bluuebunny/crossref_metadata_2025_split huggingface dataset:
Flexible fitting of AlphaFold2-predicted models to cryo-EM density maps using elastic network models: a methodical affirmation
Authors: Alshammari Maytha , He Jing , Wriggers Willy 
Published: November 2024

Abstract

Motivation
This study investigates the flexible refinement of AlphaFold2 models against corresponding cryo-electron microscopy (cryo-EM) maps using normal modes derived from elastic network models (ENMs) as basis functions for displacement. AlphaFold2 generally predicts highly accurate structures, but 18 of the 137 models of isolated chains exhibit a TM-score below 0.80. We achieved a significant improvement in four of these deviating structures and used them to systematically optimize the parameters of the ENM motion model.

Results
We successfully refined four AlphaFold2 models with notable discrepancies: lipid-preserved respiratory supercomplex (TM-score increased from 0.52 to 0.69), flagellar L-ring protein (TM-score increased from 0.53 to 0.64), cation diffusion facilitator YiiP (TM-score increased from 0.76 to 0.83), and Sulfolobus islandicus pilus (TM-score increased from 0.77 to 0.85). We explored the effect of three different mode ranges (modes 1–9, 7–9, and 1–12), masked or box-cropped density maps, numerical optimization methods, and two similarity measures (Pearson correlation and inner product). The best results were achieved for the widest mode range (modes 1–12), masked maps, inner product, and local Powell optimization. These optimal parameters were implemented in the flexible fitting utility elforge.py in version 1.4 of our Python-based ModeHunter package.

Availability and implementation
https://modehunter.biomachina.org.
Tiberius: end-to-end deep learning with an HMM for gene prediction
Authors: Gabriel Lars , Becker Felix , Hoff Katharina J , Stanke Mario 
Published: November 2024

Abstract

Motivation
For more than 25 years, learning-based eukaryotic gene predictors were driven by hidden Markov models (HMMs), which were directly inputted a DNA sequence. Recently, Holst et al. demonstrated with their program Helixer that the accuracy of ab initio eukaryotic gene prediction can be improved by combining deep learning layers with a separate HMM postprocessor.

Results
We present Tiberius, a novel deep learning-based ab initio gene predictor that end-to-end integrates convolutional and long short-term memory layers with a differentiable HMM layer. Tiberius uses a custom gene prediction loss and was trained for prediction in mammalian genomes and evaluated on human and two other genomes. It significantly outperforms existing ab initio methods, achieving F1 scores of 62% at gene level for the human genome, compared to 21% for the next best ab initio method. In de novo mode, Tiberius predicts the exon−intron structure of two out of three human genes without error. Remarkably, even Tiberius’s ab initio accuracy matches that of BRAKER3, which uses RNA-seq data and a protein database. Tiberius’s highly parallelized model is the fastest state-of-the-art gene prediction method, processing the human genome in under 2 hours.

Availability and implementation
https://github.com/Gaius-Augustus/Tiberius
DeepDR: a deep learning library for drug response prediction
Authors: Jiang Zhengxiang , Li Pengyong 
Published: November 2024

Abstract

Summary
Accurate drug response prediction is critical to advancing precision medicine and drug discovery. Recent advances in deep learning (DL) have shown promise in predicting drug response; however, the lack of convenient tools to support such modeling limits their widespread application. To address this, we introduce DeepDR, the first DL library specifically developed for drug response prediction. DeepDR simplifies the process by automating drug and cell featurization, model construction, training, and inference, all achievable with brief programming. The library incorporates three types of drug features along with nine drug encoders, four types of cell features along with nine cell encoders, and two fusion modules, enabling the implementation of up to 135 DL models for drug response prediction. We also explored benchmarking performance with DeepDR, and the optimal models are available on a user-friendly visual interface.

Availability and implementation
DeepDR can be installed from PyPI (https://pypi.org/project/deepdr). The source code and experimental data are available on GitHub (https://github.com/user15632/DeepDR).
APAtizer: a tool for alternative polyadenylation analysis of RNA-Seq data
Authors: Sousa Bruno , Bessa Maria , de Mendonça Filipa L , Ferreira Pedro G , Moreira Alexandra , Pereira-Castro Isabel 
Published: November 2024

Abstract

Summary
APAtizer is a tool designed to analyze alternative polyadenylation events on RNA-sequencing data. The tool handles different file formats, including BAM, htseq, and DaPars bedGraph files. It provides a user-friendly interface that allows users to generate informative visualizations, including Volcano plots, heatmaps, and gene lists. These outputs allow the user to retrieve useful biological insights such as the occurrence of polyadenylation events when comparing two biological conditions. In addition, it can perform differential gene expression, gene ontology analysis, visualization of Venn diagram intersections, and correlation analysis.

Availability and implementation
Source code and example case studies for APAtizer are available at https://github.com/GeneRegulationi3S/APAtizer/.
M2ara: unraveling metabolomic drug responses in whole-cell MALDI mass spectrometry bioassays
Authors: Enzlein Thomas , Geisel Alexander , Hopf Carsten , Schmidt Stefan 
Published: November 2024

Abstract

Summary
Fast computational evaluation and classification of concentration responses for hundreds of metabolites represented by their mass-to-charge (m/z) ratios is indispensable for unraveling complex metabolomic drug actions in label-free, whole-cell Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry (MALDI MS) bioassays. In particular, the identification of novel pharmacodynamic biomarkers to determine target engagement, potency, and potential polypharmacology of drug-like compounds in high-throughput applications requires robust data interpretation pipelines. Given the large number of mass features in cell-based MALDI MS bioassays, reliable identification of true biological response patterns and their differentiation from any measurement artefacts that may be present is critical. To facilitate the exploration of metabolomic responses in complex MALDI MS datasets, we present a novel software tool, M2ara. Implemented as a user-friendly R-based shiny application, it enables rapid evaluation of Molecular High Content Screening (MHCS) assay data. Furthermore, we introduce the concept of Curve Response Score (CRS) and CRS fingerprints to enable rapid visual inspection and ranking of mass features. In addition, these CRS fingerprints allow direct comparison of cellular effects among different compounds. Beyond cellular assays, our computational framework can also be applied to MALDI MS-based (cell-free) biochemical assays in general.

Availability and implementation
The software tool, code, and examples are available at https://github.com/CeMOS-Mannheim/M2ara and https://dx.doi.org/10.6084/m9.figshare.25736541.
Terminal Liminality, Life Imprisonment and the Paroled Body
Authors: Vannier Marion , Dagan Netanel 
Published: November 2024

Abstract
Based on an in-depth analysis of parole board hearings in Israel concerning life sentence prisoners who are old or severely ill, we argue that, rather than opening a window onto new beginnings, parole hearings place applicants in a state of terminal liminality that marks a transition from life into death. We uncover how terminal liminality entails constructing a broken paroled body before the parole board, where matters of life and death are performed, detailed, and contextualized. We further lay out a taxonomy to discuss applicants’ negotiation of terminal liminality through fatalism, resilience, resistance and hope, uncovering how they navigate penal and biological ‘clocks’. The performance of the broken paroled body at the back-end of the criminal justice system is revelatory of the punitiveness of the penal system towards the ageing prison population.
Ethics and ontology: comparing Amartya Sen’s ethics and Tony Lawson’s Critical Ethical Naturalism
Authors: Ragkousis Antonis 
Published: November 2024

Abstract
While Sen’s ethics, particularly through his capability approach, are recognised for their critical nature and alignment with certain realist ontological principles, this paper explores the compatibility and potential tensions between Sen’s framework and Critical Ethical Naturalism (CEN), an ethical theory introduced by Tony Lawson. This comparative exercise reveals that Sen’s adoption of realist ontological notions such as openness, relationality and the importance of process and institutions suggests compatibility with CEN—a potential compatibility noted by Lawson himself. However, there is also an important difference between Sen’s moral theory and CEN, which indicates the possibility of further fundamental tensions between them. This difference lies in their divergent orientations regarding the content and relevance of ontology. Sen’s project is shown to be predicated on the irrelevance of ontology to ethical theorising, which contrasts sharply with Lawson’s framework; indeed, the whole point of Lawson’s approach is to develop an ethical theory grounded on an explicit ontological account. Through a detailed examination of Sen’s reluctance to engage with ontology, an exploration of potential sources of this reticence and an analysis of the explicit ontological basis of CEN, the paper highlights fundamental distinctions between Sen’s approach and CEN.
Remote sensing image dehazing method in mountaineering equipment
Authors: Guo Yuanzhao , Zhang Jun 
Published: November 2024

Abstract
With the spread of national sports awareness, more people are fond of outdoor mountaineering. Intelligent mountaineering equipment can provide some safe and convenient services for outdoor mountaineering. However, the positioning accuracy is affected by the ability of remote sensing image recognition in the background. To address the haze interference in remote sensing image positioning, the Retinex algorithm is enhanced using an atmospheric scattering model. This improved Retinex algorithm adopts a multiscale retinal enhancement algorithm with color restoration to enhance images. The Gaussian kernel function plays a filtering role, while the guided filtering is used to improve image texture and details. Test data from background remote sensing images of mountaineering equipment are used to evaluate the algorithm. Results indicate that when the entire test set is used for calculations, the normalized information entropy of I-Retinex, Retinex, generative adversarial networks, and Alex models is 0.92. The median values of normalized mean squared error and mean absolute error are 0.13 and 0.15, respectively, outperforming the contrast defogging model. There is a negative correlation between the normalized peak signal-to-noise ratio and haze noise error in each model. When the entire test set is used, the normalized average gradient of I-Retinex is 0.87, significantly higher than the comparison models. However, the I-Retinex model developed in this study lacks optimal average computation time and memory consumption data. Experimental results demonstrate that the improved haze removal model effectively removes haze from remote sensing images, supporting the remote sensing image-related service functionalities of mountaineering equipment.
Central ligation or partial preservation of the right gastric artery does not seem to affect conduit or anastomotic perfusion during robot-assisted resection of gastroesophageal junction cancer: a randomized clinical trial
Authors: Osterkamp Jens Thomas Fredrik , Nerup Nikolaj , Svendsen Morten Bo S , Strandby Rune B , Svendsen Lars Bo , Aasvang Eske K , Vad Henrik , Plamboeck Astrid , Achiam Michael P 
Published: November 2024

Summary
The gastric conduit can be created with partial preservation or a central ligation of the right gastric artery. Central ligation may facilitate complete removal of lymph node (LN) station 3; however, whether this influences conduit and anastomotic perfusion is unknown. Hence this study investigated whether a central ligation of the right gastric artery would affect conduit or anastomotic perfusion compared with partial preservation (local standard) during robot-assisted resection of gastroesophageal junction cancer. Patients scheduled for robot-assisted resection of gastroesophageal junction cancer were randomized to either central ligation or partial preservation of the right gastric artery. Perfusion was assessed using quantified indocyanine green angiography: before gastric mobilization, after conduit formation, and after anastomosis. Hemodynamic variables during surgery and surgical outcomes were recorded. We included 70 patients between June 2020 and October 2021, of whom 5 were excluded from the final analysis. The two patient groups did not differ in conduit (0.07 [interquartile range (IQR), 0.05–0.08] vs. 0.07 u [IQR, 0.05–0.08], P = 0.86) or anastomotic perfusion (0.08 [standard deviation (SD), ±0.02] vs. 0.08 u [SD, ±0.02], P = 0.21), nor did they differ in intraoperative blood loss, anastomotic leaks, postoperative complications, or 1-year survival. However, more LNs were resected in the central ligation group (36 [IQR, 30–44] vs. 28 [IQR, 23–43], P = 0.02). Introducing a central ligation of the right gastric artery did not seem to affect conduit or anastomotic perfusion, compared with partial preservation. However, significantly more LNs were resected.
MI5, the Security State and Communist Political Refugees from Nazism in Second World War-Era Britain: The Case of Gustav Beuer, 1938–1946
Authors: Stibbe Matthew 
Published: November 2024

Abstract
This article examines the British Security Service’s monitoring of Gustav Beuer, a Sudeten German communist and former member of the Czechoslovak parliament who arrived in London as a refugee in 1938 and set up home there until 1946. Although from a friendly country, Beuer was placed under continuous surveillance and was interned, together with five of his compatriots, in 1940–41. The article uses this case to challenge previous interpretations of MI5’s role in spying on communist refugees from Central Europe. It does so by taking a model developed by the German political scientist Matthias Lemke for analysing the widely varying levels of threat to democracy posed by exceptional security measures taken by liberal states in closely defined time-frames and applying this to Second-World-War Britain. Far from pursuing a linear strategy based on anti-communist prejudice alone, MI5 was obliged to muddle along in its policy towards Beuer and other communist refugees, assimilating unexpected triggers, shifting legal-bureaucratic frameworks, changes in wartime alliances and public opinion, and instances of ministerial action and inaction. The paradoxical result of this was to inject a certain amount of (unforeseen) pragmatism into MI5’s handling of ‘suspect’ refugees, while at the same time undermining its belief that covert fact-finding alone was enough to establish who was and who was not a threat. The article concludes that the self-doubts and unease within the British security state which are often attributed to intelligence failings and spy scandals in the early Cold War period had deeper roots in the Second World War era.
Brain-body coevolution in incipient versus established primate species—evaluating Simpson’s “most important distinction”
Authors: Bokma Folmer , Tsuboi Masahito , Stenseth Nils Chr 
Published: November 2024

Abstract
Are differences between species the long-term consequence of microevolution within species, or does speciation involve fundamentally different processes? We analyzed the brain and body sizes of present-day primate species using a novel phylogenetic comparative method that decomposes the phenotypic covariance of these traits into speciational and anagenetic components. We estimated that approximately half of speciation events are accompanied by accelerated phenotypic change. Equivalent in magnitude to approximately 7 million years of gradual microevolution, such speciational changes in brain and body size account for about 58% of the phenotypic variation among extant species. Interestingly, speciational changes in brain and body size appear significantly less correlated (r ≈ 0.83) than gradual, microevolutionary changes in these same traits (r ≈ 0.97). This indicates that the strong allometric constraint that dictates microevolution in brain and body sizes is relaxed at speciation events. These results suggest that phenotypic evolution is not only accelerated during speciation but also involves events that seldomly occur at microevolutionary timescales.
A novel method for evaluating earthquake forecast model performance and its implications for refining seismic likelihood model
Authors: Wei Cong-Min , Meng Guo-Jie , Wu Wei-Wei , Chen Xue-Liang , Zhao Guo-Qiang , Dong Zhi-Hua , Yang Yan-Cong , Wang Yu-Fan 
Published: November 2024

SUMMARY
Utilizing statistical tests to evaluate earthquake forecasting models is crucial to improve forecasting strategies for seismic hazard assessment. We develop a novel evaluation method for alarm-based earthquake forecast, taking into account the magnitude of seismic energy and the impact area of earthquakes, instead of using solely seismic event number and epicentre locations in conventional approaches. First, we derive a scale law of Seismic Area by statistically analysing coseismal maps of past M ≥ 7.0 earthquakes. Second, we proportionally allocate Seismic Moment to surrounding cells based on corresponding seismic area within each cell (SASM-test). Compared to the Molchan test which is conventionally applied for models that forecast the epicentre location, our proposed SASM-test can be applied to the evaluation of forecasting models that focus on the whole earthquake rupture (source area). Third, we apply the SASM-test method to the time-independent probabilistic earthquake forecasting model for the southeastern Tibetan Plateau (RELM-TibetSE) and compare it with other evaluation methods. The retrospective testing shows that the SASM-test demonstrate relatively higher sensitivity, enabling to detect subtle differences between similar models that conventional methods may overlook. Additionally, retrospective test results indicate that: (i) Earthquake forecasting models using Global Navigation Satellite System (GNSS) data performed better in forecasting the ‘source area’ than the ‘epicentre location’; (ii) forecasting models based on principal strain rate outperformed the models based on maximum shear strain rate in forecasting both the epicentre location and the source area and (iii) incorporating spatially varying seismogenic layer thickness and rigidity into seismic forecasting models could improve their ability to forecast the ‘source area’ compared to using uniform seismogenic layer properties. The newly proposed SASM-test method can provide a more sensitive and comprehensive approach for the evaluation of earthquake forecasting models, contributing to the refinement of seismic hazard assessments.
Non–cost-related sources of medication nonadherence in the Medicare population
Authors: Petroski Jason , Strachan Kelly , Schluterman Nicholas , Doss William 
Published: November 2024

Abstract
Significant research and attention to date have focused on cost-related medication nonadherence as rising prescription drug prices worsen affordability and access for many Americans. This study investigated self-reported sources of medication nonadherence, measuring both cost- and non–cost-related medication nonadherence among community-dwelling Medicare Part D beneficiaries in 2022. A total of 13.7% of beneficiaries (4 589 843) reported some type of medication nonadherence; 7.5% reported medication nonadherence related to cost and 6.2% reported for non-cost reasons. Beneficiaries reporting food insecurity, poor functional status, and lack of understanding of the Part D benefit were more likely to report both types of medication nonadherence after adjustment for sociodemographic factors. Beneficiaries receiving the Low-Income Subsidy had lower odds of reporting cost-related but greater odds of reporting non–cost-related medication nonadherence. These findings suggest that non–cost-related sources of medication nonadherence, such as beneficiary preferences or beliefs, understanding of their health situation or insurance coverage, and ability to fill a prescription, are significant contributors to overall nonadherence. Non–cost-related medication nonadherence should be considered alongside recent changes to the Part D benefit and in future Part D Centers for Medicare and Medicaid Services (CMS) Innovation Center models, such as the proposed Medicare $2 Drug List Model, in order to maximize the impact of these initiatives.
Nurse practitioner race and ethnicity and interest in independent primary care practice and serving Medicaid enrollees
Authors: Muench Ulrike , Quan Amy , de Lisser Rosalind , Bates Timothy , Spetz Joanne 
Published: November 2024

Abstract
Nurse practitioners (NPs) are important providers of primary care to underserved populations, particularly in areas with lower physician supply. In 2023, California implemented new regulations aimed at improving access to care, especially primary care services, by providing a pathway for NPs to practice without formal supervision after 3 years of practice and without any physician relationship after 5 years of practice. This study used data from a representative survey of California-licensed NPs fielded in late 2022 to examine NPs' current practice and intentions following implementation of the new regulations. Results indicated notable differences in the characteristics of NPs who are considering establishing an independent primary care practice and who are considering changing their practice to serve more Medicaid enrollees at the advent of expanded scope of practice. The strong association between racial/ethnic identity and greater interest in practice change suggests that after the elimination of physician collaboration requirements, increasing the diversity of the NP workforce may be one of the most important strategies for increasing access to care for Californians and especially for people receiving Medicaid.
Applied potassium negates osmotic stress impacts on plant physiological processes: a meta-analysis
Authors: Zhu Linxing , Sun Yuming , Wang Rongfeng , Zeng Jixing , Li Jia , Huang Mengting , Wang Min , Shen Qirong , Guo Shiwei 
Published: November 2024

Abstract
Potassium (K) availability in plant cells is critical for maintaining plant productivity across many terrestrial ecosystems. Yet, there is no comprehensive assessment of the mechanisms by which plants respond to potassium application in such conditions, despite the global challenge of escalating osmotic stress. Herein, we conducted a meta-analysis using data from 2381 paired observations to investigate plant responses to potassium application across various morphological, physiological, and biochemical parameters under both osmotic and nonosmotic stress. Globally, our results showed the significant effectiveness of potassium application in promoting plant productivity (e.g. +12%~30% in total dry weight), elevating photosynthesis (+12%~30%), and alleviating osmotic damage (e.g. −19%~26% in malonaldehyde), particularly under osmotic stress. Moreover, we found evidence of interactive effects between osmotic stress and potassium on plant traits, which were more pronounced under drought than salt stress, and more evident in C3 than C4 plants. Our synthesis verifies a global potassium control over osmotic stress, and further offers valuable insights into its management and utilization in agriculture and restoration efforts.