Wegner, J A; Martinez-Zaguilan, R; Gillies, R J; Hoyer, P B
1991-02-01
A previous study demonstrated that prostaglandin F2 alpha (PGF2 alpha) stimulates a transient increase in cytosolic free Ca2+ levels [( Ca2+]i) in ovine large luteal cells. In the present study, the magnitude of the PGF2 alpha (0.5 microM)-induced calcium transient in Hanks' medium (87 +/- 2 nM increase above resting levels) was reduced (P less than 0.05) but not completely eliminated in fura-2 loaded large luteal cells incubated in Ca2(+)-free or phosphate- and carbonate-free medium (10 +/- 1 nM, 32 +/- 6 nM, above resting levels; respectively). Preincubation for 2 min with 1 mM LaCl3 (calcium antagonist) eliminated the PGF2 alpha-induced calcium transient. The inhibitory effect of PGF2 alpha on secretion of progesterone was reduced in Ca2(+)-free medium or medium plus LaCl3. Resting [Ca2+]i levels and basal secretion of progesterone were both reduced (P less than 0.05) in large cells incubated in Ca2(+)-free medium (27 +/- 4 nM; 70 +/- 6% control, respectively) or with 5 microM 5,5'-dimethyl bis-(O-aminophenoxy)ethane-N,N,N'N'-tetraacetic acid (40 +/- 2 nM; 49 +/- 1% control; respectively). In addition, secretion of progesterone was inhibited (P less than 0.05) by conditions that increased (P less than 0.05) [Ca2+]i; that is LaCl3 ([Ca2+]i, 120 +/- 17 nM; progesterone, 82 +/- 8% control) and PGF2 alpha ([Ca2+]i, 102 +/- 10 nM; progesterone, 82 +/- 3% control). In small luteal cells, resting [Ca2+]i levels and secretion of progesterone were reduced by incubation in Ca2(+)-free Hanks ([Ca2+]i, 28 +/- 2 nM; progesterone, 71 +/- 6% control), however, neither LaCl3 nor PGF2 alpha increased [Ca2+]i levels or inhibited secretion of progesterone. The findings presented here provide evidence that extracellular as well as intracellular calcium contribute to the PGF2 alpha-induced [Ca2+]i transient in large cells. Furthermore, whereas an adequate level of [Ca2+]i is required to support progesterone production in both small and large cells, optimal progesterone production in
Kowalewski, Mariusz P
2014-04-01
Canine reproductive physiology exhibits several unusual features. Among the most interesting of these are the lack of an acute luteolytic mechanism, coinciding with the apparent luteal independency of a uterine luteolysin in absence of pregnancy, contrasting with the acute prepartum luteolysis observed in pregnant animals. These features indicate the existence of mechanisms different from those in other species for regulating the extended luteal regression observed in non-pregnant dogs, and the actively regulated termination of luteal function observed prepartum as a prerequisite for parturition. Nevertheless, the supply of progesterone (P4) depends on corpora lutea (CL) as its primary source in both conditions, resulting in P4 levels that are similar in pregnant and non-pregnant bitches during almost the entire luteal life span prior to the prepartum luteolysis. Consequently, the duration of the prolonged luteal phase in non-pregnant bitches frequently exceeds that of pregnant ones, which is a peculiarity when compared with other domestic animal species. Both LH and prolactin (PRL) are endocrine luteotrophic factors in the dog, the latter being the predominant one. In spite of increased availability of these hormones, luteal regression/luteolysis still takes place. Recently, possible mechanisms regulating the expression and function of PRL receptor have been implicated in the local, i.e., intraluteal regulation of PRL bioavailability and thus its steroidogenic potential. Similar mechanisms may relate to the luteal LH receptor. Most recently, evidence has been provided for an autocrine/paracrine role of prostaglandin E2 (PGE2) as a luteotrophic factor in the canine CL acting at the level of steroidogenic acute regulatory (STAR)-protein mediated supply of steroidogenic substrate, without having a significant impact on the enzymatic activity of the respective steroidogenic enzymes, 3β-hydroxysteroid-dehydrogenase (3βHSD, HSD3B2) and cytochrome P450 side
Ribeiro, Luciana Andrea; Turba, Maria Elena; Zannoni, Augusta; Bacci, Maria Laura; Forni, Monica
2006-01-01
Background The development and regression of corpus luteum (CL) is characterized by an intense angiogenesis and angioregression accompanied by luteal tissue and extracellular matrix (ECM) remodelling. Vascular Endothelial Growth Factor (VEGF) is the main regulator of angiogenesis, promoting endothelial cell mitosis and differentiation. After the formation of neovascular tubes, the remodelling of ECM is essential for the correct development of CL, particularly by the action of specific class of proteolytic enzymes known as matrix metalloproteinases (MMPs). During luteal regression, characterized by an apoptotic process and successively by an intense ECM and luteal degradation, the activation of Ca++/Mg++-dependent endonucleases and MMPs activity are required. The levels of expression and activity of VEGF, MMP-2 and -9, and Ca++/Mg++-dependent endonucleases throughout the oestrous cycle and at pregnancy were analyzed. Results Different patterns of VEGF, MMPs and Ca++/Mg++-dependent endonuclease were observed in swine CL during different luteal phases and at pregnancy. Immediately after ovulation, the highest levels of VEGF mRNA/protein and MMP-9 activity were detected. On days 5–14 after ovulation, VEGF expression and MMP-2 and -9 activities are at basal levels, while Ca++/Mg++-dependent endonuclease levels increased significantly in relation to day 1. Only at luteolysis (day 17), Ca++/Mg++-dependent endonuclease and MMP-2 spontaneous activity increased significantly. At pregnancy, high levels of MMP-9 and VEGF were observed. Conclusion Our findings, obtained from a precisely controlled in vivo model of CL development and regression, allow us to determine relationships among VEGF, MMPs and endonucleases during angiogenesis and angioregression. Thus, CL provides a very interesting model for studying factors involved in vascular remodelling. PMID:17137503
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...
Luteal angiogenesis and its control.
Woad, Kathryn J; Robinson, Robert S
2016-07-01
Angiogenesis, the formation of new blood vessels from preexisting ones, is critical to luteal structure and function. In addition, it is a complex and tightly regulated process. Not only does rapid and extensive angiogenesis occur to provide the corpus luteum with an unusually high blood flow and support its high metabolic rate, but in the absence of pregnancy, the luteal vasculature must rapidly regress to enable the next cycle of ovarian activity. This review describes a number of key endogenous stimulatory and inhibitory factors, which act in a delicate balance to regulate luteal angiogenesis and ultimately luteal function. In vitro luteal angiogenesis cultures have demonstrated critical roles for fibroblast growth factor 2 (FGF2) in endothelial cell proliferation and sprouting, although other factors such as vascular endothelial growth factor A (VEGFA) and platelet-derived growth factor were important modulators in the control of luteal angiogenesis. Post-transcriptional regulation by small non-coding microRNAs is also likely to play a central role in the regulation of luteal angiogenesis. Appropriate luteal angiogenesis requires the coordinated activity of numerous factors expressed by several cell types at different times, and this review will also describe the role of perivascular pericytes and the importance of vascular maturation and stability. It is hoped that a better understanding of the critical processes underlying the transition from follicle to corpus luteum and subsequent luteal development will benefit the management of luteal function in the future. PMID:27177965
Madan, Pavneesh; Bridges, Phillip J; Komar, Carolyn M; Beristain, Alexander G; Rajamahendran, Rajadurai; Fortune, Joanne E; MacCalman, Colin D
2003-11-01
Extensive remodeling of the extracellular matrix occurs in the ovary during the periovulatory period. Matrix metalloproteinases and their endogenous inhibitors, tissue inhibitors of metalloproteinases, are believed to play integral roles in this highly regulated series of cellular events, but their specific roles remain unclear. Recent cloning studies have identified a novel family of metalloproteinases, the ADAMTS (A Disintegrin And Metalloproteinase with ThromboSpondin motifs) family. The regulated expression of distinct ADAMTS subtypes has been shown to be required for tissue morphogenesis during embryonic development and for maintaining the integrity of tissues in the adult. In the present studies, we have determined that multiple ADAMTS subtypes are present in the bovine ovary using a reverse transcription-polymerase chain reaction strategy. In particular, ADAMTS-1, -2, -3, -4, -5 (also known as ADAMTS-11), -7, -8, and -9, but not ADAMTS-6, -10, or -12, mRNA transcripts were detected in granulosa cells of nonatretic ovarian follicles and corpora lutea. The levels of mRNA for these ovarian ADAMTS were up- or down-regulated or remained unchanged in the granulosa and/or theca cells of the dominant follicle following the preovulatory surge of gonadotropins, depending on the subtype and/or the cell compartment, and in the corpus luteum during the luteal phase of the estrous cycle. The complex expression patterns observed for the distinct ADAMTS subtypes in the granulosa and theca cells of the periovulatory follicle and in the luteal tissues of the bovine ovary suggest that these novel proteases mediate, at least in part, the remodeling events underlying folliculogenesis and ovulation and the formation, maintenance, and regression of the corpus luteum. PMID:12855604
Lee, Seung Gee; Chung, Jin-Yong; Park, Ji-Eun; Oh, Seunghoon; Yoon, Yong-Dal; Yoo, Ki Soo; Yoo, Young Hyun
2013-01-01
Background: Bisphenol A (BPA) has been detected in human body fluids, such as serum and ovarian follicular fluids. Several reports indicated that BPA exposure is associated with the occurrence of several female reproductive diseases resulting from the disruption of steroid hormone biosynthesis in the adult ovary. Objective: We hypothesized that long-term exposure to low concentrations of BPA disrupts 17β-estradiol (E2) production in granulosa cells via an alteration of steroidogenic proteins in ovarian cells. Methods: Adult female rats received BPA for 90 days by daily gavage at doses of 0, 0.001, or 0.1 mg/kg body weight. We determined serum levels of E2, testosterone (T), follicle-stimulating hormone (FSH), and luteinizing hormone (LH). We also analyzed the expressions of steroidogenic acute regulatory protein (StAR), P450 side-chain cleavage (P450scc), 3β-hydroxysteroid dehydrogenase isomerase (3β-HSD), and aromatase cytochrome P450 (P450arom) in the ovary. Results: Exposure to BPA significantly decreased E2 serum concentration, which was accompanied by augmented follicular atresia and luteal regression via increase of caspase-3–associated apoptosis in ovarian cells. After BPA exposure, P450arom and StAR protein levels were significantly decreased in granulosa cells and theca-interstitial (T-I) cells, respectively. However, P450scc and 3β-HSD protein levels remained unchanged. The increase in LH levels appeared to be associated with the decreased synthesis of T in T-I cells after BPA exposure via homeostatic positive feedback regulation. Conclusions: BPA exposure during adulthood can disturb the maintenance of normal ovarian functions by reducing E2. The steroidogenic proteins StAR and P450arom appear to be targeted by BPA. PMID:23512349
Luteal insufficiency in first trimester
Shah, Duru; Nagarajan, Nagadeepti
2013-01-01
Luteal phase insufficiency is one of the reasons for implantation failure and has been responsible for miscarriages and unsuccessful assisted reproduction. Luteal phase defect is seen in women with polycystic ovaries, thyroid and prolactin disorder. Low progesterone environment is created iatrogenically due to interventions in assisted reproduction. Use of gonadotrophin-releasing hormone analogs to prevent the LH surge and aspiration of granulosa cells during the oocyte retrieval may impair the ability of corpus luteum to produce progesterone. Treatment of the underlying disorder and use of progestational agents like progesterone/human chorionic gonadotrophin have been found to be effective in women with a history of recurrent miscarriage. There has been no proved beneficial effect of using additional agents like ascorbic acid, estrogen, prednisolone along with progesterone. Despite their widespread use, further studies are required to establish the optimal treatment. Literature review and analysis of published studies on luteal phase support. PMID:23776852
Progesterone vaginal ring for luteal support.
Stadtmauer, Laurel; Waud, Kay
2015-02-01
Progesterone supplementation is universally used and has been shown to be beneficial in supplementation of the luteal phase in IVF. There are multiple options and the most commonly used include intramuscular and vaginal progesterone. A progesterone vaginal ring is a novel system for luteal support with advantages of controlled release with less frequent dosing. This review examines options for progesterone luteal support focusing on the rationale for a progesterone vaginal ring. Pub-med search of the literature. A weekly vaginal ring, although not yet FDA approved, is an effective and safe alternative for luteal supplementation in IVF. Large prospective clinical trials are needed to determine the best protocols for replacement cycles. PMID:25737615
Alternate Alpha Induced Reactions for NIF Radiochemistry
Shaughnessy, D A; Moody, K J; Bernstein, L A
2010-02-26
Radiochemical analysis of NIF capsule residues has been identified as a potential diagnostic of NIF capsule performance. In particular, alpha-induced nuclear reactions that occur on tracer elements added to the NIF capsule have been shown through simulation to be a very sensitive diagnostic for mix. The short range of the alpha particles makes them representative of the hot spot where they are created through the fusion of deuterium and tritium. Reactions on elements doped into the innermost part of the capsule ablator would therefore be sensitive to material that had mixed into the hot spot. Radiochemical determinations of activated detector elements may perhaps be the only true measure of mix that occurs in a NIF capsule, particularly in cases when the capsule fails.
Luteal phase support in in vitro fertilization.
Yanushpolsky, Elena H
2015-03-01
It has been well demonstrated that luteal phase physiology is disrupted in in vitro fertilization (IVF) cycles conducted with either gonadotropin-releasing hormone (GnRH) agonists or antagonists, and that supplementation of the luteal phase with either exogenous progesterone or human chorionic gonadotropin (hCG) is necessary to optimize IVF cycle outcomes. Though both progesterone and hCG supplementation resulted in comparable pregnancy rates, hCG supplementation was associated with increased risk for ovarian hyperstimulation syndrome (OHSS). For that reason progesterone has been used for luteal support by most IVF programs around the world. Vaginal progesterone preparations have been shown definitively to be equally efficacious and better tolerated by patients than intramuscular progesterone injections, but new data on the subcutaneous and oral progesterone are also emerging. New evidence has been accumulating on the benefits of low-dose luteal hCG supplementation in GnRH-antagonist cycles where GnRH agonists are used for the final maturation trigger. New approaches to luteal phase support as well as new formulations of progesterone have been developed since the last comprehensive review was published in 2011. In this article, we examine current evidence for efficacy, dosing, and timing of progesterone preparations as well as the role of hCG for luteal support in IVF cycles triggered with GnRH agonists. We also discuss the data on the role of estrogen supplementation in the luteal phase, optimal duration of progesterone support in early pregnancy, and progesterone replacement in frozen embryo transfer cycles and donor egg recipient cycles. PMID:25734349
Gestating for 22 months: luteal development and pregnancy maintenance in elephants
Lueders, Imke; Niemuller, Cheryl; Rich, Peter; Gray, Charlie; Hermes, Robert; Goeritz, Frank; Hildebrandt, Thomas B.
2012-01-01
The corpus luteum, a temporally established endocrine gland, formed on the ovary from remaining cells of the ovulated follicle, plays a key role in maintaining the early mammalian pregnancy by secreting progesterone. Despite being a monovular species, 2–12 corpora lutea (CLs) were found on the elephant ovaries during their long pregnancy lasting on average 640 days. However, the function and the formation of the additional CLs and their meaning remain unexplained. Here, we show from the example of the elephant, the close relationship between the maternally determined luteal phase length, the formation of multiple luteal structures and their progestagen secretion, the timespan of early embryonic development until implantation and maternal recognition. Through three-dimensional and Colour Flow ultrasonography of the ovaries and the uterus, we conclude that pregnant elephants maintain active CL throughout gestation that appear as main source of progestagens. Two LH peaks during the follicular phase ensure the development of a set of 5.4 ± 2.7 CLs. Accessory CLs (acCLs) form prior to ovulation after the first luteinizing hormone (LH) peak, while the ovulatory CL (ovCL) forms after the second LH peak. After five to six weeks (the normal luteal phase lifespan), all existing CLs begin to regress. However, they resume growing as soon as an embryo becomes ultrasonographically apparent on day 49 ± 2. After this time, all pregnancy CLs grow significantly larger than in a non-conceptive luteal phase and are maintained until after parturition. The long luteal phase is congruent with a slow early embryonic development and luteal rescue only starts ‘last minute’, with presumed implantation of the embryo. Our findings demonstrate a highly successful reproductive solution, different from currently described mammalian models. PMID:22719030
Luteal maintenance of pregnancy in the African elephant (Loxodonta africana).
Stansfield, F J; Allen, W R
2012-06-01
The ovaries of eight African elephant foetuses and their mothers between 2 and 22 months of gestation, and those of two cycling and two lactating elephants, were examined grossly, histologically and immunocytochemically, with emphasis on the development and regression of accessory corpora lutea (CL) of pregnancy and the steroidogenic capacities of the accessory CL and the foetal ovaries. The results supported recent findings that the accessory CL form as a result of luteinisation, with and without ovulation, of medium-sized follicles during the 3-week inter-luteal period of the oestrous cycle. They enlarge significantly and become steroidogenically active around 5 weeks of gestation, probably in response to the placental lactogen which is secreted by the implanting trophoblast of the conceptus. The large luteal cells stained strongly for 3β hydroxysteroid dehydrogenase (3βHSD) activity throughout the 22-month gestation period although they showed vacuolation and other degenerative changes in the final months of gestation coincident with hypertrophy and hyperplasia of 3βHSD-positive interstitial cells in the foetal gonads. It is proposed that the progestagens secreted by the enlarged gonads of the elephant foetus may function both to assist the maternal ovaries in supporting the pregnancy state and to induce torpor and intrauterine immobility of the rapidly growing foetus. PMID:22457432
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.
Assessment of luteal function after surgical tubal sterilization.
Garza-Flores, J; Vázquez-Estrada, L; Reyes, A; Valero, A; Morales del Olmo, A; Alba, V M; Bonilla, C
1991-12-01
To evaluate ovarian luteal function after tubal occlusion, a group of women who underwent Pomeroy sterilization were studied. A prospective group I (n = 16) were followed for one year and scheduled for blood sampling every other day during their luteal phase before surgical procedure and at 3 and 12 months thereafter. Group II (n = 15) included women who were studied during their luteal phase at 1 or 5 years post-surgery. Mid-luteal progesterone and estradiol serum levels were calculated by estimating the average of at least 3 values of serum samples obtained in days 20-25 of a menstrual cycle. The data suggest that no major changes occur in ovarian function after surgical tubal occlusion, as assessed by the mid-luteal hormone serum levels, and underscore the safety of this procedure. PMID:1776562
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
Kiso, Minako; Manabe, Noboru; Komatsu, Kohji; Shimabe, Munetake; Miyamoto, Hajime
2003-12-01
Senescence accelerated mouse-prone (SAMP) mice with a shortened life span show accelerated changes in many of the signs of aging and a shorter reproductive life span than SAM-resistant (SAMR) controls. We previously showed that functional regression (progesterone dissimilation) occurs in abnormally accumulated luteal bodies (aaLBs) of SAMP mice, but structural regression of luteal cells in aaLB is inhibited. A deficiency of luteal cell apoptosis causes the abnormal accumulation of LBs in SAMP ovaries. In the present study, to show the abnormality of Fas ligand (FasL)/Fas-mediated apoptosis signal transducing factors in the aaLBs of the SAMP ovaries, we assessed the changes in the expression of FasL, Fas, caspase-8 and caspase-3 mRNAs by reverse transcription-polymerase chain reaction, and in the expression and localization of FasL, Fas and activated caspase-3 proteins by Western blotting and immunohistochemistry, respectively, during the estrus cycle/luteolysis. These mRNAs and proteins were expressed in normal LBs of both SAMP and SAMR ovaries, but not at all or only in trace amounts in aaLBs of SAMP, indicating that structural regression is inhibited by blockage of the expression of these transducing factors in luteal cells of aaLBs in SAMP mice. PMID:14967896
Alpha Induced Reaction Cross Section Calculations of Tantalum Nucleus
NASA Astrophysics Data System (ADS)
Tel, E.; Ugur, F. A.; Gokce, A. A.
2013-04-01
The fusion energy is attractive as an energy source because the fusion will not produce CO2 or SO2 and so fusion will not contribute to environmental problems, such as particulate pollution and excessive CO2 in the atmosphere. The fusion reaction does not produce radioactive nuclides and it is not self-sustaining, as is a fission reaction when a critical mass of fissionable material is assembled. Since the fusion reaction is easily and quickly quenched the primary sources of heat to drive such an accident are heat from radioactive decay and heat from chemical reactions. Both the magnitude and time dependence of the generation of heat from radioactive decay can be controlled by proper selection and design of materials. Tantalum is one of the candidate materials for the first wall of fusion reactors and for component parts of irradiation chambers. Accurate experimental cross-section data of alpha induced reactions on Tantalum are also of great importance for thermonuclear reaction rate determinations since the models used in the study of stellar nucleosynthesis are strongly dependent on these rates (Santos et al. in J Phys G 26:301, 2000). In this study, neutron-production cross sections for target nuclei 181Ta have been investigated up to 100 MeV alpha energy. The excitation functions for (α, xn) reactions (x = 1, 2, 3) have been calculated by pre-equilibrium reaction mechanism. And also neutron emission spectra for 181Ta (α, xn) reactions at 26.8 and 45.2 MeV have been calculated. The mean free path multiplier parameters has been investigated. The pre-equilibrium results have been calculated by using the hybrid model, the geometry dependent hybrid (GDH) model. Calculation results have been also compared with the available measurements in literature.
Kol, Shahar; Breyzman, Tatiana; Segal, Linoy; Humaidan, Peter
2015-12-01
This study reports 21 IVF cases with excessive ovarian response, who received gonadotrophin-releasing hormone agonist (GnRHa) triggering for final oocyte maturation, followed by a human chorionic gonadotrophin (HCG)-based, progesterone-free, luteal support, individually timed ('luteal coasting') according to endogenous luteal progesterone concentrations. One patient developed a brief early-onset moderate ovarian hyperstimulation syndrome (OHSS) condition. Six clinical pregnancies were achieved, two of which have resulted in live births thus far. To further individualize the luteal phase support post GnRHa trigger, the same principle that holds for follicular coasting, used in the context of OHSS prevention, may be valid. Monitoring luteal progesterone concentrations from the day of oocyte retrieval, and administering a bolus of HCG (1500 IU) when the concentration drops significantly, seems to facilitate fresh embryo transfer, even in patients with excessive ovarian responses. PMID:26507279
Luteal blood flow in patients undergoing GnRH agonist long protocol
2011-01-01
Background Blood flow in the corpus luteum (CL) is closely related to luteal function. It is unclear how luteal blood flow is regulated. Standardized ovarian-stimulation protocol with a gonadotropin-releasing hormone agonist (GnRHa long protocol) causes luteal phase defect because it drastically suppresses serum LH levels. Examining luteal blood flow in the patient undergoing GnRHa long protocol may be useful to know whether luteal blood flow is regulated by LH. Methods Twenty-four infertile women undergoing GnRHa long protocol were divided into 3 groups dependent on luteal supports; 9 women were given ethinylestradiol plus norgestrel (Planovar) orally throughout the luteal phase (control group); 8 women were given HCG 2,000 IU on days 2 and 4 day after ovulation induction in addition to Planovar (HCG group); 7 women were given vitamin E (600 mg/day) orally throughout the luteal phase in addition to Planovar (vitamin E group). Blood flow impedance was measured in each CL during the mid-luteal phase by transvaginal color-pulsed-Doppler-ultrasonography and was expressed as a CL-resistance index (CL-RI). Results Serum LH levels were remarkably suppressed in all the groups. CL-RI in the control group was more than the cutoff value (0.51), and only 2 out of 9 women had CL-RI values < 0.51. Treatments with HCG or vitamin E significantly improved the CL-RI to less than 0.51. Seven of the 8 women in the HCG group and all of the women in the vitamin E group had CL-RI < 0.51. Conclusion Patients undergoing GnRHa long protocol had high luteal blood flow impedance with very low serum LH levels. HCG administration improved luteal blood flow impedance. This suggests that luteal blood flow is regulated by LH. PMID:21219663
Suganthi, Hepziba; Rudraiah, Medhamurthy
2014-01-01
In several species including the buffalo cow, prostaglandin (PG) F2α is the key molecule responsible for regression of corpus luteum (CL). Experiments were carried out to characterize gene expression changes in the CL tissue at various time points after administration of luteolytic dose of PGF2α in buffalo cows. Circulating progesterone levels decreased within 1 h of PGF2α treatment and evidence of apoptosis was demonstrable at 18 h post treatment. Microarray analysis indicated expression changes in several of immediate early genes and transcription factors within 3 h of treatment. Also, changes in expression of genes associated with cell to cell signaling, cytokine signaling, steroidogenesis, PG synthesis and apoptosis were observed. Analysis of various components of LH/CGR signaling in CL tissues indicated decreased LH/CGR protein expression, pCREB levels and PKA activity post PGF2α treatment. The novel finding of this study is the down regulation of CYP19A1 gene expression accompanied by decrease in expression of E2 receptors and circulating and intra luteal E2 post PGF2α treatment. Mining of microarray data revealed several differentially expressed E2 responsive genes. Since CYP19A1 gene expression is low in the bovine CL, mining of microarray data of PGF2α-treated macaques, the species with high luteal CYP19A1 expression, showed good correlation between differentially expressed E2 responsive genes between both the species. Taken together, the results of this study suggest that PGF2α interferes with luteotrophic signaling, impairs intra-luteal E2 levels and regulates various signaling pathways before the effects on structural luteolysis are manifest. PMID:25102061
Technology Transfer Automated Retrieval System (TEKTRAN)
We tested the hypotheses that interval from urine exposure to resumption of luteal activity and proportions of cows that resume luteal activity by the end of the urine-exposure period do not differ between cows exposed to mature bull urine or steer urine. Thirty-eight Angus x Hereford cows, four mat...
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.
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
Mechanisms behind intrauterine device-induced luteal persistence in mares.
Rivera Del Alamo, M M; Reilas, T; Kindahl, H; Katila, T
2008-08-01
Intrauterine glass balls are used to prevent oestrous signs in sports mares, but the mechanism of action is unknown. It has been suggested that the glass ball can mimic an embryo or act via an induced chronic uterine inflammation and absent or continuous low-grade prostaglandin (PG) release. The purpose of this study was to induce prolonged luteal function in mares using a small intrauterine device (IUD) and to study the mechanisms behind prolonged IUD-induced luteal function. A uterine swab and a biopsy specimen were obtained in early oestrus. A water-filled plastic ball, diameter 20mm and weight 3.6g, was inserted into the uterus 2-4 days after ovulation; the control mares underwent similar cervical manipulation without ball insertion. The mares were examined three times per week until day 23 and twice weekly thereafter until they returned to oestrus (transrectal palpation, ultrasonography and progesterone determination). The location of the IUD was recorded and ultrasound scans were video-recorded to assess the frequency of uterine contractions. When the mare returned to oestrus, a uterine swab and biopsy specimen were obtained and the bacteriological, cytological and histological (inflammation and glandular dilation) results compared with the samples obtained before the IUD insertion. The PG F(2alpha) metabolite levels were measured in the plasma of four control mares and eight IUD mares on days 11-16. The IUD induced a prolonged luteal phase in 75% of the mares (9/12; IUD-P); the mean dioestrous length was 57.0 days. The three mares that did not respond to the IUD (IUD-N) showed a mean dioestrous length of 15.7 days and the 12 control mares 16.1 days. The inflammation and glandular dilation scores were not significantly different in pre- and post-manipulation biopsy specimens. Although locational changes of the IUD were observed, they occurred over very small distances and were mostly limited within the body-bifurcation area. The IUD-N and control mares showed
The role of adrenergic activation on murine luteal cell viability and progesterone production.
Wang, Jing; Tang, Min; Jiang, Huaide; Wu, Bing; Cai, Wei; Hu, Chuan; Bao, Riqiang; Dong, Qiming; Xiao, Li; Li, Gang; Zhang, Chunping
2016-09-15
Sympathetic innervations exist in mammalian CL. The action of catecholaminergic system on luteal cells has been the focus of a variety of studies. Norepinephrine (NE) increased progesterone secretion of cattle luteal cells by activating β-adrenoceptors. In this study, murine luteal cells were treated with NE and isoprenaline (ISO). We found that NE increased the viability of murine luteal cells and ISO decreased the viability of luteal cells. Both NE and ISO promoted the progesterone production. Nonselective β-adrenergic antagonist, propranolol reversed the effect of ISO on cell viability but did not reverse the effect of NE on cell viability. Propranolol blocked the influence of NE and ISO on progesterone production. These results reveal that the increase of luteal cell viability induced by NE is not dependent on β-adrenergic activation. α-Adrenergic activation possibly contributes to it. Both NE and ISO increased progesterone production through activating β-adrenergic receptor. Further study showed that CyclinD2 is involved in the increase of luteal cell induced by NE. 3β-Hydroxysteroid dehydrogenase, LHR, steroidogenic acute regulatory protein (StAR), and PGF2α contribute to the progesterone production induced by NE and ISO. PMID:27173955
Luteal activity of pregnant rats with hypo-and hyperthyroidism
2014-01-01
Background Luteal activity is dependent on the interaction of various growth factors, cytokines and hormones, including the thyroid hormones, being that hypo- and hyperthyroidism alter the gestational period and are also a cause of miscarriage and stillbirth. Because of that, we evaluated the proliferation, apoptosis and expression of angiogenic factors and COX-2 in the corpus luteum of hypo- and hyperthyroid pregnant rats. Methods Seventy-two adult female rats were equally distributed into three groups: hypothyroid, hyperthyroid and control. Hypo- and hyperthyroidism were induced by the daily administration of propylthiouracil and L-thyroxine, respectively. The administration began five days before becoming pregnant and the animals were sacrificed at days 10, 14, and 19 of gestation. We performed an immunohistochemical analysis to evaluate the expression of CDC-47, VEGF, Flk-1 (VEGF receptor) and COX-2. Apoptosis was evaluated by the TUNEL assay. We assessed the gene expression of VEGF, Flk-1, caspase 3, COX-2 and PGF2α receptor using real time RT-PCR. The data were analyzed by SNK test. Results Hypothyroidism reduced COX-2 expression on day 10 and 19 (P < 0.05), endothelial/pericyte and luteal cell proliferation on day 10 and 14 (p < 0.05), apoptotic cell numbers on day 19 (p < 0.05) and the expression of Flk-1 and VEGF on day 14 and 19, respectively (p < 0.05). Hyperthyroidism increased the expression of COX-2 on day 19 (P < 0.05) and the proliferative activity of endothelial/pericytes cells on day 14 (p <0.05), as well as the expression of VEGF and Flk-1 on day 19 (P < 0.05). Conclusions Hypothyroidism reduces the proliferation, apoptosis and expression of angiogenic factors and COX-2in the corpus luteum of pregnant rats, contrary to what is observed in hyperthyroid animals, being this effect dependent of the gestational period. PMID:25298361
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
Tsou, T.-C. . E-mail: tctsou@nhri.org.tw; Yeh, Szu Ching; Tsai, E.-M.; Tsai, F.-Y.; Chao, H.-R.; Chang, Louis W.
2005-11-15
Epidemiological studies demonstrated a high association of vascular diseases with arsenite exposure. We hypothesize that arsenite potentiates the effect of proinflammatory cytokines on vascular endothelial cells, and hence contributes to atherosclerosis. In this study, we investigated the effect of arsenite and its induction of glutathione (GSH) on vascular cell adhesion molecule-1 (VCAM-1) protein expression in human umbilical vein endothelial cells (HUVECs) in response to tumor necrosis factor-{alpha} (TNF-{alpha}), a typical proinflammatory cytokine. Our study demonstrated that arsenite pretreatment potentiated the TNF-{alpha}-induced VCAM-1 expression with up-regulations of both activator protein-1 (AP-1) and nuclear factor-{kappa}B (NF-{kappa}B). To elucidate the role of GSH in regulation of AP-1, NF-{kappa}B, and VCAM-1 expression, we employed L-buthionine (S,R)-sulfoximine (BSO), a specific {gamma}-glutamylcysteine synthetase ({gamma}-GCS) inhibitor, to block intracellular GSH synthesis. Our investigation revealed that, by depleting GSH, arsenite attenuated the TNF-{alpha}-induced VCAM-1 expression as well as a potentiation of AP-1 and an attenuation of NF-{kappa}B activations by TNF-{alpha}. Moreover, we found that depletion of GSH would also attenuate the TNF-{alpha}-induced VCAM-1 expression with a down-regulation of the TNF-{alpha}-induced NF-{kappa}B activation and without significant effect on AP-1. On the other hand, the TNF-{alpha}-induced VCAM-1 expression could be completely abolished by inhibition of AP-1 or NF-{kappa}B activity, suggesting that activation of both AP-1 and NF-{kappa}B was necessary for VCAM-1 expression. In summary, we demonstrate that arsenite enhances the TNF-{alpha}-induced VCAM-1 expression in HUVECs via regulation of AP-1 and NF-{kappa}B activities in a GSH-sensitive manner. Our present study suggested a potential mechanism for arsenite in the induction of vascular inflammation and vascular diseases via modulating the actions
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.
Lipid droplets in cultured luteal cells in non-pregnant sheep fed different planes of nutrition.
Khanthusaeng, Vilaivan; Thammasiri, Jiratti; Bass, Casie S; Navanukraw, Chainarong; Borowicz, Pawel; Redmer, Dale A; Grazul-Bilska, Anna T
2016-07-01
Accumulation of lipid droplets (LD) in luteal cells likely is important for energy storage and steroidogenesis in the highly metabolically active corpus luteum (CL). The objective of this study was to determine the effect of plane of nutrition on progesterone (P4) secretion, and lipid droplet number and size in cultured ovine luteal cells. Ewes were randomly assigned to one of three nutritional groups: control (C; 100% NRC requirements, n=9), overfed (O; 2×C, n=12), or underfed (U; 0.6×C, n=10). Superovulation was induced by follicle stimulating hormone injections. At the early and mid-luteal phases of the estrous cycle, CL were dissected from ovaries, and luteal cells isolated enzymatically. Luteal cells were incubated overnight in medium containing serum in chamber slides. Media were then changed to serum-free and after 24h incubation, media were collected for P4 analysis, and cells were fixed in formalin and stained with BODIPY followed by DAPI staining. Z-stacks of optical sections of large and small luteal cells (LLC and SLC, respectively) were obtained using a laser-scanning microscope. Rendered 3D images of individual LLC and SLC were analyzed for cell volume, and total and individual LD volume, number and percentage of cellular volume occupied by LD by using Imaris software. Concentrations of P4 in serum and media were greater (P<0.05) at the mid than early-luteal phase, and were not affected by nutritional plane. LD total volume and number were greater (P<0.001) in LLC than SLC; however, mean volume of individual LD was greater (P<0.02) in SLC than LLC. In LLC, total LD volume was greater (P<0.02) in O than C and U ewes. In SLC, total LD volume and number was greater (P<0.003) at the mid than early-luteal phase, and percentage of cell volume occupied by LD was greater (P<0.002) in U than C and O ewes. These data demonstrate that both stage of luteal development and nutritional plane affect selected LD measurements and thus may affect luteal functions
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
Farberov, Svetlana; Meidan, Rina
2016-01-01
Thrombospondin-1 (THBS1) and transforming growth factor-beta1 (TGFB1) are specifically up-regulated by prostaglandin F2alpha in mature corpus luteum (CL). This study examined the relationship between the expression of THBS1 and TGFB1 and the underlying mechanisms of their actions in luteal endothelial cells (ECs). TGFB1 stimulated SMAD2 phosphorylation and SERPINE1 levels in dose- and time-dependent manners in luteal EC. THBS1 also elevated SERPINE1; this effect was abolished by TGFB1 receptor-1 kinase inhibitor (SB431542). The findings here further imply that THBS1 activates TGFB1 in luteal ECs: THBS1 increased the effects of latent TGFB1 on phosphorylated SMAD (phospho-SMAD) 2 and SERPINE1. THBS1 silencing significantly decreased SERPINE1 and levels of phospho-SMAD2. Lastly, THBS1 actions on SERPINE1 were inhibited by LSKL peptide (TGFB1 activation inhibitor); LSKL also counteracted latent TGFB1-induced phospho-SMAD2. We found that TGFB1 up-regulated its own mRNA levels and those of THBS1. Both compounds generated apoptosis, but THBS1 was significantly more effective (2.5-fold). Notably, this effect of THBS1 was not mediated by TGFB1. THBS1 and TGFB1 also differed in their activation of p38 mitogen-activated protein kinase. Whereas TGFB1 rapidly induced phospho-p38, THBS1 had a delayed effect. Inhibition of p38 pathway by SB203580 did not modulate TGFB1 effect on cell viability, but it amplified THBS1 actions. THBS1-stimulated caspase-3 activation coincided with p38 phosphorylation, suggesting that caspase-induced DNA damage initiated p38 phosphorylation. The in vitro data suggest that a feed-forward loop exists between THBS1, TGFB1, and SERPINE1. Indeed all these three genes were similarly induced in the regressing CL. Their gene products can promote vascular instability, apoptosis, and matrix remodeling during luteolysis. PMID:26658711
Hypercapnic blood pressure response is greater during the luteal phase of the menstrual cycle.
Edwards, N; Wilcox, I; Polo, O J; Sullivan, C E
1996-11-01
We investigated the cardiovascular responses to acute hypercapnia during the menstrual cycle. Eleven female subjects with regular menstrual cycles performed hypercapnic rebreathing tests during the follicular and luteal phases of their menstrual cycles. Ventilatory and cardiovascular variables were recorded breath by breath. Serum progesterone and estradiol were measured on each occasion. Serum progesterone was higher during the luteal [50.4 +/- 9.6 (SE) nmol/l] than during the follicular phase (2.1 +/- 0.7 nmol/l; P < 0.001), but serum estradiol did not differ (follicular phase, 324 +/- 101 pmol/l; luteal phase, 162 +/- 71 pmol/l; P = 0.61). The systolic blood pressure responses during hypercapnia were 2.0 +/- 0.3 and 4.0 +/- 0.5 mmHg/Torr (1 Torr = 1 mmHg rise in end-tidal PCO2) during the follicular and luteal phases, respectively, of the menstrual cycle (P < 0.01). The diastolic blood pressure responses were 1.1 +/- 0.2 and 2.1 +/- 0.3 mmHg/Torr during the follicular and luteal phases, respectively (P < 0.002). Heart rate responses did not differ during the luteal (1.7 +/- 0.3 beats.min-1.Torr-1) and follicular phases (1.4 +/- 0.3 beats.min-1.Torr-1; P = 0.59). These data demonstrate a greater pressor response during the luteal phase of the menstrual cycle that may be related to higher serum progesterone concentrations. PMID:8941539
2012-01-01
Background Studies suggested that microRNAs influence cellular activities in the uterus including cell differentiation and embryo implantation. In assisted reproduction cycles, luteal phase support, given to improve endometrial characteristics and to facilitate the implantation process, has been a standard practice. The effect of different types of luteal phase support using steroid hormones in relation to endometrial miRNA profiles during the peri-implantation period has not seen described. This study was designed to evaluate the expression of miRNAs during the luteal phase following controlled ovarian stimulation for IVF and the influence of different luteal phase support protocols on miRNA profiles. Methods The study was approved by the Johns Hopkins Hospital Institutional Review Board. Endometrial biopsies were obtained on the day of oocyte retrieval from 9 oocyte donors (group I). An additional endometrial biopsy was obtained 3–5 days later (Group II) after the donors were randomized into three groups. Group IIa had no luteal-phase support, group IIb had luteal support with micronized progesterone (P), and Group IIc had luteal support with progesterone plus 17-beta-estradiol (P + E). Total RNA was isolated and microarray analysis was performed using an Illumina miRNA expression panel. Results A total of 526 miRNAs were identified. Out of those, 216 miRNAs were differentially regulated (p < 0.05) between the comparison groups. As compared to the day of retrieval, 19, 11 and 6 miRNAs were differentially regulated more than 2 fold in the groups of no support, in the P support only, and in the P + E support respectively, 3–5 days after retrieval. During the peri-implantation period (3–5 days after retrieval) the expression of 33 and 6 miRNAs increased, while the expression of 3 and 0 miRNAs decreased, in the P alone and in the P + E group respectively as compared to the no steroid supplementation group. Conclusion Luteal support
Tay, P Y; Lenton, E A
2003-06-01
A prospective randomised study was done to assess the effect of supplemental oestradiol in addition to progesterone on the luteal steroid profiles and pregnancy outcome in stimulated cycles with and without pituitary down regulation. Women undergoing stimulated cycle IVF with GnRH-a and FSH (Group A, n = 63) or stimulated intrauterine insemination using CC and FSH (Group B, n = 55) were studied. These subjects were randomly allocated to receive either 400 mg daily of vaginally administrated Cyclogest (progesterone) alone or in combination with 2 mg daily of oral Oestradiol Valerate (E2V) during the luteal phase. Significant lower concentrations of plasma progesterone were observed in those subjects supplemented with both E2V and progesterone compared to those in whom progesterone only was given during the luteal phase (P < 0.05). Exogenous E2V had a minimal impact on plasma oestradiol concentrations and did not disguise the characterised mid luteal decline in oestradiol secretion. The suppressive effect of E2V on plasma progesterone was lost if implantation occurred normally because any small change in steroid concentrations was reversed by the rapidly increasing concentrations of HCG. Similar pregnancy rates were observed among subjects supplemented with or without oestradiol. The addition of oestradiol to the luteal supplement suppresses endogenous corpus luteum progesterone secretion irrespective of the type of assisted conception cycle and that its use is unlikely to be beneficial to the process of implantation. PMID:14569738
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.
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.
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. PMID:26600292
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.
Andoh, Akira; Hata, Kazunori; Shimada, Mitsue; Fujino, Sanae; Tasaki, Kazuhito; Bamba, Shigeki; Araki, Yoshio; Fujiyama, Yoshihide; Bamba, Tadao
2002-07-01
Pancreatic periacinar myofibroblasts are considered to be therapeutic targets for the suppression of acute pancreatitis. To elucidate the mechanisms mediating the therapeutic actions of somatostatin on acute pancreatitis, we investigated how somatostatin affects the tumor necrosis factor (TNF)-alpha-induced interleukin (IL)-6 and IL-8 secretion from pancreatic myofibroblasts. Cytokine secretion was determined by enzyme-linked immunosorbent assay (ELISA) and Northern blotting. Nuclear factor (NF)-kappaB DNA-binding activity was evaluated by electrophoretic mobility shift assay (EMSAs). The expression of somatostatin receptor (SSTR) mRNA was evaluated by reverse transcription-polymerase chain reaction (RT-PCR). Somatostatin dose-dependently inhibited the TNF-alpha-induced IL-6 secretion. In comparison, the effects on IL-8 secretion were modest. Northern blot analysis demonstrated that somatostatin decreased the TNF-alpha-induced IL-6 mRNA expression, and that this effect was completely blocked by the somatostatin antagonist cyclo-somatostatin. Furthermore, somatostatin suppressed TNF-alpha-induced NF-kappaB activation. These cells bear SSTR subtypes 1 and 2. Somatostatin down-regulated the TNF-alpha-induced IL-6 secretion in human pancreatic periacinar myofibroblasts. These findings suggest that some of the therapeutic actions of somatostatin on acute pancreatitis might be mediated by reducing local IL-6 secretion in the pancreas. PMID:12060857
Pregnancy-associated changes in uterine-luteal relationships in cows: A mini-review.
Sakumoto, Ryosuke
2016-06-01
The main function of the bovine corpus luteum (CL) is the production of progesterone. Adequate luteal progesterone is crucial for determining the physiological duration of the estrous cycle and for achieving a successful pregnancy. The CL is regulated not only by hypophyseal gonadotropin, but also by a number of intraluteal substances including steroids, peptides and prostaglandins. Although regulation of luteal function throughout the estrous cycle has been intensively studied, studies of the CL during the entire gestation period are limited. Understanding the role of luteal function during pregnancy might lead to ways to improve reproductive efficiencies and reduce the number of defective fetuses. Therefore, the purpose of this review is to summarize our current understanding of the gene expression profiles of bovine CL throughout the gestation period and to focus on recent studies documenting the interactions between the CL, uterus and conceptus in cows. PMID:27288343
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
Nio-Kobayashi, Junko; Kudo, Masataka; Sakuragi, Noriaki; Kimura, Shunsuke; Iwanaga, Toshihiko; Duncan, W Colin
2015-08-01
Intense macrophage infiltration is observed during luteolysis in various animals including women; however, we still do not know how macrophage infiltration into the human corpus luteum (CL) during luteolysis is regulated. In this study, we examined the expression, localization and regulation of an important chemokine for the recruitment of monocyte/macrophage lineages, C-C motif ligand 2 (CCL2), in the human CL across the luteal phase and in cultured human luteinized granulosa cells (LGCs), with special reference to the number of infiltrating macrophages and luteal cell function. CCL2 mRNA increased in the non-functional regressing CL during menstruation (P < 0.01), corresponding to an elevated mRNA expression of a macrophage-derived cytokine, tumor necrosis factor (TNF), and an increased number of infiltrating macrophages positively stained with a macrophage marker, CD68. CCL2 protein was immunohistochemically localized to the cytoplasm of granulosa-lutein and theca-lutein cells, and CCL2 mRNA was significantly reduced by hCG both in vivo (P < 0.05) and in vitro (P < 0.01). CCL2 was also down-regulated by luteotrophic prostaglandin (PG) E (P < 0.0001), but up-regulated by luteolytic PGF (P < 0.05) in vitro. Administration of TNF significantly enhanced the CCL2 mRNA expression in cultured LGCs (P < 0.01). A greater abundance of infiltrating macrophages were found around granulosa-lutein cells lacking 3β-HSD or PGE synthase (PGES) immunostaining. CCL2 mRNA expression was negatively correlated with both HSD3B1 and PGES, suggesting that locally produced progesterone and PGE suppress macrophage infiltration into the CL. Taken together, the infiltration of macrophages in the human CL is regulated by endocrine and paracrine molecules via regulation of the CCL2 expression in luteal cells. PMID:26003810
Human granulosa-luteal cells initiate an innate immune response to pathogen-associated molecules.
Ibrahim, Laila A; Kramer, Joseph M; Williams, R Stan; Bromfield, John J
2016-10-01
The microenvironment of the ovarian follicle is key to the developmental success of the oocyte. Minor changes within the follicular microenvironment can significantly disrupt oocyte development, compromising the formation of competent embryos and reducing fertility. Previously described as a sterile environment, the ovarian follicle of women has been shown to contain colonizing bacterial strains, whereas in domestic species, pathogen-associated molecules are concentrated in the follicular fluid of animals with uterine infection. The aim of this study is to determine whether human granulosa-luteal cells mount an innate immune response to pathogen-associated molecules, potentially disrupting the microenvironment of the ovarian follicle. Human granulosa-luteal cells were collected from patients undergoing assisted reproduction. Cells were cultured in the presence of pathogen-associated molecules (LPS, FSL-1 and Pam3CSK4) for 24h. Supernatants and total RNA were collected for assessment by PCR and ELISA. Granulosa-luteal cells were shown to express the molecular machinery required to respond to a range of pathogen-associated molecules. Expression of TLR4 varied up to 15-fold between individual patients. Granulosa-luteal cells increased the expression of the inflammatory mediators IL1B, IL6 and CXCL8 in the presence of the TLR4 agonist E. coli LPS. Similarly, the TLR2/6 ligand, FSL-1, increased the expression of IL6 and CXCL8. Although no detectable changes in CYP19A1 or STAR expression were observed in granulosa-luteal cells following challenge, a significant reduction in progesterone secretion was measured after treatment with FSL-1. These findings demonstrate the ability of human granulosa-luteal cells to respond to pathogen-associated molecules and generate an innate immune response. PMID:27512120
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.
ABE, HIROYUKI; ONODERA, MASAKAZU; SUGAWARA, SHICHIRO; SATOH, TAKESHI; HOSHI, HIROYOSHI
1999-01-01
The aim of the present study was to investigate the ultrastructure of secretory cells in the various regions of the goat oviduct during the follicular and luteal phases of the oestrous cycle. During the follicular phase in the fimbriae, the secretory cells contained small secretory granules with electron-dense matrices. In the luteal phase, the secretory granules disappeared and cytoplasmic protrusions, extending beyond the luminal border of the ciliated cells and often containing the nucleus, were predominant. During the follicular phase in ampullary secretory cells, numerous secretory granules with moderately electron-dense matrices were present in the supranuclear cytoplasm and exocytosis of secretory granules was observed. The number of secretory granules was dramatically reduced in the ampullary secretory cells at the luteal phase. Conspicuous cytoplasmic protrusions of secretory cells were observed similar to those of the fimbrial epithelium. Isthmic cells were almost free of secretory granules and lysosome-like bodies were found both at the follicular and luteal phases. In conclusion, our ultrastructural observations of goat oviduct revealed marked cyclic changes in the ultrastructural features of secretory cells and the ultrastructural features and the numbers of secretory granules were distinctive for each particular segment. PMID:10634690
Natural Micronized Progesterone Sustained Release (SR) and Luteal Phase: Role Redefined!!
Malik, Sonia; Krishnaprasad, Korukonda
2016-02-01
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
Destro, F C; Martin, I; Landim-Alvarenga, Fdc; Ferreira, Jcp; Pate, J L
2016-10-01
The aim of this study was to evaluate the effects of concanavalin A (CONA) on the progesterone (P4) production by bovine steroidogenic luteal cells (LCs) in vitro. Luteal cells were collected during the mid-luteal stage (at 10-12 days following ovulation) and processed in the laboratory. Luteal cells were grown for 7 days in a humid atmosphere with 5% CO2 , with or without 10% foetal bovine serum, and were subjected to the following treatments: control: no treatment; CONA (10 μg/ml); LH (100 μg/ml); CONA + LH; LH (100 μg/ml) + prostaglandin F2α (PGF2α) (10 ng/ml); CONA + LH + PGF2α. Samples of the culture media were collected on days 1 (D1) and 7 (D7) for P4 quantification. The cells were counted on D7 of culture. Differences between treatments were considered statistically significant at p < .05. Culture in the presence of CONA decreased the P4-secreting capacity of LCs on D7 of culture, particularly in the absence of serum. The cell numbers did not change between treatments. PMID:27558864
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
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 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...
Sugino, N; Zilberstein, M; Srivastava, R K; Telleria, C M; Nelson, S E; Risk, M; Chou, J Y; Gibori, G
1998-04-01
The primary culture of rat luteal cells and their long-term maintenance have been difficult. Low cellular yields have limited the possibility for the study of gene regulation in luteal cells. The goal of this study was to develop a cell line to serve as a model by which to study the expression and regulation of various genes specific to luteal cells. We attempted to develop a luteal cell line by transformation of large luteal cells through infection with a temperature-sensitive simian virus (SV-40 tsA209) mutant that has a temperature-sensitive mutation required for the maintenance of cell transformation. We report here the successful establishment of such a cell line, designated GG-CL cells. Large luteal cells were purified to homogeneity by flow cytometry from corpora lutea of day 14 pregnant rats, cultured for 24 h, and then infected with the SV-40 tsA209 mutant virus. Transformed cells were maintained at the permissive temperature (33 C) until colonies were identified. Several colonies of transformed cells were isolated and passaged. They multiplied at 33 C and formed multilayers. At the nonpermissive temperature (40 C), cells reverted to the normal differentiated phenotype similar to the primary luteal cells in culture. To determine whether GG-CL cells express the genes found in normal luteal cells, messenger RNA (mRNA) expression was examined by either Northern analysis or RT-PCR with primers specific to each mRNA. GG-CL cells were found to express receptors for interleukin-6 and glucocorticoid, as well as the newly discovered estrogen receptor-beta (ER-beta) and the orphan nuclear receptor nur 77. No receptors for ER-alpha, progesterone, LH, or PRL could be detected. This cell line also expressed 20alpha-hydroxysteroid dehydrogenase (20alpha-HSD), but not cholesterol side-chain cleavage cytochrome P450 (P450scc), 3beta-hydroxysteroid dehydrogenase, or aromatase cytochrome P450 (P450arom). Although the cells did not express the PRL receptor, they did express
Probo, Monica; Comin, Antonella; Mollo, Antonio; Cairoli, Fausto; Stradaioli, Giuseppe; Veronesi, Maria C
2011-09-01
In dairy farm management economic losses resulting from cystic ovarian degeneration are well known. In spite of this, neither the definition nor the aetiopathology of ovarian cysts are clear and agreed upon. Also the usual classification in luteal and follicular cysts, requiring ultrasound examination together with assessment of P4 to be accurate, is not very helpful in field conditions. Consequently a single treatment is often provided for both types of cysts, and since the 1970s treatments with GnRH and its analogues have been considered very useful. Nevertheless differences in recovery rates after GnRH treatment in animals with either luteal or follicular cysts are reported. Thus, the aim of this study was to evaluate recovery rate, recovery time and conception rate after treatment with buserelin (GnRH-analogue) in cows with ovarian luteal or follicular cysts. In a 5 years period, 150 cows with cysts out of a total of 990 animals, were detected and treated intravenously between 45 and 60 days PP with 20μg buserelin. No statistically significant differences were found in recovery rates and in conception rates between the two types of cysts. Comparison of recovery times showed significantly shorter recovery for cows with luteal cysts. The results emphasise the usefulness of GnRH to treat ovarian cysts regardless of their type, in relation to both recovery and conception rates. Intervals from treatment to resumption of ovarian activity were affected by the characteristics of ovarian cysts, with a faster recovery for the luteal type. PMID:21920681
Khosravi, Donya; Taheripanah, Robabeh; Taheripanah, Anahita; Tarighat Monfared, Vahid; Hosseini-Zijoud, Seyed-Mostafa
2015-01-01
Background: The aim of this study, we have compared the advantages of oral dydrogestrone with vaginal progesterone (cyclogest) for luteal support in intrauterine insemination (IUI) cycles. Progesterone supplementation is the first line treatment when luteal phase deficiency (LPD) can reasonably be assumed. Objective: This study was conduct to compare the effect of oral dydrogestrone with vaginal Cyclogest on luteal phase support in the IUI cycles. Materials and Methods: This prospective, randomized, double blind study was performed in a local infertility center from May 2013 to May 2014. It consisted of 150 infertile women younger than35years old undergoing ovarian stimulation for IUI cycles. They underwent ovarian stimulation with oral dydrogesterone (20 mg) as group A and vaginal cyclogest (400 mg) as group B in preparation for the IUI cycles. Clinical pregnancy and abortion rates, mid luteal progesterone (7daysafter IUI) and patient satisfaction were compared between two groups. Results: The mean serum progesterone levels was significantly higher in group A in comparison with group B (p=0.001). Pregnancy rates in group A was not statistically different in comparison with group B (p =0.58). Abortion rate in two groups was not statistically different (p =0.056) although rate of abortion was higher in group B in comparison with A group. Satisfaction rates were significantly higher in group A compared to group B (p<0.001). Conclusion: We concluded that oral dydrogestrone is effective as vaginal progesterone for luteal-phase support in woman undergoing IUI cycles. Moreover, the mean serum progesterone levels and satisfaction rates in dydrogestrone group were higher than cyclogest group. PMID:26494991
Huang, Dong; Cabral, Ricardo; De la Torre, Fernando
2016-02-01
Discriminative methods (e.g., kernel regression, SVM) have been extensively used to solve problems such as object recognition, image alignment and pose estimation from images. These methods typically map image features ( X) to continuous (e.g., pose) or discrete (e.g., object category) values. A major drawback of existing discriminative methods is that samples are directly projected onto a subspace and hence fail to account for outliers common in realistic training sets due to occlusion, specular reflections or noise. It is important to notice that existing discriminative approaches assume the input variables X to be noise free. Thus, discriminative methods experience significant performance degradation when gross outliers are present. Despite its obvious importance, the problem of robust discriminative learning has been relatively unexplored in computer vision. This paper develops the theory of robust regression (RR) and presents an effective convex approach that uses recent advances on rank minimization. The framework applies to a variety of problems in computer vision including robust linear discriminant analysis, regression with missing data, and multi-label classification. Several synthetic and real examples with applications to head pose estimation from images, image and video classification and facial attribute classification with missing data are used to illustrate the benefits of RR. PMID:26761740
Tumor necrosis factor-alpha-induced apoptosis in hepatocytes in long-term culture.
Bour, E. S.; Ward, L. K.; Cornman, G. A.; Isom, H. C.
1996-01-01
Apoptosis occurs naturally in the liver and increases in specific pathogenic processes. We previously described the use of a chemically defined medium supplemented with epidermal growth factor and dimethylsulfoxide to maintain rat hepatocytes in a highly differentiated state for more than 30 days (long-term culture). In this study, we showed that hepatocytes in long-term dimethylsulfoxide culture have definite advantages over using cells in short-term culture (cells in culture for 2 to 4 days) to study apoptosis. We demonstrated that treatment with tumor necrosis factor (TNF)-alpha induced apoptosis (detected morphologically and by formation of an oligonucleosomal DNA ladder) only in hepatocytes that had been subjected to dimethylsulfoxide removal. Neither treatment with TNF-alpha alone or dimethylsulfoxide removal alone induced apoptosis. Apoptosis could be induced by concentrations as low as 500 U of TNF-alpha/ml. Although a DNA ladder was not detected by 12 hours after TNF-alpha treatment, it was easily identified by 24 hours. We conclude that this system can be used 1) to examine the underlying mechanism by which TNF-alpha causes apoptosis in hepatocytes and 2) to study induction of apoptosis in hepatocytes by other agents. Images Figure 1 Figure 2 Figure 3 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 PMID:8579111
Measurement of excitation functions in alpha-induced reactions on yttrium
NASA Astrophysics Data System (ADS)
Shahid, Muhammad; Kim, Kwangsoo; Naik, Haladhara; Zaman, Muhammad; Kim, Guinyun; Yang, Sung-Chul; Song, Tae-Young
2015-01-01
The excitation functions of 89g,m,90,91m,92mNb,88,89Zr, and 87g,m,88,90m,91mY from alpha-induced reactions on 89Y were measured from their respective threshold to 45 MeV by using a stacked-foil activation technique at the MC-50 cyclotron of the Korean Institute of Radiological and Medical Sciences. The results were compared with the earlier reported data as well as with the theoretical values obtained from the TENDL-2013 library based on the TALYS1.6 code. Our measurements in the energy region from the threshold energy to 45 MeV are in general good agreement with the other experimental data and calculated results. The integral yields for thick target of the produced radionuclides were also deduced from their measured cross sections and the stopping power of 89Y. The measured excitation functions find importance in various practical applications including nuclear medicine and improvement of nuclear model calculations.
Investigation of activation cross-sections of alpha-induced nuclear reactions on natural cadmium
NASA Astrophysics Data System (ADS)
Khandaker, Mayeen Uddin; Kim, Kwangsoo; Lee, Manwoo; Kim, Guinyun
2014-08-01
We measured production cross-sections of Sn, In, and Cd radionuclides from alpha-induced reactions on natCd from their respective threshold to 45 MeV by using a stacked-foil activation technique at the MC-50 cyclotron of the Korea Institute of Radiological and Medical Sciences. The results were compared with the earlier measurements as well as with the theoretical values obtained from the TENDL-2012 library based on the TALYS 1.4 code. Our measurements for the 110,113g,117mSn, 108m,108g,109g,110m,110g,111g,113m,114m,115m,116m,117m,117gIn, and 111m,115gCd radionuclides in the energy region from the threshold energy to 45 MeV are in general good agreement with the other experimental data and calculated results. The integral yields for thick target were also deduced using the measured cross-sections and the stopping power of natural cadmium target and found in agreement with the directly measured yields available in the literature. The measured cross-sections find importance in various practical applications including nuclear medicine and improvement of nuclear model calculations.
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.
Tat-APE1/ref-1 protein inhibits TNF-{alpha}-induced endothelial cell activation
Song, Yun Jeong; Lee, Ji Young; Joo, Hee Kyoung; Kim, Hyo Shin; Lee, Sang Ki; Lee, Kwon Ho; Cho, Chung-Hyun; Park, Jin Bong; Jeon, Byeong Hwa
2008-03-28
Apurinic/apyrimidinic endonuclease 1/redox factor-1 (APE1/ref-1) is a multifunctional protein involved both in DNA base excision repair and redox regulation. In this study we evaluated the protective role of Tat-mediated APE1/ref-1 transduction on the tumor necrosis factor (TNF)-{alpha}-activated endothelial activation in cultured human umbilical vein endothelial cells. To construct Tat-APE1/ref-1 fusion protein, human full length of APE1/ref-1 was fused with Tat-protein transduction domain. Purified Tat-APE1/ref-1 fusion protein efficiently transduced cultured endothelial cells in a dose-dependent manner and reached maximum expression at 1 h after incubation. Transduced Tat-APE1/ref-1 showed inhibitory activity on the TNF-{alpha}-induced monocyte adhesion and vascular cell adhesion molecule-1 expression in cultured endothelial cells. These results suggest Tat-APE1/ref-1 might be useful to reduce vascular endothelial activation or vascular inflammatory disorders.
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...
Rajan, V.P.; Menon, K.M.
1985-12-01
Cells isolated from superovulated rat ovaries metabolize low density lipoprotein (LDL) and high density lipoprotein (HDL) of human or rat origin and use the lipoprotein-derived cholesterol as a precursor for progesterone production. Under in vitro conditions, both lipoproteins are internalized and degraded in the lysosomes, although degradation of HDL is of lower magnitude than that of LDL. In this report we have examined the role of cellular microtubules in the internalization and degradation of human LDL and HDL in cultured rat luteal cells. The microtubule depolymerizing agents colchicine, podophyllotoxin, vinblastine, and nocodazole as well as taxol, deuterium oxide, and dimethyl sulfoxide, which are known to rapidly polymerize cellular tubulin into microtubules, were used to block the function of microtubules. When these antimicrotubule agents were included in the incubations, degradation of the apolipoproteins of (/sup 125/I)iodo-LDL and (/sup 125/I)iodo-HDL by the luteal cells was inhibited by 50-85% compared to untreated control values. Maximum inhibitory effects were observed when the cells were preincubated with the inhibitor for at least 4 h at 37 C before treatment with the labeled lipoprotein. Lipoprotein-stimulated progesterone production by luteal cells was also inhibited by 50% or more in the presence of antimicrotubule agents. However, basal and hCG-stimulated progesterone production were unaffected by these inhibitors. The binding of (/sup 125/I)iodo-LDL and (/sup 125/I)iodo-HDL to luteal cell plasma membrane receptors was not affected by the microtubule inhibitors. Although binding was unaffected and degradation was impaired in the presence of the inhibitors, there was no detectable accumulation of undegraded lipoprotein within the cells during the 24 h of study.
Chapman, A B; Zamudio, S; Woodmansee, W; Merouani, A; Osorio, F; Johnson, A; Moore, L G; Dahms, T; Coffin, C; Abraham, W T; Schrier, R W
1997-11-01
Blood pressure decreases during early pregnancy in association with a decrease in peripheral vascular resistance and increases in renal plasma flow and glomerular filtration rate. These early changes suggest a potential association with corpora lutea function. To determine whether peripheral vasodilation occurs following ovulation, we studied 16 healthy women in the midfollicular and midluteal phases of the menstrual cycle. A significant decrease in mean arterial pressure in the midluteal phase of the cycle (midfollicular of 81.7 +/- 2.0 vs. midluteal of 75.4 +/- 2.3 mmHg, P < 0.005) was found in association with a decrease in systemic vascular resistance and an increase in cardiac output. Renal plasma flow and glomerular filtration rate increased. Plasma renin activity and aldosterone concentration increased significantly in the luteal phase accompanied by a decrease in atrial natriuretic peptide concentration. Serum sodium, chloride, and bicarbonate concentrations and osmolarity also declined significantly in the midluteal phase of the menstrual cycle. Urinary adenosine 3',5'-cyclic monophosphate (cAMP) excretion increased in the luteal compared with the follicular phase, whereas no changes in urinary cGMP or NO2/NO3 excretion were found. Thus peripheral vasodilation occurs in the luteal phase of the normal menstrual cycle in association with an increase in renal plasma flow and filtration. Activation of the renin-angiotensin-aldosterone axis is found in the luteal phase of the menstrual cycle. These changes are accompanied by an increase in urinary cAMP excretion indicating potential vasodilating mediators responsible for the observed hemodynamic changes. PMID:9374841
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. PMID:20151456
Stress and memory retrieval in women: no strong impairing effect during the luteal phase.
Schoofs, Daniela; Wolf, Oliver T
2009-06-01
Stress has been shown to impair delayed memory retrieval, but so far no study has been conducted solely with naturally cycling women. In a crossover design, 36 women (all in the luteal phase) participated in two experimental conditions (stress vs. control). Delayed memory retrieval of a wordlist learned 24 hours earlier was tested after stress or control treatment. Although stressed subjects showed a strong cortisol increase following stress, no influence on memory retrieval occurred. In an additional data analysis, subjects were split up into a cortisol responder and a cortisol nonresponder group. However, again no evidence for a stress-induced retrieval impairment became apparent. Similarly, no correlation was observed between the stress-induced cortisol increase and memory. This study failed to find an influence of stress on memory retrieval in women tested in the luteal phase. The findings are in contrast to our previous results obtained with men. Evidence is discussed that the luteal phase, which is characterized by elevated gonadal steroids, is associated with reduced glucocorticoid sensitivity. This might underlie the missing impact of stress on memory. PMID:19485561
Partial characterization of a luteal factor that induces implantation in the ferret.
Mead, R A; Joseph, M M; Neirinckx, S; Berria, M
1988-05-01
This study was designed to test the hypothesis that ferret corpora lutea (CL) secrete a compound that acts in conjunction with progesterone to induce blastocyst implantation and to identify the chemical nature of this compound. CL and the residual ovarian tissue, obtained predominantly on the ninth day of pseudopregnancy, were extracted with 0.05 M phosphate-buffered saline. The extracts were injected into pregnant ferrets that had been ovariectomized on Day 6 of pregnancy and had received Silastic implants containing progesterone. Aqueous luteal extracts, but not those of the residual ovarian tissue, induced implantation in test animals. Fractionation of the luteal extracts by passage through a series of filters with molecular weight (MW) cutoffs ranging from 500 to 50,000 consistently revealed that the biologically active fraction was retained on the filter with the highest MW cutoff employed. Moreover, blastocyst implantation failed to occur in ovariectomized, progesterone-treated ferrets after one-half of a luteal preparation (MW greater than 50,000) was incubated with a broad-spectrum protease. These data are consistent with the hypothesis that CL of the ferret secrete a protein during the preimplantation period that is essential for blastocyst implantation. PMID:3401538
Haroon, Ebrahim; Woolwine, Bobbi J; Chen, Xiangchuan; Pace, Thaddeus W; Parekh, Samir; Spivey, James R; Hu, Xiaoping P; Miller, Andrew H
2014-01-01
Cytokine effects on behavior may be related to alterations in glutamate metabolism. We therefore measured glutamate concentrations in brain regions shown to be affected by inflammatory stimuli including the cytokine interferon (IFN)-alpha. IFN-alpha is known to alter neural activity in the dorsal anterior cingulate cortex (dACC) and basal ganglia in association with symptoms of depression and increases in peripheral cytokines including the tumor necrosis factor (TNF) and its soluble receptor. Single-voxel magnetic resonance spectroscopy (MRS) was employed to measure glutamate concentrations normalized to creatine (Glu/Cr) in dACC and basal ganglia of 31 patients with hepatitis C before and after ∼1 month of either no treatment (n=14) or treatment with IFN-alpha (n=17). Depressive symptoms were measured at each visit using the Inventory of Depressive Symptoms-Clinician Rating (IDS-C) and the Multidimensional Fatigue Inventory. IFN-alpha was associated with a significant increase in Glu/Cr in dACC and left basal ganglia. Increases in dACC Glu/Cr were positively correlated with scores on the IDS-C in the group as a whole, but not in either group alone. Glu/Cr increases in left basal ganglia were correlated with decreased motivation in the group as a whole and in IFN-alpha-treated subjects alone. No Glu/Cr changes were found in the right basal ganglia, and no significant correlations were found between Glu/Cr and the inflammatory markers. IFN-alpha-induced increases in glutamate in dACC and basal ganglia are consistent with MRS findings in bipolar depression and suggest that inflammatory cytokines may contribute to glutamate alterations in patients with mood disorders and increased inflammation. PMID:24481242
Scotti, Leopoldina; Irusta, Griselda; Abramovich, Dalhia; Tesone, Marta; Parborell, Fernanda
2011-03-30
Ovarian hyperstimulation syndrome (OHSS) is a complication of ovarian stimulation with gonadotropins followed by the administration of human chorionic gonadotropin (hCG) to trigger the final steps of oocyte maturation. Gonadotropin-releasing hormone (GnRH) analogs are thought to be effective in preventing this complication and a clinical trial has found a lower incidence of OHSS in patients treated with these molecules. Our aim was to analyze the in vivo effect of a GnRH-I agonist on corpus luteum development and regression, ANGPT-1, ANGPT-2 and Tie-2 protein expression and luteal blood vessel stabilization, the expression of the steroidogenic acute regulatory protein (StAR) and the cytochrome P450 side-chain cleavage enzyme (P450scc) and cell proliferation, in ovaries from an OHSS rat model. To this end immature female Sprague-Dawley rats were hyperstimulated and treated with a GnRH-I agonist from the start of pregnant mare serum gonadotropin (PMSG) administration until the day of hCG injection for 5 consecutive days. Blood and tissue samples were collected 48h after hCG injection. Vascular endothelial growth factor VEGF levels were evaluated in the peritoneal fluid by ELISA. Serum progesterone and estradiol were measured by RIA. Histological features of sectioned ovaries were assessed in hematoxylin and eosin (H&E) stained slides. Luteal blood vessel stability, cell proliferation and apoptosis were assessed by immunohistochemistry for SMCA, PCNA, and TUNEL, respectively. P450scc, StAR, FLK-1, ANGPT-1, ANGPT-2, Tie-2 and PCNA protein levels were evaluated by Western blot from dissected corpora lutea (CL). The treatment with the GnRH-I agonist significantly decreased serum progesterone and estradiol levels as well as P450scc and StAR protein expression in the untreated OHSS group. In addition, the agonist significantly decreased the number of CL in the OHSS group, as compared with the untreated OHSS group. In the OHSS group, the area of periendothelial cells in the
Hastings, Julie M.; Allan, Deborah; Morris, Keith D.; Rudge, John S.; Wiegand, Stanley J.
2012-01-01
Using specific inhibitors established that angiogenesis in the ovarian follicle and corpus luteum is driven by vascular endothelial growth factor. Recently, it has been demonstrated that the Notch ligand, delta-like ligand 4 (Dll4) negatively regulates vascular endothelial growth factor-mediated vessel sprouting and branching. To investigate the role of Dll4 in regulation of the ovarian vasculature, we administered a neutralizing antibody to Dll4 to marmosets at the periovulatory period. The vasculature was examined on luteal d 3 or d 10: angiogenesis was determined by incorporation of bromodeoxyuridine, staining for CD31 and cell death by staining for activated caspase-3. Ovulatory progesterone rises were monitored to determine effects of treatment on luteal function and time to recover normal cycles in a separate group of animals. Additionally, animals were treated in the follicular or midluteal phase to determine effects of Dll4 inhibition on follicular development and luteal function. Controls were treated with human IgG (Fc). Corpora lutea from marmosets treated during the periovulatory period exhibited increased angiogenesis and increased vascular density on luteal d 3, but plasma progesterone was significantly suppressed. By luteal d 10, corpora lutea in treated ovaries were significantly reduced in size, with involution of luteal cells, increased cell death, and suppressed plasma progesterone concentrations. In contrast, initiation of anti-Dll4 treatment during the midluteal phase produced only a slight suppression of progesterone for the remainder of the cycle. Moreover, Dll4 inhibition had no appreciable effect on follicular development. These results show that Dll4 has a specific and critical role in the development of the normal luteal vasculature. PMID:22334711
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. PMID:23054443
Joseph, Chitra; Hunter, Morag G; Sinclair, Kevin D; Robinson, Robert S
2012-09-01
The role of the tissue remodelling protein, secreted protein, acidic, cysteine-rich (SPARC), in key processes (e.g. cell reorganisation and angiogenesis) that occur during the follicle-luteal transition is unknown. Hence, we investigated the regulation of SPARC in luteinsing follicular cells and potential roles of SPARC peptide 2.3 in a physiologically relevant luteal angiogenesis culture system. SPARC protein was detected mainly in the theca layer of bovine pre-ovulatory follicles, but its expression was considerably greater in the corpus haemorrhagicum. Similarly, SPARC protein (western blotting) was up-regulated in luteinising granulosa but not in theca cells during a 6-day culture period. Potential regulatory candidates were investigated in luteinising granulosa cells: LH did not affect SPARC (P>0.05); transforming growth factor (TGF) B1 (P<0.001) dose dependently induced the precocious expression of SPARC and increased final levels: this effect was blocked (P<0.001) by SB505124 (TGFB receptor 1 inhibitor). Additionally, fibronectin, which is deposited during luteal development, increased SPARC (P<0.01). In luteal cells, fibroblast growth factor 2 decreased SPARC (P<0.001) during the first 5 days of culture, while vascular endothelial growth factor A increased its expression (P<0.001). Functionally, KGHK peptide, a SPARC proteolytic fragment, stimulated the formation of endothelial cell networks in a luteal cell culture system (P<0.05) and increased progesterone production (P<0.05). Collectively, these findings indicate that SPARC is intricately regulated by pro-angiogenic and other growth factors together with components of the extracellular matrix during the follicle-luteal transition. Thus, it is possible that SPARC plays an important modulatory role in regulating angiogenesis and progesterone production during luteal development. PMID:22733805
Arosh, Joe A; Banu, Sakhila K; McCracken, John A
2016-07-01
In ruminants, the corpus luteum (CL) of early pregnancy is resistant to luteolysis. Prostaglandin (PG)E2 is considered a luteoprotective mediator. Early studies indicate that during maternal recognition of pregnancy (MRP) in ruminants, a factor(s) from the conceptus or gravid uterus reaches the ovary locally through the utero-ovarian plexus (UOP) and protects the CL from luteolysis. The local nature of the embryonic antiluteolytic or luteoprotective effect precludes any direct effect of a protein transported or acting between the gravid uterus and CL in ruminants. During MRP, interferon tau (IFNT) secreted by the trophoblast of the conceptus inhibits endometrial pulsatile release of PGF2α and increases endometrial PGE2. Our recent studies indicate that (1) luteal PG biosynthesis is selectively directed toward PGF2α at the time of luteolysis and toward PGE2 at the time of establishment of pregnancy (ESP); (2) the ability of the CL of early pregnancy to resist luteolysis is likely due to increased intraluteal biosynthesis and signaling of PGE2; and (3) endometrial PGE2 is transported from the uterus to the CL through the UOP vascular route during ESP in sheep. Intrauterine co-administration of IFNT and prostaglandin E2 synthase 1 (PGES-1) inhibitor reestablishes endometrial PGF2α pulses and regresses the CL. In contrast, intrauterine co-administration of IFNT and PGES-1 inhibitor along with intraovarian administration of PGE2 rescues the CL. Together, the accumulating information provides compelling evidence that PGE2 produced by the CL in response to endometrial PGE2 induced by pregnancy may counteract the luteolytic effect of PGF2α as an additional luteoprotective mechanism during MRP or ESP in ruminants. Targeting PGE2 biosynthesis and signaling selectively in the endometrium or CL may provide luteoprotective therapy to improve reproductive efficiency in ruminants. PMID:27179861
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
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.
Paria, Biman C; Malik, Asrar B; Kwiatek, Angela M; Rahman, Arshad; May, Michael J; Ghosh, Sankar; Tiruppathi, Chinnaswamy
2003-09-26
We investigated the role of tumor necrosis factor-alpha (TNF-alpha) in activating the store-operated Ca2+ channels in endothelial cells via the expression of transient receptor potential channel (TRPC) isoforms. We observed that TNF-alpha exposure of human umbilical vein endothelial cells resulted in TRPC1 mRNA and protein expression, whereas it had no effect on TRPC3, TRPC4, or TRPC5 expression. The TRPC1 expression was associated with increased Ca2+ influx after intracellular Ca2+ store depletion with either thrombin or thapsigargin. We cloned the 5'-regulatory region of the human TRPC1 (hTRPC1) gene which contained a TATA box and CCAAT sequence close to the transcription initiation site. We also identified four nuclear factor-kappaB (NF-kappaB)-binding sites in the 5'-regulatory region. To address the contribution of NF-kappaB in the mechanism of TRPC1 expression, we determined the effects of TNF-alpha on expression of the reporter luciferase after transfection of hTRPC1 promoter-luciferase (hTRPC1-Pro-Luc) construct in the human dermal microvascular endothelial cell line. Reporter activity increased >4-fold at 4 h after TNF-alpha challenge. TNF-alpha-induced increase in reporter activity was markedly reduced by co-expression of either kinase-defective IKKbeta kinase mutant or non-phosphorylatable IkappaB mutant. Treatment with NEMO-binding domain peptide, which prevents NF-kappaB activation by selectively inhibiting IKKgamma interaction with IKK complex, also blocked the TNF-alpha-induced TRPC1 expression. Thus, TNF-alpha induces TRPC1 expression through an NF-kappaB-dependent pathway in endothelial cells, which can trigger augmented Ca2+ entry following Ca2+ store depletion. The augmented Ca2+ entry secondary to TRPC1 expression may be an important mechanism of endothelial injury induced by TNF-alpha. PMID:12855710
Ido, M.; Hayashi, K.; Kato, S.; Ogawa, H.; Komada, Y.; Zhau, Y. W.; Zhang, X. L.; Sakurai, M.; Suzuki, K.
1996-01-01
Tumour necrosis factor (TNF)-alpha induces apoptosis in a human acute myeloid leukaemia cell line, Kasumi-1. To examine the role of protein phosphorylation in signal transduction of TNF-alpha-induced apoptosis, a variant cell line resistant to TNF-alpha was established by an intermittent challenge of Kasumi-1 cells with increasing concentrations of TNF-alpha for 6 months. The mechanism of resistance to TNF-alpha appears to be in the post-receptor pathway because expression of p55 TNF receptor in the variant cells is increased compared with that of the parental Kasumi-1 cells. In renaturation assays, TNF-alpha induced a rapid activation of different protein kinases of different molecular weights, including the 50 kDa protein kinase (PK50) followed by the 35 kDa protein kinase (PK35), in the parental Kasumi-1 cells. The dose-response of TNF-alpha required to activate PK50 and PK35 was closely related to concentrations of TNF-alpha that induced apoptosis. Treatment of Kasumi-1 cells with ceramide also activated PK35. In TNF-resistant variant cells, activation of PK35 in response to TNF-alpha or ceramide was practically nil. These findings suggest that activation of PK35 through the ceramide pathway may play an important role in signal transduction of TNF-alpha in the Kasumi-1 cell line, while the decreased activation of PK35 may explain the insensitivity of the variant cells towards TNF-alpha. Images Figure 3 Figure 4 Figure 5 Figure 6 PMID:8562342
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
Satheshkumar, S; Brindha, K; Roy, A; Devanathan, T G; Kathiresan, D; Kumanan, K
2015-07-01
The study was aimed at investigating the effect of seasonal changes on follicular and luteal dynamics in vivo in normally cycling crossbred cows during summer and winter months of the year. Six healthy regularly cycling Jersey crossbred nonlactating pluriparous cows were used for the study. Follicular and luteal developmental pattern was studied every other day throughout the estrous cycle by scanning the ovaries during two periods of a year viz., hot season (April to June; n = 16) and cold season (December to February; n = 12). Plasma progesterone (P4) concentrations were measured on Days 0 (estrus), 6, and 12 of the estrous cycle. Among the 12 cycles studied during the cold season, 11 (91.7%) had three waves and one had two waves. Of 16 cycles studied during the hot season, eight (50%) had two waves, four (25%) had three waves, and the remaining four cycles had single (n = 2) and four waves (n = 2). High P4 concentrations during the midcycle would have suppressed the dominant follicle of the second follicular wave and induced the emergence of the third wave during the cold season. The first follicular wave (wave I) of the cycle emerged much earlier (Day 0.5 ± 0.3) during the cold season than that in the hot season (Day 1.7 ± 0.4). The ovulatory wave emerged significantly earlier during the hot season (Day 11.5 ± 1.3) than in the cold season (Day 14.8 ± 0.4), and hence, the growth phase of ovulatory follicle significantly increased during the former season (11.0 ± 1.4 days) than the latter (5.8 ± 0.2 days). The ovulatory follicle attained a significantly larger diameter (12.8 ± 0.8 mm) to express the estrus during the hot season when compared to the cold season (11.3 ± 0.4 mm), which might be indicative of alterations in steroidogenic activity within the follicular microenvironment. During the midphase of the cycle, a period critical for embryonic sustenance, the P4 level was significantly reduced in the hot months indicating suppression of luteal activity
Chen, Xi-Lin; Grey, Janice Y; Thomas, Suzanne; Qiu, Fei-Hua; Medford, Russell M; Wasserman, Martin A; Kunsch, Charles
2004-10-01
Atherosclerosis is a focal inflammatory disease and preferentially occurs in areas of low fluid shear stress and oscillatory flow, whereas the risk of atherosclerosis is decreased in regions of high fluid shear stress and steady laminar flow. Sphingosine kinase-1 (SphK1) catalyzes the conversion of sphingosine to sphingosine-1 phosphate (S1P), a sphingolipid metabolite that plays important roles in angiogenesis, inflammation, and cell growth. In the present study, we demonstrated that exposure of human aortic endothelial cells to oscillatory flow (shear stress, +/-5 dyn/cm(2) for 48 h) resulted in a marked increase in SphK1 mRNA levels compared with endothelial cells kept in static culture. In contrast, laminar flow (shear stress, 20 dyn/cm(2) for 48 h) decreased SphK1 mRNA levels. We further investigated the role of SphK1 in TNF-alpha-induced expression of inflammatory genes, such as monocyte chemoattractant protein-1 (MCP-1) and VCAM-1 by using small interfering RNA (siRNA) specifically for SphK1. Treatment of endothelial cells with SphK1 siRNA suppressed TNF-alpha-induced increase in MCP-1 mRNA levels, MCP-1 protein secretion, and activation of p38 MAPK. SphK1 siRNA also inhibited TNF-alpha-induced cell surface expression of VCAM-1, but not ICAM-1, protein. Exposure of endothelial cells to S1P led to an increase in MCP-1 protein secretion and MCP-1 mRNA levels and activation of NF-kappaB-mediated transcriptional activity. Treatment of endothelial cells with the p38 MAPK inhibitor SB-203580 suppressed S1P-induced MCP-1 protein secretion. These data suggest that SphK1 mediates TNF-alpha-induced MCP-1 gene expression through a p38 MAPK-dependent pathway and may participate in oscillatory flow-mediated proinflammatory signaling pathway in the vasculature. PMID:15191888
Şimşek, Erhan; Kılıçdağ, Esra Bulgan; Aytaç, Pınar Çağlar; Çoban, Gonca; Şimşek, Seda Yüksel; Çok, Tayfun; Haydardedeoğlu, Bülent
2015-01-01
Objective Luteal phase is defective in in vitro fertilization (IVF) cycles, and many regimens were tried for the very best luteal phase support (LPS). Gonadotropin releasing hormone (GnRH) agonist use, which was administered as an adjunct to the luteal phase support in IVF cycles, was suggested to improve pregnancy outcome measures in certain randomized studies. We analyzed the effects of addition of GnRH agonist to standard progesterone luteal support on pregnancy outcome measures, particularly the live birth rates. Material and Methods This is a retrospective cohort study, including 2739 IVF cycles. Long GnRH agonist and antagonist stimulation IVF cycles with cleavage-stage embryo transfer were included. Cycles were divided into two groups: Group A included cycles with single-dose GnRH agonist plus progesterone LPS and Group B included progesterone only LPS. Live birth rates were the primary outcome measures of the analysis. Miscarriage rates and multiple pregnancy rates were the secondary outcome measures. Results Live birth rates were not statistically different in GnRH agonist plus progesterone (Group A) and progesterone only (Group B) groups in both the long agonist and antagonist stimulation arms (40.8%/41.2% and 32.8%/34.4%, p<0.05 respectively). Moreover, pregnancy rates, implantation rates, and miscarriage rates were found to be similar between groups. Multiple pregnancy rates in antagonist cycles were significantly higher in Group A than those in Group B (12.0% and 6.9%, respectively). Conclusion A beneficial effect of a single dose of GnRH agonist administration as a luteal phase supporting agent is yet to be determined because of the wide heterogeneity of data present in literature. Well-designed randomized clinical studies are required to clarify any effect of luteal GnRH agonist addition on pregnancy outcome measures with different doses, timing, and administration routes of GnRH agonists. PMID:26097392
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.…
The effect of cloprostenol on human luteal steroid and prostaglandin secretion in vitro.
McDougall, A N; Walker, F M; Watson, J
1977-01-01
1 Human luteal tissue slices from days 18, 21 and 25 of the menstrual cycle were superfused in vitro with Medium 199 alone or containing cloprostenol (1 microgram/ml). Concentrations of progesterone, oestradiol-17beta and prostaglandins F2alpha and E2 were determined in the superfusate samples. 2 Secretion of steroids and prostaglandins was maintained at an approximately constant level throughout the experiments (21 h in one case) when the tissue was perfused with M199 alone. 3 Superfusion with cloprostenol (1 microgram/ml) resulted in an initial depression of progesterone and oestradiol-17beta but this was not maintained, levels returning to control values or showing an increase, while superfusion with cloprostenol continued. Cloprostenol is not therefore considered to be luteolytic at this dose and under these conditions for human luteal tissue in vitro. 4 Superfusion with cloprostenol (1 microgram/ml) also resulted in a large stimulation of secretion of endogenous prostaglandin F2 alpha following a short lag phase. This stimulation was possibly due to the initial depression of progesterone secretion. A short-lived stimulation of prostaglandin E2 secretion was also observed. 5 The significance of the increase in prostaglandin E2 secretion and the interrelationships between the various changes observed with cloprostenol are difficult to interpret. PMID:890210
Progesterone administration for luteal phase deficiency in human reproduction: an old or new issue?
Palomba, Stefano; Santagni, Susanna; La Sala, Giovanni Battista
2015-01-01
Luteal phase deficiency (LPD) is described as a condition of insufficient progesterone exposure to maintain a regular secretory endometrium and allow for normal embryo implantation and growth. Recently, scientific focus is turning to understand the physiology of implantation, in particular the several molecular markers of endometrial competence, through the recent transcriptomic approaches and microarray technology. In spite of the wide availability of clinical and instrumental methods for assessing endometrial competence, reproducible and reliable diagnostic tests for LPD are currently lacking, so no type-IA evidence has been proposed by the main scientific societies for assessing endometrial competence in infertile couples. Nevertheless, LPD is a very common condition that may occur during a series of clinical conditions, and during controlled ovarian stimulation (COS) and hyperstimulation (COH) programs. In many cases, the correct approach to treat LPD is the identification and correction of any underlying condition while, in case of no underlying dysfunction, the treatment becomes empiric. To date, no direct data is available regarding the efficacy of luteal phase support for improving fertility in spontaneous cycles or in non-gonadotropin induced ovulatory cycles. On the contrary, in gonadotropin in vitro fertilization (IVF) and non-IVF cycles, LPD is always present and progesterone exerts a significant positive effect on reproductive outcomes. The scientific debate still remains open regarding progesterone administration protocols, specially on routes of administration, dose and timing and the potential association with other drugs, and further research is still needed. PMID:26585269
Shakibaei, Mehdi; Sung, Bokyung; Sethi, Gautam; Aggarwal, Bharat B
2010-09-15
Although much is known about how TNF-alpha induces apoptosis in the presence of inhibitors of protein synthesis, little is known about how it induces apoptosis without these inhibitors. In this report we investigated temporal sequence of events induced by TNF-alpha in the absence of protein synthesis. Regardless of whether we measured the effects by plasma membrane phosphotidylserine accumulation, by DNA strand breaks, or activation of caspases, significant changes were observed only between 12-24 h of TNF-alpha treatment. One of the earliest changes observed after TNF-alpha treatment was mitochondrial swelling at 10 min; followed by cytochrome c and Smac release at 10-30 min, and then heterochromatin clumping occurred at 60 min. While genetic deletion of receptor-interaction protein (RIP) had no effect on TNF-alpha-induced mitochondrial damage, deletion of Fas-associated death domain (FADD) abolished the TNF-induced mitochondrial swelling. Since pan-caspase inhibitor z-VAD-fmk abolished the TNF-alpha-induced mitochondrial changes, z-DEVD-fmk, an inhibitor of caspase-3 had no effect, suggesting that TNF-alpha-induced mitochondrial changes or cytochrome c and Smac release requires caspase-8 but not caspase-3 activation. Overall, our results indicated that mitochondrial changes are early events in TNF-alpha-induced apoptosis and that these mitochondrial changes require recruitment of FADD and caspase-8 activation, but not caspase-3 activation or RIP recruitment. PMID:20136500
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.
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...
Geber, Selmo; Sampaio, Marcos
2013-06-01
The effect of long-acting GnRHa, in the luteal phase, during ART cycles varies from one patient to another. The aim of this study was to evaluate whether the effect of long-acting GnRHa in the luteal phase, in ART cycles, affects pregnancy rates according to the duration of its action in such phase. This is a retrospective study of 367 patients submitted to ovulation induction for in vitro fertilization/intracytoplasmic sperm injection procedures that used long-acting depot GnRHa for pituitary suppression. Patients were stratified according to the period of action of the agonist in the luteal phase: group 1, ≤ 6 days; group 2, 7 to 12 days; and group 3, >12 days. The following variables were analyzed: ovarian response, age, infertility causes and pregnancy rates. Group 1 (n = 53) had a mean age of 33.8 ± 4.55 years (23-44 years) and a pregnancy rate of 45.2%. In group 2 (n = 118), mean age was 33.7 ± 4.5 years (24-44 years) and the pregnancy rate was 38.9%. In group 3 (n = 196), mean age was 33.7 ± 4.4 years (23-43 years) and the pregnancy rate was 47.4%. Regardless of the duration of depot GnRHa action in the luteal phase, no significant association with pregnancy rates was found. PMID:23656392
Fan, Heng-Yu; Liu, Zhilin; Cahill, Nicola; Richards, JoAnne S.
2008-01-01
FSH activates the phosphatidylinositol-3 kinase (PI3K)/acute transforming retrovirus thymoma protein kinase pathway and thereby enhances granulosa cell differentiation in culture. To identify the physiological role of the PI3K pathway in vivo we disrupted the PI3K suppressor, Pten, in developing ovarian follicles. To selectively disrupt Pten expression in granulosa cells, Ptenfl/fl mice were mated with transgenic mice expressing cAMP response element recombinase driven by Cyp19 promoter (Cyp19-Cre). The resultant Pten mutant mice were fertile, ovulated more oocytes, and produced moderately more pups than control mice. These physiological differences in the Pten mutant mice were associated with hyperactivation of the PI3K/acute transforming retrovirus thymoma protein kinase pathway, decreased susceptibility to apoptosis, and increased proliferation of mutant granulosa cells. Strikingly, corpora lutea of the Pten mutant mice persisted longer than those of control mice. Although the follicular and luteal cell steroidogenesis in Ptenfl/fl;Cyp19-Cre mice was similar to controls, viable nonsteroidogenic luteal cells escaped structural luteolysis. These findings provide the novel evidence that Pten impacts the survival/life span of granulosa/luteal cells and that its loss not only results in the facilitated ovulation but also in the persistence of nonsteroidogenic luteal structures in the adult mouse ovary. PMID:18606860
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. PMID:16478781
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.
Lee, Myung Hee; Liu, Yufeng
2013-12-01
The continuum regression technique provides an appealing regression framework connecting ordinary least squares, partial least squares and principal component regression in one family. It offers some insight on the underlying regression model for a given application. Moreover, it helps to provide deep understanding of various regression techniques. Despite the useful framework, however, the current development on continuum regression is only for linear regression. In many applications, nonlinear regression is necessary. The extension of continuum regression from linear models to nonlinear models using kernel learning is considered. The proposed kernel continuum regression technique is quite general and can handle very flexible regression model estimation. An efficient algorithm is developed for fast implementation. Numerical examples have demonstrated the usefulness of the proposed technique. PMID:24058224
Atanasov, B; De Koster, J; Bommelé, L; Dovenski, T; Opsomer, G
2015-03-01
With the increased use of different synchronization programs in cattle, attention is given to the progesterone concentration during development of the ovulatory follicle. It has been shown that low peripheral progesterone concentrations during follicular development may lead to decreased fertility. To investigate the effect of low progesterone concentrations on the fate of the dominant follicle, a study was conducted where cycles of dairy cows and heifers were manipulated to induce the development of the first dominant follicle without progesterone (PLACEBO) or under sub-luteal progesterone concentrations from a progesterone releasing intravaginal device (PRID Delta(®)). After insertion of the devices, daily follow up was performed by transrectal ultrasonography to identify and measure follicular development and blood samples were taken to determine the circulating progesterone concentration. Follow up was continued until the ovulation of a follicle occurred. After ovulation, the fate of the first dominant follicle was identified as arrested, atretic or ovulatory. Arrest was defined as persistence of the dominant follicle followed by ovulation whereas atresia was defined as regression of the dominant follicle and subsequent growth and ovulation of a new follicle. During PLACEBO treatment, heifers ovulated earlier and smaller follicles in comparison to cows. During PRID Delta(®) treatment, heifers had greater progesterone concentrations compared to cows and arrest of the dominant follicle occurred more in cows in comparison to heifers. In cycles where the dominant follicle was arrested, the ovulatory follicle was larger in comparison to cycles where the dominant follicle was atretic. PMID:25637465
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.
Kanazawa, Tomomi; Seki, Motohide; Ishiyama, Keiki; Kubo, Tomoaki; Kaneda, Yoshiyuki; Sakaguchi, Minoru; Izaike, Yoshiaki; Takahashi, Toru
2016-10-01
This study aimed to assess the suitability of luteal blood flow analyses measured by color Doppler ultrasonography (CDUS), to predict pregnancy at pre- and post-embryo transfer (ET) in dairy cows, and to compare with the established criterion like luteal size and plasma progesterone (P4) concentrations. Lactating Holstein cows (n = 65) with spontaneous (n = 34) or synchronized estrus (n = 31) were examined. Cows with a CL greater than or equal to 20 mm in diameter (n = 58) received embryo transfer on Day 7 (Day 0 = estrus). Brightness mode images were captured for calculation of the CL area, luteal cavity area, and dominant follicle area on Days 3, 5, 7, and 14. Color Doppler ultrasonography examinations were conducted to determine the blood flow area (BFA) within the CL at the maximum diameter and the time-averaged maximum velocity (TAMV) of the base of the spiral artery on the same days. Plasma P4 concentrations were determined from blood samples collected at each ultrasound examination. Pregnancy was diagnosed by an ultrasound on Day 30. There was no significant difference in the proportion of cows received embryo (91.2% vs. 87.1%, P = 0.70) and pregnancy rate (58.1% vs. 59.3%, P = 1.00) between the spontaneous estrus and synchronized groups. The BFA values of the pregnant group (n = 34) were approximately 1.42 and 1.54 times higher than those of the nonpregnant group (n = 24) on Days 7 (0.54 ± 0.04 cm(2) vs. 0.38 ± 0.02 cm(2); P < 0.01) and 14 (0.80 ± 0.23 cm(2) vs. 0.52 ± 0.22 cm(2); P < 0.01), respectively. The TAMV of the pregnant group was approximately 1.45 times higher than that of the nonpregnant group on Day 14 (57.8 ± 3.5 cm/s vs. 40.0 ± 3.3 cm/s; P < 0.01). However, no differences were found in the CL area, CL tissue area, dominant follicle area, and plasma P4 concentrations among these groups. In addition, the best logistic regression model to predict pregnancy included scores for BFA on Day 7, BFA and
Chouhan, V S; Dangi, S S; Vazhoor, B; Yadav, V P; Gupta, M; Pathak, M C; Panda, R P; Khan, F A; Verma, M R; Maurya, V P; Singh, G; Sarkar, M
2014-12-01
We evaluated the temporal (24, 48 and 72 hours) and dose-dependent (5, 10, and 100 ng/mL of LH, IGF-1, and EGF, respectively) production and secretion of progesterone (P4) in cultured luteal cells from different stages of estrous cycle as well as the expression of steroidogenic acute regulatory protein (STARD1), cytochrome P450 cholesterol side-chain cleavage (CYP11A1), and 3β-hydroxysteroid dehydrogenase (HSD3B), anti-apoptotic gene PCNA, and pro-apoptotic gene BAX in luteal cells of mid-luteal phase in buffalo. Samples from early luteal phase (ELP; Day 1 to 4; n = 4), mid-luteal phase (MLP; Day 5 to 10; n = 4), and late luteal phase (LLP; Day 11 to 16; n = 4) of estrous cycle were collected. Progesterone was assayed by RIA, whereas mRNA expression was determined by quantitative real-time polymerase chain reaction. Results depicted that highest dose (100 ng/mL) of LH, IGF-1, and EGF and longer duration of time brought about a (P < 0.05) rise in P4 level and expression of steroidogenic enzymes and PCNA compared with the lower level(s) and control while, all treatments (P < 0.05) inhibited BAX expression in a time dependent-manner. Analysis of interaction between stage and treatments revealed that LH treatment (P < 0.05) increased P4 production compared with IGF-1 and EGF in ELP and MLP. However in LLP, treatment with IGF-1 and EGF significantly (P < 0.05) increased P4 production compared with LH treatment. Summarizing, our study explores the steroidogenic potential of LH and growth factors across different luteal stages in buffalo, which on promoting steroidogenic enzyme expression and cell viability culminated in enhanced P4 production in luteal cells. PMID:25263485
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.
Nagai, Masanori; Matsumoto, Sayaka; Endo, Junko; Sakamoto, Reiko; Wada, Maki
2015-03-15
Influences of depression symptoms on the sweet taste threshold were investigated in healthy college students (30 males and 40 females). Depression symptoms were scored by SDS (Self-Rating Depression Scale), and anxiety levels by STAI (State- and Trait-Anxiety Inventory). Recognition thresholds for sucrose were determined. In female students, the menstrual phase on the day of the experiment was self-reported. Depression symptoms, anxiety levels, and the recognition threshold for sucrose were not different among the 3 groups, i.e. males, females in the follicular phase, and females in the luteal phase. Depression symptoms were positively correlated with state and trait anxiety in all groups. The sweet taste threshold was inversely correlated with depression symptoms (r=-0.472, p=0.031) and trait anxiety (r=-0.506, p=0.019) in females in the luteal phase. In males as well as females in the follicular phase, however, no correlation between sweet taste threshold and depression was found. The results show that the recognition threshold for sucrose reduces with increased depression in females with a higher anxiety trait, but only in the luteal phase. It is hypothesized that brain regions, which spatially overlap and are responsible for both aversive emotions and gustatory processing, are susceptible to periodic changes in gonadal hormones due to the menstrual cycle. PMID:25576640
Zhu, Long; Chen, Tao; Sui, Menghua; Han, Chunyang; Fang, Fugui; Ma, Yuehui; Chu, Mingxing; Zhang, Xiaorong; Liu, Cuiyan; Ling, Yinghui
2016-01-01
To explore if the regulation at post-transcriptional level of follicular phase (Fols) to luteal phase (Luts) transition occurs in the ovaries of Anhuai goats, the differentially expressed microRNAs (miRNAs) of ovaries in the Fols and Luts were analyzed using Solexa sequencing in the study. In total, 320 known miRNAs were co-expressed in the two phases, 339 and 353 known miRNAs were expressed in the ovary in the Fols and Luts, respectively. In addition, 45 novel miRNAs were co-expressed in the two phases, 70 and 94 novel miRNAs were expressed in the ovary in the Fols and Luts, respectively. Let-7f was the highest expressed significantly different known miRNA in the two phases, and mir-159 was the highest expressed significantly different novel miRNA in the two phases, which may participate in the follicular-luteal transition of Anhuai goats. GO annotation and KEGG pathway analysis were applied to analyze the target genes of differentially expressed miRNAs detected in the two phases. The results will help to further understand the role of miRNAs in the regulation of follicular to luteal transition in goat ovaries. PMID:27610292
Effect of betamethasone treatment on luteal lifespan and the LH response to GnRH in dairy cows.
Dobson, H; Alam, M G; Kanchev, L N
1987-05-01
Betamethasone (a synthetic glucocorticoid, 15 mg) was administered i.m. twice daily for 10 days to 4 regularly cycling dairy cows, beginning on Day 10 of the oestrous cycle. Luteal function, monitored by plasma progesterone, was extended by 7, 9, 19 and 20 days, respectively. Luteal function in the next cycle was normal. Endogenous cortisol values were suppressed for 14, 13, 34 and 27 days, respectively. Pituitary responsiveness to 20 micrograms GnRH was assessed by LH measurement on Days -1, +3 and +7 relative to the start of betamethasone treatment. There was a progressive decrease in peak LH concentrations after each GnRH challenge compared to control cows. Hourly measurements of PGF-2 alpha metabolite during the expected period of luteolysis failed to reveal normal increases. It is suggested that betamethasone caused prolonged luteal function, either by directly inhibiting PGF-2 alpha release, or by suppressing pituitary stimulation of follicular growth and hence lowering oestradiol concentrations, since it is known that PGF-2 alpha and oestradiol act synergistically to cause luteolysis. PMID:3298644
Eberly, Lynn E
2007-01-01
This chapter describes multiple linear regression, a statistical approach used to describe the simultaneous associations of several variables with one continuous outcome. Important steps in using this approach include estimation and inference, variable selection in model building, and assessing model fit. The special cases of regression with interactions among the variables, polynomial regression, regressions with categorical (grouping) variables, and separate slopes models are also covered. Examples in microbiology are used throughout. PMID:18450050
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.
Orthogonal Regression and Equivariance.
ERIC Educational Resources Information Center
Blankmeyer, Eric
Ordinary least-squares regression treats the variables asymmetrically, designating a dependent variable and one or more independent variables. When it is not obvious how to make this distinction, a researcher may prefer to use orthogonal regression, which treats the variables symmetrically. However, the usual procedure for orthogonal regression is…
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…
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.
Haas, Jigal; Lantsberg, Daniel; Feldman, Noa; Manela, Daphna; Machtinger, Ronit; Dar, Shir; Rabinovici, Jaron; Orvieto, Raoul
2015-01-01
With the recent trend toward single embryo transfer (ET), cryopreservation of extraneous embryos is becoming increasingly prevalent. Several replacement protocols for frozen-thawed ET (FET) exist, with no advantage of one protocol over the others. All consecutive patients undergoing natural cycle Day-3 FET cycles between May 2012 and March 2015 in our IVF unit were evaluated. While following spontaneous ovulation, all patients received progesterone luteal support. Since June 2014, patients underwent the same aforementioned natural cycle FET cycles, with two additional injections, one of recombinant hCG (250 mcg) and the other of GnRH-agonist (triptorelin 0.1 mg), on the day of transfer and 4 d later, respectively. While the patients' clinical characteristics, the prevalence of embryos that survived the thawing process and the number of embryos transferred were comparable between the earlier as compared with the later period, implantation rate, positive β-hCG, clinical, and ongoing pregnancy rates were significantly higher during the later period. We, therefore, suggest that when natural cycle FET is offered, the addition of two injections of recombinant hCG and GnRH-agonist, on the day of transfer and 4 d later, respectively, might increase clinical pregancy rates. Further large prospective studies are needed to elucidate the aforementioned recommendation prior to its routine implementation. PMID:26288149
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. PMID:26968245
Dunaeva, S.A.; McLane, V.; Savin, M.; Taova, S.
2005-05-24
The present report gives a detailed analysis of experimental works and a review of alpha-induced reaction cross-section data of five alpha-alpha nuclei, Mg-24, Si-28, S-32, Ar-36 and Ca-40, for incident alpha energy up to 20 MeV. Alpha-induced reactions play an important role in the helium burning stage of stars, novae, and supernovae. These reactions are basic to the CNO and Al-Mg cycles, and also to the production of neutrons producing S and R processes occurring in stars. Thus, the availability of cross-section data for these reactions is a prime need for the study of nuclear interactions taking place in stars.These data have been compiled as part of an international collaboration, funded in part by the Civilian Research and Development Foundation, and are available in the EXFOR databases.
Hedberg, Ylva; Dalin, Anne-Marie; Santesson, Malin; Kindahl, Hans
2006-01-01
Background Strong oestrous symptoms in the mare can cause problems with racing, training and handling. Since long-acting progesterone treatment is not permitted in mares at competition (e.g. according to FEI rules), there is a need for methods to suppress unwanted cyclicity. Spontaneous dioestrous ovulations in the late luteal phase may cause a prolongation of the luteal phase in mares. Methods In this preliminary study, in an attempt to induce ovulation during the luteal phase, human chorionic gonadotropin (hCG) (3000 IU) was injected intramuscularly in four mares (experimental group) in the luteal phase when a dioestrous follicle ≥ 30 mm was detected. A fifth mare included in this group was not treated due to no detectable dioestrous follicles ≥ 30 mm. Four control mares were similarly injected with saline. The mares were followed with ultrasound for 72 hours post injection or until ovulation. Blood samples for progesterone analysis were obtained twice weekly for one month and thereafter once weekly for another two to four months. Results Three of the hCG-treated mares ovulated within 72 hours after treatment and developed prolonged luteal phases of 58, 68 and 82 days respectively. One treated mare never ovulated after the hCG injection and progesterone levels fell below 3 nmol/l nine days post treatment. Progesterone levels in the control mares were below 3 nmol/l within nine days after saline injection, except for one mare, which developed a spontaneously prolonged luteal phase of 72 days. Conclusion HCG treatment may be a method to induce prolonged luteal phases in the mare provided there is a dioestrous follicle ≥ 30 mm that ovulates post-treatment. However, the method needs to be tested on a larger number of mares to be able to draw conclusions regarding its effectiveness. PMID:16987391
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.
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
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
Wang, Liangli; Li, Yin; Hu, Peng; Teng, Christina T
2008-12-15
ERR (oestrogen-related receptor)-alpha modulates the oestrogen signalling pathway and regulates genes participating in the physiological energy balance programme. Oestrogen and PGC-1alpha (peroxisome proliferator-activated receptor-gamma coactivator-1alpha), the master regulator of the energy homoeostasis programme, both regulate the expression of ERRalpha through the MHRE (multi-hormone response element) of the ERRalpha gene. Although the molecular mechanism of oestrogen action on ERRalpha regulation is well characterized, the mechanism of PGC-1alpha induction is unclear. In this study, we examine chromatin structural changes and protein interactions at the MHRE nucleosome in response to PGC-1alpha expression in HK2 human kidney cells. We mapped the nucleosome positions of the ERRalpha gene promoter and examined the changes of histone acetylation in response to PGC-1alpha expression. The interactions of DNA-binding proteins, ERRalpha and ERRgamma, co-activators {CBP [CREB (cAMP-response-element-binding protein)-binding protein], p300, PCAF (p300/CBP-associated factor)}, co-repressor [RIP140 (receptor-interacting protein of 140 kDa)] and RNA polymerase II at the MHRE nucleosome region were investigated over time before and after PGC-1alpha expression in the HK2 cells. We found a dynamic cyclic interaction of these proteins shortly after PGC-1alpha expression and a slower cycling interaction, with fewer proteins involved, 20 h later. By using the siRNA (small interfering RNA) knockdown approach, we discovered that ERRgamma was involved in the initial phase, but not in the later phase, of PGC-1alpha-induced ERRalpha expression. PMID:18673300
Morales, Priscilla; Reyes, Paz; Vargas, Macarena; Rios, Miguel; Imarai, Mónica; Cardenas, Hugo; Croxatto, Horacio; Orihuela, Pedro; Vargas, Renato; Fuhrer, Juan; Heckels, John E; Christodoulides, Myron; Velasquez, Luis
2006-06-01
Following infection with Neisseria gonorrhoeae, bacteria may ascend into the Fallopian tubes (FT) and induce salpingitis, a major cause of infertility. In the FT, interactions between mucosal epithelial cells and gonococci are pivotal events in the pathogen's infection cycle and the inflammatory response. In the current study, primary FT epithelial cells were infected in vitro with different multiplicities of infection (MOI) of Pil+ Opa+ gonococci. Bacteria showed a dose-dependent association with cells and induced the secretion of tumor necrosis factor alpha (TNF-alpha). A significant finding was that gonococcal infection (MOI = 1) induced apoptosis in approximately 30% of cells, whereas increasing numbers of bacteria (MOI = 10 to 100) did not induce apoptosis. Apoptosis was observed in only 11% of cells with associated bacteria, whereas >84% of cells with no adherent bacteria were apoptotic. TNF-alpha was a key contributor to apoptosis, since (i) culture supernatants from cells infected with gonococci (MOI = 1) induced apoptosis in naïve cultures, suggesting that a soluble factor was responsible; (ii) gonococcal infection-induced apoptosis was inhibited with anti-TNF-alpha antibodies; and (iii) the addition of exogenous TNF-alpha induced apoptosis, which was inhibited by the presence of increasing numbers of bacteria (MOI = 10 to 100). These data suggest that TNF-alpha-mediated apoptosis of FT epithelial cells is likely a primary host defense mechanism to prevent pathogen colonization. However, epithelial cell-associated gonococci have evolved a mechanism to protect the cells from undergoing TNF-alpha-mediated apoptosis, and this modulation of the host innate response may contribute to establishment of infection. Understanding the antiapoptotic mechanisms used by Neisseria gonorrhoeae will inform the pathogenesis of salpingitis and could suggest new intervention strategies for prevention and treatment of the disease. PMID:16714596
Garcia-Ispierto, Irina; López-Gatius, Fernando
2014-01-01
This study compares in two experiments the responses of lactating dairy cows to four different progesterone-based protocols for fixed-time artificial insemination (FTAI) in terms of their effects on follicular/luteal dynamics and fertility. The protocols consisted of a progesterone intravaginal device fitted for five days, along with the administration of different combinations of gonadotropin releasing hormone, equine chorionic gonadotropin and a single or double dose (24 h apart) of prostaglandin F2α. In Experiment I, the data were derived from 232 lactating cows. Binary logistic regression identified no effects of treatment on ovulation failure or multiple ovulation 10 days post artificial insemination (AI). Based on the odds ratio, the likelihood of ovulation failure was lower (by a factor of 0.1) in cows showing at least one corpus luteum (CL) upon treatment than in cows lacking a CL; repeat breeders (> 3 AI) and cows with multiple CLs at treatment showed lower (by a factor of 0.44) and higher (by a factor of 9.0) risks of multiple ovulation, respectively, than the remaining animals. In Experiment II, the data were derived from 5173 AIs. The independent variable treatment failed to affect the conception rate 28-34 days post AI, twin pregnancy or early fetal loss 58-64 days post AI. The results of this study demonstrate the efficacy of 5-day progesterone-based protocols for FTAI. All four protocols examined were able to induce ovulation in both cyclic and non-cyclic animals so that FTAI returned a similar pregnancy rate to spontaneous estrus. Our results suggest that the ovarian response and fertility resulting from each treatment are due more to the effect of ovarian structures at treatment than to the different combinations of hormones investigated. PMID:25196275
GARCIA-ISPIERTO, Irina; LÓPEZ-GATIUS, Fernando
2014-01-01
This study compares in two experiments the responses of lactating dairy cows to four different progesterone-based protocols for fixed-time artificial insemination (FTAI) in terms of their effects on follicular/luteal dynamics and fertility. The protocols consisted of a progesterone intravaginal device fitted for five days, along with the administration of different combinations of gonadotropin releasing hormone, equine chorionic gonadotropin and a single or double dose (24 h apart) of prostaglandin F2α. In Experiment I, the data were derived from 232 lactating cows. Binary logistic regression identified no effects of treatment on ovulation failure or multiple ovulation 10 days post artificial insemination (AI). Based on the odds ratio, the likelihood of ovulation failure was lower (by a factor of 0.1) in cows showing at least one corpus luteum (CL) upon treatment than in cows lacking a CL; repeat breeders (> 3 AI) and cows with multiple CLs at treatment showed lower (by a factor of 0.44) and higher (by a factor of 9.0) risks of multiple ovulation, respectively, than the remaining animals. In Experiment II, the data were derived from 5173 AIs. The independent variable treatment failed to affect the conception rate 28–34 days post AI, twin pregnancy or early fetal loss 58–64 days post AI. The results of this study demonstrate the efficacy of 5-day progesterone-based protocols for FTAI. All four protocols examined were able to induce ovulation in both cyclic and non-cyclic animals so that FTAI returned a similar pregnancy rate to spontaneous estrus. Our results suggest that the ovarian response and fertility resulting from each treatment are due more to the effect of ovarian structures at treatment than to the different combinations of hormones investigated. PMID:25196275
Pregnancy Rate Following Luteal Phase Support in Iranian Women with Polycystic Ovarian Syndrome
Foroozanfard, Fatemeh; Saberi, Hamidreza; Moraveji, Seyed Alireza; Bazarganipour, Fatemeh
2014-01-01
Background To assess the efficacy of luteal phase support (LPS) using intravaginal progesterone (P) on pregnancy rate in Iranian women with polycystic ovarian syndrome (PCOS) who used a combination for ovulation induction consisting of letrozole or clomi- phene citrate (CC) and human menopausal gonadotropin (HMG). Materials and Methods This was a randomized clinical trial undertaken in a fertility clinic in Kashan, Isfahan Province, Iran. A total of 198 patients completed treatment and follow up. Base on chosen ovulation induction programs, they were divided into two following group: i. CC group (n=98) used a combination consisting of CC (100 mg×5 day) and HMG (150 IU×5 day) and ii. letrozole group (n=100) used a combination consisting of letrozole (5 mg×5 day) and HMG (150 IU×5 day). After human chorionic gonadotropin (hCG) administration (5000 IU), the patients (n=122) who randomly re- ceived intravaginal P (Cyclogest, 400 mg daily) were included in LPS group, while the rest (n=123) were included in non-P cycles group. The outcome was the comparison of chemical pregnancy rate between the groups. Results Our findings showed that LPS was associated with a 10% higher pregnancy rate than in non-P cycles, although this difference did not reach statistical significant (p=0.08). LPS improved pregnancy rate in both CC (4%) and letrozole (6%) groups. In addition, patients who used letrozole for ovulation induction along with intravaginal P showed higher pregnancy rates than CC group. Conclusion Administration of vaginal P for LPS may improve the pregnancy rate in women with PCOS using letrozole or CC in combination with HMG for ovulation induc- tion (Registration Number: IRCT201206072967N4). PMID:25379150
Premenstrual dysphoria and luteal stress in dominant-social-status female macaques.
Qiao, Mingqi; Zhao, Qitao; Wei, Sheng; Zhang, Huiyun; Wang, Haijun
2013-01-01
The current study aims to extend our previous work to develop nonhuman primate model for prospectively studying the mechanism underlying premenstrual dysphoric disorder (PMDD). Thirty young dominant-status female monkeys were randomly divided into the control group, the model group, and JQP group. For two consecutive menstrual cycles, from day 18 to 22, monkeys in the model and JQP groups were housed and immobilized singly in specially designed isolation cages for 5-6 hours per day. At the same time, the pharmaceutical interference effect of jingqianping (JQP) granule, a traditional Chinese medicine specifically used to cure PMDD patients, was tested using monkeys in the JQP group. The behavior and facial expressions of monkeys were photographed with an automatic vidicon and were quantitatively analyzed by "the emotion evaluation scale of female experimental macaque." Changes in serum level of progesterone and estradiol were measured with RIA, and serum level of 5-HT, noradrenaline, and dopamine were measured with HPLC. After experiencing mentioned above stress, 70% of monkeys of model group showed PMDD symptoms during three consecutive menstrual cycles. Estradiol and progesterone serum level decreased (P < 0.01). Moreover, the peak value of secreted hormones in their follicular phase did not occur. Serum level of 5-HT and dopamine were significantly lower (P < 0.01), but the serum noradrenaline level was higher (P < 0.01). Moreover, in monkeys administered by JQP granule, both PMDD symptoms and the anormal serum level of neurotransmitters could be obviously reversed. This special luteal-phase treatment on dominant-social-status monkeys might be a feasible way to create models mimicking PMDD. PMID:24371458
Comparison of Follicular and Luteal Phase Mucosal Markers of HIV Susceptibility in Healthy Women.
Thurman, Andrea Ries; Chandra, Neelima; Yousefieh, Nazita; Zalenskaya, Irina; Kimble, Thomas; Asin, Susana; Rollenhagen, Christiane; Anderson, Sharon M; Herold, Betsy; Mesquita, Pedro M M; Richardson-Harman, Nicola; Cunningham, Tina; Schwartz, Jill L; Doncel, Gustavo F
2016-06-01
The purpose of this study was to evaluate differences in vaginal immune cell populations, vaginal tissue gene expression, antimicrobial activity of the cervicovaginal (CV) lavage (CVL), vaginal flora, and p24 antigen production from CV tissues after ex vivo human immunodeficiency virus (HIV) infection between follicular (FOL) and luteal (LUT) phases of the menstrual cycle. CV tissue biopsies, CV secretions, and blood samples were obtained as part of two longitudinal clinical trials of healthy women (CONRAD D11-119 and A12-124 studies). Participants (n = 39) were HIV-seronegative women not using exogenous hormone supplementation, with normal menstrual cycles, who were screened to exclude sexually transmitted and reproductive tract infections. Serum levels of estradiol and progesterone were significantly higher in the LUT versus the FOL phase of the menstrual cycle. Controlling for race, reported contraceptive use/sexual practices, and clinical trial, we found no differences in vaginal tissue immune cell populations and activation status, transcriptomes, inhibition of HIV, herpes simplex virus type 2 and Escherichia coli by the CVL, vaginal pH or Nugent score, or production of p24 antigen after ex vivo infection by HIV-1BaL between CV samples obtained in the FOL phase versus the LUT phase of the menstrual cycle. There were no significant correlations between serum estradiol and progesterone levels and CV endpoints. The hypothesis that the LUT phase of the menstrual cycle represents a more vulnerable stage for mucosal infection with HIV was not supported by data from samples obtained from the lower genital tract (ectocervix and vagina) from these two clinical trials. PMID:26750085
Chouhan, V S; Dangi, S S; Babitha, V; Verma, M R; Bag, S; Singh, G; Sarkar, M
2015-10-15
The purpose of this study was to evaluate the temporal (24, 48, and 72 hours) and dose-dependent (0, 5, 10, and 100 ng/mL of LH, insulin-like growth factor 1 [IGF-1], and EGF) in vitro expression and secretion patterns of vascular endothelial growth factor (VEGF) in luteal cell culture during different stages of estrous cycle in water buffaloes. Corpus luteum samples from ovaries of early luteal phase (ELP; Days 1-4), midluteal phase (Days 5-10), and late luteal phase (Days 11-16) were collected from a local slaughterhouse. The samples were then processed and cultured in (serum containing) appropriate cell culture medium and incubated separately with three factors (LH, IGF-1, or EGF) at the previously mentioned three dose-duration combinations. At the end of the respective incubation periods, VEGF was assayed in the spent culture medium by ELISA, whereas the cultured cells were used for VEGF mRNA expression by quantitative real-time polymerase chain reaction. The results of the present study disclosed dose- and time-dependent stimulatory effects of LH, IGF-1, and EGF on VEGF production in bubaline luteal cells. The VEGF expression and secretion from the cultured luteal cells were highest during the ELP, intermediate in the midluteal phase, and lowest in the late luteal phase of the estrous cycle for all the three tested factors. Comparison of the results of the three treatments depicted EGF as the most potent stimulating factor followed by IGF-1 and LH. Immunocytochemistry findings in luteal cell culture of ELP agreed with the VEGF expression and secretion. In conclusion, mRNA expression, protein secretion, and immunolocalization of VEGF data clearly indicated for the first time that LH, IGF-1, and EGF play an important role in stimulating luteal angiogenesis in buffalo CL. The highest expression and secretion of VEGF in the ELP might be associated with the development of blood vessels in early growth of CL, which in turn gets augmented by the aforementioned
Embryotoxic effects adjacent and opposite to the early regressing bovine corpus luteum.
Hernandez-Fonseca, H J; Sayre, B L; Butcher, R L; Inskeep, E K
2000-07-01
Early luteal regression in cattle has an embryotoxic effect that is not overcome by replacement with progesterone, but is prevented by removal of the regressing CL. Two experiments were designed to test the null hypothesis that the luteal component of the embryotoxic effect is delivered by a systemic pathway. Beef heifers and cows (n = 39) received two good quality embryos, one placed into each uterine horn on Day 6 or 7 of the estrous cycle. Treated animals (n = 20) received 15 mg of PGF2alpha three times per day from Day 7 (n = 11; Experiment 1) or 5 (n = 9; Experiment 2) through 8; controls (n = 19) received saline. Progestogen replacement therapy (12 mg flurogestone acetate daily, s.c.) was provided from Day 6 (Experiment 1) or 4 (Experiment 2) until ultrasonographic diagnosis of embryo survival on Day 35 after estrus. The effects of treatment, location of the embryo and location by treatment interaction on embryo survival were tested by Chi square. In Experiment 1, there was no significant difference in embryo survival rate between PGF2alpha-treated and control recipients. In Experiment 2, only 6 of 18 embryos survived to Day 35 when transferred to animals treated with PGF2alpha compared to 12 of 18 in control animals (P< 0.05). The survival of embryos did not differ with location (adjacent or opposite to the regressing CL) or location by treatment interaction. Thus no evidence was obtained to support a local effect of the regressing CL. The embryo mortality associated with luteolytic doses of PGF2alpha in cows receiving replacement therapy with progestogen probably involves compounds that either act systemically or are transported via the uterine lumen to the uterine horn contralateral to the regressing CL. PMID:10990350
Prediction in Multiple Regression.
ERIC Educational Resources Information Center
Osborne, Jason W.
2000-01-01
Presents the concept of prediction via multiple regression (MR) and discusses the assumptions underlying multiple regression analyses. Also discusses shrinkage, cross-validation, and double cross-validation of prediction equations and describes how to calculate confidence intervals around individual predictions. (SLD)
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
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.
Luteal P4 synthesis in early pregnant gilts after induction of estrus with PMSG/hCG.
Blitek, Agnieszka; Szymanska, Magdalena; Pieczywek, Marta; Morawska-Pucinska, Ewa
2016-03-01
The present study was designed to examine whether an estrus induction with gonadotropins could affect luteal P4 synthesis in early pregnant gilts. Sixteen prepubertal gilts received 750IU of PMSG and 500IU of hCG 72h later. Prepubertal gilts in the control group (n=17) were observed daily for estrus behavior. All gilts were inseminated in their first estrus. Corpora lutea (CLs) were collected on days 10, 12 and 15 of pregnancy and analyzed for (1) the mRNA and protein expression of steroidogenic acute regulatory protein (StAR), cytochrome P450 family 11 subfamily A polypeptide 1 (CYP11A1), and 3β-hydroxysteroid dehydrogenase (3βHSD); (2) the tissue concentration of P4; and (3) the mRNA expression of luteinizing hormone receptor (LHR) and estrogen receptors (ESR1 and ESR2). Additionally, P4 concentration was analyzed in blood serum of all animals. PMSG/hCG injections to induce estrus decreased mRNA expression of StAR, CYP11A1 and 3βHSD on day 10 and CYP11A1 on day 12 of pregnancy compared with the control group, while CYP11A1 and 3βHSD proteins were down-regulated on day 10 in the hormonally-treated gilts. Concentrations of P4 in luteal tissue and blood serum were also lower in animals after gonadotropin-induced estrus. In contrast, LHR and ESR1 mRNA expression was greater in PMSG/hCG-treated than control gilts on day 15 of gestation. In conclusion, induction of estrus with a PMSG/hCG protocol in prepubertal gilts impaired expression of the luteal P4 synthesis system. Low P4 content may, in turn, induce local mechanisms involving LHR and ESR1 expression to support CL function. PMID:26781360
Yildiz-Arslan, Sevim; Coon, John S; Hope, Thomas J; Kim, J Julie
2016-06-01
The endocervix plays an important role in providing appropriate protective mechanisms of the upper female reproductive tract (FRT) while at the same time providing the appropriate milieu for sperm transport. Hormone fluctuations throughout the menstrual cycle contribute to changes in the mucosal environment that render the FRT vulnerable to infectious diseases. The objective of this study was to identify genes in human endocervix tissues that were differentially expressed in the follicular versus the luteal phases of the menstrual cycle using gene expression profiling. A microarray using the IIlumina platform was performed with eight endocervix tissues from follicular and four tissues from luteal phases of the menstrual cycle. Data analysis revealed significant differential expression of 110 genes between the two phases, with a P value <0.05 and a fold change cutoff of 1.5. Categorization of these genes, using Ingenuity Pathway Analysis, MetaCore from Thomson Reuters, and DAVID, revealed genes associated with extracellular matrix remodeling and cell-matrix interactions, amino acid metabolism, and lipid metabolism, as well as immune regulation in the follicular phase tissues. In luteal phase tissues, genes associated with chromatin remodeling, inflammation, angiogenesis, oxidative stress, and immune cell regulation were predominately expressed. Using samples from additional patients' tissues, select genes were confirmed by quantitative real-time PCR; immunohistochemical staining was also done to examine protein levels. This is the first microarray analysis comparing gene expression in endocervix tissues in cycling women. This study identified key genes and molecular pathways that were differentially regulated during the menstrual cycle. PMID:27170437
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
Social and breed effects on the expression of a PGF2alpha induced oestrus in beef cows.
Landaeta-Hernández, A J; Palomares-Naveda, R; Soto-Castillo, G; Atencio, A; Chase, C C; Chenoweth, P J
2004-10-01
Social organization and breed effects following PGF2alpha were studied in mature Angus, Brahman and Senepol cows allocated into two groups (each A = 5, B = 5 and S = 5). Variables including interval to oestrus onset (IEO), oestrous duration (DE), total mounts received (TMR), and oestrous intensity (IE) were derived via HeatWatch. Breed-type influenced IEO (B = 42.6 +/- 6.7 h; S = 54.6 +/- 6.0 h; and A = 27.8 +/- 5.8 h; p < 0.003). Within breeds, dominant B (69.4 +/- 13.3 h) and S (65.5 +/- 7.4 h) cows were slower (p < 0.05) to be detected in oestrus than subordinate (38.1 +/- 4.4 h) and intermediate (40.6 +/- 6.0 h). However, within A, dominant cows (16.4 +/- 12.5 h) were detected in oestrus earlier (p < 0.05) than intermediate (44.3 +/- 9.2 h) and subordinates (32.7 +/- 5.1 h). Angus (21.5 +/- 2.4 h) and B (22.1 +/- 3.0 h) cows had longer (p < 0.01) DE than S (9.1 +/- 2.8 h). Dominants (20.4 +/- 3.0) and intermediates (20.2 +/- 2.3 h) cows had longer DE (p < 0.04) than subordinates (12.1 +/- 2.1 h) although the interaction breed x social order showed that dominant S had shorter DE than dominant A and B (10.1 +/- 3.3; 34.8 +/- 6.0 h; and 20.0 +/- 6.4 h, respectively; p < 0.001). Angus cows had less TMR than B (p < 0.02) and tended to be less than S cows (p < 0.06). Overall, greatest (p < 0.008) IE occurred in the first 9 h after onset of oestrus with no breed effect (p > 0.05). Dominant cows tended (p < 0.10) to have less TMR (3.2 +/- 0.7 mounts) than subordinate (4.1 +/- 0.4 mounts) and intermediate (4.7 +/- 0.6 mounts) throughout, especially 3-6 h after oestrus onset (p < 0.07). Breed and social order both influence PGF2alpha-induced oestrus behaviour. PMID:15367263
Schmitz, H; Fromm, M; Bode, H; Scholz, P; Riecken, E O; Schulzke, J D
1996-10-01
Increased levels of tumor necrosis factor-alpha (TNF-alpha) have been found in, for example, inflammatory bowel disease (IBD) and human immunodeficiency virus (HIV) infection. To investigate a possible contribution of TNF-alpha to the pathogenesis of diarrhea in these diseases, ion transport of human distal colon was studied in the Ussing chamber in vitro. Serosal addition of TNF-alpha increased short-circuit current (Isc) of partially stripped tissues in a dose-dependent manner. Maximum Isc increase of 1.8 +/- 0.2 mumol.h-1.cm-2 was reached after 60 +/- 9 min at 200 ng/ml TNF-alpha. Bidirectional tracer flux measurements revealed that TNF-alpha induced an increase in 36 Cl serosal-to-mucosal flux, a decrease in 36Cl- mucosal-to-serosal flux, and a slight increase in K+ secretion indicated by an increased secretory 86Rb net flux. In the highly differentiated colonic epithelial cell line HT-29/B6, TNF-alpha had no effect on Isc, suggesting a mediation step located in the subepithelium. This supposition was supported by measurements on totally stripped human tissues, since removal of subepithelial layers by total stripping reduced the TNF-alpha effect by 40%. Experiments with tetrodotoxin (10(-6)M) indicated that the TNF-alpha effect was not mediated by the enteric nervous system. The specific 5-lipoxygenase blocker ICI-230487 (5 x 10(-8)M) also had no effect on TNF-alpha action. In contrast, inhibition of cyclooxygenase by indomethacin (10(-6)M inhibited the effect of TNF-alpha. Radioimmunoassay of prostaglandin E2 (PGE2) in the serosal bathing solution revealed an increase in PGE2 production/release after addition of TNF-alpha, which paralleled the Isc response. We conclude that TNF-alpha changed Cl- and K+ transport toward secretion in human colon. This effect was mediated by PGE2 produced by subepithelial cells. Thus TNF-alpha could be a mediator of diarrhea during intestinal inflammation, e.g., in IBD and HIV infection. PMID:8897887
Glick, G; Hogeg, M; Moallem, U; Lavon, Y; Wolfenson, D
2013-01-01
A protocol based on small doses of FSH was examined for the induction of double or triple (multiple) ovulations in cattle. Ovulation rate, follicular characteristics, and luteal responses were determined. In Exp. 1, three groups of estrous-synchronized, cyclic Holstein heifers were treated once daily, on d 3 to 6 of the cycle, with a FSH product (Folltropin-V): large FSH dose (total of 150 mg; n=18), medium FSH dose (total of 130 mg, n=12), and small FSH dose (total of 80 mg; n=7). Controls received saline (n=6). Prostaglandin F(2α) was injected on d 6, ultrasound-guided aspiration of surplus follicles (if needed) was performed on d 7, and GnRH was injected on d 8 to induce ovulation. The large FSH dose induced growth of more (2.6±0.3, P<0.05) large follicles than controls on d 8; medium and small FSH doses insufficiently stimulated growth of <2 large follicles. Ovulation rates were determined in subgroups of heifers (n=10, 13, 4, and 6, respectively). The large FSH dose induced greater rates (P<0.01) of mostly double and triple ovulations (90% multiple ovulations, 70% double ovulations), most of which (89%) were bilateral, with only 2 out of 10 heifers requiring aspiration of surplus follicles. Medium and small FSH doses induced fewer multiple ovulations (38% and 25%, respectively). Estradiol concentrations on d 8 did not differ among treatments, but the concentration per large follicle in controls was greater (P<0.05) than in FSH treatments. Mean corpus luteum (CL) volume in single-ovulation controls was greater (P<0.05) than that of multiple ovulations in the large FSH group and total CL volume and progesterone concentrations were numerically greater in multiple ovulations. In Exp. 2, the characteristics of follicles aspirated on d 7 from large FSH (n=11) and control heifers (n=10) were compared. Based on estradiol-to-progesterone ratio, 57% of the large FSH-treated follicles were classified as codominant/healthy follicles and 43% as subordinate/early atretic
Weems, Yoshie S; Ma, Yan; Ford, Stephen P; Nett, Terry M; Vann, Rhonda C; Lewis, Andrew W; Neuendorff, Don A; Welsh, Thomas H; Randel, Ronald D; Weems, Charles W
2014-12-01
Previously, it was reported that intraluteal implants containing prostaglandin E1 or E2 (PGE1 and PGE2) in Angus or Brahman cows prevented luteolysis by preventing loss of mRNA expression for luteal LH receptors and luteal unoccupied and occupied LH receptors. In addition, intraluteal implants containing PGE1 or PGE2 upregulated mRNA expression for FP prostanoid receptors and downregulated mRNA expression for EP2 and EP4 prostanoid receptors. Luteal weight during the estrous cycle of Brahman cows was reported to be lesser than that of Angus cows but not during pregnancy. The objective of this experiment was to determine whether intraluteal implants containing PGE1 or PGE2 alter vascular endothelial growth factor (VEGF), fibroblast growth factor-2 (FGF-2), angiopoietin-1 (ANG-1), and angiopoietin-2 (ANG-2) protein in Brahman or Angus cows. On Day 13 of the estrous cycle, Angus cows received no intraluteal implant and corpora lutea were retrieved, or Angus and Brahman cows received intraluteal silastic implants containing vehicle, PGE1, or PGE2 on Day 13 and corpora lutea were retrieved on Day 19. Corpora lutea slices were analyzed for VEGF, FGF-2, ANG-1, and ANG-2 angiogenic proteins via Western blot. Day-13 Angus cow luteal tissue served as preluteolytic controls. Data for VEGF were not affected (P > 0.05) by day, breed, or treatment. PGE1 or PGE2 increased (P < 0.05) FGF-2 in luteal tissue of Angus cows compared with Day-13 and Day-19 Angus controls but decreased (P < 0.05) FGF-2 in luteal tissue of Brahman cows when compared w Day-13 or Day-19 Angus controls. There was no effect (P > 0.05) of PGE1 or PGE2 on ANG-1 in Angus luteal tissue when compared with Day-13 or Day-19 controls, but ANG-1 was decreased (P < 0.05) by PGE1 or PGE2 in Brahman cows when compared with Day-19 Brahman controls. ANG-2 was increased (P < 0.05) on Day 19 in Angus Vehicle controls when compared with Day-13 Angus controls, which was prevented (P < 0.05) by PGE1 but not by PGE2 in Angus
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.
Multivariate Regression with Calibration*
Liu, Han; Wang, Lie; Zhao, Tuo
2014-01-01
We propose a new method named calibrated multivariate regression (CMR) for fitting high dimensional multivariate regression models. Compared to existing methods, CMR calibrates the regularization for each regression task with respect to its noise level so that it is simultaneously tuning insensitive and achieves an improved finite-sample performance. Computationally, we develop an efficient smoothed proximal gradient algorithm which has a worst-case iteration complexity O(1/ε), where ε is a pre-specified numerical accuracy. Theoretically, we prove that CMR achieves the optimal rate of convergence in parameter estimation. We illustrate the usefulness of CMR by thorough numerical simulations and show that CMR consistently outperforms other high dimensional multivariate regression methods. We also apply CMR on a brain activity prediction problem and find that CMR is as competitive as the handcrafted model created by human experts. PMID:25620861
Abe, H; Onodera, M; Sugawara, S
1993-01-01
The luminal surfaces of epithelial cells in various regions of the oviducts of the goats at the follicular and luteal phases of the oestrous cycle were examined by scanning electron microscopy. Marked cyclic changes were observed on the surface of the epithelium in the fimbriae, ampulla and ampullar-isthmic junction, but few changes were found in the isthmus or uterotubal junction. The epithelium of the fimbriae, ampulla, and ampullar-isthmic junction of oviducts in the follicular phase was extensively ciliated and most of the cilia extended above the apical processes of the nonciliated cells. In the luteal phase, many ciliated cells were hidden by the bulbous processes of the nonciliated cells. In the isthmus and at the uterotubal junction, the apical surfaces of the nonciliated cells were flat or gently rounded at both phases of the oestrous cycle. The results demonstrate that regional variations are associated with the cyclic changes in the epithelial cells of the goat oviduct. Images Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 5 Fig. 6 Fig. 7 Fig. 8 Fig. 9 Fig. 10 PMID:8300425
Xie, Jing; Eliassen, A. Heather; Xu, Xia; Matthews, Charles E.; Hankinson, Susan E.; Ziegler, Regina G.; Tworoger, Shelley S.
2012-01-01
Estrogen metabolism profiles may play an important role in the relationship between body size and breast carcinogenesis. Previously, we observed inverse associations between current body mass index (BMI) and plasma levels of parent estrogens (estrone and estradiol) among premenopausal women during both follicular and luteal phases. Using data from the Nurses’ Health Study II (NHS II), we assessed whether height, current BMI, and BMI at age 18 were associated with the urinary concentrations of 15 estrogens and estrogen metabolites (jointly referred to as EM) measured during the luteal phase among 603 premenopausal women. We observed inverse associations with total EM for height (Ptrend=0.01) and current BMI (Ptrend=0.01), but not BMI at age 18 (Ptrend=0.26). Six EMs were 18–27% lower in women with a height 68+ inches versus ≤62 inches, primarily in the methylated catechol pathway (Ptrend=0.04). Eight EMs were 18–50% lower in women with a BMI of 30+ versus <20, primarily in the 2-catechol and methylated catechol pathways (Ptrend<0.001 for both). Our results suggest that height and current BMI are associated with estrogen metabolism profiles in premenopausal women. Further studies with timed urine and blood collections are required to confirm and extend our findings. PMID:23011724
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.
Yu, Jing; Eto, Masato; Akishita, Masahiro; Okabe, Tetsuro; Ouchi, Yasuyoshi
2009-07-01
Tumor necrosis factor (TNF-alpha) is a pleiotropic cytokine exerting both inflammatory and cell death activity and is thought to play a role in the pathogenesis of atherosclerosis. The present study was designed to examine whether the raloxifene analogue, LY117018 could inhibit TNF-alpha-induced apoptosis in vascular endothelial cells and to clarify the involved mechanisms. Apoptosis of endothelial cells was determined by DNA fragmentation assay and the activation of caspase-3. LY117018 significantly inhibited TNF-alpha-induced caspase-3 activation and cell DNA fragmentation levels in bovine carotid artery endothelial cells. The inhibitory effect of LY117018 was abolished by an estrogen receptor antagonist ICI 182,780. p38 MAPK, JNK, ERK1/2 and Akt have been shown to act as apoptotic or anti-apoptotic signals. TNF-alpha stimulated the phosphorylation levels of p38 MAPK, JNK, ERK1/2 and Akt in vascular endothelial cells. TNF-alpha-induced apoptosis was significantly decreased by SB203580, a p38 MAPK inhibitor or SP600125, a JNK inhibitor, but was enhanced by an ERK1/2 pathway inhibitor, PD98059 or a PI3-kinase/Akt pathway inhibitor, wortmannin. The anti-apoptotic effect of LY117018 was abrogated only by PD98059 but was not affected by the inhibitors for p38 MAPK, JNK, or Akt. LY117018 stimulated the further increase in phosphorylation of ERK1/2 in TNF-alpha treated endothelial cells but it did not affect phosphorylation levels of p38 MAPK, JNK or Akt. These results suggest that LY 110718 prevents caspase-3 dependent apoptosis induced by TNF-alpha in vascular endothelial cells through activation of the estrogen receptors and the ERK1/2 signaling pathway. PMID:19275968
Lin, C.-C.; Tseng, Hsiao-Wei; Hsieh, Hsi-Lung; Lee, Chiang-Wen; Wu, C.-Y.; Cheng, C.-Y.; Yang, C.-M.
2008-06-15
Matrix metalloproteinases (MMPs), in particular MMP-9, have been shown to be induced by cytokines including tumor necrosis factor-{alpha} (TNF-{alpha}) and contributes to airway inflammation. However, the mechanisms underlying MMP-9 expression induced by TNF-{alpha} in human A549 cells remain unclear. Here, we showed that TNF-{alpha} induced production of MMP-9 protein and mRNA is determined by zymographic, Western blotting, RT-PCR and ELISA assay, which were attenuated by inhibitors of MEK1/2 (U0126), JNK (SP600125), and NF-{kappa}B (helenalin), and transfection with dominant negative mutants of ERK2 ({delta}ERK) and JNK ({delta}JNK), and siRNAs for MEK1, p42 and JNK2. TNF-{alpha}-stimulated phosphorylation of p42/p44 MAPK and JNK were attenuated by pretreatment with the inhibitors U0126 and SP600125 or transfection with dominant negative mutants of {delta}ERK and {delta}JNK. Furthermore, the involvement of NF-{kappa}B in TNF-{alpha}-induced MMP-9 production was consistent with that TNF-{alpha}-stimulated degradation of I{kappa}B-{alpha} and translocation of NF-{kappa}B into the nucleus which were blocked by helenalin, but not by U0126 and SP600125, revealed by immunofluorescence staining. The regulation of MMP-9 gene transcription by MAPKs and NF-{kappa}B was further confirmed by gene luciferase activity assay. MMP-9 promoter activity was enhanced by TNF-{alpha} in A549 cells transfected with wild-type MMP-9-Luc, which was inhibited by helenalin, U0126, or SP600125. In contrast, TNF-{alpha}-stimulated MMP-9 luciferase activity was totally lost in cells transfected with mutant-NF-{kappa}B MMP-9-luc. Moreover, pretreatment with actinomycin D and cycloheximide attenuated TNF-{alpha}-induced MMP-9 expression. These results suggest that in A549 cells, phosphorylation of p42/p44 MAPK, JNK, and transactivation of NF-{kappa}B are essential for TNF-{alpha}-induced MMP-9 gene expression.
Regression versus No Regression in the Autistic Disorder: Developmental Trajectories
ERIC Educational Resources Information Center
Bernabei, P.; Cerquiglini, A.; Cortesi, F.; D' Ardia, C.
2007-01-01
Developmental regression is a complex phenomenon which occurs in 20-49% of the autistic population. Aim of the study was to assess possible differences in the development of regressed and non-regressed autistic preschoolers. We longitudinally studied 40 autistic children (18 regressed, 22 non-regressed) aged 2-6 years. The following developmental…
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.
NASA Astrophysics Data System (ADS)
Veloce, L. M.; Kuźniak, M.; Di Stefano, P. C. F.; Noble, A. J.; Boulay, M. G.; Nadeau, P.; Pollmann, T.; Clark, M.; Piquemal, M.; Schreiner, K.
2016-06-01
Liquid noble based particle detectors often use the organic wavelength shifter 1,1,4,4-tetraphenyl-1,3-butadiene (TPB) which shifts UV scintillation light to the visible regime, facilitating its detection, but which also can scintillate on its own. Dark matter searches based on this type of detector commonly rely on pulse-shape discrimination (PSD) for background mitigation. Alpha-induced scintillation therefore represents a possible background source in dark matter searches. The timing characteristics of this scintillation determine whether this background can be mitigated through PSD. We have therefore characterized the pulse shape and light yield of alpha induced TPB scintillation at temperatures ranging from 300 K down to 4 K, with special attention given to liquid noble gas temperatures. We find that the pulse shapes and light yield depend strongly on temperature. In addition, the significant contribution of long time constants above ~50 K provides an avenue for discrimination between alpha decay events in TPB and nuclear-recoil events in noble liquid detectors.
Arnold, Kelly B.; Novak, Richard M.; McCorrister, Stuart; Shaw, Souradet; Westmacott, Garrett R.; Ball, Terry B.; Lauffenburger, Douglas A.; Burgener, Adam
2015-01-01
ABSTRACT The variable infectivity and transmissibility of HIV/SHIV has been recently associated with the menstrual cycle, with particular susceptibility observed during the luteal phase in nonhuman primate models and ex vivo human explant cultures, but the mechanism is poorly understood. Here, we performed an unbiased, mass spectrometry-based proteomic analysis to better understand the mucosal immunological processes underpinning this observed susceptibility to HIV infection. Cervicovaginal lavage samples (n = 19) were collected, characterized as follicular or luteal phase using days since last menstrual period, and analyzed by tandem mass spectrometry. Biological insights from these data were gained using a spectrum of computational methods, including hierarchical clustering, pathway analysis, gene set enrichment analysis, and partial least-squares discriminant analysis with LASSO feature selection. Of the 384 proteins identified, 43 were differentially abundant between phases (P < 0.05, ≥2-fold change). Cell-cell adhesion proteins and antiproteases were reduced, and leukocyte recruitment (interleukin-8 pathway, P = 1.41E–5) and extravasation proteins (P = 5.62E–4) were elevated during the luteal phase. LASSO/PLSDA identified a minimal profile of 18 proteins that best distinguished the luteal phase. This profile included cytoskeletal elements and proteases known to be involved in cellular movement. Gene set enrichment analysis associated CD4+ T cell and neutrophil gene set signatures with the luteal phase (P < 0.05). Taken together, our findings indicate a strong association between proteins involved in tissue remodeling and leukocyte infiltration with the luteal phase, which may represent potential hormone-associated mechanisms of increased susceptibility to HIV. IMPORTANCE Recent studies have discovered an enhanced susceptibility to HIV infection during the progesterone-dominant luteal phase of the menstrual cycle. However, the mechanism responsible for
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 connection.…
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…
Webcast entitled Statistical Tools for Making Sense of Data, by the National Nutrient Criteria Support Center, N-STEPS (Nutrients-Scientific Technical Exchange Partnership. The section "Correlation and Regression" provides an overview of these two techniques in the context of nut...
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.
Partial covariate adjusted regression
Şentürk, Damla; Nguyen, Danh V.
2008-01-01
Covariate adjusted regression (CAR) is a recently proposed adjustment method for regression analysis where both the response and predictors are not directly observed (Şentürk and Müller, 2005). The available data has been distorted by unknown functions of an observable confounding covariate. CAR provides consistent estimators for the coefficients of the regression between the variables of interest, adjusted for the confounder. We develop a broader class of partial covariate adjusted regression (PCAR) models to accommodate both distorted and undistorted (adjusted/unadjusted) predictors. The PCAR model allows for unadjusted predictors, such as age, gender and demographic variables, which are common in the analysis of biomedical and epidemiological data. The available estimation and inference procedures for CAR are shown to be invalid for the proposed PCAR model. We propose new estimators and develop new inference tools for the more general PCAR setting. In particular, we establish the asymptotic normality of the proposed estimators and propose consistent estimators of their asymptotic variances. Finite sample properties of the proposed estimators are investigated using simulation studies and the method is also illustrated with a Pima Indians diabetes data set. PMID:20126296
Mechanisms of neuroblastoma regression
Brodeur, Garrett M.; Bagatell, Rochelle
2014-01-01
Recent genomic and biological studies of neuroblastoma have shed light on the dramatic heterogeneity in the clinical behaviour of this disease, which spans from spontaneous regression or differentiation in some patients, to relentless disease progression in others, despite intensive multimodality therapy. This evidence also suggests several possible mechanisms to explain the phenomena of spontaneous regression in neuroblastomas, including neurotrophin deprivation, humoral or cellular immunity, loss of telomerase activity and alterations in epigenetic regulation. A better understanding of the mechanisms of spontaneous regression might help to identify optimal therapeutic approaches for patients with these tumours. Currently, the most druggable mechanism is the delayed activation of developmentally programmed cell death regulated by the tropomyosin receptor kinase A pathway. Indeed, targeted therapy aimed at inhibiting neurotrophin receptors might be used in lieu of conventional chemotherapy or radiation in infants with biologically favourable tumours that require treatment. Alternative approaches consist of breaking immune tolerance to tumour antigens or activating neurotrophin receptor pathways to induce neuronal differentiation. These approaches are likely to be most effective against biologically favourable tumours, but they might also provide insights into treatment of biologically unfavourable tumours. We describe the different mechanisms of spontaneous neuroblastoma regression and the consequent therapeutic approaches. PMID:25331179
Bayesian ARTMAP for regression.
Sasu, L M; Andonie, R
2013-10-01
Bayesian ARTMAP (BA) is a recently introduced neural architecture which uses a combination of Fuzzy ARTMAP competitive learning and Bayesian learning. Training is generally performed online, in a single-epoch. During training, BA creates input data clusters as Gaussian categories, and also infers the conditional probabilities between input patterns and categories, and between categories and classes. During prediction, BA uses Bayesian posterior probability estimation. So far, BA was used only for classification. The goal of this paper is to analyze the efficiency of BA for regression problems. Our contributions are: (i) we generalize the BA algorithm using the clustering functionality of both ART modules, and name it BA for Regression (BAR); (ii) we prove that BAR is a universal approximator with the best approximation property. In other words, BAR approximates arbitrarily well any continuous function (universal approximation) and, for every given continuous function, there is one in the set of BAR approximators situated at minimum distance (best approximation); (iii) we experimentally compare the online trained BAR with several neural models, on the following standard regression benchmarks: CPU Computer Hardware, Boston Housing, Wisconsin Breast Cancer, and Communities and Crime. Our results show that BAR is an appropriate tool for regression tasks, both for theoretical and practical reasons. PMID:23665468
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
Gurbuzler, Levent; Yelken, Kursat; Aladag, Ibrahim; Eyibilen, Ahmet; Koc, Sema
2012-08-01
We conducted a study to examine cochlear activity in women with a naturally occurring menstrual cycle by measuring transient otoacoustic emissions (TOAEs) and distortion-product otoacoustic emissions (DPOAEs). Our study population was made up of 11 women aged 20 to 40 years (mean: 35.6) who were not taking a contraceptive medication or hormone therapy. Measurements of TOAEs and DPOAEs were made during both the follicular phase and the luteal phase of the menstrual cycle. We found no statistically significant difference in any of the TOAE amplitude values between the two phases. Although a sharp decrease at the 0.75 kHz frequency was seen in DPOAEs during both phases, none of the amplitude values in the tested frequencies were significantly different between the two phases. The absence of TOAE and DPOAE amplitude changes suggests that it is unnecessary to take into account the phase of the menstrual cycle when interpreting the results of otoacoustic emissions testing. PMID:22930081
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
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. PMID:26143362
KUBO, Haruna; OTSUKA, Midori; KADOKAWA, Hiroya
2015-01-01
Vomeronasal 1 receptors (V1R) are a family of receptors for intraspecies chemosignals, including pheromones, and are expressed in the olfactory epithelium (OE) and vomeronasal organ (VO). Even in the well-studied rodents, it is unclear which members of the V1R family cause sexual polymorphisms, as there are numerous genes and it is difficult to quantify their expressions individually. Bovine species carry only 34 V1R homologs, and the OE and VOs are large enough to sample. Here, V1R expression was quantified in the OE and VOs of individual bovines. Based on the 34 gene sequences, we obtained a molecular dendrogram consisting of four clusters and six independent branches. Semi-quantitative RT-PCR was used to obtain gene expression profiles in the VOs and OE of 5 Japanese Black bulls, 5 steers, 7 estrous heifers and 6 early luteal-phase heifers. Ten genes showed significant between-group differences, and 22 showed high expression in VOs than in OE. The bulls showed higher expression of one gene more in OE and another in VOs (both P<0.05) than did steers; both genes belonged to the first cluster. No genes were expressed more abundantly in steers than in bulls. The estrous heifers showed higher expression of a gene of the second cluster in OE, and a gene of the third cluster in VOs (both P<0.05) than did early luteal-phase heifers. These results suggest V1R expression exhibits sexual polymorphisms in cattle. PMID:26477467
Kubo, Haruna; Otsuka, Midori; Kadokawa, Hiroya
2016-02-01
Vomeronasal 1 receptors (V1R) are a family of receptors for intraspecies chemosignals, including pheromones, and are expressed in the olfactory epithelium (OE) and vomeronasal organ (VO). Even in the well-studied rodents, it is unclear which members of the V1R family cause sexual polymorphisms, as there are numerous genes and it is difficult to quantify their expressions individually. Bovine species carry only 34 V1R homologs, and the OE and VOs are large enough to sample. Here, V1R expression was quantified in the OE and VOs of individual bovines. Based on the 34 gene sequences, we obtained a molecular dendrogram consisting of four clusters and six independent branches. Semi-quantitative RT-PCR was used to obtain gene expression profiles in the VOs and OE of 5 Japanese Black bulls, 5 steers, 7 estrous heifers and 6 early luteal-phase heifers. Ten genes showed significant between-group differences, and 22 showed high expression in VOs than in OE. The bulls showed higher expression of one gene more in OE and another in VOs (both P<0.05) than did steers; both genes belonged to the first cluster. No genes were expressed more abundantly in steers than in bulls. The estrous heifers showed higher expression of a gene of the second cluster in OE, and a gene of the third cluster in VOs (both P<0.05) than did early luteal-phase heifers. These results suggest V1R expression exhibits sexual polymorphisms in cattle. PMID:26477467
Ridge Regression: A Regression Procedure for Analyzing Correlated Independent Variables.
ERIC Educational Resources Information Center
Rakow, Ernest A.
Ridge regression is presented as an analytic technique to be used when predictor variables in a multiple linear regression situation are highly correlated, a situation which may result in unstable regression coefficients and difficulties in interpretation. Ridge regression avoids the problem of selection of variables that may occur in stepwise…
Ridge Regression Signal Processing
NASA Technical Reports Server (NTRS)
Kuhl, Mark R.
1990-01-01
The introduction of the Global Positioning System (GPS) into the National Airspace System (NAS) necessitates the development of Receiver Autonomous Integrity Monitoring (RAIM) techniques. In order to guarantee a certain level of integrity, a thorough understanding of modern estimation techniques applied to navigational problems is required. The extended Kalman filter (EKF) is derived and analyzed under poor geometry conditions. It was found that the performance of the EKF is difficult to predict, since the EKF is designed for a Gaussian environment. A novel approach is implemented which incorporates ridge regression to explain the behavior of an EKF in the presence of dynamics under poor geometry conditions. The basic principles of ridge regression theory are presented, followed by the derivation of a linearized recursive ridge estimator. Computer simulations are performed to confirm the underlying theory and to provide a comparative analysis of the EKF and the recursive ridge estimator.
Fast Censored Linear Regression
HUANG, YIJIAN
2013-01-01
Weighted log-rank estimating function has become a standard estimation method for the censored linear regression model, or the accelerated failure time model. Well established statistically, the estimator defined as a consistent root has, however, rather poor computational properties because the estimating function is neither continuous nor, in general, monotone. We propose a computationally efficient estimator through an asymptotics-guided Newton algorithm, in which censored quantile regression methods are tailored to yield an initial consistent estimate and a consistent derivative estimate of the limiting estimating function. We also develop fast interval estimation with a new proposal for sandwich variance estimation. The proposed estimator is asymptotically equivalent to the consistent root estimator and barely distinguishable in samples of practical size. However, computation time is typically reduced by two to three orders of magnitude for point estimation alone. Illustrations with clinical applications are provided. PMID:24347802
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…
Correlation and simple linear regression.
Eberly, Lynn E
2007-01-01
This chapter highlights important steps in using correlation and simple linear regression to address scientific questions about the association of two continuous variables with each other. These steps include estimation and inference, assessing model fit, the connection between regression and ANOVA, and study design. Examples in microbiology are used throughout. This chapter provides a framework that is helpful in understanding more complex statistical techniques, such as multiple linear regression, linear mixed effects models, logistic regression, and proportional hazards regression. PMID:18450049
Liew, F Y; Li, Y; Millott, S
1990-01-01
Peritoneal macrophages from CBA mice incubated with recombinant murine tumour necrosis factor (TNF-alpha) are effective in killing the protozoa parasite Leishmania major in vitro. The leishmanicidal activity is directly correlated with the level of nitrite (NO2-) in the culture supernatants. The killing of intracellular parasites can be completely inhibited by L-NG-monomethyl arginine (L-NMMA), a specific inhibitor of the L-arginine:nitric oxide (NO) pathway. The level of NO2-, which is also a measurement of NO production, in the culture supernatant of TNF-alpha-activated macrophages can be progressively decreased to basal level with increasing concentrations of L-NMMA, but not with its D-enantiomer, D-NMMA. These data demonstrate that NO is an important effector mechanism in the TNF-alpha-induced macrophage killing of intracellular protozoa. PMID:2279740
Incremental hierarchical discriminant regression.
Weng, Juyang; Hwang, Wey-Shiuan
2007-03-01
This paper presents incremental hierarchical discriminant regression (IHDR) which incrementally builds a decision tree or regression tree for very high-dimensional regression or decision spaces by an online, real-time learning system. Biologically motivated, it is an approximate computational model for automatic development of associative cortex, with both bottom-up sensory inputs and top-down motor projections. At each internal node of the IHDR tree, information in the output space is used to automatically derive the local subspace spanned by the most discriminating features. Embedded in the tree is a hierarchical probability distribution model used to prune very unlikely cases during the search. The number of parameters in the coarse-to-fine approximation is dynamic and data-driven, enabling the IHDR tree to automatically fit data with unknown distribution shapes (thus, it is difficult to select the number of parameters up front). The IHDR tree dynamically assigns long-term memory to avoid the loss-of-memory problem typical with a global-fitting learning algorithm for neural networks. A major challenge for an incrementally built tree is that the number of samples varies arbitrarily during the construction process. An incrementally updated probability model, called sample-size-dependent negative-log-likelihood (SDNLL) metric is used to deal with large sample-size cases, small sample-size cases, and unbalanced sample-size cases, measured among different internal nodes of the IHDR tree. We report experimental results for four types of data: synthetic data to visualize the behavior of the algorithms, large face image data, continuous video stream from robot navigation, and publicly available data sets that use human defined features. PMID:17385628
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.
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. PMID:15240148
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
Pirard, Céline; Loumaye, Ernest; Laurent, Pascale; 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
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.
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
Pandey, A K; Ghuman, S P S; Dhaliwal, G S; Kumar, Ajeet; Agarwal, S K
2013-01-30
The present study investigated the impact of gonadotropic hormone administration on day 12 post-ovulation on subsequent luteal profile and conception rate in buffaloes. All the buffaloes (n=48) were estrus synchronized by a synthetic analogue of prostaglandin F(2α) (PGF(2α)), administered 11 days apart, followed by insemination during mid to late estrus. To examine the effect of mid-luteal phase hormonal treatment, buffaloes were randomly divided into control (normal saline, n=14), d12-BA (buserelin acetate, 20μg, n=17) and d12-hCG (hCG, 3000IU, n=17) groups. Ovaries were scanned on the day of induced estrus to measure the preovulatory follicle (POF) diameter and on days 5, 12, 16 and 21 post-ovulation to examine the alterations in corpus luteum (CL) diameter. On the day of each sonography, blood samples were collected for the estimation of plasma progesterone. In treatment groups, luteal profile (CL diameter and plasma progesterone) on day 16-21 post-ovulation was better (P<0.05) as well as first service conception rate was higher (52.9% in each treatment group vs. 28.6%, P>0.05) compared to controls. All the pregnant buffaloes exhibited higher (P<0.05) plasma progesterone on various post-ovulation days than their respective non-pregnant counterparts. Treatment-induced accessory corpus luteum (ACL) formation was observed in 58.8 per cent and 70.6 per cent buffaloes of d12-BA and d12-hCG group, respectively, that also had higher (P<0.05) plasma progesterone compared to controls. Compared to the spontaneous CL, the diameter of ACL was less (P<0.05) in the treatment groups. In conclusion, buserelin acetate and hCG administration on day 12 post-ovulation leads to accessory CL formation, improves luteal profile and consequently increases conception rate in buffaloes. PMID:23201300
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. PMID:16162390
Recursive Algorithm For Linear Regression
NASA Technical Reports Server (NTRS)
Varanasi, S. V.
1988-01-01
Order of model determined easily. Linear-regression algorithhm includes recursive equations for coefficients of model of increased order. Algorithm eliminates duplicative calculations, facilitates search for minimum order of linear-regression model fitting set of data satisfactory.
Raynaud, J P; Mary, I; Moguilewsky, M; Mouren, M; Labrie, F
1980-12-01
The administration of 200 microgram of the potent luteinizing hormone-releasing hormone (LHRH) agonist [D-Leu6,des-Gly-NH2(10)]LHRH ethylamide on day 6 following the plasma estradiol peak to 11 female monkeys (Macaca fascicularis) during two consecutive menstrual cycles decreased plasma progesterone levels by 40.0% +/- 3.9% as compared with previous control cycles. The plasma estradiol profile and the cycle length were not affected significantly by the treatment. Similar results were obtained with 25 microgram of [D-Ser(TBU)6,des-Gly-NH2(10)]LHRH ethylamide administered to one monkey at the same period of the cycle, such treatment leading to a 41% inhibition of circulating progesterone levels. Although plasma progesterone levels were still reduced in the two post-treatment cycles in monkeys treated with the high dose (200 microgram) of [D-Leu6,des-Gly-NH2(10)]LHRH ethylamide, the recovery cycle was normal after the administration of a lower dose (25 microgram) of [D-Ser(TBU)6, des-Gly-NH2(10)] LHRH ethylamide. The M. fascicularis monkey thus appears as a valid model with which to study the inhibitory effects of LHRH agonists on luteal function. PMID:6778718
Multinomial logistic regression ensembles.
Lee, Kyewon; Ahn, Hongshik; Moon, Hojin; Kodell, Ralph L; Chen, James J
2013-05-01
This article proposes a method for multiclass classification problems using ensembles of multinomial logistic regression models. A multinomial logit model is used as a base classifier in ensembles from random partitions of predictors. The multinomial logit model can be applied to each mutually exclusive subset of the feature space without variable selection. By combining multiple models the proposed method can handle a huge database without a constraint needed for analyzing high-dimensional data, and the random partition can improve the prediction accuracy by reducing the correlation among base classifiers. The proposed method is implemented using R, and the performance including overall prediction accuracy, sensitivity, and specificity for each category is evaluated on two real data sets and simulation data sets. To investigate the quality of prediction in terms of sensitivity and specificity, the area under the receiver operating characteristic (ROC) curve (AUC) is also examined. The performance of the proposed model is compared to a single multinomial logit model and it shows a substantial improvement in overall prediction accuracy. The proposed method is also compared with other classification methods such as the random forest, support vector machines, and random multinomial logit model. PMID:23611203
Bayesian Spatial Quantile Regression
Reich, Brian J.; Fuentes, Montserrat; Dunson, David B.
2013-01-01
Tropospheric ozone is one of the six criteria pollutants regulated by the United States Environmental Protection Agency under the Clean Air Act and has been linked with several adverse health effects, including mortality. Due to the strong dependence on weather conditions, ozone may be sensitive to climate change and there is great interest in studying the potential effect of climate change on ozone, and how this change may affect public health. In this paper we develop a Bayesian spatial model to predict ozone under different meteorological conditions, and use this model to study spatial and temporal trends and to forecast ozone concentrations under different climate scenarios. We develop a spatial quantile regression model that does not assume normality and allows the covariates to affect the entire conditional distribution, rather than just the mean. The conditional distribution is allowed to vary from site-to-site and is smoothed with a spatial prior. For extremely large datasets our model is computationally infeasible, and we develop an approximate method. We apply the approximate version of our model to summer ozone from 1997–2005 in the Eastern U.S., and use deterministic climate models to project ozone under future climate conditions. Our analysis suggests that holding all other factors fixed, an increase in daily average temperature will lead to the largest increase in ozone in the Industrial Midwest and Northeast. PMID:23459794
Bayesian Spatial Quantile Regression.
Reich, Brian J; Fuentes, Montserrat; Dunson, David B
2011-03-01
Tropospheric ozone is one of the six criteria pollutants regulated by the United States Environmental Protection Agency under the Clean Air Act and has been linked with several adverse health effects, including mortality. Due to the strong dependence on weather conditions, ozone may be sensitive to climate change and there is great interest in studying the potential effect of climate change on ozone, and how this change may affect public health. In this paper we develop a Bayesian spatial model to predict ozone under different meteorological conditions, and use this model to study spatial and temporal trends and to forecast ozone concentrations under different climate scenarios. We develop a spatial quantile regression model that does not assume normality and allows the covariates to affect the entire conditional distribution, rather than just the mean. The conditional distribution is allowed to vary from site-to-site and is smoothed with a spatial prior. For extremely large datasets our model is computationally infeasible, and we develop an approximate method. We apply the approximate version of our model to summer ozone from 1997-2005 in the Eastern U.S., and use deterministic climate models to project ozone under future climate conditions. Our analysis suggests that holding all other factors fixed, an increase in daily average temperature will lead to the largest increase in ozone in the Industrial Midwest and Northeast. PMID:23459794
Luo, Chongliang; Liu, Jin; Dey, Dipak K; Chen, Kun
2016-07-01
In many fields, multi-view datasets, measuring multiple distinct but interrelated sets of characteristics on the same set of subjects, together with data on certain outcomes or phenotypes, are routinely collected. The objective in such a problem is often two-fold: both to explore the association structures of multiple sets of measurements and to develop a parsimonious model for predicting the future outcomes. We study a unified canonical variate regression framework to tackle the two problems simultaneously. The proposed criterion integrates multiple canonical correlation analysis with predictive modeling, balancing between the association strength of the canonical variates and their joint predictive power on the outcomes. Moreover, the proposed criterion seeks multiple sets of canonical variates simultaneously to enable the examination of their joint effects on the outcomes, and is able to handle multivariate and non-Gaussian outcomes. An efficient algorithm based on variable splitting and Lagrangian multipliers is proposed. Simulation studies show the superior performance of the proposed approach. We demonstrate the effectiveness of the proposed approach in an [Formula: see text] intercross mice study and an alcohol dependence study. PMID:26861909
Burke-Gaffney, A.; Hellewell, P. G.
1996-01-01
1. Tumour necrosis factor-alpha (TNF alpha) increases the expression of the adhesion molecule intercellular adhesion molecule-1 (ICAM-1) on cultured endothelial and epithelial cells and modulation of this may be important in controlling inflammation. Activation of tyrosine kinase(s) is known to be involved in the signal transduction pathways of many cytokines. In this study we have investigated the effects of the tyrosine kinase inhibitors, ST638, tyrphostin AG 1288 and genistein, on TNF alpha-induced ICAM-1 expression in human alveolar epithelial (A549) and vascular endothelial (EAhy926) cell lines and also normal human lung microvascular endothelial cells (HLMVEC). 2. ICAM-1 expression on cultured cells was determined by a sensitive enzyme-linked immunosorbant assay (ELISA). Endothelial or epithelial monolayers were exposed to increasing doses of TNF-alpha (0.01-10 ng ml-1), in the presence or absence of either ST638 (3-100 microM), AG 1288 (3-100 microM) or genistein (100 microM) and ICAM-1 expression was measured at 4 and 24 h. Control experiments examined the effect of ST638 on phorbol 12-myristate 13-acetate (PMA, 20 ng ml-1, 4 h)-stimulated ICAM-1 and compared it to that of a specific protein kinase C inhibitor, R031-8220 (10 microM). Also, functional consequences of changes in ICAM-1 expression were assessed by measuring adhesion of 111 In-labelled human neutrophils to EAhy926 endothelial and A549 epithelial monolayers treated with TNF alpha, in the presence or absence of ST638. 3. ST638 caused a concentration-dependent reduction in TNF alpha- (0.1-10 ng ml-1)-induced ICAM-1 on EAhy926 endothelial (at 4 h) and A549 epithelial monolayers (at 4 and 24 h). In contrast, ST638 caused a concentration-dependent increase in TNF alpha- (0.1-10 ng ml-1)-induced ICAM-1 on EAhy926 endothelial cells at 24 h. Similar effects were seen with AG 1288 or genistein. ST638 (100 microM) significantly (P < 0.01) inhibited ICAM-1 expression on HLMVEC endothelial cells induced by
Linear regression in astronomy. I
NASA Technical Reports Server (NTRS)
Isobe, Takashi; Feigelson, Eric D.; Akritas, Michael G.; Babu, Gutti Jogesh
1990-01-01
Five methods for obtaining linear regression fits to bivariate data with unknown or insignificant measurement errors are discussed: ordinary least-squares (OLS) regression of Y on X, OLS regression of X on Y, the bisector of the two OLS lines, orthogonal regression, and 'reduced major-axis' regression. These methods have been used by various researchers in observational astronomy, most importantly in cosmic distance scale applications. Formulas for calculating the slope and intercept coefficients and their uncertainties are given for all the methods, including a new general form of the OLS variance estimates. The accuracy of the formulas was confirmed using numerical simulations. The applicability of the procedures is discussed with respect to their mathematical properties, the nature of the astronomical data under consideration, and the scientific purpose of the regression. It is found that, for problems needing symmetrical treatment of the variables, the OLS bisector performs significantly better than orthogonal or reduced major-axis regression.
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
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
Bagnell, C A; Baker, N K; McMurtry, J P; Brocht, D M; Lewis, G S
1990-06-01
The effect of an in vivo prostaglandin F2 alpha (PGF2 alpha) challenge in pregnant and cyclic sows was compared to determine whether PGF2 alpha-induced release of relaxin (RLX) from the corpus luteum (CL) in late pregnancy is also effective during the cycle. Ovarian venous RLX and progesterone were monitored by radioimmunoassay and RLX localized in the CL by immunohistochemistry. In Day 108 pregnant sows, infusion of PGF2 alpha (100 micrograms) into the ovarian artery resulted in an immediate and sustained rise in ovarian venous RLX with an initial decline in progesterone levels by 30 min which then returned to pretreatment levels. In Day 13 or 15 cyclic sows with functional corpora lutea (i.e., elevated progesterone), RLX was undetectable in ovarian venous blood after 100 micrograms of PGF2 alpha. Administration of PGF2 alpha via either the jugular vein or intramuscular route was also ineffective in releasing RLX from the CL of the cycle. The intensity of RLX immunostaining of the CL was similar in saline and PGF2 alpha-treated sows. These studies indicate that the control of RLX release from the sow CL differs in the estrous cycle and pregnancy. PMID:2349248
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
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.
Linear regression in astronomy. II
NASA Technical Reports Server (NTRS)
Feigelson, Eric D.; Babu, Gutti J.
1992-01-01
A wide variety of least-squares linear regression procedures used in observational astronomy, particularly investigations of the cosmic distance scale, are presented and discussed. The classes of linear models considered are (1) unweighted regression lines, with bootstrap and jackknife resampling; (2) regression solutions when measurement error, in one or both variables, dominates the scatter; (3) methods to apply a calibration line to new data; (4) truncated regression models, which apply to flux-limited data sets; and (5) censored regression models, which apply when nondetections are present. For the calibration problem we develop two new procedures: a formula for the intercept offset between two parallel data sets, which propagates slope errors from one regression to the other; and a generalization of the Working-Hotelling confidence bands to nonstandard least-squares lines. They can provide improved error analysis for Faber-Jackson, Tully-Fisher, and similar cosmic distance scale relations.
Quantile regression for climate data
NASA Astrophysics Data System (ADS)
Marasinghe, Dilhani Shalika
Quantile regression is a developing statistical tool which is used to explain the relationship between response and predictor variables. This thesis describes two examples of climatology using quantile regression.Our main goal is to estimate derivatives of a conditional mean and/or conditional quantile function. We introduce a method to handle autocorrelation in the framework of quantile regression and used it with the temperature data. Also we explain some properties of the tornado data which is non-normally distributed. Even though quantile regression provides a more comprehensive view, when talking about residuals with the normality and the constant variance assumption, we would prefer least square regression for our temperature analysis. When dealing with the non-normality and non constant variance assumption, quantile regression is a better candidate for the estimation of the derivative.
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…
Retro-regression--another important multivariate regression improvement.
Randić, M
2001-01-01
We review the serious problem associated with instabilities of the coefficients of regression equations, referred to as the MRA (multivariate regression analysis) "nightmare of the first kind". This is manifested when in a stepwise regression a descriptor is included or excluded from a regression. The consequence is an unpredictable change of the coefficients of the descriptors that remain in the regression equation. We follow with consideration of an even more serious problem, referred to as the MRA "nightmare of the second kind", arising when optimal descriptors are selected from a large pool of descriptors. This process typically causes at different steps of the stepwise regression a replacement of several previously used descriptors by new ones. We describe a procedure that resolves these difficulties. The approach is illustrated on boiling points of nonanes which are considered (1) by using an ordered connectivity basis; (2) by using an ordering resulting from application of greedy algorithm; and (3) by using an ordering derived from an exhaustive search for optimal descriptors. A novel variant of multiple regression analysis, called retro-regression (RR), is outlined showing how it resolves the ambiguities associated with both "nightmares" of the first and the second kind of MRA. PMID:11410035
Luo, F; Jia, R; Ying, S; Wang, Z; Wang, F
2016-06-01
Nutrition is an important factor that regulates reproductive performance of sheep and affects follicle development. However, the correlation between nutrition and follicle development is poorly understood at the molecular level. To study its possible molecular mechanisms, we performed expression profiling of granulosa cells isolated from sheep that were fed different levels of nutrition levels during the luteal phase. To do this, ewes received a maintenance diet (M), and their estrus was synchronized by intravaginal progestogen sponges for 12 days. Ewes were randomly divided into the short-term dietary-restricted group (R; 0.5 × M) and the nutrient-supplemented group (S; 1.5 × M). RNA samples were extracted from granulosa cells. Transcriptome libraries from each group were constructed by Illumina sequencing. Among 18 468 detected genes, 170 genes were significantly differentially expressed, of which 140 genes were upregulated and 30 genes were downregulated in group S relative to group R. These genes could be candidates regulating follicular development in sheep. Gene Ontology, KEGG and clustering analyses were performed. Genes related to oocyte meiosis, such as ADCY7, were upregulated. We identified two important groups of related genes that were upregulated with improved nutrition: one group comprising the genes PTGS2, UCP2 and steroidogenic acute regulatory protein and the other group comprising interleukin-1A and interleukin-1B. The genes within each group showed similar expression patterns. Additionally, all five genes are involved in the reproduction process. Quantitative real-time PCR was performed to validate the results of expression profiling. These data in our study are an abundant genomic resource to expand the understanding of the molecular and cellular events underlying follicle development. PMID:26970339
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
Friedler, S; Raziel, A; Schachter, M; Strassburger, D; Bukovsky, I; Ron-El, R
1999-08-01
This study aimed to compare the efficacy of micronized progesterone administered as luteal support following ovulation induction for in-vitro fertilization (IVF)- embryo transfer in cycles using gonadotrophin-releasing hormone agonist, either orally (200 mgx4/day) or vaginally (100 mgx2/day) and to characterize the luteal phase hormonal profile during such treatments. A total of 64 high responder patients requiring intracytoplasmic sperm injection due to male factor infertility were prospectively randomized into two treatment groups. Patients treated orally or vaginally were comparable in age (31.9 +/- 6.1 versus 30.6 +/- 5.2; mean +/- SD), number of oocytes retrieved (17 +/- 8.2 versus 18 +/- 7.0), and number of embryos transferred (3.1 +/- 1.2 versus 2.7 +/- 0.9) per cycle. Following low dose vaginal treatment, a significantly higher implantation rate (30.7 versus 10.7%, P < 0.01), but similar clinical pregnancy rate (47.0 versus 33.3%) and ongoing pregnancy rate (41.1 versus 20.0%) was observed, compared with oral treatment. In conception cycles, luteal serum progesterone and oestrogen concentrations did not differ between the treatment groups. In non-conception cycles, late luteal progesterone concentrations were significantly lower following vaginal treatment. As low dose micronized progesterone administered vaginally is simple, easy and well tolerated, it could be recommended as the method of choice for luteal support, especially for high responder patients at risk for ovarian hyperstimulation syndrome. PMID:10438404
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…
Ecological Regression and Voting Rights.
ERIC Educational Resources Information Center
Freedman, David A.; And Others
1991-01-01
The use of ecological regression in voting rights cases is discussed in the context of a lawsuit against Los Angeles County (California) in 1990. Ecological regression assumes that systematic voting differences between precincts are explained by ethnic differences. An alternative neighborhood model is shown to lead to different conclusions. (SLD)
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…
Sekar, Natesampillai; Veldhuis, Johannes D
2004-07-01
Luteinizing hormone (LH) and insulin stimulate transcriptional activity of the porcine low-density lipoprotein (LDL) receptor (LDLR) promoter supra-additively in primary cultures of granulosa-luteal cells. The mechanistic basis of this bihormonal interaction is unknown. The pig LDLR gene promoter includes three putative Sp1/Sp3-binding sites and one sterol response element (SRE) site 5' upstream to the transcriptional start site. To assess the role of SRE-binding protein (SREBP) in LDLR gene regulation, swine granulosa-luteal cells were cotransfected with CMV/SREBP-1a or SREBP-2 and the pLDLR1076/luc promoter. SREBP-1a and SREBP-2 stimulated LDLR gene transcription eight- and fourfold, respectively. LH alone augmented stimulation by SREBP-1 twofold. Conversely, cotransfection of a dominant-negative mutant form of SREBP-1a repressed basal and hormonally stimulated LDLR promoter activity by >80% (P < 0.01). Mutation of the SRE -167 ATCACCCCATG -157 to -167 ATCACCgCATG -157 bp decreased basal expression by 50% and LH + insulin- and LH + IGF-I-stimulated transcriptional activity by 80% and >90%, respectively (both P < 0.01). Mutations within each of the three flanking putative Sp1/Sp3 sites at -216/-211, -201/-196, and -151/-146 bp in the LDLR gene promoter also reduced basal activity (by >85%) and hormonal responsiveness (>95%, P < 0.05). EMSA confirmed that presumptive SRE-1 and Sp1/Sp3 elements bind respective peptides. Mithramycin, an inhibitor of Sp1/Sp3 protein(s) binding, blocked hormonally induced LDLR promoter expression by 80%. Basal transcription and supra-additive stimulation of porcine LDLR gene transcription by LH and insulin in granulosa-luteal cells require SREBP-1a and Sp1/Sp3-binding elements. PMID:14998783
2012-01-01
Background Luteal support with progesterone is necessary for successful implantation of the embryo following egg collection and embryo transfer in an in-vitro fertilization (IVF) cycle. Progesterone has been used for as little as 2 weeks and for as long as 12 weeks of gestation. The optimal length of treatment is unresolved at present and it remains unclear how long to treat women receiving luteal supplementation. Design The trial is a prospective, randomized, double-blind, placebo-controlled trial to investigate the effect of the duration of luteal support with progesterone in IVF cycles. Following 2 weeks standard treatment and a positive biochemical pregnancy test, this randomized control trial will allocate women to a supplementary 8 weeks treatment with vaginal progesterone or 8 weeks placebo. Further studies would be required to investigate whether additional supplementation with progesterone is beneficial in early pregnancy. Discussion Currently at the Hewitt Centre, approximately 32.5% of women have a positive biochemical pregnancy test 2 weeks after embryo transfer. It is this population that is eligible for trial entry and randomization. Once the patient has confirmed a positive urinary pregnancy test they will be invited to join the trial. Once the consent form has been completed by the patient a trial prescription sheet will be sent to pharmacy with a stated collection time. The patient can then be randomized and the drugs dispensed according to pharmacy protocol. A blood sample will then be drawn for measurement of baseline hormone levels (progesterone, estradiol, free beta-human chorionic gonadotrophin, pregnancy-associated plasma protein-A, Activin A, Inhibin A and Inhibin B). The primary outcome measure is the proportion of all randomized women that continue successfully to a viable pregnancy (at least one fetus with fetal heart rate >100 beats/minute) on transabdominal/transvaginal ultrasound at 10 weeks post embryo transfer/12 weeks gestation
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
Davar, Robab; Farid Mojtahedi, Maryam; Miraj, Sepideh
2015-01-01
Background: There is no doubt that luteal phase support is essential to enhance the reproductive outcome in IVF cycles. In addition to progesterone and human chorionic gonadotropin, several studies have described GnRH agonists as luteal phase support to improve implantation rate, pregnancy rate and live birth rate, whereas other studies showed dissimilar conclusions. All of these studies have been done in fresh IVF cycles. Objective: To determine whether an additional GnRH agonist administered at the time of implantation for luteal phase support in frozen-thawed embryo transfer (FET) improves the embryo developmental potential. Materials and Methods: This is a prospective controlled trial study in 200 FET cycles, patients were randomized on the day of embryo transfer into group 1 (n=100) to whom a single dose of GnRH agonist (0.1 mg triptorelin) was administered three days after transfer and group 2 (n=100), who did not receive agonist. Both groups received daily vaginal progesterone suppositories plus estradiol valerate 6 mg daily. Primary outcome measure was clinical pregnancy rate. Secondary outcome measures were implantation rate, chemical, ongoing pregnancy rate and abortion rate. Results: A total of 200 FET cycles were analyzed. Demographic data and embryo quality were comparable between two groups. No statistically significant difference in clinical and ongoing pregnancy rates was observed between the two groups (26% versus 21%, p=0.40 and 21% versus 17%, p=0.37, respectively). Conclusion: Administration of a subcutaneous GnRH agonist at the time of implantation does not increase clinical or ongoing pregnancy. PMID:26568750
Fungible weights in logistic regression.
Jones, Jeff A; Waller, Niels G
2016-06-01
In this article we develop methods for assessing parameter sensitivity in logistic regression models. To set the stage for this work, we first review Waller's (2008) equations for computing fungible weights in linear regression. Next, we describe 2 methods for computing fungible weights in logistic regression. To demonstrate the utility of these methods, we compute fungible logistic regression weights using data from the Centers for Disease Control and Prevention's (2010) Youth Risk Behavior Surveillance Survey, and we illustrate how these alternate weights can be used to evaluate parameter sensitivity. To make our work accessible to the research community, we provide R code (R Core Team, 2015) that will generate both kinds of fungible logistic regression weights. (PsycINFO Database Record PMID:26651981
[Regression grading in gastrointestinal tumors].
Tischoff, I; Tannapfel, A
2012-02-01
Preoperative neoadjuvant chemoradiation therapy is a well-established and essential part of the interdisciplinary treatment of gastrointestinal tumors. Neoadjuvant treatment leads to regressive changes in tumors. To evaluate the histological tumor response different scoring systems describing regressive changes are used and known as tumor regression grading. Tumor regression grading is usually based on the presence of residual vital tumor cells in proportion to the total tumor size. Currently, no nationally or internationally accepted grading systems exist. In general, common guidelines should be used in the pathohistological diagnostics of tumors after neoadjuvant therapy. In particularly, the standard tumor grading will be replaced by tumor regression grading. Furthermore, tumors after neoadjuvant treatment are marked with the prefix "y" in the TNM classification. PMID:22293790
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.
Pandey, A K; Ghuman, Sps; Dhaliwal, G S; Agarwal, S K; Phogat, J B
2016-08-01
This study was designed to investigate the impact of buserelin acetate (BA) or human chorionic gonadotropin (hCG) administration on the day of first artificial insemination (AI) on subsequent luteal profile (diameter of corpus luteum (CL) and plasma progesterone) and conception rate in Murrah buffalo. The present experiment was carried out at two locations in 117 buffalo that were oestrus-synchronized using cloprostenol (500 μg) administered (i.m.) 11 days apart followed by AI during standing oestrus. Based on treatment (i.m.) at the time of AI, buffalo were randomly categorized (n = 39 in each group) into control (isotonic saline solution, 5 ml), dAI-BA (buserelin acetate, 20 μg) and dAI-hCG (hCG, 3000 IU) group. Out of these, 14 buffalo of each group were subjected to ovarian ultrasonography on the day of oestrus to monitor the preovulatory follicle and on days 5, 12, 16 and 21 post-ovulation to monitor CL diameter. On the day of each sonography, jugular vein blood samples were collected for the estimation of progesterone concentrations. All the buffalo (n = 117) were confirmed for pregnancy on day 40 post-ovulation. The conception rate was better (p < 0.05) in dAI-BA (51.3%) and dAI-hCG (66.7%) groups as compared to their control counterparts (30.8%). Furthermore, the buffalo of dAI-hCG group had improved (p < 0.05) luteal profile, whereas the buffalo of dAI-BA group failed (p > 0.05) to exhibit stimulatory impact of treatment on luteal profile when compared to control group. In brief, buserelin acetate or hCG treatment on the day of first AI leads to an increase in conception rate; however, an appreciable impact on post-ovulation luteal profile was observed only in hCG-treated Murrah buffalo. PMID:27170495
Seto, Nickie L.; Bogan, Randy L.
2015-01-01
In nonprimate species, it has been well established that prostaglandin F2 alpha (PGF2alpha) initiates luteolysis. Changes in intracellular cholesterol concentrations caused by modulation of cholesterol uptake and efflux may mediate PGF2alpha-induced luteolysis. These changes in cholesterol efflux and uptake are controlled, in part, by the liver x receptors (LXR) alpha (NR1H3) and beta (NR1H2), nuclear receptors that increase expression of genes necessary for cholesterol efflux or limiting cholesterol uptake. Therefore, we hypothesized that PGF2alpha reduces expression of cholesterol uptake and increases expression of cholesterol efflux genes, mediated in part by enhanced LXR activity. To test this hypothesis, an induced luteolysis model was used whereby ewes were treated during their midluteal phase with saline or PGF2alpha and corpora lutea (CL) collected 12, 24, or 48 h later for determination of mRNA and protein concentrations by quantitative real-time PCR and Western blot analysis, respectively. As a complementary approach, CL undergoing spontaneous luteolysis were compared to midluteal phase CL. The lipoprotein receptors responsible for cholesterol uptake were significantly decreased in both luteolysis models. Expression of the LXR target gene ATP binding cassette subfamily A1 (ABCA1), an important mediator of cholesterol efflux, was significantly increased in both experimental models. Chromatin immunoprecipitation confirmed that PGF2alpha treatment resulted in enhanced NR1H3 and NR1H2 binding to the ABCA1 promoter. Qualitative changes in lipid droplet distribution were also observed following PGF2alpha treatment. These data support the hypothesis that reduced cholesterol uptake and increased efflux mediate luteolysis in sheep, which is partially controlled by PGF2alpha stimulation of LXR activity. PMID:25882703
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).
Splines for Diffeomorphic Image Regression
Singh, Nikhil; Niethammer, Marc
2016-01-01
This paper develops a method for splines on diffeomorphisms for image regression. In contrast to previously proposed methods to capture image changes over time, such as geodesic regression, the method can capture more complex spatio-temporal deformations. In particular, it is a first step towards capturing periodic motions for example of the heart or the lung. Starting from a variational formulation of splines the proposed approach allows for the use of temporal control points to control spline behavior. This necessitates the development of a shooting formulation for splines. Experimental results are shown for synthetic and real data. The performance of the method is compared to geodesic regression. PMID:25485370
Abstract Expression Grammar Symbolic Regression
NASA Astrophysics Data System (ADS)
Korns, Michael F.
This chapter examines the use of Abstract Expression Grammars to perform the entire Symbolic Regression process without the use of Genetic Programming per se. The techniques explored produce a symbolic regression engine which has absolutely no bloat, which allows total user control of the search space and output formulas, which is faster, and more accurate than the engines produced in our previous papers using Genetic Programming. The genome is an all vector structure with four chromosomes plus additional epigenetic and constraint vectors, allowing total user control of the search space and the final output formulas. A combination of specialized compiler techniques, genetic algorithms, particle swarm, aged layered populations, plus discrete and continuous differential evolution are used to produce an improved symbolic regression sytem. Nine base test cases, from the literature, are used to test the improvement in speed and accuracy. The improved results indicate that these techniques move us a big step closer toward future industrial strength symbolic regression systems.
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.
Time-Warped Geodesic Regression
Hong, Yi; Singh, Nikhil; Kwitt, Roland; Niethammer, Marc
2016-01-01
We consider geodesic regression with parametric time-warps. This allows, for example, to capture saturation effects as typically observed during brain development or degeneration. While highly-flexible models to analyze time-varying image and shape data based on generalizations of splines and polynomials have been proposed recently, they come at the cost of substantially more complex inference. Our focus in this paper is therefore to keep the model and its inference as simple as possible while allowing to capture expected biological variation. We demonstrate that by augmenting geodesic regression with parametric time-warp functions, we can achieve comparable flexibility to more complex models while retaining model simplicity. In addition, the time-warp parameters provide useful information of underlying anatomical changes as demonstrated for the analysis of corpora callosa and rat calvariae. We exemplify our strategy for shape regression on the Grassmann manifold, but note that the method is generally applicable for time-warped geodesic regression. PMID:25485368
Basis Selection for Wavelet Regression
NASA Technical Reports Server (NTRS)
Wheeler, Kevin R.; Lau, Sonie (Technical Monitor)
1998-01-01
A wavelet basis selection procedure is presented for wavelet regression. Both the basis and the threshold are selected using cross-validation. The method includes the capability of incorporating prior knowledge on the smoothness (or shape of the basis functions) into the basis selection procedure. The results of the method are demonstrated on sampled functions widely used in the wavelet regression literature. The results of the method are contrasted with other published methods.
Regression methods for spatial data
NASA Technical Reports Server (NTRS)
Yakowitz, S. J.; Szidarovszky, F.
1982-01-01
The kriging approach, a parametric regression method used by hydrologists and mining engineers, among others also provides an error estimate the integral of the regression function. The kriging method is explored and some of its statistical characteristics are described. The Watson method and theory are extended so that the kriging features are displayed. Theoretical and computational comparisons of the kriging and Watson approaches are offered.
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.
Ismail Madkour, Wael A; Noah, Bassel; Abdel Hamid, Amr M S; Zaheer, Hena; Al-Bahr, Awatif; Shaeer, Mahmoud; Moawad, Ashraf
2016-06-01
In vitro fertilization (IVF) cycles are associated with a defective luteal phase. Although progesterone supplementation to treat this problem is standard practice, estrogen addition is debatable. Our aim was to compare pregnancy outcomes in 220 patients undergoing antagonist intracytoplasmic sperm injection (ICSI) cycles protocol. The patients were randomly assigned into two equal groups to receive either vaginal progesterone alone (90 mg once daily) starting on the day of oocyte retrieval for up to 12 weeks if pregnancy occurred or estradiol addition (2 mg twice daily) starting on the same day and continuing up to seven weeks (foetal viability scan). Primary outcomes were pregnancy and ongoing pregnancy rates per embryo transfer. Secondary outcomes were implantation and early pregnancy loss rates. Pregnancy rates showed no significant difference between group 1 (39.09%) and 2 (43.63%) (p value = 0.3). Similarly, both groups were comparable regarding ongoing pregnancy rate (32.7% group 1 and 36.3% group 2, p value = 0.1). Implantation rates showed no difference between group 1 (19.25%) and group 2 (23.44%) (p value = 0.2). Early pregnancy loss rates were comparable, with 6.3% and 7.2% in groups 1 and 2, respectively, (p value = 0.4). In conclusion, the addition of 4 mg estrogen daily to progesterone for luteal support in antagonist ICSI cycles is not beneficial for pregnancy outcome. PMID:27434094
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. PMID:25244592
Interpretation of Standardized Regression Coefficients in Multiple Regression.
ERIC Educational Resources Information Center
Thayer, Jerome D.
The extent to which standardized regression coefficients (beta values) can be used to determine the importance of a variable in an equation was explored. The beta value and the part correlation coefficient--also called the semi-partial correlation coefficient and reported in squared form as the incremental "r squared"--were compared for variables…
Demosaicing Based on Directional Difference Regression and Efficient Regression Priors.
Wu, Jiqing; Timofte, Radu; Van Gool, Luc
2016-08-01
Color demosaicing is a key image processing step aiming to reconstruct the missing pixels from a recorded raw image. On the one hand, numerous interpolation methods focusing on spatial-spectral correlations have been proved very efficient, whereas they yield a poor image quality and strong visible artifacts. On the other hand, optimization strategies, such as learned simultaneous sparse coding and sparsity and adaptive principal component analysis-based algorithms, were shown to greatly improve image quality compared with that delivered by interpolation methods, but unfortunately are computationally heavy. In this paper, we propose efficient regression priors as a novel, fast post-processing algorithm that learns the regression priors offline from training data. We also propose an independent efficient demosaicing algorithm based on directional difference regression, and introduce its enhanced version based on fused regression. We achieve an image quality comparable to that of the state-of-the-art methods for three benchmarks, while being order(s) of magnitude faster. PMID:27254866
Interquantile Shrinkage in Regression Models
Jiang, Liewen; Wang, Huixia Judy; Bondell, Howard D.
2012-01-01
Conventional analysis using quantile regression typically focuses on fitting the regression model at different quantiles separately. However, in situations where the quantile coefficients share some common feature, joint modeling of multiple quantiles to accommodate the commonality often leads to more efficient estimation. One example of common features is that a predictor may have a constant effect over one region of quantile levels but varying effects in other regions. To automatically perform estimation and detection of the interquantile commonality, we develop two penalization methods. When the quantile slope coefficients indeed do not change across quantile levels, the proposed methods will shrink the slopes towards constant and thus improve the estimation efficiency. We establish the oracle properties of the two proposed penalization methods. Through numerical investigations, we demonstrate that the proposed methods lead to estimations with competitive or higher efficiency than the standard quantile regression estimation in finite samples. Supplemental materials for the article are available online. PMID:24363546
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.
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…
Regression modelling of Dst index
NASA Astrophysics Data System (ADS)
Parnowski, Aleksei
We developed a new approach to the problem of real-time space weather indices forecasting using readily available data from ACE and a number of ground stations. It is based on the regression modelling method [1-3], which combines the benefits of empirical and statistical approaches. Mathematically it is based upon the partial regression analysis and Monte Carlo simulations to deduce the empirical relationships in the system. The typical elapsed time per forecast is a few seconds on an average PC. This technique can be easily extended to other indices like AE and Kp. The proposed system can also be useful for investigating physical phenomena related to interactions between the solar wind and the magnetosphere -it already helped uncovering two new geoeffective parameters. 1. Parnowski A.S. Regression modeling method of space weather prediction // Astrophysics Space Science. — 2009. — V. 323, 2. — P. 169-180. doi:10.1007/s10509-009-0060-4 [arXiv:0906.3271] 2. Parnovskiy A.S. Regression Modeling and its Application to the Problem of Prediction of Space Weather // Journal of Automation and Information Sciences. — 2009. — V. 41, 5. — P. 61-69. doi:10.1615/JAutomatInfScien.v41.i5.70 3. Parnowski A.S. Statistically predicting Dst without satellite data // Earth, Planets and Space. — 2009. — V. 61, 5. — P. 621-624.
Fungible Weights in Multiple Regression
ERIC Educational Resources Information Center
Waller, Niels G.
2008-01-01
Every set of alternate weights (i.e., nonleast squares weights) in a multiple regression analysis with three or more predictors is associated with an infinite class of weights. All members of a given class can be deemed "fungible" because they yield identical "SSE" (sum of squared errors) and R[superscript 2] values. Equations for generating…
Spontaneous regression of breast cancer.
Lewison, E F
1976-11-01
The dramatic but rare regression of a verified case of breast cancer in the absence of adequate, accepted, or conventional treatment has been observed and documented by clinicians over the course of many years. In my practice limited to diseases of the breast, over the past 25 years I have observed 12 patients with a unique and unusual clinical course valid enough to be regarded as spontaneous regression of breast cancer. These 12 patients, with clinically confirmed breast cancer, had temporary arrest or partial remission of their disease in the absence of complete or adequate treatment. In most of these cases, spontaneous regression could not be equated ultimately with permanent cure. Three of these case histories are summarized, and patient characteristics of pertinent clinical interest in the remaining case histories are presented and discussed. Despite widespread doubt and skepticism, there is ample clinical evidence to confirm the fact that spontaneous regression of breast cancer is a rare phenomenon but is real and does occur. PMID:799758
Regression Models of Atlas Appearance
Rohlfing, Torsten; Sullivan, Edith V.; Pfefferbaum, Adolf
2010-01-01
Models of object appearance based on principal components analysis provide powerful and versatile tools in computer vision and medical image analysis. A major shortcoming is that they rely entirely on the training data to extract principal modes of appearance variation and ignore underlying variables (e.g., subject age, gender). This paper introduces an appearance modeling framework based instead on generalized multi-linear regression. The training of regression appearance models is controlled by independent variables. This makes it straightforward to create model instances for specific values of these variables, which is akin to model interpolation. We demonstrate the new framework by creating an appearance model of the human brain from MR images of 36 subjects. Instances of the model created for different ages are compared with average shape atlases created from age-matched sub-populations. Relative tissue volumes vs. age in models are also compared with tissue volumes vs. subject age in the original images. In both experiments, we found excellent agreement between the regression models and the comparison data. We conclude that regression appearance models are a promising new technique for image analysis, with one potential application being the representation of a continuum of mutually consistent, age-specific atlases of the human brain. PMID:19694260
Correlation Weights in Multiple Regression
ERIC Educational Resources Information Center
Waller, Niels G.; Jones, Jeff A.
2010-01-01
A general theory on the use of correlation weights in linear prediction has yet to be proposed. In this paper we take initial steps in developing such a theory by describing the conditions under which correlation weights perform well in population regression models. Using OLS weights as a comparison, we define cases in which the two weighting…
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…
Regression models of atlas appearance.
Rohlfing, Torsten; Sullivan, Edith V; Pfefferbaum, Adolf
2009-01-01
Models of object appearance based on principal components analysis provide powerful and versatile tools in computer vision and medical image analysis. A major shortcoming is that they rely entirely on the training data to extract principal modes of appearance variation and ignore underlying variables (e.g., subject age, gender). This paper introduces an appearance modeling framework based instead on generalized multi-linear regression. The training of regression appearance models is controlled by independent variables. This makes it straightforward to create model instances for specific values of these variables, which is akin to model interpolation. We demonstrate the new framework by creating an appearance model of the human brain from MR images of 36 subjects. Instances of the model created for different ages are compared with average shape atlases created from age-matched sub-populations. Relative tissue volumes vs. age in models are also compared with tissue volumes vs. subject age in the original images. In both experiments, we found excellent agreement between the regression models and the comparison data. We conclude that regression appearance models are a promising new technique for image analysis, with one potential application being the representation of a continuum of mutually consistent, age-specific atlases of the human brain. PMID:19694260
Ridge Regression for Interactive Models.
ERIC Educational Resources Information Center
Tate, Richard L.
1988-01-01
An exploratory study of the value of ridge regression for interactive models is reported. Assuming that the linear terms in a simple interactive model are centered to eliminate non-essential multicollinearity, a variety of common models, representing both ordinal and disordinal interactions, are shown to have "orientations" that are favorable to…
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
Okumu, L A; Fair, T; Szekeres-Bartho, J; O'Doherty, A M; Crowe, M A; Roche, J F; Lonergan, P; Forde, N
2011-07-27
Progesterone-induced blocking factor (PIBF) and galectins modulate the maternal immune response during pregnancy. We hypothesized that the relative transcript abundance of the above genes would be different during the luteal phase/early pregnancy and would be affected by progesterone supplementation. To further test this, hypothesis protein expression analyses were carried out to evaluate the abundance and localization of LGALS9 and PIBF. Following estrus synchronization, heifers were inseminated (n = 140) or not (n = 70). Half the heifers in each status (cyclic or potentially pregnant) were randomly assigned to receive a progesterone-releasing intravaginal device (PRID) on day 3 after estrus, which elevated progesterone concentrations from day 3.5 to 8 (P < 0.05), resulting in four treatment groups: cyclic and pregnant heifers, each with normal and high progesterone. After confirmation of pregnancy status in inseminated animals, uterine tissue was collected on days 5, 7, 13, or 16 of the luteal phase of the cycle/pregnancy. Gene and protein expression was determined using Q-RT-PCR and IHC, respectively, on 5 heifers per treatment per time point (i.e., 80 in total). Progesterone concentrations did not affect expression of any of the genes (P > 0.05). LGALS9 and LGALS3BP were expressed at low levels in both cyclic and pregnant endometria until day 13. On day 16, expression increased only in the pregnant heifers (P < 0.0001). LGALS1 and LGALS3 decreased on day 7 (P < 0.0001) and remained low until day 16. Pregnancy had no effect on the expression of LGALS1, LGALS3, and PIBF. Additionally, LGALS9 and PIBF proteins were expressed in distinct uterine cell types. These results indicate that the galectins may be involved in uterine receptivity and/or implantation in heifers. PMID:21610087
SANO, Masahiro; HASHIBA, Kazuhisa; NIO-KOBAYASHI, Junko; OKUDA, Kiyoshi
2015-01-01
The corpus luteum (CL) is a temporary endocrine gland producing a large amount of progesterone, which is essential for the establishment and maintenance of pregnancy. Galectin-1 is a β-galactose-binding protein that can modify functions of membrane glycoproteins and is expressed in the CL of mice and women. However, the physiological role of galectin-1 in the CL is unclear. In the present study, we investigated the expression and localization of galectin-1 in the bovine CL and the effect of galectin-1 on cultured luteal steroidogenic cells (LSCs) with special reference to its binding to the glycans on vascular endothelial growth factor receptor-2 (VEGFR-2). Galectin-1 protein was highly expressed at the mid and late luteal stages in the membrane fraction of bovine CL tissue and was localized to the surface of LSCs in a carbohydrate-dependent manner. Galectin-1 increased the viability in cultured LSCs. However, the viability of LSCs was decreased by addition of β-lactose, a competitive carbohydrate inhibitor of galectin-1 binding activity. VEGFR-2 protein, like galectin-1, is also highly expressed in the mid CL, and it was modified by multi-antennary glycans, which can be recognized by galectin-1. An overlay assay using biotinylated galectin-1 revealed that galectin-1 directly binds to asparagine-linked glycans (N-glycans) on VEGFR-2. Enhancement of LSC viability by galectin-1 was suppressed by a selective inhibitor of VEGFR-2. The overall findings suggest that galectin-1 plays a role as a survival factor in the bovine CL, possibly by binding to N-glycans on VEGFR-2. PMID:26155753
Claman, P; Domingo, M; Leader, A
1992-04-01
This study was conducted to compare the endocrine milieu and pregnancy rates in an in-vitro fertilization and embryo transfer (IVF-ET) programme employing a gonadotrophin-releasing hormone agonist (GnRHa) and human menopausal gonadotrophin (HMG) when either human chorionic gonadotrophin (HCG) or progesterone were used for luteal phase support. A total of 121 IVF-ET treatment cycles were prospectively studied. All patients started leuprolide acetate in the midluteal phase and it was continued for at least 10 days. When oestradiol levels were less than 150 pmol/l, HMG was started. When at least three follicles were greater than or equal to 17 mm in diameter, HCG 5000 IU i.m. was given. Oocytes were retrieved using transvaginal ultrasound and embryos were transferred 48 h later. The patients' cycles were prospectively randomized to receive HCG (72 cycles) or progesterone (49 cycles) luteal support. The HCG group received 1500 IU i.m. on days 3, 6 and 9 after the initial trigger. The progesterone group received 12.5 mg i.m. q.d. starting from the day after the HCG trigger. The dose of progesterone was increased to 25 mg i.m. q.d. starting on the day of embryo transfer and continued for 17-21 days. If the patient became pregnant, this dose of progesterone was continued until fetal heart activity was visualized by ultrasound. Mean ages, number of eggs retrieved, embryos transferred, oestradiol levels on the day of the HCG trigger, oestradiol and progesterone at the time of embryo transfer were the same in both groups.(ABSTRACT TRUNCATED AT 250 WORDS) PMID:1522190
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
Regression analysis of networked data
Zhou, Yan; Song, Peter X.-K.
2016-01-01
This paper concerns regression methodology for assessing relationships between multi-dimensional response variables and covariates that are correlated within a network. To address analytical challenges associated with the integration of network topology into the regression analysis, we propose a hybrid quadratic inference method that uses both prior and data-driven correlations among network nodes. A Godambe information-based tuning strategy is developed to allocate weights between the prior and data-driven network structures, so the estimator is efficient. The proposed method is conceptually simple and computationally fast, and has appealing large-sample properties. It is evaluated by simulation, and its application is illustrated using neuroimaging data from an association study of the effects of iron deficiency on auditory recognition memory in infants. PMID:27279658
Observational Studies: Matching or Regression?
Brazauskas, Ruta; Logan, Brent R
2016-03-01
In observational studies with an aim of assessing treatment effect or comparing groups of patients, several approaches could be used. Often, baseline characteristics of patients may be imbalanced between groups, and adjustments are needed to account for this. It can be accomplished either via appropriate regression modeling or, alternatively, by conducting a matched pairs study. The latter is often chosen because it makes groups appear to be comparable. In this article we considered these 2 options in terms of their ability to detect a treatment effect in time-to-event studies. Our investigation shows that a Cox regression model applied to the entire cohort is often a more powerful tool in detecting treatment effect as compared with a matched study. Real data from a hematopoietic cell transplantation study is used as an example. PMID:26712591
Heteroscedastic transformation cure regression models.
Chen, Chyong-Mei; Chen, Chen-Hsin
2016-06-30
Cure models have been applied to analyze clinical trials with cures and age-at-onset studies with nonsusceptibility. Lu and Ying (On semiparametric transformation cure model. Biometrika 2004; 91:331?-343. DOI: 10.1093/biomet/91.2.331) developed a general class of semiparametric transformation cure models, which assumes that the failure times of uncured subjects, after an unknown monotone transformation, follow a regression model with homoscedastic residuals. However, it cannot deal with frequently encountered heteroscedasticity, which may result from dispersed ranges of failure time span among uncured subjects' strata. To tackle the phenomenon, this article presents semiparametric heteroscedastic transformation cure models. The cure status and the failure time of an uncured subject are fitted by a logistic regression model and a heteroscedastic transformation model, respectively. Unlike the approach of Lu and Ying, we derive score equations from the full likelihood for estimating the regression parameters in the proposed model. The similar martingale difference function to their proposal is used to estimate the infinite-dimensional transformation function. Our proposed estimating approach is intuitively applicable and can be conveniently extended to other complicated models when the maximization of the likelihood may be too tedious to be implemented. We conduct simulation studies to validate large-sample properties of the proposed estimators and to compare with the approach of Lu and Ying via the relative efficiency. The estimating method and the two relevant goodness-of-fit graphical procedures are illustrated by using breast cancer data and melanoma data. Copyright © 2016 John Wiley & Sons, Ltd. PMID:26887342
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.
Colombo, M. P.; Lombardi, L.; Melani, C.; Parenza, M.; Baroni, C.; Ruco, L.; Stoppacciaro, A.
1996-01-01
C-26 colon adenocarcinoma cells transduced with the granulocyte colony-stimulating factor (G-CSF) gene form large tumors when injected into sublethally irradiated mice. These tumors regress when leukocyte function is reconstituted. Electron microscopy and immunocytochemical analysis of regressing C-26/G-CSF nodules indicates that tumor destruction is due mainly to hypoxia resulting from the functional loss of tumor vasculature and is only marginally due to direct cytolysis. Desegregation of basal lamina, cell swelling, and loss of junctions characterized the vessels within regressing tumors. Tumor cells were necrotic or filled with lipid vacuoles regardless of the distance from nearby vessels. Damage of tumor vasculature was dependent on the infiltrating leukocytes and the cytotoxic cytokines they produced. Locally produced interleukin-1 and tumor necrosis factor-alpha (TNF-alpha) induced vascular cellular adhesion molecule-1 (VCAM-1) and E-selectin on tumor vessels. Treatment with monoclonal antibodies to interferon-gamma (IFN-gamma) or TNF-alpha blocked tumor regression by inhibiting VCAM-1 and E-selectin expression on tumor-associated endothelial cells resulting in a reduced number of infiltrating leukocytes. Thus, C-26/G-CSF tumor regression presents features typical of hemorrhagic necrosis that occurs through the cytokines produced by infiltrating leukocytes in response to G-CSF. Images Figure 1 p477-a Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 PMID:8579110
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. PMID:24802528
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).
Gebremedhn, Samuel; Sahadevan, Sudeep; Hossain, MD Munir; Rings, Franca; Hoelker, Michael; Tholen, Ernst; Neuhoff, Christiane; Looft, Christian; Schellander, Karl; Tesfaye, Dawit
2014-01-01
This study aimed to investigate the miRNA expression patterns in granulosa cells of subordinate (SF) and dominant follicle (DF) during the early luteal phase of the bovine estrous cycle. For this, miRNA enriched total RNA isolated from granulosa cells of SF and DF obtained from heifers slaughtered at day 3 and day 7 of the estrous cycle was used for miRNAs deep sequencing. The results revealed that including 17 candidate novel miRNAs, several known miRNAs (n = 291–318) were detected in SF and DF at days 3 and 7 of the estrous cycle of which 244 miRNAs were common to all follicle groups. The let-7 families, bta-miR-10b, bta-miR-26a, bta-miR-99b and bta-miR-27b were among abundantly expressed miRNAs in both SF and DF at both days of the estrous cycle. Further analysis revealed that the expression patterns of 16 miRNAs including bta-miR-449a, bta-miR-449c and bta-miR-222 were differentially expressed between the granulosa cells of SF and DF at day 3 of the estrous cycle. However, at day 7 of the estrous cycle, 108 miRNAs including bta-miR-409a, bta-miR-383 and bta-miR-184 were differentially expressed between the two groups of granulosa cell revealing the presence of distinct miRNA expression profile changes between the two follicular stages at day 7 than day 3 of the estrous cycle. In addition, unlike the SF, marked temporal miRNA expression dynamics was observed in DF groups between day 3 and 7 of the estrous cycle. Target gene prediction and pathway analysis revealed that major signaling associated with follicular development including Wnt signaling, TGF-beta signaling, oocyte meiosis and GnRH signaling were affected by differentially expressed miRNAs. Thus, this study highlights the miRNA expression patterns of granulosa cells in subordinate and dominant follicles that could be associated with follicular recruitment, selection and dominance during the early luteal phase of the bovine estrous cycle. PMID:25192015
Residuals and regression diagnostics: focusing on logistic regression.
Zhang, Zhongheng
2016-05-01
Up to now I have introduced most steps in regression model building and validation. The last step is to check whether there are observations that have significant impact on model coefficient and specification. The article firstly describes plotting Pearson residual against predictors. Such plots are helpful in identifying non-linearity and provide hints on how to transform predictors. Next, I focus on observations of outlier, leverage and influence that may have significant impact on model building. Outlier is such an observation that its response value is unusual conditional on covariate pattern. Leverage is an observation with covariate pattern that is far away from the regressor space. Influence is the product of outlier and leverage. That is, when influential observation is dropped from the model, there will be a significant shift of the coefficient. Summary statistics for outlier, leverage and influence are studentized residuals, hat values and Cook's distance. They can be easily visualized with graphs and formally tested using the car package. PMID:27294091
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
Liao, B.-C.; Hsieh, C.-W.; Liu, Y.-C.; Tzeng, T.-T.; Sun, Y.-W.; Wung, B.-S.
2008-06-01
The production of adhesion molecules and subsequent attachment of leukocytes to endothelial cells (ECs) are critical early events in atherogenesis. These adhesion molecules thus play an important role in the development of this disease. Recent studies have highlighted the chemoprotective and anti-inflammatory effects of cinnamaldehyde, a Cinnamomum cassia Presl-specific diterpene. In our current study, we have examined the effects of both cinnamaldehyde and extracts of C. cassia on cytokine-induced monocyte/human endothelial cell interactions. We find that these compounds inhibit the adhesion of TNF{alpha}-induced monocytes to endothelial cells and suppress the expression of the cell adhesion molecules, VCAM-1 and ICAM-1, at the transcriptional level. Moreover, in TNF{alpha}-treated ECs, the principal downstream signal of VCAM-1 and ICAM-1, NF-{kappa}B, was also found to be abolished in a time-dependent manner. Interestingly, cinnamaldehyde exerts its anti-inflammatory effects by blocking the degradation of the inhibitory protein I{kappa}B-{alpha}, but only in short term pretreatments, whereas it does so via the induction of Nrf2-related genes, including heme-oxygenase-1 (HO-1), over long term pretreatments. Treating ECs with zinc protoporphyrin, a HO-1 inhibitor, partially blocks the anti-inflammatory effects of cinnamaldehyde. Elevated HO-1 protein levels were associated with the inhibition of TNF{alpha}-induced ICAM-1 expression. In addition to HO-1, we also found that cinnamaldehyde can upregulate Nrf2 in nuclear extracts, and can increase ARE-luciferase activity and upregulate thioredoxin reductase-1, another Nrf2-related gene. Moreover, cinnamaldehyde exposure rapidly reduces the cellular GSH levels in ECs over short term treatments but increases these levels after 9 h exposure. Hence, our present findings indicate that cinnamaldehyde suppresses TNF-induced singling pathways via two distinct mechanisms that are activated by different pretreatment periods.
Building Regression Models: The Importance of Graphics.
ERIC Educational Resources Information Center
Dunn, Richard
1989-01-01
Points out reasons for using graphical methods to teach simple and multiple regression analysis. Argues that a graphically oriented approach has considerable pedagogic advantages in the exposition of simple and multiple regression. Shows that graphical methods may play a central role in the process of building regression models. (Author/LS)
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…
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,…
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…
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.…
Pabuccu, E G; Pabuccu, R; Evliyaoglu Ozdegirmenci, O; Bostancı Durmus, A; Keskin, M
2016-05-01
Many reports led to the consensus on the use of progesterone (P) for luteal-phase support. Vaginal P application is the method of choice due to its simplicity and high patient convenience but is hampered by application difficulties and personal or cultural aversions. Inappropriate vaginal P use may alter successful implantation, leading physicians to consider alternate P application routes. A worldwide survey revealed that intramuscular plus vaginal P (combined P) is the method used in nearly one-third of in vitro fertilization (IVF) cycles, particularly in Asia and North America; unfortunately, the outcomes of this approach have not been clearly elucidated. In the current analysis, we evaluated any additional benefit of short course parenteral P in addition to vaginal P capsules during a specific period in terms of implantation, pregnancy rates, miscarriages and ectopic pregnancies in cleavage stage embryo transfer (ET) cycles of good-prognosis patients. Despite significantly higher implantation rates in the combined arm, clinical and ongoing pregnancies were comparable in both groups, whereas a trend toward increased pregnancy rates was observed with combined support. The available data are too limited to draw conclusions. PMID:26732029
Otağ, Aynur; Hazar, Muhsin; Otağ, İlhan; Beyleroğlu, Malik
2016-01-01
[Purpose] The performance of female athletes during their menstrual period has attracted the attention of researchers for many years. It is known that the menstrual period changes with exercise. Alpha-fetoprotein (AFP) is an oncofetal protein. In this study, the effect of maximal aerobic exercise in the luteal phase on some hormones and AFP in female athletes was researched. [Subjects and Methods] Twelve volunteers and healthy female footballers with normal menstrual cycles volunteered for this study as subjects. All the participants performed a shuttle run test. Blood samples were taken before, after, and one hour after exercise. Serum AFP, estrogen, progesterone, follicle-stimulating hormone (FSH), and luteinizing hormone (LH) values were measured using an auto analyzer and original kits. Heart rate measurements were performed before and after the exercise. [Results] AFP activity had significantly decreased after 1 h of recovery from the exercise in the female soccer players, and estrogen and LH activity had significantly increased immediately after the exercise. Progesterone activity had significantly decreased immediately after the exercise. FSH values had significantly increased immediately after the exercise. [Conclusion] The results of the present study show there were significant decreases in the values of AFP, which is a cancer parameter, 1 hour after the exercise. This result may be valuable in future physiotherapy studies on the relationship between exercise and cancer. PMID:27134362
Biberoglu, Ebru H; Tanrıkulu, Filiz; Erdem, Mehmet; Erdem, Ahmet; Biberoglu, Kutay Omer
2016-01-01
Vaginal progesterone (P) has been suggested to be used for luteal phase support (LPS) in controlled ovarian stimulation (COH)-intrauterine insemination (IUI) cycles, however, no concensus exists about the best P dose. Therefore, considering the fecundability rate as the primary end point, our main objective was to find the optimal dose of P in COH-IUI cycles, comparing the two groups of women, each of which comprised of 100 women either on 300 mg or 600 mg of intravaginal P tablets, in a prospective randomized study design. The mean age of the women, duration of infertility, basal and day of hCG injection hormone levels in the female and sperm parameters were similar in the two study groups. Also, duration and dose of gonadotropin given, number of follicles, endometrial thickness, the total, ongoing and multiple pregnancy rates were comparable in both groups. We, therefore, claim that 300 mg of intravaginal micronized P should be the maximum dose of LPS in IUI cycles. PMID:26291817
Estimating equivalence with quantile regression.
Cade, Brian 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. PMID:21516905
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.
Insulin resistance: regression and clustering.
Yoon, Sangho; Assimes, Themistocles L; Quertermous, Thomas; Hsiao, Chin-Fu; Chuang, Lee-Ming; Hwu, Chii-Min; Rajaratnam, Bala; Olshen, Richard A
2014-01-01
In this paper we try to define insulin resistance (IR) precisely for a group of Chinese women. Our definition deliberately does not depend upon body mass index (BMI) or age, although in other studies, with particular random effects models quite different from models used here, BMI accounts for a large part of the variability in IR. We accomplish our goal through application of Gauss mixture vector quantization (GMVQ), a technique for clustering that was developed for application to lossy data compression. Defining data come from measurements that play major roles in medical practice. A precise statement of what the data are is in Section 1. Their family structures are described in detail. They concern levels of lipids and the results of an oral glucose tolerance test (OGTT). We apply GMVQ to residuals obtained from regressions of outcomes of an OGTT and lipids on functions of age and BMI that are inferred from the data. A bootstrap procedure developed for our family data supplemented by insights from other approaches leads us to believe that two clusters are appropriate for defining IR precisely. One cluster consists of women who are IR, and the other of women who seem not to be. Genes and other features are used to predict cluster membership. We argue that prediction with "main effects" is not satisfactory, but prediction that includes interactions may be. PMID:24887437
Harmonic regression and scale stability.
Lee, Yi-Hsuan; Haberman, Shelby J
2013-10-01
Monitoring a very frequently administered educational test with a relatively short history of stable operation imposes a number of challenges. Test scores usually vary by season, and the frequency of administration of such educational tests is also seasonal. Although it is important to react to unreasonable changes in the distributions of test scores in a timely fashion, it is not a simple matter to ascertain what sort of distribution is really unusual. Many commonly used approaches for seasonal adjustment are designed for time series with evenly spaced observations that span many years and, therefore, are inappropriate for data from such educational tests. Harmonic regression, a seasonal-adjustment method, can be useful in monitoring scale stability when the number of years available is limited and when the observations are unevenly spaced. Additional forms of adjustments can be included to account for variability in test scores due to different sources of population variations. To illustrate, real data are considered from an international language assessment. PMID:24092490
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. PMID:27493417
A Survey of UML Based Regression Testing
NASA Astrophysics Data System (ADS)
Fahad, Muhammad; Nadeem, Aamer
Regression testing is the process of ensuring software quality by analyzing whether changed parts behave as intended, and unchanged parts are not affected by the modifications. Since it is a costly process, a lot of techniques are proposed in the research literature that suggest testers how to build regression test suite from existing test suite with minimum cost. In this paper, we discuss the advantages and drawbacks of using UML diagrams for regression testing and analyze that UML model helps in identifying changes for regression test selection effectively. We survey the existing UML based regression testing techniques and provide an analysis matrix to give a quick insight into prominent features of the literature work. We discuss the open research issues like managing and reducing the size of regression test suite, prioritization of the test cases that would be helpful during strict schedule and resources that remain to be addressed for UML based regression testing.
Regression in schizophrenia and its therapeutic value.
Yazaki, N
1992-03-01
Using the regression evaluation scale, 25 schizophrenic patients were classified into three groups of Dissolution/autism (DAUG), Dissolution----attachment (DATG) and Non-regression (NRG). The regression of DAUG was of the type in which autism occurred when destructiveness emerged, while the regression of DATG was of the type in which attachment occurred when destructiveness emerged. This suggests that the regressive phenomena are an actualized form of the approach complex. In order to determine the factors distinguishing these two groups, I investigated psychiatric symptoms, mother-child relationships, premorbid personalities and therapeutic interventions. I believe that these factors form a continuity in which they interrelatedly determine the regressive state. Foremost among them, I stressed the importance of the mother-child relationship. PMID:1353128
Data Mining within a Regression Framework
NASA Astrophysics Data System (ADS)
Berk, Richard A.
Regression analysis can imply a far wider range of statistical procedures than often appreciated. In this chapter, a number of common Data Mining procedures are discussed within a regression framework. These include non-parametric smoothers, classification and regression trees, bagging, and random forests. In each case, the goal is to characterize one or more of the distributional features of a response conditional on a set of predictors.
LRGS: Linear Regression by Gibbs Sampling
NASA Astrophysics Data System (ADS)
Mantz, Adam B.
2016-02-01
LRGS (Linear Regression by Gibbs Sampling) implements a Gibbs sampler to solve the problem of multivariate linear regression with uncertainties in all measured quantities and intrinsic scatter. LRGS extends an algorithm by Kelly (2007) that used Gibbs sampling for performing linear regression in fairly general cases in two ways: generalizing the procedure for multiple response variables, and modeling the prior distribution of covariates using a Dirichlet process.
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
Ferreira, R M; Ayres, H; Sales, J N S; Souza, A H; Rodrigues, C A; Baruselli, P S
2013-07-01
The hypotheses of this study were (1) that the administration of 400IU eCG in a TAI protocol would increase ovarian follicular growth and diameter of the largest follicle (LF), volume of the CL, and produce an earlier rise on serum concentration of progesterone (P4) to ultimately improve P/AI compared to non-treated high-producing Holstein cows; and (2) that 600IU of eCG could enhance any potential effects of a greater gonadotropin treatment upon follicular and luteal size and function, improving P/AI. Cows were subjected to a protocol of synchronization of ovulation for timed artificial insemination (TAI): D0-P4 device insert and estradiol benzoate, D8-P4 device removal and PGF2α; Experiment 1, D10PM - GnRH plus TAI; and Experiment 2, D10AM - GnRH, D10PM - TAI. In Experiment 1, at P4 device removal, cows were assigned to one of the two treatments to receive none (n=232) or 400IU (n=232) of eCG. In Experiment 2, again at P4 device removal, cows were assigned to one of the three treatments to receive no eCG, (n=166) 400 (n=145) or 600IU (n=145) of eCG. Pregnancy was diagnosed 35 days after TAI. Ultrasonographic examination of both ovaries was done in a subset of cows in Experiments 1 [no eCG (n=27) and 400IU eCG (n=14)], and 2 [no eCG (n=15), 400IU eCG (n=14) and 600IU eCG (n=11)]. Exams were conducted at device removal (D8) and TAI (D10) to measure the diameter of the LF; then twice daily from D10 to 13, to determine time to ovulation and the maximum diameter of the LF; and then 3 (D14), 6 (D17), 9 (D20) and 12 (D23) days after presumed ovulation, concurrent with blood sampling, to measure the volume of the CL and serum concentration of P4. In both studies, eCG (400 or 600IU)-treated cows had similar diameter of the LF on D8 and D10, growth rate of the LF from Days 8 to 10, ovulation rate, time to ovulation, volume of the CL, serum concentration of P4 and P/AI as compared to control animals. Thus, adding either 400 or 600IU eCG to TAI protocols was inefficient to
Roth, T L; Wolfe, B A; Long, J A; Howard, J G; Wildt, D E
1997-07-01
The effects of gonadotropin treatment and laparoscopic artificial insemination (AI) on embryo quality, serum progesterone and estradiol concentrations, and luteal progesterone content were examined in the domestic cat. These data were compared to similar historical data reported for naturally estrual, mated queens. All queens in this study (n = 32) were treated with eCG followed by 1) natural breeding (eCG-NB), 2) NB and hCG (eCG-NB-hCG), 3) NB and a sham AI procedure (eCG-NB-sham AI), or 4) hCG and actual AI (eCG-hCG-AI). Queens ovulating in response to treatment were ovariohysterectomized, and oviducts and uteri were flushed to collect embryos. Ovarian structures were recorded, corpora lutea (CL) were excised and evaluated for progesterone content, and serum was analyzed for estradiol-17beta and progesterone. Follicle and CL numbers ranged from 0 to 28 and 2 to 42 per cat, respectively, and treatment means did not differ (p > or = 0.05) among groups. Embryos were recovered from oviducts and uterine horns in all treatment groups, and recovery ranged from 60-96%. Mean embryo number per queen ranged from 8.2 +/- 2.6 to 23.2 +/- 3.8 and did not differ (p > or = 0.05) among groups. However, the proportions of unfertilized oocytes were greater (p < 0.05) for groups treated with hCG and/or artificially inseminated, and the proportion of blastocysts produced (31 of 107, 29.0%) was lower (p < 0.05) in the eCG-hCG-AI group than for any other treatment (range, 59 of 116 [50.9%] to 67 of 116 [57.8%]). Not all queens in each group produced good-quality embryos (eCG-NB, 5 of 5; eCG-NB-hCG, 5 of 8; eCG-NB-sham AI, 2 of 5; and eCG-hCG-AI, 3 of 6). Serum progesterone and estradiol-17beta, and total luteal progesterone per ovary did not differ (p > or = 0.05) among treatments. Compared to historical controls (naturally estrual, mated queens), eCG-NB queens produced > 4 times as many good-quality embryos and blastocysts. Similarly, eCG-hCG-AI-treated queens produced > 4 times the
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.
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.
Image segmentation via piecewise constant regression
NASA Astrophysics Data System (ADS)
Acton, Scott T.; Bovik, Alan C.
1994-09-01
We introduce a novel unsupervised image segmentation technique that is based on piecewise constant (PICO) regression. Given an input image, a PICO output image for a specified feature size (scale) is computed via nonlinear regression. The regression effectively provides the constant region segmentation of the input image that has a minimum deviation from the input image. PICO regression-based segmentation avoids the problems of region merging, poor localization, region boundary ambiguity, and region fragmentation. Additionally, our segmentation method is particularly well-suited for corrupted (noisy) input data. An application to segmentation and classification of remotely sensed imagery is provided.
Hybrid fuzzy regression with trapezoidal fuzzy data
NASA Astrophysics Data System (ADS)
Razzaghnia, T.; Danesh, S.; Maleki, A.
2011-12-01
In this regard, this research deals with a method for hybrid fuzzy least-squares regression. The extension of symmetric triangular fuzzy coefficients to asymmetric trapezoidal fuzzy coefficients is considered as an effective measure for removing unnecessary fuzziness of the linear fuzzy model. First, trapezoidal fuzzy variable is applied to derive a bivariate regression model. In the following, normal equations are formulated to solve the four parts of hybrid regression coefficients. Also the model is extended to multiple regression analysis. Eventually, method is compared with Y-H.O. chang's model.
Zhang, Zhenghong; Pang, Xunsheng; Tang, Zonghao; Yin, Dingzhong; Wang, Zhengchao
2015-09-01
Vascular endothelial growth factor (VEGF)-dependent angiogenesis has a crucial role in the corpus luteum formation and their functional maintenances in mammalian ovaries. A previous study by our group reported that activation of hypoxia‑inducible factor (HIF)‑1α signaling contributes to the regulation of VEGF expression in the luteal cells (LCs) in response to hypoxia and human chorionic gonadotropin. The present study was designed to test the hypothesis that HIF prolyl‑hydroxylases (PHDs) are expressed in LCs and overexpression of PHD2 attenuates the expression of VEGF induced by hypoxia in LCs. PHD2-overexpressing plasmid was transfected into LC2 cells, and successful plasmid transfection and expression was confirmed by reverse transcription quantitative polymerase chain reaction and western blot analysis. In addition, the present study investigated changes of HIF‑1α and VEGF expression after incubation under hypoxic conditions and PHD2 transfection. PHD2 expression was significantly higher expressed than the other two PHD isoforms, indicating its major role in LCs. Moreover, a significant increase of VEGF mRNA expression was identified after incubation under hypoxic conditions, which was, however, attenuated by PHD2 overexpression in LCs. Further analysis also indicated that this hypoxia‑induced increase in the mRNA expression of VEGF was consistent with increases in the protein levels of HIF‑1α, which is regulated by PHD-mediated degradation. In conclusion, the results of the present study indicated that PHD2 is the main PHD expressed in LCs and hypoxia‑induced VEGF expression can be attenuated by PHD2 overexpression through HIF‑1α‑mediated mechanisms in LCs. This PHD2-mediated transcriptional activation may be one of the mechanisms regulating VEGF expression in LCs during mammalian corpus luteum development. PMID:25975603
Killeen, Aideen P; Diskin, Michael G; Morris, Dermot G; Kenny, David A; Waters, Sinéad M
2016-04-01
Embryonic mortality is a major constraint to improving reproductive efficiency and profitability in livestock enterprises. We previously reported differential expression of genes with identified roles in cellular growth and proliferation, lipid metabolism, endometrial remodeling, inflammation, angiogenesis, and metabolic exchange in endometrial tissue on day 7 of the estrous cycle (D7), between heifers ranked as either high (HF) or low (LF) for fertility. The aim of the current study was to further elucidate the underlying molecular mechanisms contributing to early embryo loss by examining differential endometrial gene expression in HF or LF heifers at a later stage of the estrous cycle;day 14(D14). A second objective was to compare these expression profiles with those from midluteal HF and LF endometrium. Using the same animal model as employed in the previous study, we slaughtered HF and LF animals on D14, harvested endometrial tissue, and carried out global gene expression analysis using the Affymetrix Bovine GeneChip. Microarray analysis detected 430 differentially expressed genes (DEG) between HF and LF animals. Ingenuity Pathway Analysis revealed enrichment for a host of biological pathways including lipid metabolism, molecular transport, immune response, cell morphology and development, and cell growth and proliferation. Important DEG includedALB, BMPR2, CCL28, COL4A3/4, FADS1, ITGA6, LDLR, PLCB3, PPARG, PTGS2, and SLC27A4 Furthermore, DEG expressed on both D7 and D14 included:PCCB,SLC25A24,DAP, and COL4A4 This study highlights some of the pathways and mechanisms underpinning late luteal bovine endometrial physiology and endometrial-related conception rate variance. PMID:26850042
Torres, Ana; Batista, Mariana; Diniz, Patrícia; Mateus, Luisa; Lopes-da-Costa, Luís
2013-02-01
The role of progesterone (P(4)) and prostaglandins (PGs) in bovine early embryonic development and embryo-maternal crosstalk is almost unknown. Here, the in vitro steroidogenic (P(4)) and prostanoid (PGE(2) and PGF(2α)) interactions between bovine embryos and luteal cells (LC) were evaluated. In two experiments, embryos (n = 1.900) were either co-cultured with LC or cultured alone, from days 2 to 7 (day 0 = in vitro insemination). LC were also cultured alone, and medium was used as a control, all groups being cultured either with or without oil overlay of culture medium. Oil overlay of culture medium significantly decreased the amount of P(4), but not of PGE(2) and PGF(2α) measured in culture medium. Embryos and LC had transcripts of genes coding for enzymes of the PGs (PTGS2, PGES, and PGFS) and P(4) (StAR, P450scc, and 3β-HSD) synthesis pathways, and produced P(4), PGF(2α), and PGE(2) into culture medium. Co-culture with LC exerted an embryotrophic effect, significantly increasing blastocyst yield and quality. This indicates a possible direct effect of LC in early embryo development. Embryos did not exert a luteotrophic effect upon LC. This may indicate that early embryos (until day 7) probably do not exert influence in LC main function. It is suggested that production of P(4), PGE(2), and PGF(2α) by early embryos may be associated to autocrine signaling leading to events in development and to paracrine signaling in the endometrium leading to local uterine receptivity. PMID:23358866
Gurbuz, Ali Sami; Deveer, Ruya; Kucuk, Mert; Ozcimen, Necati; Incesu, Dilek; Koseoglu, Sezen
2016-01-01
Background Gonadotropin-releasing hormone (GnRH) agonist triggering plus 1,500 IU human chorionic gonadotropin (hCG) supplementation protocol was previously claimed effective in reducing the ovarian hyperstimulation syndrome (OHSS) incidence in high responders. Methods This retrospective study included women with polycystic ovarian (PCO) morphology who were at high risk of OHSS and were given the GnRH agonist trigger plus hCG luteal support protocol in a single center. Results The mean peak estradiol level was 5,336 ± 2,341 (1,187 - 19,746) pg/mL. The mean number of follicles > 12 mm on the day of trigger was 22 ± 7 (9 - 51). A total of 88 cycles were undertaken. Sixty-three (71.5%) women underwent fresh embryo transfer. Fresh embryo transfer was canceled in 21 (23.8%) and embryo transfer was canceled in four (4.5%) women. The overall clinical pregnancy rate was 46.4% per started cycle. A total of 12 (13.6%) patients developed OHSS. “Freeze-all” policy did not attenuate OHSS in four patients, and three of these patients developed OHSS despite 1,500 IU hCG was not administered. Conclusion We conclude that OHSS may still occur with the use of a GnRH agonist trigger combined with low-dose hCG supplementation protocol in women with polycystic ovary syndrome (PCOS) or PCO morphology. Furthermore, we also conclude that “freeze-all” policy also will not completely eliminate OHSS development in high-risk women. PMID:27081426
2013-01-01
Background Aglepristone (RU534) is an antiprogestin used for pregnancy termination, parturition induction and conservative pyometra treatment in bitches. Its molecular structure is similar to mifepristone, an antiprogestin used in human medicine. Mifepristone has been shown to suppress proliferation and cytokine production by T cells, whereas the effect of aglepristone on T cell function remains elusive. The purpose of this project was to investigate the in vitro influence of RU534 on IFN-γ and IL-4 synthesis by peripheral blood T cells isolated from healthy bitches (N = 16) in luteal phase. The peripheral blood mononuclear cells (PBMCs) were incubated with three different dosages of aglepristone, or dimethyl sulfoxide (DMSO), with or without mitogen. The production of cytokines by resting or mitogen-activated T cells was determined by intercellular staining and flow cytometry analysis or ELISA assay, respectively. Results Our results showed no statistically significant differences in the percentage of IFN-γ and IL-4-synthesizing CD4+ or CD8+ resting T cells between untreated and aglepristone-treated cells at 24 and 48 hours post treatment. Moreover, mitogen-activated PBMCs treated with RU534 displayed similar concentration of IFN-γ and IL-4 in culture supernatants to those observed in mitogen-activated DMSO-treated PBMCs. Presented results indicate that administration of aglepristone for 48 hours has no influence on IFN-γ and IL-4 synthesis by resting and mitogen-activated T cells isolated from diestral bitches. Conclusions We conclude that antiprogestins may differentially affect T cell function depending on the animal species in which they are applied. PMID:24284004
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. PMID:26471839
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.
Deriving the Regression Equation without Using Calculus
ERIC Educational Resources Information Center
Gordon, Sheldon P.; Gordon, Florence S.
2004-01-01
Probably the one "new" mathematical topic that is most responsible for modernizing courses in college algebra and precalculus over the last few years is the idea of fitting a function to a set of data in the sense of a least squares fit. Whether it be simple linear regression or nonlinear regression, this topic opens the door to applying the…
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.
Illustration of Regression towards the Means
ERIC Educational Resources Information Center
Govindaraju, K.; Haslett, S. J.
2008-01-01
This article presents a procedure for generating a sequence of data sets which will yield exactly the same fitted simple linear regression equation y = a + bx. Unless rescaled, the generated data sets will have progressively smaller variability for the two variables, and the associated response and covariate will "regress" towards their…
Stepwise versus Hierarchical Regression: Pros and Cons
ERIC Educational Resources Information Center
Lewis, Mitzi
2007-01-01
Multiple regression is commonly used in social and behavioral data analysis. In multiple regression contexts, researchers are very often interested in determining the "best" predictors in the analysis. This focus may stem from a need to identify those predictors that are supportive of theory. Alternatively, the researcher may simply be interested…
Cross-Validation, Shrinkage, and Multiple Regression.
ERIC Educational Resources Information Center
Hynes, Kevin
One aspect of multiple regression--the shrinkage of the multiple correlation coefficient on cross-validation is reviewed. The paper consists of four sections. In section one, the distinction between a fixed and a random multiple regression model is made explicit. In section two, the cross-validation paradigm and an explanation for the occurrence…
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…
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…
Dealing with Outliers: Robust, Resistant Regression
ERIC Educational Resources Information Center
Glasser, Leslie
2007-01-01
Least-squares linear regression is the best of statistics and it is the worst of statistics. The reasons for this paradoxical claim, arising from possible inapplicability of the method and the excessive influence of "outliers", are discussed and substitute regression methods based on median selection, which is both robust and resistant, are…
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…
Sulphasalazine and regression of rheumatoid nodules.
Englert, H J; Hughes, G R; Walport, M J
1987-03-01
The regression of small rheumatoid nodules was noted in four patients after starting sulphasalazine therapy. This coincided with an improvement in synovitis and also falls in erythrocyte sedimentation rate (ESR) and C reactive protein (CRP). The relation between the nodule regression and the sulphasalazine therapy is discussed. PMID:2883940
A Simulation Investigation of Principal Component Regression.
ERIC Educational Resources Information Center
Allen, David E.
Regression analysis is one of the more common analytic tools used by researchers. However, multicollinearity between the predictor variables can cause problems in using the results of regression analyses. Problems associated with multicollinearity include entanglement of relative influences of variables due to reduced precision of estimation,…
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…
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...
Jin, Yong Chun; Kim, Chun Wook; Kim, Young Min; Nizamutdinova, Irina Tsoy; Ha, Yu Mi; Kim, Hye Jung; Seo, Han Geuk; Son, Kun Ho; Jeon, Su Jin; Kang, Sam Sik; Kim, Yeong Shik; Kam, Sung-Chul; Lee, Jea Heun; Chang, Ki Churl
2009-07-01
The aim of the present study was to evaluate the protective effect of cryptotanshinone (CTS), one of active ingredients of Salvia miltiorrhiza root, on myocardial ischemia-reperfusion injury in rat due to inhibition of some inflammatory events that occur by NF-kappaB-activation during ischemia and reperfusion. Myocardial ischemia and reperfusion injury was induced by occluding the left anterior descending coronary artery for 30 min followed by either 2 h (biochemical analysis) or 24 h (myocardial function and infarct size measurement) reperfusion. CTS injected (i.v.) 10 min before ischemia and reperfusion insult. CTS significantly reduced the infarct size and improved ischemia and reperfusion-induced myocardial contractile dysfunction. Furthermore, CTS inhibited NF-kappaB translocation, expression of pro-inflammatory cytokines (TNF-alpha, IL-1beta, IL-6), neutrophil infiltration and MPO activity in ischemic myocardial tissues. CTS also significantly reduced plasma levels of TNF-alpha, IL-1beta due to ischemia and reperfusion. Interestingly, H(2)O(2)-stimulated NF-kappaB-luciferase activity and TNF-alpha-induced expression of vascular cell adhesion molecule-1 (VCAM-1) and intracellular adhesion molecule-1 (ICAM-1) expressions in human umbilical vein endothelial cells (HUVEC) were significantly inhibited by CTS. Taken together, it is concluded that CTS may attenuate ischemia and reperfusion-induced microcirculatory disturbances by inhibition of proinflammatory cytokine production, reduction of neutrophil infiltration and possibly inhibition of adhesion molecules through inhibition of NF-kappaB-activation during ischemia and reperfusion. PMID:19401198
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.
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)
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
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.
L-moments under nuisance regression
NASA Astrophysics Data System (ADS)
Picek, Jan; Schindler, Martin
2016-06-01
The L-moments are analogues of the conventional moments and have similar interpretations. They are calculated using linear combinations of the expectation of ordered data. In practice, L-moments must usually be estimated from a random sample drawn from an unknown distribution as a linear combination of ordered statistics. Jureckova and Picek (2014) showed that averaged regression quantile is asymptotically equivalent to the location quantile. We therefore propose a generalization of L-moments in the model with nuisance regression using the averaged regression quantiles.
Sparse Multivariate Regression With Covariance Estimation
Rothman, Adam J.; Levina, Elizaveta; Zhu, Ji
2014-01-01
We propose a procedure for constructing a sparse estimator of a multivariate regression coefficient matrix that accounts for correlation of the response variables. This method, which we call multivariate regression with covariance estimation (MRCE), involves penalized likelihood with simultaneous estimation of the regression coefficients and the covariance structure. An efficient optimization algorithm and a fast approximation are developed for computing MRCE. Using simulation studies, we show that the proposed method outperforms relevant competitors when the responses are highly correlated. We also apply the new method to a finance example on predicting asset returns. An R-package containing this dataset and code for computing MRCE and its approximation are available online. PMID:24963268
Spontaneous Regression of Primitive Merkel Cell Carcinoma
2015-01-01
Merkel cell carcinoma (MCC) is a rare, aggressive skin tumor that mainly occurs in the elderly with a generally poor prognosis. Like all skin cancers, its incidence is rising. Despite the poor prognosis, a few reports of spontaneous regression have been published. We describe the case of a 89-year-old male patient who presented two MCC lesions of the scalp. Following biopsy the lesions underwent complete regression with no clinical evidence of residual tumor up to 24 months. The current knowledge of MCC and the other cases of spontaneous regression described in the literature are reviewed. PMID:26788270
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)
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. PMID:26624223
Spontaneous Regression of an Incidental Spinal Meningioma
Yilmaz, Ali; Kizilay, Zahir; Sair, Ahmet; Avcil, Mucahit; Ozkul, Ayca
2016-01-01
AIM: The regression of meningioma has been reported in literature before. In spite of the fact that the regression may be involved by hemorrhage, calcification or some drugs withdrawal, it is rarely observed spontaneously. CASE REPORT: We report a 17 year old man with a cervical meningioma which was incidentally detected. In his cervical MRI an extradural, cranio-caudal contrast enchanced lesion at C2-C3 levels of the cervical spinal cord was detected. Despite the slight compression towards the spinal cord, he had no symptoms and refused any kind of surgical approach. The meningioma was followed by control MRI and it spontaneously regressed within six months. There were no signs of hemorrhage or calcification. CONCLUSION: Although it is a rare condition, the clinicians should consider that meningiomas especially incidentally diagnosed may be regressed spontaneously. PMID:27275345
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.
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 enhancement cannot…
Fuzzy multiple linear regression: A computational approach
NASA Technical Reports Server (NTRS)
Juang, C. H.; Huang, X. H.; Fleming, J. W.
1992-01-01
This paper presents a new computational approach for performing fuzzy regression. In contrast to Bardossy's approach, the new approach, while dealing with fuzzy variables, closely follows the conventional regression technique. In this approach, treatment of fuzzy input is more 'computational' than 'symbolic.' The following sections first outline the formulation of the new approach, then deal with the implementation and computational scheme, and this is followed by examples to illustrate the new procedure.
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.
Hierarchical regression for analyses of multiple outcomes.
Richardson, David B; Hamra, Ghassan B; MacLehose, Richard F; Cole, Stephen R; Chu, Haitao
2015-09-01
In cohort mortality studies, there often is interest in associations between an exposure of primary interest and mortality due to a range of different causes. A standard approach to such analyses involves fitting a separate regression model for each type of outcome. However, the statistical precision of some estimated associations may be poor because of sparse data. In this paper, we describe a hierarchical regression model for estimation of parameters describing outcome-specific relative rate functions and associated credible intervals. The proposed model uses background stratification to provide flexible control for the outcome-specific associations of potential confounders, and it employs a hierarchical "shrinkage" approach to stabilize estimates of an exposure's associations with mortality due to different causes of death. The approach is illustrated in analyses of cancer mortality in 2 cohorts: a cohort of dioxin-exposed US chemical workers and a cohort of radiation-exposed Japanese atomic bomb survivors. Compared with standard regression estimates of associations, hierarchical regression yielded estimates with improved precision that tended to have less extreme values. The hierarchical regression approach also allowed the fitting of models with effect-measure modification. The proposed hierarchical approach can yield estimates of association that are more precise than conventional estimates when one wishes to estimate associations with multiple outcomes. PMID:26232395
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.
Mental chronometry with simple linear regression.
Chen, J Y
1997-10-01
Typically, mental chronometry is performed by means of introducing an independent variable postulated to affect selectively some stage of a presumed multistage process. However, the effect could be a global one that spreads proportionally over all stages of the process. Currently, there is no method to test this possibility although simple linear regression might serve the purpose. In the present study, the regression approach was tested with tasks (memory scanning and mental rotation) that involved a selective effect and with a task (word superiority effect) that involved a global effect, by the dominant theories. The results indicate (1) the manipulation of the size of a memory set or of angular disparity affects the intercept of the regression function that relates the times for memory scanning with different set sizes or for mental rotation with different angular disparities and (2) the manipulation of context affects the slope of the regression function that relates the times for detecting a target character under word and nonword conditions. These ratify the regression approach as a useful method for doing mental chronometry. PMID:9347535
Alpha-induced reactions in iridium
Bhardwaj, M.K.; Rizvi, I.A.; Chaubey, A.K. )
1992-05-01
The excitation function of ({alpha},{ital xn}) reactions on {sup 191}Ir (abundance 37.3%) and on {sup 193}Ir (abundance 62.7%) has been measured for the 17--55 MeV alpha-particle bombarding energy range. The stacked foil activation technique and {gamma}-ray spectroscopy were used to determine the cross sections. The experimental data were compared with calculated values obtained by means of a geometry-dependent hybrid model. The initial exciton number {ital n}{sub 0}=4 with {ital n}=2, {ital p}=2, and {ital h}=0 gives the best agreements with the presently measured results. To calculate the excitation function theoretically a computer code was used. This set of excitation functions provides a data basis for probing the validity of combined equilibrium and preequilibrium reaction models in a considerable energy range.
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.
Efficient Regressions via Optimally Combining Quantile Information*
Zhao, Zhibiao; Xiao, Zhijie
2014-01-01
We develop a generally applicable framework for constructing efficient estimators of regression models via quantile regressions. The proposed method is based on optimally combining information over multiple quantiles and can be applied to a broad range of parametric and nonparametric settings. When combining information over a fixed number of quantiles, we derive an upper bound on the distance between the efficiency of the proposed estimator and the Fisher information. As the number of quantiles increases, this upper bound decreases and the asymptotic variance of the proposed estimator approaches the Cramér-Rao lower bound under appropriate conditions. In the case of non-regular statistical estimation, the proposed estimator leads to super-efficient estimation. We illustrate the proposed method for several widely used regression models. Both asymptotic theory and Monte Carlo experiments show the superior performance over existing methods. PMID:25484481
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.
Spontaneous hypnotic age regression: case report.
Spiegel, D; Rosenfeld, A
1984-12-01
Age regression--reliving the past as though it were occurring in the present, with age appropriate vocabulary, mental content, and affect--can occur with instruction in highly hypnotizable individuals, but has rarely been reported to occur spontaneously, especially as a primary symptom. The psychiatric presentation and treatment of a 16-year-old girl with spontaneous age regressions accessible and controllable with hypnosis and psychotherapy are described. Areas of overlap and divergence between this patient's symptoms and those found in patients with hysterical fugue and multiple personality syndrome are also discussed. PMID:6501240
Spontaneous regression of a conjunctival naevus.
Haldar, Shreya; Leyland, Martin
2016-01-01
Conjunctival naevi are one of the most common lesions affecting the conjunctiva. While benign in the vast majority of cases, the risk of malignant transformation necessitates regular follow-up. They are well known to increase in size; however, we present the first photo-documented case of spontaneous regression of conjunctival naevus. In most cases, surgical excision is performed due to the clinician's concerns over malignancy. However, a substantial proportion of patients request excision. Highlighting the potential for regression of the lesion is important to ensure patients make an informed decision when contemplating such surgery. PMID:27581234
Heritability Estimation using Regression Models for Correlation
Lee, Hye-Seung; Paik, Myunghee Cho; Rundek, Tatjana; Sacco, Ralph L; Dong, Chuanhui; Krischer, Jeffrey P
2012-01-01
Heritability estimates a polygenic effect on a trait for a population. Reliable interpretation of heritability is critical in planning further genetic studies to locate a gene responsible for the trait. This study accommodates both single and multiple trait cases by employing regression models for correlation parameter to infer the heritability. Sharing the properties of regression approach, the proposed methods are exible to incorporate non-genetic and/or non-additive genetic information in the analysis. The performances of the proposed model are compared with those using the likelihood approach through simulations and carotid Intima Media Thickness analysis from Northern Manhattan family Study. PMID:22457844
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.
Topics in route-regression analysis
Geissler, P.H.; Sauer, J.R.
1990-01-01
The route-regression method has been used in recent years to analyze data from roadside surveys. With this method, a population trend is estimated for each route in a region, then regional trends are estimated as a weighted mean of the individual route trends. This method can accurately incorporate data that is unbalanced by changes in years surveyed and observer differences. We suggest that route-regression methodology is most efficient in the estimation of long-term (>5 year) trends, and tends to provide conservative results for low-density species.
Liu, Zhan-yu; Huang, Jing-feng; Shi, Jing-jing; Tao, Rong-xiang; Zhou, Wan; Zhang, Li-Li
2007-10-01
Detecting plant health conditions plays a key role in farm pest management and crop protection. In this study, measurement of hyperspectral leaf reflectance in rice crop (Oryzasativa L.) was conducted on groups of healthy and infected leaves by the fungus Bipolaris oryzae (Helminthosporium oryzae Breda. de Hann) through the wavelength range from 350 to 2,500 nm. The percentage of leaf surface lesions was estimated and defined as the disease severity. Statistical methods like multiple stepwise regression, principal component analysis and partial least-square regression were utilized to calculate and estimate the disease severity of rice brown spot at the leaf level. Our results revealed that multiple stepwise linear regressions could efficiently estimate disease severity with three wavebands in seven steps. The root mean square errors (RMSEs) for training (n=210) and testing (n=53) dataset were 6.5% and 5.8%, respectively. Principal component analysis showed that the first principal component could explain approximately 80% of the variance of the original hyperspectral reflectance. The regression model with the first two principal components predicted a disease severity with RMSEs of 16.3% and 13.9% for the training and testing dataset, respectively. Partial least-square regression with seven extracted factors could most effectively predict disease severity compared with other statistical methods with RMSEs of 4.1% and 2.0% for the training and testing dataset, respectively. Our research demonstrates that it is feasible to estimate the disease severity of rice brown spot using hyperspectral reflectance data at the leaf level. PMID:17910117
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
Stocco, C O; Chedrese, J; Deis, R P
2001-10-01
A decrease in serum progesterone at the end of pregnancy is essential for the induction of parturition in rats. We have previously demonstrated that LH participates in this process through: 1) inhibiting 3beta-hydroxysteroid dehydrogenase (3beta-HSD) activity and 2) stimulating progesterone catabolism by inducing 20alpha-hydroxysteroid dehydrogenase (20alpha-HSD) activity. The objective of this investigation was to determine the effect of LH and progesterone on the luteal expression of the steroidogenic acute regulatory protein (StAR), cytochrome P450 side-chain cleavage (P450(scc)), 3beta-HSD, and 20alpha-HSD genes. Gene expression was analyzed by Northern blot analysis 24 and 48 h after administration of LH or vehicle on Day 19 of pregnancy. StAR and 3beta-HSD mRNA levels were lower in LH-treated rats than in rats administered with vehicle at both time points studied. P450(scc) mRNA levels were unaffected by LH. The 20alpha-HSD mRNA levels were not different between LH and control rats 24 h after treatment; however, greater expression of 20alpha-HSD, with respect to controls, was observed in LH-treated rats 48 h after treatment. Luteal progesterone content dropped in LH-treated rats at both time points studied, whereas serum progesterone decreased after 48 h only. In a second set of experiments, the anti-progesterone RU486 was injected intrabursally on Day 20 of pregnancy. RU486 had no effect on 3beta-HSD or P450(scc) expression but increased 20alpha-HSD mRNA levels after 8 h treatment. In conclusion, the luteolytic effect of LH is mediated by a drop in StAR and 3beta-HSD expression without effect on P450(scc) expression. We also provide the first in vivo evidence indicating that a decrease in luteal progesterone content may be an essential step toward the induction of 20alpha-HSD expression at the end of pregnancy in rats. PMID:11566732
NASA Astrophysics Data System (ADS)
Lin, Yingzhi; Deng, Xiangzheng; Li, Xing; Ma, Enjun
2014-12-01
Spatially explicit simulation of land use change is the basis for estimating the effects of land use and cover change on energy fluxes, ecology and the environment. At the pixel level, logistic regression is one of the most common approaches used in spatially explicit land use allocation models to determine the relationship between land use and its causal factors in driving land use change, and thereby to evaluate land use suitability. However, these models have a drawback in that they do not determine/allocate land use based on the direct relationship between land use change and its driving factors. Consequently, a multinomial logistic regression method was introduced to address this flaw, and thereby, judge the suitability of a type of land use in any given pixel in a case study area of the Jiangxi Province, China. A comparison of the two regression methods indicated that the proportion of correctly allocated pixels using multinomial logistic regression was 92.98%, which was 8.47% higher than that obtained using logistic regression. Paired t-test results also showed that pixels were more clearly distinguished by multinomial logistic regression than by logistic regression. In conclusion, multinomial logistic regression is a more efficient and accurate method for the spatial allocation of land use changes. The application of this method in future land use change studies may improve the accuracy of predicting the effects of land use and cover change on energy fluxes, ecology, and environment.
ERIC Educational Resources Information Center
Williams, John D.; Lindem, Alfred C.
Four computer programs using the general purpose multiple linear regression program have been developed. Setwise regression analysis is a stepwise procedure for sets of variables; there will be as many steps as there are sets. Covarmlt allows a solution to the analysis of covariance design with multiple covariates. A third program has three…
Bayesian nonparametric regression with varying residual density.
Pati, Debdeep; Dunson, David B
2014-02-01
We consider the problem of robust Bayesian inference on the mean regression function allowing the residual density to change flexibly with predictors. The proposed class of models is based on a Gaussian process prior for the mean regression function and mixtures of Gaussians for the collection of residual densities indexed by predictors. Initially considering the homoscedastic case, we propose priors for the residual density based on probit stick-breaking (PSB) scale mixtures and symmetrized PSB (sPSB) location-scale mixtures. Both priors restrict the residual density to be symmetric about zero, with the sPSB prior more flexible in allowing multimodal densities. We provide sufficient conditions to ensure strong posterior consistency in estimating the regression function under the sPSB prior, generalizing existing theory focused on parametric residual distributions. The PSB and sPSB priors are generalized to allow residual densities to change nonparametrically with predictors through incorporating Gaussian processes in the stick-breaking components. This leads to a robust Bayesian regression procedure that automatically down-weights outliers and influential observations in a locally-adaptive manner. Posterior computation relies on an efficient data augmentation exact block Gibbs sampler. The methods are illustrated using simulated and real data applications. PMID:24465053
Using Regression Analysis: A Guided Tour.
ERIC Educational Resources Information Center
Shelton, Fred Ames
1987-01-01
Discusses the use and interpretation of multiple regression analysis with computer programs and presents a flow chart of the process. A general explanation of the flow chart is provided, followed by an example showing the development of a linear equation which could be used in estimating manufacturing overhead cost. (Author/LRW)
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…
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…
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.
Nodular fasciitis with degeneration and regression.
Yanagisawa, Akihiro; Okada, Hideki
2008-07-01
Nodular fasciitis is a benign reactive proliferation that is frequently misdiagnosed as a sarcoma. This article describes a case of nodular fasciitis of 6-month duration located in the cheek, which degenerated and spontaneously regressed after biopsy. The nodule was fixed to the zygoma but was free from the overlying skin. The mass was 3.0 cm in diameter and demonstrated high signal intensity on T2-weighted magnetic resonance imaging. A small part of the lesion was biopsied. Pathological and immunohistochemical examinations identified the nodule as nodular fasciitis with myxoid histology. One month after the biopsy, the mass showed decreased signal intensity on T2-weighted images and measured 2.2 cm in size. The signal on T2-weighted images showed time-dependent decreases, and the mass continued to reduce in size throughout the follow-up period. The lesion presented as hypointense to the surrounding muscles on T2-weighted images and was 0.4 cm in size at 2 years of follow-up. This case demonstrates that nodular fasciitis with myxoid histology can change to that with fibrous appearance gradually with time, thus bringing about spontaneous regression. Degeneration may be involved in the spontaneous regression of nodular fasciitis with myxoid appearance. The mechanism of regression, unclarified at present, should be further studied. PMID:18650753
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. PMID:25361503
Bootstrap inference longitudinal semiparametric regression model
NASA Astrophysics Data System (ADS)
Pane, Rahmawati; Otok, Bambang Widjanarko; Zain, Ismaini; Budiantara, I. Nyoman
2016-02-01
Semiparametric regression contains two components, i.e. parametric and nonparametric component. Semiparametric regression model is represented by yt i=μ (x˜'ti,zt i)+εt i where μ (x˜'ti,zt i)=x˜'tiβ ˜+g (zt i) and yti is response variable. It is assumed to have a linear relationship with the predictor variables x˜'ti=(x1 i 1,x2 i 2,…,xT i r) . Random error εti, i = 1, …, n, t = 1, …, T is normally distributed with zero mean and variance σ2 and g(zti) is a nonparametric component. The results of this study showed that the PLS approach on longitudinal semiparametric regression models obtain estimators β˜^t=[X'H(λ)X]-1X'H(λ )y ˜ and g˜^λ(z )=M (λ )y ˜ . The result also show that bootstrap was valid on longitudinal semiparametric regression model with g^λ(b )(z ) as nonparametric component estimator.
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.
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…
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. PMID:27575130
Multiple Linear Regression: A Realistic Reflector.
ERIC Educational Resources Information Center
Nutt, A. T.; Batsell, R. R.
Examples of the use of Multiple Linear Regression (MLR) techniques are presented. This is done to show how MLR aids data processing and decision-making by providing the decision-maker with freedom in phrasing questions and by accurately reflecting the data on hand. A brief overview of the rationale underlying MLR is given, some basic definitions…
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…
A New Sample Size Formula for Regression.
ERIC Educational Resources Information Center
Brooks, Gordon P.; Barcikowski, Robert S.
The focus of this research was to determine the efficacy of a new method of selecting sample sizes for multiple linear regression. A Monte Carlo simulation was used to study both empirical predictive power rates and empirical statistical power rates of the new method and seven other methods: those of C. N. Park and A. L. Dudycha (1974); J. Cohen…
A Logistic Regression Model for Personnel Selection.
ERIC Educational Resources Information Center
Raju, Nambury S.; And Others
1991-01-01
A two-parameter logistic regression model for personnel selection is proposed. The model was tested with a database of 84,808 military enlistees. The probability of job success was related directly to trait levels, addressing such topics as selection, validity generalization, employee classification, selection bias, and utility-based fair…
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…
Climate Change Projections Using Regional Regression Models
NASA Astrophysics Data System (ADS)
Griffis, V. W.; Gyawali, R.; Watkins, D. W.
2012-12-01
A typical approach to project climate change impacts on water resources systems is to downscale general circulation model (GCM) or regional climate model (RCM) outputs as forcing data for a watershed model. With downscaled climate model outputs becoming readily available, multi-model ensemble approaches incorporating mutliple GCMs, multiple emissions scenarios and multiple initializations are increasingly being used. While these multi-model climate ensembles represent a range of plausible futures, different hydrologic models and methods may complicate impact assessment. In particular, associated loss, flow routing, snowmelt and evapotranspiration computation methods can markedly increase hydrological modeling uncertainty. Other challenges include properly calibrating and verifying the watershed model and maintaining a consistent energy budget between climate and hydrologic models. An alternative approach, particularly appealing for ungauged basins or locations where record lengths are short, is to directly predict selected streamflow quantiles from regional regression equations that include physical basin characteristics as well as meteorological variables output by climate models (Fennessey 2011). Two sets of regional regression models are developed for the Great Lakes states using ordinary least squares and weighted least squares regression. The regional regression modeling approach is compared with physically based hydrologic modeling approaches for selected Great Lakes watersheds using downscaled outputs from the Coupled Model Intercomparison Project (CMIP3) as inputs to the Large Basin Runoff Model (LBRM) and the U.S. Army Corps Hydrologic Modeling System (HEC-HMS).
Evaluating Aptness of a Regression Model
ERIC Educational Resources Information Center
Matson, Jack E.; Huguenard, Brian R.
2007-01-01
The data for 104 software projects is used to develop a linear regression model that uses function points (a measure of software project size) to predict development effort. The data set is particularly interesting in that it violates several of the assumptions required of a linear model; but when the data are transformed, the data set satisfies…
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…
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…
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…
REGRESSION METHODS FOR DATA WITH INCOMPLETE COVARIATES
Modern statistical methods in chronic disease epidemiology allow simultaneous regression of disease status on several covariates. hese methods permit examination of the effects of one covariate while controlling for those of others that may be causally related to the disease. owe...
Student Selection and the Special Regression Model.
ERIC Educational Resources Information Center
Deck, Dennis D.
The feasibility of constructing composite scores which will yield pretest measures having all the properties required by the special regression model is explored as an alternative to the single pretest score usually used in student selection for Elementary Secondary Education Act Title I compensatory education programs. Reading data, including…
Code System to Calculate Correlation & Regression Coefficients.
1999-11-23
Version 00 PCC/SRC is designed for use in conjunction with sensitivity analyses of complex computer models. PCC/SRC calculates the partial correlation coefficients (PCC) and the standardized regression coefficients (SRC) from the multivariate input to, and output from, a computer model.
Farrall, A L; Whitelaw, M L
2009-10-15
The short isoform of single-minded 2 (SIM2s), a basic helix-loop-helix/PAS (bHLH/PAS) transcription factor, is upregulated in pancreatic and prostate tumours; however, a mechanistic role for SIM2s in these cancers is unknown. Microarray studies in prostate DU145 cells identified the pro-cell death gene, BNIP3 (Bcl-2/adenovirus E1B 19 kDa interacting protein 3), as a novel putative target of SIM2s repression. Further validation showed BNIP3 repression in several prostate and pancreatic carcinoma-derived cell lines with ectopic expression of human SIM2s. BNIP3 levels are enhanced in prostate carcinoma cells upon short interfering (si)RNA-mediated knockdown of endogenous SIM2s. Chromatin immunoprecipitation and promoter studies show that SIM2s represses BNIP3 through its activities at the proximal promoter hypoxia response element (HRE), the site through which the bHLH/PAS family member, hypoxia-inducible factor 1alpha (HIF1alpha), induces BNIP3. SIM2s attenuates BNIP3 hypoxic induction via the HRE, and increased hypoxic induction of BNIP3 occurs with siRNA knockdown of endogenous SIM2s in prostate PC3AR+ cells. BNIP3 is implicated in hypoxia-induced cell death processes. Prolonged treatment of PC3AR+ cells with hypoxia mimetics, DP and DMOG, confers hypoxia-induced autophagy, measured by enhanced LC3-II levels and SQSTM1/p62 turnover. We show that PC3AR+ cells expressing ectopic SIM2s have enhanced survival in these conditions. Induction of LC3-II and turnover of SQSTM1/p62 are attenuated in PC3AR+/SIM2s DMOG and hypoxia-treated cells, suggesting that SIM2s may attenuate autophagic cell death processes, perhaps through BNIP3 repression. These data show, for the first time, SIM2s cross-talk on an endogenous HRE. SIM2s' functional interference with HIF1alpha activities on BNIP3 may indicate a novel role for SIM2s in promoting tumourigenesis. PMID:19668230
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
Zafardoust, Simin; Jeddi-Tehrani, Mahmood; Akhondi, Mohammad Mehdi; Sadeghi, Mohammad Reza; Kamali, Koroush; Mokhtar, Sara; Badehnoosh, Bita; Arjmand-Teymouri, Fatemeh; Fatemi, Farnaz; Mohammadzadeh, Afsaneh
2015-01-01
Background GnRH agonist administration in the luteal phase has been suggested to beneficially affect the outcome of intracytoplasmic sperm injection (ICSI) and embryo transfer (ET) cycles. This blind randomized controlled study evaluates the effect of GnRH (Gonadotropine Releasing Hormone) agonist administration on ICSI outcome in GnRH antagonist ovarian stimulation protocol in women with 2 or more previous IVF/ICSI-ET failures. Methods One hundred IVF failure women who underwent ICSI cycles and stimulated with GnRH antagonist ovarian stimulation protocol, were included in the study. Women were randomly assigned to intervention (received a single dose injection of GnRH agonist (0.1 mg of Decapeptil) subcutaneously 6 days after oocyte retrieval) and control (did not receive GnRH agonist) groups. Implantation and clinical pregnancy rates were the primary outcome measures. Results Although the age of women, the number of embryos transferred in the current cycle and the quality of the transferred embryos were similar in the two groups, there was a significantly higher rate of implantation (Mann Whitney test, p = 0.041) and pregnancy (32.6% vs. 12.5%, p = 0.030, OR = 3.3, 95%CI, 1.08 to 10.4) in the intervention group. Conclusion Our results suggested that, in addition to routine luteal phase support using progesterone, administration of 0.1 mg of Decapeptil 6 days after oocyte retrieval in women with previous history of 2 or more IVF/ICSI failures led to a significant improvement in implantation and pregnancy rates after ICSI following ovarian stimulation with GnRH antagonist protocol. PMID:25927026
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.
[Caudal regression sequence: clinical-radiological case].
Zepeda T, Juan; García M, Mirna; Morales S, Jorge; Pantoja H, Miguel A; Espinoza G, Aníbal
2015-01-01
Caudal regression syndrome is an uncommon congenital malformation that includes a wide spectrum of clinical presentations. Characterised by caudal musculoskeletal compromise, it can be associated to neurological, gastrointestinal, renal and genitourinary defects. Although the specific aetiology has not been clarified, it has been associated with the presence of maternal diabetes and mutations in homeobox gene HBLX9. Its diagnosis is based on a good prenatal ultrasound detection, detailed physical examination, and post-natal imaging study using radiography and magnetic resonance. Caudal regression syndrome requires multidisciplinary management, and it seems that good metabolic control of gestational diabetes constitutes the best preventive measure available. We present the clinical case and images of a male term newborn, born to a pregestational diabetic mother with poor metabolic control and a prenatal ultrasound diagnosis of lumbar spine, iliac bones and lower limbs malformation. Born in good conditions, the diagnosis was confirmed using X-rays and magnetic resonance. PMID:26455704
Joint regression analysis for discrete longitudinal data.
Madsen, L; Fang, Y
2011-09-01
We introduce an approximation to the Gaussian copula likelihood of Song, Li, and Yuan (2009, Biometrics 65, 60-68) used to estimate regression parameters from correlated discrete or mixed bivariate or trivariate outcomes. Our approximation allows estimation of parameters from response vectors of length much larger than three, and is asymptotically equivalent to the Gaussian copula likelihood. We estimate regression parameters from the toenail infection data of De Backer et al. (1996, British Journal of Dermatology 134, 16-17), which consist of binary response vectors of length seven or less from 294 subjects. Although maximizing the Gaussian copula likelihood yields estimators that are asymptotically more efficient than generalized estimating equation (GEE) estimators, our simulation study illustrates that for finite samples, GEE estimators can actually be as much as 20% more efficient. PMID:21039391
Self-Adaptive Induction of Regression Trees.
Fidalgo-Merino, Raúl; Núñez, Marlon
2011-08-01
A new algorithm for incremental construction of binary regression trees is presented. This algorithm, called SAIRT, adapts the induced model when facing data streams involving unknown dynamics, like gradual and abrupt function drift, changes in certain regions of the function, noise, and virtual drift. It also handles both symbolic and numeric attributes. The proposed algorithm can automatically adapt its internal parameters and model structure to obtain new patterns, depending on the current dynamics of the data stream. SAIRT can monitor the usefulness of nodes and can forget examples from selected regions, storing the remaining ones in local windows associated to the leaves of the tree. On these conditions, current regression methods need a careful configuration depending on the dynamics of the problem. Experimentation suggests that the proposed algorithm obtains better results than current algorithms when dealing with data streams that involve changes with different speeds, noise levels, sampling distribution of examples, and partial or complete changes of the underlying function. PMID:21263164
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.
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
2016-07-01
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
Differential correction schemes in nonlinear regression
NASA Technical Reports Server (NTRS)
Decell, H. P., Jr.; Speed, F. M.
1972-01-01
Classical iterative methods in nonlinear regression are reviewed and improved upon. This is accomplished by discussion of the geometrical and theoretical motivation for introducing modifications using generalized matrix inversion. Examples having inherent pitfalls are presented and compared in terms of results obtained using classical and modified techniques. The modification is shown to be useful alone or in conjunction with other modifications appearing in the literature.
Time series regression studies in environmental epidemiology
Bhaskaran, Krishnan; Gasparrini, Antonio; Hajat, Shakoor; Smeeth, Liam; Armstrong, Ben
2013-01-01
Time series regression studies have been widely used in environmental epidemiology, notably in investigating the short-term associations between exposures such as air pollution, weather variables or pollen, and health outcomes such as mortality, myocardial infarction or disease-specific hospital admissions. Typically, for both exposure and outcome, data are available at regular time intervals (e.g. daily pollution levels and daily mortality counts) and the aim is to explore short-term associations between them. In this article, we describe the general features of time series data, and we outline the analysis process, beginning with descriptive analysis, then focusing on issues in time series regression that differ from other regression methods: modelling short-term fluctuations in the presence of seasonal and long-term patterns, dealing with time varying confounding factors and modelling delayed (‘lagged’) associations between exposure and outcome. We finish with advice on model checking and sensitivity analysis, and some common extensions to the basic model. PMID:23760528
Time series regression studies in environmental epidemiology.
Bhaskaran, Krishnan; Gasparrini, Antonio; Hajat, Shakoor; Smeeth, Liam; Armstrong, Ben
2013-08-01
Time series regression studies have been widely used in environmental epidemiology, notably in investigating the short-term associations between exposures such as air pollution, weather variables or pollen, and health outcomes such as mortality, myocardial infarction or disease-specific hospital admissions. Typically, for both exposure and outcome, data are available at regular time intervals (e.g. daily pollution levels and daily mortality counts) and the aim is to explore short-term associations between them. In this article, we describe the general features of time series data, and we outline the analysis process, beginning with descriptive analysis, then focusing on issues in time series regression that differ from other regression methods: modelling short-term fluctuations in the presence of seasonal and long-term patterns, dealing with time varying confounding factors and modelling delayed ('lagged') associations between exposure and outcome. We finish with advice on model checking and sensitivity analysis, and some common extensions to the basic model. PMID:23760528
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.
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.
General Regression and Representation Model for Classification
Qian, Jianjun; Yang, Jian; Xu, Yong
2014-01-01
Recently, the regularized coding-based classification methods (e.g. SRC and CRC) show a great potential for pattern classification. However, most existing coding methods assume that the representation residuals are uncorrelated. In real-world applications, this assumption does not hold. In this paper, we take account of the correlations of the representation residuals and develop a general regression and representation model (GRR) for classification. GRR not only has advantages of CRC, but also takes full use of the prior information (e.g. the correlations between representation residuals and representation coefficients) and the specific information (weight matrix of image pixels) to enhance the classification performance. GRR uses the generalized Tikhonov regularization and K Nearest Neighbors to learn the prior information from the training data. Meanwhile, the specific information is obtained by using an iterative algorithm to update the feature (or image pixel) weights of the test sample. With the proposed model as a platform, we design two classifiers: basic general regression and representation classifier (B-GRR) and robust general regression and representation classifier (R-GRR). The experimental results demonstrate the performance advantages of proposed methods over state-of-the-art algorithms. PMID:25531882
The Regression Trunk Approach to Discover Treatment Covariate Interaction
ERIC Educational Resources Information Center
Dusseldorp, Elise; Meulman, Jacqueline J.
2004-01-01
The regression trunk approach (RTA) is an integration of regression trees and multiple linear regression analysis. In this paper RTA is used to discover treatment covariate interactions, in the regression of one continuous variable on a treatment variable with "multiple" covariates. The performance of RTA is compared to the classical method of…
Analyzing Historical Count Data: Poisson and Negative Binomial Regression Models.
ERIC Educational Resources Information Center
Beck, E. M.; Tolnay, Stewart E.
1995-01-01
Asserts that traditional approaches to multivariate analysis, including standard linear regression techniques, ignore the special character of count data. Explicates three suitable alternatives to standard regression techniques, a simple Poisson regression, a modified Poisson regression, and a negative binomial model. (MJP)
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
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.
Regression models for expected length of stay.
Grand, Mia Klinten; Putter, Hein
2016-03-30
In multi-state models, the expected length of stay (ELOS) in a state is not a straightforward object to relate to covariates, and the traditional approach has instead been to construct regression models for the transition intensities and calculate ELOS from these. The disadvantage of this approach is that the effect of covariates on the intensities is not easily translated into the effect on ELOS, and it typically relies on the Markov assumption. We propose to use pseudo-observations to construct regression models for ELOS, thereby allowing a direct interpretation of covariate effects while at the same time avoiding the Markov assumption. For this approach, all we need is a non-parametric consistent estimator for ELOS. For every subject (and for every state of interest), a pseudo-observation is constructed, and they are then used as outcome variables in the regression model. We furthermore show how to construct longitudinal (pseudo-) data when combining the concept of pseudo-observations with landmarking. In doing so, covariates are allowed to be time-varying, and we can investigate potential time-varying effects of the covariates. The models can be fitted using generalized estimating equations, and dependence between observations on the same subject is handled by applying the sandwich estimator. The method is illustrated using data from the US Health and Retirement Study where the impact of socio-economic factors on ELOS in health and disability is explored. Finally, we investigate the performance of our approach under different degrees of left-truncation, non-Markovianity, and right-censoring by means of simulation. PMID:26497637
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. PMID:26706761
Penalized solutions to functional regression problems
Harezlak, Jaroslaw; Coull, Brent A.; Laird, Nan M.; Magari, Shannon R.; Christiani, David C.
2007-01-01
SUMMARY Recent technological advances in continuous biological monitoring and personal exposure assessment have led to the collection of subject-specific functional data. A primary goal in such studies is to assess the relationship between the functional predictors and the functional responses. The historical functional linear model (HFLM) can be used to model such dependencies of the response on the history of the predictor values. An estimation procedure for the regression coefficients that uses a variety of regularization techniques is proposed. An approximation of the regression surface relating the predictor to the outcome by a finite-dimensional basis expansion is used, followed by penalization of the coefficients of the neighboring basis functions by restricting the size of the coefficient differences to be small. Penalties based on the absolute values of the basis function coefficient differences (corresponding to the LASSO) and the squares of these differences (corresponding to the penalized spline methodology) are studied. The fits are compared using an extension of the Akaike Information Criterion that combines the error variance estimate, degrees of freedom of the fit and the norm of the bases function coefficients. The performance of the proposed methods is evaluated via simulations. The LASSO penalty applied to the linearly transformed coefficients yields sparser representations of the estimated regression surface, while the quadratic penalty provides solutions with the smallest L2-norm of the basis functions coefficients. Finally, the new estimation procedure is applied to the analysis of the effects of occupational particulate matter (PM) exposure on the heart rate variability (HRV) in a cohort of boilermaker workers. Results suggest that the strongest association between PM exposure and HRV in these workers occurs as a result of point exposures to the increased levels of particulate matter corresponding to smoking breaks. PMID:18552972
Penalized solutions to functional regression problems.
Harezlak, Jaroslaw; Coull, Brent A; Laird, Nan M; Magari, Shannon R; Christiani, David C
2007-06-15
Recent technological advances in continuous biological monitoring and personal exposure assessment have led to the collection of subject-specific functional data. A primary goal in such studies is to assess the relationship between the functional predictors and the functional responses. The historical functional linear model (HFLM) can be used to model such dependencies of the response on the history of the predictor values. An estimation procedure for the regression coefficients that uses a variety of regularization techniques is proposed. An approximation of the regression surface relating the predictor to the outcome by a finite-dimensional basis expansion is used, followed by penalization of the coefficients of the neighboring basis functions by restricting the size of the coefficient differences to be small. Penalties based on the absolute values of the basis function coefficient differences (corresponding to the LASSO) and the squares of these differences (corresponding to the penalized spline methodology) are studied. The fits are compared using an extension of the Akaike Information Criterion that combines the error variance estimate, degrees of freedom of the fit and the norm of the bases function coefficients. The performance of the proposed methods is evaluated via simulations. The LASSO penalty applied to the linearly transformed coefficients yields sparser representations of the estimated regression surface, while the quadratic penalty provides solutions with the smallest L(2)-norm of the basis functions coefficients. Finally, the new estimation procedure is applied to the analysis of the effects of occupational particulate matter (PM) exposure on the heart rate variability (HRV) in a cohort of boilermaker workers. Results suggest that the strongest association between PM exposure and HRV in these workers occurs as a result of point exposures to the increased levels of particulate matter corresponding to smoking breaks. PMID:18552972
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.
Validation of a heteroscedastic hazards regression model.
Wu, Hong-Dar Isaac; Hsieh, Fushing; Chen, Chen-Hsin
2002-03-01
A Cox-type regression model accommodating heteroscedasticity, with a power factor of the baseline cumulative hazard, is investigated for analyzing data with crossing hazards behavior. Since the approach of partial likelihood cannot eliminate the baseline hazard, an overidentified estimating equation (OEE) approach is introduced in the estimation procedure. It by-product, a model checking statistic, is presented to test for the overall adequacy of the heteroscedastic model. Further, under the heteroscedastic model setting, we propose two statistics to test the proportional hazards assumption. Implementation of this model is illustrated in a data analysis of a cancer clinical trial. PMID:11878222
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.
Convex Regression with Interpretable Sharp Partitions
Petersen, Ashley; Simon, Noah; Witten, Daniela
2016-01-01
We consider the problem of predicting an outcome variable on the basis of a small number of covariates, using an interpretable yet non-additive model. We propose convex regression with interpretable sharp partitions (CRISP) for this task. CRISP partitions the covariate space into blocks in a data-adaptive way, and fits a mean model within each block. Unlike other partitioning methods, CRISP is fit using a non-greedy approach by solving a convex optimization problem, resulting in low-variance fits. We explore the properties of CRISP, and evaluate its performance in a simulation study and on a housing price data set.
Learning regulatory programs by threshold SVD regression
Ma, Xin; Xiao, Luo; Wong, Wing Hung
2014-01-01
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. PMID:25331876
Weather adjustment using seemingly unrelated regression
Noll, T.A.
1995-05-01
Seemingly unrelated regression (SUR) is a system estimation technique that accounts for time-contemporaneous correlation between individual equations within a system of equations. SUR is suited to weather adjustment estimations when the estimation is: (1) composed of a system of equations and (2) the system of equations represents either different weather stations, different sales sectors or a combination of different weather stations and different sales sectors. SUR utilizes the cross-equation error values to develop more accurate estimates of the system coefficients than are obtained using ordinary least-squares (OLS) estimation. SUR estimates can be generated using a variety of statistical software packages including MicroTSP and SAS.
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.
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 convex ROC curves.
Lloyd, C J
2000-09-01
The performance of a diagnostic test is summarized by its receiver operating characteristic (ROC) curve. Under quite natural assumptions about the latent variable underlying the test, the ROC curve is convex. Empirical data on a test's performance often comes in the form of observed true positive and false positive relative frequencies under varying conditions. This paper describes a family of regression models for analyzing such data. The underlying ROC curves are specified by a quality parameter delta and a shape parameter mu and are guaranteed to be convex provided delta > 1. Both the position along the ROC curve and the quality parameter delta are modeled linearly with covariates at the level of the individual. The shape parameter mu enters the model through the link functions log(p mu) - log(1 - p mu) of a binomial regression and is estimated either by search or from an appropriate constructed variate. One simple application is to the meta-analysis of independent studies of the same diagnostic test, illustrated on some data of Moses, Shapiro, and Littenberg (1993). A second application, to so-called vigilance data, is given, where ROC curves differ across subjects and modeling of the position along the ROC curve is of primary interest. PMID:10985227
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.
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%.
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
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.
Regression testing in the TOTEM DCS
NASA Astrophysics Data System (ADS)
Rodríguez, F. Lucas; Atanassov, I.; Burkimsher, P.; Frost, O.; Taskinen, J.; Tulimaki, V.
2012-12-01
The Detector Control System of the TOTEM experiment at the LHC is built with the industrial product WinCC OA (PVSS). The TOTEM system is generated automatically through scripts using as input the detector Product Breakdown Structure (PBS) structure and its pinout connectivity, archiving and alarm metainformation, and some other heuristics based on the naming conventions. When those initial parameters and automation code are modified to include new features, the resulting PVSS system can also introduce side-effects. On a daily basis, a custom developed regression testing tool takes the most recent code from a Subversion (SVN) repository and builds a new control system from scratch. This system is exported in plain text format using the PVSS export tool, and compared with a system previously validated by a human. A report is sent to the developers with any differences highlighted, in readiness for validation and acceptance as a new stable version. This regression approach is not dependent on any development framework or methodology. This process has been satisfactory during several months, proving to be a very valuable tool before deploying new versions in the production systems.
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.
Multivariate Regression with Block-structured Predictors
NASA Astrophysics Data System (ADS)
Ye, Saier
We study the problem of predicting multiple responses with a common set of predicting variables. Applying generalized Ordinary Least Squares (OLS) criterion on the responses altogether is practically equivalent to OLS estimation on the responses separately. Possible correlations between the response variables are overlooked. In order to take advantage of these interrelationships, Reduced-Rank Regression (RRR) imposes rank constraint on the coefficient matrix. RRR constructs latent factors from the original predicting variables, and the latent factors are the effective predictors. RRR reduces number of parameters to be estimated, and improves estimation efficiency. In the present work, we explore a novel regression model to incorporate "block-structured" predicting variables, where the predictors can be naturally partitioned into several groups or blocks. Variables in the same block share similar characteristics. It is reasonable to assume that in addition to an overall impact, predictors also have block-specific effects on the responses. Furthermore, we impose rank constraints on the coefficient matrices. In our framework, we construct two types of latent factors that drive the variation in the responses. We have joint factors, which are formed by all predictors across all blocks; and individual factors, which are formed by variables within individual blocks. The proposed method exceeds RRR in terms of prediction accuracy and ease of interpretation in the presence of block structure in the predicting variables.
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. PMID:16240612
NASA Astrophysics Data System (ADS)
Wheeler, David; Tiefelsdorf, Michael
2005-06-01
Present methodological research on geographically weighted regression (GWR) focuses primarily on extensions of the basic GWR model, while ignoring well-established diagnostics tests commonly used in standard global regression analysis. This paper investigates multicollinearity issues surrounding the local GWR coefficients at a single location and the overall correlation between GWR coefficients associated with two different exogenous variables. Results indicate that the local regression coefficients are potentially collinear even if the underlying exogenous variables in the data generating process are uncorrelated. Based on these findings, applied GWR research should practice caution in substantively interpreting the spatial patterns of local GWR coefficients. An empirical disease-mapping example is used to motivate the GWR multicollinearity problem. Controlled experiments are performed to systematically explore coefficient dependency issues in GWR. These experiments specify global models that use eigenvectors from a spatial link matrix as exogenous variables.
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.
Sibling dilution hypothesis: a regression surface analysis.
Marjoribanks, K
2001-08-01
This study examined relationships between sibship size (the number of children in a family), birth order, and measures of academic performance, academic self-concept, and educational aspirations at different levels of family educational resources. As part of a national longitudinal study of Australian secondary school students data were collected from 2,530 boys and 2,450 girls in Years 9 and 10. Regression surfaces were constructed from models that included terms to account for linear, interaction, and curvilinear associations among the variables. Analysis suggests the general propositions (a) family educational resources have significant associations with children's school-related outcomes at different levels of sibling variables, the relationships for girls being curvilinear, and (b) sibling variables continue to have small significant associations with affective and cognitive outcomes, after taking into account variations in family educational resources. That is, the investigation provides only partial support for the sibling dilution hypothesis. PMID:11729548
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.
Robust Mediation Analysis Based on Median Regression
Yuan, Ying; MacKinnon, David P.
2014-01-01
Mediation analysis has many applications in psychology and the social sciences. The most prevalent methods typically assume that the error distribution is normal and homoscedastic. However, this assumption may rarely be met in practice, which can affect the validity of the mediation analysis. To address this problem, we propose robust mediation analysis based on median regression. Our approach is robust to various departures from the assumption of homoscedasticity and normality, including heavy-tailed, skewed, contaminated, and heteroscedastic distributions. Simulation studies show that under these circumstances, the proposed method is more efficient and powerful than standard mediation analysis. We further extend the proposed robust method to multilevel mediation analysis, and demonstrate through simulation studies that the new approach outperforms the standard multilevel mediation analysis. We illustrate the proposed method using data from a program designed to increase reemployment and enhance mental health of job seekers. PMID:24079925
Improving phylogenetic regression under complex evolutionary models.
Mazel, Florent; Davies, T Jonathan; Georges, Damien; Lavergne, Sébastien; Thuiller, Wilfried; Peres-NetoO, Pedro R
2016-02-01
Phylogenetic Generalized Least Square (PGLS) is the tool of choice among phylogenetic comparative methods to measure the correlation between species features such as morphological and life-history traits or niche characteristics. In its usual form, it assumes that the residual variation follows a homogenous model of evolution across the branches of the phylogenetic tree. Since a homogenous model of evolution is unlikely to be realistic in nature, we explored the robustness of the phylogenetic regression when this assumption is violated. We did so by simulating a set of traits under various heterogeneous models of evolution, and evaluating the statistical performance (type I error [the percentage of tests based on samples that incorrectly rejected a true null hypothesis] and power [the percentage of tests that correctly rejected a false null hypothesis]) of classical phylogenetic regression. We found that PGLS has good power but unacceptable type I error rates. This finding is important since this method has been increasingly used in comparative analyses over the last decade. To address this issue, we propose a simple solution based on transforming the underlying variance-covariance matrix to adjust for model heterogeneity within PGLS. We suggest that heterogeneous rates of evolution might be particularly prevalent in large phylogenetic trees, while most current approaches assume a homogenous rate of evolution. Our analysis demonstrates that overlooking rate heterogeneity can result in inflated type I errors, thus misleading comparative analyses. We show that it is possible to correct for this bias even when the underlying model of evolution is not known a priori. PMID:27145604
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.
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
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)…
Technological Forecasting with a Multiple Regression Analysis Approach.
ERIC Educational Resources Information Center
Luftig, Jeffrey T.; Norton, Willis P.
1981-01-01
This article examines simple and multiple regression analysis as forecasting tools, and details the process by which multiple regression analysis may be used to increase the accuracy of the technology forecast. (CT)
Logistic Regression: Going beyond Point-and-Click.
ERIC Educational Resources Information Center
King, Jason E.
A review of the literature reveals that important statistical algorithms and indices pertaining to logistic regression are being underused. This paper describes logistic regression in comparison with discriminant analysis and linear regression, and suggests that some techniques only accessible through computer syntax should be consulted in…
Heterogeneous Treatment Effects: What Does a Regression Estimate?
ERIC Educational Resources Information Center
Rhodes, William
2010-01-01
Regressions that control for confounding factors are the workhorse of evaluation research. When treatment effects are heterogeneous, however, the workhorse regression leads to estimated treatment effects that lack behavioral interpretations even when the selection on observables assumption holds. Regressions that use propensity scores as weights…
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…
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…
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
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.
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.
Sparse Regression as a Sparse Eigenvalue Problem
NASA Technical Reports Server (NTRS)
Moghaddam, Baback; Gruber, Amit; Weiss, Yair; Avidan, Shai
2008-01-01
We extend the l0-norm "subspectral" algorithms for sparse-LDA [5] and sparse-PCA [6] to general quadratic costs such as MSE in linear (kernel) regression. The resulting "Sparse Least Squares" (SLS) problem is also NP-hard, by way of its equivalence to a rank-1 sparse eigenvalue problem (e.g., binary sparse-LDA [7]). Specifically, for a general quadratic cost we use a highly-efficient technique for direct eigenvalue computation using partitioned matrix inverses which leads to dramatic x103 speed-ups over standard eigenvalue decomposition. This increased efficiency mitigates the O(n4) scaling behaviour that up to now has limited the previous algorithms' utility for high-dimensional learning problems. Moreover, the new computation prioritizes the role of the less-myopic backward elimination stage which becomes more efficient than forward selection. Similarly, branch-and-bound search for Exact Sparse Least Squares (ESLS) also benefits from partitioned matrix inverse techniques. Our Greedy Sparse Least Squares (GSLS) generalizes Natarajan's algorithm [9] also known as Order-Recursive Matching Pursuit (ORMP). Specifically, the forward half of GSLS is exactly equivalent to ORMP but more efficient. By including the backward pass, which only doubles the computation, we can achieve lower MSE than ORMP. Experimental comparisons to the state-of-the-art LARS algorithm [3] show forward-GSLS is faster, more accurate and more flexible in terms of choice of regularization
Competing Risk Regression Models for Epidemiologic Data
Cole, Stephen R.; Gange, Stephen J.
2009-01-01
Competing events can preclude the event of interest from occurring in epidemiologic data and can be analyzed by using extensions of survival analysis methods. In this paper, the authors outline 3 regression approaches for estimating 2 key quantities in competing risks analysis: the cause-specific relative hazard (csRH) and the subdistribution relative hazard (sdRH). They compare and contrast the structure of the risk sets and the interpretation of parameters obtained with these methods. They also demonstrate the use of these methods with data from the Women's Interagency HIV Study established in 1993, treating time to initiation of highly active antiretroviral therapy or to clinical disease progression as competing events. In our example, women with an injection drug use history were less likely than those without a history of injection drug use to initiate therapy prior to progression to acquired immunodeficiency syndrome or death by both measures of association (csRH = 0.67, 95% confidence interval: 0.57, 0.80 and sdRH = 0.60, 95% confidence interval: 0.50, 0.71). Moreover, the relative hazards for disease progression prior to treatment were elevated (csRH = 1.71, 95% confidence interval: 1.37, 2.13 and sdRH = 2.01, 95% confidence interval: 1.62, 2.51). Methods for competing risks should be used by epidemiologists, with the choice of method guided by the scientific question. PMID:19494242
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
2016-04-01
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. PMID:27053774
Flexible regression models over river networks
O’Donnell, David; Rushworth, Alastair; Bowman, Adrian W; Marian Scott, E; Hallard, Mark
2014-01-01
Many statistical models are available for spatial data but the vast majority of these assume that spatial separation can be measured by Euclidean distance. Data which are collected over river networks constitute a notable and commonly occurring exception, where distance must be measured along complex paths and, in addition, account must be taken of the relative flows of water into and out of confluences. Suitable models for this type of data have been constructed based on covariance functions. The aim of the paper is to place the focus on underlying spatial trends by adopting a regression formulation and using methods which allow smooth but flexible patterns. Specifically, kernel methods and penalized splines are investigated, with the latter proving more suitable from both computational and modelling perspectives. In addition to their use in a purely spatial setting, penalized splines also offer a convenient route to the construction of spatiotemporal models, where data are available over time as well as over space. Models which include main effects and spatiotemporal interactions, as well as seasonal terms and interactions, are constructed for data on nitrate pollution in the River Tweed. The results give valuable insight into the changes in water quality in both space and time. PMID:25653460
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
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. PMID:16877249
PM10 forecasting using clusterwise regression
NASA Astrophysics Data System (ADS)
Poggi, Jean-Michel; Portier, Bruno
2011-12-01
In this paper, we are interested in the statistical forecasting of the daily mean PM10 concentration. Hourly concentrations of PM10 have been measured in the city of Rouen, in Haute-Normandie, France. Located at northwest of Paris, near the south side of Manche sea and heavily industrialised. We consider three monitoring stations reflecting the diversity of situations: an urban background station, a traffic station and an industrial station near the cereal harbour of Rouen. We have focused our attention on data for the months that register higher values, from December to March, on years 2004-2009. The models are obtained from the winter days of the four seasons 2004/2005 to 2007/2008 (training data) and then the forecasting performance is evaluated on the winter days of the season 2008/2009 (test data). We show that it is possible to accurately forecast the daily mean concentration by fitting a function of meteorological predictors and the average concentration measured on the previous day. The values of observed meteorological variables are used for fitting the models and are also considered for the test data. We have compared the forecasts produced by three different methods: persistence, generalized additive nonlinear models and clusterwise linear regression models. This last method gives very impressive results and the end of the paper tries to analyze the reasons of such a good behavior.
Sliced Inverse Regression for Time Series Analysis
NASA Astrophysics Data System (ADS)
Chen, Li-Sue
1995-11-01
In this thesis, general nonlinear models for time series data are considered. A basic form is x _{t} = f(beta_sp{1} {T}X_{t-1},beta_sp {2}{T}X_{t-1},... , beta_sp{k}{T}X_ {t-1},varepsilon_{t}), where x_{t} is an observed time series data, X_{t } is the first d time lag vector, (x _{t},x_{t-1},... ,x _{t-d-1}), f is an unknown function, beta_{i}'s are unknown vectors, varepsilon_{t }'s are independent distributed. Special cases include AR and TAR models. We investigate the feasibility applying SIR/PHD (Li 1990, 1991) (the sliced inverse regression and principal Hessian methods) in estimating beta _{i}'s. PCA (Principal component analysis) is brought in to check one critical condition for SIR/PHD. Through simulation and a study on 3 well -known data sets of Canadian lynx, U.S. unemployment rate and sunspot numbers, we demonstrate how SIR/PHD can effectively retrieve the interesting low-dimension structures for time series data.
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. PMID:26934999
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.
Comparison of Logistic Regression and Linear Regression in Modeling Percentage Data
Zhao, Lihui; Chen, Yuhuan; Schaffner, Donald W.
2001-01-01
Percentage is widely used to describe different results in food microbiology, e.g., probability of microbial growth, percent inactivated, and percent of positive samples. Four sets of percentage data, percent-growth-positive, germination extent, probability for one cell to grow, and maximum fraction of positive tubes, were obtained from our own experiments and the literature. These data were modeled using linear and logistic regression. Five methods were used to compare the goodness of fit of the two models: percentage of predictions closer to observations, range of the differences (predicted value minus observed value), deviation of the model, linear regression between the observed and predicted values, and bias and accuracy factors. Logistic regression was a better predictor of at least 78% of the observations in all four data sets. In all cases, the deviation of logistic models was much smaller. The linear correlation between observations and logistic predictions was always stronger. Validation (accomplished using part of one data set) also demonstrated that the logistic model was more accurate in predicting new data points. Bias and accuracy factors were found to be less informative when evaluating models developed for percentage data, since neither of these indices can compare predictions at zero. Model simplification for the logistic model was demonstrated with one data set. The simplified model was as powerful in making predictions as the full linear model, and it also gave clearer insight in determining the key experimental factors. PMID:11319091
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]. PMID:26539846
2014-01-01
Background In biomedical research, response variables are often encountered which have bounded support on the open unit interval - (0,1). Traditionally, researchers have attempted to estimate covariate effects on these types of response data using linear regression. Alternative modelling strategies may include: beta regression, variable-dispersion beta regression, and fractional logit regression models. This study employs a Monte Carlo simulation design to compare the statistical properties of the linear regression model to that of the more novel beta regression, variable-dispersion beta regression, and fractional logit regression models. Methods In the Monte Carlo experiment we assume a simple two sample design. We assume observations are realizations of independent draws from their respective probability models. The randomly simulated draws from the various probability models are chosen to emulate average proportion/percentage/rate differences of pre-specified magnitudes. Following simulation of the experimental data we estimate average proportion/percentage/rate differences. We compare the estimators in terms of bias, variance, type-1 error and power. Estimates of Monte Carlo error associated with these quantities are provided. Results If response data are beta distributed with constant dispersion parameters across the two samples, then all models are unbiased and have reasonable type-1 error rates and power profiles. If the response data in the two samples have different dispersion parameters, then the simple beta regression model is biased. When the sample size is small (N0 = N1 = 25) linear regression has superior type-1 error rates compared to the other models. Small sample type-1 error rates can be improved in beta regression models using bias correction/reduction methods. In the power experiments, variable-dispersion beta regression and fractional logit regression models have slightly elevated power compared to linear regression models. Similar
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
Spontaneous Regression of a Carcinoid Tumor following Pregnancy
Sewpaul, A.; Bargiela, D.; James, A.; Johnson, S. J.; French, J. J.
2014-01-01
We present a case of spontaneous regression of a neuroendocrine tumor following pregnancy in the absence of chemotherapy, radiotherapy, or alternative medicine (including herbal medicine). The diagnosis of a nonsecretory carcinoid tumor was confirmed using CT imaging, octreotide scan, and histology. Furthermore, serial imaging has demonstrated spontaneous regression of the carcinoid suggesting that pregnancy did not worsen the course of the disease but instead may have contributed to tumour regression. We discuss mechanisms underlying tumour regression and the possible effect of pregnancy on these processes. PMID:25587468
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
SPReM: Sparse Projection Regression Model For High-dimensional Linear Regression *
Sun, Qiang; Zhu, Hongtu; Liu, Yufeng; Ibrahim, Joseph G.
2014-01-01
The aim of this paper is to develop a sparse projection regression modeling (SPReM) framework to perform multivariate regression modeling with a large number of responses and a multivariate covariate of interest. We propose two novel heritability ratios to simultaneously perform dimension reduction, response selection, estimation, and testing, while explicitly accounting for correlations among multivariate responses. Our SPReM is devised to specifically address the low statistical power issue of many standard statistical approaches, such as the Hotelling’s T2 test statistic or a mass univariate analysis, for high-dimensional data. We formulate the estimation problem of SPREM as a novel sparse unit rank projection (SURP) problem and propose a fast optimization algorithm for SURP. Furthermore, we extend SURP to the sparse multi-rank projection (SMURP) by adopting a sequential SURP approximation. Theoretically, we have systematically investigated the convergence properties of SURP and the convergence rate of SURP estimates. Our simulation results and real data analysis have shown that SPReM out-performs other state-of-the-art methods. PMID:26527844
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
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…
A Comparison of Moderated Regression Techniques Considering Strength of Effect.
ERIC Educational Resources Information Center
Darrow, Arthur L.; Kahl, Douglas R.
1982-01-01
Compared the traditional moderated regression technique with a technique designed to increase the probability of indication of a moderator variable. Results indicated that detection of moderator variables is dependent on their strength. A higher probability of detecting a moderator exists if the interaction is entered into the regression first.…
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
A Regression Equation for Determining the Dimensionality of Data.
ERIC Educational Resources Information Center
Keeling, Kellie B.
2000-01-01
Developed a new regression equation to estimate the mean value of eigenvalues in parallel analysis and studied the performance of the equation in comparison with previously published regression equations through simulation. Performance of the new equation was comparable to that of the LCHF equation of G. Lautenschlager and others (1989). (SLD)
Population-Sample Regression in the Estimation of Population Proportions
ERIC Educational Resources Information Center
Weitzman, R. A.
2006-01-01
Focusing on a single sample obtained randomly with replacement from a single population, this article examines the regression of population on sample proportions and develops an unbiased estimator of the square of the correlation between them. This estimator turns out to be the regression coefficient. Use of the squared-correlation estimator as a…
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…
[Regression and revitalization in hypnosis. Doubts and certainties, therapeutic utility].
Granone, F
1981-05-12
The difference between age regression and revification is pointed out and the neurophysiological and psychological bases of hypermnesia of the past are discussed. Moreover, mental, neurological, somatic and visceral symptomatology of revification, the usual techniques to obtain it and its therapeutical usefulness are described. Possible artifacts of age regression and methods to avoid then are then presented. PMID:7231772
Augmenting Data with Published Results in Bayesian Linear Regression
ERIC Educational Resources Information Center
de Leeuw, Christiaan; Klugkist, Irene
2012-01-01
In most research, linear regression analyses are performed without taking into account published results (i.e., reported summary statistics) of similar previous studies. Although the prior density in Bayesian linear regression could accommodate such prior knowledge, formal models for doing so are absent from the literature. The goal of this…
Who Will Win?: Predicting the Presidential Election Using Linear Regression
ERIC Educational Resources Information Center
Lamb, John H.
2007-01-01
This article outlines a linear regression activity that engages learners, uses technology, and fosters cooperation. Students generated least-squares linear regression equations using TI-83 Plus[TM] graphing calculators, Microsoft[C] Excel, and paper-and-pencil calculations using derived normal equations to predict the 2004 presidential election.…
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…
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…
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...
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…
The Importance of Structure Coefficients in Regression Research.
ERIC Educational Resources Information Center
Thompson, Bruce; Borrello, Gloria M.
1985-01-01
Multiple regression analysis is frequently being employed in experimental and non-experimental research. However, when data include predictor variables that are correlated, some regression results can become difficult to interpret. This paper presents a study to provide a demonstration that structure coefficients may be useful in these cases.…
The Variance Normalization Method of Ridge Regression Analysis.
ERIC Educational Resources Information Center
Bulcock, J. W.; And Others
The testing of contemporary sociological theory often calls for the application of structural-equation models to data which are inherently collinear. It is shown that simple ridge regression, which is commonly used for controlling the instability of ordinary least squares regression estimates in ill-conditioned data sets, is not a legitimate…
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…
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 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…
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...
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…
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…
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. PMID
Regression of posterior uveal melanomas following cobalt-60 plaque radiotherapy
Cruess, A.F.; Augsburger, J.J.; Shields, J.A.; Brady, L.W.; Markoe, A.M.; Day, J.L.
1984-12-01
A method has been devised for evaluating the rate and extent of regression of the first 100 consecutive patients with a posterior uveal melanoma that had been managed by Cobalt-60 plaque radiotherapy at Wills Eye Hospital. It was found that the average posterior uveal melanoma in the series did not regress rapidly to a flat, depigmented scar but shrank slowly and persisted as a residual mass approximately 50% of the thickness of the original tumor at 54 months following Cobalt-60 plaque radiotherapy. The authors also found that the rate and extent of regression of the tumors in patients who subsequently developed metastatic melanoma were not appreciably different from the rate and extent of regression of the tumors in patients who remained well systemically. These observations indicate that the rate and extent of regression of posterior uveal melanomas following Cobalt-60 plaque radiotherapy are poor indicators of the prognosis of the affected patients for subsequent development of clinical metastatic disease.
Construction cost estimation of municipal incinerators by fuzzy linear regression
Chang, N.B.; Chen, Y.L.; Yang, H.H.
1996-12-31
Regression analysis has been widely used in engineering cost estimation. It is recognized that the fuzzy structure in cost estimation is a different type of uncertainty compared to the measurement error in the least-squares regression modeling. Hence, the uncertainties encountered in many events of construction and operating costs estimation and prediction cannot be fully depicted by conventional least-squares regression models. This paper presents a construction cost analysis of municipal incinerators by the techniques of fuzzy linear regression. A thorough investigation of construction costs in the Taiwan Resource Recovery Project was conducted based on design parameters such as design capacity, type of grate system, and the selected air pollution control process. The focus has been placed upon the methodology for dealing with the heterogeneity phenomenon of a set of observations for which regression is evaluated.
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…
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…
Calculation of Solar Radiation by Using Regression Methods
NASA Astrophysics Data System (ADS)
Kızıltan, Ö.; Şahin, M.
2016-04-01
In this study, solar radiation was estimated at 53 location over Turkey with varying climatic conditions using the Linear, Ridge, Lasso, Smoother, Partial least, KNN and Gaussian process regression methods. The data of 2002 and 2003 years were used to obtain regression coefficients of relevant methods. The coefficients were obtained based on the input parameters. Input parameters were month, altitude, latitude, longitude and landsurface temperature (LST).The values for LST were obtained from the data of the National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) satellite. Solar radiation was calculated using obtained coefficients in regression methods for 2004 year. The results were compared statistically. The most successful method was Gaussian process regression method. The most unsuccessful method was lasso regression method. While means bias error (MBE) value of Gaussian process regression method was 0,274 MJ/m2, root mean square error (RMSE) value of method was calculated as 2,260 MJ/m2. The correlation coefficient of related method was calculated as 0,941. Statistical results are consistent with the literature. Used the Gaussian process regression method is recommended for other studies.
Shrinkage regression-based methods for microarray missing value imputation
2013-01-01
Background Missing values commonly occur in the microarray data, which usually contain more than 5% missing values with up to 90% of genes affected. Inaccurate missing value estimation results in reducing the power of downstream microarray data analyses. Many types of methods have been developed to estimate missing values. Among them, the regression-based methods are very popular and have been shown to perform better than the other types of methods in many testing microarray datasets. Results To further improve the performances of the regression-based methods, we propose shrinkage regression-based methods. Our methods take the advantage of the correlation structure in the microarray data and select similar genes for the target gene by Pearson correlation coefficients. Besides, our methods incorporate the least squares principle, utilize a shrinkage estimation approach to adjust the coefficients of the regression model, and then use the new coefficients to estimate missing values. Simulation results show that the proposed methods provide more accurate missing value estimation in six testing microarray datasets than the existing regression-based methods do. Conclusions Imputation of missing values is a very important aspect of microarray data analyses because most of the downstream analyses require a complete dataset. Therefore, exploring accurate and efficient methods for estimating missing values has become an essential issue. Since our proposed shrinkage regression-based methods can provide accurate missing value estimation, they are competitive alternatives to the existing regression-based methods. PMID:24565159
Background stratified Poisson regression analysis of cohort data
Langholz, Bryan
2012-01-01
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. PMID:22193911
Impact of multicollinearity on small sample hydrologic regression models
NASA Astrophysics Data System (ADS)
Kroll, Charles N.; Song, Peter
2013-06-01
Often hydrologic regression models are developed with ordinary least squares (OLS) procedures. The use of OLS with highly correlated explanatory variables produces multicollinearity, which creates highly sensitive parameter estimators with inflated variances and improper model selection. It is not clear how to best address multicollinearity in hydrologic regression models. Here a Monte Carlo simulation is developed to compare four techniques to address multicollinearity: OLS, OLS with variance inflation factor screening (VIF), principal component regression (PCR), and partial least squares regression (PLS). The performance of these four techniques was observed for varying sample sizes, correlation coefficients between the explanatory variables, and model error variances consistent with hydrologic regional regression models. The negative effects of multicollinearity are magnified at smaller sample sizes, higher correlations between the variables, and larger model error variances (smaller R2). The Monte Carlo simulation indicates that if the true model is known, multicollinearity is present, and the estimation and statistical testing of regression parameters are of interest, then PCR or PLS should be employed. If the model is unknown, or if the interest is solely on model predictions, is it recommended that OLS be employed since using more complicated techniques did not produce any improvement in model performance. A leave-one-out cross-validation case study was also performed using low-streamflow data sets from the eastern United States. Results indicate that OLS with stepwise selection generally produces models across study regions with varying levels of multicollinearity that are as good as biased regression techniques such as PCR and PLS.
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. PMID:22193911
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.
Linear regression analysis of survival data with missing censoring indicators.
Wang, Qihua; Dinse, Gregg E
2011-04-01
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
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.
Poor smokers, poor quitters, and cigarette tax regressivity.
Remler, Dahlia K
2004-02-01
The traditional view that excise taxes are regressive has been challenged. I document the history of the term regressive tax, show that traditional definitions have always found cigarette taxes to be regressive, and illustrate the implications of the greater price responsiveness observed among the poor. I explain the different definitions of tax burden: accounting, welfare-based willingness to pay, and welfare-based time inconsistent. Progressivity (equity across income groups) is sensitive to the way in which tax burden is assessed. Analysis of horizontal equity (fairness within a given income group) shows that cigarette taxes heavily burden poor smokers who do not quit, no matter how tax burden is assessed. PMID:14759931
Sparse logistic regression with Lp penalty for biomarker identification.
Liu, Zhenqiu; Jiang, Feng; Tian, Guoliang; Wang, Suna; Sato, Fumiaki; Meltzer, Stephen J; Tan, Ming
2007-01-01
In this paper, we propose a novel method for sparse logistic regression with non-convex regularization Lp (p <1). Based on smooth approximation, we develop several fast algorithms for learning the classifier that is applicable to high dimensional dataset such as gene expression. To the best of our knowledge, these are the first algorithms to perform sparse logistic regression with an Lp and elastic net (Le) penalty. The regularization parameters are decided through maximizing the area under the ROC curve (AUC) of the test data. Experimental results on methylation and microarray data attest the accuracy, sparsity, and efficiency of the proposed algorithms. Biomarkers identified with our methods are compared with that in the literature. Our computational results show that Lp Logistic regression (p <1) outperforms the L1 logistic regression and SCAD SVM. Software is available upon request from the first author. PMID:17402921
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 ...
Role of epithelial hyperplasia in regression following photorefractive keratectomy.
Gauthier, C. A.; Holden, B. A.; Epstein, D.; Tengroth, B.; Fagerholm, P.; Hamberg-Nyström, H.
1996-01-01
AIM--To determine the relation between epithelial hyperplasia and regression of effect after photorefractive keratectomy (PRK). METHODS--Seventy unilaterally treated patients with PRK were examined. All eyes had been treated with the Summit excimer laser 27 (SD 7) months previously with zone diameters of 4.1 to 5.0 mm. The untreated fellow eyes served as controls. Epithelial thickness was measured centrally with a thin slit optical pachometer and manifest subjective refraction was performed. RESULTS--The epithelium was 21% thicker in the treated eye (p < 0.0001). The relation between refractive regression and epithelial hyperplasia was significant (r = 0.41; p < 0.001). CONCLUSIONS--Epithelial hyperplasia after PRK correlated with the myopic shift (including hyperopia reduction) after treatment with the Summit laser. A model is proposed suggesting that both subepithelial and epithelial layers contribute to regression in the Summit treated eyes with 18 microns of epithelial hyperplasia contributing each dioptre of regression. PMID:8759267
PRINCIPAL COMPONENTS ANALYSIS AND PARTIAL LEAST SQUARES REGRESSION
The mathematics behind the techniques of principal component analysis and partial least squares regression is presented in detail, starting from the appropriate extreme conditions. he meaning of the resultant vectors and many of their mathematical interrelationships are also pres...
Hierarchical regression for epidemiologic analyses of multiple exposures.
Greenland, S
1994-01-01
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 "semi-Bayes" 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. PMID:7851328
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
A VBA-based Simulation for Teaching Simple Linear Regression
ERIC Educational Resources Information Center
Jones, Gregory Todd; Hagtvedt, Reidar; Jones, Kari
2004-01-01
In spite of the name, simple linear regression presents a number of conceptual difficulties, particularly for introductory students. This article describes a simulation tool that provides a hands-on method for illuminating the relationship between parameters and sample statistics.
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
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.
Computing measures of explained variation for logistic regression models.
Mittlböck, M; Schemper, M
1999-01-01
The proportion of explained variation (R2) is frequently used in the general linear model but in logistic regression no standard definition of R2 exists. We present a SAS macro which calculates two R2-measures based on Pearson and on deviance residuals for logistic regression. Also, adjusted versions for both measures are given, which should prevent the inflation of R2 in small samples. PMID:10195643
Robust regression on noisy data for fusion scaling laws
NASA Astrophysics Data System (ADS)
Verdoolaege, Geert
2014-11-01
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.
Spontaneous regression in advanced squamous cell lung carcinoma
Park, Yeon Hee; Park, Bo Mi; Park, Se Yeon; Choi, Jae Woo; Kim, Sun Young; Kim, Ju Ock; Jung, Sung Soo; Park, Hee Sun; Moon, Jae Young
2016-01-01
Spontaneous regression of malignant tumors is rare especially of lung tumor and biological mechanism of such remission has not been addressed. We report the case of a 79-year-old Korean patient with non-small cell lung cancer, squamous cell cancer with a right hilar tumor and multiple lymph nodes, lung to lung metastasis that spontaneously regressed without any therapies. He has sustained partial remission state for one year and eight months after the first histological diagnosis. PMID:27076978
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.
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.
Ballistic limit curve regression for Freedom Station orbital debris shields
NASA Technical Reports Server (NTRS)
Jolly, William H.; Williamsen, Joel W.
1992-01-01
A procedure utilized at Marshall Space Flight Center to formulate ballistic limit curves for the Space Station Freedom's manned module orbital debris shields is presented. A stepwise linear least squares regression method similar to that employed by Burch (1967) is used to relate a penetration parameter to various projectile and target descriptors. A stepwise regression was also conducted with the model reduced to lower forms, thus eliminating the effects of generalized assumptions.
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. PMID:26529689
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. PMID:26609741
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
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
Accounting for the correlation between fellow eyes in regression analysis.
Glynn, R J; Rosner, B
1992-03-01
Regression techniques that appropriately use all available eyes have infrequently been applied in the ophthalmologic literature, despite advances both in the development of statistical models and in the availability of computer software to fit these models. We considered the general linear model and polychotomous logistic regression approaches of Rosner and the estimating equation approach of Liang and Zeger, applied to both linear and logistic regression. Methods were illustrated with the use of two real data sets: (1) impairment of visual acuity in patients with retinitis pigmentosa and (2) overall visual field impairment in elderly patients evaluated for glaucoma. We discuss the interpretation of coefficients from these models and the advantages of these approaches compared with alternative approaches, such as treating individuals rather than eyes as the unit of analysis, separate regression analyses of right and left eyes, or utilization of ordinary regression techniques without accounting for the correlation between fellow eyes. Specific advantages include enhanced statistical power, more interpretable regression coefficients, greater precision of estimation, and less sensitivity to missing data for some eyes. We concluded that these models should be used more frequently in ophthalmologic research, and we provide guidelines for choosing between alternative models. PMID:1543458
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. PMID:22449035
Counting people with low-level features and Bayesian regression.
Chan, Antoni B; Vasconcelos, Nuno
2012-04-01
An approach to the problem of estimating the size of inhomogeneous crowds, which are composed of pedestrians that travel in different directions, without using explicit object segmentation or tracking is proposed. Instead, the crowd is segmented into components of homogeneous motion, using the mixture of dynamic-texture motion model. A set of holistic low-level features is extracted from each segmented region, and a function that maps features into estimates of the number of people per segment is learned with Bayesian regression. Two Bayesian regression models are examined. The first is a combination of Gaussian process regression with a compound kernel, which accounts for both the global and local trends of the count mapping but is limited by the real-valued outputs that do not match the discrete counts. We address this limitation with a second model, which is based on a Bayesian treatment of Poisson regression that introduces a prior distribution on the linear weights of the model. Since exact inference is analytically intractable, a closed-form approximation is derived that is computationally efficient and kernelizable, enabling the representation of nonlinear functions. An approximate marginal likelihood is also derived for kernel hyperparameter learning. The two regression-based crowd counting methods are evaluated on a large pedestrian data set, containing very distinct camera views, pedestrian traffic, and outliers, such as bikes or skateboarders. Experimental results show that regression-based counts are accurate regardless of the crowd size, outperforming the count estimates produced by state-of-the-art pedestrian detectors. Results on 2 h of video demonstrate the efficiency and robustness of the regression-based crowd size estimation over long periods of time. PMID:22020684
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.
GLOBALLY ADAPTIVE QUANTILE REGRESSION WITH ULTRA-HIGH DIMENSIONAL DATA
Zheng, Qi; Peng, Limin; He, Xuming
2015-01-01
Quantile regression has become a valuable tool to analyze heterogeneous covaraite-response associations that are often encountered in practice. The development of quantile regression methodology for high dimensional covariates primarily focuses on examination of model sparsity at a single or multiple quantile levels, which are typically prespecified ad hoc by the users. The resulting models may be sensitive to the specific choices of the quantile levels, leading to difficulties in interpretation and erosion of confidence in the results. In this article, we propose a new penalization framework for quantile regression in the high dimensional setting. We employ adaptive L1 penalties, and more importantly, propose a uniform selector of the tuning parameter for a set of quantile levels to avoid some of the potential problems with model selection at individual quantile levels. Our proposed approach achieves consistent shrinkage of regression quantile estimates across a continuous range of quantiles levels, enhancing the flexibility and robustness of the existing penalized quantile regression methods. Our theoretical results include the oracle rate of uniform convergence and weak convergence of the parameter estimators. We also use numerical studies to confirm our theoretical findings and illustrate the practical utility of our proposal. PMID:26604424
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. PMID:26426798
Evaluation of regression-based 3-D shoulder rhythms.
Xu, Xu; Dickerson, Clark R; Lin, Jia-Hua; McGorry, Raymond W
2016-08-01
The movements of the humerus, the clavicle, and the scapula are not completely independent. The coupled pattern of movement of these bones is called the shoulder rhythm. To date, multiple studies have focused on providing regression-based 3-D shoulder rhythms, in which the orientations of the clavicle and the scapula are estimated by the orientation of the humerus. In this study, six existing regression-based shoulder rhythms were evaluated by an independent dataset in terms of their predictability. The datasets include the measured orientations of the humerus, the clavicle, and the scapula of 14 participants over 118 different upper arm postures. The predicted orientations of the clavicle and the scapula were derived from applying those regression-based shoulder rhythms to the humerus orientation. The results indicated that none of those regression-based shoulder rhythms provides consistently more accurate results than the others. For all the joint angles and all the shoulder rhythms, the RMSE are all greater than 5°. Among those shoulder rhythms, the scapula lateral/medial rotation has the strongest correlation between the predicted and the measured angles, while the other thoracoclavicular and thoracoscapular bone orientation angles only showed a weak to moderate correlation. Since the regression-based shoulder rhythm has been adopted for shoulder biomechanical models to estimate shoulder muscle activities and structure loads, there needs to be further investigation on how the predicted error from the shoulder rhythm affects the output of the biomechanical model. PMID:26253991
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
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.
Fuel Regression Rate Behavior of CAMUI Hybrid Rocket
NASA Astrophysics Data System (ADS)
Kaneko, Yudai; Itoh, Mitsunori; Kakikura, Akihito; Mori, Kazuhiro; Uejima, Kenta; Nakashima, Takuji; Wakita, Masashi; Totani, Tsuyoshi; Oshima, Nobuyuki; Nagata, Harunori
A series of static firing tests was conducted to investigate the fuel regression characteristics of a Cascaded Multistage Impinging-jet (CAMUI) type hybrid rocket motor. A CAMUI type hybrid rocket uses the combination of liquid oxygen and a fuel grain made of polyethylene as a propellant. The collision distance divided by the port diameter, H/D, was varied to investigate the effect of the grain geometry on the fuel regression rate. As a result, the H/D geometry has little effect on the regression rate near the stagnation point, where the heat transfer coefficient is high. On the contrary, the fuel regression rate decreases near the circumference of the forward-end face and the backward-end face of fuel blocks. Besides the experimental approaches, a method of computational fluid dynamics clarified the heat transfer distribution on the grain surface with various H/D geometries. The calculation shows the decrease of the flow velocity due to the increase of H/D on the area where the fuel regression rate decreases with the increase of H/D. To estimate the exact fuel consumption, which is necessary to design a fuel grain, real-time measurement by an ultrasonic pulse-echo method was performed.
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.
Rethinking the linear regression model for spatial ecological data.
Wagner, Helene H
2013-11-01
The linear regression model, with its numerous extensions including multivariate ordination, is fundamental to quantitative research in many disciplines. However, spatial or temporal structure in the data may invalidate the regression assumption of independent residuals. Spatial structure at any spatial scale can be modeled flexibly based on a set of uncorrelated component patterns (e.g., Moran's eigenvector maps, MEM) that is derived from the spatial relationships between sampling locations as defined in a spatial weight matrix. Spatial filtering thus addresses spatial autocorrelation in the residuals by adding such component patterns (spatial eigenvectors) as predictors to the regression model. However, space is not an ecologically meaningful predictor, and commonly used tests for selecting significant component patterns do not take into account the specific nature of these variables. This paper proposes "spatial component regression" (SCR) as a new way of integrating the linear regression model with Moran's eigenvector maps. In its unconditioned form, SCR decomposes the relationship between response and predictors by component patterns, whereas conditioned SCR provides an alternative method of spatial filtering, taking into account the statistical properties of component patterns in the design of statistical hypothesis tests. Application to the well-known multivariate mite data set illustrates how SCR may be used to condition for significant residual spatial structure and to identify additional predictors associated with residual spatial structure. Finally, I argue that all variance is spatially structured, hence spatial independence is best characterized by a lack of excess variance at any spatial scale, i.e., spatial white noise. PMID:24400490
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. PMID:18329400
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.
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.