1,054 research outputs found

    Mitral regurgitation as a phenotypic manifestation of nonphotosensitive trichothiodystrophy due to a splice variant in MPLKIP

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    Background: Nonphotosensitive trichothiodystrophy (TTDN) is a rare autosomal recessive disorder of neuroectodermal origin. The condition is marked by hair abnormalities, intellectual impairment, nail dystrophies and susceptibility to infections but with no UV sensitivity. Methods: We identified three consanguineous Pakistani families with varied TTDN features and used homozygosity mapping, linkage analysis, and Sanger and exome sequencing in order to identify pathogenic variants. Haplotype analysis was performed and haplotype age estimated. A splicing assay was used to validate the effect of the MPLKIP splice variant on expression. Results: Affected individuals from all families exhibit several TTDN features along with a heart-specific feature, i.e. mitral regurgitation. Exome sequencing in the probands from families ED168 and ED241 identified a homozygous splice mutation c.339 + 1G > A within MPLKIP. The same splice variant co-segregates with TTDN in a third family ED210. The MPLKIP splice variant was not found in public databases, e.g. the Exome Aggregation Consortium, and in unrelated Pakistani controls. Functional analysis of the splice variant confirmed intron retention, which leads to protein truncation and loss of a phosphorylation site. Haplotype analysis identified a 585.1-kb haplotype which includes the MPLKIP variant, supporting the existence of a founder haplotype that is estimated to be 25,900 years old. Conclusion: This study extends the allelic and phenotypic spectra of MPLKIP-related TTDN, to include a splice variant that causes cardiomyopathy as part of the TTDN phenotype

    Synthesis and in silico study of 2-furyl(4-{4-[(substituted)sulfonyl]benzyl}-1-piperazinyl)methanone derivatives as suitable therapeutic agents

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    Abstract In the study presented here, a new series of 2-furyl(4-{4-[(substituted)sulfonyl]benzyl}-1-piperazinyl)methanone derivatives was targeted. The synthesis was initiated by the treatment of different secondary amines (1a-h) with 4-bromomethylbenzenesulfonyl chloride (2) to obtain various 1-{[4-(bromomethyl)phenyl]sulfonyl}amines (3a-h). 2-Furyl(1-piperazinyl)methanone (2-furoyl-1-piperazine; 4) was then dissolved in acetonitrile, with the addition of K2CO3, and the mixture was refluxed for activation. This activated molecule was further treated with equi-molar amounts of 3a-h to form targeted 2-furyl(4-{4-[(substituted)sulfonyl]benzyl}-1-piperazinyl)methanone derivatives (5a-h) in the same reaction set up. The structure confirmation of all the synthesized compounds was carried out by EI-MS, IR and 1H-NMR spectral analysis. The compounds showed good enzyme inhibitory activity. Compound 5h showed excellent inhibitory effect against acetyl- and butyrylcholinesterase with respective IC50 values of 2.91±0.001 and 4.35±0.004 μM, compared to eserine, a reference standard with IC50 values of 0.04±0.0001 and 0.85±0.001 μM, respectively, against these enzymes. All synthesized molecules were active against almost all Gram-positive and Gram-negative bacterial strains tested. The cytotoxicity of the molecules was also checked to determine their utility as possible therapeutic agents

    Burnout among surgeons before and during the SARS-CoV-2 pandemic: an international survey

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    Background: SARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice. Methods: This is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure. Results: Nine hundred fifty-four surgeons completed the survey. The median length of practice was 10 years; 78.2% included were male with a median age of 37 years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout. There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management. Conclusions: There was a significant burnout among trainees. Almost all aspects of clinical and research activities were affected with a significant reduction in the volume of research, outpatient clinic visits, surgical procedures, on-call hours, and emergency cases hindering the training. Trial registration: The study was registered on clicaltrials.gov "NCT04433286" on 16/06/2020

    The development and validation of a scoring tool to predict the operative duration of elective laparoscopic cholecystectomy.

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    Population-level risks of alcohol consumption by amount, geography, age, sex, and year: a systematic analysis for the Global Burden of Disease Study 2020

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    BACKGROUND: The health risks associated with moderate alcohol consumption continue to be debated. Small amounts of alcohol might lower the risk of some health outcomes but increase the risk of others, suggesting that the overall risk depends, in part, on background disease rates, which vary by region, age, sex, and year. METHODS: For this analysis, we constructed burden-weighted dose-response relative risk curves across 22 health outcomes to estimate the theoretical minimum risk exposure level (TMREL) and non-drinker equivalence (NDE), the consumption level at which the health risk is equivalent to that of a non-drinker, using disease rates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2020 for 21 regions, including 204 countries and territories, by 5-year age group, sex, and year for individuals aged 15-95 years and older from 1990 to 2020. Based on the NDE, we quantified the population consuming harmful amounts of alcohol. FINDINGS: The burden-weighted relative risk curves for alcohol use varied by region and age. Among individuals aged 15-39 years in 2020, the TMREL varied between 0 (95% uncertainty interval 0-0) and 0·603 (0·400-1·00) standard drinks per day, and the NDE varied between 0·002 (0-0) and 1·75 (0·698-4·30) standard drinks per day. Among individuals aged 40 years and older, the burden-weighted relative risk curve was J-shaped for all regions, with a 2020 TMREL that ranged from 0·114 (0-0·403) to 1·87 (0·500-3·30) standard drinks per day and an NDE that ranged between 0·193 (0-0·900) and 6·94 (3·40-8·30) standard drinks per day. Among individuals consuming harmful amounts of alcohol in 2020, 59·1% (54·3-65·4) were aged 15-39 years and 76·9% (73·0-81·3) were male. INTERPRETATION: There is strong evidence to support recommendations on alcohol consumption varying by age and location. Stronger interventions, particularly those tailored towards younger individuals, are needed to reduce the substantial global health loss attributable to alcohol. FUNDING: Bill & Melinda Gates Foundation

    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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