bluuebunny/crossref_metadata_2025_split huggingface dataset:
Limitations in metabolic plasticity after traumatic injury are only moderately exacerbated by physical activity restriction
Authors: Bruzina Angela S. , Raymond-Pope Christiana J. , Murray Kevin J. , Lillquist Thomas J. , Castelli Katelyn M. , Bijwadia Shefali R. , Call Jarrod A. , Greising Sarah M. 
Published: April 2024

AbstractFollowing traumatic musculoskeletal injuries, prolonged bedrest and loss of physical activity may limit muscle plasticity and drive metabolic dysfunction. One specific injury, volumetric muscle loss (VML), results in frank loss of muscle and is characterized by whole-body and cellular metabolic dysfunction. However, how VML and restricted physical activity limit plasticity of the whole-body, cellular, and metabolomic environment of the remaining uninjured muscle remains unclear. Adult mice were randomized to posterior hindlimb compartment VML or were age-matched injury naïve controls, then randomized to standard or restricted activity cages for 8-wks. Activity restriction in naïve mice resulted in ~5% greater respiratory exchange ratio (RER); combined with VML, carbohydrate oxidation was ~23% greater than VML alone, but lipid oxidation was largely unchanged. Activity restriction combined with VML increased whole-body carbohydrate usage. Together there was a greater pACC:ACC ratio in the muscle remaining, which may contribute to decreased fatty acid synthesis. Further, β-HAD activity normalized to mitochondrial content was decreased following VML, suggesting a diminished capacity to oxidize fatty acids. The muscle metabolome was not altered by the restriction of physical activity. The combination of VML and activity restriction resulted in similar ( ~ 91%) up- and down-regulated metabolites and/or ratios, suggesting that VML injury alone is regulating changes in the metabolome. Data supports possible VML-induced alterations in fatty acid metabolism are exacerbated by activity restriction. Collectively, this work adds to the sequalae of VML injury, exhausting the ability of the muscle remaining to oxidize fatty acids resulting in a possible accumulation of triglycerides.
Finite‐time stabilization control of nonlinear systems with full‐state constraints
Authors: Liu Jianwen , Yan Xiao , Zhang Lin , Jia Fujin , Yang Ni 
Published: April 2024

AbstractThis paper studies the finite time stabilization control (FTSC) problem of nonlinear systems with unknown functions and full‐state constraints (FSCs). A lemma dealing with unknown functions is put forward so that the assumptions and the “explosion of terms” (EOT) of backstepping are avoided. Compared with approximation algorithms, this algorithm can make the system states converge to the origin in a finite time. On the other hand, a new logarithmic constraint function is utilized to solve the drawback of barrier Lyapunov functions (BLFs). Then, combined with finite time control (FTC), an FTSC algorithm with FSCs is proposed. Finally, simulations of Chua's circuit system are given to verify the effectiveness and superiority of this algorithm. Compared with the approximation algorithm, this algorithm can theoretically make the states of Chua's circuit system to the origin in a finite time.
Phenylazo-BODIPYs: Direct Access via Pd-Catalysis
Authors: Werz Daniel B. , Röttger Sebastian H. , Birk Anjuli J. , Butschke Burkhard , Jones Peter G. 
Published: April 2024

AbstractA new type of functionalized BODIPY dyes is described. Utilizing an established procedure for Buchwald–Hartwig reactions, we have been able to convert α-chloro BODIPYs to α-azo-BODIPYs using phenylhydrazines. Optimization of the reaction conditions and variation of the BODIPY core and the phenylhydrazine were conducted. Absorption and emission spectra were recorded.
Daily and Momentary Associations Between Gender Minority Stress and Resilience With Alcohol Outcomes
Authors: Dermody Sarah S , Uhrig Alexandra , Wardell Jeffrey D , Tellez Carmina , Raessi Tara , Kovacek Karla , Hart Trevor A , Hendershot Christian S , Abramovich Alex 
Published: April 2024

Abstract

Background and purpose
Minority stressors have been linked with alcohol use among transgender and gender diverse (TGD); however, no ecological momentary assessment studies have examined daily links between minority stress and alcohol use specifically among TGD. This study examined gender minority stressors and resilience as predictors of same-day or momentary alcohol-related outcomes. Feasibility and acceptability of procedures were evaluated.

Methods
Twenty-five TGD adults (mean age = 32.60, SD = 10.82; 88% White) were recruited Canada-wide and participated remotely. They completed 21 days of ecological momentary assessment with daily morning and random surveys (assessing alcohol outcomes, risk processes, gender minority stressors, resilience), and an exit interview eliciting feedback.

Results
Gender minority stress had significant and positive within-person relationships with same-day alcohol use (incidence risk ratio (IRR) = 1.12, 95% confidence interval [CI] [1.02, 1.23]), alcohol-related harms (IRR = 1.14, 95% CI [1.02, 1.28]), and coping motives (IRR = 1.06, 95% CI [1.03, 1.08]), as well as momentary (past 30-min) alcohol craving (IRR = 1.32, 95% CI [1.18, 1.47]), coping motives (IRR = 1.35, 95% CI [1.21, 1.51]), and negative affect (IRR = 1.28, 95% CI [1.20, 1.36]). Gender minority stress indirectly predicted same-day drinking via coping motives (ab = 0.04, 95% CI [0.02, 0.08]). Resilience was positively associated with same-day alcohol use (IRR = 1.25, 95% CI [1.03, 1.51]) but not harms.

Conclusions
TGD adults may use alcohol to cope with gender minority stress, which can increase the risk for alcohol-related harms. Interventions are needed to eliminate gender minority stressors and support adaptive coping strategies.
Daily Relationship Functioning and Disordered Eating Behaviors Among Sexual Minority Women in Same-Sex Relationships
Authors: Romano Kelly A , Sandoval Cassidy M , Lewis Robin J , Heron Kristin E 
Published: April 2024

Abstract

Background and Purpose
The present study aimed to examine associations between different types of relationship functioning and disordered eating behaviors (DEBs) in the everyday lives of sexual minority women in same-sex relationships—an at-risk population that has not been assessed in this context.

Methods
Participants included 321 young sexual minority women (Mage = 27.56, SD = 3.67) in same-sex relationships who completed surveys assessing their daily relationship functioning and DEB use each day for a 14-day daily diary period. Multilevel structural equation modeling was used to examine daily-, person-, and couple-level associations among women’s daily relationship functioning (general relationship functioning, positive and negative relational behaviors they and, separately, their partners engaged in) and DEBs (overeating, loss of control eating, emotional eating, and dietary restriction).

Results
Results generally indicated that more positive and less negative daily relationship functioning across all assessed constructs was associated with less same-day emotional eating. In contrast, associations between all daily relationship functioning constructs and loss of control eating were not significant, nor were any relationship functioning-DEB associations at the couple level. More circumscribed patterns of association were identified for associations between the relationship functioning constructs, and overeating and dietary restriction.

Conclusions
Collectively, these findings provide insight into how aspects of daily relationship functioning map onto sexual minority women’s daily engagement in DEBs that are linked to poor health long-term, and directions for future research and clinical practice that may warrant consideration moving forward to help advance the evidence-base and care for this historically overlooked and underserved population.
Diversity and Standards in Writing for Publication in the Age of AI—Between a Rock and a Hard Place
Authors: Kuteeva Maria , Andersson Marta 
Published: April 2024

Abstract
Research communities across disciplines recognize the need to diversify and decolonize knowledge. While artificial intelligence-supported large language models (LLMs) can help with access to knowledge generated in the Global North and demystify publication practices, they are still biased toward dominant norms and knowledge paradigms. LLMs lack agency, metacognition, knowledge of the local context, and understanding of how the human language works. These limitations raise doubts regarding their ability to develop the kind of rhetorical flexibility that is necessary for adapting writing to ever-changing contexts and demands. Thus, LLMs are likely to drive both language use and knowledge construction towards homogeneity and uniformity, reproducing already existing biases and structural inequalities. Since their output is based on shallow statistical associations, what these models are unable to achieve to the same extent as humans is linguistic creativity, particularly across languages, registers, and styles. This is the area where key stakeholders in academic publishing—authors, reviewers, and editors—have the upper hand, as our applied linguistics community strives to increase multilingual practices in knowledge production.
Biologically meaningful regulatory logic enhances the convergence rate in Boolean networks and bushiness of their state transition graph
Authors: Sil Priyotosh , Subbaroyan Ajay , Kulkarni Saumitra , Martin Olivier C , Samal Areejit 
Published: April 2024

Abstract
Boolean models of gene regulatory networks (GRNs) have gained widespread traction as they can easily recapitulate cellular phenotypes via their attractor states. Their overall dynamics are embodied in a state transition graph (STG). Indeed, two Boolean networks (BNs) with the same network structure and attractors can have drastically different STGs depending on the type of Boolean functions (BFs) employed. Our objective here is to systematically delineate the effects of different classes of BFs on the structural features of the STG of reconstructed Boolean GRNs while keeping network structure and biological attractors fixed, and explore the characteristics of BFs that drive those features. Using $10$ reconstructed Boolean GRNs, we generate ensembles that differ in BFs and compute from their STGs the dynamics’ rate of contraction or ‘bushiness’ and rate of ‘convergence’, quantified with measures inspired from cellular automata (CA) that are based on the garden-of-Eden (GoE) states. We find that biologically meaningful BFs lead to higher STG ‘bushiness’ and ‘convergence’ than random ones. Obtaining such ‘global’ measures gets computationally expensive with larger network sizes, stressing the need for feasible proxies. So we adapt Wuensche’s $Z$-parameter in CA to BFs in BNs and provide four natural variants, which, along with the average sensitivity of BFs computed at the network level, comprise our descriptors of local dynamics and we find some of them to be good proxies for bushiness. Finally, we provide an excellent proxy for the ‘convergence’ based on computing transient lengths originating at random states rather than GoE states.
HyGAnno: hybrid graph neural network–based cell type annotation for single-cell ATAC sequencing data
Authors: Zhang Weihang , Cui Yang , Liu Bowen , Loza Martin , Park Sung-Joon , Nakai Kenta 
Published: April 2024

Abstract
Reliable cell type annotations are crucial for investigating cellular heterogeneity in single-cell omics data. Although various computational approaches have been proposed for single-cell RNA sequencing (scRNA-seq) annotation, high-quality cell labels are still lacking in single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq) data, because of extreme sparsity and inconsistent chromatin accessibility between datasets. Here, we present a novel automated cell annotation method that transfers cell type information from a well-labeled scRNA-seq reference to an unlabeled scATAC-seq target, via a parallel graph neural network, in a semi-supervised manner. Unlike existing methods that utilize only gene expression or gene activity features, HyGAnno leverages genome-wide accessibility peak features to facilitate the training process. In addition, HyGAnno reconstructs a reference–target cell graph to detect cells with low prediction reliability, according to their specific graph connectivity patterns. HyGAnno was assessed across various datasets, showcasing its strengths in precise cell annotation, generating interpretable cell embeddings, robustness to noisy reference data and adaptability to tumor tissues.
A deep learning approach to direct immunofluorescence pattern recognition in autoimmune bullous diseases
Authors: Capurro Niccolò , Pastore Vito Paolo , Touijer Larbi , Odone Francesca , Cozzani Emanuele , Gasparini Giulia , Parodi Aurora 
Published: April 2024

Abstract

Background
Artificial intelligence (AI) is reshaping healthcare, using machine and deep learning (DL) to enhance disease management. Dermatology has seen improved diagnostics, particularly in skin cancer detection, through the integration of AI. However, the potential of AI in automating immunofluorescence imaging for autoimmune bullous skin diseases (AIBDs) remains untapped. While direct immunofluorescence (DIF) supports diagnosis, its manual interpretation can hinder efficiency. The use of DL to classify DIF patterns automatically, including the intercellular (ICP) and linear pattern (LP), holds promise for improving the diagnosis of AIBDs.

Objectives
To develop AI algorithms for automated classification of AIBD DIF patterns, such as ICP and LP, in order to enhance diagnostic accuracy, streamline disease management and improve patient outcomes through DL-driven immunofluorescence interpretation.

Methods
We collected immunofluorescence images from skin biopsies of patients suspected of having an AIBD between January 2022 and January 2024. Skin tissue was obtained via a 5-mm punch biopsy, prepared for DIF. Experienced dermatologists classified the images as ICP, LP or negative. To evaluate our DL approach, we divided the images into training (n = 436) and test sets (n = 93). We employed transfer learning with pretrained deep neural networks and conducted fivefold cross-validation to assess model performance. Our dataset’s class imbalance was addressed using weighted loss and data augmentation strategies. The models were trained for 50 epochs using Pytorch, achieving an image size of 224 × 224 pixels for both convolutional neural networks (CNNs) and the Swin Transformer.

Results
Our study compared six CNNs and the Swin Transformer for AIBD image classification, with the Swin Transformer achieving the highest average validation accuracy (98.5%). On a separate test set, the best model attained an accuracy of 94.6%, demonstrating 95.3% sensitivity and 97.5% specificity across AIBD classes. Visualization with Grad-CAM (class activation mapping) highlighted the model’s reliance on characteristic patterns for accurate classification.

Conclusions
The study highlighted the accuracy of CNNs in identifying DIF features. This approach aids automated analysis and reporting, offering reproducibility, speed, data handling and cost-efficiency. Integrating DL into skin immunofluorescence promises precise diagnostics and streamlined reporting in this branch of dermatology.
Acne-induced pathological scars: pathophysiology and current treatments
Authors: Xu Wanyu , Sinaki Dorsa Gholamali , Tang Yuchen , Chen Yunsheng , Zhang Yixin , Zhang Zheng 
Published: April 2024

Abstract
Acne is a common chronic inflammatory dermatosis that can lead to pathological scars (PSs, divided into hypertrophic scars and keloids). These kinds of abnormal scars seriously reduce the quality of life of patients. However, their mechanism is still unclear, resulting in difficult clinical prevention, unstable treatment effects and a high risk of recurrence. Available evidence supports inflammatory changes caused by infection as one of the keys to abnormal proliferation of skin fibroblasts. In acne-induced PSs, increasing knowledge of the immunopathology indicates that inflammatory cells directly secrete growth factors to activate fibroblasts and release pro-inflammatory factors to promote the formation of PSs. T helper cells contribute to PSs via the secretion of interleukin (IL)-4 and IL-13, the pro-inflammatory factors; while regulatory T cells have anti-inflammatory effects, secrete IL-10 and prostaglandin E2, and suppress fibrosis production. Several treatments are available, but there is a lack of combination regimens to target different aspects of acne-induced PSs. Overall, this review indicates that the joint involvement of inflammatory response and fibrosis plays a crucial role in acne-induced PSs, and also analyzes the interaction of current treatments for acne and PS.
Microsatellite Instability Detection in Cancer: A Multiplex qPCR Approach that Obviates the Need for Matching Normal Samples
Authors: Chen Wei , Yan Yan Helen , Young Blake , Pinto Alessandro , Jiang Qi , Song Nanjia , Yaseen Adam , Yao Weijie , Zhang David Yu , Zhang Jinny Xuemeng 
Published: April 2024

Abstract

Background
Microsatellite instability (MSI) indicates DNA mismatch repair deficiency in certain types of cancer, such as colorectal cancer. The current gold standard technique, PCR–capillary electrophoresis (CE), requires matching normal samples and specialized instrumentation. We developed VarTrace, a rapid and low-cost quantitative PCR (qPCR) assay, to evaluate MSI using solely the tumor sample DNA, obviating the requirement for matching normal samples.

Methods
One hundred and one formalin-fixed paraffin-embedded (FFPE) tumor samples were tested using VarTrace and compared with the Promega OncoMate assay utilizing PCR-CE. Tumor percentage limit of detection was evaluated on contrived samples derived from clinical high MSI (MSI-H) samples. Analytical sensitivity, specificity, limit of detection, and input requirements were assessed using synthetic commercial reference standards.

Results
VarTrace successfully analyzed all 101 clinical FFPE samples, demonstrating 100% sensitivity and 98% specificity compared to OncoMate. It detected MSI-H with 97% accuracy down to 10% tumor. Analytical studies using synthetic samples showed a limit of detection of 5% variant allele frequency and a limit of input of 0.5 ng.

Conclusions
This study validates VarTrace as a swift, accurate, and economical assay for MSI detection in samples with low tumor percentages without the need for matching normal DNA. VarTrace's capacity for highly sensitive MSI analysis holds potential for enhancing the efficiency of clinical work flows and broadening the availability of this test.
Responsibly Buying Artificial Intelligence: A ‘Regulatory Hallucination’
Authors: Sanchez-Graells Albert 
Published: April 2024

Abstract
As part of its ‘pro-innovation’ approach to artificial intelligence (AI), the UK has left public sector AI procurement and deployment to ‘regulation by contract’ based on thin guidance. Borrowing from the description of AI ‘hallucinations’ as plausible but incorrect answers given with high confidence by AI systems, I argue that this is a ‘regulatory hallucination’: an incorrect answer to the challenge of regulating the procurement and use of AI by the public sector. The pretence that public buyers can ‘confidently and responsibly procure AI technologies’ can generate individual harms and broader negative social effects as the public sector ramps up AI adoption and accumulates a potentially significant stock of AI deployments across all areas of public sector activity. I sketch an alternative strategy to boost the effectiveness of the goals of AI regulation and the protection of individual rights and collective interests through the creation of an independent authority.
Risk of metastasis among patients diagnosed with high-risk T1 esophageal adenocarcinoma who underwent endoscopic follow-up
Authors: Norton Benjamin Charles , Aslam Nasar , Telese Andrea , Papaefthymiou Apostolis , Singh Shilpi , Sehgal Vinay , Mitchison Miriam , Jansen Marnix , Banks Matthew , Graham David , Haidry Rehan 
Published: April 2024

SummaryEsophagectomy and lymphadenectomy have been the standard of care for patients at high risk (HR) of lymph node metastasis following a diagnosis of early esophageal adenocarcinoma (OAC) after endoscopic resection (ER). However, recent cohorts suggest lymph node metastasis risk is lower than initially estimated, suggesting organ preservation with close endoscopic follow-up is a viable option. We report on the 3- and 5-year risk of lymph node/distant metastasis among patients diagnosed with early HR-T1 OAC undergoing endoscopic follow-up. Patients diagnosed with HR-T1a or T1b OAC following ER at a tertiary referral center were identified and retrospectively analyzed from clinical records between 2010 and 2021. Patients were included if they underwent endoscopic follow-up after resection and were divided into HR-T1a, low risk (LR)-T1b and HR-T1b cohorts. After ER, 47 patients underwent endoscopic follow-up for early HR OAC. In total, 39 patients had an R0 resection with a combined 3- and 5-year risk of LN/distant metastasis of 6.9% [95% confidence interval (CI): 1.8–25] and 10.9% (95% CI, 3.6–30.2%), respectively. There was no significant difference when stratifying by histopathological subtype (P = 0.64). Among those without persistent luminal disease on follow-up, the 5-year risk was 4.1% (95% CI, 0.6–26.1). Two patients died secondary to OAC with an all-cause 5-year survival of 57.5% (95% CI, 39.5–71.9). The overall risk of LN/distant metastasis for early HR T1 OAC was lower than historically reported. Endoscopic surveillance can be a reasonable approach in highly selected patients with an R0 resection and complete luminal eradication, but clear, evidence-based surveillance guidelines are needed.
Proliferation in malaria parasites: How resource limitation can prevent evolution of greater virulence
Authors: Pak Damie , Kamiya Tsukushi , Greischar Megan A 
Published: April 2024

Abstract
For parasites, robust proliferation within hosts is crucial for establishing the infection and creating opportunities for onward transmission. While faster proliferation enhances transmission rates, it is often assumed to curtail transmission duration by killing the host (virulence), a trade-off constraining parasite evolution. Yet in many diseases, including malaria, the preponderance of infections with mild or absent symptoms suggests that host mortality is not a sufficient constraint, raising the question of what restrains evolution toward faster proliferation. In malaria infections, the maximum rate of proliferation is determined by the burst size, the number of daughter parasites produced per infected red blood cell. Larger burst sizes should expand the pool of infected red blood cells that can be used to produce the specialized transmission forms needed to infect mosquitoes. We use a within-host model parameterized for rodent malaria parasites (Plasmodium chabaudi) to project the transmission consequences of burst size, focusing on initial acute infection where resource limitation and risk of host mortality are greatest. We find that resource limitation restricts evolution toward higher burst sizes below the level predicted by host mortality alone. Our results suggest resource limitation could represent a more general constraint than virulence–transmission trade-offs, preventing evolution towards faster proliferation.