bluuebunny/crossref_metadata_2025_split huggingface dataset:
Allostatic Load in Parents and Offspring
Authors: Muchira James M. , Mogos Mulubrhan F. , S. Dietrich Mary , Kimathi Boniface , Ziegler Carol , Heerman William J. , Hall Kelli S. 
Published: January 2025

Background
Allostatic load (AL), a measure of cumulative stress-related physiological dysregulation, predicts the onset of chronic diseases. We investigated the relationship between AL and cardiovascular disease (CVD)–free survival in parents and offspring, including sex-specific differences.

Methods
The analysis consisted of 6145 offspring-mother-father trios derived from the Framingham Heart Study. Clinically defined cutoffs from 9 physiological biomarkers across biological systems were used to generate composite AL score. Assessments of the associations of AL with CVD-free survival were conducted using Kaplan-Meier plots, Irwin's restricted means, and Cox proportional hazards regression models.

Results
Over a 47-year period, parents and offspring experienced 1832 and 1060 incident CVD events, respectively. Parents exhibited a notably higher prevalence of high AL (29.5%) and CVD incidence rate (17.2 per 1000 person-years) compared with offspring (13.2% and 8.9, respectively, both P < .001). High parental AL was associated with 30% higher incident CVD risk in offspring, with maternal AL biomarkers being more predictive of offspring CVD risk than paternal. Parents and offspring with low AL lived 12.5 and 13.4 years longer without CVD, respectively, compared with those with high AL. The hazards of incident CVD were highest in daughters with high AL, up to 2.8 times (hazard ratio, 2.83; 95% confidence interval, 1.71–4.67), with similar risk observed in sons and parents.

Conclusion
Parental AL is associated with offspring CVD risk, with maternal AL biomarkers having a stronger association. This highlights the critical role of parental and, more importantly, maternal health in CVD risk management and broader public health strategies.
Perinatal outcomes among pregnant women living with HIV initiating antiretroviral therapy preconception and antenatally: systematic review and meta-analysis
Authors: Boering Pippa , Murray Claudia , Portwood Clara , Hey Molly , Thompson Lucy , Beck Katharina , Cowdell Imogen , Sexton Harriet , Kumarendran Mary , Brandon Zoe , Kirtley Shona , Hemelaar Joris 
Published: January 2025

Objective:
Increasingly, pregnant women living with HIV (WLHIV) initiate antiretroviral therapy (ART) before conception. We assessed the risk of adverse perinatal outcomes among pregnant WLHIV initiating ART preconception or antenatally, compared with women without HIV or ART-naïve WLHIV.

Design:
Systematic review and meta-analysis

Methods:
We searched PubMed, EMBASE, CINAHL, and Global Health for studies published between 1/1/1980 and 14/7/2023. We assessed the association of preconception/antenatal ART initiation with preterm birth (PTB), very PTB (VPTB), spontaneous PTB (sPTB), low birthweight (LBW), very LBW (VLBW), small-for-gestational-age (SGA), very SGA (VSGA), stillbirth and neonatal death (NND). Data were analysed using random effects meta-analyses. Quality assessments, subgroup and sensitivity analyses were conducted. PROSPERO registration: CRD42021248987.

Results:
Thirty-one cohort studies were eligible, including 199,156 women in 19 countries. WLHIV with preconception ART were associated with increased risk of PTB (risk ratio 1.55; 95%CI 1.27–1.90), VPTB (2.14,1.02–4.47), LBW (2.19, 1.32–3.63), VLBW (3.34, 1.08–10.35), SGA (1.92, 1.01–3.66), and VSGA (2.79, 1.04–7.47), compared with women without HIV. WLHIV with antenatal ART were associated with increased risk of PTB (1.35, 1.15–1.58), LBW (2.16, 1.39–3.34), VLBW (1.97, 1.01–3.84), SGA (1.77, 1.10–2.84), and VSGA (1.21, 1.09–1.33), compared with women without HIV. Compared to ART-naïve WLHIV, WLHIV with preconception or antenatal ART were associated with increased risk of SGA (preconception: 1.40, 1.12–1.73; antenatal: 1.39, 1.11–1.74) and VSGA (preconception: 2.44, 1.63–3.66; antenatal: 2.24, 1.48–3.40).

Conclusion:
Among WLHIV, both preconception and antenatal initiation of ART are associated with increased risks of adverse perinatal outcomes, compared to women without HIV and ART-naïve WLHIV.
Structural evolution of the estrogen receptor regulatory domain
Authors: McDougal Daniel P. , Pederick Jordan L. , Shearwin-Whyatt Linda , Grützner Frank , Bruning John B. 
Published: January 2025

AbstractEstrogen receptors (ERs) α, β and γ are ligand-dependent transcription factors that regulate vertebrate reproduction, cell survival and other physiological processes. Here, we report an integrative analysis of mammalian and teleost receptors, including the first structure of an ERγ ligand binding domain (LBD), showing that structural divergence acquired during evolution is accommodated by different strategies within functional regions to preserve intrinsic regulatory mechanisms. Supervised-learning and comparative Markov modelling uncover highly constrained network structures essential for allostery and protein folding, revealing a fundamental regulatory architecture and source of selective pressure in ER+ breast cancer and reproductive disorders. Finally, cross-referencing molecular constraints to genome sequencing reveal evolutionary origins underlying natural genetic variation in humans and widespread disruption of constraints. This work provides structural insights into the conservation of gene regulation by essential transcription factors and has implications for precision medicine.
MGM as a large-scale pretrained foundation model for microbiome analyses in diverse contexts
Authors: Zhang Haohong , Zhang Yuli , Kang Zixin , Song Lulu , Yang Ronghua , Ning Kang 
Published: January 2025

AbstractMicrobial communities significantly impact medicine, biotechnology, and agriculture. Advanced sequencing technologies have generated extensive microbiome data, enabling the discovery of substantial evolutionary and ecological patterns. However, traditional supervised learning methods struggle to capture universal patterns in microbial community data, largely due to the large data heterogeneity and profound batch effects among samples, rendering it difficult to classify samples as well as detect biomarkers from millions of samples, not to say the intricate but important dynamic patterns from a variety of contextualized sceneries. In this study, we introduce the Microbial General Model (MGM), the first microbiome community foundation model pre-trained on a dataset of 263,302 microbiome samples using language modeling techniques. MGM demonstrated significant improvements in microbial community classification compared to traditional machine learning methods. Additionally, MGM has enabled contextualized classification, effectively overcomes cross-regional limitations, showing enhanced performance on intercontinental datasets through transfer learning. Furthermore, fine-tuning MGM on a longitudinal infant dataset revealed distinct keystone genera during development, withBacteroidesandBifidobacteriumexhibiting higher attention weights in vaginal deliveries, andHaemophilusin cesarean deliveries. Finally, through in silico modeling, the model also uncovered novel microbial dynamic patterns in a Crohn’s disease cohort following antibiotic treatment. In conclusion, by leveraging self-attention and autoregressive pre-training, MGM serves as a versatile model for various downstream microbiome tasks and holds significant potential for achieving contextualized aims.Key pointsThe Microbial General Model (MGM) is a foundation model with millions of parameters pre-trained on sub-million microbial community data.MGM outperforms traditional methods in various microbiome classification and prediction tasks, such as microbial community classification.MGM effectively captures the spatial and temporal dynamics of microbial communities.MGM could detect the effects of perturbation on microbial community through in silico experiments.
Single-nucleus RNA sequencing revealed the impact of post-mortem interval on the cellular component and gene expression analysis of mouse brains
Authors: Guo Yunxia , Ma Junjie , Ma Xiaoying , Ye Kaiqiang , Jiang Chao , Xu Jitao , Huang Yan , Yang Xi , Ge Qinyu , Zhang Jianyou , Wang Guangzhong , Huang Hao , Zhao Xiangwei 
Published: January 2025

AbstractAccurate analysis of cell atlas and gene expression in biological tissues using single-nucleus RNA sequencing (snRNA-seq) is dependent on the quality of source material, and post-mortem interval (PMI) is one of the major sources of variation in RNA quality. Although the use of RNA-degraded tissues in transcriptome analysis remains controversial, such samples are sometimes the sole means to address specific questions. Current studies on the impact of PMI on transcriptome data are limited to large-scale RNA-seq, which ignores cellular heterogeneity. Thus, deciphering the non-cell- autonomous effects caused by PMI is imperative for understanding the cellular and molecular disruption it elicits. Here, we investigated the impact of PMI on cellular components and gene expression using snRNA-seq data from mouse brain tissues of post-mortem. We collected samples that were allowed to decay for varying amounts of time at 25°C prior to snRNA-seq, covering the entire range of RIN values. The different effects on the PMI to the degradation rate of mRNA and rRNA within nuclei, and the mRNA presented a more stable state. Multi-channel analysis revealed the preferential transient depletion oligodendrocytes and OPCs with increasing PMI. In addition, a rapid widespread overregulation of ribosomal transient recruitment to protein (RP) genes in various cells, and reached a plateau at PMI of 36h. Although state depletion of neuronal cells was not detected, we reported significant upregulation of PMI-dependent RP genes in its subpopulations and their cell loss. Moreover, RP genes showed the greatest differential expression in the subpopulations with greater cell perturbation, and we speculated that aberrant expression of these genes might be associated with cell death. In this study, we systematically investigated the changes in the transcriptome profile of brain tissue induced by PMI at single-cell resolution, and revealed one of the important factors that might be responsible for the changes. In addition, our data complemented a possible explanation for the changes in the cellular state of brain tissue induced by postmortem hypoxia-ischemia, and provided a reference for transcriptome studies of RNA degradation samples.
Iris Crypts Could Reduce the Chance of Angle Closure: A Computational Biomechanics Study Derived from Clinical and Human Iris Data
Authors: Tan Royston K.Y. , Tun Tin A. , Braeu Fabian A. , Perera Shamira A. , Girard Michaël J.A. 
Published: January 2025

AbstractPurposeTo investigate the effect of crypts during pupil constriction and dilation on the potential for angle closure by performing finite element analysis using clinical and experimental data on human tissues.MethodsA computational model was developed to determine the influence of small crypts (surface area of ∼0.015 mm2) and large crypts (surface area of 0.300 mm2) on the anterior chamber angles during pupil dilation. The model needed permeability data from human subjects, hence 21 enucleated human eyes (72 hours post-mortem) were procured and subjected to a flow set-up previously reported. Finally, 66 subjects were recruited to measure pupil constriction and dilation levels from optical coherence tomography (OCT) videos.ResultsThe hydraulic permeability of the human iris stroma was determined to be 2.55 ± 1.93 × 10-5mm2/Pa·s. The average iris constriction and dilation durations were 0.710 ± 0.213 seconds and 1.24 ± 0.401 seconds, respectively, with pupil diameter changes of 1.16 ± 0.39 mm and 0.75 ± 0.27 mm, respectively. The computational models had starting anterior chamber angles of 51.30° and final anterior chamber angles of 26.81° once steady state has been reached. In an extreme case with decreased anterior border layer (ABL) permeability, the anterior chamber angle narrowed to 12.37°, but the presence of crypts kept the angle above 20.36°, highlighting the potential of crypts in preventing angle closure.ConclusionsOur findings on the biomechanics of crypts in the iris may drive the development of novel treatments by altering ABL morphology, providing an alternative bypass for angle closure prevention in high-risk patients.
Real World Performance of an Individualized Antitachycardia Pacing Algorithm
Authors: Jackson Troy , Taepke Robert , Birgersdotter-Green Ulrika , Cha Yong-Mei , Singh Jagmeet , Cheng Alan , Yee Raymond 
Published: January 2025

ABSTRACTBackgroundA novel individualized antitachycardia pacing (IATP) algorithm using the post-pacing interval for real-time control has been introduced. Performance information is limited to a small safety and feasibility study with additional single-center and case studies. A larger-scale analysis is needed to better understand algorithm performance.MethodsDe-identified remote monitoring transmissions from devices with the IATP therapy applied were randomly selected. Rhythms were classified and effects of the novel algorithm were assessed. For monomorphic ventricular tachycardias (MVTs) proportions of successful therapy, shock-free episodes, and acceleration were calculated using Generalized Estimating Equations to correct for multiple episodes and compute statistics of the algorithm’s performance.ResultsThere were 2259 MVT episodes in 336 patients. IATP succeeded in 87.1% of MVT episodes with 89.9% of MVT episodes ultimately free of shock therapy. Based on multivariate analysis, significant factors in therapy success were programming of at least the recommended number of sequences (90% at least recommended vs 73%, p=0.00088) and female sex (95% for female vs 86%, p=0.002). A trend to higher success was found for MVT with cycle length of 320ms or greater (90% vs. 83%, p=0.10). The IATP accelerated 3.6% of MVT episodes. None of the available factors was significantly associated with acceleration in the multivariate analysis.ConclusionsThe IATP algorithm succeeded in large proportion of MVT episodes and with low acceleration in patients randomly selected from remote monitoring transmissions. Using at least the recommended number of sequences had the strongest association with successful therapy.CLINICAL PERSPECTIVEWhat is knownA novel method for delivering antitachycardia pacing therapy using real-time feedback has been shown safe and feasible.Comparisons in computational studies and smaller case series suggest the novel method’s performance is superior to other antitachycardia pacing methods.What the study addsUnder real-world programming and use, as evaluated on a large de-identified set of remote monitoring transmissions, the novel antitachycardia pacing algorithm treated monomorphic ventricular tachycardia episodes with high efficacy and a low proportion of acceleration.The strongest factor associated with successful therapy was programming at least the recommended number of pacing attempts.
Using green space virtual reality to prevent stress-induced working memory impairment
Authors: Xu Yingying , Yang Zixuan , Zhou Xiaoxuan , Yao Qingyi , Dai Guohang , Liu Wei , Zhao Hui 
Published: January 2025

AbstractExposure to green space is associated with both physical and mental health benefits, including the potential to buffer acute stress responses, positioning it as a promising non-pharmacological approach to protect cognitive functions against stress. However, urban residents often face significant barriers in accessing green spaces, which are not equitably distributed. Virtual Reality (VR) technology offers a potential solution by simulating green space that could be made accessible to a broader demographic. Here, we explored whether VR-stimulated green space could dampen biological stress responses (i.e., heart rate and cortical response) and prevent stress-induced working memory (WM) impairment. Healthy young participants underwent acute stress induction followed by 15 minutes of VR-based green space (N=36) or control empty space (N=30) intervention. Although we observed the expected stress-induced increase in heart rates and elevated cortisol levels under stress, VR green space exposure failed to temper cortisol responses compared to the control VR space. Further, VR green space exposure did not bring benefits to protect working memory performance under stress across three WM tasks. Applying a Bayesian analysis approach throughout enabled us to find substantial evidence for the absence of an effect of VR-based green space exposure on biological markers of acute stress responses and working memory performance. Our findings suggest that VR-generated green space may not effectively replicate the stress-buffering effects of actual green space exposure. We discussed the implications of our findings regarding the potential and limitations of using VR or green space exposure to buffer stress responses.
Experimental assessment of large mammal population estimates from airborne thermal videography
Authors: McElhinny Julia S. , Larsen Gregory D. , Messinger Max , Newbolt Chad H. , Whitworth Andrew , Ditchkoff Stephen S. , Silman Miles R. , Beaver Jared T. 
Published: January 2025

ABSTRACTWildlife resource management requires reliable, fast, and affordable methods of surveying wildlife populations to develop and adaptively adjust policies. Many methods are used to survey populations of large mammals, and thermal video from drones can yield high rates of detection over large extents with relative speed and safety. In wild populations it can be difficult to estimate detection rates and the accuracy of resulting abundance estimates, especially because many factors of study design and natural systems can influence counts from thermal surveillance. We surveyed a captive white-tailed deer (Odocoileus virginianus) population of known size at the 174-ha Auburn Deer Facility in Auburn, AL, USA, and used a designed experiment to investigate the effects of observers, time-of-day, and day-to-day variation on the accuracy of abundance estimates from trial flights using drone-based airborne thermal videography. The experiment consisted of 20 full-census trials, occurring over 4 days, at times-of-day before sunset, after sunset, near midnight, before sunrise, and after sunrise, with each trial video counted by three trained observers. Counts across all trials and observers yielded a mean point estimate of 77 (95% CI 71–83) deer representing 81–97% of the known population range. Flights near sunset yielded estimates of the highest accuracy, within or close to the true range of the population. Variability in estimates was primarily influenced by daily climatic conditions and time-of-day, with only minor observer effects. Results highlight the importance of day-to-day variability in environmental conditions and diel processes, such as nocturnal cooling of the environment and crepuscular peaks in deer activity. The estimates from our experiment and resulting model illustrate that censuses conducted at optimal times-of-day and averaged across multiple days were able to achieve accurate estimates within the known range without correction, and that by averaging across flights, even including suboptimal conditions, thermal videography returned estimates within 4% of the known range with substantial overlap of the estimate. Conversely, single estimates chosen at random from any time-of-day varied widely around the known value, highlighting the need to plan flights with respect to diurnal activity patterns and landscape thermal properties, or, in the absence of information, average multiple surveys across times and days.
Adaptability and yield stability analysis of food barley (Hordeum vulgareL.) in South Gondar zone, Northwest Ethiopia
Authors: Worku Alamir Ayenew , Fentie Dejen Bekis , Shferaw Solomon Sharie 
Published: January 2025

AbstractIn food barley, genotype-environment interaction is a frequent occurrence. By identifying stable genotypes across settings, the impact of G x E can be mitigated. Ten food barley genotypes were investigated for yield stability and adaptation in five different environments. The analyses included stability, genotype, and genotype-environment interaction, as well as additive main effect and multiplicative interaction. However, genotype-environment interaction captured 92.98% of the GGE variance. AMMI analysis only explained 27.87% of G and 20.12% of G x E. Five environments were identified using GGE analysis. Of these, Estie2022 (3591.3 kg ha−1) and Debretabor2022 (3494.47 kg ha−1) had the highest grain yields, indicating that they are suitable for the production of food barley, while Lay-Gaynt2023 (2399.82 kg ha−1) had the lowest grain yields, indicating that they are not a suitable environment. The conditions with the best yields were Estie2022, and the lowest-yielding environments were Lay-Gaynt 2023. The two genotypes with the highest yields were HB-1966 (3592.97 kg ha-1) and HB-1965 (3555.17 kg ha-1). Based on yield stability, the genotypes Biftu, followed by Adoshe and Abdene, were the most stable with the highest mean grain yield performance. The genotypes with the highest-yielding performance but relatively the lowest stability were HB-1966 and HB-1965. The genotype HB-1965 was recommended at the Estie2022 and Debretabor2023 testing environments. The ideal environment was represented by Estie2023, and the winning genotype was HB-1966. This suggests that the two winning genotypes were adapted to the specific environments tested in the current study. Whereas Guta and Harbu were adapted to a more diverse environment than the test environments of the South Gondar Zone, Northwest Ethiopia.