Re-analysis of single cell and spatial transcriptomics data reveals B cell landscape in gastric cancer microenvironment and its potential crosstalk with tumor cells for clinical prognosis.

BACKGROUND: At present, immunotherapy has become a powerful treatment for advanced gastric cancer (AGC), but not all patients can benefit from it. According to the latest research, the impact of B cell subpopulations on the immune microenvironment of gastric cancer (GC) is unknown. Exploring whether the interaction between B cells and tumor cells in GC affects the effectiveness of immunotherapy has attracted our interest. METHODS: This study involved the re-analysis of single-cell RNA (scRNA) and spatial transcriptomics (ST) data from publicly available datasets. The focus was on investigating the subpopulations and differentiation trajectories of B cells in the gastric cancer (GC) tumor immune microenvironment (TIME). Spatial transcriptomics (ST) and multiple immunofluorescence (mIF) revealed a clear co-localization pattern between B cells and tumor cells. Multiple immunotherapy datasets were collected to identify unique immunotherapy biomarkers. The unique immunotherapeutic potential of targeting CCL28 was validated through a mouse gastric cancer model. In addition, flow cytometry revealed changes in the tumor immune microenvironment targeting CCL28. RESULTS: The re-analysis of ST data from multiple cancer types revealed a co-localization pattern between B cells and tumor cells. A significant number of IgA plasma cells were identified in the GC TIME. Five different tumor-infiltrating B cell subpopulations and two unique B cell differentiation trajectories were characterized, along with seven GC-related states. By analyzing the communication between GC cells and B cells, it was further discovered that tumor cells can influence and recruit plasma cells through CCL28-CCR10 signaling. Additionally, there was a crosstalk between GC cells and B cells. Finally, we identified the LAMA/CD44 signaling axis as a potential prognostic marker for immunotherapy through a large amount of immunotherapy data. We also validated through various animal tumor models that targeting CCL28 can significantly promote CD8+T cell infiltration and function in the TME by regulating B cell and plasma cell functions, and has the ability to synergize immunotherapy. CONCLUSION: The co-localization and crosstalk between GC cells and B cells significantly affect the efficacy of immunotherapy, and inhibiting the CCL28-CCR10 signal axis is a potential immunotherapy target for GC. Meanwhile, LAMA/CD44 pair may be a potential adverse indicator for immunotherapy and tumor prognosis.

Identification and experimental validation of m7G-related molecular subtypes, immune signature, and feature genes in Alzheimer's disease.

Background: Studies has shown that N7-methylguanosine (m7G) modification plays a critical role in neurological diseases. However, the exact role and association of m7G with the immune microenvironment in Alzheimer's disease (AD) remain largely unknown and unexplored. Methods: The study datasets comprised 667 AD samples and 503 control samples selected from eight datasets in the Gene Expression Omnibus database; m7G regulator genes were obtained from previous literature. The AD subtypes were identified by consensus clustering analysis according to m7G regulator genes. The clinical characteristics, immune infiltration, and biological functions of the AD subgroups were evaluated. A combination of different types of machine-learning algorithms were used for the identification of AD genes. We also assessed and validated the diagnostic performance of the identified genes via qRT-PCR, immunofluorescence, and immunohistochemical analyses. Results: Two AD distinct subgroups, namely cluster A and cluster B, were identified. Cluster A had poor pathological progression and immune infiltration, representing a high-risk subgroup for AD. The differentially expressed genes of cluster A were enriched in immune and synapse-related pathways, suggesting that these genes probably contribute to AD progression by regulating immune-related pathways. Additionally, five feature genes (AEBP1, CARTPT, AK5, NPTX2, and COPG2IT1) were identified, which were used to construct a nomogram model with good ability to predict AD. The animal experiment analyses further confirmed that these feature genes were associated with AD development. Conclusion: To the best of our knowledge, this is the first study to reveal close correlations among m7G RNA modification, the immune microenvironment, and the pathogenesis of AD. We also identified five feature genes associated with AD, further contributing to our understanding of the underlying mechanisms and potential therapeutic targets for AD.

Evaluating computational efforts and physiological resolution of mathematical models of cardiac tissue.

Computational techniques have significantly advanced our understanding of cardiac electrophysiology, yet they have predominantly concentrated on averaged models that do not represent the intricate dynamics near individual cardiomyocytes. Recently, accurate models representing individual cells have gained popularity, enabling analysis of the electrophysiology at the micrometer level. Here, we evaluate five mathematical models to determine their computational efficiency and physiological fidelity. Our findings reveal that cell-based models introduced in recent literature offer both efficiency and precision for simulating small tissue samples (comprising thousands of cardiomyocytes). Conversely, the traditional bidomain model and its simplified counterpart, the monodomain model, are more appropriate for larger tissue masses (encompassing millions to billions of cardiomyocytes). For simulations requiring detailed parameter variations along individual cell membranes, the EMI model emerges as the only viable choice. This model distinctively accounts for the extracellular (E), membrane (M), and intracellular (I) spaces, providing a comprehensive framework for detailed studies. Nonetheless, the EMI model's applicability to large-scale tissues is limited by its substantial computational demands for subcellular resolution.

A Light-Responsive Neural Circuit Suppresses Feeding.

Light plays an essential role in a variety of physiological processes, including vision, mood, and glucose homeostasis. However, the intricate relationship between light and an animal's feeding behavior has remained elusive. Here, we found that light exposure suppresses food intake, whereas darkness amplifies it in male mice. Interestingly, this phenomenon extends its reach to diurnal male Nile grass rats and healthy humans. We further show that lateral habenula (LHb) neurons in mice respond to light exposure, which in turn activates 5-HT neurons in the dorsal Raphe nucleus (DRN). Activation of the LHb→5-HTDRN circuit in mice blunts darkness-induced hyperphagia, while inhibition of the circuit prevents light-induced anorexia. Together, we discovered a light-responsive neural circuit that relays the environmental light signals to regulate feeding behavior in mice.

Examining the association between delay discounting, delay aversion and physical activity in Chinese adults with type-2 diabetes mellitus.

BACKGROUND: The role of physical activity in diabetes is critical, influencing this disease's development, man-agement, and overall outcomes. In China, 22.3% of adults do not meet the minimum level of physical activity recommended by the World Health Organization. Therefore, it is imperative to identify the factors that contributing to lack of physical activity must be identified. AIM: To investigate the relationship among delay discounting, delay aversion, glycated hemoglobin (HbA1c), and various levels of physical activity in Chinese adults diagnosed with type 2 diabetes mellitus (T2DM). METHODS: In 2023, 400 adults with T2DM were recruited from the People's Hospital of Linxia Hui Autonomous Prefecture of Gansu Province. A face-to-face questionnaire was used to gather demographic data and details on physical activity, delay discounting, and delay aversion. In addition, HbA1c levels were measured in all 400 participants. The primary independent variables considered were delay discounting and delay aversion. The outcome variables included HbA1c levels and different intensity levels of physical activity, including walking, moderate physical activity, and vigorous physical activity. Multiple linear regression models were utilized to assess the relationship between delay discounting, delay aversion, and HbA1c levels, along with the intensity of different physical activity measured in met-hours per week. RESULTS: After controlling for the sample characteristics, delay discounting was negatively associated with moderate physical activity (ß = -2.386, 95%CI: -4.370 to -0.401). Meanwhile, delay aversion was negatively associated with the level of moderate physical activity (ß = -3.527, 95% CI: -5.578 to -1.476) in the multiple linear regression model, with statistically significant differences. CONCLUSION: Elevated delay discounting and increased delay aversion correlated with reduced levels of moderate physical activity. Result suggests that delay discounting and aversion may influence engagement in moderate physical activity. This study recommends that health administration and government consider delay discounting and delay aversion when formulating behavioral intervention strategies and treatment guidelines involving physical activity for patients with T2DM, which may increase participation in physical activity. This study contributes a novel perspective to the research on physical activity in adults with T2DM by examining the significance of future health considerations and the role of emotional responses to delays.

Prediction of the benign and malignant nature of masses in COPD background based on Habitat-based enhanced CT radiomics modeling: A preliminary study.

BACKGROUND: It is difficult to differentiate between chronic obstructive pulmonary disease (COPD)-peripheral bronchogenic carcinoma (COPD-PBC) and inflammatory masses. OBJECTIVE: This study aims to predict COPD-PBC based on clinical data and preoperative Habitat-based enhanced CT radiomics (HECT radiomics) modeling. METHODS: A retrospective analysis was conducted on clinical imaging data of 232 cases of postoperative pathological confirmed PBC or inflammatory masses. The PBC group consisted of 82 cases, while the non-PBC group consisted of 150 cases. A training set and a testing set were established using a 7:3 ratio and a time cutoff point. In the training set, multiple models were established using clinical data and radiomics texture changes within different enhanced areas of the CT mass (HECT radiomics). The AUC values of each model were compared using Delong's test, and the clinical net benefit of the models was tested using decision curve analysis (DCA). The models were then externally validated in the testing set, and a nomogram of predicting COPD-PBC was created. RESULTS: Univariate analysis confirmed that female gender, tumor morphology, CEA, Cyfra21-1, CT enhancement pattern, and Habitat-Radscore B/C were predictive factors for COPD-PBC (P< 0.05). The combination model based on these factors had significantly higher predictive performance [AUC: 0.894, 95% CI (0.836-0.936)] than the clinical data model [AUC: 0.758, 95% CI (0.685-0.822)] and radiomics model [AUC: 0.828, 95% CI (0.761-0.882)]. DCA also confirmed the higher clinical net benefit of the combination model, which was validated in the testing set. The nomogram developed based on the combination model helped predict COPD-PBC. CONCLUSION: The combination model based on clinical data and Habitat-based enhanced CT radiomics can help differentiate COPD-PBC, providing a new non-invasive and efficient method for its diagnosis, treatment, and clinical decision-making.

Ningxin-Tongyu-Zishen formula alleviates the senescence of granulosa cells on D-galactose-induced premature ovarian insufficiency mice.

Ningxin-Tongyu-Zishen formula (NTZF) is a clinical experience formula for the treatment of premature ovarian insufficiency (POI) in traditional Chinese medicine (TCM), and the potential mechanism is unknown. For in vivo experiments, POI mouse models (C57BL/6 mice), were constructed by subcutaneous injection of D-galactose (D-gal, 200 mg/kg). After treatment of NTZF (10.14, 20.27, 40.54 g/kg;) or estradiol valerate (0.15 mg/kg), ovarian function, oxidative stress (OS) and protein expression of Sirt1/p53 were evaluated. For in vitro experiments, H2O2 (200 µM) was used to treat KGN to construct ovarian granulosa cells (OGCs) cell senescence model. Pretreatment with NTZF (1.06 mg/mL) or p53 inhibitor (Pifithrin-α, 1 µM) was performed before induction of senescence, and further evaluated the cell senescence, OS, mRNA and protein expression of Sirt1/p53. In vivo, NTZF improved ovarian function, alleviated OS and Sirt1/p53 signaling abnormalities in POI mice. In vitro experiments showed that NTZF reduced the level of OS and alleviated the senescence of H2O2-induced KGN. In addition, NTZF activated the protein expression of Sirt1, inhibited the mRNA transcription and protein expression of p53 and p21. Alleviating OGCs senescence and protecting ovarian function through Sirt1/p53 is one of the potential mechanisms of NTZF in the treatment of POI.

Analysis and experimental validation of necroptosis-related molecular classification, immune signature and feature genes in Alzheimer's disease.

Necroptosis, a programmed cell death pathway, has been demonstrated to be activated in Alzheimer's disease (AD). However, the precise role of necroptosis and its correlation with immune cell infiltration in AD remains unclear. In this study, we conducted non-negative matrix factorization clustering analysis to identify three subtypes of AD based on necroptosis-relevant genes. Notably, these subtypes exhibited varying necroptosis scores, clinical characteristics and immune infiltration signatures. Cluster B, characterized by high necroptosis scores, showed higher immune cell infiltration and was associated with a more severe pathology, potentially representing a high-risk subgroup. To identify potential biomarkers for AD within cluster B, we employed two machine learning algorithms: the least absolute shrinkage and selection operator regression and Random Forest. Subsequently, we identified eight feature genes (CARTPT, KLHL35, NRN1, NT5DC3, PCYOX1L, RHOQ, SLC6A12, and SLC38A2) that were utilized to develop a diagnosis model with remarkable predictive capacity for AD. Moreover, we conducted validation using bulk RNA-seq, single-nucleus RNA-seq, and in vivo experiments to confirm the expression of these feature genes. In summary, our study identified a novel necroptosis-related subtype of AD and eight diagnostic biomarkers, explored the roles of necroptosis in AD progression and shed new light for the clinical diagnosis and treatment of this disease.

Spatiotemporal variations, sources, and atmospheric transformation potential of volatile organic compounds in an industrial zone based on high-resolution measurements in three plants.

Industrial emissions are significant sources of volatile organic compounds (VOCs). This study conducted a field campaign at high temporal and spatial resolution to monitor VOCs within three plants in an industrial park in southern China. VOC concentrations showed significant spatial variability in this industrial zone, with median concentrations of 75.22, 40.53, and 29.41 µg/m3 for the total VOCs in the three plants, respectively, with oxygenated VOCs (OVOCs) or aromatics being the major VOCs. Spatial variability within each plant was also significant but VOC-dependent. Seasonal variations in the VOC levels were governed by their industrial emissions, meteorological conditions, and photochemical losses, and they were different for the four groups of VOCs. The temporal and spatial variations in the VOC compositions suggest similar sources of each class of VOCs during different periods of the year in each plant. The diurnal patterns of VOCs (unimodal or bimodal) clearly differed from those at most industrial/urban locations previously, reflecting a dependence on industrial activities. The secondary transformation potential of VOCs also varied temporally and spatially, and aromatics generally made the predominant contributions in this industrial park. The loss rate of OH radicals and ozone formation potential were highly correlated, but the linear relationship substantially changed in summer and autumn due to the intensive emissions of an OVOC species. The lifetime cancer and non-cancer risks via occupational inhalation of the VOCs in the plants were acceptable but merit attention. Taking the secondary transformation potential and health risks into consideration, styrene, xylene, toluene, trichloroethylene, and benzene were proposed to be the priority VOCs regulated in the plants.

Ntsr1 contributes to pulmonary hypertension by enhancing endoplasmic reticulum stress via JAK2-STAT3-Thbs1 signaling.

Pulmonary hypertension (PH) is a severe clinical syndrome with pulmonary vascular remodeling and poor long-term prognosis. Neurotensin receptor 1 (Ntsr1), serve as one of the G protein-coupled receptors (GPCRs), implicates in various biological processes, but the potential effects of Ntsr1 in PH development are unclear. The Sugen/Hypoxia (SuHx) or monocrotaline (MCT) induced rat PH model was used in our study and the PH rats showed aggravated pulmonary artery remodeling and increased right ventricular systolic pressure (RVSP). Our results revealed that Ntsr1 induced endoplasmic reticulum (ER) stress response via ATF6 activation contributed to the development of PH. Moreover, RNA-sequencing (RNA-seq) and phosphoproteomics were performed and the Ntsr1-JAK2-STAT3-thrombospondin 1 (Thbs1)-ATF6 signaling was distinguished as the key pathway. In vitro, pulmonary artery smooth muscle cells (PASMCs) under hypoxia condition showed enhanced proliferation and migration properties, which could be inhibited by Ntsr1 knockdown, JAK2 inhibitor (Fedratinib) treatment, STAT3 inhibitior (Stattic) treatment, Thbs1 knockdown or ATF6 knockdown. In addition, adeno-associated virus 1 (AAV1) were used to knockdown the expression of Ntsr1, Thbs1 or ATF6 in rats and reversed the phenotype of PH. In summary, our results reveal that Ntsr1-JAK2-STAT3-Thbs1 pathway can induce enhanced ER stress via ATF6 activation and increased PASMC proliferation and migration capacities, which can be mechanism of the pulmonary artery remodeling and PH. Targeting Ntsr1 might be a novel therapeutic strategy to ameliorate PH.