Infection with Helicobacter pylori (Hp) is associated with various gastric disorders, and its virulence factor cytotoxin-associated protein A (CagA) drives cytopathological changes, cellular transformation, and tumor progression. N6-methyladenosine (m6A) mRNA modification plays a key role in carcinogenesis, including gastric cancer (GC). However, whether Hp promotes GC malignancy by regulating m6A modification remains poorly understood. The expression levels of CagA and related genes were detected by RT-qPCR and Western blotting. Functional validation of CagA-mediated malignant phenotypes in GC cells was performed using CCK-8, colony formation, wound healing, and Transwell assays. Global m6A modification levels were evaluated by RNA dot blot analysis. The expression and distribution of METTL3 and other target genes in cells and tissues were assessed by immunofluorescence and immunohistochemistry. Co-immunoprecipitation (Co-IP) and ubiquitination assays were used to examine the interaction between METTL3 and USP7, as well as the ubiquitin-dependent degradation of METTL3. CagA promoted GC cell proliferation, metastasis, and glycolysis both in vitro and in vivo. Omics data analysis, RT-qPCR, and Western blotting results demonstrated that CagA increased METTL3 expression and global m6A levels in GC cells. Mechanistically, CagA enhanced the interaction between USP7 and METTL3, thereby inhibiting METTL3 ubiquitination and proteasomal degradation. CagA upregulates m6A modification of DUSP6 to boost glycolysis and accelerate GC progression.

Roosters play a crucial role in breeder chicken production. A decline in reproductive performance during the late breeding stage is a major factor limiting economic returns. Testosterone, a key hormone for maintaining secondary sexual characteristics and supporting spermatogenesis, is primarily synthesized and processed within mitochondria. With advancing age, mitochondrial function deteriorates in roosters, leading to reduced testosterone synthesis and impaired reproductive capacity. This study aimed to elucidate the mechanisms through which rest and sport affect the reproductive performance of aging roosters. A total of 36 Tianfu Pink roosters aged 110 weeks were allocated into three groups with three replicates per group. After a 4-week intervention involving rest and sport regimens, natural mating was conducted to collect reproductive performance data. The results showed that rest and sport exerted anti-inflammatory effects, significantly improved semen quality and hatching performance, increased serum levels of testosterone and gonadotropins, enhanced systemic antioxidant capacity, and markedly upregulated FUNDC1 expression in the testes. In primary chicken testicular interstitial cells, overexpression or knockdown of FUNDC1 significantly enhanced or suppressed mitochondrial function, as well as the expression of genes and proteins related to antioxidant defense and testosterone synthesis. Moreover, FUNDC1 overexpression alleviated rotenone-induced mitochondrial damage and restored testosterone synthesis in testicular interstitial cells. These findings suggest that sport may enhance testosterone synthesis in testicular interstitial cells by modulating FUNDC1 expression, thereby improving mitochondrial function and antioxidant defense. This study provides theoretical and technical insights for improving the reproductive performance of breeding roosters during the late production phase.

Due to the high cost of sequencing, there is a scarcity of high-resolved spatial transcriptome (ST) data available for downstream analysis. In this paper, we propose a deep generative model based on a dependency-aware Variational AutoEncoder (VAE) with bi-decoders, called HistoSST, to infer super-resolved ST data from histology images. HistoSST combines a Gaussian Process prior and a Gaussian prior to dynamically capture the spatial dependency and global information in histology images. And then, it establishes the close correlation between the image patch and gene expression via dual decoders. Depending on the size of the image patch, HistoSST can generate ST data of any resolution. If the patch is smaller than a spot of existing ST data, HistoSST can generate its super-resolved data. The source code is available at https://github.com/PelenJiang/HistoSST .

Tea polyphenols (TPs), bioactive secondary metabolites from Camellia sinensis, demonstrate significant potential for enhancing poultry reproductive efficiency. This 43-week study systematically evaluated graded TPs supplementation (0-500 mg/kg Food Weight) in Tianfu G02 Blue-shell roosters (n = 540) through growth monitoring, histopathological analysis (Hematoxylin and Eosin staining, H&E), and molecular profiling (ELISA, qPCR). The data were analyzed using a sampling T-test or ANOVA and Tukey's Test. Optimal growth performance was achieved at 100-400 mg/kg TP doses, improved daily feed intake and weight gain. The 200 mg/kg cohort exhibited peak spermatogenic capacity at week 28 (sperm density, P < 0.05) and week 43 (motility, P < 0.05), while 300 mg/kg enhanced sperm viability. Paradoxically, 500 mg/kg impaired reproductive parameters (the lowest sperm density, motility and viability). Testicular morphology revealed dose-dependent effects: 300-400 mg/kg groups showed seminiferous tubule expansion with concomitant testosterone elevation. Molecular analyses demonstrated TPs-mediated upregulation of androgen pathway genes (AR, Pgk2, P < 0.05) and antioxidant enhancement (MDA reduction, SOD/GSH-Px activation, P < 0.05). Immune modulation was evidenced by 200 mg/kg-induced immunoglobulin elevation (IgM, IgA, P < 0.05) and cytokine upregulation (IL-1β, IL-2, P < 0.05). Intestinal barrier integrity improved via ZO-1 and Claudin3 expression in 200-300 mg/kg groups (P < 0.05). These findings establish 200-300 mg/kg TPs as the optimal dosage window for enhancing rooster productivity, while cautioning against supra-nutritional (>400 mg/kg) applications.

Programmed cell death (PCD), including autophagy, apoptosis, and ferroptosis, is a fundamental biological process that plays a critical role in follicular development and atresia in livestock. In ovaries, the vast majority of follicles undergo atresia, while only a small fraction reach ovulation. Emerging evidence suggests that these three forms of PCD are intricately involved in regulating follicular fate through distinct yet interconnected molecular mechanisms. This review summarizes recent advances in understanding the roles of autophagy, apoptosis, and ferroptosis in follicular development and atresia, with a focus on their molecular mechanisms and interactions. By elucidating the complex regulatory networks of PCD in ovarian physiology, this review aims to provide new insights into improving reproductive efficiency in livestock through targeted modulation of these pathways.

Transcriptional regulation is a dynamic process that coordinates diverse cellular activities, and the use of small molecules to perturb gene expression has propelled our understanding of the fundamental regulatory mechanisms. However, small molecules typically lack the spatiotemporal precision required in highly non-invasive, controlled settings. Here we present the development of a cell-permeable small-molecule DNA G-quadruplex (G4) binder, termed G4switch, that can be reversibly toggled on and off by visible light. We have biophysically characterized the light-mediated control of G4 binding in vitro, followed by cellular, genomic mapping of G4switch to G4 targets in chromatin to confirm G4-selective, light-dependent binding in a cellular context. By deploying G4switch in living cells, we show spatiotemporal control over the expression of a set of G4-containing genes and G4-associated cell proliferation. Our studies demonstrate a chemical tool and approach to interrogate the dynamics of key biological processes directly at the molecular level in cells.

The spatial structure of cells is highly organized at multiscale levels from global spatial domains to local cell type heterogeneity. Existing methods for analyzing spatially resolved transcriptomics (SRT) are separately designed for either domain alignment across multiple slices or deconvoluting cell type compositions within a single slice. To this end, a novel deep learning method, SMILE, is proposed which combines graph contrastive autoencoder and multilayer perceptron with local constraints to learn multiscale and informative spot representations. By comparing SMILE with the state-of-the-art methods on simulation and real datasets, the superior performance of SMILE is demonstrated on spatial alignment, domain identification, and cell type deconvolution. The results show SMILE's capability not only in simultaneously dissecting spatial variations at different scales but also in unraveling altered cellular microenvironments in diseased conditions. Moreover, SMILE can utilize prior domain annotation information of one slice to further enhance the performance.

Non-alcoholic fatty liver disease (NAFLD) is a clinical syndrome characterized primarily by hepatocellular steatosis and lipid accumulation, which leads to hepatocyte apoptosis, autophagy, inflammation, and intracellular oxidative stress. NAFLD is recognized as one of the most prevalent and complex chronic liver diseases globally, with its occurrence and associated mortality rates rising swiftly each year. Due to the high similarity between chicken fatty liver syndrome (FLS) and NAFLD, as well as the easy availability of diseased chickens, the chicken is considered an ideal model for studying the pathogenesis of NAFLD. Previous studies have pinpointed several circular RNAs (circRNAs) implicated in the pathogenesis of NAFLD, yet the underlying functions and mechanisms of numerous circRNAs continue to remain elusive. In this experiment, we utilized circRNA sequencing of chicken livers to identify a novel circRNA, named circACACA, and discovered that it disrupts the metabolic homeostasis of lipids within hepatocytes. Consequently, this disruption leads to oxidative stress and the induction of autophagy, ultimately exerting an adverse effect on chicken liver health. Mechanistically, circACACA functions as a molecular sponge for miR-132b-5p and miR-101-2-5p to modulate the expression of the downstream CBFB/PIM1 complex. Consequently, it influenced the activity of the AKT/mTOR and PPAR-γ signaling pathways to perform its physiological functions. Crucially, we noticed substantial sequence similarity of circACACA across diverse species by comprehensively searching databases. Further, our research with a mouse model confirmed that the functional conservation of circACACA across livers of different species. Overall, this study built a mechanistic network for circACACA and confirmed its sequence conservation and functional relevance across various species. Our results not only provide new targets for the prevention and treatment of NAFLD but also present fresh perspectives for progress in healthy production of laying hens.

BACKGROUND:Follicular atresia, a complex degenerative process regulated by multiple molecular mechanisms, significantly affects female reproductive performance in animals. While granulosa cell (GC) apoptosis has been well established as a primary mechanism underlying follicular atresia, the potential involvement of ferroptosis, which is an iron-dependent form of regulated cell death, remains largely unexplored in chickens. RESULTS:Using a tamoxifen (TMX)-induced avian model of follicular atresia, we demonstrated that ferroptosis plays a critical role in follicular degeneration. Inhibition of ferroptosis through pharmacological agents significantly restored follicular function, underscoring its potential as a therapeutic target. Notably, we observed a significant upregulation of ubiquitin-specific peptidase 9, X-linked (USP9X) in GCs during atresia. Through comprehensive in vitro and in vivo investigations, we confirmed that USP9X facilitates follicular atresia by promoting ferroptosis in GCs. Mechanistically, USP9X induces ferroptosis by stabilizing Beclin1 through deubiquitination, thereby activating autophagy-dependent ferroptosis. This pathway was effectively suppressed by autophagy inhibitors, emphasizing the essential role of autophagy in USP9X-mediated ferroptosis. CONCLUSIONS:Our findings provide the evidence that the USP9X-Beclin1 axis regulates autophagy-dependent ferroptosis during avian follicular atresia. These insights reveal novel molecular targets and potential genetic markers for improving reproductive efficiency in chicken breeding programs.

Strategies focusing on dually targeting tumor cells and immune cells within the immunosuppressive tumor microenvironment (TME) hold promising potential for improving the efficacy of cancer immunotherapy; however, they are challenging due to the off-target adverse effects of the nonselective killing effect on tumor cells and immune cells. Herein, a ferritin-albumin nanocomplex (IL@FA NPs) encapsulated with the photosensitizer IR820 and lipoic acid (LA) is designed to selectively reinforce the ferroptosis-induced tumor cell death, promote DC activation and tumor-associated macrophage (TAM) transformation from M2 to M1, and ultimately boost the antitumor immunity. Upon laser irradiation, the introduction of IR820 and LA significantly contributes to accelerating the release of ferrous ions from ferritin in IL@FA NPs to further induce the ferroptosis of the tumor cells. The ferroptosis-induced immunogenic cell death (ICD) of tumor cells could promote DC maturation and activate cytotoxic CD8+ T cells. Meanwhile, upon laser irradiation, reactive oxygen species (ROS), produced by IL@FA NPs, can facilitate DC maturation and M2-to-M1 repolarization of TAMs. Effective tumor growth suppression was realized by IL@FA NPs without showing toxicities. This study presents a promising "three birds with one stone" strategy to synergistically reinforce the ferroptosis of tumor cells, DC maturation, and TAM repolarization from M2 to M1 for enhanced cancer immunotherapy.

85% of colon cancer patients don’t respond to anti-PD-L1 due to the lack of immune infiltration while the efficacy of photodynamic therapy (PDT) was limited to hypoxic environment. Thus, a PD-L1 small molecule inhibitor C2 was chose to self-assemble into nanoparticles with photosensitizer, leveraging the unique advantages and active targeting of small molecule, the passive targeting of nanoparticles, and immunogenic cell death (ICD) induced by PDT. Stable nanoparticles C2-Ce6 NPs was formed by Ce6 and C2 meticulously selected from our compound library through Docking, Homogeneous Time Resolved Fluorescence (HTRF), Surface Plasmon Resonance (SPR), and Molecular dynamics (MD). C2-Ce6 NPs demonstrated good safety while achieving a TGI of 94.7 % in the MC38 mouse model with significantly increase of T cell infiltration, reduction of the expression of Ki67 and ICD effect proved via the detection of damage-associated molecular patterns (DAMPs), which indicated combined treatment is more advantageous. Tumor cells were subjected to both internal and external pressures, which is expected to mitigate the primary resistance and strong immunogenicity of antibody-based immune checkpoint inhibitors, further activate the immune system to broad the scope of immunotherapy indications and simultaneously enhance the efficacy comparing to single PDT.

Deep learning has advanced the development of automated cervical cytology, yet limited studies have delved into methods for incorporating medical domain knowledge, and model interpretability has not been thoroughly investigated. To address this issue, this paper proposes a novel, explainable detection method for abnormal cervical cells, called dual -stream self -attention based feature fusion and origin grouping network (DSAFFOGNet). To encourage the model to focus more on lesion cells and cell nuclei of diagnostic significance, the dual -stream self -attention (DSA) module is introduced to enhance the learning of lesion -specific features. In view of the complex background, cell dense distribution, cell overlap, or clumps existing in the actual cervical cytology images, multi -scale features are extracted and fused by using the path aggregation network (PAN) to enhance the feature representation ability. By integrating biomedical insights regarding cell provenance and formulating an origin grouping loss, DSA-FFOGNet adjusts the penalties for cervical cells originating from different groups, thereby enhancing the optimization of the model training process. To further improve the detection performance, the classification and localization tasks are decoupled via the use of double detection heads. Extensive experiments validate the robustness of the proposed DSA-FFOGNet. The visualization of class activation maps (CAMs) showcases the model's interpretability. The proposed approach advances the application and development of explainable artificial intelligence (XAI) models in cervical cytology and inspires further research in automated cervical cytology.

Accumulating evidence indicates that G-quadruplexes (G4s) are involved in transcriptional regulation. Previous studies have demonstrated that DHX36 preferentially resolves G4s, suggesting its potential impact on gene transcription mediated by these structures. However, systematic validation is required to establish a link between DHX36 activity and its roles in transcriptional regulation. In this study, we investigate the role of DHX36 in transcription. First, we employ the cleavage under targets and tagmentation (CUT&Tag), an efficient method for mapping protein–DNA interactions, to identify the binding sites in the chromatin of MCF-7 cells. Subsequently, we use the auxin-inducible degron (AID) protein degradation system and improved nascent RNA sequencing method acrylonitrile-mediated uridine-to-cytidine conversion sequencing (AMUC-seq) to pinpoint genes directly regulated by DHX36. Our results reveal a significant enrichment of G4 structures at DHX36 target sites, predominantly located in active genomic regions. In vitro assays further demonstrate DHX36's interaction with G4 sequences from three specific oncogenes. These findings underscore the potential role of DHX36 in modulating gene transcription through G4 structures.

Four-stranded G-quadruplexes (G4s) are DNA secondary structures that can form in the human genome. G4 structures have been detected in gene promoters and are associated with transcriptionally active chromatin and the recruitment of transcription factors and chromatin remodelers. We adopted a controlled, synthetic biology approach to understand how G4s can influence transcription. We stably integrated G4-forming sequences into the promoter of a synthetic reporter gene and inserted these into the genome of human cells. The integrated G4 sequences were shown to fold into a G4 structure within a cellular genomic context. We demonstrate that G4 structure formation within a gene promoter stimulates transcription compared to the corresponding G4-negative control promoter in a way that is not dependent on primary sequence or inherent G-richness. Systematic variation in the stability of folded G4s showed that in this system, transcriptional levels increased with higher stability of the G4 structure. By creating and manipulating a chromosomally integrated synthetic promoter, we have shown that G4 structure formation in a defined gene promoter can cause gene transcription to increase, which aligns with earlier observational correlations reported in the literature linking G4s to active transcription.

This study aimed to compare the effects of various selenium (Se) sources (2 mg/kg) on the performance, quality, and antioxidant capacity of laying hens as well as the Se content in their eggs and blood. We selected 720 34-wk-old Lohmann pink-shell laying hens were randomly assigned into 6 groups and fed a basal diet (control) or a basal diet supplemented with various Se sources (Se-enriched yeast, SY-A, SY-C, SY-N; selenomethionine SM, nano-Se SN) for 16 wk. There were 10 replicates of 120 hens per group. Dietary Se supplementation increased the egg production rate of all laying hens. Egg and serum Se deposition was highest in the SM group. Yolk color scores of SY-A and SY-N groups were significantly lower than those of other groups (P < 0.01). The protein height and Haugh unit were significantly lower in the SN group than in the other groups (P < 0.05). The yolk height was significantly higher in the SN and SY-N groups than in the SY-A group (P < 0.05). Dietary supplementation of selenium can improve the antioxidant capacity of laying hens. The SOD content of SM group was significantly lower than that of SY-A and SN group (P < 0.05). The malondialdehyde (MDA) content was significantly higher in the SM group than in the SY-A group (P < 0.05). The present work empirically demonstrated that the production performance of laying hens supplemented with 2 mg/kg Se was superior to that of the hens receiving only a basal diet. The SY-C group exhibited the best production performance, the SY-A group had the highest antioxidant capacity, and the SM group produced eggs with the highest level of Se enrichment.

The number of mitotic cells is an important indicator of grading invasive breast cancer. It is very challenging for pathologists to identify and count mitotic cells in pathological sections with naked eyes under the microscope. Therefore, many computational models for the automatic identification of mitotic cells based on machine learning, especially deep learning, have been proposed. However, converging to the local optimal solution is one of the main problems in model training. In this paper, we proposed a novel multilevel iterative training strategy to address the problem. To evaluate the proposed training strategy, we constructed the mitotic cell classification model with ResNet50 and trained the model with different training strategies. The results showed that the models trained with the proposed training strategy performed better than those trained with the conventional strategy in the independent test set, illustrating the effectiveness of the new training strategy. Furthermore, after training with our proposed strategy, the ResNet50 model with Adam optimizer has achieved 89.26% F1 score on the public MITOSI14 dataset, which is higher than that of the state-of-the-art methods reported in the literature.

The molecular subtype of breast cancer plays an important role in the prognosis of patients and guides physicians to develop scientific therapeutic regimes. In clinical practice, physicians classify molecular subtypes of breast cancer with immunohistochemistry(IHC) technology, which requires a long cycle for diagnosis, resulting in a delay in effective treatment of patients with breast cancer. To improve the diagnostic rate, we proposed a machine learning method that predicted molecular subtypes of breast cancer from H E-stained histopathological images. Although some molecular subtype prediction methods have been suggested, they are noisy and lack clinical evidence. To address these issues, we introduced a patch filter-based molecular subtype prediction (PFMSP) method using spatial transcriptomics data, training a patch filter with spatial transcriptomics data first, and then the trained filter was used to select valuable patches for molecular subtype prediction in other H E-stained histopathological images. These valuable patches contained one or more genes expressed of ESR1, ESR2, PGR, and ERBB2. We evaluated the performance of our method on the spatial transcriptomics(ST) dataset and the TCGA-BRCA dataset, and the patches filtered by the patch filter achieved accuracies of 80

Background The reproductive performance of chickens mainly depends on the development of follicles. Abnormal follicle development can lead to decreased reproductive performance and even ovarian disease among chickens. Chicken is the only non-human animal with a high incidence of spontaneous ovarian cancer. In recent years, the involvement of circRNAs in follicle development and atresia regulation has been confirmed. Results In the present study, we used healthy and atretic chicken follicles for circRNA RNC-seq. The results showed differential expression of circRALGPS2. It was then confirmed that circRALGPS2 can translate into a protein, named circRALGPS2-212aa, which has IRES activity. Next, we found that circRALGPS2-212aa promotes apoptosis and autophagy in chicken granulosa cells by forming a complex with PARP1 and HMGB1. Conclusions Our results revealed that circRALGPS2 can regulate chicken granulosa cell apoptosis and autophagy through the circRALGPS2-212aa/PARP1/HMGB1 axis.

Lung granuloma is a very common lung disease, and its specific diagnosis is important for determining the exact cause of the disease as well as the prognosis of the patient. And, an effective lung granuloma detection model based on computer-aided diagnostics (CAD) can help pathologists to localize granulomas, thereby improving the efficiency of the specific diagnosis. However, for lung granuloma detection models based on CAD, the significant size differences between granulomas and how to better utilize the morphological features of granulomas are both critical challenges to be addressed. In this paper, we propose an automatic method CRDet to localize granulomas in histopathological images and deal with these challenges. We first introduce the multi-scale feature extraction network with self-attention to extract features at different scales at the same time. Then, the features will be converted to circle representations of granulomas by circle representation detection heads to achieve the alignment of features and ground truth. In this way, we can also more effectively use the circular morphological features of granulomas. Finally, we propose a center point calibration method at the inference stage to further optimize the circle representation. For model evaluation, we built a lung granuloma circle representation dataset named LGCR, including 288 images from 50 subjects. Our method yielded 0.316 mAP and 0.571 mAR, outperforming the state-of-the-art object detection methods on our proposed LGCR.