bluuebunny/crossref_metadata_2025_split huggingface dataset:
Risk factors associated with Ahmed valve implant dysfunction in patients with neovascular glaucoma during the first postoperative year
Authors: Ureña-Wong K. , Jimenez-Román J. , Rivas-Ruiz R. , Morales-Gonzalez J A. 
Published: May 2022

AbstractBackgroundThe current surgical management of Neovascular Glaucoma (NVG) is with the placement of the Ahmed Valve. However, up to 70% fail and the factors associated with this failure are unknown. Recognizing the factors associated with dysfunction will help to identify patients prone to failure promptly to establish prompt management and improve visual and functional prognosis.ObjectiveTo determine the risk factors associated with Ahmed valve dysfunction in patients with NVG during the first year after surgery.PopulationPatients diagnosed with VNG who have undergone Ahmed valve implantation in the Glaucoma - APEC service, during the 2013 to 2019 period.Methodsambispective cohort. Patients with NVG defined as the Presence of neovessels in the iris or angle of the anterior chamber were included, those who had a history of implantation of a drainage device, and patients with a diagnosis of glaucoma in the terminal phase, worse visual acuity of perception were excluded. of light. The research unit was eyes subjected to Ahmed valve implantation. The demographic characteristics of the patients were evaluated, as well as the characteristics of the eyes.The primary outcome and the secondary outcomes were adverse events, visual acuity, and final intraocular pressure. An unadjusted Cox proportional hazards model was used to determine risk factors such as Hazzard ratios (HR). Those significant factors were included in a Cox proportional hazards model to adjust for the main confounding variables.Results174 eyes were included. Baseline intraocular pressure (IOP) was 46.03 (±11.8) mmHG. Baseline VA in LogMAR was 1.52(0.89-2.3). Risk factors were: Age <50 years with HR 1.54(95% CI 1.04-2.30); HB1Ac >8% HR 1.71 (95% CI 1.12-2.60) and presence hypertensive phase HR 3.13 (95% CI 1.57-6.23). The multivariate model was adjusted for the following variables, baseline IOP less than 40mmHg HR 1.60 (95% CI 1.04-2.47); HB1Ac >8% HR 1.80 (95% CI 1.16-2.78); FP7 valve type HR 1.75(95% CI 1.04-2.94) and presence of hypertensive phase HR 3.24 (95% CI 1.60-6.59).ConclusionBasal IOP less than 40mmHg, HB1Ac >8%, type of FP7 valve, surgery performed by a resident, lack of photocoagulation after implantation, and the presence of a hypertensive phase are the independent risk factors for implant valvular dysfunction.
Low serum levels of magnesium, phosphate, and zinc in ICU patients – prevalence, management, characteristics, and outcomes Protocol and statistical analysis plan for The WhyTrace cohort study
Authors: Vesterlund Gitte Kingo , Thorsen-Meyer Hans-Christian , Kaas-Hansen Benjamin Skov , Møller Morten Hylander , Perner Anders 
Published: May 2022

AbstractBackgroundPatients admitted to the intensive care unit often have low serum levels of magnesium, phosphate, and zinc. We aim to describe the prevalence, management, characteristics, and outcomes of patients with low levels of these minerals in a large cohort of Danish ICU patients.MethodsIn this multicenter cohort, we will include all adult ICU patients admitted to one of 10 ICUs during a six years period. Patients will be excluded if the ICU admission is post-operative after planned surgery, length of stay is <24 hours, they are transferred from ICUs not participating in the study, or are without measurements of neither magnesium, phosphate nor zinc. First, we will do a descriptive assessment of the prevalence of low serum levels and management of supplementation according to different patient characteristics. Second, we will conduct a cohort study using prospectively registered outcome data, to assess associations between serum levels of magnesium, phosphate, and zinc respectively, and each of two principal outcomes: time to successful extubation and incident tachyarrhythmia. We will use a joint modelling approach for estimating the strengths of associations, combining time to event data and longitudinal data from repeated measurements of serum levels.DiscussionThis study will provide information from a very large cohort of Danish ICU patients. Strengths of the study will be the large number of patients, the interconnection of data from several registers, and for the association analysis the use of a statistical approach making the optimal use of the repeated measures of serum levels. Limitations will be the risk of bias from unmeasured or unregistered confounding factors, and the lack of randomization in the observational design, which will prevent us from interpreting possible associations between serum levels and outcomes as definite effects on the outcome.
UDCA and INT-777 suppress cardiac fibrosis triggered by IL-11 through involvement of TGR5
Authors: Reilly-O’Donnell B. , Ferraro E. , Tikhomirov R. , Nunez-Toldra R. , Shchendrygina A. , Patel L. , Wu Y. , Mitchell A. L. , Endo A. , Adorini L. , Chowdhury R. A. , Srivastava P. K. , Ng F. S. , Terracciano C. M. , Williamson C. , Gorelik J. 
Published: May 2022

AbstractCardiac fibrosis occurs in a wide range of cardiac diseases and is characterised by the transdifferentiation of cardiac fibroblasts (FB) into myofibroblasts (MFB). Myofibroblasts produce large quantities of extracellular matrix proteins, resulting in myocardial scar. The antifibrotic effect of the bile acid ursodeoxycholic acid (UDCA) is established in cases of liver fibrosis but not the adult myocardium.Our hypothesis is: UDCA is antifibrotic in the adult heart, mediated by the membrane bile acid receptor Takeda G protein-coupled receptor 5 (TGR5).We constructed a predictive network of fibrosis using RNA-seq datasets. We found that UDCA and it’s analogue INT-777, both reduced MFB markers in rat and human FBs and living myocardial slices (LMS). Utilising a knock-out mouse model, we show that the antifibrotic effect of UDCA is mediated by TGR5. Finally, we performed RNA-seq upon UDCA-treated human FB and integrated with our network of fibrosis, establishing the mechanism of TGR5 agonists.
Multi-omics Mendelian randomisation using expression, splicing and protein quantitative trait loci: identification of novel drug targets for gliomagenesis
Authors: Thornton Zak A , Andrews Lily J , Zhao Huiling , Zheng Jie , Paternoster Lavinia , Robinson Jamie W , Kurian Kathreena M 
Published: May 2022

AbstractBackgroundGenetic variants associated with molecular traits that are also associated with liability to glioma can provide causal evidence for the prioritisation of these traits as candidate drug targets.MethodsWe performed two-sample Mendelian randomisation and genetic colocalisation of a large panel of molecular traits on glioma. Molecular data were taken from studies of expression quantitative trait loci (QTL) [11,985 genes]; splicing QTL [13,285 genes] and protein QTL [7,376 proteins] derived from 15 brain tissues. Glioma summary-level data was extracted from a genome-wide association meta-analysis of 12,496 cases and 18,190 controls.ResultsOur MR analysis showed evidence for a causal effect of 85 molecular traits on glioma – 37 were robust according to colocalisation and Steiger filtering. We found causal evidence for 10 genes previously associated with glioma risk. We identified one novel genetic locus with strong causal evidence in the gene expression analysis:HBEGF(5q31.3) in all glioma [OR 1.36 (95%CI 1.19 to 1.55); P = 4.41 x 10-6]. We also identified three novel genetic loci with strong causal evidence in the splicing variation analysis:CEP192(18p11.21) in glioblastoma [OR 4.40 (95%CI 2.28 to 8.48); P = 9.78 x 10-4];FAIM(3q22.3) in all glioma [OR 2.72 to 3.43; P = 1.03 x 10-5to 1.09 x 10-5] andSLC8A1(2p22.1) in all glioma [OR 0.37 (95%CI 0.24 to 0.56; P = 5.72 x 10-6].ConclusionsWe provide robust causal evidence for genes previously associated with glioma risk in genome-wide association studies, as well as four novel genes.
Performance study of a point-of-care antigen test during the SARS-CoV-2 Delta to Omicron variant transition in the USA
Authors: Drain Paul K , Chiklis Gregory , Guest Poppy , Lindner Nigel M , Ellis Jayne E 
Published: May 2022

AbstractIntroductionConcerns have been raised regarding the accuracy of diagnostic antigen testing for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant. We compared the performance of the LumiraDx SARS-CoV-2 Antigen Test between symptomatic participants recruited prospectively during the Delta to Omicron variant transition in the USA.MethodsTwo paired anterior nasal swabs were collected from each participant (adults and children) within 12 days of symptom onset between November 24th, 2021 and February 1st, 2022, during which time Omicron replaced Delta as the dominant variant in the sample population. Swabs were tested by the LumiraDx SARS-CoV-2 Antigen Test and compared using real-time polymerase chain reaction (RT-PCR) reference testing. Reference samples identified as positive were sequenced to identify the SARS-CoV-2 variant. Positive percent agreement (PPA) was calculated, with results stratified by RT-PCR cycle threshold (Ct).ResultsOf the 38 participants for whom LumiraDx SARS-CoV-2 Antigen Test results were available, 36 were confirmed positive by RT-PCR. Overall, PPA of the LumiraDx SARS-CoV-2 Antigen Test was 94.7% (95% confidence interval: 82.3%, 99.4%) and PPA was 100% for samples with a Ct <33. Sufficient viral load for sequencing was present in nine samples (six Delta, three Omicron), all of which returned a positive result using the LumiraDx SARS-CoV-2 Antigen Test. There were no performance differences observed between participants with the Delta and Omicron variants.ConclusionsSARS-CoV-2 differences between Delta and Omicron variant mutations did not affect the performance of the LumiraDx SARS-CoV-2 Antigen Test which detects the nucleocapsid protein antigen. The LumiraDx SARS-CoV-2 Antigen Test can be a useful antigen test to diagnose emerging variants of coronavirus disease 2019.
The impact of trade and investment agreements on the implementation non-communicable disease policies, 2014-2019: protocol for a statistical study
Authors: Barlow P. , Allen L. 
Published: May 2022

AbstractIntroductionRegulating tobacco, alcohol, and unhealthy foods and drinks is a cornerstone of global efforts to combat the Non-Communicable Disease (NCD) pandemic, but implementation of these policies remains slow. It has been suggested that producers of these unhealthy commodities use rules in Trade and Investment Agreements (TIAs) to delay and undermine NCD policy implementation. Yet, there is no systematic empirical evidence linking TIA participation to reduced implementation. Here we present a study protocol for a statistical analysis of the relationship between TIA participation and the implementation of regulations on tobacco, alcohol, and unhealthy food and drink in 154 countries, 2014-2019.Methods and analysisWe aim to examine whether participation in TIAs with the EU and US is associated with implementation of regulations targeting tobacco, alcohol, and unhealthy food and drink. We focus on TIAs with these countries as their TIAs create multiple opportunities to contest health regulations, and a majority of the major unhealthy commodity producers are registered in these jurisdictions. Partial and full implementation is captured in a recently published dataset which systematically coded implementation of 11 NCD policies in 2014, 2016 and 2019. We will combine these outcome data with TIA membership and covariate data from multiple sources. We will calculate descriptive statistics and use both regression adjustment and matching to conduct covariate-adjusted, quasi-experimental comparisons of implementation levels and progress according to whether or not countries have a TIA with the EU or US. Further analyses and robustness checks will examine additional TIA participation arrangements and test the sensitivity of our results to our model specifications.Ethics and disseminationEthics approval will not be required as the study uses anonymised and pre-aggregated data. Findings will be disseminated to policymakers via personal contacts and press releases in parallel with scientific papers and conference presentations.FundingThis research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.
Humoral immune responses against SARS-CoV-2 Spike variants after mRNA vaccination in solid organ transplant recipients
Authors: Tauzin Alexandra , Beaudoin-Bussières Guillaume , Gong Shang Yu , Chatterjee Debashree , Gendron-Lepage Gabrielle , Bourassa Catherine , Goyette Guillaume , Racine Normand , Khrifi Zineb , Turgeon Julie , Tremblay Cécile , Martel-Laferrière Valérie , Kaufmann Daniel E. , Cloutier Marc , Bazin Renée , Duerr Ralf , Dieudé Mélanie , Hébert Marie-Josée , Finzi Andrés 
Published: May 2022

SUMMARYWhile SARS-CoV-2 mRNA vaccination has been shown to be safe and effective in the general population, immunocompromised solid organ transplant recipients (SOTR) were reported to have impaired immune responses after one or two doses of vaccine. In this study, we examined humoral responses induced after the second and the third dose of mRNA vaccine in different SOTR (kidney, liver, lung and heart). Compared to a cohort of SARS-CoV-2 naïve immunocompetent health care workers (HCW), the second dose induced weak humoral responses in SOTR, except for the liver recipients. The third dose boosted these responses but they did not reach the same level as in HCW. Interestingly, while the neutralizing activity against Delta and Omicron variants remained very low after the third dose, Fc-mediated effector functions in SOTR reached similar levels as in the HCW cohort. Whether these responses will suffice to protect SOTR from severe outcome remains to be determined.
Neuroinflammation in neuronopathic Gaucher disease: Role of microglia and NK cells
Authors: Boddupalli Chandra Sekhar , Nair Shiny , Belinsky Glenn , Gans Joseph , Teeple Erin , Nguyen Tri-Hung , Mehta Sameet , Guo Lilu , Kramer Martin L , Ruan Jiapeng , Wang Hongge , Davison Matthew , Vidyadhara D.J , Bailin Zhang , Klinger Katherine , Mistry Pramod K. 
Published: May 2022

AbstractBackgroundNeuronopathic Gaucher Disease (nGD) is a rare neurodegenerative disorder caused by biallelic mutations in Gba, and buildup of glycosphingolipids in lysosomes. Neuronal injury and cell death are prominent pathological features, however the role of Gba in individual cell types and involvement of microglia, blood derived macrophages and immune infiltrates in nGD pathology remains enigmatic.MethodsHere, using single cell resolution of mouse nGD brains, we found induction of neuroinflammation pathways involving microglia, NK cells, astrocytes, and neurons.ResultsTargeted rescue of Gba in microglia and in neurons, respectively in Gba deficient, nGD mice reversed the buildup of glucosylceramide (GlcCer) and glucosylsphingosine (GlcSph), concomitant with amelioration of neuroinflammation, reduced level of serum neurofilament light chain (Nf-L) and improved survival. The levels of bioactive lipid, GlcSph was strongly correlated with serum Nf-L and ApoE in nGD mouse models as well as GD patients. Gba rescue in microglia/macrophage compartment prolonged survival, that was further enhanced upon treatment with brain permeant inhibitor of glucosylceramide synthase, effects mediated via improved glycosphingolipid homeostasis and reversal of neuroinflammation involving activation of microglia, brain macrophages and NK cells.ConclusionsTogether, our study delineates individual cellular effects of Gba deficiency in nGD brains, highlighting the central role of neuroinflammation driven by microglia activation and the role of brain permeant small molecule glucosylceramide inhibitor in reversing complex multidimensional pathophysiology of nGD. Our findings advance disease biology whilst identifying compelling biomarkers of nGD to improve patient management, enrich clinical trials and illuminate therapeutic targets.Funding:Research grant from Sanofi Genzyme; other support includes R01NS110354.Yale Liver Center P30DK034989, pilot project grant.
Shedding Light on functional Near Infrared Spectroscopy and Open Science Practices
Authors: Kelsey Caroline M. , Taylor Jebediah , Pirazzoli Laura , Lorenzo Renata Di , Sullivan Eileen F. , Nelson Charles A. 
Published: May 2022

AbstractOpen science practices work to increase methodological rigor, transparency, and replicability of published findings. This review aims to reflect and commemorate what the functional Near Infrared Spectroscopy (fNIRS) community has done to promote open science practices in fNIRS research and set goals to accomplish over the next ten years.
Novel sterol binding domains in bacteria
Authors: Zhai Liting , Bonds Amber C. , Smith Clyde A. , Oo Hannah , Chou Jonathan Chiu-Chun , Welander Paula V. , Dassama Laura M. K. 
Published: May 2022

AbstractSterol lipids are widely present in eukaryotes and play essential roles in signaling and modulating membrane fluidity. Although rare, some bacteria also produce sterols, but their function in bacteria is not known. Moreover, many more species, including pathogens and commensal microbes, acquire or modify sterols from eukaryotic hosts through poorly understood molecular mechanisms. The aerobic methanotrophMethylococcus capsulatuswas the first bacterium shown to synthesize sterols, producing a mixture of C-4 methylated sterols that are distinct from those observed in eukaryotes. C-4 methylated sterols are synthesized in the cytosol and localized to the outer membrane, suggesting that a bacterial sterol transport machinery exists. Until now, the identity of such machinery remained a mystery. In this study, we identified three novel proteins that may be the first examples of transporters for bacterial sterol lipids. The proteins, which all belong to well-studied families of bacterial metabolite transporters, are predicted to reside in the inner membrane, periplasm, and outer membrane ofM. capsulatus,and may work as a conduit to move modified sterols to the outer membrane. Quantitative analysis of ligand binding revealed their remarkable specificity for 4-methylsterols, and crystallographic structures coupled with docking and molecular dynamics simulations revealed the structural bases for substrate binding by two of the putative transporters. Their striking structural divergence from eukaryotic sterol transporters signals that they form a distinct sterol transport system within the bacterial domain. Finally, bioinformatics revealed the widespread presence of similar transporters in bacterial genomes, including in some pathogens that use host sterol lipids to construct their cell envelopes. The unique folds of these bacterial sterol binding proteins should now guide the discovery of other proteins that handle this essential metabolite.
Comprehensive machine-learning survival framework develop a consensus model in large scale multi-center cohorts for pancreatic cancer
Authors: Wang Libo , Liu Zaoqu , Liang Ruopeng , Wang Weijie , Zhu Rongtao , Li Jian , Xing Zhe , Weng Siyuan , Han Xinwei , Sun Yuling 
Published: May 2022

AbstractBackgroundAs the most aggressive tumor, the outcome of pancreatic cancer (PACA) has not improved observably over the last decade. Anatomy-based TNM staging does not exactly identify treatment-sensitive patients, and an ideal biomarker is urgently needed for precision medicine.MethodsA total of 1280 patients from 10 multi-center cohorts were enrolled. 10 machine-learning algorithms were transformed into 76 combinations, which were performed to construct an artificial intelligence-derived prognostic signature (AIDPS). The predictive performance, multi-omic alterations, immune landscape, and clinical significance of AIDPS were further explored.ResultsBased on 10 independent cohorts, we screened 32 consensus prognostic genes via univariate Cox regression. According to the criterion with the largest average C-index in the nine validation sets, we selected the optimal algorithm to construct the AIDPS. After incorporating several vital clinicopathological features and 86 published signatures, AIDPS exhibited robust and dramatically superior predictive capability. Moreover, in other prevalent digestive system tumors, the 9-gene AIDPS could still accurately stratify the prognosis. Of note, our AIDPS had important clinical implications for PACA, and patients with low AIDPS owned a dismal prognosis, relatively high frequency of mutations and copy number alterations, and denser immune cell infiltrates as well as were more sensitive to immunotherapy. Correspondingly, the high AIDPS group possessed dramatically prolonged survival, and panobinostat might be a potential agent for patients with high AIDPS.ConclusionsThe AIDPS could accurately predict the prognosis and immunotherapy efficacy of PACA, which might become an attractive tool to further guide the stratified management and individualized treatment.FundingThis study was supported by the National Natural Science Foundation of China (No. 81870457, 82172944).
Studying protein-protein interaction through side-chain modeling method OPUS-Mut
Authors: Xu Gang , Wang Yilin , Wang Qinghua , Ma Jianpeng 
Published: May 2022

AbstractProtein side chains are vitally important to many biological processes such as protein-protein interaction. In this study, we evaluate the performance of our previous released side-chain modeling method OPUS-Mut, together with some other methods, on three oligomer datasets, CASP14 (11), CAMEO-Homo (65), and CAMEO-Hetero (21). The results show that OPUS-Mut outperforms other methods measured by all residues or by the interfacial residues. We also demonstrate our method on evaluating protein-protein docking pose on a dataset Oligomer-Dock (75) created using the top 10 predictions from ZDOCK 3.0.2. Our scoring function correctly identifies the native pose as the top-1 in 45 out of 75 targets. Different from traditional scoring functions, our method is based on the overall side-chain packing favorableness in accordance with the local packing environment. It emphasizes the significance of side chains and provides a new and effective scoring term for studying protein-protein interaction.
Feature Importance Network reveals novel functional relationships between biological features inArabidopsis thaliana
Authors: Ng Jonathan Wei Xiong , Chua Swee Kwang , Mutwil Marek 
Published: May 2022

AbstractUnderstanding how the different cellular components are working together to form a living cell requires multidisciplinary approaches combining molecular and computational biology. Machine learning shows great potential in life sciences, as it has the ability to find novel relationships between biological features. Here, we constructed a dataset of 11,801 gene features for 31,522Arabidopsis thalianagenes, and developed a machine learning workflow to identify linked features. The detected linked features are visualised as a Feature Important Network (FIN), which can be mined to reveal a variety of novel biological insights pertaining to gene function. We demonstrate how FIN can be used to generate novel insights into gene function. To make this network easily accessible to the scientific community, we present the FINder database, available at finder.plant.tools (http://finder.plant.tools/).