bluuebunny/crossref_metadata_2025_split huggingface dataset:
Atomistic simulations suggest dietary flavonoids from Beta vulgaris (beet) as promising inhibitors of human angiotensin-converting enzyme and 2-alpha-adrenergic receptors in hypertension
Authors: Adetunji Joy A , Ogunyemi Oludare M , Gyebi Gideon A , Adewumi Anuoluwapo E , Olaiya Charles O 
Published: September 2023

Abstract

Motivation
Beta vulgaris (beet) is extensively reported for its antihypertensive activity. However, the mechanismunderpinning its antihypertensive activity is not well understood. In this study, we evaluated the in silico interactionsof 70 compounds derived from beta vulgaris against the active sites of angiotensin-converting enzyme (ACE) and alpha-adrenergic receptor (AR).

Results
Structure-based virtual screening against angiotensin-converting enzyme revealed that, Cochliophilin A (−9.0 Kcal/mol), Miraxanthin (−8.3 Kcal/mol), and quercimeritrin (−9.7 Kcal/mol) had lower docking scores than the reference lisinopril (−7.9 Kcal/mol). These compounds exhibited dual binding tendency as they also ranked top compounds upon screening against adrenergic receptor. The thermodynamic parameters computed from the resulting trajectories obtained from the 100 ns full atomistic molecular dynamics simulation revealed structural stability and conformational flexibility of the ligand–receptor complexes as indicated by the RMSD, RMSF, RoG, SASA, and H-bond calculations. The molecular mechanics with generalized Born and surface area solvation binding energy calculations revealed that the proteins exhibit considerable binding energy with the phytochemicals in a dynamic environment. Furthermore, the hit compounds possess good physicochemical properties and drug-likeness. Overall, cochliophilin and quercimeritrin are promising dual-target directed flavonoids from Beta vulgaris; and are suggested for further experimental and preclinical evaluation.

Availability and implementation
All data was provided in the manuscript.
GOAT: Gene-level biomarker discovery from multi-Omics data using graph ATtention neural network for eosinophilic asthma subtype
Authors: Jeong Dabin , Koo Bonil , Oh Minsik , Kim Tae-Bum , Kim Sun 
Published: September 2023

Abstract

Motivation
Asthma is a heterogeneous disease where various subtypes are established and molecular biomarkers of the subtypes are yet to be discovered. Recent availability of multi-omics data paved a way to discover molecular biomarkers for the subtypes. However, multi-omics biomarker discovery is challenging because of the complex interplay between different omics layers.

Results
We propose a deep attention model named Gene-level biomarker discovery from multi-Omics data using graph ATtention neural network (GOAT) for identifying molecular biomarkers for eosinophilic asthma subtypes with multi-omics data. GOAT identifies genes that discriminate subtypes using a graph neural network by modeling complex interactions among genes as the attention mechanism in the deep learning model. In experiments with multi-omics profiles of the COREA (Cohort for Reality and Evolution of Adult Asthma in Korea) asthma cohort of 300 patients, GOAT outperforms existing models and suggests interpretable biological mechanisms underlying asthma subtypes. Importantly, GOAT identified genes that are distinct only in terms of relationship with other genes through attention. To better understand the role of biomarkers, we further investigated two transcription factors, CTNNB1 and JUN, captured by GOAT. We were successful in showing the role of the transcription factors in eosinophilic asthma pathophysiology in a network propagation and transcriptional network analysis, which were not distinct in terms of gene expression level differences.

Availability and implementation
Source code is available https://github.com/DabinJeong/Multi-omics_biomarker. The preprocessed data underlying this article is accessible in data folder of the github repository. Raw data are available in Multi-Omics Platform at http://203.252.206.90:5566/, and it can be accessible when requested.
Unbiased curriculum learning enhanced global-local graph neural network for protein thermodynamic stability prediction
Authors: Gong Haifan , Zhang Yumeng , Dong Chenhe , Wang Yue , Chen Guanqi , Liang Bilin , Li Haofeng , Liu Lanxuan , Xu Jie , Li Guanbin 
Published: September 2023

Abstract

Motivation
Proteins play crucial roles in biological processes, with their functions being closely tied to thermodynamic stability. However, measuring stability changes upon point mutations of amino acid residues using physical methods can be time-consuming. In recent years, several computational methods for protein thermodynamic stability prediction (PTSP) based on deep learning have emerged. Nevertheless, these approaches either overlook the natural topology of protein structures or neglect the inherent noisy samples resulting from theoretical calculation or experimental errors.

Results
We propose a novel Global-Local Graph Neural Network powered by Unbiased Curriculum Learning for the PTSP task. Our method first builds a Siamese graph neural network to extract protein features before and after mutation. Since the graph’s topological changes stem from local node mutations, we design a local feature transformation module to make the model focus on the mutated site. To address model bias caused by noisy samples, which represent unavoidable errors from physical experiments, we introduce an unbiased curriculum learning method. This approach effectively identifies and re-weights noisy samples during the training process. Extensive experiments demonstrate that our proposed method outperforms advanced protein stability prediction methods, and surpasses state-of-the-art learning methods for regression prediction tasks.

Availability and implementation
All code and data is available at https://github.com/haifangong/UCL-GLGNN.
Using a novel structure/function approach to select diverse swine major histocompatibility complex 1 alleles to predict epitopes for vaccine development
Authors: Khatooni Zahed , Teymourian Navid , Wilson Heather L 
Published: September 2023

Abstract

Motivation
Swine leukocyte antigens (SLAs) (i.e. swine major histocompatibility complex proteins) conduct a fundamental role in swine immunity. To generate a protective vaccine across an outbred species, such as pigs, it is critical that epitopes that bind to diverse SLA alleles are used in the vaccine development process. We introduced a new strategy for epitope prediction.

Results
We employed molecular dynamics simulation to identify key amino acids for interactions with epitopes. We developed an algorithm wherein each SLA-1 is compared to a crystalized reference allele with unique weighting for non-conserved amino acids based on R group and position. We then performed homology modeling and electrostatic contact mapping to visualize how relatively small changes in sequences impacted the charge distribution in the binding site. We selected eight diverse SLA-1 alleles and performed homology modeling followed, by protein–peptide docking and binding affinity analyses, to identify porcine reproductive and respiratory syndrome virus matrix protein epitopes that bind with high affinity to these alleles. We also performed docking analysis on the epitopes identified as strong binders using NetMHCpan 4.1. Epitopes predicted to bind to our eight SLA-1 alleles had equivalent or higher energetic interactions than those predicted to bind to the NetMHCpan 4.1 allele repertoire. This approach of selecting diverse SLA-1 alleles, followed by homology modeling, and docking simulations, can be used as a novel strategy for epitope prediction that complements other available tools and is especially useful when available tools do not offer a prediction for SLAs/major histocompatibility complex.

Availability and implementation
The data underlying this article are available in the online Supplementary Material.
DeepUMQA3: a web server for accurate assessment of interface residue accuracy in protein complexes
Authors: Liu Jun , Liu Dong , Zhang Gui-Jun 
Published: September 2023

Abstract

Motivation
Model quality assessment is a crucial part of protein structure prediction and a gateway to proper usage of models in biomedical applications. Many methods have been proposed for assessing the quality of structural models of protein monomers, but few methods for evaluating protein complex models. As protein complex structure prediction becomes a new challenge, there is an urgent need for model quality assessment methods that can accurately assess the accuracy of interface residues of complex structures.

Results
Here, we present DeepUMQA3, a web server for evaluating the accuracy of interface residues of protein complex structures using deep neural networks. For an input complex structure, features are extracted from three levels of overall complex, intra-monomer, and inter-monomer, and an improved deep residual neural network is used to predict per-residue lDDT and interface residue accuracy. DeepUMQA3 ranks first in the blind test of interface residue accuracy estimation in CASP15, with Pearson, Spearman, and AUC of 0.564, 0.535, and 0.755 under the lDDT measurement, which are 17.6%, 23.6%, and 10.9% higher than the second best method, respectively. DeepUMQA3 can also assess the accuracy of all residues in the entire complex and distinguish high- and low-precision residues.

Availability and implementation
The web sever of DeepUMQA3 are freely available at http://zhanglab-bioinf.com/DeepUMQA_server/.
Soluble TREM2 triggers microglial dysfunction in neuromyelitis optica spectrum disorders
Authors: Qin Chuan , Chen Man , Dong Ming-Hao , Yang Sheng , Zhang Hang , You Yun-Fan , Zhou Luo-Qi , Chu Yun-Hui , Tang Yue , Pang Xiao-Wei , Wu Long-Jun , Tian Dai-Shi , Wang Wei 
Published: September 2023

Abstract
Microglia-mediated neuroinflammation contributes to acute demyelination in neuromyelitis optica spectrum disorders (NMOSD). Soluble triggering receptor expressed on myeloid cells 2 (sTREM2) in the CSF has been associated with microglial activation in several neurodegenerative diseases. However, the basis for this immune-mediated attack and the pathophysiological role of sTREM2 in NMOSD remain to be elucidated.
Here, we performed Mendelian randomization analysis and identified a genetic association between increased CSF sTREM2 and NMOSD risk. CSF sTREM2 was elevated in patients with NMOSD and was positively correlated with neural injury and other neuroinflammation markers. Single-cell RNA sequencing of human macrophage/microglia-like cells in CSF, a proxy for microglia, showed that increased CSF sTREM2 was positively associated with microglial dysfunction in patients with NMOSD. Furthermore, we demonstrated that sTREM2 is a reliable biomarker of microglial activation in a mouse model of NMOSD. Using unbiased transcriptomic and lipidomic screens, we identified that excessive activation, overwhelmed phagocytosis of myelin debris, suppressed lipid metabolism and enhanced glycolysis underlie sTREM2-mediated microglial dysfunction, possibly through the nuclear factor kappa B (NF-κB) signalling pathway.
These molecular and cellular findings provide a mechanistic explanation for the genetic association between CSF sTREM2 and NMOSD risk and indicate that sTREM2 could be a potential biomarker of NMOSD progression and a therapeutic target for microglia-mediated neuroinflammation.
Kū Kia‘i Kahuku: indigenizing social media, civic streaming, and sociospatial symmetry
Authors: Burroughs Benjamin , Ka‘ili Tēvita O 
Published: September 2023

Abstract
This research critiques Western approaches to social media by using an Indigenous theoretical tool/concept, the Moanan (Pacific Islander) conception of tā and vā, to center Indigenous knowledge through an analysis of the Kū Kiaʻi Kahuku community movement (an Indigenous and ecological stand for environmental justice to protect native species and push back against colonial development in the form of giant wind turbines (568 feet high) placed over schools and the homes of community members and Kanaka Maoli in Kahuku, Hawaiʻi). We argue that Kū Kiaʻi Kahuku’s livestreaming inspired movement within the space of digital connectivity, a civic rhythm, forging symmetry and reciprocity within sociospatial ties. Moanan peoples inscribed within social media a distinct Moanan rhythm. In this case, the vibrations of the protecting, an affectively charged tā, engaged the community and diaspora in a moment of rupture—opening up a space for symmetry within the dissymmetry of colonial capitalism.
Long-acting Injectable Cabotegravir/Rilpivirine Effective in a Small Patient Cohort With Virologic Failure on Oral Antiretroviral Therapy
Authors: Brock James B , Herrington Peyton , Hickman Melissa , Hickman Aubri 
Published: September 2023

Abstract
We report 12 patients with persistent viremia on oral antiretroviral therapy who were initiated on injectable cabotegravir/rilpivirine (iCAB/RPV) without oral lead-in. All patients achieved viral suppression without any virologic rebound. iCAB/RPV may be considered as an option for patients unable to maintain suppression on oral antiretroviral therapy.
More Than a Decade Since the Latest CONSORT Non-inferiority Trials Extension: Do Infectious Diseases Trials Do Enough?
Authors: Komorowski Adam S , Lo Carson K L , Kapoor Andrew K , Smieja Marek , Loeb Mark , Mertz Dominik , Bai Anthony D 
Published: September 2023

Abstract
More than a decade after the Consolidated Standards of Reporting Trials group released a reporting items checklist for non-inferiority randomized controlled trials, the infectious diseases literature continues to underreport these items. Trialists, journals, and peer reviewers should redouble their efforts to ensure infectious diseases studies meet these minimum reporting standards.
Moving Beyond Mortality: Development and Application of a Desirability of Outcome Ranking (DOOR) Endpoint for Hospital-Acquired Bacterial Pneumonia and Ventilator-Associated Bacterial Pneumonia
Authors: Howard-Anderson Jessica , Hamasaki Toshimitsu , Dai Weixiao , Collyar Deborah , Rubin Daniel , Nambiar Sumathi , Kinamon Tori , Leister-Tebbe Heidi , Hill Carol , Geres Holly , Holland Thomas L , Doernberg Sarah B , Chambers Henry F , Fowler Vance G , Evans Scott R , Boucher Helen W ,   for the Antibacterial Resistance Leadership Group, Boucher Helen , Cosgrove Sara , Doernberg Sarah , Evans Scott , Hamasaki Toshi , Holland Tom , Howard-Anderson Jessica , Fowler Vance , King Heather , Nambiar Sumati , Tsalik Ephraim , Gopinath Ramya , Kim Peter , Natarajan Mukil , Needles Mark , Rubin Dan , Waack Ursula , Collyar Deborah 
Published: September 2023

Abstract

Background
Hospital-acquired and ventilator-associated bacterial pneumonia (HABP/VABP) are frequently caused by multidrug-resistant organisms. Patient-centered endpoints in clinical trials are needed to develop new antibiotics for HABP/VABP. Desirability of outcome ranking (DOOR) is a paradigm for the design, analysis, and interpretation of clinical trials based on a patient-centered, benefit-risk evaluation.

Methods
A multidisciplinary committee created an infectious diseases DOOR endpoint customized for HABP/VABP, incorporating infectious complications, serious adverse events, and mortality. We applied this to 2 previously completed, large randomized controlled trials for HABP/VABP. ZEPHyR compared vancomycin to linezolid and VITAL compared linezolid to tedizolid. For each trial, we evaluated the DOOR distribution and probability, including DOOR component and partial credit analyses. We also applied DOOR in subgroup analyses.

Results
In both trials, the HABP/VABP DOOR demonstrated similar overall clinical outcomes between treatment groups. In ZEPHyR, the probability that a participant treated with linezolid would have a more desirable outcome than a participant treated with vancomycin was 50.2% (95% confidence interval [CI], 45.1%­−55.3%). In VITAL, the probability that a participant treated with tedizolid would have a more desirable outcome than a participant treated with linezolid was 48.7% (95% CI, 44.8%–52.6%). The DOOR component analysis revealed that participants treated with tedizolid had a less desirable outcome than those treated with linezolid when considering clinical response alone. However, participants with decreased renal function had improved overall outcomes with tedizolid.

Conclusions
The HABP/VABP DOOR provided more granular information about clinical outcomes than is typically presented in clinical trials. HABP/VABP trials would benefit from prospectively using DOOR.
Vedolizumab in Mild-to-Moderate Crohn’s Disease Patients Naïve to Biological Therapy: A Multicentric Observational Study
Authors: Dotti Adriana Zanoni , Magro Daniela Oliveira , Vilela Eduardo Garcia , Chebli Julio Maria Fonseca , Chebli Liliana Andrade , Steinwurz Flavio , Argollo Marjorie , Carvalho Nayara Salgado , Parente Jose Miguel Luz , Lima Murilo Moura , Parra Rogério Serafim , Perin Ramir Luan , Flores Cristina , Morsoletto Eloá Marussi , da Costa Ferreira Sandro , Ludvig Juliano Coelho , Kaiser Junior Roberto Luiz , Faria Mikaell Alexandre Gouvea , Nicollelli Guilherme Mattioli , Andrade Adriana Ribas , Queiroz Natalia Sousa Freitas , Kotze Paulo Gustavo 
Published: September 2023

Abstract

Background
In real-world experience, the number of patients using vedolizumab as first-line biological therapy was low. We aimed to evaluate the effectiveness and safety of vedolizumab in mild-to-moderate Crohn’s disease (CD) biologic-naïve patients.

Methods
We performed a retrospective multicentric cohort study with patients who had clinical activity scores (Harvey–Bradshaw Index [HBI]) measured at baseline and weeks 12, 26, 52, as well as at the last follow-up. Clinical response was defined as a reduction ≥3 in HBI, whereas clinical remission as HBI ≤4. Mucosal healing was defined as the complete absence of ulcers in control colonoscopies. Kaplan–Meier survival analysis was used to assess the persistence with vedolizumab.

Results
From a total of 66 patients, 53% (35/66) reached clinical remission at week 12. This percentage increased to 69.7% (46/66) at week 26, and 78.8% (52/66) at week 52. Mucosal healing was achieved in 62.3% (33/53) of patients. Vedolizumab was well tolerated, and most adverse events were minor. During vedolizumab treatment, 3/66 patients underwent surgery.

Conclusions
This study demonstrates the effectiveness and safety of vedolizumab as a first-line biological agent in patients with mild-to-moderate CD.
Targeted activation of human ether-à-go-go-related gene channels rescues electrical instability induced by the R56Q+/− long QT syndrome variant
Authors: Venkateshappa Ravichandra , Hunter Diana V , Muralidharan Priya , Nagalingam Raghu S , Huen Galvin , Faizi Shoaib , Luthra Shreya , Lin Eric , Cheng Yen May , Hughes Julia , Khelifi Rania , Dhunna Daman Parduman , Johal Raj , Sergeev Valentine , Shafaattalab Sanam , Julian Lisa M , Poburko Damon T , Laksman Zachary , Tibbits Glen F , Claydon Tom W 
Published: September 2023

Abstract

Aims
Long QT syndrome type 2 (LQTS2) is associated with inherited variants in the cardiac human ether-à-go-go-related gene (hERG) K+ channel. However, the pathogenicity of hERG channel gene variants is often uncertain. Using CRISPR–Cas9 gene-edited hiPSC-derived cardiomyocytes (hiPSC-CMs), we investigated the pathogenic mechanism underlying the LQTS-associated hERG R56Q variant and its phenotypic rescue by using the Type 1 hERG activator, RPR260243.

Methods and results
The above approaches enable characterization of the unclear causative mechanism of arrhythmia in the R56Q variant (an N-terminal PAS domain mutation that primarily accelerates channel deactivation) and translational investigation of the potential for targeted pharmacologic manipulation of hERG deactivation. Using perforated patch clamp electrophysiology of single hiPSC-CMs, programmed electrical stimulation showed that the hERG R56Q variant does not significantly alter the mean action potential duration (APD90). However, the R56Q variant increases the beat-to-beat variability in APD90 during pacing at constant cycle lengths, enhances the variance of APD90 during rate transitions, and increases the incidence of 2:1 block. During paired S1–S2 stimulations measuring electrical restitution properties, the R56Q variant was also found to increase the variability in rise time and duration of the response to premature stimulations. Application of the hERG channel activator, RPR260243, reduces the APD variance in hERG R56Q hiPSC-CMs, reduces the variability in responses to premature stimulations, and increases the post-repolarization refractoriness.

Conclusion
Based on our findings, we propose that the hERG R56Q variant leads to heterogeneous APD dynamics, which could result in spatial dispersion of repolarization and increased risk for re-entry without significantly affecting the average APD90. Furthermore, our data highlight the antiarrhythmic potential of targeted slowing of hERG deactivation gating, which we demonstrate increases protection against premature action potentials and reduces electrical heterogeneity in hiPSC-CMs.
Cybersecurity in UK Universities: mapping (or managing) threat intelligence sharing within the higher education sector
Authors: Piazza Anna , Vasudevan Srinidhi , Carr Madeline 
Published: September 2023

Abstract
Higher education has recently been identified as a sector of concern by the UK National Cyber Security Centre (NCSC). In 2021, the NCSC reported that universities and higher education institutions (HEI) had been exponentially targeted by cyber-criminals. Existing challenges were amplified or highlighted over the course of the global pandemic when universities struggled to continue to function through hybrid and remote teaching provision that relied heavily on their digital estate and services. Despite the value of the sector and the vulnerabilities within it, higher education has received relatively little attention from the cybersecurity research community. Over 2 years, we carried out numerous interventions and engagements with the UK higher education sector. Through interviews with cybersecurity practitioners working in the sector as well as roundtables, and questionnaires, we conducted a qualitative and quantitative analysis of threat intelligence sharing, which we use as a proxy for measuring and analysing collaboration. In a unique approach to studying collaboration in cybersecurity, we utilized social network analysis. This paper presents the study and our findings about the state of cybersecurity in UK universities. It also presents some recommendations for future steps that we argue will be necessary to equip the higher education sector to continue to support UK national interests going forward. Key findings include the positive inclination of those working in university cybersecurity to collaborate as well as the factors that impede that collaboration. These include management and insurance constraints, concerns about individual and institutional reputational damage, a lack of trusted relationships, and the lack of effective mechanisms or channels for sectoral collaboration. In terms of the network itself, we found that it is highly fragmented with a very small number of the possible connections active, none of the organizations we might expect to facilitate collaboration in the network are playing a significant role, and some universities are currently acting as key information bridges. For these reasons, any changes that might be led by sectoral bodies such as Jisc, UCISA or government bodies such as NCSC, would need to go through these information brokers.