Disulfidptosis-Related LncRNA Signatures for Prognostic Prediction in Kidney Renal Clear Cell Carcinoma.

INTRODUCTION BACKGROUND: Disulfidptosis is a prevalent apoptotic mechanism, intrinsically linked to cancer prognosis. However, the specific involvement of disulfidptosis-related long non-coding RNA (DRLncRNAs) in Kidney renal clear cell carcinoma (KIRC) remains incompletely understood. This study aims to elucidate the potential prognostic significance of disulfidptosis-related LncRNAs in KIRC. MATERIALS AND METHODS: Expression profiles and clinical data of KIRC patients were retrieved from the TCGA database to discern differentially expressed DRLncRNAs correlated with overall survival. Cox univariate analysis, Lasso Regression, and Cox multivariate analysis were used to construct a clinical prediction model. RESULTS: Six signatures, namely FAM83C.AS1, AC136475.2, AC121338.2, AC026401.3, AC254562.3, and AC000050.2, were established to evaluate overall survival (OS) in the context of Kidney renal clear cell carcinoma (KIRC) in this study. Survival analysis and ROC curves demonstrated the strong predictive performance of the associated signature. The nomogram exhibited accurate prognostic predictions for overall patient survival, offering substantial clinical utility. Gene set enrichment analysis revealed that risk signals were enriched in various immune-related pathways. Furthermore, the risk features exhibited significant correlations with immune cells, immune function, immune cell infiltration, and immune checkpoints. CONCLUSION: This study has unveiled, for the first time, six disulfdptosis-related LncRNA signatures, laying a solid foundation for enhanced and precise prognostic predictions in KIRC.

Resistive Memristors Using Robust Electropolymerized Porous Organic Polymer Films as Switchable Materials.

Porous organic polymers (POPs) with inherent porosity, tunable pore environment, and semiconductive property are ideally suitable for application in various advanced semiconductor-related devices. However, owing to the lack of processability, POPs are usually prepared in powder forms, which limits their application in advanced devices. Herein, we demonstrate an example of information storage application of POPs with film form prepared by an electrochemical method. The growth process of the electropolymerized films in accordance with the Volmer-Weber model was proposed by observation of atomic force microscopy. Given the mechanism of the electron transfer system, we verified and mainly emphasized the importance of porosity and interfacial properties of porous polymer films for memristor. As expected, the as-fabricated memristors exhibit good performance on low turn-on voltage (0.65 ± 0.10 V), reliable data storage, and high on/off current ratio (104). This work offers inspiration for applying POPs in the form of electropolymerized films in various advanced semiconductor-related devices.

Exposure to nanopollutants (nZnO) enhances the negative effects of hypoxia and delays recovery of the mussels' immune system.

Aquatic environments face escalating challenges from multiple stressors like hypoxia and nanoparticle exposure, with impact of these combined stressors on mussel immunity being poorly understood. We investigated the individual and combined effects of short-term and long-term hypoxia and exposure to zinc oxide nanoparticles (nZnO) on immune system of the mussels (Mytilus edulis). Hemocyte functional traits (mortality, adhesion capacity, phagocytosis, lysosomal abundance, and oxidative burst), and transcript levels of immune-related genes involved in pathogen recognition (the Toll-like receptors, the complement system components, and the adaptor proteins MyD88) were assessed. Short-term hypoxia minimally affected hemocyte parameters, while prolonged exposure led to immunosuppression, impacting hemocyte abundance, viability, phagocytosis, and defensin gene expression. Under normoxia, nZnO stimulated immune responses of mussel hemocytes. However, combined nZnO and hypoxia induced more pronounced and rapid immunosuppression than hypoxia alone, indicating a synergistic interaction. nZnO exposure hindered immune parameter recovery during post-hypoxic reoxygenation, suggesting persistent impact. Opposing trends were observed in pathogen-sensing and pathogen-elimination mechanisms, with a positive correlation between pathogen-recognition system activation and hemocyte mortality. These findings underscore a complex relationship and potential conflict between pathogen-recognition ability, immune function, and cell survival in mussel hemocytes under hypoxia and nanopollutant stress, and emphasize the importance of considering multiple stressors in assessing the vulnerability and adaptability of mussel immune system under complex environmental conditions of anthropogenically modified coastal ecosystems.

Nasal mucosal fibroblasts produce IL-4 to induce Th2 response.

Th2 polarization is essential for the pathogenesis of allergic rhinitis (AR). Th2 polarization's mechanism requires further understanding. IL-4 is the primary cytokine involved in Th2 response. Fibroblasts play a role in immune regulation. This study aims to elucidate the role of nasal mucosal fibroblast-derived IL-4 in the induction of Th2 responses. Nasal mucosal tissues were obtained from surgically removed samples from patients with nasal polyps, whether with or without AR. Fibroblasts were isolated from the tissues by flow cytometry cell sorting, and analyzed by RNA sequencing (RNAseq). The data from RNAseq showed that nasal fibroblasts expressed genes of GATA3, CD80, CD83, CD86, STAT6, IL2, IL4, IL5, IL6, IL13 and costimulatory factor. The data were verified by RT-qPCR. The level of gene activity was positively correlated with those of AR-related cytokines present in nasal secretions. Nasal fibroblasts release IL-4 upon activation. Nasal fibroblasts had the ability to transform naive CD4+ T cells into Th2 cells, which can be eliminated by inhibiting IL-4 receptor or CD28 in CD4+ T cells. To sum up, nasal mucosal fibroblasts produce IL-4, which can induce Th2 cell development. The data implicate that nasal fibroblasts are involved in the pathogenesis of nasal allergy.

Impacts of active mobility on individual health mediated by physical activities.

Active mobility, encompassing walking and cycling for transportation, is a potential solution to health issues arising from inadequate physical activity in modern society. However, the extent of active mobility's impact on individual physical activity levels, and its association with health as mediated by physical activities, is not fully quantified. This study aims to clarify the direct relationship between active mobility usage and individual health, as well as the indirect relationship mediated by physical activity, with a focus on varying levels of physical activity intensity. Utilizing data from the 2017 U.S. National Household Travel Survey (NHTS), we employed Poisson regression to predict active mobility usage based on socio-demographic and household socio-economic characteristics. A Structural Equation Model (SEM) was then used to investigate the direct and indirect effects of active mobility on individual health, mediated by physical activity. We further segmented individuals according to their intensity of physical activity to examine how such effect differs between different levels of physical activity. The study demonstrates that active mobility usage positively correlates with both the amount and intensity of physical activity. The effect of active mobility on individual health includes a direct positive effect (29% for intensity, 67.7% for amount) and an indirect effect mediated by physical activity (71% for intensity, 32.3% for amount). Notably, the mediation effect of active mobility on health is more substantial in the context of vigorous physical activities compared to light or moderate activities. Our findings reveal a significant positive influence of active mobility on individual health, encompassing both direct and indirect effects mediated by physical activities. These results quantitatively underscore the health benefits of active mobility and suggest the importance of promoting active mobility as a strategy to improve public health.

Phytochemicals against Osteoarthritis by Inhibiting Apoptosis.

Osteoarthritis (OA) is a chronic joint disease that causes pathological changes in articular cartilage, synovial membrane, or subchondral bone. Conventional treatments for OA include surgical and non-surgical methods. Surgical treatment is suitable for patients in the terminal stage of OA. It is often the last choice because of the associated risks and high cost. Medication of OA mainly includes non-steroidal anti-inflammatory drugs, analgesics, hyaluronic acid, and cortico-steroid anti-inflammatory drugs. However, these drugs often have severe side effects and cannot meet the needs of patients. Therefore, safe and clinically appropriate long-term treatments for OA are urgently needed. Apoptosis is programmed cell death, which is a kind of physiologic cell suicide determined by heredity and conserved by evolution. Inhibition of apoptosis-related pathways has been found to prevent and treat a variety of diseases. Excessive apoptosis can destroy cartilage homeostasis and aggravate the pathological process of OA. Therefore, inhibition of apoptosis-related factors or signaling pathways has become an effective means to treat OA. Phytochemicals are active ingredients from plants, and it has been found that phytochemicals can play an important role in the prevention and treatment of OA by inhibiting apoptosis. We summarize preclinical and clinical studies of phytochemicals for the treatment of OA by inhibiting apoptosis. The results show that phytochemicals can treat OA by targeting apoptosis-related pathways. On the basis of improving some phytochemicals with low bioavailability, poor water solubility, and high toxicity by nanotechnology-based drug delivery systems, and at the same time undergoing strict clinical and pharmacological tests, phytochemicals can be used as a potential therapeutic drug for OA and may be applied in clinical settings.

Biocompatible Electronic Skins for Cardiovascular Health Monitoring.

Cardiovascular diseases represent a significant threat to the overall well-being of the global population. Continuous monitoring of vital signs related to cardiovascular health is essential for improving daily health management. Currently, there has been remarkable proliferation of technology focused on collecting data related to cardiovascular diseases through daily electronic skin monitoring. However, concerns have arisen regarding potential skin irritation and inflammation due to the necessity for prolonged wear of wearable devices. To ensure comfortable and uninterrupted cardiovascular health monitoring, the concept of biocompatible electronic skin has gained substantial attention. In this review, biocompatible electronic skins for cardiovascular health monitoring are comprehensively summarized and discussed. The recent achievements of biocompatible electronic skin in cardiovascular health monitoring are introduced. Their working principles, fabrication processes, and performances in sensing technologies, materials, and integration systems are highlighted, and comparisons are made with other electronic skins used for cardiovascular monitoring. In addition, the significance of integrating sensing systems and the updating wireless communication for the development of the smart medical field is explored. Finally, the opportunities and challenges for wearable electronic skin are also examined.

Carbon Dots Derived from Curcumae Radix and Their Heartprotective Effect.

Background: Acute myocardial infarction (AMI) is a common cardiovascular disease in clinic. Currently, there is no specific treatment for AMI. Carbon dots (CDs) have been reported to show excellent biological activities, which hold promise for the development of novel nanomedicines for the treatment of cardiovascular diseases. Methods: In this study, we firstly prepared CDs from the natural herb Curcumae Radix Carbonisata (CRC-CDs) by a green, simple calcination method. The aim of this study is to investigate the cardioprotective effect and mechanism of CRC-CDs on isoproterenol (ISO) -induced myocardial infarction (MI) in rats. Results: The results showed that pretreatment with CRC-CDs significantly reduced serum levels of cardiac enzymes (CK-MB, LDH, AST) and lipids (TC, TG, LDL) and reduced st-segment elevation and myocardial infarct size on the ECG in AMI rats. Importantly, cardiac ejection fraction (EF) and shortening fraction (FS) were markedly elevated, as was ATPase activity. In addition, CRC-CDs could significantly increase the levels of superoxide dismutase (SOD), reduced glutathione (GSH), catalase (CAT), and reduce the levels of malondialdehyde (MDA) and reactive oxygen species (ROS) in myocardial tissue, thereby exerting cardioprotective effect by enhancing the antioxidant capacity of myocardial tissue. Moreover, the TUNEL staining image showed that positive apoptotic cells were markedly declined after CRC-CDs treatment, which indicate that CRC-CDs could inhibit cardiomyocyte apoptosis. Importantly, The protective effect of CRC-CDs on H2O2 -pretreated H9c2 cells was also verified in vitro. Conclusion: Taken together, CRC-CDs has the potential for clinical application as an anti-myocardial ischemia drug candidate, which not only provides evidence for further broadening the biological application of cardiovascular diseases, but also offers potential hope for the application of nanomedicine to treat intractable diseases.

Ditch control and land reclamation promote vegetation recovery in Loess Plateau.

This study aimed to assess the impact of land consolidation projects and climate change on changes in vegetation in the Loess Plateau during 2012-2021. The study also explored the impacts of human activities and climate change on the ecological quality of the Loess Plateau during this period. The spatial and temporal normalized difference combined meteorological monitoring data, project data, and normalized difference vegetation index (NDVI) data that was used to create the vegetation index dataset spanning from 2012-2021. The study discussed and assessed the effectiveness of the project, revealing the following results: 1) A significant increase was observed in the vegetation index of the Loess Plateau region from 2012 to 2021, with an upward trend of 0.0024 per year (P < 0.05). 2) Contributions to changes in vegetation attributed to climatic factors and the anthropogenic factors of the ditch construction project were 82.74 and 17.62%, respectively, with climatic factors dominating and the degree of response of the ditch construction project increasing annually. 3) In the Loess Plateau, climatic variables dominated changes in vegetation. However, land consolidation projects in vegetation factors played a key role in changes in vegetation, and the degree of influence was gradually increasing.

Spatial transcriptomics reveals heterogeneity of histological subtypes between lepidic and acinar lung adenocarcinoma.

BACKGROUND: Patients who possess various histological subtypes of early-stage lung adenocarcinoma (LUAD) have considerably diverse prognoses. The simultaneous existence of several histological subtypes reduces the clinical accuracy of the diagnosis and prognosis of early-stage LUAD due to intratumour intricacy. METHODS: We included 11 postoperative LUAD patients pathologically confirmed to be stage IA. Single-cell RNA sequencing (scRNA-seq) was carried out on matched tumour and normal tissue. Three formalin-fixed and paraffin-embedded cases were randomly selected for 10× Genomics Visium analysis, one of which was analysed by digital spatial profiler (DSP). RESULTS: Using DSP and 10× Genomics Visium analysis, signature gene profiles for lepidic and acinar histological subtypes were acquired. The percentage of histological subtypes predicted for the patients from samples of 11 LUAD fresh tissues by scRNA-seq showed a degree of concordance with the clinicopathologic findings assessed by visual examination. DSP proteomics and 10× Genomics Visium transcriptomics analyses revealed that a negative correlation (Spearman correlation analysis: r = -.886; p = .033) between the expression levels of CD8 and the expression trend of programmed cell death 1(PD-L1) on tumour endothelial cells. The percentage of CD8+ T cells in the acinar region was lower than in the lepidic region. CONCLUSIONS: These findings illustrate that assessing patient histological subtypes at the single-cell level is feasible. Additionally, tumour endothelial cells that express PD-L1 in stage IA LUAD suppress immune-responsive CD8+ T cells.

Diagnostic strategy of metagenomic next-generation sequencing for gram negative bacteria in respiratory infections.

OBJECTIVE: This study aims to identify the most effective diagnostic method for distinguishing pathogenic and non-pathogenic Gram-negative bacteria (GNB) in suspected pneumonia cases using metagenomic next-generation sequencing (mNGS) on bronchoalveolar lavage fluid (BALF) samples. METHODS: The effectiveness of mNGS was assessed on BALF samples collected from 583 patients, and the results were compared with those from microbiological culture and final clinical diagnosis. Three interpretational approaches were evaluated for diagnostic accuracy. RESULTS: mNGS outperformed culture significantly. Among the interpretational approaches, Clinical Interpretation (CI) demonstrated the best diagnostic performance with a sensitivity of 87.3%, specificity of 100%, positive predictive value of 100%, and negative predictive value of 98.3%. CI's specificity was significantly higher than Simple Interpretation (SI) at 37.9%. Additionally, CI excluded some microorganisms identified as putative pathogens by SI, including Haemophilus parainfluenzae, Haemophilus parahaemolyticus, and Klebsiella aerogenes. CONCLUSION: Proper interpretation of mNGS data is crucial for accurately diagnosing respiratory infections caused by GNB. CI is recommended for this purpose.

Circadian rhythms of melatonin and its relationship with anhedonia in patients with mood disorders: a cross-sectional study.

BACKGROUND: Mood disorders are strongly associated with melatonin disturbances. However, it is unclear whether there is a difference in melatonin concentrations and melatonin circadian rhythm profiles between depression and bipolar disorder. In addition, the relationship between anhedonia, a common symptom of affective disorders, and its melatonin circadian rhythm remains under-investigated. METHODS: Thirty-four patients with depression disorder, 20 patients diagnosed with bipolar disorder and 21 healthy controls participated in this study. The Revised Physical Anhedonia Scale (RPAS) was performed to assess anhedonia. Saliva samples were collected from all subjects at fixed time points (a total of 14 points) in two consecutive days for measuring the melatonin concentrations to fit circadian rhythms of subjects. Melatonin circadian rhythms were compared between the three groups using ANOVA. Partial correlation analysis and linear regression analysis were used to explore the correlation between melatonin rhythm variables and anhedonia. RESULTS: We found that the peak phase of melatonin in the depression group was significantly advanced compared to the control group (P < 0.001) and the bipolar disorder group (P = 0.004). The peak phase of melatonin and RPAS showed a negative correlation (P = 0.003) in depression patients, which was also demonstrated in the multiple linear regression model (B=-2.47, P = 0.006). CONCLUSIONS: These results suggest that circadian rhythms of melatonin are differentiated in depression and bipolar disorder and correlate with anhedonia in depression. Future research needs to explore the neurobiological mechanisms linking anhedonia and melatonin circadian rhythms in depressed patients.

Dual-environment-sensitive probe to detect protein aggregation in stressed laryngeal carcinoma cells and tissues.

The interplay between protein folding and biological activity is crucial, with the integrity of the proteome being paramount to ensuring effective biological function execution. In this study, we report a dual-environment-sensitive probe A1, capable of selectively binding to protein aggregates and dynamically monitoring their formation and degradation. Through in vitro, cellular, and tissue assays, A1 demonstrated specificity in distinguishing aggregated from folded protein states, selectively partitioning into aggregated proteins. Thermal shift assays revealed A1 could monitor the process of protein aggregation upon binding to misfolded proteins and preceding to insoluble aggregate formation. In cellular models, A1 detected stress-induced proteome aggregation in TU212 cells (laryngeal carcinoma cells), revealing a less polar microenvironment within the aggregated proteome. Similarly, tissue samples showed more severe proteome aggregation in cancerous tissues compared to paracancerous tissues. Overall, A1 represents a versatile tool for probing protein aggregation with significant implications for both fundamental research and clinical diagnostics.

GSB: Group superposition binarization for vision transformer with limited training samples.

Vision Transformer (ViT) has performed remarkably in various computer vision tasks. Nonetheless, affected by the massive amount of parameters, ViT usually suffers from serious overfitting problems with a relatively limited number of training samples. In addition, ViT generally demands heavy computing resources, which limit its deployment on resource-constrained devices. As a type of model-compression method, model binarization is potentially a good choice to solve the above problems. Compared with the full-precision one, the model with the binarization method replaces complex tensor multiplication with simple bit-wise binary operations and represents full-precision model parameters and activations with only 1-bit ones, which potentially solves the problem of model size and computational complexity, respectively. In this paper, we investigate a binarized ViT model. Empirically, we observe that the existing binarization technology designed for Convolutional Neural Networks (CNN) cannot migrate well to a ViT's binarization task. We also find that the decline of the accuracy of the binary ViT model is mainly due to the information loss of the Attention module and the Value vector. Therefore, we propose a novel model binarization technique, called Group Superposition Binarization (GSB), to deal with these issues. Furthermore, in order to further improve the performance of the binarization model, we have investigated the gradient calculation procedure in the binarization process and derived more proper gradient calculation equations for GSB to reduce the influence of gradient mismatch. Then, the knowledge distillation technique is introduced to alleviate the performance degradation caused by model binarization. Analytically, model binarization can limit the parameter's search space during parameter updates while training a model. Therefore, the binarization process can actually play an implicit regularization role and help solve the problem of overfitting in the case of insufficient training data. Experiments on three datasets with limited numbers of training samples demonstrate that the proposed GSB model achieves state-of-the-art performance among the binary quantization schemes and exceeds its full-precision counterpart on some indicators. Code and models are available at: https://github.com/IMRL/GSB-Vision-Transformer.

DPP-4 exacerbates LPS-induced endothelial cells inflammation via integrin-α5ß1/FAK/AKT signaling.

Endothelial dysfunction plays a pivotal role in the pathogenesis of acute lung injury (ALI)/acute respiratory distress syndrome (ARDS). Dipeptidyl peptidase IV (DPP-4), a cell surface glycoprotein, has been implicated in endothelial inflammation and barrier dysfunction. In this study, the role of DPP-4 on lipopolysaccharide (LPS)-induced pulmonary microvascular endothelial cells (HPMECs) dysfunction and the underlying mechanism were investigated by siRNA-mediated knockdown of DPP-4. Our results indicated that LPS (1 µg/ml) challenge resulted in either the production and releasing of DPP-4, as well as the secretion of IL-6 and IL-8 in HPMECs. DPP-4 knockdown inhibited chemokine releasing and monolayer hyper-permeability in LPS challenged HPMECs. When cocultured with human polymorphonuclear neutrophils (PMNs), DPP4 knockdown suppressed LPS-induced neutrophil-endothelial adhesion, PMN chemotaxis and trans-endothelial migration. Western blotting showed that DPP-4 knockdown attenuated LPS-induced activation of TLR4/NF-κB pathway. Immunoprecipitation and liquid chromatography-tandem mass spectrometry revealed that DPP-4 mediated LPS-induced endothelial inflammation by interacting with integrin-α5ß1. Moreover, exogenous soluble DPP-4 treatment sufficiently activated integrin-α5ß1 downstream FAK/AKT/NF-κB signaling, thereafter inducing ICAM-1 upregulation in HPMECs. Collectively, our results suggest that endothelia synthesis and release DPP-4 under the stress of endotoxin, which interact with integrin-α5ß1 complex in an autocrine or paracrine manner to exacerbate endothelial inflammation and enhance endothelial cell permeability. Therefore, blocking DDP-4 could be a potential therapeutic strategy to prevent endothelial dysfunction in ALI/ARDS.

NLRP3 inflammasome mediates abnormal epithelial regeneration and distal lung remodeling in silica­induced lung fibrosis.

NOD-like receptor protein 3 (NLRP3) inflammasome is closely related to silica particle­induced chronic lung inflammation but its role in epithelial remodeling, repair and regeneration in the distal lung during development of silicosis remains to be elucidated. The present study aimed to determine the effects of the NLRP3 inflammasome on epithelial remodeling and cellular regeneration and potential mechanisms in the distal lung of silica­treated mice at three time points. Pulmonary function assessment, inflammatory cell counting, enzyme­linked immunosorbent assay, histological and immunological analyses, hydroxyproline assay and western blotting were used in the study. Single intratracheal instillation of a silica suspension caused sustained NLRP3 inflammasome activation in the distal lung. Moreover, a time­dependent increase in airway resistance and a decrease in lung compliance accompanied progression of pulmonary fibrosis. In the terminal bronchiole, lung remodeling including pyroptosis (membrane­distributed GSDMD+), excessive proliferation (Ki67+), mucus overproduction (mucin 5 subtype AC and B) and epithelial­mesenchymal transition (decreased E­Cadherin+ and increased Vimentin+), was observed by immunofluorescence analysis. Notably, aberrant spatiotemporal expression of the embryonic lung stem/progenitor cell markers SOX2 and SOX9 and ectopic distribution of bronchioalveolar stem cells were observed in the distal lung only on the 7th day after silica instillation (the early inflammatory phase of silicosis). Western blotting revealed that the Sonic hedgehog/Glioma­associated oncogene (Shh/Gli) and Wnt/ß­catenin pathways were involved in NLRP3 inflammasome activation­mediated epithelial remodeling and dysregulated regeneration during the inflammatory and fibrotic phases. Overall, sustained NLRP3 inflammasome activation led to epithelial remodeling in the distal lung of mice. Moreover, understanding the spatiotemporal profile of dysregulated epithelial repair and regeneration may provide a novel therapeutic strategy for inhalable particle­related chronic inflammatory and fibrotic lung disease.

Knowledge-guided machine learning can improve carbon cycle quantification in agroecosystems.

Accurate and cost-effective quantification of the carbon cycle for agroecosystems at decision-relevant scales is critical to mitigating climate change and ensuring sustainable food production. However, conventional process-based or data-driven modeling approaches alone have large prediction uncertainties due to the complex biogeochemical processes to model and the lack of observations to constrain many key state and flux variables. Here we propose a Knowledge-Guided Machine Learning (KGML) framework that addresses the above challenges by integrating knowledge embedded in a process-based model, high-resolution remote sensing observations, and machine learning (ML) techniques. Using the U.S. Corn Belt as a testbed, we demonstrate that KGML can outperform conventional process-based and black-box ML models in quantifying carbon cycle dynamics. Our high-resolution approach quantitatively reveals 86% more spatial detail of soil organic carbon changes than conventional coarse-resolution approaches. Moreover, we outline a protocol for improving KGML via various paths, which can be generalized to develop hybrid models to better predict complex earth system dynamics.

Protein tyrosine phosphatase PTPRO represses lung adenocarcinoma progression by inducing mitochondria-dependent apoptosis and restraining tumor metastasis.

Emerging evidence indicates that protein activities regulated by receptor protein tyrosine phosphatases (RPTPs) are crucial for a variety of cellular processes, such as proliferation, apoptosis, and immunological response. Protein tyrosine phosphatase receptor type O (PTPRO), an RPTP, has been revealed as a putative suppressor in the development of particular tumors. However, the function and the underlying mechanisms of PTPRO in regulating of lung adenocarcinoma (LUAD) are not well understood. In this view, the present work investigated the role of PTPRO in LUAD. Analysis of 90 pairs of clinical LUAD specimens revealed significantly lower PTPRO levels in LUAD compared with adjacent non-tumor tissue, as well as a negative correlation of PTPRO expression with tumor size and TNM stage. Survival analyses demonstrated that PTPRO level can help stratify the prognosis of LUAD patients. Furthermore, PTPRO overexpression was found to suppress the progression of LUAD both in vitro and in vivo by inducing cell death via mitochondria-dependent apoptosis, downregulating protein expression of molecules (Bcl-2, Bax, caspase 3, cleaved-caspase 3/9, cleaved-PARP and Bid) essential in cell survival. Additionally, PTPRO decreased LUAD migration and invasion by regulating proteins involved in the epithelial-to-mesenchymal transition (E-cadherin, N-cadherin, and Snail). Moreover, PTPRO was shown to restrain JAK2/STAT3 signaling pathways. Expression of PTPRO was negatively correlated with p-JAK2, p-STAT3, Bcl-2, and Snail levels in LUAD tumor samples. Furthermore, the anti-tumor effect of PTPRO in LUAD was significant but compromised in STAT3-deficient cells. These data support the remarkable suppressive role of PTPRO in LUAD, which may represent a viable therapeutic target for LUAD patients.

Oxidative phosphorylation rather than glycolysis is the primary energy source for sperm motility in the mussels Mytilus edulis.

Broadcast-spawning marine mussels rely on high sperm motility for successful fertilization in the dynamic seawater environment. Mitochondria are typically considered the primary source of ATP generation via oxidative phosphorylation (OXPHOS); however, the ATP generation pathways of mussel sperm have not been fully characterized. To better understand the importance of both OXPHOS and glycolysis for mussel sperm function, we conducted experiments inhibiting these pathways in sperm from Mytilus edulis. Our results indicate that oligomycin, an inhibitor of the mitochondrial ATP synthase, immediately decreased sperm motility rate, velocity, and ATP content, while 2-deoxy-d-glucose, a glycolysis inhibitor, had no effect. The OXPHOS inhibitor rotenone also partially reduced sperm motility rate and velocity. Interestingly, no evidence was found for the inhibitors' effects on the content of energy-rich compounds (lipids, carbohydrates, and proteins) in the mussels' sperm, indicating only modest energy demand to fuel sperm motility. Based on these findings, we conclude that OXPHOS is the primary energy source for sperm motility in marine mussels. Our study sheds light on the intricacies of mussel sperm physiology and highlights the importance of understanding the energy requirements for successful fertilization in broadcast-spawning marine invertebrates.