Process for preparing tapes from thermoplastic polymers and carbon fibers

The instant invention involves a process for use in preparing tapes or rovings, which are formed from a thermoplastic material used to impregnate longitudinally extended bundles of carbon fibers. The process involves the steps of (a) gas spreading a tow of carbon fibers; (b) feeding the spread tow into a crosshead die; (c) impregnating the tow in the die with a thermoplastic polymer; (d) withdrawing the impregnated tow from the die; and (e) gas cooling the impregnated tow with a jet of air. The crosshead die useful in the instant invention includes a horizontally extended, carbon fiber bundle inlet channel, means for providing melted polymer under pressure to the die, means for dividing the polymeric material flowing into the die into an upper flow channel and a lower flow channel disposed above and below the moving carbon fiber bundle, means for applying the thermoplastic material from both the upper and lower channels to the fiber bundle, and means for withdrawing the resulting tape from the die

Protein co-expression network analysis (ProCoNA)

Abstract Background Biological networks are important for elucidating disease etiology due to their ability to model complex high dimensional data and biological systems. Proteomics provides a critical data source for such models, but currently lacks robust de novo methods for network construction, which could bring important insights in systems biology. Results We have evaluated the construction of network models using methods derived from weighted gene co-expression network analysis (WGCNA). We show that approximately scale-free peptide networks, composed of statistically significant modules, are feasible and biologically meaningful using two mouse lung experiments and one human plasma experiment. Within each network, peptides derived from the same protein are shown to have a statistically higher topological overlap and concordance in abundance, which is potentially important for inferring protein abundance. The module representatives, called eigenpeptides, correlate significantly with biological phenotypes. Furthermore, within modules, we find significant enrichment for biological function and known interactions (gene ontology and protein-protein interactions). Conclusions Biological networks are important tools in the analysis of complex systems. In this paper we evaluate the application of weighted co-expression network analysis to quantitative proteomics data. Protein co-expression networks allow novel approaches for biological interpretation, quality control, inference of protein abundance, a framework for potentially resolving degenerate peptide-protein mappings, and a biomarker signature discovery

Free 25-Hydroxyvitamin D: Impact of Vitamin D Binding Protein Assays on Racial-Genotypic Associations

Context: Total 25-hydroxyvitamin D (25OHD) is a marker of vitamin D status and is lower in African Americans than in whites. Whether this difference holds for free 25OHOD (f25OHD) is unclear, considering reported genetic-racial differences in vitamin D binding protein (DBP) used to calculate f25OHD.  Objectives: Our objective was to assess racial-geographic differences in f25OHD and to understand inconsistencies in racial associations with DBP and calculated f25OHD.  Design: This study used a cross-sectional design.  Setting: The general community in the United States, United Kingdom, and The Gambia were included in this study.  Participants: Men in Osteoporotic Fractures in Men and Medical Research Council studies (N = 1057) were included.  Exposures: Total 25OHD concentration, race, and DBP (GC) genotype exposures were included.  Outcome Measures: Directly measured f25OHD, DBP assessed by proteomics, monoclonal and polyclonal immunoassays, and calculated f25OHD were the outcome measures.  Results: Total 25OHD correlated strongly with directly measured f25OHD (Spearman r = 0.84). Measured by monoclonal assay, mean DBP in African-ancestry subjects was approximately 50% lower than in whites, whereas DBP measured by polyclonal DBP antibodies or proteomic methods was not lower in African-ancestry. Calculated f25OHD (using polyclonal DBP assays) correlated strongly with directly measured f25OHD (r = 0.80–0.83). Free 25OHD, measured or calculated from polyclonal DBP assays, reflected total 25OHD concentration irrespective of race and was lower in African Americans than in US whites.  Conclusions: Previously reported racial differences in DBP concentration are likely from monoclonal assay bias, as there was no racial difference in DBP concentration by other methods. This confirms the poor vitamin D status of many African-Americans and the utility of total 25OHD in assessing vitamin D in the general population

Identification of novel loci associated with hip shape:a meta-analysis of genome-wide association studies

This study was funded by Arthritis Research UK project grant 20244, which also provided salary funding for DB and CVG. LP works in the MRC Integrative Epidemiology Unit, a UK MRC‐funded unit (MC_ UU_ 12013/4 & MC_UU_12013/5). ALSPAC: We are extremely grateful to all the families who took part in this study, the midwives for their help in recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists, and nurses. ALSPAC data collection was supported by the Wellcome Trust (grants WT092830M; WT088806; WT102215/2/13/2), UK Medical Research Council (G1001357), and University of Bristol. The UK Medical Research Council and the Wellcome Trust (102215/2/13/2) and the University of Bristol provide core support for ALSPAC. Framingham Heart Study: The Framingham Osteoporosis Study is supported by grants from the National Institute of Arthritis, Musculoskeletal, and Skin Diseases and the National Institute on Aging (R01 AR41398, R01 AR 061162, R01 AR050066, and R01 AR061445). The analyses reflect intellectual input and resource development from the Framingham Heart Study investigators participating in the SNP Health Association Resource project. The Framingham Heart Study of the National Heart, Lung, and Blood Institute of the National Institutes of Health and Boston University School of Medicine were supported by the National Heart, Lung, and Blood Institute's Framingham Heart Study (N01‐HC‐25195) and its contract with Affymetrix, Inc., for genotyping services (N02‐HL‐6‐4278). Analyses reflect intellectual input and resource development from the Framingham Heart Study investigators participating in the SNP Health Association Resource (SHARe) project. A portion of this research was conducted using the Linux Cluster for Genetic Analysis (LinGA‐II) funded by the Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center. DK was also supported by Israel Science Foundation grant #1283/14. TDC and DR thank Dr Claire Reardon and the entire Harvard University Bauer Core facility for assistance with ATAC‐seq next generation sequencing. This work was funded in part by the Harvard University Milton Fund, NSF (BCS‐1518596), and NIH NIAMS (1R01AR070139‐01A1) to TDC. MrOS: The Osteoporotic Fractures in Men (MrOS) Study is supported by National Institutes of Health funding. The following institutes provide support: the National Institute on Aging (NIA), the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), the National Center for Advancing Translational Sciences (NCATS), and NIH Roadmap for Medical Research under the following grant numbers: U01 AG027810, U01 AG042124, U01 AG042139, U01 AG042140, U01 AG042143, U01 AG042145, U01 AG042168, U01 AR066160, and UL1 TR000128. The National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) provides funding for the MrOS ancillary study “Replication of candidate gene associations and bone strength phenotype in MrOS” under the grant number R01 AR051124. The National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) provides funding for the MrOS ancillary study “GWAS in MrOS and SOF” under the grant number RC2 AR058973. SOF: The Study of Osteoporotic Fractures (SOF) is supported by National Institutes of Health funding. The National Institute on Aging (NIA) provides support under the following grant numbers: R01 AG005407, R01 AR35582, R01 AR35583, R01 AR35584, R01 AG005394, R01 AG027574, and R01 AG027576. TwinsUK: The study was funded by the Wellcome Trust; European Community's Seventh Framework Programme (FP7/2007‐2013). The study also receives support from the National Institute for Health Research (NIHR)‐funded BioResource, Clinical Research Facility, and Biomedical Research Centre based at Guy's and St Thomas’ NHS Foundation Trust in partnership with King's College London. SNP genotyping was performed by The Wellcome Trust Sanger Institute and National Eye Institute via NIH/CIDR. This study was also supported by the Australian National Health and Medical Research Council (project grants 1048216 and 1127156), the Sir Charles Gairdner Hospital RAC (SGW), and the iVEC/Pawsey Supercomputing Centre (project grants Pawsey0162 and Director2025 [SGW]). The salary of BHM was supported by a Raine Medical Research Foundation Priming Grant. The Umeå Fracture and Osteoporosis Study (UFO) is supported by the Swedish Research Council (K20006‐72X‐20155013), the Swedish Sports Research Council (87/06), the Swedish Society of Medicine, the Kempe‐Foundation (JCK‐1021), and by grants from the Medical Faculty of Umeå Unviersity (ALFVLL:968:22‐2005, ALFVL:‐937‐2006, ALFVLL:223:11‐2007, and ALFVLL:78151‐2009) and from the county council of Västerbotten (Spjutspetsanslag VLL:159:33‐2007). This publication is the work of the authors and does not necessarily reflect the views of any funders. None of the funders had any influence on data collection, analysis, interpretation of the results, or writing of the paper. DB will serve as the guarantor of the paper. Authors’ roles: Study conception and design: DAB, JSG, RMA, LP, DK, and JHT. Data collection: DJ, DPK, ESO, SRC, NEL, BHM, FMKW, JBR, SGW, TDC, BGF, DAL, CO, and UP‐L. Data analysis: DAB, DSE, FKK, JSG, FRS, CVG, RJB, RMA, SGW, EG, TDC, DR, and TB. Data interpretation: JSG, RMA, TDC, DR, DME, LP, DK, and JHT. Drafting manuscript: DAB and JHT. Revising manuscript content: JHT. All authors approved the final version of manuscript. DAB takes responsibility for the integrity of the data analysis.Peer reviewedPublisher PD

A framework for future national pediatric pandemic respiratory disease severity triage: The HHS pediatric COVID-19 data challenge

Abstract Introduction: With persistent incidence, incomplete vaccination rates, confounding respiratory illnesses, and few therapeutic interventions available, COVID-19 continues to be a burden on the pediatric population. During a surge, it is difficult for hospitals to direct limited healthcare resources effectively. While the overwhelming majority of pediatric infections are mild, there have been life-threatening exceptions that illuminated the need to proactively identify pediatric patients at risk of severe COVID-19 and other respiratory infectious diseases. However, a nationwide capability for developing validated computational tools to identify pediatric patients at risk using real-world data does not exist. Methods: HHS ASPR BARDA sought, through the power of competition in a challenge, to create computational models to address two clinically important questions using the National COVID Cohort Collaborative: (1) Of pediatric patients who test positive for COVID-19 in an outpatient setting, who are at risk for hospitalization? (2) Of pediatric patients who test positive for COVID-19 and are hospitalized, who are at risk for needing mechanical ventilation or cardiovascular interventions? Results: This challenge was the first, multi-agency, coordinated computational challenge carried out by the federal government as a response to a public health emergency. Fifty-five computational models were evaluated across both tasks and two winners and three honorable mentions were selected. Conclusion: This challenge serves as a framework for how the government, research communities, and large data repositories can be brought together to source solutions when resources are strapped during a pandemic

Genetic determinants of heel bone properties: genome-wide association meta-analysis and replication in the GEFOS/GENOMOS consortium

Quantitative ultrasound of the heel captures heel bone properties that independently predict fracture risk and, with bone mineral density (BMD) assessed by X-ray (DXA), may be convenient alternatives for evaluating osteoporosis and fracture risk. We performed a meta-analysis of genome-wide association (GWA) studies to assess the genetic determinants of heel broadband ultrasound attenuation (BUA; n = 14 260), velocity of sound (VOS; n = 15 514) and BMD (n = 4566) in 13 discovery cohorts. Independent replication involved seven cohorts with GWA data (in silico n = 11 452) and new genotyping in 15 cohorts (de novo n = 24 902). In combined random effects, meta-analysis of the discovery and replication cohorts, nine single nucleotide polymorphisms (SNPs) had genome-wide significant (P < 5 × 10(-8)) associations with heel bone properties. Alongside SNPs within or near previously identified osteoporosis susceptibility genes including ESR1 (6q25.1: rs4869739, rs3020331, rs2982552), SPTBN1 (2p16.2: rs11898505), RSPO3 (6q22.33: rs7741021), WNT16 (7q31.31: rs2908007), DKK1 (10q21.1: rs7902708) and GPATCH1 (19q13.11: rs10416265), we identified a new locus on chromosome 11q14.2 (rs597319 close to TMEM135, a gene recently linked to osteoblastogenesis and longevity) significantly associated with both BUA and VOS (P < 8.23 × 10(-14)). In meta-analyses involving 25 cohorts with up to 14 985 fracture cases, six of 10 SNPs associated with heel bone properties at P < 5 × 10(-6) also had the expected direction of association with any fracture (P < 0.05), including three SNPs with P < 0.005: 6q22.33 (rs7741021), 7q31.31 (rs2908007) and 10q21.1 (rs7902708). In conclusion, this GWA study reveals the effect of several genes common to central DXA-derived BMD and heel ultrasound/DXA measures and points to a new genetic locus with potential implications for better understanding of osteoporosis pathophysiology

New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk

To increase our understanding of the genetic basis of adiposity and its links to cardiometabolic disease risk, we conducted a genome-wide association meta-analysis of body fat percentage (BF%) in up to 100,716 individuals. Twelve loci reached genome-wide significance (P<5 × 10−8), of which eight were previously associated with increased overall adiposity (BMI, BF%) and four (in or near COBLL1/GRB14, IGF2BP1, PLA2G6, CRTC1) were novel associations with BF%. Seven loci showed a larger effect on BF% than on BMI, suggestive of a primary association with adiposity, while five loci showed larger effects on BMI than on BF%, suggesting association with both fat and lean mass. In particular, the loci more strongly associated with BF% showed distinct cross-phenotype association signatures with a range of cardiometabolic traits revealing new insights in the link between adiposity and disease risk

A Validated Age-Related Normative Model for Male Total Testosterone Shows Increasing Variance but No Decline after Age 40 Years

The diagnosis of hypogonadism in human males includes identification of low serum testosterone levels, and hence there is an underlying assumption that normal ranges of testosterone for the healthy population are known for all ages. However, to our knowledge, no such reference model exists in the literature, and hence the availability of an applicable biochemical reference range would be helpful for the clinical assessment of hypogonadal men. In this study, using model selection and validation analysis of data identified and extracted from thirteen studies, we derive and validate a normative model of total testosterone across the lifespan in healthy men. We show that total testosterone peaks [mean (2.5-97.5 percentile)] at 15.4 (7.2-31.1) nmol/L at an average age of 19 years, and falls in the average case [mean (2.5-97.5 percentile)] to 13.0 (6.6-25.3) nmol/L by age 40 years, but we find no evidence for a further fall in mean total testosterone with increasing age through to old age. However we do show that there is an increased variation in total testosterone levels with advancing age after age 40 years. This model provides the age related reference ranges needed to support research and clinical decision making in males who have symptoms that may be due to hypogonadism.Publisher PDFPeer reviewe

Large meta-analysis of genome-wide association studies identifies five loci for lean body mass

Lean body mass, consisting mostly of skeletal muscle, is important for healthy aging. We performed a genome-wide association study for whole body (20 cohorts of European ancestry with n = 38,292) and appendicular (arms and legs) lean body mass (n = 28,330) measured using dual energy X-ray absorptiometry or bioelectrical impedance analysis, adjusted for sex, age, height, and fat mass. Twenty-one single-nucleotide polymorphisms were significantly associated with lean body mass either genome wide (p < 5 x 10(-8)) or suggestively genome wide (p < 2.3 x 10(-6)). Replication in 63,475 (47,227 of European ancestry) individuals from 33 cohorts for whole body lean body mass and in 45,090 (42,360 of European ancestry) subjects from 25 cohorts for appendicular lean body mass was successful for five single-nucleotide polymorphisms in/ near HSD17B11, VCAN, ADAMTSL3, IRS1, and FTO for total lean body mass and for three single-nucleotide polymorphisms in/ near VCAN, ADAMTSL3, and IRS1 for appendicular lean body mass. Our findings provide new insight into the genetics of lean body mass

New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk

To increase our understanding of the genetic basis of adiposity and its links to cardiometabolic disease risk, we conducted a genome-wide association meta-analysis of body fat percentage (BF%) in up to 100,716 individuals. Twelve loci reached genome-wide significance (P <5 x 10(-8)), of which eight were previously associated with increased overall adiposity (BMI, BF%) and four (in or near COBLL1/GRB14, IGF2BP1, PLA2G6, CRTC1) were novel associations with BF%. Seven loci showed a larger effect on BF% than on BMI, suggestive of a primary association with adiposity, while five loci showed larger effects on BMI than on BF%, suggesting association with both fat and lean mass. In particular, the loci more strongly associated with BF% showed distinct cross-phenotype association signatures with a range of cardiometabolic traits revealing new insights in the link between adiposity and disease risk.Peer reviewe