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The global epidemic of COVID-19 makes people realize that wearing a mask is one of the most effective ways to protect ourselves from virus infections, which poses serious challenges for the existing face recognition system. To tackle the difficulties, a new method for masked face recognition is proposed by integrating a cropping-based approach with the Convolutional Block Attention Module (CBAM). The optimal cropping is explored for each case, while the CBAM module is adopted to focus on the regions around eyes. Two special application scenarios, using faces without mask for training to recognize masked faces, and using masked faces for training to recognize faces without mask, have also been studied. Comprehensive experiments on SMFRD, CISIA-Webface, AR and Extend Yela B datasets show that the proposed approach can significantly improve the performance of masked face recognition compared with other state-of-the-art approaches.

The development of smartphones equipped with accelerometers gives a promising way for researchers to accurately recognize an individual’s physical activity in order to better understand the relationship between physical activity and health. However, a huge challenge for such sensor-based activity recognition task is the collection of annotated or labelled training data. In this work, we employ an unsupervised method for recognizing physical activities using smartphone accelerometers. Features are extracted from the raw acceleration data collected by smartphones, then an unsupervised classification method called MCODE is used for activity recognition. We evaluate the effectiveness of our method on three real-world datasets, i.e., a public dataset of daily living activities and two datasets of sports activities of race walking and basketball playing collected by ourselves, and we find our method outperforms other existing methods. The results show that our method is viable to recognize physical activities using smartphone accelerometers.

Ultraconserved (uc) RNAs, a class of long non-coding RNAs (lncRNAs), are conserved across humans, mice, and rats, but the physiological significance and pathological role of ucRNAs is largely unknown. Here we show that uc.372 is upregulated in the livers of db/db mice, HFD-fed mice, and NAFLD patients. Gain-of-function and loss-of-function studies indicate that uc.372 drives hepatic lipid accumulation in mice by promoting lipogenesis. We further demonstrate that uc.372 binds to pri-miR-195/pri-miR-4668 and suppresses maturation of miR-195/miR-4668 to regulate expression of genes related to lipid synthesis and uptake, including ACC , FAS , SCD1 , and CD36 . Finally, we identify that uc.372 is located downstream of the insulinoma-associated 2 ( INSM2 ) gene that is transcriptionally activated by upstream transcription factor 1 ( USF1 ). Our findings reveal a novel mechanism by which uc.372 drives hepatic steatosis through inhibition of miR-195/miR-4668 maturation to relieve miR-195/miR-4668-mediated suppression of functional target gene expression. Ultraconserved RNAs are a class of long non-coding RNAs whose functions are yet to be identified. Here Guo and colleagues show that an ultraconserved RNA uc.372 promotes lipogenesis and lipid accumulation within the hepatocytes by suppressing the maturation of miR-195/miR-4668 that inhibits lipogenic gene expression.

Precision oncology enables molecularly guided cancer therapy through multi-omics profiling, AI-driven classification, and biomarker-targeted interventions. Disulfidptosis has emerged as a promising therapeutic target, yet no ovarian cancer classification system currently incorporates this mechanism. The sequencing data of the samples in this study were obtained from TCGA and GEO databases. We analyzed 76 genes associated with disulfidptosis and performed consensus clustering based on their expression profiles to stratify the samples into two molecular subtypes. Differentially expressed genes (DEGs) were identified by comparing ovarian cancer tissues with normal samples. LASSO regression and random forest algorithms were then applied to screen marker genes that significantly influenced the clustering outcome. Ultimately, Ten disulfidptosis-related genes were ultimately selected to construct the predictive model. Single-cell sequencing was employed to characterize the tumor-specific expression patterns of key biomarkers. Digital spatial pathology analysis precisely mapped therapeutic target regions within tumor architectures. Immunohistochemical validation ultimately yielded clinically translatable biomarkers with diagnostic and therapeutic potential. Analysis of 76 disulfidptosis-related genes in ovarian cancer (OV) identified two molecular subtypes with distinct genomic profiles, tumor microenvironment characteristics, m6A regulator expression patterns, and clinical outcomes. Subgroup 1 showed copy number gains and immunosuppression, while Subgroup 2 exhibited higher tumor mutational burden (TMB) and immune activation. Subgroup 2 exhibited significantly higher immune infiltration, along with upregulated immune checkpoints. A 10-gene signature and CNN+GRU classifier robustly stratified patients. Single-cell and spatial transcriptomics confirmed epithelial-specific overexpression of key genes. This study identified a 10-gene signature related to disulfidptosis that is associated with distinct tumor microenvironment features, molecular heterogeneity, m6A modification patterns, and immune infiltration characteristics in ovarian cancer. Through multi-omics analyses-including single-cell and spatial transcriptomics-along with protein-level validation, our findings provide insights into the molecular landscape of ovarian cancer and suggest potential targets for future investigation into subtype-specific treatment strategies. All relevant code and analysis pipelines are publicly available at https://github.com/jinqy-lzu/Molecular_Subgroups_OV.git .

Sperm acrosomal membrane proteins, such as Izumo sperm–egg fusion 1 (IZUMO1) and sperm acrosome-associated 6 (SPACA6), play essential roles in mammalian gamete binding or fusion. How their biosynthesis is regulated during spermiogenesis has largely remained elusive. Here, we show that 1700029I15Rik knockout male mice are severely subfertile and their spermatozoa do not fuse with eggs. 1700029I15Rik is a type-II transmembrane protein expressed in early round spermatids but not in mature spermatozoa. It interacts with proteins involved in N-linked glycosylation, disulfide isomerization, and endoplasmic reticulum (ER)–Golgi trafficking, suggesting a potential role in nascent protein processing. The ablation of 1700029I15Rik destabilizes non-catalytic subunits of the oligosaccharyltransferase (OST) complex that are pivotal for N-glycosylation. The knockout testes exhibit normal expression of sperm plasma membrane proteins, but decreased abundance of multiple acrosomal membrane proteins involved in fertilization. The knockout sperm show upregulated chaperones related to ER-associated degradation (ERAD) and elevated protein ubiquitination; strikingly, SPACA6 becomes undetectable. Our results support for a specific, 1700029I15Rik-mediated pathway underpinning the biosynthesis of acrosomal membrane proteins during spermiogenesis.

Gastric cancer (GC) is characterized by pronounced molecular and clinical heterogeneity, creating major challenges for therapeutic decision-making. Limitations in current molecular classification hinder the development of personalized therapies, underscoring the need for improved diagnostic and prognostic frameworks. we conducted an integrated multi-omics analysis of bulk, single-cell, and spatial transcriptomic data to systematically characterize three key programmed cell death pathways—pyroptosis, apoptosis, and necroptosis (collectively abbreviated as PAN). A scoring-based clustering framework integrating multiple machine learning algorithms was developed to define high-resolution molecular subtypes and construct a deep learning signature. A hybrid CNN+BiLSTM model with cross-fusion attention was applied for transcriptomic feature extraction and subtype classification, achieving superior performance compared with existing approaches. Validation in the TCGA cohort confirmed the robustness and biological relevance of our model. Among the identified subtypes, Subtype 2 showed the most favorable prognosis. We further established a nine-gene prognostic signature with strong predictive value. High-risk patients exhibited poor survival, enhanced immune infiltration, and potential sensitivity to AKT inhibitors, with several drugs, including gefitinib and paclitaxel, identified as promising candidates. Experimental validation was conducted using the Human Protein Atlas (HPA) and RT-qPCR in clinical samples. CFLAR and TNFSF13B were upregulated and PDK4 downregulated in GC, while UACA showed no significant change. Additional prognostic genes (DFFB, PSMB6, GLP1R, HDAC9, BACH2) displayed expression patterns largely consistent across HPA, TCGA, and RT-qPCR, with minor discrepancies likely due to sample size. This study integrates multi-omics and deep learning with experimental validation, providing insights into programmed cell death regulation and offering robust biomarkers and therapeutic targets for GC.

In this study, the vibration characteristics of a bullet-loaded recorder’s vibration damping system under various preload conditions are investigated through theoretical analysis, numerical simulations, and experimental verification. The findings indicate that the inclusion of a polyurethane elastomer vibration damping buffer layer between the cartridge and the recorder, along with the application of a specific preload, significantly reduces the amplitude of vibration acceleration transmitted to the recorder’s interior. This, in turn, enhances the overload resistance of the cartridge’s internal circuit. Numerical simulation results and theoretical analysis suggest that increasing the preload on the buffer material between the elastomer and the recorder reduces both the frequency ratio and damping ratio of the damping system. This reduction further decreases the amplitude of vibration transmitted to the recorder. However, excessively high preload generates substantial compressive stress within the recorder under static conditions, intensifying during the projectile’s accelerated movement. As a consequence, deformation and damage occur to the internal circuitry. Therefore, ensuring that the recorder possesses the structural strength necessary to withstand increased preload is crucial. This balancing act improves the recorder’s resistance to shock, vibration, and overload, while also preventing excessive stress-induced damage.

More than 1000 genes are predicted to be predominantly expressed in mouse testis, yet many of them remain unstudied in terms of their roles in spermatogenesis and sperm function and their essentiality in male reproduction. Since individually indispensable factors can provide important implications for the diagnosis of genetically related idiopathic male infertility and may serve as candidate targets for the development of nonhormonal male contraceptives, our laboratories continuously analyze the functions of testis-enriched genes in vivo by generating knockout mouse lines using the CRISPR/Cas9 system. The dispensability of genes in male reproduction is easily determined by examining the fecundity of knockout males. During our large-scale screening of essential factors, we knocked out 30 genes that have a strong bias of expression in the testis and are mostly conserved in mammalian species including human. Fertility tests reveal that the mutant males exhibited normal fecundity, suggesting these genes are individually dispensable for male reproduction. Since such functionally redundant genes are of diminished biological and clinical significance, we believe that it is crucial to disseminate this list of genes, along with their phenotypic information, to the scientific community to avoid unnecessary expenditure of time and research funds and duplication of efforts by other laboratories. Summary Sentence Thirty testis-enriched genes are dispensable for male fertility based on phenotypic analyses of knockout mice produced by the CRISPR/Cas9 system.

Lenvatinib is the first target drug approved for advanced hepatocellular carcinoma (HCC). However, the development of drug resistance is common, and the mechanisms of lenvatinib resistance and resistant targets in HCC are poorly understood. By using CRISPR/Cas9 library screening, we screened out two key resistance genes, neurofibromin 1(NF1), and dual specificity phosphatase 9 (DUSP9), as critical drivers for lenvatinib resistance in HCC. With RNAi knockdown and CRISPR/Cas9 knockout models, we further clarified the mechanisms by which NF1 loss reactivates the PI3K/AKT and MAPK/ERK signaling pathways, while DUSP9 loss activates the MAPK/ERK signaling pathways, thereby inactivating FOXO3, followed by degradation of FOXO3, finally induced lenvatinib resistance. We also screened out trametinib, a small molecule pathway inhibitor for MEK, that can be used to reverse resistance induced by NF1 and DUSP9 loss in HCC cells. Trametinib was still able to halt HCC growth even when NF1 was knocked out in mice. Collectively, the findings indicate that NF1 and DUSP9 takes critical role in lenvatinib resistance and may be novel specific targets and predictive markers for lenvatinib resistance in HCC.

With increasing global energy transition and environmental awareness, liquefied natural gas (LNG) is rapidly developing as an efficient and clean energy source. LNG pumps are widely used in industrial applications. This study focuses on the LNG pump and pipeline system, and it innovatively establishes a computational model based on weak compressible fluid in order to better reflect the characteristics of pressure pulsation and the flow situation. Through numerical simulations, the flow characteristics of the pump were analyzed. In addition, the flow conditions at the pipe tee were analyzed, and the attenuation patterns of pressure waves at different frequencies within the pipe were also investigated. The internal flow field of the pump was analyzed at three specific time points. The results indicate that, during the initial start-up phase, the internal flow state of the pump is complex, with significant vortices and pressure fluctuations. As the flow rate and rotational speed increase, the flow gradually stabilizes. Moreover, the pressure pulsation coefficient within the pipeline varies significantly with position.