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Localized 2D/3D heterojunction enhances photovoltage for perovskite-organic tandem solar cells

Systematic proteomics analysis of lysine acetylation reveals critical features of renal proteins in kidney calculi formation

In this study, we systematically integrated proteome and acetyl proteome (acetylome) approaches to investigate the characteristics of renal proteins in a CaOx crystal rat model. We aimed to understand the pathogenesis of kidney calculi and delineate the landscape of acetylation within kidney calculi, potentially leading to the identification of valuable and novel biomarkers. Using liquid chromatography-tandem mass spectrometry (LC-MS/MS), we analyzed the protein expression profiles and lysine acetylation (Kac) features in kidney tissues obtained from rats with kidney calculi and those without (normal controls). Our results revealed 118 downregulated and 129 upregulated proteins. Furthermore, we identified 538 upregulated Kac sites in 258 proteins and 133 downregulated Kac sites in 118 proteins between kidney calculi and paired normal rats. Functional enrichment and protein-protein interaction network analyses revealed that the mitochondria were the most abundant acetylated protein fraction, and metabolic pathways were predominated among the GO and KEGG pathways. Furthermore, the LC-MS/MS findings were verified by immunofluorescence. The study is the first comparative study of Kac modification associated with kidney calculi. These findings offer significant insights into the molecular mechanism underlying the formation and development of renal stones.

Leveraging glucan-induced trained immunity for the epigenetic and metabolic rewiring of macrophages to enhance colorectal cancer vaccine response

Distinct brain pathways link depressive symptoms due to respiratory dysfunction and reduced physical activity in patients with chronic obstructive pulmonary disease: A single-center observational pilot study

Mental health issues, such as depression, are increasingly recognized as critical comorbidities in chronic obstructive pulmonary disease (COPD). While analyses of individual domains or pairwise relationships among airflow obstruction severity, brain morphological features, and mental health conditions in COPD have provided valuable insights into their direct associations, a more integrative approach may offer additional mechanistic understanding. This study aimed to clarify potential mediators in multiple brain regions between airflow obstruction and depressive tendencies in patients with COPD. We analyzed 19 patients with COPD and 23 age-matched healthy controls. Path analysis was used to evaluate the relationships among respiratory indices, regional brain volumes, and depressive symptoms. The path analysis revealed two potential pathways to depressive symptoms in the COPD group. One was a pulmonary pathway, involving forced expiratory volume in one second (%FEV 1 ) and the genu of the corpus callosum (β = 0.503, p  < 0.05) leading to depressive symptoms (β = 0.532, p  < 0.05). The other was a behavioral pathway, in which physical activity (β = 0.444, p  < 0.05) affected the right postcentral gyrus (β = −0.286, p  < 0.05) and, in turn, depressive symptoms. No significant group differences were observed in other examined regions, including the posterior cingulate, hippocampus, hypothalamus, insula, or other corpus callosum subregions, nor in depression or anxiety scores. The model demonstrated a good fit in the COPD group (GFI = 0.876), whereas in controls, the model showed poor fit and no significant relationships (GFI = 0.784). These preliminary findings suggest potential brain pathways linking airflow obstruction, physical activity, and depressive symptoms in COPD, which warrant confirmation in larger, longitudinal studies.

Polyacid-Protonated Covalent Organic Frameworks Enable Stable and Efficient Photothermal Textiles

Arp2/3 complex contributes to the actin-dependent uptake of Aspergillus terreus conidia by alveolar epithelial cells

Aspergillus terreus is an opportunistic fungal pathogen associated with high mortality rates and intrinsic resistance to amphotericin B. Its ability to persist within host tissues without inducing strong immune responses was suggested to contribute to poor clinical outcomes. The cellular mechanisms underlying A. terreus interactions with host cells remain largely unexplored. In this study, we have used a micropattern-based infection model to investigate the early interactions between A. terreus conidia and alveolar epithelial cells, focusing on the role of Arp2/3-dependent actin remodeling. This system allows quantitative analysis of conidia-cell interactions under defined spatial conditions. We show that A. terreus conidia rapidly bind to micropatterned A549 cell islands, with conidial numbers increasing over time. Conidia were found in actin- and Lamp1-positive vesicles already after one hour of infection. Inhibition of the Arp2/3 complex significantly impaired conidial binding and disrupted the formation of actin-positive vesicles, confirming the essential role of Arp2/3-mediated actin remodeling in early stages of conidial uptake. A subset of conidia was localized to Lamp1-positive phagolysosomes and accumulated over time. Interestingly, we have identified a small but consistent population of Lamp1-positive vesicles decorated with actin structures, potentially resembling actin flashes. These structures were entirely abolished upon Arp2/3 inhibition, indicating active cytoskeletal remodeling at the phagolysosomal interface. Our findings provide the first mechanistic insights into A. terreus internalization by alveolar epithelial cells and establish Arp2/3-mediated actin dynamics as a key process in early host-pathogen interactions. This cellular pathway may further contribute to intracellular trafficking and help understand the delayed onset of A. terreus infections.

The relationship between the level of economic development, the scale of youth football development and competitive strength in Chinese provinces

This study aims to explore the relationship between the economic development level of Chinese provinces, the scale of youth football development, and competitive strength. The data are derived from 31 provinces of China (excluding Hong Kong, Macao, and Taiwan). Indicators of economic development level include GDP, per capita GDP, per capita disposable income, and per capita consumption expenditure. Indicators of the scale of youth football development include the number of featured schools, the number of campus football fields, the level of football clubs in the three-tier league system, the number of social brand youth training institutions, and the number of sports schools. Indicators of youth football competitive strength include the number of top teams and elite teams in the Chinese Youth Football League. The study found that after controlling for total population size and youth population size, per capita disposable income showed a marginally significant positive correlation with both the number of top teams ( r  = 0.320, P  = 0.091) and the number of elite teams ( r  = 0.359, P  = 0.056); GDP ( r  = 0.458, P  = 0.012), per capita GDP ( r  = 0.466, P  = 0.011), per capita disposable income ( r  = 0.414, P  = 0.026), and per capita consumption expenditure ( r  = 0.412, P  = 0.026) all exhibited a moderately significant positive correlation with the number of social youth training institutions; per capita disposable income ( r  = −0.469, P  = 0.010) and per capita consumption expenditure ( r  = −0.448, P  = 0.015) showed a moderately significant negative correlation with the number of featured schools; the level of clubs in the three-tier league system displayed a highly significant positive correlation with both the number of top teams ( r  = 0.648, P  < 0.001) and the number of elite teams ( r  = 0.778, P  < 0.001); and the number of featured schools had a weakly significant negative correlation with the number of top teams ( r  = −0.369, P  = 0.049). In addition, the level of clubs in the three-tier league system played a mediating role between economic indicators and competitive strength. The above research findings can provide a scientific basis for the Chinese government to optimize football policy orientations and the allocation of financial resources.

The social learning and development of intra- and inter-ethnic sharing norms in the Congo Basin

Compared to other species, the extent of human cooperation is unparalleled. Such cooperation is coordinated between community members via social norms. Developmental research has demonstrated that very young children are sensitive to social norms, and that social norms are internalized by middle childhood. Most research on social norm acquisition has focused on norms that modulate intra-group cooperation. Yet around the world, multi-ethnic communities also cooperate, and this cooperation is often shaped by distinct inter-group social norms. In the present study, we investigated whether intra-ethnic and inter-ethnic social norm acquisition follows the same, or distinct, developmental trajectories. Specifically, we worked with BaYaka foragers and Bandongo fisher-farmers who inhabit multi-ethnic villages in the Republic of the Congo. In these villages, inter-ethnic cooperation is regulated by sharing norms. Based on our ethnographic knowledge of the participating communities, we predicted that children’s intra-ethnic sharing choices would match those of adults at an earlier age than their inter-ethnic sharing choices. To test this prediction, children (5–17 years) and adults (17 + years) participated in a modified Dictator Game to investigate the developmental trajectories of children’s intra- and inter-ethnic sharing choices. Contrary to our prediction, both intra- and inter-ethnic sharing norms were acquired in middle childhood. Interviews with adult participants suggested that intra- and inter-ethnic sharing norms are acquired from multiple sources, including parents and peers. Further, Bandongo adults primarily reported learning sharing norms via Instruction, whereas BaYaka adults primarily reported learning via Observation/Imitation. These cross-cultural differences may reflect variation in norm complexity. Together, these findings suggest that when social contexts regularly expose children to out-group collaboration, inter-ethnic norms are acquired at similar timelines to intra-ethnic ones, as part of children’s broader cooperative repertoire.

2025: A Banner Year

In Situ SERS Monitoring of Plasmon-Mediated Degradation of Microplastics

Effect of high shear-dispersed nano-alumina on concrete strength, durability, and microstructure

Reclassifying hospital energy demand toward industry-like requirements for hygienic and resilient indoor environments

Thyroid cancer detection and classification using spectral imaging and artificial intelligence

Results of percutaneous needle culture sampling and synchronous irrigation with Dakins’ solution in Wagner Grade 3 diabetic foot osteomyelitis

Radiomics analysis of early pregnancy ultrasound images to predict viability at the end of first trimester

Abstract To determine whether there are radiomic ultrasound features of early pregnancy when viability is unknown, which in combination with clinical features, may predict subsequent loss. Multi-centre retrospective cohort study, which included 500 cases of pregnancies of unknown viability (PUV) collected from January 2021 to January 2023. Longitudinal ultrasound images were identified from Queen Charlotte’s and Chelsea Hospital (QCCH), London ( n  = 400, split 8:2 for training and validation) and St Mary’s Hospital (SMH), London (test data set n  = 100). Images were extracted and segmented to include firstly the gestation sac and secondly the sac endometrial border. A segmentation model was developed using a deep learning (DL) model (multi-task nnUNet v2) and standard Dice Coefficient (DICE) was used to measure performance. A prediction model, using clinical and radiomic features, was developed by comparing several machine learning (ML) methods. The area under the ROC curve (AUC), F1-score, and recall were used to assess model performance. The QCCH and SMH data sets were in the majority well matched and consisted of 53.3% and 53.0% miscarriage cases by the end of first trimester, respectively. The DL segmentation model for gestation sac achieved a mean DICE score of 0.950 and 0.940 in the training and test data sets respectively. The segmentation model for the sac endometrial border achieved a mean DICE score of 0.917 (QCCH) and 0.922 (SMH). The best performing PUV outcome classification model (XGBoost and LASSO) for predicting miscarriage (PUVPS model); achieved an AUC of 1.00 (F1-score 1.00), 0.92 (F1-score 0.79) and 0.84 (F1-score 0.76) in the QCCH training, QCCH validation and SMH test set respectively. We have developed an end-to-end radiomics-based model to segment and predict early pregnancy outcomes. The main limitation of this study is its sample size, which can make a ML model prone to overfitting. This study sets the stage for future trials to prospectively evaluate the performance of the PUVPS model, in a large multi-centre cohort, which can then be used to help patients navigate the uncertainty of a PUV early pregnancy classification.

Validation of a fast LC-MS/MS method for the analysis of bisphenol A (BPA) and urethane dimethacrylate (UDMA) in eluates of dental polymer-based materials

Integrated GIS-machine learning approach to irrigation water quality assessment in coastal aquifers

Abstract Groundwater has become a vital and increasingly relied-upon resource, especially in semi-arid and arid regions. Thus, to ensure groundwater complies with standards before use, continuous monitoring and comprehensive quality assessment are essential. This study was conducted to assess the quality of groundwater (GW) in the Skikda aquifer, northeastern Algeria, for irrigation using irrigation water quality indices (IWQIs), multivariate statistical analysis, and machine learning algorithms (MLAs): Random Forest regression (RF), Extreme Gradient Boosting regression (XGBR), and Adaptive Boosting Regression (ABR), integrated with SHAP analysis. Forty-four groundwater samples were collected from the study area during summer and winter seasons and analysed for temperature, pH (6.25–9.29; mean 7.24), electrical conductivity (EC: 532–5830 µS/cm; mean 1798.22 µS/cm), turbidity, total dissolved solids (TDS: 258–3020 mg/L; mean 962.33 mg/L), and concentrations of calcium (Ca 2+ : 40–366 mg/L), magnesium (Mg 2+ : 10–167 mg/L), sodium (Na + : 62–510 mg/L), potassium (K + : 0.40–45.6 mg/L), chloride (Cl – : 30.9–1800 mg/L), bicarbonate (HCO 3 – : 198–695 mg/L), sulfate (SO 4 2– : 1–429 mg/L), and nitrate (NO 3 – : 0.12–2.99 mg/L).The dominating hydrochemical facies in the study area were Mg-Ca-SO 4 , accompanied by the Sodium-Chloride (Na-Cl).Principle Component Analysis (PCA) for summer and winter datasets identified four key components suggesting a strong correlation between variables and factors, with PCA indicating that geochemical processes, such as rock0water interaction and dissolution of evaporate minerals, control the groundwater’s chemical composition. Groundwater quality for irrigation varied across the samples, with most exhibiting moderate to high constraints based on IWQI (26.88–74.00; mean 54.56 in summer and 56.70 in winter). Sodium Adsorption Ratio (SAR: 1.13–7.10) and Permeability Index (PI: 33.06–83.39) suggested excellent to good water quality, while Sodium Percent (Na%: 19–69%),) and Soluble Sodium Percentage (SSP: 19–70%) indicate a small but significant fraction (9–16%) of in appropriate samples. Magnesium Hazard (MH: 22–62) and SSP indicated that most samples were safe. Compared to winter, summer samples showed slightly poorer quality (higher Na%, SSP, and lower IWQI), likely due to evaporative solute concentration. Random Forest (RF) model integrated with SHAP analysis showed superior predictive accuracy for all Water Quality Indices (WQIs), with strong validation results (R 2 > 0.95; RMSE < 0.5) for both seasons. A comparative evaluation of RF, XGBR, and ABR further highlighted differences in predictive performance, with RF consistently providing the most reliable predictions of WQIs across both seasons (R 2  = 0.73–0.94). These results highlight RF’s effectiveness in predicting WQIs and highlight the influence of seasonal geochemical processes on groundwater quality, requiring the development of management strategies for sustainable irrigation. This study presents a novel approach by combining machine learning algorithms with GIS-supported hydrogeochemical assessment to evaluate irrigation water quality in a semi-arid coastal aquifer of Algeria. By integrating advanced ML techniques (RF, XGBR, ABR) with water quality indices and SHAP analysis, it captures the complex interactions between natural geochemical processes and human activities. The approach offers a replicable framework for sustainable groundwater management in underexplored regions.

Synergistic effects of ground granulated blast furnace slag and nano-silica on the consolidation, compressibility and microstructural behavior of high plasticity clay

Abstract High plasticity clays are prone to excessive deformation and low load-bearing capacity, which frequently leads to structural instability in geotechnical applications. To address these challenges, sustainable and cost-effective stabilization strategies such as the incorporation of nanomaterials and industrial by-products are receiving increasing attention. This study investigates the combined effects of ground granulated blast furnace slag (GGBFS) and nano-silica (NS) on the compressibility, consolidation, and swelling behavior of high plasticity clay using Atterberg limits, standard Proctor compaction, one-dimensional consolidation, and swell tests. Microstructural changes were also investigated using SEM, EDS, and XRD, providing insights into gel-like reaction products and the evolution of soil fabric. Experimental data indicate that the combined use of GGBFS and NS leads to enhanced consolidation-related stiffness (E oed ), faster consolidation, and reduced swelling in high plasticity clays. The observed improvements in compressibility, consolidation-related stiffness, and swelling behavior are attributed to microstructural refinement induced by stabilization. These effects are associated with pozzolanic reactions, micro-filling, and the formation of gel-like products, as supported by SEM, EDS, and XRD observations. This work demonstrates the integration of GGBFS and NS as a promising strategy for improving the compressibility and swell-related behavior of high plasticity clays.

Experimental petroleum resin production and optimization using response surface modeling

Assessing ethnic inequalities in diagnostic intervals of breast cancer among patients presenting symptoms to general practitioners in England

Abstract This retrospective-cohort study examined ethnic differences in breast cancer diagnostic intervals among women aged aged ≥40 years who were diagnosed in England between 2017 and 2021. We analysed primary care-linked hospital data, with diagnostic interval divided into primary care interval (period between first presentation and referral), referral interval (period between referral and first specialist appointment), and secondary care interval (period between first specialist appointment and diagnosis). Across the cohort, the median diagnostic interval was 24 days and was longer for women presenting with non-lump symptoms than for those with a breast lump (ATR = 1.56, 95%CI: 1.31–1.86). Black patients had longer diagnostic interval than White patients regardless of symptom type: [ATR = 1.38, 95%CI:1.11–1.71]. The median primary care interval was 1 day. It was longer for women with non-lump symptoms than those with a breast lump [ATR = 1.49, 95%CI:1.16–1.92], but shorter for Asian patients, especially those with a breast lump, compared to White patients [ATR = 0.89, 95%CI: 0.84–0.96]. The median referral interval was 11 days, with no evidence of variation by symptom type or ethnicity. The secondary care interval was also 11 days and was longer for patients with non-lump symptoms [ATR = 1.41, 95%CI:1.14–1.74] and for Black patients, particularly those with a breast lump, compared to White patients [ATR = 1.66, 95%CI:1.21–2.28]. Our findings highlight the need for targeted interventions to address ethnic disparities in breast cancer outcomes, including both lump and non-lump symptom presentations. Such interventions should prioritise optimising the entire diagnostic pathway—from initial presentation through to diagnosis—rather than concentrating solely on primary care, ensuring timely and equitable access across all healthcare settings.