bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Landscape of Observational COVID-19 Cohort Studies Funded by the National Institute of Allergy and Infectious Diseases
Authors: Shabman Reed S , Booth Mason , Cooper Michael , DeGrace Marciela M , Fulkerson Patricia C , Hauguel Teresa , Lane Chelsea , Meyer Alyssa , Newman Lori , Post Diane , Prabhudas Mercy , Qidwai Rubya , Rojas Cynthia , Schuster Claire , Williams Carolyn , Brown Liliana 
Published: November 2023

Abstract
The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) since late 2019 represented an unprecedented public health emergency, which included a need to fully understand coronavirus disease 2019 (COVID-19) across all ages and populations. In response, the US National Institute of Allergy and Infectious Diseases (NIAID) rapidly funded epidemiology studies that monitored COVID-19. However, the diversity and breadth of the populations studied in NIAID-funded COVID-19 observational cohorts were not easy to extrapolate because of siloed approaches to collect and report data within NIAID. Here, we describe the effort to develop a harmonized cohort-study reporting tool that includes common epidemiologic data elements as well as NIAID priorities. We report its implementation to analyze metadata from 58 COVID-19 cohort studies funded from February 2020 to June 2021, and we visualize key metadata, including geographic distribution, study duration, participant demographic characteristics, sample types collected, and scientific priorities addressed. A bibliographic analysis highlights the scientific publications and citations across these funded studies and demonstrates their enormous impact on the COVID-19 field. These analyses highlight how common data elements and reporting tools can assist funding agencies to capture the landscape and potential gaps during public health responses and how they can assist in decision making.
Loss, resilience and recovery of kelp forests in a region of rapid ocean warming
Authors: Krumhansl K A , Brooks C M , Lowen J B , O’Brien J M , Wong M C , DiBacco C 
Published: November 2023

Abstract

Background and Aims
Changes in kelp abundances on regional scales have been highly variable over the past half-century owing to strong effects of local and regional drivers. Here, we assess patterns and dominant environmental variables causing spatial and interspecific variability in kelp persistence and resilience to change in Nova Scotia over the past 40 years.

Methods
We conducted a survey of macrophyte abundance at 251 sites spanning the Atlantic coast of Nova Scotia from 2019 to 2022. We use this dataset to describe spatial variability in kelp species abundances, compare species occurrences to surveys conducted in 1982 and assess changes in kelp abundance over the past 22 years. We then relate spatial and temporal patterns in abundance and resilience to environmental metrics.

Key Results
Our results show losses of sea urchins and the cold-tolerant kelp species Alaria esculenta, Saccorhiza dermatodea and Agarum clathratum in Nova Scotia since 1982 in favour of the more warm-tolerant kelps Saccharina latissima and Laminaria digitata. Kelp abundances have increased slightly since 2000, and Saccharina latissima and L. digitata are widely abundant in the region today. The highest kelp cover occurs on wave-exposed shores and at sites where temperatures have remained below thresholds for growth (21 °C) and mortality (23 °C). Moreover, kelp has recovered from turf dominance following losses at some sites during a warm period from 2010 to 2012.

Conclusions
Our results indicate that dramatic changes in kelp community composition and a loss of sea urchin herbivory as a dominant driver of change in the system have occurred in Nova Scotia over the past 40 years. However, a broad-scale shift to turf-dominance has not occurred, as predicted, and our results suggest that resilience and persistence are still a feature of kelp forests in the region despite rapid warming over the past several decades.
Eugeniin improves cholesterol metabolism in HepG2 cells and Caco-2 cells
Authors: Ye Yuyang , Takeuchi Asahi , Kawaguchi Yuya , Matsuba Shoya , Zhang Ni , Mijiti Maihemuti , Banno Arata , Hiramatsu Naoto , Okada Toshitaka , Nagaoka Satoshi 
Published: November 2023

ABSTRACT
Considering the absence of prior studies on the cholesterol metabolism-improving effects of eugeniin, the present investigation aimed to explore the potential impact of eugeniin on cholesterol metabolism. This study sought to elucidate the molecular mechanisms involved in this process using HepG2 and Caco-2 cells treated with 5 µm eugeniin. The intracellular cholesterol levels in HepG2 and Caco-2 cells were significantly decreased in the 24-h eugeniin-treated group. The protein and messenger ribonucleic acid (mRNA) levels of the low-density lipoprotein receptor (LDLR) were increased, while 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase protein and mRNA levels were decreased in HepG2 cells 6 h of the eugeniin-treated group. Additionally, LDLR protein and mRNA levels were increased in HepG2 cells after 24 h of eugeniin treatment. In Caco-2, the protein and mRNA levels of ATP-binding cassette transporter 1 were increased after 24 h eugeniin treatment. This novel finding indicates that eugeniin improves cholesterol metabolism in human cell cultures.
Exploiting the structure of biochemical pathways to investigate dynamical properties with neural networks for graphs
Authors: Fontanesi Michele , Micheli Alessio , Milazzo Paolo , Podda Marco 
Published: November 2023

Abstract

Motivation
Dynamical properties of biochemical pathways (BPs) help in understanding the functioning of living cells. Their in silico assessment requires simulating a dynamical system with a large number of parameters such as kinetic constants and species concentrations. Such simulations are based on numerical methods that can be time-expensive for large BPs. Moreover, parameters are often unknown and need to be estimated.

Results
We developed a framework for the prediction of dynamical properties of BPs directly from the structure of their graph representation. We represent BPs as Petri nets, which can be automatically generated, for instance, from standard SBML representations. The core of the framework is a neural network for graphs that extracts relevant information directly from the Petri net structure and exploits them to learn the association with the desired dynamical property. We show experimentally that the proposed approach reliably predicts a range of diverse dynamical properties (robustness, monotonicity, and sensitivity) while being faster than numerical methods at prediction time. In synergy with the neural network models, we propose a methodology based on Petri nets arc knock-out that allows the role of each molecule in the occurrence of a certain dynamical property to be better elucidated. The methodology also provides insights useful for interpreting the predictions made by the model. The results support the conjecture often considered in the context of systems biology that the BP structure plays a primary role in the assessment of its dynamical properties.

Availability and implementation
https://github.com/marcopodda/petri-bio (code), https://zenodo.org/record/7610382 (data).
PiDeeL: metabolic pathway-informed deep learning model for survival analysis and pathological classification of gliomas
Authors: Kaynar Gun , Cakmakci Doruk , Bund Caroline , Todeschi Julien , Namer Izzie Jacques , Cicek A Ercument 
Published: November 2023

AbstractMotivationOnline assessment of tumor characteristics during surgery is important and has the potential to establish an intra-operative surgeon feedback mechanism. With the availability of such feedback, surgeons could decide to be more liberal or conservative regarding the resection of the tumor. While there are methods to perform metabolomics-based tumor pathology prediction, their model complexity predictive performance is limited by the small dataset sizes. Furthermore, the information conveyed by the feedback provided on the tumor tissue could be improved both in terms of content and accuracy.ResultsIn this study, we propose a metabolic pathway-informed deep learning model (PiDeeL) to perform survival analysis and pathology assessment based on metabolite concentrations. We show that incorporating pathway information into the model architecture substantially reduces parameter complexity and achieves better survival analysis and pathological classification performance. With these design decisions, we show that PiDeeL improves tumor pathology prediction performance of the state-of-the-art in terms of the Area Under the ROC Curve by 3.38% and the Area Under the Precision–Recall Curve by 4.06%. Similarly, with respect to the time-dependent concordance index (c-index), PiDeeL achieves better survival analysis performance (improvement of 4.3%) when compared to the state-of-the-art. Moreover, we show that importance analyses performed on input metabolite features as well as pathway-specific neurons of PiDeeL provide insights into tumor metabolism. We foresee that the use of this model in the surgery room will help surgeons adjust the surgery plan on the fly and will result in better prognosis estimates tailored to surgical procedures.Availability and implementationThe code is released at https://github.com/ciceklab/PiDeeL. The data used in this study are released at https://zenodo.org/record/7228791.
cellsig plug-in enhances CIBERSORTx signature selection for multidataset transcriptomes with sparse multilevel modelling
Authors: Al Kamran Khan Md Abdullah , Wu Jian , Sun Yuhan , Barrow Alexander D , Papenfuss Anthony T , Mangiola Stefano 
Published: November 2023

Abstract

Motivation
The precise characterization of cell-type transcriptomes is pivotal to understanding cellular lineages, deconvolution of bulk transcriptomes, and clinical applications. Single-cell RNA sequencing resources like the Human Cell Atlas have revolutionised cell-type profiling. However, challenges persist due to data heterogeneity and discrepancies across different studies. One limitation of prevailing tools such as CIBERSORTx is their inability to address hierarchical data structures and handle nonoverlapping gene sets across samples, relying on filtering or imputation.

Results
Here, we present cellsig, a Bayesian sparse multilevel model designed to improve signature estimation by adjusting data for multilevel effects and modelling for gene-set sparsity. Our model is tailored to large-scale, heterogeneous pseudobulk and bulk RNA sequencing data collections with nonoverlapping gene sets. We tested the performances of cellsig on a novel curated Human Bulk Cell-type Catalogue, which harmonizes 1435 samples across 58 datasets. We show that cellsig significantly enhances cell-type marker gene ranking performance. This approach is valuable for cell-type signature selection, with implications for marker gene validation, single-cell annotation, and deconvolution benchmarks.

Availability and implementation
Codes and the interactive app are available at https://github.com/stemangiola/cellsig; and the database is available at https://doi.org/10.5281/zenodo.7582421.
Molecular generation strategy and optimization based on A2C reinforcement learning in de novo drug design
Authors: Wang Qian , Wei Zhiqiang , Hu Xiaotong , Wang Zhuoya , Dong Yujie , Liu Hao 
Published: November 2023

Abstract

Motivation
In the field of pharmacochemistry, it is a time-consuming and expensive process for the new drug development. The existing drug design methods face a significant challenge in terms of generation efficiency and quality.

Results
In this paper, we proposed a novel molecular generation strategy and optimization based on A2C reinforcement learning. In molecular generation strategy, we adopted transformer-DNN to retain the scaffolds advantages, while accounting for the generated molecules’ similarity and internal diversity by dynamic parameter adjustment, further improving the overall quality of molecule generation. In molecular optimization, we introduced heterogeneous parallel supercomputing for large-scale molecular docking based on message passing interface communication technology to rapidly obtain bioactive information, thereby enhancing the efficiency of drug design. Experiments show that our model can generate high-quality molecules with multi-objective properties at a high generation efficiency, with effectiveness and novelty close to 100%. Moreover, we used our method to assist shandong university school of pharmacy to find several candidate drugs molecules of anti-PEDV.

Availability and implementation
The datasets involved in this method and the source code are freely available to academic users at https://github.com/wq-sunshine/MomdTDSRL.git.
Methods for studying mammalian aquaporin biology
Authors: Banerjee Shohini , Smith Ian M , Hengen Autumn C , Stroka Kimberly M 
Published: November 2023

AbstractAquaporins (AQPs), transmembrane water-conducting channels, have earned a great deal of scrutiny for their critical physiological roles in healthy and disease cell states, especially in the biomedical field. Numerous methods have been implemented to elucidate the involvement of AQP-mediated water transport and downstream signaling activation in eliciting whole cell, tissue, and organ functional responses. To modulate these responses, other methods have been employed to investigate AQP druggability. This review discusses standard in vitro, in vivo, and in silico methods for studying AQPs, especially for biomedical and mammalian cell biology applications. We also propose some new techniques and approaches for future AQP research to address current gaps in methodology.
Policing and Sense of Place: ‘Shallow’ and ‘Deep’ Security in an English Town
Authors: Bradford Ben , Girling Evi , Loader Ian , Sparks Richard 
Published: November 2023

Abstract
Much policy discourse concentrates on the contribution police make to keeping people safe. Often, this means minimizing fear of crime. Yet, more expansive accounts stress the extent to which deeper-rooted forms of security and belonging might also be important ‘outcomes’ of police activity. Using data collected from a survey of residents of a mid-sized English town, Macclesfield in Cheshire, we consider the extent to which evaluations of policing are associated with (1) a ‘shallow’ sense of security—roughly speaking, feeling safe—and (2) a ‘deeper’ sense of security—being comfortable in, and with, one’s environment. Focussing more accurately on the forms of safety and security police can hope to ‘produce’ opens up space for consideration of the ends they seek as well as the means they use.
Re-Envisioning Field Education in Australian Social Work to Combat Placement Poverty: Students’, Educators’ and Practitioners’ Perceptions
Authors: Morley Christine , Ryan Vanessa , Hodge Lisa , Higgins Maree , Briskman Linda , Martin Robyn 
Published: November 2023

Abstract
In Australia, pressure is mounting from multiple stakeholders for a full review of the national social work education standards for field education as evidence grows about compulsory, unpaid placements exacerbating student poverty and the related adverse consequences for students’ learning and well-being. This article reports on the findings of an Australian nation-wide qualitative and quantitative survey that explored social work students’, educators’ and practitioners’ perceptions of proposed strategies to address the challenges identified with existing field education requirements. Descriptive statistics were calculated using Excel. Qualitative data were coded for thematic analysis. The main finding of the survey involving 1,191 participants was a call for a reimagined model of field education with flexibility in all aspects of how future placements are conceptualised, structured and delivered. The findings provide important and previously unavailable empirical evidence about field education strategies to inform and support the reimagining of existing Australian Social Work Education and Accreditation Standards. Recommendations for change, which have implications for both the Australian Association of Social Workers and the Australian Government, are discussed in the context of international standards for social work education and the social justice goals of the profession.
Robustness of edge-coupled interdependent networks with reinforced edges
Authors: Zhang Junjie , Liu Caixia , Liu Shuxin , Pan Fei , Zang Weifei 
Published: November 2023

Abstract
Previous studies on cascade failures in interdependent networks have mainly focused on node coupling relationships. However, in realistic scenarios, interactions often occur at the edges connecting nodes rather than at the nodes themselves, giving rise to edge-coupled interdependent networks. In this article, we extend the model of partially edge-coupled interdependent networks by introducing reinforced edges with a ratio of ρ. We analyse the formation of finite surviving components in edge-coupled networks, wherein the reinforced edges can function and support their neighbouring nodes to form functional components. To accomplish this, we develop a framework through a detailed mathematical derivation of the proposed model. We then investigate the critical value ρ* of the reinforced edge ratio that can change the phase transition type of the network. Our model is verified by theoretical analysis, simulation experiments and real network systems. The results show that the introduction of a small proportion of reinforced edges in the edge-coupled interdependent network can avoid the sudden collapse of the network and significantly improve the robustness of the network.
Patients’ Perspectives, Experiences, and Concerns With Perianal Fistulae: Insights From Online Targeted-Disease Forums
Authors: Khalil Carine , van Deen Welmoed K , Dupuy Taylor , Syal Gaurav , Arnold Corey , Cazzetta Susan E , Nazarey Pradeep P , Almario Christopher V , Spiegel Brennan M R 
Published: November 2023

Abstract

Background
Perianal fistulae can undermine physical, emotional, and social well-being in patients with Crohn’s disease and are challenging to manage. Social media offers a rich opportunity to gain an in-depth understanding of the impact of perianal fistulae on patients’ daily lives outside of controlled environments. In this study, we conducted social media analytics to examine patients’ experiences with perianal fistulae and assessed the impact of perianal fistulae on patients’ behavior and overall well-being.

Methods
We used a mixed-method approach to examine 119 986 publicly available posts collected from 10 Crohn’s disease forums in the United States between January 01, 2010 and January 01, 2020. Discussions related to Crohn’s perianal fistulae were retrieved. We randomly selected 700 posts and qualitatively analyzed them using an inductive thematic approach. We then applied a latent Dirichlet allocation probabilistic topic model to explore themes in an unsupervised manner on the collection of 119 986 posts.

Results
In the qualitative analysis, 5 major themes were identified: (1) burden of perianal fistula; (2) challenges associated with treatment; (3) online information seeking and sharing; (4) patient experiences with treatments; and (5) patients’ apprehension about treatments. In the quantitative analysis, the percentages of posts related to the major themes were (1) 20%, (2) 29%, (3) 66%, and (4) 28%, while the topic model did not identify theme 5.

Conclusions
Social media reveals a dynamic range of themes governing patients’ perspectives and experiences with Crohn’s perianal fistulae. In addition to the biopsychosocial burden, patients frequently express dissatisfaction with current treatments and often struggle to navigate among available management options.
Genome features of a novel hydrocarbonoclastic Chryseobacterium oranimense strain and its comparison to bacterial oil-degraders and to other C. oranimense strains
Authors: Ramdass Amanda Christine , Rampersad Sephra Nalini 
Published: November 2023

Abstract
For the first time, we report the whole genome sequence of a hydrocarbonoclastic Chryseobacterium oranimense strain isolated from Trinidad and Tobago (COTT) and its genes involved in the biotransformation of hydrocarbons and xenobiotics through functional annotation. The assembly consisted of 11 contigs with 2,794 predicted protein-coding genes which included a diverse group of gene families involved in aliphatic and polycyclic hydrocarbon degradation. Comparative genomic analyses with 18 crude-oil degrading bacteria in addition to two C. oranimense strains not associated with oil were carried out. The data revealed important differences in terms of annotated genes involved in the hydrocarbon degradation process that may explain the molecular mechanisms of hydrocarbon and xenobiotic biotransformation. Notably, many gene families were expanded to explain COTT’s competitive ability to manage habitat-specific stressors. Gene-based evidence of the metabolic potential of COTT supports the application of indigenous microbes for the remediation of polluted terrestrial environments and provides a genomic resource for improving our understanding of how to optimize these characteristics for more effective bioremediation.
The Safety, Tolerability, Pharmacokinetics, and Clinical Efficacy of the NLRX1 agonist NX-13 in Active Ulcerative Colitis: Results of a Phase 1b Study
Authors: Verstockt Bram , Vermeire Severine , Peyrin-Biroulet Laurent , Mosig Rebecca , Feagan Brian G , Colombel Jean-Frederic , Siegmund Britta , Rieder Florian , Schreiber Stefan , Yarur Andres , Panaccione Remo , Dubinsky Marla , Lichtiger Simon , Cataldi Fabio , Danese Silvio 
Published: November 2023

Abstract

Background and Aims
NX-13 activation of NLRX1 reduces intracellular reactive oxygen species and decreases inflammation in animal models of colitis. A phase 1a trial demonstrated a gut-selective pharmacokinetic profile with good tolerability. This phase Ib study aimed to evaluate the safety, tolerability, and pharmacokinetics of NX-13 in patients with active ulcerative colitis [UC].

Methods
We conducted a multicentre, randomized, double-blind, placebo-controlled trial of NX-13 in patients with active UC. Patients with a Mayo Clinic Score of 4–10 were randomly assigned [3:3:3:1 ratio] to three NX-13 oral dose groups (250 mg immediate release [IR], 500 mg IR, or 500 mg delayed release [DR], or placebo) once daily for 4 weeks. Safety and pharmacokinetics were the primary and secondary objectives, respectively.

Results
Thirty-eight patients [11 females] were recruited and randomized to placebo [five], NX-13 250 mg IR [11], NX-13 500 mg IR [11], or NX-13 500 mg DR [11] and received at least one dose. There were no serious adverse events or deaths during the trial. One patient [500 mg DR, 1/11] withdrew due to worsening of UC and a second [500 mg IR, 1/11] on the last day of treatment after a panic attack associated with atrial fibrillation. In the efficacy population [36 patients], clinical improvement in rectal bleeding and stool frequency scores relative to placebo were seen as early as week 2 and endoscopic response was seen at week 4.

Conclusions
NX-13 was generally safe and well tolerated with early signs of rapid symptom and endoscopic improvement. This novel mechanism of action warrants further investigation. ClinicalTrials.gov: NCT04862741.