Tag: pubmed

Sci Rep. 2025 Apr 10;15(1):12352. doi: 10.1038/s41598-025-87663-8.

ABSTRACT

This study investigates the impact of lithium-ion battery (LIB) design characteristics on recycling efficiency through a comprehensive mixed-methods research approach. The study employs structural equation modeling (SEM) and analytic hierarchy process (AHP) methodologies, analyzing data collected through systematic expert interviews with 15 industry professionals and structured surveys of 150 battery manufacturing and recycling facilities. Through rigorous qualitative and quantitative analysis, this research examines the relationships between design complexity, material diversity, connection methods, and recycling process efficiency and overall recycling performance. The research methodology combines in-depth interviews, expert consultations, and statistical analysis to ensure robust findings. Data sources include primary data from industry surveys, expert interviews, and secondary data from technical documentation and recycling facility reports, providing a comprehensive foundation for the analysis. The research compares recycling efficiency across different battery types, including traditional designs, cell-to-pack (CTP), and cell-to-body (CTB), utilizing multi-group analysis. Through life cycle cost analysis and environmental impact assessment, the study quantifies the potential economic and ecological benefits of optimized designs. Results indicate that while optimized LIB designs may increase initial production costs, they significantly enhance recycling efficiency, reduce total lifecycle costs, and minimize environmental impacts. SEM analysis reveals that design characteristics indirectly influence overall recycling performance by affecting recycling process efficiency. Multi-group analysis demonstrates the superior recyclability of CTP and CTB designs compared to traditional configurations. The study also evaluates the improvement potential for recycling efficiency across various materials, providing a basis for optimizing recycling strategies. This research offers valuable insights for battery design, recycling technology innovation, and policy formulation, emphasizing the importance of incorporating recyclability considerations in LIB development. It contributes significantly to advancing the energy storage industry towards a circular economy model.

PMID:40211024 | DOI:10.1038/s41598-025-87663-8

Sci Rep. 2025 Apr 10;15(1):12251. doi: 10.1038/s41598-025-91469-z.

ABSTRACT

Viral codon fitness (VCF) of the host and the VCF shifting has seldom been studied under quantitative measurements, although they could be concepts vital to understand pathogen epidemiology. This study demonstrates that the relative synonymous codon usage (RSCU) of virus genomes together with other genomic properties are predictive of virus host codon fitness through tree-based machine learning. Statistical analysis on the RSCU data matrix also revealed that the wobble position of the virus codons is critically important for the host codon fitness distinction. As the trained models can well characterise the host codon fitness of the viruses, the frequency and other details stored at the leaf nodes of these models can be reliably translated into human virus codon fitness score (HVCF score) as a readout of codon fitness of any virus infecting human. Specifically, we evaluated and compared HVCF of virus genome sequences from human sources and others and evaluated HVCF of SARS-CoV-2 genome sequences from NCBI virus database, where we found no obvious shifting trend in host codon fitness towards human-non-infectious. We also developed a bioinformatics tool to simulate codon-based virus fitness shifting using codon compositions of the viruses, and we found that Tylonycteris bat coronavirus HKU4 related viruses may have close relationship with SARS-CoV-2 in terms of human codon fitness. The finding of abundant synonymous mutations in the predicted codon fitness shifting path also provides new insights for evolution research and virus monitoring in environmental surveillance.

PMID:40211017 | DOI:10.1038/s41598-025-91469-z

Eye (Lond). 2025 Apr 10. doi: 10.1038/s41433-025-03787-1. Online ahead of print.

ABSTRACT

BACKGROUND/OBJECTIVE: To provide a large-scale analysis on the demographics and ocular comorbidities in Ehlers-Danlos Syndrome (EDS) patients in the US.

SUBJECTS/METHODS: This is an exploratory cross-sectional study comparing medical records of EDS patients to the general population on demographic variables and ICD-10 ocular diagnoses. A research platform with de-identified EHR data of over 99 million patients across 60 healthcare organizations was utilized. Groups were stratified by 30-year age groups. Patients aged 0-61+ with an ICD-10 diagnosis of EDS (76,526), the general platform population aged 0-61+ (99,836,639), and patients with a concurrent ICD-10 ocular diagnosis were queried to determine the prevalence of EDS across demographic variables, ocular disease, and odds of ocular disease. Statistical analysis was conducted using Microsoft Excel and R studio, using p < 0.01 and 95% confidence intervals (CI).

RESULTS: An EDS diagnosis was most prevalent in white females aged 0-30 years old (259.6 per 100,000). The majority of ocular diagnoses were more prevalent in the 0-60-year-old EDS population compared to the general population including myopia (5227.0 per 100,000) and dry eye (4211.6 per 100,000). Overall, diagnoses of angioid streaks (POR 18.72, 95% CI 10.32, 33.94) and idiopathic intracranial hypertension (IIH) (POR 18.43, 95% CI 17.51, 19.39) showed the highest increased odds in patients with EDS while significantly decreased odds were shown for type 2 diabetic retinopathy, age-related macular degeneration, and retinal vein occlusion.

CONCLUSIONS: EDS was associated with increased odds of having a concurrent ocular pathology, suggesting that, upon diagnosis of EDS, referral to ophthalmology may be valuable.

PMID:40211016 | DOI:10.1038/s41433-025-03787-1

Nat Methods. 2025 Apr 10. doi: 10.1038/s41592-025-02653-y. Online ahead of print.

ABSTRACT

Advances in computer vision and increasingly widespread video-based behavioral monitoring are currently transforming how we study animal behavior. However, there is still a gap between the prospects and practical application, especially in videos from the wild. In this Perspective, we aim to present the capabilities of current methods for behavioral analysis, while at the same time highlighting unsolved computer vision problems that are relevant to the study of animal behavior. We survey state-of-the-art methods for computer vision problems relevant to the video-based study of individualized animal behavior, including object detection, multi-animal tracking, individual identification and (inter)action understanding. We then review methods for effort-efficient learning, one of the challenges from a practical perspective. In our outlook on the emerging field of computer vision for animal behavior, we argue that the field should develop approaches to unify detection, tracking, identification and (inter)action understanding in a single, video-based framework.

PMID:40211003 | DOI:10.1038/s41592-025-02653-y

Sci Rep. 2025 Apr 11;15(1):12367. doi: 10.1038/s41598-025-97396-3.

ABSTRACT

To explore the relationship between DED and sleep disorders and examine the impact of DED’s duration on sleep disorders. This multi-institutional, retrospective cohort study used the TriNetX database. We recruited participants with and without DED diagnosis from 2004 to 2023. Dry eye patients were propensity-matched to individuals from our non-DED cohort (1:1 ratio) based on variables such as age (every 5 year), sex, ethnicity, race, and relevant comorbidities. The Cox proportional hazards regression model was utilized to assess the impact of variables on sleep disorder risk, reporting hazard ratios (HRs) with 95% confidence intervals (CI). Kaplan-Meier survival analysis and log-rank tests were applied to estimate the cumulative incidence of sleep disorder. A total of 688,413 DED adult patients (64.91% female; mean age at index 56.96 ± 15.93) and 688,413 propensity-matched non-DED comparators (64.92% female; mean age at index 56.96 ± 15.93) were recruited. Our analysis showed an overall increased risk of uveitis among DED patients at 5-year time points (HR = 1.04) and all-year (19 years) follow-up durations (HR = 1.03). We observed a higher risk of sleep apnea in DED individuals irrespective of follow-up intervals. Further analyses revealed this increased risk specifically in those diagnosed with Sjögren syndrome (HR = 1.22). This study highlights the significant link between sleep disorders and DED, emphasizing the role of sleep apnea in DED patients. Aqueous-deficient DED has a more pronounced impact on sleep disturbances compared to evaporative DED, while the influence of DED on non-physiological insomnia may be overstated.

PMID:40210997 | DOI:10.1038/s41598-025-97396-3

Commun Med (Lond). 2025 Apr 11;5(1):109. doi: 10.1038/s43856-025-00827-5.

ABSTRACT

BACKGROUND: Shared symptoms and biological abnormalities between post-acute sequelae of SARS-CoV-2 infection (PASC) and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) could suggest common pathophysiological bases and would support coordinated treatment efforts. Empirical studies comparing these syndromes are needed to better understand their commonalities and differences.

METHODS: We analyzed electronic health record data from 6.5 million adult patients from the National COVID Cohort Collaborative. PASC and ME/CFS diagnostic groups were defined based on recorded diagnoses, and other recorded conditions within the two groups were used to train separate machine learning-driven computable phenotypes (CPs). The most predictive conditions for each CP were examined and compared, and the overlap of patients labeled by each CP was examined. Condition records from the diagnostic groups were also used to statistically derive condition clusters. Rates of subphenotypes based on these clusters were compared between PASC and ME/CFS groups.

RESULTS: Approximately half of patients labeled by one CP are also labeled by the other. Dyspnea, fatigue, and cognitive impairment are the most-predictive conditions shared by both CPs, whereas other most-predictive conditions are specific to one CP. Recorded conditions separate into cardiopulmonary, neurological, and comorbidity clusters, with the cardiopulmonary cluster showing partial specificity for the PASC groups.

CONCLUSIONS: Data-driven approaches indicate substantial overlap in the condition records associated with PASC and ME/CFS diagnoses. Nevertheless, cardiopulmonary conditions are somewhat more commonly associated with PASC diagnosis, whereas other conditions, such as pain and sleep disturbances, are more associated with ME/CFS diagnosis. These findings suggest that symptom management approaches to these illnesses could overlap.

PMID:40210986 | DOI:10.1038/s43856-025-00827-5

Sci Rep. 2025 Apr 10;15(1):12356. doi: 10.1038/s41598-025-91089-7.

ABSTRACT

We aim to evaluate the myopia control effect of defocus incorporated multiple segments’ (DIMS) spectacle lens in combination with different concentrations of atropine (ATR). A retrospective cohort study was conducted and DIMS users were categorized according to ATR concentration: 55 DIMS alone, 55 DIMS-Low ATR (0.01%) and 50 DIMS-High ATR (0.125%) groups. All three myopia control methods were applied for one year. Primary outcomes measures were changes in spherical equivalent refraction (SER) and axial length (AXL). One-way ANOVA was utilized to compare the outcome differences among the three groups, and multiple linear regression was utilized to analyze the effects of age, sex, baseline SER and baseline AXL on myopia progression among the three groups. The cycloplegic SER progression was-0.30 ± 0.25 D, -0.17 ± 0.49 D and – 0.16 ± 0.14 D in DIMS, DIMS-Low ATR and DIMS-High ATR groups respectively. The DIMS group showed a significant higher cycloplegia SER progression (P = 0.003). The AXL elongation was 0.13 ± 0.08 mm, 0.06 ± 0.20 mm and 0.06 ± 0.14 mm in DIMS, DIMS-Low ATR and DIMS-High ATR groups respectively and AXL elongation was significantly higher in DIMS group (P = 0.011). The young age demonstrated positive correlation to the higher cycloplegia SER progression in all groups (all P < 0.05). The young age is also correlated to higher AXL elongation in the DIMS and DIMS-Low ATR groups (both P < 0.05). The myopia control effects of low- and high-concentration ATRs in DIMS users show no significant difference, while the addition of atropine in combination with DIMS spectacles had a greater effect on myopia control than DIMS spectacles alone.

PMID:40210984 | DOI:10.1038/s41598-025-91089-7

Sci Rep. 2025 Apr 10;15(1):12235. doi: 10.1038/s41598-025-90975-4.

ABSTRACT

Pulmonary arterial hypertension (PAH) poses a substantial burden, including hospitalizations. This study assessed the impact of treatment escalation on rehospitalization. The Komodo Research Data (10/2015-03/2022) was used to identify adults with ≥ 1 PAH-related hospitalization (index: first hospitalization). Patients on monotherapy pre-index were assigned to the Escalation-to-combination cohort (treatment added ≤ 90 days post-index) or the Monotherapy cohort (no treatment change ≤ 90 days post-index). A sensitivity analysis was conducted among all patients who were treated pre-index. Entropy balancing was used to create cohorts with similar characteristics. All-cause hospitalizations per-patient-per-month (PPPM) during ≤ 12 months post-index were compared across balanced cohorts. A total of 203 and 1252 patients were included in the Escalation-to-combination and Monotherapy cohorts, respectively (mean age: 61 vs. 62 years; 67% vs. 68% female); most received PDE5i monotherapy pre-index (65.3% vs. 75.9%). Post-index, 84.5% of the Escalation-to-combination cohort increased to dual therapy, most commonly PDE5i + ERA (39.4%) and PDE5i + PPA (24.7%). Rehospitalization was lower in the Escalation-to-combination than Monotherapy cohort (incidence rate ratio [95% confidence interval]: 0.69 [0.55-0.90]; p < 0.001); the sensitivity analysis yielded similar results. Treatment escalation was associated with a lower rehospitalization rate, suggesting that earlier escalation and broader use of combination therapy may reduce PAH burden.

PMID:40210983 | DOI:10.1038/s41598-025-90975-4

Sci Rep. 2025 Apr 10;15(1):12288. doi: 10.1038/s41598-025-97180-3.

ABSTRACT

Historically overshadowed by communicable diseases, the burden of non-communicable diseases (NCDs) has surged over the past two decades, posing a significant threat to public health, and necessitating urgent attention. This study examines the mortality burden from four major groups/categories of NCDs including cancers, cardiovascular diseases (CVD), chronic respiratory diseases (CRD) and diabetes, prevalence of four NCD associated risk factors including tobacco use, alcohol consumption, physical inactivity and overweight, availability of NCD essential medicines and progress indicators of the NCD response in the WHO African region. The data used in this study were obtained from the WHO NCD data portal, Global Health Observatory, and Global Health Estimates, covering the most recent available data for each indicator, ranging from 2000 to 2019 to assess how trends in NCD mortality burden have evolved, as well as the current status of the four main risk factors, availability of essential medicines, and key NCD response indicators. The analysis focused on descriptive statistics for globally used, disease-specific key indicators to examine trends and variations across countries: (i) age-standardized mortality rates (ASMR) for major NCDs (cancers, CRD, CVD and diabetes), (ii) prevalence of NCD risk factors (tobacco use, alcohol consumption, physical inactivity, and overweight), (iii) availability of essential medicines for NCDs in public health facilities, and (iv) national NCD response indicators, such as the presence of NCD targets, mortality data, risk factor reduction measures, and surveillance. Mortality was reported as ASMR or percentages; risk factors as prevalence, except alcohol (litres per capita). Changes in mortality were calculated as absolute and relative differences, with tables and figures generated in Microsoft Excel. Between 2000-2019, NCD-related deaths and the percentage of deaths due to NCDs increased from 24.2 to 37.1% resulting in 12.9 and 53.3% absolute and relative increases. The ASMR decreased by 130.6 per 100,000 population resulting in an 18.2% relative decrease, during the same period; however, it remains consistently higher than the global average. In 2019, 64% of NCD deaths were among people 70 years or younger and the percentage of premature deaths from NCDs ranged from 36.5 to 72.1%. Despite the burden of NCDs, the availability of essential medicines and health services was sub-optimal in public health facilities. The prevalence of key risk factors such as tobacco use, physical inactivity, overweight, and alcohol consumption per capita varied by sex and across the region, with the prevalence of tobacco use and consumption of alcohol higher among men, while the prevalence of insufficient physical activity and overweight higher among women. Public health responses to NCDs remained sub-optimal due to limited national NCD targets, inadequate surveillance, risk factor reduction measures, and access to essential medicines. Though the NCD ASMR has decreased, there has been an increase in NCD-related deaths and the percentage of deaths due to NCDs over the last two decades in the WHO African Region. The mortality burden of NCDs and the prevalence of risk factors remains relatively high, while mounting a public health response for preventing and controlling these NCDs remains challenging. Accelerated action is essential to meet global and regional NCD reduction targets. Strengthening national NCD targets, improving surveillance, ensuring access to essential medicines, and scaling up risk factor reduction strategies are critical to reversing current trends and achieving the 2030 SDG NCD targets.

PMID:40210980 | DOI:10.1038/s41598-025-97180-3

Sci Data. 2025 Apr 10;12(1):603. doi: 10.1038/s41597-025-04925-w.

ABSTRACT

Accurate snow depth datasets are crucial for water resource management, comprehensive climate change evaluations, and the sustainable advancement of the ice-and-snow economy in the context of rapid climate change. To create a high-resolution monthly snow depth dataset tailored for the Northern Hemisphere winter months (NHMSD), this study employed the Delta statistical downscaling method, in conjunction with a spatial feature transfer technique, to refine snow depth data derived from 21 major general circulation models and four shared socioeconomic pathways sourced from the CMIP6 project. The NHMSD stands as the world’s pioneering long-term 0.05° snow depth dataset, encompassing the historical era from 1980 to 2014 and extending into future projections from 2015 to 2100. Validation using 2062 ground snow depth observations has confirmed that NHMSD outperforms reanalysis datasets, including ERA5-Land and GLDAS, in terms of root mean square error, bias, and mean absolute error for the periods 1980-2014 and 2015-2023. This dataset facilitates the exploration of potential alterations in snow depth under future scenarios in the Northern Hemisphere.

PMID:40210961 | DOI:10.1038/s41597-025-04925-w