Six-Month Chronic Toxicity Study of Tamarind Pulp (Tamarindus indica L.) Water Extract.

PubMed

Iskandar, Irene; Setiawan, Finna; Sasongko, Lucy D N; Adnyana, I Ketut

2017-03-08

Tamarind water extract has been shown to demonstrate an anti-obesity effect. In this research, long-term use of tamarind pulp water extract safety was evaluated. Tamarind pulp was extracted by reflux method, followed by freeze-drying to obtain dry extract. Wistar rats were divided into six groups, with 20 animals of each sex per group. The control group and satellite control group received carboxymethylcellulose sodium (CMC-Na) 0.5% 1 mL/100 g bw (body weight) per day. Treatment groups received tamarind pulp extract at doses of 75, 200, 1000, satellite 1000 mg/kg bw per day for six months. After six months, control groups and the treatment group were sacrificed. Satellite groups were sacrificed one month later. Relative organ weights, hematology and clinical biochemistry profiles were determined. After six months, there were no significant change in body weight, hematologic, and clinical biochemistry profiles of the tested group. Body weight of male rats in the satellite 1000 mg/kg bw group was significantly increased in week 30 compared to the satellite control group ( p < 0.05). The relative spleen weight of female rats of the 200 mg/kg bw group was reduced ( p < 0.05). The relative kidney weight of male rats in the 1000 mg/kg bw group was increased ( p < 0.05). This study showed that tamarind pulp extract was generally safe and well tolerated at the tested dose.

Synchrotron Microtomography Reveals the Fine Three-Dimensional Porosity of Composite Polysaccharide Aerogels

PubMed Central

Ghafar, Abdul; Parikka, Kirsti; Tenkanen, Maija; Suuronen, Jussi-Petteri

2017-01-01

This study investigates the impact of ice-templating conditions on the morphological features of composite polysaccharide aerogels in relation to their mechanical behavior and aims to get a better insight into the parameters governing these properties. We have prepared polysaccharide aerogels of guar galactomannan (GM) and tamarind seed xyloglucan (XG) by enzymatic oxidation with galactose oxidase (GaO) to form hydrogels, followed by conventional and unidirectional ice-templating (freezing) methods and lyophilization to form aerogels. Composite polysaccharide aerogels were prepared by incorporating nanofibrillated cellulose (NFC) into polysaccharide solutions prior to enzymatic oxidation and gel formation; such a cross linking technique enabled the homogeneous distribution of the NFC reinforcement into the gel matrix. We conducted phase-enhanced synchrotron X-ray microtomography (XMT) scans and visualized the internal microstructure of the aerogels in three-dimensional (3D) space. Volume-weighted pore-size and pore-wall thickness distributions were quantitatively measured and correlated to the aerogels’ mechanical properties regarding ice-templating conditions. Pore-size distribution and orientation depended on the ice-templating methods and the NFC reinforcement that significantly determined the mechanical and shape-recovery behavior of the aerogels. The results obtained will guide the design of the microporous structure of polysaccharide aerogels with optimal morphology and mechanical behavior for life-sciences applications. PMID:28773235

Establishing the tolerability and performance of tamarind seed polysaccharide (TSP) in treating dry eye syndrome: results of a clinical study.

PubMed

Rolando, Maurizio; Valente, Cristiana

2007-03-29

One of the problems arising from available preparations for dry eye syndrome is the limited residence time of products on the ocular surface. In this paper, we look at an innovative new treatment for dry eye, tamarind seed polysaccharide (TSP). TSP possesses mucomimetic, mucoadhesive and pseudoplastic properties. The 'mucin-like' molecular structure of TSP is similar to corneal and conjunctival mucin 1 (MUC1), a transmembrane glycoprotein thought to play an essential role in protecting and wetting the corneal surface and may explain its increased retention on the eye surface. The activity of TSP and hyaluronic acid (HA) in the treatment of dry eye syndrome was compared in an open-label, randomised, single-centre clinical study. Thirty patients were randomised to receive three or more applications per day of either TSP 0.5%, TSP 1% or HA 0.2% (Hyalistiltrade mark) over a period of 90 days. The primary objective of tolerability was assessed by visual analogue scale (VAS), scoring of specific symptoms and the incidence of adverse events. Secondary objectives included improvement in stability of the precorneal tear film, subjective symptoms and corneal and conjunctival staining. TSP 0.5% and 1% were comparable to HA 0.2% with regard to both primary and secondary objective parameters.TSP 1% showed benefits over HA 0.2% for the subjective symptoms; trouble blinking, ocular burning and foreign body sensation. This study suggests that TSP 0.5% and 1% offer at least equivalent relief to HA 0.2% for dry eye syndrome. All treatments demonstrated optimal tolerability and are suitable for frequent use in the therapy of dry eye.TSP 1% produced promising results in terms of improvements in certain patient symptoms and suggests benefits of the TSP formulation. This study paves the way for a larger study to further establish the performance and safety of TSP compared with HA and highlights the need to expand this therapeutic agent to a wider dry eye population.

Microbial quality of yellow seasoned “pindang” fish treated with turmeric and tamarind

NASA Astrophysics Data System (ADS)

Handayani, B. R.; Dipokusumo, B.; Werdiningsih, W.; Rahayu, T. I.; Sugita, D. L.

2018-01-01

The objective of this study was to determine the microbial quality of yellow seasoned pindang fish. The fish was treated using combination of turmeric and tamarind at different ratio. This research used Randomized Block Design with 2 (two) factors ie concentration of turmeric (0%, 2%, and 6%) and concentration of tamarind (0%, 3%, and 6%). Each treatment was replicated 3 times to obtain 27 experimental units. The parameters observed were total microbe, total fungi and some pathogenic bacteria. Some microbial data were analyzed using descriptive method, however, the number of S. aureus was analyzed at 5% significance level by using software co-Stat and if there was a real difference then tested further by test Honestly Significant Difference (HSD). The results showed that increasing the use of curcumin and tamarind tended to decrease the total number of microbial from treatment control 5.1 x 105 CFU/gram to <1.0 x 103 CFU/gram. All the treatment produced yellow seasoned pindang fish with fungi <1.0 x 102 CFU/gram. The products contain pathogenic bacteria E. coli < 3 MPN/gram; S. aureus <1.0 x 103 CFU/gram; Salmonella and V. cholerae were negative in 25 gram of sample. Based on microbial quality, it is recommended that the use of 3-6% of turmeric and 2-4% of tamarind are the best spices combination to produce safe consumption of yellow seasoned pindang fish.

Feasibility study and sensory test of turmeric tamarind traditional drink with various processing

NASA Astrophysics Data System (ADS)

Rudyatmi, E.; Bintari, S. H.; Iswari, R. S.

2018-03-01

Turmeric tamarind traditional drink as anti-oxidant, good for health, and has a potency to developed. The objectives of this study are to determine the feasibility and the favorite level of consumer towards two turmerics tamarind traditional drink which processed differently. Feasibility depended on sensory test and microbe's contamination according to a quality standard of BPOM and complemented with an anti-bacterial test. The anti-bacterial test is determined by a diameter of inhibition zone towards E coli and B subtilist. Consumer’s favorites level is determined by organoleptic test to 40 testers. Sensory test results to form, odor, taste, and color are normal. TPC first traditional drink 6,9 x 102 col/gr and TKK ≤1,0x10 col/gr, TPC second traditional drink 2,0 x 101 col/gr and TKK ≤1,0x10 col/gr; all tests toward E coli, Salmonella SP, Staphylococcus aureus, Pseudomonas aeruginosa, shigella sp negative/gr; inhibiting capabilities towards B.subtilis and E coli of first traditional drink > second traditional drink. Inhibiting capabilities towards B.subtilis > E coli. All parameters comply with BPOM standard. Most of the tester love the first method turmeric tamarind traditional drink.

Preparation and efficacy assessment of malva nut polysaccharide for skin hydrating products.

PubMed

Kanlayavattanakul, M; Fungpaisalpong, K; Pumcharoen, M; Lourith, N

2017-11-01

Scaphium scaphigerum or malva nut has long been served in Chinese medicine. However, the use of this herb in modern health care applications has, to date, been rarely reported. Maceration of the herb in water afforded malva nut polysaccharide which was standardized. Safety and skin hydrating efficacy of the polysaccharide and products were evaluated in human volunteers. Malva nut polysaccharide (41.71±0.64%) having 36.58±0.51% total sugar content was isolated, with further analysis quantifying ash, carbohydrate, reducing sugar and moisture contents to be 6.05±0.00, 40.06±1.00, 12.20±0.05 and 12.64±0.31%, respectively. The polysaccharide exhibited swelling and hydrating capacities of 0.46±0.01% and 54.46±0.02g/g, with L*, a* and b* of 52.56±0.04, 9.02±0.06 and 18.42±0.03, respectively, and a viscosity of 1263.00±2.00 cps. Accelerated testing indicated the biopolysaccharide to be stable, resulting in no skin irritation in 15 human volunteers. The skin hydrating efficacy as assessed via a randomized single-blind, placebo-controlled study in 24 volunteers highlighted the superior performance of malva nut over the vehicle (moisture retainment for 70min as examined by Corneometer ® CM 825). A stable skin moisturizing gel containing malva nut was developed and was shown to exhibit improved performance over benchmark tamarind and algae polysaccharide gels (after 180min observation). Malva nut polysaccharide has potential as a key ingredient in skin hydrating products, which should encourage its further development. Copyright © 2017 Académie Nationale de Pharmacie. Published by Elsevier Masson SAS. All rights reserved.

Optimization of production conditions for activated carbons from Tamarind wood by zinc chloride using response surface methodology.

PubMed

Sahu, J N; Acharya, Jyotikusum; Meikap, B C

2010-03-01

The low-cost activated carbon was prepared from Tamarind wood an agricultural waste material, by chemical activation with zinc chloride. Activated carbon adsorption is an effective means for reducing organic chemicals, chlorine, heavy metals and unpleasant tastes and odours in effluent or colored substances from gas or liquid streams. Central composite design (CCD) was applied to study the influence of activation temperature, chemical ratio of zinc chloride to Tamarind wood and activation time on the chemical activation process of Tamarind wood. Two quadratic models were developed for yield of activated carbon and adsorption of malachite green oxalate using Design-Expert software. The models were used to calculate the optimum operating conditions for production of activated carbon providing a compromise between yield and adsorption of the process. The yield (45.26 wt.%) and adsorption (99.9%) of the activated carbon produced at these operating conditions showed an excellent agreement with the amounts predicted by the models. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

Bioactive characteristics and optimization of tamarind seed protein hydrolysate for antioxidant-rich food formulations.

PubMed

Bagul, Mayuri B; Sonawane, Sachin K; Arya, Shalini S

2018-04-01

Tamarind seed has been a source of valuable nutrients such as protein (contains high amount of many essential amino acids), essential fatty acids, and minerals which are recognized as additive to develop perfect balanced functional foods. The objective of present work was to optimize the process parameters for extraction and hydrolysis of protein from tamarind seeds. Papain-derived hydrolysates showed a maximum degree of hydrolysis (39.49%) and radical scavenging activity (42.92 ± 2.83%) at optimized conditions such as enzyme-to-substrate ratio (1:5), hydrolysis time (3 h), hydrolysis temperature (65 °C), and pH 6. From this study, papain hydrolysate can be considered as good source of natural antioxidants in developing food formulations.

Characterization and Properties of Activated Carbon Prepared from Tamarind Seeds by KOH Activation for Fe(III) Adsorption from Aqueous Solution

PubMed Central

Mopoung, Sumrit; Moonsri, Phansiri; Palas, Wanwimon; Khumpai, Sataporn

2015-01-01

This research studies the characterization of activated carbon from tamarind seed with KOH activation. The effects of 0.5 : 1–1.5 : 1 KOH : tamarind seed charcoal ratios and 500–700°C activation temperatures were studied. FTIR, SEM-EDS, XRD, and BET were used to characterize tamarind seed and the activated carbon prepared from them. Proximate analysis, percent yield, iodine number, methylene blue number, and preliminary test of Fe(III) adsorption were also studied. Fe(III) adsorption was carried out by 30 mL column with 5–20 ppm Fe(III) initial concentrations. The percent yield of activated carbon prepared from tamarind seed with KOH activation decreased with increasing activation temperature and impregnation ratios, which were in the range from 54.09 to 82.03 wt%. The surface functional groups of activated carbon are O–H, C=O, C–O, –CO3, C–H, and Si–H. The XRD result showed high crystallinity coming from a potassium compound in the activated carbon. The main elements found in the activated carbon by EDS are C, O, Si, and K. The results of iodine and methylene blue adsorption indicate that the pore size of the activated carbon is mostly in the range of mesopore and macropore. The average BET pore size and BET surface area of activated carbon are 67.9764 Å and 2.7167 m2/g, respectively. Finally, the tamarind seed based activated carbon produced with 500°C activation temperature and 1.0 : 1 KOH : tamarind seed charcoal ratio was used for Fe(III) adsorption test. It was shown that Fe(III) was adsorbed in alkaline conditions and adsorption increased with increasing Fe(III) initial concentration from 5 to 20 ppm with capacity adsorption of 0.0069–0.019 mg/g. PMID:26689357

Development of Suppositories Containing Flutamide-Loaded Alginate-Tamarind Microparticles for Rectal Administration: In Vitro and in Vivo Studies.

PubMed

Patil, Bharati Shivajirao; Mahajan, Hitendra Shaligram; Surana, Sanjay Javerilal

2015-01-01

In the present work the absorption of flutamide from suppositories containing hydrophilic tamarind alginate microparticles after rectal administration in rats was investigated with the purpose of enhancing bioavailability and to avoid hepatic toxicity. Microparticles were developed by ionic gelation method and optimized using one factorial design of response surface methodology. The optimized batch of microparticles had tamarind gum-sodium alginate (1 : 3) ratio and showed entrapment efficiency 94.969% and mucoadhesion strength 94.646% with desirability of 0.961. Suppositories loaded with microparticles were developed by fusion method using poloxamer 407 and poloxamer 188 in combination as suppository base. Kinetic analysis of the release data of microparticle-loaded suppositories showed time-independent release of drug. Higher values of 'n' (>0.89) represent Super Case II-type drug release. The pharmacokinetics of flutamide from flutamide tamarind alginate microparticle-loaded suppository were compared with oral suspension. Cmax of microparticle-loaded suppository was significantly larger than that of oral suspension (1.711 and 0.859 µg/mL, respectively).

Cleansing lotion containing tamarind fruit pulp extract. II. Study of cumulative irritation effects in human.

PubMed

Maenthaisong, Ratree; Viyoch, Jarupa; Chaiyakunapruk, Nathorn; Warnnissorn, Prateep

2007-09-01

Cleansing lotion containing extract of tamarind fruit pulp was developed to provide skin a lighter effect. Skin irritation may occur due to keratolytic effect of alpha-hydroxyl acids (AHA) in the tamarind fruit pulp extract. To assess the cumulative irritation effect of cleansing lotion containing tamarind fruit extract with 2% (w/w) tartaric acid on human skin compared with placebo product and de-ionized water. The study design was a single-blinded, randomized side of arm, and controlled study. Three samples, including test product, placebo product, and de-ionized water, were repeatedly applied on the inner forearm of 15 healthy females (aged 28.3 +/- 3.1 years) for 30 min daily for 5 days under semi-occlusive patch. Skin irritation was measured by using visual scoring and instruments such as Tewameter and Mexameter. All measurements were done before application of samples every day from day 1 until day 5. Final measurements were done after the last application for 3 days (day 8). The results obtained from the visual scoring scale indicated no irritation signs and symptoms of test product. Mean differences of transepidermal water loss and erythema values between test product and de-ionized water and between test and placebo products were not statistically significant (P > 0.05). These findings indicate a preliminary safety evidence of our developed cleansing lotion containing the natural AHAs and can be used as cumulative evidence for supporting the future home use study of this product in human.

Combustion of peanut and tamarind shells in a conical fluidized-bed combustor: a comparative study.

PubMed

Kuprianov, Vladimir I; Arromdee, Porametr

2013-07-01

Combustion of peanut and tamarind shells was studied in the conical fluidized-bed combustor using alumina sand as the bed material to prevent bed agglomeration. Morphological, thermogravimetric and kinetic characteristics were investigated to compare thermal and combustion reactivity between the biomass fuels. The thermogravimetric kinetics of the biomasses was fitted using the Coats-Redfern method. Experimental tests on the combustor were performed at 60 and 45 kg/h fuel feed rates, with excess air within 20-80%. Temperature and gas concentrations were measured along radial and axial directions in the reactor and at stack. The axial temperature and gas concentration profiles inside the combustor exhibited sensible effects of fuel properties and operating conditions on combustion and emission performance. High (≈ 99%) combustion efficiency and acceptable levels of CO, CxHy, and NO emissions are achievable when firing peanut shells at excess air of about 40%, whereas 60% is more preferable for burning tamarind shells. Copyright © 2013 Elsevier Ltd. All rights reserved.

Hydroxyethyl methacrylate grafted carboxy methyl tamarind (CMT-g-HEMA) polysaccharide based matrix as a suitable scaffold for skin tissue engineering.

PubMed

Choudhury, Priyanka; Kumar, Satish; Singh, Abhishek; Kumar, Ashutosh; Kaur, Navneet; Sanyasi, Sridhar; Chawla, Saurabh; Goswami, Chandan; Goswami, Luna

2018-06-01

Patho-physiologies related to skin are diverse in nature such as burns, skin ulcers, atopic dermatitis, psoriasis etc. which impose severe bio-medical problems and thus enforce requirement of new and healthy skin prepared through tissues engineering methodologies. However, fully functional and biodegradable matrix for attachment, growth, proliferation and differentiation of the relevant cells is not available. In the present study, we introduce a set of hydrogels synthesized by incorporation of a synthetic monomer (Hydroxyethlmethacryate) with a semi-synthetic polymer backbone (carboxy methyl tamarind, CMT) in different mole ratios. We termed these materials as CMT:HEMA based hydrogels and these were characterized by different physico-chemical techniques, namely by X-Ray Diffraction, SEM and Dynamic Light Scattering. Biocompatibility studies with HaCaT, NIH-3T3 and mouse dermal fibroblasts confirm that this material is biocompatible. MTT assay further confirmed that this material does not have any cytotoxic effects. Assays for mitochondrial functionality such as ATP assay and mitochondrial reactive oxygen (ROS) generation also suggest that this material is safe and does not have any cytotoxicity. Hemolytic assay with red blood cells and acute skin irritation test on SD Rats confirmed that this material is suitable for ex-vivo application in future. We suggest that this hydrogel is suitable for in-vivo applications and may have clinical and commercial importance against skin disorders. Copyright © 2018. Published by Elsevier Ltd.

Xyloglucans from flaxseed kernel cell wall: Structural and conformational characterisation.

PubMed

Ding, Huihuang H; Cui, Steve W; Goff, H Douglas; Chen, Jie; Guo, Qingbin; Wang, Qi

2016-10-20

The structure of ethanol precipitated fraction from 1M KOH extracted flaxseed kernel polysaccharides (KPI-EPF) was studied for better understanding the molecular structures of flaxseed kernel cell wall polysaccharides. Based on methylation/GC-MS, NMR spectroscopy, and MALDI-TOF-MS analysis, the dominate sugar residues of KPI-EPF fraction comprised of (1,4,6)-linked-β-d-glucopyranose (24.1mol%), terminal α-d-xylopyranose (16.2mol%), (1,2)-α-d-linked-xylopyranose (10.7mol%), (1,4)-β-d-linked-glucopyranose (10.7mol%), and terminal β-d-galactopyranose (8.5mol%). KPI-EPF was proposed as xyloglucans: The substitution rate of the backbone is 69.3%; R1 could be T-α-d-Xylp-(1→, or none; R2 could be T-α-d-Xylp-(1→, T-β-d-Galp-(1→2)-α-d-Xylp-(1→, or T-α-l-Araf-(1→2)-α-d-Xylp-(1→; R3 could be T-α-d-Xylp-(1→, T-β-d-Galp-(1→2)-α-d-Xylp-(1→, T-α-l-Fucp-(1→2)-β-d-Galp-(1→2)-α-d-Xylp-(1→, or none. The Mw of KPI-EPF was calculated to be 1506kDa by static light scattering (SLS). The structure-sensitive parameter (ρ) of KPI-EPF was calculated as 1.44, which confirmed the highly branched structure of extracted xyloglucans. This new findings on flaxseed kernel xyloglucans will be helpful for understanding its fermentation properties and potential applications. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Production and characterization of cellulose reinforced starch (CRT) films.

PubMed

Sudharsan, K; Chandra Mohan, C; Azhagu Saravana Babu, P; Archana, G; Sabina, K; Sivarajan, M; Sukumar, M

2016-02-01

Starch from Tamarind seed is considered to be a nonedible and inexpensive component, with many industrial applications. Extraction and characterization of tamarind seed starch was carried out for the synthesis of biopolymer. Tamarind seeds were collected, cleaned and further roasted, decorticated, and pulverized to get starch powder. Total starch content present in each tamarind seed is estimated to be around 65-70%. About 84.68% purified starch can be recovered from the tamarind seed. Defatted Tamarind seed starch has an amylose content of 27.55 wt.% and 72.45 wt.% of amylopectin. Morphological (SEM) and X-ray diffraction were used to evaluate crystallinity. Likewise, TGA and DSC of starch have also been analyzed. Thermal properties of starch obtained from tamarind seeds showed good thermal stability when compared to other starch sources such as Mesquite seed and Mango kernel. This study proved that the tamarind seed starch can be used as a potential biopolymer material. Thermo-stable biofilms were produced through initial optimization studies. Predictive response surface quadratic models were constructed for prediction and optimization of biofilm mechanical properties. Correlation coefficient values were calculated to me more than 0.90 for mechanical responses which implies the fitness of constructed model with experimental data. Copyright © 2015 Elsevier B.V. All rights reserved.

X-ray photoelectron spectroscopic analysis of rice kernels and flours: Measurement of surface chemical composition.

PubMed

Nawaz, Malik A; Gaiani, Claire; Fukai, Shu; Bhandari, Bhesh

2016-12-01

The objectives of this study were to evaluate the ability of X-ray photoelectron spectroscopy (XPS) to differentiate rice macromolecules and to calculate the surface composition of rice kernels and flours. The uncooked kernels and flours surface composition of the two selected rice varieties, Thadokkham-11 (TDK11) and Doongara (DG) demonstrated an over-expression of lipids and proteins and an under-expression of starch compared to the bulk composition. The results of the study showed that XPS was able to differentiate rice polysaccharides (mainly starch), proteins and lipids in uncooked rice kernels and flours. Nevertheless, it was unable to distinguish components in cooked rice samples possibly due to complex interactions between gelatinized starch, denatured proteins and lipids. High resolution imaging methods (Scanning Electron Microscopy and Confocal Laser Scanning Microscopy) were employed to obtain complementary information about the properties and location of starch, proteins and lipids in rice kernels and flours. Copyright © 2016. Published by Elsevier Ltd.

Effects of bilimbi (Averrhoa bilimbi L.) and tamarind (Tamarindus indica L.) juice on Listeria monocytogenes Scott A and Salmonella Typhimurium ATCC 14028 and the sensory properties of raw shrimps.

PubMed

Norhana, M N Wan; Azman, Mohd Nor A; Poole, Susan E; Deeth, Hilton C; Dykes, Gary A

2009-11-30

The potential of using juice of bilimbi (Averrhoa bilimbi L.) and tamarind (Tamarindus indica L.) to reduce Listeria monocytogenes Scott A and Salmonella Typhimurium ATCC 14028 populations on raw shrimps after washing and during storage (4 degrees C) was investigated. The uninoculated raw shrimps and those inoculated with approximately 9 log cfu/ml of L. monocytogenes Scott A and S. Typhimurium ATCC 14028 were washed (dipped or rubbed) in distilled water (SDW) (control), bilimbi or tamarind juice at 1:4 (w/v) concentrations for 10 and 5 min. Naturally occurring aerobic bacteria (APC), L. monocytogenes Scott A and S. Typhimurium ATCC 14028 counts, pH values and sensory analysis of washed shrimps were determined immediately after washing (day 0), and on days 3 and 7 of storage. Compared to SDW, bilimbi and tamarind juice significantly (p<0.05) reduced APC (0.40-0.70 log cfu/g), L. monocytogenes Scott A (0.84-1.58 log cfu/g) and S. Typhimurium ATCC 14028 (1.03-2.00 log cfu/g) populations immediately after washing (0 day). There was a significant difference (p<0.05) in bacterial reduction between the dipping (0.40-0.41 log for APC; 0.84 for L. monocytogenes Scott A and 1.03-1.09 log for S. Typhimurium ATCC 14028) and rubbing (0.68-0.70 log for APC; 1.34-1.58 for L. monocytogenes Scott A and 1.67-2.00 log for S. Typhimurium ATCC 14028) methods. Regardless of washing treatments or methods, populations of S. Typhimurium ATCC 14028 decreased slightly (5.10-6.29 log cfu/g on day 7 of storage) while populations of L. monocytogenes Scott A (8.74-9.20 log cfu/g) and APC (8.68-8.92 log cfu/g) increased significantly during refrigerated storage. The pH of experimental shrimps were significantly (p<0.05) decreased by 0.15-0.22 pH units after washing with bilimbi and tamarind juice. The control, bilimbi or tamarind-washed shrimps did not differ in sensory panellist acceptability (p>0.05) throughout the storage except for odour (p<0.05) attributes at 0 day when acidic or lemony

Polysaccharide-capped silver Nanoparticles inhibit biofilm formation and eliminate multi-drug-resistant bacteria by disrupting bacterial cytoskeleton with reduced cytotoxicity towards mammalian cells

NASA Astrophysics Data System (ADS)

Sanyasi, Sridhar; Majhi, Rakesh Kumar; Kumar, Satish; Mishra, Mitali; Ghosh, Arnab; Suar, Mrutyunjay; Satyam, Parlapalli Venkata; Mohapatra, Harapriya; Goswami, Chandan; Goswami, Luna

2016-04-01

Development of effective anti-microbial therapeutics has been hindered by the emergence of bacterial strains with multi-drug resistance and biofilm formation capabilities. In this article, we report an efficient green synthesis of silver nanoparticle (AgNP) by in situ reduction and capping with a semi-synthetic polysaccharide-based biopolymer (carboxymethyl tamarind polysaccharide). The CMT-capped AgNPs were characterized by UV, DLS, FE-SEM, EDX and HR-TEM. These AgNPs have average particle size of ~20-40 nm, and show long time stability, indicated by their unchanged SPR and Zeta-potential values. These AgNPs inhibit growth and biofilm formation of both Gram positive (B. subtilis) and Gram negative (E. coli and Salmonella typhimurium) bacterial strains even at concentrations much lower than the minimum inhibitory concentration (MIC) breakpoints of antibiotics, but show reduced or no cytotoxicity against mammalian cells. These AgNPs alter expression and positioning of bacterial cytoskeletal proteins FtsZ and FtsA. CMT-capped AgNPs can effectively block growth of several clinical isolates and MDR strains representing different genera and resistant towards multiple antibiotics belonging to different classes. We propose that the CMT-capped AgNPs can have potential bio-medical application against multi-drug-resistant microbes with minimal cytotoxicity towards mammalian cells.

Polysaccharide-capped silver Nanoparticles inhibit biofilm formation and eliminate multi-drug-resistant bacteria by disrupting bacterial cytoskeleton with reduced cytotoxicity towards mammalian cells

PubMed Central

Sanyasi, Sridhar; Majhi, Rakesh Kumar; Kumar, Satish; Mishra, Mitali; Ghosh, Arnab; Suar, Mrutyunjay; Satyam, Parlapalli Venkata; Mohapatra, Harapriya; Goswami, Chandan; Goswami, Luna

2016-01-01

Development of effective anti-microbial therapeutics has been hindered by the emergence of bacterial strains with multi-drug resistance and biofilm formation capabilities. In this article, we report an efficient green synthesis of silver nanoparticle (AgNP) by in situ reduction and capping with a semi-synthetic polysaccharide-based biopolymer (carboxymethyl tamarind polysaccharide). The CMT-capped AgNPs were characterized by UV, DLS, FE-SEM, EDX and HR-TEM. These AgNPs have average particle size of ~20–40 nm, and show long time stability, indicated by their unchanged SPR and Zeta-potential values. These AgNPs inhibit growth and biofilm formation of both Gram positive (B. subtilis) and Gram negative (E. coli and Salmonella typhimurium) bacterial strains even at concentrations much lower than the minimum inhibitory concentration (MIC) breakpoints of antibiotics, but show reduced or no cytotoxicity against mammalian cells. These AgNPs alter expression and positioning of bacterial cytoskeletal proteins FtsZ and FtsA. CMT-capped AgNPs can effectively block growth of several clinical isolates and MDR strains representing different genera and resistant towards multiple antibiotics belonging to different classes. We propose that the CMT-capped AgNPs can have potential bio-medical application against multi-drug-resistant microbes with minimal cytotoxicity towards mammalian cells. PMID:27125749

Kernel Machine SNP-set Testing under Multiple Candidate Kernels

PubMed Central

Wu, Michael C.; Maity, Arnab; Lee, Seunggeun; Simmons, Elizabeth M.; Harmon, Quaker E.; Lin, Xinyi; Engel, Stephanie M.; Molldrem, Jeffrey J.; Armistead, Paul M.

2013-01-01

Joint testing for the cumulative effect of multiple single nucleotide polymorphisms grouped on the basis of prior biological knowledge has become a popular and powerful strategy for the analysis of large scale genetic association studies. The kernel machine (KM) testing framework is a useful approach that has been proposed for testing associations between multiple genetic variants and many different types of complex traits by comparing pairwise similarity in phenotype between subjects to pairwise similarity in genotype, with similarity in genotype defined via a kernel function. An advantage of the KM framework is its flexibility: choosing different kernel functions allows for different assumptions concerning the underlying model and can allow for improved power. In practice, it is difficult to know which kernel to use a priori since this depends on the unknown underlying trait architecture and selecting the kernel which gives the lowest p-value can lead to inflated type I error. Therefore, we propose practical strategies for KM testing when multiple candidate kernels are present based on constructing composite kernels and based on efficient perturbation procedures. We demonstrate through simulations and real data applications that the procedures protect the type I error rate and can lead to substantially improved power over poor choices of kernels and only modest differences in power versus using the best candidate kernel. PMID:23471868

Formulation and development of a patch containing tamarind fruit extract by using the blended chitosan-starch as a rate-controlling matrix.

PubMed

Viyoch, J; Patcharaworakulchai, P; Songmek, R; Pimsan, V; Wittaya-Areekul, S

2003-06-01

A cosmetic patch containing tamarind fruit extract was formulated and developed by blending two types of natural polymers: chitosan with molecular weight of 100 000 and starch such as corn, potato or tapioca starch. The physicochemical characteristics, i.e. flexibility, colour, transparency, integrity, gloss, water sorption and bioadhesion property and the stability of the patch without tamarind content were investigated. Stability test was performed by keeping the prepared patches at 4 degrees C, at room temperature or at 45 degrees C for 2 weeks. The results showed that the formulations composed of chitosan:corn starch ratio of 4.5 : 0.5 (CC(4.5 : 0.5)) and chitosan:tapioca starch ratios of 4.5 : 0.5 (CT(4.5 : 0.5)) and 4.0 : 1.0 (CT(4 : 1)) provide patches with favourable physical characteristics, high water sorption, good bioadhesion ability and good stability. After the lyophilized tamarind extract in an amount corresponding to 5% of tartaric acid was incorporated into the formulations of CC(4.5 : 0.5), CT(4.5 : 0.5) and CT(4 : 1), the ability of the patches to adhere to skin was improved. However, after keeping the test patches at room temperature or at 45 degrees C for 6 weeks, their colours were intensified while their flexibilities and skin adhesion properties decreased. A 12-h in vitro permeation was investigated by studying the cumulative amount of tartaric acid permeated through the Silastic membrane (Dow-Coming, Midland, MI, USA). The CC(4.5 : 0.5) patch tended to give the highest amount of tartaric acid released. The release pattern of all the blended polymeric matrices was exhibited in two distinct phases: the rapid phase, where the flux averaged 3.61 microg min(-1) mm(-2); and the slow phase, where the flux averaged 1.89 microg min(-1) mm(-2).

Chemical and functional properties of fibre concentrates obtained from by-products of coconut kernel.

PubMed

Yalegama, L L W C; Nedra Karunaratne, D; Sivakanesan, Ramiah; Jayasekara, Chitrangani

2013-11-01

The coconut kernel residues obtained after extraction of coconut milk (MR) and virgin coconut oil (VOR) were analysed for their potential as dietary fibres. VOR was defatted and treated chemically using three solvent systems to isolate coconut cell wall polysaccharides (CCWP). Nutritional composition of VOR, MR and CCWPs indicated that crude fibre, neutral detergent fibre, acid detergent fibre and hemicelluloses contents were higher in CCWPs than in VOR and MR. MR contained a notably higher content of fat than VOR and CCWPs. The oil holding capacity, water holding capacity and swelling capacity were also higher in CCWPs than in VOR and MR. All the isolates and MR and VOR had high metal binding capacities. The CCWPs when compared with commercially available fibre isolates, indicated improved dietary fibre properties. These results show that chemical treatment of coconut kernel by-products can enhance the performance of dietary fibre to yield a better product. Copyright © 2013 Elsevier Ltd. All rights reserved.

Property evaluations of dry-cast reconstituted bacterial cellulose/tamarind xyloglucan biocomposites.

PubMed

de Souza, Clayton F; Lucyszyn, Neoli; Woehl, Marco A; Riegel-Vidotti, Izabel C; Borsali, Redouane; Sierakowski, Maria Rita

2013-03-01

We describe the mechanical defibrillation of bacterial cellulose (BC) followed by the dry-cast generation of reconstituted BC films (RBC). Xyloglucan (XGT), extracted from tamarind seeds, was incorporated into the defibrillated cellulose at various compositions, and new films were created using the same process. Microscopy and contact angle analyses of films revealed an increase in the microfibre adhesion, a reduced polydispersity in the diameters of the microfibrils and increased hydrophobic behaviour as a function of %XGT. X-ray diffraction analysis revealed changes to the crystallographic planes of the RBC and the biocomposite films with preferential orientation along the (110) plane. Compared with BC, RBC/XGT biocomposite with 10% XGT exhibited improvement in its thermal properties and in Young's modulus. These results indicated a reorganisation of the microfibres with mechanical treatment, which when combined with hydrocolloids, can create cellulose-based materials that could be applied as scaffolding for tissue engineering and drug release. Copyright © 2012 Elsevier Ltd. All rights reserved.

Kernel Abortion in Maize 1

PubMed Central

Hanft, Jonathan M.; Jones, Robert J.

1986-01-01

Kernels cultured in vitro were induced to abort by high temperature (35°C) and by culturing six kernels/cob piece. Aborting kernels failed to enter a linear phase of dry mass accumulation and had a final mass that was less than 6% of nonaborting field-grown kernels. Kernels induced to abort by high temperature failed to synthesize starch in the endosperm and had elevated sucrose concentrations and low fructose and glucose concentrations in the pedicel during early growth compared to nonaborting kernels. Kernels induced to abort by high temperature also had much lower pedicel soluble acid invertase activities than did nonaborting kernels. These results suggest that high temperature during the lag phase of kernel growth may impair the process of sucrose unloading in the pedicel by indirectly inhibiting soluble acid invertase activity and prevent starch synthesis in the endosperm. Kernels induced to abort by culturing six kernels/cob piece had reduced pedicel fructose, glucose, and sucrose concentrations compared to kernels from field-grown ears. These aborting kernels also had a lower pedicel soluble acid invertase activity compared to nonaborting kernels from the same cob piece and from field-grown ears. The low invertase activity in pedicel tissue of the aborting kernels was probably caused by a lack of substrate (sucrose) for the invertase to cleave due to the intense competition for available assimilates. In contrast to kernels cultured at 35°C, aborting kernels from cob pieces containing all six kernels accumulated starch in a linear fashion. These results indicate that kernels cultured six/cob piece abort because of an inadequate supply of sugar and are similar to apical kernels from field-grown ears that often abort prior to the onset of linear growth. PMID:16664846

Approximate kernel competitive learning.

PubMed

Wu, Jian-Sheng; Zheng, Wei-Shi; Lai, Jian-Huang

2015-03-01

Kernel competitive learning has been successfully used to achieve robust clustering. However, kernel competitive learning (KCL) is not scalable for large scale data processing, because (1) it has to calculate and store the full kernel matrix that is too large to be calculated and kept in the memory and (2) it cannot be computed in parallel. In this paper we develop a framework of approximate kernel competitive learning for processing large scale dataset. The proposed framework consists of two parts. First, it derives an approximate kernel competitive learning (AKCL), which learns kernel competitive learning in a subspace via sampling. We provide solid theoretical analysis on why the proposed approximation modelling would work for kernel competitive learning, and furthermore, we show that the computational complexity of AKCL is largely reduced. Second, we propose a pseudo-parallelled approximate kernel competitive learning (PAKCL) based on a set-based kernel competitive learning strategy, which overcomes the obstacle of using parallel programming in kernel competitive learning and significantly accelerates the approximate kernel competitive learning for large scale clustering. The empirical evaluation on publicly available datasets shows that the proposed AKCL and PAKCL can perform comparably as KCL, with a large reduction on computational cost. Also, the proposed methods achieve more effective clustering performance in terms of clustering precision against related approximate clustering approaches. Copyright © 2014 Elsevier Ltd. All rights reserved.

Simultaneous saccharification and cofermentation of lignocellulosic residues from commercial furfural production and corn kernels using different nutrient media

PubMed Central

2011-01-01

Background As the supply of starch grain and sugar cane, currently the main feedstocks for bioethanol production, become limited, lignocelluloses will be sought as alternative materials for bioethanol production. Production of cellulosic ethanol is still cost-inefficient because of the low final ethanol concentration and the addition of nutrients. We report the use of simultaneous saccharification and cofermentation (SSCF) of lignocellulosic residues from commercial furfural production (furfural residue, FR) and corn kernels to compare different nutritional media. The final ethanol concentration, yield, number of live yeast cells, and yeast-cell death ratio were investigated to evaluate the effectiveness of integrating cellulosic and starch ethanol. Results Both the ethanol yield and number of live yeast cells increased with increasing corn-kernel concentration, whereas the yeast-cell death ratio decreased in SSCF of FR and corn kernels. An ethanol concentration of 73.1 g/L at 120 h, which corresponded to a 101.1% ethanol yield based on FR cellulose and corn starch, was obtained in SSCF of 7.5% FR and 14.5% corn kernels with mineral-salt medium. SSCF could simultaneously convert cellulose into ethanol from both corn kernels and FR, and SSCF ethanol yield was similar between the organic and mineral-salt media. Conclusions Starch ethanol promotes cellulosic ethanol by providing important nutrients for fermentative organisms, and in turn cellulosic ethanol promotes starch ethanol by providing cellulosic enzymes that convert the cellulosic polysaccharides in starch materials into additional ethanol. It is feasible to produce ethanol in SSCF of FR and corn kernels with mineral-salt medium. It would be cost-efficient to produce ethanol in SSCF of high concentrations of water-insoluble solids of lignocellulosic materials and corn kernels. Compared with prehydrolysis and fed-batch strategy using lignocellulosic materials, addition of starch hydrolysates to cellulosic

Classification With Truncated Distance Kernel.

PubMed

Huang, Xiaolin; Suykens, Johan A K; Wang, Shuning; Hornegger, Joachim; Maier, Andreas

2018-05-01

This brief proposes a truncated distance (TL1) kernel, which results in a classifier that is nonlinear in the global region but is linear in each subregion. With this kernel, the subregion structure can be trained using all the training data and local linear classifiers can be established simultaneously. The TL1 kernel has good adaptiveness to nonlinearity and is suitable for problems which require different nonlinearities in different areas. Though the TL1 kernel is not positive semidefinite, some classical kernel learning methods are still applicable which means that the TL1 kernel can be directly used in standard toolboxes by replacing the kernel evaluation. In numerical experiments, the TL1 kernel with a pregiven parameter achieves similar or better performance than the radial basis function kernel with the parameter tuned by cross validation, implying the TL1 kernel a promising nonlinear kernel for classification tasks.

Optimized Kernel Entropy Components.

PubMed

Izquierdo-Verdiguier, Emma; Laparra, Valero; Jenssen, Robert; Gomez-Chova, Luis; Camps-Valls, Gustau

2017-06-01

This brief addresses two main issues of the standard kernel entropy component analysis (KECA) algorithm: the optimization of the kernel decomposition and the optimization of the Gaussian kernel parameter. KECA roughly reduces to a sorting of the importance of kernel eigenvectors by entropy instead of variance, as in the kernel principal components analysis. In this brief, we propose an extension of the KECA method, named optimized KECA (OKECA), that directly extracts the optimal features retaining most of the data entropy by means of compacting the information in very few features (often in just one or two). The proposed method produces features which have higher expressive power. In particular, it is based on the independent component analysis framework, and introduces an extra rotation to the eigen decomposition, which is optimized via gradient-ascent search. This maximum entropy preservation suggests that OKECA features are more efficient than KECA features for density estimation. In addition, a critical issue in both the methods is the selection of the kernel parameter, since it critically affects the resulting performance. Here, we analyze the most common kernel length-scale selection criteria. The results of both the methods are illustrated in different synthetic and real problems. Results show that OKECA returns projections with more expressive power than KECA, the most successful rule for estimating the kernel parameter is based on maximum likelihood, and OKECA is more robust to the selection of the length-scale parameter in kernel density estimation.

In vivo anti-radiation activities of the Ulva pertusa polysaccharides and polysaccharide-iron(III) complex.

PubMed

Shi, Jinming; Cheng, Cuilin; Zhao, Haitian; Jing, Jing; Gong, Ning; Lu, Weihong

2013-09-01

Polysaccharides with different molecular weights were extracted from Ulva pertusa and fractionated by ultrafiltration. Iron(III) complex of the low molecular-weight U. pertusa polysaccharides were synthesized. Atomic absorption spectrum showed that the iron content of iron(III)-polysaccharide complex was 27.4%. The comparison between U. pertusa polysaccharides and their iron(III) complex showed that iron chelating altered the structural characteristics of the polysaccharides. The bioactivity analysis showed that polysaccharide with low molecular weight was more effective than polysaccharide with high molecular weight in protecting mice from radiation induced damages on bone marrow cells and immune system. Results also proved that the anti-radiation and anti-oxidative activity of iron(III) complex of low molecular-weight polysaccharides were not less than that of low molecular-weight polysaccharides. Copyright © 2013 Elsevier B.V. All rights reserved.

Method for producing capsular polysaccharides

NASA Technical Reports Server (NTRS)

Richards, Gil F. (Inventor); Kern, Roger G. (Inventor); Petersen, Gene R. (Inventor)

1994-01-01

Structurally altered capsular polysaccharides are produced by mutant bacteria. These polysaccharides are isolated by selecting a wild type bacterial strain and a phage producing degradative enzymes that have substrate specificity for the capsular polysaccharides produced by the wild type bacteria. Phage-resistant mutants producing capsular polysaccharides are selected and the structurally altered capsular polysaccharide is isolated therefrom.

7 CFR 981.408 - Inedible kernel.

Code of Federal Regulations, 2014 CFR

2014-01-01

... kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as... purposes of determining inedible kernels, pieces, or particles of almond kernels. [59 FR 39419, Aug. 3...

7 CFR 981.408 - Inedible kernel.

Code of Federal Regulations, 2011 CFR

2011-01-01

... kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as... purposes of determining inedible kernels, pieces, or particles of almond kernels. [59 FR 39419, Aug. 3...

7 CFR 981.408 - Inedible kernel.

Code of Federal Regulations, 2012 CFR

2012-01-01

... kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as... purposes of determining inedible kernels, pieces, or particles of almond kernels. [59 FR 39419, Aug. 3...

7 CFR 981.408 - Inedible kernel.

Code of Federal Regulations, 2013 CFR

2013-01-01

... kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as... purposes of determining inedible kernels, pieces, or particles of almond kernels. [59 FR 39419, Aug. 3...

UNICOS Kernel Internals Application Development

NASA Technical Reports Server (NTRS)

Caredo, Nicholas; Craw, James M. (Technical Monitor)

1995-01-01

Having an understanding of UNICOS Kernel Internals is valuable information. However, having the knowledge is only half the value. The second half comes with knowing how to use this information and apply it to the development of tools. The kernel contains vast amounts of useful information that can be utilized. This paper discusses the intricacies of developing utilities that utilize kernel information. In addition, algorithms, logic, and code will be discussed for accessing kernel information. Code segments will be provided that demonstrate how to locate and read kernel structures. Types of applications that can utilize kernel information will also be discussed.

Protein Subcellular Localization with Gaussian Kernel Discriminant Analysis and Its Kernel Parameter Selection.

PubMed

Wang, Shunfang; Nie, Bing; Yue, Kun; Fei, Yu; Li, Wenjia; Xu, Dongshu

2017-12-15

Kernel discriminant analysis (KDA) is a dimension reduction and classification algorithm based on nonlinear kernel trick, which can be novelly used to treat high-dimensional and complex biological data before undergoing classification processes such as protein subcellular localization. Kernel parameters make a great impact on the performance of the KDA model. Specifically, for KDA with the popular Gaussian kernel, to select the scale parameter is still a challenging problem. Thus, this paper introduces the KDA method and proposes a new method for Gaussian kernel parameter selection depending on the fact that the differences between reconstruction errors of edge normal samples and those of interior normal samples should be maximized for certain suitable kernel parameters. Experiments with various standard data sets of protein subcellular localization show that the overall accuracy of protein classification prediction with KDA is much higher than that without KDA. Meanwhile, the kernel parameter of KDA has a great impact on the efficiency, and the proposed method can produce an optimum parameter, which makes the new algorithm not only perform as effectively as the traditional ones, but also reduce the computational time and thus improve efficiency.

Chemical Modification of Polysaccharides

PubMed Central

Cumpstey, Ian

2013-01-01

This review covers methods for modifying the structures of polysaccharides. The introduction of hydrophobic, acidic, basic, or other functionality into polysaccharide structures can alter the properties of materials based on these substances. The development of chemical methods to achieve this aim is an ongoing area of research that is expected to become more important as the emphasis on using renewable starting materials and sustainable processes increases in the future. The methods covered in this review include ester and ether formation using saccharide oxygen nucleophiles, including enzymatic reactions and aspects of regioselectivity; the introduction of heteroatomic nucleophiles into polysaccharide chains; the oxidation of polysaccharides, including oxidative glycol cleavage, chemical oxidation of primary alcohols to carboxylic acids, and enzymatic oxidation of primary alcohols to aldehydes; reactions of uronic-acid-based polysaccharides; nucleophilic reactions of the amines of chitosan; and the formation of unsaturated polysaccharide derivatives. PMID:24151557

7 CFR 981.7 - Edible kernel.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Edible kernel. 981.7 Section 981.7 Agriculture... Regulating Handling Definitions § 981.7 Edible kernel. Edible kernel means a kernel, piece, or particle of almond kernel that is not inedible. [41 FR 26852, June 30, 1976] ...

Unconventional protein sources: apricot seed kernels.

PubMed

Gabrial, G N; El-Nahry, F I; Awadalla, M Z; Girgis, S M

1981-09-01

Hamawy apricot seed kernels (sweet), Amar apricot seed kernels (bitter) and treated Amar apricot kernels (bitterness removed) were evaluated biochemically. All kernels were found to be high in fat (42.2--50.91%), protein (23.74--25.70%) and fiber (15.08--18.02%). Phosphorus, calcium, and iron were determined in all experimental samples. The three different apricot seed kernels were used for extensive study including the qualitative determination of the amino acid constituents by acid hydrolysis, quantitative determination of some amino acids, and biological evaluation of the kernel proteins in order to use them as new protein sources. Weanling albino rats failed to grow on diets containing the Amar apricot seed kernels due to low food consumption because of its bitterness. There was no loss in weight in that case. The Protein Efficiency Ratio data and blood analysis results showed the Hamawy apricot seed kernels to be higher in biological value than treated apricot seed kernels. The Net Protein Ratio data which accounts for both weight, maintenance and growth showed the treated apricot seed kernels to be higher in biological value than both Hamawy and Amar kernels. The Net Protein Ratio for the last two kernels were nearly equal.

7 CFR 981.8 - Inedible kernel.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Inedible kernel. 981.8 Section 981.8 Agriculture... Regulating Handling Definitions § 981.8 Inedible kernel. Inedible kernel means a kernel, piece, or particle of almond kernel with any defect scored as serious damage, or damage due to mold, gum, shrivel, or...

7 CFR 51.1415 - Inedible kernels.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Inedible kernels. 51.1415 Section 51.1415 Agriculture... Standards for Grades of Pecans in the Shell 1 Definitions § 51.1415 Inedible kernels. Inedible kernels means that the kernel or pieces of kernels are rancid, moldy, decayed, injured by insects or otherwise...

7 CFR 981.408 - Inedible kernel.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Inedible kernel. 981.408 Section 981.408 Agriculture... Administrative Rules and Regulations § 981.408 Inedible kernel. Pursuant to § 981.8, the definition of inedible kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as...

LZW-Kernel: fast kernel utilizing variable length code blocks from LZW compressors for protein sequence classification.

PubMed

Filatov, Gleb; Bauwens, Bruno; Kertész-Farkas, Attila

2018-05-07

Bioinformatics studies often rely on similarity measures between sequence pairs, which often pose a bottleneck in large-scale sequence analysis. Here, we present a new convolutional kernel function for protein sequences called the LZW-Kernel. It is based on code words identified with the Lempel-Ziv-Welch (LZW) universal text compressor. The LZW-Kernel is an alignment-free method, it is always symmetric, is positive, always provides 1.0 for self-similarity and it can directly be used with Support Vector Machines (SVMs) in classification problems, contrary to normalized compression distance (NCD), which often violates the distance metric properties in practice and requires further techniques to be used with SVMs. The LZW-Kernel is a one-pass algorithm, which makes it particularly plausible for big data applications. Our experimental studies on remote protein homology detection and protein classification tasks reveal that the LZW-Kernel closely approaches the performance of the Local Alignment Kernel (LAK) and the SVM-pairwise method combined with Smith-Waterman (SW) scoring at a fraction of the time. Moreover, the LZW-Kernel outperforms the SVM-pairwise method when combined with BLAST scores, which indicates that the LZW code words might be a better basis for similarity measures than local alignment approximations found with BLAST. In addition, the LZW-Kernel outperforms n-gram based mismatch kernels, hidden Markov model based SAM and Fisher kernel, and protein family based PSI-BLAST, among others. Further advantages include the LZW-Kernel's reliance on a simple idea, its ease of implementation, and its high speed, three times faster than BLAST and several magnitudes faster than SW or LAK in our tests. LZW-Kernel is implemented as a standalone C code and is a free open-source program distributed under GPLv3 license and can be downloaded from https://github.com/kfattila/LZW-Kernel. akerteszfarkas@hse.ru. Supplementary data are available at Bioinformatics Online.

Mediating chemical reactions using polysaccharides

NASA Astrophysics Data System (ADS)

Tyler, Lauren E.

We have studied the NaBH4-mediated hydrogenation of select alkenes catalyzed by polysaccharide-stabilized nanoparticles. We compared the catalytic properties of Ni-based nanoparticles or Au/Co-based nanoparticles on the hydrogenation of cinnamic acid, cinnamide, cinnamyl alcohol, and ethyl cinnamate. We evaluated the possibility that the type of stabilizing polysaccharide surrounding the nanoparticle may affect the selectivity towards the alkene compounds that undergo the hydrogenation reaction. We found that the hydrogenation of cinnamide or ethyl cinnamate proceeded readily to 100% completion independent of the type of polysaccharide stabilizing the nanoparticle. However, the extent of the hydrogenation of cinnamyl alcohol and cinnamic acid varied greatly depending on the type of polysaccharide stabilizing the nanoparticle. In the course of these studies, we observed that some polysaccharides by themselves promoted the hydrolysis of ethyl cinnamate. Thus, we have raised the hypothesis that some polysaccharides may act as "esterases" and explored the interaction between select polysaccharides and a variety of ester compounds.

Partial Deconvolution with Inaccurate Blur Kernel.

PubMed

Ren, Dongwei; Zuo, Wangmeng; Zhang, David; Xu, Jun; Zhang, Lei

2017-10-17

Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning-based models to suppress the adverse effect of kernel estimation error. Furthermore, an E-M algorithm is developed for estimating the partial map and recovering the latent sharp image alternatively. Experimental results show that our partial deconvolution model is effective in relieving artifacts caused by inaccurate blur kernel, and can achieve favorable deblurring quality on synthetic and real blurry images.Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning

Polysaccharide-Modified Synthetic Polymeric Biomaterials

PubMed Central

Baldwin, Aaron D.; Kiick, Kristi L.

2010-01-01

This review presents an overview of polysaccharide-conjugated synthetic polymers and their use in tissue-engineered scaffolds and drug-delivery applications. This topic will be divided into four categories: (1) polymeric materials modified with non-mammalian polysaccharides such as alginate, chitin, and dextran; (2) polymers modified with mammalian polysaccharides such as hyaluronan, chondroitin sulfate, and heparin; (3) multi-polysaccharide-derivatized polymer conjugate systems; and (4) polymers containing polysaccharide-mimetic molecules. Each section will discuss relevant conjugation techniques, analysis, and the impact of these materials as micelles, particles, or hydrogels used in in-vitro and in-vivo biomaterial applications. PMID:20091875

7 CFR 981.9 - Kernel weight.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Kernel weight. 981.9 Section 981.9 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing Agreements... Regulating Handling Definitions § 981.9 Kernel weight. Kernel weight means the weight of kernels, including...

Biochemical And Genetic Modification Of Polysaccharides

NASA Technical Reports Server (NTRS)

Kern, Roger G.; Petersen, Gene R.; Richards, Gil F.

1993-01-01

Bacteriophages producing endopolysaccharase-type enzymes used to produce, isolate, and purify high yields of modified polysaccharides from polysaccharides produced by, and incorporated into capsules of, certain bacteria. Bacteriophages used in conversion of native polysaccharide materials into polymers of nearly uniform high molecular weight or, alternatively, into highly pure oligosaccharides. Also used in genetic selection of families of polysaccharides structurally related to native polysaccharide materials, but having altered properties. Resulting new polysaccharides and oligosaccharides prove useful in variety of products, including pharmaceutical chemicals, coating materials, biologically active carbohydrates, and drag-reducing additives for fluids.

7 CFR 51.2295 - Half kernel.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Half kernel. 51.2295 Section 51.2295 Agriculture... Standards for Shelled English Walnuts (Juglans Regia) Definitions § 51.2295 Half kernel. Half kernel means the separated half of a kernel with not more than one-eighth broken off. ...

Oecophylla longinoda (Hymenoptera: Formicidae) Lead to Increased Cashew Kernel Size and Kernel Quality.

PubMed

Anato, F M; Sinzogan, A A C; Offenberg, J; Adandonon, A; Wargui, R B; Deguenon, J M; Ayelo, P M; Vayssières, J-F; Kossou, D K

2017-06-01

Weaver ants, Oecophylla spp., are known to positively affect cashew, Anacardium occidentale L., raw nut yield, but their effects on the kernels have not been reported. We compared nut size and the proportion of marketable kernels between raw nuts collected from trees with and without ants. Raw nuts collected from trees with weaver ants were 2.9% larger than nuts from control trees (i.e., without weaver ants), leading to 14% higher proportion of marketable kernels. On trees with ants, the kernel: raw nut ratio from nuts damaged by formic acid was 4.8% lower compared with nondamaged nuts from the same trees. Weaver ants provided three benefits to cashew production by increasing yields, yielding larger nuts, and by producing greater proportions of marketable kernel mass. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Kernel abortion in maize : I. Carbohydrate concentration patterns and Acid invertase activity of maize kernels induced to abort in vitro.

PubMed

Hanft, J M; Jones, R J

1986-06-01

Kernels cultured in vitro were induced to abort by high temperature (35 degrees C) and by culturing six kernels/cob piece. Aborting kernels failed to enter a linear phase of dry mass accumulation and had a final mass that was less than 6% of nonaborting field-grown kernels. Kernels induced to abort by high temperature failed to synthesize starch in the endosperm and had elevated sucrose concentrations and low fructose and glucose concentrations in the pedicel during early growth compared to nonaborting kernels. Kernels induced to abort by high temperature also had much lower pedicel soluble acid invertase activities than did nonaborting kernels. These results suggest that high temperature during the lag phase of kernel growth may impair the process of sucrose unloading in the pedicel by indirectly inhibiting soluble acid invertase activity and prevent starch synthesis in the endosperm. Kernels induced to abort by culturing six kernels/cob piece had reduced pedicel fructose, glucose, and sucrose concentrations compared to kernels from field-grown ears. These aborting kernels also had a lower pedicel soluble acid invertase activity compared to nonaborting kernels from the same cob piece and from field-grown ears. The low invertase activity in pedicel tissue of the aborting kernels was probably caused by a lack of substrate (sucrose) for the invertase to cleave due to the intense competition for available assimilates. In contrast to kernels cultured at 35 degrees C, aborting kernels from cob pieces containing all six kernels accumulated starch in a linear fashion. These results indicate that kernels cultured six/cob piece abort because of an inadequate supply of sugar and are similar to apical kernels from field-grown ears that often abort prior to the onset of linear growth.

An Approximate Approach to Automatic Kernel Selection.

PubMed

Ding, Lizhong; Liao, Shizhong

2016-02-02

Kernel selection is a fundamental problem of kernel-based learning algorithms. In this paper, we propose an approximate approach to automatic kernel selection for regression from the perspective of kernel matrix approximation. We first introduce multilevel circulant matrices into automatic kernel selection, and develop two approximate kernel selection algorithms by exploiting the computational virtues of multilevel circulant matrices. The complexity of the proposed algorithms is quasi-linear in the number of data points. Then, we prove an approximation error bound to measure the effect of the approximation in kernel matrices by multilevel circulant matrices on the hypothesis and further show that the approximate hypothesis produced with multilevel circulant matrices converges to the accurate hypothesis produced with kernel matrices. Experimental evaluations on benchmark datasets demonstrate the effectiveness of approximate kernel selection.

Viscozyme L pretreatment on palm kernels improved the aroma of palm kernel oil after kernel roasting.

PubMed

Zhang, Wencan; Leong, Siew Mun; Zhao, Feifei; Zhao, Fangju; Yang, Tiankui; Liu, Shaoquan

2018-05-01

With an interest to enhance the aroma of palm kernel oil (PKO), Viscozyme L, an enzyme complex containing a wide range of carbohydrases, was applied to alter the carbohydrates in palm kernels (PK) to modulate the formation of volatiles upon kernel roasting. After Viscozyme treatment, the content of simple sugars and free amino acids in PK increased by 4.4-fold and 4.5-fold, respectively. After kernel roasting and oil extraction, significantly more 2,5-dimethylfuran, 2-[(methylthio)methyl]-furan, 1-(2-furanyl)-ethanone, 1-(2-furyl)-2-propanone, 5-methyl-2-furancarboxaldehyde and 2-acetyl-5-methylfuran but less 2-furanmethanol and 2-furanmethanol acetate were found in treated PKO; the correlation between their formation and simple sugar profile was estimated by using partial least square regression (PLS1). Obvious differences in pyrroles and Strecker aldehydes were also found between the control and treated PKOs. Principal component analysis (PCA) clearly discriminated the treated PKOs from that of control PKOs on the basis of all volatile compounds. Such changes in volatiles translated into distinct sensory attributes, whereby treated PKO was more caramelic and burnt after aqueous extraction and more nutty, roasty, caramelic and smoky after solvent extraction. Copyright © 2018 Elsevier Ltd. All rights reserved.

7 CFR 51.1441 - Half-kernel.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Half-kernel. 51.1441 Section 51.1441 Agriculture... Standards for Grades of Shelled Pecans Definitions § 51.1441 Half-kernel. Half-kernel means one of the separated halves of an entire pecan kernel with not more than one-eighth of its original volume missing...

An introduction to kernel-based learning algorithms.

PubMed

Müller, K R; Mika, S; Rätsch, G; Tsuda, K; Schölkopf, B

2001-01-01

This paper provides an introduction to support vector machines, kernel Fisher discriminant analysis, and kernel principal component analysis, as examples for successful kernel-based learning methods. We first give a short background about Vapnik-Chervonenkis theory and kernel feature spaces and then proceed to kernel based learning in supervised and unsupervised scenarios including practical and algorithmic considerations. We illustrate the usefulness of kernel algorithms by discussing applications such as optical character recognition and DNA analysis.

A new discriminative kernel from probabilistic models.

PubMed

Tsuda, Koji; Kawanabe, Motoaki; Rätsch, Gunnar; Sonnenburg, Sören; Müller, Klaus-Robert

2002-10-01

Recently, Jaakkola and Haussler (1999) proposed a method for constructing kernel functions from probabilistic models. Their so-called Fisher kernel has been combined with discriminative classifiers such as support vector machines and applied successfully in, for example, DNA and protein analysis. Whereas the Fisher kernel is calculated from the marginal log-likelihood, we propose the TOP kernel derived; from tangent vectors of posterior log-odds. Furthermore, we develop a theoretical framework on feature extractors from probabilistic models and use it for analyzing the TOP kernel. In experiments, our new discriminative TOP kernel compares favorably to the Fisher kernel.

Kernel Abortion in Maize 1

PubMed Central

Hanft, Jonathan M.; Jones, Robert J.

1986-01-01

This study was designed to compare the uptake and distribution of 14C among fructose, glucose, sucrose, and starch in the cob, pedicel, and endosperm tissues of maize (Zea mays L.) kernels induced to abort by high temperature with those that develop normally. Kernels cultured in vitro at 30 and 35°C were transferred to [14C]sucrose media 10 days after pollination. Kernels cultured at 35°C aborted prior to the onset of linear dry matter accumulation. Significant uptake into the cob, pedicel, and endosperm of radioactivity associated with the soluble and starch fractions of the tissues was detected after 24 hours in culture on labeled media. After 8 days in culture on [14C]sucrose media, 48 and 40% of the radioactivity associated with the cob carbohydrates was found in the reducing sugars at 30 and 35°C, respectively. This indicates that some of the sucrose taken up by the cob tissue was cleaved to fructose and glucose in the cob. Of the total carbohydrates, a higher percentage of label was associated with sucrose and a lower percentage with fructose and glucose in pedicel tissue of kernels cultured at 35°C compared to kernels cultured at 30°C. These results indicate that sucrose was not cleaved to fructose and glucose as rapidly during the unloading process in the pedicel of kernels induced to abort by high temperature. Kernels cultured at 35°C had a much lower proportion of label associated with endosperm starch (29%) than did kernels cultured at 30°C (89%). Kernels cultured at 35°C had a correspondingly higher proportion of 14C in endosperm fructose, glucose, and sucrose. These results indicate that starch synthesis in the endosperm is strongly inhibited in kernels induced to abort by high temperature even though there is an adequate supply of sugar. PMID:16664847

Polysaccharides and food processing.

PubMed

Pilnik, W; Rombouts, F M

1985-10-01

The rôle of polysaccharides during processing and for the quality of foods is discussed. Starch is the most important energy source for man. Most other polysaccharides are not metabolized for energy, but play an important rôle as dietary fibres. Pectins, alginates, carrageenans, and galactomannans are discussed as functional food additives in relation to their structure and their rheological behaviour, stability and interactions. Endogenous polysaccharides of fruits and vegetables and in products derived from them are responsible for such phenomena as texture (changes), press yields, ease of filtration and clarification, cloud stability, and mouth feel. To achieve desirable properties, the action of endogenous enzymes on polysaccharides must be inactivated and/or exogenous enzymes added as processing aids. This is also true for overcoming haze phenomena in clear juices or to break down undesirable microbial polysaccharides. Dough properties for bread baking can be improved by enzymic breakdown of a restrictive pentoglycan network. Network formation may come about by oxidative coupling of phenol rings of ferulic acid bound to hemicelluloses by ester links. Gels may be made by inducing oxidative coupling in natural or synthetic systems. Stagnation in development of new polysaccharide food additives is ascribed to difficulties in obtaining government approval for food use.

Uronic polysaccharide degrading enzymes.

PubMed

Garron, Marie-Line; Cygler, Miroslaw

2014-10-01

In the past several years progress has been made in the field of structure and function of polysaccharide lyases (PLs). The number of classified polysaccharide lyase families has increased to 23 and more detailed analysis has allowed the identification of more closely related subfamilies, leading to stronger correlation between each subfamily and a unique substrate. The number of as yet unclassified polysaccharide lyases has also increased and we expect that sequencing projects will allow many of these unclassified sequences to emerge as new families. The progress in structural analysis of PLs has led to having at least one representative structure for each of the families and for two unclassified enzymes. The newly determined structures have folds observed previously in other PL families and their catalytic mechanisms follow either metal-assisted or Tyr/His mechanisms characteristic for other PL enzymes. Comparison of PLs with glycoside hydrolases (GHs) shows several folds common to both classes but only for the β-helix fold is there strong indication of divergent evolution from a common ancestor. Analysis of bacterial genomes identified gene clusters containing multiple polysaccharide cleaving enzymes, the Polysaccharides Utilization Loci (PULs), and their gene complement suggests that they are organized to process completely a specific polysaccharide. Copyright © 2014 Elsevier Ltd. All rights reserved.

Local Observed-Score Kernel Equating

ERIC Educational Resources Information Center

Wiberg, Marie; van der Linden, Wim J.; von Davier, Alina A.

2014-01-01

Three local observed-score kernel equating methods that integrate methods from the local equating and kernel equating frameworks are proposed. The new methods were compared with their earlier counterparts with respect to such measures as bias--as defined by Lord's criterion of equity--and percent relative error. The local kernel item response…

Polysaccharide-based antibiofilm surfaces.

PubMed

Junter, Guy-Alain; Thébault, Pascal; Lebrun, Laurent

2016-01-01

Surface treatment by natural or modified polysaccharide polymers is a promising means to fight against implant-associated biofilm infections. The present review focuses on polysaccharide-based coatings that have been proposed over the last ten years to impede biofilm formation on material surfaces exposed to bacterial contamination. Anti-adhesive and bactericidal coatings are considered. Besides classical hydrophilic coatings based on hyaluronic acid and heparin, the promising anti-adhesive properties of the algal polysaccharide ulvan are underlined. Surface functionalization by antimicrobial chitosan and derivatives is extensively surveyed, in particular chitosan association with other polysaccharides in layer-by-layer assemblies to form both anti-adhesive and bactericidal coatings. Bacterial contamination of surfaces, leading to biofilm formation, is a major problem in fields as diverse as medicine, first, but also food and cosmetics. Many prophylactic strategies have emerged to try to eliminate or reduce bacterial adhesion and biofilm formation on surfaces of materials exposed to bacterial contamination, in particular implant materials. Polysaccharides are widely distributed in nature. A number of these natural polymers display antibiofilm properties. Hence, surface treatment by natural or modified polysaccharides is a promising means to fight against implant-associated biofilm infections. The present manuscript is an in-depth look at polysaccharide-based antibiofilm surfaces that have been proposed over the last ten years. This review, which is a novelty compared to published literature, will bring well documented and updated information to readers of Acta Biomaterialia. Copyright © 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Credit scoring analysis using kernel discriminant

NASA Astrophysics Data System (ADS)

Widiharih, T.; Mukid, M. A.; Mustafid

2018-05-01

Credit scoring model is an important tool for reducing the risk of wrong decisions when granting credit facilities to applicants. This paper investigate the performance of kernel discriminant model in assessing customer credit risk. Kernel discriminant analysis is a non- parametric method which means that it does not require any assumptions about the probability distribution of the input. The main ingredient is a kernel that allows an efficient computation of Fisher discriminant. We use several kernel such as normal, epanechnikov, biweight, and triweight. The models accuracy was compared each other using data from a financial institution in Indonesia. The results show that kernel discriminant can be an alternative method that can be used to determine who is eligible for a credit loan. In the data we use, it shows that a normal kernel is relevant to be selected for credit scoring using kernel discriminant model. Sensitivity and specificity reach to 0.5556 and 0.5488 respectively.

Tannins of tamarind seed husk: preparation, structural characterization, and antioxidant activities.

PubMed

Sinchaiyakit, Puksiri; Ezure, Yohji; Sriprang, Sarin; Pongbangpho, Supakorn; Povichit, Nasapon; Suttajit, Maitree

2011-06-01

The high content (about 39%) of polymeric tannins in tamarind (Tamarindus indica L.) seed husk (TSH) was demonstrated, and an extract (crude TSE) with a high content (about 94%) of polymeric tannins was prepared from TSH with a one pot extraction using ethanol/water (3:2, v/v). The crude TSE was further purified with Sephadex LH20 to give one fraction (metTSE) eluted with methanol/water (3:2, v/v) and another (acTSE) eluted with acetone/water (3:2, v/v). The tannins of acTSE were established as polymeric proanthocyanidins (PA) by 13C NMR spectroscopy; this was further confirmed by IR and UV spectroscopy, n-BuOH/HCl and vanillin assays, and from HPLC pattern. The ratio of procyanidins to prodelphinidins was 2:3, and the average degree of polymerization of acTSE was 7. Galloylated flavan-3-ols were not detected in acTSE. The main ingredients of metTSE were confirmed to be polymeric PA by 13C NMR spectroscopy. The antioxidant activities using DPPH and ABTS assays were investigated. The IC50 values of acTSE were 4.2 +/- 0.2 (DPPH assay) and 6.2 +/- 0.3 microg/mL (ABTS assay).

Drug Release Studies from Caesalpinia pulcherrima Seed Polysaccharide.

PubMed

Jeevanandham, Somasundaram; Dhachinamoorthi, Duraiswamy; Bannoth Chandra Sekhar, Kothapalli

2011-01-01

This study examines the controlled release behavior of both water-soluble (acetaminophen, caffeine, theophylline and salicylic acid) and water insoluble (indomethacin) drugs derived from Caesalpinia pulcherrima seed Gum isolated from Caesalpinia pulcherrima kernel powder. It further investigates the effect of incorporating diluents such as microcrystalline cellulose and lactose on caffeine release. In addition the effect the gum's (polysaccharide) partial cross-linking had on release of acetaminophen was examined. Applying the exponential equation, the soluble drugs mechanism of release was found to be anomalous. The insoluble drugs showed a near case II or zero order release mechanism. The rate of release in descending order was caffeine, acetaminophen, theophylline, salicylic acid and indomethacin. An increase in the release kinetics of the drug was observed on blending with diluents. However, the rate of release varied with the type and amount of blend within the matrix. The mechanism of release due to effect of diluents was found to be anomalous. The rate of drug release decreased upon partial cross-linking and the mechanism of release was found to be of super case II.

Modeling adaptive kernels from probabilistic phylogenetic trees.

PubMed

Nicotra, Luca; Micheli, Alessio

2009-01-01

Modeling phylogenetic interactions is an open issue in many computational biology problems. In the context of gene function prediction we introduce a class of kernels for structured data leveraging on a hierarchical probabilistic modeling of phylogeny among species. We derive three kernels belonging to this setting: a sufficient statistics kernel, a Fisher kernel, and a probability product kernel. The new kernels are used in the context of support vector machine learning. The kernels adaptivity is obtained through the estimation of the parameters of a tree structured model of evolution using as observed data phylogenetic profiles encoding the presence or absence of specific genes in a set of fully sequenced genomes. We report results obtained in the prediction of the functional class of the proteins of the budding yeast Saccharomyces cerevisae which favorably compare to a standard vector based kernel and to a non-adaptive tree kernel function. A further comparative analysis is performed in order to assess the impact of the different components of the proposed approach. We show that the key features of the proposed kernels are the adaptivity to the input domain and the ability to deal with structured data interpreted through a graphical model representation.

Nonlinear Deep Kernel Learning for Image Annotation.

PubMed

Jiu, Mingyuan; Sahbi, Hichem

2017-02-08

Multiple kernel learning (MKL) is a widely used technique for kernel design. Its principle consists in learning, for a given support vector classifier, the most suitable convex (or sparse) linear combination of standard elementary kernels. However, these combinations are shallow and often powerless to capture the actual similarity between highly semantic data, especially for challenging classification tasks such as image annotation. In this paper, we redefine multiple kernels using deep multi-layer networks. In this new contribution, a deep multiple kernel is recursively defined as a multi-layered combination of nonlinear activation functions, each one involves a combination of several elementary or intermediate kernels, and results into a positive semi-definite deep kernel. We propose four different frameworks in order to learn the weights of these networks: supervised, unsupervised, kernel-based semisupervised and Laplacian-based semi-supervised. When plugged into support vector machines (SVMs), the resulting deep kernel networks show clear gain, compared to several shallow kernels for the task of image annotation. Extensive experiments and analysis on the challenging ImageCLEF photo annotation benchmark, the COREL5k database and the Banana dataset validate the effectiveness of the proposed method.

Computer simulation and experimental study of the polysaccharide-polysaccharide interaction in the bacteria Azospirillum brasilense Sp245

NASA Astrophysics Data System (ADS)

Arefeva, Oksana A.; Kuznetsov, Pavel E.; Tolmachev, Sergey A.; Kupadze, Machammad S.; Khlebtsov, Boris N.; Rogacheva, Svetlana M.

2003-09-01

We have studied the conformational properties and molecular dynamics of polysaccharides by using molecular modeling methods. Theoretical and experimental results of polysaccharide-polysaccharide interactions are described.

Graph Kernels for Molecular Similarity.

PubMed

Rupp, Matthias; Schneider, Gisbert

2010-04-12

Molecular similarity measures are important for many cheminformatics applications like ligand-based virtual screening and quantitative structure-property relationships. Graph kernels are formal similarity measures defined directly on graphs, such as the (annotated) molecular structure graph. Graph kernels are positive semi-definite functions, i.e., they correspond to inner products. This property makes them suitable for use with kernel-based machine learning algorithms such as support vector machines and Gaussian processes. We review the major types of kernels between graphs (based on random walks, subgraphs, and optimal assignments, respectively), and discuss their advantages, limitations, and successful applications in cheminformatics. Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparing Alternative Kernels for the Kernel Method of Test Equating: Gaussian, Logistic, and Uniform Kernels. Research Report. ETS RR-08-12

ERIC Educational Resources Information Center

Lee, Yi-Hsuan; von Davier, Alina A.

2008-01-01

The kernel equating method (von Davier, Holland, & Thayer, 2004) is based on a flexible family of equipercentile-like equating functions that use a Gaussian kernel to continuize the discrete score distributions. While the classical equipercentile, or percentile-rank, equating method carries out the continuization step by linear interpolation,…

Polysaccharide-Based Micelles for Drug Delivery

PubMed Central

Zhang, Nan; Wardwell, Patricia R.; Bader, Rebecca A.

2013-01-01

Delivery of hydrophobic molecules and proteins has been an issue due to poor bioavailability following administration. Thus, micelle carrier systems are being investigated to improve drug solubility and stability. Due to problems with toxicity and immunogenicity, natural polysaccharides are being explored as substitutes for synthetic polymers in the development of new micelle systems. By grafting hydrophobic moieties to the polysaccharide backbone, self-assembled micelles can be readily formed in aqueous solution. Many polysaccharides also possess inherent bioactivity that can facilitate mucoadhesion, enhanced targeting of specific tissues, and a reduction in the inflammatory response. Furthermore, the hydrophilic nature of some polysaccharides can be exploited to enhance circulatory stability. This review will highlight the advantages of polysaccharide use in the development of drug delivery systems and will provide an overview of the polysaccharide-based micelles that have been developed to date. PMID:24300453

High performance solid-state electric double layer capacitor from redox mediated gel polymer electrolyte and renewable tamarind fruit shell derived porous carbon.

PubMed

Senthilkumar, S T; Selvan, R Kalai; Melo, J S; Sanjeeviraja, C

2013-11-13

The activated carbon was derived from tamarind fruit shell and utilized as electrodes in a solid state electrochemical double layer capacitor (SSEDLC). The fabricated SSEDLC with PVA (polyvinyl alcohol)/H2SO4 gel electrolyte delivered high specific capacitance and energy density of 412 F g(-1) and 9.166 W h kg(-1), respectively, at 1.56 A g(-1). Subsequently, Na2MoO4 (sodium molybdate) added PVA/H2SO4 gel electrolyte was also prepared and applied for SSEDLC, to improve the performance. Surprisingly, 57.2% of specific capacitance (648 F g(-1)) and of energy density (14.4 Wh kg(-1)) was increased while introducing Na2MoO4 as the redox mediator in PVA/H2SO4 gel electrolyte. This improved performance is owed to the redox reaction between Mo(VI)/Mo(V) and Mo(VI)/Mo(IV) redox couples in Na2MoO4/PVA/H2SO4 gel electrolyte. Similarly, the fabricated device shows the excellent capacitance retention of 93% for over 3000 cycles. The present work suggests that the Na2MoO4 added PVA/H2SO4 gel is a potential electrolyte to improve the performance instead of pristine PVA/H2SO4 gel electrolyte. Based on the overall performance, it is strongly believed that the combination of tamarind fruit shell derived activated carbon and Na2MoO4/PVA/H2SO4 gel electrolyte is more attractive in the near future for high performance SSEDLCs.

7 CFR 981.401 - Adjusted kernel weight.

Code of Federal Regulations, 2012 CFR

2012-01-01

... based on the analysis of a 1,000 gram sample taken from a lot of almonds weighing 10,000 pounds with less than 95 percent kernels, and a 1,000 gram sample taken from a lot of almonds weighing 10,000... percent kernels containing the following: Edible kernels, 530 grams; inedible kernels, 120 grams; foreign...

7 CFR 981.401 - Adjusted kernel weight.

Code of Federal Regulations, 2011 CFR

2011-01-01

... based on the analysis of a 1,000 gram sample taken from a lot of almonds weighing 10,000 pounds with less than 95 percent kernels, and a 1,000 gram sample taken from a lot of almonds weighing 10,000... percent kernels containing the following: Edible kernels, 530 grams; inedible kernels, 120 grams; foreign...

7 CFR 981.401 - Adjusted kernel weight.

Code of Federal Regulations, 2013 CFR

2013-01-01

... based on the analysis of a 1,000 gram sample taken from a lot of almonds weighing 10,000 pounds with less than 95 percent kernels, and a 1,000 gram sample taken from a lot of almonds weighing 10,000... percent kernels containing the following: Edible kernels, 530 grams; inedible kernels, 120 grams; foreign...

7 CFR 981.401 - Adjusted kernel weight.

Code of Federal Regulations, 2010 CFR

2010-01-01

... based on the analysis of a 1,000 gram sample taken from a lot of almonds weighing 10,000 pounds with less than 95 percent kernels, and a 1,000 gram sample taken from a lot of almonds weighing 10,000... percent kernels containing the following: Edible kernels, 530 grams; inedible kernels, 120 grams; foreign...

7 CFR 981.401 - Adjusted kernel weight.

Code of Federal Regulations, 2014 CFR

2014-01-01

... based on the analysis of a 1,000 gram sample taken from a lot of almonds weighing 10,000 pounds with less than 95 percent kernels, and a 1,000 gram sample taken from a lot of almonds weighing 10,000... percent kernels containing the following: Edible kernels, 530 grams; inedible kernels, 120 grams; foreign...

7 CFR 51.1403 - Kernel color classification.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Kernel color classification. 51.1403 Section 51.1403... STANDARDS) United States Standards for Grades of Pecans in the Shell 1 Kernel Color Classification § 51.1403 Kernel color classification. (a) The skin color of pecan kernels may be described in terms of the color...

Formulation of mucoadhesive gastric retentive drug delivery using thiolated xyloglucan.

PubMed

Bhalekar, Mangesh R; Bargaje, Rajesh V; Upadhaya, Prashant G; Madgulkar, Ashwini R; Kshirsagar, Sanjay J

2016-01-20

Tamarind seed xyloglucan is a polymer reported to possess mucoadhesive property. In the present work, role of cysteine derivative of tamarind seed polysaccharide (thiomer) to enhance the mucoadhesion and its influence on drug permeation has been studied. The xyloglucan was first chemically modified to carboxymethyl derivative which was further converted to thiomer by conjugation with cysteine in presence of a coupling agent, EDAC. The matrix tablets of simvastatin prepared using thiomer demonstrated drug release retardation, increased mucoadhesion force and increased ex vivo permeation, the same were proportional to the increase in the amount of thiomer. The in vivo residence of thiomer placebo was more than 7h in rabbit. Pharmacokinetic evaluation in rabbits indicated higher AUC for the formulation with highest content of thiomer and level 'A' correlation could be established from the generated dissolution and bioavailability data. Copyright © 2015 Elsevier Ltd. All rights reserved.

Cytochemical Localization of Polysaccharides in Dendrobium officinale and the Involvement of DoCSLA6 in the Synthesis of Mannan Polysaccharides

PubMed Central

He, Chunmei; Wu, Kunlin; Zhang, Jianxia; Liu, Xuncheng; Zeng, Songjun; Yu, Zhenming; Zhang, Xinghua; Teixeira da Silva, Jaime A.; Deng, Rufang; Tan, Jianwen; Luo, Jianping; Duan, Jun

2017-01-01

Dendrobium officinale is a precious traditional Chinese medicinal plant because of its abundant polysaccharides found in stems. We determined the composition of water-soluble polysaccharides and starch content in D. officinale stems. The extracted water-soluble polysaccharide content was as high as 35% (w/w). Analysis of the composition of monosaccharides showed that the water-soluble polysaccharides were dominated by mannose, to a lesser extent glucose, and a small amount of galactose, in a molar ratio of 223:48:1. Although starch was also found, its content was less than 10%. This result indicated that the major polysaccharides in D. officinale stems were non-starch polysaccharides, which might be mannan polysaccharides. The polysaccharides formed granules and were stored in plastids similar to starch grains, were localized in D. officinale stems by semi-thin and ultrathin sections. CELLULOSE SYNTHASE-LIKE A (CSLA) family members encode mannan synthases that catalyze the formation of mannan polysaccharides. To determine whether the CSLA gene from D. officinale was responsible for the synthesis of mannan polysaccharides, 35S:DoCSLA6 transgenic lines were generated and characterized. Our results suggest that the CSLA family genes from D. officinale play an important role in the biosynthesis of mannan polysaccharides. PMID:28261235

Out-of-Sample Extensions for Non-Parametric Kernel Methods.

PubMed

Pan, Binbin; Chen, Wen-Sheng; Chen, Bo; Xu, Chen; Lai, Jianhuang

2017-02-01

Choosing suitable kernels plays an important role in the performance of kernel methods. Recently, a number of studies were devoted to developing nonparametric kernels. Without assuming any parametric form of the target kernel, nonparametric kernel learning offers a flexible scheme to utilize the information of the data, which may potentially characterize the data similarity better. The kernel methods using nonparametric kernels are referred to as nonparametric kernel methods. However, many nonparametric kernel methods are restricted to transductive learning, where the prediction function is defined only over the data points given beforehand. They have no straightforward extension for the out-of-sample data points, and thus cannot be applied to inductive learning. In this paper, we show how to make the nonparametric kernel methods applicable to inductive learning. The key problem of out-of-sample extension is how to extend the nonparametric kernel matrix to the corresponding kernel function. A regression approach in the hyper reproducing kernel Hilbert space is proposed to solve this problem. Empirical results indicate that the out-of-sample performance is comparable to the in-sample performance in most cases. Experiments on face recognition demonstrate the superiority of our nonparametric kernel method over the state-of-the-art parametric kernel methods.

Computed tomography coronary stent imaging with iterative reconstruction: a trade-off study between medium kernel and sharp kernel.

PubMed

Zhou, Qijing; Jiang, Biao; Dong, Fei; Huang, Peiyu; Liu, Hongtao; Zhang, Minming

2014-01-01

To evaluate the improvement of iterative reconstruction in image space (IRIS) technique in computed tomographic (CT) coronary stent imaging with sharp kernel, and to make a trade-off analysis. Fifty-six patients with 105 stents were examined by 128-slice dual-source CT coronary angiography (CTCA). Images were reconstructed using standard filtered back projection (FBP) and IRIS with both medium kernel and sharp kernel applied. Image noise and the stent diameter were investigated. Image noise was measured both in background vessel and in-stent lumen as objective image evaluation. Image noise score and stent score were performed as subjective image evaluation. The CTCA images reconstructed with IRIS were associated with significant noise reduction compared to that of CTCA images reconstructed using FBP technique in both of background vessel and in-stent lumen (the background noise decreased by approximately 25.4% ± 8.2% in medium kernel (P kernel (P kernel (P kernel (P kernel showed better visualization of the stent struts and in-stent lumen than that with medium kernel. Iterative reconstruction in image space reconstruction can effectively reduce the image noise and improve image quality. The sharp kernel images constructed with iterative reconstruction are considered the optimal images to observe coronary stents in this study.

Enzymatic method for improving the injectability of polysaccharides

DOEpatents

Griffith, William L.; Compere, Alicia L.; Holleman, James W.

1982-01-01

A method for enhancing the ability of polysaccharides in aqueous solution to flow through a porous medium comprises contacting the polysaccharides with an endoenzyme capable of hydrolyzing at least one of the linkages of the sugar units of the polysaccharides and maintaining the polysaccharides in contact with the enzyme under hydrolysis conditions for a time sufficient to decrease the tendency of the polysaccharides to plug the porous medium yet insufficient to decrease the viscosity of the aqueous polysaccharides by more than 25%. The partially hydrolyzed polysaccharides are useful as thickening agents for flooding water used to recover oil from oil-containing subterranean formations.

Anisotropic hydrodynamics with a scalar collisional kernel

NASA Astrophysics Data System (ADS)

Almaalol, Dekrayat; Strickland, Michael

2018-04-01

Prior studies of nonequilibrium dynamics using anisotropic hydrodynamics have used the relativistic Anderson-Witting scattering kernel or some variant thereof. In this paper, we make the first study of the impact of using a more realistic scattering kernel. For this purpose, we consider a conformal system undergoing transversally homogenous and boost-invariant Bjorken expansion and take the collisional kernel to be given by the leading order 2 ↔2 scattering kernel in scalar λ ϕ4 . We consider both classical and quantum statistics to assess the impact of Bose enhancement on the dynamics. We also determine the anisotropic nonequilibrium attractor of a system subject to this collisional kernel. We find that, when the near-equilibrium relaxation-times in the Anderson-Witting and scalar collisional kernels are matched, the scalar kernel results in a higher degree of momentum-space anisotropy during the system's evolution, given the same initial conditions. Additionally, we find that taking into account Bose enhancement further increases the dynamically generated momentum-space anisotropy.

Polysaccharide Degradation

NASA Astrophysics Data System (ADS)

Stone, Bruce A.; Svensson, Birte; Collins, Michelle E.; Rastall, Robert A.

An overview of current and potential enzymes used to degrade polysaccharides is presented. Such depolymerases are comprised of glycoside hydrolases, glycosyl transferases, phosphorylases and lyases, and their classification, active sites and action patterns are discussed. Additionally, the mechanisms that these enzymes use to cleave glycosidic linkages is reviewed as are inhibitors of depolymerase activity; reagents which react with amino acid residues, glycoside derivatives, transition state inhibitors and proteinaceous inhibitors. The characterization of various enzymes of microbial, animal or plant origin has led to their widespread use in the production of important oligosaccharides which can be incorporated into food stuffs. Sources of polysaccharides of particular interest in this chapter are those from plants and include inulin, dextran, xylan and pectin, as their hydrolysis products are purported to be functional foods in the context of gastrointestinal health. An alternative use of degraded polysaccharides is in the treatment of disease. The possibility exists to treat bacterial exopolysaccharide with lyases from bacteriophage to produce oligosaccharides exhibiting bioactive sequences. Although this area is currently in its infancy the knowledge is available to investigate further.

Ranking Support Vector Machine with Kernel Approximation

PubMed Central

Dou, Yong

2017-01-01

Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM) is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels) can give higher accuracy than linear RankSVM (RankSVM with a linear kernel) for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss) objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms. PMID:28293256

Ranking Support Vector Machine with Kernel Approximation.

PubMed

Chen, Kai; Li, Rongchun; Dou, Yong; Liang, Zhengfa; Lv, Qi

2017-01-01

Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM) is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels) can give higher accuracy than linear RankSVM (RankSVM with a linear kernel) for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss) objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

Rare variant testing across methods and thresholds using the multi-kernel sequence kernel association test (MK-SKAT).

PubMed

Urrutia, Eugene; Lee, Seunggeun; Maity, Arnab; Zhao, Ni; Shen, Judong; Li, Yun; Wu, Michael C

Analysis of rare genetic variants has focused on region-based analysis wherein a subset of the variants within a genomic region is tested for association with a complex trait. Two important practical challenges have emerged. First, it is difficult to choose which test to use. Second, it is unclear which group of variants within a region should be tested. Both depend on the unknown true state of nature. Therefore, we develop the Multi-Kernel SKAT (MK-SKAT) which tests across a range of rare variant tests and groupings. Specifically, we demonstrate that several popular rare variant tests are special cases of the sequence kernel association test which compares pair-wise similarity in trait value to similarity in the rare variant genotypes between subjects as measured through a kernel function. Choosing a particular test is equivalent to choosing a kernel. Similarly, choosing which group of variants to test also reduces to choosing a kernel. Thus, MK-SKAT uses perturbation to test across a range of kernels. Simulations and real data analyses show that our framework controls type I error while maintaining high power across settings: MK-SKAT loses power when compared to the kernel for a particular scenario but has much greater power than poor choices.

Structurally altered capsular polysaccharides produced by mutant bacteria

NASA Technical Reports Server (NTRS)

Petersen, Gene R. (Inventor); Kern, Roger G. (Inventor); Richards, Gil F. (Inventor)

1995-01-01

Structurally altered capsular polysaccharides are produced by mutant bacteria. These polysaccharides are isolated by selecting a wild type bacterial strain and a phage producing degradative enzymes that have substrate specificity for the capsular polysaccharides produced by the wild type bacteria. Phage-resistant mutants producing capsular polysaccharides are selected and the structurally altered capsular polysaccharide is isolated therefrom.

Wigner functions defined with Laplace transform kernels.

PubMed

Oh, Se Baek; Petruccelli, Jonathan C; Tian, Lei; Barbastathis, George

2011-10-24

We propose a new Wigner-type phase-space function using Laplace transform kernels--Laplace kernel Wigner function. Whereas momentum variables are real in the traditional Wigner function, the Laplace kernel Wigner function may have complex momentum variables. Due to the property of the Laplace transform, a broader range of signals can be represented in complex phase-space. We show that the Laplace kernel Wigner function exhibits similar properties in the marginals as the traditional Wigner function. As an example, we use the Laplace kernel Wigner function to analyze evanescent waves supported by surface plasmon polariton. © 2011 Optical Society of America

Knowledge, attitudes and practices in tamarind (Tamarindus indica L) use and conservation in Eastern Uganda.

PubMed

Ebifa-Othieno, Esther; Mugisha, Antony; Nyeko, Philip; Kabasa, John David

2017-01-21

Tamarindus indica L is one of the indigenous fruit tree species that traditionally contributes to food security and ecosystem stability in sub-Saharan Africa. We hypothesized that the indigenous people of Eastern Uganda have used T. indica for generations and developed practices that promote its conservation and therefore we expected that they possess an elaborate indigenous knowledge (IK) system and that most of them have planted the species. The aim of this study was to assess the influence of IK, attitudes and practices on the use and conservation of T. indica. A cross sectional survey was conducted in two districts purposively selected from the T. indica natural range. Focus group discussions, key informant interviews, semi-structured interviews and observation were used to collect data. Data was processed using qualitative analytical methods. Tamarindus indica was highly valued by the majority of the population. Tamarindus indica was used for food, medicinal, cultural, social, environmental amelioration and income generation purposes. The population possessed a high level of IK about T. indica evidenced by 18 categories of uses and multiple modes of use. Fruit pulp was the most commonly used tamarind product. Relative frequency of citation of the different uses provides insight into usage levels and IK possessed. The communities' food and medicinal uses concurred with scientific reports of health benefits of consuming T. indica. Approximately half of respondents had T. indica on their compounds or homegardens (53%). Fifty two percent of the tamarind population was self-propagated, 45% were planted while the propagation history for the remaining 3% was not known. Constraints towards planting T. indica included limited land, long maturation period and low monetary value. Fifty three percent of those who were growing T. indica did not carry out any silvicultural practices. The majority of T. indica encountered (87%) was intercropped with other crops or trees

Metabolic network prediction through pairwise rational kernels.

PubMed

Roche-Lima, Abiel; Domaratzki, Michael; Fristensky, Brian

2014-09-26

Metabolic networks are represented by the set of metabolic pathways. Metabolic pathways are a series of biochemical reactions, in which the product (output) from one reaction serves as the substrate (input) to another reaction. Many pathways remain incompletely characterized. One of the major challenges of computational biology is to obtain better models of metabolic pathways. Existing models are dependent on the annotation of the genes. This propagates error accumulation when the pathways are predicted by incorrectly annotated genes. Pairwise classification methods are supervised learning methods used to classify new pair of entities. Some of these classification methods, e.g., Pairwise Support Vector Machines (SVMs), use pairwise kernels. Pairwise kernels describe similarity measures between two pairs of entities. Using pairwise kernels to handle sequence data requires long processing times and large storage. Rational kernels are kernels based on weighted finite-state transducers that represent similarity measures between sequences or automata. They have been effectively used in problems that handle large amount of sequence information such as protein essentiality, natural language processing and machine translations. We create a new family of pairwise kernels using weighted finite-state transducers (called Pairwise Rational Kernel (PRK)) to predict metabolic pathways from a variety of biological data. PRKs take advantage of the simpler representations and faster algorithms of transducers. Because raw sequence data can be used, the predictor model avoids the errors introduced by incorrect gene annotations. We then developed several experiments with PRKs and Pairwise SVM to validate our methods using the metabolic network of Saccharomyces cerevisiae. As a result, when PRKs are used, our method executes faster in comparison with other pairwise kernels. Also, when we use PRKs combined with other simple kernels that include evolutionary information, the accuracy

Polysaccharide components from the scape of Musa paradisiaca: main structural features of water-soluble polysaccharide component.

PubMed

Anjaneyalu, Y V; Jagadish, R L; Raju, T S

1997-06-01

Polysaccharide components present in the pseudo-stem (scape) of M. paradisiaca were purified from acetone powder of the scape by delignification followed by extraction with aqueous solvents into water soluble polysaccharide (WSP), EDTA-soluble polysaccharide (EDTA-SP), alkali-soluble polysaccharide (ASP) and alkali-insoluble polysaccharide (AISP) fractions. Sugar compositional analysis showed that WSP and EDTA-SP contained only D-Glc whereas ASP contained D-Glc, L-Ara and D-Xyl in approximately 1:1:10 ratio, respectively, and AISP contained D-Glc, L-Ara and D-Xyl in approximately 10:1:2 ratio, respectively. WSP was further purified by complexation with iso-amylalcohol and characterized by specific rotation, IR spectroscopy, Iodine affinity, ferricyanide number, blue value, hydrolysis with alpha-amylase and glucoamylase, and methylation linkage analysis, and shown to be a amylopectin type alpha-D-glucan.

Advances on Bioactive Polysaccharides from Medicinal Plants.

PubMed

Xie, Jian-Hua; Jin, Ming-Liang; Morris, Gordon A; Zha, Xue-Qiang; Chen, Han-Qing; Yi, Yang; Li, Jing-En; Wang, Zhi-Jun; Gao, Jie; Nie, Shao-Ping; Shang, Peng; Xie, Ming-Yong

2016-07-29

In recent decades, the polysaccharides from the medicinal plants have attracted a lot of attention due to their significant bioactivities, such as anti-tumor activity, antioxidant activity, anticoagulant activity, antidiabetic activity, radioprotection effect, anti-viral activity, hypolipidemic and immunomodulatory activities, which make them suitable for medicinal applications. Previous studies have also shown that medicinal plant polysaccharides are non-toxic and show no side effects. Based on these encouraging observations, most researches have been focusing on the isolation and identification of polysaccharides, as well as their bioactivities. A large number of bioactive polysaccharides with different structural features and biological effects from medicinal plants have been purified and characterized. This review provides a comprehensive summary of the most recent developments in physiochemical, structural features and biological activities of bioactive polysaccharides from a number of important medicinal plants, such as polysaccharides from Astragalus membranaceus, Dendrobium plants, Bupleurum, Cactus fruits, Acanthopanax senticosus, Angelica sinensis (Oliv.) Diels, Aloe barbadensis Miller, and Dimocarpus longan Lour. Moreover, the paper has also been focused on the applications of bioactive polysaccharides for medicinal applications. Recent studies have provided evidence that polysaccharides from medicinal plants can play a vital role in bioactivities. The contents and data will serve as a useful reference material for further investigation, production, and application of these polysaccharides in functional foods and therapeutic agents.

Ideal regularization for learning kernels from labels.

PubMed

Pan, Binbin; Lai, Jianhuang; Shen, Lixin

2014-08-01

In this paper, we propose a new form of regularization that is able to utilize the label information of a data set for learning kernels. The proposed regularization, referred to as ideal regularization, is a linear function of the kernel matrix to be learned. The ideal regularization allows us to develop efficient algorithms to exploit labels. Three applications of the ideal regularization are considered. Firstly, we use the ideal regularization to incorporate the labels into a standard kernel, making the resulting kernel more appropriate for learning tasks. Next, we employ the ideal regularization to learn a data-dependent kernel matrix from an initial kernel matrix (which contains prior similarity information, geometric structures, and labels of the data). Finally, we incorporate the ideal regularization to some state-of-the-art kernel learning problems. With this regularization, these learning problems can be formulated as simpler ones which permit more efficient solvers. Empirical results show that the ideal regularization exploits the labels effectively and efficiently. Copyright © 2014 Elsevier Ltd. All rights reserved.

SEMI-SUPERVISED OBJECT RECOGNITION USING STRUCTURE KERNEL

PubMed Central

Wang, Botao; Xiong, Hongkai; Jiang, Xiaoqian; Ling, Fan

2013-01-01

Object recognition is a fundamental problem in computer vision. Part-based models offer a sparse, flexible representation of objects, but suffer from difficulties in training and often use standard kernels. In this paper, we propose a positive definite kernel called “structure kernel”, which measures the similarity of two part-based represented objects. The structure kernel has three terms: 1) the global term that measures the global visual similarity of two objects; 2) the part term that measures the visual similarity of corresponding parts; 3) the spatial term that measures the spatial similarity of geometric configuration of parts. The contribution of this paper is to generalize the discriminant capability of local kernels to complex part-based object models. Experimental results show that the proposed kernel exhibit higher accuracy than state-of-art approaches using standard kernels. PMID:23666108

Structural analysis of cell wall polysaccharides using PACE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mortimer, Jennifer C.

The plant cell wall is composed of many complex polysaccharides. The composition and structure of the polysaccharides affect various cell properties including cell shape, cell function and cell adhesion. Many techniques to characterize polysaccharide structure are complicated, requiring expensive equipment and specialized operators e.g. NMR, MALDI-MS. PACE (Polysaccharide Analysis using Carbohydrate gel Electrophoresis) uses a simple, rapid technique to analyze polysaccharide quantity and structure (Goubet et al. 2002). Whilst the method here describes xylan analysis, it can be applied (by use of the appropriate glycosyl hydrolase) to any cell wall polysaccharide.

The pre-image problem in kernel methods.

PubMed

Kwok, James Tin-yau; Tsang, Ivor Wai-hung

2004-11-01

In this paper, we address the problem of finding the pre-image of a feature vector in the feature space induced by a kernel. This is of central importance in some kernel applications, such as on using kernel principal component analysis (PCA) for image denoising. Unlike the traditional method which relies on nonlinear optimization, our proposed method directly finds the location of the pre-image based on distance constraints in the feature space. It is noniterative, involves only linear algebra and does not suffer from numerical instability or local minimum problems. Evaluations on performing kernel PCA and kernel clustering on the USPS data set show much improved performance.

Exploiting graph kernels for high performance biomedical relation extraction.

PubMed

Panyam, Nagesh C; Verspoor, Karin; Cohn, Trevor; Ramamohanarao, Kotagiri

2018-01-30

Relation extraction from biomedical publications is an important task in the area of semantic mining of text. Kernel methods for supervised relation extraction are often preferred over manual feature engineering methods, when classifying highly ordered structures such as trees and graphs obtained from syntactic parsing of a sentence. Tree kernels such as the Subset Tree Kernel and Partial Tree Kernel have been shown to be effective for classifying constituency parse trees and basic dependency parse graphs of a sentence. Graph kernels such as the All Path Graph kernel (APG) and Approximate Subgraph Matching (ASM) kernel have been shown to be suitable for classifying general graphs with cycles, such as the enhanced dependency parse graph of a sentence. In this work, we present a high performance Chemical-Induced Disease (CID) relation extraction system. We present a comparative study of kernel methods for the CID task and also extend our study to the Protein-Protein Interaction (PPI) extraction task, an important biomedical relation extraction task. We discuss novel modifications to the ASM kernel to boost its performance and a method to apply graph kernels for extracting relations expressed in multiple sentences. Our system for CID relation extraction attains an F-score of 60%, without using external knowledge sources or task specific heuristic or rules. In comparison, the state of the art Chemical-Disease Relation Extraction system achieves an F-score of 56% using an ensemble of multiple machine learning methods, which is then boosted to 61% with a rule based system employing task specific post processing rules. For the CID task, graph kernels outperform tree kernels substantially, and the best performance is obtained with APG kernel that attains an F-score of 60%, followed by the ASM kernel at 57%. The performance difference between the ASM and APG kernels for CID sentence level relation extraction is not significant. In our evaluation of ASM for the PPI task, ASM

Correlation and classification of single kernel fluorescence hyperspectral data with aflatoxin concentration in corn kernels inoculated with Aspergillus flavus spores.

PubMed

Yao, H; Hruska, Z; Kincaid, R; Brown, R; Cleveland, T; Bhatnagar, D

2010-05-01

The objective of this study was to examine the relationship between fluorescence emissions of corn kernels inoculated with Aspergillus flavus and aflatoxin contamination levels within the kernels. Aflatoxin contamination in corn has been a long-standing problem plaguing the grain industry with potentially devastating consequences to corn growers. In this study, aflatoxin-contaminated corn kernels were produced through artificial inoculation of corn ears in the field with toxigenic A. flavus spores. The kernel fluorescence emission data were taken with a fluorescence hyperspectral imaging system when corn kernels were excited with ultraviolet light. Raw fluorescence image data were preprocessed and regions of interest in each image were created for all kernels. The regions of interest were used to extract spectral signatures and statistical information. The aflatoxin contamination level of single corn kernels was then chemically measured using affinity column chromatography. A fluorescence peak shift phenomenon was noted among different groups of kernels with different aflatoxin contamination levels. The fluorescence peak shift was found to move more toward the longer wavelength in the blue region for the highly contaminated kernels and toward the shorter wavelengths for the clean kernels. Highly contaminated kernels were also found to have a lower fluorescence peak magnitude compared with the less contaminated kernels. It was also noted that a general negative correlation exists between measured aflatoxin and the fluorescence image bands in the blue and green regions. The correlation coefficients of determination, r(2), was 0.72 for the multiple linear regression model. The multivariate analysis of variance found that the fluorescence means of four aflatoxin groups, <1, 1-20, 20-100, and >or=100 ng g(-1) (parts per billion), were significantly different from each other at the 0.01 level of alpha. Classification accuracy under a two-class schema ranged from 0.84 to

Adaptive kernel function using line transect sampling

NASA Astrophysics Data System (ADS)

Albadareen, Baker; Ismail, Noriszura

2018-04-01

The estimation of f(0) is crucial in the line transect method which is used for estimating population abundance in wildlife survey's. The classical kernel estimator of f(0) has a high negative bias. Our study proposes an adaptation in the kernel function which is shown to be more efficient than the usual kernel estimator. A simulation study is adopted to compare the performance of the proposed estimators with the classical kernel estimators.

Kernel K-Means Sampling for Nyström Approximation.

PubMed

He, Li; Zhang, Hong

2018-05-01

A fundamental problem in Nyström-based kernel matrix approximation is the sampling method by which training set is built. In this paper, we suggest to use kernel -means sampling, which is shown in our works to minimize the upper bound of a matrix approximation error. We first propose a unified kernel matrix approximation framework, which is able to describe most existing Nyström approximations under many popular kernels, including Gaussian kernel and polynomial kernel. We then show that, the matrix approximation error upper bound, in terms of the Frobenius norm, is equal to the -means error of data points in kernel space plus a constant. Thus, the -means centers of data in kernel space, or the kernel -means centers, are the optimal representative points with respect to the Frobenius norm error upper bound. Experimental results, with both Gaussian kernel and polynomial kernel, on real-world data sets and image segmentation tasks show the superiority of the proposed method over the state-of-the-art methods.

Marine Polysaccharides in Pharmaceutical Applications: An Overview

PubMed Central

Laurienzo, Paola

2010-01-01

The enormous variety of polysaccharides that can be extracted from marine plants and animal organisms or produced by marine bacteria means that the field of marine polysaccharides is constantly evolving. Recent advances in biological techniques allow high levels of polysaccharides of interest to be produced in vitro. Biotechnology is a powerful tool to obtain polysaccharides from a variety of micro-organisms, by controlling the growth conditions in a bioreactor while tailoring the production of biologically active compounds. Following an overview of the current knowledge on marine polysaccharides, with special attention to potential pharmaceutical applications and to more recent progress on the discovering of new polysaccharides with biological appealing characteristics, this review will focus on possible strategies for chemical or physical modification aimed to tailor the final properties of interest. PMID:20948899

7 CFR 51.2125 - Split or broken kernels.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Split or broken kernels. 51.2125 Section 51.2125 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards... kernels. Split or broken kernels means seven-eighths or less of complete whole kernels but which will not...

Robotic Intelligence Kernel: Driver

DOE Office of Scientific and Technical Information (OSTI.GOV)

The INL Robotic Intelligence Kernel-Driver is built on top of the RIK-A and implements a dynamic autonomy structure. The RIK-D is used to orchestrate hardware for sensing and action as well as software components for perception, communication, behavior and world modeling into a single cognitive behavior kernel that provides intrinsic intelligence for a wide variety of unmanned ground vehicle systems.

Bell nozzle kernel analysis program

NASA Technical Reports Server (NTRS)

Elliot, J. J.; Stromstra, R. R.

1969-01-01

Bell Nozzle Kernel Analysis Program computes and analyzes the supersonic flowfield in the kernel, or initial expansion region, of a bell or conical nozzle. It analyzes both plane and axisymmetric geometrices for specified gas properties, nozzle throat geometry and input line.

7 CFR 51.2296 - Three-fourths half kernel.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Three-fourths half kernel. 51.2296 Section 51.2296 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards...-fourths half kernel. Three-fourths half kernel means a portion of a half of a kernel which has more than...

Polysaccharide structure of tetrasporic red seaweed Tichocarpus crinitus.

PubMed

Byankina Barabanova, A O; Sokolova, E V; Anastyuk, S D; Isakov, V V; Glazunov, V P; Volod'ko, A V; Yakovleva, I M; Solov'eva, T F; Yermak, I M

2013-10-15

Sulfated polysaccharide isolated from tetrasporic plants of Tichocarpus crinitus was investigated. The polysaccharide was isolated by two methods: with water extraction at 80 °C (HT) and with a mild alkaline extraction (AE). The extracted polysaccharides were presented by non-gelling ones only, while galactose and 3,6-AG were the main monosaccharides, at the same time amount of 3,6-AG in AE polysaccharides was the similar to that of HT. According to methods of spectroscopy and mass spectrometry, the polysaccharide from tetrasporic T. crinitus contains main blocks of 1,3-linked β-D-galactopyranosyl-2,4-disulfates and 1,4-linked 3,6-anhydro-α-D-galactopyranosyl while 6-sulfated 4-linked galactopyranosyl resudies are randomly distributed along the polysaccharide chain. The alkaline treatment of HT polysaccharide results in obtaining polysaccharide with regular structure that composed of alternating 1,3-linked β-D-galactopyranosyl-2,4-disulfates and 1,4-linked 3,6-anhydro-α-D-galactopyranosyl residues. Native polysaccharide (HT) possessed both high anticoagulant and antiplatelet activity measured by fibrin clotting and platelet aggregation induced by collagen. This activity could be connected with peculiar chemical structure of HT polysaccharide which has high sulfation degree and contains also 3,6-anhydrogalactose in the polymer chain. Copyright © 2013 Elsevier Ltd. All rights reserved.

Application of kernel method in fluorescence molecular tomography

NASA Astrophysics Data System (ADS)

Zhao, Yue; Baikejiang, Reheman; Li, Changqing

2017-02-01

Reconstruction of fluorescence molecular tomography (FMT) is an ill-posed inverse problem. Anatomical guidance in the FMT reconstruction can improve FMT reconstruction efficiently. We have developed a kernel method to introduce the anatomical guidance into FMT robustly and easily. The kernel method is from machine learning for pattern analysis and is an efficient way to represent anatomical features. For the finite element method based FMT reconstruction, we calculate a kernel function for each finite element node from an anatomical image, such as a micro-CT image. Then the fluorophore concentration at each node is represented by a kernel coefficient vector and the corresponding kernel function. In the FMT forward model, we have a new system matrix by multiplying the sensitivity matrix with the kernel matrix. Thus, the kernel coefficient vector is the unknown to be reconstructed following a standard iterative reconstruction process. We convert the FMT reconstruction problem into the kernel coefficient reconstruction problem. The desired fluorophore concentration at each node can be calculated accordingly. Numerical simulation studies have demonstrated that the proposed kernel-based algorithm can improve the spatial resolution of the reconstructed FMT images. In the proposed kernel method, the anatomical guidance can be obtained directly from the anatomical image and is included in the forward modeling. One of the advantages is that we do not need to segment the anatomical image for the targets and background.

Examining Potential Boundary Bias Effects in Kernel Smoothing on Equating: An Introduction for the Adaptive and Epanechnikov Kernels.

PubMed

Cid, Jaime A; von Davier, Alina A

2015-05-01

Test equating is a method of making the test scores from different test forms of the same assessment comparable. In the equating process, an important step involves continuizing the discrete score distributions. In traditional observed-score equating, this step is achieved using linear interpolation (or an unscaled uniform kernel). In the kernel equating (KE) process, this continuization process involves Gaussian kernel smoothing. It has been suggested that the choice of bandwidth in kernel smoothing controls the trade-off between variance and bias. In the literature on estimating density functions using kernels, it has also been suggested that the weight of the kernel depends on the sample size, and therefore, the resulting continuous distribution exhibits bias at the endpoints, where the samples are usually smaller. The purpose of this article is (a) to explore the potential effects of atypical scores (spikes) at the extreme ends (high and low) on the KE method in distributions with different degrees of asymmetry using the randomly equivalent groups equating design (Study I), and (b) to introduce the Epanechnikov and adaptive kernels as potential alternative approaches to reducing boundary bias in smoothing (Study II). The beta-binomial model is used to simulate observed scores reflecting a range of different skewed shapes.

7 CFR 868.254 - Broken kernels determination.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 7 2010-01-01 2010-01-01 false Broken kernels determination. 868.254 Section 868.254 Agriculture Regulations of the Department of Agriculture (Continued) GRAIN INSPECTION, PACKERS AND STOCKYARD... Governing Application of Standards § 868.254 Broken kernels determination. Broken kernels shall be...

Evaluating the Gradient of the Thin Wire Kernel

NASA Technical Reports Server (NTRS)

Wilton, Donald R.; Champagne, Nathan J.

2008-01-01

Recently, a formulation for evaluating the thin wire kernel was developed that employed a change of variable to smooth the kernel integrand, canceling the singularity in the integrand. Hence, the typical expansion of the wire kernel in a series for use in the potential integrals is avoided. The new expression for the kernel is exact and may be used directly to determine the gradient of the wire kernel, which consists of components that are parallel and radial to the wire axis.

Study on extraction process and activity of plant polysaccharides

NASA Astrophysics Data System (ADS)

Ma, Xiaogen; Wang, Xiaojing; Fan, Shuangli; Chen, Jiezhong

2017-10-01

Recent studies have shown that plant polysaccharides have many pharmacological activities, such as hypoglycemic, anti-inflammatory and tumor inhibition. The pharmacological activities of plant polysaccharides were summarized. The extraction methods of plant polysaccharides were discussed. Finally, the extraction process of Herba Taraxaci polysaccharides was optimized by ultrasonic assisted extraction. Through single factor experiments and orthogonal experiment to optimize the optimum extraction process from dandelion polysaccharide, optimum conditions of dandelion root polysaccharide by ultrasonic assisted extraction method for ultrasonic power 320W, temperature 80°C, extraction time 40min, can get higher dandelion polysaccharide extract.

KITTEN Lightweight Kernel 0.1 Beta

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pedretti, Kevin; Levenhagen, Michael; Kelly, Suzanne

2007-12-12

The Kitten Lightweight Kernel is a simplified OS (operating system) kernel that is intended to manage a compute node's hardware resources. It provides a set of mechanisms to user-level applications for utilizing hardware resources (e.g., allocating memory, creating processes, accessing the network). Kitten is much simpler than general-purpose OS kernels, such as Linux or Windows, but includes all of the esssential functionality needed to support HPC (high-performance computing) MPI, PGAS and OpenMP applications. Kitten provides unique capabilities such as physically contiguous application memory, transparent large page support, and noise-free tick-less operation, which enable HPC applications to obtain greater efficiency andmore » scalability than with general purpose OS kernels.« less

Implementing Kernel Methods Incrementally by Incremental Nonlinear Projection Trick.

PubMed

Kwak, Nojun

2016-05-20

Recently, the nonlinear projection trick (NPT) was introduced enabling direct computation of coordinates of samples in a reproducing kernel Hilbert space. With NPT, any machine learning algorithm can be extended to a kernel version without relying on the so called kernel trick. However, NPT is inherently difficult to be implemented incrementally because an ever increasing kernel matrix should be treated as additional training samples are introduced. In this paper, an incremental version of the NPT (INPT) is proposed based on the observation that the centerization step in NPT is unnecessary. Because the proposed INPT does not change the coordinates of the old data, the coordinates obtained by INPT can directly be used in any incremental methods to implement a kernel version of the incremental methods. The effectiveness of the INPT is shown by applying it to implement incremental versions of kernel methods such as, kernel singular value decomposition, kernel principal component analysis, and kernel discriminant analysis which are utilized for problems of kernel matrix reconstruction, letter classification, and face image retrieval, respectively.

7 CFR 868.304 - Broken kernels determination.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 7 2011-01-01 2011-01-01 false Broken kernels determination. 868.304 Section 868.304 Agriculture Regulations of the Department of Agriculture (Continued) GRAIN INSPECTION, PACKERS AND STOCKYARD... Application of Standards § 868.304 Broken kernels determination. Broken kernels shall be determined by the use...

7 CFR 868.304 - Broken kernels determination.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 7 2010-01-01 2010-01-01 false Broken kernels determination. 868.304 Section 868.304 Agriculture Regulations of the Department of Agriculture (Continued) GRAIN INSPECTION, PACKERS AND STOCKYARD... Application of Standards § 868.304 Broken kernels determination. Broken kernels shall be determined by the use...

Polysaccharide-based nanocomposites and their applications

PubMed Central

Zheng, Yingying; Monty, Jonathan; Linhardt, Robert J.

2014-01-01

Polysaccharide nanocomposites have become increasingly important materials over the past decade. Polysaccharides offer a green alternative to synthetic polymers in the preparation of soft nanomaterials. They have also been used in composites with hard nanomaterials, such as metal nanoparticles and carbon-based nanomaterials. This mini review describes methods for polysaccharide nanocomposite preparation and reviews the various types and diverse applications for these novel materials. PMID:25498200

Kernel learning at the first level of inference.

PubMed

Cawley, Gavin C; Talbot, Nicola L C

2014-05-01

Kernel learning methods, whether Bayesian or frequentist, typically involve multiple levels of inference, with the coefficients of the kernel expansion being determined at the first level and the kernel and regularisation parameters carefully tuned at the second level, a process known as model selection. Model selection for kernel machines is commonly performed via optimisation of a suitable model selection criterion, often based on cross-validation or theoretical performance bounds. However, if there are a large number of kernel parameters, as for instance in the case of automatic relevance determination (ARD), there is a substantial risk of over-fitting the model selection criterion, resulting in poor generalisation performance. In this paper we investigate the possibility of learning the kernel, for the Least-Squares Support Vector Machine (LS-SVM) classifier, at the first level of inference, i.e. parameter optimisation. The kernel parameters and the coefficients of the kernel expansion are jointly optimised at the first level of inference, minimising a training criterion with an additional regularisation term acting on the kernel parameters. The key advantage of this approach is that the values of only two regularisation parameters need be determined in model selection, substantially alleviating the problem of over-fitting the model selection criterion. The benefits of this approach are demonstrated using a suite of synthetic and real-world binary classification benchmark problems, where kernel learning at the first level of inference is shown to be statistically superior to the conventional approach, improves on our previous work (Cawley and Talbot, 2007) and is competitive with Multiple Kernel Learning approaches, but with reduced computational expense. Copyright © 2014 Elsevier Ltd. All rights reserved.

Multiple kernels learning-based biological entity relationship extraction method.

PubMed

Dongliang, Xu; Jingchang, Pan; Bailing, Wang

2017-09-20

Automatic extracting protein entity interaction information from biomedical literature can help to build protein relation network and design new drugs. There are more than 20 million literature abstracts included in MEDLINE, which is the most authoritative textual database in the field of biomedicine, and follow an exponential growth over time. This frantic expansion of the biomedical literature can often be difficult to absorb or manually analyze. Thus efficient and automated search engines are necessary to efficiently explore the biomedical literature using text mining techniques. The P, R, and F value of tag graph method in Aimed corpus are 50.82, 69.76, and 58.61%, respectively. The P, R, and F value of tag graph kernel method in other four evaluation corpuses are 2-5% higher than that of all-paths graph kernel. And The P, R and F value of feature kernel and tag graph kernel fuse methods is 53.43, 71.62 and 61.30%, respectively. The P, R and F value of feature kernel and tag graph kernel fuse methods is 55.47, 70.29 and 60.37%, respectively. It indicated that the performance of the two kinds of kernel fusion methods is better than that of simple kernel. In comparison with the all-paths graph kernel method, the tag graph kernel method is superior in terms of overall performance. Experiments show that the performance of the multi-kernels method is better than that of the three separate single-kernel method and the dual-mutually fused kernel method used hereof in five corpus sets.

Gamma scintigraphic evaluation of floating gastroretentive tablets of metformin HCl using a combination of three natural polymers in rabbits

PubMed Central

Razavi, Mahboubeh; Karimian, Hamed; Yeong, Chai Hong; Chung, Lip Yong; Nyamathulla, Shaik; Noordin, Mohamed Ibrahim

2015-01-01

The present research was aimed at formulating a metformin HCl sustained-release formulation from a combination of polymers, using the wet granulation technique. A total of 16 formulations (F1–F16) were produced using different combinations of the gel-forming polymers: tamarind kernel powder, salep (palmate tubers of Orchis morio), and xanthan. Post-compression studies showed that there were no interactions between the active drug and the polymers. Results of in vitro drug-release studies indicated that the F10 formulation which contained 5 mg of tamarind kernel powder, 33.33 mg of xanthan, and 61.67 mg of salep could sustain a 95% release in 12 hours. The results also showed that F2 had a 55% similarity factor with the commercial formulation (C-ER), and the release kinetics were explained with zero order and Higuchi models. The in vivo study was performed in New Zealand White rabbits by gamma scintigraphy; the F10 formulation was radiolabeled using samarium (III) oxide (153Sm2O3) to trace transit of the tablets in the gastrointestinal tract. The in vivo data supported the retention of F10 formulation in the gastric region for 12 hours. In conclusion, the use of a combination of polymers in this study helped to develop an optimal gastroretentive drug-delivery system with improved bioavailability, swelling, and floating characteristics. PMID:26273196

α-Amylase-assisted extraction of polysaccharides from Panax ginseng.

PubMed

Sun, Lin; Wu, Di; Ning, Xin; Yang, Guang; Lin, Ziheng; Tian, Meihong; Zhou, Yifa

2015-04-01

In this paper, α-amylase-assisted extraction was used to isolate the polysaccharide that remained in hot water-extracted ginseng. The yield of the polysaccharide was 9.0%, almost equal to that of the hot water-extracted polysaccharide. Using anion exchange and gel permeation chromatography, the polysaccharide was fractionated into a neutral polysaccharide fraction and six pectic fractions. The neutral fraction accounted for 76% of the polysaccharide and contained both amylopectin and amylose. The pectic polysaccharide fractions were identified to be arabinogalactan, type-I rhamnogalacturonan and homogalacturonan-type pectin by high-performance liquid chromatography, Fourier transform-infrared and nuclear magnetic resonance analysis. Structural and lymphocyte proliferation activity results showed that these polysaccharides were different from those extracted by hot water, indicating that ginseng contains complex polysaccharides with diverse structures, which results in its diverse pharmacological activities. The α-amylase-assisted extraction is a novel method for preparing ginseng polysaccharides and could be applied toward the further study and exploration of ginseng. These findings provide technical and theoretical support for ginseng pharmacology. Copyright © 2015 Elsevier B.V. All rights reserved.

Structural modification of polysaccharides: A biochemical-genetic approach

NASA Technical Reports Server (NTRS)

Kern, Roger G.; Petersen, Gene R.

1991-01-01

Polysaccharides have a wide range of industrial and biomedical applications. An industry trend is underway towards the increased use of bacteria to produce polysaccharides. Long term goals of this work are the adaptation and enhancement of saccharide properties for electronic and optic applications. In this report we illustrate the application of enzyme-bearing bacteriophage on strains of the enteric bacterium Klebsiella pneumoniae, which produces a polysaccharide with the relatively rare rheological property of drag-reduction. This has resulted in the production of new polysaccharides with enhanced rheological properties. Our laboratory is developing techniques for processing and structurally modifying bacterial polysaccharides and oligosaccharides which comprise their basic polymeric repeat units. Our research has focused on bacteriophage which produce specific polysaccharide degrading enzymes. This has lead to the development of enzymes generated by bacteriophage as tools for polysaccharide modification and purification. These enzymes were used to efficiently convert the native material to uniform-sized high molecular weight polymers, or alternatively into high-purity oligosaccharides. Enzyme-bearing bacteriophage also serve as genetic selection tools for bacteria that produce new families of polysaccharides with modified structures.

Unexplored possibilities of all-polysaccharide composites.

PubMed

Simkovic, Ivan

2013-06-20

Composites made solely from polysaccharides are mostly ecological because they can degrade without leaving behind ecologically harmful residues, in contrast to composites which contain synthetic polymers. Herein, the following groups of all-polysaccharide composites (APCs) are discussed: an all-cellulose group that includes cotton composites, cellulose combined with other polysaccharides, as well as those based on chitin/chitosan, heparin, hyaluronan, xylan, glucomannan, pectin, xyloglucan, arabinan, starch, carrageenan, alginate, galactan as one of the components in combination with other polysaccharides. They can be used in medical, paper, food, packing, textile, electronic, mechanical engineering and other applications. The composites were tested for absorptivity, biodegradability, crystallinity, rheology, and mechanical, optical, separation, gelling, pasting, film-forming, adhesive, antimicrobial properties, as well as water vapor permeability, water repellency, dye uptake, and fire-retardancy. Except for food applications, composites based on more than two types of polysaccharides have rarely been used and many possible combinations remain unexplored. Copyright © 2013 Elsevier Ltd. All rights reserved.

7 CFR 51.1403 - Kernel color classification.

Code of Federal Regulations, 2013 CFR

2013-01-01

... generally conforms to the “light” or “light amber” classification, that color classification may be used to... 7 Agriculture 2 2013-01-01 2013-01-01 false Kernel color classification. 51.1403 Section 51.1403... Color Classification § 51.1403 Kernel color classification. (a) The skin color of pecan kernels may be...

7 CFR 51.1403 - Kernel color classification.

Code of Federal Regulations, 2014 CFR

2014-01-01

... generally conforms to the “light” or “light amber” classification, that color classification may be used to... 7 Agriculture 2 2014-01-01 2014-01-01 false Kernel color classification. 51.1403 Section 51.1403... Color Classification § 51.1403 Kernel color classification. (a) The skin color of pecan kernels may be...

Synthesis, characterization and applications of a new cation exchanger tamarind sulphonic acid (TSA) resin.

PubMed

Singh, A V; Sharma, Naresh Kumar; Rathore, Abhay S

2012-01-01

A new composite cation exchanger, tamarind sulphonic acid (TSA) resin has been synthesized. The chemically modified TSA ion exchange resin has been used for the removal and preconcentration of Zn2+, Cd2+, Fe2+, Co2+ and Cu2+ ions in aqueous solution and effluent from the Laxmi steel plant in Jodhpur, India. This type of composite represents a new class of hybrid ion exchangers with good ion exchange capacity, stability, reproducibility and selectivity for toxic metal ions found in effluent from the steel industry. The characterization of the resin was carried out by determining the ion-exchange capacity, elemental analysis, pH titration, Fourier transform infrared spectra and thermal analysis. The distribution coefficients (K(d)) of toxic metal ions were determined in a reference aqueous solution and the steel plant effluent at different pH values; the absorbency of different metal ions on the TSA resin was studied for up to 10 cycles. The adsorption of different metal ions on TSA resin follows the order: Co2+ > Cu2+ > Zn2+ > Fe2+ > Cd2+. The ion exchange capacity of TSA resin is 2.87%.

Evidence-based Kernels: Fundamental Units of Behavioral Influence

PubMed Central

Biglan, Anthony

2008-01-01

This paper describes evidence-based kernels, fundamental units of behavioral influence that appear to underlie effective prevention and treatment for children, adults, and families. A kernel is a behavior–influence procedure shown through experimental analysis to affect a specific behavior and that is indivisible in the sense that removing any of its components would render it inert. Existing evidence shows that a variety of kernels can influence behavior in context, and some evidence suggests that frequent use or sufficient use of some kernels may produce longer lasting behavioral shifts. The analysis of kernels could contribute to an empirically based theory of behavioral influence, augment existing prevention or treatment efforts, facilitate the dissemination of effective prevention and treatment practices, clarify the active ingredients in existing interventions, and contribute to efficiently developing interventions that are more effective. Kernels involve one or more of the following mechanisms of behavior influence: reinforcement, altering antecedents, changing verbal relational responding, or changing physiological states directly. The paper describes 52 of these kernels, and details practical, theoretical, and research implications, including calling for a national database of kernels that influence human behavior. PMID:18712600

Integrating the Gradient of the Thin Wire Kernel

NASA Technical Reports Server (NTRS)

Champagne, Nathan J.; Wilton, Donald R.

2008-01-01

A formulation for integrating the gradient of the thin wire kernel is presented. This approach employs a new expression for the gradient of the thin wire kernel derived from a recent technique for numerically evaluating the exact thin wire kernel. This approach should provide essentially arbitrary accuracy and may be used with higher-order elements and basis functions using the procedure described in [4].When the source and observation points are close, the potential integrals over wire segments involving the wire kernel are split into parts to handle the singular behavior of the integrand [1]. The singularity characteristics of the gradient of the wire kernel are different than those of the wire kernel, and the axial and radial components have different singularities. The characteristics of the gradient of the wire kernel are discussed in [2]. To evaluate the near electric and magnetic fields of a wire, the integration of the gradient of the wire kernel needs to be calculated over the source wire. Since the vector bases for current have constant direction on linear wire segments, these integrals reduce to integrals of the form

THERMOS. 30-Group ENDF/B Scattered Kernels

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCrosson, F.J.; Finch, D.R.

1973-12-01

These data are 30-group THERMOS thermal scattering kernels for P0 to P5 Legendre orders for every temperature of every material from s(alpha,beta) data stored in the ENDF/B library. These scattering kernels were generated using the FLANGE2 computer code. To test the kernels, the integral properties of each set of kernels were determined by a precision integration of the diffusion length equation and compared to experimental measurements of these properties. In general, the agreement was very good. Details of the methods used and results obtained are contained in the reference. The scattering kernels are organized into a two volume magnetic tapemore » library from which they may be retrieved easily for use in any 30-group THERMOS library.« less

Polysaccharide Nanosystems for Future Progress in Cardiovascular Pathologies

PubMed Central

Silva, Amanda Karine Andriola; Letourneur, Didier; Chauvierre, Cédric

2014-01-01

Natural polysaccharides have received a lot of attention in the biomedical field. Indeed, sources of polysaccharides, extracted or produced from plants, bacteria, fungi or algae, are diverse and renewable. Moreover, recent progresses in polysaccharide chemistry and nanotechnologies allow elaborating new dedicated nanosystems. Polysaccharide-based nanosystems may be designed for interacting in several biological processes. In particular, the atherothrombotic pathology is highly concerned by polysaccharide-mediated recognition. Atherothrombotic diseases, regardless of the anatomical localization, remain the main causes of morbidity and mortality in the industrialized world. This review intends to provide an overview on polysaccharide-based nanosystems as drug delivery systems and targeted contrast agents for molecular imaging with an emphasis on the treatment and imaging of cardiovascular pathologies. PMID:24723980

The Classification of Diabetes Mellitus Using Kernel k-means

NASA Astrophysics Data System (ADS)

Alamsyah, M.; Nafisah, Z.; Prayitno, E.; Afida, A. M.; Imah, E. M.

2018-01-01

Diabetes Mellitus is a metabolic disorder which is characterized by chronicle hypertensive glucose. Automatics detection of diabetes mellitus is still challenging. This study detected diabetes mellitus by using kernel k-Means algorithm. Kernel k-means is an algorithm which was developed from k-means algorithm. Kernel k-means used kernel learning that is able to handle non linear separable data; where it differs with a common k-means. The performance of kernel k-means in detecting diabetes mellitus is also compared with SOM algorithms. The experiment result shows that kernel k-means has good performance and a way much better than SOM.

Brain tumor image segmentation using kernel dictionary learning.

PubMed

Jeon Lee; Seung-Jun Kim; Rong Chen; Herskovits, Edward H

2015-08-01

Automated brain tumor image segmentation with high accuracy and reproducibility holds a big potential to enhance the current clinical practice. Dictionary learning (DL) techniques have been applied successfully to various image processing tasks recently. In this work, kernel extensions of the DL approach are adopted. Both reconstructive and discriminative versions of the kernel DL technique are considered, which can efficiently incorporate multi-modal nonlinear feature mappings based on the kernel trick. Our novel discriminative kernel DL formulation allows joint learning of a task-driven kernel-based dictionary and a linear classifier using a K-SVD-type algorithm. The proposed approaches were tested using real brain magnetic resonance (MR) images of patients with high-grade glioma. The obtained preliminary performances are competitive with the state of the art. The discriminative kernel DL approach is seen to reduce computational burden without much sacrifice in performance.

Development of a kernel function for clinical data.

PubMed

Daemen, Anneleen; De Moor, Bart

2009-01-01

For most diseases and examinations, clinical data such as age, gender and medical history guides clinical management, despite the rise of high-throughput technologies. To fully exploit such clinical information, appropriate modeling of relevant parameters is required. As the widely used linear kernel function has several disadvantages when applied to clinical data, we propose a new kernel function specifically developed for this data. This "clinical kernel function" more accurately represents similarities between patients. Evidently, three data sets were studied and significantly better performances were obtained with a Least Squares Support Vector Machine when based on the clinical kernel function compared to the linear kernel function.

Towards the Geometry of Reproducing Kernels

NASA Astrophysics Data System (ADS)

Galé, J. E.

2010-11-01

It is shown here how one is naturally led to consider a category whose objects are reproducing kernels of Hilbert spaces, and how in this way a differential geometry for such kernels may be settled down.

Formation and functional properties of protein-polysaccharide electrostatic hydrogels in comparison to protein or polysaccharide hydrogels.

PubMed

Le, Xuan T; Rioux, Laurie-Eve; Turgeon, Sylvie L

2017-01-01

Protein and polysaccharide mixed systems have been actively studied for at least 50years as they can be assembled into functional particles or gels. This article reviews the properties of electrostatic gels, a recently discovered particular case of associative protein-polysaccharide mixtures formed through associative electrostatic interaction under appropriate solution conditions (coupled gel). This review highlights the factors influencing gel formation such as protein-polysaccharide ratio, biopolymer structural characteristics, final pH, ionic strength and total solid concentration. For the first time, the functional properties of protein-polysaccharide coupled gels are presented and discussed in relationship to individual protein and polysaccharide hydrogels. One of their outstanding characteristics is their gel water retention. Up to 600g of water per g of biopolymer may be retained in the electrostatic gel network compared to a protein gel (3-9g of water per g of protein). Potential applications of the gels are proposed to enable the food and non-food industries to develop new functional products with desirable attributes or new interesting materials to incorporate bioactive molecules. Copyright © 2016 Elsevier B.V. All rights reserved.

Extraction, characterisation and antioxidant activity of Allium sativum polysaccharide.

PubMed

Cheng, Hao; Huang, Gangliang

2018-07-15

Extraction and antioxidant activity of polysaccharide from Allium sativum were investigated. The crude polysaccharide was obtained by the hot-water extraction method. The molecular weight of polysaccharide deproteinized with CaCl 2 was 7.35×10 3 . It indicated that polysaccharide from Allium sativum consisted of three monosaccharides, namely fructose, glucose, and galactose by HPLC. The polysaccharide had the β-glycosidic bond. Moreover, it was proved that the polysaccharide had the potential scavenging ability to superoxide anions and hydroxyl radicals. So, it should be a potential antioxidant. Copyright © 2018 Elsevier B.V. All rights reserved.

Effect of polysaccharide admixtures on expression of multiple polysaccharide-degrading enzymes in Microbulbifer strain CMC-5.

PubMed

Jonnadula, RaviChand; Imran, Md; Poduval, Preethi B; Ghadi, Sanjeev C

2018-03-01

Microbulbifer strain CMC-5 produces agarase, alginate lyase, xylanase, carboxymethyl cellulase and carrageenase. The extracellular production of the above carbohydrases was investigated by growing Microbulbifer strain CMC-5 in a sea water based medium containing homologous/heterologous polysaccharides as a single substrate or as a combination of mixed assorted substrate. Presence of singular homologous polysaccharides in the growth medium induces respective carbohydrase at high levels. Any two polysaccharides in various combinations produced high level of homologous carbohydrase and low level of other heterologous carbohydrase. All five carbohydrases were consistently produced by strain CMC-5, when carboxymethyl cellulose was included as one of the substrate in dual substrate combination, or in presence of mix blends of all five polysaccharides. Interestingly, thalli of Gracilaria sp. that contain agar and cellulose predominantly in their cell wall induces only agarase expression in strain CMC-5.

Kernel-PCA data integration with enhanced interpretability

PubMed Central

2014-01-01

Background Nowadays, combining the different sources of information to improve the biological knowledge available is a challenge in bioinformatics. One of the most powerful methods for integrating heterogeneous data types are kernel-based methods. Kernel-based data integration approaches consist of two basic steps: firstly the right kernel is chosen for each data set; secondly the kernels from the different data sources are combined to give a complete representation of the available data for a given statistical task. Results We analyze the integration of data from several sources of information using kernel PCA, from the point of view of reducing dimensionality. Moreover, we improve the interpretability of kernel PCA by adding to the plot the representation of the input variables that belong to any dataset. In particular, for each input variable or linear combination of input variables, we can represent the direction of maximum growth locally, which allows us to identify those samples with higher/lower values of the variables analyzed. Conclusions The integration of different datasets and the simultaneous representation of samples and variables together give us a better understanding of biological knowledge. PMID:25032747

Gaussian mass optimization for kernel PCA parameters

NASA Astrophysics Data System (ADS)

Liu, Yong; Wang, Zulin

2011-10-01

This paper proposes a novel kernel parameter optimization method based on Gaussian mass, which aims to overcome the current brute force parameter optimization method in a heuristic way. Generally speaking, the choice of kernel parameter should be tightly related to the target objects while the variance between the samples, the most commonly used kernel parameter, doesn't possess much features of the target, which gives birth to Gaussian mass. Gaussian mass defined in this paper has the property of the invariance of rotation and translation and is capable of depicting the edge, topology and shape information. Simulation results show that Gaussian mass leads a promising heuristic optimization boost up for kernel method. In MNIST handwriting database, the recognition rate improves by 1.6% compared with common kernel method without Gaussian mass optimization. Several promising other directions which Gaussian mass might help are also proposed at the end of the paper.

Design of CT reconstruction kernel specifically for clinical lung imaging

NASA Astrophysics Data System (ADS)

Cody, Dianna D.; Hsieh, Jiang; Gladish, Gregory W.

2005-04-01

In this study we developed a new reconstruction kernel specifically for chest CT imaging. An experimental flat-panel CT scanner was used on large dogs to produce 'ground-truth" reference chest CT images. These dogs were also examined using a clinical 16-slice CT scanner. We concluded from the dog images acquired on the clinical scanner that the loss of subtle lung structures was due mostly to the presence of the background noise texture when using currently available reconstruction kernels. This qualitative evaluation of the dog CT images prompted the design of a new recon kernel. This new kernel consisted of the combination of a low-pass and a high-pass kernel to produce a new reconstruction kernel, called the 'Hybrid" kernel. The performance of this Hybrid kernel fell between the two kernels on which it was based, as expected. This Hybrid kernel was also applied to a set of 50 patient data sets; the analysis of these clinical images is underway. We are hopeful that this Hybrid kernel will produce clinical images with an acceptable tradeoff of lung detail, reliable HU, and image noise.

Quality changes in macadamia kernel between harvest and farm-gate.

PubMed

Walton, David A; Wallace, Helen M

2011-02-01

Macadamia integrifolia, Macadamia tetraphylla and their hybrids are cultivated for their edible kernels. After harvest, nuts-in-shell are partially dried on-farm and sorted to eliminate poor-quality kernels before consignment to a processor. During these operations, kernel quality may be lost. In this study, macadamia nuts-in-shell were sampled at five points of an on-farm postharvest handling chain from dehusking to the final storage silo to assess quality loss prior to consignment. Shoulder damage, weight of pieces and unsound kernel were assessed for raw kernels, and colour, mottled colour and surface damage for roasted kernels. Shoulder damage, weight of pieces and unsound kernel for raw kernels increased significantly between the dehusker and the final silo. Roasted kernels displayed a significant increase in dark colour, mottled colour and surface damage during on-farm handling. Significant loss of macadamia kernel quality occurred on a commercial farm during sorting and storage of nuts-in-shell before nuts were consigned to a processor. Nuts-in-shell should be dried as quickly as possible and on-farm handling minimised to maintain optimum kernel quality. 2010 Society of Chemical Industry.

Unified heat kernel regression for diffusion, kernel smoothing and wavelets on manifolds and its application to mandible growth modeling in CT images.

PubMed

Chung, Moo K; Qiu, Anqi; Seo, Seongho; Vorperian, Houri K

2015-05-01

We present a novel kernel regression framework for smoothing scalar surface data using the Laplace-Beltrami eigenfunctions. Starting with the heat kernel constructed from the eigenfunctions, we formulate a new bivariate kernel regression framework as a weighted eigenfunction expansion with the heat kernel as the weights. The new kernel method is mathematically equivalent to isotropic heat diffusion, kernel smoothing and recently popular diffusion wavelets. The numerical implementation is validated on a unit sphere using spherical harmonics. As an illustration, the method is applied to characterize the localized growth pattern of mandible surfaces obtained in CT images between ages 0 and 20 by regressing the length of displacement vectors with respect to a surface template. Copyright © 2015 Elsevier B.V. All rights reserved.

Hypolipidemic effects of crude green tea polysaccharide on rats, and structural features of tea polysaccharides isolated from the crude polysaccharide.

PubMed

Nakamura, Michiko; Miura, Sayaka; Takagaki, Akiko; Nanjo, Fumio

2017-05-01

Crude tea polysaccharide (crude TPS) was prepared from instant green tea by ethanol precipitation followed by ultrafiltration membrane treatment and its effects on blood lipid, liver lipid, and fecal lipid levels were examined with Sprague-Dawley rats fed a high-fat diet. Although crude TPS showed no effects on the serum lipid levels, it suppressed the liver lipid accumulation and increased the fecal excretion of dietary fat. Then, the structural features of crude TPS were investigated. After separation of crude TPS by DEAE-cellulose and gel-filtration column chromatography, two kinds of neutral tea polysaccharides (NTPS-LP and NTPS-HH) and an acidic polysaccharide (ATPS-MH) were obtained. According to monosaccharide composition, methylation, and NMR analyses, NTPS-LP, NPTS-HH, and ATPS-MH were presumed to be starch, arabinogalactan with β-1,3-linked galactosyl backbone blanched at position 6 and with 1,5-linked arabinofuranosyl residues, and α-1,4-linked galacturonic acid backbone with arabinogalactan region, respectively.

Quantum kernel applications in medicinal chemistry.

PubMed

Huang, Lulu; Massa, Lou

2012-07-01

Progress in the quantum mechanics of biological molecules is being driven by computational advances. The notion of quantum kernels can be introduced to simplify the formalism of quantum mechanics, making it especially suitable for parallel computation of very large biological molecules. The essential idea is to mathematically break large biological molecules into smaller kernels that are calculationally tractable, and then to represent the full molecule by a summation over the kernels. The accuracy of the kernel energy method (KEM) is shown by systematic application to a great variety of molecular types found in biology. These include peptides, proteins, DNA and RNA. Examples are given that explore the KEM across a variety of chemical models, and to the outer limits of energy accuracy and molecular size. KEM represents an advance in quantum biology applicable to problems in medicine and drug design.

Generalization Performance of Regularized Ranking With Multiscale Kernels.

PubMed

Zhou, Yicong; Chen, Hong; Lan, Rushi; Pan, Zhibin

2016-05-01

The regularized kernel method for the ranking problem has attracted increasing attentions in machine learning. The previous regularized ranking algorithms are usually based on reproducing kernel Hilbert spaces with a single kernel. In this paper, we go beyond this framework by investigating the generalization performance of the regularized ranking with multiscale kernels. A novel ranking algorithm with multiscale kernels is proposed and its representer theorem is proved. We establish the upper bound of the generalization error in terms of the complexity of hypothesis spaces. It shows that the multiscale ranking algorithm can achieve satisfactory learning rates under mild conditions. Experiments demonstrate the effectiveness of the proposed method for drug discovery and recommendation tasks.

Multineuron spike train analysis with R-convolution linear combination kernel.

PubMed

Tezuka, Taro

2018-06-01

A spike train kernel provides an effective way of decoding information represented by a spike train. Some spike train kernels have been extended to multineuron spike trains, which are simultaneously recorded spike trains obtained from multiple neurons. However, most of these multineuron extensions were carried out in a kernel-specific manner. In this paper, a general framework is proposed for extending any single-neuron spike train kernel to multineuron spike trains, based on the R-convolution kernel. Special subclasses of the proposed R-convolution linear combination kernel are explored. These subclasses have a smaller number of parameters and make optimization tractable when the size of data is limited. The proposed kernel was evaluated using Gaussian process regression for multineuron spike trains recorded from an animal brain. It was compared with the sum kernel and the population Spikernel, which are existing ways of decoding multineuron spike trains using kernels. The results showed that the proposed approach performs better than these kernels and also other commonly used neural decoding methods. Copyright © 2018 Elsevier Ltd. All rights reserved.

Putting Priors in Mixture Density Mercer Kernels

NASA Technical Reports Server (NTRS)

Srivastava, Ashok N.; Schumann, Johann; Fischer, Bernd

2004-01-01

This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly infinite dimensional feature space. We describe a new method called Mixture Density Mercer Kernels to learn kernel function directly from data, rather than using predefined kernels. These data adaptive kernels can en- code prior knowledge in the kernel using a Bayesian formulation, thus allowing for physical information to be encoded in the model. We compare the results with existing algorithms on data from the Sloan Digital Sky Survey (SDSS). The code for these experiments has been generated with the AUTOBAYES tool, which automatically generates efficient and documented C/C++ code from abstract statistical model specifications. The core of the system is a schema library which contains template for learning and knowledge discovery algorithms like different versions of EM, or numeric optimization methods like conjugate gradient methods. The template instantiation is supported by symbolic- algebraic computations, which allows AUTOBAYES to find closed-form solutions and, where possible, to integrate them into the code. The results show that the Mixture Density Mercer-Kernel described here outperforms tree-based classification in distinguishing high-redshift galaxies from low- redshift galaxies by approximately 16% on test data, bagged trees by approximately 7%, and bagged trees built on a much larger sample of data by approximately 2%.

Increasing accuracy of dispersal kernels in grid-based population models

USGS Publications Warehouse

Slone, D.H.

2011-01-01

Dispersal kernels in grid-based population models specify the proportion, distance and direction of movements within the model landscape. Spatial errors in dispersal kernels can have large compounding effects on model accuracy. Circular Gaussian and Laplacian dispersal kernels at a range of spatial resolutions were investigated, and methods for minimizing errors caused by the discretizing process were explored. Kernels of progressively smaller sizes relative to the landscape grid size were calculated using cell-integration and cell-center methods. These kernels were convolved repeatedly, and the final distribution was compared with a reference analytical solution. For large Gaussian kernels (σ > 10 cells), the total kernel error was <10 &sup-11; compared to analytical results. Using an invasion model that tracked the time a population took to reach a defined goal, the discrete model results were comparable to the analytical reference. With Gaussian kernels that had σ ≤ 0.12 using the cell integration method, or σ ≤ 0.22 using the cell center method, the kernel error was greater than 10%, which resulted in invasion times that were orders of magnitude different than theoretical results. A goal-seeking routine was developed to adjust the kernels to minimize overall error. With this, corrections for small kernels were found that decreased overall kernel error to <10-11 and invasion time error to <5%.

An SVM model with hybrid kernels for hydrological time series

NASA Astrophysics Data System (ADS)

Wang, C.; Wang, H.; Zhao, X.; Xie, Q.

2017-12-01

Support Vector Machine (SVM) models have been widely applied to the forecast of climate/weather and its impact on other environmental variables such as hydrologic response to climate/weather. When using SVM, the choice of the kernel function plays the key role. Conventional SVM models mostly use one single type of kernel function, e.g., radial basis kernel function. Provided that there are several featured kernel functions available, each having its own advantages and drawbacks, a combination of these kernel functions may give more flexibility and robustness to SVM approach, making it suitable for a wide range of application scenarios. This paper presents such a linear combination of radial basis kernel and polynomial kernel for the forecast of monthly flowrate in two gaging stations using SVM approach. The results indicate significant improvement in the accuracy of predicted series compared to the approach with either individual kernel function, thus demonstrating the feasibility and advantages of such hybrid kernel approach for SVM applications.

Graph wavelet alignment kernels for drug virtual screening.

PubMed

Smalter, Aaron; Huan, Jun; Lushington, Gerald

2009-06-01

In this paper, we introduce a novel statistical modeling technique for target property prediction, with applications to virtual screening and drug design. In our method, we use graphs to model chemical structures and apply a wavelet analysis of graphs to summarize features capturing graph local topology. We design a novel graph kernel function to utilize the topology features to build predictive models for chemicals via Support Vector Machine classifier. We call the new graph kernel a graph wavelet-alignment kernel. We have evaluated the efficacy of the wavelet-alignment kernel using a set of chemical structure-activity prediction benchmarks. Our results indicate that the use of the kernel function yields performance profiles comparable to, and sometimes exceeding that of the existing state-of-the-art chemical classification approaches. In addition, our results also show that the use of wavelet functions significantly decreases the computational costs for graph kernel computation with more than ten fold speedup.

Small convolution kernels for high-fidelity image restoration

NASA Technical Reports Server (NTRS)

Reichenbach, Stephen E.; Park, Stephen K.

1991-01-01

An algorithm is developed for computing the mean-square-optimal values for small, image-restoration kernels. The algorithm is based on a comprehensive, end-to-end imaging system model that accounts for the important components of the imaging process: the statistics of the scene, the point-spread function of the image-gathering device, sampling effects, noise, and display reconstruction. Subject to constraints on the spatial support of the kernel, the algorithm generates the kernel values that restore the image with maximum fidelity, that is, the kernel minimizes the expected mean-square restoration error. The algorithm is consistent with the derivation of the spatially unconstrained Wiener filter, but leads to a small, spatially constrained kernel that, unlike the unconstrained filter, can be efficiently implemented by convolution. Simulation experiments demonstrate that for a wide range of imaging systems these small kernels can restore images with fidelity comparable to images restored with the unconstrained Wiener filter.

Reduced multiple empirical kernel learning machine.

PubMed

Wang, Zhe; Lu, MingZhe; Gao, Daqi

2015-02-01

Multiple kernel learning (MKL) is demonstrated to be flexible and effective in depicting heterogeneous data sources since MKL can introduce multiple kernels rather than a single fixed kernel into applications. However, MKL would get a high time and space complexity in contrast to single kernel learning, which is not expected in real-world applications. Meanwhile, it is known that the kernel mapping ways of MKL generally have two forms including implicit kernel mapping and empirical kernel mapping (EKM), where the latter is less attracted. In this paper, we focus on the MKL with the EKM, and propose a reduced multiple empirical kernel learning machine named RMEKLM for short. To the best of our knowledge, it is the first to reduce both time and space complexity of the MKL with EKM. Different from the existing MKL, the proposed RMEKLM adopts the Gauss Elimination technique to extract a set of feature vectors, which is validated that doing so does not lose much information of the original feature space. Then RMEKLM adopts the extracted feature vectors to span a reduced orthonormal subspace of the feature space, which is visualized in terms of the geometry structure. It can be demonstrated that the spanned subspace is isomorphic to the original feature space, which means that the dot product of two vectors in the original feature space is equal to that of the two corresponding vectors in the generated orthonormal subspace. More importantly, the proposed RMEKLM brings a simpler computation and meanwhile needs a less storage space, especially in the processing of testing. Finally, the experimental results show that RMEKLM owns a much efficient and effective performance in terms of both complexity and classification. The contributions of this paper can be given as follows: (1) by mapping the input space into an orthonormal subspace, the geometry of the generated subspace is visualized; (2) this paper first reduces both the time and space complexity of the EKM-based MKL; (3

7 CFR 981.61 - Redetermination of kernel weight.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Redetermination of kernel weight. 981.61 Section 981... GROWN IN CALIFORNIA Order Regulating Handling Volume Regulation § 981.61 Redetermination of kernel weight. The Board, on the basis of reports by handlers, shall redetermine the kernel weight of almonds...

Enhanced gluten properties in soft kernel durum wheat

USDA-ARS?s Scientific Manuscript database

Soft kernel durum wheat is a relatively recent development (Morris et al. 2011 Crop Sci. 51:114). The soft kernel trait exerts profound effects on kernel texture, flour milling including break flour yield, milling energy, and starch damage, and dough water absorption (DWA). With the caveat of reduce...

Accelerating the Original Profile Kernel.

PubMed

Hamp, Tobias; Goldberg, Tatyana; Rost, Burkhard

2013-01-01

One of the most accurate multi-class protein classification systems continues to be the profile-based SVM kernel introduced by the Leslie group. Unfortunately, its CPU requirements render it too slow for practical applications of large-scale classification tasks. Here, we introduce several software improvements that enable significant acceleration. Using various non-redundant data sets, we demonstrate that our new implementation reaches a maximal speed-up as high as 14-fold for calculating the same kernel matrix. Some predictions are over 200 times faster and render the kernel as possibly the top contender in a low ratio of speed/performance. Additionally, we explain how to parallelize various computations and provide an integrative program that reduces creating a production-quality classifier to a single program call. The new implementation is available as a Debian package under a free academic license and does not depend on commercial software. For non-Debian based distributions, the source package ships with a traditional Makefile-based installer. Download and installation instructions can be found at https://rostlab.org/owiki/index.php/Fast_Profile_Kernel. Bugs and other issues may be reported at https://rostlab.org/bugzilla3/enter_bug.cgi?product=fastprofkernel.

Effects of selenizing angelica polysaccharide and selenizing garlic polysaccharide on immune function of murine peritoneal macrophage.

PubMed

Gao, Zhenzhen; Liu, Kuanhui; Tian, Weijun; Wang, Hongchao; Liu, Zhenguang; Li, Youying; Li, Entao; Liu, Cui; Li, Xiuping; Hou, Ranran; Yue, Chanjuan; Wang, Deyun; Hu, Yuanliang

2015-07-01

The effects of two selenizing polysaccharides (sCAP2 and sGPS6) on immune function of murine peritoneal macrophages taking two non-selenizing polysaccharides (CAP and GPS) and modifier Na2SeO3 as control. In vitro test, the changes of selenizing polysaccharides, non-selenizing polysaccharides and Na2SeO3 on murine macrophages function were evaluated by phagocytosis and nitric oxide (NO) secretion tests. In vivo test, the mice were injected respectively with 0.2, 0.4 and 0.6 mg of sCAP2, sGPS6, CAP and GPS, or Na2SeO3 80 μg or normal saline 0.4 mL. The peritoneal macrophages were collected and cultured to determine the contents of TNF-α, IL-6 and IL-10 in supernatants by enzyme-linked immunosorbent assay. The results showed that sCAP2 and sGPS6 could significantly promote the phagocytosis and secretion of NO and three cytokines of macrophages in comparison with CAP and GPS. sCAP2 possessed the strongest activity. This indicates that selenylation modification can further improve the immune-enhancing activity of polysaccharide, and sCAP2 could be as a new immunopotentiator. Copyright © 2015 Elsevier B.V. All rights reserved.

7 CFR 981.60 - Determination of kernel weight.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Determination of kernel weight. 981.60 Section 981.60... Regulating Handling Volume Regulation § 981.60 Determination of kernel weight. (a) Almonds for which settlement is made on kernel weight. All lots of almonds, whether shelled or unshelled, for which settlement...

End-use quality of soft kernel durum wheat

USDA-ARS?s Scientific Manuscript database

Kernel texture is a major determinant of end-use quality of wheat. Durum wheat has very hard kernels. We developed soft kernel durum wheat via Ph1b-mediated homoeologous recombination. The Hardness locus was transferred from Chinese Spring to Svevo durum wheat via back-crossing. ‘Soft Svevo’ had SKC...

Deep Restricted Kernel Machines Using Conjugate Feature Duality.

PubMed

Suykens, Johan A K

2017-08-01

The aim of this letter is to propose a theory of deep restricted kernel machines offering new foundations for deep learning with kernel machines. From the viewpoint of deep learning, it is partially related to restricted Boltzmann machines, which are characterized by visible and hidden units in a bipartite graph without hidden-to-hidden connections and deep learning extensions as deep belief networks and deep Boltzmann machines. From the viewpoint of kernel machines, it includes least squares support vector machines for classification and regression, kernel principal component analysis (PCA), matrix singular value decomposition, and Parzen-type models. A key element is to first characterize these kernel machines in terms of so-called conjugate feature duality, yielding a representation with visible and hidden units. It is shown how this is related to the energy form in restricted Boltzmann machines, with continuous variables in a nonprobabilistic setting. In this new framework of so-called restricted kernel machine (RKM) representations, the dual variables correspond to hidden features. Deep RKM are obtained by coupling the RKMs. The method is illustrated for deep RKM, consisting of three levels with a least squares support vector machine regression level and two kernel PCA levels. In its primal form also deep feedforward neural networks can be trained within this framework.

Improved modeling of clinical data with kernel methods.

PubMed

Daemen, Anneleen; Timmerman, Dirk; Van den Bosch, Thierry; Bottomley, Cecilia; Kirk, Emma; Van Holsbeke, Caroline; Valentin, Lil; Bourne, Tom; De Moor, Bart

2012-02-01

Despite the rise of high-throughput technologies, clinical data such as age, gender and medical history guide clinical management for most diseases and examinations. To improve clinical management, available patient information should be fully exploited. This requires appropriate modeling of relevant parameters. When kernel methods are used, traditional kernel functions such as the linear kernel are often applied to the set of clinical parameters. These kernel functions, however, have their disadvantages due to the specific characteristics of clinical data, being a mix of variable types with each variable its own range. We propose a new kernel function specifically adapted to the characteristics of clinical data. The clinical kernel function provides a better representation of patients' similarity by equalizing the influence of all variables and taking into account the range r of the variables. Moreover, it is robust with respect to changes in r. Incorporated in a least squares support vector machine, the new kernel function results in significantly improved diagnosis, prognosis and prediction of therapy response. This is illustrated on four clinical data sets within gynecology, with an average increase in test area under the ROC curve (AUC) of 0.023, 0.021, 0.122 and 0.019, respectively. Moreover, when combining clinical parameters and expression data in three case studies on breast cancer, results improved overall with use of the new kernel function and when considering both data types in a weighted fashion, with a larger weight assigned to the clinical parameters. The increase in AUC with respect to a standard kernel function and/or unweighted data combination was maximum 0.127, 0.042 and 0.118 for the three case studies. For clinical data consisting of variables of different types, the proposed kernel function--which takes into account the type and range of each variable--has shown to be a better alternative for linear and non-linear classification problems

Synthesis and characterization of hydrogel films of carboxymethyl tamarind gum using citric acid.

PubMed

Mali, Kailas K; Dhawale, Shashikant C; Dias, Remeth J

2017-12-01

The objective of this study was to synthesize and characterize citric acid crosslinked carboxymethyl tamarind gum (CMTG) hydrogels films. The hydrogel films were characterized by Attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy, solid state 13 C-nuclear magnetic resonance ( 13 C NMR) spectroscopy and differential scanning calorimeter (DSC). The prepared hydrogel films were evaluated for the carboxyl content and swelling ratio. The model drug moxifloxacin hydrochloride was loaded into hydrogels films and drug release was studied at pH 7.4. The hemolysis assay was used to study the biocompatibility of hydrogel films. The results of ATR-FTIR, solid state 13 C NMR and DSC confirmed the formation of ester crosslinks between citric acid and CMTG. The total carboxyl content of hydrogel film was found to be decreased when amount of CMTG was increased. The swelling of hydrogel film was found to be decreased with increase in curing temperature and time. CMTG hydrogel films showed high drug loading with non-Fickian release mechanism suggesting controlled release of drug. The hydrogel films were found to be biocompatible. It can be concluded that the citric acid can be used for the preparation of CMTG hydrogel films. Further, CMTG hydrogel film can be used potentially for controlled release of drug. Copyright © 2017 Elsevier B.V. All rights reserved.

In vitro prebiotic effects of seaweed polysaccharides

NASA Astrophysics Data System (ADS)

Chen, Xiaolin; Sun, Yuhao; Hu, Linfeng; Liu, Song; Yu, Huahua; Xing, Rong'e.; Li, Rongfeng; Wang, Xueqin; Li, Pengcheng

2017-09-01

Although prebiotic activities of alginate and agar oligosaccharides isolated from seaweeds have been reported, it remains unknown whether seaweed polysaccharides have prebiotic activity. In this study, we isolated polysaccharides from four species of seaweeds, such as Grateloupia filicina (GFP), Eucheuma spinosum (ESP), Ulva pertusa (UPP), and Ascophyllum nodosum (ANP), and characterized their structures and prebiotic effects in vitro. The results showed that these polysaccharides were different in total sugar and sulfate contents as well as monosaccharide composition. GFP and ESP significantly promoted bifidobacterium proliferation and 0.1% ESP and 0.4% GFP resulted in the highest proliferation rates of beneficial bacteria, whereas UPP and ANP inhibited the growth of beneficial bacteria at all tested concentrations (0.1%-0.5%). The different behaviors of the four seaweed-originated polysaccharides might be reflected by differences in monosaccharide composition and structure. Therefore, polysaccharides isolated from GFP and ESP could be utilized as prebiotics. However, more studies must be carried out in vivo.

Triso coating development progress for uranium nitride kernels

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jolly, Brian C.; Lindemer, Terrence; Terrani, Kurt A.

2015-08-01

In support of fully ceramic matrix (FCM) fuel development [1-2], coating development work is ongoing at the Oak Ridge National Laboratory (ORNL) to produce tri-structural isotropic (TRISO) coated fuel particles with UN kernels [3]. The nitride kernels are used to increase fissile density in these SiC-matrix fuel pellets with details described elsewhere [4]. The advanced gas reactor (AGR) program at ORNL used fluidized bed chemical vapor deposition (FBCVD) techniques for TRISO coating of UCO (two phase mixture of UO2 and UCx) kernels [5]. Similar techniques were employed for coating of the UN kernels, however significant changes in processing conditions weremore » required to maintain acceptable coating properties due to physical property and dimensional differences between the UCO and UN kernels (Table 1).« less

Preparation Methods and Antioxidant Activities of Polysaccharides and Their Derivatives.

PubMed

Mei, Xinya; Yi, Chengkun; Huang, Gangliang

2017-01-01

In recent years, the antioxidant effects of polysaccharides have become a hot spot in the field of polysaccharide research. Herein, the action mechanisms of polysaccharide antioxidation and scavenging free radicals were analyzed. The research progresses on the preparation methods and antioxidant properties of polysaccharides and their derivatives were summarized. Investigating the antioxidant activities of polysaccharides and their derivatives can find useful polysaccharides and their derivatives, which have great potential as natural antioxidants used in functional foods or medicines. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Bioactivities in the tamarind seed extracts: A preliminary study

NASA Astrophysics Data System (ADS)

Garg, Sukant; Muangman, Thanchanok; Huifu, He; Ling, Li; Kaul, Sunil C.; Wadhwa, Renu

2018-01-01

Stress is a state that triggers change in normal physiology and recognized by human body and brain as an unfavorable event causing concern, worry or anxiety. It may vary from physical, metabolic, physiological or emotional often culminating into wide range of ailments that may range from common cold, decline in functional efficacy of body systems or even cancer. Skin is the largest tissue of the body and makes the first interface with the environment. Skin color and characteristics are highly influenced by environment stress. A variety of natural compounds have been used for anti-stress and disease preventive potentials in worldwide traditional home medicine systems. They have recently attracted attention in research laboratories to dissect their mode of action to promote safe and economic drug development. We have earlier identified anti-stress and anti-aging activities in Withania somnifera, Helicteres angustifolia and honeybee propolis using human cultured normal and cancer cells. In the present study, we explored the effect of tamarind seed extracts prepared in water or 95% ethanol. In cell-based assays, we found that the extracts were safe to use in viable cells (in the range of 0.01-1.0%, for at least 4 weeks). Consistently, molecular studies revealed no effect on the expression/activity of cancer promoting proteins. We recruited oxidative stress models, such as, hydrogen peroxide (H2O2), ultraviolet radiation (UV) and diacylglycerol 1-oleoyl-2-acetyl-sn-glycerol (OAG). Investigation on anti-stress potential of the extracts revealed that they do not offer remarkable protection against stress caused by either H2O2 or UV, however, significantly compromised OAG-induced melanogenesis. The preliminary data warrant further investigations on the active components and mechanism of action to develop useful natural compounds/extracts for manipulation of melanogenesis that plays important role in response of cells to UV and its consequences including DNA damage

Bioactive polysaccharides and gut microbiome (abstract)

USDA-ARS?s Scientific Manuscript database

Many polysaccharides have shown the ability to reduce plasma cholesterol or postprandial glycemia. Viscosity in the small intestine seems to be required to slow glucose uptake. Cereal mixed linkage beta-glucans, psyllium, glucomannans, and other polysaccharides also seem to require higher molecula...

Unified Heat Kernel Regression for Diffusion, Kernel Smoothing and Wavelets on Manifolds and Its Application to Mandible Growth Modeling in CT Images

PubMed Central

Chung, Moo K.; Qiu, Anqi; Seo, Seongho; Vorperian, Houri K.

2014-01-01

We present a novel kernel regression framework for smoothing scalar surface data using the Laplace-Beltrami eigenfunctions. Starting with the heat kernel constructed from the eigenfunctions, we formulate a new bivariate kernel regression framework as a weighted eigenfunction expansion with the heat kernel as the weights. The new kernel regression is mathematically equivalent to isotropic heat diffusion, kernel smoothing and recently popular diffusion wavelets. Unlike many previous partial differential equation based approaches involving diffusion, our approach represents the solution of diffusion analytically, reducing numerical inaccuracy and slow convergence. The numerical implementation is validated on a unit sphere using spherical harmonics. As an illustration, we have applied the method in characterizing the localized growth pattern of mandible surfaces obtained in CT images from subjects between ages 0 and 20 years by regressing the length of displacement vectors with respect to the template surface. PMID:25791435

Bacterial Extracellular Polysaccharides in Biofilm Formation and Function

PubMed Central

Limoli, Dominique H.; Jones, Christopher J.; Wozniak, Daniel J.

2015-01-01

Microbes produce a biofilm matrix consisting of proteins, extracellular DNA, and polysaccharides that is integral in the formation of bacterial communities. Historical studies of polysaccharides revealed that their overproduction often alters the colony morphology and can be diagnostic in identifying certain species. The polysaccharide component of the matrix can provide many diverse benefits to the cells in the biofilm, including adhesion, protection, and structure. Aggregative polysaccharides act as molecular glue, allowing the bacterial cells to adhere to each other as well as surfaces. Adhesion facilitates the colonization of both biotic and abiotic surfaces by allowing the bacteria to resist physical stresses imposed by fluid movement that could separate the cells from a nutrient source. Polysaccharides can also provide protection from a wide range of stresses, such as desiccation, immune effectors, and predators such as phagocytic cells and amoebae. Finally, polysaccharides can provide structure to biofilms, allowing stratification of the bacterial community and establishing gradients of nutrients and waste products. This can be advantageous for the bacteria by establishing a heterogeneous population that is prepared to endure stresses created by the rapidly changing environments that many bacteria encounter. The diverse range of polysaccharide structures, properties, and roles highlight the importance of this matrix constituent to the successful adaptation of bacteria to nearly every niche. Here, we present an overview of the current knowledge regarding the diversity and benefits that polysaccharide production provides to bacterial communities within biofilms. PMID:26185074

Bacterial Extracellular Polysaccharides in Biofilm Formation and Function.

PubMed

Limoli, Dominique H; Jones, Christopher J; Wozniak, Daniel J

2015-06-01

Microbes produce a biofilm matrix consisting of proteins, extracellular DNA, and polysaccharides that is integral in the formation of bacterial communities. Historical studies of polysaccharides revealed that their overproduction often alters the colony morphology and can be diagnostic in identifying certain species. The polysaccharide component of the matrix can provide many diverse benefits to the cells in the biofilm, including adhesion, protection, and structure. Aggregative polysaccharides act as molecular glue, allowing the bacterial cells to adhere to each other as well as surfaces. Adhesion facilitates the colonization of both biotic and abiotic surfaces by allowing the bacteria to resist physical stresses imposed by fluid movement that could separate the cells from a nutrient source. Polysaccharides can also provide protection from a wide range of stresses, such as desiccation, immune effectors, and predators such as phagocytic cells and amoebae. Finally, polysaccharides can provide structure to biofilms, allowing stratification of the bacterial community and establishing gradients of nutrients and waste products. This can be advantageous for the bacteria by establishing a heterogeneous population that is prepared to endure stresses created by the rapidly changing environments that many bacteria encounter. The diverse range of polysaccharide structures, properties, and roles highlight the importance of this matrix constituent to the successful adaptation of bacteria to nearly every niche. Here, we present an overview of the current knowledge regarding the diversity and benefits that polysaccharide production provides to bacterial communities within biofilms.

Macrophage immunomodulatory activity of polysaccharides isolated from Opuntia polyacantha

PubMed Central

Schepetkin, Igor A.; Xie, Gang; Kirpotina, Liliya N.; Klein, Robyn A.; Jutila, Mark A.; Quinn, Mark T.

2008-01-01

Opuntia polyacantha (prickly pear cactus) has been used extensively for its nutritional properties; however, less is known regarding medicinal properties of Opuntia tissues. In the present study, we extracted polysaccharides from O. polyacantha and used size-exclusion chromatography to fractionate the crude polysaccharides into four polysaccharide fractions (designated as Opuntia polysaccharides C-I to C-IV). The average Mr of fractions C-I through C-IV was estimated to be 733, 550, 310, and 168 kDa, respectively, and sugar composition analysis revealed that Opuntia polysaccharides consisted primarily of galactose, galacturonic acid, xylose, arabinose, and rhamnose. Analysis of the effects of Opuntia polysaccharides on human and murine macrophages demonstrated that all four fractions had potent immunomodulatory activity, inducing production of reactive oxygen species, nitric oxide, tumor necrosis factor α, and interleukin 6. Furthermore, modulation of macrophage function by Opuntia polysaccharides was mediated, at least in part, through activation of nuclear factor κB. Together, our results provide a molecular basis to explain a portion of the beneficial therapeutic properties of extracts from O. polyacantha and support the concept of using Opuntia polysaccharides as an immunotherapeutic adjuvant. PMID:18597716

A dynamic kernel modifier for linux

DOE Office of Scientific and Technical Information (OSTI.GOV)

Minnich, R. G.

2002-09-03

Dynamic Kernel Modifier, or DKM, is a kernel module for Linux that allows user-mode programs to modify the execution of functions in the kernel without recompiling or modifying the kernel source in any way. Functions may be traced, either function entry only or function entry and exit; nullified; or replaced with some other function. For the tracing case, function execution results in the activation of a watchpoint. When the watchpoint is activated, the address of the function is logged in a FIFO buffer that is readable by external applications. The watchpoints are time-stamped with the resolution of the processor highmore » resolution timers, which on most modem processors are accurate to a single processor tick. DKM is very similar to earlier systems such as the SunOS trace device or Linux TT. Unlike these two systems, and other similar systems, DKM requires no kernel modifications. DKM allows users to do initial probing of the kernel to look for performance problems, or even to resolve potential problems by turning functions off or replacing them. DKM watchpoints are not without cost: it takes about 200 nanoseconds to make a log entry on an 800 Mhz Pentium-Ill. The overhead numbers are actually competitive with other hardware-based trace systems, although it has less 'Los Alamos National Laboratory is operated by the University of California for the National Nuclear Security Administration of the United States Department of Energy under contract W-7405-ENG-36. accuracy than an In-Circuit Emulator such as the American Arium. Once the user has zeroed in on a problem, other mechanisms with a higher degree of accuracy can be used.« less

Immunomodulatory dietary polysaccharides: a systematic review of the literature

PubMed Central

2010-01-01

Background A large body of literature suggests that certain polysaccharides affect immune system function. Much of this literature, however, consists of in vitro studies or studies in which polysaccharides were injected. Their immunologic effects following oral administration is less clear. The purpose of this systematic review was to consolidate and evaluate the available data regarding the specific immunologic effects of dietary polysaccharides. Methods Studies were identified by conducting PubMed and Google Scholar electronic searches and through reviews of polysaccharide article bibliographies. Only articles published in English were included in this review. Two researchers reviewed data on study design, control, sample size, results, and nature of outcome measures. Subsequent searches were conducted to gather information about polysaccharide safety, structure and composition, and disposition. Results We found 62 publications reporting statistically significant effects of orally ingested glucans, pectins, heteroglycans, glucomannans, fucoidans, galactomannans, arabinogalactans and mixed polysaccharide products in rodents. Fifteen controlled human studies reported that oral glucans, arabinogalactans, heteroglycans, and fucoidans exerted significant effects. Although some studies investigated anti-inflammatory effects, most studies investigated the ability of oral polysaccharides to stimulate the immune system. These studies, as well as safety and toxicity studies, suggest that these polysaccharide products appear to be largely well-tolerated. Conclusions Taken as a whole, the oral polysaccharide literature is highly heterogenous and is not sufficient to support broad product structure/function generalizations. Numerous dietary polysaccharides, particularly glucans, appear to elicit diverse immunomodulatory effects in numerous animal tissues, including the blood, GI tract and spleen. Glucan extracts from the Trametes versicolor mushroom improved survival and

Solution NMR spectroscopy of food polysaccharides

USDA-ARS?s Scientific Manuscript database

Many polysaccharides are allowed for direct food use, where they serve a number of useful functions. In addition to possibly being a source of calories, a food polysaccharide may be a dietary fiber, bulking agent, crystallization inhibitor, thickener, encapsulant, gelling agent, foam and emulsion s...

Modulating surface rheology by electrostatic protein/polysaccharide interactions.

PubMed

Ganzevles, Renate A; Zinoviadou, Kyriaki; van Vliet, Ton; Cohen, Martien A; de Jongh, Harmen H

2006-11-21

There is a large interest in mixed protein/polysaccharide layers at air-water and oil-water interfaces because of their ability to stabilize foams and emulsions. Mixed protein/polysaccharide adsorbed layers at air-water interfaces can be prepared either by adsorption of soluble protein/polysaccharide complexes or by sequential adsorption of complexes or polysaccharides to a previously formed protein layer. Even though the final protein and polysaccharide bulk concentrations are the same, the behavior of the adsorbed layers can be very different, depending on the method of preparation. The surface shear modulus of a sequentially formed beta-lactoglobulin/pectin layer can be up to a factor of 6 higher than that of a layer made by simultaneous adsorption. Furthermore, the surface dilatational modulus and surface shear modulus strongly (up to factors of 2 and 7, respectively) depend on the bulk -lactoglobulin/pectin mixing ratio. On the basis of the surface rheological behavior, a mechanistic understanding of how the structure of the adsorbed layers depends on the protein/polysaccharide interaction in bulk solution, mixing ratio, ionic strength, and order of adsorption to the interface (simultaneous or sequential) is derived. Insight into the effect of protein/polysaccharide interactions on the properties of adsorbed layers provides a solid basis to modulate surface rheological behavior.

Hadamard Kernel SVM with applications for breast cancer outcome predictions.

PubMed

Jiang, Hao; Ching, Wai-Ki; Cheung, Wai-Shun; Hou, Wenpin; Yin, Hong

2017-12-21

Breast cancer is one of the leading causes of deaths for women. It is of great necessity to develop effective methods for breast cancer detection and diagnosis. Recent studies have focused on gene-based signatures for outcome predictions. Kernel SVM for its discriminative power in dealing with small sample pattern recognition problems has attracted a lot attention. But how to select or construct an appropriate kernel for a specified problem still needs further investigation. Here we propose a novel kernel (Hadamard Kernel) in conjunction with Support Vector Machines (SVMs) to address the problem of breast cancer outcome prediction using gene expression data. Hadamard Kernel outperform the classical kernels and correlation kernel in terms of Area under the ROC Curve (AUC) values where a number of real-world data sets are adopted to test the performance of different methods. Hadamard Kernel SVM is effective for breast cancer predictions, either in terms of prognosis or diagnosis. It may benefit patients by guiding therapeutic options. Apart from that, it would be a valuable addition to the current SVM kernel families. We hope it will contribute to the wider biology and related communities.

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.

Aflatoxin contamination of developing corn kernels.

PubMed

Amer, M A

2005-01-01

Preharvest of corn and its contamination with aflatoxin is a serious problem. Some environmental and cultural factors responsible for infection and subsequent aflatoxin production were investigated in this study. Stage of growth and location of kernels on corn ears were found to be one of the important factors in the process of kernel infection with A. flavus & A. parasiticus. The results showed positive correlation between the stage of growth and kernel infection. Treatment of corn with aflatoxin reduced germination, protein and total nitrogen contents. Total and reducing soluble sugar was increase in corn kernels as response to infection. Sucrose and protein content were reduced in case of both pathogens. Shoot system length, seeding fresh weigh and seedling dry weigh was also affected. Both pathogens induced reduction of starch content. Healthy corn seedlings treated with aflatoxin solution were badly affected. Their leaves became yellow then, turned brown with further incubation. Moreover, their total chlorophyll and protein contents showed pronounced decrease. On the other hand, total phenolic compounds were increased. Histopathological studies indicated that A. flavus & A. parasiticus could colonize corn silks and invade developing kernels. Germination of A. flavus spores was occurred and hyphae spread rapidly across the silk, producing extensive growth and lateral branching. Conidiophores and conidia had formed in and on the corn silk. Temperature and relative humidity greatly influenced the growth of A. flavus & A. parasiticus and aflatoxin production.

Use of fluorescent ANTS to examine the BBB-permeability of polysaccharide

PubMed Central

Christopher, Kevin; Makani, Vishruti; Judy, Wesley; Lee, Erica; Chiaia, Nicolas; Kim, Dong Shik; Park, Joshua

2015-01-01

Recently, some polysaccharides showed therapeutic potentials for the treatment of neurodegenerative diseases while the most important property, their permeability to the blood brain barrier (BBB) that sheathes the brain and spinal cord, is not yet determined. The determination has been delayed by the difficulty in tracking a target polysaccharide among endogenous polysaccharides in animal. We developed an easy way to examine the BBB-permeability and, possibly, tissue distribution of a target polysaccharide in animal. We tagged a polysaccharide with fluorescent 8-aminonaphthalene-1,3,6-trisulfonic acid disodium salt (ANTS) for tracking. We also developed a simple method to separate ANTS-tagged polysaccharide from unconjugated free ANTS using 75% ethanol. After ANTS-polysaccharide was intra-nasally administered into animals, we could quantify the amounts of ANTS-polysaccharide in the brain and the serum by fluorocytometry. We could also separate free ANTS-polysaccharide from serum proteins using trichloroacetic acid (TCA) and 75% ethanol. Our method will help to track a polysaccharide in animal easily. • ANTS-labeling is less tedious than but as powerful as radiolabeling for tracking a target polysaccharide in animal. • Our simple method can separate structurally intact ANTS-polysaccharide from animal serum and tissues. • This method is good for the fluorometry-based measurement of ANTS-conjugated macromolecules in tissues. PMID:25914873

Anthraquinones isolated from the browned Chinese chestnut kernels (Castanea mollissima blume)

NASA Astrophysics Data System (ADS)

Zhang, Y. L.; Qi, J. H.; Qin, L.; Wang, F.; Pang, M. X.

2016-08-01

Anthraquinones (AQS) represent a group of secondary metallic products in plants. AQS are often naturally occurring in plants and microorganisms. In a previous study, we found that AQS were produced by enzymatic browning reaction in Chinese chestnut kernels. To find out whether non-enzymatic browning reaction in the kernels could produce AQS too, AQS were extracted from three groups of chestnut kernels: fresh kernels, non-enzymatic browned kernels, and browned kernels, and the contents of AQS were determined. High performance liquid chromatography (HPLC) and nuclear magnetic resonance (NMR) methods were used to identify two compounds of AQS, rehein(1) and emodin(2). AQS were barely exists in the fresh kernels, while both browned kernel groups sample contained a high amount of AQS. Thus, we comfirmed that AQS could be produced during both enzymatic and non-enzymatic browning process. Rhein and emodin were the main components of AQS in the browned kernels.

Performance Characteristics of a Kernel-Space Packet Capture Module

DTIC Science & Technology

2010-03-01

Defense, or the United States Government . AFIT/GCO/ENG/10-03 PERFORMANCE CHARACTERISTICS OF A KERNEL-SPACE PACKET CAPTURE MODULE THESIS Presented to the...3.1.2.3 Prototype. The proof of concept for this research is the design, development, and comparative performance analysis of a kernel level N2d capture...changes to kernel code 5. Can be used for both user-space and kernel-space capture applications in order to control comparative performance analysis to

Enzymatic method for improving the injectability of polysaccharides. [US Patent Application

DOEpatents

Griffith, W.L.; Compere, A.L.; Holleman, J.W.

A method for enhancing the ability of polysaccharides in aqueous solution to flow through a porous medium comprises contacting the polysaccharides with an endoenzyme capable of hydrolyzing at least one of the linkages of the sugar units of the polysaccharides and maintaining the polysaccharides in contact with the enzyme under hydrolysis conditions for a time sufficient to decrease the tendency of the polysaccharides to plug the porous medium yet insufficient to decrease the viscosity of the aqueous polysaccharides by more than 25%. The partially hydrolyzed polysaccharides are useful as thickening agents for flooding water used to recover oil from oil-containing subterranean formations.

Anatomically-Aided PET Reconstruction Using the Kernel Method

PubMed Central

Hutchcroft, Will; Wang, Guobao; Chen, Kevin T.; Catana, Ciprian; Qi, Jinyi

2016-01-01

This paper extends the kernel method that was proposed previously for dynamic PET reconstruction, to incorporate anatomical side information into the PET reconstruction model. In contrast to existing methods that incorporate anatomical information using a penalized likelihood framework, the proposed method incorporates this information in the simpler maximum likelihood (ML) formulation and is amenable to ordered subsets. The new method also does not require any segmentation of the anatomical image to obtain edge information. We compare the kernel method with the Bowsher method for anatomically-aided PET image reconstruction through a simulated data set. Computer simulations demonstrate that the kernel method offers advantages over the Bowsher method in region of interest (ROI) quantification. Additionally the kernel method is applied to a 3D patient data set. The kernel method results in reduced noise at a matched contrast level compared with the conventional ML expectation maximization (EM) algorithm. PMID:27541810

Anatomically-aided PET reconstruction using the kernel method.

PubMed

Hutchcroft, Will; Wang, Guobao; Chen, Kevin T; Catana, Ciprian; Qi, Jinyi

2016-09-21

This paper extends the kernel method that was proposed previously for dynamic PET reconstruction, to incorporate anatomical side information into the PET reconstruction model. In contrast to existing methods that incorporate anatomical information using a penalized likelihood framework, the proposed method incorporates this information in the simpler maximum likelihood (ML) formulation and is amenable to ordered subsets. The new method also does not require any segmentation of the anatomical image to obtain edge information. We compare the kernel method with the Bowsher method for anatomically-aided PET image reconstruction through a simulated data set. Computer simulations demonstrate that the kernel method offers advantages over the Bowsher method in region of interest quantification. Additionally the kernel method is applied to a 3D patient data set. The kernel method results in reduced noise at a matched contrast level compared with the conventional ML expectation maximization algorithm.

Anatomically-aided PET reconstruction using the kernel method

NASA Astrophysics Data System (ADS)

Hutchcroft, Will; Wang, Guobao; Chen, Kevin T.; Catana, Ciprian; Qi, Jinyi

2016-09-01

This paper extends the kernel method that was proposed previously for dynamic PET reconstruction, to incorporate anatomical side information into the PET reconstruction model. In contrast to existing methods that incorporate anatomical information using a penalized likelihood framework, the proposed method incorporates this information in the simpler maximum likelihood (ML) formulation and is amenable to ordered subsets. The new method also does not require any segmentation of the anatomical image to obtain edge information. We compare the kernel method with the Bowsher method for anatomically-aided PET image reconstruction through a simulated data set. Computer simulations demonstrate that the kernel method offers advantages over the Bowsher method in region of interest quantification. Additionally the kernel method is applied to a 3D patient data set. The kernel method results in reduced noise at a matched contrast level compared with the conventional ML expectation maximization algorithm.

Embedded real-time operating system micro kernel design

NASA Astrophysics Data System (ADS)

Cheng, Xiao-hui; Li, Ming-qiang; Wang, Xin-zheng

2005-12-01

Embedded systems usually require a real-time character. Base on an 8051 microcontroller, an embedded real-time operating system micro kernel is proposed consisting of six parts, including a critical section process, task scheduling, interruption handle, semaphore and message mailbox communication, clock managent and memory managent. Distributed CPU and other resources are among tasks rationally according to the importance and urgency. The design proposed here provides the position, definition, function and principle of micro kernel. The kernel runs on the platform of an ATMEL AT89C51 microcontroller. Simulation results prove that the designed micro kernel is stable and reliable and has quick response while operating in an application system.

Immune cell activation and cytokine release after stimulation of whole blood with pneumococcal C-polysaccharide and capsular polysaccharides.

PubMed

Sundberg-Kövamees, Marianne; Grunewald, Johan; Wahlström, Jan

2016-11-01

Streptococcus pneumonia is a major cause of morbidity and mortality in children and adults worldwide. Lack of fully effective pneumococcal vaccines is a problem. Streptococcus pneumoniae exposes on its surface C-polysaccharide (cell wall polysaccharide, CWPS) and serospecific capsular polysaccharides, used in pneumococcal vaccines. We investigated the effect of CWPS and individual capsular polysaccharides, with regard to activation of subsets of immune cells of healthy controls. Three different capsular polysaccharides, CWPS and LPS were used for in vitro stimulation of whole blood. Cell activation (CD69 expression) was assessed in CD4+ and CD4- T cells, NK-like T cells, NK cells and monocytes by flow cytometry. Cytokine levels in supernatants were quantified by Cytometric Bead Array (CBA). CWPS and the capsules activated immune cell subsets, but to different degrees. NK cells and NK-like T cells showed the strongest activation, followed by monocytes. Among the three capsules, capsule type 23 induced the strongest activation and cytokine release, followed by type 9 and type 3. This study increases the understanding of how the human immune system reacts to pneumococcal vaccine components. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Kernel Temporal Differences for Neural Decoding

PubMed Central

Bae, Jihye; Sanchez Giraldo, Luis G.; Pohlmeyer, Eric A.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

2015-01-01

We study the feasibility and capability of the kernel temporal difference (KTD)(λ) algorithm for neural decoding. KTD(λ) is an online, kernel-based learning algorithm, which has been introduced to estimate value functions in reinforcement learning. This algorithm combines kernel-based representations with the temporal difference approach to learning. One of our key observations is that by using strictly positive definite kernels, algorithm's convergence can be guaranteed for policy evaluation. The algorithm's nonlinear functional approximation capabilities are shown in both simulations of policy evaluation and neural decoding problems (policy improvement). KTD can handle high-dimensional neural states containing spatial-temporal information at a reasonable computational complexity allowing real-time applications. When the algorithm seeks a proper mapping between a monkey's neural states and desired positions of a computer cursor or a robot arm, in both open-loop and closed-loop experiments, it can effectively learn the neural state to action mapping. Finally, a visualization of the coadaptation process between the decoder and the subject shows the algorithm's capabilities in reinforcement learning brain machine interfaces. PMID:25866504

Online selective kernel-based temporal difference learning.

PubMed

Chen, Xingguo; Gao, Yang; Wang, Ruili

2013-12-01

In this paper, an online selective kernel-based temporal difference (OSKTD) learning algorithm is proposed to deal with large scale and/or continuous reinforcement learning problems. OSKTD includes two online procedures: online sparsification and parameter updating for the selective kernel-based value function. A new sparsification method (i.e., a kernel distance-based online sparsification method) is proposed based on selective ensemble learning, which is computationally less complex compared with other sparsification methods. With the proposed sparsification method, the sparsified dictionary of samples is constructed online by checking if a sample needs to be added to the sparsified dictionary. In addition, based on local validity, a selective kernel-based value function is proposed to select the best samples from the sample dictionary for the selective kernel-based value function approximator. The parameters of the selective kernel-based value function are iteratively updated by using the temporal difference (TD) learning algorithm combined with the gradient descent technique. The complexity of the online sparsification procedure in the OSKTD algorithm is O(n). In addition, two typical experiments (Maze and Mountain Car) are used to compare with both traditional and up-to-date O(n) algorithms (GTD, GTD2, and TDC using the kernel-based value function), and the results demonstrate the effectiveness of our proposed algorithm. In the Maze problem, OSKTD converges to an optimal policy and converges faster than both traditional and up-to-date algorithms. In the Mountain Car problem, OSKTD converges, requires less computation time compared with other sparsification methods, gets a better local optima than the traditional algorithms, and converges much faster than the up-to-date algorithms. In addition, OSKTD can reach a competitive ultimate optima compared with the up-to-date algorithms.

Influence of wheat kernel physical properties on the pulverizing process.

PubMed

Dziki, Dariusz; Cacak-Pietrzak, Grażyna; Miś, Antoni; Jończyk, Krzysztof; Gawlik-Dziki, Urszula

2014-10-01

The physical properties of wheat kernel were determined and related to pulverizing performance by correlation analysis. Nineteen samples of wheat cultivars about similar level of protein content (11.2-12.8 % w.b.) and obtained from organic farming system were used for analysis. The kernel (moisture content 10 % w.b.) was pulverized by using the laboratory hammer mill equipped with round holes 1.0 mm screen. The specific grinding energy ranged from 120 kJkg(-1) to 159 kJkg(-1). On the basis of data obtained many of significant correlations (p < 0.05) were found between wheat kernel physical properties and pulverizing process of wheat kernel, especially wheat kernel hardness index (obtained on the basis of Single Kernel Characterization System) and vitreousness significantly and positively correlated with the grinding energy indices and the mass fraction of coarse particles (> 0.5 mm). Among the kernel mechanical properties determined on the basis of uniaxial compression test only the rapture force was correlated with the impact grinding results. The results showed also positive and significant relationships between kernel ash content and grinding energy requirements. On the basis of wheat physical properties the multiple linear regression was proposed for predicting the average particle size of pulverized kernel.

Kernel-based Linux emulation for Plan 9.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Minnich, Ronald G.

2010-09-01

CNKemu is a kernel-based system for the 9k variant of the Plan 9 kernel. It is designed to provide transparent binary support for programs compiled for IBM's Compute Node Kernel (CNK) on the Blue Gene series of supercomputers. This support allows users to build applications with the standard Blue Gene toolchain, including C++ and Fortran compilers. While the CNK is not Linux, IBM designed the CNK so that the user interface has much in common with the Linux 2.0 system call interface. The Plan 9 CNK emulator hence provides the foundation of kernel-based Linux system call support on Plan 9.more » In this paper we discuss cnkemu's implementation and some of its more interesting features, such as the ability to easily intermix Plan 9 and Linux system calls.« less

The Selenylation Modification of Epimedium Polysaccharide and Isatis Root Polysaccharide and the Immune-enhancing Activity Comparison of Their Modifiers.

PubMed

Li, Xiuping; Hou, Ranran; Yue, Chanjuan; Liu, Jie; Gao, Zhenzhen; Chen, Jin; Lu, Yu; Wang, Deyun; Liu, Cui; Hu, Yuanliang

2016-05-01

Epimedium polysaccharide (EPS) and isatis root polysaccharide (IRPS) were extracted, purified, and selenizingly modified by nitric acid-sodium selenite method to obtain nine selenizing EPSs (sEPSs), sEPS1-sEPS9 and nine selenizing IRPSs (sIRPSs), sIRPS1-sIRPS9, respectively. Their effects on chicken peripheral lymphocyte proliferation in vitro were compared by MTT assay. The results showed that selenium polysaccharides at appropriate concentration could promote lymphocyte proliferation more significantly than unmodified polysaccharides, sEPS5 and sIRPS5 with stronger actions were picked out and injected into the chickens vaccinated with Newcastle disease vaccine in vivo tests. The peripheral lymphocyte proliferation and serum antibody titer were determined. The results showed that sEPS5 and sIRPS5 could elevate serum antibody titer and promote lymphocyte proliferation more significantly than unmodified polysaccharides, sEPS5 possessed the strongest efficacy. These results indicate that selenylation modification can significantly enhance the immune-enhancing activity of EPS and IRPS, and sEPS5 can be as a new-type immunopotentiator of chickens.

Rheology of interfacial protein-polysaccharide composites

NASA Astrophysics Data System (ADS)

Fischer, P.

2013-05-01

The morphology and mechanical properties of protein adsorption layers can significantly be altered by the presence of surfactants, lipids, particles, other proteins, and polysaccharides. In food emulsions, polysaccharides are primarily considered as bulk thickener but can under appropriate environmental conditions stabilize or destabilize the protein adsorption layer and, thus, the entire emulsion system. Despite their ubiquitous usage as stabilization agent, relatively few investigations focus on the interfacial rheology of composite protein/polysaccharide adsorption layers. The manuscript provides a brief review on both main stabilization mechanisms, thermodynamic phase separation and electrostatic interaction and discusses the rheological response in light of the environmental conditions such as ionic strength and pH.

Chemical analysis of Agaricus blazei polysaccharides and effect of the polysaccharides on IL-1beta mRNA expression in skin of burn wound-treated rats.

PubMed

Sui, ZhiFu; Yang, RongYa; Liu, Biao; Gu, TingMin; Zhao, Zhili; Shi, Dongfang; Chang, DongQing

2010-08-01

Agaricus blazei polysaccharides were analyzed by GC-MS. Results indicated that the polysaccharides contained glucose (93.87%), mannose (3.54%), and arabinose (2.25%). The compositional analysis was completed by the methylation data. These data indicated that Agaricus blazei polysaccharides are glucans. Compared to model rats, rats fed with Agaricus blazei polysaccharides showed a decrease of ratio of IL-1beta/beta-actin and IL-1beta level in skin of burn wound. Recovery rate of wound skin increased with increasing dose of polysaccharides. The results indicated that Agaricus blazei polysaccharides could be useful in promote burn wound healing. Copyright 2010 Elsevier B.V. All rights reserved.

Gradient-based adaptation of general gaussian kernels.

PubMed

Glasmachers, Tobias; Igel, Christian

2005-10-01

Gradient-based optimizing of gaussian kernel functions is considered. The gradient for the adaptation of scaling and rotation of the input space is computed to achieve invariance against linear transformations. This is done by using the exponential map as a parameterization of the kernel parameter manifold. By restricting the optimization to a constant trace subspace, the kernel size can be controlled. This is, for example, useful to prevent overfitting when minimizing radius-margin generalization performance measures. The concepts are demonstrated by training hard margin support vector machines on toy data.

Gabor-based kernel PCA with fractional power polynomial models for face recognition.

PubMed

Liu, Chengjun

2004-05-01

This paper presents a novel Gabor-based kernel Principal Component Analysis (PCA) method by integrating the Gabor wavelet representation of face images and the kernel PCA method for face recognition. Gabor wavelets first derive desirable facial features characterized by spatial frequency, spatial locality, and orientation selectivity to cope with the variations due to illumination and facial expression changes. The kernel PCA method is then extended to include fractional power polynomial models for enhanced face recognition performance. A fractional power polynomial, however, does not necessarily define a kernel function, as it might not define a positive semidefinite Gram matrix. Note that the sigmoid kernels, one of the three classes of widely used kernel functions (polynomial kernels, Gaussian kernels, and sigmoid kernels), do not actually define a positive semidefinite Gram matrix either. Nevertheless, the sigmoid kernels have been successfully used in practice, such as in building support vector machines. In order to derive real kernel PCA features, we apply only those kernel PCA eigenvectors that are associated with positive eigenvalues. The feasibility of the Gabor-based kernel PCA method with fractional power polynomial models has been successfully tested on both frontal and pose-angled face recognition, using two data sets from the FERET database and the CMU PIE database, respectively. The FERET data set contains 600 frontal face images of 200 subjects, while the PIE data set consists of 680 images across five poses (left and right profiles, left and right half profiles, and frontal view) with two different facial expressions (neutral and smiling) of 68 subjects. The effectiveness of the Gabor-based kernel PCA method with fractional power polynomial models is shown in terms of both absolute performance indices and comparative performance against the PCA method, the kernel PCA method with polynomial kernels, the kernel PCA method with fractional power

Immune Recognition of Fungal Polysaccharides.

PubMed

Snarr, Brendan D; Qureshi, Salman T; Sheppard, Donald C

2017-08-28

The incidence of fungal infections has dramatically increased in recent years, in large part due to increased use of immunosuppressive medications, as well as aggressive medical and surgical interventions that compromise natural skin and mucosal barriers. There are relatively few currently licensed antifungal drugs, and rising resistance to these agents has led to interest in the development of novel preventative and therapeutic strategies targeting these devastating infections. One approach to combat fungal infections is to augment the host immune response towards these organisms. The polysaccharide-rich cell wall is the initial point of contact between fungi and the host immune system, and therefore, represents an important target for immunotherapeutic approaches. This review highlights the advances made in our understanding of the mechanisms by which the immune system recognizes and interacts with exopolysaccharides produced by four of the most common fungal pathogens: Aspergillus fumigatus , Candida albicans , Cryptococcus neoformans , and Histoplasma capsulatum . Work to date suggests that inner cell wall polysaccharides that play an important structural role are the most conserved across diverse members of the fungal kingdom, and elicit the strongest innate immune responses. The immune system senses these carbohydrates through receptors, such as lectins and complement proteins. In contrast, a greater diversity of polysaccharides is found within the outer cell walls of pathogenic fungi. These glycans play an important role in immune evasion, and can even induce anti-inflammatory host responses. Further study of the complex interactions between the host immune system and the fungal polysaccharides will be necessary to develop more effective therapeutic strategies, as well as to explore the use of immunosuppressive polysaccharides as therapeutic agents to modulate inflammation.

Genetic dissection of the maize kernel development process via conditional QTL mapping for three developing kernel-related traits in an immortalized F2 population.

PubMed

Zhang, Zhanhui; Wu, Xiangyuan; Shi, Chaonan; Wang, Rongna; Li, Shengfei; Wang, Zhaohui; Liu, Zonghua; Xue, Yadong; Tang, Guiliang; Tang, Jihua

2016-02-01

Kernel development is an important dynamic trait that determines the final grain yield in maize. To dissect the genetic basis of maize kernel development process, a conditional quantitative trait locus (QTL) analysis was conducted using an immortalized F2 (IF2) population comprising 243 single crosses at two locations over 2 years. Volume (KV) and density (KD) of dried developing kernels, together with kernel weight (KW) at different developmental stages, were used to describe dynamic changes during kernel development. Phenotypic analysis revealed that final KW and KD were determined at DAP22 and KV at DAP29. Unconditional QTL mapping for KW, KV and KD uncovered 97 QTLs at different kernel development stages, of which qKW6b, qKW7a, qKW7b, qKW10b, qKW10c, qKV10a, qKV10b and qKV7 were identified under multiple kernel developmental stages and environments. Among the 26 QTLs detected by conditional QTL mapping, conqKW7a, conqKV7a, conqKV10a, conqKD2, conqKD7 and conqKD8a were conserved between the two mapping methodologies. Furthermore, most of these QTLs were consistent with QTLs and genes for kernel development/grain filling reported in previous studies. These QTLs probably contain major genes associated with the kernel development process, and can be used to improve grain yield and quality through marker-assisted selection.

A trace ratio maximization approach to multiple kernel-based dimensionality reduction.

PubMed

Jiang, Wenhao; Chung, Fu-lai

2014-01-01

Most dimensionality reduction techniques are based on one metric or one kernel, hence it is necessary to select an appropriate kernel for kernel-based dimensionality reduction. Multiple kernel learning for dimensionality reduction (MKL-DR) has been recently proposed to learn a kernel from a set of base kernels which are seen as different descriptions of data. As MKL-DR does not involve regularization, it might be ill-posed under some conditions and consequently its applications are hindered. This paper proposes a multiple kernel learning framework for dimensionality reduction based on regularized trace ratio, termed as MKL-TR. Our method aims at learning a transformation into a space of lower dimension and a corresponding kernel from the given base kernels among which some may not be suitable for the given data. The solutions for the proposed framework can be found based on trace ratio maximization. The experimental results demonstrate its effectiveness in benchmark datasets, which include text, image and sound datasets, for supervised, unsupervised as well as semi-supervised settings. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Kernel-based Lagrangian method for imperfectly-mixed chemical reactions

NASA Astrophysics Data System (ADS)

Schmidt, Michael J.; Pankavich, Stephen; Benson, David A.

2017-05-01

Current Lagrangian (particle-tracking) algorithms used to simulate diffusion-reaction equations must employ a certain number of particles to properly emulate the system dynamics-particularly for imperfectly-mixed systems. The number of particles is tied to the statistics of the initial concentration fields of the system at hand. Systems with shorter-range correlation and/or smaller concentration variance require more particles, potentially limiting the computational feasibility of the method. For the well-known problem of bimolecular reaction, we show that using kernel-based, rather than Dirac delta, particles can significantly reduce the required number of particles. We derive the fixed width of a Gaussian kernel for a given reduced number of particles that analytically eliminates the error between kernel and Dirac solutions at any specified time. We also show how to solve for the fixed kernel size by minimizing the squared differences between solutions over any given time interval. Numerical results show that the width of the kernel should be kept below about 12% of the domain size, and that the analytic equations used to derive kernel width suffer significantly from the neglect of higher-order moments. The simulations with a kernel width given by least squares minimization perform better than those made to match at one specific time. A heuristic time-variable kernel size, based on the previous results, performs on par with the least squares fixed kernel size.

Detection of maize kernels breakage rate based on K-means clustering

NASA Astrophysics Data System (ADS)

Yang, Liang; Wang, Zhuo; Gao, Lei; Bai, Xiaoping

2017-04-01

In order to optimize the recognition accuracy of maize kernels breakage detection and improve the detection efficiency of maize kernels breakage, this paper using computer vision technology and detecting of the maize kernels breakage based on K-means clustering algorithm. First, the collected RGB images are converted into Lab images, then the original images clarity evaluation are evaluated by the energy function of Sobel 8 gradient. Finally, the detection of maize kernels breakage using different pixel acquisition equipments and different shooting angles. In this paper, the broken maize kernels are identified by the color difference between integrity kernels and broken kernels. The original images clarity evaluation and different shooting angles are taken to verify that the clarity and shooting angles of the images have a direct influence on the feature extraction. The results show that K-means clustering algorithm can distinguish the broken maize kernels effectively.

Image quality of mixed convolution kernel in thoracic computed tomography.

PubMed

Neubauer, Jakob; Spira, Eva Maria; Strube, Juliane; Langer, Mathias; Voss, Christian; Kotter, Elmar

2016-11-01

The mixed convolution kernel alters his properties geographically according to the depicted organ structure, especially for the lung. Therefore, we compared the image quality of the mixed convolution kernel to standard soft and hard kernel reconstructions for different organ structures in thoracic computed tomography (CT) images.Our Ethics Committee approved this prospective study. In total, 31 patients who underwent contrast-enhanced thoracic CT studies were included after informed consent. Axial reconstructions were performed with hard, soft, and mixed convolution kernel. Three independent and blinded observers rated the image quality according to the European Guidelines for Quality Criteria of Thoracic CT for 13 organ structures. The observers rated the depiction of the structures in all reconstructions on a 5-point Likert scale. Statistical analysis was performed with the Friedman Test and post hoc analysis with the Wilcoxon rank-sum test.Compared to the soft convolution kernel, the mixed convolution kernel was rated with a higher image quality for lung parenchyma, segmental bronchi, and the border between the pleura and the thoracic wall (P < 0.03). Compared to the hard convolution kernel, the mixed convolution kernel was rated with a higher image quality for aorta, anterior mediastinal structures, paratracheal soft tissue, hilar lymph nodes, esophagus, pleuromediastinal border, large and medium sized pulmonary vessels and abdomen (P < 0.004) but a lower image quality for trachea, segmental bronchi, lung parenchyma, and skeleton (P < 0.001).The mixed convolution kernel cannot fully substitute the standard CT reconstructions. Hard and soft convolution kernel reconstructions still seem to be mandatory for thoracic CT.

Formation of a Soluble Amylopectin-Like Polysaccharide in Potato Tubers 1

PubMed Central

Frydman, Rosalia B.; Cardini, Carlos E.

1967-01-01

When potato sprouts or potato tuber slices were incubated with 0.1 m glucose 1-phosphate, a soluble amylopectin-like polysaccharide was excreted to the medium. This polysaccharide was found to be a very good primer for phosphorylase and a poor one for starch synthetase. Beside the formation of this extracellular polysaccharide, a more branched intracellular polysaccharide could be isolated. This polysaccharide was an excellent primer for starch synthetase. Fructose 6-phosphate, glucose 6-phosphate, fructose 1,6-diphosphate, glucose or sucrose could not substitute for glucose 1-phosphate. 2,4-Dinitrophenol or nitrogen did not affect the excretion of the polysaccharide. Some properties of these 2 polysaccharides are described. PMID:16656546

Plant-Polysaccharide-Degrading Enzymes from Basidiomycetes

PubMed Central

Rytioja, Johanna; Hildén, Kristiina; Yuzon, Jennifer; Hatakka, Annele; de Vries, Ronald P.

2014-01-01

SUMMARY Basidiomycete fungi subsist on various types of plant material in diverse environments, from living and dead trees and forest litter to crops and grasses and to decaying plant matter in soils. Due to the variation in their natural carbon sources, basidiomycetes have highly varied plant-polysaccharide-degrading capabilities. This topic is not as well studied for basidiomycetes as for ascomycete fungi, which are the main sources of knowledge on fungal plant polysaccharide degradation. Research on plant-biomass-decaying fungi has focused on isolating enzymes for current and future applications, such as for the production of fuels, the food industry, and waste treatment. More recently, genomic studies of basidiomycete fungi have provided a profound view of the plant-biomass-degrading potential of wood-rotting, litter-decomposing, plant-pathogenic, and ectomycorrhizal (ECM) basidiomycetes. This review summarizes the current knowledge on plant polysaccharide depolymerization by basidiomycete species from diverse habitats. In addition, these data are compared to those for the most broadly studied ascomycete genus, Aspergillus, to provide insight into specific features of basidiomycetes with respect to plant polysaccharide degradation. PMID:25428937

Coupling individual kernel-filling processes with source-sink interactions into GREENLAB-Maize.

PubMed

Ma, Yuntao; Chen, Youjia; Zhu, Jinyu; Meng, Lei; Guo, Yan; Li, Baoguo; Hoogenboom, Gerrit

2018-02-13

Failure to account for the variation of kernel growth in a cereal crop simulation model may cause serious deviations in the estimates of crop yield. The goal of this research was to revise the GREENLAB-Maize model to incorporate source- and sink-limited allocation approaches to simulate the dry matter accumulation of individual kernels of an ear (GREENLAB-Maize-Kernel). The model used potential individual kernel growth rates to characterize the individual potential sink demand. The remobilization of non-structural carbohydrates from reserve organs to kernels was also incorporated. Two years of field experiments were conducted to determine the model parameter values and to evaluate the model using two maize hybrids with different plant densities and pollination treatments. Detailed observations were made on the dimensions and dry weights of individual kernels and other above-ground plant organs throughout the seasons. Three basic traits characterizing an individual kernel were compared on simulated and measured individual kernels: (1) final kernel size; (2) kernel growth rate; and (3) duration of kernel filling. Simulations of individual kernel growth closely corresponded to experimental data. The model was able to reproduce the observed dry weight of plant organs well. Then, the source-sink dynamics and the remobilization of carbohydrates for kernel growth were quantified to show that remobilization processes accompanied source-sink dynamics during the kernel-filling process. We conclude that the model may be used to explore options for optimizing plant kernel yield by matching maize management to the environment, taking into account responses at the level of individual kernels. © The Author(s) 2018. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Stochastic subset selection for learning with kernel machines.

PubMed

Rhinelander, Jason; Liu, Xiaoping P

2012-06-01

Kernel machines have gained much popularity in applications of machine learning. Support vector machines (SVMs) are a subset of kernel machines and generalize well for classification, regression, and anomaly detection tasks. The training procedure for traditional SVMs involves solving a quadratic programming (QP) problem. The QP problem scales super linearly in computational effort with the number of training samples and is often used for the offline batch processing of data. Kernel machines operate by retaining a subset of observed data during training. The data vectors contained within this subset are referred to as support vectors (SVs). The work presented in this paper introduces a subset selection method for the use of kernel machines in online, changing environments. Our algorithm works by using a stochastic indexing technique when selecting a subset of SVs when computing the kernel expansion. The work described here is novel because it separates the selection of kernel basis functions from the training algorithm used. The subset selection algorithm presented here can be used in conjunction with any online training technique. It is important for online kernel machines to be computationally efficient due to the real-time requirements of online environments. Our algorithm is an important contribution because it scales linearly with the number of training samples and is compatible with current training techniques. Our algorithm outperforms standard techniques in terms of computational efficiency and provides increased recognition accuracy in our experiments. We provide results from experiments using both simulated and real-world data sets to verify our algorithm.

RTOS kernel in portable electrocardiograph

NASA Astrophysics Data System (ADS)

Centeno, C. A.; Voos, J. A.; Riva, G. G.; Zerbini, C.; Gonzalez, E. A.

2011-12-01

This paper presents the use of a Real Time Operating System (RTOS) on a portable electrocardiograph based on a microcontroller platform. All medical device digital functions are performed by the microcontroller. The electrocardiograph CPU is based on the 18F4550 microcontroller, in which an uCOS-II RTOS can be embedded. The decision associated with the kernel use is based on its benefits, the license for educational use and its intrinsic time control and peripherals management. The feasibility of its use on the electrocardiograph is evaluated based on the minimum memory requirements due to the kernel structure. The kernel's own tools were used for time estimation and evaluation of resources used by each process. After this feasibility analysis, the migration from cyclic code to a structure based on separate processes or tasks able to synchronize events is used; resulting in an electrocardiograph running on one Central Processing Unit (CPU) based on RTOS.

Interaction of antimicrobial peptides with bacterial polysaccharides from lung pathogens.

PubMed

Herasimenka, Yury; Benincasa, Monica; Mattiuzzo, Maura; Cescutti, Paola; Gennaro, Renato; Rizzo, Roberto

2005-07-01

The interaction of two cathelicidin antimicrobial peptides, LL-37 and SMAP-29, with three bacterial polysaccharides, respectively, produced by Pseudomonas aeruginosa, Burkholderia cepacia and Klebsiella pneumoniae, was investigated to identify possible mechanisms adopted by lung pathogens to escape the action of innate immunity effectors. In vitro assays indicated that the antibacterial activity of both peptides was inhibited to a variable extent by the three polysaccharides. Circular dichroism experiments showed that these induced an alpha-helical conformation in the two peptides, with the polysaccharides from K. pneumoniae and B. cepacia showing, respectively, the highest and the lowest effect. Fluorescence measurements also indicated the presence of peptide-polysaccharide interactions. A model is proposed in which the binding of peptides to the polysaccharide molecules induces, at low polysaccharide to peptide ratios, a higher order of aggregation, due to peptide-peptide interactions. Overall, these results suggest that binding of the peptides by the polysaccharides produced by lung pathogens can contribute to the impairment of peptide-based innate defenses of airway surface.

A Robustness Testing Campaign for IMA-SP Partitioning Kernels

NASA Astrophysics Data System (ADS)

Grixti, Stephen; Lopez Trecastro, Jorge; Sammut, Nicholas; Zammit-Mangion, David

2015-09-01

With time and space partitioned architectures becoming increasingly appealing to the European space sector, the dependability of partitioning kernel technology is a key factor to its applicability in European Space Agency projects. This paper explores the potential of the data type fault model, which injects faults through the Application Program Interface, in partitioning kernel robustness testing. This fault injection methodology has been tailored to investigate its relevance in uncovering vulnerabilities within partitioning kernels and potentially contributing towards fault removal campaigns within this domain. This is demonstrated through a robustness testing case study of the XtratuM partitioning kernel for SPARC LEON3 processors. The robustness campaign exposed a number of vulnerabilities in XtratuM, exhibiting the potential benefits of using such a methodology for the robustness assessment of partitioning kernels.

Visualization of bacterial polysaccharides by scanning transmission electron microscopy.

PubMed

Wolanski, B S; McAleer, W J; Hilleman, M R

1983-04-01

Highly purified capsular polysaccharides of Neisseria meningitidis groups A, B, and C have been visualized by high resolution Scanning Transmission Electron Microscopy (STEM). Spheroidal macromolecules approximately 200 A in diameter are characteristic of the Meningococcus A and C polysaccharides whereas filaments that are 400-600 A in length are found in Meningococcus B polysaccharide preparations. Filaments are occasionally found associated with the spheroidal Meningococcus A and C polysaccharides and it is proposed that these structures are composed of a long (1-4 microns) filament or filaments that are arranged in spheroidal molecules or micelles of high molecular weight. The Meningococcus B polysaccharide, by contrast, is a short flexuous filament or strand of relatively low molecular weight. A relationship between morphology and antigenicity is proposed.

Marine polysaccharide-based nanomaterials as a novel source of nanobiotechnological applications.

PubMed

Manivasagan, Panchanathan; Oh, Junghwan

2016-01-01

Research on marine polysaccharide-based nanomaterials is emerging in nanobiotechnological fields such as drug delivery, gene delivery, tissue engineering, cancer therapy, wound dressing, biosensors, and water treatment. Important properties of the marine polysaccharides include biocompatibility, biodegradability, nontoxicity, low cost, and abundance. Most of the marine polysaccharides are derived from natural sources such as fucoidan, alginates, carrageenan, agarose, porphyran, ulvan, mauran, chitin, chitosan, and chitooligosaccharide. Marine polysaccharides are very important biological macromolecules that widely exist in marine organisms. Marine polysaccharides exhibit a vast variety of structures and are still under-exploited and thus should be considered as a novel source of natural products for drug discovery. An enormous variety of polysaccharides can be extracted from marine organisms such as algae, crustaceans, and microorganisms. Marine polysaccharides have been shown to have a variety of biological and biomedical properties. Recently, research and development of marine polysaccharide-based nanomaterials have received considerable attention as one of the major resources for nanotechnological applications. This review highlights the recent research on marine polysaccharide-based nanomaterials for biotechnological and biomedical applications. Copyright © 2015 Elsevier B.V. All rights reserved.

Chemical studies on the polysaccharides of Salicornia brachiata.

PubMed

Sanandiya, Naresh D; Siddhanta, A K

2014-11-04

A group of 12 polysaccharide extracts were prepared from the tips, stem and roots of an Indian halophyte Salicornia brachiata Roxb. obtained by sequential extractions with cold water (CW), hot water (HW), aqueous ammonium oxalate (OX) and aqueous sodium hydroxide (ALK) solutions. Monosaccharide composition analysis revealed that all the polysaccharide extract samples consisted primarily of rhamnose, arabinose, mannose, galactose, glucose, whereas ribose and xylose were present only in some of the extracts. All the extracts exhibited low apparent viscosity (1.47-2.02 cP) and sulphate and contained no prominent toxic metal ions. Fucose was detected only in OX extract of the roots. These polysaccharides were found to be heterogeneous and highly branched (glycoside linkage analysis, size-exclusion chromatography, (13)C-NMR, FT-IR, circular dichroism and optical rotation data). Physico-chemical analyses of these polysaccharides including uronic acid, sulphate and protein contents were also carried out. This constitutes the first report on the profiling of Salicornia polysaccharides. Copyright © 2014 Elsevier Ltd. All rights reserved.

Searching for efficient Markov chain Monte Carlo proposal kernels

PubMed Central

Yang, Ziheng; Rodríguez, Carlos E.

2013-01-01

Markov chain Monte Carlo (MCMC) or the Metropolis–Hastings algorithm is a simulation algorithm that has made modern Bayesian statistical inference possible. Nevertheless, the efficiency of different Metropolis–Hastings proposal kernels has rarely been studied except for the Gaussian proposal. Here we propose a unique class of Bactrian kernels, which avoid proposing values that are very close to the current value, and compare their efficiency with a number of proposals for simulating different target distributions, with efficiency measured by the asymptotic variance of a parameter estimate. The uniform kernel is found to be more efficient than the Gaussian kernel, whereas the Bactrian kernel is even better. When optimal scales are used for both, the Bactrian kernel is at least 50% more efficient than the Gaussian. Implementation in a Bayesian program for molecular clock dating confirms the general applicability of our results to generic MCMC algorithms. Our results refute a previous claim that all proposals had nearly identical performance and will prompt further research into efficient MCMC proposals. PMID:24218600

Polysaccharides in fungi. XXXII. Hypoglycemic activity and chemical properties of a polysaccharide from the cultural mycelium of Cordyceps sinensis.

PubMed

Kiho, T; Hui, J; Yamane, A; Ukai, S

1993-12-01

Crude polysaccharides were obtained from a hot-water extract and alkaline extracts of the cultural mycelium of Cordyceps sinensis. They showed significant activity in normal mice and streptozotocin-induced diabetic mice as a result of intraperitoneal (i.p.) injection. A crude polysaccharide (CS-OHEP) obtained from 5% sodium hydroxide extract slightly lowered the plasma glucose level in normal mice by oral (p.o.) administration. A neutral polysaccharide (CS-F30) exhibited higher hypoglycemic activity than its crude polysaccharide (CS-OHEP), exhibited by i.p. injection, and it significantly lowered the glucose level by p.o. administration (50 mg/kg). However, it hardly affected the plasma insulin level in normal mice. CS-F30 ([alpha]D + 21 degrees in water) is composed of galactose, glucose and mannose (molar percent, 62:28:10), and its molecular weight is about 45000.

Sealing effect of a polysaccharide nanosheet for murine cecal puncture.

PubMed

Fujie, Toshinori; Kinoshita, Manabu; Shono, Satoshi; Saito, Akihiro; Okamura, Yosuke; Saitoh, Daizoh; Takeoka, Shinji

2010-07-01

Recent developments in nanobiotechnology have led us to develop a method of producing a free-standing polymer nanosheet composed of polysaccharides (ie, polysaccharide nanosheet) with a thickness of tens of nanometers. Owing to its enormous aspect ratio, the polysaccharide nanosheet is semi-absorbent and has a physical adhesive strength 7.5-fold greater than that of conventional films of >1 microm thickness. Herein, we have investigated the therapeutic sealing effect of this polysaccharide nanosheet on murine cecal puncture as a wound dressing material. Murine cecum was punctured and then overlapped with the polysaccharide nanosheet. Thereafter, we evaluated its sealing effect on bacterial peritonitis as well as the protection offered by the polysaccharide nanosheet against bacterial permeability using an in vitro transmembrane assay. The 39-nm-thick polysaccharide nanosheet overlapped tightly the perforated cecum. No adhering agents were required because of the ability of the polysaccharide nanosheet to adhere to the tissue surface by physical adsorption (eg, van der Waals interaction). Sealing the perforated cecum with the polysaccharide nanosheet increased survival rate without postoperative adhesion by comparison with untreated mice (90 vs 30%; P < .01). These data were supported by the improvement in peritonitis related to bacterial counts, white blood cell counts, and the serum tumor necrosis factor level. Moreover, using an in vitro transmembrane assay, we showed that the polysaccharide nanosheet inhibited effectively bacterial penetration. We have demonstrated the potential clinical benefits of the nanosheet-type biomaterial that can be used for repairing a cecal colotomy without chemical bonding agents. Copyright 2010 Mosby, Inc. All rights reserved.

Defect Analysis Of Quality Palm Kernel Meal Using Statistical Quality Control In Kernels Factory

NASA Astrophysics Data System (ADS)

Sembiring, M. T.; Marbun, N. J.

2018-04-01

The production quality has an important impact retain the totality of characteristics of a product or service to pay attention to its capabilities to meet the needs that have been established. Quality criteria Palm Kernel Meal (PKM) set Factory kernel is as follows: oil content: max 8.50%, water content: max 12,00% and impurity content: max 4.00% While the average quality of the oil content of 8.94%, the water content of 5.51%, and 8.45% impurity content. To identify the defective product quality PKM produced, then used a method of analysis using Statistical Quality Control (SQC). PKM Plant Quality Kernel shows the oil content was 0.44% excess of a predetermined maximum value, and 4.50% impurity content. With excessive PKM content of oil and dirt cause disability content of production for oil, amounted to 854.6078 kg PKM and 8643.193 kg impurity content of PKM. Analysis of the results of cause and effect diagram and SQC, the factors that lead to poor quality of PKM is Ampere second press oil expeller and hours second press oil expeller.

Scuba: scalable kernel-based gene prioritization.

PubMed

Zampieri, Guido; Tran, Dinh Van; Donini, Michele; Navarin, Nicolò; Aiolli, Fabio; Sperduti, Alessandro; Valle, Giorgio

2018-01-25

The uncovering of genes linked to human diseases is a pressing challenge in molecular biology and precision medicine. This task is often hindered by the large number of candidate genes and by the heterogeneity of the available information. Computational methods for the prioritization of candidate genes can help to cope with these problems. In particular, kernel-based methods are a powerful resource for the integration of heterogeneous biological knowledge, however, their practical implementation is often precluded by their limited scalability. We propose Scuba, a scalable kernel-based method for gene prioritization. It implements a novel multiple kernel learning approach, based on a semi-supervised perspective and on the optimization of the margin distribution. Scuba is optimized to cope with strongly unbalanced settings where known disease genes are few and large scale predictions are required. Importantly, it is able to efficiently deal both with a large amount of candidate genes and with an arbitrary number of data sources. As a direct consequence of scalability, Scuba integrates also a new efficient strategy to select optimal kernel parameters for each data source. We performed cross-validation experiments and simulated a realistic usage setting, showing that Scuba outperforms a wide range of state-of-the-art methods. Scuba achieves state-of-the-art performance and has enhanced scalability compared to existing kernel-based approaches for genomic data. This method can be useful to prioritize candidate genes, particularly when their number is large or when input data is highly heterogeneous. The code is freely available at https://github.com/gzampieri/Scuba .

Genomic Prediction of Genotype × Environment Interaction Kernel Regression Models.

PubMed

Cuevas, Jaime; Crossa, José; Soberanis, Víctor; Pérez-Elizalde, Sergio; Pérez-Rodríguez, Paulino; Campos, Gustavo de Los; Montesinos-López, O A; Burgueño, Juan

2016-11-01

In genomic selection (GS), genotype × environment interaction (G × E) can be modeled by a marker × environment interaction (M × E). The G × E may be modeled through a linear kernel or a nonlinear (Gaussian) kernel. In this study, we propose using two nonlinear Gaussian kernels: the reproducing kernel Hilbert space with kernel averaging (RKHS KA) and the Gaussian kernel with the bandwidth estimated through an empirical Bayesian method (RKHS EB). We performed single-environment analyses and extended to account for G × E interaction (GBLUP-G × E, RKHS KA-G × E and RKHS EB-G × E) in wheat ( L.) and maize ( L.) data sets. For single-environment analyses of wheat and maize data sets, RKHS EB and RKHS KA had higher prediction accuracy than GBLUP for all environments. For the wheat data, the RKHS KA-G × E and RKHS EB-G × E models did show up to 60 to 68% superiority over the corresponding single environment for pairs of environments with positive correlations. For the wheat data set, the models with Gaussian kernels had accuracies up to 17% higher than that of GBLUP-G × E. For the maize data set, the prediction accuracy of RKHS EB-G × E and RKHS KA-G × E was, on average, 5 to 6% higher than that of GBLUP-G × E. The superiority of the Gaussian kernel models over the linear kernel is due to more flexible kernels that accounts for small, more complex marker main effects and marker-specific interaction effects. Copyright © 2016 Crop Science Society of America.

Phosphorylation of psyllium seed polysaccharide and its characterization.

PubMed

Rao, Monica R P; Warrier, Deepa U; Gaikwad, Snehal R; Shevate, Prachi M

2016-04-01

Psyllium is widely used as a medicinally active natural polysaccharide for treating conditions like constipation, diarrhea, and irritable bowel syndrome, inflammatory bowel disease, ulcerative colitis and colon cancer. Studies have been performed to characterize and modify the polysaccharide obtained from psyllium seed husk and to evaluate its use as a pharmaceutical excipient, but no studies have been performed to evaluate the properties of the polysaccharide present in psyllium seeds. The present study focuses on phosphorylation of psyllium seed polysaccharide (PPS) using sodium tri-meta phosphate as the cross-linking agent. The modified phosphorylated psyllium seed polysaccharide was then evaluated for physicochemical properties, rheological properties, spectral analysis, thermal analysis, crosslinking density and acute oral toxicity studies. The modified polysaccharide (PhPPS) has a high swelling index due to which it can be categorized as a hydrogel. The percent increase in swelling of PhPPS as compared to PPS was found to be 90.26%. The PPS & PhPPS mucilages of all strengths were found to have shear thinning properties. These findings are suggestive of the potential use of PhPPS as gelling & suspending agent. PhPPS was found to have a mucoadhesive property which was comparable with carbopol. Copyright © 2015 Elsevier B.V. All rights reserved.

Differential regulation of polysaccharide-specific antibody responses to isolated polysaccharides, conjugate vaccines, and intact Gram-positive versus Gram-negative extracellular bacteria.

PubMed

Snapper, Clifford M

2016-06-24

Bacterial capsular polysaccharides are major virulence factors and are key targets in a number of licensed anti-bacterial vaccines. Their major characteristics are their large molecular weight and expression of repeating antigenic epitopes that mediate multivalent B cell receptor cross-linking. In addition, since the majority of these antigens cannot associate with MHC-II they fail to recruit CD4+ T cell help and are referred to as T cell-independent antigens. In this review I will discuss a series of studies from my laboratory that have underscored the importance of understanding polysaccharide-specific antibody responses within the context in which the PS is expressed (i.e. in isolation, as a component of conjugate vaccines, and expressed naturally by intact bacteria). We have shown that multivalent B cell receptor crosslinking, as mediated by polysaccharides, uniquely determines the qualitative response of the B cell to subsequent stimuli, but by itself is insufficient to induce antibody secretion or class switching. For these latter events to occur, second signals must act in concert with primary signals derived from the B cell receptor. The co-expression of polysaccharide and protein within intact bacteria promotes recruitment of CD4+ T cell help for the associated PS-specific IgG response, in contrast to isolated polysaccharides. Further, the particulate nature of extracellular bacteria confers properties to the polysaccharide-specific IgG response that makes it distinct immunologically from soluble conjugate vaccines. Finally, the underlying biochemical and/or structural differences that distinguish Gram-positive and Gram-negative bacteria appear to play critical roles in differentially regulating the associated polysaccharide-specific IgG responses to these groups of pathogens. These studies have a number of implications for the understanding and future design of polysaccharide-based vaccines. Published by Elsevier Ltd.

Sepsis mortality prediction with the Quotient Basis Kernel.

PubMed

Ribas Ripoll, Vicent J; Vellido, Alfredo; Romero, Enrique; Ruiz-Rodríguez, Juan Carlos

2014-05-01

This paper presents an algorithm to assess the risk of death in patients with sepsis. Sepsis is a common clinical syndrome in the intensive care unit (ICU) that can lead to severe sepsis, a severe state of septic shock or multi-organ failure. The proposed algorithm may be implemented as part of a clinical decision support system that can be used in combination with the scores deployed in the ICU to improve the accuracy, sensitivity and specificity of mortality prediction for patients with sepsis. In this paper, we used the Simplified Acute Physiology Score (SAPS) for ICU patients and the Sequential Organ Failure Assessment (SOFA) to build our kernels and algorithms. In the proposed method, we embed the available data in a suitable feature space and use algorithms based on linear algebra, geometry and statistics for inference. We present a simplified version of the Fisher kernel (practical Fisher kernel for multinomial distributions), as well as a novel kernel that we named the Quotient Basis Kernel (QBK). These kernels are used as the basis for mortality prediction using soft-margin support vector machines. The two new kernels presented are compared against other generative kernels based on the Jensen-Shannon metric (centred, exponential and inverse) and other widely used kernels (linear, polynomial and Gaussian). Clinical relevance is also evaluated by comparing these results with logistic regression and the standard clinical prediction method based on the initial SAPS score. As described in this paper, we tested the new methods via cross-validation with a cohort of 400 test patients. The results obtained using our methods compare favourably with those obtained using alternative kernels (80.18% accuracy for the QBK) and the standard clinical prediction method, which are based on the basal SAPS score or logistic regression (71.32% and 71.55%, respectively). The QBK presented a sensitivity and specificity of 79.34% and 83.24%, which outperformed the other kernels

Kernel Methods for Mining Instance Data in Ontologies

NASA Astrophysics Data System (ADS)

Bloehdorn, Stephan; Sure, York

The amount of ontologies and meta data available on the Web is constantly growing. The successful application of machine learning techniques for learning of ontologies from textual data, i.e. mining for the Semantic Web, contributes to this trend. However, no principal approaches exist so far for mining from the Semantic Web. We investigate how machine learning algorithms can be made amenable for directly taking advantage of the rich knowledge expressed in ontologies and associated instance data. Kernel methods have been successfully employed in various learning tasks and provide a clean framework for interfacing between non-vectorial data and machine learning algorithms. In this spirit, we express the problem of mining instances in ontologies as the problem of defining valid corresponding kernels. We present a principled framework for designing such kernels by means of decomposing the kernel computation into specialized kernels for selected characteristics of an ontology which can be flexibly assembled and tuned. Initial experiments on real world Semantic Web data enjoy promising results and show the usefulness of our approach.

Biasing anisotropic scattering kernels for deep-penetration Monte Carlo calculations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carter, L.L.; Hendricks, J.S.

1983-01-01

The exponential transform is often used to improve the efficiency of deep-penetration Monte Carlo calculations. This technique is usually implemented by biasing the distance-to-collision kernel of the transport equation, but leaving the scattering kernel unchanged. Dwivedi obtained significant improvements in efficiency by biasing an isotropic scattering kernel as well as the distance-to-collision kernel. This idea is extended to anisotropic scattering, particularly the highly forward Klein-Nishina scattering of gamma rays.

Direct Measurement of Wave Kernels in Time-Distance Helioseismology

NASA Technical Reports Server (NTRS)

Duvall, T. L., Jr.

2006-01-01

Solar f-mode waves are surface-gravity waves which propagate horizontally in a thin layer near the photosphere with a dispersion relation approximately that of deep water waves. At the power maximum near 3 mHz, the wavelength of 5 Mm is large enough for various wave scattering properties to be observable. Gizon and Birch (2002,ApJ,571,966)h ave calculated kernels, in the Born approximation, for the sensitivity of wave travel times to local changes in damping rate and source strength. In this work, using isolated small magnetic features as approximate point-sourc'e scatterers, such a kernel has been measured. The observed kernel contains similar features to a theoretical damping kernel but not for a source kernel. A full understanding of the effect of small magnetic features on the waves will require more detailed modeling.

Characterization of polysaccharides from Ganoderma spp. using saccharide mapping.

PubMed

Wu, Ding-Tao; Xie, Jing; Hu, De-Jun; Zhao, Jing; Li, Shao-Ping

2013-09-12

Polysaccharides from Ganoderma spp. and their adulterants were firstly investigated and compared using saccharide mapping, enzymatic (endo-1,3-β-D-glucanase and pectinase) digestion followed by polysaccharide analysis using carbohydrate gel electrophoresis analysis. The results showed that both 1,3-β-D-glucosidic and 1,4-α-D-galactosiduronic linkages were existed in Lingzhi (Ganoderma lucidum and Ganoderma sinense), and the similarity of polysaccharides from G. lucidum and G. sinense was high, which may contribute to rational use of Lingzhi. Different species of Ganoderma and their adulterants can be differentiated based on the saccharide mapping, which is helpful to well understand the structural characters of polysaccharides from different species of Ganoderma and to improve the quality control of polysaccharides in Lingzhi. Copyright © 2013 Elsevier Ltd. All rights reserved.

Dropping macadamia nuts-in-shell reduces kernel roasting quality.

PubMed

Walton, David A; Wallace, Helen M

2010-10-01

Macadamia nuts ('nuts-in-shell') are subjected to many impacts from dropping during postharvest handling, resulting in damage to the raw kernel. The effect of dropping on roasted kernel quality is unknown. Macadamia nuts-in-shell were dropped in various combinations of moisture content, number of drops and receiving surface in three experiments. After dropping, samples from each treatment and undropped controls were dry oven-roasted for 20 min at 130 °C, and kernels were assessed for colour, mottled colour and surface damage. Dropping nuts-in-shell onto a bed of nuts-in-shell at 3% moisture content or 20% moisture content increased the percentage of dark roasted kernels. Kernels from nuts dropped first at 20%, then 10% moisture content, onto a metal plate had increased mottled colour. Dropping nuts-in-shell at 3% moisture content onto nuts-in-shell significantly increased surface damage. Similarly, surface damage increased for kernels dropped onto a metal plate at 20%, then at 10% moisture content. Postharvest dropping of macadamia nuts-in-shell causes concealed cellular damage to kernels, the effects not evident until roasting. This damage provides the reagents needed for non-enzymatic browning reactions. Improvements in handling, such as reducing the number of drops and improving handling equipment, will reduce cellular damage and after-roast darkening. Copyright © 2010 Society of Chemical Industry.

Anticancer properties of polysaccharides isolated from fungi of the Basidiomycetes class.

PubMed

Lemieszek, Marta; Rzeski, Wojciech

2012-01-01

Basidiomycete mushrooms represent a valuable source of biologically active compounds with anticancer properties. This feature is primarily attributed to polysaccharides and their derivatives. The anticancer potential of polysaccharides is linked to their origin, composition and chemical structure, solubility and method of isolation. Moreover, their activity can be significantly increased by chemical modifications. Anticancer effects of polysaccharides can be expressed indirectly (immunostimulation) or directly (cell proliferation inhibition and/or apoptosis induction). Among the wide range of polysaccharides with documented anticancer properties, lentinan, polysaccharide-K (PSK) and schizophyllan deserve special attention. These polysaccharides for many years have been successfully applied in cancer treatment and their mechanism of action is the best known.

Compound analysis via graph kernels incorporating chirality.

PubMed

Brown, J B; Urata, Takashi; Tamura, Takeyuki; Arai, Midori A; Kawabata, Takeo; Akutsu, Tatsuya

2010-12-01

High accuracy is paramount when predicting biochemical characteristics using Quantitative Structural-Property Relationships (QSPRs). Although existing graph-theoretic kernel methods combined with machine learning techniques are efficient for QSPR model construction, they cannot distinguish topologically identical chiral compounds which often exhibit different biological characteristics. In this paper, we propose a new method that extends the recently developed tree pattern graph kernel to accommodate stereoisomers. We show that Support Vector Regression (SVR) with a chiral graph kernel is useful for target property prediction by demonstrating its application to a set of human vitamin D receptor ligands currently under consideration for their potential anti-cancer effects.

Chemical characteristics and anti-proliferation activities of Ganoderma tsugae polysaccharides.

PubMed

Chien, Rao-Chi; Yen, Ming-Tsung; Tseng, Yu-Hsiu; Mau, Jeng-Leun

2015-09-05

Polysaccharides were extracted by hot-water and hot-alkali from four forms of Ganoderma tsugae including mature and baby Ling chih, mycelium and filtrate. Different profiles of proximate composition and monosaccharide constituents, and element contents were found in the extracted polysaccharides from different extractions and different forms. The molecular weight distributions of polysaccharides were 2.8×10(4)-6.5×10(5)Da and their infrared spectra were comparable. The hot-alkali extracted polysaccharides exhibited better anti-proliferation on IMR32 cells than the hot-water extracted polysaccharides, which were in turn more effective than the hot-water extracts. Besides, most hot-water extracts and both extracted polysaccharides exhibited an anti-proliferation effect on Hep G2 cells. However, the hot-water extracts showed less effective in anti-proliferation of IMR32 and Hep G2 cells. Based on the anti-tumor effects, both polysaccharides could be prepared for use in the formulation of nutraceuticals and functional foods. Copyright © 2015 Elsevier Ltd. All rights reserved.

Kernel-aligned multi-view canonical correlation analysis for image recognition

NASA Astrophysics Data System (ADS)

Su, Shuzhi; Ge, Hongwei; Yuan, Yun-Hao

2016-09-01

Existing kernel-based correlation analysis methods mainly adopt a single kernel in each view. However, only a single kernel is usually insufficient to characterize nonlinear distribution information of a view. To solve the problem, we transform each original feature vector into a 2-dimensional feature matrix by means of kernel alignment, and then propose a novel kernel-aligned multi-view canonical correlation analysis (KAMCCA) method on the basis of the feature matrices. Our proposed method can simultaneously employ multiple kernels to better capture the nonlinear distribution information of each view, so that correlation features learned by KAMCCA can have well discriminating power in real-world image recognition. Extensive experiments are designed on five real-world image datasets, including NIR face images, thermal face images, visible face images, handwritten digit images, and object images. Promising experimental results on the datasets have manifested the effectiveness of our proposed method.

A kernel adaptive algorithm for quaternion-valued inputs.

PubMed

Paul, Thomas K; Ogunfunmi, Tokunbo

2015-10-01

The use of quaternion data can provide benefit in applications like robotics and image recognition, and particularly for performing transforms in 3-D space. Here, we describe a kernel adaptive algorithm for quaternions. A least mean square (LMS)-based method was used, resulting in the derivation of the quaternion kernel LMS (Quat-KLMS) algorithm. Deriving this algorithm required describing the idea of a quaternion reproducing kernel Hilbert space (RKHS), as well as kernel functions suitable with quaternions. A modified HR calculus for Hilbert spaces was used to find the gradient of cost functions defined on a quaternion RKHS. In addition, the use of widely linear (or augmented) filtering is proposed to improve performance. The benefit of the Quat-KLMS and widely linear forms in learning nonlinear transformations of quaternion data are illustrated with simulations.

Improving the Bandwidth Selection in Kernel Equating

ERIC Educational Resources Information Center

Andersson, Björn; von Davier, Alina A.

2014-01-01

We investigate the current bandwidth selection methods in kernel equating and propose a method based on Silverman's rule of thumb for selecting the bandwidth parameters. In kernel equating, the bandwidth parameters have previously been obtained by minimizing a penalty function. This minimization process has been criticized by practitioners…

Anticancer polysaccharides from natural resources: a review of recent research.

PubMed

Zong, Aizhen; Cao, Hongzhi; Wang, Fengshan

2012-11-06

Taking into account the rising trend of the incidence of cancers of various organs, effective therapies are urgently needed to control human malignancies. However, almost all of the chemotherapy drugs currently on the market cause serious side effects. Fortunately, several previous studies have shown that some non-toxic biological macromolecules, including polysaccharides and polysaccharide-protein complexes, possess anti-cancer activities or can increase the efficacy of conventional chemotherapy drugs. Based on these encouraging observations, a great deal of effort has been focused on discovering anti-cancer polysaccharides and complexes for the development of effective therapeutics for various human cancers. This review focuses on the advancements in the anti-cancer efficacy of various natural polysaccharides and polysaccharide complexes in the past 5 years. Most polysaccharides were tested using model systems, while several involved clinical trials. Copyright © 2012 Elsevier Ltd. All rights reserved.

Nature and composition of fat bloom from palm kernel stearin and hydrogenated palm kernel stearin compound chocolates.

PubMed

Smith, Kevin W; Cain, Fred W; Talbot, Geoff

2004-08-25

Palm kernel stearin and hydrogenated palm kernel stearin can be used to prepare compound chocolate bars or coatings. The objective of this study was to characterize the chemical composition, polymorphism, and melting behavior of the bloom that develops on bars of compound chocolate prepared using these fats. Bars were stored for 1 year at 15, 20, or 25 degrees C. At 15 and 20 degrees C the bloom was enriched in cocoa butter triacylglycerols, with respect to the main fat phase, whereas at 25 degrees C the enrichment was with palm kernel triacylglycerols. The bloom consisted principally of solid fat and was sharper melting than was the fat in the chocolate. Polymorphic transitions from the initial beta' phase to the beta phase accompanied the formation of bloom at all temperatures.

Rheologically interesting polysaccharides from yeasts

NASA Technical Reports Server (NTRS)

Petersen, G. R.; Nelson, G. A.; Cathey, C. A.; Fuller, G. G.

1989-01-01

We have examined the relationships between primary, secondary, and tertiary structures of polysaccharides exhibiting the rheological property of friction (drag) reduction in turbulent flows. We found an example of an exopolysaccharide from the yeast Cryptococcus laurentii that possessed high molecular weight but exhibited lower than expected drag reducing activity. Earlier correlations by Hoyt showing that beta 1 --> 3, beta 2 --> 4, and alpha 1 --> 3 linkages in polysaccharides favored drag reduction were expanded to include correlations to secondary structure. The effect of sidechains in a series of gellan gums was shown to be related to sidechain length and position. Disruption of secondary structure in drag reducing polysaccharides reduced drag reducing activity for some but not all exopolysaccharides. The polymer from C. laurentii was shown to be more stable than xanthan gum and other exopolysaccharides under the most vigorous of denaturing conditions. We also showed a direct relationship between extensional viscosity measurements and the drag reducing coefficient for four exopolysaccharides.

Online learning control using adaptive critic designs with sparse kernel machines.

PubMed

Xu, Xin; Hou, Zhongsheng; Lian, Chuanqiang; He, Haibo

2013-05-01

In the past decade, adaptive critic designs (ACDs), including heuristic dynamic programming (HDP), dual heuristic programming (DHP), and their action-dependent ones, have been widely studied to realize online learning control of dynamical systems. However, because neural networks with manually designed features are commonly used to deal with continuous state and action spaces, the generalization capability and learning efficiency of previous ACDs still need to be improved. In this paper, a novel framework of ACDs with sparse kernel machines is presented by integrating kernel methods into the critic of ACDs. To improve the generalization capability as well as the computational efficiency of kernel machines, a sparsification method based on the approximately linear dependence analysis is used. Using the sparse kernel machines, two kernel-based ACD algorithms, that is, kernel HDP (KHDP) and kernel DHP (KDHP), are proposed and their performance is analyzed both theoretically and empirically. Because of the representation learning and generalization capability of sparse kernel machines, KHDP and KDHP can obtain much better performance than previous HDP and DHP with manually designed neural networks. Simulation and experimental results of two nonlinear control problems, that is, a continuous-action inverted pendulum problem and a ball and plate control problem, demonstrate the effectiveness of the proposed kernel ACD methods.

Polysaccharides from Traditional Chinese Medicines: Extraction, Purification, Modification, and Biological Activity.

PubMed

Chen, Yun; Yao, Fangke; Ming, Ke; Wang, Deyun; Hu, Yuanliang; Liu, Jiaguo

2016-12-13

Traditional Chinese Medicine (TCM) has been used to treat diseases in China for thousands of years. TCM compositions are complex, using as their various sources plants, animals, fungi, and minerals. Polysaccharides are one of the active and important ingredients of TCMs. Polysaccharides from TCMs exhibit a wide range of biological activities in terms of immunity- modifying, antiviral, anti-inflammatory, anti-oxidative, and anti-tumor properties. With their widespread biological activities, polysaccharides consistently attract scientist's interests, and the studies often concentrate on the extraction, purification, and biological activity of TCM polysaccharides. Currently, numerous studies have shown that the modification of polysaccharides can heighten or change the biological activities, which is a new angle of polysaccharide research. This review highlights the current knowledge of TCM polysaccharides, including their extraction, purification, modification, and biological activity, which will hopefully provide profound insights facilitating further research and development.

Kernel analysis of partial least squares (PLS) regression models.

PubMed

Shinzawa, Hideyuki; Ritthiruangdej, Pitiporn; Ozaki, Yukihiro

2011-05-01

An analytical technique based on kernel matrix representation is demonstrated to provide further chemically meaningful insight into partial least squares (PLS) regression models. The kernel matrix condenses essential information about scores derived from PLS or principal component analysis (PCA). Thus, it becomes possible to establish the proper interpretation of the scores. A PLS model for the total nitrogen (TN) content in multiple Thai fish sauces is built with a set of near-infrared (NIR) transmittance spectra of the fish sauce samples. The kernel analysis of the scores effectively reveals that the variation of the spectral feature induced by the change in protein content is substantially associated with the total water content and the protein hydration. Kernel analysis is also carried out on a set of time-dependent infrared (IR) spectra representing transient evaporation of ethanol from a binary mixture solution of ethanol and oleic acid. A PLS model to predict the elapsed time is built with the IR spectra and the kernel matrix is derived from the scores. The detailed analysis of the kernel matrix provides penetrating insight into the interaction between the ethanol and the oleic acid.

A multi-label learning based kernel automatic recommendation method for support vector machine.

PubMed

Zhang, Xueying; Song, Qinbao

2015-01-01

Choosing an appropriate kernel is very important and critical when classifying a new problem with Support Vector Machine. So far, more attention has been paid on constructing new kernels and choosing suitable parameter values for a specific kernel function, but less on kernel selection. Furthermore, most of current kernel selection methods focus on seeking a best kernel with the highest classification accuracy via cross-validation, they are time consuming and ignore the differences among the number of support vectors and the CPU time of SVM with different kernels. Considering the tradeoff between classification success ratio and CPU time, there may be multiple kernel functions performing equally well on the same classification problem. Aiming to automatically select those appropriate kernel functions for a given data set, we propose a multi-label learning based kernel recommendation method built on the data characteristics. For each data set, the meta-knowledge data base is first created by extracting the feature vector of data characteristics and identifying the corresponding applicable kernel set. Then the kernel recommendation model is constructed on the generated meta-knowledge data base with the multi-label classification method. Finally, the appropriate kernel functions are recommended to a new data set by the recommendation model according to the characteristics of the new data set. Extensive experiments over 132 UCI benchmark data sets, with five different types of data set characteristics, eleven typical kernels (Linear, Polynomial, Radial Basis Function, Sigmoidal function, Laplace, Multiquadric, Rational Quadratic, Spherical, Spline, Wave and Circular), and five multi-label classification methods demonstrate that, compared with the existing kernel selection methods and the most widely used RBF kernel function, SVM with the kernel function recommended by our proposed method achieved the highest classification performance.

A Multi-Label Learning Based Kernel Automatic Recommendation Method for Support Vector Machine

PubMed Central

Zhang, Xueying; Song, Qinbao

2015-01-01

Choosing an appropriate kernel is very important and critical when classifying a new problem with Support Vector Machine. So far, more attention has been paid on constructing new kernels and choosing suitable parameter values for a specific kernel function, but less on kernel selection. Furthermore, most of current kernel selection methods focus on seeking a best kernel with the highest classification accuracy via cross-validation, they are time consuming and ignore the differences among the number of support vectors and the CPU time of SVM with different kernels. Considering the tradeoff between classification success ratio and CPU time, there may be multiple kernel functions performing equally well on the same classification problem. Aiming to automatically select those appropriate kernel functions for a given data set, we propose a multi-label learning based kernel recommendation method built on the data characteristics. For each data set, the meta-knowledge data base is first created by extracting the feature vector of data characteristics and identifying the corresponding applicable kernel set. Then the kernel recommendation model is constructed on the generated meta-knowledge data base with the multi-label classification method. Finally, the appropriate kernel functions are recommended to a new data set by the recommendation model according to the characteristics of the new data set. Extensive experiments over 132 UCI benchmark data sets, with five different types of data set characteristics, eleven typical kernels (Linear, Polynomial, Radial Basis Function, Sigmoidal function, Laplace, Multiquadric, Rational Quadratic, Spherical, Spline, Wave and Circular), and five multi-label classification methods demonstrate that, compared with the existing kernel selection methods and the most widely used RBF kernel function, SVM with the kernel function recommended by our proposed method achieved the highest classification performance. PMID:25893896

Corn kernel oil and corn fiber oil

USDA-ARS?s Scientific Manuscript database

Unlike most edible plant oils that are obtained directly from oil-rich seeds by either pressing or solvent extraction, corn seeds (kernels) have low levels of oil (4%) and commercial corn oil is obtained from the corn germ (embryo) which is an oil-rich portion of the kernel. Commercial corn oil cou...

Convolution kernels for multi-wavelength imaging

NASA Astrophysics Data System (ADS)

Boucaud, A.; Bocchio, M.; Abergel, A.; Orieux, F.; Dole, H.; Hadj-Youcef, M. A.

2016-12-01

Astrophysical images issued from different instruments and/or spectral bands often require to be processed together, either for fitting or comparison purposes. However each image is affected by an instrumental response, also known as point-spread function (PSF), that depends on the characteristics of the instrument as well as the wavelength and the observing strategy. Given the knowledge of the PSF in each band, a straightforward way of processing images is to homogenise them all to a target PSF using convolution kernels, so that they appear as if they had been acquired by the same instrument. We propose an algorithm that generates such PSF-matching kernels, based on Wiener filtering with a tunable regularisation parameter. This method ensures all anisotropic features in the PSFs to be taken into account. We compare our method to existing procedures using measured Herschel/PACS and SPIRE PSFs and simulated JWST/MIRI PSFs. Significant gains up to two orders of magnitude are obtained with respect to the use of kernels computed assuming Gaussian or circularised PSFs. A software to compute these kernels is available at https://github.com/aboucaud/pypher

Blend-modification of soy protein/lauric acid edible films using polysaccharides.

PubMed

Pan, Hongyang; Jiang, Bo; Chen, Jie; Jin, Zhengyu

2014-05-15

Different types of polysaccharides (propyleneglycol alginate (PGA), pectin, carrageenan and aloe polysaccharide) were incorporated into soy protein isolate (SPI)/lauric acid (La) films using a co-drying process or by direct addition to form biodegradable composite films with modified water vapour permeability (WVP) and mechanical properties. The WVP of SPI/La/polysaccharide films decreased when polysaccharides were added using the co-drying process, regardless of the type of polysaccharide. The tensile strength of SPI/La film was increased by the addition of polysaccharides, and the percentage elongation at break was increased by incorporating PGA using the co-drying process. Regarding oxygen-barrier performance, no notable differences were observed between the SPI/La and SPI/La/polysaccharide films. The most significant improvement was observed by blending PGA, with the co-dried preparation exhibiting better properties than the direct-addition preparation. Scanning electron microscopy (SEM) revealed that the microstructures of the films are the basis for the differences in the barrier and mechanical properties of the modified blends of SPI, polysaccharides and La. Copyright © 2013 Elsevier Ltd. All rights reserved.

Aureobasidium pullulans morphology: two adapted polysaccharide stains.

PubMed

Oller, Anna R

2005-12-01

Morphological stages of Aureobasidium pullulans were investigated utilizing different media ingredients and were visualized by bright-field microscopy. A polysaccharide stain was developed to stain chlamydospores, cell walls, hyphae, and conidia, since current staining techniques do not reveal subcellular details to identify fungi, especially those that exhibit polysaccharide secretions.

Unsupervised multiple kernel learning for heterogeneous data integration.

PubMed

Mariette, Jérôme; Villa-Vialaneix, Nathalie

2018-03-15

Recent high-throughput sequencing advances have expanded the breadth of available omics datasets and the integrated analysis of multiple datasets obtained on the same samples has allowed to gain important insights in a wide range of applications. However, the integration of various sources of information remains a challenge for systems biology since produced datasets are often of heterogeneous types, with the need of developing generic methods to take their different specificities into account. We propose a multiple kernel framework that allows to integrate multiple datasets of various types into a single exploratory analysis. Several solutions are provided to learn either a consensus meta-kernel or a meta-kernel that preserves the original topology of the datasets. We applied our framework to analyse two public multi-omics datasets. First, the multiple metagenomic datasets, collected during the TARA Oceans expedition, was explored to demonstrate that our method is able to retrieve previous findings in a single kernel PCA as well as to provide a new image of the sample structures when a larger number of datasets are included in the analysis. To perform this analysis, a generic procedure is also proposed to improve the interpretability of the kernel PCA in regards with the original data. Second, the multi-omics breast cancer datasets, provided by The Cancer Genome Atlas, is analysed using a kernel Self-Organizing Maps with both single and multi-omics strategies. The comparison of these two approaches demonstrates the benefit of our integration method to improve the representation of the studied biological system. Proposed methods are available in the R package mixKernel, released on CRAN. It is fully compatible with the mixOmics package and a tutorial describing the approach can be found on mixOmics web site http://mixomics.org/mixkernel/. jerome.mariette@inra.fr or nathalie.villa-vialaneix@inra.fr. Supplementary data are available at Bioinformatics online.

Protein fold recognition using geometric kernel data fusion.

PubMed

Zakeri, Pooya; Jeuris, Ben; Vandebril, Raf; Moreau, Yves

2014-07-01

Various approaches based on features extracted from protein sequences and often machine learning methods have been used in the prediction of protein folds. Finding an efficient technique for integrating these different protein features has received increasing attention. In particular, kernel methods are an interesting class of techniques for integrating heterogeneous data. Various methods have been proposed to fuse multiple kernels. Most techniques for multiple kernel learning focus on learning a convex linear combination of base kernels. In addition to the limitation of linear combinations, working with such approaches could cause a loss of potentially useful information. We design several techniques to combine kernel matrices by taking more involved, geometry inspired means of these matrices instead of convex linear combinations. We consider various sequence-based protein features including information extracted directly from position-specific scoring matrices and local sequence alignment. We evaluate our methods for classification on the SCOP PDB-40D benchmark dataset for protein fold recognition. The best overall accuracy on the protein fold recognition test set obtained by our methods is ∼ 86.7%. This is an improvement over the results of the best existing approach. Moreover, our computational model has been developed by incorporating the functional domain composition of proteins through a hybridization model. It is observed that by using our proposed hybridization model, the protein fold recognition accuracy is further improved to 89.30%. Furthermore, we investigate the performance of our approach on the protein remote homology detection problem by fusing multiple string kernels. The MATLAB code used for our proposed geometric kernel fusion frameworks are publicly available at http://people.cs.kuleuven.be/∼raf.vandebril/homepage/software/geomean.php?menu=5/. © The Author 2014. Published by Oxford University Press.

Intestinal microbiota are involved in the immunomodulatory activities of longan polysaccharide.

PubMed

Zhang, Jiachao; Yang, Guangmei; Wen, Yazhou; Liu, Sixin; Li, Congfa; Yang, Ruili; Li, Wu

2017-11-01

It is difficult for polysaccharides to be directly absorbed through the intestine, which implies other utilization mechanisms involved in the bioactivity performance of polysaccharide. In this study, the multi-omics approach was applied to investigate the impacts of longan polysaccharide on mouse intestinal microbiome and the interaction between the polysaccharide-derived microbiome and host immune system. According to the result, the longan polysaccharide showed a significant improvement in the typical intestinal immunity index of mice. Meanwhile, at the taxonomy level, the intestinal microbiota from the control group and polysaccharide group were highly distinct in organismal structure. At the functional level, a significant decline in the microbial metabolites of pyruvate, butanoate fructose and mannose in the control group was found. Additionally, a significant increase was observed in the succinic acid and the short-chain fatty acid, including acetic acid, propionic acid and butyric acid, in the polysaccharide group. Furthermore, the multi-omic based network analysis indicated that the intake of longan polysaccharide resulted in the changes of the intestinal microbiota as well as the gut metabolites, which led to the enhancement of host's immune function under the stress conditions. These results indicated the polysaccharide-derived changes in intestinal microbiota were involved in the immunomodulatory activities. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Proteome analysis of the almond kernel (Prunus dulcis).

PubMed

Li, Shugang; Geng, Fang; Wang, Ping; Lu, Jiankang; Ma, Meihu

2016-08-01

Almond (Prunus dulcis) is a popular tree nut worldwide and offers many benefits to human health. However, the importance of almond kernel proteins in the nutrition and function in human health requires further evaluation. The present study presents a systematic evaluation of the proteins in the almond kernel using proteomic analysis. The nutrient and amino acid content in almond kernels from Xinjiang is similar to that of American varieties; however, Xinjiang varieties have a higher protein content. Two-dimensional electrophoresis analysis demonstrated a wide distribution of molecular weights and isoelectric points of almond kernel proteins. A total of 434 proteins were identified by LC-MS/MS, and most were proteins that were experimentally confirmed for the first time. Gene ontology (GO) analysis of the 434 proteins indicated that proteins involved in primary biological processes including metabolic processes (67.5%), cellular processes (54.1%), and single-organism processes (43.4%), the main molecular function of almond kernel proteins are in catalytic activity (48.0%), binding (45.4%) and structural molecule activity (11.9%), and proteins are primarily distributed in cell (59.9%), organelle (44.9%), and membrane (22.8%). Almond kernel is a source of a wide variety of proteins. This study provides important information contributing to the screening and identification of almond proteins, the understanding of almond protein function, and the development of almond protein products. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

Control Transfer in Operating System Kernels

DTIC Science & Technology

1994-05-13

microkernel system that runs less code in the kernel address space. To realize the performance benefit of allocating stacks in unmapped kseg0 memory, the...review how I modified the Mach 3.0 kernel to use continuations. Because of Mach’s message-passing microkernel structure, interprocess communication was...critical control transfer paths, deeply- nested call chains are undesirable in any case because of the function call overhead. 4.1.3 Microkernel Operating

Experimental study of turbulent flame kernel propagation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mansour, Mohy; Peters, Norbert; Schrader, Lars-Uve

2008-07-15

Flame kernels in spark ignited combustion systems dominate the flame propagation and combustion stability and performance. They are likely controlled by the spark energy, flow field and mixing field. The aim of the present work is to experimentally investigate the structure and propagation of the flame kernel in turbulent premixed methane flow using advanced laser-based techniques. The spark is generated using pulsed Nd:YAG laser with 20 mJ pulse energy in order to avoid the effect of the electrodes on the flame kernel structure and the variation of spark energy from shot-to-shot. Four flames have been investigated at equivalence ratios, {phi}{submore » j}, of 0.8 and 1.0 and jet velocities, U{sub j}, of 6 and 12 m/s. A combined two-dimensional Rayleigh and LIPF-OH technique has been applied. The flame kernel structure has been collected at several time intervals from the laser ignition between 10 {mu}s and 2 ms. The data show that the flame kernel structure starts with spherical shape and changes gradually to peanut-like, then to mushroom-like and finally disturbed by the turbulence. The mushroom-like structure lasts longer in the stoichiometric and slower jet velocity. The growth rate of the average flame kernel radius is divided into two linear relations; the first one during the first 100 {mu}s is almost three times faster than that at the later stage between 100 and 2000 {mu}s. The flame propagation is slightly faster in leaner flames. The trends of the flame propagation, flame radius, flame cross-sectional area and mean flame temperature are related to the jet velocity and equivalence ratio. The relations obtained in the present work allow the prediction of any of these parameters at different conditions. (author)« less

Bivariate discrete beta Kernel graduation of mortality data.

PubMed

Mazza, Angelo; Punzo, Antonio

2015-07-01

Various parametric/nonparametric techniques have been proposed in literature to graduate mortality data as a function of age. Nonparametric approaches, as for example kernel smoothing regression, are often preferred because they do not assume any particular mortality law. Among the existing kernel smoothing approaches, the recently proposed (univariate) discrete beta kernel smoother has been shown to provide some benefits. Bivariate graduation, over age and calendar years or durations, is common practice in demography and actuarial sciences. In this paper, we generalize the discrete beta kernel smoother to the bivariate case, and we introduce an adaptive bandwidth variant that may provide additional benefits when data on exposures to the risk of death are available; furthermore, we outline a cross-validation procedure for bandwidths selection. Using simulations studies, we compare the bivariate approach proposed here with its corresponding univariate formulation and with two popular nonparametric bivariate graduation techniques, based on Epanechnikov kernels and on P-splines. To make simulations realistic, a bivariate dataset, based on probabilities of dying recorded for the US males, is used. Simulations have confirmed the gain in performance of the new bivariate approach with respect to both the univariate and the bivariate competitors.

A Linear Kernel for Co-Path/Cycle Packing

NASA Astrophysics Data System (ADS)

Chen, Zhi-Zhong; Fellows, Michael; Fu, Bin; Jiang, Haitao; Liu, Yang; Wang, Lusheng; Zhu, Binhai

Bounded-Degree Vertex Deletion is a fundamental problem in graph theory that has new applications in computational biology. In this paper, we address a special case of Bounded-Degree Vertex Deletion, the Co-Path/Cycle Packing problem, which asks to delete as few vertices as possible such that the graph of the remaining (residual) vertices is composed of disjoint paths and simple cycles. The problem falls into the well-known class of 'node-deletion problems with hereditary properties', is hence NP-complete and unlikely to admit a polynomial time approximation algorithm with approximation factor smaller than 2. In the framework of parameterized complexity, we present a kernelization algorithm that produces a kernel with at most 37k vertices, improving on the super-linear kernel of Fellows et al.'s general theorem for Bounded-Degree Vertex Deletion. Using this kernel,and the method of bounded search trees, we devise an FPT algorithm that runs in time O *(3.24 k ). On the negative side, we show that the problem is APX-hard and unlikely to have a kernel smaller than 2k by a reduction from Vertex Cover.

7 CFR 51.1403 - Kernel color classification.

Code of Federal Regulations, 2011 CFR

2011-01-01

... classifications provided in this section. When the color of kernels in a lot generally conforms to the “light” or “light amber” classification, that color classification may be used to describe the lot in connection with the grade. (1) “Light” means that the outer surface of the kernel is mostly golden color or...

7 CFR 51.1403 - Kernel color classification.

Code of Federal Regulations, 2012 CFR

2012-01-01

... classifications provided in this section. When the color of kernels in a lot generally conforms to the “light” or “light amber” classification, that color classification may be used to describe the lot in connection with the grade. (1) “Light” means that the outer surface of the kernel is mostly golden color or...

Pneumococcal polysaccharide vaccine - what you need to know

MedlinePlus

... taken in its entirety from the CDC Pneumococcal Polysaccharide Vaccine Information Statement (VIS): www.cdc.gov/vaccines/ ... statements/ppv.html CDC review information for Pneumococcal Polysaccharide VIS: Page last reviewed: April 24, 2015 Page ...

A framework for optimal kernel-based manifold embedding of medical image data.

PubMed

Zimmer, Veronika A; Lekadir, Karim; Hoogendoorn, Corné; Frangi, Alejandro F; Piella, Gemma

2015-04-01

Kernel-based dimensionality reduction is a widely used technique in medical image analysis. To fully unravel the underlying nonlinear manifold the selection of an adequate kernel function and of its free parameters is critical. In practice, however, the kernel function is generally chosen as Gaussian or polynomial and such standard kernels might not always be optimal for a given image dataset or application. In this paper, we present a study on the effect of the kernel functions in nonlinear manifold embedding of medical image data. To this end, we first carry out a literature review on existing advanced kernels developed in the statistics, machine learning, and signal processing communities. In addition, we implement kernel-based formulations of well-known nonlinear dimensional reduction techniques such as Isomap and Locally Linear Embedding, thus obtaining a unified framework for manifold embedding using kernels. Subsequently, we present a method to automatically choose a kernel function and its associated parameters from a pool of kernel candidates, with the aim to generate the most optimal manifold embeddings. Furthermore, we show how the calculated selection measures can be extended to take into account the spatial relationships in images, or used to combine several kernels to further improve the embedding results. Experiments are then carried out on various synthetic and phantom datasets for numerical assessment of the methods. Furthermore, the workflow is applied to real data that include brain manifolds and multispectral images to demonstrate the importance of the kernel selection in the analysis of high-dimensional medical images. Copyright © 2014 Elsevier Ltd. All rights reserved.

Relationship of source and sink in determining kernel composition of maize

PubMed Central

Seebauer, Juliann R.; Singletary, George W.; Krumpelman, Paulette M.; Ruffo, Matías L.; Below, Frederick E.

2010-01-01

The relative role of the maternal source and the filial sink in controlling the composition of maize (Zea mays L.) kernels is unclear and may be influenced by the genotype and the N supply. The objective of this study was to determine the influence of assimilate supply from the vegetative source and utilization of assimilates by the grain sink on the final composition of maize kernels. Intermated B73×Mo17 recombinant inbred lines (IBM RILs) which displayed contrasting concentrations of endosperm starch were grown in the field with deficient or sufficient N, and the source supply altered by ear truncation (45% reduction) at 15 d after pollination (DAP). The assimilate supply into the kernels was determined at 19 DAP using the agar trap technique, and the final kernel composition was measured. The influence of N supply and kernel ear position on final kernel composition was also determined for a commercial hybrid. Concentrations of kernel protein and starch could be altered by genotype or the N supply, but remained fairly constant along the length of the ear. Ear truncation also produced a range of variation in endosperm starch and protein concentrations. The C/N ratio of the assimilate supply at 19 DAP was directly related to the final kernel composition, with an inverse relationship between the concentrations of starch and protein in the mature endosperm. The accumulation of kernel starch and protein in maize is uniform along the ear, yet adaptable within genotypic limits, suggesting that kernel composition is source limited in maize. PMID:19917600

Resummed memory kernels in generalized system-bath master equations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mavros, Michael G.; Van Voorhis, Troy, E-mail: tvan@mit.edu

2014-08-07

Generalized master equations provide a concise formalism for studying reduced population dynamics. Usually, these master equations require a perturbative expansion of the memory kernels governing the dynamics; in order to prevent divergences, these expansions must be resummed. Resummation techniques of perturbation series are ubiquitous in physics, but they have not been readily studied for the time-dependent memory kernels used in generalized master equations. In this paper, we present a comparison of different resummation techniques for such memory kernels up to fourth order. We study specifically the spin-boson Hamiltonian as a model system bath Hamiltonian, treating the diabatic coupling between themore » two states as a perturbation. A novel derivation of the fourth-order memory kernel for the spin-boson problem is presented; then, the second- and fourth-order kernels are evaluated numerically for a variety of spin-boson parameter regimes. We find that resumming the kernels through fourth order using a Padé approximant results in divergent populations in the strong electronic coupling regime due to a singularity introduced by the nature of the resummation, and thus recommend a non-divergent exponential resummation (the “Landau-Zener resummation” of previous work). The inclusion of fourth-order effects in a Landau-Zener-resummed kernel is shown to improve both the dephasing rate and the obedience of detailed balance over simpler prescriptions like the non-interacting blip approximation, showing a relatively quick convergence on the exact answer. The results suggest that including higher-order contributions to the memory kernel of a generalized master equation and performing an appropriate resummation can provide a numerically-exact solution to system-bath dynamics for a general spectral density, opening the way to a new class of methods for treating system-bath dynamics.« less

Improving prediction of heterodimeric protein complexes using combination with pairwise kernel.

PubMed

Ruan, Peiying; Hayashida, Morihiro; Akutsu, Tatsuya; Vert, Jean-Philippe

2018-02-19

Since many proteins become functional only after they interact with their partner proteins and form protein complexes, it is essential to identify the sets of proteins that form complexes. Therefore, several computational methods have been proposed to predict complexes from the topology and structure of experimental protein-protein interaction (PPI) network. These methods work well to predict complexes involving at least three proteins, but generally fail at identifying complexes involving only two different proteins, called heterodimeric complexes or heterodimers. There is however an urgent need for efficient methods to predict heterodimers, since the majority of known protein complexes are precisely heterodimers. In this paper, we use three promising kernel functions, Min kernel and two pairwise kernels, which are Metric Learning Pairwise Kernel (MLPK) and Tensor Product Pairwise Kernel (TPPK). We also consider the normalization forms of Min kernel. Then, we combine Min kernel or its normalization form and one of the pairwise kernels by plugging. We applied kernels based on PPI, domain, phylogenetic profile, and subcellular localization properties to predicting heterodimers. Then, we evaluate our method by employing C-Support Vector Classification (C-SVC), carrying out 10-fold cross-validation, and calculating the average F-measures. The results suggest that the combination of normalized-Min-kernel and MLPK leads to the best F-measure and improved the performance of our previous work, which had been the best existing method so far. We propose new methods to predict heterodimers, using a machine learning-based approach. We train a support vector machine (SVM) to discriminate interacting vs non-interacting protein pairs, based on informations extracted from PPI, domain, phylogenetic profiles and subcellular localization. We evaluate in detail new kernel functions to encode these data, and report prediction performance that outperforms the state-of-the-art.

Density Estimation with Mercer Kernels

NASA Technical Reports Server (NTRS)

Macready, William G.

2003-01-01

We present a new method for density estimation based on Mercer kernels. The density estimate can be understood as the density induced on a data manifold by a mixture of Gaussians fit in a feature space. As is usual, the feature space and data manifold are defined with any suitable positive-definite kernel function. We modify the standard EM algorithm for mixtures of Gaussians to infer the parameters of the density. One benefit of the approach is it's conceptual simplicity, and uniform applicability over many different types of data. Preliminary results are presented for a number of simple problems.

Immobilized phosphorylase for synthesis of polysaccharides from glucose

NASA Technical Reports Server (NTRS)

Marshall, D. L.

1972-01-01

Continuous processes for enzymatic production of carbohydrates from glucose are discussed. Key reactant in process is identified as phosphorylase which catalyzes reversible formation or degradation of polysaccharide. Chemical compounds and reactions to synthesize polysaccharides are analyzed.

Polysaccharide-based micro/nanocarriers for oral colon-targeted drug delivery.

PubMed

Zhang, Lin; Sang, Yuan; Feng, Jing; Li, Zhaoming; Zhao, Aili

2016-08-01

Oral colon-targeted drug delivery has attracted many researchers because of its distinct advantages of increasing the bioavailability of the drug at the target site and reducing the side effects. Polysaccharides that are precisely activated by the physiological environment of the colon hold greater promise for colon targeting. Considerable research efforts have been directed towards developing polysaccharide-based micro/nanocarriers. Types of polysaccharides for colon targeting and in vitro/in vivo assessments of polysaccharide-based carriers for oral colon-targeted drug delivery are summarised. Polysaccharide-based microspheres have gained increased importance not just for the delivery of the drugs for the treatment of local diseases associated with the colon (colon cancer, inflammatory bowel disease (IBD), amoebiasis and irritable bowel syndrome (IBS)), but also for it's potential for the delivery of anti-rheumatoid arthritis and anti-chronic stable angina drugs. Besides, Polysaccharide-based micro/nanocarriers such as microbeads, microcapsules, microparticles, nanoparticles, nanogels and nanospheres are also introduced in this review.

Multiple fingerprinting analyses in quality control of Cassiae Semen polysaccharides.

PubMed

Cheng, Jing; He, Siyu; Wan, Qiang; Jing, Pu

2018-03-01

Quality control issue overshadows potential health benefits of Cassiae Semen due to the analytic limitations. In this study, multiple-fingerprint analysis integrated with several chemometrics was performed to assess the polysaccharide quality of Cassiae Semen harvested from different locations. FT-IR, HPLC, and GC fingerprints of polysaccharide extracts from the authentic source were established as standard profiles, applying to assess the quality of foreign sources. Analyses of FT-IR fingerprints of polysaccharide extracts using either Pearson correlation analysis or principal component analysis (PCA), or HPLC fingerprints of partially hydrolyzed polysaccharides with PCA, distinguished the foreign sources from the authentic source. However, HPLC or GC fingerprints of completely hydrolyzed polysaccharides couldn't identify all foreign sources and the methodology using GC is quite limited in determining the monosaccharide composition. This indicates that FT-IR/HPLC fingerprints of non/partially-hydrolyzed polysaccharides, respectively, accompanied by multiple chemometrics methods, might be potentially applied in detecting and differentiating sources of Cassiae Semen. Copyright © 2018 Elsevier B.V. All rights reserved.

Characterization and antioxidant activities of polysaccharides from thirteen boletus mushrooms.

PubMed

Zhang, Lan; Hu, Yu; Duan, Xiaoyu; Tang, Tingting; Shen, Yingbin; Hu, Bin; Liu, Aiping; Chen, Hong; Li, Cheng; Liu, Yuntao

2018-07-01

Water-soluble polysaccharides were extracted from the caps and stipes of thirteen boletus mushrooms representing five different species collected in Southwest China. Investigations of their structures and antioxidant activities allowed an evaluation of structure-function relationships. The polysaccharides were composed mainly of the monosaccharides arabinose, xylose, mannose, glucose and galactose. Most samples displayed a broad molecular weight range, with significant differences observed between the molecular weight ranges of the polysaccharides from the caps and the stipes. FT-IR spectral analysis of the polysaccharides revealed that most of polysaccharides from boletus mushrooms (except Boletus edulis) contained a pyranose ring. The antioxidant activities of the polysaccharides in stipes showed a significant correlation with their monosaccharide composition, and were also related to their molecular weight and anomeric configuration. Suillellus luridus collected in Pingwu, Mianyang, Sichuan, China had remarkably superior antioxidant activity and might be developed as a natural antioxidant. Copyright © 2018 Elsevier B.V. All rights reserved.

Correlation Between Chain Architecture and Hydration Water Structure in Polysaccharides

NASA Astrophysics Data System (ADS)

Grossutti, Michael; Dutcher, John

The physical properties of confined water can differ dramatically from those of bulk water. Hydration water associated with polysaccharides provides a particularly important example of confined water, with differences in polysaccharide structure providing different spatially confined environments for water adsorption. We have used attenuated total reflection infrared (ATR-IR) spectroscopy to investigate the structure of hydration water in films of three different polysaccharides under controlled relative humidity (RH) conditions. We compare the results obtained for films of highly branched, monodisperse phytoglycogen nanoparticles to those obtained for two unbranched polysaccharides, hyaluronic acid (HA) and chitosan. We find similarities between water structuring in the two linear polysaccharides, and significant differences for phytoglycogen. In particular, the phytoglycogen nanoparticles exhibited high network water connectivity, and a large increase in the fraction of multimer water clusters with increasing RH, whereas the water structure for HA and chitosan was found to be insensitive to changes in RH. These measurements provide unique insight into the relationship between the chain architecture and hydration of polysaccharides.

Studies on water soluble polysaccharides from Pithecellobium dulce (Roxb.) Benth. seeds.

PubMed

Bagchi, S; Kumar, K Jayaram

2016-03-15

In this existing experimental work, water soluble PDP polysaccharides were secluded from Pithecellobium dulce (Roxb.) Benth. seeds. The physicochemical properties were analyzed in terms of swelling power, solubility, pH and water holding capacity. Micromeretic studies proved the polysaccharide may be used a potential pharmaceutical adjuvant. The polysaccharide was characterized by FT-IR, SEM, TGA and NMR techniques. Methylation analysis confirmed that the polysaccharide is composed of Arabinose (Araf) units. The chemical shifts of anomeric proton region were found in the region of 4.4-5.5ppm. Thermogravimetric analysis showed that PDP polysaccharide was thermally stable. The in vitro antioxidant capacities of the polysaccharide were investigated in terms of scavenging of hydroxyl radicals, 2, 2-diphenyl-1-picrylhydrazyl (DPPH) radicals, hydrogen peroxide (H2O2) and reducing power assay. The polysaccharide fractions showed activity in a concentration dependent manner which was comparable to the standard, ascorbic acid. Copyright © 2015 Elsevier Ltd. All rights reserved.

Broken rice kernels and the kinetics of rice hydration and texture during cooking.

PubMed

Saleh, Mohammed; Meullenet, Jean-Francois

2013-05-01

During rice milling and processing, broken kernels are inevitably present, although to date it has been unclear as to how the presence of broken kernels affects rice hydration and cooked rice texture. Therefore, this work intended to study the effect of broken kernels in a rice sample on rice hydration and texture during cooking. Two medium-grain and two long-grain rice cultivars were harvested, dried and milled, and the broken kernels were separated from unbroken kernels. Broken rice kernels were subsequently combined with unbroken rice kernels forming treatments of 0, 40, 150, 350 or 1000 g kg(-1) broken kernels ratio. Rice samples were then cooked and the moisture content of the cooked rice, the moisture uptake rate, and rice hardness and stickiness were measured. As the amount of broken rice kernels increased, rice sample texture became increasingly softer (P < 0.05) but the unbroken kernels became significantly harder. Moisture content and moisture uptake rate were positively correlated, and cooked rice hardness was negatively correlated to the percentage of broken kernels in rice samples. Differences in the proportions of broken rice in a milled rice sample play a major role in determining the texture properties of cooked rice. Variations in the moisture migration kinetics between broken and unbroken kernels caused faster hydration of the cores of broken rice kernels, with greater starch leach-out during cooking affecting the texture of the cooked rice. The texture of cooked rice can be controlled, to some extent, by varying the proportion of broken kernels in milled rice. © 2012 Society of Chemical Industry.

A new discrete dipole kernel for quantitative susceptibility mapping.

PubMed

Milovic, Carlos; Acosta-Cabronero, Julio; Pinto, José Miguel; Mattern, Hendrik; Andia, Marcelo; Uribe, Sergio; Tejos, Cristian

2018-09-01

Most approaches for quantitative susceptibility mapping (QSM) are based on a forward model approximation that employs a continuous Fourier transform operator to solve a differential equation system. Such formulation, however, is prone to high-frequency aliasing. The aim of this study was to reduce such errors using an alternative dipole kernel formulation based on the discrete Fourier transform and discrete operators. The impact of such an approach on forward model calculation and susceptibility inversion was evaluated in contrast to the continuous formulation both with synthetic phantoms and in vivo MRI data. The discrete kernel demonstrated systematically better fits to analytic field solutions, and showed less over-oscillations and aliasing artifacts while preserving low- and medium-frequency responses relative to those obtained with the continuous kernel. In the context of QSM estimation, the use of the proposed discrete kernel resulted in error reduction and increased sharpness. This proof-of-concept study demonstrated that discretizing the dipole kernel is advantageous for QSM. The impact on small or narrow structures such as the venous vasculature might by particularly relevant to high-resolution QSM applications with ultra-high field MRI - a topic for future investigations. The proposed dipole kernel has a straightforward implementation to existing QSM routines. Copyright © 2018 Elsevier Inc. All rights reserved.

Genetic Analysis of Kernel Traits in Maize-Teosinte Introgression Populations.

PubMed

Liu, Zhengbin; Garcia, Arturo; McMullen, Michael D; Flint-Garcia, Sherry A

2016-08-09

Seed traits have been targeted by human selection during the domestication of crop species as a way to increase the caloric and nutritional content of food during the transition from hunter-gather to early farming societies. The primary seed trait under selection was likely seed size/weight as it is most directly related to overall grain yield. Additional seed traits involved in seed shape may have also contributed to larger grain. Maize (Zea mays ssp. mays) kernel weight has increased more than 10-fold in the 9000 years since domestication from its wild ancestor, teosinte (Z. mays ssp. parviglumis). In order to study how size and shape affect kernel weight, we analyzed kernel morphometric traits in a set of 10 maize-teosinte introgression populations using digital imaging software. We identified quantitative trait loci (QTL) for kernel area and length with moderate allelic effects that colocalize with kernel weight QTL. Several genomic regions with strong effects during maize domestication were detected, and a genetic framework for kernel traits was characterized by complex pleiotropic interactions. Our results both confirm prior reports of kernel domestication loci and identify previously uncharacterized QTL with a range of allelic effects, enabling future research into the genetic basis of these traits. Copyright © 2016 Liu et al.

Genetic Analysis of Kernel Traits in Maize-Teosinte Introgression Populations

PubMed Central

Liu, Zhengbin; Garcia, Arturo; McMullen, Michael D.; Flint-Garcia, Sherry A.

2016-01-01

Seed traits have been targeted by human selection during the domestication of crop species as a way to increase the caloric and nutritional content of food during the transition from hunter-gather to early farming societies. The primary seed trait under selection was likely seed size/weight as it is most directly related to overall grain yield. Additional seed traits involved in seed shape may have also contributed to larger grain. Maize (Zea mays ssp. mays) kernel weight has increased more than 10-fold in the 9000 years since domestication from its wild ancestor, teosinte (Z. mays ssp. parviglumis). In order to study how size and shape affect kernel weight, we analyzed kernel morphometric traits in a set of 10 maize-teosinte introgression populations using digital imaging software. We identified quantitative trait loci (QTL) for kernel area and length with moderate allelic effects that colocalize with kernel weight QTL. Several genomic regions with strong effects during maize domestication were detected, and a genetic framework for kernel traits was characterized by complex pleiotropic interactions. Our results both confirm prior reports of kernel domestication loci and identify previously uncharacterized QTL with a range of allelic effects, enabling future research into the genetic basis of these traits. PMID:27317774

[Gravity resistance, another graviresponse in plants--function of anti-gravitational polysaccharides].

PubMed

Hoson, Takayuki; Wakabayashi, Kazuyuki; Soga, Kouichi

2003-08-01

The involvement of anti-gravitational polysaccharides in gravity resistance, one of two major gravity responses in plants, was discussed. In dicotyledons, xyloglucans are the only cell wall polysaccharides, whose level, molecular size, and metabolic turnover were modified under both hypergravity and microgravity conditions, suggesting that xyloglucans act as anti-gravitational polysaccharides. In monocotyledonous Poaceae, (1-->3),(1-->4)-beta glucans, instead of xyloglucans, were shown to play a role as anti-gravitational polysaccharides. These polysaccharides are also involved in plant responses to other environmental factors, such as light and temperature, and to some phytohormones, such as auxin and ethylene. Thus, the type of anti-gravitational polysaccharides is different between dicotyledons and Poaceae, but such polysaccharides are universally involved in plant responses to environmental and hormonal signals. In gravity resistance, the gravity signal may be received by the plasma membrane mechanoreceptors, transformed and transduced within each cell, and then may modify the processes of synthesis and secretion of the anti-gravitational polysaccharides and the cell wall enzymes responsible for their degradation, as well as the apoplastic pH, leading to the cell wall reinforcement. A series of events inducing gravity resistance are quite independent of those leading to gravitropism.

Polysaccharides Isolated from Açaí Fruit Induce Innate Immune Responses

PubMed Central

Holderness, Jeff; Schepetkin, Igor A.; Freedman, Brett; Kirpotina, Liliya N.; Quinn, Mark T.; Hedges, Jodi F.; Jutila, Mark A.

2011-01-01

The Açaí (Acai) fruit is a popular nutritional supplement that purportedly enhances immune system function. These anecdotal claims are supported by limited studies describing immune responses to the Acai polyphenol fraction. Previously, we characterized γδ T cell responses to both polyphenol and polysaccharide fractions from several plant-derived nutritional supplements. Similar polyphenol and polysaccharide fractions are found in Acai fruit. Thus, we hypothesized that one or both of these fractions could activate γδ T cells. Contrary to previous reports, we did not identify agonist activity in the polyphenol fraction; however, the Acai polysaccharide fraction induced robust γδ T cell stimulatory activity in human, mouse, and bovine PBMC cultures. To characterize the immune response to Acai polysaccharides, we fractionated the crude polysaccharide preparation and tested these fractions for activity in human PBMC cultures. The largest Acai polysaccharides were the most active in vitro as indicated by activation of myeloid and γδ T cells. When delivered in vivo, Acai polysaccharide induced myeloid cell recruitment and IL-12 production. These results define innate immune responses induced by the polysaccharide component of Acai and have implications for the treatment of asthma and infectious disease. PMID:21386979

Synthesis and characterization of PEPO grafted carboxymethyl guar and carboxymethyl tamarind as new thermo-associating polymers.

PubMed

Gupta, Nivika R; Torris A T, Arun; Wadgaonkar, Prakash P; Rajamohanan, P R; Ducouret, Guylaine; Hourdet, Dominique; Creton, Costantino; Badiger, Manohar V

2015-03-06

New thermo associating polymers were designed and synthesized by grafting amino terminated poly(ethylene oxide-co-propylene oxide) (PEPO) onto carboxymethyl guar (CMG) and carboxymethyl tamarind (CMT). The grafting was performed by coupling reaction between NH2 groups of PEPO and COOH groups of CMG and CMT using water-soluble EDC/NHS as coupling agents. The grafting efficiency and the temperature of thermo-association, T(assoc) in the copolymer were studied by NMR spectroscopy. The graft copolymers, CMG-g-PEPO and CMT-g-PEPO exhibited interesting thermo-associating behavior which was evidenced by the detailed rheological and fluorescence measurements. The visco-elastic properties (storage modulus, G'; loss modulus, G") of the copolymer solutions were investigated using oscillatory shear experiments. The influence of salt and surfactant on the T(assoc) was also studied by rheology, where the phenomenon of "Salting out" and "Salting in" was observed for salt and surfactant, respectively, which can give an easy access to tunable properties of these copolymers. These thermo-associating polymers with biodegradable nature of CMG and CMT can have potential applications as smart injectables in controlled release technology and as thickeners in cosmetics and pharmaceutical formulations. Copyright © 2014 Elsevier Ltd. All rights reserved.

Investigation of various energy deposition kernel refinements for the convolution/superposition method

PubMed Central

Huang, Jessie Y.; Eklund, David; Childress, Nathan L.; Howell, Rebecca M.; Mirkovic, Dragan; Followill, David S.; Kry, Stephen F.

2013-01-01

Purpose: Several simplifications used in clinical implementations of the convolution/superposition (C/S) method, specifically, density scaling of water kernels for heterogeneous media and use of a single polyenergetic kernel, lead to dose calculation inaccuracies. Although these weaknesses of the C/S method are known, it is not well known which of these simplifications has the largest effect on dose calculation accuracy in clinical situations. The purpose of this study was to generate and characterize high-resolution, polyenergetic, and material-specific energy deposition kernels (EDKs), as well as to investigate the dosimetric impact of implementing spatially variant polyenergetic and material-specific kernels in a collapsed cone C/S algorithm. Methods: High-resolution, monoenergetic water EDKs and various material-specific EDKs were simulated using the EGSnrc Monte Carlo code. Polyenergetic kernels, reflecting the primary spectrum of a clinical 6 MV photon beam at different locations in a water phantom, were calculated for different depths, field sizes, and off-axis distances. To investigate the dosimetric impact of implementing spatially variant polyenergetic kernels, depth dose curves in water were calculated using two different implementations of the collapsed cone C/S method. The first method uses a single polyenergetic kernel, while the second method fully takes into account spectral changes in the convolution calculation. To investigate the dosimetric impact of implementing material-specific kernels, depth dose curves were calculated for a simplified titanium implant geometry using both a traditional C/S implementation that performs density scaling of water kernels and a novel implementation using material-specific kernels. Results: For our high-resolution kernels, we found good agreement with the Mackie et al. kernels, with some differences near the interaction site for low photon energies (<500 keV). For our spatially variant polyenergetic kernels, we

Mapping the polysaccharide degradation potential of Aspergillus niger

PubMed Central

2012-01-01

Background The degradation of plant materials by enzymes is an industry of increasing importance. For sustainable production of second generation biofuels and other products of industrial biotechnology, efficient degradation of non-edible plant polysaccharides such as hemicellulose is required. For each type of hemicellulose, a complex mixture of enzymes is required for complete conversion to fermentable monosaccharides. In plant-biomass degrading fungi, these enzymes are regulated and released by complex regulatory structures. In this study, we present a methodology for evaluating the potential of a given fungus for polysaccharide degradation. Results Through the compilation of information from 203 articles, we have systematized knowledge on the structure and degradation of 16 major types of plant polysaccharides to form a graphical overview. As a case example, we have combined this with a list of 188 genes coding for carbohydrate-active enzymes from Aspergillus niger, thus forming an analysis framework, which can be queried. Combination of this information network with gene expression analysis on mono- and polysaccharide substrates has allowed elucidation of concerted gene expression from this organism. One such example is the identification of a full set of extracellular polysaccharide-acting genes for the degradation of oat spelt xylan. Conclusions The mapping of plant polysaccharide structures along with the corresponding enzymatic activities is a powerful framework for expression analysis of carbohydrate-active enzymes. Applying this network-based approach, we provide the first genome-scale characterization of all genes coding for carbohydrate-active enzymes identified in A. niger. PMID:22799883

Mapping the polysaccharide degradation potential of Aspergillus niger.

PubMed

Andersen, Mikael R; Giese, Malene; de Vries, Ronald P; Nielsen, Jens

2012-07-16

The degradation of plant materials by enzymes is an industry of increasing importance. For sustainable production of second generation biofuels and other products of industrial biotechnology, efficient degradation of non-edible plant polysaccharides such as hemicellulose is required. For each type of hemicellulose, a complex mixture of enzymes is required for complete conversion to fermentable monosaccharides. In plant-biomass degrading fungi, these enzymes are regulated and released by complex regulatory structures. In this study, we present a methodology for evaluating the potential of a given fungus for polysaccharide degradation. Through the compilation of information from 203 articles, we have systematized knowledge on the structure and degradation of 16 major types of plant polysaccharides to form a graphical overview. As a case example, we have combined this with a list of 188 genes coding for carbohydrate-active enzymes from Aspergillus niger, thus forming an analysis framework, which can be queried. Combination of this information network with gene expression analysis on mono- and polysaccharide substrates has allowed elucidation of concerted gene expression from this organism. One such example is the identification of a full set of extracellular polysaccharide-acting genes for the degradation of oat spelt xylan. The mapping of plant polysaccharide structures along with the corresponding enzymatic activities is a powerful framework for expression analysis of carbohydrate-active enzymes. Applying this network-based approach, we provide the first genome-scale characterization of all genes coding for carbohydrate-active enzymes identified in A. niger.

Effects of sample size on KERNEL home range estimates

USGS Publications Warehouse

Seaman, D.E.; Millspaugh, J.J.; Kernohan, Brian J.; Brundige, Gary C.; Raedeke, Kenneth J.; Gitzen, Robert A.

1999-01-01

Kernel methods for estimating home range are being used increasingly in wildlife research, but the effect of sample size on their accuracy is not known. We used computer simulations of 10-200 points/home range and compared accuracy of home range estimates produced by fixed and adaptive kernels with the reference (REF) and least-squares cross-validation (LSCV) methods for determining the amount of smoothing. Simulated home ranges varied from simple to complex shapes created by mixing bivariate normal distributions. We used the size of the 95% home range area and the relative mean squared error of the surface fit to assess the accuracy of the kernel home range estimates. For both measures, the bias and variance approached an asymptote at about 50 observations/home range. The fixed kernel with smoothing selected by LSCV provided the least-biased estimates of the 95% home range area. All kernel methods produced similar surface fit for most simulations, but the fixed kernel with LSCV had the lowest frequency and magnitude of very poor estimates. We reviewed 101 papers published in The Journal of Wildlife Management (JWM) between 1980 and 1997 that estimated animal home ranges. A minority of these papers used nonparametric utilization distribution (UD) estimators, and most did not adequately report sample sizes. We recommend that home range studies using kernel estimates use LSCV to determine the amount of smoothing, obtain a minimum of 30 observations per animal (but preferably a?Y50), and report sample sizes in published results.

Local coding based matching kernel method for image classification.

PubMed

Song, Yan; McLoughlin, Ian Vince; Dai, Li-Rong

2014-01-01

This paper mainly focuses on how to effectively and efficiently measure visual similarity for local feature based representation. Among existing methods, metrics based on Bag of Visual Word (BoV) techniques are efficient and conceptually simple, at the expense of effectiveness. By contrast, kernel based metrics are more effective, but at the cost of greater computational complexity and increased storage requirements. We show that a unified visual matching framework can be developed to encompass both BoV and kernel based metrics, in which local kernel plays an important role between feature pairs or between features and their reconstruction. Generally, local kernels are defined using Euclidean distance or its derivatives, based either explicitly or implicitly on an assumption of Gaussian noise. However, local features such as SIFT and HoG often follow a heavy-tailed distribution which tends to undermine the motivation behind Euclidean metrics. Motivated by recent advances in feature coding techniques, a novel efficient local coding based matching kernel (LCMK) method is proposed. This exploits the manifold structures in Hilbert space derived from local kernels. The proposed method combines advantages of both BoV and kernel based metrics, and achieves a linear computational complexity. This enables efficient and scalable visual matching to be performed on large scale image sets. To evaluate the effectiveness of the proposed LCMK method, we conduct extensive experiments with widely used benchmark datasets, including 15-Scenes, Caltech101/256, PASCAL VOC 2007 and 2011 datasets. Experimental results confirm the effectiveness of the relatively efficient LCMK method.

Extraction process of palm kernel cake as a source of mannan for feed additive on poultry diet

NASA Astrophysics Data System (ADS)

Tafsin, M.; Hanafi, N. D.; Yusraini, E.

2017-05-01

Palm Kernel Cake (PKC) is a by-product of palm kernel oil extraction and found in large quantity in Indonesia. The inclusion of PKC on poultry diet are limited due to some nutritional problems such as anti-nutritional properties (mannan). On the other hand, mannan containing polysaccharides play in various biological functions particularly in enhancing the immune response and to control pathogen in poultry. The research objective to find out the extraction process of PKC and conducted at animal nutrition and Feed Science Laboratory, Agricultural Faculty, University of Sumatera Utara. Various extraction methode were used in this experiment, including fraction analysis used 7 number sieves, and followed by water and acetic acid extraction. The result indicated that PKC had different particle size according to sieve size and dominated by particle size 850 um. The analysis of sugar content indicated that each particle size had different characteristic on treatment by hot water extraction. The particle size 180—850 um had higher sugar content than coarse PKC (2000—3000 um). The total sugar content were recovered vary between 0.9—3,2% from PKC were extracted. Treatment grinding method followed by hot water extraction (100—120 °C, 1 h) increased total sugar content than previous treatments and reach 8% from PKC were extracted. Utilisation acetic acid decreased the total amount of total sugar from PKC were extracted. It is concluded that treatment by hot temperature (110—120 °C) for 1 h show highest yield to extract sugar from PKC.

Hot-compressed water extraction of polysaccharides from soy hulls.

PubMed

Liu, Hua-Min; Wang, Fei-Yun; Liu, Yu-Lan

2016-07-01

The polysaccharides of soy hulls were extracted by hot-compressed water at temperatures of 110 from 180°C and various treatment times (10-150min) in a batch system. It was determined that a moderate temperature and short time are suitable for the preparation of polysaccharides. The structure of xylan and the inter- and intra-chain hydrogen bonding of cellulose fibrils in the soy hulls were not significantly broken down. The polysaccharides obtained were primarily composed of α-L-arabinofuranosyl units, 4-O-methyl-glucuronic acid units and α-D-galactose units attached with substituted units. A sugar analysis indicated that arabinose was the major component, constituting 35.6-46.9% of the polysaccharide products extracted at 130°C, 140°C, and 150°C. This investigation contributes to the knowledge of the polysaccharides of soy by-products, which can reduce the environmental impact of waste from the food industries. Copyright © 2016 Elsevier Ltd. All rights reserved.

Bacillus subtilis biofilm induction by plant polysaccharides.

PubMed

Beauregard, Pascale B; Chai, Yunrong; Vlamakis, Hera; Losick, Richard; Kolter, Roberto

2013-04-23

Bacillus subtilis is a plant-beneficial Gram-positive bacterium widely used as a biofertilizer. However, relatively little is known regarding the molecular processes underlying this bacterium's ability to colonize roots. In contrast, much is known about how this bacterium forms matrix-enclosed multicellular communities (biofilms) in vitro. Here, we show that, when B. subtilis colonizes Arabidopsis thaliana roots it forms biofilms that depend on the same matrix genes required in vitro. B. subtilis biofilm formation was triggered by certain plant polysaccharides. These polysaccharides served as a signal for biofilm formation transduced via the kinases controlling the phosphorylation state of the master regulator Spo0A. In addition, plant polysaccharides are used as a source of sugars for the synthesis of the matrix exopolysaccharide. The bacterium's response to plant polysaccharides was observed across several different strains of the species, some of which are known to have beneficial effects on plants. These observations provide evidence that biofilm genes are crucial for Arabidopsis root colonization by B. subtilis and provide insights into how matrix synthesis may be triggered by this plant.

Hyperspectral Image Classification via Kernel Sparse Representation

DTIC Science & Technology

2013-01-01

classification algorithms. Moreover, the spatial coherency across neighboring pixels is also incorporated through a kernelized joint sparsity model , where...joint sparsity model , where all of the pixels within a small neighborhood are jointly represented in the feature space by selecting a few common training...hyperspectral imagery, joint spar- sity model , kernel methods, sparse representation. I. INTRODUCTION HYPERSPECTRAL imaging sensors capture images

Effects of Amygdaline from Apricot Kernel on Transplanted Tumors in Mice.

PubMed

Yamshanov, V A; Kovan'ko, E G; Pustovalov, Yu I

2016-03-01

The effects of amygdaline from apricot kernel added to fodder on the growth of transplanted LYO-1 and Ehrlich carcinoma were studied in mice. Apricot kernels inhibited the growth of both tumors. Apricot kernels, raw and after thermal processing, given 2 days before transplantation produced a pronounced antitumor effect. Heat-processed apricot kernels given in 3 days after transplantation modified the tumor growth and prolonged animal lifespan. Thermal treatment did not considerably reduce the antitumor effect of apricot kernels. It was hypothesized that the antitumor effect of amygdaline on Ehrlich carcinoma and LYO-1 lymphosarcoma was associated with the presence of bacterial genome in the tumor.

Extraction, purification and antioxidant activities of the polysaccharides from maca (Lepidium meyenii).

PubMed

Zha, Shenghua; Zhao, Qingsheng; Chen, Jinjin; Wang, Liwei; Zhang, Guifeng; Zhang, Hong; Zhao, Bing

2014-10-13

Water-soluble polysaccharides were separated from maca (Lepidium meyenii) aqueous extract (MAE). The crude polysaccharides were deproteinized by Sevag method. During the preparation process of maca polysaccharides, amylase and glucoamylase effectively removed starch in maca polysaccharides. Four Lepidium meyenii polysaccharides (LMPs) were obtained by changing the concentration of ethanol in the process of polysaccharide precipitation. All of the LMPs were composed of rhamnose, arabinose, glucose and galactose. Antioxidant activity tests revealed that LMP-60 showed good capability of scavenging hydroxyl free radical and superoxide radical at 2.0mg/mL, the scavenging rate was 52.9% and 85.8%, respectively. Therefore, the results showed that maca polysaccharides had a high antioxidant activity and could be explored as the source of bioactive compounds. Copyright © 2014 Elsevier Ltd. All rights reserved.

Detection of Inulin, a Prebiotic Polysaccharide, in Maple Syrup.

PubMed

Sun, Jiadong; Ma, Hang; Seeram, Navindra P; Rowley, David C

2016-09-28

Maple syrup is a widely consumed plant-derived natural sweetener produced by concentrating xylem sap collected from certain maple (Acer) species. During thermal evaporation of water, natural phytochemical components are concentrated in maple syrup. The polymeric components from maple syrup were isolated by ethanol precipitation, dialysis, and anion exchange chromatography and structurally characterized by glycosyl composition analysis, glycosyl linkage analysis, and nuclear magnetic resonance spectroscopy. Among the maple syrup polysaccharides, one neutral polysaccharide was characterized as inulin with a broad molecular weight distribution, representing the first isolation of this prebiotic carbohydrate from a xylem sap. In addition, two acidic polysaccharides with structural similarity were identified as arabinogalactans derived from rhamnogalacturonan type I pectic polysaccharides.

Using the Intel Math Kernel Library on Peregrine | High-Performance

Science.gov Websites

Computing | NREL the Intel Math Kernel Library on Peregrine Using the Intel Math Kernel Library on Peregrine Learn how to use the Intel Math Kernel Library (MKL) with Peregrine system software. MKL architectures. Core math functions in MKL include BLAS, LAPACK, ScaLAPACK, sparse solvers, fast Fourier

Semi-supervised learning for ordinal Kernel Discriminant Analysis.

PubMed

Pérez-Ortiz, M; Gutiérrez, P A; Carbonero-Ruz, M; Hervás-Martínez, C

2016-12-01

Ordinal classification considers those classification problems where the labels of the variable to predict follow a given order. Naturally, labelled data is scarce or difficult to obtain in this type of problems because, in many cases, ordinal labels are given by a user or expert (e.g. in recommendation systems). Firstly, this paper develops a new strategy for ordinal classification where both labelled and unlabelled data are used in the model construction step (a scheme which is referred to as semi-supervised learning). More specifically, the ordinal version of kernel discriminant learning is extended for this setting considering the neighbourhood information of unlabelled data, which is proposed to be computed in the feature space induced by the kernel function. Secondly, a new method for semi-supervised kernel learning is devised in the context of ordinal classification, which is combined with our developed classification strategy to optimise the kernel parameters. The experiments conducted compare 6 different approaches for semi-supervised learning in the context of ordinal classification in a battery of 30 datasets, showing (1) the good synergy of the ordinal version of discriminant analysis and the use of unlabelled data and (2) the advantage of computing distances in the feature space induced by the kernel function. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Antiviral Activities and Mechanisms of Marine Polysaccharides: An Overview

PubMed Central

Wang, Wei; Wang, Shi-Xin; Guan, Hua-Shi

2012-01-01

Recently, the studies on the antiviral activities of marine natural products, especially marine polysaccharides, are attracting more and more attention all over the world. Marine-derived polysaccharides and their lower molecular weight oligosaccharide derivatives have been shown to possess a variety of antiviral activities. This paper will review the recent progress in research on the antiviral activities and the mechanisms of these polysaccharides obtained from marine organisms. In particular, it will provide an update on the antiviral actions of the sulfated polysaccharides derived from marine algae including carrageenans, alginates, and fucans, relating to their structure features and the structure–activity relationships. In addition, the recent findings on the different mechanisms of antiviral actions of marine polysaccharides and their potential for therapeutic application will also be summarized in detail. PMID:23235364

High speed sorting of Fusarium-damaged wheat kernels

USDA-ARS?s Scientific Manuscript database

Recent studies have found that resistance to Fusarium fungal infection can be inherited in wheat from one generation to another. However, there is not yet available a cost effective method to separate Fusarium-damaged wheat kernels from undamaged kernels so that wheat breeders can take advantage of...

CW-SSIM kernel based random forest for image classification

NASA Astrophysics Data System (ADS)

Fan, Guangzhe; Wang, Zhou; Wang, Jiheng

2010-07-01

Complex wavelet structural similarity (CW-SSIM) index has been proposed as a powerful image similarity metric that is robust to translation, scaling and rotation of images, but how to employ it in image classification applications has not been deeply investigated. In this paper, we incorporate CW-SSIM as a kernel function into a random forest learning algorithm. This leads to a novel image classification approach that does not require a feature extraction or dimension reduction stage at the front end. We use hand-written digit recognition as an example to demonstrate our algorithm. We compare the performance of the proposed approach with random forest learning based on other kernels, including the widely adopted Gaussian and the inner product kernels. Empirical evidences show that the proposed method is superior in its classification power. We also compared our proposed approach with the direct random forest method without kernel and the popular kernel-learning method support vector machine. Our test results based on both simulated and realworld data suggest that the proposed approach works superior to traditional methods without the feature selection procedure.

Insights from Classifying Visual Concepts with Multiple Kernel Learning

PubMed Central

Binder, Alexander; Nakajima, Shinichi; Kloft, Marius; Müller, Christina; Samek, Wojciech; Brefeld, Ulf; Müller, Klaus-Robert; Kawanabe, Motoaki

2012-01-01

Combining information from various image features has become a standard technique in concept recognition tasks. However, the optimal way of fusing the resulting kernel functions is usually unknown in practical applications. Multiple kernel learning (MKL) techniques allow to determine an optimal linear combination of such similarity matrices. Classical approaches to MKL promote sparse mixtures. Unfortunately, 1-norm regularized MKL variants are often observed to be outperformed by an unweighted sum kernel. The main contributions of this paper are the following: we apply a recently developed non-sparse MKL variant to state-of-the-art concept recognition tasks from the application domain of computer vision. We provide insights on benefits and limits of non-sparse MKL and compare it against its direct competitors, the sum-kernel SVM and sparse MKL. We report empirical results for the PASCAL VOC 2009 Classification and ImageCLEF2010 Photo Annotation challenge data sets. Data sets (kernel matrices) as well as further information are available at http://doc.ml.tu-berlin.de/image_mkl/(Accessed 2012 Jun 25). PMID:22936970

Polysaccharide production by lactic acid bacteria: from genes to industrial applications.

PubMed

Zeidan, Ahmad A; Poulsen, Vera Kuzina; Janzen, Thomas; Buldo, Patrizia; Derkx, Patrick M F; Øregaard, Gunnar; Neves, Ana Rute

2017-08-01

The ability to produce polysaccharides with diverse biological functions is widespread in bacteria. In lactic acid bacteria (LAB), production of polysaccharides has long been associated with the technological, functional and health-promoting benefits of these microorganisms. In particular, the capsular polysaccharides and exopolysaccharides have been implicated in modulation of the rheological properties of fermented products. For this reason, screening and selection of exocellular polysaccharide-producing LAB has been extensively carried out by academia and industry. To further exploit the ability of LAB to produce polysaccharides, an in-depth understanding of their biochemistry, genetics, biosynthetic pathways, regulation and structure-function relationships is mandatory. Here, we provide a critical overview of the latest advances in the field of glycosciences in LAB. Surprisingly, the understanding of the molecular processes involved in polysaccharide synthesis is lagging behind, and has not accompanied the increasing commercial value and application potential of these polymers. Seizing the natural diversity of polysaccharides for exciting new applications will require a concerted effort encompassing in-depth physiological characterization of LAB at the systems level. Combining high-throughput experimentation with computational approaches, biochemical and structural characterization of the polysaccharides and understanding of the structure-function-application relationships is essential to achieve this ambitious goal. © FEMS 2017.

Nonparametric entropy estimation using kernel densities.

PubMed

Lake, Douglas E

2009-01-01

The entropy of experimental data from the biological and medical sciences provides additional information over summary statistics. Calculating entropy involves estimates of probability density functions, which can be effectively accomplished using kernel density methods. Kernel density estimation has been widely studied and a univariate implementation is readily available in MATLAB. The traditional definition of Shannon entropy is part of a larger family of statistics, called Renyi entropy, which are useful in applications that require a measure of the Gaussianity of data. Of particular note is the quadratic entropy which is related to the Friedman-Tukey (FT) index, a widely used measure in the statistical community. One application where quadratic entropy is very useful is the detection of abnormal cardiac rhythms, such as atrial fibrillation (AF). Asymptotic and exact small-sample results for optimal bandwidth and kernel selection to estimate the FT index are presented and lead to improved methods for entropy estimation.

Sulfated Polysaccharides in Marine Sponges: Extraction Methods and Anti-HIV Activity

PubMed Central

Esteves, Ana I. S.; Nicolai, Marisa; Humanes, Madalena; Goncalves, Joao

2011-01-01

The extraction, fractionation and HIV-1 inhibition potential of polysaccharides extracted from three species of marine sponges, Erylus discophorus, Cliona celata and Stelletta sp., collected in the Northeastern Atlantic, is presented in this work. The anti-HIV activity of 23 polysaccharide pellets and three crude extracts was tested. Crude extracts prepared from Erylus discophorus specimens were all highly active against HIV-1 (90 to 95% inhibition). Cliona celata pellets showed low polysaccharide content (bellow 38.5%) and almost no anti-HIV activity (<10% inhibition). Stelletta sp. pellets, although quite rich in polysaccharide (up to 97.3%), showed only modest bioactivity (<36% HIV-1 inhibition). Erylus discophorus pellets were among the richest in terms of polysaccharide content (up to 98%) and the most active against HIV-1 (up to 95% inhibition). Chromatographic fractionation of the polysaccharide pellet obtained from a specimen of Erylus discophorus (B161) yielded only modestly active fractions. However, we could infer that the active molecule is most probably a high molecular weight sulfated polysaccharide (>2000 kDa), whose mechanism is possibly preventing viral attachment and entry (fusion inhibitor). PMID:21339952

Chemical Functionalization of Polysaccharides-Towards Biocompatible Hydrogels for Biomedical Applications.

PubMed

Kirschning, Andreas; Dibbert, Nick; Dräger, Gerald

2018-01-26

Hydrogels have emerged as a highly interdisciplinary topic as they play a significant role for a vast number of applications. They have been studied extensively as materials for contact lenses, wound dressing and as filler material in soft-tissue augmentation, in which classical polymer backbones such as hydroxyethylmethacrylate (HEMA) are typically employed. More recently, polysaccharides have received attention, particularly in the fields of regenerative medicine and tissue engineering, as ideal candidate materials for artificial extracellular matrices (ECM). The polysaccharides of choice are dextran, alginate, chitosan, hyaluronic acid and pullulan and in order to obtain suitable hydrogels from these polysaccharides, controlled chemical functionalization is of critical importance. This short review summarizes recent developments in the chemical derivatization of polysaccharides to pave the way for crosslinking and to decorate individual polysaccharide chains with bioactive ligands. The report covers convergent and divergent protocols for crosslinking, as well strategies for bisfunctionalization of polysaccharides. Additionally, information on biological properties and biomedical applications are covered. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Correlation Between Chain Architecture and Hydration Water Structure in Polysaccharides.

PubMed

Grossutti, Michael; Dutcher, John R

2016-03-14

The physical properties of confined water can differ dramatically from those of bulk water. Hydration water associated with polysaccharides provides a particularly interesting example of confined water, because differences in polysaccharide structure provide different spatially confined environments for water sorption. We have used attenuated total reflection infrared (ATR-IR) spectroscopy to investigate the structure of hydration water in films of three different polysaccharides under controlled relative humidity (RH) conditions. We compare the results obtained for films of highly branched, dendrimer-like phytoglycogen nanoparticles to those obtained for two unbranched polysaccharides, hyaluronic acid (HA), and chitosan. We find similarities between the water structuring in the two linear polysaccharides and significant differences for phytoglycogen. In particular, the results suggest that the high degree of branching in phytoglycogen leads to a much more well-ordered water structure (low density, high connectivity network water), indicating the strong influence of chain architecture on the structuring of water. These measurements provide unique insight into the relationship between the structure and hydration of polysaccharides, which is important for understanding and exploiting these sustainable nanomaterials in a wide range of applications.

Proteomic analysis of scallop hepatopancreatic extract provides insights into marine polysaccharide digestion.

PubMed

Lyu, Qianqian; Jiao, Wenqian; Zhang, Keke; Bao, Zhenmin; Wang, Shi; Liu, Weizhi

2016-12-16

Marine polysaccharides are used in a variety of applications, and the enzymes that degrade these polysaccharides are of increasing interest. The main food source of herbivorous marine mollusks is seaweed, and several polysaccharide-degrading enzymes have been extracted from mollusk digestive glands (hepatopancreases). Here, we used a comprehensive proteomic approach to examine the hepatopancreatic proteins of the Zhikong scallop (Chlamys farreri). We identified 435 proteins, the majority of which were lysosomal enzymes and carbohydrate and protein metabolism enzymes. However, several new enzymes related to polysaccharide metabolism were also identified. Phylogenetic and structural analyses of these enzymes suggest that these polysaccharide-degrading enzymes may have a variety of potential substrate specificities. Taken together, our study characterizes several novel polysaccharide-degrading enzymes in the scallop hepatopancreas and provides an enhanced view of these enzymes and a greater understanding of marine polysaccharide digestion.

Polysaccharides purified from wild Cordyceps activate FGF2/FGFR1c signaling

NASA Astrophysics Data System (ADS)

Zeng, Yangyang; Han, Zhangrun; Yu, Guangli; Hao, Jiejie; Zhang, Lijuan

2015-02-01

Land animals as well as all organisms in ocean synthesize sulfated polysaccharides. Fungi split from animals about 1.5 billion years ago. As fungi make the evolutionary journey from ocean to land, the biggest changes in their living environment may be a sharp decrease in salt concentration. It is established that sulfated polysaccharides interact with hundreds of signaling molecules and facilitate many signaling transduction pathways, including fibroblast growth factor (FGF) and FGF receptor signaling pathway. The disappearance of sulfated polysaccharides in fungi and plants on land might indicate that polysaccharides without sulfation might be sufficient in facilitating protein ligand/receptor interactions in low salinity land. Recently, it was reported that plants on land start to synthesize sulfated polysaccharides in high salt environment, suggesting that fungi might be able to do the same when exposed in such environment. Interestingly, Cordyceps, a fungus habituating inside caterpillar body, is the most valued traditional Chinese Medicine. One of the important pharmaceutical active ingredients in Cordyceps is polysaccharides. Therefore, we hypothesize that the salty environment inside caterpillar body might allow the fungi to synthesize sulfated polysaccharides. To test the hypothesis, we isolated polysaccharides from both lava and sporophore of wild Cordyceps and also from Cordyceps militaris cultured without or with added salts. We then measured the polysaccharide activity using a FGF2/FGFR1c signaling-dependent BaF3 cell proliferation assay and found that polysaccharides isolated from wild Cordyceps activated FGF2/FGFR signaling, indicating that the polysaccharides synthesized by wild Cordyceps are indeed different from those by the cultured mycelium.

New Fukui, dual and hyper-dual kernels as bond reactivity descriptors.

PubMed

Franco-Pérez, Marco; Polanco-Ramírez, Carlos-A; Ayers, Paul W; Gázquez, José L; Vela, Alberto

2017-06-21

We define three new linear response indices with promising applications for bond reactivity using the mathematical framework of τ-CRT (finite temperature chemical reactivity theory). The τ-Fukui kernel is defined as the ratio between the fluctuations of the average electron density at two different points in the space and the fluctuations in the average electron number and is designed to integrate to the finite-temperature definition of the electronic Fukui function. When this kernel is condensed, it can be interpreted as a site-reactivity descriptor of the boundary region between two atoms. The τ-dual kernel corresponds to the first order response of the Fukui kernel and is designed to integrate to the finite temperature definition of the dual descriptor; it indicates the ambiphilic reactivity of a specific bond and enriches the traditional dual descriptor by allowing one to distinguish between the electron-accepting and electron-donating processes. Finally, the τ-hyper dual kernel is defined as the second-order derivative of the Fukui kernel and is proposed as a measure of the strength of ambiphilic bonding interactions. Although these quantities have never been proposed, our results for the τ-Fukui kernel and for τ-dual kernel can be derived in zero-temperature formulation of the chemical reactivity theory with, among other things, the widely-used parabolic interpolation model.

Navicula sp. Sulfated Polysaccharide Gels Induced by Fe(III): Rheology and Microstructure

PubMed Central

Fimbres-Olivarría, Diana; López-Elías, José Antonio; Carvajal-Millán, Elizabeth; Márquez-Escalante, Jorge Alberto; Martínez-Córdova, Luis Rafael; Miranda-Baeza, Anselmo; Enríquez-Ocaña, Fernando; Valdéz-Holguín, José Eduardo; Brown-Bojórquez, Francisco

2016-01-01

A sulfated polysaccharide extracted from Navicula sp. presented a yield of 4.4 (% w/w dry biomass basis). Analysis of the polysaccharide using gas chromatography showed that this polysaccharide contained glucose (29%), galactose (21%), rhamnose (10%), xylose (5%) and mannose (4%). This polysaccharide presented an average molecular weight of 107 kDa. Scanning electron microscopy (SEM) micrographs showed that the lyophilized Navicula sp. polysaccharide is an amorphous solid with particles of irregular shapes and sharp angles. The polysaccharide at 1% (w/v) solution in water formed gels in the presence of 0.4% (w/v) FeCl3, showing elastic and viscous moduli of 1 and 0.7 Pa, respectively. SEM analysis performed on the lyophilized gel showed a compact pore structure, with a pore size of approximately 150 nm. Very few studies on the gelation of sulfated polysaccharides using trivalent ions exist in the literature, and, to the best of our knowledge, this study is the first to describe the gelation of sulfated polysaccharides extracted from Navicula sp. PMID:27483255

Navicula sp. Sulfated Polysaccharide Gels Induced by Fe(III): Rheology and Microstructure.

PubMed

Fimbres-Olivarría, Diana; López-Elías, José Antonio; Carvajal-Millán, Elizabeth; Márquez-Escalante, Jorge Alberto; Martínez-Córdova, Luis Rafael; Miranda-Baeza, Anselmo; Enríquez-Ocaña, Fernando; Valdéz-Holguín, José Eduardo; Brown-Bojórquez, Francisco

2016-07-30

A sulfated polysaccharide extracted from Navicula sp. presented a yield of 4.4 (% w/w dry biomass basis). Analysis of the polysaccharide using gas chromatography showed that this polysaccharide contained glucose (29%), galactose (21%), rhamnose (10%), xylose (5%) and mannose (4%). This polysaccharide presented an average molecular weight of 107 kDa. Scanning electron microscopy (SEM) micrographs showed that the lyophilized Navicula sp. polysaccharide is an amorphous solid with particles of irregular shapes and sharp angles. The polysaccharide at 1% (w/v) solution in water formed gels in the presence of 0.4% (w/v) FeCl₃, showing elastic and viscous moduli of 1 and 0.7 Pa, respectively. SEM analysis performed on the lyophilized gel showed a compact pore structure, with a pore size of approximately 150 nm. Very few studies on the gelation of sulfated polysaccharides using trivalent ions exist in the literature, and, to the best of our knowledge, this study is the first to describe the gelation of sulfated polysaccharides extracted from Navicula sp.

Antiviral activity of polysaccharide extract from Laminaria japonica against respiratory syncytial virus.

PubMed

Cao, Yin-Guang; Hao, Yu; Li, Zhi-Hui; Liu, Shun-Tao; Wang, Le-Xin

2016-12-01

This study was designed to investigate the inhibition activity of polysaccharide extract from Laminaria japonica against RSV. The polysaccharide from Laminaria japonica was isolated by ethanol precipitation. HEK293 cells were infected with RVS, and the antiviral activity of polysaccharide extract against RSV in host cells was tested. By using ELISA and western blot assay, the expression level of IFN-α and IRF3 and their functional roles in polysaccharide-mediated antiviral activity against RSV were investigated. The polysaccharide extract from Laminaria japonica had low toxicity to HEK293 cell. The TC50 to HEK293 cells was up to 1.76mg/mL. Furthermore, the EC50 of polysaccharide extract to RSV was 5.27μg/mL, and TI was 334. The polysaccharide extract improved IRF-3 expression which promoted the level of IFN-α. Polysaccharide extract from Laminaria japonica elicits antiviral activity against RSV by up-regulation of IRF3 signaling-mediated IFN-α production. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Quasi-Dual-Packed-Kerneled Au49 (2,4-DMBT)27 Nanoclusters and the Influence of Kernel Packing on the Electrochemical Gap.

PubMed

Liao, Lingwen; Zhuang, Shengli; Wang, Pu; Xu, Yanan; Yan, Nan; Dong, Hongwei; Wang, Chengming; Zhao, Yan; Xia, Nan; Li, Jin; Deng, Haiteng; Pei, Yong; Tian, Shi-Kai; Wu, Zhikun

2017-10-02

Although face-centered cubic (fcc), body-centered cubic (bcc), hexagonal close-packed (hcp), and other structured gold nanoclusters have been reported, it was unclear whether gold nanoclusters with mix-packed (fcc and non-fcc) kernels exist, and the correlation between kernel packing and the properties of gold nanoclusters is unknown. A Au 49 (2,4-DMBT) 27 nanocluster with a shell electron count of 22 has now been been synthesized and structurally resolved by single-crystal X-ray crystallography, which revealed that Au 49 (2,4-DMBT) 27 contains a unique Au 34 kernel consisting of one quasi-fcc-structured Au 21 and one non-fcc-structured Au 13 unit (where 2,4-DMBTH=2,4-dimethylbenzenethiol). Further experiments revealed that the kernel packing greatly influences the electrochemical gap (EG) and the fcc structure has a larger EG than the investigated non-fcc structure. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Maca polysaccharides: A review of compositions, isolation, therapeutics and prospects.

PubMed

Li, Yujuan; Xu, Fangxue; Zheng, Mengmeng; Xi, Xiaozhi; Cui, Xiaowei; Han, Chunchao

2018-05-01

Maca polysaccharides, some of the major bioactive substances in Lepidium meyenii (Walp.) (Maca), have various biological properties, including anti-oxidant, anti-fatigue, anti-tumor, and immunomodulatory effects, as well as hepatoprotective activity and regulation function. Although many therapeutics depend on multiple structures of maca polysaccharides in addition to providing sufficient foundations for maca polysaccharide products in industrial applications, the relationships between the pharmacological effects and structures have not been established. Therefore, this article summarizes the extraction and purification methods, compositions, pharmacological effects, prospects and industrial applications of maca polysaccharides. Copyright © 2018 Elsevier B.V. All rights reserved.

Fast generation of sparse random kernel graphs

DOE PAGES

Hagberg, Aric; Lemons, Nathan; Du, Wen -Bo

2015-09-10

The development of kernel-based inhomogeneous random graphs has provided models that are flexible enough to capture many observed characteristics of real networks, and that are also mathematically tractable. We specify a class of inhomogeneous random graph models, called random kernel graphs, that produces sparse graphs with tunable graph properties, and we develop an efficient generation algorithm to sample random instances from this model. As real-world networks are usually large, it is essential that the run-time of generation algorithms scales better than quadratically in the number of vertices n. We show that for many practical kernels our algorithm runs in timemore » at most ο(n(logn)²). As an example, we show how to generate samples of power-law degree distribution graphs with tunable assortativity.« less

Wavelet SVM in Reproducing Kernel Hilbert Space for hyperspectral remote sensing image classification

NASA Astrophysics Data System (ADS)

Du, Peijun; Tan, Kun; Xing, Xiaoshi

2010-12-01

Combining Support Vector Machine (SVM) with wavelet analysis, we constructed wavelet SVM (WSVM) classifier based on wavelet kernel functions in Reproducing Kernel Hilbert Space (RKHS). In conventional kernel theory, SVM is faced with the bottleneck of kernel parameter selection which further results in time-consuming and low classification accuracy. The wavelet kernel in RKHS is a kind of multidimensional wavelet function that can approximate arbitrary nonlinear functions. Implications on semiparametric estimation are proposed in this paper. Airborne Operational Modular Imaging Spectrometer II (OMIS II) hyperspectral remote sensing image with 64 bands and Reflective Optics System Imaging Spectrometer (ROSIS) data with 115 bands were used to experiment the performance and accuracy of the proposed WSVM classifier. The experimental results indicate that the WSVM classifier can obtain the highest accuracy when using the Coiflet Kernel function in wavelet transform. In contrast with some traditional classifiers, including Spectral Angle Mapping (SAM) and Minimum Distance Classification (MDC), and SVM classifier using Radial Basis Function kernel, the proposed wavelet SVM classifier using the wavelet kernel function in Reproducing Kernel Hilbert Space is capable of improving classification accuracy obviously.

Distributed smoothed tree kernel for protein-protein interaction extraction from the biomedical literature

PubMed Central

Murugesan, Gurusamy; Abdulkadhar, Sabenabanu; Natarajan, Jeyakumar

2017-01-01

Automatic extraction of protein-protein interaction (PPI) pairs from biomedical literature is a widely examined task in biological information extraction. Currently, many kernel based approaches such as linear kernel, tree kernel, graph kernel and combination of multiple kernels has achieved promising results in PPI task. However, most of these kernel methods fail to capture the semantic relation information between two entities. In this paper, we present a special type of tree kernel for PPI extraction which exploits both syntactic (structural) and semantic vectors information known as Distributed Smoothed Tree kernel (DSTK). DSTK comprises of distributed trees with syntactic information along with distributional semantic vectors representing semantic information of the sentences or phrases. To generate robust machine learning model composition of feature based kernel and DSTK were combined using ensemble support vector machine (SVM). Five different corpora (AIMed, BioInfer, HPRD50, IEPA, and LLL) were used for evaluating the performance of our system. Experimental results show that our system achieves better f-score with five different corpora compared to other state-of-the-art systems. PMID:29099838

Distributed smoothed tree kernel for protein-protein interaction extraction from the biomedical literature.

PubMed

Murugesan, Gurusamy; Abdulkadhar, Sabenabanu; Natarajan, Jeyakumar

2017-01-01

Automatic extraction of protein-protein interaction (PPI) pairs from biomedical literature is a widely examined task in biological information extraction. Currently, many kernel based approaches such as linear kernel, tree kernel, graph kernel and combination of multiple kernels has achieved promising results in PPI task. However, most of these kernel methods fail to capture the semantic relation information between two entities. In this paper, we present a special type of tree kernel for PPI extraction which exploits both syntactic (structural) and semantic vectors information known as Distributed Smoothed Tree kernel (DSTK). DSTK comprises of distributed trees with syntactic information along with distributional semantic vectors representing semantic information of the sentences or phrases. To generate robust machine learning model composition of feature based kernel and DSTK were combined using ensemble support vector machine (SVM). Five different corpora (AIMed, BioInfer, HPRD50, IEPA, and LLL) were used for evaluating the performance of our system. Experimental results show that our system achieves better f-score with five different corpora compared to other state-of-the-art systems.

Genome-wide Association Analysis of Kernel Weight in Hard Winter Wheat

USDA-ARS?s Scientific Manuscript database

Wheat kernel weight is an important and heritable component of wheat grain yield and a key predictor of flour extraction. Genome-wide association analysis was conducted to identify genomic regions associated with kernel weight and kernel weight environmental response in 8 trials of 299 hard winter ...

Evidence-Based Kernels: Fundamental Units of Behavioral Influence

ERIC Educational Resources Information Center

Embry, Dennis D.; Biglan, Anthony

2008-01-01

This paper describes evidence-based kernels, fundamental units of behavioral influence that appear to underlie effective prevention and treatment for children, adults, and families. A kernel is a behavior-influence procedure shown through experimental analysis to affect a specific behavior and that is indivisible in the sense that removing any of…

Extraction, characterization and antioxidant activities of Se-enriched tea polysaccharides.

PubMed

Wang, Yuanfeng; Li, Yongfu; Liu, Yangyang; Chen, Xueqing; Wei, Xinlin

2015-01-01

Se-polysaccharides from Se-enriched tea leaves were purified by DEAE-sepharose fast flow gel column (2.5×60cm) and three polysaccharide fractions (Se-TPS1, Se-TPS2, and Se-TPS3) were isolated and purified with yields of 6.5, 37.14, and 8.57%, respectively. The average sizes of Se-TPS1 and Se-TPS2 were determined by HPGPC system, with molecular weights of 1.1×10(5) and 2.4×10(5)Da, respectively. Se-TPS3 was a polysaccharide polymer with two peaks with molecular weights of 9.2×10(5) and 2.5×10(5)Da. Monosaccharide components analysis by ion chromatography revealed Se-polysaccharides were acidic polysaccharoses and different from each other in monosaccharide kinds and molar ratio. Elements of Se, C, H, N, S, and 14 kinds of mineral elements were analyzed by AFS, EA, and ICP-AES, respectively. Spectral analysis (IR and UV) indicated Se-polysaccharides were typical glycoproteins. Morphological analyses of the samples were determined by SEM and AFM. In addition, the DPPH and superoxide radicals scavenging activities were also discussed to assess antioxidant activities of the samples, and Se-polysaccharides showed higher antioxidant activities compared to the ordinary polysaccharides. Copyright © 2015 Elsevier B.V. All rights reserved.

Molecular weight determination and correlation analysis of Dalbergia sissoo polysaccharide with constituent oligosaccharides.

PubMed

Kumar, Vineet; Rana, Vikas; Soni, P L

2013-01-01

Mucilaginous polysaccharide extracted from Dalbergia sissoo Roxb. leaves has a number of medicinal applications. Molecular weight studies and correlation analysis of the structure of polysaccharide with oligosaccharides can be helpful for further utilisation, modification and structure-activity relationship for biological applications. To determine molecular weight of medicinally important polysaccharide. To establish an unequivocal correlation of the polysaccharide monosugars with constituting oligosaccharides and glucuronic acid content based on gas-liquid chromatography (GLC) with the spectrophotometric method. Complete and partial hydrolytic studies of pure polysaccharide yielded constituting monosugars and oligosaccharides. The ratio of sugars in polysaccharide and oligosaccharides was studied by preparation of alditol acetates and analysed using GLC. The uronic acid content was studied by GLC analysis and spectrophotometry. Molecular weight of the polysaccharide was determined using the viscometric method. Dalbergia sissoo leaves yielded 14.0% pure polysaccharide, containing 15.7% of glucuronic acid. Complete hydrolysis and GLC analysis of alditol acetate derivatives of reduced and unreduced monosugars indicated the presence of L-rhamnose, D-glucuronic acid, D-galactose and D-glucose in 1.00:1.00:2.00:2.33 molar ratios. Partial hydrolysis followed by monosugar analysis of oligosaccharides established the monosugar ratio in complete agreement with polysaccharide, thereby corroborating the sugar ratio. Similar uronic acid content was obtained by GLC and spectrophotometry. The polysaccharide had an average molecular weight of 1.5 × 10⁵  Da. The study has established an obvious correlation of the structure of polysaccharide with oligosaccharides, leading to unambiguous identification of monosaccharides, which normally is not studied conclusively while reporting the polysaccharide structure. The molecular weight of the polysaccharide was determined

Value of allohaemagglutinins in the diagnosis of a polysaccharide antibody deficiency

PubMed Central

Schaballie, H; Vermeulen, F; Verbinnen, B; Frans, G; Vermeulen, E; Proesmans, M; De Vreese, K; Emonds, MP; De Boeck, K; Moens, L; Picard, C; Bossuyt, X; Meyts, I

2015-01-01

Polysaccharide antibody deficiency is characterized by a poor or absent antibody response after vaccination with an unconjugated pneumococcal polysaccharide vaccine. Allohaemagglutinins (AHA) are antibodies to A or B polysaccharide antigens on the red blood cells, and are often used as an additional or alternative measure to assess the polysaccharide antibody response. However, few studies have been conducted to establish the clinical significance of AHA. To investigate the value of AHA to diagnose a polysaccharide antibody deficiency, pneumococcal polysaccharide antibody titres and AHA were studied retrospectively in 180 subjects in whom both tests had been performed. Receiver operating characteristic curves for AHA versus the pneumococcal vaccine response as a marker for the anti-polysaccharide immune response revealed an area under the curve between 0·5 and 0·573. Sensitivity and specificity of AHA to detect a polysaccharide antibody deficiency, as diagnosed by vaccination response, were low (calculated for cut-off 1/4–1/32). In subjects with only low pneumococcal antibody response, the prevalence of bronchiectasis was significantly higher than in subjects with only low AHA (45·5 and 1·3%, respectively) or normal pneumococcal antibody response and AHA (2·4%). A logistic regression model showed that low pneumococcal antibody response but not AHA was associated with bronchiectasis (odds ratio 46·2). The results of this study do not support the routine use of AHA to assess the polysaccharide antibody response in patients with suspected immunodeficiency, but more studies are warranted to clarify the subject further. PMID:25516411

Noise kernels of stochastic gravity in conformally-flat spacetimes

NASA Astrophysics Data System (ADS)

Cho, H. T.; Hu, B. L.

2015-03-01

The central object in the theory of semiclassical stochastic gravity is the noise kernel, which is the symmetric two point correlation function of the stress-energy tensor. Using the corresponding Wightman functions in Minkowski, Einstein and open Einstein spaces, we construct the noise kernels of a conformally coupled scalar field in these spacetimes. From them we show that the noise kernels in conformally-flat spacetimes, including the Friedmann-Robertson-Walker universes, can be obtained in closed analytic forms by using a combination of conformal and coordinate transformations.

Travel-time sensitivity kernels in long-range propagation.

PubMed

Skarsoulis, E K; Cornuelle, B D; Dzieciuch, M A

2009-11-01

Wave-theoretic travel-time sensitivity kernels (TSKs) are calculated in two-dimensional (2D) and three-dimensional (3D) environments and their behavior with increasing propagation range is studied and compared to that of ray-theoretic TSKs and corresponding Fresnel-volumes. The differences between the 2D and 3D TSKs average out when horizontal or cross-range marginals are considered, which indicates that they are not important in the case of range-independent sound-speed perturbations or perturbations of large scale compared to the lateral TSK extent. With increasing range, the wave-theoretic TSKs expand in the horizontal cross-range direction, their cross-range extent being comparable to that of the corresponding free-space Fresnel zone, whereas they remain bounded in the vertical. Vertical travel-time sensitivity kernels (VTSKs)-one-dimensional kernels describing the effect of horizontally uniform sound-speed changes on travel-times-are calculated analytically using a perturbation approach, and also numerically, as horizontal marginals of the corresponding TSKs. Good agreement between analytical and numerical VTSKs, as well as between 2D and 3D VTSKs, is found. As an alternative method to obtain wave-theoretic sensitivity kernels, the parabolic approximation is used; the resulting TSKs and VTSKs are in good agreement with normal-mode results. With increasing range, the wave-theoretic VTSKs approach the corresponding ray-theoretic sensitivity kernels.

Extraction, purification, characterization and antioxidant activities of polysaccharides from Cistanche tubulosa.

PubMed

Zhang, Wiejie; Huang, Jing; Wang, Wei; Li, Qian; Chen, Yao; Feng, Weiwei; Zheng, Daheng; Zhao, Ting; Mao, Guanghua; Yang, Liuqing; Wu, Xiangyang

2016-12-01

An efficient ultrasonic-cellulase-assisted extraction (UCE) of Cistanche tubulosa polysaccharide (CTP) was established. The response surface methodology based on Box-Behnken Design was employed to further optimize extraction conditions. After quaternary ammonium salt precipitation, the polysaccharide of C. tubulosa was characterized by different techniques. The results showed that a maximum polysaccharide yield of 22.31±0.45% was achieved at a pH of 5.2 for 31.5min at 54.1°C. Compared to hot water extraction, the yield of CTP in UCE and polysaccharide content increased to 44.96% and 70.13±2.19%, respectively. There was no marked difference among polysaccharides extracted using different methods from the infrared spectrum. Ultrasonic-cellulase-assisted extraction polysaccharide showed a fibrous structure from scanning electron microscopy and was composed of rhamnose, mannose, glucose, and galactose in a molar ratio of 2.18:1:28.29:1.43 by gas chromatography. The circular dichroism results indicated that polysaccharides had a maximum positive peak around 210nm with different peak values. The thermogravimetric analysis and differential scanning calorimetry were used to test the thermostability of CTP. Besides, CTP demonstrated appreciable antioxidant potential on antioxidant experiments in vitro. The results suggested that UCE is an effective method for CTP extraction and its polysaccharide showed appreciable antioxidant activity. Copyright © 2016 Elsevier B.V. All rights reserved.

Galactosaminogalactan, a New Immunosuppressive Polysaccharide of Aspergillus fumigatus

PubMed Central

Simenel, Catherine; Coddeville, Bernadette; van Vliet, Sandra J.; van Kooyk, Yvette; Bozza, Silvia; Moretti, Silvia; Schwarz, Flavio; Trichot, Coline; Aebi, Markus; Delepierre, Muriel; Elbim, Carole; Romani, Luigina; Latgé, Jean-Paul

2011-01-01

A new polysaccharide secreted by the human opportunistic fungal pathogen Aspergillus fumigatus has been characterized. Carbohydrate analysis using specific chemical degradations, mass spectrometry, 1H and 13C nuclear magnetic resonance showed that this polysaccharide is a linear heterogeneous galactosaminogalactan composed of α1-4 linked galactose and α1-4 linked N-acetylgalactosamine residues where both monosacharides are randomly distributed and where the percentage of galactose per chain varied from 15 to 60%. This polysaccharide is antigenic and is recognized by a majority of the human population irrespectively of the occurrence of an Aspergillus infection. GalNAc oligosaccharides are an essential epitope of the galactosaminogalactan that explains the universal antibody reaction due to cross reactivity with other antigenic molecules containing GalNAc stretches such as the N-glycans of Campylobacter jejuni. The galactosaminogalactan has no protective effect during Aspergillus infections. Most importantly, the polysaccharide promotes fungal development in immunocompetent mice due to its immunosuppressive activity associated with disminished neutrophil infiltrates. PMID:22102815

Scutellaria polysaccharide inhibits the infectivity of Newcastle disease virus to chicken embryo fibroblast.

PubMed

Xiaona, Zhao; Jianzhu, Liu

2014-03-15

To select the antiviral active site of Scutellaria polysaccharide (SPS), safe concentrations of crude total Scutellaria polysaccharide (SPS(t)) and fractional polysaccharide SPS₅₀, SPS₆₀, SPS₇₀ and SPS₈₀ on chicken embryo fibroblast (CEF) were first compared using the MTT method. Then, SPS(t), SPS₅₀, SPS₆₀, SPS₇₀, and SPS₈₀ at five concentrations within the safe concentration, together with Newcastle disease virus (NDV), were added to the cultivating system of CEF in three models: pre-addition of polysaccharide, post-addition of polysaccharide, and simultaneous addition of polysaccharides and NDV after mixing. The effects of SPS on the cellular infectivity of NDV (A₅₇₀ value and the highest viral inhibitory rate) were compared using the MTT method. At appropriate concentrations, the five polysaccharides could significantly inhibit the infectivity of NDV on CEF. Among the five polysaccharide groups, the SPS₈₀ group exhibited the highest viral inhibitory rate in the three sample-addition modes. This finding indicates that SPS₈₀ possesses the best efficacy as a component of antiviral polysaccharide drug. © 2013 Society of Chemical Industry.

Validation of Born Traveltime Kernels

NASA Astrophysics Data System (ADS)

Baig, A. M.; Dahlen, F. A.; Hung, S.

2001-12-01

Most inversions for Earth structure using seismic traveltimes rely on linear ray theory to translate observed traveltime anomalies into seismic velocity anomalies distributed throughout the mantle. However, ray theory is not an appropriate tool to use when velocity anomalies have scale lengths less than the width of the Fresnel zone. In the presence of these structures, we need to turn to a scattering theory in order to adequately describe all of the features observed in the waveform. By coupling the Born approximation to ray theory, the first order dependence of heterogeneity on the cross-correlated traveltimes (described by the Fréchet derivative or, more colourfully, the banana-doughnut kernel) may be determined. To determine for what range of parameters these banana-doughnut kernels outperform linear ray theory, we generate several random media specified by their statistical properties, namely the RMS slowness perturbation and the scale length of the heterogeneity. Acoustic waves are numerically generated from a point source using a 3-D pseudo-spectral wave propagation code. These waves are then recorded at a variety of propagation distances from the source introducing a third parameter to the problem: the number of wavelengths traversed by the wave. When all of the heterogeneity has scale lengths larger than the width of the Fresnel zone, ray theory does as good a job at predicting the cross-correlated traveltime as the banana-doughnut kernels do. Below this limit, wavefront healing becomes a significant effect and ray theory ceases to be effective even though the kernels remain relatively accurate provided the heterogeneity is weak. The study of wave propagation in random media is of a more general interest and we will also show our measurements of the velocity shift and the variance of traveltime compare to various theoretical predictions in a given regime.

End-use quality of soft kernel durum wheat

USDA-ARS?s Scientific Manuscript database

Kernel texture is a major determinant of end-use quality of wheat. Durum wheat is known for its very hard texture, which influences how it is milled and for what products it is well suited. We developed soft kernel durum wheat lines via Ph1b-mediated homoeologous recombination with Dr. Leonard Joppa...

Kernelized Elastic Net Regularization: Generalization Bounds, and Sparse Recovery.

PubMed

Feng, Yunlong; Lv, Shao-Gao; Hang, Hanyuan; Suykens, Johan A K

2016-03-01

Kernelized elastic net regularization (KENReg) is a kernelization of the well-known elastic net regularization (Zou & Hastie, 2005). The kernel in KENReg is not required to be a Mercer kernel since it learns from a kernelized dictionary in the coefficient space. Feng, Yang, Zhao, Lv, and Suykens (2014) showed that KENReg has some nice properties including stability, sparseness, and generalization. In this letter, we continue our study on KENReg by conducting a refined learning theory analysis. This letter makes the following three main contributions. First, we present refined error analysis on the generalization performance of KENReg. The main difficulty of analyzing the generalization error of KENReg lies in characterizing the population version of its empirical target function. We overcome this by introducing a weighted Banach space associated with the elastic net regularization. We are then able to conduct elaborated learning theory analysis and obtain fast convergence rates under proper complexity and regularity assumptions. Second, we study the sparse recovery problem in KENReg with fixed design and show that the kernelization may improve the sparse recovery ability compared to the classical elastic net regularization. Finally, we discuss the interplay among different properties of KENReg that include sparseness, stability, and generalization. We show that the stability of KENReg leads to generalization, and its sparseness confidence can be derived from generalization. Moreover, KENReg is stable and can be simultaneously sparse, which makes it attractive theoretically and practically.

[Analysis of thickening polysaccharides by the improved diethyldithioacetal derivatization method].

PubMed

Akiyama, Takumi; Yamazaki, Takeshi; Tanamoto, Kenichi

2011-01-01

The identification test for thickening polysaccharides containing neutral saccharides and uronic acids was investigated by GC analysis of constituent monosaccharides. The reported method, in which monosaccharides were converted to diethyldithioacetal derivatives with ethanethiol followed by trimethylsilylation, was improved in terms of operability and reproducibility of GC/MS analysis. The suitability of the improved diethyldithioacetal derivatization method was determined for seven thickening polysaccharides, i.e., carob bean gum, guar gum, karaya gum, gum arabic, gum ghatti, tragacanth gum and peach gum. The samples were acid-hydrolyzed to form monosaccharides. The hydrolysates were derivatized and analyzed with GC/FID. Each sugar derivative was detected as a single peak and was well separated from others on the chromatograms. The amounts of constituent monosaccharides in thickening polysaccharides were successfully estimated. Seven polysaccharides were distinguished from each other on the basis of constituent monosaccharides. Further examination of the time period of hydrolysis of polysaccharides using peach gum showed that the optimal times were not the same for all monosaccharides. A longer time was needed to hydrolyze glucuronic acid than neutral saccharides. The findings suggest that hydrolysis time may sometimes affect the analytical results on composition of constituent monosaccharides in polysaccharides.

Prioritizing individual genetic variants after kernel machine testing using variable selection.

PubMed

He, Qianchuan; Cai, Tianxi; Liu, Yang; Zhao, Ni; Harmon, Quaker E; Almli, Lynn M; Binder, Elisabeth B; Engel, Stephanie M; Ressler, Kerry J; Conneely, Karen N; Lin, Xihong; Wu, Michael C

2016-12-01

Kernel machine learning methods, such as the SNP-set kernel association test (SKAT), have been widely used to test associations between traits and genetic polymorphisms. In contrast to traditional single-SNP analysis methods, these methods are designed to examine the joint effect of a set of related SNPs (such as a group of SNPs within a gene or a pathway) and are able to identify sets of SNPs that are associated with the trait of interest. However, as with many multi-SNP testing approaches, kernel machine testing can draw conclusion only at the SNP-set level, and does not directly inform on which one(s) of the identified SNP set is actually driving the associations. A recently proposed procedure, KerNel Iterative Feature Extraction (KNIFE), provides a general framework for incorporating variable selection into kernel machine methods. In this article, we focus on quantitative traits and relatively common SNPs, and adapt the KNIFE procedure to genetic association studies and propose an approach to identify driver SNPs after the application of SKAT to gene set analysis. Our approach accommodates several kernels that are widely used in SNP analysis, such as the linear kernel and the Identity by State (IBS) kernel. The proposed approach provides practically useful utilities to prioritize SNPs, and fills the gap between SNP set analysis and biological functional studies. Both simulation studies and real data application are used to demonstrate the proposed approach. © 2016 WILEY PERIODICALS, INC.

Recent Advances in Marine Algae Polysaccharides: Isolation, Structure, and Activities.

PubMed

Xu, Shu-Ying; Huang, Xuesong; Cheong, Kit-Leong

2017-12-13

Marine algae have attracted a great deal of interest as excellent sources of nutrients. Polysaccharides are the main components in marine algae, hence a great deal of attention has been directed at isolation and characterization of marine algae polysaccharides because of their numerous health benefits. In this review, extraction and purification approaches and chemico-physical properties of marine algae polysaccharides (MAPs) are summarized. The biological activities, which include immunomodulatory, antitumor, antiviral, antioxidant, and hypolipidemic, are also discussed. Additionally, structure-function relationships are analyzed and summarized. MAPs' biological activities are closely correlated with their monosaccharide composition, molecular weights, linkage types, and chain conformation. In order to promote further exploitation and utilization of polysaccharides from marine algae for functional food and pharmaceutical areas, high efficiency, and low-cost polysaccharide extraction and purification methods, quality control, structure-function activity relationships, and specific mechanisms of MAPs activation need to be extensively investigated.

THE ANTIBODY-FORMATION BY POLYSACCHARIDS

PubMed Central

Nishimura, Shoji

1929-01-01

1. By complement fixation tests, it has been clearly demonstrated that the sera of rabbits immunized with inulin, soluble starch and dextrine contain specific antibodies. 2. All these immune sera gave a negative precipitation reaction. 3. The kind of dextrine which has a construction very near to starch has an antigenic property, but those in a state of further decomposition do not give rise to antibodies. 4. All the three kinds of polysaccharids have power to produce antibodies without any vehicle. Dextrine is the only one of the three that gives rise to immune bodies more readily when pig serum is added to it. 5. Regarded as antigens, inulin stood first and soluble starch and dextrine next in order. 6. All three kinds of polysaccharids that were employed gave a negative protein color reaction. All of them, however, contained nitrogen. It has been proved that the large portion of the nitrogen contained in the soluble starch is derived from its protein contents. 7. It is suggested that in the production of immune bodies by these three kinds of polysaccharids, proteins might play the part of the vehicle. This is, however, still to be determined. PMID:19869634

THE ANTIBODY-FORMATION BY POLYSACCHARIDS.

PubMed

Nishimura, S

1929-09-30

1. By complement fixation tests, it has been clearly demonstrated that the sera of rabbits immunized with inulin, soluble starch and dextrine contain specific antibodies. 2. All these immune sera gave a negative precipitation reaction. 3. The kind of dextrine which has a construction very near to starch has an antigenic property, but those in a state of further decomposition do not give rise to antibodies. 4. All the three kinds of polysaccharids have power to produce antibodies without any vehicle. Dextrine is the only one of the three that gives rise to immune bodies more readily when pig serum is added to it. 5. Regarded as antigens, inulin stood first and soluble starch and dextrine next in order. 6. All three kinds of polysaccharids that were employed gave a negative protein color reaction. All of them, however, contained nitrogen. It has been proved that the large portion of the nitrogen contained in the soluble starch is derived from its protein contents. 7. It is suggested that in the production of immune bodies by these three kinds of polysaccharids, proteins might play the part of the vehicle. This is, however, still to be determined.

Structural Characterization of Mannan Cell Wall Polysaccharides in Plants Using PACE.

PubMed

Pidatala, Venkataramana R; Mahboubi, Amir; Mortimer, Jenny C

2017-10-16

Plant cell wall polysaccharides are notoriously difficult to analyze, and most methods require expensive equipment, skilled operators, and large amounts of purified material. Here, we describe a simple method for gaining detailed polysaccharide structural information, including resolution of structural isomers. For polysaccharide analysis by gel electrophoresis (PACE), plant cell wall material is hydrolyzed with glycosyl hydrolases specific to the polysaccharide of interest (e.g., mannanases for mannan). Large format polyacrylamide gels are then used to separate the released oligosaccharides, which have been fluorescently labeled. Gels can be visualized with a modified gel imaging system (see Table of Materials). The resulting oligosaccharide fingerprint can either be compared qualitatively or, with replication, quantitatively. Linkage and branching information can be established using additional glycosyl hydrolases (e.g., mannosidases and galactosidases). Whilst this protocol describes a method for analyzing glucomannan structure, it can be applied to any polysaccharide for which characterized glycosyl hydrolases exist. Alternatively, it can be used to characterize novel glycosyl hydrolases using defined polysaccharide substrates.

Characterization of polysaccharides extracted from spent coffee grounds by alkali pretreatment.

PubMed

Ballesteros, Lina F; Cerqueira, Miguel A; Teixeira, José A; Mussatto, Solange I

2015-01-01

Spent coffee grounds (SCG), obtained during the processing of coffee powder with hot water to make soluble coffee, are the main coffee industry residues and retain approximately seventy percent of the polysaccharides present in the roasted coffee beans. The purpose of this study was to extract polysaccharides from SCG by using an alkali pretreatment with sodium hydroxide at 25°C, and determine the chemical composition, as well as the antioxidant and antimicrobial properties of the extracted polysaccharides. Galactose (60.27%mol) was the dominant sugar in the recovered polysaccharides, followed by arabinose (19.93%mol), glucose (15.37%mol) and mannose (4.43%mol). SCG polysaccharides were thermostable, and presented a typical carbohydrate pattern. Additionally, they showed good antioxidant activity through different methods and presented high antimicrobial percent inhibition against Phoma violacea and Cladosporium cladosporioides (41.27% and 54.60%, respectively). These findings allow identifying possible applications for these polysaccharides in the food industry. Copyright © 2015 Elsevier Ltd. All rights reserved.

Non-cellulosic polysaccharides from cotton fibre are differently impacted by textile processing.

PubMed

Runavot, Jean-Luc; Guo, Xiaoyuan; Willats, William G T; Knox, J Paul; Goubet, Florence; Meulewaeter, Frank

2014-01-01

Cotton fibre is mainly composed of cellulose, although non-cellulosic polysaccharides play key roles during fibre development and are still present in the harvested fibre. This study aimed at determining the fate of non-cellulosic polysaccharides during cotton textile processing. We analyzed non-cellulosic cotton fibre polysaccharides during different steps of cotton textile processing using GC-MS, HPLC and comprehensive microarray polymer profiling to obtain monosaccharide and polysaccharide amounts and linkage compositions. Additionally, in situ detection was used to obtain information on polysaccharide localization and accessibility. We show that pectic and hemicellulosic polysaccharide levels decrease during cotton textile processing and that some processing steps have more impact than others. Pectins and arabinose-containing polysaccharides are strongly impacted by the chemical treatments, with most being removed during bleaching and scouring. However, some forms of pectin are more resistant than others. Xylan and xyloglucan are affected in later processing steps and to a lesser extent, whereas callose showed a strong resistance to the chemical processing steps. This study shows that non-cellulosic polysaccharides are differently impacted by the treatments used in cotton textile processing with some hemicelluloses and callose being resistant to these harsh treatments.

Multitasking kernel for the C and Fortran programming languages

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brooks, E.D. III

1984-09-01

A multitasking kernel for the C and Fortran programming languages which runs on the Unix operating system is presented. The kernel provides a multitasking environment which serves two purposes. The first is to provide an efficient portable environment for the coding, debugging and execution of production multiprocessor programs. The second is to provide a means of evaluating the performance of a multitasking program on model multiprocessors. The performance evaluation features require no changes in the source code of the application and are implemented as a set of compile and run time options in the kernel.

Deep kernel learning method for SAR image target recognition

NASA Astrophysics Data System (ADS)

Chen, Xiuyuan; Peng, Xiyuan; Duan, Ran; Li, Junbao

2017-10-01

With the development of deep learning, research on image target recognition has made great progress in recent years. Remote sensing detection urgently requires target recognition for military, geographic, and other scientific research. This paper aims to solve the synthetic aperture radar image target recognition problem by combining deep and kernel learning. The model, which has a multilayer multiple kernel structure, is optimized layer by layer with the parameters of Support Vector Machine and a gradient descent algorithm. This new deep kernel learning method improves accuracy and achieves competitive recognition results compared with other learning methods.

PERI - Auto-tuning Memory Intensive Kernels for Multicore

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bailey, David H; Williams, Samuel; Datta, Kaushik

2008-06-24

We present an auto-tuning approach to optimize application performance on emerging multicore architectures. The methodology extends the idea of search-based performance optimizations, popular in linear algebra and FFT libraries, to application-specific computational kernels. Our work applies this strategy to Sparse Matrix Vector Multiplication (SpMV), the explicit heat equation PDE on a regular grid (Stencil), and a lattice Boltzmann application (LBMHD). We explore one of the broadest sets of multicore architectures in the HPC literature, including the Intel Xeon Clovertown, AMD Opteron Barcelona, Sun Victoria Falls, and the Sony-Toshiba-IBM (STI) Cell. Rather than hand-tuning each kernel for each system, we developmore » a code generator for each kernel that allows us to identify a highly optimized version for each platform, while amortizing the human programming effort. Results show that our auto-tuned kernel applications often achieve a better than 4X improvement compared with the original code. Additionally, we analyze a Roofline performance model for each platform to reveal hardware bottlenecks and software challenges for future multicore systems and applications.« less

Pneumococcal Capsular Polysaccharide Immunity in the Elderly

PubMed Central

Ferreira, Daniela M.; Gordon, Stephen B.; Rylance, Jamie

2017-01-01

ABSTRACT Immunity to pneumococcal infections is impaired in older people, and current vaccines are poorly protective against pneumococcal disease in this population. Naturally acquired immunity to pneumococcal capsular polysaccharides develops during childhood and is robust in young adults but deteriorates with advanced age. In particular, antibody levels and function are reduced in older people. Pneumococcal vaccines are recommended for people >65 years old. However, the benefits of polysaccharide and protein-conjugated vaccines in this population are small, because of both serotype replacement and incomplete protection against vaccine serotype pneumococcal disease. In this review, we overview the immune mechanisms by which naturally acquired and vaccine-induced pneumococcal capsular polysaccharide immunity declines with age, including altered colonization dynamics, reduced opsonic activity of antibodies (particularly IgM), and impaired mucosal immunity. PMID:28424198

Polysaccharide-Based Membranes in Food Packaging Applications.

PubMed

Ferreira, Ana R V; Alves, Vítor D; Coelhoso, Isabel M

2016-04-13

Plastic packaging is essential nowadays. However, the huge environmental problem caused by landfill disposal of non-biodegradable polymers in the end of life has to be minimized and preferentially eliminated. The solution may rely on the use of biopolymers, in particular polysaccharides. These macromolecules with film-forming properties are able to produce attracting biodegradable materials, possibly applicable in food packaging. Despite all advantages of using polysaccharides obtained from different sources, some drawbacks, mostly related to their low resistance to water, mechanical performance and price, have hindered their wider use and commercialization. Nevertheless, with increasing attention and research on this field, it has been possible to trace some strategies to overcome the problems and recognize solutions. This review summarizes some of the most used polysaccharides in food packaging applications.

Polysaccharide-Based Membranes in Food Packaging Applications

PubMed Central

Ferreira, Ana R. V.; Alves, Vítor D.; Coelhoso, Isabel M.

2016-01-01

Plastic packaging is essential nowadays. However, the huge environmental problem caused by landfill disposal of non-biodegradable polymers in the end of life has to be minimized and preferentially eliminated. The solution may rely on the use of biopolymers, in particular polysaccharides. These macromolecules with film-forming properties are able to produce attracting biodegradable materials, possibly applicable in food packaging. Despite all advantages of using polysaccharides obtained from different sources, some drawbacks, mostly related to their low resistance to water, mechanical performance and price, have hindered their wider use and commercialization. Nevertheless, with increasing attention and research on this field, it has been possible to trace some strategies to overcome the problems and recognize solutions. This review summarizes some of the most used polysaccharides in food packaging applications. PMID:27089372

An Ensemble Approach to Building Mercer Kernels with Prior Information

NASA Technical Reports Server (NTRS)

Srivastava, Ashok N.; Schumann, Johann; Fischer, Bernd

2005-01-01

This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly dimensional feature space. we describe a new method called Mixture Density Mercer Kernels to learn kernel function directly from data, rather than using pre-defined kernels. These data adaptive kernels can encode prior knowledge in the kernel using a Bayesian formulation, thus allowing for physical information to be encoded in the model. Specifically, we demonstrate the use of the algorithm in situations with extremely small samples of data. We compare the results with existing algorithms on data from the Sloan Digital Sky Survey (SDSS) and demonstrate the method's superior performance against standard methods. The code for these experiments has been generated with the AUTOBAYES tool, which automatically generates efficient and documented C/C++ code from abstract statistical model specifications. The core of the system is a schema library which contains templates for learning and knowledge discovery algorithms like different versions of EM, or numeric optimization methods like conjugate gradient methods. The template instantiation is supported by symbolic-algebraic computations, which allows AUTOBAYES to find closed-form solutions and, where possible, to integrate them into the code.

A survey of kernel-type estimators for copula and their applications

NASA Astrophysics Data System (ADS)

Sumarjaya, I. W.

2017-10-01

Copulas have been widely used to model nonlinear dependence structure. Main applications of copulas include areas such as finance, insurance, hydrology, rainfall to name but a few. The flexibility of copula allows researchers to model dependence structure beyond Gaussian distribution. Basically, a copula is a function that couples multivariate distribution functions to their one-dimensional marginal distribution functions. In general, there are three methods to estimate copula. These are parametric, nonparametric, and semiparametric method. In this article we survey kernel-type estimators for copula such as mirror reflection kernel, beta kernel, transformation method and local likelihood transformation method. Then, we apply these kernel methods to three stock indexes in Asia. The results of our analysis suggest that, albeit variation in information criterion values, the local likelihood transformation method performs better than the other kernel methods.

Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies

PubMed Central

Manitz, Juliane; Burger, Patricia; Amos, Christopher I.; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike

2017-01-01

The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility. PMID:28785300

Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies.

PubMed

Friedrichs, Stefanie; Manitz, Juliane; Burger, Patricia; Amos, Christopher I; Risch, Angela; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike; Hofner, Benjamin

2017-01-01

The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility.

Oil point and mechanical behaviour of oil palm kernels in linear compression

NASA Astrophysics Data System (ADS)

Kabutey, Abraham; Herak, David; Choteborsky, Rostislav; Mizera, Čestmír; Sigalingging, Riswanti; Akangbe, Olaosebikan Layi

2017-07-01

The study described the oil point and mechanical properties of roasted and unroasted bulk oil palm kernels under compression loading. The literature information available is very limited. A universal compression testing machine and vessel diameter of 60 mm with a plunger were used by applying maximum force of 100 kN and speed ranging from 5 to 25 mm min-1. The initial pressing height of the bulk kernels was measured at 40 mm. The oil point was determined by a litmus test for each deformation level of 5, 10, 15, 20, and 25 mm at a minimum speed of 5 mmmin-1. The measured parameters were the deformation, deformation energy, oil yield, oil point strain and oil point pressure. Clearly, the roasted bulk kernels required less deformation energy compared to the unroasted kernels for recovering the kernel oil. However, both kernels were not permanently deformed. The average oil point strain was determined at 0.57. The study is an essential contribution to pursuing innovative methods for processing palm kernel oil in rural areas of developing countries.

Pressure Sensitivity Kernels Applied to Time-reversal Acoustics

DTIC Science & Technology

2009-06-29

experimental data, along with an internal wave model, using various metrics. The linear limitations of the kernels are explored in the context of time...Acknowledgments . . . . . . . . . . . . . . . . . . . . . . 82 3.A Internal wave modeling . . . . . . . . . . . . . . . . . . . 82 Bibliography...multipaths corresponding to direct path, single surface/bottom bounce, double bounce off the surface and bot- tom, Bottom: Time-domain sensitivity kernel for

Optimal Bandwidth Selection in Observed-Score Kernel Equating

ERIC Educational Resources Information Center

Häggström, Jenny; Wiberg, Marie

2014-01-01

The selection of bandwidth in kernel equating is important because it has a direct impact on the equated test scores. The aim of this article is to examine the use of double smoothing when selecting bandwidths in kernel equating and to compare double smoothing with the commonly used penalty method. This comparison was made using both an equivalent…

Unconventional Signal Processing Using the Cone Kernel Time-Frequency Representation.

DTIC Science & Technology

1992-10-30

Wigner - Ville distribution ( WVD ), the Choi- Williams distribution , and the cone kernel distribution were compared with the spectrograms. Results were...ambiguity function. Figures A-18(c) and (d) are the Wigner - Ville Distribution ( WVD ) and CK-TFR Doppler maps. In this noiseless case all three exhibit...kernel is the basis for the well known Wigner - Ville distribution . In A-9(2), the cone kernel defined by Zhao, Atlas and Marks [21 is described

Kernel structures for Clouds

NASA Technical Reports Server (NTRS)

Spafford, Eugene H.; Mckendry, Martin S.

1986-01-01

An overview of the internal structure of the Clouds kernel was presented. An indication of how these structures will interact in the prototype Clouds implementation is given. Many specific details have yet to be determined and await experimentation with an actual working system.

Biophysical functionality in polysaccharides: from Lego-blocks to nano-particles.

PubMed

Cesàro, Attilio; Bellich, Barbara; Borgogna, Massimiliano

2012-04-01

The objective of the paper is to show the very important biophysical concepts that have been developed with polysaccharides. In particular, an attempt will be made to relate "a posteriori" the fundamental aspects, both experimental and theoretical, with some industrial applications of polysaccharide-based materials. The overview of chain conformational aspects includes relationships between topological features and local dynamics, exemplified for some naturally occurring carbohydrate polymers. Thus, by using simulation techniques and computational studies, the physicochemical properties of aqueous solutions of polysaccharides are interpreted. The relevance of conformational disorder-order transitions, chain aggregation, and phase separation to the underlying role of the ionic contribution to these processes is discussed. We stress the importance of combining information from analysis of experimental data with that from statistical-thermodynamic models for understanding the conformation, size, and functional stability of industrially important polysaccharides. The peculiar properties of polysaccharides in industrial applications are summarized for the particularly important example of nanoparticles production, a field of growing relevance and scientific interest.

Immobilized polysaccharide derivatives: chiral packing materials for efficient HPLC resolution.

PubMed

Ikai, Tomoyuki; Yamamoto, Chiyo; Kamigaito, Masami; Okamoto, Yoshio

2007-01-01

Polysaccharide-based chiral packing materials (CPMs) for high-performance liquid chromatography have frequently been used not only to determine the enantiomeric excess of chiral compounds but also to preparatively resolve a wide range of racemates. However, these CPMs can be used with only a limited number of solvents as mobile phases because some organic solvents, such as tetrahydrofuran, chloroform, and so on, dissolve or swell the polysaccharide derivatives coated on a support, e.g., silica gel, and destroy their packed columns. The limitation of mobile phase selection is sometimes a serious problem for the efficient analytical and preparative resolution of enantiomers. This defect can be resolved by the immobilization of the polysaccharide derivatives onto silica gel. Efficient immobilizations have been attained through the radical copolymerization of the polysaccharide derivatives bearing small amounts of polymerizable residues and also through the polycondensation of the polysaccharide derivatives containing a few percent of 3-(triethoxysilyl)propyl residue. (c) 2007 The Japan Chemical Journal Forum and Wiley Periodicals, Inc.

The Anti-Oxidant and Antitumor Properties of Plant Polysaccharides.

PubMed

Jiao, Rui; Liu, Yingxia; Gao, Hao; Xiao, Jia; So, Kwok Fai

2016-01-01

Oxidative stress has been increasingly recognized as a major contributing factor in a variety of human diseases, from inflammation to cancer. Although certain parts of signaling pathways are still under investigation, detailed molecular mechanisms for the induction of diseases have been elucidated, especially the link between excessive oxygen reactive species (ROS) damage and tumorigenesis. Emerging evidence suggests anti-oxidant therapy can play a key role in treating those diseases. Among potential drug resources, plant polysaccharides are natural anti-oxidant constituents important for human health because of their long history in ethnopharmacology, wide availability and few side effects upon consumption. Plant polysaccharides have been shown to possess anti-oxidant, anti-inflammation, cell viability promotion, immune-regulation and antitumor functions in a number of disease models, both in laboratory studies and in the clinic. In this paper, we reviewed the research progress of signaling pathways involved in the initiation and progression of oxidative stress- and cancer-related diseases in humans. The natural sources, structural properties and biological actions of several common plant polysaccharides, including Lycium barbarum, Ginseng, Zizyphus Jujuba, Astragalus lentiginosus, and Ginkgo biloba are discussed in detail, with emphasis on their signaling pathways. All of the mentioned common plant polysaccharides have great potential to treat oxidative stress and cancinogenic disorders in cell models, animal disease models and clinical cases. ROS-centered pathways (e.g. mitochondrial autophagy, MAPK and JNK) and transcription factor-related pathways (e.g. NF-[Formula: see text]B and HIF) are frequently utilized by these polysaccharides with or without the further involvement of inflammatory and death receptor pathways. Some of the polysaccharides may also influence tumorigenic pathways, such as Wnt and p53 to play their anti-tumor roles. In addition, current

Immunochemistry of the Group-Specific Polysaccharide of Nocardia brasiliensis

PubMed Central

Estrada-Parra, Sergio; Zamora, Abel; Bojalil, L. F.

1965-01-01

Estrada-Parra, Sergio (Escuela Nacional de Ciencias Biológicas, México, D.F., México), Abel Zamora, and L. F. Bojalil. Immunochemistry of the group-specific polysaccharide of Nocardia brasiliensis. J. Bacteriol. 90:571–574. 1965.—The group-specific polysaccharide of Nocardia brasiliensis was further purified, yielding an amorphous white material with the following characteristics: [α]D20 = + 48; nitrogen, 0.5%; phosphorus, 0.1%; and ash as sodium, 0.8%. The polymer is made of d-arabinose and d-galactose in a molar ratio of 3:1, and no other sugars were detected. Mild hydrolysis liberates mainly arabinose. The polysaccharide consumes 3.46 μmoles of periodate per mg of polymer in 15 days at 4 C (this value remains constant after 4 more days). Oxidation results in destruction of two of the arabinose, with the formation of two glycerols after borohydride reduction and hydrolysis. The polysaccharide oxidized by periodate and reduced under mild acid hydrolysis at 20 C yields glycerol and a polymer formed by galactose and arabinose (in a ratio of 1:1) which is resistant to a second oxidation. Therefore, the polysaccharide is probably formed by a main chain of glactose linked 1,3 and arabinose linked 1,2 or 1,3 or both, and nonreducing side chains of arabofuranose residues. The intact polysaccharide cross-reacts with sera from patients with active tuberculosis, and this, as well as the homologous reaction, is abolished by oxidation with periodate. PMID:16562050

The Potential of Brittle Star Extracted Polysaccharide in Promoting Apoptosis via Intrinsic Signaling Pathway.

PubMed

Baharara, Javad; Amini, Elaheh

2015-01-01

Anti-cancer potential of marine natural products such as polysaccharides represented therapeutic potential in oncological researches. In this study, total polysaccharide from brittle star [Ophiocoma erinaceus (O. erinaceus)] was extracted and chemopreventive efficacy of Persian Gulf brittle star polysaccharide was investigated in HeLa human cervical cancer cells. To extract polysaccharide, dried brittle stars were ground and extracted mechanically. Then, detection of polysaccharide was performed by phenol sulfuric acid, Ultra Violet (UV)-sulfuric acid method and FTIR. The anti proliferative activity of isolated polysaccharide was examined by MTT assay and evaluation of cell death was done through morphological cell changes; Propodium Iodide staining, fluorescence microscopy and caspase-3, -9 enzymatic measurements. To assess its underlying mechanism, expression of Bax, Bcl-2 was evaluated. The polysaccharide detection methods demonstrated isolation of crude polysaccharide from Persian Gulf brittle star. The results revealed that O. erinaceus polysaccharide suppressed the proliferation of HeLa cells in a dose and time dependent manner. Morphological observation of DAPI and Acridine Orange/Propodium Iodide staining was documented by typical characteristics of apoptotic cell death. Flow cytometry analyses exhibited the accumulation of treated cells in sub-G1 region. Additionally, polysaccharide extracted induced intrinsic apoptosis via up-regulation of caspase-3, caspase-9 and Bax along with down-regulation of Bcl-2 in HeLa cells. Taken together, the apoptosis inducing effect of brittle star polysaccharide via intrinsic pathway confirmed the anti tumor potential of marine polysaccharide. Therefore, these findings proposed new insight into anti cancer properties of brittle star polysaccharide as a promising agent in cervical cancer treatment.

Molecular Assembly of Polysaccharide-Based Microcapsules and Their Biomedical Applications.

PubMed

Feng, Xiyun; Du, Cuiling; Li, Junbai

2016-08-01

Advanced multifunctional microcapsules have revealed great potential in biomedical applications owing to their tunable size, shape, surface properties, and stimuli responsiveness. Polysaccharides are one of the most acceptable biomaterials for biomedical applications because of their outstanding virtues such as biocompatibility, biodegradability, and low toxicity. Many efforts have been devoted to investigating novel molecular design and efficient building blocks for polysaccharide-based microcapsules. In this Personal Account, we first summarize the common features of polysaccharides and the main principles of the design and fabrication of polysaccharide-based microcapsules, and further discuss their applications in biomedical areas and perspectives for future research. © 2016 The Chemical Society of Japan & Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Toll-like receptor 4-related immunostimulatory polysaccharides: Primary structure, activity relationships, and possible interaction models.

PubMed

Zhang, Xiaorui; Qi, Chunhui; Guo, Yan; Zhou, Wenxia; Zhang, Yongxiang

2016-09-20

Toll-like receptor (TLR) 4 is an important polysaccharide receptor; however, the relationships between the structures and biological activities of TLR4 and polysaccharides remain unknown. Many recent findings have revealed the primary structure of TLR4/MD-2-related polysaccharides, and several three-dimensional structure models of polysaccharide-binding proteins have been reported; and these models provide insights into the mechanisms through which polysaccharides interact with TLR4. In this review, we first discuss the origins of polysaccharides related to TLR4, including polysaccharides from higher plants, fungi, bacteria, algae, and animals. We then briefly describe the glucosidic bond types of TLR4-related heteroglycans and homoglycans and describe the typical molecular weights of TLR4-related polysaccharides. The primary structures and activity relationships of polysaccharides with TLR4/MD-2 are also discussed. Finally, based on the existing interaction models of LPS with TLR4/MD-2 and linear polysaccharides with proteins, we provide insights into the possible interaction models of polysaccharide ligands with TLR4/MD-2. To our knowledge, this review is the first to summarize the primary structures and activity relationships of TLR4-related polysaccharides and the possible mechanisms of interaction for TLR4 and TLR4-related polysaccharides. Copyright © 2016 Elsevier Ltd. All rights reserved.

Unusual monosaccharides: components of O-antigenic polysaccharides of microorganisms

NASA Astrophysics Data System (ADS)

Kochetkov, Nikolai K.

1996-09-01

The data on new monosaccharides detected in O-antigenic polysaccharides of Gram-negative bacteria have been surveyed. The results of isolation and structure determination of these unusual monosaccharides have been arranged and described systematically. The NMR spectroscopy techniques are shown to be promising for the O-antigenic polysaccharides structure determination. The information about fine structure of monosaccharides which constitute the base of important class of microbial polysaccharides, is of great significance for applied studies, first of all, the design and synthesis of biologically active substances. The bibliography includes 216 references.

Rising from the Sea: Correlations between Sulfated Polysaccharides and Salinity in Plants

PubMed Central

Aquino, Rafael S.; Grativol, Clicia; Mourão, Paulo A. S.

2011-01-01

High salinity soils inhibit crop production worldwide and represent a serious agricultural problem. To meet our ever-increasing demand for food, it is essential to understand and engineer salt-resistant crops. In this study, we evaluated the occurrence and function of sulfated polysaccharides in plants. Although ubiquitously present in marine algae, the presence of sulfated polysaccharides among the species tested was restricted to halophytes, suggesting a possible correlation with salt stress or resistance. To test this hypothesis, sulfated polysaccharides from plants artificially and naturally exposed to different salinities were analyzed. Our results revealed that the sulfated polysaccharide concentration, as well as the degree to which these compounds were sulfated in halophytic species, were positively correlated with salinity. We found that sulfated polysaccharides produced by Ruppia maritima Loisel disappeared when the plant was cultivated in the absence of salt. However, subjecting the glycophyte Oryza sativa Linnaeus to salt stress did not induce the biosynthesis of sulfated polysaccharides but increased the concentration of the carboxylated polysaccharides; this finding suggests that negatively charged cell wall polysaccharides might play a role in coping with salt stress. These data suggest that the presence of sulfated polysaccharides in plants is an adaptation to high salt environments, which may have been conserved during plant evolution from marine green algae. Our results address a practical biological concept; additionally, we suggest future strategies that may be beneficial when engineering salt-resistant crops. PMID:21552557

Rising from the sea: correlations between sulfated polysaccharides and salinity in plants.

PubMed

Aquino, Rafael S; Grativol, Clicia; Mourão, Paulo A S

2011-04-28

High salinity soils inhibit crop production worldwide and represent a serious agricultural problem. To meet our ever-increasing demand for food, it is essential to understand and engineer salt-resistant crops. In this study, we evaluated the occurrence and function of sulfated polysaccharides in plants. Although ubiquitously present in marine algae, the presence of sulfated polysaccharides among the species tested was restricted to halophytes, suggesting a possible correlation with salt stress or resistance. To test this hypothesis, sulfated polysaccharides from plants artificially and naturally exposed to different salinities were analyzed. Our results revealed that the sulfated polysaccharide concentration, as well as the degree to which these compounds were sulfated in halophytic species, were positively correlated with salinity. We found that sulfated polysaccharides produced by Ruppia maritima Loisel disappeared when the plant was cultivated in the absence of salt. However, subjecting the glycophyte Oryza sativa Linnaeus to salt stress did not induce the biosynthesis of sulfated polysaccharides but increased the concentration of the carboxylated polysaccharides; this finding suggests that negatively charged cell wall polysaccharides might play a role in coping with salt stress. These data suggest that the presence of sulfated polysaccharides in plants is an adaptation to high salt environments, which may have been conserved during plant evolution from marine green algae. Our results address a practical biological concept; additionally, we suggest future strategies that may be beneficial when engineering salt-resistant crops.

Polysaccharide enhances Radix Saposhnikoviae efficacy through inhibiting chromones decomposition in intestinal tract.

PubMed

Yang, Jing-Ming; Jiang, Hua; Dai, Hong-Liang; Wang, Zi-Wei; Jia, Gui-Zhi; Meng, Xiang-Cai

2016-09-06

Vegetative but not reproductive stage of Saposhnikovia divaricate (Turxz.) schischk possesses pharmacological activities. However, our recent study showed that reproductive S. divaricate supplemented with polysaccharide showed evidently elevated pharmacological activities and increased cimifugin content in rat serum. The aims of present study were to assess the influence of polysaccharides on the chromones pharmacological activities in Radix Saposhnikoviae (RS), the dried root of vegetative stage of S. divaricate, and to explore the underlying mechanisms. Only cimifugin was detected in the plasma of chromone treated animals and RS polysaccharide significantly increased the plasma content of cimifugin. It was shown that neither cimifugin absorption nor glycoside components transformation in simulated digestive fluid was affected by RS polysaccharide. However, a significant promotion of transformation of cimifugin to more stable prime-O-glucosylcimifugin (PGCN) by RS polysaccharide, and a protective effect of polysaccharide on chromone components were observed in small intestine solutions. Meanwhile, RS polysaccharide produced a significant elevation of cimifugin and PGCN concentration in vivo. Based on these findings, we concluded that RS polysaccharide could greatly increase the content of cimifugin, which might be related to its degradation-proof effect on cimifugin, via transforming cimifugin to comparatively more stable PGCN and spatial structure protection.

Polysaccharide production by a reduced pigmentation mutant of Aureobasidium pullulans NYS-1.

PubMed

West, T P; Strohfus, B

2001-08-01

To isolate a reduced pigmentation mutant of Aureobasidium pullulans NYS-1 and characterize its cellular pigmentation plus its polysaccharide and biomass production relative to carbon source. Cellular pigmentation, polysaccharide levels and biomass production by the isolated mutant NYSRP-1 were analysed relative to carbon source. Cellular pigmentation of the mutant was lower than its parent strain using either carbon source. The mutant elaborated higher polysaccharide levels on sucrose than on corn syrup. The pullulan content of the polysaccharide synthesized and biomass production by the mutant rose as the carbon source concentration was increased. It is feasible to isolate a reduced pigmentation mutant from strain NYS-1 that exhibits elevated polysaccharide production using corn syrup as a carbon source. The mutant provides an advantage for commercial pullulan production because of its reduced pigmentation and enhanced polysaccharide synthesis.

TICK: Transparent Incremental Checkpointing at Kernel Level

DOE Office of Scientific and Technical Information (OSTI.GOV)

Petrini, Fabrizio; Gioiosa, Roberto

2004-10-25

TICK is a software package implemented in Linux 2.6 that allows the save and restore of user processes, without any change to the user code or binary. With TICK a process can be suspended by the Linux kernel upon receiving an interrupt and saved in a file. This file can be later thawed in another computer running Linux (potentially the same computer). TICK is implemented as a Linux kernel module, in the Linux version 2.6.5

Aloe arborescens Polysaccharides: In Vitro Immunomodulation and Potential Cytotoxic Activity.

PubMed

Nazeam, Jilan A; Gad, Haidy A; Esmat, Ahmed; El-Hefnawy, Hala M; Singab, Abdel-Naser B

2017-05-01

Different polysaccharides were isolated from the leaves of Aloe arborescens using the gradient power of hydrogen followed by antitumor and immunomodulatory assay. The total polysaccharide content of different fractions, water-soluble polysaccharide (WAP), acid-soluble polysaccharide (ACP), and alkaline-soluble polysaccharide (ALP), was estimated using a phenol-sulfuric acid spectrophotometric method. WAP possessed a higher content of mannose and glucose than either ACP or ALP. In vitro antitumor activity was investigated in three different cancer cell lines, and in vitro immunomodulatory potential was assessed through phagocytosis and lymphocyte transformation assay. The results showed that WAP and ALP exhibited the most significant cytotoxicity against HepG2 human liver cancer cells, with IC 50 values of 26.14 and 21.46 μg/mL, respectively. In contrast, ALP was able to enhance lymphocyte transformation, whereas WAP had the most potent phagocytic activity. Molecular weight, total sugar and uronic acid content, Fourier transform-infrared analysis, and linkage type of bioactive polysaccharides were investigated. These findings revealed that the potential antitumor activity of the natural agents WAP and ALP was through an immunomodulation mechanism, which verifies the use of the plant as adjuvant supplement for cancer patients suffering immunosuppression during chemotherapy.

Phenolic constituents of shea (Vitellaria paradoxa) kernels.

PubMed

Maranz, Steven; Wiesman, Zeev; Garti, Nissim

2003-10-08

Analysis of the phenolic constituents of shea (Vitellaria paradoxa) kernels by LC-MS revealed eight catechin compounds-gallic acid, catechin, epicatechin, epicatechin gallate, gallocatechin, epigallocatechin, gallocatechin gallate, and epigallocatechin gallate-as well as quercetin and trans-cinnamic acid. The mean kernel content of the eight catechin compounds was 4000 ppm (0.4% of kernel dry weight), with a 2100-9500 ppm range. Comparison of the profiles of the six major catechins from 40 Vitellaria provenances from 10 African countries showed that the relative proportions of these compounds varied from region to region. Gallic acid was the major phenolic compound, comprising an average of 27% of the measured total phenols and exceeding 70% in some populations. Colorimetric analysis (101 samples) of total polyphenols extracted from shea butter into hexane gave an average of 97 ppm, with the values for different provenances varying between 62 and 135 ppm of total polyphenols.

Occurrence of 'super soft' wheat kernel texture in hexaploid and tetraploid wheats

USDA-ARS?s Scientific Manuscript database

Wheat kernel texture is a key trait that governs milling performance, flour starch damage, flour particle size, flour hydration properties, and baking quality. Kernel texture is commonly measured using the Perten Single Kernel Characterization System (SKCS). The SKCS returns texture values (Hardness...

Finite-frequency sensitivity kernels for head waves

NASA Astrophysics Data System (ADS)

Zhang, Zhigang; Shen, Yang; Zhao, Li

2007-11-01

Head waves are extremely important in determining the structure of the predominantly layered Earth. While several recent studies have shown the diffractive nature and the 3-D Fréchet kernels of finite-frequency turning waves, analogues of head waves in a continuous velocity structure, the finite-frequency effects and sensitivity kernels of head waves are yet to be carefully examined. We present the results of a numerical study focusing on the finite-frequency effects of head waves. Our model has a low-velocity layer over a high-velocity half-space and a cylindrical-shaped velocity perturbation placed beneath the interface at different locations. A 3-D finite-difference method is used to calculate synthetic waveforms. Traveltime and amplitude anomalies are measured by the cross-correlation of synthetic seismograms from models with and without the velocity perturbation and are compared to the 3-D sensitivity kernels constructed from full waveform simulations. The results show that the head wave arrival-time and amplitude are influenced by the velocity structure surrounding the ray path in a pattern that is consistent with the Fresnel zones. Unlike the `banana-doughnut' traveltime sensitivity kernels of turning waves, the traveltime sensitivity of the head wave along the ray path below the interface is weak, but non-zero. Below the ray path, the traveltime sensitivity reaches the maximum (absolute value) at a depth that depends on the wavelength and propagation distance. The sensitivity kernels vary with the vertical velocity gradient in the lower layer, but the variation is relatively small at short propagation distances when the vertical velocity gradient is within the range of the commonly accepted values. Finally, the depression or shoaling of the interface results in increased or decreased sensitivities, respectively, beneath the interface topography.

Enzyme-catalyzed modifications of polysaccharides and poly(ethylene glycol)

USDA-ARS?s Scientific Manuscript database

Polysaccharides are used extensively in various industrial applications, such as food, adhesives, coatings, construction, paper, pharmaceuticals, and personal care. Many polysaccharide structures need to be modified in order to improve their end-use properties; these are mostly done through chemica...

Structural Characterization of Mannan Cell Wall Polysaccharides in Plants Using PACE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pidatala, Venkataramana R.; Mahboubi, Amir; Mortimer, Jenny C.

Plant cell wall polysaccharides are notoriously difficult to analyze, and most methods require expensive equipment, skilled operators, and large amounts of purified material. Here, we describe a simple method for gaining detailed polysaccharide structural information, including resolution of structural isomers. For polysaccharide analysis by gel electrophoresis (PACE), plant cell wall material is hydrolyzed with glycosyl hydrolases specific to the polysaccharide of interest (e.g., mannanases for mannan). Large format polyacrylamide gels are then used to separate the released oligosaccharides, which have been fluorescently labeled. Gels can be visualized with a modified gel imaging system (see Table of Materials). The resulting oligosaccharidemore » fingerprint can either be compared qualitatively or, with replication, quantitatively. Linkage and branching information can be established using additional glycosyl hydrolases (e.g., mannosidases and galactosidases). Whilst this protocol describes a method for analyzing glucomannan structure, it can be applied to any polysaccharide for which characterized glycosyl hydrolases exist. Alternatively, it can be used to characterize novel glycosyl hydrolases using defined polysaccharide substrates.« less

Structural Characterization of Mannan Cell Wall Polysaccharides in Plants Using PACE

DOE PAGES

Pidatala, Venkataramana R.; Mahboubi, Amir; Mortimer, Jenny C.

2017-10-16

Plant cell wall polysaccharides are notoriously difficult to analyze, and most methods require expensive equipment, skilled operators, and large amounts of purified material. Here, we describe a simple method for gaining detailed polysaccharide structural information, including resolution of structural isomers. For polysaccharide analysis by gel electrophoresis (PACE), plant cell wall material is hydrolyzed with glycosyl hydrolases specific to the polysaccharide of interest (e.g., mannanases for mannan). Large format polyacrylamide gels are then used to separate the released oligosaccharides, which have been fluorescently labeled. Gels can be visualized with a modified gel imaging system (see Table of Materials). The resulting oligosaccharidemore » fingerprint can either be compared qualitatively or, with replication, quantitatively. Linkage and branching information can be established using additional glycosyl hydrolases (e.g., mannosidases and galactosidases). Whilst this protocol describes a method for analyzing glucomannan structure, it can be applied to any polysaccharide for which characterized glycosyl hydrolases exist. Alternatively, it can be used to characterize novel glycosyl hydrolases using defined polysaccharide substrates.« less

Separation of water-soluble polysaccharides from Cyclocarya paliurus by ultrafiltration process.

PubMed

Xie, Jian-Hua; Shen, Ming-Yue; Nie, Shao-Ping; Zhao, Qiang; Li, Chang; Xie, Ming-Yong

2014-01-30

In this study, ultrafiltration membrane process was employed to separate polysaccharides from Cyclocarya paliurus (Batal.) Iljinskaja (C. paliurus) to simulate industrial production. Meanwhile, the molecular weight distribution of C. paliurus polysaccharides was investigated by gel permeation chromatography. Four fractions were obtained and named as CPPS-A, CPPS-B, CPPS-C and CPPS-D, respectively. CPPS-A and CPPS-B contained approximately 69.5% and 12.7% of polysaccharides, whose molecular weight were in the range of 100-300 kDa and 120 kDa, respectively. CPPS-C was comprised of two polysaccharides with average molecular weight of 40 kDa and 15 kDa. Results showed that ultrafiltration resulted in the removal of parts of small molecule weight polysaccharides, the increase of proportion of high molecule weight ones and the obvious improvement of quality of products. Compared with ethanol precipitation and gel permeation chromatography techniques, ultrafiltration showed many advantages, and also provided theoretical support for industrial manufacturing of C. paliurus polysaccharides in separation. Copyright © 2013 Elsevier Ltd. All rights reserved.

DNA sequence+shape kernel enables alignment-free modeling of transcription factor binding.

PubMed

Ma, Wenxiu; Yang, Lin; Rohs, Remo; Noble, William Stafford

2017-10-01

Transcription factors (TFs) bind to specific DNA sequence motifs. Several lines of evidence suggest that TF-DNA binding is mediated in part by properties of the local DNA shape: the width of the minor groove, the relative orientations of adjacent base pairs, etc. Several methods have been developed to jointly account for DNA sequence and shape properties in predicting TF binding affinity. However, a limitation of these methods is that they typically require a training set of aligned TF binding sites. We describe a sequence + shape kernel that leverages DNA sequence and shape information to better understand protein-DNA binding preference and affinity. This kernel extends an existing class of k-mer based sequence kernels, based on the recently described di-mismatch kernel. Using three in vitro benchmark datasets, derived from universal protein binding microarrays (uPBMs), genomic context PBMs (gcPBMs) and SELEX-seq data, we demonstrate that incorporating DNA shape information improves our ability to predict protein-DNA binding affinity. In particular, we observe that (i) the k-spectrum + shape model performs better than the classical k-spectrum kernel, particularly for small k values; (ii) the di-mismatch kernel performs better than the k-mer kernel, for larger k; and (iii) the di-mismatch + shape kernel performs better than the di-mismatch kernel for intermediate k values. The software is available at https://bitbucket.org/wenxiu/sequence-shape.git. rohs@usc.edu or william-noble@uw.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Multiple Kernel Sparse Representation based Orthogonal Discriminative Projection and Its Cost-Sensitive Extension.

PubMed

Zhang, Guoqing; Sun, Huaijiang; Xia, Guiyu; Sun, Quansen

2016-07-07

Sparse representation based classification (SRC) has been developed and shown great potential for real-world application. Based on SRC, Yang et al. [10] devised a SRC steered discriminative projection (SRC-DP) method. However, as a linear algorithm, SRC-DP cannot handle the data with highly nonlinear distribution. Kernel sparse representation-based classifier (KSRC) is a non-linear extension of SRC and can remedy the drawback of SRC. KSRC requires the use of a predetermined kernel function and selection of the kernel function and its parameters is difficult. Recently, multiple kernel learning for SRC (MKL-SRC) [22] has been proposed to learn a kernel from a set of base kernels. However, MKL-SRC only considers the within-class reconstruction residual while ignoring the between-class relationship, when learning the kernel weights. In this paper, we propose a novel multiple kernel sparse representation-based classifier (MKSRC), and then we use it as a criterion to design a multiple kernel sparse representation based orthogonal discriminative projection method (MK-SR-ODP). The proposed algorithm aims at learning a projection matrix and a corresponding kernel from the given base kernels such that in the low dimension subspace the between-class reconstruction residual is maximized and the within-class reconstruction residual is minimized. Furthermore, to achieve a minimum overall loss by performing recognition in the learned low-dimensional subspace, we introduce cost information into the dimensionality reduction method. The solutions for the proposed method can be efficiently found based on trace ratio optimization method [33]. Extensive experimental results demonstrate the superiority of the proposed algorithm when compared with the state-of-the-art methods.

Mixed kernel function support vector regression for global sensitivity analysis

NASA Astrophysics Data System (ADS)

Cheng, Kai; Lu, Zhenzhou; Wei, Yuhao; Shi, Yan; Zhou, Yicheng

2017-11-01

Global sensitivity analysis (GSA) plays an important role in exploring the respective effects of input variables on an assigned output response. Amongst the wide sensitivity analyses in literature, the Sobol indices have attracted much attention since they can provide accurate information for most models. In this paper, a mixed kernel function (MKF) based support vector regression (SVR) model is employed to evaluate the Sobol indices at low computational cost. By the proposed derivation, the estimation of the Sobol indices can be obtained by post-processing the coefficients of the SVR meta-model. The MKF is constituted by the orthogonal polynomials kernel function and Gaussian radial basis kernel function, thus the MKF possesses both the global characteristic advantage of the polynomials kernel function and the local characteristic advantage of the Gaussian radial basis kernel function. The proposed approach is suitable for high-dimensional and non-linear problems. Performance of the proposed approach is validated by various analytical functions and compared with the popular polynomial chaos expansion (PCE). Results demonstrate that the proposed approach is an efficient method for global sensitivity analysis.

Semisupervised kernel marginal Fisher analysis for face recognition.

PubMed

Wang, Ziqiang; Sun, Xia; Sun, Lijun; Huang, Yuchun

2013-01-01

Dimensionality reduction is a key problem in face recognition due to the high-dimensionality of face image. To effectively cope with this problem, a novel dimensionality reduction algorithm called semisupervised kernel marginal Fisher analysis (SKMFA) for face recognition is proposed in this paper. SKMFA can make use of both labelled and unlabeled samples to learn the projection matrix for nonlinear dimensionality reduction. Meanwhile, it can successfully avoid the singularity problem by not calculating the matrix inverse. In addition, in order to make the nonlinear structure captured by the data-dependent kernel consistent with the intrinsic manifold structure, a manifold adaptive nonparameter kernel is incorporated into the learning process of SKMFA. Experimental results on three face image databases demonstrate the effectiveness of our proposed algorithm.

Searching remote homology with spectral clustering with symmetry in neighborhood cluster kernels.

PubMed

Maulik, Ujjwal; Sarkar, Anasua

2013-01-01

Remote homology detection among proteins utilizing only the unlabelled sequences is a central problem in comparative genomics. The existing cluster kernel methods based on neighborhoods and profiles and the Markov clustering algorithms are currently the most popular methods for protein family recognition. The deviation from random walks with inflation or dependency on hard threshold in similarity measure in those methods requires an enhancement for homology detection among multi-domain proteins. We propose to combine spectral clustering with neighborhood kernels in Markov similarity for enhancing sensitivity in detecting homology independent of "recent" paralogs. The spectral clustering approach with new combined local alignment kernels more effectively exploits the unsupervised protein sequences globally reducing inter-cluster walks. When combined with the corrections based on modified symmetry based proximity norm deemphasizing outliers, the technique proposed in this article outperforms other state-of-the-art cluster kernels among all twelve implemented kernels. The comparison with the state-of-the-art string and mismatch kernels also show the superior performance scores provided by the proposed kernels. Similar performance improvement also is found over an existing large dataset. Therefore the proposed spectral clustering framework over combined local alignment kernels with modified symmetry based correction achieves superior performance for unsupervised remote homolog detection even in multi-domain and promiscuous domain proteins from Genolevures database families with better biological relevance. Source code available upon request. sarkar@labri.fr.

Polysaccharide Microarray Technology for the Detection of Burkholderia Pseudomallei and Burkholderia Mallei Antibodies

DTIC Science & Technology

2006-04-27

polysaccharide microarray platform was prepared by immobilizing Burkholderia pseudomallei and Burkholderia mallei polysaccharides . This... polysaccharide array was tested with success for detecting B. pseudomallei and B. mallei serum (human and animal) antibodies. The advantages of this microarray... Polysaccharide microarrays; Burkholderia pseudomallei; Burkholderia mallei; Glanders; Melioidosis1. Introduction There has been a great deal of emphasis on the

A dry-inoculation method for nut kernels.

PubMed

Blessington, Tyann; Theofel, Christopher G; Harris, Linda J

2013-04-01

A dry-inoculation method for almonds and walnuts was developed to eliminate the need for the postinoculation drying required for wet-inoculation methods. The survival of Salmonella enterica Enteritidis PT 30 on wet- and dry-inoculated almond and walnut kernels stored under ambient conditions (average: 23 °C; 41 or 47% RH) was then compared over 14 weeks. For wet inoculation, an aqueous Salmonella preparation was added directly to almond or walnut kernels, which were then dried under ambient conditions (3 or 7 days, respectively) to initial nut moisture levels. For the dry inoculation, liquid inoculum was mixed with sterilized sand and dried for 24 h at 40 °C. The dried inoculated sand was mixed with kernels, and the sand was removed by shaking the mixture in a sterile sieve. Mixing procedures to optimize the bacterial transfer from sand to kernel were evaluated; in general, similar levels were achieved on walnuts (4.8-5.2 log CFU/g) and almonds (4.2-5.1 log CFU/g). The decline of Salmonella Enteritidis populations was similar during ambient storage (98 days) for both wet-and dry-inoculation methods for both almonds and walnuts. The dry-inoculation method mimics some of the suspected routes of contamination for tree nuts and may be appropriate for some postharvest challenge studies. Copyright © 2012 Elsevier Ltd. All rights reserved.

Differential evolution algorithm-based kernel parameter selection for Fukunaga-Koontz Transform subspaces construction

NASA Astrophysics Data System (ADS)

Binol, Hamidullah; Bal, Abdullah; Cukur, Huseyin

2015-10-01

The performance of the kernel based techniques depends on the selection of kernel parameters. That's why; suitable parameter selection is an important problem for many kernel based techniques. This article presents a novel technique to learn the kernel parameters in kernel Fukunaga-Koontz Transform based (KFKT) classifier. The proposed approach determines the appropriate values of kernel parameters through optimizing an objective function constructed based on discrimination ability of KFKT. For this purpose we have utilized differential evolution algorithm (DEA). The new technique overcomes some disadvantages such as high time consumption existing in the traditional cross-validation method, and it can be utilized in any type of data. The experiments for target detection applications on the hyperspectral images verify the effectiveness of the proposed method.

Design of a multiple kernel learning algorithm for LS-SVM by convex programming.

PubMed

Jian, Ling; Xia, Zhonghang; Liang, Xijun; Gao, Chuanhou

2011-06-01

As a kernel based method, the performance of least squares support vector machine (LS-SVM) depends on the selection of the kernel as well as the regularization parameter (Duan, Keerthi, & Poo, 2003). Cross-validation is efficient in selecting a single kernel and the regularization parameter; however, it suffers from heavy computational cost and is not flexible to deal with multiple kernels. In this paper, we address the issue of multiple kernel learning for LS-SVM by formulating it as semidefinite programming (SDP). Furthermore, we show that the regularization parameter can be optimized in a unified framework with the kernel, which leads to an automatic process for model selection. Extensive experimental validations are performed and analyzed. Copyright © 2011 Elsevier Ltd. All rights reserved.

Chemical components of cold pressed kernel oils from different Torreya grandis cultivars.

PubMed

He, Zhiyong; Zhu, Haidong; Li, Wangling; Zeng, Maomao; Wu, Shengfang; Chen, Shangwei; Qin, Fang; Chen, Jie

2016-10-15

The chemical compositions of cold pressed kernel oils of seven Torreya grandis cultivars from China were analyzed in this study. The contents of the chemical components of T. grandis kernels and kernel oils varied to different extents with the cultivar. The T. grandis kernels contained relatively high oil and protein content (45.80-53.16% and 10.34-14.29%, respectively). The kernel oils were rich in unsaturated fatty acids including linoleic (39.39-47.77%), oleic (30.47-37.54%) and eicosatrienoic acid (6.78-8.37%). The kernel oils contained some abundant bioactive substances such as tocopherols (0.64-1.77mg/g) consisting of α-, β-, γ- and δ-isomers; sterols including β-sitosterol (0.90-1.29mg/g), campesterol (0.06-0.32mg/g) and stigmasterol (0.04-0.18mg/g) in addition to polyphenols (9.22-22.16μgGAE/g). The results revealed that the T. grandis kernel oils possessed the potentially important nutrition and health benefits and could be used as oils in the human diet or functional ingredients in the food industry. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparison of antioxidant and antiproliferation activities of polysaccharides from eight species of medicinal mushrooms.

PubMed

Chen, Peiying; Yong, Yangyang; Gu, Yifan; Wang, Zeliang; Zhang, Shizhu; Lu, Ling

2015-01-01

Polysaccharides from mushrooms including Pleurotus eryngii, P. ostreatus, P. nebrodensis, Lentinus edodes, Hypsizygus marmoreus, Flammulina velutipes, Ganoderma lucidum, and Hericium erinaceus were isolated by water extraction and alcohol precipitation. Our results suggest that all tested polysaccharides have the significant antioxidant capacities of scavenging free radicals (1,1-diphenyl-2-picrylhydrazyl and hydroxyl radicals). Among them, the H. erinaceus polysaccharide exhibits the highest 1,1-diphenyl-2-picrylhydrazyl radical-scavenging activity, whereas the L. edodes polysaccharide shows the strongest scavenging ability for hydroxyl radicals. Furthermore, using the MCF-7 breast cancer cell line and HeLa cells, all 8 selected polysaccharides are able to inhibit the proliferation of tumor cells, but the strength of inhibition varied depending on the mushroom species and the concentration used. Notably, G. lucidum polysaccharide shows the highest inhibition activity on MCF-7 cells. By comparison, H. erinaceus polysaccharide has the strongest inhibitory effect on HeLa cells. Moreover, high-performance liquid chromatography with a carbohydrate analysis column showed significant differences in polysaccharide components among these mushrooms. Thus our data suggest that the different species of mushrooms have the variable functions because of their own specific polysaccharide components. The 8 mushroom polysaccharides have the potential to be used as valuable functional food additives or sources of therapeutic agents for antioxidant and cancer treatments, especially polysaccharides from H. erinaceus, L. edodes, and G. lucidum.

The structure of mushroom polysaccharides and their beneficial role in health.

PubMed

Huang, Xiaojun; Nie, Shaoping

2015-10-01

Mushroom is a kind of fungus that has been popular for its special flavour and renowned biological values. The polysaccharide contained in mushroom is regarded as one of the primary bioactive constituents and is beneficial for health. The structural features and bioactivities of mushroom polysaccharides have been studied extensively. It is believed that the diverse biological bioactivities of polysaccharides are closely related to their structure or conformation properties. In this review, the structural characteristics, conformational features and bioactivities of several mushroom polysaccharides are summarized, and their beneficial mechanisms and the relationships between their structure and bioactivities are also discussed.

Structural studies of the O-specific polysaccharide(s) from the lipopolysaccharide of Azospirillum brasilense type strain Sp7.

PubMed

Sigida, Elena N; Fedonenko, Yuliya P; Shashkov, Alexander S; Zdorovenko, Evelina L; Konnova, Svetlana A; Ignatov, Vladimir V; Knirel, Yuriy A

2013-10-18

Lipopolysaccharide was obtained by phenol-water extraction from dried bacterial cells of Azospirillum brasilense type strain Sp7. Mild acid hydrolysis of the lipopolysaccharide followed by GPC on Sephadex G-50 resulted in a polysaccharide mixture, which was studied by composition and methylation analyses, Smith degradation and (1)H and (13)C NMR spectroscopy. The following polysaccharide structures were established, where italics indicate a non-stoichiometric (∼40%) 2-O-methylation of l-rhamnose. Copyright © 2013 Elsevier Ltd. All rights reserved.

Biosynthesis of plant cell wall polysaccharides.

PubMed

Gibeaut, D M; Carpita, N C

1994-09-01

The cell wall is the principal structural element of plant form. Cellulose, long crystals of several dozen glucan chains, forms the microfibrillar foundation of plant cell walls and is synthesized at the plasma membrane. Except for callose, all other noncellulosic components are secreted to the cell surface and form a porous matrix assembled around the cellulose microfibrils. These diverse noncellulosic polysaccharides and proteins are made in the endomembrane system. Many questions about the biosynthesis and modification within the Golgi apparatus and integration of cell components at the cell surface remain unanswered. The lability of synthetic complexes upon isolation is one reason for slow progress. However, with new methods of membrane isolation and analysis of products in vitro, recent advances have been made in purifying active synthases from plasma membrane and Golgi apparatus. Likely synthase polypeptides have been identified by affinity-labeling techniques, but we are just beginning to understand the unique features of the coordinated assembly of complex polysaccharides. Nevertheless, such progress renews hope that the first gene of a synthase for a wall polysaccharide from higher plants is within our grasp.

Polysaccharide based nanogels in the drug delivery system: Application as the carrier of pharmaceutical agents.

PubMed

Debele, Tilahun Ayane; Mekuria, Shewaye Lakew; Tsai, Hsieh-Chih

2016-11-01

Polysaccharide-based nanoparticles have fascinated attention as a vesicle of different pharmaceutical agents due to their unique multi-functional groups in addition to their physicochemical properties, including biocompatibility and biodegradability. The existence of multi-functional groups on the polysaccharide backbone permits facile chemical or biochemical modification to synthesize polysaccharide based nanoparticles with miscellaneous structures. Polysaccharide-based nanogels have high water content, large surface area for multivalent bioconjugation, tunable size, and interior network for the incorporation of different pharmaceutical agents. These unique properties offer great potential for the utilization of polysaccharide-based nanogels in the drug delivery systems. Hence, this review describes chemistry of certain common polysaccharides, several methodologies used to synthesize polysaccharide nanoparticles and primarily focused on the polysaccharide (or polysaccharide derivative) based nanogels as the carrier of pharmaceutical agents. Copyright © 2016 Elsevier B.V. All rights reserved.

Matrix polyelectrolyte capsules based on polysaccharide/MnCO₃ hybrid microparticle templates.

PubMed

Wei, Qingrong; Ai, Hua; Gu, Zhongwei

2011-06-15

An efficient strategy for biomacromolecule encapsulation based on spontaneous deposition into polysaccharide matrix-containing capsules is introduced in this study. First, hybrid microparticles composed of manganese carbonate and ionic polysaccharides including sodium hyaluronate (HA), sodium alginate (SA) and dextran sulfate sodium (DS) with narrow size distribution were synthesized to provide monodisperse templates. Incorporation of polysaccharide into the hybrid templates was successful as verified by thermogravimetric analysis (TGA) and confocal laser scanning microscopy (CLSM). Matrix polyelectrolyte microcapsules were fabricated through layer-by-layer (LbL) self-assembly of oppositely charged polyelectrolytes (PEs) onto the hybrid particles, followed by removal of the inorganic part of the cores, leaving polysaccharide matrix inside the capsules. The loading and release properties of the matrix microcapsules were investigated using myoglobin as a model biomacromolecule. Compared to matrix-free capsules, the matrix capsules had a much higher loading capacity up to four times; the driving force is mostly due to electrostatic interactions between myoglobin and the polysaccharide matrix. From our observations, for the same kind of polysaccharide, a higher amount of polysaccharide inside the capsules usually led to better loading capacity. The release behavior of the loaded myoglobin could be readily controlled by altering the environmental pH. These matrix microcapsules may be used as efficient delivery systems for various charged water-soluble macromolecules with applications in biomedical fields. Copyright © 2010 Elsevier B.V. All rights reserved.

Quasi-kernel polynomials and convergence results for quasi-minimal residual iterations

NASA Technical Reports Server (NTRS)

Freund, Roland W.

1992-01-01

Recently, Freund and Nachtigal have proposed a novel polynominal-based iteration, the quasi-minimal residual algorithm (QMR), for solving general nonsingular non-Hermitian linear systems. Motivated by the QMR method, we have introduced the general concept of quasi-kernel polynomials, and we have shown that the QMR algorithm is based on a particular instance of quasi-kernel polynomials. In this paper, we continue our study of quasi-kernel polynomials. In particular, we derive bounds for the norms of quasi-kernel polynomials. These results are then applied to obtain convergence theorems both for the QMR method and for a transpose-free variant of QMR, the TFQMR algorithm.

Tamarind seed gum-hydrolyzed polymethacrylamide-g-gellan beads for extended release of diclofenac sodium using 32 full factorial design.

PubMed

Nandi, Gouranga; Nandi, Amit Kumar; Khan, Najim Sarif; Pal, Souvik; Dey, Sibasish

2018-07-15

Development of tamarind seed gum (TSG)-hydrolyzed polymethacrylamide-g-gellan (h-Pmaa-g-GG) composite beads for extended release of diclofenac sodium using 3 2 full factorial design is the main purpose of this study. The ratio of h-Pmaa-g-GG and TSG and concentration of cross-linker CaCl 2 were taken as independent factors with three different levels of each. Effects of polymer ratio and CaCl 2 on drug entrapment efficiency (DEE), drug release, bead size and swelling were investigated. Responses such as DEE and different drug release parameters were statistically analyzed by 3 2 full factorial design using Design-Expert software and finally the formulation factors were optimized to obtain USP-reference release profile. Drug release rate was found to decrease with decrease in the ratio of h-Pmaa-g-GG:TSG and increase in the concentration of Ca 2+ ions in cross-linking medium. The optimized formulation showed DEE of 93.25% and an extended drug release profile over a period of 10h with f 2 =80.13. Kinetic modeling unveiled case-I-Fickian diffusion based drug release mechanism. Copyright © 2018 Elsevier B.V. All rights reserved.

Defective anti-polysaccharide IgG vaccine responses in IgA deficient mice

USDA-ARS?s Scientific Manuscript database

IgA deficient patients often show defects in antibody responses following immunization with polysaccharide vaccines. We now show that IgA-/- mice exhibit specific defects in IgG antibody responses to various polysaccharide vaccines, but not protein vaccines. Defects in anti-polysaccharide IgG resp...

Structural characterization of alkali-soluble polysaccharides from Panax ginseng C. A. Meyer

PubMed Central

Ji, Li; Jie, Zhenjing; Ying, Xin; Yue, Qi; Zhou, Yifa

2018-01-01

Panax ginseng C. A. Meyer (ginseng) has been widely used as a herb and functional food in the world. Polysaccharides are the main active components of ginseng. In this paper, the polysaccharides were sequentially extracted by 50 mM Na2CO3, 1 M KOH and 4 M KOH from ginseng roots treated sequentially with hot water, α-amylase and ethylenediaminetetraacetic acid extraction. Na2CO3-soluble ginseng polysaccharide (NGP) was fractionated into one neutral and three acidic fractions by anion exchange and gel permeation chromatography. Fourier transform infrared, NMR and methylation analysis indicated acidic fractions in NGP were highly branched rhamnogalacturonan-I domains, with  → 4)-α-GalpA-(1 → 2)-α-Rhap-(1 → disaccharide repeating units as backbone and β-1,4-galactan, α-1,5/1,3,5-arabinan and type II arabinogalactan as side chains. 1-KGP (1 M KOH-soluble ginseng polysaccharide) and 4-KGP (4 M KOH-soluble ginseng polysaccharide) were mainly composed of hemicellulose besides starch-like polysaccharides and minor pectin. Antibody detection, enzymic hydrolysis, high performance anion exchange chromatography and methylation analysis demonstrated xylan was the major component in 1-KGP, while xyloglucan was predominant in 4-KGP. Comparing the polysaccharides obtained by different solvent extractions, we have a comprehensive understanding about total ginseng polysaccharides. PMID:29657770

Mapping QTLs controlling kernel dimensions in a wheat inter-varietal RIL mapping population.

PubMed

Cheng, Ruiru; Kong, Zhongxin; Zhang, Liwei; Xie, Quan; Jia, Haiyan; Yu, Dong; Huang, Yulong; Ma, Zhengqiang

2017-07-01

Seven kernel dimension QTLs were identified in wheat, and kernel thickness was found to be the most important dimension for grain weight improvement. Kernel morphology and weight of wheat (Triticum aestivum L.) affect both yield and quality; however, the genetic basis of these traits and their interactions has not been fully understood. In this study, to investigate the genetic factors affecting kernel morphology and the association of kernel morphology traits with kernel weight, kernel length (KL), width (KW) and thickness (KT) were evaluated, together with hundred-grain weight (HGW), in a recombinant inbred line population derived from Nanda2419 × Wangshuibai, with data from five trials (two different locations over 3 years). The results showed that HGW was more closely correlated with KT and KW than with KL. A whole genome scan revealed four QTLs for KL, one for KW and two for KT, distributed on five different chromosomes. Of them, QKl.nau-2D for KL, and QKt.nau-4B and QKt.nau-5A for KT were newly identified major QTLs for the respective traits, explaining up to 32.6 and 41.5% of the phenotypic variations, respectively. Increase of KW and KT and reduction of KL/KT and KW/KT ratios always resulted in significant higher grain weight. Lines combining the Nanda 2419 alleles of the 4B and 5A intervals had wider, thicker, rounder kernels and a 14% higher grain weight in the genotype-based analysis. A strong, negative linear relationship of the KW/KT ratio with grain weight was observed. It thus appears that kernel thickness is the most important kernel dimension factor in wheat improvement for higher yield. Mapping and marker identification of the kernel dimension-related QTLs definitely help realize the breeding goals.

Characterization of polysaccharides with marked inhibitory effect on lipid accumulation in Pleurotus eryngii.

PubMed

Chen, Jingjing; Yong, Yangyang; Xing, Meichun; Gu, Yifan; Zhang, Zhao; Zhang, Shizhu; Lu, Ling

2013-09-12

Mushrooms have a great potential for the production of useful bioactive metabolites. To explore the bioactive compounds from edible mushrooms for interfering with the development of macrophage-derived foam cells, which is recognized as the hallmark of early atherosclerosis, eight types of mushrooms polysaccharides had been selected to be tested. Consequently, different mushrooms polysaccharides displayed diverse component profiles. Of polysaccharides that we tested, the Pleurotus eryngii polysaccharide had the strongest inhibitory effect on lipid accumulation. Furthermore, through fractionation of DEAE-52 and Sephadex G-100, the polysaccharide from P. eryngii had been successfully purified and identified. By the analysis of IR, GC, and HPLC, the purified polysaccharide was estimated to be 30-38 kDa for the average molecular weight with the monosaccharide composition mainly composed of D-types of mannose, glucose and galactose. Findings presented in this report firstly provide direct evidence, which links the purified polysaccharide moiety with the biological function in foam-cell model. Copyright © 2013 Elsevier Ltd. All rights reserved.

Immunogold scanning electron microscopy can reveal the polysaccharide architecture of xylem cell walls

PubMed Central

Sun, Yuliang; Juzenas, Kevin

2017-01-01

Abstract Immunofluorescence microscopy (IFM) and immunogold transmission electron microscopy (TEM) are the two main techniques commonly used to detect polysaccharides in plant cell walls. Both are important in localizing cell wall polysaccharides, but both have major limitations, such as low resolution in IFM and restricted sample size for immunogold TEM. In this study, we have developed a robust technique that combines immunocytochemistry with scanning electron microscopy (SEM) to study cell wall polysaccharide architecture in xylem cells at high resolution over large areas of sample. Using multiple cell wall monoclonal antibodies (mAbs), this immunogold SEM technique reliably localized groups of hemicellulosic and pectic polysaccharides in the cell walls of five different xylem structures (vessel elements, fibers, axial and ray parenchyma cells, and tyloses). This demonstrates its important advantages over the other two methods for studying cell wall polysaccharide composition and distribution in these structures. In addition, it can show the three-dimensional distribution of a polysaccharide group in the vessel lateral wall and the polysaccharide components in the cell wall of developing tyloses. This technique, therefore, should be valuable for understanding the cell wall polysaccharide composition, architecture and functions of diverse cell types. PMID:28398585

O-sulfated bacterial polysaccharides with low anticoagulant activity inhibit metastasis.

PubMed

Borgenström, Marjut; Wärri, Anni; Hiilesvuo, Katri; Käkönen, Rami; Käkönen, Sanna; Nissinen, Liisa; Pihlavisto, Marjo; Marjamäki, Anne; Vlodavsky, Israel; Naggi, Annamaria; Torri, Giangiacomo; Casu, Benito; Veromaa, Timo; Salmivirta, Markku; Elenius, Klaus

2007-07-01

Heparin-like polysaccharides possess the capacity to inhibit cancer cell proliferation, angiogenesis, heparanase-mediated cancer cell invasion, and cancer cell adhesion to vascular endothelia via adhesion receptors, such as selectins. The clinical applicability of the antitumor effect of such polysaccharides, however, is compromised by their anticoagulant activity. We have compared the potential of chemically O-sulfated and N,O-sulfated bacterial polysaccharide (capsular polysaccharide from E. COLI K5 [K5PS]) species to inhibit metastasis of mouse B16-BL6 melanoma cells and human MDA-MB-231 breast cancer cells in two in vivo models. We demonstrate that in both settings, O-sulfated K5PS was a potent inhibitor of metastasis. Reducing the molecular weight of the polysaccharide, however, resulted in lower antimetastatic capacity. Furthermore, we show that O-sulfated K5PS efficiently inhibited the invasion of B16-BL6 cells through Matrigel and also inhibited the in vitro activity of heparanase. Moreover, treatment with O-sulfated K5PS lowered the ability of B16-BL6 cells to adhere to endothelial cells, intercellular adhesion molecule-1, and P-selectin, but not to E-selectin. Importantly, O-sulfated K5PSs were largely devoid of anticoagulant activity. These findings indicate that O-sulfated K5PS polysaccharide should be considered as a potential antimetastatic agent.

Carboxymethylated degraded polysaccharides from Enteromorpha prolifera: Preparation and in vitro antioxidant activity.

PubMed

Shi, Mei-Jia; Wei, Xiaoyi; Xu, Jie; Chen, Bing-Jie; Zhao, De-Yin; Cui, Shuai; Zhou, Tao

2017-01-15

In order to improve the bioactivities of the polysaccharide from Enteromorpha prolifera (PE), crude PE (Mw 1400kDa) was degraded to low molecular weight polysaccharide (44kDa) in the presence of hydrogen peroxide/ascorbic acid, followed by carboxymethylation. The reaction conditions for carboxymethylation of degraded polysaccharide (DPE) were optimized by Response Surface Methodology. The carboxymethyled degraded polysaccharide (CDPE) obtained under optimized conditions, with a degree of carboxymethylation of 0.849, was characterized by FT-IR and (13)C NMR. The molecular weight of CDPE was measured to be 53.7kDa. CDPE was evaluated for its antioxidant activity by determining the ability to scavenge 1,1-diphenyl-2-picrylhydrazyl (DPPH), hydroxyl and superoxide anion radicals, and by determining the ferric reducing power. The antioxidant activity of CDPE was found to be greatly improved in comparison with degraded polysaccharide (DPE) and crude polysaccharide from Enteromorpha prolifera (PE). Copyright © 2016 Elsevier Ltd. All rights reserved.

Optimization of polysaccharides extraction from watermelon rinds: Structure, functional and biological activities.

PubMed

Romdhane, Molka Ben; Haddar, Anissa; Ghazala, Imen; Jeddou, Khawla Ben; Helbert, Claire Boisset; Ellouz-Chaabouni, Semia

2017-02-01

In the present work, optimization of hot water extraction, structural characteristics, functional properties, and biological activities of polysaccharides extracted from watermelon rinds (WMRP) were investigated. The physicochemical characteristics and the monosaccharide composition of these polysaccharides were then determined using chemical composition analysis, Fourier transform infrared (FT-IR) spectroscopy, scanning electron microscopy (SEM) and gas chromatography-flame ionization detection (GC-FID). SEM images showed that extracted polysaccharides had a rough surface with many cavities. GC-FID results proved that galactose was the dominant sugar in the extracted polysaccharides, followed by arabinose, glucose, galacturonic acid, rhamnose, mannose, xylose and traces of glucuronic acid. The findings revealed that WMRP displayed excellent antihypertensive and antioxidant activities. Those polysaccharides had also a protection effect against hydroxyl radical-induced DNA damage. Functional properties of extracted polysaccharides were also evaluated. WMRP showed good interfacial dose-dependent proprieties. Overall, the results suggested that WMRP presents a promising natural source of antioxidants and antihypertensive agents. Copyright © 2016 Elsevier Ltd. All rights reserved.

Weighted Feature Gaussian Kernel SVM for Emotion Recognition

PubMed Central

Jia, Qingxuan

2016-01-01

Emotion recognition with weighted feature based on facial expression is a challenging research topic and has attracted great attention in the past few years. This paper presents a novel method, utilizing subregion recognition rate to weight kernel function. First, we divide the facial expression image into some uniform subregions and calculate corresponding recognition rate and weight. Then, we get a weighted feature Gaussian kernel function and construct a classifier based on Support Vector Machine (SVM). At last, the experimental results suggest that the approach based on weighted feature Gaussian kernel function has good performance on the correct rate in emotion recognition. The experiments on the extended Cohn-Kanade (CK+) dataset show that our method has achieved encouraging recognition results compared to the state-of-the-art methods. PMID:27807443

Searching Remote Homology with Spectral Clustering with Symmetry in Neighborhood Cluster Kernels

PubMed Central

Maulik, Ujjwal; Sarkar, Anasua

2013-01-01

Remote homology detection among proteins utilizing only the unlabelled sequences is a central problem in comparative genomics. The existing cluster kernel methods based on neighborhoods and profiles and the Markov clustering algorithms are currently the most popular methods for protein family recognition. The deviation from random walks with inflation or dependency on hard threshold in similarity measure in those methods requires an enhancement for homology detection among multi-domain proteins. We propose to combine spectral clustering with neighborhood kernels in Markov similarity for enhancing sensitivity in detecting homology independent of “recent” paralogs. The spectral clustering approach with new combined local alignment kernels more effectively exploits the unsupervised protein sequences globally reducing inter-cluster walks. When combined with the corrections based on modified symmetry based proximity norm deemphasizing outliers, the technique proposed in this article outperforms other state-of-the-art cluster kernels among all twelve implemented kernels. The comparison with the state-of-the-art string and mismatch kernels also show the superior performance scores provided by the proposed kernels. Similar performance improvement also is found over an existing large dataset. Therefore the proposed spectral clustering framework over combined local alignment kernels with modified symmetry based correction achieves superior performance for unsupervised remote homolog detection even in multi-domain and promiscuous domain proteins from Genolevures database families with better biological relevance. Source code available upon request. Contact: sarkar@labri.fr. PMID:23457439

Celluclast 1.5L pretreatment enhanced aroma of palm kernels and oil after kernel roasting.

PubMed

Zhang, Wencan; Zhao, Fangju; Yang, Tiankui; Zhao, Feifei; Liu, Shaoquan

2017-12-01

The aroma of palm kernel oil (PKO) affects its applications. Little information is available on how enzymatic modification of palm kernels (PK) affects PK and PKO aroma after kernel roasting. Celluclast (cellulase) pretreatment of PK resulted in a 2.4-fold increment in the concentration of soluble sugars, with glucose being increased by 6.0-fold. Higher levels of 1.7-, 1.8- and 1.9-fold of O-heterocyclic volatile compounds were found in the treated PK after roasting at 180 °C for 8, 14 and 20 min respectively relative to the corresponding control, with furfural, 5-methyl-2-furancarboxaldehyde, 2-furanmethanol and maltol in particularly higher amounts. Volatile differences between PKOs from control and treated PK were also found, though less obvious owing to the aqueous extraction process. Principal component analysis based on aroma-active compounds revealed that upon the proceeding of roasting, the differentiation between control and treated PK was enlarged while that of corresponding PKOs was less clear-cut. Celluclast pretreatment enabled the medium roasted PK to impart more nutty, roasty and caramelic odor and the corresponding PKO to impart more caramelic but less roasty and burnt notes. Celluclast pretreatment of PK followed by roasting may be a promising new way of improving PKO aroma. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Isolation and antiviral activity of water-soluble Cynomorium songaricum Rupr. polysaccharides.

PubMed

Tuvaanjav, Suvdmaa; Shuqin, Han; Komata, Masashi; Ma, Chunjie; Kanamoto, Taisei; Nakashima, Hideki; Yoshida, Takashi

2016-01-01

The plant, Cynomorium songaricum Rupr., is used as a traditional medicine in China and Mongolia. In the present study, two new water-soluble polysaccharides isolated from C. songaricum Rupr. were purified by successive Sephadex G-75 and G-50 column chromatographies and then characterized by high resolution NMR and IR spectroscopies. The molecular weights of two polysaccharides were determined by an aqueous GPC to be [Formula: see text] = 3.7 × 10(4) and 1.0 × 10(4), respectively. In addition, it was found that the polysaccharide with the larger molecular weight was an acidic polysaccharide. It was found that the iodine-starch reaction of both isolated polysaccharides was negative and the methylation analysis gave 2, 4, 6-tri-O-methyl alditol acetate as a main product. NMR and IR measurements and sugar analysis revealed that both polysaccharides had a (1 → 3)-α-d-glucopyranosidic main chain with a small number of branches. After sulfation, the sulfated C. songaricum Rupr. polysaccharides were found to have a potent inhibitory effect on HIV infection of MT-4 cells at a 50% effective concentration of 0.3-0.4 μg/ml, a concentration that has almost the same high activity as standard dextran and curdlan sulfates, EC50 = 0.35 and 0.14 μg/ml, respectively. The 50% cytotoxic concentration was low, CC50>1000 μg/ml. In addition, the interaction between the sulfated polysaccharides and poly-l-lysine as a model protein compound was investigated by a surface plasmon resonance to reveal the anti-HIV mechanism.

Sustainability, polysaccharide science, and bio-economy.

PubMed

ten Bos, René; van Dam, Jan E G

2013-03-01

At the opening of the 2nd EPNOE conference the role and responsibility of polysaccharide scientists was reflected upon and placed in the context of actual global issues like the transition process towards "sustainable bio-economy". Difficulties in the chain of communication between the different parties involved and towards the wider public was addressed. The need for change in the relations between science and the public and to go beyond the horizon of the specialization was discussed. It was stated that polysaccharide science is one of the key sciences in those transitions. Copyright © 2012 Elsevier Ltd. All rights reserved.

Antiviral Potential of Algae Polysaccharides Isolated from Marine Sources: A Review.

PubMed

Ahmadi, Azin; Zorofchian Moghadamtousi, Soheil; Abubakar, Sazaly; Zandi, Keivan

2015-01-01

From food to fertilizer, algal derived products are largely employed in assorted industries, including agricultural, biomedical, food, and pharmaceutical industries. Among different chemical compositions isolated from algae, polysaccharides are the most well-established compounds, which were subjected to a variety of studies due to extensive bioactivities. Over the past few decades, the promising results for antiviral potential of algae-derived polysaccharides have advocated them as inordinate candidates for pharmaceutical research. Numerous studies have isolated various algal polysaccharides possessing antiviral activities, including carrageenan, alginate, fucan, laminaran, and naviculan. In addition, different mechanisms of action have been reported for these polysaccharides, such as inhibiting the binding or internalization of virus into the host cells or suppressing DNA replication and protein synthesis. This review strives for compiling previous antiviral studies of algae-derived polysaccharides and their mechanism of action towards their development as natural antiviral agents for future investigations.

Extraction, Structural Characterization, and Potential Antioxidant Activity of the Polysaccharides from Four Seaweeds

PubMed Central

He, Jinzhe; Xu, Yaoyang; Chen, Hongbo; Sun, Peilong

2016-01-01

Four seaweed polysaccharides were extracted from Sarcodia ceylonensis, Ulva lactuca L., Gracilaria lemaneiformis, and Durvillaea antarctica, respectively, by microwave-assisted extraction. The effect of three significant variables (extraction time, extraction temperature, and the ratio of water to raw material) on the process for extracting polysaccharides was investigated, along with the optimization of the extraction using the response surface method (RSM) with a Box–Behnken design. The polysaccharide structure, monosaccharide composition, degree of sulfation, and molecular weight (MW) distribution were analyzed by infrared (IR) spectrometry, gas chromatography (GC), and high-performance gel permeation chromatography (HPGPC). IR spectrometry showed that Sarcodia ceylonensis polysaccharide (SCP), Ulva lactuca L. polysaccharide (ULLP), and Durvillaea antarctica polysaccharide (DAP) were all sulfated polysaccharides and, except Gracilaria lemaneiformis polysaccharide (GLP), all belong to β-pyranosidic polysaccharides. The average molecular weight (MW) of SCP, ULLP, GLP, and DAP was 466, 404, 591, and 482 kDa, respectively. The quantitative and comparative results with external standards indicated that the main monosaccharide in SCP and ULLP was mannose; and GLP and DAP were mainly composed of galactose and glucose, respectively. Then the in vitro antioxidant activity of all of the polysaccharides was evaluated using different assays—2,2–azino –bis (3-ethylbenzthiazoline-6- sulfonate) (ABTS), hydroxyl radical, nitrite scavenging capacity, and reducing power—and the relationship between their antioxidant activity and chemical characteristics were also examined. ULLP presented the highest ABTS radical scavenging activity; ULLP, SCP and DAP also showed a strong effect on the ABTS radical scavenging activity. SCP and ULLP exhibited excellent hydroxyl radical scavenging activities, about 83.33% ± 2.31% and 80.07% ± 2.17%, respectively, at 4 mg/mL. The

Extraction, Structural Characterization, and Potential Antioxidant Activity of the Polysaccharides from Four Seaweeds.

PubMed

He, Jinzhe; Xu, Yaoyang; Chen, Hongbo; Sun, Peilong

2016-11-28

Four seaweed polysaccharides were extracted from Sarcodia ceylonensis , Ulva lactuca L., Gracilaria lemaneiformis , and Durvillaea antarctica , respectively, by microwave-assisted extraction. The effect of three significant variables (extraction time, extraction temperature, and the ratio of water to raw material) on the process for extracting polysaccharides was investigated, along with the optimization of the extraction using the response surface method (RSM) with a Box-Behnken design. The polysaccharide structure, monosaccharide composition, degree of sulfation, and molecular weight ( M W ) distribution were analyzed by infrared (IR) spectrometry, gas chromatography (GC), and high-performance gel permeation chromatography (HPGPC). IR spectrometry showed that Sarcodia ceylonensis polysaccharide (SCP), Ulva lactuca L. polysaccharide (ULLP), and Durvillaea antarctica polysaccharide (DAP) were all sulfated polysaccharides and, except Gracilaria lemaneiformis polysaccharide (GLP), all belong to β-pyranosidic polysaccharides. The average molecular weight ( M W ) of SCP, ULLP, GLP, and DAP was 466, 404, 591, and 482 kDa, respectively. The quantitative and comparative results with external standards indicated that the main monosaccharide in SCP and ULLP was mannose; and GLP and DAP were mainly composed of galactose and glucose, respectively. Then the in vitro antioxidant activity of all of the polysaccharides was evaluated using different assays-2,2-azino -bis (3-ethylbenzthiazoline-6- sulfonate) (ABTS), hydroxyl radical, nitrite scavenging capacity, and reducing power-and the relationship between their antioxidant activity and chemical characteristics were also examined. ULLP presented the highest ABTS radical scavenging activity; ULLP, SCP and DAP also showed a strong effect on the ABTS radical scavenging activity. SCP and ULLP exhibited excellent hydroxyl radical scavenging activities, about 83.33% ± 2.31% and 80.07% ± 2.17%, respectively, at 4 mg/mL. The reducing

Size resolved airborne particulate polysaccharides in summer high Arctic

NASA Astrophysics Data System (ADS)

Leck, C.; Gao, Q.; Mashayekhy Rad, F.; Nilsson, U.

2013-04-01

Size-resolved aerosol samples for subsequent determination of polysaccharides (monosaccharides in combined form) were collected in air over the central Arctic Ocean during the biologically most active period between the late summer melt season and into the transition to autumn freeze-up. The analysis was carried out using liquid chromatography coupled with highly selective and sensitive tandem mass spectrometry. Polysaccharides were detected in all sizes ranging from 0.035 to 10 μm in diameter with distinct features of heteropolysaccharides, enriched in xylose, glucose + mannose as well as a substantial fraction of deoxysugars. Polysaccharides containing deoxysugars showed a bimodal structure with about 60% of their mass found in the Aitken mode over the pack ice area. Pentose (xylose) and hexose (glucose + mannose) showed a weaker bimodal character and were largely found in the coarse mode in addition to a minor fraction apportioned in the sub-micrometer size range. The concentration of total hydrolysable neutral sugars (THNS) in the samples collected varied over 3 orders of magnitude (1 to 692 pmol m-3) in the super-micrometer size fraction and to a lesser extent in sub-micrometer particles (4 to 88 pmol m-3). Lowest THNS concentrations were observed in air masses that had spent more than 5 days over the pack ice. Within the pack ice area, about 53% (by mass) of the total mass of polysaccharides were found in sub-micrometer particles. The relative abundance of sub-micrometer polysaccharides was closely related to the length of time that the air mass spent over pack ice, with highest fraction (> 90%) observed for > 7 days of advection. The ambient aerosol particles collected onboard ship showed similar monosaccharide composition, compared to particles generated experimentally in situ at the open lead site. This supports the existence of a primary source of particulate polysaccharides from open leads by bubble bursting at the air-sea interface. We speculate that

Multiple kernel learning in protein-protein interaction extraction from biomedical literature.

PubMed

Yang, Zhihao; Tang, Nan; Zhang, Xiao; Lin, Hongfei; Li, Yanpeng; Yang, Zhiwei

2011-03-01

Knowledge about protein-protein interactions (PPIs) unveils the molecular mechanisms of biological processes. The volume and content of published biomedical literature on protein interactions is expanding rapidly, making it increasingly difficult for interaction database administrators, responsible for content input and maintenance to detect and manually update protein interaction information. The objective of this work is to develop an effective approach to automatic extraction of PPI information from biomedical literature. We present a weighted multiple kernel learning-based approach for automatic PPI extraction from biomedical literature. The approach combines the following kernels: feature-based, tree, graph and part-of-speech (POS) path. In particular, we extend the shortest path-enclosed tree (SPT) and dependency path tree to capture richer contextual information. Our experimental results show that the combination of SPT and dependency path tree extensions contributes to the improvement of performance by almost 0.7 percentage units in F-score and 2 percentage units in area under the receiver operating characteristics curve (AUC). Combining two or more appropriately weighed individual will further improve the performance. Both on the individual corpus and cross-corpus evaluation our combined kernel can achieve state-of-the-art performance with respect to comparable evaluations, with 64.41% F-score and 88.46% AUC on the AImed corpus. As different kernels calculate the similarity between two sentences from different aspects. Our combined kernel can reduce the risk of missing important features. More specifically, we use a weighted linear combination of individual kernels instead of assigning the same weight to each individual kernel, thus allowing the introduction of each kernel to incrementally contribute to the performance improvement. In addition, SPT and dependency path tree extensions can improve the performance by including richer context information

Relationship between processing score and kernel-fraction particle size in whole-plant corn silage.

PubMed

Dias Junior, G S; Ferraretto, L F; Salvati, G G S; de Resende, L C; Hoffman, P C; Pereira, M N; Shaver, R D

2016-04-01

Kernel processing increases starch digestibility in whole-plant corn silage (WPCS). Corn silage processing score (CSPS), the percentage of starch passing through a 4.75-mm sieve, is widely used to assess degree of kernel breakage in WPCS. However, the geometric mean particle size (GMPS) of the kernel-fraction that passes through the 4.75-mm sieve has not been well described. Therefore, the objectives of this study were (1) to evaluate particle size distribution and digestibility of kernels cut in varied particle sizes; (2) to propose a method to measure GMPS in WPCS kernels; and (3) to evaluate the relationship between CSPS and GMPS of the kernel fraction in WPCS. Composite samples of unfermented, dried kernels from 110 corn hybrids commonly used for silage production were kept whole (WH) or manually cut in 2, 4, 8, 16, 32 or 64 pieces (2P, 4P, 8P, 16P, 32P, and 64P, respectively). Dry sieving to determine GMPS, surface area, and particle size distribution using 9 sieves with nominal square apertures of 9.50, 6.70, 4.75, 3.35, 2.36, 1.70, 1.18, and 0.59 mm and pan, as well as ruminal in situ dry matter (DM) digestibilities were performed for each kernel particle number treatment. Incubation times were 0, 3, 6, 12, and 24 h. The ruminal in situ DM disappearance of unfermented kernels increased with the reduction in particle size of corn kernels. Kernels kept whole had the lowest ruminal DM disappearance for all time points with maximum DM disappearance of 6.9% at 24 h and the greatest disappearance was observed for 64P, followed by 32P and 16P. Samples of WPCS (n=80) from 3 studies representing varied theoretical length of cut settings and processor types and settings were also evaluated. Each WPCS sample was divided in 2 and then dried at 60 °C for 48 h. The CSPS was determined in duplicate on 1 of the split samples, whereas on the other split sample the kernel and stover fractions were separated using a hydrodynamic separation procedure. After separation, the

Boundary conditions for gas flow problems from anisotropic scattering kernels

NASA Astrophysics Data System (ADS)

To, Quy-Dong; Vu, Van-Huyen; Lauriat, Guy; Léonard, Céline

2015-10-01

The paper presents an interface model for gas flowing through a channel constituted of anisotropic wall surfaces. Using anisotropic scattering kernels and Chapman Enskog phase density, the boundary conditions (BCs) for velocity, temperature, and discontinuities including velocity slip and temperature jump at the wall are obtained. Two scattering kernels, Dadzie and Méolans (DM) kernel, and generalized anisotropic Cercignani-Lampis (ACL) are examined in the present paper, yielding simple BCs at the wall fluid interface. With these two kernels, we rigorously recover the analytical expression for orientation dependent slip shown in our previous works [Pham et al., Phys. Rev. E 86, 051201 (2012) and To et al., J. Heat Transfer 137, 091002 (2015)] which is in good agreement with molecular dynamics simulation results. More important, our models include both thermal transpiration effect and new equations for the temperature jump. While the same expression depending on the two tangential accommodation coefficients is obtained for slip velocity, the DM and ACL temperature equations are significantly different. The derived BC equations associated with these two kernels are of interest for the gas simulations since they are able to capture the direction dependent slip behavior of anisotropic interfaces.

Structured Kernel Dictionary Learning with Correlation Constraint for Object Recognition.

PubMed

Wang, Zhengjue; Wang, Yinghua; Liu, Hongwei; Zhang, Hao

2017-06-21

In this paper, we propose a new discriminative non-linear dictionary learning approach, called correlation constrained structured kernel KSVD, for object recognition. The objective function for dictionary learning contains a reconstructive term and a discriminative term. In the reconstructive term, signals are implicitly non-linearly mapped into a space, where a structured kernel dictionary, each sub-dictionary of which lies in the span of the mapped signals from the corresponding class, is established. In the discriminative term, by analyzing the classification mechanism, the correlation constraint is proposed in kernel form, constraining the correlations between different discriminative codes, and restricting the coefficient vectors to be transformed into a feature space, where the features are highly correlated inner-class and nearly independent between-classes. The objective function is optimized by the proposed structured kernel KSVD. During the classification stage, the specific form of the discriminative feature is needless to be known, while the inner product of the discriminative feature with kernel matrix embedded is available, and is suitable for a linear SVM classifier. Experimental results demonstrate that the proposed approach outperforms many state-of-the-art dictionary learning approaches for face, scene and synthetic aperture radar (SAR) vehicle target recognition.

Ambered kernels in stenospermocarpic fruit of eastern black walnut

Treesearch

Michele R. Warmund; J.W. Van Sambeek

2014-01-01

"Ambers" is a term used to describe poorly filled, shriveled eastern black walnut (Juglans nigra L.) kernels with a dark brown or black-colored pellicle that are unmarketable. Studies were conducted to determine the incidence of ambered black walnut kernels and to ascertain when symptoms were apparent in specific tissues. The occurrence of...

Antioxidant and antimicrobial activities of bitter and sweet apricot (Prunus armeniaca L.) kernels.

PubMed

Yiğit, D; Yiğit, N; Mavi, A

2009-04-01

The present study describes the in vitro antimicrobial and antioxidant activity of methanol and water extracts of sweet and bitter apricot (Prunus armeniaca L.) kernels. The antioxidant properties of apricot kernels were evaluated by determining radical scavenging power, lipid peroxidation inhibition activity and total phenol content measured with a DPPH test, the thiocyanate method and the Folin method, respectively. In contrast to extracts of the bitter kernels, both the water and methanol extracts of sweet kernels have antioxidant potential. The highest percent inhibition of lipid peroxidation (69%) and total phenolic content (7.9 +/- 0.2 microg/mL) were detected in the methanol extract of sweet kernels (Hasanbey) and in the water extract of the same cultivar, respectively. The antimicrobial activities of the above extracts were also tested against human pathogenic microorganisms using a disc-diffusion method, and the minimal inhibitory concentration (MIC) values of each active extract were determined. The most effective antibacterial activity was observed in the methanol and water extracts of bitter kernels and in the methanol extract of sweet kernels against the Gram-positive bacteria Staphylococcus aureus. Additionally, the methanol extracts of the bitter kernels were very potent against the Gram-negative bacteria Escherichia coli (0.312 mg/mL MIC value). Significant anti-candida activity was also observed with the methanol extract of bitter apricot kernels against Candida albicans, consisting of a 14 mm in diameter of inhibition zone and a 0.625 mg/mL MIC value.

Preparation of tamarind fruit seed activated carbon by microwave heating for the adsorptive treatment of landfill leachate: A laboratory column evaluation.

PubMed

Foo, K Y; Lee, L K; Hameed, B H

2013-04-01

The preparation of tamarind fruit seed granular activated carbon (TSAC) by microwave induced chemical activation for the adsorptive treatment of semi-aerobic landfill leachate has been attempted. The chemical and physical properties of TSAC were examined. A series of column tests were performed to determine the breakthrough characteristics, by varying the operational parameters, hydraulic loading rate (5-20 mL/min) and adsorbent bed height (15-21 cm). Ammonical nitrogen and chemical oxygen demand (COD), which provide a prerequisite insight into the prediction of leachate quality was quantified. Results illustrated an encouraging performance for the adsorptive removal of ammonical nitrogen and COD, with the highest bed capacity of 84.69 and 55.09 mg/g respectively, at the hydraulic loading rate of 5 mL/min and adsorbent bed height of 21 cm. The dynamic adsorption behavior was satisfactory described by the Thomas and Yoon-Nelson models. The findings demonstrated the applicability of TSAC for the adsorptive treatment of landfill leachate. Copyright © 2013 Elsevier Ltd. All rights reserved.

Acute cyanide toxicity caused by apricot kernel ingestion.

PubMed

Suchard, J R; Wallace, K L; Gerkin, R D

1998-12-01

A 41-year-old woman ingested apricot kernels purchased at a health food store and became weak and dyspneic within 20 minutes. The patient was comatose and hypothermic on presentation but responded promptly to antidotal therapy for cyanide poisoning. She was later treated with a continuous thiosulfate infusion for persistent metabolic acidosis. This is the first reported case of cyanide toxicity from apricot kernel ingestion in the United States since 1979.

Nutrition quality of extraction mannan residue from palm kernel cake on brolier chicken

NASA Astrophysics Data System (ADS)

Tafsin, M.; Hanafi, N. D.; Kejora, E.; Yusraini, E.

2018-02-01

This study aims to find out the nutrient residue of palm kernel cake from mannan extraction on broiler chicken by evaluating physical quality (specific gravity, bulk density and compacted bulk density), chemical quality (proximate analysis and Van Soest Test) and biological test (metabolizable energy). Treatment composed of T0 : palm kernel cake extracted aquadest (control), T1 : palm kernel cake extracted acetic acid (CH3COOH) 1%, T2 : palm kernel cake extracted aquadest + mannanase enzyme 100 u/l and T3 : palm kernel cake extracted acetic acid (CH3COOH) 1% + enzyme mannanase 100 u/l. The results showed that mannan extraction had significant effect (P<0.05) in improving the quality of physical and numerically increase the value of crude protein and decrease the value of NDF (Neutral Detergent Fiber). Treatments had highly significant influence (P<0.01) on the metabolizable energy value of palm kernel cake residue in broiler chickens. It can be concluded that extraction with aquadest + enzyme mannanase 100 u/l yields the best nutrient quality of palm kernel cake residue for broiler chicken.

The site, size, spatial stability, and energetics of an X-ray flare kernel

NASA Technical Reports Server (NTRS)

Petrasso, R.; Gerassimenko, M.; Nolte, J.

1979-01-01

The site, size evolution, and energetics of an X-ray kernel that dominated a solar flare during its rise and somewhat during its peak are investigated. The position of the kernel remained stationary to within about 3 arc sec over the 30-min interval of observations, despite pulsations in the kernel X-ray brightness in excess of a factor of 10. This suggests a tightly bound, deeply rooted magnetic structure, more plausibly associated with the near chromosphere or low corona rather than with the high corona. The H-alpha flare onset coincided with the appearance of the kernel, again suggesting a close spatial and temporal coupling between the chromospheric H-alpha event and the X-ray kernel. At the first kernel brightness peak its size was no larger than about 2 arc sec, when it accounted for about 40% of the total flare flux. In the second rise phase of the kernel, a source power input of order 2 times 10 to the 24th ergs/sec is minimally required.

Production of capsular polysaccharide from Escherichia coli K4 for biotechnological applications.

PubMed

Cimini, Donatella; Restaino, Odile Francesca; Catapano, Angela; De Rosa, Mario; Schiraldi, Chiara

2010-02-01

The production of industrially relevant microbial polysaccharides has recently gained much interest. The capsular polysaccharide of Escherichia coli K4 is almost identical to chondroitin, a commercially valuable biopolymer that is so far obtained from animal tissues entailing complex and expensive extraction procedures. In the present study, the production of capsular polysaccharide by E. coli K4 was investigated taking into consideration a potential industrial application. Strain physiology was first characterized in shake flask experiments to determine the optimal culture conditions for the growth of the microorganism and correlate it to polysaccharide production. Results show that the concentration of carbon source greatly affects polysaccharide production, while the complex nitrogen source is mainly responsible for the build up of biomass. Small-scale batch processes were performed to further evaluate the effect of the initial carbon source concentration and of growth temperatures on polysaccharide production, finally leading to the establishment of the medium to use in following fermentation experiments on a bigger scale. The fed-batch strategy next developed on a 2-L reactor resulted in a maximum cell density of 56 g(cww)/L and a titre of capsular polysaccharide equal to 1.4 g/L, approximately ten- and fivefold higher than results obtained in shake flask and 2-L batch experiments, respectively. The release kinetics of K4 polysaccharide into the medium were also explored to gain insight into the mechanisms underlying a complex aspect of the strain physiology.

Antioxidant and anticoagulant activity of sulfated polysaccharide from Gracilaria debilis (Forsskal).

PubMed

Sudharsan, Sadhasivam; Subhapradha, Namasivayam; Seedevi, Palaniappan; Shanmugam, Vairamani; Madeswaran, Perumal; Shanmugam, Annaian; Srinivasan, Alagiri

2015-11-01

Sulfated polysaccharide was isolated from Gracilaria debilis and purified through gel chromatography and their molecular weight was determined through AGE and PAGE. The total sugars in the crude, fractionated and purified polysaccharide were estimated as 52.65%, 59.70% and 67.60%, respectively. The ash and moisture content of crude and purified polysaccharide was found to be 14.2% and 23.5% and the polysaccharide was free from protein contamination. The sulfate and uronic acid contents in the crude, fractionated and purified were estimated as 14.08%, 15.33% and 16.01% and 10.12%, 13.56%, 16.70%. The elemental composition including carbon (crude - 23.12%, purified - 21.05%), hydrogen (crude - 3.4%, purified - 4.13%) and nitrogen (crude - 1.22%, purified - 0.56%) were also analyzed. The anticoagulant activity of the sulfated polysaccharide through APTT and PT was estimated at 14.11 and 8.23IU/mg. The purified polysaccharide with the molecular mass of 20kDa showed highest antioxidant activity (38.57%, 43.48% and 38.88%) in all the assays tested such as DPPH hydroxyl radical, superoxide radical, hydroxyl radical scavenging activities and the structural property was analyzed through FT-IR and (1)H NMR spectrum. The results together suggest that the isolated low molecular weight sulfated polysaccharide will demonstrate as a enormously available alternative natural source of antioxidant for industrial uses. Copyright © 2015 Elsevier B.V. All rights reserved.

Reduction of Aflatoxins in Apricot Kernels by Electronic and Manual Color Sorting.

PubMed

Zivoli, Rosanna; Gambacorta, Lucia; Piemontese, Luca; Solfrizzo, Michele

2016-01-19

The efficacy of color sorting on reducing aflatoxin levels in shelled apricot kernels was assessed. Naturally-contaminated kernels were submitted to an electronic optical sorter or blanched, peeled, and manually sorted to visually identify and sort discolored kernels (dark and spotted) from healthy ones. The samples obtained from the two sorting approaches were ground, homogenized, and analysed by HPLC-FLD for their aflatoxin content. A mass balance approach was used to measure the distribution of aflatoxins in the collected fractions. Aflatoxin B₁ and B₂ were identified and quantitated in all collected fractions at levels ranging from 1.7 to 22,451.5 µg/kg of AFB₁ + AFB₂, whereas AFG₁ and AFG₂ were not detected. Excellent results were obtained by manual sorting of peeled kernels since the removal of discolored kernels (2.6%-19.9% of total peeled kernels) removed 97.3%-99.5% of total aflatoxins. The combination of peeling and visual/manual separation of discolored kernels is a feasible strategy to remove 97%-99% of aflatoxins accumulated in naturally-contaminated samples. Electronic optical sorter gave highly variable results since the amount of AFB₁ + AFB₂ measured in rejected fractions (15%-18% of total kernels) ranged from 13% to 59% of total aflatoxins. An improved immunoaffinity-based HPLC-FLD method having low limits of detection for the four aflatoxins (0.01-0.05 µg/kg) was developed and used to monitor the occurrence of aflatoxins in 47 commercial products containing apricot kernels and/or almonds commercialized in Italy. Low aflatoxin levels were found in 38% of the tested samples and ranged from 0.06 to 1.50 μg/kg for AFB₁ and from 0.06 to 1.79 μg/kg for total aflatoxins.

Reduction of Aflatoxins in Apricot Kernels by Electronic and Manual Color Sorting

PubMed Central

Zivoli, Rosanna; Gambacorta, Lucia; Piemontese, Luca; Solfrizzo, Michele

2016-01-01

The efficacy of color sorting on reducing aflatoxin levels in shelled apricot kernels was assessed. Naturally-contaminated kernels were submitted to an electronic optical sorter or blanched, peeled, and manually sorted to visually identify and sort discolored kernels (dark and spotted) from healthy ones. The samples obtained from the two sorting approaches were ground, homogenized, and analysed by HPLC-FLD for their aflatoxin content. A mass balance approach was used to measure the distribution of aflatoxins in the collected fractions. Aflatoxin B1 and B2 were identified and quantitated in all collected fractions at levels ranging from 1.7 to 22,451.5 µg/kg of AFB1 + AFB2, whereas AFG1 and AFG2 were not detected. Excellent results were obtained by manual sorting of peeled kernels since the removal of discolored kernels (2.6%–19.9% of total peeled kernels) removed 97.3%–99.5% of total aflatoxins. The combination of peeling and visual/manual separation of discolored kernels is a feasible strategy to remove 97%–99% of aflatoxins accumulated in naturally-contaminated samples. Electronic optical sorter gave highly variable results since the amount of AFB1 + AFB2 measured in rejected fractions (15%–18% of total kernels) ranged from 13% to 59% of total aflatoxins. An improved immunoaffinity-based HPLC-FLD method having low limits of detection for the four aflatoxins (0.01–0.05 µg/kg) was developed and used to monitor the occurrence of aflatoxins in 47 commercial products containing apricot kernels and/or almonds commercialized in Italy. Low aflatoxin levels were found in 38% of the tested samples and ranged from 0.06 to 1.50 μg/kg for AFB1 and from 0.06 to 1.79 μg/kg for total aflatoxins. PMID:26797635

Gaussian processes with optimal kernel construction for neuro-degenerative clinical onset prediction

NASA Astrophysics Data System (ADS)

Canas, Liane S.; Yvernault, Benjamin; Cash, David M.; Molteni, Erika; Veale, Tom; Benzinger, Tammie; Ourselin, Sébastien; Mead, Simon; Modat, Marc

2018-02-01

Gaussian Processes (GP) are a powerful tool to capture the complex time-variations of a dataset. In the context of medical imaging analysis, they allow a robust modelling even in case of highly uncertain or incomplete datasets. Predictions from GP are dependent of the covariance kernel function selected to explain the data variance. To overcome this limitation, we propose a framework to identify the optimal covariance kernel function to model the data.The optimal kernel is defined as a composition of base kernel functions used to identify correlation patterns between data points. Our approach includes a modified version of the Compositional Kernel Learning (CKL) algorithm, in which we score the kernel families using a new energy function that depends both the Bayesian Information Criterion (BIC) and the explained variance score. We applied the proposed framework to model the progression of neurodegenerative diseases over time, in particular the progression of autosomal dominantly-inherited Alzheimer's disease, and use it to predict the time to clinical onset of subjects carrying genetic mutation.

A Comparative Study of Pairwise Learning Methods Based on Kernel Ridge Regression.

PubMed

Stock, Michiel; Pahikkala, Tapio; Airola, Antti; De Baets, Bernard; Waegeman, Willem

2018-06-12

Many machine learning problems can be formulated as predicting labels for a pair of objects. Problems of that kind are often referred to as pairwise learning, dyadic prediction, or network inference problems. During the past decade, kernel methods have played a dominant role in pairwise learning. They still obtain a state-of-the-art predictive performance, but a theoretical analysis of their behavior has been underexplored in the machine learning literature. In this work we review and unify kernel-based algorithms that are commonly used in different pairwise learning settings, ranging from matrix filtering to zero-shot learning. To this end, we focus on closed-form efficient instantiations of Kronecker kernel ridge regression. We show that independent task kernel ridge regression, two-step kernel ridge regression, and a linear matrix filter arise naturally as a special case of Kronecker kernel ridge regression, implying that all these methods implicitly minimize a squared loss. In addition, we analyze universality, consistency, and spectral filtering properties. Our theoretical results provide valuable insights into assessing the advantages and limitations of existing pairwise learning methods.

Isolation and partial characterization of immunostimulating polysaccharides from Imperata cylindrica.

PubMed

Pinilla, V; Luu, B

1999-08-01

The water-soluble crude extract prepared from Imperata cylindrica (Beauv.) was investigated for its immunomodulating activity. A set of polysaccharides with high molecular weights has been isolated by fractionation using gel filtration and anion-exchange chromatography. Each step of purification was monitored by bioassays. The presence of six monosaccharides has been established by chemical analysis. Quantitative analysis showed that the ratio of these monosaccharides differed from one polysaccharide to another. The crude extract as well as some of the purified polysaccharides enhance the proliferation of murine splenocytes.

A Novel Extreme Learning Machine Classification Model for e-Nose Application Based on the Multiple Kernel Approach

PubMed Central

Jian, Yulin; Huang, Daoyu; Yan, Jia; Lu, Kun; Huang, Ying; Wen, Tailai; Zeng, Tanyue; Zhong, Shijie; Xie, Qilong

2017-01-01

A novel classification model, named the quantum-behaved particle swarm optimization (QPSO)-based weighted multiple kernel extreme learning machine (QWMK-ELM), is proposed in this paper. Experimental validation is carried out with two different electronic nose (e-nose) datasets. Being different from the existing multiple kernel extreme learning machine (MK-ELM) algorithms, the combination coefficients of base kernels are regarded as external parameters of single-hidden layer feedforward neural networks (SLFNs). The combination coefficients of base kernels, the model parameters of each base kernel, and the regularization parameter are optimized by QPSO simultaneously before implementing the kernel extreme learning machine (KELM) with the composite kernel function. Four types of common single kernel functions (Gaussian kernel, polynomial kernel, sigmoid kernel, and wavelet kernel) are utilized to constitute different composite kernel functions. Moreover, the method is also compared with other existing classification methods: extreme learning machine (ELM), kernel extreme learning machine (KELM), k-nearest neighbors (KNN), support vector machine (SVM), multi-layer perceptron (MLP), radical basis function neural network (RBFNN), and probabilistic neural network (PNN). The results have demonstrated that the proposed QWMK-ELM outperforms the aforementioned methods, not only in precision, but also in efficiency for gas classification. PMID:28629202

A Novel Extreme Learning Machine Classification Model for e-Nose Application Based on the Multiple Kernel Approach.

PubMed

Jian, Yulin; Huang, Daoyu; Yan, Jia; Lu, Kun; Huang, Ying; Wen, Tailai; Zeng, Tanyue; Zhong, Shijie; Xie, Qilong

2017-06-19

A novel classification model, named the quantum-behaved particle swarm optimization (QPSO)-based weighted multiple kernel extreme learning machine (QWMK-ELM), is proposed in this paper. Experimental validation is carried out with two different electronic nose (e-nose) datasets. Being different from the existing multiple kernel extreme learning machine (MK-ELM) algorithms, the combination coefficients of base kernels are regarded as external parameters of single-hidden layer feedforward neural networks (SLFNs). The combination coefficients of base kernels, the model parameters of each base kernel, and the regularization parameter are optimized by QPSO simultaneously before implementing the kernel extreme learning machine (KELM) with the composite kernel function. Four types of common single kernel functions (Gaussian kernel, polynomial kernel, sigmoid kernel, and wavelet kernel) are utilized to constitute different composite kernel functions. Moreover, the method is also compared with other existing classification methods: extreme learning machine (ELM), kernel extreme learning machine (KELM), k-nearest neighbors (KNN), support vector machine (SVM), multi-layer perceptron (MLP), radical basis function neural network (RBFNN), and probabilistic neural network (PNN). The results have demonstrated that the proposed QWMK-ELM outperforms the aforementioned methods, not only in precision, but also in efficiency for gas classification.

Improved scatter correction using adaptive scatter kernel superposition

NASA Astrophysics Data System (ADS)

Sun, M.; Star-Lack, J. M.

2010-11-01

Accurate scatter correction is required to produce high-quality reconstructions of x-ray cone-beam computed tomography (CBCT) scans. This paper describes new scatter kernel superposition (SKS) algorithms for deconvolving scatter from projection data. The algorithms are designed to improve upon the conventional approach whose accuracy is limited by the use of symmetric kernels that characterize the scatter properties of uniform slabs. To model scatter transport in more realistic objects, nonstationary kernels, whose shapes adapt to local thickness variations in the projection data, are proposed. Two methods are introduced: (1) adaptive scatter kernel superposition (ASKS) requiring spatial domain convolutions and (2) fast adaptive scatter kernel superposition (fASKS) where, through a linearity approximation, convolution is efficiently performed in Fourier space. The conventional SKS algorithm, ASKS, and fASKS, were tested with Monte Carlo simulations and with phantom data acquired on a table-top CBCT system matching the Varian On-Board Imager (OBI). All three models accounted for scatter point-spread broadening due to object thickening, object edge effects, detector scatter properties and an anti-scatter grid. Hounsfield unit (HU) errors in reconstructions of a large pelvis phantom with a measured maximum scatter-to-primary ratio over 200% were reduced from -90 ± 58 HU (mean ± standard deviation) with no scatter correction to 53 ± 82 HU with SKS, to 19 ± 25 HU with fASKS and to 13 ± 21 HU with ASKS. HU accuracies and measured contrast were similarly improved in reconstructions of a body-sized elliptical Catphan phantom. The results show that the adaptive SKS methods offer significant advantages over the conventional scatter deconvolution technique.

Notes on a storage manager for the Clouds kernel

NASA Technical Reports Server (NTRS)

Pitts, David V.; Spafford, Eugene H.

1986-01-01

The Clouds project is research directed towards producing a reliable distributed computing system. The initial goal is to produce a kernel which provides a reliable environment with which a distributed operating system can be built. The Clouds kernal consists of a set of replicated subkernels, each of which runs on a machine in the Clouds system. Each subkernel is responsible for the management of resources on its machine; the subkernal components communicate to provide the cooperation necessary to meld the various machines into one kernel. The implementation of a kernel-level storage manager that supports reliability is documented. The storage manager is a part of each subkernel and maintains the secondary storage residing at each machine in the distributed system. In addition to providing the usual data transfer services, the storage manager ensures that data being stored survives machine and system crashes, and that the secondary storage of a failed machine is recovered (made consistent) automatically when the machine is restarted. Since the storage manager is part of the Clouds kernel, efficiency of operation is also a concern.

Metabolite identification through multiple kernel learning on fragmentation trees.

PubMed

Shen, Huibin; Dührkop, Kai; Böcker, Sebastian; Rousu, Juho

2014-06-15

Metabolite identification from tandem mass spectrometric data is a key task in metabolomics. Various computational methods have been proposed for the identification of metabolites from tandem mass spectra. Fragmentation tree methods explore the space of possible ways in which the metabolite can fragment, and base the metabolite identification on scoring of these fragmentation trees. Machine learning methods have been used to map mass spectra to molecular fingerprints; predicted fingerprints, in turn, can be used to score candidate molecular structures. Here, we combine fragmentation tree computations with kernel-based machine learning to predict molecular fingerprints and identify molecular structures. We introduce a family of kernels capturing the similarity of fragmentation trees, and combine these kernels using recently proposed multiple kernel learning approaches. Experiments on two large reference datasets show that the new methods significantly improve molecular fingerprint prediction accuracy. These improvements result in better metabolite identification, doubling the number of metabolites ranked at the top position of the candidates list. © The Author 2014. Published by Oxford University Press.

Efficient Multiple Kernel Learning Algorithms Using Low-Rank Representation.