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Objective Older adults are more vulnerable to digital exclusion, which has been associated with psychological distress. This study investigated the relationship between digital exclusion and loneliness among older adults across three countries using three longitudinal surveys. Design and measurements Digital exclusion was defined as self-reported non-use of the internet. Loneliness was assessed using the Three-Item Loneliness Scale (T-ILS). We employed Generalized Estimating Equations (GEE) with binary logistic regression and propensity score matching (PSM) to examine the association between digital exclusion and loneliness, adjusting for covariates including Age; Gender; Education; Marital status; Employment status; Cohabitation with children; Self-rated health; and Income. Setting and participants Nationally representative samples of older adults were obtained from three longitudinal studies: the China Health and Retirement Longitudinal Study (CHARLS), the Health and Retirement Study (HRS), and the English Longitudinal Study of Ageing (ELSA). The analysis included 39,190 participants (87,256 observations) across the three studies. Results Substantial cross-national disparities in digital exclusion rates were observed: CHARLS (96.20%), HRS (52.13%), and ELSA (33.54%). In the fully adjusted model (Model 3), digital exclusion was significantly associated with loneliness in all three studies (CHARLS: OR = 1.22; HRS: OR = 1.16; ELSA: OR = 1.30). These associations remained statistically significant after propensity score matching (CHARLS: OR = 1.33; HRS: OR = 1.23; ELSA: OR = 1.23). Conclusion Our findings indicate that a substantial proportion of older adults experience digital exclusion, particularly in China. Digital exclusion demonstrates a positive association with loneliness, suggesting that enhancing digital inclusion may serve as a critical strategy for alleviating loneliness and mitigating psychological distress in ageing populations.

The longevity of grafts remains a major challenge in allogeneic transplantation due to immune rejection. Systemic immunosuppression can impair graft function and can also cause severe adverse effects. Here, we report a local immuno-protective strategy to enhance post-transplant persistence of allografts using a mesenchymal stem cell membrane-derived vesicle (MMV)-crosslinked hydrogel (MMV-Gel). MMVs are engineered to upregulate expression of Fas ligand (FasL) and programmed death ligand 1 (PD-L1). The MMVs are retained within the hydrogel by crosslinking. The immuno-protective microenvironment of the hydrogel protects allografts by presenting FasL and PD-L1. The binding of these ligands to T effector cells, the dominant contributors to graft destruction and rejection, results in apoptosis of T effector cells and generation of regulatory T cells. We demonstrate that implantation with MMV-Gel prolongs the survival and function of grafts in mouse models of allogeneic pancreatic islet cells and skin transplantation. Immune rejection of allografts is a major issue which limits interventional strategies. Here, the authors report on the use of vesicles presenting immunosuppression markers entrapped within hydrogels to provide a local immuno-protective environment for allogenic transplantation.

Esophageal squamous-cell carcinoma (ESCC), one of the most prevalent and lethal malignant disease, has a complex but unknown tumor ecosystem. Here, we investigate the composition of ESCC tumors based on 208,659 single-cell transcriptomes derived from 60 individuals. We identify 8 common expression programs from malignant epithelial cells and discover 42 cell types, including 26 immune cell and 16 nonimmune stromal cell subtypes in the tumor microenvironment (TME), and analyse the interactions between cancer cells and other cells and the interactions among different cell types in the TME. Moreover, we link the cancer cell transcriptomes to the somatic mutations and identify several markers significantly associated with patients’ survival, which may be relevant to precision care of ESCC patients. These results reveal the immunosuppressive status in the ESCC TME and further our understanding of ESCC. Esophageal squamous-cell carcinomas (ESCC) have poor prognosis, and detailed molecular profiles are necessary to identify prognostic markers. Here the authors analyse 60 ESCC patient samples using scRNA-seq, TCR-seq and genomics; they find mucosal immunity markers associated with survival and immunosuppressive microenvironments.

Somatic mutations that accumulate in normal tissues are associated with ageing and disease 1 , 2 . Here we performed a comprehensive genomic analysis of 1,737 morphologically normal tissue biopsies of 9 organs from 5 donors. We found that somatic mutation accumulations and clonal expansions were widespread, although to variable extents, in morphologically normal human tissues. Somatic copy number alterations were rarely detected, except for in tissues from the oesophagus and cardia. Endogenous mutational processes with the SBS1 and SBS5 mutational signatures are ubiquitous among normal tissues, although they exhibit different relative activities. Exogenous mutational processes operate in multiple tissues from the same donor. We reconstructed the spatial somatic clonal architecture with sub-millimetre resolution. In the oesophagus and cardia, macroscopic somatic clones that expanded to hundreds of micrometres were frequently seen, whereas in tissues such as the colon, rectum and duodenum, somatic clones were microscopic in size and evolved independently, possibly restricted by local tissue microstructures. Our study depicts a body map of somatic mutations and clonal expansions from the same individual. Laser-capture microdissection and mini-bulk exome sequencing are combined to analyse somatic mutations in morphologically normal tissues from nine organs from five donors, revealing variation in mutation burdens, mutational signatures and clonal expansions.

Hepatocellular carcinoma (HCC) is a malignancy with high morbidity and mortality but lacks effective treatments thus far. Although the emergence of immune checkpoint inhibitors in recent years has shed light on the treatment of HCC, a considerable number of patients are still unable to achieve durable and ideal clinical benefits. Therefore, refining the combination of immune checkpoint inhibitors (ICIs) to enhance the therapeutic effect has become a global research hotspot. Several histone deacetylase 2 inhibitors have shown advantages in ICIs in many solid cancers, except for HCC. Additionally, the latest evidence has shown that histone deacetylase 2 inhibition can regulate PD-L1 acetylation, thereby blocking the nuclear translocation of PD-L1 and consequently enhancing the efficacy of PD-1/PD-L1 inhibitors and improving anti-cancer immunity. Moreover, our team has recently discovered a novel HDAC2 inhibitor (HDAC2i), valetric acid (VA), that possesses great potential in HCC treatment as a monotherapy. Thus, a new combination strategy, combining HDAC2 inhibitors with ICIs, has emerged with significant development value. This perspective aims to ignite enthusiasm for exploring the application of ideal HDAC2 inhibitors with solid anti-tumor efficacy in combination with immunotherapy for HCC.

The evaluation of Water Resources Carrying Capacity (WRCC) plays a critical role in understanding regional resource dynamics and guiding the sustainable allocation of water resources. Addressing the inherent uncertainties in hydrological systems and the subjectivity associated with indicator weighting, this study focuses on the headwater region of the Changbai Mountain area. A total of 28 indicators were selected from the “production–living–ecological” framework. Cloud model coupled with entropy weight method and entropy value method were applied to comprehensively assess WRCC, while a geodetector was employed to identify key driving factors. Furthermore, the coordination of WRCC among four regions was quantitatively evaluated by using the Coupling Coordination Degree Model (CCDM). Key findings include: (1) The WRCC of Fusong County was at Level II (good carrying capacity) from 2013 to 2016 and in 2019, and at Level III (carrying capacity) in all other years; Jingyu County was at Level II in 2021–2022, and at Level III in all other years; Changbai Korean Autonomous County was at Level III throughout; Linjiang City was at Level II in 2019–2020, and at Level III in all other years. (2) WRCC indices generally declined from northeast to southwest. (3) Urbanization rate (0.712), water consumption rate for forestry (0.584), animal husbandry and fishery (0.539) were the most significant drivers. (4) Coupling degrees among regions ranged from 0.973 to 0.996, with most areas transitioning from imbalance to coordination, except Jingyu County. The study provides scientific insights for optimizing water resource allocation and balancing economic development, human livelihoods, and ecological preservation in the Changbai Mountain area and the middle and lower reaches of the cities in Jilin Province.

Surface Defect Detection (SDD) is a significant research content in Industry 4.0 field. In the real complex industrial environment, SDD is often faced with many challenges, such as small difference between defect imaging and background, low contrast, large variation of defect scale and diverse types, and large amount of noise in defect images. Jujubes are naturally growing plants, and the appearance of the same type of surface defect can vary greatly, so it is more difficult than industrial products produced according to the prescribed process. In this paper, a ConvNeXt-based high-precision lightweight classification network JujubeNet is presented to address the practical needs of Jujube Surface Defect (JSD) classification. In the proposed method, a Multi-branching module using Depthwise separable Convolution (MDC) is designed to extract more feature information through multi-branching and substantially reduces the number of parameters in the model by using depthwise separable convolutions. What’s more, in our proposed method, the Convolutional Block Attention Module (CBAM) is introduced to make the model concentrate on different classes of JSD features. The proposed JujubeNet is compared with other mainstream networks in the actual production environment. The experimental results show that the proposed JujubeNet can achieve 99.1% classification accuracy, which is significantly better than the current mainstream classification models. The FLOPS and parameters are only 30.7% and 30.6% of ConvNeXt-Tiny respectively, indicating that the model can quickly and effectively classify JSD and is of great practical value.

Photovoltaic panels are the core components of photovoltaic power generation systems, and their quality directly affects power generation efficiency and circuit safety. To address the shortcomings of existing photovoltaic defect detection technologies, such as high labor costs, large workloads, high sensor failure rates, low reliability, high false alarm rates, high network demands, and slow detection speeds of traditional algorithms, we propose an algorithm named ST-YOLO specifically for photovoltaic module defect detection. This algorithm is based on YOLOv8s. First, it introduces the C2f-SCconv convolution module, which is based on SCconv convolution. This module reduces the computational burden of model parameters and improves detection speed through lightweight design. Additionally, the Triplet Attention mechanism is incorporated, significantly enhancing detection accuracy without substantially increasing model parameter computations. Experiments on a self-built photovoltaic array infrared defect image dataset show that ST-YOLO, compared to the baseline YOLOv8s, achieves a 15% reduction in model weight, a 2.9% improvement in Precision, and a 1.4% increase in mAP@0.5. Compared to YOLOv7-Tiny and YOLOv5s, ST-YOLO also demonstrates superior detection performance and advantages. This indicates that ST-YOLO has significant application value in photovoltaic defect detection.

This study examined the psychometric properties of the Chinese version of the Multidimensional Competitive Orientation Inventory (Ch-MCOI) in adults from Mainland China. A total of 1121 participants (50.6% male; M = 28.86, SD = 8.70) were recruited for this study. All participants completed the Chinese versions of the MCOI, the Connor-Davidson Resilience Scale (CD-RISC), the Warwick-Edinburgh Mental Well-being Scale (WEMWBS), the Almost Perfect Scale-Revised (APS), the Frost Multidimensional Perfectionism Scale (MPS-f), and the Competition Attitude Scale (Ch-CAS). A subsample of 239 participants (50.6% male; M = 32.04, SD = 8.13) completed the Ch-MCOI again after a two-week interval to assess test–retest reliability. Exploratory Structural Equation Modeling (ESEM) yielded a four-factor structure (hyper-competitive orientation, self-developmental competitive orientation, anxiety-driven competition avoidance, and lack of interest toward competition), which was further validated by confirmatory factor analyses with a satisfactory fit. Furthermore, test–retest reliability, internal consistency, and convergent and concurrent validity were also acceptable. Our findings suggest that the Ch-MCOI could be a reliable and valid instrument for assessing the adaptive and maladaptive facets of competitive orientations in the Chinese-speaking population.

Aelia fieberi Scott, 1874 is a pest of crops. The mitogenome of A . fieberi (OL631608) was decoded by next-generation sequencing. The mitogenome, with 41.89% A, 31.70% T, 15.44% C and 10.97% G, is 15,471 bp in size. The phylogenetic tree showed that Asopinae and Phyllocephalinae were monophyletic; however, Pentatominae and Podopinae were not monophyletic, suggesting that the phylogenetic relationships of Pentatomoidae are complex and need revaluation and revision. Phytophagous bugs had a ~20-nucleotide longer in nad2 than predatory bugs. There were differences in amino acid sequence at six sites between phytophagous bugs and predatory bugs. The codon usage analysis indicated that frequently used codons used either A or T at the third position of the codon. The analysis of amino acid usage showed that leucine, isoleucine, serine, methionine, and phenylalanine were the most abundant in 53 species of Pentatomoidae. Thirteen protein-coding genes were evolving under purifying selection, cox1 , and atp8 had the strongest and weakest purifying selection stress, respectively. Phytophagous bugs and predatory bugs had different evolutionary rates for eight genes. The mitogenomic information of A . fieberi could fill the knowledge gap for this important crop pest. The differences between phytophagous bugs and predatory bugs deepen our understanding of the effect of feeding habit on mitogenome.