809 research outputs found

    Identification of protein carbonyls in serum of the fetal and neonatal pig

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    Oxidation of serum proteins leads to non-reversible carbonyl formation which alters their function and is associated with stress-related disease processes. The primary objective of this study was to quantify and identify oxidized serum proteins in fetal and newborn piglets. Protein carbonyls were converted to hydrazones with dinitrophenyl hydrazine and quantified spectrophotometrically. For identification, serum protein carbonyls were derivatized with biotin hydrazide, separated by 2D PAGE and stained with FITCavidin. Biotin-labeled proteins were excised from gels and identified by mass spectrometry. At birth, carbonyls were determined to be ∼600 pmole/mg serum protein. Fetuses at 50 and 100 days of gestation had similar levels of protein carbonyls as newborns. Carbonyl levels were also similar for control and runt (birth) piglets between 1 and 21 days of age; however, distribution of many proteins varied by age and was also influenced by birth weight. Major oxidized proteins identified in fetal (f) and newborn (n) pigs included; albumin (f, n), transferrin (f, n), fetuin-A (f, n) alpha fetoprotein (f, n), plasminogen (f, n), fetuin-B (f), alpha-1-antitrypsin (f, n) alpha-1-acid glycoprotein (f) and immunoglobulins (n). While abundance and distribution of oxidized proteins changed over time, these changes appear to primarily reflect relative amounts of those proteins in serum

    Purification and Biochemical Characterization of Polygalacturonase Produced by Penicillium expansum During Postharvest Decay of 'Anjou' Pear

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    A polygalacturonase (PG) was extracted and purified from decayed tissue of 'Anjou' pear fruit inoculated with Penicillium expansum. Ammonium sulfate precipitation, gel filtration, and cation exchange chromatography were used to purify the enzyme. Both chromatographic methods revealed a single peak corresponding to PG activity. PG enzyme activity from healthy and wounded pear tissue was undetectable, which supports the claim that the purified PG is of fungal origin. The purified enzyme had a molecular mass of 41 kDa and a pI of 7.8. Activity of the PG was not associated with a glycosylated protein. The enzyme was active over a broad pH range from 3 to 6, with optimal activity at 4.5 in sodium citrate and sodium acetate buffers. The optimal temperature for activity was 37 degrees C but the enzyme was also active at 0, 5, 10, 20, and 50 degrees C. Thin-layer chromatographic analysis of PG hydrolysis products showed that the enzyme exhibits endo- and exo-activity. The purified enzyme macerated tissue in vitro causing approximate to 30% reduction in mass of pear plugs compared with approximate to 17% reduction for apple. Additionally, it produced 1.5-fold more soluble polyuronides on pear than apple tissue. This work shows for the first time the production of a PG by P. expansum during postharvest decay of pear fruit is different from the previously described PG produced in decayed apple fruit by the same pathogen

    A Robust Determination of the Time Delay in 0957+561A,B and a Measurement of the Global Value of Hubble's Constant

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    Photometric monitoring of the gravitational lens system 0957+561A,B in the g and r bands with the Apache Point Observatory (APO) 3.5 m telescope during 1996 shows a sharp g band event in the trailing (B) image light curve at the precise time predicted from the observation of an event during 1995 in the leading (A) image with a delay of 415 days. This success confirms the "short delay," and the lack of any feature at a delay near 540 days rejects the "long delay" for this system, resolving a long-standing controversy. A series of statistical analyses of our light curve data yield a best fit delay of 417 +/- 3 days (95% confidence interval). Recent improvements in the modeling of the lens system (consisting of a galaxy and cluster) allow us to derive a value of the global (at z = 0.36) value of Hubble's constant H_0 using Refsdal's method, a simple and direct distance determination based on securely understood physics and geometry. The result is H_0 = 63 +/- 12 km/s/Mpc (for Omega = 1) where this 95% confidence interval is dominated by remaining lens model uncertainties.Comment: accepted by ApJ, AASTeX 4.0 preprint, 4 PostScript figure

    Fluid Accumulation After Neonatal Congenital Cardiac Surgery; Clinical Implications and Outcomes

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    BACKGROUND To determine the association between fluid balance metrics and mortality and other postoperative outcomes after neonatal cardiac surgery in a contemporary multi-center cohort. METHODS Observational cohort study across 22 hospitals in neonates (≤30 days) undergoing cardiac surgery. We explored overall % fluid overload, postoperative day 1 % fluid overload, peak % fluid overload, and time to first negative daily fluid balance. The primary outcome was in-hospital mortality. Secondary outcomes included postoperative duration of mechanical ventilation, and intensive care unit (ICU) and hospital length of stay. Multivariable logistic or negative binomial regression was used to determine independent associations between fluid overload variables and each outcome. RESULTS The cohort included 2223 patients. In-hospital mortality was 3.9% (n=87). Overall median peak % fluid overload was 4.9%, (interquartile range 0.4-10.5%). Peak % fluid overload and postoperative day 1 % fluid overload were not associated with primary or secondary outcomes. Hospital resource utilization increased on each successive day of not achieving a first negative daily fluid balance and was characterized by longer duration of mechanical ventilation (incidence rate ratio 1.11, 95% confidence interval 1.08-1.14, ICU length of stay (incidence rate ratio 1.08, 95% confidence interval 1.03-1.12), and hospital length of stay (incidence rate ratio 1.09, 95% confidence interval 1.05-1.13). CONCLUSIONS Time to first negative daily fluid balance, but not % fluid overload is associated with improved postoperative outcomes in neonates after cardiac surgery. Specific treatments to achieve an early negative fluid balance may decrease postoperative care durations

    Potential causal association between gut microbiome and posttraumatic stress disorder

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    Funding Information: We thank the participants and working staff including the Psychiatric Genomics Consortium Posttraumatic Stress Disorder Working Group, the FinnGen consortium, and the MiBioGen consortium. Publisher Copyright: © 2024, The Author(s).Background: The causal effects of gut microbiome and the development of posttraumatic stress disorder (PTSD) are still unknown. This study aimed to clarify their potential causal association using mendelian randomization (MR). Methods: The summary-level statistics for gut microbiome were retrieved from a genome-wide association study (GWAS) of the MiBioGen consortium. As to PTSD, the Freeze 2 datasets were originated from the Psychiatric Genomics Consortium Posttraumatic Stress Disorder Working Group (PGC-PTSD), and the replicated datasets were obtained from FinnGen consortium. Single nucleotide polymorphisms meeting MR assumptions were selected as instrumental variables. The inverse variance weighting (IVW) method was employed as the main approach, supplemented by sensitivity analyses to evaluate potential pleiotropy and heterogeneity and ensure the robustness of the MR results. We also performed reverse MR analyses to explore PTSD’s causal effects on the relative abundances of specific features of the gut microbiome. Results: In Freeze 2 datasets from PGC-PTSD, eight bacterial traits revealed a potential causal association between gut microbiome and PTSD (IVW, all P < 0.05). In addition, Genus.Dorea and genus.Sellimonas were replicated in FinnGen datasets, in which eight bacterial traits revealed a potential causal association between gut microbiome and the occurrence of PTSD. The heterogeneity and pleiotropy analyses further supported the robustness of the IVW findings, providing additional evidence for their reliability. Conclusion: Our study provides the potential causal impact of gut microbiomes on the development of PTSD, shedding new light on the understanding of the dysfunctional gut-brain axis in this disorder. Our findings present novel evidence and call for investigations to confirm the association between their links, as well as to illuminate the underlying mechanisms.publishersversionpublishe

    Enhancing Discovery of Genetic Variants for Posttraumatic Stress Disorder Through Integration of Quantitative Phenotypes and Trauma Exposure Information

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    Funding Information: This work was supported by the National Institute of Mental Health / U.S. Army Medical Research and Development Command (Grant No. R01MH106595 [to CMN, IL, MBS, KJRe, and KCK], National Institutes of Health (Grant No. 5U01MH109539 to the Psychiatric Genomics Consortium ), and Brain & Behavior Research Foundation (Young Investigator Grant [to KWC]). Genotyping of samples was provided in part through the Stanley Center for Psychiatric Genetics at the Broad Institute supported by Cohen Veterans Bioscience . Statistical analyses were carried out on the LISA/Genetic Cluster Computer ( https://userinfo.surfsara.nl/systems/lisa ) hosted by SURFsara. This research has been conducted using the UK Biobank resource (Application No. 41209). This work would have not been possible without the financial support provided by Cohen Veterans Bioscience, the Stanley Center for Psychiatric Genetics at the Broad Institute, and One Mind. Funding Information: MBS has in the past 3 years received consulting income from Actelion, Acadia Pharmaceuticals, Aptinyx, Bionomics, BioXcel Therapeutics, Clexio, EmpowerPharm, GW Pharmaceuticals, Janssen, Jazz Pharmaceuticals, and Roche/Genentech and has stock options in Oxeia Biopharmaceuticals and Epivario. In the past 3 years, NPD has held a part-time paid position at Cohen Veterans Bioscience, has been a consultant for Sunovion Pharmaceuticals, and is on the scientific advisory board for Sentio Solutions for unrelated work. In the past 3 years, KJRe has been a consultant for Datastat, Inc., RallyPoint Networks, Inc., Sage Pharmaceuticals, and Takeda. JLM-K has received funding and a speaking fee from COMPASS Pathways. MU has been a consultant for System Analytic. HRK is a member of the Dicerna scientific advisory board and a member of the American Society of Clinical Psychopharmacology Alcohol Clinical Trials Initiative, which during the past 3 years was supported by Alkermes, Amygdala Neurosciences, Arbor Pharmaceuticals, Dicerna, Ethypharm, Indivior, Lundbeck, Mitsubishi, and Otsuka. HRK and JG are named as inventors on Patent Cooperative Treaty patent application number 15/878,640, entitled “Genotype-guided dosing of opioid agonists,” filed January 24, 2018. RP and JG are paid for their editorial work on the journal Complex Psychiatry. OAA is a consultant to HealthLytix. All other authors report no biomedical financial interests or potential conflicts of interest. Funding Information: This work was supported by the National Institute of Mental Health/ U.S. Army Medical Research and Development Command (Grant No. R01MH106595 [to CMN, IL, MBS, KJRe, and KCK], National Institutes of Health (Grant No. 5U01MH109539 to the Psychiatric Genomics Consortium), and Brain & Behavior Research Foundation (Young Investigator Grant [to KWC]). Genotyping of samples was provided in part through the Stanley Center for Psychiatric Genetics at the Broad Institute supported by Cohen Veterans Bioscience. Statistical analyses were carried out on the LISA/Genetic Cluster Computer (https://userinfo.surfsara.nl/systems/lisa) hosted by SURFsara. This research has been conducted using the UK Biobank resource (Application No. 41209). This work would have not been possible without the financial support provided by Cohen Veterans Bioscience, the Stanley Center for Psychiatric Genetics at the Broad Institute, and One Mind. This material has been reviewed by the Walter Reed Army Institute of Research. There is no objection to its presentation and/or publication. The opinions or assertions contained herein are the private views of the authors and are not to be construed as official or as reflecting true views of the U.S. Department of the Army or the Department of Defense. We thank the investigators who comprise the PGC-PTSD working group and especially the more than 206,000 research participants worldwide who shared their life experiences and biological samples with PGC-PTSD investigators. We thank Mark Zervas for his critical input. Full acknowledgments are in Supplement 1. MBS has in the past 3 years received consulting income from Actelion, Acadia Pharmaceuticals, Aptinyx, Bionomics, BioXcel Therapeutics, Clexio, EmpowerPharm, GW Pharmaceuticals, Janssen, Jazz Pharmaceuticals, and Roche/Genentech and has stock options in Oxeia Biopharmaceuticals and Epivario. In the past 3 years, NPD has held a part-time paid position at Cohen Veterans Bioscience, has been a consultant for Sunovion Pharmaceuticals, and is on the scientific advisory board for Sentio Solutions for unrelated work. In the past 3 years, KJRe has been a consultant for Datastat, Inc. RallyPoint Networks, Inc. Sage Pharmaceuticals, and Takeda. JLM-K has received funding and a speaking fee from COMPASS Pathways. MU has been a consultant for System Analytic. HRK is a member of the Dicerna scientific advisory board and a member of the American Society of Clinical Psychopharmacology Alcohol Clinical Trials Initiative, which during the past 3 years was supported by Alkermes, Amygdala Neurosciences, Arbor Pharmaceuticals, Dicerna, Ethypharm, Indivior, Lundbeck, Mitsubishi, and Otsuka. HRK and JG are named as inventors on Patent Cooperative Treaty patent application number 15/878,640, entitled ?Genotype-guided dosing of opioid agonists,? filed January 24, 2018. RP and JG are paid for their editorial work on the journal Complex Psychiatry. OAA is a consultant to HealthLytix. All other authors report no biomedical financial interests or potential conflicts of interest. Publisher Copyright: © 2021 Society of Biological PsychiatryBackground: Posttraumatic stress disorder (PTSD) is heritable and a potential consequence of exposure to traumatic stress. Evidence suggests that a quantitative approach to PTSD phenotype measurement and incorporation of lifetime trauma exposure (LTE) information could enhance the discovery power of PTSD genome-wide association studies (GWASs). Methods: A GWAS on PTSD symptoms was performed in 51 cohorts followed by a fixed-effects meta-analysis (N = 182,199 European ancestry participants). A GWAS of LTE burden was performed in the UK Biobank cohort (N = 132,988). Genetic correlations were evaluated with linkage disequilibrium score regression. Multivariate analysis was performed using Multi-Trait Analysis of GWAS. Functional mapping and annotation of leading loci was performed with FUMA. Replication was evaluated using the Million Veteran Program GWAS of PTSD total symptoms. Results: GWASs of PTSD symptoms and LTE burden identified 5 and 6 independent genome-wide significant loci, respectively. There was a 72% genetic correlation between PTSD and LTE. PTSD and LTE showed largely similar patterns of genetic correlation with other traits, albeit with some distinctions. Adjusting PTSD for LTE reduced PTSD heritability by 31%. Multivariate analysis of PTSD and LTE increased the effective sample size of the PTSD GWAS by 20% and identified 4 additional loci. Four of these 9 PTSD loci were independently replicated in the Million Veteran Program. Conclusions: Through using a quantitative trait measure of PTSD, we identified novel risk loci not previously identified using prior case-control analyses. PTSD and LTE have a high genetic overlap that can be leveraged to increase discovery power through multivariate methods.publishersversionpublishe

    AI is a viable alternative to high throughput screening: a 318-target study

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    : High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery
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