpha-induced VCAM-1 expression. Thienyl or benzothienyl substitution at the meta-position of ring B helps boost potency while large substitution at the para-position on ring B is detrimental. Various substitutions are tolerated on ring A. A lipophilicity-potency relationship has been observed in several sub-series of compounds.
Luan, Y Y; Yao, Y M; Sheng, Z Y
2013-01-01
Within the immune system homeostasis is maintained by a myriad of mechanisms that include the regulation of immune cell activation and programmed cell death. The breakdown of immune homeostasis may lead to fatal inflammatory diseases. We set out to identify genes of tumor necrosis factor-alpha-induced protein 8 (TNFAIP8) family that has a functional role in the process of immune homeostasis. Tumor necrosis factor-alpha-induced protein 8 (TNFAIP8), which functions as an oncogenic molecule, is also associated with enhanced cell survival and inhibition of apoptosis. Tumor necrosis factor-alpha-induced protein 8-like 2 (TIPE2) governs immune homeostasis in both the innate and adaptive immune system and prevents hyper-responsiveness by negatively regulating signaling via T cell receptors and Toll-like receptors (TLRs). There also exist two highly homologous but uncharacterized proteins, TIPE1 and TIPE3. This review is an attempt to provide a summary of TNFAIP8 family associated with immune homeostasis and inflammatory cancer diseases.
Kim, Nam Hee; Jung, Hye Jin; Shibasaki, Futoshi; Kwon, Ho Jeong
2010-01-15
Nuclear factor-{kappa}B (NF-{kappa}B) is a crucial transcription factor that contributes to cancer development by regulating a number of genes involved in angiogenesis and tumorigenesis. Here, we describe (Z)-N-(3-(7-nitro-3-oxobenzo[d][1,2]selenazol-2(3H)-yl)benzylidene) propan-2-amine oxide (NBBA) as a new anti-angiogenic small molecule that targets NF-{kappa}B activity. NBBA showed stronger growth inhibition on human umbilical vein endothelial cells (HUVECs) than on the cancer cell lines we tested. Moreover, NBBA inhibited tumor necrosis factor-alpha (TNF-{alpha})-induced tube formation and invasion of HUVECs. In addition, NBBA suppressed the neovascularization of chorioallantonic membrane from growing chick embryos in vivo. To address the mode of action of the compound, the effect of NBBA on TNF-{alpha}-induced NF-{kappa}B transcription activity was investigated. NBBA suppressed TNF-{alpha}-induced c-Jun N-terminal kinase phosphorylation, which resulted in suppression of transcription of NF-{kappa}B and its target genes, including interleukin-8, interleukin-1{alpha}, and epidermal growth factor. Collectively, these results demonstrated that NBBA is a new anti-angiogenic small molecule that targets the NF-{kappa}B signaling pathway.
Gutiérrez, Gisela; Mendoza, Criselda; Zapata, Estrella; Montiel, Angélica; Reyes, Elba; Montaño, Luis Felipe; López-Marure, Rebeca
2007-01-01
Dehydroepiandrosterone (DHEA) has a protective role against atherosclerosis. We determined the effect of pharmacological doses of DHEA upon the adhesion of monocytic U937 cells to human umbilical vein endothelial cells (HUVEC), as well as the expression of adhesion and chemoattractant molecules, the translocation of NF-kappaB, the degradation of IkappaB-alpha and the production of reactive oxygen species (ROS) in HUVEC. Adhesion of U937 cells to DHEA-treated HUVEC was evaluated by co-culture experiments using [(3)H]-thymidine-labeled U937 cells. The expression of adhesion and chemoattractant molecules was evaluated by flow cytometry and RT-PCR, respectively; NF-kappaB translocation was determined by Electrophoretic Mobility Shift Assay (EMSA) and IkappaB-alpha degradation by Western blot. ROS production was determined by the reduction of fluorescent DCFDA. TNF-alpha was used to induce inflammatory responses in HUVEC. One hundred micromolar of DHEA-treatment inhibited the TNF-alpha-induced expression of ICAM-1, E-selectin, ROS production and U937 cells adhesion to HUVEC, and interfered with NF-kappaB translocation and IkappaB-alpha degradation. DHEA at the above mention concentration also inhibited the mRNA expression of MCP-1 and IL-8 in basal conditions but not in TNF-alpha-stimulated conditions. Our results suggest that DHEA inhibits the expression of molecules involved in the inflammatory process, therefore it could be used as an alternative in the treatment of chronic inflammatory diseases such as atherosclerosis.
Batista, M; Torres, A; Diniz, P; Mateus, L; Lopes-da-Costa, L
2012-10-01
The cross talk between the corpus luteum (CL) and the early embryo, potentially relevant to pregnancy establishment, is difficult to evaluate in the in vivo bovine model. In vitro co-culture of bovine luteal cells and early embryos (days 2-8 post in vitro fertilization) may allow the deciphering of this poorly understood cross talk. However, early embryos and somatic cells require different in vitro culture conditions. The objective of this study was to develop a bovine luteal cell in vitro culture system suitable for co-culture with early embryos in order to evaluate their putative steroidogenic and prostanoid interactions. The corpora lutea of the different stages of the estrous cycle (early, mid, and late) were recovered postmortem and enriched luteal cell populations were obtained. In experiments 1 and 2, the effects of CL stage, culture medium (TCM, DMEM-F12, or SOF), serum concentration (5 or 10%), atmosphere oxygen tension (5 or 20%), and refreshment of the medium on the ability of luteal cells to produce progesterone (P(4)) were evaluated. The production of P(4) was significantly increased in early CL cultures, and luteal cells adapted well to simple media (SOF), low serum concentrations (5%), and oxygen tensions (5%). In experiment 3, previous luteal cell cryopreservation did not affect the production of P(4), PGF(2α), and PGE(2) compared to fresh cell cultures. This enables the use of pools of frozen-thawed cells to decrease the variation in cell function associated with primary cell cultures. In experiment 4, mineral oil overlaying culture wells resulted in a 50-fold decrease of the P(4) quantified in the medium, but had no effect on PGF(2α) and PGE(2) quantification. In conclusion, a luteal cell in vitro culture system suitable for the 5-d-long co-culture with early embryos was developed.
Parr, M H; Crowe, M A; Lonergan, P; Evans, A C O; Rizos, D; Diskin, M G
2014-11-10
One of the main determining factors of pregnancy per artificial insemination (P/AI) is an optimum concentration of progesterone (P4) in the early luteal phase. This study examined the effects of P4 supplementation on P/AI in lactating Holstein-Friesian cows. A total of 453 cows in 8 spring-calving herds were used in the study. Following AI, cows were randomly assigned to 1 of 2 treatment groups: (1) no subsequent treatment (control; n=221); (2) insertion of a Controlled Internal Drug Release device (CIDR) from day 4 to day 9 post-estrus (supplemented; n=232). Pregnancy per AI was determined by transrectal ultrasonography at day 30 following AI. Insertion of a CIDR increased concentrations of milk P4 in supplemented cows by 4.78ng/mL between day 4 and 4.5 in comparison with a 0.55ng/mL increase in control cows. Progesterone supplementation from day 4 to 9 after AI decreased P/AI by 12 percentage points (56 vs 44%). There was a positive linear and quadratic relationship between P/AI and milk concentration of P4 on day 4 post-estrus in control cows. An optimum concentration of 2.5ng/mL on day 4 was calculated from the logistic regression curve to achieve a probability of P/AI of 65%. When both treatments groups were included in the analysis, there was no association between P/AI and concentrations of P4 on day 4. The results of the study indicate that supplementation with P4 initiated in the early luteal phase had a negative effect on P/AI in dairy cows.
NASA Technical Reports Server (NTRS)
Bhat, G. K.; Yang, H.; Sridaran, R.
2001-01-01
The purpose of this study was to assess whether simulated conditions of microgravity induce changes in the production of progesterone by luteal cells of the pregnant rat ovary using an in vitro model system. The microgravity environment was simulated using either a high aspect ratio vessel (HARV) bioreactor with free fall or a clinostat without free fall of cells. A mixed population of luteal cells isolated from the corpora lutea of day 8 pregnant rats was attached to cytodex microcarrier beads (cytodex 3). These anchorage dependent cells were placed in equal numbers in the HARV or a spinner flask control vessel in culture conditions. It was found that HARV significantly reduced the daily production of progesterone from day 1 through day 8 compared to controls. Scanning electron microscopy showed that cells attached to the microcarrier beads throughout the duration of the experiment in both types of culture vessels. Cells cultured in chamber slide flasks and placed in a clinostat yielded similar results when compared to those in the HARV. Also, when they were stained by Oil Red-O for lipid droplets, the clinostat flasks showed a larger number of stained cells compared to control flasks at 48 h. Further, the relative amount of Oil Red-O staining per milligram of protein was found to be higher in the clinostat than in the control cells at 48 h. It is speculated that the increase in the level of lipid content in cells subjected to simulated conditions of microgravity may be due to a disruption in cholesterol transport and/or lesions in the steroidogenic pathway leading to a fall in the synthesis of progesterone. Additionally, the fall in progesterone in simulated conditions of microgravity could be due to apoptosis of luteal cells.
Woad, Kathryn J; Hunter, Morag G; Mann, George E; Laird, Mhairi; Hammond, Amanda J; Robinson, Robert S
2012-01-01
Fibroblast growth factor (FGF) 2 and vascular endothelial growth factor (VEGF) A are thought to be key controllers of luteal angiogenesis; however, their precise roles in the regulation and coordination of this complex process remain unknown. Thus, the temporal and spatial patterns of endothelial network formation were determined by culturing mixed cell types from early bovine corpora lutea on fibronectin in the presence of FGF2 and VEGFA (6 h to 9 days). Endothelial cells, as determined by von Willebrand factor immunohistochemistry, initially grew in cell islands (days 0-3), before undergoing a period of vascular sprouting to display a more tubule-like appearance (days 3-6), and after 9 days in culture had formed extensive intricate networks. Mixed populations of luteal cells were treated with SU1498 (VEGF receptor 2 inhibitor) or SU5402 (FGF receptor 1 inhibitor) or control on days 0-3, 3-6 or 6-9 to determine the role of FGF2 and VEGFA during these specific windows. The total area of endothelial cells was unaffected by SU1498 treatment during any window. In contrast, SU5402 treatment caused maximal reduction in the total area of endothelial cell networks on days 3-6 vs controls (mean reduction 81%; P<0.001) during the period of tubule initiation. Moreover, SU5402 treatment on days 3-6 dramatically reduced the total number of branch points (P<0.001) and degree of branching per endothelial cell island (P<0.05) in the absence of changes in mean island area. This suggests that FGF2 is a key determinant of vascular sprouting and hence critical to luteal development.
Zhuang, Jin-Ying; Wang, Jia-Xi
2014-01-01
The present study examined women's attentional bias toward ornamental objects in relation to their menstrual phase as well as to motivations of intersexual courtship or intrasexual competition. In Experiment 1, 33 healthy heterosexual women were tested in a bias-assessment visual cuing task twice: once on a high-fertility day (during the ovulatory phase) and once on a low-fertility day (during the luteal phase). They paid greater attention to pictures of ornamental objects than to pictures of non-ornamental objects near ovulation, but not during the luteal phase, suggesting an ornamental bias during the high-fertility phase. In Experiment 2, before the visual cuing task, 40 participants viewed 10 same-sex or opposite-sex facial photographs with either high or low attractiveness as priming tasks to activate the intrasexual competition or intersexual courtship motives. Results showed that women's ornamental bias was dependent on the interaction of menstrual phase and mating motive. Specifically, the ornamental bias was observed on the high-fertility day when the subjects were primed with high-attractive same-sex images (intrasexual competition) and was observed on the low-fertility day when they were primed with high-attractive opposite-sex photographs (intersexual courtship). In conclusion, the present findings confirm the hypothesis that, during the high-fertility phase, women have an attentional bias toward ornamental objects and further support the hypothesis that the ornamental bias is driven by intrasexual competition motivation near ovulation, but driven by intersexual courtship motivation during the luteal phase. PMID:25180577
Luteal Expression of Thyroid Hormone Receptors During Gestation and Postpartum in the Rat
Navas, Paola B.; Redondo, Analía L.; Cuello-Carrión, F. Darío; Roig, Laura M. Vargas; Valdez, Susana R.; Jahn, Graciela A.
2014-01-01
Background: Progesterone (P4) is the main steroid secreted by the corpora lutea (CL) and is required for successful implantation and maintenance of pregnancy. Although adequate circulating levels of thyroid hormone (TH) are needed to support formation and maintenance of CL during pregnancy, TH signaling had not been described in this gland. We determined luteal thyroid hormone receptor isoforms (TR) expression and regulation throughout pregnancy and under the influence of thyroid status, and in vitro effects of triiodothyronine (T3) exposure on luteal P4 synthesis. Methods: Euthyroid female Wistar rats were sacrificed by decapitation on gestational day (G) 5, G10, G15, G19, or G21 of pregnancy or on day 2 postpartum (L2). Hyperthyroidism and hypothyroidism were induced in female Wistar rats by daily administration of thyroxine (T4; 0.25 mg/kg subcutaneously) or 6-propyl-2-thiouracil (PTU; 0.1 g/L in drinking water), respectively. Luteal TR expression of mRNA was determined using real-time reverse-transcription quantitative polymerase chain reaction, and of protein using Western blot and immunohistochemistry. Primary cultures of luteal cells and of luteinized granulosa cells were used to study in vitro effects of T3 on P4 synthesis. In addition, the effect of T3 on P4 synthesis under basal conditions and under stimulation with luteinizing hormone (LH), prolactin (PRL), and prostaglandin E2 (PGE2) was evaluated. Results: TRα1, TRα2, and TRβ1 mRNA were present in CL, increasing during the first half and decreasing during the second half of pregnancy. At the protein level, TRβ1 was abundantly expressed during gestation reaching a peak at G19 and decreasing afterwards. TRα1 was barely expressed during early gestation, peaked at G19, and diminished thereafter. Expression of TRβ1 and TRα1 at the protein and mRNA level were not influenced by thyroid status. T3 neither modified P4 secretion from CL of pregnancy nor its synthesis in luteinized granulosa cells in
Xu, Jin-Wen; Ikeda, Katsumi; Yamori, Yukio
2007-08-01
The aim of this study was to investigate the inhibitory effect of non-aglycone cyanidin on TNF-alpha-induced endothelial cell apoptosis and its mechanism through enhancing expression of thioredoxin in endothelial cells. We found that exposure of the serum-starved BAECs to TNF-alpha increased significantly the number of dead cells, the cleaved caspase-3 and cleaved poly(ADP-ribose)polymerase (RARP)assayed by Western blot, whereas supplementation with cyanidin considerably suppressed these events. Inhibitors of the Akt, ERK1/2, Src kinase and transfection with a dominant-negative Akt cDNA blocked the inhibitory effect of cyanidin on cleaved caspase-3. Cyanidin significantly elevated expression of endothelial nitric oxide synthase (eNOS) and thioredoxin (Trx). The increased Trx expression was blocked by siRNA transfection of cGMP-dependent protein kinase (PKG) and by using a PKG inhibitor, KT5823. Cyanidin also ameliorated TNF-alpha-induced decrease of Trx S-nitrosylation and intracellular glutathione and elevation of 4-hydroxynonenal (4-HNE), a major aldehydic product of lipid peroxidation. Furthermore, cyanidin also restored S-nitrosylation of caspase-3 and reduced the rise in expression and acetylation of tumor suppression gene p53. However, KT5823 or L-NAME, an inhibitor of eNOS, removed the preventive effects of cyanidin. Our data show that inhibitory effect of cyanidin on TNF-alpha-induced apoptosis involves multiple pathways, such as Akt activation, eNOS and thioredoxin expression in endothelial cells.
Behera, B K; Sharma, C G; Singh, S K; Kumar, H; Chaudhari, R K; Mahla, A S; Das, G K; Krishnaswamy, N
2016-10-01
In this study, alteration in the follicular fluid composition and luteal function was investigated in the buffalo with endometritis. Genitalia were classified into cytological and purulent endometritis on the basis of polymorphonuclear cell cut off while non-endometritis served as control (n = 10/group). In the follicular phase, the number of surface follicles was counted, diameter of the largest follicle was measured and the follicular fluid was assayed for total protein, cholesterol, malondialdehyde (MDA), total antioxidant capacity (TAC), oestradiol (E2 ) and progesterone (P4 ). The P4 content of corpus luteum during mid-luteal phase was estimated by radioimmunoassay. Ovaries from the follicular phase of oestrous cycle showed no significant difference in the total number of surface follicles, size of the largest follicle and volume of follicular fluid in the buffaloes with and without endometritis (p > .05). However, the antral fluid of the largest follicle from the genitalia of buffalo with cytological and purulent endometritis showed a significant decrease in the concentration of total protein, cholesterol, TAC and E2 and a significant increase in the concentration of MDA and P4 (p < .05). The results indicated that there is an association between endometritis and decreased ovarian function.
Zheng, Xiao-ke; Liu, Cai-xia; Zhai, Ying-ying; Li, Ling-ling; Wang, Xiao-lan; Feng, Wei-sheng
2013-09-01
This study is to observe the protection effect of amentoflavone (AMT) in Selaginella tamariscina against TNF-alpha-induced vascular inflammation injury of endothelial cells. On the basis of TNF-alpha induced human umbilical vein endothelial cell, observe the influence of AMT on endothelial active factor, the contents of SOD and MDA, the protein expression of vascular endothelial adhesion molecules and inflammatory factor; study the effect of its common related signal pathways such as NF-kappaB; research the effect of AMT against TNF-a induced human umbilical vein endothelial cell injury by means of MTT, ELISA, Western blotting and the cell immunofluorescence. The results showed that AMT could increase the content of NO and decrease the levels of VCAM-1, E-selectin, IL-6, IL-8 and ET-1; enhance the activity of SOD, reduce the content of MDA; downregulate the protein expressions of VCAM-1, E-selectin, NF-kappaBp65 and up-regulate IkappaBalpha, attenuate the NF-kappaBp65 transfer to cell nucleus. AMT has the effect of protect vascular endothelial and maybe via the signal pathway of NF-kappaB to down-regulate the inflammation factor and oxidative damage factor of downstream.
ERIC Educational Resources Information Center
Pedrini, D. T.; Pedrini, Bonnie C.
Regression, another mechanism studied by Sigmund Freud, has had much research, e.g., hypnotic regression, frustration regression, schizophrenic regression, and infra-human-animal regression (often directly related to fixation). Many investigators worked with hypnotic age regression, which has a long history, going back to Russian reflexologists.…
Chartier, M; Roger, M; Barrat, J; Michelon, B
1979-02-01
Plasma luteinizing hormone (LH-human chorionic gonadotropin (hCG) and beta-hCG activities were measured during the late luteal phase in 321 cycles of 147 infertile women. In 71 cycles the hCG measurement permitted the diagnosis of pregnancy between the 10th and 14th days after the thermal nadir. The slope of the regression line derived from hCG levels during the first 22 days of pregnancy was significantly lower in pregnancies which aborted before the 60th day than in normal pregnancies (P less than 0.01). Among 72 cycles ended by apparently normal menses which exhibited an LH-hCG activity at least equal to 7 mIU of hCG/ml during the late luteal phase, the beta-hCG activity was measured in 49 cycles during which hCG had not been given. Significant beta-hCG activity (greater than or equal to 4 mIU of hCG/ml) was detected in 19 cases. This finding supports the assumption that secretory trophoblastic tissue had been present and that spontaneous menstrual abortions had occurred in these women.
Technology Transfer Automated Retrieval System (TEKTRAN)
After ovulation, somatic cells of the ovarian follicle (theca and granulosa cells) become the small and large luteal cells of the corpus luteum. Aside from known cell type-specific receptors and steroidogenic enzymes, little is known about the differences in the gene expression profiles of these fou...
Technology Transfer Automated Retrieval System (TEKTRAN)
After ovulation, somatic cells of the ovarian follicle (theca and granulosa cells) become the small and large luteal cells of the corpus luteum. Aside from known cell type-specific receptors and steroidogenic enzymes, little is known about the differences in the gene expression profiles of these fou...
Franczak, Anita; Kurowicka, Beata; Kowalik, Magdalena; Ciereszko, Renata Elzbieta; Kotwica, Genowefa
2009-03-01
Oxytocin (OT) is involved in the regulation of steroid secretion by the corpus luteum (CL) in pigs, but OT signal transduction in the porcine CL has not been identified. In this study, the effects of OT on in vitro progesterone (P4) secretion, phosphoinositide (PI) hydrolysis and intracellular mobilisation of Ca2+ ([Ca2+]i) were investigated in porcine luteal cells during the early (days 3-5), mid(days 8-10) and late luteal phases (days 12-14) of the oestrous cycle. Basal concentrations of P4 and accumulation of inositol phosphates (IPs) were higher (P < 0.05) on days 3-5 and 8-10 of the oestrous cycle than on days 12-14. Basal [Ca2+]i mobilisation did not differ among studied periods of the oestrous cycle. Oxytocin (10(-7) M) enhanced P4 secretion and PI hydrolysis (P < 0.05) by luteal cells harvested on days 8-10 of the oestrous cycle. Moreover, OT started to increase mobilisation of [Ca2+]i at the 15th (days 3-5 and 8-10) or 30th second (days 12-14) in porcine luteal cells. It was concluded that in pigs OT acts as a regulator of steroidogenesis, stimulating P4 secretion in mature CL. This OT action may be mediated by changes in PI hydrolysis and [Ca2+]i mobilisation.
Effects of follicular versus luteal phase-based strength training in young women.
Sung, Eunsook; Han, Ahreum; Hinrichs, Timo; Vorgerd, Matthias; Manchado, Carmen; Platen, Petra
2014-01-01
Hormonal variations during the menstrual cycle (MC) may influence trainability of strength. We investigated the effects of a follicular phase-based strength training (FT) on muscle strength, muscle volume and microscopic parameters, comparing it to a luteal phase-based training (LT). Eumenorrheic women without oral contraception (OC) (N = 20, age: 25.9 ± 4.5 yr, height: 164.2 ± 5.5 cm, weight: 60.6 ± 7.8 kg) completed strength training on a leg press for three MC, and 9 of them participated in muscle biopsies. One leg had eight training sessions in the follicular phases (FP) and only two sessions in the luteal phases (LP) for follicular phase-based training (FT), while the other leg had eight training sessions in LP and only two sessions in FP for luteal phase-based training (LT). Estradiol (E2), progesterone (P4), total testosterone (T), free testosterone (free T) and DHEA-s were analysed once during FP (around day 11) and once during LP (around day 25). Maximum isometric force (Fmax), muscle diameter (Mdm), muscle fibre composition (No), fibre diameter (Fdm) and cell nuclei-to-fibre ratio (N/F) were analysed before and after the training intervention. T and free T were higher in FP compared to LP prior to the training intervention (P < 0.05). The increase in Fmax after FT was higher compared to LT (P <0.05). FT also showed a higher increase in Mdm than LT (P < 0.05). Moreover, we found significant increases in Fdm of fibre type ΙΙ and in N/F only after FT; however, there was no significant difference from LT. With regard to change in fibre composition, no differences were observed between FT and LT. FT showed a higher gain in muscle strength and muscle diameter than LT. As a result, we recommend that eumenorrheic females without OC should base the periodization of their strength training on their individual MC.
Becher, A; Wehrend, A; Goericke-Pesch, S
2010-01-01
Insufficient progesterone synthesis, so called hypoluteoidism or luteal insufficiency, is one of the possible reasons for infertility in the bitch. Confirming this diagnosis may be difficult if the dynamic changes of progesterone during the reproductive cycle are not taken into account. The bitch ovulates at progesterone concentrations of about 5-10ng/ml (15.7-31.4 nmol/L). The concentrations increase to >25ng/mL (78.5 nmol/L) within 3-4 weeks and then subsequently decrease after a plateau of 7-14 days. In the pregnant bitch, progesterone rapidly drops to <2ng/ml (6.3 nmol/L) approximately 24-48 hours before parturition induced by PGF2α secretion. Luteal insufficiency, characterized as an early decrease of progesterone secretion, is most commonly observed between days 20 and 35 of pregnancy. Progesterone concentrations of approximately 2ng/ml (6.3nmol/L) are thought to be necessary for maintaining pregnancy. Lower concentrations result in resorption and abortion, respectively. In bitches suspected to have luteal insufficiency, weekly progesterone determinations using quantitative tests should be performed from 5-7 days after mating or at least from the date of early pregnancy diagnosis. The frequency has to be increased in the case of progesterone concentrations below 10ng/ml (31.4 nmol/L). Progesterone administration is indicated in the case of viable foetuses and progesterone concentrations <5 ng/ml (15.7 nmol/L) before day 58/60 of pregnancy or after the detection of a rapid progesterone decline of about 10-15ng/ml (31.4-47.1 nmol/L) between days 20 and 35 with viable foetuses in the sonographic examination. Either natural or synthetic progestins can be used. However, synthetic progestins have a greater risk potential for side effects (masculinisation of female puppies and cryptorchidism in male puppies), especially when administered between days 20 and 35 of pregnancy. Administration of natural progesterone should be stopped 2-3 days before expected
Lee, Jeeyun |; Im, Young-Hyuck | E-mail: imyh@smc.samsung.co.kr; Jung, Hae Hyun; Kim, Joo Hyun; Park, Joon Oh |; Kim, Kihyun |; Kim, Won Seog |; Ahn, Jin Seok
2005-08-26
The A549 cells, non-small cell lung cancer cell line from human, were resistant to interferon (IFN)-{alpha} treatment. The IFN-{alpha}-treated A549 cells showed increase in protein expression levels of NF-{kappa}B and COX-2. IFN-{alpha} induced NF-{kappa}B binding activity within 30 min and this increased binding activity was markedly suppressed with inclusion of curcumin. Curcumin also inhibited IFN-{alpha}-induced COX-2 expression in A549 cells. Within 10 min, IFN-{alpha} rapidly induced the binding activity of a {gamma}-{sup 32}P-labeled consensus GAS oligonucleotide probe, which was profoundly reversed by curcumin. Taken together, IFN-{alpha}-induced activations of NF-{kappa}B and COX-2 were inhibited by the addition of curcumin in A549 cells.
Pepperell, John R; Nemeth, Gabor; Yamada, Yuji; Naftolin, Frederick; Merino, Maricruz
2006-08-01
These studies aim to investigate subcellular distribution of angiotensin II (ANG II) in rat luteal cells, identify other bioactive angiotensin peptides, and investigate a role for angiotensin peptides in luteal steroidogenesis. Confocal microscopy showed ANG II distributed within the cytoplasm and nuclei of luteal cells. HPLC analysis showed peaks that eluted with the same retention times as ANG-(1-7), ANG II, and ANG III. Their relative concentrations were ANG II >or= ANG-(1-7) > ANG III, and accumulation was modulated by quinapril, an inhibitor of angiotensin-converting enzyme (ACE), Z-proprolinal (ZPP), an inhibitor of prolyl endopeptidase (PEP), and parachloromercurylsulfonic acid (PCMS), an inhibitor of sulfhydryl protease. Phenylmethylsulfonyl fluoride (PMSF), a serine protease inhibitor, did not affect peptide accumulation. Quinapril, ZPP, PCMS, and PMSF, as well as losartan and PD-123319, the angiotensin receptor type 1 (AT1) and type 2 (AT2) receptor antagonists, were used in progesterone production studies. ZPP significantly reduced luteinizing hormone (LH)-dependent progesterone production (P < 0.05). Quinapril plus ZPP had a greater inhibitory effect on LH-stimulated progesterone than either inhibitor alone, but this was not reversed by exogenous ANG II or ANG-(1-7). Both PCMS and PMSF acutely blocked LH-stimulated progesterone, and PCMS blocked LH-sensitive cAMP accumulation. Losartan inhibited progesterone production in permeabilized but not intact luteal cells and was reversed by ANG II. PD-123319 had no significant effect on luteal progesterone production in either intact or permeabilized cells. These data suggest that steroidogenesis may be modulated by angiotensin peptides that act in part through intracellular AT1 receptors.
Kanda, Naoko; Watanabe, Shinichi
2006-08-14
Antimycotic agents are reported to improve cutaneous symptoms of atopic dermatitis or psoriasis vulgaris. Keratinocytes in these lesions excessively produce chemokines, CCL27, CCL2, or CCL5 which trigger inflammatory infiltrates. Tumor necrosis factor-alpha (TNF-alpha) induces production of these chemokines via activating nuclear factor-kappaB (NF-kappaB). We examined in vitro effects of antimycotics on TNF-alpha-induced CCL27, CCL2, and CCL5 production in human keratinocytes. Antimycotics ketoconazole and terbinafine hydrochloride suppressed TNF-alpha-induced CCL27, CCL2, and CCL5 secretion and mRNA expression in keratinocytes in parallel to the inhibition of NF-kappaB activity while fluconazole was ineffective. Anti-prostaglandin E2 (PGE2) antiserum or antisense oligonucleotides against PGE2 receptor EP2 or EP3 abrogated inhibitory effects of ketoconazole and terbinafine hydrochloride on TNF-alpha-induced NF-kappaB activity and CCL27, CCL2, and CCL5 production, indicating the involvement of endogenous PGE2 in the inhibitory effects. Prostaglandin H2, a precursor of PGE2 can be converted to thromboxane A2. Ketoconazole, terbinafine hydrochloride and thromboxane A2 synthase (EC 5.3.99.5) inhibitor, carboxyheptyl imidazole increased PGE2 release from keratinocytes and reduced that of thromboxane B2, a stable metabolite of thromboxane A2. Carboxyheptyl imidazole also suppressed TNF-alpha-induced NF-kappaB activity and CCL27, CCL2, and CCL5 production. These results suggest that ketoconazole and terbinafine hydrochloride may suppress TNF-alpha-induced NF-kappaB activity and CCL27, CCL2, and CCL5 production by increasing PGE2 release from keratinocytes. These antimycotics may suppress thromboxane A2 synthesis and redirect the conversion of PGH2 toward PGE2. These antimycotics may alleviate inflammatory infiltration in atopic dermatitis or psoriasis vulgaris by suppressing chemokine production.
Ahmed, C.E.; Sawyer, H.R.; Niswender, G.D.
1981-11-01
Ovine luteal cells grown in suspensions and/or monolayer culture were used to study the rates of internalization and degradation of (/sup 125/I)hCG. At specified times after a 5- to 7-min exposure to (/sup 125/I)hCG, cells were treated with acidic buffer (pH 3.9) to elute membrane-bound hormone, which left the internalized radioactivity associated with the cell pellet. Radioactivity released into the medium during the incubation periods was subjected to 20% trichloroacetic acid and/or thin layer chromatography to monitor the extent of degradation of the radioactive hormone. Secretion of progesterone into the medium and exclusion of trypan blue were used to monitor the viability of the cells in each experiment. Radioactivity was lost from the plasma membrane with a tsub1/2 of 9.6 h, with approximately 85% of the radioactivity being lost within 24 h. Cell-associated radioactivity increased linearly with time to a plateau at 4 h, remained stable until 12 h, and then decreased between 12-24 h. The plateau between 4-12 h reflected an equilibrium between the (/sup 125/I)hCG which was internalized and degraded and the (/sup 125/I)hCG which was released into the medium. The degraded (/sup 125/I)hCG increased essentially linearly up to 24 h. These data suggest that the majority of (/sup 125/I)hCG bound to receptors in luteal cells is internalized and degraded. Less than 20% of the radioactivity bound initially to cells dissociated into the incubation medium and was trichloroacetic acid precipitable within 24 h. The internalization and degradation of (/sup 125/I)hCG was temperature dependent, with essentially no hCG internalized and/or degraded at 4C.
ERIC Educational Resources Information Center
Walton, Joseph M.; And Others
1978-01-01
Ridge regression is an approach to the problem of large standard errors of regression estimates of intercorrelated regressors. The effect of ridge regression on the estimated squared multiple correlation coefficient is discussed and illustrated. (JKS)
Wu, Lixiang; Zhang, Zhenghong; Pan, Xiaoyan; Wang, Zhengchao
2015-11-01
Vascular endothelial growth factor (VEGF) is vital in normal and abnormal angiogenesis in the ovary, particularly during the early development of the corpus luteum in the ovary. However, the molecular regulation of the expression VEGF during luteal development in vivo remains to be fully elucidated. As the expression of VEGF is mediated by hypoxia‑inducible factor (HIF)‑1α in luteal cells cultured in vitro, determined in our previous study, the present study was performed to confirm the hypothesis that HIF‑1α is induced and then regulates the expression of VEGF and VEGF‑dependent luteal development/function in vivo. This was investigated using a pregnant rat model treated with a small‑molecule inhibitor of HIF‑1α, echinomycin (Ech). The development of the corpus luteum in the pregnant rat ovary was identified via performing assays of the serum progesterone, testosterone and estradiol concentrations by radioimmunoassay, accompanied with determination of the changes in the expression levels of HIF‑1α and VEGF by reverse transcription‑quantitative polymerase chain reaction at different days of the developmental process. On day 5, serum progesterone levels were markedly increased, whereas serum levels of testosterone and estradiol did not change significantly. On day 17, the highest level of serum progesterone was observed, however, this was not the case for testosterone and estradiol. Further analysis of the expression levels of HIF‑1α and VEGF revealed that their changes were consistent with the changes in serum levels of progesterone, which occurred in the development of the corpus luteum in the ovaries of pregnant rats. Further investigation demonstrated that Ech inhibited luteal development through inhibiting the expression of VEGF, mediated by HIF‑1α, and subsequent luteal function, which was determined by detecting changes in serum progesterone on days 8 and 14. Taken together, these results demonstrated that HIF‑1
Lee, Syng-Ook; Jeong, Yun-Jeong; Yu, Mi Hee; Lee, Ji-Won; Hwangbo, Mi Hyang; Kim, Cheorl-Ho; Lee, In-Seon . E-mail: inseon@kmu.ac.kr
2006-12-08
Matrix metalloproteinase-9 (MMP-9) plays a major role in the pathogenesis of atherosclerosis and restenosis by regulating both migration and proliferation of vascular smooth muscle cells (VSMC) after an arterial injury. In this study, we examined the inhibitory effect of three major flavonoids in Scutellariae Radix, baicalin, baicalein, and wogonin, on TNF-{alpha}-induced MMP-9 expression in human aortic smooth muscle cells (HASMC). Wogonin, but not baicalin and baicalein, significantly and selectively suppressed TNF-{alpha}-induced MMP-9 expression in HASMC. Reporter gene, electrophoretic mobility shift, and Western blotting assays showed that wogonin inhibits MMP-9 gene transcriptional activity by blocking the activation of NF-{kappa}B via MAPK signaling pathways. Moreover, the Matrigel migration assay showed that wogonin reduced TNF-{alpha}-induced HASMC migration. These results suggest that wogonin effectively suppresses TNF-{alpha}-induced HASMC migration through the selective inhibition of MMP-9 expression and represents a potential agent for the prevention of vascular disorders related to the migration of VSMC.
Choi, Kyungsun; Kim, Myungsun; Ryu, Jeonghee; Choi, Chulhee
2007-06-21
Ginsenosides, the main component of Panax ginseng, have been known for the anti-inflammatory and anti-proliferative activities. In this study, we investigated the molecular mechanisms responsible for the anti-inflammatory effects of ginsenosides on activated astroglial cells. Among 13 different ginsenosides, intestinal bacterial metabolites Rh(2) and compound K (C-K) showed a significant inhibitory effect on tumor necrosis factor-alpha (TNF-alpha)-induced expression of intercellular adhesion molecule-1 in human astroglial cells. Pretreatment with C-K or Rh(2) suppressed TNF-alpha-induced phosphorylation of IkappaBalpha kinase and the subsequent phosphorylation and degradation of IkappaBalpha. Additionally, the same treatment inhibited TNF-alpha-induced phosphorylation of MKK4 and the subsequent activation of the JNK-AP-1 pathway. The inhibitory effect of ginsenosides on TNF-alpha-induced activation of the NF-kappaB and JNK pathways was not observed in human monocytic U937 cells. These results collectively indicate that ginsenoside metabolites C-K and Rh(2) exert anti-inflammatory effects by the inhibition of both NF-kappaB and JNK pathways in a cell-specific manner.
FSH up-regulates angiogenic factors in luteal cells of buffaloes.
Fátima, L A; Evangelista, M C; Silva, R S; Cardoso, A P M; Baruselli, P S; Papa, P C
2013-11-01
Follicle-stimulating hormone has been widely used to induce superovulation in buffaloes and cows and usually triggers functional and morphologic alterations in the corpus luteum (CL). Several studies have shown that FSH is involved in regulating vascular development and that adequate angiogenesis is essential for normal luteal development. Angiogenesis is regulated by many growth factors, of which vascular endothelial growth factor (VEGF) and fibroblast growth factor 2 (FGF2) have an established central role. Therefore, we have used a combination of in vitro and in vivo studies to assess the effects of FSH on the expression of VEGF and FGF2 and their receptors in buffalo luteal cells. The in vivo model consisted of 12 buffalo cows, divided into control (n = 6) and superovulated (n = 6) groups, and CL samples were collected on day 6 after ovulation. In this model, we analyzed the gene and protein expression of FGF2 and its receptors and the protein expression of VEGFA systems with the use of real-time PCR, Western blot analysis, and immunohistochemistry. In the in vitro model, granulosa cells were collected from small follicles (diameter, 4-6 mm) of buffaloes and cultured for 4 d in serum-free medium with or without FSH (10 ng/mL). To induce in vitro luteinization, LH (250 ng/mL) and fetal bovine serum (10%) were added to the medium, and granulosa cells were maintained in culture for 4 d more. The progesterone concentration in the medium was measured at days 4, 5, and 8 after the beginning of cell culture. Cells were collected at day 8 and subjected to real-time PCR, Western blot analysis, and immunofluorescence for assessment of the expression of FGF2, VEGF, and their receptors. To address the percentage of steroidogenic and growth factor-expressing cells in the culture, flow cytometry was performed. We observed that in superovulated buffalo CL, the FGF2 system mRNA expression was decreased even as protein expression was increased and that the VEGF protein was
Eftekhar, Maryam; Miraj, Sepideh; Mortazavifar, Zahrasadat
2016-01-01
Background: Gonadotropin-releasing hormone (GnRH) plays essential roles in embryo implantation, invasion of trophoblastic tissue, and steroid synthesis in the placenta. Objective: The aim of this study was to evaluate the effect of GnRH antagonist administration on pregnancy outcomes in early implantation period. Materials and Methods: In this retrospective study, 94 infertile women undergoing GnRH antagonist protocol who were at risk of ovarian hyperstimulation syndrome (OHSS) were included. Sixty-seven patients (group I) received Cetrorelix 0.25 mg/daily in the luteal phase for 3 days while in 27 participants (group II), it was not administered. Pregnancy outcomes were assessed based on chemical and clinical pregnancy rates. Results: The pregnancy outcomes were not significantly different between two groups (p=0.224). Conclusion: The present study proposed that luteal phase GnRH antagonist administration does not influence the chance of successful pregnancy outcomes. PMID:27679825
Kellokumpu, S.
1987-02-01
The metabolic fate of LH/hCG receptors after exposure to human chorionic gonadotropin (hCG) was examined in cultured rat luteal cells and murine Leydig tumor cells (MLTC-1). Kinetic studies performed after pulse-labelling of the cells with (/sup 125/I)hCG indicated that the bound hormone was lost much more rapidly from the tumor cells than from the luteal cells. The tumor cells were also found to internalize and degrade the hormone more effectively than the luteal cells. Chemical cross-linking and analyses by SDS-PAGE of this material revealed that both cell types also released, in addition to intact hCG, two previously characterized receptor fragment-(/sup 125/I)hCG complexes (M/sub r/ 96,000 and 74,000) into the medium, although their amount was negligible in MLTC-1 cells. Possibly due to rapid discharge of the ligand from its receptor, no similar complexes could be detected inside the MLTC-1 cells, suggesting that they were released directly from the cell surface. However, the M/sub r/ 74,000 complex was observed inside MLTC-1 cells if chloroquine, a lysosomotropic agent, was present during the incubations. This suggests that the internalized receptor also becomes degraded, at least when complexed to hCG. The results thus provide evidence that there exist two different mechanisms for proteolytic processing of LH/hCG receptors in these target cells. In tumor cells, the degradation seems to occur almost exclusively intracellularly, whereas in luteal cells a substantial portion of the receptors is also degraded at the cell surface.
Zhang, H Y; Yu, X Z; Wang, G L
1992-08-01
53 patients with Luteal phase defect (LPD) were treated with different Chinese medicinal herbs at different phases of menstrual cycle. On the 5th day of the menstrual cycle, the treatment was implemented with the rationale of "nourishing the Kidney Yin, invigorating the Spleen and replenishing the Qi, promoting the blood circulation and enriching the Blood" which might promote follicular development. The principle for the postovulatory treatment was that "invigorating the Kidney and strengthening the Yang" might enhance the development of corpus luteum and maintain its function. The patients were treated for three menstrual cycles. There were significant improvement in the luteal phase of endometrium, and prolonged basal body temperature elevation in progestational stage with a tendency for normalization of the wave forms and its amplitude after the treatment. In the mid-progestational stage, the level of serum LH and PRL were reduced (P < 0.05) and that of serum progestin (P) rose significantly (P < 0.01), as compared with those before the treatment. The findings suggested that Chinese herbal medicines capable of replenishing the Kidney could regulate the hypothalamus-pituitary-ovarian axis and thus improve the luteal function. Among the 53 cases, 22 (41.5%) conceived but 68.18% of them required other measures to preserve the pregnancy.
Satir, Funda; Toptas, Tayfun; Inel, Murat; Erman-Akar, Munire; Taskin, Omur
2013-06-01
The main objective of this study was to compare the pregnancy rates of intramuscular (IM) 17-α-hydroxyprogesterone caproate (17-HPC) and intravaginal (IV) progesterone gel administration in in vitro fertilization-embryo transfer (IVF-ET) cycles. The IM 17-HPC and IV progesterone groups included 632 (66.4%) and 320 (33.6%) women undergoing the first cycles of IVF-ET treatment, respectively. Multivariate analyses annotated for all potential confounders showed that the use of IV progesterone retained a predictive value for the total β-human chorionic gonadotropin (hCG) positivity and clinical pregnancy rates [adjusted odds ratio (OR), 1.97; 95% confidence interval (CI), 1.28-3.03; P=0.002; and OR, 1.66; 95% CI, 1.07-2.60; P=0.03, respectively]. However, biochemical and on-going pregnancy rates did not differ significantly between the groups (OR, 1.85; 95% CI, 1.00-3.41; P=0.05; and OR, 1.43, 95% CI, 0.89-2.30; P=0.14, respectively). Luteal phase support (LPS) with IV progesterone gel in comparison with IM 17-HPC appears to be associated with higher clinical pregnancy rates in IVF-ET cycles. However, this benefit is clinically irrelevant in terms of on-going pregnancy outcomes.
SATIR, FUNDA; TOPTAS, TAYFUN; INEL, MURAT; ERMAN-AKAR, MUNIRE; TASKIN, OMUR
2013-01-01
The main objective of this study was to compare the pregnancy rates of intramuscular (IM) 17-α-hydroxyprogesterone caproate (17-HPC) and intravaginal (IV) progesterone gel administration in in vitro fertilization-embryo transfer (IVF-ET) cycles. The IM 17-HPC and IV progesterone groups included 632 (66.4%) and 320 (33.6%) women undergoing the first cycles of IVF-ET treatment, respectively. Multivariate analyses annotated for all potential confounders showed that the use of IV progesterone retained a predictive value for the total β-human chorionic gonadotropin (hCG) positivity and clinical pregnancy rates [adjusted odds ratio (OR), 1.97; 95% confidence interval (CI), 1.28–3.03; P=0.002; and OR, 1.66; 95% CI, 1.07–2.60; P=0.03, respectively]. However, biochemical and on-going pregnancy rates did not differ significantly between the groups (OR, 1.85; 95% CI, 1.00–3.41; P=0.05; and OR, 1.43, 95% CI, 0.89–2.30; P=0.14, respectively). Luteal phase support (LPS) with IV progesterone gel in comparison with IM 17-HPC appears to be associated with higher clinical pregnancy rates in IVF-ET cycles. However, this benefit is clinically irrelevant in terms of on-going pregnancy outcomes. PMID:23837065
Change of uterine histroph proteins during follicular and luteal phase in pigs.
Lee, Sang-Hee; Song, Eun-Ji; Hwangbo, Yong; Lee, Seunghyung; Park, Choon-Keun
2016-05-01
The aim of this study was to examine protein expression patterns of uterine histroph (UH) during the follicular phase (FP) and luteal phase (LP) in pigs. Forty-nine common proteins were identified from FP and LP samples; five were significantly down-regulated (>1.5-fold), while 15 were significantly up-regulated (>1.5-fold) in LPUH compared with FPUH (P<0.05). The 20 differentially-expressed proteins are involved in cell proliferation, cell responses, translation, transport, and metabolism and their molecular functions include nucleic acid binding, oxygen activity, enzymatic activity, growth activity, iron binding, and redox binding. Protein expression of vascular endothelial growth factor D (VEGFD), coatomer subunit gamma-2 (G2COP), collagen alpha 4 chain (COL4), cysteine rich protein 2 (CRP2), myoglobin (MYG), and galactoside 3-L-fucosyltransferase 4 (FUT4) was analyzed by Western blotting. These proteins were significantly higher in LPUH compared to FPUH (P<0.05). These data expand our understanding of changes in the intrauterine environment during the pre-implantation period in pigs.
Conrad, Kirk P; Baker, Valerie L
2013-01-15
Investigations in the rat model of pregnancy indicate an important role for the corpus luteal (CL) hormone relaxin in the maternal circulatory and osmoregulatory changes in pregnancy, which are epitomized by profound vasodilation and modest hypoosmolality, respectively. In a pilot study of infertile women who became pregnant through donor eggs, in vitro fertilization, and embryo transfer, the gestational rise in glomerular filtration and fall in plasma osmolality were markedly subdued. Because these women were infertile, they lacked a CL and circulating relaxin (and possibly other vasoactive CL hormones). Based on these findings in pregnant rats and women, we hypothesize that infertile women conceiving through donor eggs will have overall subdued circulatory changes (e.g., attenuated reduction in systemic vascular resistance and subdued increase in cardiac output) particularly during early pregnancy when CL hormones predominate before the full development and maturation of the placenta. In contrast, infertile women conceiving by autologous eggs retrieved after ovarian stimulation and fresh embryo transfer may have a relatively hyperdynamic circulation due to the presence of many CL (up to 20 or more) and higher circulating levels of vasodilatory ovarian hormones such as relaxin. Emerging evidence suggests that women undergoing Assisted Reproductive Technologies (ART) have increased risk for adverse pregnancy outcomes such as preeclampsia and small for gestational-age babies. This increased risk may be partly caused by the maternal milieu, which is not physiological in ART pregnancies due to the abnormal status of the CL.
Relaxin in sera during the luteal phase of in-vitro fertilization cycles.
Eddie, L W; Martinez, F; Healy, D L; Sutton, B; Bell, R J; Tregear, G W
1990-03-01
To identify the time when relaxin can first be detected in peripheral sera after in-vitro fertilization (IVF) and embryo transfer, blood samples were collected from 20 women up to 14 days after oocyte retrieval. Sixteen women did not become pregnant and in eight of them relaxin (but not beta-human chorionic gonadotrophin, beta-hCG) was measurable for the first time at days 6 to 12. Concentrations of other hormones measured were also different in these eight women compared with the remaining eight non-pregnant women; their serum concentrations of 17 alpha-OH progesterone, progesterone and oestradiol were higher but concentrations of luteinizing hormone and follicle-stimulating hormone were lower. Three women became pregnant; relaxin and beta-hCG were first detected on the same day (10 to 12). The remaining woman had increased beta-hCG levels but did not develop a clinical pregnancy. Measurement of serum relaxin during IVF cycles may allow assessment of corpora luteal function before its identification by levels of steroid hormones.
TNF-alpha-induced apoptosis is prevented by erythropoietin treatment on SH-SY5Y cells
Pregi, Nicolas Wenker, Shirley; Vittori, Daniela; Leiros, Claudia Perez; Nesse, Alcira
2009-02-01
The growth factor erythropoietin (Epo) has shown neuronal protective action in addition to its well known proerythroid activity. Furthermore, Epo has dealt with cellular inflammation by inhibiting the expression of several proinflammatory cytokines, such as IL-1 and TNF-{alpha}. The action of TNF can have both apoptotic and antiapoptotic consequences due to altered balance between different cell signalling pathways. This work has focused on the apoptotic effects of this cytokine and the potential protective action of Epo. The model we used was neuroblastoma SH-SY5Y cells cultured in the presence of 25 ng/ml TNF-{alpha} or pretreated with 25 U/ml Epo for 12 h before the addition of TNF-{alpha}. Apoptosis was evaluated by differential cell count after Hoechst staining, analysis of DNA ladder pattern, and measurement of caspase activity. Despite its ability to induce NF-{kappa}B nuclear translocation, TNF-{alpha} induced cell death, which was found to be associated to upregulation of TNF Receptor 1 expression. On the other hand, cells activated by Epo became resistant to cell death. Prevention of death receptor upregulation and caspase activation may explain this antiapoptotic effect of Epo, which may be also favoured by the induction of a higher expression of protective factors, such as Bcl-2 and NF-{kappa}B, through mechanisms involving Jak/STAT and PI3K signalling pathways.
Vicente-Manzanares, M; Rey, M; Jones, D R; Sancho, D; Mellado, M; Rodriguez-Frade, J M; del Pozo, M A; Yáñez-Mó, M; de Ana, A M; Martínez-A, C; Mérida, I; Sánchez-Madrid, F
1999-10-01
The role of phosphatidylinositol 3-kinase (PI3-kinase), an important enzyme involved in signal transduction events, has been studied in the polarization and chemotaxis of lymphocytes induced by the chemokine stromal cell-derived factor-1 alpha (SDF-1 alpha). This chemokine was able to directly activate p85/p110 PI3-kinase in whole human PBL and to induce the association of PI3-kinase to the SDF-1 alpha receptor, CXCR4, in a pertussis toxin-sensitive manner. Two unrelated chemical inhibitors of PI3-kinase, wortmannin and Ly294002, prevented ICAM-3 and ERM protein moesin polarization as well as the chemotaxis of PBL in response to SDF-1 alpha. However, they did not interfere with the reorganization of either tubulin or the actin cytoskeleton. Moreover, the transient expression of a dominant negative form of the PI3-kinase 85-kDa regulatory subunit in the constitutively polarized Peer T cell line inhibited ICAM-3 polarization and markedly reduced SDF-1 alpha-induced chemotaxis. Conversely, overexpression of a constitutively activated mutant of the PI3-kinase 110-kDa catalytic subunit in the round-shaped PM-1 T cell line induced ICAM-3 polarization. These results underline the role of PI3-kinase in the regulation of lymphocyte polarization and motility and indicate that PI3-kinase plays a selective role in the regulation of adhesion and ERM proteins redistribution in the plasma membrane of lymphocytes.
2013-01-01
Background Tumor invasion and metastasis are the major reasons for leading death of patients with hepatocellular carcinoma (HCC). Therefore, to identify molecules that can suppress invasion and metastasis of tumor will provide novel targets for HCC therapies. Tumor necrosis factor (TNF)-alpha-induced protein 8-like 2, TIPE2, is a novel immune negative molecule and an inhibitor of the oncogenic Ras in mice but its function in human is unclear. Our previous research has shown that TIPE2 is downregulated in human primary HCC compared with the paired adjacent non-tumor tissues. Results In present study, we provide evidence that TIPE2 inhibits effectively human hepatocellular carcinoma metastasis. The forced expression of TIPE2 in HCC-derived cell lines markedly inhibits tumor cell growth, migration and invasion in vitro and suppresses growth and metastasis of HCC in vivo. Clinical information from a cohort of 112 patients reveals that loss or reduced expression of TIPE2 in primary HCC tissues is significantly associated with tumor metastasis. Mechanically, TIPE2 inhibits the migration and invasion through targeting Rac1 and then reduces F-actin polymerization and expression of matrix metallopeptidase 9 (MMP9) and urokinase plasminogen activator (uPA). Conclusion Our results indicate that human TIPE2 is endogenous inhibitor of Rac1 in HCC by which it attenuates invasion and metastasis of HCC. The data suggest that TIPE2 will be a new target for HCC therapy. PMID:24274578
Zhou-Stache, J; Buettner, R; Artmann, G; Mittermayer, C; Bosserhoff, A K
2002-11-01
The Chinese herb radix Salviae miltiorrhizae (RSM) is used in traditional Chinese medicine as a treatment for cardiovascular and cerebrovascular diseases. Several components of the plant extract from salvia mitorrhiza bunge have been determined previously, one of which is protocatechuic acid (PAC). It has been found, in the study, that PAC inhibited TNF-alpha-induced cell death of human umbilical vein endothelial cells (HUVECs) and Jurkat cells in a concentration of 100 microM when applied 2 h prior to TNF-alpha exposure. Molecular studies revealed that PAC activated NF-kappaB with a maximum effect after 30 min of treatment. Inhibition of NF-kappaB action by MG132 and NF-kappaB inhibitory peptide suppressed the cell-protective effect of PAC. Further, degradation of IkBalpha occurred in response to PAC treatment. The results provide evidence that activation of NF-kappaB plays an important role in mediating the cell-protecting effect of PAC on HUVECs and Jurkat cells. Further studies are required to test whether PAC, a component of radix salviae miltiorrhizae, could be useful in preventing in vivo cell death resulting from cardiovascular or cerebrovascular diseases.
Regressive systemic sclerosis.
Black, C; Dieppe, P; Huskisson, T; Hart, F D
1986-01-01
Systemic sclerosis is a disease which usually progresses or reaches a plateau with persistence of symptoms and signs. Regression is extremely unusual. Four cases of established scleroderma are described in which regression is well documented. The significance of this observation and possible mechanisms of disease regression are discussed. Images PMID:3718012
Tharrington, Arnold N.
2015-09-09
The NCCS Regression Test Harness is a software package that provides a framework to perform regression and acceptance testing on NCCS High Performance Computers. The package is written in Python and has only the dependency of a Subversion repository to store the regression tests.
Unitary Response Regression Models
ERIC Educational Resources Information Center
Lipovetsky, S.
2007-01-01
The dependent variable in a regular linear regression is a numerical variable, and in a logistic regression it is a binary or categorical variable. In these models the dependent variable has varying values. However, there are problems yielding an identity output of a constant value which can also be modelled in a linear or logistic regression with…
Ehrsam, Eric; Kallini, Joseph R.; Lebas, Damien; Modiano, Philippe; Cotten, Hervé
2016-01-01
Fully regressive melanoma is a phenomenon in which the primary cutaneous melanoma becomes completely replaced by fibrotic components as a result of host immune response. Although 10 to 35 percent of cases of cutaneous melanomas may partially regress, fully regressive melanoma is very rare; only 47 cases have been reported in the literature to date. AH of the cases of fully regressive melanoma reported in the literature were diagnosed in conjunction with metastasis on a patient. The authors describe a case of fully regressive melanoma without any metastases at the time of its diagnosis. Characteristic findings on dermoscopy, as well as the absence of melanoma on final biopsy, confirmed the diagnosis. PMID:27672418
Amelkina, Olga; Zschockelt, Lina; Painer, Johanna; Serra, Rodrigo; Villaespesa, Francisco; Braun, Beate C.; Jewgenow, Katarina
2015-01-01
The corpus luteum (CL) is a transient gland formed in the ovary after ovulation and is the major source of progesterone. In the Iberian and Eurasian lynx, CL physiologically persist after parturition and retain their capacity to produce progesterone, thus suppressing the ovarian activity. This unique reproductive characteristic has a big impact on the success of assisted reproduction techniques in the endangered Iberian lynx. The mechanisms behind CL persistence are not yet understood and require extensive studies on potential luteotropic and luteolytic factors in felids. Because the apoptosis system has been shown to be involved in structural regression of CL in many species, we aimed to investigate the capacity of perCL to undergo apoptosis. In addition, we performed initial studies on the apoptosis system in the luteal phase of the domestic cat. No previous research on this system has been made in this species. Our factors of interest included agents of the intrinsic apoptosis pathway, i.e., pro-survival B-cell CLL/lymphoma 2 (BCL2) and pro-apoptotic BCL2-associated X protein (BAX), the executioner caspase-3 (CASP3), as well as of the extrinsic pathway, i.e., pro-apoptotic receptor FAS, and tumor necrosis factor (TNF) and its receptors (pro-apoptotic TNFRSF1A and pro-survival TNFRSF1B). We analyzed the relative mRNA levels of these factors, as well as protein localization of CASP3 and TNF during stages of pregnancy and the non-pregnant luteal phase in CL of domestic cats. The same factors were investigated in freshly ovulated CL (frCL) and perCL of Iberian and Eurasian lynx, which were histologically analyzed. All factors were present in the CL tissue of both domestic cat and lynx throughout all analyzed stages. The presence of pro-apoptotic factors BAX, CASP3, FAS and TNFRSF1A in perCL of the Eurasian and Iberian lynx might indicate the potential sensitivity of perCL to apoptotic signals. The expression of pro-survival factors BCL2 and TNFRSF1B was
Amelkina, Olga; Zschockelt, Lina; Painer, Johanna; Serra, Rodrigo; Villaespesa, Francisco; Braun, Beate C; Jewgenow, Katarina
2015-01-01
The corpus luteum (CL) is a transient gland formed in the ovary after ovulation and is the major source of progesterone. In the Iberian and Eurasian lynx, CL physiologically persist after parturition and retain their capacity to produce progesterone, thus suppressing the ovarian activity. This unique reproductive characteristic has a big impact on the success of assisted reproduction techniques in the endangered Iberian lynx. The mechanisms behind CL persistence are not yet understood and require extensive studies on potential luteotropic and luteolytic factors in felids. Because the apoptosis system has been shown to be involved in structural regression of CL in many species, we aimed to investigate the capacity of perCL to undergo apoptosis. In addition, we performed initial studies on the apoptosis system in the luteal phase of the domestic cat. No previous research on this system has been made in this species. Our factors of interest included agents of the intrinsic apoptosis pathway, i.e., pro-survival B-cell CLL/lymphoma 2 (BCL2) and pro-apoptotic BCL2-associated X protein (BAX), the executioner caspase-3 (CASP3), as well as of the extrinsic pathway, i.e., pro-apoptotic receptor FAS, and tumor necrosis factor (TNF) and its receptors (pro-apoptotic TNFRSF1A and pro-survival TNFRSF1B). We analyzed the relative mRNA levels of these factors, as well as protein localization of CASP3 and TNF during stages of pregnancy and the non-pregnant luteal phase in CL of domestic cats. The same factors were investigated in freshly ovulated CL (frCL) and perCL of Iberian and Eurasian lynx, which were histologically analyzed. All factors were present in the CL tissue of both domestic cat and lynx throughout all analyzed stages. The presence of pro-apoptotic factors BAX, CASP3, FAS and TNFRSF1A in perCL of the Eurasian and Iberian lynx might indicate the potential sensitivity of perCL to apoptotic signals. The expression of pro-survival factors BCL2 and TNFRSF1B was
Hojo, Takuo; Siemieniuch, Marta J.; Lukasik, Karolina; Piotrowska-Tomala, Katarzyna K.; Jonczyk, Agnieszka W.; Okuda, Kiyoshi; Skarzynski, Dariusz J.
2016-01-01
Programmed necrosis (necroptosis) is an alternative form of programmed cell death that is regulated by receptor-interacting protein kinase (RIPK) 1 and 3-dependent, but is a caspase (CASP)-independent pathway. In the present study, to determine if necroptosis participates in bovine structural luteolysis, we investigated RIPK1 and RIPK3 expression throughout the estrous cycle, during prostaglandin F2α (PGF)-induced luteolysis in the bovine corpus luteum (CL), and in cultured luteal steroidogenic cells (LSCs) after treatment with selected luteolytic factors. In addition, effects of a RIPK1 inhibitor (necrostatin-1, Nec-1; 50 μM) on cell viability, progesterone secretion, apoptosis related factors and RIPKs expression, were evaluated. Expression of RIPK1 and RIPK3 increased in the CL tissue during both spontaneous and PGF-induced luteolysis (P < 0.05). In cultured LSCs, tumor necrosis factor α (TNF; 2.3 nM) in combination with interferon γ (IFNG; 2.5 nM) up-regulated RIPK1 mRNA and protein expression (P < 0.05). TNF + IFNG also up-regulated RIPK3 mRNA expression (P < 0.05), but not RIPK3 protein. Although Nec-1 prevented TNF + IFNG-induced cell death (P < 0.05), it did not affect CASP3 and CASP8 expression. Nec-1 decreased both RIPK1 and RIPK3 protein expression (P < 0.05). These findings suggest that RIPKs-dependent necroptosis is a potent mechanism responsible for bovine structural luteolysis induced by pro-inflammatory cytokines. PMID:27901113
Wagley, Yadav; Yoo, Yung-Choon; Seo, Han Geuk; Rhee, Man Hee; Kim, Tae-Hyoung; Kang, Keon Wook; Nah, Seung-Yeol; Oh, Jae-Wook . E-mail: ohjw@mail.chosun.ac.kr
2007-03-23
Melanoma is an intractable tumor that has shown very impressive and promising response to local administration of high dose recombinant TNF-{alpha} in combination with IFN-{gamma} in clinical studies. In this study, we investigated the effect of IL-6/sIL-6R on TNF-{alpha}-resistant B16/F10.9 melanoma cells. A low dose of TNF-{alpha} or IL-6/sIL-6R had minimal affect on the cell growth. However, the highly active fusion protein of sIL-6R and IL-6 (IL6RIL6), covalently linked by a flexible peptide, sensitized TNF-{alpha}-resistant F10.9 melanoma cells to TNF-{alpha}-induced apoptosis. Stimulation of the cells with IL6RIL6 plus TNF-{alpha} resulted in both the activation of caspase-3 and the reduction of bcl-2 expression. Flow cytometry analysis showed that IL6RIL6-upregulated TNF-R55 and TNF-R75 expression, suggesting an increase in TNF-{alpha} responsiveness by IL6RIL6 resulting from the induction of TNF receptors. Moreover, exposure of F10.9 cells to neutralizing antibody to TNF-R55 significantly inhibited IL6RIL6/TNF-{alpha}-induced cytotoxicity. These results suggest that the IL6/sIL6R/gp130 system, which sensitizes TNF-{alpha}-resistant melanoma cells to TNF-{alpha}-induced apoptosis, may provide a new target for immunotherapy.
Han, Jian-Wen; Wang, Yong; Alateng, Chulu; Li, Hong-Bin; Bai, Yun-Hua; Lyu, Xin-Xiang; Wu, Rina
2016-01-01
Background: Psoriasis is a common immune-mediated inflammatory dermatosis. Generalized pustular psoriasis (GPP) is the severe and rare type of psoriasis. The association between tumor necrosis factor-alpha induced protein 3 interacting protein 1 (TNIP1) gene and psoriasis was confirmed in people with multiple ethnicities. This study was to investigate the association between TNIP1 gene polymorphisms and pustular psoriasis in Chinese Han population. Methods: Seventy-three patients with GPP, 67 patients with palmoplantar pustulosis (PPP), and 476 healthy controls were collected from Chinese Han population. Six single nucleotide polymorphisms (SNPs) of the TNIP1 gene, namely rs3805435, rs3792798, rs3792797, rs869976, rs17728338, and rs999011 were genotyped by using polymerase chain reaction-ligase detection reaction. Statistical analyses were performed using the PLINK 1.07 package. Allele frequencies and genotyping frequencies for six SNPs were compared by using Chi-square test, odd ratio (OR) (including 95% confidence interval) were calculated. The haplotype analysis was conducted by Haploview software. Results: The frequencies of alleles of five SNPs were significantly different between the GPP group and the control group (P ≤ 7.22 × 10−3), especially in the GPP patients without psoriasis vulgaris (PsV). In the haplotype analysis, the most significantly different haplotype was H4: ACGAAC, with 13.1% frequency in the GPP group but only 3.4% in the control group (OR = 4.16, P = 4.459 × 10−7). However, no significant difference in the allele frequencies was found between the PPP group and control group for each of the six SNPs (P > 0.05). Conclusions: Polymorphisms in TNIP1 are associated with GPP in Chinese Han population. However, no association with PPP was found. These findings suggest that TNIP1 might be a susceptibility gene for GPP. PMID:27364786
Młynarczuk, J; Wróbel, M H; Kotwica, J
2013-07-01
Coumestrol is one of a few biologically active substances present in leguminous plants, which are widely used as fodder for ruminants. Depending on the doses, coumestrol acts on the reproductive processes as an estrogen-like factor or antiestrogen to evoke a decrease in ovulation frequency, elongation of estrous cycle duration. The aim of the current investigations was to study the influence of coumestrol on secretory function of luteal cells obtained from first trimester of pregnant cows. Luteal cells (2.5 × 10(5) /mL) from 3rd to 5th, 6th to 8th, and 9th to 12th week of pregnancy were preincubated for 24 h and incubated with coumestrol (1 × 10(-6) M) for successive 48 h and the medium concentrations of progesterone (P4), oxytocin (OT), prostaglandin (PG) E2 and F2α were determined. Moreover, the expression of mRNA for neurophysin-I/oxytocin (NP-I/OT; precursor of OT) and peptidyl-glycine-α-amidating mono-oxygenase (PGA, an enzyme responsible for post-translational OT synthesis) was determined after 8 h of treatment. Coumestrol did not affect P4 secretion but increased the secretion of OT from the cells collected at all stages of gestation studied. Hence, the ratio of P4 to OT was markedly decreased. Simultaneously, coumestrol increased the expression of NP-I/OT mRNA during 9th to 12th weeks of pregnancy, and mRNA for PGA during 3rd to 5th and 9th to 12th weeks of gestation. Furthermore, coumestrol decreased PGE2 secretion from luteal cells in all studied stages of pregnancy, while it affected PGF2α metabolite (PGFM) concentration only from week 3 to 5 of pregnancy. Obtained results suggest that coumestrol impairs secretory function of the corpus luteum (CL) and this way it can affect the maintenance of pregnancy in the cow.
Zhang, Xiao-Mei; Lv, Fang; Wang, Pin; Huang, Xia-Man; Liu, Kai-Feng; Pan, Yu; Dong, Nai-Jun; Ji, Yu-Rong; She, Hong; Hu, Rong
2015-02-01
Meta-analyses have found conflicting results with respect to the use of progesterone or progesterone plus estrogen as luteal phase support for in vitro fertilization (IVF) protocols involving gonadotropins and/or gonadotropin-releasing hormone analogs. The aim of the present study was to perform an updated meta-analysis on the efficacy of progesterone versus progesterone plus estrogen as luteal phase support. We searched the MEDLINE, Cochrane Library, and Google Scholar databases (up to March 18, 2014). The search terms were (estrogen OR estradiol OR oestradiol) AND (progesterone) AND (IVF OR in vitro fertilization) AND (randomized OR prospective). We did not limit the form of estrogen and included subjects who contributed more than 1 cycle to a study. The primary outcome was clinical pregnancy rate. Secondary outcomes were ongoing pregnancy rate, fertilization rate, implantation rate, and miscarriage rate. A total of 11 articles were included in the present analysis, with variable numbers of studies assessing each outcome measure. Results of statistical analyses indicated that progesterone plus estrogen treatment was more likely to result in clinical pregnancy than progesterone alone (pooled odds ratio 1.617, 95% confidence interval 1.059-2.471; P = 0.026). No significant difference between the 2 treatment regimens was found for the other outcome measures. Progesterone plus estrogen for luteal phase support is associated with a higher clinical pregnancy rate than progesterone alone in women undergoing IVF, but other outcomes such as ongoing pregnancy rate, fertilization rate, implantation rate, and miscarriage rate are the same for both treatments.
Köhne, Martin; Ille, Natascha; Erber, Regina; Adib Razavi, Mahsa S; Walter, Ingrid; Aurich, Christine
2016-12-01
Progestin concentration in plasma during the early luteal phase is crucial for endometrial function and conceptus development. We hypothesized that periovulatory gonadotrophin treatment via support of luteal function affects endometrial gene expression in horses. Effect of age was analyzed as well. Shetland mares (n = 8, age 4-25 years) were assigned to the following treatments during five consecutive cycles in alternating order following a cross-over design: treatment hCG/-: preovulatory injection of hCG, but no gonadotrophin injection at detection of ovulation, treatment -/hCG: no preovulatory gonadodrophin injection, but injection of hCG at detection of ovulation, treatment eCG/-: preovulatory injection of eCG, but no gonadotrophin injection at detection of ovulation, treatment -/eCG: no preovulatory gonadotrophin injection, but injection of eCG at detection of ovulation, treatment control: no treatment. Concentration of progestin was analyzed by ELISA from the day of ovulation until Day 10. On Day 10, endometrial cells were collected transvaginally by cytobrush technique. Expression of mRNA of cyclooxygenase-2 (COX-2), prostaglandin F2α-synthase, prostaglandin E-synthase, progesterone receptor (PR), estradiol receptor (E2R), acyl-CoA-dehydrogenase (ACAD), uteroglobin (UGB), uteroferrin, and uterocalin was analyzed by RT qPCR. Immunohistological staining of endometrial tissue, obtained via biopsy, was performed for COX-2, PR and UGB. The P4 concentration was influenced by day of cycle (P < 0.01), but not by treatment. No effects of age on gene expression were determined. Neither of the periovulatory gonadotrophin treatments nor age influenced mRNA expression of the genes of interest. Treatment did also not affect immunohistological staining of the endometrium. In contrast, age affected the percentage of PR positive stromal cells (e.g. mare 1 (4 years): 65.5 ± 2.6, mare 2 (24 years): 82.7 ± 2.2%, P < 0.05) and COX-2 positive stained ciliated cells
Gerber, Samuel; Rubel, Oliver; Bremer, Peer -Timo; Pascucci, Valerio; Whitaker, Ross T.
2012-01-19
This paper introduces a novel partition-based regression approach that incorporates topological information. Partition-based regression typically introduces a quality-of-fit-driven decomposition of the domain. The emphasis in this work is on a topologically meaningful segmentation. Thus, the proposed regression approach is based on a segmentation induced by a discrete approximation of the Morse–Smale complex. This yields a segmentation with partitions corresponding to regions of the function with a single minimum and maximum that are often well approximated by a linear model. This approach yields regression models that are amenable to interpretation and have good predictive capacity. Typically, regression estimates are quantified by their geometrical accuracy. For the proposed regression, an important aspect is the quality of the segmentation itself. Thus, this article introduces a new criterion that measures the topological accuracy of the estimate. The topological accuracy provides a complementary measure to the classical geometrical error measures and is very sensitive to overfitting. The Morse–Smale regression is compared to state-of-the-art approaches in terms of geometry and topology and yields comparable or improved fits in many cases. Finally, a detailed study on climate-simulation data demonstrates the application of the Morse–Smale regression. Supplementary Materials are available online and contain an implementation of the proposed approach in the R package msr, an analysis and simulations on the stability of the Morse–Smale complex approximation, and additional tables for the climate-simulation study.
Improved Regression Calibration
ERIC Educational Resources Information Center
Skrondal, Anders; Kuha, Jouni
2012-01-01
The likelihood for generalized linear models with covariate measurement error cannot in general be expressed in closed form, which makes maximum likelihood estimation taxing. A popular alternative is regression calibration which is computationally efficient at the cost of inconsistent estimation. We propose an improved regression calibration…
Gerber, Samuel; Rübel, Oliver; Bremer, Peer-Timo; Pascucci, Valerio; Whitaker, Ross T.
2012-01-01
This paper introduces a novel partition-based regression approach that incorporates topological information. Partition-based regression typically introduce a quality-of-fit-driven decomposition of the domain. The emphasis in this work is on a topologically meaningful segmentation. Thus, the proposed regression approach is based on a segmentation induced by a discrete approximation of the Morse-Smale complex. This yields a segmentation with partitions corresponding to regions of the function with a single minimum and maximum that are often well approximated by a linear model. This approach yields regression models that are amenable to interpretation and have good predictive capacity. Typically, regression estimates are quantified by their geometrical accuracy. For the proposed regression, an important aspect is the quality of the segmentation itself. Thus, this paper introduces a new criterion that measures the topological accuracy of the estimate. The topological accuracy provides a complementary measure to the classical geometrical error measures and is very sensitive to over-fitting. The Morse-Smale regression is compared to state-of-the-art approaches in terms of geometry and topology and yields comparable or improved fits in many cases. Finally, a detailed study on climate-simulation data demonstrates the application of the Morse-Smale regression. Supplementary materials are available online and contain an implementation of the proposed approach in the R package msr, an analysis and simulations on the stability of the Morse-Smale complex approximation and additional tables for the climate-simulation study. PMID:23687424
Yovich, John L; Conceicao, Jason L; Stanger, James D; Hinchliffe, Peter M; Keane, Kevin N
2015-08-01
This study explores the relevance of mid-luteal serum hormonal concentrations in cryopreserved embryo transfer cycles conducted under hormone replacement therapy (HRT) control and which involved single-embryo transfer (SET) of 529 vitrified blastocysts. Widely ranging mid-luteal oestradiol and progesterone concentrations ensued from the unique HRT regimen. Oestradiol had no influence on clinical pregnancy or live birth rates, but an optimal progesterone range between 70 and 99 nmol/l (P < 0.005) was identified in this study. Concentrations of progesterone below 50 nmol/l and above 99 nmol/l were associated with decreased implantation rates. There was no clear interaction between oestradiol and progesterone concentrations but embryo quality grading did show a significant influence on outcomes (P < 0.001 and P = 0.002 for clinical pregnancy and live birth rates, respectively). Multiple comparison analysis showed that the progesterone effect was influential regardless of embryo grading, body mass index or the woman's age, either at vitrification or at cryopreserved embryo transfer. The results support the argument that careful monitoring of serum progesterone concentrations in HRT-cryopreserved embryo transfer is warranted and that further studies should explore pessary adjustments to optimize concentrations for individual women to enhance implantation rates.
Baum, M.S.
1989-01-01
The present study was performed in order to further elucidate the mechanism of action of PGF2 alpha in luteolysis in the rat ovary. Seven days after priming with superovulatory doses of pregnant mare serum gonadotropin and human chorionic gonadotropin to induce luteal tissue formation, the rats were injected with a luteolytic dose of the prostaglandin F2 alpha analogue cloprostenol. The ovaries were then homogenized, a 30,000 x g supernatant and pellet were prepared, whereafter aliquots of the preparations were incubated in the presence of (gamma-/sup 32/P)ATP with or without Ca2+. The phosphorylated proteins were separated by sodium dodecyl sulfate polyacrylamide gel electrophoresis and localized by autoradiography. The presence of Ca2+ caused an increased phosphorylation of a 45 kDa protein band in the particulate, but not in the cytosol, fraction. Furthermore, PGF2 alpha rapidly increased the /sup 32/P incorporation into the same protein band of 45 kDa. Thus, the PGF2 alpha-stimulated /sup 32/P incorporation was Ca2+-dependent and seen only in the particulate fraction. These results suggest that PGF2 alpha in its role as a luteolytic agent stimulates a Ca2+-dependent phosphorylation of a specific protein in luteal membranes of the rat ovary.
Schmid, Matthias; Wickler, Florian; Maloney, Kelly O.; Mitchell, Richard; Fenske, Nora; Mayr, Andreas
2013-01-01
Regression analysis with a bounded outcome is a common problem in applied statistics. Typical examples include regression models for percentage outcomes and the analysis of ratings that are measured on a bounded scale. In this paper, we consider beta regression, which is a generalization of logit models to situations where the response is continuous on the interval (0,1). Consequently, beta regression is a convenient tool for analyzing percentage responses. The classical approach to fit a beta regression model is to use maximum likelihood estimation with subsequent AIC-based variable selection. As an alternative to this established - yet unstable - approach, we propose a new estimation technique called boosted beta regression. With boosted beta regression estimation and variable selection can be carried out simultaneously in a highly efficient way. Additionally, both the mean and the variance of a percentage response can be modeled using flexible nonlinear covariate effects. As a consequence, the new method accounts for common problems such as overdispersion and non-binomial variance structures. PMID:23626706
Growth and regression in bovine corpora lutea: regulation by local survival and death pathways.
Skarzynski, D J; Piotrowska-Tomala, K K; Lukasik, K; Galvão, A; Farberov, S; Zalman, Y; Meidan, R
2013-09-01
The bovine corpus luteum (CL) is a transient gland with a life span of only 18 days in the cyclic cow. Mechanisms controlling CL development and secretory function may involve factors produced both within and outside this gland. Although luteinizing hormone (LH) surge is the main trigger of ovulation and granulosa cells luteinization, many locally produced agents such as arachidonic acid (AA) metabolites, growth factors and cytokines were shown to complement gonadotropins action in the process of CL development. Bovine CL is a highly vascular gland, where the very rapid angiogenesis rate (until Day 5 of the cycle) results in the development of a capillary network, endowing this gland with one of the highest blood flow rate per unit mass in the body. Angiogenesis in the developing CL is later followed by either controlled regression of the microvascular tree in the non-fertile cycle or maintenance and stabilization of the blood vessels, as seen during pregnancy. Different luteal cell types (both steroidogenic and accessory luteal cells: immune cells, endothelial cells, pericytes and fibroblasts) are involved in the pro- and/or anti-angiogenic responses. The balance between pro- and anti-angiogenic responses to the main luteolysin - prostaglandin F2α (PGF2α) could be decisive in whether or not PGF2α induces CL regression. Fibroblast growth factor-2 (FGF2) may be one of the factors that modulate the angiogenic response to PGF2α. Manipulation of local production and action of FGF2 will provide new tools for reproductive management of dairy cattle. Luteolysis is characterized by a rapid decrease in progesterone production, followed by structural regression. Factors like endothelin-1, cytokines (tumour necrosis factorα, interferons) and nitric oxide were all shown to play critical roles in functional and structural regression of the CL by inhibiting steroidogenesis and inducting apoptosis.
George: Gaussian Process regression
NASA Astrophysics Data System (ADS)
Foreman-Mackey, Daniel
2015-11-01
George is a fast and flexible library, implemented in C++ with Python bindings, for Gaussian Process regression useful for accounting for correlated noise in astronomical datasets, including those for transiting exoplanet discovery and characterization and stellar population modeling.
Understanding poisson regression.
Hayat, Matthew J; Higgins, Melinda
2014-04-01
Nurse investigators often collect study data in the form of counts. Traditional methods of data analysis have historically approached analysis of count data either as if the count data were continuous and normally distributed or with dichotomization of the counts into the categories of occurred or did not occur. These outdated methods for analyzing count data have been replaced with more appropriate statistical methods that make use of the Poisson probability distribution, which is useful for analyzing count data. The purpose of this article is to provide an overview of the Poisson distribution and its use in Poisson regression. Assumption violations for the standard Poisson regression model are addressed with alternative approaches, including addition of an overdispersion parameter or negative binomial regression. An illustrative example is presented with an application from the ENSPIRE study, and regression modeling of comorbidity data is included for illustrative purposes.
Bonaccorso, Stefania; Marino, Valentina; Puzella, Antonella; Pasquini, Massimo; Biondi, Massimo; Artini, Marco; Almerighi, Cristiana; Verkerk, Robert; Meltzer, Herbert; Maes, Michael
2002-02-01
There is now evidence that repeated administration of interferon-alpha (IFN-alpha) to patients with chronic active hepatitis and cancers induces depressive symptoms. There is also evidence that induction of the cytokine network modulates the serotonergic system and that major depression is related to activation of the cytokine network and disturbances in the serotonergic metabolism. The aims of this study were to examine the effects of IFN-alpha-based immunotherapy on the development of depressive symptoms in relation to its effects on plasma tryptophan and kynurenine and serum serotonin (5-HT). Eighteen patients affected by chronic active hepatitis C were treated with IFN-alpha (3-6 million units subcutaneously three to six times a week for 6 months) and had measurements of the previous parameters before starting immunotherapy and 2, 4, 16, and 24 weeks later. Severity of depression and anxiety were measured with the Montgomery-Asberg Depression Rating Scale (MADRS) and the Hamilton Rating Scale for Anxiety (HAM-A) scale, respectively. Immunochemotherapy with IFN-alpha (1) significantly increased the MADRS and HAM-A scores and serum kynurenine concentrations and (2) significantly reduced plasma tryptophan and serum 5-HT concentrations. IFN-alpha-based immunotherapy significantly increased the kynurenine per tryptophan quotient, which estimates the activity of indoleamine 2,3-dioxygenase, the major tryptophan-catabolizing enzyme, which is induced by IFNs. There are significant relationships between the IFN-alpha-induced changes in the MADRS score and serum kynurenine (positive) and 5-HT (negative) concentrations. Immunotherapy with IFN-alpha significantly increases the severity of depressive symptoms. The latter is related to changes in the serotonergic system, such as depletion of serum 5-HT and induction of the catabolism of tryptophan to kynurenine. It is suggested that the IFN-alpha-induced changes in the serotonergic turnover could play a role in the
Perez-Marin, C
2009-06-01
The corpus luteum (CL) may be looked upon as a compact or cavitary structure. A number of papers have addressed the relationship between CL type and parameters such as fertility or progesterone levels. The present study assessed the morphological and functional sequence observed in cows with different CL types, comparing pre-ovulatory follicle size, progesterone levels, luteal tissue formation and some blood biochemical parameters (calcium, albumin, inorganic phosphorus, glucose, magnesium, copper and zinc), oestrus cycle length and oestrus expression, as a function of CL type. Twenty-eight lactating dairy cows from two commercial dairy farms in southern Spain were studied. Oestrus detection was performed by monitoring daily oestrus behaviour, and artificial insemination (AI) was performed using the AM/PM rule. Ovaries and uterus were sonographically examined and blood samples were collected to measure progesterone and various biochemical parameters. There was a slight tendency towards the appearance of luteal cavities when pre-ovulatory follicles were larger (1.9 +/- 0.2 vs 1.7 +/- 03; p = 0.074). Fertility was not affected by cavity presence (cavity = 42.9% and compact = 57.1%; n.s.). Luteal tissue and function were not modified as a function of CL type. Cows with luteal cavities displayed significantly higher levels of albumin, suggesting a possible metabolic influence on the formation of these structures, although specific research is required to confirm this observation.
Ziolkowska, A; Mlynarczuk, J; Kotwica, J
2013-01-01
Cortisol stimulates the synthesis and secretion of oxytocin (OT) from bovine granulosa and luteal cells, but the molecular mechanisms of cortisol action remain unknown. In this study, granulosa cells or luteal cells from days 1-5 and 11-15 of the oestrous cycle were incubated for 4 or 8 h with cortisol (1 x 10(-5), 1 x 10(-7) M). After testing cell viability and hormone secretion (OT, progesterone, estradiol), we studied the effect of cortisol on mRNA expression for precursor of OT (NP-I/OT) and peptidyl glycine-alpha-amidating mono-oxygenase (PGA). The influence of RU 486 (1 x 10(-5) M), a progesterone receptor blocker and inhibitor of the glucocorticosteroid receptor (GR), on the expression for both genes was tested. Cortisol increased the mRNA expression for NP-I/OT and PGA in granulosa cells and stimulated the expression for NP-I/OT mRNA in luteal cells obtained from days 1-5 and days 11-15 of the oestrous cycle. Expression for PGA mRNA was increased only in luteal cells from days 11-15 of the oestrous cycle. In addition, RU 486 blocked the cortisol-stimulated mRNA expression for NP-I/OT and PGA in both types of cells. These data suggest that cortisol affects OT synthesis and secretion in bovine ovarian cells, by acting on the expression of key genes, that may impair ovary
Cataldi, Natalia I; Lux-Lantos, Victoria A R; Libertun, Carlos
2012-10-10
Orexin-A and orexin-B are neuropeptides controlling sleep-wakefulness, feeding and neuroendocrine functions via their G protein-coupled receptors, orexin-1R and orexin-2R. They are synthesized in the lateral hypothalamus and project throughout the brain. Orexins and orexin receptors have also been described outside the brain. Previously we demonstrated the presence of both receptors in the ovary, their increased expression during proestrous afternoon and the dependence on the gonadotropins. Here we studied the effects of orexins on the mRNA expression of both receptors, by quantitative real-time PCR, on luteal cells from superovulated rat ovaries and granulosa cells from diethylstilbestrol-treated rat ovaries. Effects on progesterone secretion were also measured. In luteal cells, 1 nM of either orexin-A or orexin-B decreased progesterone secretion. Orexin-A treatment increased expression of both orexin-1R and orexin-2R mRNA. The effect on orexin-1R mRNA expression was abolished by an orexin-1R selective receptor antagonist SB-334867 and the effect on orexin-2R mRNA expression was abolished by a selective orexin-2R antagonist JNJ-10397049. Orexin-B did not modify orexin-1R mRNA expression, but increased orexin-2R mRNA expression. The effect of orexin-B on orexin-2R was abolished by a selective orexin-2R antagonist. Neither the expression of orexin receptors nor progesterone secretions by granulosa cells were affected by orexins. FSH, as positive control, increased both steroid hormones secretion, but did not induce the expression of OX receptors in granulosa cells isolated from late preantral/early antral follicles. Finally in ovaries obtained immediately after sacrifice, the expression of orexin-1R and orexin-2R was higher in superovulated rat ovaries compared to control or diethylstilbestrol treated rat ovaries. A selective presence and function of both orexinergic receptors in luteal and granulosa cells is described, suggesting that the orexinergic system may
[Understanding logistic regression].
El Sanharawi, M; Naudet, F
2013-10-01
Logistic regression is one of the most common multivariate analysis models utilized in epidemiology. It allows the measurement of the association between the occurrence of an event (qualitative dependent variable) and factors susceptible to influence it (explicative variables). The choice of explicative variables that should be included in the logistic regression model is based on prior knowledge of the disease physiopathology and the statistical association between the variable and the event, as measured by the odds ratio. The main steps for the procedure, the conditions of application, and the essential tools for its interpretation are discussed concisely. We also discuss the importance of the choice of variables that must be included and retained in the regression model in order to avoid the omission of important confounding factors. Finally, by way of illustration, we provide an example from the literature, which should help the reader test his or her knowledge.
Rahayu, Larasati Puji; El Behiry, Mohammed; Endo, Natsumi; Tanaka, Tomomi
2017-03-25
This study aimed to examine the response of luteinizing hormone (LH) secretion and ovarian steroid profile to TAK-683, an investigational metastin/kisspeptin analog, through treatment during different stages of the luteal phase in goats. Nine cycling Shiba goats (4.4 ± 2.3 years old) were assigned to early luteal phase (ELP, n = 4), mid-luteal phase (MLP, n = 4), and control (n = 5) groups. The ELP and MLP groups were administered 50 µg of TAK-683 intravenously on either day 5 or between days 7-14 after ovulation, respectively. The control group received vehicle between days 7-14 after ovulation. Blood samples were collected at 10-min (2-6 h), 2-h (6-24 h), and 24-h (24-96 h) intervals after treatment. Significant increases in plasma LH concentration were detected during the periods of 3 to 5 h and 2 to 5 h in the ELP and MLP groups, respectively. Estradiol concentrations continuously increased with the rise of basal LH secretion after TAK-683 treatment in two goats of the ELP group with a surge-like release of LH, but not in the goats without LH surge, i.e. the MLP and control group ones. Plasma progesterone concentration and the lengths of estrous cycle in all groups did not change significantly from the time before and after treatment. Present findings indicate that the responses of LH and ovarian steroids to treatment with TAK-683 depend on the stage of the luteal phase of the estrous cycle. We suggest that the stimulatory effects of TAK-683 on LH secretion are reduced in the process leading to the mid-luteal phase in cycling goats.
Kanyima, BM; Båge, R; Owiny, DO; Ntallaris, T; Lindahl, J; Magnusson, U; Nassuna-Musoke, MG
2014-01-01
Contents The study investigated the influence of selected husbandry factors on interval to resumption of post-partum cyclicity among dairy cows in urban and peri-urban Kampala. A prospective study of 85 day post-partum period of 59 dairy cows in open (n = 38) and zero grazing (n = 21) systems was conducted on 24 farms. Cows of parity 1–6 were recruited starting 15–30 days post-partum. Progesterone (P4) content in milk taken at 10–12 day intervals was analysed using ELISA. The cow P4 profiles were classified into ‘normal’ (< 56 days), ‘delayed’ (> 56 days), ‘ceased’ or ‘prolonged’ (if started < 56 days but with abnormal P4 displays) resumption of luteal activity and tested for association with husbandry and cow factors. Of the 59 cows, luteal activity in 81.4% resumed normally and in 18.6%, delayed. Only 23.7% maintained regular luteal activity, while the others had ceased (10.2%), prolonged (37.3%) or unclear luteal activity (20.3%). There were no differences between open and zero-grazed cows. Milk production was higher (p < 0.05) in zero than open grazing, in urban than peri-urban and in cows fed on brew waste (p < 0.001) compared with mill products and banana peels. Results suggest that luteal activity resumes normally in a majority of cows, although only a minority experienced continued normal cyclicity once ovulation had occurred, in the two farming systems irrespective of feed supplements or water, and that supplementing with brew waste is beneficial for milk production. PMID:24930481
Pan, X Y; Zhang, Z H; Wu, L X; Wang, Z C
2015-08-03
The corpus luteum is a temporary endocrine structure in mammals that plays an important role in the female reproductive cycle and is formed from a ruptured and ovulated follicle with rapid angiogenesis. Vascular endothelial growth factor (VEGF) is thought to be vital in normal and abnormal angiogenesis in the ovary, but the molecular regulation of luteal VEGF expression during corpus luteum development in vivo is still poorly understood at present. Therefore, we examined whether hypoxia-inducible factor-1a (HIF-1a) is induced and regulates VEGF expression and luteal function in vivo using a pseudopregnant rat model treated with a small-molecule inhibitor of HIF-1a, echinomycin. Corpus luteum development in the pseudopregnant rat ovary was determined after measuring plasma progesterone concentration and ovarian prostaglandin F2a content to reflect changes in HIF-1a and VEGF on different days of this developmental process. At day 7, the corpus luteum was formed and the expression of HIF- 1a/VEGF reached a maximum, while a significant decrease in HIF-1a/ VEGF expression was observed when luteolysis occurred at day 13. Additionally, echinomycin blocked luteal development by inhibiting VEGF expression mediated by HIF-1a and following luteal function by detecting the progesterone changes at day 7. These results demonstrated that HIF-1a-mediated VEGF expression might be an important mechanism regulating ovarian luteal development in mammals in vivo, which may provide new strategies for fertility control and for treating some types of ovarian dysfunction, such as polycystic ovarian syndrome, ovarian hyperstimulation syndrome, and ovarian neoplasia.
Practical Session: Logistic Regression
NASA Astrophysics Data System (ADS)
Clausel, M.; Grégoire, G.
2014-12-01
An exercise is proposed to illustrate the logistic regression. One investigates the different risk factors in the apparition of coronary heart disease. It has been proposed in Chapter 5 of the book of D.G. Kleinbaum and M. Klein, "Logistic Regression", Statistics for Biology and Health, Springer Science Business Media, LLC (2010) and also by D. Chessel and A.B. Dufour in Lyon 1 (see Sect. 6 of http://pbil.univ-lyon1.fr/R/pdf/tdr341.pdf). This example is based on data given in the file evans.txt coming from http://www.sph.emory.edu/dkleinb/logreg3.htm#data.
Nam, Sang-Jip; Gaudêncio, Susana P; Kauffman, Christopher A; Jensen, Paul R; Kondratyuk, Tamara P; Marler, Laura E; Pezzuto, John M; Fenical, William
2010-06-25
Fijiolide A, a potent inhibitor of TNF-alpha-induced NFkappaB activation, along with fijiolide B, were isolated from a marine-derived bacterium of the genus Nocardiopsis. The planar structures of fijiolides A (1) and B (2) were elucidated by interpretation of 2D NMR spectroscopic data, while the absolute configurations of these compounds were defined by interpretation of circular dichroism and 2D NMR data combined with application of the advanced Mosher's method. Fijiolides A and B are related to several recently isolated chloroaromatic compounds, which appear to be the Bergman cyclization products of enediyne precursors. Fijiolide A reduced TNF-alpha-induced NFkappaB activation by 70.3%, with an IC(50) value of 0.57 micro-M. Fijiolide B demonstrated less inhibition, only 46.5%, without dose dependence. The same pattern was also observed with quinone reductase (QR) activity: fijiolide A was found to induce quinone reductase-1 (QR1) with an induction ratio of 3.5 at a concentration of 20 microg/mL (28.4 microM). The concentration required to double the activity was 1.8 microM. Fijiolide B did not affect QR1 activity, indicating the importance of the nitrogen substitution pattern for biological activity. On the basis of these data, fijiolide A is viewed as a promising lead for more advanced anticancer testing.
Ridge Regression: A Regression Procedure for Analyzing correlated Independent Variables
ERIC Educational Resources Information Center
Rakow, Ernest A.
1978-01-01
Ridge regression is a technique used to ameliorate the problem of highly correlated independent variables in multiple regression analysis. This paper explains the fundamentals of ridge regression and illustrates its use. (JKS)
Cuervo-Arango, J; Aguilar, J J; Vettorazzi, M L; Martínez-Boví, R
2015-10-01
The present study characterizes the relationship between the levels of eCG, ovarian morphology, resumption of cyclicity, and fertility in postaborted embryo transfer recipient mares. A total of 32 pregnant recipient mares carrying a male fetus were aborted at approximately 65 days of gestation by single transcervical administration of cloprostenol. In addition, 25 gestation age-matched mares were used as nonaborted controls. The concentration of progesterone, but not of eCG, differed significantly between controls and aborted mares 48 hours after abortion. Of treated mares, 84.4% (27 of 32) expelled the fetus within 48 hours of treatment. The eCG concentration and the number of supplementary luteal structures were lower in mares aborted in November (equivalent to May in Northern Hemisphere) than in January. A total of 6.2%, 37.5%, and 56.2% of the mares entered anestrus, ovulated normally, and had 1 to 2 consecutive anovulatory cycles, respectively. The mean interval from abortion to the first ovulation was 28.5 ± 3.3 days (range, 5-65 days). The correlation between the levels of eCG at abortion and the interval to the first ovulation was poor (r = 0.38; P = 0.03). Of aborted mares, 90% (18 of 20) were reused and became pregnant after embryo transfer at a mean of 57.6 ± 4.4 days after abortion (range, 19-103 days) and eCG concentration of 0.9 ± 0.3 IU/mL (range, 0.1-3.6 IU/mL). In conclusion, the levels of eCG at the time of abortion were extremely variable and did not correlate well with the number of luteal structures or the interval from abortion to the first ovulation.
Zhao, Xiaoming; Ji, Xiaowei; Hong, Yan; Wang, Yuan; Zhu, Qinling; Xu, Bin; Sun, Yun
2015-01-01
To compare Crinone vaginal progesterone gel with intramuscularly injected progesterone for luteal phase support in progesterone-supplemented frozen-thawed embryo transfer (FET) cycles, a randomized prospective study of patients qualified for FET was conducted between September 2010 and January 2013 at a hospital in Shanghai, China. From the day of transformation into secretory phase endometrium (day 0), Crinone vaginal gel (90 mg/d) was administered to patients in the Gel Group, while progesterone (40 mg/d) was injected intramuscularly in patients in the Inj Group (n = 750 per group). All patients received oral dydrogesterone (20 mg/d) and estradiol valerate (4–8 mg/d). Day 3 embryos with the highest pre-frozen scores were transferred to patients in the two groups and the clinical outcomes compared. This study comprised 1,500 cycles (750 in each group). Twenty-nine cycles in the Gel Group and 24 in the Inj Group were withdrawn. There were no significant differences between groups in age, endometrial thickness, endometrial preparation time or number of embryos transferred. No significant differences were observed between the Gel Group and Inj Group in the rates of live birth (32.6% vs. 31.7%, P = 0.71), clinical pregnancy (40.1% vs. 40.6%, P = 0.831), implantation (25.8% vs. 25.3%, P = 0.772), abortion (16.3% vs. 18.3%, P = 0.514) or ectopic pregnancy (2.8% vs. 4.4%, P = 0.288). Multivariate logistic regression analysis revealed that the odds ratios (95% confidence intervals) for the rates of live birth, clinical pregnancy, abortion and ectopic pregnancy (Gel Group relative to Inj Group) were 1.036 (0.829–1.295), 0.971 (0.785–1.200), 0.919 (0.595–1.420) and 0.649 (0.261–1.614), respectively. Our study revealed that using Crinone vaginal gel in FET cycles achieved similar pregnancy outcomes to intramuscular progesterone, indicating that vaginal gel is a viable alternative to intramuscular injection. Trial Registration Chinese Clinical Trial Registry Chi
Modern Regression Discontinuity Analysis
ERIC Educational Resources Information Center
Bloom, Howard S.
2012-01-01
This article provides a detailed discussion of the theory and practice of modern regression discontinuity (RD) analysis for estimating the effects of interventions or treatments. Part 1 briefly chronicles the history of RD analysis and summarizes its past applications. Part 2 explains how in theory an RD analysis can identify an average effect of…
Multiple linear regression analysis
NASA Technical Reports Server (NTRS)
Edwards, T. R.
1980-01-01
Program rapidly selects best-suited set of coefficients. User supplies only vectors of independent and dependent data and specifies confidence level required. Program uses stepwise statistical procedure for relating minimal set of variables to set of observations; final regression contains only most statistically significant coefficients. Program is written in FORTRAN IV for batch execution and has been implemented on NOVA 1200.
Explorations in Statistics: Regression
ERIC Educational Resources Information Center
Curran-Everett, Douglas
2011-01-01
Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This seventh installment of "Explorations in Statistics" explores regression, a technique that estimates the nature of the relationship between two things for which we may only surmise a mechanistic or predictive…
Weems, Yoshie S; Bridges, Phillip J; Jeoung, Myoungkun; Arreguin-Arevalo, J Alejandro; Nett, Torrance M; Vann, Rhonda C; Ford, Stephen P; Lewis, Andrew W; Neuendorff, Don A; Welsh, Thomas H; Randel, Ronald D; Weems, Charles W
2012-01-01
Previously, it was reported that chronic intra-uterine infusion of PGE(1) or PGE(2) every 4h inhibited luteolysis in ewes by altering luteal mRNA for luteinizing hormone (LH) receptors and unoccupied and occupied luteal LH receptors. However, estradiol-17β or PGE(2) given intra-uterine every 8h did not inhibit luteolysis in cows, but infusion of estradiol+PGE(2) inhibited luteolysis. In contrast, intra-luteal implants containing PGE(1) or PGE(2) in Angus or Brahman cows also inhibited the decline in circulating progesterone, mRNA for LH receptors, and loss of unoccupied and occupied receptors for LH to prevent luteolysis. The objective of this experiment was to determine how intra-luteal implants of PGE(1) or PGE(2) alter mRNA for prostanoid receptors and how this could influence luteolysis in Brahman or Angus cows. On day-13 Angus cows received no intra-luteal implant and corpora lutea were retrieved or Angus and Brahman cows received intra-luteal silastic implants containing Vehicle, PGE(1), or PGE(2) and corpora lutea were retrieved on day-19. Corpora lutea slices were analyzed for mRNA for prostanoid receptors (FP, EP1, EP2, EP3 (A-D), EP3A, EP3B, EP3C, EP3D, and EP4) by RT-PCR. Day-13 Angus cow luteal tissue served as pre-luteolytic controls. mRNA for FP receptors decreased in day-19 Vehicle controls compared to day-13 Vehicle controls regardless of breed. PGE(1) and PGE(2) up-regulated FP gene expression on day-19 compared to day-19 Vehicle controls regardless of breed. EP1 mRNA was not altered by any treatment. PGE(1) and PGE(2) down-regulated EP2 and EP4 mRNA compared to day-19 Vehicle controls regardless of breed. PGE(1) or PGE(2) up-regulated mRNA EP3B receptor subtype compared to day-19 Vehicle control cows regardless of breed. The similarities in relative gene expression profiles induced by PGE(1) and PGE(2) support their agonistic effects. We conclude that both PGE(1) and PGE(2) may prevent luteolysis by altering expression of mRNA for prostanoid
Liu, Ke; Qin, Cheng-Kun; Wang, Zhi-Yi; Liu, Su-Xia; Cui, Xian-Ping; Zhang, Dong-Yuan
2012-01-01
Tumor necrosis factor (TNF)-alpha-induced protein 8 (TNFAIP8 or TIPE) is a recently identified protein considered to be associated with carcinogenesis. To investigate its expression pattern in pancreatic cancer patients and to analyse its correlation with clinicopathological significance and the expression levels of epithelial growth factor receptor (EGFR), immunohistochemistry was performed to detect the TNFAIP8 and EGFR proteins in pancreatic cancers, pancreatitis tissues, and healthy controls. The results showed stronger staining of TNFAIP8 protein in pancreatic cancer tissues compared with normal pancreas tissue. Furthermore, in 56 patients with pancreatic cancer, the expression levels of TNFAIP8 in patients with low tumor stage was higher than that with high tumor stage, and correlated with tumor staging and lymph node metastasis (P<0.05). Furthermore, TNFAIP8 expression positively correlated with EGFR levels (r=0.671135, P<0.05). These results indicate that TNFAIP8 may play important roles in the progression of pancreatic cancer.
Calculating a Stepwise Ridge Regression.
ERIC Educational Resources Information Center
Morris, John D.
1986-01-01
Although methods for using ordinary least squares regression computer programs to calculate a ridge regression are available, the calculation of a stepwise ridge regression requires a special purpose algorithm and computer program. The correct stepwise ridge regression procedure is given, and a parallel FORTRAN computer program is described.…
Orthogonal Regression: A Teaching Perspective
ERIC Educational Resources Information Center
Carr, James R.
2012-01-01
A well-known approach to linear least squares regression is that which involves minimizing the sum of squared orthogonal projections of data points onto the best fit line. This form of regression is known as orthogonal regression, and the linear model that it yields is known as the major axis. A similar method, reduced major axis regression, is…
SOCS-1 and SOCS-3 inhibit IFN-alpha-induced expression of the antiviral proteins 2,5-OAS and MxA.
Vlotides, George; Sörensen, Astrid S; Kopp, Florian; Zitzmann, Kathrin; Cengic, Neziha; Brand, Stephan; Zachoval, Reinhart; Auernhammer, Christoph J
2004-07-30
Although the use of IFN-alpha in combination with ribavirin has improved the treatment efficacy of chronic hepatitis C virus (HCV) infection, 20-50% of patients still fail to eradicate the virus depending on the HCV genotype. Recently, overexpression of HCV core protein has been shown to inhibit IFN signaling and induce SOCS-3 expression. Aim of this study was to examine the putative role of SOCS proteins in IFN resistance. By Western blot analysis, a 4-fold induction of STAT-1/3 phosphorylation by IFN-alpha was observed in mock-transfected HepG2 clones. In contrast, IFN-induced STAT-1/3 phosphorylation was considerably downregulated by SOCS-1/3 overexpression. In mock-transfected cells, IFN-alpha induced 2',5'-OAS and myxovirus resistance A (MxA) promoter activity 40- to 80-fold and 10- to 35-fold, respectively, and this effect was abrogated in SOCS-1/3 overexpressing cells. As detected by Northern blot technique, IFN-alpha potently induced 2',5'-OAS and MxA mRNA expression in the control clones. Overexpression of SOCS-1 completely abolished both 2',5'-OAS and MxA mRNA expression, whereas SOCS-3 mainly inhibited 2',5'-OAS mRNA expression. Our results demonstrate that SOCS-1 and SOCS-3 proteins inhibit IFN-alpha-induced activation of the Jak-STAT pathway and expression of the antiviral proteins 2',5'-OAS and MxA. These data suggest a potential role of SOCS proteins in IFN resistance during antiviral treatment.
Steganalysis using logistic regression
NASA Astrophysics Data System (ADS)
Lubenko, Ivans; Ker, Andrew D.
2011-02-01
We advocate Logistic Regression (LR) as an alternative to the Support Vector Machine (SVM) classifiers commonly used in steganalysis. LR offers more information than traditional SVM methods - it estimates class probabilities as well as providing a simple classification - and can be adapted more easily and efficiently for multiclass problems. Like SVM, LR can be kernelised for nonlinear classification, and it shows comparable classification accuracy to SVM methods. This work is a case study, comparing accuracy and speed of SVM and LR classifiers in detection of LSB Matching and other related spatial-domain image steganography, through the state-of-art 686-dimensional SPAM feature set, in three image sets.
Dosiou, Chrysoula; Lathi, Ruth B; Tulac, Suzana; Huang, S-T Joseph; Giudice, Linda C
2004-05-01
Interaction between the endocrine and the immune systems has been suggested by observations of sexual dimorphism of the immune response, differential susceptibility to autoimmunity between the sexes, changes in autoimmune disease activity during the menstrual cycle and in pregnancy and in vitro studies of hormonal influence on cytokine production.We hypothesized that if there is hormonal regulation of the immune response, this would be manifest in peripheral blood leukocytes (PBLs) at different phases of the menstrual cycle. In this study, we describe gene profiling of PBLs from the follicular and luteal phases of the menstrual cycle. We observe important differences in immune gene expression, with significant down-regulation of the Th1 immune response in the luteal phase. A significant number of interferon (IFN)-related genes are amongst the downregulated genes. These results support significant hormonal regulation of the immune system and may have therapeutic implications in diseases of autoimmunity in women.
Ichimura, Ryohei; Shibutani, Makoto; Mizukami, Sayaka; Suzuki, Terumasa; Shimada, Yuko; Mitsumori, Kunitoshi
2010-02-01
We report a rare case of benign sex cord-stromal tumor consisted largely of luteoma with minor portion of Sertoli cell tumor located at the position of the left ovary excision in an 11-year-old ovariectomized bitch. Granulosa cell component was lacking, and both luteal and Sertoli cell portions were entirely positive for inhibin alpha and neuron-specific enolase, whereas luteoma portion alone was positive for Wilms' tumor-1 (WT1), immunohistochemically. The results suggest that this tumor is a possible complication of incomplete ovarian excision at the time of ovariectomy and consisted of uncommon hybrid of luteal and Sertoli cells to be diagnosed as an unclassified sex cord-stromal tumor if applied in human cases. WT1-expression pattern suggested the signature of the difference in the phenotype of these cell types.
Pirard, Céline; Loumaye, Ernest; Wyns, Christine
2015-01-01
Background. The aim of this pilot study was to evaluate intranasal buserelin for luteal phase support and compare its efficacy with standard vaginal progesterone in IVF/ICSI antagonist cycles. Methods. This is a prospective, randomized, open, parallel group study. Forty patients underwent ovarian hyperstimulation with human menopausal gonadotropin under pituitary inhibition with gonadotropin-releasing hormone antagonist, while ovulation trigger and luteal support were achieved using intranasal GnRH agonist (group A). Twenty patients had their cycle downregulated with buserelin and stimulated with hMG, while ovulation trigger was achieved using 10,000 IU human chorionic gonadotropin with luteal support by intravaginal progesterone (group B). Results. No difference was observed in estradiol levels. Progesterone levels on day 5 were significantly lower in group A. However, significantly higher levels of luteinizing hormone were observed in group A during the entire luteal phase. Pregnancy rates (31.4% versus 22.2%), implantation rates (22% versus 15.4%), and clinical pregnancy rates (25.7% versus 16.7%) were not statistically different between groups, although a trend towards higher rates was observed in group A. No luteal phase lasting less than 10 days was recorded in either group. Conclusion. Intranasal administration of buserelin is effective for providing luteal phase support in IVF/ICSI antagonist protocols. PMID:25945092
Goletiani, Nathalie V.; Siegel, Arthur J.; Lukas, Scott E.; Hudson, James I.
2015-01-01
Objectives To determine the acute effects of cigarette smoking on hypothalamic-pituitary-adrenal axis (HPA) hormones and subjective states as a function of the menstrual cycle in nicotine-dependent women. Methods Seventeen healthy nicotine-dependent women were studied during the follicular and/or luteal phase of the menstrual cycle. Due to observation of a possible bimodal distribution of progesterone levels within the luteal phase group, we performed a set of a posteriori analyses. Therefore, we divided the luteal group into a low progesterone and a high progesterone groups. Results Smoked nicotine activated HPA, measured by ACTH, cortisol, and DHEA response and affected subjective states in both follicular and luteal phases, with increased “High”, “Rush”, and decreased “Craving”. The HPA stimulation revealed a blunting of ACTH response. There was only modest evidence for a blunting of subjective state responses in the luteal phase. However upon post hoc analyses, the high progesterone luteal group showed a marked blunting of measures of subjective states and a blunted ACTH response. Examining the association between hormone and measures of subjective states revealed tentative associations of ACTH stimulation with increased “Rush” and “Craving”, and DHEA stimulation with increased “Craving”. Conclusions This pilot study suggests that menstrual cycle phase differences in progesterone levels may attenuate nicotine’s addictive effects via diminution of its reinforcing properties, and augmentation of its aversive effects interfering with the pleasure associated with cigarette smoking. PMID:25783522
Kramer, S.
1996-12-31
In many real-world domains the task of machine learning algorithms is to learn a theory for predicting numerical values. In particular several standard test domains used in Inductive Logic Programming (ILP) are concerned with predicting numerical values from examples and relational and mostly non-determinate background knowledge. However, so far no ILP algorithm except one can predict numbers and cope with nondeterminate background knowledge. (The only exception is a covering algorithm called FORS.) In this paper we present Structural Regression Trees (SRT), a new algorithm which can be applied to the above class of problems. SRT integrates the statistical method of regression trees into ILP. It constructs a tree containing a literal (an atomic formula or its negation) or a conjunction of literals in each node, and assigns a numerical value to each leaf. SRT provides more comprehensible results than purely statistical methods, and can be applied to a class of problems most other ILP systems cannot handle. Experiments in several real-world domains demonstrate that the approach is competitive with existing methods, indicating that the advantages are not at the expense of predictive accuracy.
Juengel, J L; Melner, M H; Clapper, J A; Turzillo, A M; Moss, G E; Nett, T M; Niswender, G D
1998-07-01
Prostaglandin F2 alpha (PGF2 alpha) decreases secretion of progesterone from the corpus luteum in domestic ruminants. However, it is less effective during the early part of the oestrous cycle (Louis et al., 1973) and at the time of maternal recognition of pregnancy (Silvia and Niswender, 1984; Lacroix and Kann, 1986). Decreased luteal responsiveness may be due to failure of PGF2 alpha to activate fully its normal second messenger system, protein kinase C (PKC). Alternatively, increased resistance of the corpus luteum to PGF2 alpha might be attributable to greater concentrations of recently identified biological inhibitors of PKC. These possibilities were addressed by measuring steady-state concentrations of mRNA encoding PGF2 alpha receptor and two inhibitors of PKC, protein kinase C inhibitor-1 (PKCI-1) and kinase C inhibitor protein-1 (KCIP-1, brain 14-3-3 protein), in corpora lutea collected from ewes on days 4, 10 and 15 of the oestrous cycle (n = 5 per day) and day 15 of pregnancy (n = 7). There were no differences in mean concentrations of mRNA encoding PGF2 alpha receptor among the groups. However, concentrations of mRNA encoding both inhibitors of PKC were higher (P < 0.01) on day 4 of the oestrous cycle compared with the other groups. Treatment of ewes with a luteolytic dose of PGF2 alpha, which activates PKC, did not change concentrations of mRNA encoding either PKCI-1 or KCIP-I up to 24 h later. Luteal expression of mRNA encoding the PKC inhibitors and PGF2 alpha receptor was also examined in ewes treated with oestradiol in vivo for 16 h in the midluteal phase. High concentrations of oestradiol in serum (20 and 70 pg ml-1) did not influence quantities of any of the mRNAs examined. Therefore, an increase in PKC inhibitors may be involved in resistance of the corpus luteum to PGF2 alpha during the early part of the oestrous cycle but does not appear to mediate the increased resistance of the corpus luteum to PGF2 alpha during maternal recognition of
Liu, Jianqi; Kuulasmaa, Tiina; Kosma, Veli-Matti; Bützow, Ralf; Vänttinen, Teemu; Hydén-Granskog, Christel; Voutilainen, Raimo
2003-10-01
Activins and inhibins are often antagonistic in the regulation of ovarian function. TGFbeta type III receptor, betaglycan, has been identified as a coreceptor to enhance the binding of inhibins to activin type II receptor and thus to prevent the binding of activins to their receptor. In this study we characterized the expression and regulation pattern of betaglycan gene in normal ovaries and sex cord-stromal tumors and in cultured human granulosa-luteal cells from women undergoing in vitro fertilization. Expression of betaglycan mRNA was detected by RT-PCR or Northern blotting in normal ovarian granulosa, thecal, and stroma cells as well as in granulosa-luteal cells. Immunohistochemical analysis revealed positive staining for betaglycan in antral and preovulatory follicular granulosa and thecal cells and in corpora lutea of normal ovaries. Furthermore, betaglycan expression was detected in the vast majority of granulosa cell tumors, thecomas, and fibromas, with weaker staining in granulosa cell tumors compared with fibrothecomas. In cultured granulosa-luteal cells, FSH and LH treatment increased dose-dependently the accumulation of betaglycan mRNA, as did the protein kinase A activator dibutyryl cAMP and the protein kinase C inhibitor staurosporine. In contrast, the protein kinase C activator 12-O-tetradecanoyl phorbol 13-acetate had no significant effect on betaglycan mRNA levels. Treatment with prostaglandin E(2) and with its receptor EP2 subtype agonist butaprost increased betaglycan mRNA accumulation and progesterone secretion dose- and time-dependently. In summary, betaglycan gene is expressed in normal human ovarian steroidogenic cells and sex cord-stromal ovarian tumors. The accumulation of its mRNA in cultured granulosa-luteal cells is up-regulated by gonadotropins and prostaglandin E(2), probably via the protein kinase A pathway. The specific expression and regulation pattern of betaglycan gene may be related to the functional antagonism of inhibins to
Martinez, Pedro E; Rubinow, David R; Nieman, Lynnette K; Koziol, Deloris E; Morrow, A Leslie; Schiller, Crystal E; Cintron, Dahima; Thompson, Karla D; Khine, Khursheed K; Schmidt, Peter J
2016-03-01
Changes in neurosteroid levels during the luteal phase of the menstrual cycle may precipitate affective symptoms. To test this hypothesis, we stabilized neurosteroid levels by administering the 5α-reductase inhibitor dutasteride to block conversion of progesterone to its neurosteroid metabolite allopregnanolone in women with premenstrual dysphoric disorder (PMDD) and in asymptomatic control women. Sixteen women with prospectively confirmed PMDD and 16 control women participated in one of two separate randomized, double-blind, placebo-controlled, cross-over trials, each lasting three menstrual cycles. After one menstrual cycle of single-blind placebo, participants were randomized to receive, for the next two menstrual cycles, either double-blind placebo or dutasteride (low-dose 0.5 mg/day in the first eight PMDD and eight control women or high-dose 2.5 mg/day in the second group of women). All women completed the daily rating form (DRF) and were evaluated in clinic during the follicular and luteal phases of each menstrual cycle. Main outcome measures were the DRF symptoms of irritability, sadness, and anxiety. Analyses were performed with SAS PROC MIXED. In the low-dose group, no significant effect of dutasteride on PMDD symptoms was observed compared with placebo (ie, symptom cyclicity maintained), and plasma allopregnanolone levels increased in women with PMDD from follicular to the luteal phases, suggesting the absence of effect of the low-dose dutasteride on 5α-reductase. In contrast, the high-dose group experienced a statistically significant reduction in several core PMDD symptoms (ie, irritability, sadness, anxiety, food cravings, and bloating) on dutasteride compared with placebo. Dutasteride had no effect on mood in controls. Stabilization of allopregnanolone levels from the follicular to the luteal phase of the menstrual cycle by blocking the conversion of progesterone to its 5α-reduced neurosteroid metabolite mitigates symptoms in PMDD. These data
Sierralta, Walter D; Kohen, Paulina; Castro, Olga; Muñoz, Alex; Strauss, Jerome F; Devoto, Luigi
2005-10-20
The distribution of the steroidogenic acute regulatory protein (StAR) inside thecal and granulosa-lutein cells of human corpus luteum (CL) was assessed by immunoelectron microscopy. We found greater levels of StAR immunolabeling in steroidogenic cells from early- and mid-than in late luteal phase CL and lower levels in cells from women treated with a GnRH antagonist in the mid-luteal phase. Immunoelectron microscopy revealed significant levels of StAR antigen in the mitochondria and in the cytoplasm of luteal cells. The 30 kDa mature StAR protein was present in both mitochondria and cytosol (post-mitochondrial) fractions from homogenates of CL at different ages, whereas cytochrome c and mitochondrial HSP70 were detected only in the mitochondrial fraction. Therefore, we hypothesized that either appreciable processing of StAR 37 kDa pre-protein occurs outside the mitochondria, or mature StAR protein is selectively released into the cytoplasm after mitochondrial processing. The presence of mature StAR in the cytoplasm is consonant with the notion that StAR acts on the outer mitochondrial membrane to effect sterol import, and that StAR may interact with other cytoplasmic proteins involved in cholesterol metabolism, including hormone sensitive lipase.
NASA Technical Reports Server (NTRS)
Kuhl, Mark R.
1990-01-01
Current navigation requirements depend on a geometric dilution of precision (GDOP) criterion. As long as the GDOP stays below a specific value, navigation requirements are met. The GDOP will exceed the specified value when the measurement geometry becomes too collinear. A new signal processing technique, called Ridge Regression Processing, can reduce the effects of nearly collinear measurement geometry; thereby reducing the inflation of the measurement errors. It is shown that the Ridge signal processor gives a consistently better mean squared error (MSE) in position than the Ordinary Least Mean Squares (OLS) estimator. The applicability of this technique is currently being investigated to improve the following areas: receiver autonomous integrity monitoring (RAIM), coverage requirements, availability requirements, and precision approaches.
Nintasen, Rungrat; Riches, Kirsten; Mughal, Romana S.; Viriyavejakul, Parnpen; Chaisri, Urai; Maneerat, Yaowapa; Turner, Neil A.; Porter, Karen E.
2012-04-20
Highlights: Black-Right-Pointing-Pointer TNF-{alpha} augments neointimal hyperplasia in human saphenous vein. Black-Right-Pointing-Pointer TNF-{alpha} induces detrimental effects on endothelial and smooth muscle cell function. Black-Right-Pointing-Pointer Estradiol exerts modulatory effects on TNF-induced vascular cell functions. Black-Right-Pointing-Pointer The modulatory effects of estradiol are discriminatory and cell-type specific. -- Abstract: Coronary heart disease (CHD) is a condition characterized by increased levels of proinflammatory cytokines, including tumor necrosis factor-{alpha} (TNF-{alpha}). TNF-{alpha} can induce vascular endothelial cell (EC) and smooth muscle cell (SMC) dysfunction, central events in development of neointimal lesions. The reduced incidence of CHD in young women is believed to be due to the protective effects of estradiol (E2). We therefore investigated the effects of TNF-{alpha} on human neointima formation and SMC/EC functions and any modulatory effects of E2. Saphenous vein (SV) segments were cultured in the presence of TNF-{alpha} (10 ng/ml), E2 (2.5 nM) or both in combination. Neointimal thickening was augmented by incubation with TNF-{alpha}, an effect that was abolished by co-culture with E2. TNF-{alpha} increased SV-SMC proliferation in a concentration-dependent manner that was optimal at 10 ng/ml (1.5-fold increase), and abolished by E2 at all concentrations studied (1-50 nM). Surprisingly, E2 itself at low concentrations (1 and 5 nM) stimulated SV-SMC proliferation to a level comparable to that of TNF-{alpha} alone. SV-EC migration was significantly impaired by TNF-{alpha} (42% of control), and co-culture with E2 partially restored the ability of SV-EC to migrate and repair the wound. In contrast, TNF-{alpha} increased SV-SMC migration by 1.7-fold, an effect that was completely reversed by co-incubation with E2. Finally, TNF-{alpha} potently induced ICAM-1 and VCAM-1 expression in both SV-EC and SV-SMC. However there
Xu, Runbing; Shao, Zengwu; Xiong, Liming
2008-10-01
The inhibitory effect of niacinamide on tumor necrosis factor-alpha (TNF-alpha) induced annulus fibrous (AF) degradation was assessed, and the mechanism of the inhibition was investigated. Chiba's intervertebral disc (IVD) culture model was established. Forty-eight IVDs from 12 adult Japanese white rabbits were randomly divided into 4 groups (12 IVDs in each group), and various concentrations of niacinamide and TNF-alpha were added to the medium for intervention: negative control group, niacinamide control group (0.5 mg/mL niacinamide), degeneration group (10 ng/mL TNF-alpha), and treatment group (0.5 mg/mL niacinamide and 10 ng/mL TNF-alpha). After one week's culture, AFs were collected for glycosaminoglycan (GS) content measurement, safranin O-fast green staining, and immunohistochemical staining for type I, II collagen and cysteine containing aspartate specific protease-3 (Caspase-3). It was found that the GS content in treatment group was increased by about 48% as compared with degeneration group (t=16.93, P<0.001), and close to that in niacinamide control group (t=0.71, P=0.667). Safranine O-fast green staining exhibited higher staining density and better histological structure of AF in the treatment group as compared with the degeneration group. Immunohistochemical staining for both Type I and II collagen demonstrated that lamellar structure and continuity of collagen in treatment group were better reserved than in degeneration group. Positive staining rate of Caspase-3 in AFs of negative control group, niacinamide control group, degeneration group and treatment group was 3.4%, 4.3%, 17.9% and 10.3% respectively. The positive rate in treatment group was significantly lower than in degeneration group (P<0.01). It was concluded that niacinamide could effectively alleviate TNF-alpha induced destruction and synthesis inhibition of matrix ingredients in AFs. The inhibition may be related with reduction of expression of Caspase-3. Thus, niacinamide is of potential
Peng, Cheng-Fei; Han, Ya-Ling; Jie-Deng,; Yan, Cheng-Hui; Jian-Kang,; Bo-Luan,; Jie-Li
2011-03-25
Research highlights: {yields} CREG protected MSCs from tumor necrosis factor-{alpha} (TNF-{alpha}) induced apoptosis. {yields} CREG inhibits the phosphorylation of I{kappa}B{alpha} and prevents the activation of NF-{kappa}B. {yields} CREG inhibits NF-{kappa}B nuclear translocation and pro-apoptosis protein transcription. {yields} CREG anti-apoptotic effect involves inhibition of the death receptor pathway. {yields} p53 is downregulated by CREG via NF-{kappa}B pathway under TNF-{alpha} stimulation. -- Abstract: Bone marrow-derived mesenchymal stem cells (MSCs) show great potential for therapeutic repair after myocardial infarction. However, poor viability of transplanted MSCs in the ischemic heart has limited their use. Cellular repressor of E1A-stimulated genes (CREG) has been identified as a potent inhibitor of apoptosis. This study therefore aimed to determine if rat bone marrow MSCs transfected with CREG-were able to effectively resist apoptosis induced by inflammatory mediators, and to demonstrate the mechanism of CREG action. Apoptosis was determined by flow cytometric and terminal deoxynucleotidyl transferase-mediated dUTP-biotin nick end-labeling assays. The pathways mediating these apoptotic effects were investigated by Western blotting. Overexpression of CREG markedly protected MSCs from tumor necrosis factor-{alpha} (TNF-{alpha}) induced apoptosis by 50% after 10 h, through inhibition of the death-receptor-mediated apoptotic pathway, leading to attenuation of caspase-8 and caspase-3. Moreover, CREG resisted the serine phosphorylation of I{kappa}B{alpha} and prevented the nuclear translocation of the transcription factor nuclear factor-{kappa}B (NF-{kappa}B) under TNF-{alpha} stimulation. Treatment of cells with the NF-{kappa}B inhibitor pyrrolidine dithiocarbamate (PDTC) significantly increased the transcription of pro-apoptosis proteins (p53 and Fas) by NF-{kappa}B, and attenuated the anti-apoptotic effects of CREG on MSCs. The results of this study
Stewart, Rosemary A.; Pelican, Katharine M.; Crosier, Adrienne E.; Pukazhenthi, Budhan S.; Wildt, David E.; Ottinger, Mary Ann; Howard, JoGayle
2012-01-01
ABSTRACT As the only domesticated species known to exhibit both induced and spontaneous ovulation, the cat is a model for understanding the nuances of ovarian control. To explore ovarian sensitivity to exogenous gonadotropins and the influence of progestin priming, we conducted a study of queens that were down-regulated with oral progestin or allowed to cycle normally, followed by low or high doses of equine chorionic gonadotropin (eCG) and human chorionic gonadotropin (hCG). Our metrics included 1) fecal steroid metabolite profiles before and after ovulation induction, 2) laparoscopic examination of ovarian follicles and corpora lutea (CL) on Days 2 and 17 (Day 0 = hCG administration), and 3) ovariohysterectomy (Day 17) to assess CL progesterone concentrations, morphometrics, and histology. Reproductive tracts from time-matched, naturally mated queens (n = 6) served as controls. Every progestin-primed cat (n = 12) produced the desired response of morphologically similar, fresh CL (regardless of eCG/hCG dose) by Day 2, whereas 41.7% of unprimed counterparts (n = 12) failed to ovulate or had variable-aged CL suggestive of prior spontaneous ovulation (P < 0.05). The ovarian response to low, but not high, eCG/hCG was improved (P < 0.05) in primed compared to unprimed cats, indicating increased sensitivity to gonadotropin in the progestin-primed ovary. Progestin priming prevented hyperelevated fecal steroid metabolites and normalized CL progesterone capacity, but only when combined with low eCG/hCG. However, priming failed to prevent ancillary CL formation, smaller CL mass, or abnormal luteal cell density, which were common to all eCG/hCG-treated cats. Thus, the domestic cat exposed to eCG/hCG produces CL with structural and functional aberrations. These anomalies can be partially mitigated by progestin priming, possibly due to a protective effect of progestin associated with enhanced ovarian sensitivity to gonadotropins. PMID:23100619
Slit2/Robo4 Signaling: Potential Role of a VEGF-Antagonist Pathway to Regulate Luteal Permeability
Bekes, I.; Haunerdinger, V.; Sauter, R.; Holzheu, I.; Janni, W.; Wöckel, A.; Wulff, C.
2017-01-01
Introduction The corpus luteum (CL) is dependent on luteal vascular permeability, which is controlled by human chorionic gonadotropin (hCG) via vascular endothelial growth factor (VEGF). In this study we investigated the role of a potential VEGF antagonist pathway – Slit2/Robo4 – and its influence on endothelial cell adhesion. Materials and Methods Luteinized granulosa cells (LGCs) were stimulated with hCG in the absence or presence of a VEGF inhibitor. The expression of VEGF and Slit2 were measured. Human umbilical vein endothelial cells (HUVECs) were stimulated with Slit2 or VEGF, and gene expressions of cadherin 5 (CDH5) and claudin 5 (CLDN5) were measured. Following Robo4 knockdown, CDH5, CLDN5 and endothelial permeability were measured. Results Stimulation of human LGCs with hCG significantly increased VEGF while Slit2 expression was significantly suppressed. Inhibition of VEGF action after hCG stimulation did not change Slit2 suppression. Slit2 knockdown did not affect VEGF expression. While VEGF stimulation of HUVECs significantly suppressed CDH5 and CLDN5 gene expression, stimulation of HUVECs with Slit2 resulted in a significant increase in CDH5 and CLDN5. Robo4 knockdown was done, leading to downregulation of CDH5 and CLDN5 which resulted in significantly increased permeability. Conclusions Our results indicate the existence of a VEGF-antagonist pathway in the CL that decreases vascular permeability. During the functional life of the CL the pathway is suppressed by hCG. It is possible that stimulation of this pathway could be used to treat ovarian hyperstimulation syndrome. PMID:28190892
Ballantyne, K; Matson, P; Noakes, N; Nicolson, V; Johnston, S D
2009-01-01
Endocrinology of the oestrous cycle, pregnancy and early lactation was investigated in captive Western Australian greater bilbies (Macrotis lagotis). Initially, six females were monitored for changes in urogenital cytology, plasma progestogen, pericloacal and pouch morphology in the absence of a male. This was followed by the introduction of a male and a reproductive assessment through mating, gestation and early lactation. In the absence of a male, there was no cyclical pattern of urogenital cytology, pericloacal or pouch development, and progestogen concentrations remained basal. Within 5 days of the introduction of a male, all females had a karyopycnotic index of 100%. Spermatozoa were present in the urogenital smear within 3 days of male introduction in all five females that gave birth. Five to 9 days after the introduction of a male, there was an increase in plasma progestogen concentration that remained elevated for 14-19 days. Six of the seven females gave birth approximately 3 days after reaching peak plasma progestogen concentrations. Gestation length ranged between 14 and 17 days. Plasma progestogen concentrations of the postpartum and early lactation period were lower (P < 0.0001) than during gestation, but greater (P < 0.0001) than those recorded before the introduction of a male. One female that gave birth early in the study that was examined until weaning of the pouch young showed a cyclical pattern of plasma progestogen secretion that ended at weaning. This study provides evidence that the luteal phase in the greater bilby is induced by the presence of a male. Similar to female reproductive physiology in the Peramelidae, elevated progestogen concentration in the greater bilby was extended into lactation.
Saharkhiz, Nasrin; Zamaniyan, Marzieh; Salehpour, Saghar; Zadehmodarres, Shahrzad; Hoseini, Sedighe; Cheraghi, Leila; Seif, Samira; Baheiraei, Nafiseh
2016-01-01
The aim of the present study was to compare the efficacy, tolerability and patients' satisfaction after the use of oral dydrogesterone with vaginal micronized progesterone for luteal-phase support (LPS) among infertile women undergoing in vitro fertilization (IVF). A total of 210 women (aged 20-40 years old) with a history of infertility, who underwent controlled ovarian stimulation for fresh intra-cytoplasmic sperm injection-embryo transfer cycles, were included in the study. Consequently, they were randomized to receive LPS with dydrogesterone 20 mg twice daily (n = 96) or micronized progesterone 400 mg twice daily at the day of oocyte retrieval (n = 114). The clinical success rate (31% versus 33%; p = 0.888), miscarriage rate (5.0% versus 3.0%; p = 0.721), ongoing pregnancy rate (30.0% versus 30.0%; p = 1.000), implantation (22.0% versus 24.0%; p = 0.254) and multiple pregnancy rate (5.30% versus 7.20%; p = 0.394) were comparable among the two groups. Serum progesterone levels were significantly lower among the patients receiving dydrogesterone than the control group (13.62 ± 13.83 ng/ml versus 20.66 ± 18.09 ng/ml; p = 0.001). However, there was no statistically significant difference regarding the patients' satisfaction (p = 0.825) and tolerability (0.790) between the two groups. Our results showed that oral dydrogesterone (40 mg/day) is as effective as vaginal micronized progesterone considering its clinical outcomes and patients' satisfaction and tolerability, for LPS among women undergoing IVF.
Evaluating differential effects using regression interactions and regression mixture models
Van Horn, M. Lee; Jaki, Thomas; Masyn, Katherine; Howe, George; Feaster, Daniel J.; Lamont, Andrea E.; George, Melissa R. W.; Kim, Minjung
2015-01-01
Research increasingly emphasizes understanding differential effects. This paper focuses on understanding regression mixture models, a relatively new statistical methods for assessing differential effects by comparing results to using an interactive term in linear regression. The research questions which each model answers, their formulation, and their assumptions are compared using Monte Carlo simulations and real data analysis. The capabilities of regression mixture models are described and specific issues to be addressed when conducting regression mixtures are proposed. The paper aims to clarify the role that regression mixtures can take in the estimation of differential effects and increase awareness of the benefits and potential pitfalls of this approach. Regression mixture models are shown to be a potentially effective exploratory method for finding differential effects when these effects can be defined by a small number of classes of respondents who share a typical relationship between a predictor and an outcome. It is also shown that the comparison between regression mixture models and interactions becomes substantially more complex as the number of classes increases. It is argued that regression interactions are well suited for direct tests of specific hypotheses about differential effects and regression mixtures provide a useful approach for exploring effect heterogeneity given adequate samples and study design. PMID:26556903
Production of A=16, 20 and 24 in alpha-induced fragmentation of ^28Si at 102.7 (cm) MeV
NASA Astrophysics Data System (ADS)
Sabra, Mohammad S.; Bary Malik, F.
2004-10-01
The emission probabilities of particles of mass numbers 16, 20 and 24 in 102.7 (cm) MeV alpha-induced fragmentation of ^28Si have been calculated using the statistical model of [1]. This model is distinct from the usual evaporation model in the sense that it takes into account the final state interaction between two emerging fragments. Calculated emission probabilities indicate that particles are emitted in all possible excited states commensurate with energy conservation law. The emission spectra as a function of excitation energy and the most probable kinetic energy associated with it will be presented. Calculated differential cross sections at 30^o for these masses are in agreement with the data of [2]. The final state interaction is obtained by a scaling procedure. The emission probabilities of different isotopes of these masses will also be presented. 1. B. Compani-Tabrizi and F. B. Malik, J. Phys. G: Nucl. Phys. 8, 1447 (1982). 2. L. W. Woo et al. Phys. Rev. C 47, 267 (1993).
Garcia, J A; Ferreira, H L; Vieira, F V; Gameiro, R; Andrade, A L; Eugênio, F R; Flores, E F; Cardoso, T C
2015-09-16
Oncolytic virotherapy is a novel strategy for treatment of cancer in humans and companion animals as well. Canine distemper virus (CDV), a paramyxovirus, has proven to be oncolytic through induction of apoptosis in canine-derived tumour cells, yet the mechanism behind this inhibitory action is poorly understood. In this study, three human mammary tumour cell lines and one canine-derived adenofibrosarcoma cell line were tested regarding to their susceptibility to CDV infection, cell proliferation, apoptosis, mitochondrial membrane potential and expression of tumour necrosis factor-alpha-induced protein 8 (TNFAIP8). CDV replication-induced cytopathic effect, decrease of cell proliferation rates, and >45% of infected cells were considered death and/or under late apoptosis/necrosis. TNFAIP8 and CDVM gene expression were positively correlated in all cell lines. In addition, mitochondrial membrane depolarization was associated with increase in virus titres (p < 0.005). Thus, these results strongly suggest that both human and canine mammary tumour cells are potential candidates for studies concerning CDV-induced cancer therapy.
Hao, Qiang; Li, Weina; Zhang, Cun; Qin, Xin; Xue, Xiaochang; Li, Meng; Shu, Zhen; Xu, Tianjiao; Xu, Yujin; Wang, Weihua; Zhang, Wei; Zhang, Yingqi
2013-01-04
Highlights: Black-Right-Pointing-Pointer FOXP3 inhibition of cell proliferation is p21-dependent under basal conditions. Black-Right-Pointing-Pointer Inflammation induced by TNF{alpha} inhibits the tumor suppressor role of FOXP3. Black-Right-Pointing-Pointer Interaction between p65 and FOXP3 inhibits p21 transcription activation. -- Abstract: Controversial roles of FOXP3 in different cancers have been reported previously, while its role in gastric cancer is largely unknown. Here we found that FOXP3 is unexpectedly upregulated in some gastric cancer cells. To test whether increased FOXP3 remains the tumor suppressor role in gastric cancer as seen in other cancers, we test its function in cell proliferation both at basal and TNF{alpha} mimicked inflammatory condition. Compared with the proliferation inhibitory role observed in basal condition, FOXP3 is insufficient to inhibit the cell proliferation under TNF{alpha} treatment. Molecularly, we found that TNF{alpha} induced an interaction between FOXP3 and p65, which in turn drive the FOXP3 away from the promoter of the well known target p21. Our data here suggest that although FOXP3 is upregulated in gastric cancer, its tumor suppressor role has been dampened due to the inflammation environment.
Kwon, Oh Eok; Lee, Hyun Sun; Lee, Seung Woong; Chung, Mi Yeon; Bae, Ki Hwan; Rho, Mun-Chual; Kim, Young-Kook
2005-01-01
Leukocyte adhesion to the vascular endothelium is a critical initiating step in inflammation and atherosclerosis. We have herein studied the effect of manassantin A (1) and B (2), dineolignans, on interaction of THP-1 monocytic cells and human umbilical vein endothelial cells (HUVEC) and expression of intercellular adhesion molecule-1 (ICAM-1), vascular cell adhesion molecule-1 (VCAM-1), and E-selectin in HUVEC. When HUVEC were pretreated with 1 and 2 followed by stimulation with TNF-alpha, adhesion of THP-1 cells to HUVEC decreased in dose-dependent manner with IC50 values of 5 ng/mL and 7 ng/mL, respectively, without cytotoxicity. Also, 1 and 2 inhibited TNF-alpha-induced up-regulation of ICAM-1, VCAM-1 and E-selectin. The present findings suggest that 1 and 2 prevent monocyte adhesion to HUVEC through the inhibition of ICAM-1, VCAM-1 and E-selectin expression stimulated by TNF-alpha, and may imply their usefulness for the prevention of atherosclerosis relevant to endothelial activation.
Clementi, Marisa A; Deis, Ricardo P; Telleria, Carlos M
2004-01-01
Background In the rat, the maintenance of gestation is dependent on progesterone production from the corpora lutea (CL), which are under the control of pituitary, decidual and placental hormones. The luteal metabolism of progesterone during gestation has been amply studied. However, the regulation of progesterone synthesis and degradation during pseudopregnancy (PSP), in which the CL are mainly under the control of pituitary prolactin (PRL), is not well known. The objectives of this investigation were: i) to study the luteal metabolism of progesterone during PSP by measuring the activities of the enzymes 3beta-hydroxysteroid dehydrogenase (3betaHSD), involved in progesterone biosynthesis, and that of 20alpha-hydroxysteroid dehydrogenase (20alphaHSD), involved in progesterone catabolism; and ii) to determine the role of decidualization on progesterone metabolism in PSP. Methods PSP was induced mechanically at 10:00 h on the estrus of 4-day cycling Wistar rats, and the stimulus for decidualization was provided by scratching the uterus on day 4 of PSP. 3betaHSD and 20alphaHSD activities were measured in the CL isolated from ovaries of PSP rats using a spectrophotometric method. Serum concentrations of progesterone, PRL, androstenedione, and estradiol were measured by radioimmunoassay (RIA). Results The PSP stage induced mechanically in cycling rats lasted 11.3 ± 0.09 days (n = 14). Serum progesterone concentration was high until day 10 of PSP, and declined thereafter. Serum PRL concentration was high on the first days of PSP but decreased significantly from days 6 to 9, having minimal values on days 10 and 11. Luteal 3betaHSD activities were elevated until day 6 of PSP, after which they progressively declined, reaching minimal values at the end of PSP. Luteal 20alphaHSD activities were very low until day 9, but abruptly increased at the end of PSP. When the deciduoma was induced by scratching the uterus of pseudopregnant animals on day 4 (PSP+D), PSP was extended to
Khrouf, Mohamed; Slimani, Soufiene; Khrouf, Myriam Razgallah; Braham, Marouen; Bouyahia, Maha; Berjeb, Khadija Kacem; Chaabane, Hanene Elloumi; Merdassi, Ghaya; Kaffel, Aida Zahaf; Zhioua, Amel; Zhioua, Fethi
2016-01-01
BACKGROUND In IVF, Luteal phase support is usually performed using vaginal progesterone. A part of patients using this route reports being uncomfortable with this route. We tried to study whether the rectal route could be an effective alternative and associated with less discomfort. PATIENTS AND METHODS A prospective randomized controlled study. All patient were eligible for IVF treatment for infertility. After oocyte pickup, 186 patients were allocated to one the following protocols for luteal phase support: (i) rectal pessaries group: natural progesterone pessaries administered rectally 200 mg three times a day, (ii) vaginal pessaries group: natural progesterone pessaries administered vaginally 200 mg three times a day), and (iii) vaginal capsules group: natural micronized progesterone capsules administered vaginally 200 mg three times a day. On the day of pregnancy test, patients were asked to fill in a questionnaire conducted by an investigator in order to assess the tolerability and side effects of the LPS treatment taken. The primary endpoint was the occurrence of perineal irritation. RESULTS Fifty eight patients were assigned to the rectal pessaries group, 68 patients to the vaginal pessaries group, and 60 patients to the vaginal capsules group. All patients adhered to their allocated treatment. Implantation and clinical pregnancy rates per transfer did not differ between the three groups. Perineal irritation, which was our primary endpoint, was the same for all the three groups (respectively 1.7 % versus 5.9 % versus 11.7%). Regarding the other side effects, more patients experienced constipation and flatulence with the rectal route, whereas more patients reported vaginal discharge in the vaginal capsules group. CONCLUSION Rectal administration for luteal phase support is effective and well accepted alternative to vaginal route. PMID:28096703
LÓPEZ-GATIUS, Fernando; LÓPEZ-HELGUERA, Irene; DE RENSIS, Fabio; GARCIA-ISPIERTO, Irina
2015-01-01
This study compared the responses shown by lactating dairy cows to four different P4-based protocols for AI at estrus. Cows with no estrous signs 96 h after progesterone intravaginal device (PRID) removal were subjected to fixed-time AI (FTAI), and their data were also included in the study. In Experiment I, follicular/luteal and endometrial dynamics were assessed every 12 h from the beginning of treatment until AI. The estrous response was examined in Experiment II, and fertility was assessed in both experiments. The protocols consisted of a PRID fitted for five days, along with the administration of different combinations of gonadotropin releasing hormone (GnRH), equine chorionic gonadotropin and a single or double dose (24 h apart) of prostaglandin F2α. In Experiment I (40 cows), animals receiving GnRH at the start of treatment showed a significantly higher ovulation rate during the PRID insertion period while estrus was delayed. In Experiment II (351 cows), according to the odds ratios, cows showing luteal activity at the time of treatment were less likely to show estrus than cows with no signs of luteal activity. Treatment affected the estrous response and the interval from PRID removal to estrus but did not affect conception rates 28–34 days post AI. Primiparous cows displayed a better estrous response than multiparous cows. Our findings reveal acceptable results of 5-day P4-based protocols for AI at estrus in high-producing dairy cows. Time from treatment to estrus emerged as a good guide for FTAI after a 5-day P4-based synchronization protocol. PMID:26211922
Emam, Mahmoud Abdelghaffar; Abouelroos, Mahmoud E A; Gad, Fatma A
2016-06-01
Uteri of mature Egyptian buffalo cows (5-10 years old) were collected at follicular (n=12) and luteal (n=16) phases of estrous cycle to investigate the expression of calbindin-D9k (CaPB-9k) and vitamin D receptor (VDR). This study was done using avidin-biotin immunohistochemistry method. In addition, blood levels of calcium (Ca), vitamin D3 (Vit D), estrogen (E2) and progesterone (P4) were measured. The immunohistochemical findings restricted the expressions of CaBP-9k and VDR to the luminal and glandular epithelia of the endometrium implicating the importance of CaBP-9K and VDR in the function of endometrial epithelium, especially the glandular one, in order to prepare a receptive uterus. On the other hand, the myometrium did not express CaBP-9k or VDR that denies the potential role of CaBP-9k and VDR in the uterine contractility during the estrous cycle of Egyptian buffalo. All of Ca, Vit D, and P4 blood levels significantly (P<0.05) increased during luteal phase however, blood level of E2 significantly (P<0.05) increased during follicular phase. The expressions of CaBP-9k and VDR in the uterus of Egyptian buffalo were significantly (P<0.05) higher during luteal (P4 dominant) phase than during the follicular (E2 dominant) phase indicating that P4 up-regulates the expressions of CaBP-9k and VDR. In view of these observations, this study represents the first characterization of CaBP-9K and VDR expression in the uterus of Egyptian buffalo and suggests the pivotal role of CaBP-9k and VDR in the uterine receptivity. Furthermore, it demonstrates the regulatory role of P4 for expressions of CaBP-9k and VDR in buffalo uterus.
Evaluating Differential Effects Using Regression Interactions and Regression Mixture Models
ERIC Educational Resources Information Center
Van Horn, M. Lee; Jaki, Thomas; Masyn, Katherine; Howe, George; Feaster, Daniel J.; Lamont, Andrea E.; George, Melissa R. W.; Kim, Minjung
2015-01-01
Research increasingly emphasizes understanding differential effects. This article focuses on understanding regression mixture models, which are relatively new statistical methods for assessing differential effects by comparing results to using an interactive term in linear regression. The research questions which each model answers, their…
Error bounds in cascading regressions
Karlinger, M.R.; Troutman, B.M.
1985-01-01
Cascading regressions is a technique for predicting a value of a dependent variable when no paired measurements exist to perform a standard regression analysis. Biases in coefficients of a cascaded-regression line as well as error variance of points about the line are functions of the correlation coefficient between dependent and independent variables. Although this correlation cannot be computed because of the lack of paired data, bounds can be placed on errors through the required properties of the correlation coefficient. The potential meansquared error of a cascaded-regression prediction can be large, as illustrated through an example using geomorphologic data. ?? 1985 Plenum Publishing Corporation.
Nayak, N R; Sengupta, J; Ghosh, D
1998-08-01
Luteal phase administration of mifepristone provides a significant degree of pregnancy protection to monkeys and women. Among several proposed mediators of the antinidatory action of luteal phase mifepristone, prostaglandins (PG) at the endometrial level appear important, and was examined in the present study using the rhesus monkey as the primate model. To this end, the concentrations of PGE2 and PGF2 alpha in endometrium and the profiles of cyclooxygenase (COX) and 15-hydroxy prostaglandin dehydrogenase (PGDH) were examined in untreated control animals, in animals subjected to mifepristone treatment (2 mg/day) alone or along with diclofenac (25 mg/day), or along with a PGE1 analog (100 micrograms misoprostol), in animals subjected to diclofenac alone treatment, and in animals treated with misoprostol alone on cycle days 16, 17, and 18. Tissue samples were collected on day 20 of treatment cycles from animals with discernible corpora lutea. Early luteal phase treatment with diclofenac did not result in any remarkable change in endometrial prostaglandin concentrations, however, there was an increase in the profile of COX. Animals exposed to misoprostol in the prereceptive stage, on the other hand, exhibited decreased expression of endometrial COX. The concentrations of PGF2 alpha and PGE2, as well as the ratios of PGF2 alpha to PGE2 concentrations, were increased along with a decrease in COX and PGD in endometrial samples following luteal phase mifepristone treatment. Although the underlying cellular mechanism of regulation of COX and PGDH in mifepistone-treated endometrium remains to be examined, the decrease in PG catabolism through low PGDH may contribute to the increased PG and high ratio of PGF2 alpha to PGE2 in mifepristone-exposed endometrium. It is plausible that mifepristone action on endometrial cells is mediated by an altered ratio of PGF2 alpha to PGE2. Furthermore, it appears that the regulation of PG milieu by COX and PGDH activities in reproductive
NASA Technical Reports Server (NTRS)
Pavalko, Fredrick M.; Gerard, Rita L.; Ponik, Suzanne M.; Gallagher, Patricia J.; Jin, Yijun; Norvell, Suzanne M.
2003-01-01
In bone, a large proportion of osteoblasts, the cells responsible for deposition of new bone, normally undergo programmed cell death (apoptosis). Because mechanical loading of bone increases the rate of new bone formation, we hypothesized that mechanical stimulation of osteoblasts might increase their survival. To test this hypothesis, we investigated the effects of fluid shear stress (FSS) on osteoblast apoptosis using three osteoblast cell types: primary rat calvarial osteoblasts (RCOB), MC3T3-E1 osteoblastic cells, and UMR106 osteosarcoma cells. Cells were treated with TNF-alpha in the presence of cyclohexamide (CHX) to rapidly induce apoptosis. Osteoblasts showed significant signs of apoptosis within 4-6 h of exposure to TNF-alpha and CHX, and application of FSS (12 dyne/cm(2)) significantly attenuated this TNF-alpha-induced apoptosis. FSS activated PI3-kinase signaling, induced phosphorylation of Akt, and inhibited TNF-alpha-induced activation of caspase-3. Inhibition of PI3-kinase, using LY294002, blocked the ability of FSS to rescue osteoblasts from TNF-alpha-induced apoptosis and blocked FSS-induced inhibition of caspase-3 activation in osteoblasts treated with TNF-alpha. LY294002 did not, however, prevent FSS-induced phosphorylation of Akt suggesting that activation of Akt alone is not sufficient to rescue cells from apoptosis. This result also suggests that FSS can activate Akt via a PI3-kinase-independent pathway. These studies demonstrate for the first time that application of FSS to osteoblasts in vitro results in inhibition of TNF-alpha-induced apoptosis through a mechanism involving activation of PI3-kinase signaling and inhibition of caspases. FSS-induced activation of PI3-kinase may promote cell survival through a mechanism that is distinct from the Akt-mediated survival pathway. Copyright 2002 Wiley-Liss, Inc.
Logistic Regression: Concept and Application
ERIC Educational Resources Information Center
Cokluk, Omay
2010-01-01
The main focus of logistic regression analysis is classification of individuals in different groups. The aim of the present study is to explain basic concepts and processes of binary logistic regression analysis intended to determine the combination of independent variables which best explain the membership in certain groups called dichotomous…
Precision Efficacy Analysis for Regression.
ERIC Educational Resources Information Center
Brooks, Gordon P.
When multiple linear regression is used to develop a prediction model, sample size must be large enough to ensure stable coefficients. If the derivation sample size is inadequate, the model may not predict well for future subjects. The precision efficacy analysis for regression (PEAR) method uses a cross- validity approach to select sample sizes…
Nahar, Asrafun; Kadokawa, Hiroya
2016-07-28
Whether macrophage migration inhibitory factor (MIF) in the bovine oviduct is important for early embryogenesis has not been well substantiated. The aim of the present study was to test the hypothesis that bovine oviduct expresses higher levels of MIF during the post-ovulation phase. Both ampullary and isthmic samples were collected from Japanese black heifers during oestrus (Day 0; n=5), postovulation (Day 3; n=6) and luteal phase (Days 9-12; n=5). MIF mRNA and protein were extracted from the ampullary and isthmic samples and their levels measured by real-time polymerase chain reaction and western blot analysis respectively. Fluorescent immunohistochemistry was performed on frozen ampullary and isthmic sections using antibodies against MIF. MIF mRNA and protein expression was higher in the postovulatory phase than during oestrus and the luteal phase (P<0.05). Fluorescent immunohistochemistry confirmed that in all phases of the oestrous cycle evaluated, the primary site of MIF expression in the ampulla and isthmus was the tunica mucosa. In conclusion, the bovine ampulla and isthmus have higher MIF expression during the postovulatory phase. Further studies are needed to clarify the role of MIF in bovine oviducts.
Vishwanathan, Sundaram A; Guenthner, Patricia C; Lin, Carol Y; Dobard, Charles; Sharma, Sunita; Adams, Debra R; Otten, Ron A; Heneine, Walid; Hendry, R Michael; McNicholl, Janet M; Kersh, Ellen N
2011-08-01
Fluctuations in susceptibility to HIV or SHIV during the menstrual cycle are currently not fully documented. To address this, the time point of infection was determined in 19 adult female pigtail macaques vaginally challenged during their undisturbed menstrual cycles with repeated, low-dose SHIV(SF162P3) exposures. Eighteen macaques (95%) first displayed viremia in the follicular phase, as compared with 1 macaque (5%) in the luteal phase (P < 0.0001). Due to a viral eclipse phase, we estimated a window of most frequent virus transmission between days 24 and 31 of the menstrual cycle, in the late luteal phase. Thus, susceptibility to vaginal SHIV infection is significantly elevated in the second half of the menstrual cycle when progesterone levels are high and when local immunity may be low. Such susceptibility windows have been postulated before but not definitively documented. Our data support the findings of higher susceptibility to HIV in women during progesterone-dominated periods including pregnancy and contraceptive use.
Esinler, I; Bozdag, G; Esinler, D; Lale, K S; Yarali, H
2015-04-01
A total of 413 consecutive infertile patients (572 cycles) with a body mass index (BMI) of ≥ 25 kg/m(2) were enrolled into the study. The luteal-long GnRH agonist group (Group I) constituted 211 patients (300 cycles) and the flexible-multidose GnRH antagonist group (Group II) constituted 202 patients (272 cycles). The duration of stimulation (d) (10.1 ± 2.5 vs. 9.2 ± 2.0; p < 0.01); the total dose of gonadotrophin used (IU) (3,099.4 ± 2,885.0 vs. 2,684.0 ± 1,046.4; p < 0.05) and the E2 level on the day of hCG (pg/ml) (2,375.8 ± 1,554.6 vs. 1,905.6 ± 1,598.8; p < 0.01) were significantly lower in Group II when compared with Group I. However, the ongoing pregnancy per embryo transfer (37.0% vs. 25.7%; p < 0.05) and the implantation rate (25.7% vs. 15.6%; p < 0.01) were significantly lower in Group II when compared with Group I. In conclusion, we noted that the luteal-long GnRH agonist protocol produced higher implantation rates and higher clinical-ongoing pregnancy rates in overweight and obese patients when compared with the flexible-multidose GnRH antagonist protocol.
Rank regression: an alternative regression approach for data with outliers.
Chen, Tian; Tang, Wan; Lu, Ying; Tu, Xin
2014-10-01
Linear regression models are widely used in mental health and related health services research. However, the classic linear regression analysis assumes that the data are normally distributed, an assumption that is not met by the data obtained in many studies. One method of dealing with this problem is to use semi-parametric models, which do not require that the data be normally distributed. But semi-parametric models are quite sensitive to outlying observations, so the generated estimates are unreliable when study data includes outliers. In this situation, some researchers trim the extreme values prior to conducting the analysis, but the ad-hoc rules used for data trimming are based on subjective criteria so different methods of adjustment can yield different results. Rank regression provides a more objective approach to dealing with non-normal data that includes outliers. This paper uses simulated and real data to illustrate this useful regression approach for dealing with outliers and compares it to the results generated using classical regression models and semi-parametric regression models.
Practical Session: Simple Linear Regression
NASA Astrophysics Data System (ADS)
Clausel, M.; Grégoire, G.
2014-12-01
Two exercises are proposed to illustrate the simple linear regression. The first one is based on the famous Galton's data set on heredity. We use the lm R command and get coefficients estimates, standard error of the error, R2, residuals …In the second example, devoted to data related to the vapor tension of mercury, we fit a simple linear regression, predict values, and anticipate on multiple linear regression. This pratical session is an excerpt from practical exercises proposed by A. Dalalyan at EPNC (see Exercises 1 and 2 of http://certis.enpc.fr/~dalalyan/Download/TP_ENPC_4.pdf).
Lee, C M; Tekpetey, F R; Armstrong, D T; Khalil, M W
1991-05-01
We have previously suggested that in porcine granulosa cells, a putative intermediate, 5(10)-oestrene-3,17-dione is involved in 4-oestrene-3,17-dione (19-norandrostenedione; 19-norA) and 4-oestren-17 beta-ol-3-one (19-nortestosterone: 19-norT) formation from C19 aromatizable androgens. In this study, luteal cells prepared from porcine, bovine and rat corpora lutea by centrifugal elutriation were used as a source of 3 beta-hydroxysteroid dehydrogenase/isomerase in order to investigate the role of this enzyme in the biosynthesis of 19-norsteroids. Small porcine luteal cells made mainly 19-norT and large porcine luteal cells 19-norA from 5(10)-oestrene-3 beta,17 beta-diol, the reduced product of the putative intermediate 5(10)-oestrene-3,17-dione. However, neither small nor large cells metabolized androstenedione to 19-norsteroids. Serum and serum plus LH significantly stimulated formation of both 19-norA and 19-norT from 5(10)-oestrene-3 beta,17 beta-diol, compared with controls. Inhibitors of the 3 beta-hydroxysteroid dehydrogenase/isomerase (trilostane and cyanoketone) significantly reduced formation of 19-norT in small porcine luteal cells and 19-norA in large porcine luteal cells, although they were effective at different concentrations in each cell type. In parallel incubations, formation of [4-14C]androstenedione from added [4-14C]dehydroepiandrosterone was also inhibited by cyanoketone in both small and large porcine luteal cells in a dose-dependent manner; however, trilostane (up to 100 mumol/l) did not inhibit androstenedione formation in large porcine luteal cells. In addition, the decrease in progesterone synthesis induced by trilostane and cyanoketone (100 mumol/l each) was accompanied by a parallel accumulation of pregnenolone in both cell types. These results suggest that 3 beta-hydroxysteroid dehydrogenase/isomerase, or a closely related enzyme, present in small and large porcine luteal cells can convert added 5(10)-3 beta-hydroxysteroids into 19-nor-4
Multiple Regression and Its Discontents
ERIC Educational Resources Information Center
Snell, Joel C.; Marsh, Mitchell
2012-01-01
Multiple regression is part of a larger statistical strategy originated by Gauss. The authors raise questions about the theory and suggest some changes that would make room for Mandelbrot and Serendipity.
Wrong Signs in Regression Coefficients
NASA Technical Reports Server (NTRS)
McGee, Holly
1999-01-01
When using parametric cost estimation, it is important to note the possibility of the regression coefficients having the wrong sign. A wrong sign is defined as a sign on the regression coefficient opposite to the researcher's intuition and experience. Some possible causes for the wrong sign discussed in this paper are a small range of x's, leverage points, missing variables, multicollinearity, and computational error. Additionally, techniques for determining the cause of the wrong sign are given.
Qin, B; Dawson, H; Polansky, M M; Anderson, R A
2009-07-01
We have previously reported that the obesity-associated proinflammatory cytokine, TNF-alpha, stimulates the overproduction of intestinal apolipoprotein (apo) B48 containing lipoproteins. In the current study, we have evaluated whether a water-soluble cinnamon extract [CE (Cinnulin PF)] attenuates the dyslipidemia induced by TNF-alpha in Triton WR-1339 treated hamsters, and whether CE inhibits the oversecrection of apoB48-induced by TNF-alpha in enterocytes in a 35S labeling study. In vivo, oral treatment of Cinnulin PF (50 mg per kg BW), inhibited the postprandial overproduction of apoB48-containing lipoproteins and serum triglyceride levels. In ex vivo 35S labeling studies, CE (10 and 20 microg/ml) inhibited the oversecretion of apoB48 induced by TNF-alpha treated enterocytes into the media. To determine the molecular mechanisms, TNF-alpha treated primary enterocytes isolated from chow-fed hamsters, were incubated with CE (10 microg/ml), and the expression of the inflammatory factor genes, IL1-beta, IL-6, and TNF-alpha, insulin signaling pathway genes, insulin receptor (IR), IRS1, IRS2, phosphatidylinositol 3-kinase (PI3-K), Akt1 and phosphatase and tensin homology (PTEN), as well as the key regulators of lipid metabolism, cluster of differentiation (CD)36, microsomal triglyceride transfer protein (MTTP), and sterol regulatory element binding protein (SREBP)-1c were evaluated. Quantitative real-time PCR assays showed that CE treatment decreased the mRNA expression of IL-1beta, IL-6 and TNF-alpha, improved the mRNA expression of IR, IRS1, IRS2, PI3K and Akt1, inhibited CD36, MTTP, and PTEN, and enhanced the impaired SREBP-1c expression in TNF-alpha treated enterocytes. These data suggest that a water extract of cinnamon reverses TNF-alpha-induced overproduction of intestinal apoB48 by regulating gene expression involving inflammatory, insulin, and lipoprotein signaling pathways. In conclusion, Cinulin PF improves inflammation related intestinal dyslipidemia.
Taylor, Monica; Dunn, Sheila; Martin, Lisa; Chavez, Sonia; Stanitz, Greg; Huszti, Ella; Minkin, Salomon; Boyd, Norman
2016-01-01
Background In previous work in young women aged 15–30 years we measured breast water and fat using MR and obtained blood for hormone assays on the same day in the follicular phase of the menstrual cycle. Only serum growth hormone levels and sex hormone binding globulin (SHBG) were significantly associated with percent breast water after adjustment for covariates. The sex hormones estradiol, progesterone and testosterone were not associated with percent water in the breast in the follicular phase of the menstrual cycle. In the present study we have examined the association of percent breast water with serum levels of sex hormones in both follicular and luteal phase of the menstrual cycle. Methods In 315 healthy white Caucasian young women aged 15–30 with regular menstrual cycles who had not used oral contraceptives or other hormones in the previous 6 months, we used MR to determine percent breast water, and obtained blood samples for hormone assays within 10 days of the onset of the most recent menstrual cycle (follicular phase) of the cycle on the same day as the MR scan, and a second blood sample on days 19–24 of the cycle. Serum progesterone levels of > = 5 mmol/L in days 19–24 were used to define the 225 subjects with ovulatory menstrual cycles, whose data are the subject of the analyses shown here. Results SHBG was positively associated with percent water in both follicular and luteal phases of the menstrual cycle. Total and free estradiol and total and free testosterone were not associated with percent water in the follicular phase, but in young women with ovulatory cycles, were all negatively associated with percent water in the luteal phase. Conclusions Our results from young women aged 15–30 years add to the evidence that the extent of fibroglandular tissue in the breast that is reflected in both mammographic density and breast water is associated positively with higher serum levels of SHBG, but not with higher levels of sex hormones. PMID
XRA image segmentation using regression
NASA Astrophysics Data System (ADS)
Jin, Jesse S.
1996-04-01
Segmentation is an important step in image analysis. Thresholding is one of the most important approaches. There are several difficulties in segmentation, such as automatic selecting threshold, dealing with intensity distortion and noise removal. We have developed an adaptive segmentation scheme by applying the Central Limit Theorem in regression. A Gaussian regression is used to separate the distribution of background from foreground in a single peak histogram. The separation will help to automatically determine the threshold. A small 3 by 3 widow is applied and the modal of the local histogram is used to overcome noise. Thresholding is based on local weighting, where regression is used again for parameter estimation. A connectivity test is applied to the final results to remove impulse noise. We have applied the algorithm to x-ray angiogram images to extract brain arteries. The algorithm works well for single peak distribution where there is no valley in the histogram. The regression provides a method to apply knowledge in clustering. Extending regression for multiple-level segmentation needs further investigation.
Survival Data and Regression Models
NASA Astrophysics Data System (ADS)
Grégoire, G.
2014-12-01
We start this chapter by introducing some basic elements for the analysis of censored survival data. Then we focus on right censored data and develop two types of regression models. The first one concerns the so-called accelerated failure time models (AFT), which are parametric models where a function of a parameter depends linearly on the covariables. The second one is a semiparametric model, where the covariables enter in a multiplicative form in the expression of the hazard rate function. The main statistical tool for analysing these regression models is the maximum likelihood methodology and, in spite we recall some essential results about the ML theory, we refer to the chapter "Logistic Regression" for a more detailed presentation.
Regressive evolution in Astyanax cavefish.
Jeffery, William R
2009-01-01
A diverse group of animals, including members of most major phyla, have adapted to life in the perpetual darkness of caves. These animals are united by the convergence of two regressive phenotypes, loss of eyes and pigmentation. The mechanisms of regressive evolution are poorly understood. The teleost Astyanax mexicanus is of special significance in studies of regressive evolution in cave animals. This species includes an ancestral surface dwelling form and many con-specific cave-dwelling forms, some of which have evolved their recessive phenotypes independently. Recent advances in Astyanax development and genetics have provided new information about how eyes and pigment are lost during cavefish evolution; namely, they have revealed some of the molecular and cellular mechanisms involved in trait modification, the number and identity of the underlying genes and mutations, the molecular basis of parallel evolution, and the evolutionary forces driving adaptation to the cave environment.
Bianchi, C P; Cavilla, M V; Jorgensen, E; Benavente, M A; Aba, M A
2012-04-01
The aim of the present study was to evaluate the susceptibility of the corpus luteum to d-cloprostenol (synthetic analog of PGF(2α)) throughout the luteal phase in llamas. Female llamas (n=43) were induced to ovulate by GnRH injection in the presence of an ovulatory follicle and randomly assigned into one of six groups: control and treated with an injection of d-cloprostenol on Day 3, 4, 5, 6 or 8 post GnRH. Blood samples were collected to determine plasma progesterone concentrations. There was no effect of treatment on animals injected on Day 3 or 4 post-GnRH. In animals treated on Day 5, different responses were observed. No effect of treatment was recorded in 27% of the animals whereas 55% of the llamas showed a transitory decrease followed by a recovery in plasma progesterone concentrations after d-cloprostenol injection, indicative of a resurgence of the corpus luteum, extending the luteal phase a day more than in control animals. In the remaining 18% of the animals injected on Day 5, (corresponding to those exhibiting the greatest plasma progesterone concentrations at the day of injection), complete luteolysis was observed. Plasma progesterone concentrations decreased to below 1 ng ml(-1) 24 h after d-cloprostenol in llamas injected on Day 6 or 8 post-GnRH. In conclusion, the corpus luteum of llamas is completely refractory to PGF(2α) until Day 4 after induction of ovulation, being partially sensitive by Day 5 and fully responsive to PGF(2α), by Day 6 after induction of ovulation.
Wientjes, J G M; Soede, N M; van den Brand, H; Kemp, B
2012-02-01
Insulin-stimulating sow diets before mating improve piglet uniformity. We studied effects of nutritionally induced differences in insulin levels during the weaning-to-ovulation interval (WOI) on luteal development, progesterone secretion and pre-implantation conceptus development and uniformity (d10). To create insulin contrasts, 32 multiparous sows were fed either a dextrose plus lactose containing diet (each 150 g/day) at 4 h intervals (DL treatment) or an isocalorically control diet (containing soybean oil) at 12 h intervals (CTRL treatment) during the WOI. After ovulation, all sows received a standard gestation diet at 12 h intervals. Ovulation rate, plasma progesterone levels, pregnancy rate and embryo survival did not differ between treatments. CTRL sows had a higher total luteal weight (11.2 vs 9.7 g; p = 0.03) than DL sows. Conceptus diameter at d10 of pregnancy tended to be larger in CTRL sows (diameter: 7.1 vs 6.4 mm; p = 0.07). Conceptus uniformity was not influenced by treatment. Insulin area under the curve (AUC) and mean insulin during the WOI were positively related with mean progesterone (β values were 0.78 (ng/ml)/1000 μU and 0.14 (ng/ml)/(μU/ml) for AUC and mean, respectively; p < 0.05) and maximal progesterone (β values were 1.46 (ng/ml)/1000 μU and 0.27 (ng/ml)/(μU/ml) for AUC and mean, respectively; p < 0.05) levels during the first 10 days of pregnancy, but not with conceptus development and uniformity. In conclusion, high insulin levels during the WOI seem to be beneficial for progesterone secretion in sows, probably mediated through beneficial effects of insulin on follicle development.
Cactus: An Introduction to Regression
ERIC Educational Resources Information Center
Hyde, Hartley
2008-01-01
When the author first used "VisiCalc," the author thought it a very useful tool when he had the formulas. But how could he design a spreadsheet if there was no known formula for the quantities he was trying to predict? A few months later, the author relates he learned to use multiple linear regression software and suddenly it all clicked into…
Multiple Regression: A Leisurely Primer.
ERIC Educational Resources Information Center
Daniel, Larry G.; Onwuegbuzie, Anthony J.
Multiple regression is a useful statistical technique when the researcher is considering situations in which variables of interest are theorized to be multiply caused. It may also be useful in those situations in which the researchers is interested in studies of predictability of phenomena of interest. This paper provides an introduction to…
Weighting Regressions by Propensity Scores
ERIC Educational Resources Information Center
Freedman, David A.; Berk, Richard A.
2008-01-01
Regressions can be weighted by propensity scores in order to reduce bias. However, weighting is likely to increase random error in the estimates, and to bias the estimated standard errors downward, even when selection mechanisms are well understood. Moreover, in some cases, weighting will increase the bias in estimated causal parameters. If…
Quantile Regression with Censored Data
ERIC Educational Resources Information Center
Lin, Guixian
2009-01-01
The Cox proportional hazards model and the accelerated failure time model are frequently used in survival data analysis. They are powerful, yet have limitation due to their model assumptions. Quantile regression offers a semiparametric approach to model data with possible heterogeneity. It is particularly powerful for censored responses, where the…
Baker, Valerie L.; Jones, Christopher A.; Doody, Kevin; Foulk, Russell; Yee, Bill; Adamson, G. David; Cometti, Barbara; DeVane, Gary; Hubert, Gary; Trevisan, Silvia; Hoehler, Fred; Jones, Clarence; Soules, Michael
2014-01-01
STUDY QUESTION Is the ongoing pregnancy rate with a new aqueous formulation of subcutaneous progesterone (Prolutex®) non-inferior to vaginal progesterone (Endometrin®) when used for luteal phase support of in vitro fertilization? SUMMARY ANSWER In the per-protocol (PP) population, the ongoing pregnancy rates per oocyte retrieval at 12 weeks of gestation were comparable between Prolutex and Endometrin (41.6 versus 44.4%), with a difference between groups of −2.8% (95% confidence interval (CI) −9.7, 4.2), consistent with the non-inferiority of subcutaneous progesterone for luteal phase support. WHAT IS KNOWN ALREADY Luteal phase support has been clearly demonstrated to improve pregnancy rates in women undergoing in vitro fertilization (IVF). Because of the increased risk of ovarian hyperstimulation syndrome associated with the use of hCG, progesterone has become the treatment of choice for luteal phase support. STUDY DESIGN, SIZE, DURATION This prospective, open-label, randomized, controlled, parallel-group, multicentre, two-arm, non-inferiority study was performed at eight fertility clinics. A total of 800 women, aged 18–42 years, with a BMI of ≤30 kg/m2, with <3 prior completed assisted reproductive technology (ART) cycles, exhibiting baseline (Days 2–3) FSH of ≤15 IU/L and undergoing IVF at 8 centres (seven private, one academic) in the USA, were enrolled from January 2009 through June 2011. PARTICIPANTS/MATERIALS, SETTING, METHODS In total, 800 women undergoing IVF were randomized after retrieval of at least three oocytes to an aqueous preparation of progesterone administered subcutaneously (25 mg daily) or vaginal progesterone (100 mg bid daily). Randomization was performed to enrol 100 patients at each site using a randomization list that was generated with Statistical Analysis Software (SAS®). If a viable pregnancy occurred, progesterone treatment was continued up to 12 weeks of gestation. MAIN RESULTS AND THE ROLE OF CHANCE Using a PP analysis
Hierarchical Adaptive Regression Kernels for Regression with Functional Predictors
Woodard, Dawn B.; Crainiceanu, Ciprian; Ruppert, David
2013-01-01
We propose a new method for regression using a parsimonious and scientifically interpretable representation of functional predictors. Our approach is designed for data that exhibit features such as spikes, dips, and plateaus whose frequency, location, size, and shape varies stochastically across subjects. We propose Bayesian inference of the joint functional and exposure models, and give a method for efficient computation. We contrast our approach with existing state-of-the-art methods for regression with functional predictors, and show that our method is more effective and efficient for data that include features occurring at varying locations. We apply our methodology to a large and complex dataset from the Sleep Heart Health Study, to quantify the association between sleep characteristics and health outcomes. Software and technical appendices are provided in online supplemental materials. PMID:24293988
Regression Verification Using Impact Summaries
NASA Technical Reports Server (NTRS)
Backes, John; Person, Suzette J.; Rungta, Neha; Thachuk, Oksana
2013-01-01
Regression verification techniques are used to prove equivalence of syntactically similar programs. Checking equivalence of large programs, however, can be computationally expensive. Existing regression verification techniques rely on abstraction and decomposition techniques to reduce the computational effort of checking equivalence of the entire program. These techniques are sound but not complete. In this work, we propose a novel approach to improve scalability of regression verification by classifying the program behaviors generated during symbolic execution as either impacted or unimpacted. Our technique uses a combination of static analysis and symbolic execution to generate summaries of impacted program behaviors. The impact summaries are then checked for equivalence using an o-the-shelf decision procedure. We prove that our approach is both sound and complete for sequential programs, with respect to the depth bound of symbolic execution. Our evaluation on a set of sequential C artifacts shows that reducing the size of the summaries can help reduce the cost of software equivalence checking. Various reduction, abstraction, and compositional techniques have been developed to help scale software verification techniques to industrial-sized systems. Although such techniques have greatly increased the size and complexity of systems that can be checked, analysis of large software systems remains costly. Regression analysis techniques, e.g., regression testing [16], regression model checking [22], and regression verification [19], restrict the scope of the analysis by leveraging the differences between program versions. These techniques are based on the idea that if code is checked early in development, then subsequent versions can be checked against a prior (checked) version, leveraging the results of the previous analysis to reduce analysis cost of the current version. Regression verification addresses the problem of proving equivalence of closely related program
Interaction Models for Functional Regression
USSET, JOSEPH; STAICU, ANA-MARIA; MAITY, ARNAB
2015-01-01
A functional regression model with a scalar response and multiple functional predictors is proposed that accommodates two-way interactions in addition to their main effects. The proposed estimation procedure models the main effects using penalized regression splines, and the interaction effect by a tensor product basis. Extensions to generalized linear models and data observed on sparse grids or with measurement error are presented. A hypothesis testing procedure for the functional interaction effect is described. The proposed method can be easily implemented through existing software. Numerical studies show that fitting an additive model in the presence of interaction leads to both poor estimation performance and lost prediction power, while fitting an interaction model where there is in fact no interaction leads to negligible losses. The methodology is illustrated on the AneuRisk65 study data. PMID:26744549
Astronomical Methods for Nonparametric Regression
NASA Astrophysics Data System (ADS)
Steinhardt, Charles L.; Jermyn, Adam
2017-01-01
I will discuss commonly used techniques for nonparametric regression in astronomy. We find that several of them, particularly running averages and running medians, are generically biased, asymmetric between dependent and independent variables, and perform poorly in recovering the underlying function, even when errors are present only in one variable. We then examine less-commonly used techniques such as Multivariate Adaptive Regressive Splines and Boosted Trees and find them superior in bias, asymmetry, and variance both theoretically and in practice under a wide range of numerical benchmarks. In this context the chief advantage of the common techniques is runtime, which even for large datasets is now measured in microseconds compared with milliseconds for the more statistically robust techniques. This points to a tradeoff between bias, variance, and computational resources which in recent years has shifted heavily in favor of the more advanced methods, primarily driven by Moore's Law. Along these lines, we also propose a new algorithm which has better overall statistical properties than all techniques examined thus far, at the cost of significantly worse runtime, in addition to providing guidance on choosing the nonparametric regression technique most suitable to any specific problem. We then examine the more general problem of errors in both variables and provide a new algorithm which performs well in most cases and lacks the clear asymmetry of existing non-parametric methods, which fail to account for errors in both variables.
Vicente-Manzanares, Miguel; Cabrero, José Román; Rey, Mercedes; Pérez-Martínez, Manuel; Ursa, Angeles; Itoh, Kazuyuki; Sánchez-Madrid, Francisco
2002-01-01
The possible involvement of the Rho-p160ROCK (Rho coiled-coil kinase) pathway in the signaling induced by the chemokine Stromal cell-derived factor (SDF)-1alpha has been studied in human PBL. SDF-1alpha induced activation of RhoA, but not that of Rac. RhoA activation was followed by p160ROCK activation mediated by RhoA, which led to myosin light chain (MLC) phosphorylation, which was dependent on RhoA and p160ROCK activities. The kinetics of MLC activation was similar to that of RhoA and p160ROCK. The role of this cascade in overall cell morphology and functional responses to the chemokine was examined employing different chemical inhibitors. Inhibition of either RhoA or p160ROCK did not block SDF-1alpha-induced short-term actin polymerization, but induced the formation of long spikes arising from the cell body, which were found to be microtubule based. This morphological change was associated with an increase in microtubule instability, which argues for an active microtubule polymerization in the formation of these spikes. Inhibition of the Rho-p160ROCK-MLC kinase signaling cascade at different steps blocked lymphocyte migration and the chemotaxis induced by SDF-1alpha. Our results indicate that the Rho-p160ROCK axis plays a pivotal role in the control of the cell shape as a step before lymphocyte migration toward a chemotactic gradient.
Regression analysis of cytopathological data
Whittemore, A.S.; McLarty, J.W.; Fortson, N.; Anderson, K.
1982-12-01
Epithelial cells from the human body are frequently labelled according to one of several ordered levels of abnormality, ranging from normal to malignant. The label of the most abnormal cell in a specimen determines the score for the specimen. This paper presents a model for the regression of specimen scores against continuous and discrete variables, as in host exposure to carcinogens. Application to data and tests for adequacy of model fit are illustrated using sputum specimens obtained from a cohort of former asbestos workers.
Multiatlas segmentation as nonparametric regression.
Awate, Suyash P; Whitaker, Ross T
2014-09-01
This paper proposes a novel theoretical framework to model and analyze the statistical characteristics of a wide range of segmentation methods that incorporate a database of label maps or atlases; such methods are termed as label fusion or multiatlas segmentation. We model these multiatlas segmentation problems as nonparametric regression problems in the high-dimensional space of image patches. We analyze the nonparametric estimator's convergence behavior that characterizes expected segmentation error as a function of the size of the multiatlas database. We show that this error has an analytic form involving several parameters that are fundamental to the specific segmentation problem (determined by the chosen anatomical structure, imaging modality, registration algorithm, and label-fusion algorithm). We describe how to estimate these parameters and show that several human anatomical structures exhibit the trends modeled analytically. We use these parameter estimates to optimize the regression estimator. We show that the expected error for large database sizes is well predicted by models learned on small databases. Thus, a few expert segmentations can help predict the database sizes required to keep the expected error below a specified tolerance level. Such cost-benefit analysis is crucial for deploying clinical multiatlas segmentation systems.
Multiatlas Segmentation as Nonparametric Regression
Awate, Suyash P.; Whitaker, Ross T.
2015-01-01
This paper proposes a novel theoretical framework to model and analyze the statistical characteristics of a wide range of segmentation methods that incorporate a database of label maps or atlases; such methods are termed as label fusion or multiatlas segmentation. We model these multiatlas segmentation problems as nonparametric regression problems in the high-dimensional space of image patches. We analyze the nonparametric estimator’s convergence behavior that characterizes expected segmentation error as a function of the size of the multiatlas database. We show that this error has an analytic form involving several parameters that are fundamental to the specific segmentation problem (determined by the chosen anatomical structure, imaging modality, registration algorithm, and label-fusion algorithm). We describe how to estimate these parameters and show that several human anatomical structures exhibit the trends modeled analytically. We use these parameter estimates to optimize the regression estimator. We show that the expected error for large database sizes is well predicted by models learned on small databases. Thus, a few expert segmentations can help predict the database sizes required to keep the expected error below a specified tolerance level. Such cost-benefit analysis is crucial for deploying clinical multiatlas segmentation systems. PMID:24802528
Recognition of caudal regression syndrome.
Boulas, Mari M
2009-04-01
Caudal regression syndrome, also referred to as caudal dysplasia and sacral agenesis syndrome, is a rare congenital malformation characterized by varying degrees of developmental failure early in gestation. It involves the lower extremities, the lumbar and coccygeal vertebrae, and corresponding segments of the spinal cord. This is a rare disorder, and true pathogenesis is unclear. The etiology is thought to be related to maternal diabetes, genetic predisposition, and vascular hypoperfusion, but no true causative factor has been determined. Fetal diagnostic tools allow for early recognition of the syndrome, and careful examination of the newborn is essential to determine the extent of the disorder. Associated organ system dysfunction depends on the severity of the disease. Related defects are structural, and systematic problems including respiratory, cardiac, gastrointestinal, urinary, orthopedic, and neurologic can be present in varying degrees of severity and in different combinations. A multidisciplinary approach to management is crucial. Because the primary pathology is irreversible, treatment is only supportive.
Practical Session: Multiple Linear Regression
NASA Astrophysics Data System (ADS)
Clausel, M.; Grégoire, G.
2014-12-01
Three exercises are proposed to illustrate the simple linear regression. In the first one investigates the influence of several factors on atmospheric pollution. It has been proposed by D. Chessel and A.B. Dufour in Lyon 1 (see Sect. 6 of http://pbil.univ-lyon1.fr/R/pdf/tdr33.pdf) and is based on data coming from 20 cities of U.S. Exercise 2 is an introduction to model selection whereas Exercise 3 provides a first example of analysis of variance. Exercises 2 and 3 have been proposed by A. Dalalyan at ENPC (see Exercises 2 and 3 of http://certis.enpc.fr/~dalalyan/Download/TP_ENPC_5.pdf).
Lumbar herniated disc: spontaneous regression
Yüksel, Kasım Zafer
2017-01-01
Background Low back pain is a frequent condition that results in substantial disability and causes admission of patients to neurosurgery clinics. To evaluate and present the therapeutic outcomes in lumbar disc hernia (LDH) patients treated by means of a conservative approach, consisting of bed rest and medical therapy. Methods This retrospective cohort was carried out in the neurosurgery departments of hospitals in Kahramanmaraş city and 23 patients diagnosed with LDH at the levels of L3−L4, L4−L5 or L5−S1 were enrolled. Results The average age was 38.4 ± 8.0 and the chief complaint was low back pain and sciatica radiating to one or both lower extremities. Conservative treatment was administered. Neurological examination findings, durations of treatment and intervals until symptomatic recovery were recorded. Laségue tests and neurosensory examination revealed that mild neurological deficits existed in 16 of our patients. Previously, 5 patients had received physiotherapy and 7 patients had been on medical treatment. The number of patients with LDH at the level of L3−L4, L4−L5, and L5−S1 were 1, 13, and 9, respectively. All patients reported that they had benefit from medical treatment and bed rest, and radiologic improvement was observed simultaneously on MRI scans. The average duration until symptomatic recovery and/or regression of LDH symptoms was 13.6 ± 5.4 months (range: 5−22). Conclusions It should be kept in mind that lumbar disc hernias could regress with medical treatment and rest without surgery, and there should be an awareness that these patients could recover radiologically. This condition must be taken into account during decision making for surgical intervention in LDH patients devoid of indications for emergent surgery. PMID:28119770
Van Molle, W; Hochepied, T; Brouckaert, P; Libert, C
2000-09-01
The proinflammatory cytokine tumor necrosis factor alpha (TNF-alpha) induces lethal hepatitis when injected into D-(+)-galactosamine-sensitized mice on the one hand or systemic inflammatory response syndrome (SIRS) in normal mice on the other hand. We studied whether serum amyloid P component (SAP), the major acute-phase protein in mice, plays a protective role in both lethal models. For this purpose, we used SAP(0/0) mice generated by gene targeting. We studied the lethal response of SAP(0/0) or SAP(+/+) mice to both lethal triggers but found no differences in the sensitivity of both types of mice. We also investigated whether SAP is involved in establishing two types of endogenous protection: one using a single injection of interleukin-1beta (IL-1beta) for desensitization and clearly involving a liver protein, the other by tolerizing mice for 5 days using small doses of human TNF-alpha. Although after IL-1beta or after tolerization the SAP levels in the serum had risen fourfold in the control mice and not in the SAP(0/0) mice, the same extents of desensitization and tolerization were achieved. Finally, we observed that the induction of hemorrhagic necrosis in the skin of mice by two consecutive local injections with TNF-alpha was not altered in SAP(0/0) mice. We conclude that the presence or absence of SAP has no influence on the sensitivity of mice to TNF-alpha-induced hepatitis, SIRS, and hemorrhagic necrosis or on the endogenous protective mechanisms of desensitization or tolerization.
Tian, Qingping; Miyazaki, Ryohei; Ichiki, Toshihiro; Imayama, Ikuyo; Inanaga, Keita; Ohtsubo, Hideki; Yano, Kotaro; Takeda, Kotaro; Sunagawa, Kenji
2009-05-01
Telmisartan, an angiotensin II type 1 receptor antagonist, was reported to be a partial agonist of peroxisome proliferator-activated receptor-gamma. Although peroxisome proliferator-activated receptor-gamma activators have been shown to have an anti-inflammatory effect, such as inhibition of cytokine production, it has not been determined whether telmisartan has such effects. We examined whether telmisartan inhibits expression of interleukin-6 (IL-6), a proinflammatory cytokine, in vascular smooth muscle cells. Telmisartan, but not valsartan, attenuated IL-6 mRNA expression induced by tumor necrosis factor-alpha (TNF-alpha). Telmisartan decreased TNF-alpha-induced IL-6 mRNA and protein expression in a dose-dependent manner. Because suppression of IL-6 mRNA expression was prevented by pretreatment with GW9662, a specific peroxisome proliferator-activated receptor-gamma antagonist, peroxisome proliferator-activated receptor-gamma may be involved in the process. Telmisartan suppressed IL-6 gene promoter activity induced by TNF-alpha. Deletion analysis suggested that the DNA segment between -150 bp and -27 bp of the IL-6 gene promoter that contains nuclear factor kappaB and CCAAT/enhancer-binding protein-beta sites was responsible for telmisartan suppression. Telmisartan attenuated TNF-alpha-induced nuclear factor kappaB- and CCAAT/enhancer-binding protein-beta-dependent gene transcription and DNA binding. Telmisartan also attenuated serum IL-6 level in TNF-alpha-infused mice and IL-6 production from rat aorta stimulated with TNF-alpha ex vivo. These data suggest that telmisartan may attenuate inflammatory process induced by TNF-alpha in addition to the blockade of angiotensin II type 1 receptor. Because both TNF-alpha and angiotensin II play important roles in atherogenesis through enhancement of vascular inflammation, telmisartan may be beneficial for treatment of not only hypertension but also vascular inflammatory change.
Genetics Home Reference: caudal regression syndrome
... of a genetic condition? Genetic and Rare Diseases Information Center Frequency Caudal regression syndrome is estimated to occur in 1 to ... parts of the skeleton, gastrointestinal system, and genitourinary ... caudal regression syndrome results from the presence of an abnormal ...
Semiparametric regression during 2003–2007*
Ruppert, David; Wand, M.P.; Carroll, Raymond J.
2010-01-01
Semiparametric regression is a fusion between parametric regression and nonparametric regression that integrates low-rank penalized splines, mixed model and hierarchical Bayesian methodology – thus allowing more streamlined handling of longitudinal and spatial correlation. We review progress in the field over the five-year period between 2003 and 2007. We find semiparametric regression to be a vibrant field with substantial involvement and activity, continual enhancement and widespread application. PMID:20305800
Bayesian Unimodal Density Regression for Causal Inference
ERIC Educational Resources Information Center
Karabatsos, George; Walker, Stephen G.
2011-01-01
Karabatsos and Walker (2011) introduced a new Bayesian nonparametric (BNP) regression model. Through analyses of real and simulated data, they showed that the BNP regression model outperforms other parametric and nonparametric regression models of common use, in terms of predictive accuracy of the outcome (dependent) variable. The other,…
Developmental Regression in Autism Spectrum Disorders
ERIC Educational Resources Information Center
Rogers, Sally J.
2004-01-01
The occurrence of developmental regression in autism is one of the more puzzling features of this disorder. Although several studies have documented the validity of parental reports of regression using home videos, accumulating data suggest that most children who demonstrate regression also demonstrated previous, subtle, developmental differences.…
Standards for Standardized Logistic Regression Coefficients
ERIC Educational Resources Information Center
Menard, Scott
2011-01-01
Standardized coefficients in logistic regression analysis have the same utility as standardized coefficients in linear regression analysis. Although there has been no consensus on the best way to construct standardized logistic regression coefficients, there is now sufficient evidence to suggest a single best approach to the construction of a…
Regression Analysis by Example. 5th Edition
ERIC Educational Resources Information Center
Chatterjee, Samprit; Hadi, Ali S.
2012-01-01
Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. "Regression Analysis by Example, Fifth Edition" has been expanded and thoroughly…
Synthesizing Regression Results: A Factored Likelihood Method
ERIC Educational Resources Information Center
Wu, Meng-Jia; Becker, Betsy Jane
2013-01-01
Regression methods are widely used by researchers in many fields, yet methods for synthesizing regression results are scarce. This study proposes using a factored likelihood method, originally developed to handle missing data, to appropriately synthesize regression models involving different predictors. This method uses the correlations reported…
Streamflow forecasting using functional regression
NASA Astrophysics Data System (ADS)
Masselot, Pierre; Dabo-Niang, Sophie; Chebana, Fateh; Ouarda, Taha B. M. J.
2016-07-01
Streamflow, as a natural phenomenon, is continuous in time and so are the meteorological variables which influence its variability. In practice, it can be of interest to forecast the whole flow curve instead of points (daily or hourly). To this end, this paper introduces the functional linear models and adapts it to hydrological forecasting. More precisely, functional linear models are regression models based on curves instead of single values. They allow to consider the whole process instead of a limited number of time points or features. We apply these models to analyse the flow volume and the whole streamflow curve during a given period by using precipitations curves. The functional model is shown to lead to encouraging results. The potential of functional linear models to detect special features that would have been hard to see otherwise is pointed out. The functional model is also compared to the artificial neural network approach and the advantages and disadvantages of both models are discussed. Finally, future research directions involving the functional model in hydrology are presented.
Survival analysis and Cox regression.
Benítez-Parejo, N; Rodríguez del Águila, M M; Pérez-Vicente, S
2011-01-01
The data provided by clinical trials are often expressed in terms of survival. The analysis of survival comprises a series of statistical analytical techniques in which the measurements analysed represent the time elapsed between a given exposure and the outcome of a certain event. Despite the name of these techniques, the outcome in question does not necessarily have to be either survival or death, and may be healing versus no healing, relief versus pain, complication versus no complication, relapse versus no relapse, etc. The present article describes the analysis of survival from both a descriptive perspective, based on the Kaplan-Meier estimation method, and in terms of bivariate comparisons using the log-rank statistic. Likewise, a description is provided of the Cox regression models for the study of risk factors or covariables associated to the probability of survival. These models are defined in both simple and multiple forms, and a description is provided of how they are calculated and how the postulates for application are checked - accompanied by illustrating examples with the shareware application R.
Estimating equivalence with quantile regression
Cade, B.S.
2011-01-01
Equivalence testing and corresponding confidence interval estimates are used to provide more enlightened statistical statements about parameter estimates by relating them to intervals of effect sizes deemed to be of scientific or practical importance rather than just to an effect size of zero. Equivalence tests and confidence interval estimates are based on a null hypothesis that a parameter estimate is either outside (inequivalence hypothesis) or inside (equivalence hypothesis) an equivalence region, depending on the question of interest and assignment of risk. The former approach, often referred to as bioequivalence testing, is often used in regulatory settings because it reverses the burden of proof compared to a standard test of significance, following a precautionary principle for environmental protection. Unfortunately, many applications of equivalence testing focus on establishing average equivalence by estimating differences in means of distributions that do not have homogeneous variances. I discuss how to compare equivalence across quantiles of distributions using confidence intervals on quantile regression estimates that detect differences in heterogeneous distributions missed by focusing on means. I used one-tailed confidence intervals based on inequivalence hypotheses in a two-group treatment-control design for estimating bioequivalence of arsenic concentrations in soils at an old ammunition testing site and bioequivalence of vegetation biomass at a reclaimed mining site. Two-tailed confidence intervals based both on inequivalence and equivalence hypotheses were used to examine quantile equivalence for negligible trends over time for a continuous exponential model of amphibian abundance. ?? 2011 by the Ecological Society of America.
Developmental regression in autism spectrum disorder.
Al Backer, Nouf Backer
2015-01-01
The occurrence of developmental regression in autism spectrum disorder (ASD) is one of the most puzzling phenomena of this disorder. A little is known about the nature and mechanism of developmental regression in ASD. About one-third of young children with ASD lose some skills during the preschool period, usually speech, but sometimes also nonverbal communication, social or play skills are also affected. There is a lot of evidence suggesting that most children who demonstrate regression also had previous, subtle, developmental differences. It is difficult to predict the prognosis of autistic children with developmental regression. It seems that the earlier development of social, language, and attachment behaviors followed by regression does not predict the later recovery of skills or better developmental outcomes. The underlying mechanisms that lead to regression in autism are unknown. The role of subclinical epilepsy in the developmental regression of children with autism remains unclear.
Martin, A D; Afseth, N K; Kohler, A; Randby, Å; Eknæs, M; Waldmann, A; Dørum, G; Måge, I; Reksen, O
2015-08-01
To investigate the feasibility of milk fatty acids as predictors of onset of luteal activity (OLA), 87 lactations taken from 73 healthy Norwegian Red cattle were surveyed over 2 winter housing seasons. The feasibility of using frozen milk samples for dry-film Fourier transform infrared (FTIR) determination of milk samples was also tested. Morning milk samples were collected thrice weekly (Monday, Wednesday, Friday) for the first 10 wk in milk (WIM). These samples had bronopol (2-bromo-2-nitropropane-1,3-diol) added to them before being frozen at -20°C, thawed, and analyzed by ELISA to determine progesterone concentration and the concentrations of the milk fatty acids C4:0, C14:0, C16:0, C18:0, and cis-9 C18:1 as a proportion of total milk fatty acid content using dry-film FTIR, and averaged by WIM. Onset of luteal activity was defined as the first day that milk progesterone concentrations were >3 ng/mL for 2 successive measurements; the study population was categorized as early (n=47) or late (n=40) OLA, using the median value of 21 DIM as the cutoff. Further milk samples were collected 6 times weekly, from morning and afternoon milkings, these were pooled by WIM, and one proportional sample was analyzed fresh for fat, protein, and lactose content by the dairy company Tine SA, using traditional FTIR spectrography in the wet phase of milk. Daily energy-balance calculations were performed in 42 lactations and averaged by WIM. Animals experiencing late OLA had a more negative energy balance in WIM 1, 3, 4, and 5, with the greatest differences been seen in WIM 3 and 4. A higher proportion of the fatty acids were medium chained, C14:0 and C16:0, in the early than in the late OLA group from WIM 1. In WIM 4, the proportion of total fatty acid content that was C16:0 predicted late OLA, with 74% sensitivity and 80% specificity. The long-chain proportion of the fatty acids C18:0 and cis-9 C18:1 were lower in the early than in the late OLA group. Differences were greatest in
Cuervo-Arango, J
2011-08-01
Flunixin meglumine (FM), a prostaglandin synthetase inhibitor, causes ovulatory failure in the mare. However, the effect of the FM treatment relative to the time of hCG administration on the ovulation failure has not been determined nor has its effect on the luteal function of treated mares. Estrous mares with a follicle ≥32 mm (range of 32-38 mm) were treated with 1.7 mg/kg b.w. of FM iv at zero, 12, 24 and 36 h (n=6), at 24 and 36 h (n=6), at 28 and 36 h (n=6), at 24h (n=6) or at 30 h (n=6) after treatment with 1500 IU hCG. One group received no FM (control, n=6). Progesterone concentrations were determined using RIA. Mares treated with FM 0-36 h and 24-36 h had higher (P<0.05) incidence of ovulatory failure (83 and 80%, respectively) than mares treated twice at 28 and 36 h, or once at 24 or at 30 h after hCG (16.7, 0 and 0%, respectively). The anovulatory follicles of FM treated mares luteinized and produced progesterone (>2 ng/ml). The progesterone concentration was lower in mares treated with FM at zero to 36 h and at 24-36 h after hCG than in the other groups. In conclusion, the FM administration was effective in blocking ovulation only when the treatment began ≤24 h after hCG and was continued every 12 h until ≥36 h. In addition, the FM-induced anovulatory follicles underwent luteinization of follicular cells with active production of progesterone.
Silvia, W J; Niswender, G D
1986-10-01
Two experiments were conducted to examine the temporal aspects of luteal resistance to the luteolytic effect of prostaglandin (PG) F2 alpha during early pregnancy. In Exp. 1, 14 pregnant and 12 nonpregnant ewes were treated with PGF2 alpha either on d 10 or 13 post-estrus. Jugular venous blood samples were collected at -30 min, 0, 6, 12, 18, 24, 30 and 36 h post-injection for quantification of progesterone. The difference (delta P) between pre-treatment and post-treatment concentrations of progesterone was calculated for each ewe. There was a significant interaction between pregnancy status and day of treatment on delta P (P less than .05). Pregnant and nonpregnant ewes treated on d 10 showed a large delta P. A large delta P also was observed in nonpregnant ewes treated on d 13 post-estrus. However, delta P in pregnant ewes treated on d 13 was smaller than in the other three groups (P less than .05). The temporal patterns of concentrations of progesterone in serum were different among treatment groups (P less than .05). A suppression in the concentration of progesterone was observed by 24 h post-injection in all four treatment groups. Progesterone returned to pre-treatment levels only in pregnant ewes treated on d 13. In Exp. 2, 47 pregnant ewes were treated with PGF2 alpha on d 10, 13, 16, 19, 22, 26 or 30 postestrus. Blood samples were collected and data were analyzed as described for Exp. 1.(ABSTRACT TRUNCATED AT 250 WORDS)
Pandey, A K; Dhaliwal, G S; Ghuman, S P S; Agarwal, S K
2015-11-01
The present study aimed to establish the impact of buserelin acetate or hCG administration on day 5 post-ovulation on subsequent luteal profile and conception rate in buffalo. The buffalo (n=45) were subjected to an estrous synchronization protocol (synthetic analog of PGF2α administered, through intramuscular route, 11 days apart), followed by artificial insemination (AI) during mid to late estrus. On day 5 post-ovulation, buffalo were administered (i.m.) normal saline (Control, n=14), buserelin acetate (20μg, d5-BA, n=14) or human chorionic gonadotropin (3000IU, d5-hCG, n=17). Ovarian ultrasonography was conducted on the day of induced estrus and on days 0, 5, 12, 16 and 21 post-ovulation to assess preovulatory follicle or corpus luteum (CL) diameter. Also, on these days, jugular vein blood sampling was conducted for the estimation of plasma progesterone. First service conception rate was greater (χ(2)=5.18, P>0.05) in d5-BA and d5-hCG groups (71.4% and 47.1%, respectively) as compared to control (28.6%). Both treatment groups had a greater (P<0.05) CL diameter and plasma progesterone during the post-treatment period in comparison to that control treatment group. Treatment-induced accessory CL formation was observed in 92.9% and 76.5% buffalo of d5-BA and d5-hCG groups, respectively. In conclusion, buserelin acetate and hCG administration on day 5 post-ovulation leads to accessory CL formation that may have a role in enhancing conception rate.
Zmijewska, Agata; Franczak, Anita; Kotwica, Genowefa
2012-09-01
Interleukin-1β (IL-1β) may regulate ovarian physiology. In this study, the influence of IL-1β on secretory activity within the corpora lutea (CL) of cyclic and gravid pigs was determined in vitro during different stages of the CL lifespan, e.g. on Days 10-11, 12-13 and 15-16 of the oestrous cycle and pregnancy. IL-1β (10 ng/ml) increased prostaglandin E2 (PGE2) secretion from CL of the cyclic and gravid pigs during studied days of the oestrous cycle and pregnancy. Increase (P < 0.05) of prostaglandin F2α (PGF2α) in IL-1β-treated CL was demonstrated only on Days 10-11 of the oestrous cycle. More potent stimulatory effect of IL-1β on PGE2 than PGF2α secretion resulted in the enhancement of the PGE2:PGF2α ratio in cyclic and early pregnant CL. IL-1β increased (P < 0.05) progesterone (P4) secretion only in gravid CL and had no effect on oestradiol-17β (E2) release. Expression of cyclooxygenase-2 (COX-2) mRNA was stimulated (P < 0.05) in IL-1β-treated cyclic and gravid CL. Expression of prostaglandin synthase mRNAs in response to IL-1β did not increase. In conclusion, IL-1β modulates PGE2, PGF2α and P4 secretion from porcine CL, depending on luteal stage and the surrounding hormonal milieu. The cytokine may act locally in porcine CL for luteotrophic support throughout the PGE2-mediated synthesis and secretion.
Formation and regression of the corpus luteum of the American alligator
Guillette, L.J.; Woodward, A.R.; You-Xiang, Q.; Cox, M.C.; Matter, J.H.; Gross, T.S.
1995-01-01
Luteal morphology of the American alligator is unique when compared to other reptiles but is similar to that of its phylogenetic relatives, the birds. The theca is extensively hypertrophied, but the granulosa never fills the cavity formed following the ovulation of the ovum. The formation of the corpus luteum (CL) is correlated with elevated plasma progesterone concentrations, which decline dramatically after oviposition with the onset of luteolysis. Unlike those of most other reptiles, the central luteal cell mass is composed of two cell types; one presumably is derived from the granulosa, whereas the other is from the theca interna. Both cell types are present throughout gravidity but only one cell type is seen during mid to late luteolysis. A significant decline in luteal volume occurs following oviposition and continues throughout the post-oviposition period. The fastest decline in luteal volume occurs in the month immediately after oviposition; this rate then slows. Luteolysis appears to continue for a year or more following oviposition, as distinct structures of luteal origin can still be identified in animals 9 months after oviposition. The size of persistent CL can be used to determine whether a given female oviposited during the previous nesting season. Females with CL having volumes greater than 0.2 cm2 or CL diameters greater than 0.4 cm were active the previous season.
Sueldo, Carolina; Liu, Xiufang; Peluso, John J
2015-09-01
The present studies were designed to determine the role of progesterone receptor membrane component 1 (PGRMC1), PGRMC2, progestin and adipoQ receptor 7 (PAQR7), and progesterone receptor (PGR) in mediating the antimitotic action of progesterone (P4) in human granulosa/luteal cells. For these studies granulosa/luteal cells of 10 women undergoing controlled ovarian hyperstimulation were isolated, maintained in culture, and depleted of PGRMC1, PGRMC2, PAQR7, or PGR by siRNA treatment. The rate of entry into the cell cycle was assessed using the FUCCI cell cycle sensor to determine the percentage of cells in the G1/S stage of the cell cycle. PGRMC1, PGRMC2, PAQR7, and PGR mRNA levels were assessed by real-time PCR and their interactions monitored by in situ proximity ligation assays (PLAs). These studies revealed that PGRMC1, PGRMC2, PAQR7, and PGR were expressed by granulosa/luteal cells from all patients, with PGRMC1 mRNA being most abundant, followed by PAQR7, PGRMC2, and PGR. However, their mRNA levels showed considerable patient variation. P4's ability to suppress entry into the cell cycle was dependent on PGRMC1, PGRMC2, and PAQR7 but not PGR. Moreover, PLAs indicated that PGRMC1, PGRMC2, and PAQR7 formed a complex within the cytoplasm. Based on these studies, it is proposed that these three P4 mediators form a complex within the cytoplasm that is required for P4's action. Moreover, P4's ability to regulate human follicle development may be dependent in part on the expression levels of each of these P4 mediators.
Ciechanowska, Magdalena; Lapot, Magdalena; Malewski, Tadeusz; Mateusiak, Krystyna; Misztal, Tomasz; Przekop, Franciszek
2008-11-01
Data exists showing that seasonal changes in the innervations of GnRH cells in the hypothalamus and functions of some neural systems affecting GnRH neurons are associated with GnRH release in ewes. Consequently, we put the question as to how the expression of GnRH gene and GnRH-R gene in the hypothalamus and GnRH-R gene in the anterior pituitary gland is reflected with LH secretion in anestrous and luteal phase ewes. Analysis of GnRH gene expression by RT-PCR in anestrous ewes indicated comparable levels of GnRH mRNA in the preoptic area, anterior and ventromedial hypothalamus. GnRH-R mRNA at different concentrations was found throughout the preoptic area, anterior and ventromedial hypothalamus, stalk/median eminence and in the anterior pituitary gland. The highest GnRH-R mRNA levels were detected in the stalk/median eminence and in the anterior pituitary gland. During the luteal phase of the estrous cycle in ewes, the levels of GnRH mRNA and GnRH-R mRNA in all structures were significantly higher than in anestrous ewes. Also LH concentrations in blood plasma of luteal phase ewes were significantly higher than those of anestrous ewes. In conclusion, results from this study suggest that low expression of the GnRH and GnRH-R genes in the hypothalamus and of the GnRH-R gene in the anterior pituitary gland, amongst others, may be responsible for a decrease in LH secretion and the anovulatory state in ewes during the long photoperiod.
Mlynarczuk, Jaroslaw; Wrobel, Michal H; Kotwica, Jan
2009-11-01
The effect of polychlorinated biphenyls (PCBs) congeners (PCB 77, PCB 126, PCB 153) and their technical mixture-Aroclor (Ar) 1248, as well as dichlorodiphenyltrichloroethane (DDT) and its metabolite-dichlorodiphenyldichloroethylene (DDE; two individual isomers p,p'- and o,p'- or their mixture, 95% and 5%, respectively) at the dose of 10 ng/ml each, on the gene expression of (a) oxytocin (OT) precursor-neurophysin-oxytocin (NP-I/OT) and (b) peptidyl glycine-alpha-amidating mono-oxygenase (PGA), the terminal enzyme in the pathway of OT synthesis, was studied. Granulosa cells from follicles >1cm in diameter, collected on days 19-21 of estrous cycle, and luteal cells from corpora lutea (CL) collected on days 8-12 of the estrous cycle were used. The cells were incubated (6h) with these xenobiotics and the expression of NP-I/OT and PGA genes was determined. All PCBs increased (P<0.05) NP-I/OT gene expression in granulosa cells. Similarly, all PCBs but PCB 126 increased (P<0.05) PGA gene expression in these cells. DDT and DDE increased (P<0.05) gene expression of NP-I/OT in granulosa cells, while gene expression of PGA in these cells was stimulated (P<0.05) by DDE only. The mRNA expression for NP-I/OT and PGA in luteal cells was increased (P<0.05) by PCB 77 and PCB 153. Both DDE isomers and mixture also stimulated (P<0.05) of NP-I/OT mRNA expression, while increase (P<0.05) of PGA mRNA expression was elicited by incubation of these cells with DDE mixture and Ar 1248. Obtained data suggest that PCBs, DDT and DDE can affect the mRNA expression for NP-I/OT and PGA in bovine granulosa and luteal cells.
Process modeling with the regression network.
van der Walt, T; Barnard, E; van Deventer, J
1995-01-01
A new connectionist network topology called the regression network is proposed. The structural and underlying mathematical features of the regression network are investigated. Emphasis is placed on the intricacies of the optimization process for the regression network and some measures to alleviate these difficulties of optimization are proposed and investigated. The ability of the regression network algorithm to perform either nonparametric or parametric optimization, as well as a combination of both, is also highlighted. It is further shown how the regression network can be used to model systems which are poorly understood on the basis of sparse data. A semi-empirical regression network model is developed for a metallurgical processing operation (a hydrocyclone classifier) by building mechanistic knowledge into the connectionist structure of the regression network model. Poorly understood aspects of the process are provided for by use of nonparametric regions within the structure of the semi-empirical connectionist model. The performance of the regression network model is compared to the corresponding generalization performance results obtained by some other nonparametric regression techniques.
Quantile regression applied to spectral distance decay
Rocchini, D.; Cade, B.S.
2008-01-01
Remotely sensed imagery has long been recognized as a powerful support for characterizing and estimating biodiversity. Spectral distance among sites has proven to be a powerful approach for detecting species composition variability. Regression analysis of species similarity versus spectral distance allows us to quantitatively estimate the amount of turnover in species composition with respect to spectral and ecological variability. In classical regression analysis, the residual sum of squares is minimized for the mean of the dependent variable distribution. However, many ecological data sets are characterized by a high number of zeroes that add noise to the regression model. Quantile regressions can be used to evaluate trend in the upper quantiles rather than a mean trend across the whole distribution of the dependent variable. In this letter, we used ordinary least squares (OLS) and quantile regressions to estimate the decay of species similarity versus spectral distance. The achieved decay rates were statistically nonzero (p < 0.01), considering both OLS and quantile regressions. Nonetheless, the OLS regression estimate of the mean decay rate was only half the decay rate indicated by the upper quantiles. Moreover, the intercept value, representing the similarity reached when the spectral distance approaches zero, was very low compared with the intercepts of the upper quantiles, which detected high species similarity when habitats are more similar. In this letter, we demonstrated the power of using quantile regressions applied to spectral distance decay to reveal species diversity patterns otherwise lost or underestimated by OLS regression. ?? 2008 IEEE.
[From clinical judgment to linear regression model.
Palacios-Cruz, Lino; Pérez, Marcela; Rivas-Ruiz, Rodolfo; Talavera, Juan O
2013-01-01
When we think about mathematical models, such as linear regression model, we think that these terms are only used by those engaged in research, a notion that is far from the truth. Legendre described the first mathematical model in 1805, and Galton introduced the formal term in 1886. Linear regression is one of the most commonly used regression models in clinical practice. It is useful to predict or show the relationship between two or more variables as long as the dependent variable is quantitative and has normal distribution. Stated in another way, the regression is used to predict a measure based on the knowledge of at least one other variable. Linear regression has as it's first objective to determine the slope or inclination of the regression line: Y = a + bx, where "a" is the intercept or regression constant and it is equivalent to "Y" value when "X" equals 0 and "b" (also called slope) indicates the increase or decrease that occurs when the variable "x" increases or decreases in one unit. In the regression line, "b" is called regression coefficient. The coefficient of determination (R(2)) indicates the importance of independent variables in the outcome.
Geodesic least squares regression on information manifolds
Verdoolaege, Geert
2014-12-05
We present a novel regression method targeted at situations with significant uncertainty on both the dependent and independent variables or with non-Gaussian distribution models. Unlike the classic regression model, the conditional distribution of the response variable suggested by the data need not be the same as the modeled distribution. Instead they are matched by minimizing the Rao geodesic distance between them. This yields a more flexible regression method that is less constrained by the assumptions imposed through the regression model. As an example, we demonstrate the improved resistance of our method against some flawed model assumptions and we apply this to scaling laws in magnetic confinement fusion.
Technology Transfer Automated Retrieval System (TEKTRAN)
The pulsatile uterine secretion of prostaglandin F2 alpha (PGF) triggers the regression of the corpus luteum (CL). Recent studies have explored global changes in gene expression in response to PGF that may contribute to structural and functional regression of the CL. Activating transcription facto...
Suppression Situations in Multiple Linear Regression
ERIC Educational Resources Information Center
Shieh, Gwowen
2006-01-01
This article proposes alternative expressions for the two most prevailing definitions of suppression without resorting to the standardized regression modeling. The formulation provides a simple basis for the examination of their relationship. For the two-predictor regression, the author demonstrates that the previous results in the literature are…
Regression Analysis: Legal Applications in Institutional Research
ERIC Educational Resources Information Center
Frizell, Julie A.; Shippen, Benjamin S., Jr.; Luna, Andrew L.
2008-01-01
This article reviews multiple regression analysis, describes how its results should be interpreted, and instructs institutional researchers on how to conduct such analyses using an example focused on faculty pay equity between men and women. The use of multiple regression analysis will be presented as a method with which to compare salaries of…
Principles of Quantile Regression and an Application
ERIC Educational Resources Information Center
Chen, Fang; Chalhoub-Deville, Micheline
2014-01-01
Newer statistical procedures are typically introduced to help address the limitations of those already in practice or to deal with emerging research needs. Quantile regression (QR) is introduced in this paper as a relatively new methodology, which is intended to overcome some of the limitations of least squares mean regression (LMR). QR is more…
Three-Dimensional Modeling in Linear Regression.
ERIC Educational Resources Information Center
Herman, James D.
Linear regression examines the relationship between one or more independent (predictor) variables and a dependent variable. By using a particular formula, regression determines the weights needed to minimize the error term for a given set of predictors. With one predictor variable, the relationship between the predictor and the dependent variable…
A Practical Guide to Regression Discontinuity
ERIC Educational Resources Information Center
Jacob, Robin; Zhu, Pei; Somers, Marie-Andrée; Bloom, Howard
2012-01-01
Regression discontinuity (RD) analysis is a rigorous nonexperimental approach that can be used to estimate program impacts in situations in which candidates are selected for treatment based on whether their value for a numeric rating exceeds a designated threshold or cut-point. Over the last two decades, the regression discontinuity approach has…
Regression Analysis and the Sociological Imagination
ERIC Educational Resources Information Center
De Maio, Fernando
2014-01-01
Regression analysis is an important aspect of most introductory statistics courses in sociology but is often presented in contexts divorced from the central concerns that bring students into the discipline. Consequently, we present five lesson ideas that emerge from a regression analysis of income inequality and mortality in the USA and Canada.
Atherosclerotic plaque regression: fact or fiction?
Shanmugam, Nesan; Román-Rego, Ana; Ong, Peter; Kaski, Juan Carlos
2010-08-01
Coronary artery disease is the major cause of death in the western world. The formation and rapid progression of atheromatous plaques can lead to serious cardiovascular events in patients with atherosclerosis. The better understanding, in recent years, of the mechanisms leading to atheromatous plaque growth and disruption and the availability of powerful HMG CoA-reductase inhibitors (statins) has permitted the consideration of plaque regression as a realistic therapeutic goal. This article reviews the existing evidence underpinning current therapeutic strategies aimed at achieving atherosclerotic plaque regression. In this review we also discuss imaging modalities for the assessment of plaque regression, predictors of regression and whether plaque regression is associated with a survival benefit.
Should metacognition be measured by logistic regression?
Rausch, Manuel; Zehetleitner, Michael
2017-03-01
Are logistic regression slopes suitable to quantify metacognitive sensitivity, i.e. the efficiency with which subjective reports differentiate between correct and incorrect task responses? We analytically show that logistic regression slopes are independent from rating criteria in one specific model of metacognition, which assumes (i) that rating decisions are based on sensory evidence generated independently of the sensory evidence used for primary task responses and (ii) that the distributions of evidence are logistic. Given a hierarchical model of metacognition, logistic regression slopes depend on rating criteria. According to all considered models, regression slopes depend on the primary task criterion. A reanalysis of previous data revealed that massive numbers of trials are required to distinguish between hierarchical and independent models with tolerable accuracy. It is argued that researchers who wish to use logistic regression as measure of metacognitive sensitivity need to control the primary task criterion and rating criteria.
Almost efficient estimation of relative risk regression
Fitzmaurice, Garrett M.; Lipsitz, Stuart R.; Arriaga, Alex; Sinha, Debajyoti; Greenberg, Caprice; Gawande, Atul A.
2014-01-01
Relative risks (RRs) are often considered the preferred measures of association in prospective studies, especially when the binary outcome of interest is common. In particular, many researchers regard RRs to be more intuitively interpretable than odds ratios. Although RR regression is a special case of generalized linear models, specifically with a log link function for the binomial (or Bernoulli) outcome, the resulting log-binomial regression does not respect the natural parameter constraints. Because log-binomial regression does not ensure that predicted probabilities are mapped to the [0,1] range, maximum likelihood (ML) estimation is often subject to numerical instability that leads to convergence problems. To circumvent these problems, a number of alternative approaches for estimating RR regression parameters have been proposed. One approach that has been widely studied is the use of Poisson regression estimating equations. The estimating equations for Poisson regression yield consistent, albeit inefficient, estimators of the RR regression parameters. We consider the relative efficiency of the Poisson regression estimator and develop an alternative, almost efficient estimator for the RR regression parameters. The proposed method uses near-optimal weights based on a Maclaurin series (Taylor series expanded around zero) approximation to the true Bernoulli or binomial weight function. This yields an almost efficient estimator while avoiding convergence problems. We examine the asymptotic relative efficiency of the proposed estimator for an increase in the number of terms in the series. Using simulations, we demonstrate the potential for convergence problems with standard ML estimation of the log-binomial regression model and illustrate how this is overcome using the proposed estimator. We apply the proposed estimator to a study of predictors of pre-operative use of beta blockers among patients undergoing colorectal surgery after diagnosis of colon cancer. PMID
Brito, L F C; Baldrighi, J M; Wolf, C A; Ginther, O J
2017-01-01
The objective of the present study was to investigate the effect of reproductive hormones (GnRH, hCG, LH and progesterone) on the regulation of corpus luteum (CL) and ovarian blood flow. Diestrous mares received a single treatment of saline, 100μg gonadorelin (GnRH), or 1500IU hCG 10days after ovulation. Plasma LH and progesterone concentrations, resistance index (RI) for ovarian artery blood-flow, and percentage of corpus luteum (CL) with color-Doppler signals of blood flow were determined immediately before treatment (hour 0) and at hours 0.25, 0.5, 1, 1.5, 2, 3, 4, 5, and 6. In the GnRH group, LH increased (P<0.0001) between hours 0 and 0.25 and then progressively decreased; concentration of LH was not affected in the saline and hCG groups. Progesterone concentration was not different among groups. In the GnRH group, RI tended (P<0.07) to decrease between hours 0 and 1.5 and increased (P<0.01) between hours 1.5 and 4. In the hCG group, two transient RI decreases (P<0.05) occurred before hour 2. The percentage change from hour 0 in the percentage of CL with blood-flow signals was greater at hour 0.5 in the GnRH group than in the saline group and was intermediate in the hCG group. The similarity among groups in progesterone concentration indicated that changes in progesterone were not involved in the GnRH and hCG stimulation of ovarian vascular perfusion. Effects of treatment might have been mediated through LH; however, since hCG biological activity is primarily LH-like, the differences in timing and degree of ovarian and luteal blood flow changes after GnRH or hCG administration in the present study suggest that GnRH might have a direct effect on ovarian blood vessels and vascular control.
Investigating bias in squared regression structure coefficients
Nimon, Kim F.; Zientek, Linda R.; Thompson, Bruce
2015-01-01
The importance of structure coefficients and analogs of regression weights for analysis within the general linear model (GLM) has been well-documented. The purpose of this study was to investigate bias in squared structure coefficients in the context of multiple regression and to determine if a formula that had been shown to correct for bias in squared Pearson correlation coefficients and coefficients of determination could be used to correct for bias in squared regression structure coefficients. Using data from a Monte Carlo simulation, this study found that squared regression structure coefficients corrected with Pratt's formula produced less biased estimates and might be more accurate and stable estimates of population squared regression structure coefficients than estimates with no such corrections. While our findings are in line with prior literature that identified multicollinearity as a predictor of bias in squared regression structure coefficients but not coefficients of determination, the findings from this study are unique in that the level of predictive power, number of predictors, and sample size were also observed to contribute bias in squared regression structure coefficients. PMID:26217273
Investigating bias in squared regression structure coefficients.
Nimon, Kim F; Zientek, Linda R; Thompson, Bruce
2015-01-01
The importance of structure coefficients and analogs of regression weights for analysis within the general linear model (GLM) has been well-documented. The purpose of this study was to investigate bias in squared structure coefficients in the context of multiple regression and to determine if a formula that had been shown to correct for bias in squared Pearson correlation coefficients and coefficients of determination could be used to correct for bias in squared regression structure coefficients. Using data from a Monte Carlo simulation, this study found that squared regression structure coefficients corrected with Pratt's formula produced less biased estimates and might be more accurate and stable estimates of population squared regression structure coefficients than estimates with no such corrections. While our findings are in line with prior literature that identified multicollinearity as a predictor of bias in squared regression structure coefficients but not coefficients of determination, the findings from this study are unique in that the level of predictive power, number of predictors, and sample size were also observed to contribute bias in squared regression structure coefficients.
Regression modeling of ground-water flow
Cooley, R.L.; Naff, R.L.
1985-01-01
Nonlinear multiple regression methods are developed to model and analyze groundwater flow systems. Complete descriptions of regression methodology as applied to groundwater flow models allow scientists and engineers engaged in flow modeling to apply the methods to a wide range of problems. Organization of the text proceeds from an introduction that discusses the general topic of groundwater flow modeling, to a review of basic statistics necessary to properly apply regression techniques, and then to the main topic: exposition and use of linear and nonlinear regression to model groundwater flow. Statistical procedures are given to analyze and use the regression models. A number of exercises and answers are included to exercise the student on nearly all the methods that are presented for modeling and statistical analysis. Three computer programs implement the more complex methods. These three are a general two-dimensional, steady-state regression model for flow in an anisotropic, heterogeneous porous medium, a program to calculate a measure of model nonlinearity with respect to the regression parameters, and a program to analyze model errors in computed dependent variables such as hydraulic head. (USGS)
Mlynarczuk, J; Wrobel, M H; Kotwica, J
2014-04-15
The orphan receptor steroidogenic factor-1 (SF-1) is involved in the regulation of ovarian steroidogenesis in cows. It is hypothesized that estrogen-like chlorinated compounds might affect SF-1, and thus impair the function of the ovary. Bovine luteal cells from the estrous cycle (Days: 1-5, 6-10, 11-15, and 16-19) were treated for 50 hours with DDT, 1,1-dichloro-2,2-bis(4-chlorophenyl)ethene, 3,3'4,4'-tetrachlorobiphenyl or 2'2'4,4',5,5'-hexachlorobiphenyl (each at a dose of 10 ng/mL). Luteal cells were also treated with 4-(heptyloxy)phenol (1 × 10(-7) M), an SF-1 agonist, and F0160 (1 × 10(-6) M), an SF-1 blocker, jointly or separately. The secretion of progesterone and oxytocin and the expression of oxytocin precursor (NP-I/OT) messenger RNA were increased (P < 0.05) by all studied xenobiotics and 4-(heptyloxy)phenol, although they were inhibited (P < 0.05) by F0160. However, the xenobiotics did not affect (P > 0.05) SF-1 messenger RNA expression. In summary, SF-1 is involved in the adverse effect of chlorinated xenobiotics on the regulation of the bovine CL.
Relative risk regression analysis of epidemiologic data.
Prentice, R L
1985-11-01
Relative risk regression methods are described. These methods provide a unified approach to a range of data analysis problems in environmental risk assessment and in the study of disease risk factors more generally. Relative risk regression methods are most readily viewed as an outgrowth of Cox's regression and life model. They can also be viewed as a regression generalization of more classical epidemiologic procedures, such as that due to Mantel and Haenszel. In the context of an epidemiologic cohort study, relative risk regression methods extend conventional survival data methods and binary response (e.g., logistic) regression models by taking explicit account of the time to disease occurrence while allowing arbitrary baseline disease rates, general censorship, and time-varying risk factors. This latter feature is particularly relevant to many environmental risk assessment problems wherein one wishes to relate disease rates at a particular point in time to aspects of a preceding risk factor history. Relative risk regression methods also adapt readily to time-matched case-control studies and to certain less standard designs. The uses of relative risk regression methods are illustrated and the state of development of these procedures is discussed. It is argued that asymptotic partial likelihood estimation techniques are now well developed in the important special case in which the disease rates of interest have interpretations as counting process intensity functions. Estimation of relative risks processes corresponding to disease rates falling outside this class has, however, received limited attention. The general area of relative risk regression model criticism has, as yet, not been thoroughly studied, though a number of statistical groups are studying such features as tests of fit, residuals, diagnostics and graphical procedures. Most such studies have been restricted to exponential form relative risks as have simulation studies of relative risk estimation
Technology Transfer Automated Retrieval System (TEKTRAN)
In precision agriculture regression has been used widely to quality the relationship between soil attributes and other environmental variables. However, spatial correlation existing in soil samples usually makes the regression model suboptimal. In this study, a regression-kriging method was attemp...
NASA Astrophysics Data System (ADS)
Darnah
2016-04-01
Poisson regression has been used if the response variable is count data that based on the Poisson distribution. The Poisson distribution assumed equal dispersion. In fact, a situation where count data are over dispersion or under dispersion so that Poisson regression inappropriate because it may underestimate the standard errors and overstate the significance of the regression parameters, and consequently, giving misleading inference about the regression parameters. This paper suggests the generalized Poisson regression model to handling over dispersion and under dispersion on the Poisson regression model. The Poisson regression model and generalized Poisson regression model will be applied the number of filariasis cases in East Java. Based regression Poisson model the factors influence of filariasis are the percentage of families who don't behave clean and healthy living and the percentage of families who don't have a healthy house. The Poisson regression model occurs over dispersion so that we using generalized Poisson regression. The best generalized Poisson regression model showing the factor influence of filariasis is percentage of families who don't have healthy house. Interpretation of result the model is each additional 1 percentage of families who don't have healthy house will add 1 people filariasis patient.
Regressive language in severe head injury.
Thomsen, I V; Skinhoj, E
1976-09-01
In a follow-up study of 50 patients with severe head injuries three patients had echolalia. One patient with initially global aphasia had echolalia for some weeks when he started talking. Another patient with severe diffuse brain damage, dementia, and emotional regression had echolalia. The dysfunction was considered a detour performance. In the third patient echolalia and palilalia were details in a total pattern of regression lasting for months. The patient, who had extensive frontal atrophy secondary to a very severe head trauma, presented an extreme state of regression returning to a foetal-body pattern and behaving like a baby.
Regression of altitude-produced cardiac hypertrophy.
NASA Technical Reports Server (NTRS)
Sizemore, D. A.; Mcintyre, T. W.; Van Liere, E. J.; Wilson , M. F.
1973-01-01
The rate of regression of cardiac hypertrophy with time has been determined in adult male albino rats. The hypertrophy was induced by intermittent exposure to simulated high altitude. The percentage hypertrophy was much greater (46%) in the right ventricle than in the left (16%). The regression could be adequately fitted to a single exponential function with a half-time of 6.73 plus or minus 0.71 days (90% CI). There was no significant difference in the rates of regression for the two ventricles.
A new bivariate negative binomial regression model
NASA Astrophysics Data System (ADS)
Faroughi, Pouya; Ismail, Noriszura
2014-12-01
This paper introduces a new form of bivariate negative binomial (BNB-1) regression which can be fitted to bivariate and correlated count data with covariates. The BNB regression discussed in this study can be fitted to bivariate and overdispersed count data with positive, zero or negative correlations. The joint p.m.f. of the BNB1 distribution is derived from the product of two negative binomial marginals with a multiplicative factor parameter. Several testing methods were used to check overdispersion and goodness-of-fit of the model. Application of BNB-1 regression is illustrated on Malaysian motor insurance dataset. The results indicated that BNB-1 regression has better fit than bivariate Poisson and BNB-2 models with regards to Akaike information criterion.
Some Simple Computational Formulas for Multiple Regression
ERIC Educational Resources Information Center
Aiken, Lewis R., Jr.
1974-01-01
Short-cut formulas are presented for direct computation of the beta weights, the standard errors of the beta weights, and the multiple correlation coefficient for multiple regression problems involving three independent variables and one dependent variable. (Author)
An introduction to multilevel regression models.
Austin, P C; Goel, V; van Walraven, C
2001-01-01
Data in health research are frequently structured hierarchically. For example, data may consist of patients nested within physicians, who in turn may be nested in hospitals or geographic regions. Fitting regression models that ignore the hierarchical structure of the data can lead to false inferences being drawn from the data. Implementing a statistical analysis that takes into account the hierarchical structure of the data requires special methodologies. In this paper, we introduce the concept of hierarchically structured data, and present an introduction to hierarchical regression models. We then compare the performance of a traditional regression model with that of a hierarchical regression model on a dataset relating test utilization at the annual health exam with patient and physician characteristics. In comparing the resultant models, we see that false inferences can be drawn by ignoring the structure of the data.
Multiple Instance Regression with Structured Data
NASA Technical Reports Server (NTRS)
Wagstaff, Kiri L.; Lane, Terran; Roper, Alex
2008-01-01
This slide presentation reviews the use of multiple instance regression with structured data from multiple and related data sets. It applies the concept to a practical problem, that of estimating crop yield using remote sensed country wide weekly observations.
Bayesian Comparison of Two Regression Lines.
ERIC Educational Resources Information Center
Tsutakawa, Robert K.
1978-01-01
A Bayesian solution is presented for the Johnson-Neyman problem (whether or not the distance between two regression lines is statistically significant over a finite interval of the independent variable). (Author/CTM)
TWSVR: Regression via Twin Support Vector Machine.
Khemchandani, Reshma; Goyal, Keshav; Chandra, Suresh
2016-02-01
Taking motivation from Twin Support Vector Machine (TWSVM) formulation, Peng (2010) attempted to propose Twin Support Vector Regression (TSVR) where the regressor is obtained via solving a pair of quadratic programming problems (QPPs). In this paper we argue that TSVR formulation is not in the true spirit of TWSVM. Further, taking motivation from Bi and Bennett (2003), we propose an alternative approach to find a formulation for Twin Support Vector Regression (TWSVR) which is in the true spirit of TWSVM. We show that our proposed TWSVR can be derived from TWSVM for an appropriately constructed classification problem. To check the efficacy of our proposed TWSVR we compare its performance with TSVR and classical Support Vector Regression(SVR) on various regression datasets.
Marginal longitudinal semiparametric regression via penalized splines
Kadiri, M. Al; Carroll, R.J.; Wand, M.P.
2010-01-01
We study the marginal longitudinal nonparametric regression problem and some of its semiparametric extensions. We point out that, while several elaborate proposals for efficient estimation have been proposed, a relative simple and straightforward one, based on penalized splines, has not. After describing our approach, we then explain how Gibbs sampling and the BUGS software can be used to achieve quick and effective implementation. Illustrations are provided for nonparametric regression and additive models. PMID:21037941
Discriminative Elastic-Net Regularized Linear Regression.
Zhang, Zheng; Lai, Zhihui; Xu, Yong; Shao, Ling; Wu, Jian; Xie, Guo-Sen
2017-03-01
In this paper, we aim at learning compact and discriminative linear regression models. Linear regression has been widely used in different problems. However, most of the existing linear regression methods exploit the conventional zero-one matrix as the regression targets, which greatly narrows the flexibility of the regression model. Another major limitation of these methods is that the learned projection matrix fails to precisely project the image features to the target space due to their weak discriminative capability. To this end, we present an elastic-net regularized linear regression (ENLR) framework, and develop two robust linear regression models which possess the following special characteristics. First, our methods exploit two particular strategies to enlarge the margins of different classes by relaxing the strict binary targets into a more feasible variable matrix. Second, a robust elastic-net regularization of singular values is introduced to enhance the compactness and effectiveness of the learned projection matrix. Third, the resulting optimization problem of ENLR has a closed-form solution in each iteration, which can be solved efficiently. Finally, rather than directly exploiting the projection matrix for recognition, our methods employ the transformed features as the new discriminate representations to make final image classification. Compared with the traditional linear regression model and some of its variants, our method is much more accurate in image classification. Extensive experiments conducted on publicly available data sets well demonstrate that the proposed framework can outperform the state-of-the-art methods. The MATLAB codes of our methods can be available at http://www.yongxu.org/lunwen.html.
The Geometry of Enhancement in Multiple Regression
ERIC Educational Resources Information Center
Waller, Niels G.
2011-01-01
In linear multiple regression, "enhancement" is said to occur when R[superscript 2] = b[prime]r greater than r[prime]r, where b is a p x 1 vector of standardized regression coefficients and r is a p x 1 vector of correlations between a criterion y and a set of standardized regressors, x. When p = 1 then b [is congruent to] r and…
[Iris movement mediates pupillary membrane regression].
Morizane, Yuki
2007-11-01
In the course of mammalian lens development, a transient capillary meshwork called as the pupillary membrane (PM) forms. It is located in the pupil area to nourish the anterior surface of the lens, and then regresses to clear the optical path. Although the involvement of the apoptotic process has been reported in PM regression, the initiating factor remains unknown. We initially found that regression of the PM coincided with the development of iris motility, and that iris movement caused cessation and resumption of blood flow within the PM. Therefore, we investigated whether the development of the capacity of the iris to constrict and dilate can function as an essential signal that induces apoptosis in the PM. Continuous inhibition of iris movement with mydriatic agents suppressed apoptosis of the PM and resulted in the persistence of PM in rats. The distribution of apoptotic cells in the regressing PM was diffuse and showed no apparent localization. These results indicated that iris movement induced regression of the PM by changing the blood flow within it. This study suggests the importance of the physiological interactions between tissues-in this case, the iris and the PM-as a signal to advance vascular regression during organ development.
Multiple-Instance Regression with Structured Data
NASA Technical Reports Server (NTRS)
Wagstaff, Kiri L.; Lane, Terran; Roper, Alex
2008-01-01
We present a multiple-instance regression algorithm that models internal bag structure to identify the items most relevant to the bag labels. Multiple-instance regression (MIR) operates on a set of bags with real-valued labels, each containing a set of unlabeled items, in which the relevance of each item to its bag label is unknown. The goal is to predict the labels of new bags from their contents. Unlike previous MIR methods, MI-ClusterRegress can operate on bags that are structured in that they contain items drawn from a number of distinct (but unknown) distributions. MI-ClusterRegress simultaneously learns a model of the bag's internal structure, the relevance of each item, and a regression model that accurately predicts labels for new bags. We evaluated this approach on the challenging MIR problem of crop yield prediction from remote sensing data. MI-ClusterRegress provided predictions that were more accurate than those obtained with non-multiple-instance approaches or MIR methods that do not model the bag structure.
Reynolds, Kasey A.; Omurtag, Kenan R.; Jimenez, Patricia T.; Rhee, Julie S.; Tuuli, Method G.; Jungheim, Emily S.
2013-01-01
STUDY QUESTION Does a luteal estradiol (LE) stimulation protocol improve outcomes in poor responders to IVF? SUMMARY ANSWER LE priming is associated with decreased cycle cancellation and increased chance of clinical pregnancy in poor responders WHAT IS KNOWN ALREADY Poor responders to IVF are one of the most challenging patient populations to treat. Many standard protocols currently exist for stimulating these patients but all have failed to improve outcomes. STUDY DESIGN, SIZE, DURATION Systematic review and meta-analysis including eight published studies comparing assisted reproduction technology (ART) outcomes in poor responders exposed to controlled ovarian hyperstimulation with and without LE priming. A search of the databases MEDLINE, EMBASE and PUBMED was carried out for studies in the English language published up to January 2012. PARTICIPANTS/MATERIALS, SETTING, METHODS Studies evaluating women defined as poor responders to ART were evaluated. These studies were identified following a systematic review of the literature and data were analyzed using the DerSimonian–Laird random effects model. The main outcomes of interest were cycle cancellation rate and clinical pregnancy. Although the definition of clinical pregnancy varied between studies, the principal definition included fetal cardiac activity as assessed by transvaginal ultrasonography after 5 weeks of gestation. MAIN RESULTS AND THE ROLE OF CHANCE A total of 2249 publications were identified from the initial search, and the bibliographies, abstracts and other sources yielded 11 more. After excluding duplications, 1227 studies remained and 8 ultimately met the inclusion criteria. Compared with women undergoing non-LE primed protocols (n = 621), women exposed to LE priming (n = 468) had a lower risk of cycle cancellation [relative risk (RR): 0.60, 95% confidence interval (CI): 0.45–0.78] and an improved chance of clinical pregnancy (RR: 1.33, 95% CI: 1.02–1.72). There was no significant
MULTILINEAR TENSOR REGRESSION FOR LONGITUDINAL RELATIONAL DATA.
Hoff, Peter D
2015-09-01
A fundamental aspect of relational data, such as from a social network, is the possibility of dependence among the relations. In particular, the relations between members of one pair of nodes may have an effect on the relations between members of another pair. This article develops a type of regression model to estimate such effects in the context of longitudinal and multivariate relational data, or other data that can be represented in the form of a tensor. The model is based on a general multilinear tensor regression model, a special case of which is a tensor autoregression model in which the tensor of relations at one time point are parsimoniously regressed on relations from previous time points. This is done via a separable, or Kronecker-structured, regression parameter along with a separable covariance model. In the context of an analysis of longitudinal multivariate relational data, it is shown how the multilinear tensor regression model can represent patterns that often appear in relational and network data, such as reciprocity and transitivity.
On regression adjustment for the propensity score.
Vansteelandt, S; Daniel, R M
2014-10-15
Propensity scores are widely adopted in observational research because they enable adjustment for high-dimensional confounders without requiring models for their association with the outcome of interest. The results of statistical analyses based on stratification, matching or inverse weighting by the propensity score are therefore less susceptible to model extrapolation than those based solely on outcome regression models. This is attractive because extrapolation in outcome regression models may be alarming, yet difficult to diagnose, when the exposed and unexposed individuals have very different covariate distributions. Standard regression adjustment for the propensity score forms an alternative to the aforementioned propensity score methods, but the benefits of this are less clear because it still involves modelling the outcome in addition to the propensity score. In this article, we develop novel insights into the properties of this adjustment method. We demonstrate that standard tests of the null hypothesis of no exposure effect (based on robust variance estimators), as well as particular standardised effects obtained from such adjusted regression models, are robust against misspecification of the outcome model when a propensity score model is correctly specified; they are thus not vulnerable to the aforementioned problem of extrapolation. We moreover propose efficient estimators for these standardised effects, which retain a useful causal interpretation even when the propensity score model is misspecified, provided the outcome regression model is correctly specified.
Hyperglycemia impairs atherosclerosis regression in mice.
Gaudreault, Nathalie; Kumar, Nikit; Olivas, Victor R; Eberlé, Delphine; Stephens, Kyle; Raffai, Robert L
2013-12-01
Diabetic patients are known to be more susceptible to atherosclerosis and its associated cardiovascular complications. However, the effects of hyperglycemia on atherosclerosis regression remain unclear. We hypothesized that hyperglycemia impairs atherosclerosis regression by modulating the biological function of lesional macrophages. HypoE (Apoe(h/h)Mx1-Cre) mice express low levels of apolipoprotein E (apoE) and develop atherosclerosis when fed a high-fat diet. Atherosclerosis regression occurs in these mice upon plasma lipid lowering induced by a change in diet and the restoration of apoE expression. We examined the morphological characteristics of regressed lesions and assessed the biological function of lesional macrophages isolated with laser-capture microdissection in euglycemic and hyperglycemic HypoE mice. Hyperglycemia induced by streptozotocin treatment impaired lesion size reduction (36% versus 14%) and lipid loss (38% versus 26%) after the reversal of hyperlipidemia. However, decreases in lesional macrophage content and remodeling in both groups of mice were similar. Gene expression analysis revealed that hyperglycemia impaired cholesterol transport by modulating ATP-binding cassette A1, ATP-binding cassette G1, scavenger receptor class B family member (CD36), scavenger receptor class B1, and wound healing pathways in lesional macrophages during atherosclerosis regression. Hyperglycemia impairs both reduction in size and loss of lipids from atherosclerotic lesions upon plasma lipid lowering without significantly affecting the remodeling of the vascular wall.
Regression models for estimating coseismic landslide displacement
Jibson, R.W.
2007-01-01
Newmark's sliding-block model is widely used to estimate coseismic slope performance. Early efforts to develop simple regression models to estimate Newmark displacement were based on analysis of the small number of strong-motion records then available. The current availability of a much larger set of strong-motion records dictates that these regression equations be updated. Regression equations were generated using data derived from a collection of 2270 strong-motion records from 30 worldwide earthquakes. The regression equations predict Newmark displacement in terms of (1) critical acceleration ratio, (2) critical acceleration ratio and earthquake magnitude, (3) Arias intensity and critical acceleration, and (4) Arias intensity and critical acceleration ratio. These equations are well constrained and fit the data well (71% < R2 < 88%), but they have standard deviations of about 0.5 log units, such that the range defined by the mean ?? one standard deviation spans about an order of magnitude. These regression models, therefore, are not recommended for use in site-specific design, but rather for regional-scale seismic landslide hazard mapping or for rapid preliminary screening of sites. ?? 2007 Elsevier B.V. All rights reserved.
Plewes, M R; Burns, P D; Graham, P E; Hyslop, R M; Barisas, B G
2017-01-01
Lipid microdomains are ordered regions on the plasma membrane of cells, rich in cholesterol and sphingolipids, ranging in size from 10 to 200 nm in diameter. These lipid-ordered domains may serve as platforms to facilitate colocalization of intracellular signaling proteins during agonist-induced signal transduction. It is hypothesized that fish oil will disrupt the lipid microdomains, increasing spatial distribution of these lipid-ordered domains and lateral mobility of the prostaglandin (PG) F2α (FP) receptors in bovine luteal cells. The objectives of this study were to examine the effects of fish oil on (1) the spatial distribution of lipid microdomains, (2) lateral mobility of FP receptors, and (3) lateral mobility of FP receptors in the presence of PGF2α on the plasma membrane of bovine luteal cells in vitro. Bovine ovaries were obtained from a local abattoir and corpora lutea were digested using collagenase. In experiment 1, lipid microdomains were labeled using cholera toxin subunit B Alexa Fluor 555. Domains were detected as distinct patches on the plasma membrane of mixed luteal cells. Fish oil treatment decreased fluorescent intensity in a dose-dependent manner (P < 0.01). In experiment 2, single particle tracking was used to examine the effects of fish oil treatment on lateral mobility of FP receptors. Fish oil treatment increased microdiffusion and macrodiffusion coefficients of FP receptors as compared to control cells (P < 0.05). In addition, compartment diameters of domains were larger, and residence times were reduced for receptors in fish oil-treated cells (P < 0.05). In experiment 3, single particle tracking was used to determine the effects of PGF2α on lateral mobility of FP receptors and influence of fish oil treatment. Lateral mobility of receptors was decreased within 5 min following the addition of ligand for control cells (P < 0.05). However, lateral mobility of receptors was unaffected by addition of ligand for fish oil-treated cells
Spontaneous skin regression and predictors of skin regression in Thai scleroderma patients.
Foocharoen, Chingching; Mahakkanukrauh, Ajanee; Suwannaroj, Siraphop; Nanagara, Ratanavadee
2011-09-01
Skin tightness is a major clinical manifestation of systemic sclerosis (SSc). Importantly for both clinicians and patients, spontaneous regression of the fibrosis process has been documented. The purpose of this study is to identify the incidence and related clinical characteristics of spontaneous regression among Thai SSc patients. A historical cohort with 4 years of follow-up was performed among SSc patients over 15 years of age diagnosed with SSc between January 1, 2005 and December 31, 2006 in Khon Kaen, Thailand. The start date was the date of the first symptom and the end date was the date of the skin score ≤2. To estimate the respective probability of regression and to assess the associated factors, the Kaplan-Meier method and Cox regression analysis was used. One hundred seventeen cases of SSc were included with a female to male ratio of 1.5:1. Thirteen patients (11.1%) experienced regression. The incidence rate of spontaneous skin regression was 0.31 per 100 person-months and the average duration of SSc at the time of regression was 35.9±15.6 months (range, 15.7-60 months). The factors that negatively correlated with regression were (a) diffuse cutaneous type, (b) Raynaud's phenomenon, (c) esophageal dysmotility, and (d) colchicine treatment at onset with a respective hazard ratio (HR) of 0.19, 0.19, 0.26, and 0.20. By contrast, the factor that positively correlated with regression was active alveolitis with cyclophosphamide therapy at onset with an HR of 4.23 (95% CI, 1.23-14.10). After regression analysis, only Raynaud's phenomenon at onset and diffuse cutaneous type had a significantly negative correlation to regression. A spontaneous regression of the skin fibrosis process was not uncommon among Thai SSc patients. The factors suggesting a poor predictor for cutaneous manifestation were Raynaud's phenomenon, diffuse cutaneous type while early cyclophosphamide therapy might be related to a better skin outcome.
Parametric modeling of quantile regression coefficient functions.
Frumento, Paolo; Bottai, Matteo
2016-03-01
Estimating the conditional quantiles of outcome variables of interest is frequent in many research areas, and quantile regression is foremost among the utilized methods. The coefficients of a quantile regression model depend on the order of the quantile being estimated. For example, the coefficients for the median are generally different from those of the 10th centile. In this article, we describe an approach to modeling the regression coefficients as parametric functions of the order of the quantile. This approach may have advantages in terms of parsimony, efficiency, and may expand the potential of statistical modeling. Goodness-of-fit measures and testing procedures are discussed, and the results of a simulation study are presented. We apply the method to analyze the data that motivated this work. The described method is implemented in the qrcm R package.
Computing aspects of power for multiple regression.
Dunlap, William P; Xin, Xue; Myers, Leann
2004-11-01
Rules of thumb for power in multiple regression research abound. Most such rules dictate the necessary sample size, but they are based only upon the number of predictor variables, usually ignoring other critical factors necessary to compute power accurately. Other guides to power in multiple regression typically use approximate rather than precise equations for the underlying distribution; entail complex preparatory computations; require interpolation with tabular presentation formats; run only under software such as Mathmatica or SAS that may not be immediately available to the user; or are sold to the user as parts of power computation packages. In contrast, the program we offer herein is immediately downloadable at no charge, runs under Windows, is interactive, self-explanatory, flexible to fit the user's own regression problems, and is as accurate as single precision computation ordinarily permits.
Uncertainty quantification in DIC with Kriging regression
NASA Astrophysics Data System (ADS)
Wang, Dezhi; DiazDelaO, F. A.; Wang, Weizhuo; Lin, Xiaoshan; Patterson, Eann A.; Mottershead, John E.
2016-03-01
A Kriging regression model is developed as a post-processing technique for the treatment of measurement uncertainty in classical subset-based Digital Image Correlation (DIC). Regression is achieved by regularising the sample-point correlation matrix using a local, subset-based, assessment of the measurement error with assumed statistical normality and based on the Sum of Squared Differences (SSD) criterion. This leads to a Kriging-regression model in the form of a Gaussian process representing uncertainty on the Kriging estimate of the measured displacement field. The method is demonstrated using numerical and experimental examples. Kriging estimates of displacement fields are shown to be in excellent agreement with 'true' values for the numerical cases and in the experimental example uncertainty quantification is carried out using the Gaussian random process that forms part of the Kriging model. The root mean square error (RMSE) on the estimated displacements is produced and standard deviations on local strain estimates are determined.
A tutorial on Bayesian Normal linear regression
NASA Astrophysics Data System (ADS)
Klauenberg, Katy; Wübbeler, Gerd; Mickan, Bodo; Harris, Peter; Elster, Clemens
2015-12-01
Regression is a common task in metrology and often applied to calibrate instruments, evaluate inter-laboratory comparisons or determine fundamental constants, for example. Yet, a regression model cannot be uniquely formulated as a measurement function, and consequently the Guide to the Expression of Uncertainty in Measurement (GUM) and its supplements are not applicable directly. Bayesian inference, however, is well suited to regression tasks, and has the advantage of accounting for additional a priori information, which typically robustifies analyses. Furthermore, it is anticipated that future revisions of the GUM shall also embrace the Bayesian view. Guidance on Bayesian inference for regression tasks is largely lacking in metrology. For linear regression models with Gaussian measurement errors this tutorial gives explicit guidance. Divided into three steps, the tutorial first illustrates how a priori knowledge, which is available from previous experiments, can be translated into prior distributions from a specific class. These prior distributions have the advantage of yielding analytical, closed form results, thus avoiding the need to apply numerical methods such as Markov Chain Monte Carlo. Secondly, formulas for the posterior results are given, explained and illustrated, and software implementations are provided. In the third step, Bayesian tools are used to assess the assumptions behind the suggested approach. These three steps (prior elicitation, posterior calculation, and robustness to prior uncertainty and model adequacy) are critical to Bayesian inference. The general guidance given here for Normal linear regression tasks is accompanied by a simple, but real-world, metrological example. The calibration of a flow device serves as a running example and illustrates the three steps. It is shown that prior knowledge from previous calibrations of the same sonic nozzle enables robust predictions even for extrapolations.
Salience Assignment for Multiple-Instance Regression
NASA Technical Reports Server (NTRS)
Wagstaff, Kiri L.; Lane, Terran
2007-01-01
We present a Multiple-Instance Learning (MIL) algorithm for determining the salience of each item in each bag with respect to the bag's real-valued label. We use an alternating-projections constrained optimization approach to simultaneously learn a regression model and estimate all salience values. We evaluate this algorithm on a significant real-world problem, crop yield modeling, and demonstrate that it provides more extensive, intuitive, and stable salience models than Primary-Instance Regression, which selects a single relevant item from each bag.
The Lax-Onsager regression `theorem' revisited
NASA Astrophysics Data System (ADS)
Lax, Melvin
2000-05-01
It is stated by Ford and O'Connell in this festschrift issue and elsewhere that "there is no quantum regression theorem" although Lax "obtained a formula for correlation in a driven quantum system that has come to be called the quantum regression theorem". This produces a puzzle: "How can it be that a non-existent theorem gives correct results?" Clarification will be provided in this paper by a description of the Lax procedure, with a quantitative estimate of the error for a damped harmonic oscillator based on expressions published in the 1960's.
Demonstration of a Fiber Optic Regression Probe
NASA Technical Reports Server (NTRS)
Korman, Valentin; Polzin, Kurt A.
2010-01-01
The capability to provide localized, real-time monitoring of material regression rates in various applications has the potential to provide a new stream of data for development testing of various components and systems, as well as serving as a monitoring tool in flight applications. These applications include, but are not limited to, the regression of a combusting solid fuel surface, the ablation of the throat in a chemical rocket or the heat shield of an aeroshell, and the monitoring of erosion in long-life plasma thrusters. The rate of regression in the first application is very fast, while the second and third are increasingly slower. A recent fundamental sensor development effort has led to a novel regression, erosion, and ablation sensor technology (REAST). The REAST sensor allows for measurement of real-time surface erosion rates at a discrete surface location. The sensor is optical, using two different, co-located fiber-optics to perform the regression measurement. The disparate optical transmission properties of the two fiber-optics makes it possible to measure the regression rate by monitoring the relative light attenuation through the fibers. As the fibers regress along with the parent material in which they are embedded, the relative light intensities through the two fibers changes, providing a measure of the regression rate. The optical nature of the system makes it relatively easy to use in a variety of harsh, high temperature environments, and it is also unaffected by the presence of electric and magnetic fields. In addition, the sensor could be used to perform optical spectroscopy on the light emitted by a process and collected by fibers, giving localized measurements of various properties. The capability to perform an in-situ measurement of material regression rates is useful in addressing a variety of physical issues in various applications. An in-situ measurement allows for real-time data regarding the erosion rates, providing a quick method for
1989-12-20
species. A series of projects focused on: 1) analyzing the effects of various hormonal ovulation induction procedures on ovarian function and the... hormone (FSH-P)- and human menopausal gonadotropin (hMG)-treated sheep than in pregnant mares’ serum gonadotropin (PMSG)-treated ewes. However...Regression in Superovulated Sheep: Relationship to Estrous Synchronization Method, Circulating Hormones , Luteinizing Hormone /Prostaglandin Fzo
Creativity and Regression on the Rorschach.
ERIC Educational Resources Information Center
Lazar, Billie S.
This paper describes the results of a study to further test and replicate previous studies partially supporting Kris's view that creativity is a regression in the service of the ego. For this sample of 42 female art and business college students, it was predicted that (1) highly creative Ss (measured by the Torrance Tests) produce more, and more…
Locating the Extrema of Fungible Regression Weights
ERIC Educational Resources Information Center
Waller, Niels G.; Jones, Jeff A.
2009-01-01
In a multiple regression analysis with three or more predictors, every set of alternate weights belongs to an infinite class of "fungible weights" (Waller, Psychometrica, "in press") that yields identical "SSE" (sum of squared errors) and R[superscript 2] values. When the R[superscript 2] using the alternate weights is a fixed value, fungible…
Assessing risk factors for periodontitis using regression
NASA Astrophysics Data System (ADS)
Lobo Pereira, J. A.; Ferreira, Maria Cristina; Oliveira, Teresa
2013-10-01
Multivariate statistical analysis is indispensable to assess the associations and interactions between different factors and the risk of periodontitis. Among others, regression analysis is a statistical technique widely used in healthcare to investigate and model the relationship between variables. In our work we study the impact of socio-demographic, medical and behavioral factors on periodontal health. Using regression, linear and logistic models, we can assess the relevance, as risk factors for periodontitis disease, of the following independent variables (IVs): Age, Gender, Diabetic Status, Education, Smoking status and Plaque Index. The multiple linear regression analysis model was built to evaluate the influence of IVs on mean Attachment Loss (AL). Thus, the regression coefficients along with respective p-values will be obtained as well as the respective p-values from the significance tests. The classification of a case (individual) adopted in the logistic model was the extent of the destruction of periodontal tissues defined by an Attachment Loss greater than or equal to 4 mm in 25% (AL≥4mm/≥25%) of sites surveyed. The association measures include the Odds Ratios together with the correspondent 95% confidence intervals.
Predicting Social Trust with Binary Logistic Regression
ERIC Educational Resources Information Center
Adwere-Boamah, Joseph; Hufstedler, Shirley
2015-01-01
This study used binary logistic regression to predict social trust with five demographic variables from a national sample of adult individuals who participated in The General Social Survey (GSS) in 2012. The five predictor variables were respondents' highest degree earned, race, sex, general happiness and the importance of personally assisting…
Invariant Ordering of Item-Total Regressions
ERIC Educational Resources Information Center
Tijmstra, Jesper; Hessen, David J.; van der Heijden, Peter G. M.; Sijtsma, Klaas
2011-01-01
A new observable consequence of the property of invariant item ordering is presented, which holds under Mokken's double monotonicity model for dichotomous data. The observable consequence is an invariant ordering of the item-total regressions. Kendall's measure of concordance "W" and a weighted version of this measure are proposed as measures for…
Superquantile Regression: Theory, Algorithms, and Applications
2014-12-01
buffered reliability, uncertainty quantification, surrogate estimation, superquantile tracking, dualization of risk 147 Unclassified Unclassified...series of numerical examples that show some of the ap- plication of superquantile regression, such as superquantile tracking and surrogate estimation...dissertation by surrogate estimation. It usually occurs when the explanatory random variable is beyond our direct control, but the dependence between the
A Skew-Normal Mixture Regression Model
ERIC Educational Resources Information Center
Liu, Min; Lin, Tsung-I
2014-01-01
A challenge associated with traditional mixture regression models (MRMs), which rest on the assumption of normally distributed errors, is determining the number of unobserved groups. Specifically, even slight deviations from normality can lead to the detection of spurious classes. The current work aims to (a) examine how sensitive the commonly…
Regression Segmentation for M³ Spinal Images.
Wang, Zhijie; Zhen, Xiantong; Tay, KengYeow; Osman, Said; Romano, Walter; Li, Shuo
2015-08-01
Clinical routine often requires to analyze spinal images of multiple anatomic structures in multiple anatomic planes from multiple imaging modalities (M(3)). Unfortunately, existing methods for segmenting spinal images are still limited to one specific structure, in one specific plane or from one specific modality (S(3)). In this paper, we propose a novel approach, Regression Segmentation, that is for the first time able to segment M(3) spinal images in one single unified framework. This approach formulates the segmentation task innovatively as a boundary regression problem: modeling a highly nonlinear mapping function from substantially diverse M(3) images directly to desired object boundaries. Leveraging the advancement of sparse kernel machines, regression segmentation is fulfilled by a multi-dimensional support vector regressor (MSVR) which operates in an implicit, high dimensional feature space where M(3) diversity and specificity can be systematically categorized, extracted, and handled. The proposed regression segmentation approach was thoroughly tested on images from 113 clinical subjects including both disc and vertebral structures, in both sagittal and axial planes, and from both MRI and CT modalities. The overall result reaches a high dice similarity index (DSI) 0.912 and a low boundary distance (BD) 0.928 mm. With our unified and expendable framework, an efficient clinical tool for M(3) spinal image segmentation can be easily achieved, and will substantially benefit the diagnosis and treatment of spinal diseases.
Categorical Variables in Multiple Regression: Some Cautions.
ERIC Educational Resources Information Center
O'Grady, Kevin E.; Medoff, Deborah R.
1988-01-01
Limitations of dummy coding and nonsense coding as methods of coding categorical variables for use as predictors in multiple regression analysis are discussed. The combination of these approaches often yields estimates and tests of significance that are not intended by researchers for inclusion in their models. (SLD)
Revisiting Regression in Autism: Heller's "Dementia Infantilis"
ERIC Educational Resources Information Center
Westphal, Alexander; Schelinski, Stefanie; Volkmar, Fred; Pelphrey, Kevin
2013-01-01
Theodor Heller first described a severe regression of adaptive function in normally developing children, something he termed dementia infantilis, over one 100 years ago. Dementia infantilis is most closely related to the modern diagnosis, childhood disintegrative disorder. We translate Heller's paper, Uber Dementia Infantilis, and discuss…
A Spline Regression Model for Latent Variables
ERIC Educational Resources Information Center
Harring, Jeffrey R.
2014-01-01
Spline (or piecewise) regression models have been used in the past to account for patterns in observed data that exhibit distinct phases. The changepoint or knot marking the shift from one phase to the other, in many applications, is an unknown parameter to be estimated. As an extension of this framework, this research considers modeling the…
Model building in nonproportional hazard regression.
Rodríguez-Girondo, Mar; Kneib, Thomas; Cadarso-Suárez, Carmen; Abu-Assi, Emad
2013-12-30
Recent developments of statistical methods allow for a very flexible modeling of covariates affecting survival times via the hazard rate, including also the inspection of possible time-dependent associations. Despite their immediate appeal in terms of flexibility, these models typically introduce additional difficulties when a subset of covariates and the corresponding modeling alternatives have to be chosen, that is, for building the most suitable model for given data. This is particularly true when potentially time-varying associations are given. We propose to conduct a piecewise exponential representation of the original survival data to link hazard regression with estimation schemes based on of the Poisson likelihood to make recent advances for model building in exponential family regression accessible also in the nonproportional hazard regression context. A two-stage stepwise selection approach, an approach based on doubly penalized likelihood, and a componentwise functional gradient descent approach are adapted to the piecewise exponential regression problem. These three techniques were compared via an intensive simulation study. An application to prognosis after discharge for patients who suffered a myocardial infarction supplements the simulation to demonstrate the pros and cons of the approaches in real data analyses.
Commonality Analysis for the Regression Case.
ERIC Educational Resources Information Center
Murthy, Kavita
Commonality analysis is a procedure for decomposing the coefficient of determination (R superscript 2) in multiple regression analyses into the percent of variance in the dependent variable associated with each independent variable uniquely, and the proportion of explained variance associated with the common effects of predictors in various…
Prediction of dynamical systems by symbolic regression
NASA Astrophysics Data System (ADS)
Quade, Markus; Abel, Markus; Shafi, Kamran; Niven, Robert K.; Noack, Bernd R.
2016-07-01
We study the modeling and prediction of dynamical systems based on conventional models derived from measurements. Such algorithms are highly desirable in situations where the underlying dynamics are hard to model from physical principles or simplified models need to be found. We focus on symbolic regression methods as a part of machine learning. These algorithms are capable of learning an analytically tractable model from data, a highly valuable property. Symbolic regression methods can be considered as generalized regression methods. We investigate two particular algorithms, the so-called fast function extraction which is a generalized linear regression algorithm, and genetic programming which is a very general method. Both are able to combine functions in a certain way such that a good model for the prediction of the temporal evolution of a dynamical system can be identified. We illustrate the algorithms by finding a prediction for the evolution of a harmonic oscillator based on measurements, by detecting an arriving front in an excitable system, and as a real-world application, the prediction of solar power production based on energy production observations at a given site together with the weather forecast.
Prediction of dynamical systems by symbolic regression.
Quade, Markus; Abel, Markus; Shafi, Kamran; Niven, Robert K; Noack, Bernd R
2016-07-01
We study the modeling and prediction of dynamical systems based on conventional models derived from measurements. Such algorithms are highly desirable in situations where the underlying dynamics are hard to model from physical principles or simplified models need to be found. We focus on symbolic regression methods as a part of machine learning. These algorithms are capable of learning an analytically tractable model from data, a highly valuable property. Symbolic regression methods can be considered as generalized regression methods. We investigate two particular algorithms, the so-called fast function extraction which is a generalized linear regression algorithm, and genetic programming which is a very general method. Both are able to combine functions in a certain way such that a good model for the prediction of the temporal evolution of a dynamical system can be identified. We illustrate the algorithms by finding a prediction for the evolution of a harmonic oscillator based on measurements, by detecting an arriving front in an excitable system, and as a real-world application, the prediction of solar power production based on energy production observations at a given site together with the weather forecast.
A Constrained Linear Estimator for Multiple Regression
ERIC Educational Resources Information Center
Davis-Stober, Clintin P.; Dana, Jason; Budescu, David V.
2010-01-01
"Improper linear models" (see Dawes, Am. Psychol. 34:571-582, "1979"), such as equal weighting, have garnered interest as alternatives to standard regression models. We analyze the general circumstances under which these models perform well by recasting a class of "improper" linear models as "proper" statistical models with a single predictor. We…
Assumptions of Multiple Regression: Correcting Two Misconceptions
ERIC Educational Resources Information Center
Williams, Matt N.; Gomez Grajales, Carlos Alberto; Kurkiewicz, Dason
2013-01-01
In 2002, an article entitled "Four assumptions of multiple regression that researchers should always test" by Osborne and Waters was published in "PARE." This article has gone on to be viewed more than 275,000 times (as of August 2013), and it is one of the first results displayed in a Google search for "regression…
The Shadow Side of Regressive Groups.
ERIC Educational Resources Information Center
McClure, Bud A.
1994-01-01
Contends that inability of groups to address conflict, encourage dissenting views, and face their negative characteristics can result in destructive behavior toward others that remains largely outside awareness of individual members. Examines regressive group characteristics; behavior of United States during Persian Gulf War is used to highlight…
Moving the Bar: Transformations in Linear Regression.
ERIC Educational Resources Information Center
Miranda, Janet
The assumption that is most important to the hypothesis testing procedure of multiple linear regression is the assumption that the residuals are normally distributed, but this assumption is not always tenable given the realities of some data sets. When normal distribution of the residuals is not met, an alternative method can be initiated. As an…
Kim, Tae Rim; Lee, Hee Min; Lee, So Yong; Kim, Eun Jin; Kim, Kug Chan; Paik, Sang Gi; Cho, Eun Wie; Kim, In Gyu
2010-09-10
Research highlights: {yields} SM22{alpha} overexpression in HepG2 cells leads cells to a growth arrest state, and the treatment of a subclinical dose of {gamma}-radiation or doxorubicin promotes cellular senescence. {yields} SM22{alpha} overexpression elevates p16{sup INK4a} followed by pRB activation, but there are no effects on p53/p21{sup WAF1/Cip1} pathway. {yields} SM22{alpha}-induced MT-1G activates p16{sup INK4a}/pRB pathway, which promotes cellular senescence by damaging agents. -- Abstract: Smooth muscle protein 22-alpha (SM22{alpha}) is known as a transformation- and shape change-sensitive actin cross-linking protein found in smooth muscle tissue and fibroblasts; however, its functional role remains uncertain. We reported previously that SM22{alpha} overexpression confers resistance against anti-cancer drugs or radiation via induction of metallothionein (MT) isozymes in HepG2 cells. In this study, we demonstrate that SM22{alpha} overexpression leads cells to a growth arrest state and promotes cellular senescence caused by treatment with a subclinical dose of {gamma}-radiation (0.05 and 0.1 Gy) or doxorubicin (0.01 and 0.05 {mu}g/ml), compared to control cells. Senescence growth arrest is known to be controlled by p53 phosphorylation/p21{sup WAF1/Cip1} induction or p16{sup INK4a}/retinoblastoma protein (pRB) activation. SM22{alpha} overexpression in HepG2 cells elevated p16{sup INK4a} followed by pRB activation, but did not activate the p53/p21{sup WAF1/Cip1} pathway. Moreover, MT-1G, which is induced by SM22{alpha} overexpression, was involved in the activation of the p16{sup INK4a}/pRB pathway, which led to a growth arrest state and promoted cellular senescence caused by damaging agents. Our findings provide the first demonstration that SM22{alpha} modulates cellular senescence caused by damaging agents via regulation of the p16{sup INK4a}/pRB pathway in HepG2 cells and that these effects of SM22{alpha} are partially mediated by MT-1G.
Embedded Sensors for Measuring Surface Regression
NASA Technical Reports Server (NTRS)
Gramer, Daniel J.; Taagen, Thomas J.; Vermaak, Anton G.
2006-01-01
The development and evaluation of new hybrid and solid rocket motors requires accurate characterization of the propellant surface regression as a function of key operational parameters. These characteristics establish the propellant flow rate and are prime design drivers affecting the propulsion system geometry, size, and overall performance. There is a similar need for the development of advanced ablative materials, and the use of conventional ablatives exposed to new operational environments. The Miniature Surface Regression Sensor (MSRS) was developed to serve these applications. It is designed to be cast or embedded in the material of interest and regresses along with it. During this process, the resistance of the sensor is related to its instantaneous length, allowing the real-time thickness of the host material to be established. The time derivative of this data reveals the instantaneous surface regression rate. The MSRS could also be adapted to perform similar measurements for a variety of other host materials when it is desired to monitor thicknesses and/or regression rate for purposes of safety, operational control, or research. For example, the sensor could be used to monitor the thicknesses of brake linings or racecar tires and indicate when they need to be replaced. At the time of this reporting, over 200 of these sensors have been installed into a variety of host materials. An MSRS can be made in either of two configurations, denoted ladder and continuous (see Figure 1). A ladder MSRS includes two highly electrically conductive legs, across which narrow strips of electrically resistive material are placed at small increments of length. These strips resemble the rungs of a ladder and are electrically equivalent to many tiny resistors connected in parallel. A substrate material provides structural support for the legs and rungs. The instantaneous sensor resistance is read by an external signal conditioner via wires attached to the conductive legs on the
Logistic models--an odd(s) kind of regression.
Jupiter, Daniel C
2013-01-01
The logistic regression model bears some similarity to the multivariable linear regression with which we are familiar. However, the differences are great enough to warrant a discussion of the need for and interpretation of logistic regression.
Parametric regression model for survival data: Weibull regression model as an example
2016-01-01
Weibull regression model is one of the most popular forms of parametric regression model that it provides estimate of baseline hazard function, as well as coefficients for covariates. Because of technical difficulties, Weibull regression model is seldom used in medical literature as compared to the semi-parametric proportional hazard model. To make clinical investigators familiar with Weibull regression model, this article introduces some basic knowledge on Weibull regression model and then illustrates how to fit the model with R software. The SurvRegCensCov package is useful in converting estimated coefficients to clinical relevant statistics such as hazard ratio (HR) and event time ratio (ETR). Model adequacy can be assessed by inspecting Kaplan-Meier curves stratified by categorical variable. The eha package provides an alternative method to model Weibull regression model. The check.dist() function helps to assess goodness-of-fit of the model. Variable selection is based on the importance of a covariate, which can be tested using anova() function. Alternatively, backward elimination starting from a full model is an efficient way for model development. Visualization of Weibull regression model after model development is interesting that it provides another way to report your findings. PMID:28149846
NASA Astrophysics Data System (ADS)
Polat, Esra; Gunay, Suleyman
2013-10-01
One of the problems encountered in Multiple Linear Regression (MLR) is multicollinearity, which causes the overestimation of the regression parameters and increase of the variance of these parameters. Hence, in case of multicollinearity presents, biased estimation procedures such as classical Principal Component Regression (CPCR) and Partial Least Squares Regression (PLSR) are then performed. SIMPLS algorithm is the leading PLSR algorithm because of its speed, efficiency and results are easier to interpret. However, both of the CPCR and SIMPLS yield very unreliable results when the data set contains outlying observations. Therefore, Hubert and Vanden Branden (2003) have been presented a robust PCR (RPCR) method and a robust PLSR (RPLSR) method called RSIMPLS. In RPCR, firstly, a robust Principal Component Analysis (PCA) method for high-dimensional data on the independent variables is applied, then, the dependent variables are regressed on the scores using a robust regression method. RSIMPLS has been constructed from a robust covariance matrix for high-dimensional data and robust linear regression. The purpose of this study is to show the usage of RPCR and RSIMPLS methods on an econometric data set, hence, making a comparison of two methods on an inflation model of Turkey. The considered methods have been compared in terms of predictive ability and goodness of fit by using a robust Root Mean Squared Error of Cross-validation (R-RMSECV), a robust R2 value and Robust Component Selection (RCS) statistic.
Use of Multiple Correlation Analysis and Multiple Regression Analysis.
ERIC Educational Resources Information Center
Huberty, Carl J.; Petoskey, Martha D.
1999-01-01
Distinguishes between multiple correlation and multiple regression analysis. Illustrates suggested information reporting methods and reviews the use of regression methods when dealing with problems of missing data. (SK)
Model selection for logistic regression models
NASA Astrophysics Data System (ADS)
Duller, Christine
2012-09-01
Model selection for logistic regression models decides which of some given potential regressors have an effect and hence should be included in the final model. The second interesting question is whether a certain factor is heterogeneous among some subsets, i.e. whether the model should include a random intercept or not. In this paper these questions will be answered with classical as well as with Bayesian methods. The application show some results of recent research projects in medicine and business administration.
Modeling confounding by half-sibling regression
Schölkopf, Bernhard; Hogg, David W.; Wang, Dun; Foreman-Mackey, Daniel; Janzing, Dominik; Simon-Gabriel, Carl-Johann; Peters, Jonas
2016-01-01
We describe a method for removing the effect of confounders to reconstruct a latent quantity of interest. The method, referred to as “half-sibling regression,” is inspired by recent work in causal inference using additive noise models. We provide a theoretical justification, discussing both independent and identically distributed as well as time series data, respectively, and illustrate the potential of the method in a challenging astronomy application. PMID:27382154
Modeling confounding by half-sibling regression.
Schölkopf, Bernhard; Hogg, David W; Wang, Dun; Foreman-Mackey, Daniel; Janzing, Dominik; Simon-Gabriel, Carl-Johann; Peters, Jonas
2016-07-05
We describe a method for removing the effect of confounders to reconstruct a latent quantity of interest. The method, referred to as "half-sibling regression," is inspired by recent work in causal inference using additive noise models. We provide a theoretical justification, discussing both independent and identically distributed as well as time series data, respectively, and illustrate the potential of the method in a challenging astronomy application.
Satellite rainfall retrieval by logistic regression
NASA Technical Reports Server (NTRS)
Chiu, Long S.
1986-01-01
The potential use of logistic regression in rainfall estimation from satellite measurements is investigated. Satellite measurements provide covariate information in terms of radiances from different remote sensors.The logistic regression technique can effectively accommodate many covariates and test their significance in the estimation. The outcome from the logistical model is the probability that the rainrate of a satellite pixel is above a certain threshold. By varying the thresholds, a rainrate histogram can be obtained, from which the mean and the variant can be estimated. A logistical model is developed and applied to rainfall data collected during GATE, using as covariates the fractional rain area and a radiance measurement which is deduced from a microwave temperature-rainrate relation. It is demonstrated that the fractional rain area is an important covariate in the model, consistent with the use of the so-called Area Time Integral in estimating total rain volume in other studies. To calibrate the logistical model, simulated rain fields generated by rainfield models with prescribed parameters are needed. A stringent test of the logistical model is its ability to recover the prescribed parameters of simulated rain fields. A rain field simulation model which preserves the fractional rain area and lognormality of rainrates as found in GATE is developed. A stochastic regression model of branching and immigration whose solutions are lognormally distributed in some asymptotic limits has also been developed.
Transfer Learning Based on Logistic Regression
NASA Astrophysics Data System (ADS)
Paul, A.; Rottensteiner, F.; Heipke, C.
2015-08-01
In this paper we address the problem of classification of remote sensing images in the framework of transfer learning with a focus on domain adaptation. The main novel contribution is a method for transductive transfer learning in remote sensing on the basis of logistic regression. Logistic regression is a discriminative probabilistic classifier of low computational complexity, which can deal with multiclass problems. This research area deals with methods that solve problems in which labelled training data sets are assumed to be available only for a source domain, while classification is needed in the target domain with different, yet related characteristics. Classification takes place with a model of weight coefficients for hyperplanes which separate features in the transformed feature space. In term of logistic regression, our domain adaptation method adjusts the model parameters by iterative labelling of the target test data set. These labelled data features are iteratively added to the current training set which, at the beginning, only contains source features and, simultaneously, a number of source features are deleted from the current training set. Experimental results based on a test series with synthetic and real data constitutes a first proof-of-concept of the proposed method.
Variable Selection in Semiparametric Regression Modeling.
Li, Runze; Liang, Hua
2008-01-01
In this paper, we are concerned with how to select significant variables in semiparametric modeling. Variable selection for semiparametric regression models consists of two components: model selection for nonparametric components and select significant variables for parametric portion. Thus, it is much more challenging than that for parametric models such as linear models and generalized linear models because traditional variable selection procedures including stepwise regression and the best subset selection require model selection to nonparametric components for each submodel. This leads to very heavy computational burden. In this paper, we propose a class of variable selection procedures for semiparametric regression models using nonconcave penalized likelihood. The newly proposed procedures are distinguished from the traditional ones in that they delete insignificant variables and estimate the coefficients of significant variables simultaneously. This allows us to establish the sampling properties of the resulting estimate. We first establish the rate of convergence of the resulting estimate. With proper choices of penalty functions and regularization parameters, we then establish the asymptotic normality of the resulting estimate, and further demonstrate that the proposed procedures perform as well as an oracle procedure. Semiparametric generalized likelihood ratio test is proposed to select significant variables in the nonparametric component. We investigate the asymptotic behavior of the proposed test and demonstrate its limiting null distribution follows a chi-squared distribution, which is independent of the nuisance parameters. Extensive Monte Carlo simulation studies are conducted to examine the finite sample performance of the proposed variable selection procedures.
Quantile regression modeling for Malaysian automobile insurance premium data
NASA Astrophysics Data System (ADS)
Fuzi, Mohd Fadzli Mohd; Ismail, Noriszura; Jemain, Abd Aziz
2015-09-01
Quantile regression is a robust regression to outliers compared to mean regression models. Traditional mean regression models like Generalized Linear Model (GLM) are not able to capture the entire distribution of premium data. In this paper we demonstrate how a quantile regression approach can be used to model net premium data to study the effects of change in the estimates of regression parameters (rating classes) on the magnitude of response variable (pure premium). We then compare the results of quantile regression model with Gamma regression model. The results from quantile regression show that some rating classes increase as quantile increases and some decrease with decreasing quantile. Further, we found that the confidence interval of median regression (τ = O.5) is always smaller than Gamma regression in all risk factors.
Mission assurance increased with regression testing
NASA Astrophysics Data System (ADS)
Lang, R.; Spezio, M.
Knowing what to test is an important attribute in any testing campaign, especially when it has to be right or the mission could be in jeopardy. The New Horizons mission, developed and operated by the John Hopkins University Applied Physics Laboratory, received a planned major upgrade to their Mission Operations and Control (MOC) ground system architecture. Early in the mission planning it was recognized that the ground system platform would require an upgrade to assure continued support of technology used for spacecraft operations. With the planned update to the six year operational ground architecture from Solaris 8 to Solaris 10, it was critical that the new architecture maintain critical operations and control functions. The New Horizons spacecraft is heading to its historic rendezvous with Pluto in July 2015 and then proceeding into the Kuiper Belt. This paper discusses the Independent Software Acceptance Testing (ISAT) Regression test campaign that played a critical role to assure the continued success of the New Horizons mission. The New Horizons ISAT process was designed to assure all the requirements were being met for the ground software functions developed to support the mission objectives. The ISAT team developed a test plan with a series of test case designs. The test objectives were to verify that the software developed from the requirements functioned as expected in the operational environment. As the test cases were developed and executed, a regression test suite was identified at the functional level. This regression test suite would serve as a crucial resource in assuring the operational system continued to function as required with such a large scale change being introduced. Some of the New Horizons ground software changes required modifications to the most critical functions of the operational software. Of particular concern was the new MOC architecture (Solaris 10) is Intel based and little endian, and the legacy architecture (Solaris 8) was SPA
Mapping geogenic radon potential by regression kriging.
Pásztor, László; Szabó, Katalin Zsuzsanna; Szatmári, Gábor; Laborczi, Annamária; Horváth, Ákos
2016-02-15
Radon ((222)Rn) gas is produced in the radioactive decay chain of uranium ((238)U) which is an element that is naturally present in soils. Radon is transported mainly by diffusion and convection mechanisms through the soil depending mainly on the physical and meteorological parameters of the soil and can enter and accumulate in buildings. Health risks originating from indoor radon concentration can be attributed to natural factors and is characterized by geogenic radon potential (GRP). Identification of areas with high health risks require spatial modeling, that is, mapping of radon risk. In addition to geology and meteorology, physical soil properties play a significant role in the determination of GRP. In order to compile a reliable GRP map for a model area in Central-Hungary, spatial auxiliary information representing GRP forming environmental factors were taken into account to support the spatial inference of the locally measured GRP values. Since the number of measured sites was limited, efficient spatial prediction methodologies were searched for to construct a reliable map for a larger area. Regression kriging (RK) was applied for the interpolation using spatially exhaustive auxiliary data on soil, geology, topography, land use and climate. RK divides the spatial inference into two parts. Firstly, the deterministic component of the target variable is determined by a regression model. The residuals of the multiple linear regression analysis represent the spatially varying but dependent stochastic component, which are interpolated by kriging. The final map is the sum of the two component predictions. Overall accuracy of the map was tested by Leave-One-Out Cross-Validation. Furthermore the spatial reliability of the resultant map is also estimated by the calculation of the 90% prediction interval of the local prediction values. The applicability of the applied method as well as that of the map is discussed briefly.
Monthly streamflow forecasting using Gaussian Process Regression
NASA Astrophysics Data System (ADS)
Sun, Alexander Y.; Wang, Dingbao; Xu, Xianli
2014-04-01
Streamflow forecasting plays a critical role in nearly all aspects of water resources planning and management. In this work, Gaussian Process Regression (GPR), an effective kernel-based machine learning algorithm, is applied to probabilistic streamflow forecasting. GPR is built on Gaussian process, which is a stochastic process that generalizes multivariate Gaussian distribution to infinite-dimensional space such that distributions over function values can be defined. The GPR algorithm provides a tractable and flexible hierarchical Bayesian framework for inferring the posterior distribution of streamflows. The prediction skill of the algorithm is tested for one-month-ahead prediction using the MOPEX database, which includes long-term hydrometeorological time series collected from 438 basins across the U.S. from 1948 to 2003. Comparisons with linear regression and artificial neural network models indicate that GPR outperforms both regression methods in most cases. The GPR prediction of MOPEX basins is further examined using the Budyko framework, which helps to reveal the close relationships among water-energy partitions, hydrologic similarity, and predictability. Flow regime modification and the resulting loss of predictability have been a major concern in recent years because of climate change and anthropogenic activities. The persistence of streamflow predictability is thus examined by extending the original MOPEX data records to 2012. Results indicate relatively strong persistence of streamflow predictability in the extended period, although the low-predictability basins tend to show more variations. Because many low-predictability basins are located in regions experiencing fast growth of human activities, the significance of sustainable development and water resources management can be even greater for those regions.
Multiple linear regression for isotopic measurements
NASA Astrophysics Data System (ADS)
Garcia Alonso, J. I.
2012-04-01
There are two typical applications of isotopic measurements: the detection of natural variations in isotopic systems and the detection man-made variations using enriched isotopes as indicators. For both type of measurements accurate and precise isotope ratio measurements are required. For the so-called non-traditional stable isotopes, multicollector ICP-MS instruments are usually applied. In many cases, chemical separation procedures are required before accurate isotope measurements can be performed. The off-line separation of Rb and Sr or Nd and Sm is the classical procedure employed to eliminate isobaric interferences before multicollector ICP-MS measurement of Sr and Nd isotope ratios. Also, this procedure allows matrix separation for precise and accurate Sr and Nd isotope ratios to be obtained. In our laboratory we have evaluated the separation of Rb-Sr and Nd-Sm isobars by liquid chromatography and on-line multicollector ICP-MS detection. The combination of this chromatographic procedure with multiple linear regression of the raw chromatographic data resulted in Sr and Nd isotope ratios with precisions and accuracies typical of off-line sample preparation procedures. On the other hand, methods for the labelling of individual organisms (such as a given plant, fish or animal) are required for population studies. We have developed a dual isotope labelling procedure which can be unique for a given individual, can be inherited in living organisms and it is stable. The detection of the isotopic signature is based also on multiple linear regression. The labelling of fish and its detection in otoliths by Laser Ablation ICP-MS will be discussed using trout and salmon as examples. As a conclusion, isotope measurement procedures based on multiple linear regression can be a viable alternative in multicollector ICP-MS measurements.
Min-Max Bias Robust Regression.
1987-08-01
2 UL uIImImmIIIEllmlllllllll llEllllhllllEI El 1 .1 25 11111 -.4 ___ . .. . . N ~ . MIN- MAX BIAS ROBUST REGRESSION by R. D. Martin V. J. Yohai R. H...shown than an S-estimate based on a jump-function type p solves the n- max bias problem for the class of NI-estimates with very general scale. This...5, (X() -- .5 and the rin- max estimator approaches the least median of squared residuals estimator introduced by Rousseeuw [J. Am. Statist. Assoc
A method for nonlinear exponential regression analysis
NASA Technical Reports Server (NTRS)
Junkin, B. G.
1971-01-01
A computer-oriented technique is presented for performing a nonlinear exponential regression analysis on decay-type experimental data. The technique involves the least squares procedure wherein the nonlinear problem is linearized by expansion in a Taylor series. A linear curve fitting procedure for determining the initial nominal estimates for the unknown exponential model parameters is included as an integral part of the technique. A correction matrix was derived and then applied to the nominal estimate to produce an improved set of model parameters. The solution cycle is repeated until some predetermined criterion is satisfied.
Semiparametric regression in capture-recapture modeling.
Gimenez, O; Crainiceanu, C; Barbraud, C; Jenouvrier, S; Morgan, B J T
2006-09-01
Capture-recapture models were developed to estimate survival using data arising from marking and monitoring wild animals over time. Variation in survival may be explained by incorporating relevant covariates. We propose nonparametric and semiparametric regression methods for estimating survival in capture-recapture models. A fully Bayesian approach using Markov chain Monte Carlo simulations was employed to estimate the model parameters. The work is illustrated by a study of Snow petrels, in which survival probabilities are expressed as nonlinear functions of a climate covariate, using data from a 40-year study on marked individuals, nesting at Petrels Island, Terre Adélie.
Learning regulatory programs by threshold SVD regression.
Ma, Xin; Xiao, Luo; Wong, Wing Hung
2014-11-04
We formulate a statistical model for the regulation of global gene expression by multiple regulatory programs and propose a thresholding singular value decomposition (T-SVD) regression method for learning such a model from data. Extensive simulations demonstrate that this method offers improved computational speed and higher sensitivity and specificity over competing approaches. The method is used to analyze microRNA (miRNA) and long noncoding RNA (lncRNA) data from The Cancer Genome Atlas (TCGA) consortium. The analysis yields previously unidentified insights into the combinatorial regulation of gene expression by noncoding RNAs, as well as findings that are supported by evidence from the literature.
Postpartum Regression of a Presumed Cavernous Meningioma
Phang, See Yung; Whitfield, Peter
2016-01-01
Meningiomas are known to be more common in females than males. They are also known in rare cases to grow in size during pregnancy, which can complicate its management. We describe a 31-year-old Caucasian woman who presented with blurring of her vision and diplopia during the third trimester of her pregnancy. Magnetic resonance imaging (MRI) showed a small left cavernous sinus meningioma. The patient was treated conservatively until her uncomplicated delivery. A postpartum MRI scan showed complete regression of the suspected meningioma. Currently the patient is contemplating a further pregnancy. PMID:27066285
An operational GLS model for hydrologic regression
Tasker, Gary D.; Stedinger, J.R.
1989-01-01
Recent Monte Carlo studies have documented the value of generalized least squares (GLS) procedures to estimate empirical relationships between streamflow statistics and physiographic basin characteristics. This paper presents a number of extensions of the GLS method that deal with realities and complexities of regional hydrologic data sets that were not addressed in the simulation studies. These extensions include: (1) a more realistic model of the underlying model errors; (2) smoothed estimates of cross correlation of flows; (3) procedures for including historical flow data; (4) diagnostic statistics describing leverage and influence for GLS regression; and (5) the formulation of a mathematical program for evaluating future gaging activities. ?? 1989.
Inferring gene regression networks with model trees
2010-01-01
Background Novel strategies are required in order to handle the huge amount of data produced by microarray technologies. To infer gene regulatory networks, the first step is to find direct regulatory relationships between genes building the so-called gene co-expression networks. They are typically generated using correlation statistics as pairwise similarity measures. Correlation-based methods are very useful in order to determine whether two genes have a strong global similarity but do not detect local similarities. Results We propose model trees as a method to identify gene interaction networks. While correlation-based methods analyze each pair of genes, in our approach we generate a single regression tree for each gene from the remaining genes. Finally, a graph from all the relationships among output and input genes is built taking into account whether the pair of genes is statistically significant. For this reason we apply a statistical procedure to control the false discovery rate. The performance of our approach, named REGNET, is experimentally tested on two well-known data sets: Saccharomyces Cerevisiae and E.coli data set. First, the biological coherence of the results are tested. Second the E.coli transcriptional network (in the Regulon database) is used as control to compare the results to that of a correlation-based method. This experiment shows that REGNET performs more accurately at detecting true gene associations than the Pearson and Spearman zeroth and first-order correlation-based methods. Conclusions REGNET generates gene association networks from gene expression data, and differs from correlation-based methods in that the relationship between one gene and others is calculated simultaneously. Model trees are very useful techniques to estimate the numerical values for the target genes by linear regression functions. They are very often more precise than linear regression models because they can add just different linear regressions to separate
Introduction to the use of regression models in epidemiology.
Bender, Ralf
2009-01-01
Regression modeling is one of the most important statistical techniques used in analytical epidemiology. By means of regression models the effect of one or several explanatory variables (e.g., exposures, subject characteristics, risk factors) on a response variable such as mortality or cancer can be investigated. From multiple regression models, adjusted effect estimates can be obtained that take the effect of potential confounders into account. Regression methods can be applied in all epidemiologic study designs so that they represent a universal tool for data analysis in epidemiology. Different kinds of regression models have been developed in dependence on the measurement scale of the response variable and the study design. The most important methods are linear regression for continuous outcomes, logistic regression for binary outcomes, Cox regression for time-to-event data, and Poisson regression for frequencies and rates. This chapter provides a nontechnical introduction to these regression models with illustrating examples from cancer research.
ERIC Educational Resources Information Center
Giannotti, Flavia; Cortesi, Flavia; Cerquiglini, Antonella; Miraglia, Daniela; Vagnoni, Cristina; Sebastiani, Teresa; Bernabei, Paola
2008-01-01
This study investigated sleep of children with autism and developmental regression and the possible relationship with epilepsy and epileptiform abnormalities. Participants were 104 children with autism (70 non-regressed, 34 regressed) and 162 typically developing children (TD). Results suggested that the regressed group had higher incidence of…
Regression Models For Saffron Yields in Iran
NASA Astrophysics Data System (ADS)
S. H, Sanaeinejad; S. N, Hosseini
Saffron is an important crop in social and economical aspects in Khorassan Province (Northeast of Iran). In this research wetried to evaluate trends of saffron yield in recent years and to study the relationship between saffron yield and the climate change. A regression analysis was used to predict saffron yield based on 20 years of yield data in Birjand, Ghaen and Ferdows cities.Climatologically data for the same periods was provided by database of Khorassan Climatology Center. Climatologically data includedtemperature, rainfall, relative humidity and sunshine hours for ModelI, and temperature and rainfall for Model II. The results showed the coefficients of determination for Birjand, Ferdows and Ghaen for Model I were 0.69, 0.50 and 0.81 respectively. Also coefficients of determination for the same cities for model II were 0.53, 0.50 and 0.72 respectively. Multiple regression analysisindicated that among weather variables, temperature was the key parameter for variation ofsaffron yield. It was concluded that increasing temperature at spring was the main cause of declined saffron yield during recent years across the province. Finally, yield trend was predicted for the last 5 years using time series analysis.
Supporting Regularized Logistic Regression Privately and Efficiently.
Li, Wenfa; Liu, Hongzhe; Yang, Peng; Xie, Wei
2016-01-01
As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects that are contingent upon strict privacy regulations. Concerns over data privacy make it increasingly difficult to coordinate and conduct large-scale collaborative studies, which typically rely on cross-institution data sharing and joint analysis. Our work here focuses on safeguarding regularized logistic regression, a widely-used statistical model while at the same time has not been investigated from a data security and privacy perspective. We consider a common use scenario of multi-institution collaborative studies, such as in the form of research consortia or networks as widely seen in genetics, epidemiology, social sciences, etc. To make our privacy-enhancing solution practical, we demonstrate a non-conventional and computationally efficient method leveraging distributing computing and strong cryptography to provide comprehensive protection over individual-level and summary data. Extensive empirical evaluations on several studies validate the privacy guarantee, efficiency and scalability of our proposal. We also discuss the practical implications of our solution for large-scale studies and applications from various disciplines, including genetic and biomedical studies, smart grid, network analysis, etc.
Quantile Regression Models for Current Status Data.
Ou, Fang-Shu; Zeng, Donglin; Cai, Jianwen
2016-11-01
Current status data arise frequently in demography, epidemiology, and econometrics where the exact failure time cannot be determined but is only known to have occurred before or after a known observation time. We propose a quantile regression model to analyze current status data, because it does not require distributional assumptions and the coefficients can be interpreted as direct regression effects on the distribution of failure time in the original time scale. Our model assumes that the conditional quantile of failure time is a linear function of covariates. We assume conditional independence between the failure time and observation time. An M-estimator is developed for parameter estimation which is computed using the concave-convex procedure and its confidence intervals are constructed using a subsampling method. Asymptotic properties for the estimator are derived and proven using modern empirical process theory. The small sample performance of the proposed method is demonstrated via simulation studies. Finally, we apply the proposed method to analyze data from the Mayo Clinic Study of Aging.
Double linear regression classification for face recognition
NASA Astrophysics Data System (ADS)
Feng, Qingxiang; Zhu, Qi; Tang, Lin-Lin; Pan, Jeng-Shyang
2015-02-01
A new classifier designed based on linear regression classification (LRC) classifier and simple-fast representation-based classifier (SFR), named double linear regression classification (DLRC) classifier, is proposed for image recognition in this paper. As we all know, the traditional LRC classifier only uses the distance between test image vectors and predicted image vectors of the class subspace for classification. And the SFR classifier uses the test image vectors and the nearest image vectors of the class subspace to classify the test sample. However, the DLRC classifier computes out the predicted image vectors of each class subspace and uses all the predicted vectors to construct a novel robust global space. Then, the DLRC utilizes the novel global space to get the novel predicted vectors of each class for classification. A mass number of experiments on AR face database, JAFFE face database, Yale face database, Extended YaleB face database, and PIE face database are used to evaluate the performance of the proposed classifier. The experimental results show that the proposed classifier achieves better recognition rate than the LRC classifier, SFR classifier, and several other classifiers.
A Gibbs sampler for multivariate linear regression
NASA Astrophysics Data System (ADS)
Mantz, Adam B.
2016-04-01
Kelly described an efficient algorithm, using Gibbs sampling, for performing linear regression in the fairly general case where non-zero measurement errors exist for both the covariates and response variables, where these measurements may be correlated (for the same data point), where the response variable is affected by intrinsic scatter in addition to measurement error, and where the prior distribution of covariates is modelled by a flexible mixture of Gaussians rather than assumed to be uniform. Here, I extend the Kelly algorithm in two ways. First, the procedure is generalized to the case of multiple response variables. Secondly, I describe how to model the prior distribution of covariates using a Dirichlet process, which can be thought of as a Gaussian mixture where the number of mixture components is learned from the data. I present an example of multivariate regression using the extended algorithm, namely fitting scaling relations of the gas mass, temperature, and luminosity of dynamically relaxed galaxy clusters as a function of their mass and redshift. An implementation of the Gibbs sampler in the R language, called LRGS, is provided.
Scientific Progress or Regress in Sports Physiology?
Böning, Dieter
2016-11-01
In modern societies there is strong belief in scientific progress, but, unfortunately, a parallel partial regress occurs because of often avoidable mistakes. Mistakes are mainly forgetting, erroneous theories, errors in experiments and manuscripts, prejudice, selected publication of "positive" results, and fraud. An example of forgetting is that methods introduced decades ago are used without knowing the underlying theories: Basic articles are no longer read or cited. This omission may cause incorrect interpretation of results. For instance, false use of actual base excess instead of standard base excess for calculation of the number of hydrogen ions leaving the muscles raised the idea that an unknown fixed acid is produced in addition to lactic acid during exercise. An erroneous theory led to the conclusion that lactate is not the anion of a strong acid but a buffer. Mistakes occur after incorrect application of a method, after exclusion of unwelcome values, during evaluation of measurements by false calculations, or during preparation of manuscripts. Co-authors, as well as reviewers, do not always carefully read papers before publication. Peer reviewers might be biased against a hypothesis or an author. A general problem is selected publication of positive results. An example of fraud in sports medicine is the presence of doped subjects in groups of investigated athletes. To reduce regress, it is important that investigators search both original and recent articles on a topic and conscientiously examine the data. All co-authors and reviewers should read the text thoroughly and inspect all tables and figures in a manuscript.
Supporting Regularized Logistic Regression Privately and Efficiently
Li, Wenfa; Liu, Hongzhe; Yang, Peng; Xie, Wei
2016-01-01
As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects that are contingent upon strict privacy regulations. Concerns over data privacy make it increasingly difficult to coordinate and conduct large-scale collaborative studies, which typically rely on cross-institution data sharing and joint analysis. Our work here focuses on safeguarding regularized logistic regression, a widely-used statistical model while at the same time has not been investigated from a data security and privacy perspective. We consider a common use scenario of multi-institution collaborative studies, such as in the form of research consortia or networks as widely seen in genetics, epidemiology, social sciences, etc. To make our privacy-enhancing solution practical, we demonstrate a non-conventional and computationally efficient method leveraging distributing computing and strong cryptography to provide comprehensive protection over individual-level and summary data. Extensive empirical evaluations on several studies validate the privacy guarantee, efficiency and scalability of our proposal. We also discuss the practical implications of our solution for large-scale studies and applications from various disciplines, including genetic and biomedical studies, smart grid, network analysis, etc. PMID:27271738
A reconsideration of the concept of regression.
Dowling, A Scott
2004-01-01
Regression has been a useful psychoanalytic concept, linking present mental functioning with past experiences and levels of functioning. The concept originated as an extension of the evolutionary zeitgeist of the day as enunciated by H. Spencer and H. Jackson and applied by Freud to psychological phenomena. The value system implicit in the contrast of evolution/progression vs dissolution/regression has given rise to unfortunate and powerful assumptions of social, cultural, developmental and individual value as embodied in notions of "higher," "lower;" "primitive," "mature," "archaic," and "advanced." The unhelpful results of these assumptions are evident, for example, in attitudes concerning cultural, sexual, and social "correctness, " same-sex object choice, and goals of treatment. An alternative, a continuously constructed, continuously emerging mental life, in analogy to the ever changing, continuous physical body, is suggested. This view retains the fundamentals of psychoanalysis, for example, unconscious mental life, drive, defense, and psychic structure, but stresses a functional, ever changing, present oriented understanding of mental life as contrasted with a static, onion-layered view.
Shape regression for vertebra fracture quantification
NASA Astrophysics Data System (ADS)
Lund, Michael Tillge; de Bruijne, Marleen; Tanko, Laszlo B.; Nielsen, Mads
2005-04-01
Accurate and reliable identification and quantification of vertebral fractures constitute a challenge both in clinical trials and in diagnosis of osteoporosis. Various efforts have been made to develop reliable, objective, and reproducible methods for assessing vertebral fractures, but at present there is no consensus concerning a universally accepted diagnostic definition of vertebral fractures. In this project we want to investigate whether or not it is possible to accurately reconstruct the shape of a normal vertebra, using a neighbouring vertebra as prior information. The reconstructed shape can then be used to develop a novel vertebra fracture measure, by comparing the segmented vertebra shape with its reconstructed normal shape. The vertebrae in lateral x-rays of the lumbar spine were manually annotated by a medical expert. With this dataset we built a shape model, with equidistant point distribution between the four corner points. Based on the shape model, a multiple linear regression model of a normal vertebra shape was developed for each dataset using leave-one-out cross-validation. The reconstructed shape was calculated for each dataset using these regression models. The average prediction error for the annotated shape was on average 3%.
Montgomery, Katherine L; Vaughn, Michael G; Thompson, Sanna J; Howard, Matthew O
2013-11-01
Research on juvenile offenders has largely treated this population as a homogeneous group. However, recent findings suggest that this at-risk population may be considerably more heterogeneous than previously believed. This study compared mixture regression analyses with standard regression techniques in an effort to explain how known factors such as distress, trauma, and personality are associated with drug abuse among juvenile offenders. Researchers recruited 728 juvenile offenders from Missouri juvenile correctional facilities for participation in this study. Researchers investigated past-year substance use in relation to the following variables: demographic characteristics (gender, ethnicity, age, familial use of public assistance), antisocial behavior, and mental illness symptoms (psychopathic traits, psychiatric distress, and prior trauma). Results indicated that standard and mixed regression approaches identified significant variables related to past-year substance use among this population; however, the mixture regression methods provided greater specificity in results. Mixture regression analytic methods may help policy makers and practitioners better understand and intervene with the substance-related subgroups of juvenile offenders.
Haydardedeoğlu, Bülent; Kılıçdağ, Esra Bulgan
2016-01-01
Objective Corifollitropin alfa is a good choice for assisted reproductive technology (ART) cycles because fewer injections are needed than with other agents. In this retrospective cohort, we analyzed luteal injected half-dose depot gonadotropin hormone-releasing hormone (GnRH) agonist cycles in women who received corifollitropin alfa and those who underwent a conventional corifollitropin alfa cycle with a GnRH antagonist. Material and Methods In this retrospective cohort, we analyzed luteal injected half-dose depot GnRH agonist cycles in women who received corifollitropin alfa and those who underwent a conventional corifollitropin alfa cycle with a GnRH antagonist at the Division of Reproductive Endocrinology and IVF Unit, Obstetrics and Gynecology Department, Başkent University School of Medicine, Adana, Turkey, from March 2014 to August 2015. The patient’s baseline characteristics were similar between the two groups. Forty-five patients underwent the long protocol, in which a half-dose of depot GnRH agonist was administered on day 21 of the preceding cycle. Forty-nine patients underwent the GnRH-antagonist protocol. Corifollitropin alfa was administered on the menstrual cycle day 3. Results The mean ages of the two groups were similar (32.77±5.55 vs. 34.2±4.51 years [“for the long- and antagonist-protocol groups, respectively”]). The total number of retrieved oocytes, the fertilization rate, and the number of transferred embryos were similar between the two groups. The only significant difference between the two protocols was the number of injections during the controlled ovarian stimulation (COH) cycle, which included the depot-agonist injection in the long-protocol group (4.46±1.64 vs. 5.71±2.51, p=0.006). The clinical pregnancy and implantation rates were similar in the two protocols (16/45 [35.6%] vs. 16/49 [32.7%] for the intention to treat and 32.5±6.82% vs. 36.25±8.58%, respectively). Conclusion Our results show that ART cycles could be
Estimates on compressed neural networks regression.
Zhang, Yongquan; Li, Youmei; Sun, Jianyong; Ji, Jiabing
2015-03-01
When the neural element number n of neural networks is larger than the sample size m, the overfitting problem arises since there are more parameters than actual data (more variable than constraints). In order to overcome the overfitting problem, we propose to reduce the number of neural elements by using compressed projection A which does not need to satisfy the condition of Restricted Isometric Property (RIP). By applying probability inequalities and approximation properties of the feedforward neural networks (FNNs), we prove that solving the FNNs regression learning algorithm in the compressed domain instead of the original domain reduces the sample error at the price of an increased (but controlled) approximation error, where the covering number theory is used to estimate the excess error, and an upper bound of the excess error is given.
[Logistic regression against a divergent Bayesian network].
Sánchez Trujillo, Noel Antonio
2015-02-03
This article is a discussion about two statistical tools used for prediction and causality assessment: logistic regression and Bayesian networks. Using data of a simulated example from a study assessing factors that might predict pulmonary emphysema (where fingertip pigmentation and smoking are considered); we posed the following questions. Is pigmentation a confounding, causal or predictive factor? Is there perhaps another factor, like smoking, that confounds? Is there a synergy between pigmentation and smoking? The results, in terms of prediction, are similar with the two techniques; regarding causation, differences arise. We conclude that, in decision-making, the sum of both: a statistical tool, used with common sense, and previous evidence, taking years or even centuries to develop; is better than the automatic and exclusive use of statistical resources.
Conjoined legs: Sirenomelia or caudal regression syndrome?
Das, Sakti Prasad; Ojha, Niranjan; Ganesh, G Shankar; Mohanty, Ram Narayan
2013-01-01
Presence of single umbilical persistent vitelline artery distinguishes sirenomelia from caudal regression syndrome. We report a case of a12-year-old boy who had bilateral umbilical arteries presented with fusion of both legs in the lower one third of leg. Both feet were rudimentary. The right foot had a valgus rocker-bottom deformity. All toes were present but rudimentary. The left foot showed absence of all toes. Physical examination showed left tibia vara. The chest evaluation in sitting revealed pigeon chest and elevated right shoulder. Posterior examination of the trunk showed thoracic scoliosis with convexity to right. The patient was operated and at 1 year followup the boy had two separate legs with a good aesthetic and functional results. PMID:23960288
Macrophages, dendritic cells, and regression of atherosclerosis
Feig, Jonathan E.; Feig, Jessica L.
2012-01-01
Atherosclerosis is the number one cause of death in the Western world. It results from the interaction between modified lipoproteins and cells such as macrophages, dendritic cells (DCs), T cells, and other cellular elements present in the arterial wall. This inflammatory process can ultimately lead to the development of complex lesions, or plaques, that protrude into the arterial lumen. Ultimately, plaque rupture and thrombosis can occur leading to the clinical complications of myocardial infarction or stroke. Although each of the cell types plays roles in the pathogenesis of atherosclerosis, the focus of this review will be primarily on the macrophages and DCs. The role of these two cell types in atherosclerosis is discussed, with a particular emphasis on their involvement in atherosclerosis regression. PMID:22934038
Reliable prediction intervals with regression neural networks.
Papadopoulos, Harris; Haralambous, Haris
2011-10-01
This paper proposes an extension to conventional regression neural networks (NNs) for replacing the point predictions they produce with prediction intervals that satisfy a required level of confidence. Our approach follows a novel machine learning framework, called Conformal Prediction (CP), for assigning reliable confidence measures to predictions without assuming anything more than that the data are independent and identically distributed (i.i.d.). We evaluate the proposed method on four benchmark datasets and on the problem of predicting Total Electron Content (TEC), which is an important parameter in trans-ionospheric links; for the latter we use a dataset of more than 60000 TEC measurements collected over a period of 11 years. Our experimental results show that the prediction intervals produced by our method are both well calibrated and tight enough to be useful in practice.
Subgroup finding via Bayesian additive regression trees.
Sivaganesan, Siva; Müller, Peter; Huang, Bin
2017-03-09
We provide a Bayesian decision theoretic approach to finding subgroups that have elevated treatment effects. Our approach separates the modeling of the response variable from the task of subgroup finding and allows a flexible modeling of the response variable irrespective of potential subgroups of interest. We use Bayesian additive regression trees to model the response variable and use a utility function defined in terms of a candidate subgroup and the predicted response for that subgroup. Subgroups are identified by maximizing the expected utility where the expectation is taken with respect to the posterior predictive distribution of the response, and the maximization is carried out over an a priori specified set of candidate subgroups. Our approach allows subgroups based on both quantitative and categorical covariates. We illustrate the approach using simulated data set study and a real data set. Copyright © 2017 John Wiley & Sons, Ltd.
Sparse brain network using penalized linear regression
NASA Astrophysics Data System (ADS)
Lee, Hyekyoung; Lee, Dong Soo; Kang, Hyejin; Kim, Boong-Nyun; Chung, Moo K.
2011-03-01
Sparse partial correlation is a useful connectivity measure for brain networks when it is difficult to compute the exact partial correlation in the small-n large-p setting. In this paper, we formulate the problem of estimating partial correlation as a sparse linear regression with a l1-norm penalty. The method is applied to brain network consisting of parcellated regions of interest (ROIs), which are obtained from FDG-PET images of the autism spectrum disorder (ASD) children and the pediatric control (PedCon) subjects. To validate the results, we check their reproducibilities of the obtained brain networks by the leave-one-out cross validation and compare the clustered structures derived from the brain networks of ASD and PedCon.
Censored Median Regression and Profile Empirical Likelihood
Subramanian, Sundarraman
2007-01-01
We implement profile empirical likelihood based inference for censored median regression models. Inference for any specified sub-vector is carried out by profiling out the nuisance parameters from the “plug-in” empirical likelihood ratio function proposed by Qin and Tsao. To obtain the critical value of the profile empirical likelihood ratio statistic, we first investigate its asymptotic distribution. The limiting distribution is a sum of weighted chi square distributions. Unlike for the full empirical likelihood, however, the derived asymptotic distribution has intractable covariance structure. Therefore, we employ the bootstrap to obtain the critical value, and compare the resulting confidence intervals with the ones obtained through Basawa and Koul’s minimum dispersion statistic. Furthermore, we obtain confidence intervals for the age and treatment effects in a lung cancer data set. PMID:19112527
Early development and regression in Rett syndrome.
Lee, J Y L; Leonard, H; Piek, J P; Downs, J
2013-12-01
This study utilized developmental profiling to examine symptoms in 14 girls with genetically confirmed Rett syndrome and whose families were participating in the Australian Rett syndrome or InterRett database. Regression was mostly characterized by loss of hand and/or communication skills (13/14) except one girl demonstrated slowing of skill development. Social withdrawal and inconsolable crying often developed simultaneously (9/14), with social withdrawal for shorter duration than inconsolable crying. Previously acquired gross motor skills declined in just over half of the sample (8/14), mostly observed as a loss of balance. Early abnormalities such as vomiting and strabismus were also seen. Our findings provide additional insight into the early clinical profile of Rett syndrome.
Tolerance bounds for log gamma regression models
NASA Technical Reports Server (NTRS)
Jones, R. A.; Scholz, F. W.; Ossiander, M.; Shorack, G. R.
1985-01-01
The present procedure for finding lower confidence bounds for the quantiles of Weibull populations, on the basis of the solution of a quadratic equation, is more accurate than current Monte Carlo tables and extends to any location-scale family. It is shown that this method is accurate for all members of the log gamma(K) family, where K = 1/2 to infinity, and works well for censored data, while also extending to regression data. An even more accurate procedure involving an approximation to the Lawless (1982) conditional procedure, with numerical integrations whose tables are independent of the data, is also presented. These methods are applied to the case of failure strengths of ceramic specimens from each of three billets of Si3N4, which have undergone flexural strength testing.
Magnetotelluric Data, Stable Distributions and Stable Regression
NASA Astrophysics Data System (ADS)
Chave, A. D.
2013-12-01
The author has noted for many years that the residuals from robust or bounded influence estimates of the magnetotelluric response function are systematically long tailed compared to a Gaussian or Rayleigh distribution. Consequently, the standard statistical model of a Gaussian core contaminated by a fraction of outlying data is not really valid. However, the typical result is an improvement on ordinary least squares, and has become standard in the electromagnetic induction community. A recent re-evaluation of the statistics of magnetotelluric response function estimation has shown that, in almost all cases, the residuals are alpha stable rather than Gaussian. Alpha stable distributions are characterized by four parameters: a shape parameter lying on (0, 2], a skewness parameter, a scale parameter and a location parameter, and cannot be expressed in closed form except for a few special cases. When the shape parameter is 2, the result is Gaussian, but when it is smaller the resulting distribution has infinite variance. Typical magnetotelluric residuals are alpha stable with a shape parameter lying between 1 and 2. This suggests that robust methods improve response function estimates by eliminating data corresponding to the largest stable residuals while leaving the bulk of the population alone. A better statistical approach is based on stable regression that directly accommodates the actual residual distribution without eliminating the most extreme ones. This paper will introduce such an algorithm, and illustrate its functionality with a variety of magnetotelluric data. Further work remains to produce a robust stable regression algorithm that will eliminate real outliers such as lightning strikes or instrument problems without affecting the bulk stable population. Stable distributions are intimately associated with fractional derivative physical processes. Since the Maxwell equations and the constitutive relations pertaining to the earth do not contain any fractional
Learning Inverse Rig Mappings by Nonlinear Regression.
Holden, Daniel; Saito, Jun; Komura, Taku
2016-11-11
We present a framework to design inverse rig-functions - functions that map low level representations of a character's pose such as joint positions or surface geometry to the representation used by animators called the animation rig. Animators design scenes using an animation rig, a framework widely adopted in animation production which allows animators to design character poses and geometry via intuitive parameters and interfaces. Yet most state-of-the-art computer animation techniques control characters through raw, low level representations such as joint angles, joint positions, or vertex coordinates. This difference often stops the adoption of state-of-the-art techniques in animation production. Our framework solves this issue by learning a mapping between the low level representations of the pose and the animation rig. We use nonlinear regression techniques, learning from example animation sequences designed by the animators. When new motions are provided in the skeleton space, the learned mapping is used to estimate the rig controls that reproduce such a motion. We introduce two nonlinear functions for producing such a mapping: Gaussian process regression and feedforward neural networks. The appropriate solution depends on the nature of the rig and the amount of data available for training. We show our framework applied to various examples including articulated biped characters, quadruped characters, facial animation rigs, and deformable characters. With our system, animators have the freedom to apply any motion synthesis algorithm to arbitrary rigging and animation pipelines for immediate editing. This greatly improves the productivity of 3D animation, while retaining the flexibility and creativity of artistic input.
Collaborative Regression-based Anatomical Landmark Detection
Gao, Yaozong; Shen, Dinggang
2015-01-01
Anatomical landmark detection plays an important role in medical image analysis, e.g., for registration, segmentation and quantitative analysis. Among various existing methods for landmark detection, regression-based methods recently have drawn much attention due to robustness and efficiency. In such methods, landmarks are localized through voting from all image voxels, which is completely different from classification-based methods that use voxel-wise classification to detect landmarks. Despite robustness, the accuracy of regression-based landmark detection methods is often limited due to 1) inclusion of uninformative image voxels in the voting procedure, and 2) lack of effective ways to incorporate inter-landmark spatial dependency into the detection step. In this paper, we propose a collaborative landmark detection framework to address these limitations. The concept of collaboration is reflected in two aspects. 1) Multi-resolution collaboration. A multi-resolution strategy is proposed to hierarchically localize landmarks by gradually excluding uninformative votes from faraway voxels. Moreover, for the informative voxels near the landmark, a spherical sampling strategy is also designed in the training stage to improve their prediction accuracy. 2) Inter-landmark collaboration. A confidence-based landmark detection strategy is proposed to improve the detection accuracy of “difficult-to-detect” landmarks by using spatial guidance from “easy-to-detect” landmarks. To evaluate our method, we conducted experiments extensively on three datasets for detecting prostate landmarks and head & neck landmarks in computed tomography (CT) images, and also dental landmarks in cone beam computed tomography (CBCT) images. The results show the effectiveness of our collaborative landmark detection framework in improving landmark detection accuracy, compared to other state-of-the-art methods. PMID:26579736
Collaborative regression-based anatomical landmark detection
NASA Astrophysics Data System (ADS)
Gao, Yaozong; Shen, Dinggang
2015-12-01
Anatomical landmark detection plays an important role in medical image analysis, e.g. for registration, segmentation and quantitative analysis. Among the various existing methods for landmark detection, regression-based methods have recently attracted much attention due to their robustness and efficiency. In these methods, landmarks are localised through voting from all image voxels, which is completely different from the classification-based methods that use voxel-wise classification to detect landmarks. Despite their robustness, the accuracy of regression-based landmark detection methods is often limited due to (1) the inclusion of uninformative image voxels in the voting procedure, and (2) the lack of effective ways to incorporate inter-landmark spatial dependency into the detection step. In this paper, we propose a collaborative landmark detection framework to address these limitations. The concept of collaboration is reflected in two aspects. (1) Multi-resolution collaboration. A multi-resolution strategy is proposed to hierarchically localise landmarks by gradually excluding uninformative votes from faraway voxels. Moreover, for informative voxels near the landmark, a spherical sampling strategy is also designed at the training stage to improve their prediction accuracy. (2) Inter-landmark collaboration. A confidence-based landmark detection strategy is proposed to improve the detection accuracy of ‘difficult-to-detect’ landmarks by using spatial guidance from ‘easy-to-detect’ landmarks. To evaluate our method, we conducted experiments extensively on three datasets for detecting prostate landmarks and head & neck landmarks in computed tomography images, and also dental landmarks in cone beam computed tomography images. The results show the effectiveness of our collaborative landmark detection framework in improving landmark detection accuracy, compared to other state-of-the-art methods.
Logistic Regression Applied to Seismic Discrimination
BG Amindan; DN Hagedorn
1998-10-08
The usefulness of logistic discrimination was examined in an effort to learn how it performs in a regional seismic setting. Logistic discrimination provides an easily understood method, works with user-defined models and few assumptions about the population distributions, and handles both continuous and discrete data. Seismic event measurements from a data set compiled by Los Alamos National Laboratory (LANL) of Chinese events recorded at station WMQ were used in this demonstration study. PNNL applied logistic regression techniques to the data. All possible combinations of the Lg and Pg measurements were tried, and a best-fit logistic model was created. The best combination of Lg and Pg frequencies for predicting the source of a seismic event (earthquake or explosion) used Lg{sub 3.0-6.0} and Pg{sub 3.0-6.0} as the predictor variables. A cross-validation test was run, which showed that this model was able to correctly predict 99.7% earthquakes and 98.0% explosions for this given data set. Two other models were identified that used Pg and Lg measurements from the 1.5 to 3.0 Hz frequency range. Although these other models did a good job of correctly predicting the earthquakes, they were not as effective at predicting the explosions. Two possible biases were discovered which affect the predicted probabilities for each outcome. The first bias was due to this being a case-controlled study. The sampling fractions caused a bias in the probabilities that were calculated using the models. The second bias is caused by a change in the proportions for each event. If at a later date the proportions (a priori probabilities) of explosions versus earthquakes change, this would cause a bias in the predicted probability for an event. When using logistic regression, the user needs to be aware of the possible biases and what affect they will have on the predicted probabilities.
Sekar, N; Veldhuis, J D
2001-07-01
Insulin and insulin-like growth factor I (IGF-I) can amplify gonadotropin-stimulated steroidogenesis by augmenting the expression of key sterol regulatory genes in ovarian cells, viz. low density lipoprotein (LDL) receptor, steroidogenic acute regulatory protein, and P450 cholesterol side-chain cleavage enzyme (CYP11A). The mechanisms underlying the foregoing bihormonal interactions are not known. Accordingly, in relation to the LDL receptor gene, the present study tests the hypothesis that insulin/IGF-I and LH can act via concerted transcriptional control of promoter expression. To this end, we transiently transfected primary monolayer cultures of porcine granulosa-luteal cells with a reporter vector containing the putative 5'-upstream full-length (pLDLR1076/luc) regulatory region (-1076 to +11 bp) of the homologous LDL receptor gene driving firefly luciferase in the presence or absence of insulin (or IGF-I) and/or LH (each 100 ng/ml). Combined exposure to LH and insulin (or IGF-I) stimulated LDL receptor transcriptional activity maximally at 4 h by 8- to 20-fold, as normalized by coexpression of Renilla luciferase. Further analysis of multiple 5'-nested deletional constructs of the LDL receptor gene promoter showed that deletion of -139 bp upstream of the transcriptional start site virtually abolished basal expression and promoter responsiveness to LH and insulin/IGF-I. In contrast, full basal activity and 60-80% of maximal monohormonal and bihormonal drive were retained by the -255 to +11 bp fragment. As LDL receptor gene expression in other tissues is negatively regulated by the abundance of intracellular free cholesterol, we assessed the impact of concomitant pretreatment of granulosa-luteal cells with an exogenous soluble sterol (25-hydroxycholesterol, 1 and 10 microM). Excess sterol markedly (50-70%) attenuated bihormonally and, in lesser measure, LH-stimulated and basal LDL receptor promoter expression, thus affirming a feedback-sensitive sterol
Charter, Richard A
2009-04-01
Over 50 years ago Payne and Jones (1957) developed what has been labeled the traditional reliable difference formula that continues to be useful as a significance test for the difference between two test scores. The traditional reliable difference is based on the standard error of measurement (SEM) and has been updated to a confidence interval approach. As an alternative to the traditional reliable difference, this article presents the regression-based reliable difference that is based on the standard error of estimate (SEE) and estimated true scores. This new approach should be attractive to clinicians preferring the idea of scores regressing toward the mean. The new approach is also presented in confidence interval form with an interpretation that can be viewed as a statement of all hypotheses that are tenable and consistent with the observed data and has the backing of several authorities. Two well-known conceptualizations for true score confidence intervals are the traditional and regression-based. Now clinicians favoring the regression-based conceptualization are not restricted to the use of traditional model when testing score differences using confidence intervals.
ERIC Educational Resources Information Center
Hecht, Jeffrey B.
The analysis of regression residuals and detection of outliers are discussed, with emphasis on determining how deviant an individual data point must be to be considered an outlier and the impact that multiple suspected outlier data points have on the process of outlier determination and treatment. Only bivariate (one dependent and one independent)…
2012-01-01
Background Genomic selection (GS) is emerging as an efficient and cost-effective method for estimating breeding values using molecular markers distributed over the entire genome. In essence, it involves estimating the simultaneous effects of all genes or chromosomal segments and combining the estimates to predict the total genomic breeding value (GEBV). Accurate prediction of GEBVs is a central and recurring challenge in plant and animal breeding. The existence of a bewildering array of approaches for predicting breeding values using markers underscores the importance of identifying approaches able to efficiently and accurately predict breeding values. Here, we comparatively evaluate the predictive performance of six regularized linear regression methods-- ridge regression, ridge regression BLUP, lasso, adaptive lasso, elastic net and adaptive elastic net-- for predicting GEBV using dense SNP markers. Methods We predicted GEBVs for a quantitative trait using a dataset on 3000 progenies of 20 sires and 200 dams and an accompanying genome consisting of five chromosomes with 9990 biallelic SNP-marker loci simulated for the QTL-MAS 2011 workshop. We applied all the six methods that use penalty-based (regularization) shrinkage to handle datasets with far more predictors than observations. The lasso, elastic net and their adaptive extensions further possess the desirable property that they simultaneously select relevant predictive markers and optimally estimate their effects. The regression models were trained with a subset of 2000 phenotyped and genotyped individuals and used to predict GEBVs for the remaining 1000 progenies without phenotypes. Predictive accuracy was assessed using the root mean squared error, the Pearson correlation between predicted GEBVs and (1) the true genomic value (TGV), (2) the true breeding value (TBV) and (3) the simulated phenotypic values based on fivefold cross-validation (CV). Results The elastic net, lasso, adaptive lasso and the
Spatial vulnerability assessments by regression kriging
NASA Astrophysics Data System (ADS)
Pásztor, László; Laborczi, Annamária; Takács, Katalin; Szatmári, Gábor
2016-04-01
information representing IEW or GRP forming environmental factors were taken into account to support the spatial inference of the locally experienced IEW frequency and measured GRP values respectively. An efficient spatial prediction methodology was applied to construct reliable maps, namely regression kriging (RK) using spatially exhaustive auxiliary data on soil, geology, topography, land use and climate. RK divides the spatial inference into two parts. Firstly the deterministic component of the target variable is determined by a regression model. The residuals of the multiple linear regression analysis represent the spatially varying but dependent stochastic component, which are interpolated by kriging. The final map is the sum of the two component predictions. Application of RK also provides the possibility of inherent accuracy assessment. The resulting maps are characterized by global and local measures of its accuracy. Additionally the method enables interval estimation for spatial extension of the areas of predefined risk categories. All of these outputs provide useful contribution to spatial planning, action planning and decision making. Acknowledgement: Our work was partly supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).
Deep Wavelet Scattering for Quantum Energy Regression
NASA Astrophysics Data System (ADS)
Hirn, Matthew
Physical functionals are usually computed as solutions of variational problems or from solutions of partial differential equations, which may require huge computations for complex systems. Quantum chemistry calculations of ground state molecular energies is such an example. Indeed, if x is a quantum molecular state, then the ground state energy E0 (x) is the minimum eigenvalue solution of the time independent Schrödinger Equation, which is computationally intensive for large systems. Machine learning algorithms do not simulate the physical system but estimate solutions by interpolating values provided by a training set of known examples {(xi ,E0 (xi) } i <= n . However, precise interpolations may require a number of examples that is exponential in the system dimension, and are thus intractable. This curse of dimensionality may be circumvented by computing interpolations in smaller approximation spaces, which take advantage of physical invariants. Linear regressions of E0 over a dictionary Φ ={ϕk } k compute an approximation E 0 as: E 0 (x) =∑kwkϕk (x) , where the weights {wk } k are selected to minimize the error between E0 and E 0 on the training set. The key to such a regression approach then lies in the design of the dictionary Φ. It must be intricate enough to capture the essential variability of E0 (x) over the molecular states x of interest, while simple enough so that evaluation of Φ (x) is significantly less intensive than a direct quantum mechanical computation (or approximation) of E0 (x) . In this talk we present a novel dictionary Φ for the regression of quantum mechanical energies based on the scattering transform of an intermediate, approximate electron density representation ρx of the state x. The scattering transform has the architecture of a deep convolutional network, composed of an alternating sequence of linear filters and nonlinear maps. Whereas in many deep learning tasks the linear filters are learned from the training data, here
Regression-kriging for characterizing soils with remotesensing data
NASA Astrophysics Data System (ADS)
Ge, Yufeng; Thomasson, J. Alex; Sui, Ruixiu; Wooten, James
2011-09-01
In precision agriculture regression has been used widely to quantify the relationship between soil attributes and other environmental variables. However, spatial correlation existing in soil samples usually violates a basic assumption of regression: sample independence. In this study, a regression-kriging method was attempted in relating soil properties to the remote sensing image of a cotton field near Vance, Mississippi, USA. The regression-kriging model was developed and tested by using 273 soil samples collected from the field. The result showed that by properly incorporating the spatial correlation information of regression residuals, the regression-kriging model generally achieved higher prediction accuracy than the stepwise multiple linear regression model. Most strikingly, a 50% increase in prediction accuracy was shown in soil sodium concentration. Potential usages of regression-kriging in future precision agriculture applications include real-time soil sensor development and digital soil mapping.
Poisson Mixture Regression Models for Heart Disease Prediction.
Mufudza, Chipo; Erol, Hamza
2016-01-01
Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model.
Automation of Flight Software Regression Testing
NASA Technical Reports Server (NTRS)
Tashakkor, Scott B.
2016-01-01
NASA is developing the Space Launch System (SLS) to be a heavy lift launch vehicle supporting human and scientific exploration beyond earth orbit. SLS will have a common core stage, an upper stage, and different permutations of boosters and fairings to perform various crewed or cargo missions. Marshall Space Flight Center (MSFC) is writing the Flight Software (FSW) that will operate the SLS launch vehicle. The FSW is developed in an incremental manner based on "Agile" software techniques. As the FSW is incrementally developed, testing the functionality of the code needs to be performed continually to ensure that the integrity of the software is maintained. Manually testing the functionality on an ever-growing set of requirements and features is not an efficient solution and therefore needs to be done automatically to ensure testing is comprehensive. To support test automation, a framework for a regression test harness has been developed and used on SLS FSW. The test harness provides a modular design approach that can compile or read in the required information specified by the developer of the test. The modularity provides independence between groups of tests and the ability to add and remove tests without disturbing others. This provides the SLS FSW team a time saving feature that is essential to meeting SLS Program technical and programmatic requirements. During development of SLS FSW, this technique has proved to be a useful tool to ensure all requirements have been tested, and that desired functionality is maintained, as changes occur. It also provides a mechanism for developers to check functionality of the code that they have developed. With this system, automation of regression testing is accomplished through a scheduling tool and/or commit hooks. Key advantages of this test harness capability includes execution support for multiple independent test cases, the ability for developers to specify precisely what they are testing and how, the ability to add
Testing the gonadal regression-cytoprotection hypothesis.
Crawford, B A; Spaliviero, J A; Simpson, J M; Handelsman, D J
1998-11-15
Germinal damage is an almost universal accompaniment of cancer treatment as the result of bystander damage to the testis from cytotoxic drugs and/or irradiation. Cancer treatment for the most common cancers of the reproductive age group in men has improved such that most are now treated with curative intent, and many others are treated with likelihood of prolonged survival, so that the preservation of fertility is an important component of posttreatment quality of life. This has led to the consideration of developing adjuvant treatments that may reduce the gonadal toxicity of cancer therapy. One dominant hypothesis has been based on the supposition that the immature testis was resistant to cytotoxin damage. Hence, if hormonal treatment were able to cause spermatogenic regression to an immature state via an effective withdrawal of gonadotrophin secretion, the testis might be maintained temporarily in a protected state during cytotoxin exposure. However, clinical studies have been disappointing but have also been unable to test the hypothesis definitively thus far, due to the inability to completely suppress gonadotrophin secretion. Similarly, experimental models have also given conflicting results and, at best, a modest cytoprotection. To definitively test this hypothesis experimentally, we used the fact that the functionally hpg mouse has complete gonadotrophin deficiency but can undergo the induction of full spermatogenesis by testosterone. Thus, if complete gonadotrophin deficiency were an advantage during cytotoxin exposure, then the hpg mouse should exhibit some degree of germinal protection against cytotoxin-induced damage. We therefore administered three different cytotoxins (200 mg/kg procarbazine, 9 mg/kg doxorubicin, 8 Gy of X irradiation) to produce a range of severity in testicular damage and mechanism of action to either phenotypically normal or hpg mice. Testis weight and homogenization-resistant spermatid numbers were measured to evaluate the
Survival Regression Modeling Strategies in CVD Prediction
Barkhordari, Mahnaz; Padyab, Mojgan; Sardarinia, Mahsa; Hadaegh, Farzad; Azizi, Fereidoun; Bozorgmanesh, Mohammadreza
2016-01-01
Background A fundamental part of prevention is prediction. Potential predictors are the sine qua non of prediction models. However, whether incorporating novel predictors to prediction models could be directly translated to added predictive value remains an area of dispute. The difference between the predictive power of a predictive model with (enhanced model) and without (baseline model) a certain predictor is generally regarded as an indicator of the predictive value added by that predictor. Indices such as discrimination and calibration have long been used in this regard. Recently, the use of added predictive value has been suggested while comparing the predictive performances of the predictive models with and without novel biomarkers. Objectives User-friendly statistical software capable of implementing novel statistical procedures is conspicuously lacking. This shortcoming has restricted implementation of such novel model assessment methods. We aimed to construct Stata commands to help researchers obtain the aforementioned statistical indices. Materials and Methods We have written Stata commands that are intended to help researchers obtain the following. 1, Nam-D’Agostino X2 goodness of fit test; 2, Cut point-free and cut point-based net reclassification improvement index (NRI), relative absolute integrated discriminatory improvement index (IDI), and survival-based regression analyses. We applied the commands to real data on women participating in the Tehran lipid and glucose study (TLGS) to examine if information relating to a family history of premature cardiovascular disease (CVD), waist circumference, and fasting plasma glucose can improve predictive performance of Framingham’s general CVD risk algorithm. Results The command is adpredsurv for survival models. Conclusions Herein we have described the Stata package “adpredsurv” for calculation of the Nam-D’Agostino X2 goodness of fit test as well as cut point-free and cut point-based NRI, relative
Laplacian embedded regression for scalable manifold regularization.
Chen, Lin; Tsang, Ivor W; Xu, Dong
2012-06-01
Semi-supervised learning (SSL), as a powerful tool to learn from a limited number of labeled data and a large number of unlabeled data, has been attracting increasing attention in the machine learning community. In particular, the manifold regularization framework has laid solid theoretical foundations for a large family of SSL algorithms, such as Laplacian support vector machine (LapSVM) and Laplacian regularized least squares (LapRLS). However, most of these algorithms are limited to small scale problems due to the high computational cost of the matrix inversion operation involved in the optimization problem. In this paper, we propose a novel framework called Laplacian embedded regression by introducing an intermediate decision variable into the manifold regularization framework. By using ∈-insensitive loss, we obtain the Laplacian embedded support vector regression (LapESVR) algorithm, which inherits the sparse solution from SVR. Also, we derive Laplacian embedded RLS (LapERLS) corresponding to RLS under the proposed framework. Both LapESVR and LapERLS possess a simpler form of a transformed kernel, which is the summation of the original kernel and a graph kernel that captures the manifold structure. The benefits of the transformed kernel are two-fold: (1) we can deal with the original kernel matrix and the graph Laplacian matrix in the graph kernel separately and (2) if the graph Laplacian matrix is sparse, we only need to perform the inverse operation for a sparse matrix, which is much more efficient when compared with that for a dense one. Inspired by kernel principal component analysis, we further propose to project the introduced decision variable into a subspace spanned by a few eigenvectors of the graph Laplacian matrix in order to better reflect the data manifold, as well as accelerate the calculation of the graph kernel, allowing our methods to efficiently and effectively cope with large scale SSL problems. Extensive experiments on both toy and real
Relationship between Multiple Regression and Selected Multivariable Methods.
ERIC Educational Resources Information Center
Schumacker, Randall E.
The relationship of multiple linear regression to various multivariate statistical techniques is discussed. The importance of the standardized partial regression coefficient (beta weight) in multiple linear regression as it is applied in path, factor, LISREL, and discriminant analyses is emphasized. The multivariate methods discussed in this paper…
Using Dominance Analysis to Determine Predictor Importance in Logistic Regression
ERIC Educational Resources Information Center
Azen, Razia; Traxel, Nicole
2009-01-01
This article proposes an extension of dominance analysis that allows researchers to determine the relative importance of predictors in logistic regression models. Criteria for choosing logistic regression R[superscript 2] analogues were determined and measures were selected that can be used to perform dominance analysis in logistic regression. A…
Using Time-Series Regression to Predict Academic Library Circulations.
ERIC Educational Resources Information Center
Brooks, Terrence A.
1984-01-01
Four methods were used to forecast monthly circulation totals in 15 midwestern academic libraries: dummy time-series regression, lagged time-series regression, simple average (straight-line forecasting), monthly average (naive forecasting). In tests of forecasting accuracy, dummy regression method and monthly mean method exhibited smallest average…
Orthogonal Projection in Teaching Regression and Financial Mathematics
ERIC Educational Resources Information Center
Kachapova, Farida; Kachapov, Ilias
2010-01-01
Two improvements in teaching linear regression are suggested. The first is to include the population regression model at the beginning of the topic. The second is to use a geometric approach: to interpret the regression estimate as an orthogonal projection and the estimation error as the distance (which is minimized by the projection). Linear…
NUCLEI SEGMENTATION VIA SPARSITY CONSTRAINED CONVOLUTIONAL REGRESSION
Zhou, Yin; Chang, Hang; Barner, Kenneth E.; Parvin, Bahram
2017-01-01
Automated profiling of nuclear architecture, in histology sections, can potentially help predict the clinical outcomes. However, the task is challenging as a result of nuclear pleomorphism and cellular states (e.g., cell fate, cell cycle), which are compounded by the batch effect (e.g., variations in fixation and staining). Present methods, for nuclear segmentation, are based on human-designed features that may not effectively capture intrinsic nuclear architecture. In this paper, we propose a novel approach, called sparsity constrained convolutional regression (SCCR), for nuclei segmentation. Specifically, given raw image patches and the corresponding annotated binary masks, our algorithm jointly learns a bank of convolutional filters and a sparse linear regressor, where the former is used for feature extraction, and the latter aims to produce a likelihood for each pixel being nuclear region or background. During classification, the pixel label is simply determined by a thresholding operation applied on the likelihood map. The method has been evaluated using the benchmark dataset collected from The Cancer Genome Atlas (TCGA). Experimental results demonstrate that our method outperforms traditional nuclei segmentation algorithms and is able to achieve competitive performance compared to the state-of-the-art algorithm built upon human-designed features with biological prior knowledge. PMID:28101301
Semiparametric Bayesian Regression with Applications in Astronomy
NASA Astrophysics Data System (ADS)
Broadbent, Mary Elizabeth
In this thesis we describe a class of Bayesian semiparametric models, known as Levy Adaptive Regression Kernels (LARK); a novel method for posterior computation for those models; and the applications of these models in astronomy, in particular to the analysis of the photon fluence time series of gamma-ray bursts. Gamma-ray bursts are bursts of photons which arrive in a varying number of overlapping pulses with a distinctive "fast-rise, exponential decay" shape in the time domain. LARK models allow us to do inference both on the number of pulses, but also on the parameters which describe the pulses, such as incident time, or decay rate. In Chapter 2, we describe a novel method to aid posterior computation in infinitely-divisible models, of which LARK models are a special case, when the posterior is evaluated through Markov chain Monte Carlo. This is applied in Chapter 3, where time series representing the photon fluence in a single energy channel is analyzed using LARK methods. Due to the effect of the discriminators on BATSE and other instruments, it is important to model the gamma-ray bursts in the incident space. Chapter 4 describes the first to model bursts in the incident photon space, instead of after they have been distorted by the discriminators; since to model photons as they enter the detector is to model both the energy and the arrival time of the incident photon, this model is also the first to jointly model the time and energy domains.
A rotor optimization using regression analysis
NASA Technical Reports Server (NTRS)
Giansante, N.
1984-01-01
The design and development of helicopter rotors is subject to the many design variables and their interactions that effect rotor operation. Until recently, selection of rotor design variables to achieve specified rotor operational qualities has been a costly, time consuming, repetitive task. For the past several years, Kaman Aerospace Corporation has successfully applied multiple linear regression analysis, coupled with optimization and sensitivity procedures, in the analytical design of rotor systems. It is concluded that approximating equations can be developed rapidly for a multiplicity of objective and constraint functions and optimizations can be performed in a rapid and cost effective manner; the number and/or range of design variables can be increased by expanding the data base and developing approximating functions to reflect the expanded design space; the order of the approximating equations can be expanded easily to improve correlation between analyzer results and the approximating equations; gradients of the approximating equations can be calculated easily and these gradients are smooth functions reducing the risk of numerical problems in the optimization; the use of approximating functions allows the problem to be started easily and rapidly from various initial designs to enhance the probability of finding a global optimum; and the approximating equations are independent of the analysis or optimization codes used.
Interactive natural image segmentation via spline regression.
Xiang, Shiming; Nie, Feiping; Zhang, Chunxia; Zhang, Changshui
2009-07-01
This paper presents an interactive algorithm for segmentation of natural images. The task is formulated as a problem of spline regression, in which the spline is derived in Sobolev space and has a form of a combination of linear and Green's functions. Besides its nonlinear representation capability, one advantage of this spline in usage is that, once it has been constructed, no parameters need to be tuned to data. We define this spline on the user specified foreground and background pixels, and solve its parameters (the combination coefficients of functions) from a group of linear equations. To speed up spline construction, K-means clustering algorithm is employed to cluster the user specified pixels. By taking the cluster centers as representatives, this spline can be easily constructed. The foreground object is finally cut out from its background via spline interpolation. The computational complexity of the proposed algorithm is linear in the number of the pixels to be segmented. Experiments on diverse natural images, with comparison to existing algorithms, illustrate the validity of our method.
Data selection using support vector regression
NASA Astrophysics Data System (ADS)
Richman, Michael B.; Leslie, Lance M.; Trafalis, Theodore B.; Mansouri, Hicham
2015-03-01
Geophysical data sets are growing at an ever-increasing rate, requiring computationally efficient data selection (thinning) methods to preserve essential information. Satellites, such as WindSat, provide large data sets for assessing the accuracy and computational efficiency of data selection techniques. A new data thinning technique, based on support vector regression (SVR), is developed and tested. To manage large on-line satellite data streams, observations from WindSat are formed into subsets by Voronoi tessellation and then each is thinned by SVR (TSVR). Three experiments are performed. The first confirms the viability of TSVR for a relatively small sample, comparing it to several commonly used data thinning methods (random selection, averaging and Barnes filtering), producing a 10% thinning rate (90% data reduction), low mean absolute errors (MAE) and large correlations with the original data. A second experiment, using a larger dataset, shows TSVR retrievals with MAE < 1 m s-1 and correlations ⩽ 0.98. TSVR was an order of magnitude faster than the commonly used thinning methods. A third experiment applies a two-stage pipeline to TSVR, to accommodate online data. The pipeline subsets reconstruct the wind field with the same accuracy as the second experiment, is an order of magnitude faster than the nonpipeline TSVR. Therefore, pipeline TSVR is two orders of magnitude faster than commonly used thinning methods that ingest the entire data set. This study demonstrates that TSVR pipeline thinning is an accurate and computationally efficient alternative to commonly used data selection techniques.
Father regression. Clinical narratives and theoretical reflections.
Stein, Ruth
2006-08-01
The author deals with love-hate enthrallment and submission to a primitive paternal object. This is a father-son relationship that extends through increasing degrees of 'primitiveness' or extremeness, and is illustrated through three different constellations that constitute a continuum. One pole of the continuum encompasses certain male patients who show a loving, de-individuated connection to a father experienced as trustworthy, soft, and in need of protection. Further along the continuum is the case of a transsexual patient whose analysis revealed an intense 'God-transference', a bondage to an idealized, feared, and ostensibly protective father-God introject. A great part of this patient's analysis consisted in a fierce struggle to liberate himself from this figure. The other end of the continuum is occupied by religious terrorists, who exemplify the most radical thralldom to a persecutory, godly object, a regressive submission that banishes woman and enthrones a cruel superego, and that ends in destruction and self-destruction. Psychoanalytic thinking has traditionally dealt with the oedipal father and recently with the nurturing father, but there is a gap in thinking about the phallic, archaic father, and his relations with his son(s). The author aims at filling this gap, at the same time as she also raises the very question of 'What is a father?' linking it with literary and religious themes.
Gravitational Wave Emulation Using Gaussian Process Regression
NASA Astrophysics Data System (ADS)
Doctor, Zoheyr; Farr, Ben; Holz, Daniel
2017-01-01
Parameter estimation (PE) for gravitational wave signals from compact binary coalescences (CBCs) requires reliable template waveforms which span the parameter space. Waveforms from numerical relativity are accurate but computationally expensive, so approximate templates are typically used for PE. These `approximants', while quick to compute, can introduce systematic errors and bias PE results. We describe a machine learning method for generating CBC waveforms and uncertainties using existing accurate waveforms as a training set. Coefficients of a reduced order waveform model are computed and each treated as arising from a Gaussian process. These coefficients and their uncertainties are then interpolated using Gaussian process regression (GPR). As a proof of concept, we construct a training set of approximant waveforms (rather than NR waveforms) in the two-dimensional space of chirp mass and mass ratio and interpolate new waveforms with GPR. We demonstrate that the mismatch between interpolated waveforms and approximants is below the 1% level for an appropriate choice of training set and GPR kernel hyperparameters.
Boosted Regression Tree Models to Explain Watershed ...
Boosted regression tree (BRT) models were developed to quantify the nonlinear relationships between landscape variables and nutrient concentrations in a mesoscale mixed land cover watershed during base-flow conditions. Factors that affect instream biological components, based on the Index of Biotic Integrity (IBI), were also analyzed. Seasonal BRT models at two spatial scales (watershed and riparian buffered area [RBA]) for nitrite-nitrate (NO2-NO3), total Kjeldahl nitrogen, and total phosphorus (TP) and annual models for the IBI score were developed. Two primary factors — location within the watershed (i.e., geographic position, stream order, and distance to a downstream confluence) and percentage of urban land cover (both scales) — emerged as important predictor variables. Latitude and longitude interacted with other factors to explain the variability in summer NO2-NO3 concentrations and IBI scores. BRT results also suggested that location might be associated with indicators of sources (e.g., land cover), runoff potential (e.g., soil and topographic factors), and processes not easily represented by spatial data indicators. Runoff indicators (e.g., Hydrological Soil Group D and Topographic Wetness Indices) explained a substantial portion of the variability in nutrient concentrations as did point sources for TP in the summer months. The results from our BRT approach can help prioritize areas for nutrient management in mixed-use and heavily impacted watershed
Cyclodextrin promotes atherosclerosis regression via macrophage reprogramming
Zimmer, Sebastian; Grebe, Alena; Bakke, Siril S.; Bode, Niklas; Halvorsen, Bente; Ulas, Thomas; Skjelland, Mona; De Nardo, Dominic; Labzin, Larisa I.; Kerksiek, Anja; Hempel, Chris; Heneka, Michael T.; Hawxhurst, Victoria; Fitzgerald, Michael L; Trebicka, Jonel; Gustafsson, Jan-Åke; Westerterp, Marit; Tall, Alan R.; Wright, Samuel D.; Espevik, Terje; Schultze, Joachim L.; Nickenig, Georg; Lütjohann, Dieter; Latz, Eicke
2016-01-01
Atherosclerosis is an inflammatory disease linked to elevated blood cholesterol levels. Despite ongoing advances in the prevention and treatment of atherosclerosis, cardiovascular disease remains the leading cause of death worldwide. Continuous retention of apolipoprotein B-containing lipoproteins in the subendothelial space causes a local overabundance of free cholesterol. Since cholesterol accumulation and deposition of cholesterol crystals (CCs) triggers a complex inflammatory response, we tested the efficacy of the cyclic oligosaccharide 2-hydroxypropyl-β-cyclodextrin (CD), a compound that increases cholesterol solubility, in preventing and reversing atherosclerosis. Here we show that CD treatment of murine atherosclerosis reduced atherosclerotic plaque size and CC load, and promoted plaque regression even with a continued cholesterol-rich diet. Mechanistically, CD increased oxysterol production in both macrophages and human atherosclerotic plaques, and promoted liver X receptor (LXR)-mediated transcriptional reprogramming to improve cholesterol efflux and exert anti-inflammatory effects. In vivo, this CD-mediated LXR agonism was required for the anti-atherosclerotic and anti-inflammatory effects of CD as well as for augmented reverse cholesterol transport. Since CD treatment in humans is safe and CD beneficially affects key mechanisms of atherogenesis, it may therefore be used clinically to prevent or treat human atherosclerosis. PMID:27053774
Cyclodextrin promotes atherosclerosis regression via macrophage reprogramming.
Zimmer, Sebastian; Grebe, Alena; Bakke, Siril S; Bode, Niklas; Halvorsen, Bente; Ulas, Thomas; Skjelland, Mona; De Nardo, Dominic; Labzin, Larisa I; Kerksiek, Anja; Hempel, Chris; Heneka, Michael T; Hawxhurst, Victoria; Fitzgerald, Michael L; Trebicka, Jonel; Björkhem, Ingemar; Gustafsson, Jan-Åke; Westerterp, Marit; Tall, Alan R; Wright, Samuel D; Espevik, Terje; Schultze, Joachim L; Nickenig, Georg; Lütjohann, Dieter; Latz, Eicke
2016-04-06
Atherosclerosis is an inflammatory disease linked to elevated blood cholesterol concentrations. Despite ongoing advances in the prevention and treatment of atherosclerosis, cardiovascular disease remains the leading cause of death worldwide. Continuous retention of apolipoprotein B-containing lipoproteins in the subendothelial space causes a local overabundance of free cholesterol. Because cholesterol accumulation and deposition of cholesterol crystals (CCs) trigger a complex inflammatory response, we tested the efficacy of the cyclic oligosaccharide 2-hydroxypropyl-β-cyclodextrin (CD), a compound that increases cholesterol solubility in preventing and reversing atherosclerosis. We showed that CD treatment of murine atherosclerosis reduced atherosclerotic plaque size and CC load and promoted plaque regression even with a continued cholesterol-rich diet. Mechanistically, CD increased oxysterol production in both macrophages and human atherosclerotic plaques and promoted liver X receptor (LXR)-mediated transcriptional reprogramming to improve cholesterol efflux and exert anti-inflammatory effects. In vivo, this CD-mediated LXR agonism was required for the antiatherosclerotic and anti-inflammatory effects of CD as well as for augmented reverse cholesterol transport. Because CD treatment in humans is safe and CD beneficially affects key mechanisms of atherogenesis, it may therefore be used clinically to prevent or treat human atherosclerosis.
Rank-preserving regression: a more robust rank regression model against outliers.
Chen, Tian; Kowalski, Jeanne; Chen, Rui; Wu, Pan; Zhang, Hui; Feng, Changyong; Tu, Xin M
2016-08-30
Mean-based semi-parametric regression models such as the popular generalized estimating equations are widely used to improve robustness of inference over parametric models. Unfortunately, such models are quite sensitive to outlying observations. The Wilcoxon-score-based rank regression (RR) provides more robust estimates over generalized estimating equations against outliers. However, the RR and its extensions do not sufficiently address missing data arising in longitudinal studies. In this paper, we propose a new approach to address outliers under a different framework based on the functional response models. This functional-response-model-based alternative not only addresses limitations of the RR and its extensions for longitudinal data, but, with its rank-preserving property, even provides more robust estimates than these alternatives. The proposed approach is illustrated with both real and simulated data. Copyright © 2016 John Wiley & Sons, Ltd.
van Houwelingen, Hans C; Putter, Hein
2015-04-01
By far the most popular model to obtain survival predictions for individual patients is the Cox model. The Cox model does not make any assumptions on the underlying hazard, but it relies heavily on the proportional hazards assumption. The most common ways to circumvent this robustness problem are 1) to categorize patients based on their prognostic risk score and to base predictions on Kaplan-Meier curves for the risk categories, or 2) to include interactions with the covariates and suitable functions of time. Robust estimators of the t(0)-year survival probabilities can also be obtained from a "stopped Cox" regression model, in which all observations are administratively censored at t(0). Other recent approaches to solve this robustness problem, originally proposed in the context of competing risks, are pseudo-values and direct binomial regression, based on unbiased estimating equations. In this paper stopped Cox regression is compared with these direct approaches. This is done by means of a simulation study to assess the biases of the different approaches and an analysis of breast cancer data to get some feeling for the performance in practice. The tentative conclusion is that stopped Cox and direct models agree well if the follow-up is not too long. There are larger differences for long-term follow-up data. There stopped Cox might be more efficient, but less robust.
Yang, Shun-hua; Zhang, Hai-tao; Guo, Long; Ren, Yan
2015-06-01
Relative elevation and stream power index were selected as auxiliary variables based on correlation analysis for mapping soil organic matter. Geographically weighted regression Kriging (GWRK) and regression Kriging (RK) were used for spatial interpolation of soil organic matter and compared with ordinary Kriging (OK), which acts as a control. The results indicated that soil or- ganic matter was significantly positively correlated with relative elevation whilst it had a significantly negative correlation with stream power index. Semivariance analysis showed that both soil organic matter content and its residuals (including ordinary least square regression residual and GWR resi- dual) had strong spatial autocorrelation. Interpolation accuracies by different methods were esti- mated based on a data set of 98 validation samples. Results showed that the mean error (ME), mean absolute error (MAE) and root mean square error (RMSE) of RK were respectively 39.2%, 17.7% and 20.6% lower than the corresponding values of OK, with a relative-improvement (RI) of 20.63. GWRK showed a similar tendency, having its ME, MAE and RMSE to be respectively 60.6%, 23.7% and 27.6% lower than those of OK, with a RI of 59.79. Therefore, both RK and GWRK significantly improved the accuracy of OK interpolation of soil organic matter due to their in- corporation of auxiliary variables. In addition, GWRK performed obviously better than RK did in this study, and its improved performance should be attributed to the consideration of sample spatial locations.
NASA Astrophysics Data System (ADS)
Ahn, Kuk-Hyun; Palmer, Richard
2016-09-01
Despite wide use of regression-based regional flood frequency analysis (RFFA) methods, the majority are based on either ordinary least squares (OLS) or generalized least squares (GLS). This paper proposes 'spatial proximity' based RFFA methods using the spatial lagged model (SLM) and spatial error model (SEM). The proposed methods are represented by two frameworks: the quantile regression technique (QRT) and parameter regression technique (PRT). The QRT develops prediction equations for flooding quantiles in average recurrence intervals (ARIs) of 2, 5, 10, 20, and 100 years whereas the PRT provides prediction of three parameters for the selected distribution. The proposed methods are tested using data incorporating 30 basin characteristics from 237 basins in Northeastern United States. Results show that generalized extreme value (GEV) distribution properly represents flood frequencies in the study gages. Also, basin area, stream network, and precipitation seasonality are found to be the most effective explanatory variables in prediction modeling by the QRT and PRT. 'Spatial proximity' based RFFA methods provide reliable flood quantile estimates compared to simpler methods. Compared to the QRT, the PRT may be recommended due to its accuracy and computational simplicity. The results presented in this paper may serve as one possible guidepost for hydrologists interested in flood analysis at ungaged sites.
Kepler AutoRegressive Planet Search
NASA Astrophysics Data System (ADS)
Feigelson, Eric
NASA's Kepler mission is the source of more exoplanets than any other instrument, but the discovery depends on complex statistical analysis procedures embedded in the Kepler pipeline. A particular challenge is mitigating irregular stellar variability without loss of sensitivity to faint periodic planetary transits. This proposal presents a two-stage alternative analysis procedure. First, parametric autoregressive ARFIMA models, commonly used in econometrics, remove most of the stellar variations. Second, a novel matched filter is used to create a periodogram from which transit-like periodicities are identified. This analysis procedure, the Kepler AutoRegressive Planet Search (KARPS), is confirming most of the Kepler Objects of Interest and is expected to identify additional planetary candidates. The proposed research will complete application of the KARPS methodology to the prime Kepler mission light curves of 200,000: stars, and compare the results with Kepler Objects of Interest obtained with the Kepler pipeline. We will then conduct a variety of astronomical studies based on the KARPS results. Important subsamples will be extracted including Habitable Zone planets, hot super-Earths, grazing-transit hot Jupiters, and multi-planet systems. Groundbased spectroscopy of poorly studied candidates will be performed to better characterize the host stars. Studies of stellar variability will then be pursued based on KARPS analysis. The autocorrelation function and nonstationarity measures will be used to identify spotted stars at different stages of autoregressive modeling. Periodic variables with folded light curves inconsistent with planetary transits will be identified; they may be eclipsing or mutually-illuminating binary star systems. Classification of stellar variables with KARPS-derived statistical properties will be attempted. KARPS procedures will then be applied to archived K2 data to identify planetary transits and characterize stellar variability.
Deep Human Parsing with Active Template Regression.
Liang, Xiaodan; Liu, Si; Shen, Xiaohui; Yang, Jianchao; Liu, Luoqi; Dong, Jian; Lin, Liang; Yan, Shuicheng
2015-12-01
In this work, the human parsing task, namely decomposing a human image into semantic fashion/body regions, is formulated as an active template regression (ATR) problem, where the normalized mask of each fashion/body item is expressed as the linear combination of the learned mask templates, and then morphed to a more precise mask with the active shape parameters, including position, scale and visibility of each semantic region. The mask template coefficients and the active shape parameters together can generate the human parsing results, and are thus called the structure outputs for human parsing. The deep Convolutional Neural Network (CNN) is utilized to build the end-to-end relation between the input human image and the structure outputs for human parsing. More specifically, the structure outputs are predicted by two separate networks. The first CNN network is with max-pooling, and designed to predict the template coefficients for each label mask, while the second CNN network is without max-pooling to preserve sensitivity to label mask position and accurately predict the active shape parameters. For a new image, the structure outputs of the two networks are fused to generate the probability of each label for each pixel, and super-pixel smoothing is finally used to refine the human parsing result. Comprehensive evaluations on a large dataset well demonstrate the significant superiority of the ATR framework over other state-of-the-arts for human parsing. In particular, the F1-score reaches 64.38 percent by our ATR framework, significantly higher than 44.76 percent based on the state-of-the-art algorithm [28].
Extensive regression in pigmented skin lesions: a dangerous confounding feature
Lallas, Aimilios; Apalla, Zoe; Moscarella, Elvira; Zalaudek, Iris; Tzellos, Thrasivoulos; Lefaki, Ioanna; Cota, Carlo; Argenziano, Giuseppe
2012-01-01
Spontaneous regression in melanomas is not an uncommon phenomenon, as it has been described in 10–35% of primary cutaneous lesions [1]. Regression does not appear to predict a more favorable course, since even fully regressed melanomas may progress into metastatic disease [2]. Several dermoscopic features have been correlated with the regression process, including white scar-like depigmented areas and gray-blue, pepper-like granules, which correspond to dermal scarring, pigment incontinence and presence of melanophages [3,4]. Regression may occur not only in melanomas, but also in melanocytic nevi, which similarly may exhibit white areas and gray-blue granules or areas under dermoscopy [5]. Overall, white areas have been proposed to be associated with the fibrosis type of regression and gray-blue areas to the melanosis type of regression of melanocytic tumors [3]. Lichen planus like keratosis (LPLK) is considered to represent a regressed solar lentigo or seborrheic keratosis. Dermoscopy of LPLK at the late stage of the regression process reveals a diffuse gray-blue granular pattern, similar to that observed in regressed melanocytic lesions [6]. In this context, when evaluating skin lesions that exhibit high degree of regression, interpretation of dermoscopic findings may be problematic, especially when no other dermoscopic clues can be recognized. PMID:23785596
Extensive regression in pigmented skin lesions: a dangerous confounding feature.
Lallas, Aimilios; Apalla, Zoe; Moscarella, Elvira; Zalaudek, Iris; Tzellos, Thrasivoulos; Lefaki, Ioanna; Cota, Carlo; Argenziano, Giuseppe
2012-04-01
Spontaneous regression in melanomas is not an uncommon phenomenon, as it has been described in 10-35% of primary cutaneous lesions [1]. Regression does not appear to predict a more favorable course, since even fully regressed melanomas may progress into metastatic disease [2]. Several dermoscopic features have been correlated with the regression process, including white scar-like depigmented areas and gray-blue, pepper-like granules, which correspond to dermal scarring, pigment incontinence and presence of melanophages [3,4]. Regression may occur not only in melanomas, but also in melanocytic nevi, which similarly may exhibit white areas and gray-blue granules or areas under dermoscopy [5]. Overall, white areas have been proposed to be associated with the fibrosis type of regression and gray-blue areas to the melanosis type of regression of melanocytic tumors [3]. Lichen planus like keratosis (LPLK) is considered to represent a regressed solar lentigo or seborrheic keratosis. Dermoscopy of LPLK at the late stage of the regression process reveals a diffuse gray-blue granular pattern, similar to that observed in regressed melanocytic lesions [6]. In this context, when evaluating skin lesions that exhibit high degree of regression, interpretation of dermoscopic findings may be problematic, especially when no other dermoscopic clues can be recognized.
Kepler AutoRegressive Planet Search
NASA Astrophysics Data System (ADS)
Caceres, Gabriel Antonio; Feigelson, Eric
2016-01-01
The Kepler AutoRegressive Planet Search (KARPS) project uses statistical methodology associated with autoregressive (AR) processes to model Kepler lightcurves in order to improve exoplanet transit detection in systems with high stellar variability. We also introduce a planet-search algorithm to detect transits in time-series residuals after application of the AR models. One of the main obstacles in detecting faint planetary transits is the intrinsic stellar variability of the host star. The variability displayed by many stars may have autoregressive properties, wherein later flux values are correlated with previous ones in some manner. Our analysis procedure consisting of three steps: pre-processing of the data to remove discontinuities, gaps and outliers; AR-type model selection and fitting; and transit signal search of the residuals using a new Transit Comb Filter (TCF) that replaces traditional box-finding algorithms. The analysis procedures of the project are applied to a portion of the publicly available Kepler light curve data for the full 4-year mission duration. Tests of the methods have been made on a subset of Kepler Objects of Interest (KOI) systems, classified both as planetary `candidates' and `false positives' by the Kepler Team, as well as a random sample of unclassified systems. We find that the ARMA-type modeling successfully reduces the stellar variability, by a factor of 10 or more in active stars and by smaller factors in more quiescent stars. A typical quiescent Kepler star has an interquartile range (IQR) of ~10 e-/sec, which may improve slightly after modeling, while those with IQR ranging from 20 to 50 e-/sec, have improvements from 20% up to 70%. High activity stars (IQR exceeding 100) markedly improve. A periodogram based on the TCF is constructed to concentrate the signal of these periodic spikes. When a periodic transit is found, the model is displayed on a standard period-folded averaged light curve. Our findings to date on real
Gallet, Claire; Dupont, Joëlle; Campbell, Bruce K; Monniaux, Danielle; Guillaume, Daniel; Scaramuzzi, Rex J
2011-09-01
Short-term nutritional supplementation stimulates folliculogenesis in ewes probably by insulin-mediated actions of glucose in the follicle. The aim of this study was to determine the effect of glucose on follicle number and granulosa levels of Aromatase P450 and phosphorylated Akt and AMPK. Twelve Ile-de-France ewes were allocated to two groups; one (n=7) infused with saline and the other (n=5) with glucose (10mM/h) for 72h in the luteal phase. At the end of infusion, ovaries were collected and all follicles >1mm in diameter were dissected to recover granulosa cells. Aromatase P450 and phosphorylated Akt and AMPK were analysed by Western blotting of granulosa cell lysates. Blood plasmas collected before and during the infusions were analysed for progesterone, oestradiol, LH, FSH, glucose, insulin and IGF-I. The infusion of glucose significantly increased follicle number but, significantly reduced Aromatase P450 and phosphorylated Akt and AMPK in granulosa cells. The circulating concentration of glucose rose significantly 3h after the start of the glucose infusion and remained elevated until 27h then fell; the circulating concentration of insulin rose significantly by 3h and remained elevated. The circulating concentration of oestradiol fell significantly by 32h and remained low; the circulating concentrations of LH and FSH were unaffected. These data show that short-term infusion of glucose stimulated follicular growth but decreased Aromatase P450 in granulosa cells. The reduced levels of phosphorylated Akt and AMPK suggest that the phosphatidylinositol 3-kinase pathway has been inhibited by high concentrations of glucose. These data also suggest that there may be functional cross-talk between FSH and insulin signalling in granulosa cells.
Ginther, O J; Bashir, S T
2013-07-15
In Survey 1, the records for 196 interovulatory intervals (IOIs) from 24 heifers were used to study the frequency and repeatability for number of follicular waves per IOI and to study the ipsilateral and contralateral relationships between the extant corpus luteum and ovulatory follicle. In Survey 2, 96 IOIs were used from the controls of the previous experiments that included the day of the end of the luteolytic period (progesterone <1.0 ng/mL). In Survey 1, the percentage of two-wave IOIs (63%) was greater (P < 0.0002) than for three-wave IOIs (37%). The percentage of ovulatory periods with a contralateral relationship (59%) was greater (P < 0.003) than with the ipsilateral relationship (41%). There were more repeats (66%) than reverses (34%) between adjacent IOIs in number of waves per IOI (P < 0.004), but there was no difference in number of corpus luteum/follicle relationships between the ovulatory periods at the beginning and end of an IOI. For the four permutations of ipsilateral and two waves, contralateral and two waves, ipsilateral and three waves, and contralateral and three waves in Survey 2, the interval (days) from ovulation to the day the progesterone was <1.0 ng/mL was 17.8 ± 0.2(a), 17.6 ± 0.2(a), 20.0 ± 0.3(b), and 21.4 ± 0.3(c), respectively, and the number of IOIs was 33 (34%)(a), 34 (35%)(a), 8 (8%)(b), and 22 (23%)(a), respectively; means with different superscripts are different (P < 0.05). The luteal phase was longer for the contralateral relationship than for the ipsilateral relationship for three-wave IOIs but not for two-wave IOIs. The hypothesis was supported that the frequency of the ipsilateral and three-wave permutation was less than for each of the other three permutations.
Estimating peak flow characteristics at ungaged sites by ridge regression
Tasker, Gary D.
1982-01-01
A regression simulation model, is combined with a multisite streamflow generator to simulate a regional regression of 50-year peak discharge against a set of basin characteristics. Monte Carlo experiments are used to compare the unbiased ordinary lease squares parameter estimator with Hoerl and Kennard's (1970a) ridge estimator in which the biasing parameter is that proposed by Hoerl, Kennard, and Baldwin (1975). The simulation results indicate a substantial improvement in parameter estimation using ridge regression when the correlation between basin characteristics is more than about 0.90. In addition, results indicate a strong potential for improving the mean square error of prediction of a peak-flow characteristic versus basin characteristics regression model when the basin characteristics are approximately colinear. The simulation covers a range of regression parameters, streamflow statistics, and basin characteristics commonly found in regional regression studies.
Inference in Adaptive Regression via the Kac-Rice Formula
2014-05-15
Inference in Adaptive Regression via the Kac- Rice Formula Jonathan Taylor∗, Joshua Loftus, Ryan J. Tibshirani Department of Statistics Stanford...general adaptive regression setting. Our approach uses the Kac- Rice formula (as described in Adler & Taylor 2007) applied to the problem of maximizing a...SUBTITLE Inference in Adaptive Regression via the Kac- Rice Formula 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d
Algorithm For Solution Of Subset-Regression Problems
NASA Technical Reports Server (NTRS)
Verhaegen, Michel
1991-01-01
Reliable and flexible algorithm for solution of subset-regression problem performs QR decomposition with new column-pivoting strategy, enables selection of subset directly from originally defined regression parameters. This feature, in combination with number of extensions, makes algorithm very flexible for use in analysis of subset-regression problems in which parameters have physical meanings. Also extended to enable joint processing of columns contaminated by noise with those free of noise, without using scaling techniques.
Union Support Recovery in High-Dimensional Multivariate Regression
2008-08-01
view the Lasso as a shrinkage estimator to be compared to traditional least squares or ridge regression ; in this case, it is natural to study the `2... instance , in a hierarchical regression model, groups of regression coefficients may be required to be zero or non-zero in a blockwise manner; for example...Neural Information Processing Systems, 18. MIT Press, Cambridge, MA. Bach, F. (2008). Consistency of the group Lasso and multiple kernel learning
The Allometry of Coarse Root Biomass: Log-Transformed Linear Regression or Nonlinear Regression?
Lai, Jiangshan; Yang, Bo; Lin, Dunmei; Kerkhoff, Andrew J.; Ma, Keping
2013-01-01
Precise estimation of root biomass is important for understanding carbon stocks and dynamics in forests. Traditionally, biomass estimates are based on allometric scaling relationships between stem diameter and coarse root biomass calculated using linear regression (LR) on log-transformed data. Recently, it has been suggested that nonlinear regression (NLR) is a preferable fitting method for scaling relationships. But while this claim has been contested on both theoretical and empirical grounds, and statistical methods have been developed to aid in choosing between the two methods in particular cases, few studies have examined the ramifications of erroneously applying NLR. Here, we use direct measurements of 159 trees belonging to three locally dominant species in east China to compare the LR and NLR models of diameter-root biomass allometry. We then contrast model predictions by estimating stand coarse root biomass based on census data from the nearby 24-ha Gutianshan forest plot and by testing the ability of the models to predict known root biomass values measured on multiple tropical species at the Pasoh Forest Reserve in Malaysia. Based on likelihood estimates for model error distributions, as well as the accuracy of extrapolative predictions, we find that LR on log-transformed data is superior to NLR for fitting diameter-root biomass scaling models. More importantly, inappropriately using NLR leads to grossly inaccurate stand biomass estimates, especially for stands dominated by smaller trees. PMID:24116197
Neither fixed nor random: weighted least squares meta-regression.
Stanley, T D; Doucouliagos, Hristos
2017-03-01
Our study revisits and challenges two core conventional meta-regression estimators: the prevalent use of 'mixed-effects' or random-effects meta-regression analysis and the correction of standard errors that defines fixed-effects meta-regression analysis (FE-MRA). We show how and explain why an unrestricted weighted least squares MRA (WLS-MRA) estimator is superior to conventional random-effects (or mixed-effects) meta-regression when there is publication (or small-sample) bias that is as good as FE-MRA in all cases and better than fixed effects in most practical applications. Simulations and statistical theory show that WLS-MRA provides satisfactory estimates of meta-regression coefficients that are practically equivalent to mixed effects or random effects when there is no publication bias. When there is publication selection bias, WLS-MRA always has smaller bias than mixed effects or random effects. In practical applications, an unrestricted WLS meta-regression is likely to give practically equivalent or superior estimates to fixed-effects, random-effects, and mixed-effects meta-regression approaches. However, random-effects meta-regression remains viable and perhaps somewhat preferable if selection for statistical significance (publication bias) can be ruled out and when random, additive normal heterogeneity is known to directly affect the 'true' regression coefficient. Copyright © 2016 John Wiley & Sons, Ltd.
Compound Identification Using Penalized Linear Regression on Metabolomics
Liu, Ruiqi; Wu, Dongfeng; Zhang, Xiang; Kim, Seongho
2014-01-01
Compound identification is often achieved by matching the experimental mass spectra to the mass spectra stored in a reference library based on mass spectral similarity. Because the number of compounds in the reference library is much larger than the range of mass-to-charge ratio (m/z) values so that the data become high dimensional data suffering from singularity. For this reason, penalized linear regressions such as ridge regression and the lasso are used instead of the ordinary least squares regression. Furthermore, two-step approaches using the dot product and Pearson’s correlation along with the penalized linear regression are proposed in this study. PMID:27212894
Ozonoff, Sally; Williams, Brenda J; Landa, Rebecca
2005-12-01
Most children with autism demonstrate developmental abnormalities in their first year, whereas others display regression after mostly normal development. Few studies have examined the early development of the latter group. This study developed a retrospective measure, the Early Development Questionnaire (EDQ), to collect specific, parent-reported information about development in the first 18 months. Based on their EDQ scores, 60 children with autism between the ages of 3 and 9 were divided into three groups: an early onset group (n = 29), a definite regression group (n = 23), and a heterogeneous mixed group (n = 8). Significant differences in early social development were found between the early onset and regression groups. However, over 50 percent of the children who experienced a regression demonstrated some early social deficits during the first year of life, long before regression and the apparent onset of autism. This group, tentatively labeled 'delays-plus-regression', deserves further study.
Takagi, Daisuke; Ikeda, Ken'ichi; Kawachi, Ichiro
2012-11-01
Crime is an important determinant of public health outcomes, including quality of life, mental well-being, and health behavior. A body of research has documented the association between community social capital and crime victimization. The association between social capital and crime victimization has been examined at multiple levels of spatial aggregation, ranging from entire countries, to states, metropolitan areas, counties, and neighborhoods. In multilevel analysis, the spatial boundaries at level 2 are most often drawn from administrative boundaries (e.g., Census tracts in the U.S.). One problem with adopting administrative definitions of neighborhoods is that it ignores spatial spillover. We conducted a study of social capital and crime victimization in one ward of Tokyo city, using a spatial Durbin model with an inverse-distance weighting matrix that assigned each respondent a unique level of "exposure" to social capital based on all other residents' perceptions. The study is based on a postal questionnaire sent to 20-69 years old residents of Arakawa Ward, Tokyo. The response rate was 43.7%. We examined the contextual influence of generalized trust, perceptions of reciprocity, two types of social network variables, as well as two principal components of social capital (constructed from the above four variables). Our outcome measure was self-reported crime victimization in the last five years. In the spatial Durbin model, we found that neighborhood generalized trust, reciprocity, supportive networks and two principal components of social capital were each inversely associated with crime victimization. By contrast, a multilevel regression performed with the same data (using administrative neighborhood boundaries) found generally null associations between neighborhood social capital and crime. Spatial regression methods may be more appropriate for investigating the contextual influence of social capital in homogeneous cultural settings such as Japan.
A Model for Quadratic Outliers in Linear Regression.
ERIC Educational Resources Information Center
Elashoff, Janet Dixon; Elashoff, Robert M.
This paper introduces a model for describing outliers (observations which are extreme in some sense or violate the apparent pattern of other observations) in linear regression which can be viewed as a mixture of a quadratic and a linear regression. The maximum likelihood estimators of the parameters in the model are derived and their asymptotic…
Strategies for Detecting Outliers in Regression Analysis: An Introductory Primer.
ERIC Educational Resources Information Center
Evans, Victoria P.
Outliers are extreme data points that have the potential to influence statistical analyses. Outlier identification is important to researchers using regression analysis because outliers can influence the model used to such an extent that they seriously distort the conclusions drawn from the data. The effects of outliers on regression analysis are…
Regression Commonality Analysis: A Technique for Quantitative Theory Building
ERIC Educational Resources Information Center
Nimon, Kim; Reio, Thomas G., Jr.
2011-01-01
When it comes to multiple linear regression analysis (MLR), it is common for social and behavioral science researchers to rely predominately on beta weights when evaluating how predictors contribute to a regression model. Presenting an underutilized statistical technique, this article describes how organizational researchers can use commonality…
A SEMIPARAMETRIC BAYESIAN MODEL FOR CIRCULAR-LINEAR REGRESSION
We present a Bayesian approach to regress a circular variable on a linear predictor. The regression coefficients are assumed to have a nonparametric distribution with a Dirichlet process prior. The semiparametric Bayesian approach gives added flexibility to the model and is usefu...
Interpreting Bivariate Regression Coefficients: Going beyond the Average
ERIC Educational Resources Information Center
Halcoussis, Dennis; Phillips, G. Michael
2010-01-01
Statistics, econometrics, investment analysis, and data analysis classes often review the calculation of several types of averages, including the arithmetic mean, geometric mean, harmonic mean, and various weighted averages. This note shows how each of these can be computed using a basic regression framework. By recognizing when a regression model…
Canonical Analysis as a Generalized Regression Technique for Multivariate Analysis.
ERIC Educational Resources Information Center
Williams, John D.
The use of characteristic coding (dummy coding) is made in showing solutions to four multivariate problems using canonical analysis. The canonical variates can be themselves analyzed by the use of multiple linear regression. When the canonical variates are used as criteria in a multiple linear regression, the R2 values are equal to 0, where 0 is…
A Methodology for Generating Placement Rules that Utilizes Logistic Regression
ERIC Educational Resources Information Center
Wurtz, Keith
2008-01-01
The purpose of this article is to provide the necessary tools for institutional researchers to conduct a logistic regression analysis and interpret the results. Aspects of the logistic regression procedure that are necessary to evaluate models are presented and discussed with an emphasis on cutoff values and choosing the appropriate number of…
Multiple Regression in a Two-Way Layout.
ERIC Educational Resources Information Center
Lindley, Dennis V.
This paper discusses Bayesian m-group regression where the groups are arranged in a two-way layout into m rows and n columns, there still being a regression of y on the x's within each group. The mathematical model is then provided as applied to the case where the rows correspond to high schools and the columns to colleges: the predictor variables…
Biases and Standard Errors of Standardized Regression Coefficients
ERIC Educational Resources Information Center
Yuan, Ke-Hai; Chan, Wai
2011-01-01
The paper obtains consistent standard errors (SE) and biases of order O(1/n) for the sample standardized regression coefficients with both random and given predictors. Analytical results indicate that the formulas for SEs given in popular text books are consistent only when the population value of the regression coefficient is zero. The sample…
Moderation analysis using a two-level regression model.
Yuan, Ke-Hai; Cheng, Ying; Maxwell, Scott
2014-10-01
Moderation analysis is widely used in social and behavioral research. The most commonly used model for moderation analysis is moderated multiple regression (MMR) in which the explanatory variables of the regression model include product terms, and the model is typically estimated by least squares (LS). This paper argues for a two-level regression model in which the regression coefficients of a criterion variable on predictors are further regressed on moderator variables. An algorithm for estimating the parameters of the two-level model by normal-distribution-based maximum likelihood (NML) is developed. Formulas for the standard errors (SEs) of the parameter estimates are provided and studied. Results indicate that, when heteroscedasticity exists, NML with the two-level model gives more efficient and more accurate parameter estimates than the LS analysis of the MMR model. When error variances are homoscedastic, NML with the two-level model leads to essentially the same results as LS with the MMR model. Most importantly, the two-level regression model permits estimating the percentage of variance of each regression coefficient that is due to moderator variables. When applied to data from General Social Surveys 1991, NML with the two-level model identified a significant moderation effect of race on the regression of job prestige on years of education while LS with the MMR model did not. An R package is also developed and documented to facilitate the application of the two-level model.
Using partial least squares regression to analyze cellular response data.
Kreeger, Pamela K
2013-04-16
This Teaching Resource provides lecture notes, slides, and a problem set for a lecture introducing the mathematical concepts and interpretation of partial least squares regression (PLSR) that were part of a course entitled "Systems Biology: Mammalian Signaling Networks." PLSR is a multivariate regression technique commonly applied to analyze relationships between signaling or transcriptional data and cellular behavior.
Tutorial on Using Regression Models with Count Outcomes Using R
ERIC Educational Resources Information Center
Beaujean, A. Alexander; Morgan, Grant B.
2016-01-01
Education researchers often study count variables, such as times a student reached a goal, discipline referrals, and absences. Most researchers that study these variables use typical regression methods (i.e., ordinary least-squares) either with or without transforming the count variables. In either case, using typical regression for count data can…
An Importance Sampling EM Algorithm for Latent Regression Models
ERIC Educational Resources Information Center
von Davier, Matthias; Sinharay, Sandip
2007-01-01
Reporting methods used in large-scale assessments such as the National Assessment of Educational Progress (NAEP) rely on latent regression models. To fit the latent regression model using the maximum likelihood estimation technique, multivariate integrals must be evaluated. In the computer program MGROUP used by the Educational Testing Service for…
Stochastic Approximation Methods for Latent Regression Item Response Models
ERIC Educational Resources Information Center
von Davier, Matthias; Sinharay, Sandip
2010-01-01
This article presents an application of a stochastic approximation expectation maximization (EM) algorithm using a Metropolis-Hastings (MH) sampler to estimate the parameters of an item response latent regression model. Latent regression item response models are extensions of item response theory (IRT) to a latent variable model with covariates…
Semisupervised Clustering by Iterative Partition and Regression with Neuroscience Applications.
Qian, Guoqi; Wu, Yuehua; Ferrari, Davide; Qiao, Puxue; Hollande, Frédéric
2016-01-01
Regression clustering is a mixture of unsupervised and supervised statistical learning and data mining method which is found in a wide range of applications including artificial intelligence and neuroscience. It performs unsupervised learning when it clusters the data according to their respective unobserved regression hyperplanes. The method also performs supervised learning when it fits regression hyperplanes to the corresponding data clusters. Applying regression clustering in practice requires means of determining the underlying number of clusters in the data, finding the cluster label of each data point, and estimating the regression coefficients of the model. In this paper, we review the estimation and selection issues in regression clustering with regard to the least squares and robust statistical methods. We also provide a model selection based technique to determine the number of regression clusters underlying the data. We further develop a computing procedure for regression clustering estimation and selection. Finally, simulation studies are presented for assessing the procedure, together with analyzing a real data set on RGB cell marking in neuroscience to illustrate and interpret the method.
Contrasting OLS and Quantile Regression Approaches to Student "Growth" Percentiles
ERIC Educational Resources Information Center
Castellano, Katherine Elizabeth; Ho, Andrew Dean
2013-01-01
Regression methods can locate student test scores in a conditional distribution, given past scores. This article contrasts and clarifies two approaches to describing these locations in terms of readily interpretable percentile ranks or "conditional status percentile ranks." The first is Betebenner's quantile regression approach that results in…
An Effect Size for Regression Predictors in Meta-Analysis
ERIC Educational Resources Information Center
Aloe, Ariel M.; Becker, Betsy Jane
2012-01-01
A new effect size representing the predictive power of an independent variable from a multiple regression model is presented. The index, denoted as r[subscript sp], is the semipartial correlation of the predictor with the outcome of interest. This effect size can be computed when multiple predictor variables are included in the regression model…
Quantile Regression in the Study of Developmental Sciences
ERIC Educational Resources Information Center
Petscher, Yaacov; Logan, Jessica A. R.
2014-01-01
Linear regression analysis is one of the most common techniques applied in developmental research, but only allows for an estimate of the average relations between the predictor(s) and the outcome. This study describes quantile regression, which provides estimates of the relations between the predictor(s) and outcome, but across multiple points of…
The Precision Efficacy Analysis for Regression Sample Size Method.
ERIC Educational Resources Information Center
Brooks, Gordon P.; Barcikowski, Robert S.
The general purpose of this study was to examine the efficiency of the Precision Efficacy Analysis for Regression (PEAR) method for choosing appropriate sample sizes in regression studies used for precision. The PEAR method, which is based on the algebraic manipulation of an accepted cross-validity formula, essentially uses an effect size to…
Using Weighted Least Squares Regression for Obtaining Langmuir Sorption Constants
Technology Transfer Automated Retrieval System (TEKTRAN)
One of the most commonly used models for describing phosphorus (P) sorption to soils is the Langmuir model. To obtain model parameters, the Langmuir model is fit to measured sorption data using least squares regression. Least squares regression is based on several assumptions including normally dist...
Semisupervised Clustering by Iterative Partition and Regression with Neuroscience Applications
Qian, Guoqi; Wu, Yuehua; Ferrari, Davide; Qiao, Puxue; Hollande, Frédéric
2016-01-01
Regression clustering is a mixture of unsupervised and supervised statistical learning and data mining method which is found in a wide range of applications including artificial intelligence and neuroscience. It performs unsupervised learning when it clusters the data according to their respective unobserved regression hyperplanes. The method also performs supervised learning when it fits regression hyperplanes to the corresponding data clusters. Applying regression clustering in practice requires means of determining the underlying number of clusters in the data, finding the cluster label of each data point, and estimating the regression coefficients of the model. In this paper, we review the estimation and selection issues in regression clustering with regard to the least squares and robust statistical methods. We also provide a model selection based technique to determine the number of regression clusters underlying the data. We further develop a computing procedure for regression clustering estimation and selection. Finally, simulation studies are presented for assessing the procedure, together with analyzing a real data set on RGB cell marking in neuroscience to illustrate and interpret the method. PMID:27212939
Identification of high leverage points in binary logistic regression
NASA Astrophysics Data System (ADS)
Fitrianto, Anwar; Wendy, Tham
2016-10-01
Leverage points are those which measures uncommon observations in x space of regression diagnostics. Detection of high leverage points plays a vital role because it is responsible in masking outlier. In regression, high observations which made at extreme in the space of explanatory variables and they are far apart from the average of the data are called as leverage points. In this project, a method for identification of high leverage point in logistic regression was shown using numerical example. We investigate the effects of high leverage point in the logistic regression model. The comparison of the result in the model with and without leverage model is being discussed. Some graphical analyses based on the result of the analysis are presented. We found that the presence of HLP have effect on the hii, estimated probability, estimated coefficients, p-value of variable, odds ratio and regression equation.
Robust regression with asymmetric heavy-tail noise distributions.
Takeuchi, Ichiro; Bengio, Yoshua; Kanamori, Takafumi
2002-10-01
In the presence of a heavy-tail noise distribution, regression becomes much more difficult. Traditional robust regression methods assume that the noise distribution is symmetric, and they downweight the influence of so-called outliers. When the noise distribution is asymmetric, these methods yield biased regression estimators. Motivated by data-mining problems for the insurance industry, we propose a new approach to robust regression tailored to deal with asymmetric noise distribution. The main idea is to learn most of the parameters of the model using conditional quantile estimators (which are biased but robust estimators of the regression) and to learn a few remaining parameters to combine and correct these estimators, to minimize the average squared error in an unbiased way. Theoretical analysis and experiments show the clear advantages of the approach. Results are on artificial data as well as insurance data, using both linear and neural network predictors.
Lima, F S; Greco, L F; Bisinotto, R S; Ribeiro, E S; Martinez, N M; Thatcher, W W; Santos, J E P; Reinhard, M K; Galvão, K N
2015-11-01
Objectives were to determine the effects of intrauterine infusion (IUI) of Trueperella pyogenes on endometrial expression of proinflammatory cytokines and luteal life span. Holstein cows (n = 32) were allocated randomly, in two replicates (15 then 17 cows), to receive one of three treatments on Day 5 of the estrous cycle: TP (n = 13), IUI containing 10(9) colony-forming units/mL of T. pyogenes; tumor necrosis factor (TNF; n = 9), IUI containing 1 μg of TNFα; and control (n = 10), IUI of saline solution. Five cows per treatment had uterine biopsies collected at 6, 12, and 24 hours after treatment to evaluate the endometrial messenger RNA expression of TNFα (TNF), interleukin-1β (IL1B), IL6, IL8, prostaglandin E synthase (PGES), prostaglandin F synthase (PGFS), and oxytocin receptor (OXR), and histologic evidence of inflammation. Messenger RNA expression was measured using quantitative reverse transcription polymerase chain reaction. The remaining cows had ovaries scanned and blood collected for progesterone evaluation; however, only seven, four, and three cows in the TP, TNF, and control groups were used for comparison in replicate 2. The GLIMMIX procedure of SAS was used for statistical analysis. All TP and TNF cows had moderate to severe endometrial inflammation, whereas only one control had mild inflammation. Premature luteolysis occurred in three, one, and zero cows in the TP, TNF and control groups, respectively. Delayed luteolysis occurred in one TP and one TNF cow. Interleukin-1β expression was greater in the TP cows than in the TNF cows at 24 hours after IUI. Moreover, IL6 expression tended to be greater for the TP cows than for the control cows at 12 hours after IUI. Interleukin 8 expression was greater in the TP cows than in the control and TNF cows at 24 hours after IUI. Oxytocin receptor expression tended to be greater for the TP cows and was greater for the TNF cows than for the control cows at 12 hours. The messenger RNA expressions of TNF, PGES
ERIC Educational Resources Information Center
Koon, Sharon; Petscher, Yaacov
2015-01-01
The purpose of this report was to explicate the use of logistic regression and classification and regression tree (CART) analysis in the development of early warning systems. It was motivated by state education leaders' interest in maintaining high classification accuracy while simultaneously improving practitioner understanding of the rules by…
ERIC Educational Resources Information Center
Crawford, John R.; Garthwaite, Paul H.; Denham, Annie K.; Chelune, Gordon J.
2012-01-01
Regression equations have many useful roles in psychological assessment. Moreover, there is a large reservoir of published data that could be used to build regression equations; these equations could then be employed to test a wide variety of hypotheses concerning the functioning of individual cases. This resource is currently underused because…
Background stratified Poisson regression analysis of cohort data.
Richardson, David B; Langholz, Bryan
2012-03-01
Background stratified Poisson regression is an approach that has been used in the analysis of data derived from a variety of epidemiologically important studies of radiation-exposed populations, including uranium miners, nuclear industry workers, and atomic bomb survivors. We describe a novel approach to fit Poisson regression models that adjust for a set of covariates through background stratification while directly estimating the radiation-disease association of primary interest. The approach makes use of an expression for the Poisson likelihood that treats the coefficients for stratum-specific indicator variables as 'nuisance' variables and avoids the need to explicitly estimate the coefficients for these stratum-specific parameters. Log-linear models, as well as other general relative rate models, are accommodated. This approach is illustrated using data from the Life Span Study of Japanese atomic bomb survivors and data from a study of underground uranium miners. The point estimate and confidence interval obtained from this 'conditional' regression approach are identical to the values obtained using unconditional Poisson regression with model terms for each background stratum. Moreover, it is shown that the proposed approach allows estimation of background stratified Poisson regression models of non-standard form, such as models that parameterize latency effects, as well as regression models in which the number of strata is large, thereby overcoming the limitations of previously available statistical software for fitting background stratified Poisson regression models.
Physiological capillary regression is not dependent on reducing VEGF expression
Olfert, I. Mark
2015-01-01
Investigations into physiologically-controlled capillary regression report the provocative finding that microvessel regression occurs in the face of persistent elevation of skeletal muscle vascular endothelial growth factor-A (VEGF) expression. Thrombospondin-1 (TSP-1), a negative angiogenic regulator, is increasingly being observed to temporally correlate with capillary regression, suggesting that increased TSP-1 (and not reduction in VEGF per se) is needed to initiate, and likely regulate, capillary regression. Based on evidence being gleaned from physiologically-mediated regression of capillaries, it needs to be recognized that capillary regression (and perhaps capillary rarefaction with disease) is not simply the reversal of factors used to stimulate angiogenesis. Rather, the conceptual understanding that angiogenesis and capillary regression each have specific and unique requirements that are biologically constrained to opposite sides of the balance between positive and negative angioregulatory factors may shed light on why anti-VEGF therapies have not lived up to the promise in reversing angiogenesis and providing the cure that many had hoped toward fighting cancer. Emerging evidence from physiological controlled angiogenesis suggest that cases involving excessive or uncontrolled capillary expansion may be best treated by therapies designed to increase expression of negative angiogenic regulators, whereas those involving capillary rarefaction may benefit from inhibiting negative regulators (like TSP-1). PMID:26660949
1995-01-01
Tumor necrosis factor (TNF) alpha participates in the regulation of the acute-phase, immune, and inflammatory responses. Target genes known to be transcriptionally activated by TNF-alpha include the granulocyte (G)- colony-stimulating factor (CSF) gene, the granulocyte/macrophage (GM)- CSF gene, as well as the interleukin (IL) 6 gene. Functional nuclear factor (NF)-IL6 recognition sites have been identified in regulatory regions of these genes by transient transfection studies using deleted promoter constructs. In addition, NF-IL6 is known to form heterodimeric complexes with the NF-kappa B transcription factor, which is also engaged in the transcriptional regulation of these genes. The indispensable importance of NF-IL6 for regulating gene expression of proinflammatory cytokine genes in response to inflammatory stimuli in vivo remains, however, unclear. We here report, by using both antisense (AS) oligodesoxyribonucleotide (ODN) and ribozyme (RZ)-mediated specific elimination of NF-IL6 transcripts in human fibroblasts, that TNF-alpha-induced synthesis of G-CSF, but not of GM-CSF or IL-6, is abolished in the absence of functional NF-IL6 in vivo. Both AS ODN and RZ targeting of the NF-IL6 transcript eliminate NF-IL6 protein, as shown in Western blot analysis and electrophoretic mobility shift assays. Similarly, fibroblasts exposed to either the AS NF-IL6 ODN or the NF-IL6 RZ, but not to the sense or nonsense ODN or a mutated ribozyme, also failed to respond with functional activation of NF-IL6 as assayed in transient transfection studies using heterologous promoter constructs harboring the NF-IL6 recognition site. In contrast, protein synthesis, DNA-binding activity, and transcriptional activation capacity of the NF-kappa B transcription factor is not impaired upon exposure to either ODN or RZ. Fibroblasts that had been cultured in the presence of the AS NF-IL6 ODN or the NF-IL6RZ failed to synthesize G- CSF protein in response to TNF-alpha, while TNF-alpha-inducible
Spontaneous Regression and Recurrence of a Tumefactive Perivascular Space
Muttikkal, Thomas Jose Eluvathingal; Raghavan, Prashant
2014-01-01
Summary Perivascular spaces can occasionally appear mass-like (tumefactive or giant perivascular space), and can be associated with clinical symptoms. Spontaneous regression of a tumefactive perivascular space is a very rare phenomenon with only two reported cases in the English medical literature. Spontaneous regression of a tumefactive perivascular space along with resolution of clinical symptoms, followed by spontaneous recurrence associated with symptom recurrence is an extremely rare occurrence, which to the best of our knowledge, has not been reported in the medical literature. We describe a case of spontaneous regression of a tumefactive perivascular space, three years after its initial detection, followed by spontaneous recurrence after two years. PMID:24750709
Reducing geometric dilution of precision using ridge regression signal processing
NASA Astrophysics Data System (ADS)
Kelly, R. J.
The authors propose a method for reducing the effects of GDOP (geometric dilution of precision) in position-fix navigation systems. The idea is to incorporate ridge regression into the aircraft navigation signal processor. MSE (mean square error) performance of an ordinary LMS (least mean square) signal processor was compared with one using ridge regression. Computer simulations confirmed the theory that variance inflation caused by GDOP can be measurably reduced by the ridge regression algorithm. The technique is applicable not only to DME/DME (distance measuring equipment) and GPS but applies also to any position-fix navigation aid, e.g. Loran-C, Omega, and JTIDS relative navigation.
[Unconditioned logistic regression and sample size: a bibliographic review].
Ortega Calvo, Manuel; Cayuela Domínguez, Aurelio
2002-01-01
Unconditioned logistic regression is a highly useful risk prediction method in epidemiology. This article reviews the different solutions provided by different authors concerning the interface between the calculation of the sample size and the use of logistics regression. Based on the knowledge of the information initially provided, a review is made of the customized regression and predictive constriction phenomenon, the design of an ordinal exposition with a binary output, the event of interest per variable concept, the indicator variables, the classic Freeman equation, etc. Some skeptical ideas regarding this subject are also included.
Comparison of regression modeling techniques for resource estimation
NASA Technical Reports Server (NTRS)
Card, D. N.
1983-01-01
The development and validation of resource utilization models is an active area of software engineering research. Regression analysis is the principal tool employed in these studies. However, little attention was given to determining which of the various regression methods available is the most appropriate. The objective of the study is to compare three alternative regession procedures by examining the results of their application to one commonly accepted equations for resource estimation. The data studied was summarized, the resource estimation equation was described, the regression procedures were explained, and the results obtained from the proceures were compared.
Linear regression analysis of survival data with missing censoring indicators
Wang, Qihua
2010-01-01
Linear regression analysis has been studied extensively in a random censorship setting, but typically all of the censoring indicators are assumed to be observed. In this paper, we develop synthetic data methods for estimating regression parameters in a linear model when some censoring indicators are missing. We define estimators based on regression calibration, imputation, and inverse probability weighting techniques, and we prove all three estimators are asymptotically normal. The finite-sample performance of each estimator is evaluated via simulation. We illustrate our methods by assessing the effects of sex and age on the time to non-ambulatory progression for patients in a brain cancer clinical trial. PMID:20559722
Quantiles Regression Approach to Identifying the Determinant of Breastfeeding Duration
NASA Astrophysics Data System (ADS)
Mahdiyah; Norsiah Mohamed, Wan; Ibrahim, Kamarulzaman
In this study, quantiles regression approach is applied to the data of Malaysian Family Life Survey (MFLS), to identify factors which are significantly related to the different conditional quantiles of the breastfeeding duration. It is known that the classical linear regression methods are based on minimizing residual sum of squared, but quantiles regression use a mechanism which are based on the conditional median function and the full range of other conditional quantile functions. Overall, it is found that the period of breastfeeding is significantly related to place of living, religion and total number of children in the family.
Preserving Institutional Privacy in Distributed binary Logistic Regression.
Wu, Yuan; Jiang, Xiaoqian; Ohno-Machado, Lucila
2012-01-01
Privacy is becoming a major concern when sharing biomedical data across institutions. Although methods for protecting privacy of individual patients have been proposed, it is not clear how to protect the institutional privacy, which is many times a critical concern of data custodians. Built upon our previous work, Grid Binary LOgistic REgression (GLORE)1, we developed an Institutional Privacy-preserving Distributed binary Logistic Regression model (IPDLR) that considers both individual and institutional privacy for building a logistic regression model in a distributed manner. We tested our method using both simulated and clinical data, showing how it is possible to protect the privacy of individuals and of institutions using a distributed strategy.
Using ridge regression in systematic pointing error corrections
NASA Technical Reports Server (NTRS)
Guiar, C. N.
1988-01-01
A pointing error model is used in the antenna calibration process. Data from spacecraft or radio star observations are used to determine the parameters in the model. However, the regression variables are not truly independent, displaying a condition known as multicollinearity. Ridge regression, a biased estimation technique, is used to combat the multicollinearity problem. Two data sets pertaining to Voyager 1 spacecraft tracking (days 105 and 106 of 1987) were analyzed using both linear least squares and ridge regression methods. The advantages and limitations of employing the technique are presented. The problem is not yet fully resolved.
Spontaneous regression of congenital cutaneous hemangiomas in a calf.
Priestnall, S L; De Bellis, F; Bond, R; Alony-Gilboa, Y; Summers, B A
2010-03-01
Congenital vascular tumors of the skin have been described in people and a few animals, but unlike infantile hemangiomas in children, spontaneous regression has not been described in animals. A 2-day-old male Belgian Blue cross calf was presented for multiple congenital cutaneous masses that were soft, alopecic, and hyperemic; the calf had no other apparent abnormalities. Two weeks later, one mass had regressed. Surgical excision of one of the remaining masses was performed; histopathologic and immunohistochemical findings were considered diagnostic for epithelioid hemangioma. Eight months following initial presentation, all the masses had regressed spontaneously. This constitutes the first account in the veterinary literature of spontaneous regression in a congenital vascular tumor.
Large unbalanced credit scoring using Lasso-logistic regression ensemble.
Wang, Hong; Xu, Qingsong; Zhou, Lifeng
2015-01-01
Recently, various ensemble learning methods with different base classifiers have been proposed for credit scoring problems. However, for various reasons, there has been little research using logistic regression as the base classifier. In this paper, given large unbalanced data, we consider the plausibility of ensemble learning using regularized logistic regression as the base classifier to deal with credit scoring problems. In this research, the data is first balanced and diversified by clustering and bagging algorithms. Then we apply a Lasso-logistic regression learning ensemble to evaluate the credit risks. We show that the proposed algorithm outperforms popular credit scoring models such as decision tree, Lasso-logistic regression and random forests in terms of AUC and F-measure. We also provide two importance measures for the proposed model to identify important variables in the data.
Joint regression analysis of correlated data using Gaussian copulas.
Song, Peter X-K; Li, Mingyao; Yuan, Ying
2009-03-01
This article concerns a new joint modeling approach for correlated data analysis. Utilizing Gaussian copulas, we present a unified and flexible machinery to integrate separate one-dimensional generalized linear models (GLMs) into a joint regression analysis of continuous, discrete, and mixed correlated outcomes. This essentially leads to a multivariate analogue of the univariate GLM theory and hence an efficiency gain in the estimation of regression coefficients. The availability of joint probability models enables us to develop a full maximum likelihood inference. Numerical illustrations are focused on regression models for discrete correlated data, including multidimensional logistic regression models and a joint model for mixed normal and binary outcomes. In the simulation studies, the proposed copula-based joint model is compared to the popular generalized estimating equations, which is a moment-based estimating equation method to join univariate GLMs. Two real-world data examples are used in the illustration.
Estimating the exceedance probability of rain rate by logistic regression
NASA Technical Reports Server (NTRS)
Chiu, Long S.; Kedem, Benjamin
1990-01-01
Recent studies have shown that the fraction of an area with rain intensity above a fixed threshold is highly correlated with the area-averaged rain rate. To estimate the fractional rainy area, a logistic regression model, which estimates the conditional probability that rain rate over an area exceeds a fixed threshold given the values of related covariates, is developed. The problem of dependency in the data in the estimation procedure is bypassed by the method of partial likelihood. Analyses of simulated scanning multichannel microwave radiometer and observed electrically scanning microwave radiometer data during the Global Atlantic Tropical Experiment period show that the use of logistic regression in pixel classification is superior to multiple regression in predicting whether rain rate at each pixel exceeds a given threshold, even in the presence of noisy data. The potential of the logistic regression technique in satellite rain rate estimation is discussed.
MODELING SNAKE MICROHABITAT FROM RADIOTELEMETRY STUDIES USING POLYTOMOUS LOGISTIC REGRESSION
Multivariate analysis of snake microhabitat has historically used techniques that were derived under assumptions of normality and common covariance structure (e.g., discriminant function analysis, MANOVA). In this study, polytomous logistic regression (PLR which does not require ...
Hierarchical regression for epidemiologic analyses of multiple exposures
Greenland, S.
1994-11-01
Many epidemiologic investigations are designed to study the effects of multiple exposures. Most of these studies are analyzed either by fitting a risk-regression model with all exposures forced in the model, or by using a preliminary-testing algorithm, such as stepwise regression, to produce a smaller model. Research indicates that hierarchical modeling methods can outperform these conventional approaches. These methods are reviewed and compared to two hierarchical methods, empirical-Bayes regression and a variant here called {open_quotes}semi-Bayes{close_quotes} regression, to full-model maximum likelihood and to model reduction by preliminary testing. The performance of the methods in a problem of predicting neonatal-mortality rates are compared. Based on the literature to date, it is suggested that hierarchical methods should become part of the standard approaches to multiple-exposure studies. 35 refs., 1 fig., 1 tab.
Large Unbalanced Credit Scoring Using Lasso-Logistic Regression Ensemble
Wang, Hong; Xu, Qingsong; Zhou, Lifeng
2015-01-01
Recently, various ensemble learning methods with different base classifiers have been proposed for credit scoring problems. However, for various reasons, there has been little research using logistic regression as the base classifier. In this paper, given large unbalanced data, we consider the plausibility of ensemble learning using regularized logistic regression as the base classifier to deal with credit scoring problems. In this research, the data is first balanced and diversified by clustering and bagging algorithms. Then we apply a Lasso-logistic regression learning ensemble to evaluate the credit risks. We show that the proposed algorithm outperforms popular credit scoring models such as decision tree, Lasso-logistic regression and random forests in terms of AUC and F-measure. We also provide two importance measures for the proposed model to identify important variables in the data. PMID:25706988
Kernel Partial Least Squares for Nonlinear Regression and Discrimination
NASA Technical Reports Server (NTRS)
Rosipal, Roman; Clancy, Daniel (Technical Monitor)
2002-01-01
This paper summarizes recent results on applying the method of partial least squares (PLS) in a reproducing kernel Hilbert space (RKHS). A previously proposed kernel PLS regression model was proven to be competitive with other regularized regression methods in RKHS. The family of nonlinear kernel-based PLS models is extended by considering the kernel PLS method for discrimination. Theoretical and experimental results on a two-class discrimination problem indicate usefulness of the method.
Multiple regression analyses in clinical child and adolescent psychology.
Jaccard, James; Guilamo-Ramos, Vincent; Johansson, Margaret; Bouris, Alida
2006-09-01
A major form of data analysis in clinical child and adolescent psychology is multiple regression. This article reviews issues in the application of such methods in light of the research designs typical of this field. Issues addressed include controlling covariates, evaluation of predictor relevance, comparing predictors, analysis of moderation, analysis of mediation, assumption violations, outliers, limited dependent variables, and directed regression and its relation to structural equation modeling. Analytic guidelines are provided within each domain.
3D Regression Heat Map Analysis of Population Study Data.
Klemm, Paul; Lawonn, Kai; Glaßer, Sylvia; Niemann, Uli; Hegenscheid, Katrin; Völzke, Henry; Preim, Bernhard
2016-01-01
Epidemiological studies comprise heterogeneous data about a subject group to define disease-specific risk factors. These data contain information (features) about a subject's lifestyle, medical status as well as medical image data. Statistical regression analysis is used to evaluate these features and to identify feature combinations indicating a disease (the target feature). We propose an analysis approach of epidemiological data sets by incorporating all features in an exhaustive regression-based analysis. This approach combines all independent features w.r.t. a target feature. It provides a visualization that reveals insights into the data by highlighting relationships. The 3D Regression Heat Map, a novel 3D visual encoding, acts as an overview of the whole data set. It shows all combinations of two to three independent features with a specific target disease. Slicing through the 3D Regression Heat Map allows for the detailed analysis of the underlying relationships. Expert knowledge about disease-specific hypotheses can be included into the analysis by adjusting the regression model formulas. Furthermore, the influences of features can be assessed using a difference view comparing different calculation results. We applied our 3D Regression Heat Map method to a hepatic steatosis data set to reproduce results from a data mining-driven analysis. A qualitative analysis was conducted on a breast density data set. We were able to derive new hypotheses about relations between breast density and breast lesions with breast cancer. With the 3D Regression Heat Map, we present a visual overview of epidemiological data that allows for the first time an interactive regression-based analysis of large feature sets with respect to a disease.
Robust regression on noisy data for fusion scaling laws
Verdoolaege, Geert
2014-11-15
We introduce the method of geodesic least squares (GLS) regression for estimating fusion scaling laws. Based on straightforward principles, the method is easily implemented, yet it clearly outperforms established regression techniques, particularly in cases of significant uncertainty on both the response and predictor variables. We apply GLS for estimating the scaling of the L-H power threshold, resulting in estimates for ITER that are somewhat higher than predicted earlier.
Iris movement mediates vascular apoptosis during rat pupillary membrane regression.
Morizane, Yuki; Mohri, Satoshi; Kosaka, Jun; Toné, Shigenobu; Kiyooka, Takahiko; Miyasaka, Takehiro; Shimizu, Juichiro; Ogasawara, Yasuo; Shiraga, Fumio; Minatogawa, Yohsuke; Sasaki, Junzo; Ohtsuki, Hiroshi; Kajiya, Fumihiko
2006-03-01
In the course of mammalian lens development, a transient capillary meshwork known as the pupillary membrane (PM) forms, which is located at the pupil area; the PM nourishes the anterior surface of the lens and then regresses to make the optical path clear. Although the involvement of apoptotic process has been reported in the PM regression, the initiating factor remains unknown. We initially found that regression of the PM coincided with the development of iris motility, and iris movement caused cessation and resumption of blood flow within the PM. Therefore, we investigated whether the development of the iris's ability to constrict and dilate functions as an essential signal that induces apoptosis in the PM. Continuous inhibition of iris movement with mydriatic agents from postnatal day 7 to day 12 suppressed apoptosis of the PM and migration of macrophage toward the PM, and resulted in the persistence of PM in rats. The distribution of apoptotic cells in the regressing PM was diffuse and showed no apparent localization. These results indicated that iris movement induced regression of the PM by changing the blood flow within it. This study suggests the importance of the physiological interactions between tissues-in this case, the iris and the PM-as a signal to advance vascular regression during organ development, and defines a novel function of the iris during ocular development in addition to the well-known function, that is, optimization of light transmission into the eye.
Bootstrap Enhanced Penalized Regression for Variable Selection with Neuroimaging Data
Abram, Samantha V.; Helwig, Nathaniel E.; Moodie, Craig A.; DeYoung, Colin G.; MacDonald, Angus W.; Waller, Niels G.
2016-01-01
Recent advances in fMRI research highlight the use of multivariate methods for examining whole-brain connectivity. Complementary data-driven methods are needed for determining the subset of predictors related to individual differences. Although commonly used for this purpose, ordinary least squares (OLS) regression may not be ideal due to multi-collinearity and over-fitting issues. Penalized regression is a promising and underutilized alternative to OLS regression. In this paper, we propose a nonparametric bootstrap quantile (QNT) approach for variable selection with neuroimaging data. We use real and simulated data, as well as annotated R code, to demonstrate the benefits of our proposed method. Our results illustrate the practical potential of our proposed bootstrap QNT approach. Our real data example demonstrates how our method can be used to relate individual differences in neural network connectivity with an externalizing personality measure. Also, our simulation results reveal that the QNT method is effective under a variety of data conditions. Penalized regression yields more stable estimates and sparser models than OLS regression in situations with large numbers of highly correlated neural predictors. Our results demonstrate that penalized regression is a promising method for examining associations between neural predictors and clinically relevant traits or behaviors. These findings have important implications for the growing field of functional connectivity research, where multivariate methods produce numerous, highly correlated brain networks. PMID:27516732
Kernel regression for fMRI pattern prediction
Chu, Carlton; Ni, Yizhao; Tan, Geoffrey; Saunders, Craig J.; Ashburner, John
2011-01-01
This paper introduces two kernel-based regression schemes to decode or predict brain states from functional brain scans as part of the Pittsburgh Brain Activity Interpretation Competition (PBAIC) 2007, in which our team was awarded first place. Our procedure involved image realignment, spatial smoothing, detrending of low-frequency drifts, and application of multivariate linear and non-linear kernel regression methods: namely kernel ridge regression (KRR) and relevance vector regression (RVR). RVR is based on a Bayesian framework, which automatically determines a sparse solution through maximization of marginal likelihood. KRR is the dual-form formulation of ridge regression, which solves regression problems with high dimensional data in a computationally efficient way. Feature selection based on prior knowledge about human brain function was also used. Post-processing by constrained deconvolution and re-convolution was used to furnish the prediction. This paper also contains a detailed description of how prior knowledge was used to fine tune predictions of specific “feature ratings,” which we believe is one of the key factors in our prediction accuracy. The impact of pre-processing was also evaluated, demonstrating that different pre-processing may lead to significantly different accuracies. Although the original work was aimed at the PBAIC, many techniques described in this paper can be generally applied to any fMRI decoding works to increase the prediction accuracy. PMID:20348000
Learning a Nonnegative Sparse Graph for Linear Regression.
Fang, Xiaozhao; Xu, Yong; Li, Xuelong; Lai, Zhihui; Wong, Wai Keung
2015-09-01
Previous graph-based semisupervised learning (G-SSL) methods have the following drawbacks: 1) they usually predefine the graph structure and then use it to perform label prediction, which cannot guarantee an overall optimum and 2) they only focus on the label prediction or the graph structure construction but are not competent in handling new samples. To this end, a novel nonnegative sparse graph (NNSG) learning method was first proposed. Then, both the label prediction and projection learning were integrated into linear regression. Finally, the linear regression and graph structure learning were unified within the same framework to overcome these two drawbacks. Therefore, a novel method, named learning a NNSG for linear regression was presented, in which the linear regression and graph learning were simultaneously performed to guarantee an overall optimum. In the learning process, the label information can be accurately propagated via the graph structure so that the linear regression can learn a discriminative projection to better fit sample labels and accurately classify new samples. An effective algorithm was designed to solve the corresponding optimization problem with fast convergence. Furthermore, NNSG provides a unified perceptiveness for a number of graph-based learning methods and linear regression methods. The experimental results showed that NNSG can obtain very high classification accuracy and greatly outperforms conventional G-SSL methods, especially some conventional graph construction methods.
Descriptor Learning via Supervised Manifold Regularization for Multioutput Regression.
Zhen, Xiantong; Yu, Mengyang; Islam, Ali; Bhaduri, Mousumi; Chan, Ian; Li, Shuo
2016-06-08
Multioutput regression has recently shown great ability to solve challenging problems in both computer vision and medical image analysis. However, due to the huge image variability and ambiguity, it is fundamentally challenging to handle the highly complex input-target relationship of multioutput regression, especially with indiscriminate high-dimensional representations. In this paper, we propose a novel supervised descriptor learning (SDL) algorithm for multioutput regression, which can establish discriminative and compact feature representations to improve the multivariate estimation performance. The SDL is formulated as generalized low-rank approximations of matrices with a supervised manifold regularization. The SDL is able to simultaneously extract discriminative features closely related to multivariate targets and remove irrelevant and redundant information by transforming raw features into a new low-dimensional space aligned to targets. The achieved discriminative while compact descriptor largely reduces the variability and ambiguity for multioutput regression, which enables more accurate and efficient multivariate estimation. We conduct extensive evaluation of the proposed SDL on both synthetic data and real-world multioutput regression tasks for both computer vision and medical image analysis. Experimental results have shown that the proposed SDL can achieve high multivariate estimation accuracy on all tasks and largely outperforms the algorithms in the state of the arts. Our method establishes a novel SDL framework for multioutput regression, which can be widely used to boost the performance in different applications.
Direction of Effects in Multiple Linear Regression Models.
Wiedermann, Wolfgang; von Eye, Alexander
2015-01-01
Previous studies analyzed asymmetric properties of the Pearson correlation coefficient using higher than second order moments. These asymmetric properties can be used to determine the direction of dependence in a linear regression setting (i.e., establish which of two variables is more likely to be on the outcome side) within the framework of cross-sectional observational data. Extant approaches are restricted to the bivariate regression case. The present contribution extends the direction of dependence methodology to a multiple linear regression setting by analyzing distributional properties of residuals of competing multiple regression models. It is shown that, under certain conditions, the third central moments of estimated regression residuals can be used to decide upon direction of effects. In addition, three different approaches for statistical inference are discussed: a combined D'Agostino normality test, a skewness difference test, and a bootstrap difference test. Type I error and power of the procedures are assessed using Monte Carlo simulations, and an empirical example is provided for illustrative purposes. In the discussion, issues concerning the quality of psychological data, possible extensions of the proposed methods to the fourth central moment of regression residuals, and potential applications are addressed.
Quantum regression theorem and non-Markovianity of quantum dynamics
NASA Astrophysics Data System (ADS)
Guarnieri, Giacomo; Smirne, Andrea; Vacchini, Bassano
2014-08-01
We explore the connection between two recently introduced notions of non-Markovian quantum dynamics and the validity of the so-called quantum regression theorem. While non-Markovianity of a quantum dynamics has been defined looking at the behavior in time of the statistical operator, which determines the evolution of mean values, the quantum regression theorem makes statements about the behavior of system correlation functions of order two and higher. The comparison relies on an estimate of the validity of the quantum regression hypothesis, which can be obtained exactly evaluating two-point correlation functions. To this aim we consider a qubit undergoing dephasing due to interaction with a bosonic bath, comparing the exact evaluation of the non-Markovianity measures with the violation of the quantum regression theorem for a class of spectral densities. We further study a photonic dephasing model, recently exploited for the experimental measurement of non-Markovianity. It appears that while a non-Markovian dynamics according to either definition brings with itself violation of the regression hypothesis, even Markovian dynamics can lead to a failure of the regression relation.
Solid-fuel regression during ignition transient in a ramjet
Yang, J.T.; Wu, C.Y.Y.
1994-12-31
The transient regression and ignition of a solid fuel in a hot-oxidizing flow in a simulated combustor of a solid-fuel ramjet (SFRJ) were experimentally investigated. The local regression of solid fuel was measured at various intervals before ignition, and the controlled variables of the experiments were the inlet flow velocity, gas temperature, oxygen content, and step height. The maximum regression was located at 5.0--5.5 step heights from the entrance. The results of regression tests indicate that the influence of heat transfer was more important than the flow structure of the separated-reattaching flow. The regression rate increased with increasing the flow temperature and mass flow rate but decreased with increasing step height. The oxygen content had no significant influence on the regression before ignition. The transport phenomena in the combustor before ignition were closely related to the ignition mechanisms, which were diffusion control and chemical kinetics control. Diffusion control applied in the region of oxygen concentration greater than 20%, and the ignition delay decreased as pyrolyzed fuel vapor increased during the preignition period. Chemical kinetics control applied in the region of oxygen concentration less than 15%, and the flow feature of flame stabilization was more important than pyrolysis for decreasing the ignition delay.
Wilcox, Rand R
2013-04-01
It is well known that the ordinary least squares (OLS) regression estimator is not robust. Many robust regression estimators have been proposed and inferential methods based on these estimators have been derived. However, for two independent groups, let θj (X) be some conditional measure of location for the jth group, given X, based on some robust regression estimator. An issue that has not been addressed is computing a 1 - α confidence interval for θ1(X) - θ2(X) in a manner that allows both within group and between group hetereoscedasticity. The paper reports the finite sample properties of a simple method for accomplishing this goal. Simulations indicate that, in terms of controlling the probability of a Type I error, the method performs very well for a wide range of situations, even with a relatively small sample size. In principle, any robust regression estimator can be used. The simulations are focused primarily on the Theil-Sen estimator, but some results using Yohai's MM-estimator, as well as the Koenker and Bassett quantile regression estimator, are noted. Data from the Well Elderly II study, dealing with measures of meaningful activity using the cortisol awakening response as a covariate, are used to illustrate that the choice between an extant method based on a nonparametric regression estimator, and the method suggested here, can make a practical difference.
Crawford, John R; Garthwaite, Paul H; Denham, Annie K; Chelune, Gordon J
2012-12-01
Regression equations have many useful roles in psychological assessment. Moreover, there is a large reservoir of published data that could be used to build regression equations; these equations could then be employed to test a wide variety of hypotheses concerning the functioning of individual cases. This resource is currently underused because (a) not all psychologists are aware that regression equations can be built not only from raw data but also using only basic summary data for a sample, and (b) the computations involved are tedious and prone to error. In an attempt to overcome these barriers, Crawford and Garthwaite (2007) provided methods to build and apply simple linear regression models using summary statistics as data. In the present study, we extend this work to set out the steps required to build multiple regression models from sample summary statistics and the further steps required to compute the associated statistics for drawing inferences concerning an individual case. We also develop, describe, and make available a computer program that implements these methods. Although there are caveats associated with the use of the methods, these need to be balanced against pragmatic considerations and against the alternative of either entirely ignoring a pertinent data set or using it informally to provide a clinical "guesstimate." Upgraded versions of earlier programs for regression in the single case are also provided; these add the point and interval estimates of effect size developed in the present article.
NASA Astrophysics Data System (ADS)
Haddad, Khaled; Rahman, Ataur
2012-04-01
SummaryIn this article, an approach using Bayesian Generalised Least Squares (BGLS) regression in a region-of-influence (ROI) framework is proposed for regional flood frequency analysis (RFFA) for ungauged catchments. Using the data from 399 catchments in eastern Australia, the BGLS-ROI is constructed to regionalise the flood quantiles (Quantile Regression Technique (QRT)) and the first three moments of the log-Pearson type 3 (LP3) distribution (Parameter Regression Technique (PRT)). This scheme firstly develops a fixed region model to select the best set of predictor variables for use in the subsequent regression analyses using an approach that minimises the model error variance while also satisfying a number of statistical selection criteria. The identified optimal regression equation is then used in the ROI experiment where the ROI is chosen for a site in question as the region that minimises the predictive uncertainty. To evaluate the overall performances of the quantiles estimated by the QRT and PRT, a one-at-a-time cross-validation procedure is applied. Results of the proposed method indicate that both the QRT and PRT in a BGLS-ROI framework lead to more accurate and reliable estimates of flood quantiles and moments of the LP3 distribution when compared to a fixed region approach. Also the BGLS-ROI can deal reasonably well with the heterogeneity in Australian catchments as evidenced by the regression diagnostics. Based on the evaluation statistics it was found that both BGLS-QRT and PRT-ROI perform similarly well, which suggests that the PRT is a viable alternative to QRT in RFFA. The RFFA methods developed in this paper is based on the database available in eastern Australia. It is expected that availability of a more comprehensive database (in terms of both quality and quantity) will further improve the predictive performance of both the fixed and ROI based RFFA methods presented in this study, which however needs to be investigated in future when such a
Use of probabilistic weights to enhance linear regression myoelectric control
NASA Astrophysics Data System (ADS)
Smith, Lauren H.; Kuiken, Todd A.; Hargrove, Levi J.
2015-12-01
Objective. Clinically available prostheses for transradial amputees do not allow simultaneous myoelectric control of degrees of freedom (DOFs). Linear regression methods can provide simultaneous myoelectric control, but frequently also result in difficulty with isolating individual DOFs when desired. This study evaluated the potential of using probabilistic estimates of categories of gross prosthesis movement, which are commonly used in classification-based myoelectric control, to enhance linear regression myoelectric control. Approach. Gaussian models were fit to electromyogram (EMG) feature distributions for three movement classes at each DOF (no movement, or movement in either direction) and used to weight the output of linear regression models by the probability that the user intended the movement. Eight able-bodied and two transradial amputee subjects worked in a virtual Fitts’ law task to evaluate differences in controllability between linear regression and probability-weighted regression for an intramuscular EMG-based three-DOF wrist and hand system. Main results. Real-time and offline analyses in able-bodied subjects demonstrated that probability weighting improved performance during single-DOF tasks (p < 0.05) by preventing extraneous movement at additional DOFs. Similar results were seen in experiments with two transradial amputees. Though goodness-of-fit evaluations suggested that the EMG feature distributions showed some deviations from the Gaussian, equal-covariance assumptions used in this experiment, the assumptions were sufficiently met to provide improved performance compared to linear regression control. Significance. Use of probability weights can improve the ability to isolate individual during linear regression myoelectric control, while maintaining the ability to simultaneously control multiple DOFs.
Analysis of Sting Balance Calibration Data Using Optimized Regression Models
NASA Technical Reports Server (NTRS)
Ulbrich, N.; Bader, Jon B.
2010-01-01
Calibration data of a wind tunnel sting balance was processed using a candidate math model search algorithm that recommends an optimized regression model for the data analysis. During the calibration the normal force and the moment at the balance moment center were selected as independent calibration variables. The sting balance itself had two moment gages. Therefore, after analyzing the connection between calibration loads and gage outputs, it was decided to choose the difference and the sum of the gage outputs as the two responses that best describe the behavior of the balance. The math model search algorithm was applied to these two responses. An optimized regression model was obtained for each response. Classical strain gage balance load transformations and the equations of the deflection of a cantilever beam under load are used to show that the search algorithm s two optimized regression models are supported by a theoretical analysis of the relationship between the applied calibration loads and the measured gage outputs. The analysis of the sting balance calibration data set is a rare example of a situation when terms of a regression model of a balance can directly be derived from first principles of physics. In addition, it is interesting to note that the search algorithm recommended the correct regression model term combinations using only a set of statistical quality metrics that were applied to the experimental data during the algorithm s term selection process.
Hybrid rocket fuel combustion and regression rate study
NASA Technical Reports Server (NTRS)
Strand, L. D.; Ray, R. L.; Anderson, F. A.; Cohen, N. S.
1992-01-01
The objectives of this study are to develop hybrid fuels (1) with higher regression rates and reduced dependence on fuel grain geometry and (2) that maximize potential specific impulse using low-cost materials. A hybrid slab window motor system was developed to screen candidate fuels - their combustion behavior and regression rate. Combustion behavior diagnostics consisted of video and high speed motion pictures coverage. The mean fuel regression rates were determined by before and after measurements of the fuel slabs. The fuel for this initial investigation consisted of hydroxyl-terminated polybutadiene binder with coal and aluminum fillers. At low oxidizer flux levels (and corresponding fuel regression rates) the filled-binder fuels burn in a layered fashion, forming an aluminum containing binder/coal surface melt that, in turn, forms into filigrees or flakes that are stripped off by the crossflow. This melt process appears to diminish with increasing oxidizer flux level. Heat transfer by radiation is a significant contributor, producing the desired increase in magnitude and reduction in flow dependency (power law exponent) of the fuel regression rate.
Abundant Inverse Regression using Sufficient Reduction and its Applications
Kim, Hyunwoo J.; Smith, Brandon M.; Adluru, Nagesh; Dyer, Charles R.; Johnson, Sterling C.; Singh, Vikas
2016-01-01
Statistical models such as linear regression drive numerous applications in computer vision and machine learning. The landscape of practical deployments of these formulations is dominated by forward regression models that estimate the parameters of a function mapping a set of p covariates, x, to a response variable, y. The less known alternative, Inverse Regression, offers various benefits that are much less explored in vision problems. The goal of this paper is to show how Inverse Regression in the “abundant” feature setting (i.e., many subsets of features are associated with the target label or response, as is the case for images), together with a statistical construction called Sufficient Reduction, yields highly flexible models that are a natural fit for model estimation tasks in vision. Specifically, we obtain formulations that provide relevance of individual covariates used in prediction, at the level of specific examples/samples — in a sense, explaining why a particular prediction was made. With no compromise in performance relative to other methods, an ability to interpret why a learning algorithm is behaving in a specific way for each prediction, adds significant value in numerous applications. We illustrate these properties and the benefits of Abundant Inverse Regression (AIR) on three distinct applications. PMID:27796010
Digression and Value Concatenation to Enable Privacy-Preserving Regression
Li, Xiao-Bai; Sarkar, Sumit
2015-01-01
Regression techniques can be used not only for legitimate data analysis, but also to infer private information about individuals. In this paper, we demonstrate that regression trees, a popular data-analysis and data-mining technique, can be used to effectively reveal individuals’ sensitive data. This problem, which we call a “regression attack,” has not been addressed in the data privacy literature, and existing privacy-preserving techniques are not appropriate in coping with this problem. We propose a new approach to counter regression attacks. To protect against privacy disclosure, our approach introduces a novel measure, called digression, which assesses the sensitive value disclosure risk in the process of building a regression tree model. Specifically, we develop an algorithm that uses the measure for pruning the tree to limit disclosure of sensitive data. We also propose a dynamic value-concatenation method for anonymizing data, which better preserves data utility than a user-defined generalization scheme commonly used in existing approaches. Our approach can be used for anonymizing both numeric and categorical data. An experimental study is conducted using real-world financial, economic and healthcare data. The results of the experiments demonstrate that the proposed approach is very effective in protecting data privacy while preserving data quality for research and analysis. PMID:26752802
Regression analysis for solving diagnosis problem of children's health
NASA Astrophysics Data System (ADS)
Cherkashina, Yu A.; Gerget, O. M.
2016-04-01
The paper includes results of scientific researches. These researches are devoted to the application of statistical techniques, namely, regression analysis, to assess the health status of children in the neonatal period based on medical data (hemostatic parameters, parameters of blood tests, the gestational age, vascular-endothelial growth factor) measured at 3-5 days of children's life. In this paper a detailed description of the studied medical data is given. A binary logistic regression procedure is discussed in the paper. Basic results of the research are presented. A classification table of predicted values and factual observed values is shown, the overall percentage of correct recognition is determined. Regression equation coefficients are calculated, the general regression equation is written based on them. Based on the results of logistic regression, ROC analysis was performed, sensitivity and specificity of the model are calculated and ROC curves are constructed. These mathematical techniques allow carrying out diagnostics of health of children providing a high quality of recognition. The results make a significant contribution to the development of evidence-based medicine and have a high practical importance in the professional activity of the author.
Study of Rapid-Regression Liquefying Hybrid Rocket Fuels
NASA Technical Reports Server (NTRS)
Zilliac, Greg; DeZilwa, Shane; Karabeyoglu, M. Arif; Cantwell, Brian J.; Castellucci, Paul
2004-01-01
A report describes experiments directed toward the development of paraffin-based hybrid rocket fuels that burn at regression rates greater than those of conventional hybrid rocket fuels like hydroxyl-terminated butadiene. The basic approach followed in this development is to use materials such that a hydrodynamically unstable liquid layer forms on the melting surface of a burning fuel body. Entrainment of droplets from the liquid/gas interface can substantially increase the rate of fuel mass transfer, leading to surface regression faster than can be achieved using conventional fuels. The higher regression rate eliminates the need for the complex multi-port grain structures of conventional solid rocket fuels, making it possible to obtain acceptable performance from single-port structures. The high-regression-rate fuels contain no toxic or otherwise hazardous components and can be shipped commercially as non-hazardous commodities. Among the experiments performed on these fuels were scale-up tests using gaseous oxygen. The data from these tests were found to agree with data from small-scale, low-pressure and low-mass-flux laboratory tests and to confirm the expectation that these fuels would burn at high regression rates, chamber pressures, and mass fluxes representative of full-scale rocket motors.
A Multiple Regression Approach to Normalization of Spatiotemporal Gait Features.
Wahid, Ferdous; Begg, Rezaul; Lythgo, Noel; Hass, Chris J; Halgamuge, Saman; Ackland, David C
2016-04-01
Normalization of gait data is performed to reduce the effects of intersubject variations due to physical characteristics. This study reports a multiple regression normalization approach for spatiotemporal gait data that takes into account intersubject variations in self-selected walking speed and physical properties including age, height, body mass, and sex. Spatiotemporal gait data including stride length, cadence, stance time, double support time, and stride time were obtained from healthy subjects including 782 children, 71 adults, 29 elderly subjects, and 28 elderly Parkinson's disease (PD) patients. Data were normalized using standard dimensionless equations, a detrending method, and a multiple regression approach. After normalization using dimensionless equations and the detrending method, weak to moderate correlations between walking speed, physical properties, and spatiotemporal gait features were observed (0.01 < |r| < 0.88), whereas normalization using the multiple regression method reduced these correlations to weak values (|r| <0.29). Data normalization using dimensionless equations and detrending resulted in significant differences in stride length and double support time of PD patients; however the multiple regression approach revealed significant differences in these features as well as in cadence, stance time, and stride time. The proposed multiple regression normalization may be useful in machine learning, gait classification, and clinical evaluation of pathological gait patterns.
Penalized spline estimation for functional coefficient regression models.
Cao, Yanrong; Lin, Haiqun; Wu, Tracy Z; Yu, Yan
2010-04-01
The functional coefficient regression models assume that the regression coefficients vary with some "threshold" variable, providing appreciable flexibility in capturing the underlying dynamics in data and avoiding the so-called "curse of dimensionality" in multivariate nonparametric estimation. We first investigate the estimation, inference, and forecasting for the functional coefficient regression models with dependent observations via penalized splines. The P-spline approach, as a direct ridge regression shrinkage type global smoothing method, is computationally efficient and stable. With established fixed-knot asymptotics, inference is readily available. Exact inference can be obtained for fixed smoothing parameter λ, which is most appealing for finite samples. Our penalized spline approach gives an explicit model expression, which also enables multi-step-ahead forecasting via simulations. Furthermore, we examine different methods of choosing the important smoothing parameter λ: modified multi-fold cross-validation (MCV), generalized cross-validation (GCV), and an extension of empirical bias bandwidth selection (EBBS) to P-splines. In addition, we implement smoothing parameter selection using mixed model framework through restricted maximum likelihood (REML) for P-spline functional coefficient regression models with independent observations. The P-spline approach also easily allows different smoothness for different functional coefficients, which is enabled by assigning different penalty λ accordingly. We demonstrate the proposed approach by both simulation examples and a real data application.
Quantile regression provides a fuller analysis of speed data.
Hewson, Paul
2008-03-01
Considerable interest already exists in terms of assessing percentiles of speed distributions, for example monitoring the 85th percentile speed is a common feature of the investigation of many road safety interventions. However, unlike the mean, where t-tests and ANOVA can be used to provide evidence of a statistically significant change, inference on these percentiles is much less common. This paper examines the potential role of quantile regression for modelling the 85th percentile, or any other quantile. Given that crash risk may increase disproportionately with increasing relative speed, it may be argued these quantiles are of more interest than the conditional mean. In common with the more usual linear regression, quantile regression admits a simple test as to whether the 85th percentile speed has changed following an intervention in an analogous way to using the t-test to determine if the mean speed has changed by considering the significance of parameters fitted to a design matrix. Having briefly outlined the technique and briefly examined an application with a widely published dataset concerning speed measurements taken around the introduction of signs in Cambridgeshire, this paper will demonstrate the potential for quantile regression modelling by examining recent data from Northamptonshire collected in conjunction with a "community speed watch" programme. Freely available software is used to fit these models and it is hoped that the potential benefits of using quantile regression methods when examining and analysing speed data are demonstrated.
Optimization of Regression Models of Experimental Data Using Confirmation Points
NASA Technical Reports Server (NTRS)
Ulbrich, N.
2010-01-01
A new search metric is discussed that may be used to better assess the predictive capability of different math term combinations during the optimization of a regression model of experimental data. The new search metric can be determined for each tested math term combination if the given experimental data set is split into two subsets. The first subset consists of data points that are only used to determine the coefficients of the regression model. The second subset consists of confirmation points that are exclusively used to test the regression model. The new search metric value is assigned after comparing two values that describe the quality of the fit of each subset. The first value is the standard deviation of the PRESS residuals of the data points. The second value is the standard deviation of the response residuals of the confirmation points. The greater of the two values is used as the new search metric value. This choice guarantees that both standard deviations are always less or equal to the value that is used during the optimization. Experimental data from the calibration of a wind tunnel strain-gage balance is used to illustrate the application of the new search metric. The new search metric ultimately generates an optimized regression model that was already tested at regression model independent confirmation points before it is ever used to predict an unknown response from a set of regressors.
An adequate design for regression analysis of yield trials.
Gusmão, L
1985-12-01
Based on theoretical demonstrations and illustrated with a numerical example from triticale yield trials in Portugal, the Completely Randomized Design is proposed as the one suited for Regression Analysis. When trials are designed in Complete Randomized Blocks the regression of plot production on block mean instead of the regression of cultivar mean on the overall mean of the trial is proposed as the correct procedure for regression analysis. These proposed procedures, in addition to providing a better agreement with the assumptions for regression and the philosophy of the method, induce narrower confidence intervals and attenuation of the hyperbolic effect. The increase in precision is brought about by both a decrease in the t Student values by an increased number of degrees of freedom, and by a decrease in standard error by a non proportional increase of residual variance and non proportional increase of the sum of squares of the assumed independent variable. The new procedures seem to be promising for a better understanding of the mechanism of specific instability.
Differentially private distributed logistic regression using private and public data
2014-01-01
Background Privacy protecting is an important issue in medical informatics and differential privacy is a state-of-the-art framework for data privacy research. Differential privacy offers provable privacy against attackers who have auxiliary information, and can be applied to data mining models (for example, logistic regression). However, differentially private methods sometimes introduce too much noise and make outputs less useful. Given available public data in medical research (e.g. from patients who sign open-consent agreements), we can design algorithms that use both public and private data sets to decrease the amount of noise that is introduced. Methodology In this paper, we modify the update step in Newton-Raphson method to propose a differentially private distributed logistic regression model based on both public and private data. Experiments and results We try our algorithm on three different data sets, and show its advantage over: (1) a logistic regression model based solely on public data, and (2) a differentially private distributed logistic regression model based on private data under various scenarios. Conclusion Logistic regression models built with our new algorithm based on both private and public datasets demonstrate better utility than models that trained on private or public datasets alone without sacrificing the rigorous privacy guarantee. PMID:25079786
Regression of Pathological Cardiac Hypertrophy: Signaling Pathways and Therapeutic Targets
Hou, Jianglong; Kang, Y. James
2012-01-01
Pathological cardiac hypertrophy is a key risk factor for heart failure. It is associated with increased interstitial fibrosis, cell death and cardiac dysfunction. The progression of pathological cardiac hypertrophy has long been considered as irreversible. However, recent clinical observations and experimental studies have produced evidence showing the reversal of pathological cardiac hypertrophy. Left ventricle assist devices used in heart failure patients for bridging to transplantation not only improve peripheral circulation but also often cause reverse remodeling of the geometry and recovery of the function of the heart. Dietary supplementation with physiologically relevant levels of copper can reverse pathological cardiac hypertrophy in mice. Angiogenesis is essential and vascular endothelial growth factor (VEGF) is a constitutive factor for the regression. The action of VEGF is mediated by VEGF receptor-1, whose activation is linked to cyclic GMP-dependent protein kinase-1 (PKG-1) signaling pathways, and inhibition of cyclic GMP degradation leads to regression of pathological cardiac hypertrophy. Most of these pathways are regulated by hypoxia-inducible factor. Potential therapeutic targets for promoting the regression include: promotion of angiogenesis, selective enhancement of VEGF receptor-1 signaling pathways, stimulation of PKG-1 pathways, and sustention of hypoxia-inducible factor transcriptional activity. More exciting insights into the regression of pathological cardiac hypertrophy are emerging. The time of translating the concept of regression of pathological cardiac hypertrophy to clinical practice is coming. PMID:22750195
copCAR: A Flexible Regression Model for Areal Data.
Hughes, John
2015-09-16
Non-Gaussian spatial data are common in many fields. When fitting regressions for such data, one needs to account for spatial dependence to ensure reliable inference for the regression coefficients. The two most commonly used regression models for spatially aggregated data are the automodel and the areal generalized linear mixed model (GLMM). These models induce spatial dependence in different ways but share the smoothing approach, which is intuitive but problematic. This article develops a new regression model for areal data. The new model is called copCAR because it is copula-based and employs the areal GLMM's conditional autoregression (CAR). copCAR overcomes many of the drawbacks of the automodel and the areal GLMM. Specifically, copCAR (1) is flexible and intuitive, (2) permits positive spatial dependence for all types of data, (3) permits efficient computation, and (4) provides reliable spatial regression inference and information about dependence strength. An implementation is provided by R package copCAR, which is available from the Comprehensive R Archive Network, and supplementary materials are available online.
Regression Model Optimization for the Analysis of Experimental Data
NASA Technical Reports Server (NTRS)
Ulbrich, N.
2009-01-01
A candidate math model search algorithm was developed at Ames Research Center that determines a recommended math model for the multivariate regression analysis of experimental data. The search algorithm is applicable to classical regression analysis problems as well as wind tunnel strain gage balance calibration analysis applications. The algorithm compares the predictive capability of different regression models using the standard deviation of the PRESS residuals of the responses as a search metric. This search metric is minimized during the search. Singular value decomposition is used during the search to reject math models that lead to a singular solution of the regression analysis problem. Two threshold dependent constraints are also applied. The first constraint rejects math models with insignificant terms. The second constraint rejects math models with near-linear dependencies between terms. The math term hierarchy rule may also be applied as an optional constraint during or after the candidate math model search. The final term selection of the recommended math model depends on the regressor and response values of the data set, the user s function class combination choice, the user s constraint selections, and the result of the search metric minimization. A frequently used regression analysis example from the literature is used to illustrate the application of the search algorithm to experimental data.
Rastegari, Azam; Haghdoost, Ali Akbar; Baneshi, Mohammad Reza
2013-01-01
Background Due to the importance of medical studies, researchers of this field should be familiar with various types of statistical analyses to select the most appropriate method based on the characteristics of their data sets. Classification and regression trees (CARTs) can be as complementary to regression models. We compared the performance of a logistic regression model and a CART in predicting drug injection among prisoners. Methods Data of 2720 Iranian prisoners was studied to determine the factors influencing drug injection. The collected data was divided into two groups of training and testing. A logistic regression model and a CART were applied on training data. The performance of the two models was then evaluated on testing data. Findings The regression model and the CART had 8 and 4 significant variables, respectively. Overall, heroin use, history of imprisonment, age at first drug use, and marital status were important factors in determining the history of drug injection. Subjects without the history of heroin use or heroin users with short-term imprisonment were at lower risk of drug injection. Among heroin addicts with long-term imprisonment, individuals with higher age at first drug use and married subjects were at lower risk of drug injection. Although the logistic regression model was more sensitive than the CART, the two models had the same levels of specificity and classification accuracy. Conclusion In this study, both sensitivity and specificity were important. While the logistic regression model had better performance, the graphical presentation of the CART simplifies the interpretation of the results. In general, a combination of different analytical methods is recommended to explore the effects of variables. PMID:24494152
Regression of oral lichenoid lesions after replacement of dental restorations.
Mårell, L; Tillberg, A; Widman, L; Bergdahl, J; Berglund, A
2014-05-01
The aim of the study was to determine the prognosis and to evaluate the regression of lichenoid contact reactions (LCR) and oral lichen planus (OLP) after replacement of dental restorative materials suspected as causing the lesions. Forty-four referred patients with oral lesions participated in a follow-up study that was initiated an average of 6 years after the first examination at the Department of Odontology, i.e. the baseline examination. The patients underwent odontological clinical examination and answered a questionnaire with questions regarding dental health, medical and psychological health, and treatments undertaken from baseline to follow-up. After exchange of dental materials, regression of oral lesions was significantly higher among patients with LCR than with OLP. As no cases with OLP regressed after an exchange of materials, a proper diagnosis has to be made to avoid unnecessary exchanges of intact restorations on patients with OLP.
Spinocerebellar ataxia type 2 presenting with cognitive regression in childhood.
Ramocki, Melissa B; Chapieski, Lynn; McDonald, Ryan O; Fernandez, Fabio; Malphrus, Amy D
2008-09-01
Spinocerebellar ataxia type 2 typically presents in adulthood with progressive ataxia, dysarthria, tremor, and slow saccadic eye movements. Childhood-onset spinocerebellar ataxia type 2 is rare, and only the infantile-onset form has been well characterized clinically. This article describes a girl who met all developmental milestones until age 3(1/2) years, when she experienced cognitive regression that preceded motor regression by 6 months. A diagnosis of spinocerebellar ataxia type 2 was delayed until she presented to the emergency department at age 7 years. This report documents the results of her neuropsychologic evaluation at both time points. This case broadens the spectrum of spinocerebellar ataxia type 2 presentation in childhood, highlights the importance of considering a spinocerebellar ataxia in a child who presents with cognitive regression only, and extends currently available clinical information to help clinicians discuss the prognosis in childhood spinocerebellar ataxia type 2.
Shell Element Verification & Regression Problems for DYNA3D
Zywicz, E
2008-02-01
A series of quasi-static regression/verification problems were developed for the triangular and quadrilateral shell element formulations contained in Lawrence Livermore National Laboratory's explicit finite element program DYNA3D. Each regression problem imposes both displacement- and force-type boundary conditions to probe the five independent nodal degrees of freedom employed in the targeted formulation. When applicable, the finite element results are compared with small-strain linear-elastic closed-form reference solutions to verify select aspects of the formulations implementation. Although all problems in the suite depict the same geometry, material behavior, and loading conditions, each problem represents a unique combination of shell formulation, stabilization method, and integration rule. Collectively, the thirty-six new regression problems in the test suite cover nine different shell formulations, three hourglass stabilization methods, and three families of through-thickness integration rules.
Regression with repeated measures in the experimental units.
Garsd, A
1999-01-01
The most satisfactory solution to the problem of modeling a family of regressions with repeated measures in the experimental units is multivariate in nature. However, multivariate methods are difficult to follow and implement. Furthermore, by keeping the focus on the experimental unit, a family of simple univariate linear models will often parallel both the investigator's intuitive grasp of the statistical task at hand. We present two examples based on data from a study of the suckling stimulus during breastfeeding in newborn infants. We show how a family of regression lines can provide useful, if approximate, answers to the questions of interest. One example involves a regression setting proper and the other a typical case of correlation. We discuss alternative univariate models that may be useful for this type of problems.
Circular piecewise regression with applications to cell-cycle data.
Rueda, Cristina; Fernández, Miguel A; Barragán, Sandra; Mardia, Kanti V; Peddada, Shyamal D
2016-12-01
Applications of circular regression models appear in many different fields such as evolutionary psychology, motor behavior, biology, and, in particular, in the analysis of gene expressions in oscillatory systems. Specifically, for the gene expression problem, a researcher may be interested in modeling the relationship among the phases of cell-cycle genes in two species with differing periods. This challenging problem reduces to the problem of constructing a piecewise circular regression model and, with this objective in mind, we propose a flexible circular regression model which allows different parameter values depending on sectors along the circle. We give a detailed interpretation of the parameters in the model and provide maximum likelihood estimators. We also provide a model selection procedure based on the concept of generalized degrees of freedom. The model is then applied to the analysis of two different cell-cycle data sets and through these examples we highlight the power of our new methodology.
Norming clinical questionnaires with multiple regression: the Pain Cognition List.
Van Breukelen, Gerard J P; Vlaeyen, Johan W S
2005-09-01
Questionnaires for measuring patients' feelings or beliefs are commonly used in clinical settings for diagnostic purposes, clinical decision making, or treatment evaluation. Raw scores of a patient can be evaluated by comparing them with norms based on a reference population. Using the Pain Cognition List (PCL-2003) as an example, this article shows how clinical questionnaires can be normed with multiple regression of raw scores on demographic and other patient variables. Compared with traditional norm tables for subgroups based on age or gender, this approach offers 2 advantages. First, multiple regression allows determination of which patient variables are relevant to the norming and which are not (validity). Second, by using information from the entire sample, multiple regression leads to continuous and more stable norms for any subgroup defined in terms of prognostic variables (reliability).
Omnibus hypothesis testing in dominance-based ordinal multiple regression.
Long, Jeffrey D
2005-09-01
Often quantitative data in the social sciences have only ordinal justification. Problems of interpretation can arise when least squares multiple regression (LSMR) is used with ordinal data. Two ordinal alternatives are discussed, dominance-based ordinal multiple regression (DOMR) and proportional odds multiple regression. The Q2 statistic is introduced for testing the omnibus null hypothesis in DOMR. A simulation study is discussed that examines the actual Type I error rate and power of Q2 in comparison to the LSMR omnibus F test under normality and non-normality. Results suggest that Q2 has favorable sampling properties as long as the sample size-to-predictors ratio is not too small, and Q2 can be a good alternative to the omnibus F test when the response variable is non-normal.
Tensor Regression with Applications in Neuroimaging Data Analysis
Zhou, Hua; Li, Lexin; Zhu, Hongtu
2013-01-01
Classical regression methods treat covariates as a vector and estimate a corresponding vector of regression coefficients. Modern applications in medical imaging generate covariates of more complex form such as multidimensional arrays (tensors). Traditional statistical and computational methods are proving insufficient for analysis of these high-throughput data due to their ultrahigh dimensionality as well as complex structure. In this article, we propose a new family of tensor regression models that efficiently exploit the special structure of tensor covariates. Under this framework, ultrahigh dimensionality is reduced to a manageable level, resulting in efficient estimation and prediction. A fast and highly scalable estimation algorithm is proposed for maximum likelihood estimation and its associated asymptotic properties are studied. Effectiveness of the new methods is demonstrated on both synthetic and real MRI imaging data. PMID:24791032
Spatial regression with covariate measurement error: A semiparametric approach.
Huque, Md Hamidul; Bondell, Howard D; Carroll, Raymond J; Ryan, Louise M
2016-09-01
Spatial data have become increasingly common in epidemiology and public health research thanks to advances in GIS (Geographic Information Systems) technology. In health research, for example, it is common for epidemiologists to incorporate geographically indexed data into their studies. In practice, however, the spatially defined covariates are often measured with error. Naive estimators of regression coefficients are attenuated if measurement error is ignored. Moreover, the classical measurement error theory is inapplicable in the context of spatial modeling because of the presence of spatial correlation among the observations. We propose a semiparametric regression approach to obtain bias-corrected estimates of regression parameters and derive their large sample properties. We evaluate the performance of the proposed method through simulation studies and illustrate using data on Ischemic Heart Disease (IHD). Both simulation and practical application demonstrate that the proposed method can be effective in practice.
Birthweight Related Factors in Northwestern Iran: Using Quantile Regression Method
Fallah, Ramazan; Kazemnejad, Anoshirvan; Zayeri, Farid; Shoghli, Alireza
2016-01-01
Introduction: Birthweight is one of the most important predicting indicators of the health status in adulthood. Having a balanced birthweight is one of the priorities of the health system in most of the industrial and developed countries. This indicator is used to assess the growth and health status of the infants. The aim of this study was to assess the birthweight of the neonates by using quantile regression in Zanjan province. Methods: This analytical descriptive study was carried out using pre-registered (March 2010 - March 2012) data of neonates in urban/rural health centers of Zanjan province using multiple-stage cluster sampling. Data were analyzed using multiple linear regressions andquantile regression method and SAS 9.2 statistical software. Results: From 8456 newborn baby, 4146 (49%) were female. The mean age of the mothers was 27.1±5.4 years. The mean birthweight of the neonates was 3104 ± 431 grams. Five hundred and seventy-three patients (6.8%) of the neonates were less than 2500 grams. In all quantiles, gestational age of neonates (p<0.05), weight and educational level of the mothers (p<0.05) showed a linear significant relationship with the i of the neonates. However, sex and birth rank of the neonates, mothers age, place of residence (urban/rural) and career were not significant in all quantiles (p>0.05). Conclusion: This study revealed the results of multiple linear regression and quantile regression were not identical. We strictly recommend the use of quantile regression when an asymmetric response variable or data with outliers is available. PMID:26925889
Sparse Regression by Projection and Sparse Discriminant Analysis.
Qi, Xin; Luo, Ruiyan; Carroll, Raymond J; Zhao, Hongyu
2015-04-01
Recent years have seen active developments of various penalized regression methods, such as LASSO and elastic net, to analyze high dimensional data. In these approaches, the direction and length of the regression coefficients are determined simultaneously. Due to the introduction of penalties, the length of the estimates can be far from being optimal for accurate predictions. We introduce a new framework, regression by projection, and its sparse version to analyze high dimensional data. The unique nature of this framework is that the directions of the regression coefficients are inferred first, and the lengths and the tuning parameters are determined by a cross validation procedure to achieve the largest prediction accuracy. We provide a theoretical result for simultaneous model selection consistency and parameter estimation consistency of our method in high dimension. This new framework is then generalized such that it can be applied to principal components analysis, partial least squares and canonical correlation analysis. We also adapt this framework for discriminant analysis. Compared to the existing methods, where there is relatively little control of the dependency among the sparse components, our method can control the relationships among the components. We present efficient algorithms and related theory for solving the sparse regression by projection problem. Based on extensive simulations and real data analysis, we demonstrate that our method achieves good predictive performance and variable selection in the regression setting, and the ability to control relationships between the sparse components leads to more accurate classification. In supplemental materials available online, the details of the algorithms and theoretical proofs, and R codes for all simulation studies are provided.
Sugarcane Land Classification with Satellite Imagery using Logistic Regression Model
NASA Astrophysics Data System (ADS)
Henry, F.; Herwindiati, D. E.; Mulyono, S.; Hendryli, J.
2017-03-01
This paper discusses the classification of sugarcane plantation area from Landsat-8 satellite imagery. The classification process uses binary logistic regression method with time series data of normalized difference vegetation index as input. The process is divided into two steps: training and classification. The purpose of training step is to identify the best parameter of the regression model using gradient descent algorithm. The best fit of the model can be utilized to classify sugarcane and non-sugarcane area. The experiment shows high accuracy and successfully maps the sugarcane plantation area which obtained best result of Cohen’s Kappa value 0.7833 (strong) with 89.167% accuracy.
Saddlepoint approximations for small sample logistic regression problems.
Platt, R W
2000-02-15
Double saddlepoint approximations provide quick and accurate approximations to exact conditional tail probabilities in a variety of situations. This paper describes the use of these approximations in two logistic regression problems. An investigation of regression analysis of the log-odds ratio in a sequence or set of 2x2 tables via simulation studies shows that in practical settings the saddlepoint methods closely approximate exact conditional inference. The double saddlepoint approximation in the test for trend in a sequence of binomial random variates is also shown, via simulation studies, to be an effective approximation to exact conditional inference.
Time series analysis using semiparametric regression on oil palm production
NASA Astrophysics Data System (ADS)
Yundari, Pasaribu, U. S.; Mukhaiyar, U.
2016-04-01
This paper presents semiparametric kernel regression method which has shown its flexibility and easiness in mathematical calculation, especially in estimating density and regression function. Kernel function is continuous and it produces a smooth estimation. The classical kernel density estimator is constructed by completely nonparametric analysis and it is well reasonable working for all form of function. Here, we discuss about parameter estimation in time series analysis. First, we consider the parameters are exist, then we use nonparametrical estimation which is called semiparametrical. The selection of optimum bandwidth is obtained by considering the approximation of Mean Integrated Square Root Error (MISE).
[Regression of coronary arteriosclerosis with hypolipidemic treatment, myth or reality?].
Lahoz, C; Monereo, A; Mostaza, J M; de Oya, M
1992-11-01
Coronary atherosclerosis regression with hypolipemiant treatment is a well known fact in the animal model since years ago. In humans, during these last years, several clinical trials have been performed to ellucidate the truth to this fact. All of these clinical trials have in common the evolutive study of the coronary lesions with angiographies, in patients following treatment with diet, surgery or drugs, to reduce plasmatic cholesterol. Clinical, analytical and angiographic results of said studies are reviewed. We conclude that the bigger the lowering in plasmatic cholesterol levels, smaller is the progression of these coronary lesions and more probable is finding patients with partial regression of the lesions.
Geographically weighted regression and multicollinearity: dispelling the myth
NASA Astrophysics Data System (ADS)
Fotheringham, A. Stewart; Oshan, Taylor M.
2016-10-01
Geographically weighted regression (GWR) extends the familiar regression framework by estimating a set of parameters for any number of locations within a study area, rather than producing a single parameter estimate for each relationship specified in the model. Recent literature has suggested that GWR is highly susceptible to the effects of multicollinearity between explanatory variables and has proposed a series of local measures of multicollinearity as an indicator of potential problems. In this paper, we employ a controlled simulation to demonstrate that GWR is in fact very robust to the effects of multicollinearity. Consequently, the contention that GWR is highly susceptible to multicollinearity issues needs rethinking.
Subsonic Aircraft With Regression and Neural-Network Approximators Designed
NASA Technical Reports Server (NTRS)
Patnaik, Surya N.; Hopkins, Dale A.
2004-01-01
At the NASA Glenn Research Center, NASA Langley Research Center's Flight Optimization System (FLOPS) and the design optimization testbed COMETBOARDS with regression and neural-network-analysis approximators have been coupled to obtain a preliminary aircraft design methodology. For a subsonic aircraft, the optimal design, that is the airframe-engine combination, is obtained by the simulation. The aircraft is powered by two high-bypass-ratio engines with a nominal thrust of about 35,000 lbf. It is to carry 150 passengers at a cruise speed of Mach 0.8 over a range of 3000 n mi and to operate on a 6000-ft runway. The aircraft design utilized a neural network and a regression-approximations-based analysis tool, along with a multioptimizer cascade algorithm that uses sequential linear programming, sequential quadratic programming, the method of feasible directions, and then sequential quadratic programming again. Optimal aircraft weight versus the number of design iterations is shown. The central processing unit (CPU) time to solution is given. It is shown that the regression-method-based analyzer exhibited a smoother convergence pattern than the FLOPS code. The optimum weight obtained by the approximation technique and the FLOPS code differed by 1.3 percent. Prediction by the approximation technique exhibited no error for the aircraft wing area and turbine entry temperature, whereas it was within 2 percent for most other parameters. Cascade strategy was required by FLOPS as well as the approximators. The regression method had a tendency to hug the data points, whereas the neural network exhibited a propensity to follow a mean path. The performance of the neural network and regression methods was considered adequate. It was at about the same level for small, standard, and large models with redundancy ratios (defined as the number of input-output pairs to the number of unknown coefficients) of 14, 28, and 57, respectively. In an SGI octane workstation (Silicon Graphics
Cardiovascular Response Identification Based on Nonlinear Support Vector Regression
NASA Astrophysics Data System (ADS)
Wang, Lu; Su, Steven W.; Chan, Gregory S. H.; Celler, Branko G.; Cheng, Teddy M.; Savkin, Andrey V.
This study experimentally investigates the relationships between central cardiovascular variables and oxygen uptake based on nonlinear analysis and modeling. Ten healthy subjects were studied using cycle-ergometry exercise tests with constant workloads ranging from 25 Watt to 125 Watt. Breath by breath gas exchange, heart rate, cardiac output, stroke volume and blood pressure were measured at each stage. The modeling results proved that the nonlinear modeling method (Support Vector Regression) outperforms traditional regression method (reducing Estimation Error between 59% and 80%, reducing Testing Error between 53% and 72%) and is the ideal approach in the modeling of physiological data, especially with small training data set.
Estimating effects of limiting factors with regression quantiles
Cade, B.S.; Terrell, J.W.; Schroeder, R.L.
1999-01-01
In a recent Concepts paper in Ecology, Thomson et al. emphasized that assumptions of conventional correlation and regression analyses fundamentally conflict with the ecological concept of limiting factors, and they called for new statistical procedures to address this problem. The analytical issue is that unmeasured factors may be the active limiting constraint and may induce a pattern of unequal variation in the biological response variable through an interaction with the measured factors. Consequently, changes near the maxima, rather than at the center of response distributions, are better estimates of the effects expected when the observed factor is the active limiting constraint. Regression quantiles provide estimates for linear models fit to any part of a response distribution, including near the upper bounds, and require minimal assumptions about the form of the error distribution. Regression quantiles extend the concept of one-sample quantiles to the linear model by solving an optimization problem of minimizing an asymmetric function of absolute errors. Rank-score tests for regression quantiles provide tests of hypotheses and confidence intervals for parameters in linear models with heteroscedastic errors, conditions likely to occur in models of limiting ecological relations. We used selected regression quantiles (e.g., 5th, 10th, ..., 95th) and confidence intervals to test hypotheses that parameters equal zero for estimated changes in average annual acorn biomass due to forest canopy cover of oak (Quercus spp.) and oak species diversity. Regression quantiles also were used to estimate changes in glacier lily (Erythronium grandiflorum) seedling numbers as a function of lily flower numbers, rockiness, and pocket gopher (Thomomys talpoides fossor) activity, data that motivated the query by Thomson et al. for new statistical procedures. Both example applications showed that effects of limiting factors estimated by changes in some upper regression quantile (e
An Approach to the Programming of Biased Regression Algorithms.
1978-11-01
Due to the near nonexistence of computer algorithms for calculating estimators and ancillary statistics that are needed for biased regression methodologies, many users of these methodologies are forced to write their own programs. Brute-force coding of such programs can result in a great waste of computer core and computing time, as well as inefficient and inaccurate computing techniques. This article proposes some guides to more efficient programming by taking advantage of mathematical similarities among several of the more popular biased regression estimators.
Improving Predictions in Imbalanced Data Using Pairwise Expanded Logistic Regression
Jiang, Xiaoqian; El-Kareh, Robert; Ohno-Machado, Lucila
2011-01-01
Building classifiers for medical problems often involves dealing with rare, but important events. Imbalanced datasets pose challenges to ordinary classification algorithms such as Logistic Regression (LR) and Support Vector Machines (SVM). The lack of effective strategies for dealing with imbalanced training data often results in models that exhibit poor discrimination. We propose a novel approach to estimate class memberships based on the evaluation of pairwise relationships in the training data. The method we propose, Pairwise Expanded Logistic Regression, improved discrimination and had higher accuracy when compared to existing methods in two imbalanced datasets, thus showing promise as a potential remedy for this problem. PMID:22195118