bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Structural Equation Model Predicts Chronic Wound Healing Time Using Patient Characteristics and Wound Microbiome Composition
Authors: Ancira Jacob , Gabrilska Rebecca , Tipton Craig , Miller Clint , Stickley Zachary , Omeir Khalid , Wakeman Catherine , Little Todd , Wolcott Joseph , Philips Caleb D. 
Published: January 2025

ABSTRACTWound etiology, host characteristics, and the wound microbiome contribute to chronic wound development. Yet, there is little accounting for the relative importance of these factors to predict wound healing. Here, a structural equation model was developed to provide such an explanatory and predictive framework. Chronic wounds from 565 patients treated at a clinic practicing biofilm-based wound care were included. Patient information included DNA sequencing-based wound microbiome clinical reports corresponding to initial clinical visit. Wound microbiome data was integrated into the SEM as a latent variable using a pre-modeling parcel optimization routine presented herein for the first time (available as R libraryparcelR). A microbiome latent construct associated with improved healing was validated, and the final SEM included this latent construct plus three species associated with diminished healing (Anaerococcus vaginalis, Finegoldia magna, Pseudomonas aeruginosa), as well as smoking, wound volume, slough, exudate, edema, percent granulation, and wound etiology This model explained 46% of variation in healing time with the microbiome contributing the largest proportion of variance explained. Model validity was confirmed with an independent cohort (n = 79) through which ∼60% of variation in healing time was predicted. This model can serve as foundation for development of a predictive tool that may have clinical utility.
Neural Correlates of Non-Suicidal Self-Injury Functions: Neurobiological Vulnerabilities and Psychosocial Risks in Psychiatric Disorders
Authors: Li Mingzhu , Xiao Yang , Ge Yuqi , Yan Huiru , Li Xueni , Yue Weihua , Yan Hao 
Published: January 2025

AbstractBackgroundNon-suicidal self-injury (NSSI) is common in adolescents and young adults, especially among psychiatric disorders. It arises from neurobiological and psychosocial factors, yet its underlying mechanisms remain unclear.MethodsA total of 304 inpatients (aged 16–25 years) with NSSI and psychiatric diagnoses (major depressive disorder [MDD], bipolar disorder [BD], and eating disorders [ED]) were assessed using the Ottawa Self-Injury Inventory. Resting-state functional magnetic resonance imaging were collected from 163 of them. Functional factors, representing motivations of NSSI, were identified using orthogonal projection non-negative matrix factorization. These factors were then linked to brain functional connections (FC) via canonical correlation analysis and used to classify patients into subtypes through fuzzy C-means clustering. Differences in FC and psychosocial characteristics were analyzed across subtypes.ResultsTwo NSSI functional factors were identified: self-related and social-related. Self-related factor was associated with an amygdala-centered cortico-limbic network and prevalent in affective disorders (MDD and BD). Social-related factor correlated with frontoparietal and frontotemporal networks, prominent in ED. Clustering identified three NSSI functional subtypes. Subtype 1 was primarily driven by self-related functions. Subtype 2 was influenced by both self- and social-related functions with greater exposure to psychosocial risks. Subtype 3 remained undifferentiated. No subtype exclusively driven by social-related function was observed.ConclusionThis study establishes the neural correlates of a “self-social” functional model of NSSI. Self-related functions are underpinned by emotional regulation networks, while social-related functions synergize with psychosocial risks via cognitive-emotional regulation pathways. These findings highlight the need for tailored psychological and neuromodulatory interventions targeting specific functional subtypes.
A Systematic Literature Review of Randomized Trials Comparing In-Person and Digital Interventions for Type 2 Diabetes Prevention
Authors: Riera-Serra Pau , Morales-Hernández David , Fiol-deRoque Maria Antonia , Zamanillo-Campos Rocío , Ricci-Cabello Ignacio 
Published: January 2025

ABSTRACTBackgroundDigital and in-person lifestyle interventions to prevent type 2 diabetes (T2DM) are being increasingly implemented in some countries, particularly in the United States. However, their comparative effectiveness remains unclear, partly due to variability in intervention designs and limited robust evidence from randomized controlled trials (RCTs). Understanding their relative impacts is critical for informing evidence-based implementation in diverse healthcare settings.AimTo compare the effectiveness of digital versus in-person interventions for preventing T2DM.MethodsWe conducted a systematic literature review, following Cochrane methodology to identify and synthesize evidence from RCTs. Searches were conducted in EMBASE, MEDLINE, and Cochrane CENTRAL from inception to December 2024, including completed and ongoing trials published in English or Spanish. Studies comparing purely digital and in-person interventions were eligible. Meta-analyses were performed where appropriate, and narrative syntheses were provided for remaining outcomes. The GRADE approach was used to assess the certainty of evidence.ResultsEight RCTs met the inclusion criteria, including six completed trials with published results and two ongoing trials. The completed trials encompassed a total of 2,450 participants across various healthcare settings. At 12 months, digital interventions were associated with significantly greater weight loss than in-person interventions (mean difference: –1.38 kg [95% CI: –2.34 to –0.43]), with moderate certainty of evidence. At shorter (3 and 6 months) and longer (>12 months) time points, no relevant differences were observed for weight, body mass index, or glycosylated haemoglobin levels between the modalities, with the certainty of evidence rated as low to very low. Evidence about cost-effectiveness was scarce. No trials evaluated key outcomes such as incidence of T2DM or health-related quality. For adverse events, no significant differences were found between modalities (RR: 1.06 [95% CI: 0.45 to 2.50]).ConclusionsThis systematic review highlights that while digital and in-person interventions can both be effective for T2DM prevention, their relative benefits depend on follow-up duration and contextual factors. The limited certainty of evidence and the absence of trials addressing critical outcomes, such as T2DM incidence, underscore the need for further well- designed RCTs. Future research should prioritize equivalence in intervention intensity, longer follow-up durations, and standardized reporting of outcomes to better inform public health decision-making.
Understanding the causes and consequences of low statin adherence: evidence from UK Biobank primary care data
Authors: Türkmen Deniz , Liang Xiaoran , Masoli Jane A H , Gill Dipender , Pilling Luke C , Bowden Jack 
Published: January 2025

AbstractBackgroundStatins are commonly prescribed to lower LDL cholesterol. Clinical guidelines recommend 30-50% reduction within 3 months, yet many patients do not achieve this. We investigated the impact of patient characteristics and genetics on LDL-c reduction, treatment adherence, and adverse clinical outcomes.MethodsWe analysed 76,000 UK Biobank participants prescribed atorvastatin or simvastatin in primary care: 41,000 had LDL-c measurements before statin initiation (median=16 days prior, IQR=28) and within a year of starting treatment (median=89 days, IQR=125). Adherence was defined as the “proportion of days covered” (PDC). We estimated associations between PDC within one year of statin initiation, genetic factors, post-treatment LDL reduction, and clinical adverse outcomes. For 13,000 patients with ≥3 LDL-c measures, we used inverse probability weighting methods to estimate the effect of sustained adherence intervention on LDL-c reduction longitudinally.ResultsPredictors of LDL-c reduction following statin initiation included the time until the 1stmeasurement, PDC, and the pharmacogenetic variantSLCO1B1*5. LDL-c reduction was greater in those with high adherence versus lower adherence (38% reduction when PDC>95% [high] vs. 15% when PDC<50% [low]). Longitudinal causal modelling showed that the most recent PDC measure exerted the largest influence on overall LDL-c reduction, followed by the initial PDC.Genetic predictors of reduced PDC included liability to schizophrenia (Coeftop20%-1.94, 95%CI -2.69 to -1.19), whilst genetic liability to cardiovascular diseases increased PDC (Coeftop20%1.30, 95%CI 0.55 to 2.05). High PDC was associated with increased risk of incident iron deficiency anaemia (HR 1.30, 95%CI 1.09-1.54) and cataract (HR 1.20, 95%CI 1.07-1.34), and decreased risk of incident coronary heart disease (HR 0.78, 95%CI 0.73-0.84).ConclusionWe identify substantial variability in the time to first on-treatment LDL measurements and also in adherence to statin medication, highlighting a gap between NHS guidelines, LDL monitoring and statin adherence. We show its subsequent impact on long term health, demonstrating the potential effect of targeted interventions to improve adherence. We identify important predictors of reduced statin effectiveness, including pharmacogenetic variants, polygenic scores, but most of all, adherence. Tailored statin therapy strategies with patient education on statin indication and adherence could optimise treatment efficacy, safety, and long-term clinical outcomes.
Assessment of SARS-CoV2 genome sequence recovery from four lateral flow device products available in the UK
Authors: Lewandowski Kuiama , Stokes Matthew , Alexandridou Alexandra , Fenwick Abigail , White Mia L. , Crook Jack , Rogers-Broadway Karly-Rai , Ryan Catherine , Williamson Deborah A. , Vipond Richard , Pullan Steven T. 
Published: January 2025

AbstractLateral flow tests have played a key role in the response to the COVID-19 pandemic and are likely to be a major component of diagnostic strategies to combat future outbreaks of infectious disease. One challenge posed by widescale use of lateral flow tests in the community is the loss of sequence information to track virus evolution and epidemiology.Beyond their primary diagnostic function, it has been demonstrated that recovery of viral RNA for genome sequencing purposes is possible, from positive lateral flow devices (LFDs).To assess the robustness and broader applicability of this process, we assessed SARS-CoV-2 RNA recovery and sequencing from the four major LFDs in use in the UK.Testing both cultured virus and residual clinical nasal swab samples demonstrated that sequencing from LFD eluates is possible, at clinically relevant titres, within a reasonable processing time frame post-use, and gave sequences concordant with routine methods, but results varied across the four devices used.This highlights the requirement for refinement of existing LFDs or of second–generation LFD design, where sequencing is an intended output from positive LFDs.
Approach-Avoidance Tendencies Influence the Relationship Between Fear of Movement and Physical Activity in Osteoarthritis
Authors: Goubran Miriam , Zammar Christian , Tellez Alvarez Santiago , Héran Élodie , Proulx Sara , Bilodeau Martin , Boisgontier Matthieu P. 
Published: January 2025

ABSTRACTPurposeAlmost twice as many people with arthritis report being physically inactive compared to people without arthritis. The objective of this study was to examine whether psychological processes including fear of movement, explicit attitudes, and approach-avoidance tendencies toward physical activity, are associated with lower physical activity levels in people with arthritis.MethodsAn online observational study was conducted in 197 participants, including 68 with osteoarthritis and 13 with rheumatoid arthritis. Arthritis, fear of movement, usual level of physical activity, and explicit attitudes were assessed using questionnaires. Approach-avoidance tendencies, an indicator of implicit attitudes, was derived from reaction times in an approach-avoidance task.ResultsResults showed that higher fear of movement was associated with lower physical activity levels in participants with osteoarthritis than in those without osteoarthritis. This association was moderated by approach-avoidance tendencies toward physical activity, with a significant effect only in participants with an automatic tendency to avoid physical activity or a weak tendency to approach it. In addition, contrary to our hypothesis, higher fear of movement was associated with a stronger tendency to approach physical activity and avoid sedentary behaviors, suggesting that people who were most fearful of movement may also be those who unconsciously internalized the importance of physical activity the most.ConclusionThis study suggests that in adults with osteoarthritis, the detrimental effect of fear of movement on usual physical activity levels may be mitigated by strong automatic tendencies to approach physical activity. Since these tendencies result from the automatic activation of affective memories, health professionals should consider not only promoting physical activity but also ensuring its association with positive emotional experiences.
Changes in public perception of AI in healthcare after exposure to ChatGPT
Authors: Isaksen Anders Aasted , Schaarup Jonas Rosborg , Bjerg Lasse , Hulman Adam 
Published: January 2025

AbstractBackgroundArtificial intelligence (AI) is expected to become an integral part of healthcare services, and the widespread adoption of AI tools in all areas of life is making AI accessible to the general public. Public perception of the benefits and risks of AI in healthcare is key to large-scale acceptance and implementation, and is increasingly influenced by first-hand experiences of AI. The aim of this study was to assess how exposure to ChatGPT changed public perception of AI in healthcare.MethodsWe used baseline and follow-up data from 5,899 survey participants, who reported their perception of AI in 2022 and 2024, and ChatGPT use in 2024. Administrative and healthcare data from nationwide Danish registers was used for weighting and adjustment. Multinomial multivariate logistic regression was used to model how exposure to ChatGPT use affected changes in perception of AI.ResultsAt baseline (before ChatGPT’s launch) 2,236 individuals (37%) were unsure of the benefits and risks of AI in healthcare, 2,384 (40%) perceived net benefits, 1,083 (18%) perceived benefits and risks as equal, and 196 (3.3%) perceived net risks. At follow-up, 1,195 individuals (20%) had been exposed to ChatGPT use, which was associated with higher odds of changing perception of AI to benefits (OR 3.21 [95% CI: 2.34-4.40]) among individuals who were unsure at baseline, and lower odds of changing to uncertainty from more defined baseline perceptions (from benefits (OR 0.32 [0.24-0.42]), equal (OR 0.47 [0.32-0.69]) and risks (OR 0.27 [0.08-0.98])).ConclusionExposure to ChatGPT was associated with a change towards positive perception of benefits and risks of AI in healthcare among individuals who were uncertain prior to exposure, and individuals with more defined perceptions of AI were less likely to become uncertain after exposure to ChatGPT.
Network meta-analysis combining survival and count outcome data: A simple frequentist approach
Authors: Noma Hisashi , Maruo Kazushi 
Published: January 2025

AbstractNetwork meta-analysis for survival outcome data often involves several studies only reported dichotomized outcomes (i.e., the numbers of events and sample sizes of individual arms). To avoid the reporting biases via eliminating these studies in the syntesis analyses, Woods et al. (2010;BMC Med Res Methodol10:54) proposed a Bayesian approach to combine the survival and dichotomized outcome data using hierarchical models. However, the Bayesian methods require complicated computations involving the Markov Chain Monte Carlo and the technical aspects are generally difficult to handle by non-statisticians (e.g., the convergence diagnostics). Besides, frequentist approaches have been alternative standard methods for statistical analyses of network meta-analysis. The methodology has been well established, and several effective software packages have been developed (e.g.,netmetapackage in R). In this article, we propose a simple method to synthesis the survival and dichotomized outcome data within the frequentist framework using the contrast-based models. We also provide a R packagesurvNMA(https://doi.org/10.32614/CRAN.package.survNMA) to calculate hazard ratio statistics from the dichotomized outcome data that can be directly used for implementing general analyses of network meta-analysis usingnetmetapackage of R.
Seasonal Variations and Challenges in Estimating Populations and Identifying Species of Korean Ungulates Using Drone-Derived Thermal Orthomosaic Maps
Authors: Kim Jinhwi , Woo Donggul 
Published: January 2025

AbstractThermal drones offer significant time and labor savings in estimating wild ungulate populations. Among available methods, Thermal Infrared (TIR) orthomosaic maps have shown potential for animal counting and population estimation. In this study, we assessed the feasibility of counting Korean ungulates in March and June using TIR and RGB orthomosaic maps, aiming to compare population estimates across season and identify the appropriate Ground Sampling Distance (GSD). The average estimated population was 25.3 ± 4.2 individuals (range: 18–29) in March and 28.2 ± 9.1 individuals (range: 14–40) in June. The average counting error was 4.1 (95% CI: 1.3–6.9) across the orthomosaic maps, with no substantial difference between March and June (P = 0.75). Counting errors increased when RGB GSD exceeded 2.5 cm/pix and TIR GSD exceeded 7.5 cm/pix, suggesting that these thresholds may guide future GSD selection for more accurate population estimates. We measured 149 thermal marks for species identification across three ungulate species. MANOVA revealed strong effects of species (P < 0.001) and posture (P < 0.001) on body measurements, but variations in posture limited the effectiveness of thermal mark measurements for species identification. This issue was especially prominent in lying positions, where species overlap occurred. Further data collection on thermal measurements from TIR orthomosaic maps, particularly from a perpendicular angle and across diverse environments and postures, could improve the accuracy of thermal methods for species identification.
High-dose DFMO alters protein translation in neuroblastoma
Authors: Franson Andrea T. , Liu Kangning , Vemu Rohan , Scadden Elizabeth , Li Yimei , Vu Annette , Hogarty Michael D. 
Published: January 2025

ABSTRACTDFMO has been studied as a cancer therapeutic at doses ranging from 500-9,000 mg/m2/day. Lower doses are favored for cancer prevention studies while higher doses, often with chemotherapy, are studied in refractory cancers. DFMO inhibits the rate-limiting enzyme in polyamine synthesis, ornithine decarboxylase (ODC), an oncogene transcriptionally regulated by MYC.MYCgenes are the principal oncogenic drivers of neuroblastoma, andODC1is co-amplified in a subset with dismal outcome, so DFMO is a rational therapeutic candidate. Low-dose DFMO has now been FDA-approved for high-risk patients though the mechanisms for its anti-tumor activity, and the exposures required to elicit them, remain obscure. We sought to define biomarkers of activity across exposures achieved in the clinic with low through high-dose DFMO. Polyamines support protein translation by providing spermidine, which is essential to hypusinate (and activate) the elongation factor, eIF5A. Selective binding of polyamines with tRNA and rRNA provide eIF5A-independent mechanisms of translation support. We show that low-dose DFMO does not extend survival in mouse modelsin vivonor alter translation biomarkersin vitro. High-dose DFMO consistently extends survival in neuroblastoma models, and, in a subset of neuroblastoma cell lines, inhibits eIF5A hypusination and global translation at achievable concentrations. However, the concentration required to engage these changes across many cell lines exceeded that achievable even with high-dose DFMO. No correlation was seen amongMYCNand/orODC1copy number and sensitivity to DFMO. Combining high-dose DFMO with additional agents to further deplete tumor polyamines may be necessary to fully engage polyamine-depletion effects on tumors, and more granular measures of translation, including codon-resolution ribosome profiling, may be required to define these effects.STATEMENT OF TRANSLATIONAL RELEVANCELow-dose DFMO is approved by the FDA for the treatment of neuroblastoma. The depletion of tumor polyamines has been shown to have activity against tumors with activatedMYCsignaling, like neuroblastoma, yet the degree of polyamine depletion required, the mechanisms by which this impedes tumor progression, and the DFMO exposures required to enable these are poorly understood. Here we evaluate alterations in protein translation as putative mechanisms for DFMO activity. Translation biomarkers and colony formation can be inhibited by DFMOin vitroat exposures achievablein vivowith high-dose DFMO. Similarly, high-dose DFMO, but not low-dose DFMO, extends neuroblastoma-prone mouse survival. These findings support studying DFMO at higher doses and in therapeutic combinations that further augment polyamine depletion within tumors.
Efficacy of Deferoxamine Mesylate in Serum and Serum-Free Media: Adult Schwann Cell Survival Following Hydrogen Peroxide Induced Cell Death
Authors: Ma Yee H.E. , Putta Abhinay R. , Chan Cyrus H. H. , Vidman Stephen , Monje Paula , Plant Giles W. 
Published: January 2025

AbstractSchwann cell (SC) transplantation shows promise in treating spinal cord injury as a pro-regenerative agent to allow host endogenous neurons to bridge over the lesion. However, SC transplants face significant oxidative stress facilitated by ROS in the lesion leading to poor survival. Deferoxamine Mesylate (DFO) is a neuroprotection agent shown to reduce H2O2induced cell death in serum containing conditions, here we show that DFO is not necessary to induce neuroprotection under serumfree conditions by cell survival quantification and phenotypic analysis via immunohistochemistry, Hif1a and collagen IV quantification via whole cell corrected total cell fluorescence, and cell death transcript changes via RT-qPCR. Our results indicate survival of SC regardless of DFO pretreatment in serum-free conditions and an increased survival facilitated by DFO in serum containing conditions. Furthermore, our results showed strong nuclear expression of Hif1a in serum-free conditions regardless of DFO pretreatment and a nuclear expression of Hif1a in DFO treated SCs in serum conditions. Transcriptomic analysis reveals upregulation of autophagy transcripts in SCs grown in serum-free media relative to SCs in serum conditions, with and without DFO and H2O2. Thus, indicating a pro-repair and regenerative state of the SCs in serum free conditions. Overall, results indicate the protectiveness of chemically defined medium in enhancing SC survival against ROS induced cell deathin vitro.