Tag: pubmed

ACS Mater Lett. 2025 Jul 12;7(8):2902-2909. doi: 10.1021/acsmaterialslett.5c00878. eCollection 2025 Aug 4.

ABSTRACT

The blending of glassy copolymer-brush modified colloids with a viscoelastic linear copolymer featuring intrinsic self-healing enabled disordered hyperuniform hybrid materials that combined mechanical robustness with structural color, processability, environmental stability, and the ability to recover structure and properties after incurring physical damage via ‘integrated self-healing’. Symmetric linear n-butyl acrylate/methyl methacrylate (BA/MMA) were co-assembled with asymmetric glassy BA/MMA statistical copolymer brush (silica) particles. ‘Confinement-driven segregation’ resulted in a microphase-separated morphology in which the linear copolymer resided within the interstitial regions of a rigid (∼1 GPa) copolymer brush particle template with disordered hyperuniform microstructure. Diffusion of the self-healing copolymer additive into damage regions drove the recovery after damage, along with the restoration of structural color due to the materials hyperuniform microstructure. The synergistic action of intrinsic and extrinsic healing mechanisms could provide a versatile platform for the bottom-up fabrication of multifunctional hybrid materials with increased damage resistance and functional longevity.

PMID:40778388 | PMC:PMC12326392 | DOI:10.1021/acsmaterialslett.5c00878

Data Brief. 2025 Jul 23;62:111910. doi: 10.1016/j.dib.2025.111910. eCollection 2025 Oct.

ABSTRACT

This dataset provides a high-resolution, spatially explicit baseline of Ecuadorian cropping systems and associated pedoclimatic conditions to support long-term modeling of soil organic carbon (SOC) dynamics and biomass resource planning. The dataset is built from national sources, including Ecuadorian agricultural statistics and crop production surveys spanning 2002 – 2019. Ten dominant crops, representing over 90 % of the country’s cultivated area, are characterized across 23,021 Agricultural Pedoclimatic Units (APCUs), each defined by unique combinations of soil attributes, climate variables, and crop types. For each APCU, the dataset includes theoretical harvestable crop residue potentials, above- and belowground carbon inputs, and SOC-relevant parameters such as root depth distribution and biomass composition. Residue-to-product ratios (RPR), root-to-shoot biomass ratios (R:S), and biomass-to-carbon conversion coefficients were compiled through a comprehensive literature review and transparently documented. Additionally, the dataset includes monthly projections of average temperature, cumulative precipitation, and estimated evapotranspiration from 2020 to 2070 under the RCP4.5 climate scenario. Temperature and precipitation data were obtained from downscaled daily projections based on an ensemble of global climate models, and evapotranspiration was subsequently calculated using the Thornthwaite method. All variables were spatially assigned to each APCU. This open-access dataset is designed for reuse in soil carbon modeling frameworks, supports the design of biomass mobilization strategies, and informs climate-smart land-use strategies in tropical agricultural systems.

PMID:40778376 | PMC:PMC12329475 | DOI:10.1016/j.dib.2025.111910

Forensic Sci Int Synerg. 2025 Jul 29;11:100633. doi: 10.1016/j.fsisyn.2025.100633. eCollection 2025 Dec.

ABSTRACT

Forensic genetic frequency databases (FGFD) are used in estimating the probability of a DNA match in forensic investigations. They provide reference population data that can be used for statistical estimation for the rarity of a genotype, haplotype or a DNA profile in a population hence giving probative value for forensic evidence. Currently, three FGFD databases are recommended by the International Society for Forensic Genetics (ISFG) for forensic use; the Y-Chromosome Haplotype Reference Database (YHRD), the EDNAP Mitochondrial DNA Population Database (EMPOP), and the STRs for Identity ENFSI Reference Database (STRidER). There is need to generate updated and comprehensive genetic frequency data for the Kenyan population in compliance with ethical standards. This study sought to develop a forensic biobank to facilitate generation of comprehensive genetic frequency data for the Kenyan population. A total of 893 samples were collected from study volunteers in compliance with prescribed ethical standards. The data set comprises 60.8 % Bantu, 24.9 % Nilotic, and 14.3 % Cushitic samples closely mirroring current population structure in Kenya. The samples are currently stored in duplicate as FTA cards and extracted DNA. 132 quality mitogenome reference data has been generated for the coastal region in Kenya. With the broad consent obtained, the resource will be used to generate additional mitogenome reference data for other geographical regions, Y-chromosome haplotype and autosomal STRs for inclusion in recommended forensic databases as per revised guidelines. With the emergence of new technologies in forensic genetics, we anticipate the resource will be valuable in forensic genetics validation studies in future.

PMID:40778372 | PMC:PMC12329276 | DOI:10.1016/j.fsisyn.2025.100633

Ophthalmol Sci. 2025 May 17;5(6):100828. doi: 10.1016/j.xops.2025.100828. eCollection 2025 Nov-Dec.

ABSTRACT

PURPOSE: To achieve clear in vivo imaging and systematic quantification of choriocapillaris (CC), enabling the exploration of age-related and disease-related changes of CC within a large sample size.

DESIGN: Cross-sectional study.

PARTICIPANTS: A total of 1050 eyes from 727 individuals, comprising 633 healthy eyes, 277 eyes with age-related macular degeneration (AMD), and 140 eyes with high myopia.

METHODS: The 3-dimensional (3D) topographic maps of CC were obtained by performing image enhancement, depth reconstruction, and 3D rendering on a single OCT angiography enface image. Based on this map, we targeted key quantitative parameters to analyze vessel thickness, vascular complexity, vascular distribution uniformity, and blood perfusion of CC. We statistically analyzed the correlation between CC metrics and age in healthy population, as well as differences in CC metrics between healthy and diseased populations. To further explore the association between changes in CC and choroidal large vessels, we defined a parameter called “arterial zone (AZ) to venous zone (VZ) ratio” to assess the choroidal large-vessel perfusion.

MAIN OUTCOME MEASURES: The 3D topographic map of CC, 8 parameters of CC, and AZ/VZ.

RESULTS: The 3D topographic map effectively displayed the morphology of CC while maintaining high image accuracy. Statistical analysis revealed that with aging, the vessel thickness of CC in healthy eyes became thicker, and there was a decrease in vascular complexity, distribution uniformity, and perfusion. Additionally, AZ/VZ exhibited a trend of initial decline followed by an increase. In eyes with increasing severity of AMD, the vessel thickness of CC showed bidirectional changes followed by significant thickening. Complexity and distribution uniformity initially increased, followed by a marked decrease, whereas blood perfusion decreased initially before increasing. However, no significant intergroup differences in AZ/VZ were observed. In highly myopic eyes, compared to healthy eyes, the CC exhibited vessel thickening, reduced complexity and distribution uniformity, decreased perfusion, and a significant reduction in AZ/VZ.

CONCLUSIONS: This study explores age-related and disease-related CC changes via clear in vivo imaging and quantification. It aids understanding of CC states and may contribute to early disease diagnosis and prognosis.

FINANCIAL DISCLOSURES: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

PMID:40778359 | PMC:PMC12329102 | DOI:10.1016/j.xops.2025.100828

Front Psychiatry. 2025 Jul 24;16:1533652. doi: 10.3389/fpsyt.2025.1533652. eCollection 2025.

ABSTRACT

BACKGROUND: Traditional Chinese medicine is one of the important methods for treating chronic insomnia disorder (CID).

AIMS: We aimed to observe the multi-dimensional clinical outcomes of modified suanzaoren decoction (SZRD) compared to esazolam tablets in the treatment of CID patients.

METHODS: A total of 80 patients with CID were divided into two treatment groups, and were given modified SZRD and esazolam tablets treatment respectively for 6 weeks. The Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index, Hamilton Anxiety Scale, Hamilton Depression Scale, polysomnography (PSG), repeated battery for the assessment of neuropsychological status were performed to assess the changes of subjective and objective sleep, mood, and cognitive function.

RESULTS: Intra-group improvement: Compared to before treatment, both the modified SZRD and estazolam groups showed improvements in subjective sleep, depression, anxiety, immediate memory, and delayed memory scores (P<0.05). Inter-group comparison: There was a significant difference between the modified SZRD and estazolam groups in subjective PSQI scores (P=0.033). Based on PSG objective assessment results, both the estazolam and modified SZRD groups demonstrated a significant increase in N3 stage sleep (slow-wave sleep) duration compared to before treatment (P=0.037). However, there was no statistically significant difference in the effect size between the two groups (P>0.05), indicating that both interventions were equivalent in improving deep sleep. Nevertheless, residual variance analysis indicates that estazolam showed enhanced predictive stability in subjective sleep quality assessed by ISI (SSR=11.73 vs. 31.19; F=13.39, P<0.001), while modified SZRD exhibited enhanced predictive stability in objective slow-wave sleep maintenance, specifically in N3 stage duration (SSR=703.11 vs. 1761.08; F=4.98, P=0.029).

CONCLUSION: After the treatment of CID with the modified SZRD and esazolam, they have the comparable clinical efficacy. However, estazolam showed a more consistent treatment effect in subjective sleep quality assessment among the study population, whereas modified SZRD showed a more consistent treatment effect in objective slow-wave sleep maintenance, specifically in N3 stage duration. The registration number was NCT06452953.

PMID:40778328 | PMC:PMC12328296 | DOI:10.3389/fpsyt.2025.1533652

Front Psychiatry. 2025 Jul 23;16:1624825. doi: 10.3389/fpsyt.2025.1624825. eCollection 2025.

ABSTRACT

BACKGROUND: Adolescents are in a critical stage of development and represent a high-risk population for depression. Various studies have demonstrated the efficacy of acupuncture therapies in the treatment of adolescent depression. However, trials directly comparing the efficacy and safety of different acupuncture therapies for adolescent depression are still lacking. To identify the optimal acupuncture therapy for treating adolescent depression, we will conduct a systematic review and network meta-analysis of various acupuncture therapies for adolescent depression.

METHODS: Randomized controlled trials (RCTs) investigating the efficacy and safety of acupuncture in adolescent depression will be systematically searched across the Cochrane Central Register of Controlled Trials (CENTRAL), PubMed, Embase, Web of Science, and the China National Knowledge Infrastructure (CNKI) databases from inception to December 2025. Study quality will be assessed using the Cochrane Risk of Bias Tool (RoB 2.0), while the Confidence in Network Meta-Analysis (CINeMA) framework will evaluate evidence certainty. The primary outcomes will be included at least one validated depression rating scale for adolescent. Secondary endpoints include safety outcomes, measured by the incidence of adverse events during the study period. Bayesian network meta-analysis will be performed using the gemtc package (v0.8-7) in R statistical software (version 4.0.5).

DISCUSSION: This study will clarify the comparative efficacy and safety of acupuncture for adolescent depression, guiding clinical decision-making.

PROSPERO REGISTRATION NUMBER: identifier (CRD 42024581768).

PMID:40778325 | PMC:PMC12329222 | DOI:10.3389/fpsyt.2025.1624825

Front Surg. 2025 Jul 24;12:1610776. doi: 10.3389/fsurg.2025.1610776. eCollection 2025.

ABSTRACT

INTRODUCTION AND AIM: Head and neck cancer (HNC) is the third most common cancer worldwide, with oral squamous cell carcinoma (OSCC) having the highest incidence. Despite early diagnosis in 50% of cases, recurrence and poor survival remain concerns. This study compares survival outcomes between primary and second primary cT1-T2 OSCC.

MATERIALS AND METHODS: A single-center historical cohort study included 60 patients treated for cT1-T2 OSCC between 2010 and 2022. Patient demographics, tumor characteristics, and treatment modalities were collected. Treatment followed ESMO guidelines, primarily involving surgery with or without postoperative radiotherapy. Kaplan-Meier analysis and Cox proportional hazards models assessed overall survival (OS), disease-specific survival (DSS), and disease-free survival (DFS).

RESULTS: The 2- and 5-year OS rates were 85% and 64.9%, while DSS rates were 91.4% and 87.3%, respectively. Median OS was 7.4 years. Patients with primary tumors had significantly better OS (HR = 0.409, p = 0.038) and DFS (HR = 0.399, p = 0.036) than those with second primary tumors. Female patients had a 74.7% lower risk of death, and males had significantly shorter DFS (p = 0.024). Advancing tumor stage increased disease-specific mortality risk (HR = 1.737, p = 0.043). Multiple lymph node involvement correlated with worse OS (HR = 2.884, p = 0.031) and DFS (HR = 3.971, p = 0.006). Gross extranodal extension (ENE) was significantly associated with poorer OS (p = 0.048) and showed a borderline association with DFS (p = 0.050).

CONCLUSION: This study confirms second primary malignancies as a key prognostic factor for survival in OSCC. Male sex, advanced TNM stage, gross ENE, multiple lymph node involvement, and active smoking status were linked to poorer outcomes. Larger studies with multivariate analysis comparing primary and non-primary tumors are needed to validate these findings.

PMID:40778322 | PMC:PMC12328369 | DOI:10.3389/fsurg.2025.1610776

Comput Struct Biotechnol J. 2025 Jul 23;27:3264-3274. doi: 10.1016/j.csbj.2025.07.019. eCollection 2025.

ABSTRACT

Single-cell RNA sequencing (scRNA-seq) enables high-resolution analysis of cellular heterogeneity, yet accurate and consistent cell-type annotation remains a crucial challenge. Numerous automated tools exist, but their complex modeling assumptions can hinder reliability across varied datasets and protocols. We propose PCLDA, a pipeline composed of three modules: t-test-based gene screening, principal component analysis (PCA) and linear discriminant analysis (LDA), all built on simple statistical methods. An ablation study shows that each module in PCLDA contributes significantly to performance and robustness, with two novel enhancements in the second module yielding substantial gains. Despite these additions, the model retains its original assumptions, computational efficiency, and interpretability. Benchmarking against nine state-of-the-art methods across 22 public scRNA-seq datasets and 35 distinct evaluation scenarios, PCLDA consistently achieves top-tier accuracy under both intra-dataset (cross-validation) and inter-dataset (cross-platform) conditions. Notably, when reference and query data are generated via different protocols, PCLDA remains stable and often outperforms more complex machine-learning approaches. Furthermore, PCLDA offers strong interpretability, attributed to the linear nature of its PCA and LDA modules. The final decision boundaries are linear combinations of the original gene expression values, directly reflecting the contribution of each gene to the classification. Top-weighted genes identified by PCLDA better capture biologically meaningful signals in enrichment analyses than those selected via marginal screening alone, offering deeper functional insights into cell-type specificity. In conclusion, our work underscores the utility of carefully enhanced simple statistics methods for single-cell annotation. PCLDA’s simplicity, interpretability, and consistently high performance make it a practical, reliable alternative to more complex annotation pipelines. Code is available on GitHub:https://github.com/kellen8hao/PCLDA.

PMID:40778314 | PMC:PMC12329077 | DOI:10.1016/j.csbj.2025.07.019

Front Aging Neurosci. 2025 Jul 24;17:1617611. doi: 10.3389/fnagi.2025.1617611. eCollection 2025.

ABSTRACT

BACKGROUND: Alzheimer’s Disease (AD) is heterogeneous and shows complex interconnected pathways at various biological levels. Risk scores contribute greatly to disease prognosis and biomarker discovery but typically represent generic risk factors. However, large-scale multi-omics data can generate individualized risk factors. Filtering these risk factors with brain-derived extracellular vesicles (EVs) could yield key pathologic pathways and vesicular vehicles for treatment delivery.

METHODS: A list of 460 EV-related genes was curated from brain tissue samples in the ExoCarta database. This list was used to select genes from transcriptomics, proteomics, and DNA methylation data. Significant risk factors included demographic features (age, sex) and genes significant for progression in transcriptomics data. These genes were selected using Cox regression, aided by the Least Absolute Shrinkage and Selection Operator (LASSO), and were used to construct three risk models at different omics levels. Gene signatures from the significant risk factors were used as biomarkers for further evaluation, including gene set enrichment analysis (GSEA) and drug perturbation analysis.

RESULTS: Nine EV-related genes were identified as significant risk factors. All three risk models predicted high/low risk groups with significant separation in Kaplan-Meier analysis. Training the transcriptomics risk models on EV-related genes yielded better AD classification results than using all genes in an independent dataset. GSEA revealed Mitophagy and several other significant pathways related to AD. Four drugs showed therapeutic potential to target the identified risk factors based on Connectivity Map analysis.

CONCLUSION: The proposed risk score model demonstrates a novel approach to AD using EV-related large-scale multi-omics data. Potential biomarkers and pathways related to AD were identified for further investigation. Drug candidates were identified for further evaluation in biological experiments, potentially transported to targeted tissues via bioengineered EVs.

PMID:40778305 | PMC:PMC12328399 | DOI:10.3389/fnagi.2025.1617611

Front Cell Infect Microbiol. 2025 Jul 24;15:1610445. doi: 10.3389/fcimb.2025.1610445. eCollection 2025.

ABSTRACT

INTRODUCTION: Upper respiratory tract infections (URTIs) represent a significant global health burden, impacting patient morbidity and quality of life. The implementation of accurate pathogen detection methods is crucial for precise diagnosis and effective clinical management of URTIs. This study evaluates the clinical performance of targeted next-generation sequencing (tNGS) as a diagnostic tool for comprehensive identification of URTI-associated pathogens.

METHODS: A total of 190 nasopharyngeal swab specimens from patients were enrolled for the study. These specimens underwent pathogen identification using both tNGS and the FilmArray respiratory panel. The results obtained from these two methods were then compared.

RESULTS: Overall, tNGS identified 164 positive samples, compared to 91 positives identified by FilmArray. Regarding the shared target species or subtypes, tNGS identified 97 positive samples, whereas the FilmArray respiratory panel detected 88 positives out of 190 specimens. tNGS identified a diverse array of 34 different pathogens, significantly surpassing the 12 pathogens identified by the FilmArray panel. The detection rates for tNGS and FilmArray were 51.05% (97/190) and 46.32% (88/190), respectively. Statistical analysis revealed no significant difference in the detection rates of 10 specific respiratory pathogens (with ≥3 positives). Furthermore, the overall pathogen detection accuracy of tNGS was determined to be 90.16% (95%_CI = 83.45%~94.81%), with a sensitivity of 95.45% (88.77%~98.75%).

CONCLUSIONS: The tNGS method demonstrates broader pathogen detection capability compared to the FilmArray, achieving a higher positive detection rate in upper respiratory tract infections. It demonstrates high accuracy and sensitivity, offering a viable and rapid diagnostic approach for upper respiratory tract infections.

PMID:40778290 | PMC:PMC12329660 | DOI:10.3389/fcimb.2025.1610445