[Mechanism of tetramethylpyrazine attenuates inflammatory injury in endothelial cells by activating the SIRT1 signaling pathway]. / 川芎嗪通过激活SIRT1ä¿¡å·é€šè·¯å‡è½»å† çš®ç»†èƒžç‚Žç—‡æŸä¼¤çš„æœºåˆ¶ç ”ç©¶.

OBJECTIVES: To study the effects and mechanisms of tetramethylpyrazine (TMP) on tumor necrosis factor-α (TNF-α)-induced inflammatory injury in human coronary artery endothelial cells (HCAEC). METHODS: HCAEC were randomly divided into four groups: the control group (no treatment), the model group (treated with TNF-α, 50 ng/mL for 24 hours), the TMP group (pre-treated with TMP, 80 µg/mL for 12 hours followed by TNF-α treatment for 24 hours), and the SIRT1 inhibitor group (pre-treated with TMP and the specific SIRT1 inhibitor EX527 for 12 hours followed by TNF-α treatment for 24 hours). Cell viability was assessed using the CCK-8 method, lactate dehydrogenase (LDH) activity was measured using an LDH assay kit, reactive oxygen species (ROS) levels were observed using DCFH-DA staining, expression of pyroptosis-related proteins was detected by Western blot, and SIRT1 expression was analyzed using immunofluorescence staining. RESULTS: Compared to the control group, the model group showed decreased cell viability, increased LDH activity, ROS level and expression of pyroptosis-related proteins, and decreased SIRT1 expression (P<0.05). Compared to the model group, the TMP group exhibited increased cell viability, decreased LDH activity, ROS level and expression of pyroptosis-related proteins, and increased SIRT1 expression (P<0.05). In comparison to the TMP group, the SIRT1 inhibitor group showed decreased cell viability, increased LDH activity, ROS level and expression of pyroptosis-related proteins, and decreased SIRT1 expression (P<0.05). CONCLUSIONS: TMP may attenuate TNF-α-induced inflammatory injury in HCAEC, which is associated with the inhibition of pyroptosis and activation of the SIRT1 signaling pathway.

Therapeutic types and advantages of functionalized nanoparticles in inducing ferroptosis in cancer therapy.

BACKGROUND: The clinical efficacy of cancer treatment protocols remains unsatisfactory; however, the emergence of ferroptosis-driven therapy strategies has renewed hope for tumor treatment, owing to their remarkable tumor suppression effects. Biologically based small-molecule inducers are used in conventional method to induce ferroptosis. Nevertheless, some molecular drugs have limited solubility, poor ability to target cells, and fast metabolism, which hinder their ability to induce ferroptosis over a prolonged period. Fortunately, further investigations of ferroptosis and the development of nanotechnology have demonstrated that nanoparticles (NPs) are more efficient in inducing ferroptosis than drugs alone, which opens up new perspectives for cancer therapy. OBJECTIVE: In order to organize a profile of recent advance in NPs for inducing ferroptosis in cancer therapy, and NPs were comprehensively classified in a new light.Materials and methods: We comprehensively searched the databases such as PubMed and Embase. The time limit for searching was from the establishment of the database to 2023.11. All literatures were related to "ferroptosis", "nanoparticles", "nanodelivery systems", "tumors", "cancer". RESULTS: We summarized and classified the available NPs from a new perspective. The NPs were classified into six categories based on their properties: (1) iron oxide NPs (2) iron - based conversion NPs (3) core-shell structure (4) organic framework (5) silica NPs (6) lipoprotein NPs. According to the therapeutic types of NPs, they can be divided into categories: (1) NPs induced ferroptosis-related immunotherapy (2) NPs loaded with drugs (3) targeted therapy of NPs (4) multidrug resistance therapy (5) gene therapy with NPs (6) energy conversion therapy. CONCLUSIONS: The insights gained from this review can provide ideas for the development of original NPs and nanodelivery systems, pave the way for related nanomaterials application in clinical cancer therapy, and advance the application and development of nanotechnology in the medical field.

Lr34/Yr18/Sr57/Pm38 confers broad-spectrum resistance to fungal diseases via transport of sinapyl alcohol for cell wall lignification in wheat.

Widely known pleiotropic adult plant resistance (PAPR) gene, Lr34 encodes an ATP-binding cassette transporter and plays an important role in breeding wheat for enhancing resistance against multiple fungal diseases. Despite its recognized significance, the mechanism underlying Lr34 in pathogen defense remains largely elusive. Our study demonstrated that wheat lines harboring the Lr34res allele exhibit thicker cell walls and enhanced resistance to fungal penetration compared to lines lacking Lr34res. Transcriptome and metabolite profiling revealed that the lignin biosynthetic pathway was repressed in lr34 mutants, indicating a disruption in cell wall lignification. Furthermore, our investigation uncovered the hypersensitivity of lr34 mutant lines to sinapyl alcohol, a major monolignol crucial for cell wall lignification. Yeast accumulation and efflux assays confirmed that Lr34 protein functions as a sinapyl alcohol transporter. Both genetic and virus-induced gene silencing (VIGS) experiments revealed that the disease resistance conferred by Lr34 could be enhanced with the addition of the TaCOMT-3B gene, which is responsible for biosynthesis of sinapyl alcohol. Collectively, our findings provide novel insights into the role of Lr34 in disease resistance, through mediating sinapyl alcohol transport and cell wall deposition. Moreover, TaCOMT-3B plays a synergistic role in the Lr34 facilitated defensive lignification in adult wheat plants against multiple fungal pathogens.

Hyperglycemia induced cathepsin L maturation linked to diabetic comorbidities and COVID-19 mortality.

Diabetes, a prevalent chronic condition, significantly increases the risk of mortality from COVID-19, yet the underlying mechanisms remain elusive. Emerging evidence implicates Cathepsin L (CTSL) in diabetic complications, including nephropathy and retinopathy. Our previous research identified CTSL as a pivotal protease promoting SARS-CoV-2 infection. Here, we demonstrate elevated blood CTSL levels in individuals with diabetes, facilitating SARS-CoV-2 infection. Chronic hyperglycemia correlates positively with CTSL concentration and activity in diabetic patients, while acute hyperglycemia augments CTSL activity in healthy individuals. In vitro studies reveal high glucose, but not insulin, promotes SARS-CoV-2 infection in wild-type cells, with CTSL knockout cells displaying reduced susceptibility. Utilizing lung tissue samples from diabetic and non-diabetic patients, alongside Leprdb/dbmice and Leprdb/+mice, we illustrate increased CTSL activity in both humans and mice under diabetic conditions. Mechanistically, high glucose levels promote CTSL maturation and translocation from the endoplasmic reticulum (ER) to the lysosome via the ER-Golgi-lysosome axis. Our findings underscore the pivotal role of hyperglycemia-induced CTSL maturation in diabetic comorbidities and complications.

People with diabetes are at greater risk of developing severe COVID-19 and dying from the illness, which is caused by a virus known as SARS-CoV-2. The high blood sugar levels associated with diabetes appear to be a contributing factor to this heightened risk. However, diabetes is a complex condition encompassing a range of metabolic disorders, and it is therefore likely that other factors may contribute. Previous research identified a link between an enzyme called cathepsin L and more severe COVID-19 in people with diabetes. Elevated cathepsin L levels are known to contribute to diabetes complications, such as kidney damage and vision loss. It has also been shown that cathepsin L helps SARS-CoV-2 to enter and infect cells. This raised the question of whether elevated cathepsin L is responsible for the increased COVID-19 vulnerability in patients with diabetes. To investigate, He, Zhao et al. monitored disease severity and cathepsin L levels in patients with COVID-19. This confirmed that people with diabetes had more severe COVID-19 and that higher levels of cathepsin L are linked to more severe disease. Analysis also revealed that cathepsin L activity increases as blood glucose levels increase. In laboratory experiments, cells exposed to glucose or fluid from the blood of people with diabetes were more easily infected with SARS-CoV-2, with cells genetically modified to lack cathepsin L being more resistant to infection. Further experiments revealed this was due to glucose promoting maturation and migration of cathepsin L in the cells. The findings of He, Zhao et al. help to explain why people with diabetes are more likely to develop severe or fatal COVID-19. Therefore, controlling blood glucose levels in people with diabetes may help to prevent or reduce the severity of the disease. Additionally, therapies targeting cathepsin L could also potentially help to treat COVID-19, especially in patients with diabetes, although more research is needed to develop and test these treatments.

Radiomics Models Derived From Arterial-Phase-Enhanced CT Reliably Predict Both PD-L1 Expression and Immunotherapy Prognosis in Non-small Cell Lung Cancer: A Retrospective, Multicenter Cohort Study.

RATIONALE AND OBJECTIVES: Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of non-small cell lung cancer (NSCLC) and programmed cell death-ligand 1 (PD-L1) is a companion biomarker. This study aims to use baseline arterial-phase enhanced CT (APECT) to construct efficient radiomic models for predicting PD-L1 expression and immunotherapy prognosis in NSCLC. MATERIALS AND METHODS: We extracted radiomics features from the baseline APECT images of 204 patients enrolled in a published multicenter clinical trial that commenced on August 23, 2018, and concluded on November 15, 2019 (ClinicalTrials.gov: NCT03607539). Of these patients, 146 patients from selected centers were assigned to the training cohort. The least absolute shrinkage and selection operator (LASSO) method was used to reduce dimensionality of radiomics features and calculate tumor scores. Models were created using naive bayes, decision trees, XGBoost, and random forest algorithms according to tumor scores. These models were then validated in an independent validation cohort comprising 58 patients from the remaining centers. RESULTS: The random forest algorithm outperformed the other methods. In the three-classification scenario, the random forest model achieving the area under the curve (AUC) values of 0.98 and 0.94 in the training and validation cohorts, respectively. In the two-classification scenario, the random forest model achieved AUCs of 0.99 (95%CI: 0.97-1.0, P < 0.0001) and 0.93 (95%CI: 0.83-0.98, P < 0.0001) in the training and validation cohorts, respectively. Furthermore, patients classified as PD-L1 high-expression by this model can predict treatment response (AUC=0.859, 95%CI: 0.7-0.96, P < 0.001) and improved survival (HR=0.2, 95%CI: 0.08-0.53, P = 0.001) only in validation sintilimab arm. CONCLUSION: Radiomics models based on APECT represent a potential non-invasive approach to robustly predict PD-L1 expression and ICI treatment outcomes in patients with NSCLC, which could significantly improve precision cancer immunotherapy.

Repetitive transcranial magnetic stimulation combined with imaginal exposure therapy for adolescents with acute stress disorder: case report.

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N6-methyladenosine modification and post-translational modification of epithelial-mesenchymal transition in colorectal cancer.

Colorectal cancer is a leading cause of cancer-related mortality worldwide. Traditionally, colorectal cancer has been recognized as a disease caused by genetic mutations. However, recent studies have revealed the significant role of epigenetic alterations in the progression of colorectal cancer. Epithelial-mesenchymal transition, a critical step in cancer cell metastasis, has been found to be closely associated with the tumor microenvironment and immune factors, thereby playing a crucial role in many kinds of biological behaviors of cancers. In this review, we explored the impact of N6-methyladenosine and post-translational modifications (like methylation, acetylation, ubiquitination, SUMOylation, glycosylation, etc.) on the process of epithelial-mesenchymal transition in colorectal cancer and the epigenetic regulation for the transcription factors and pathways correlated to epithelial-mesenchymal transition. Furthermore, we emphasized that the complex regulation of epithelial-mesenchymal transition by epigenetics can provide new strategies for overcoming drug resistance and improving treatment outcomes. This review aims to provide important scientific evidence for the prevention and treatment of colorectal cancer based on epigenetic modifications.

Graph convolutional network with attention mechanism improve major depressive depression diagnosis based on plasma biomarkers and neuroimaging data.

BACKGROUND: The absence of clinically-validated biomarkers or objective protocols hinders effective major depressive disorder (MDD) diagnosis. Compared to healthy control (HC), MDD exhibits anomalies in plasma protein levels and neuroimaging presentations. Despite extensive machine learning studies in psychiatric diagnosis, a reliable tool integrating multi-modality data is still lacking. METHODS: In this study, blood samples from 100 MDD and 100 HC were analyzed, along with MRI images from 46 MDD and 49 HC. Here, we devised a novel algorithm, integrating graph neural networks and attention modules, for MDD diagnosis based on inflammatory cytokines, neurotrophic factors, and Orexin A levels in the blood samples. Model performance was assessed via accuracy and F1 value in 3-fold cross-validation, comparing with 9 traditional algorithms. We then applied our algorithm to a dataset containing both the aforementioned protein quantifications and neuroimages, evaluating if integrating neuroimages into the model improves performance. RESULTS: Compared to HC, MDD showed significant alterations in plasma protein levels and gray matter volume revealed by MRI. Our new algorithm exhibited superior performance, achieving an F1 value and accuracy of 0.9436 and 94.08 %, respectively. Integration of neuroimaging data enhanced our novel algorithm's performance, resulting in an improved F1 value and accuracy, reaching 0.9543 and 95.06 %. LIMITATIONS: This single-center study with a small sample size requires future evaluations on a larger test set for improved reliability. CONCLUSIONS: In comparison to traditional machine learning models, our newly developed MDD diagnostic model exhibited superior performance and showed promising potential for inclusion in routine clinical diagnosis for MDD.

The relationship between family functioning and social media addiction among university students: a moderated mediation model of depressive symptoms and peer support.

BACKGROUND: Social media addiction (SMA) is an increasing problem, especially among young adults. Little is known about university students' SMA and family functioning. This study aimed to explore the mediating effect of depressive symptoms and the moderating effect of peer support in the relationship between family functioning and SMA among young adults. METHODS: A sample of 1862 Chinese university students completed an online survey including the Bergen Social Media Addiction Scale (BSMAS), Family APGAR, the Patient Health Questionnaire (PHQ-9), peer support, and demographic characteristics. Hierarchical regression and moderated mediation analysis were used to test the effects and pathways among them. RESULTS: Of the 1840 participants, 30.11% experienced SMA, 38.80% had family dysfunction and 15.98% had depressive symptoms. Hierarchical multiple regression showed better family functioning significantly predicted less SMA (ß = -0.26, p < 0.001) and lower depressive symptoms (ß = -0.58, p < 0.001), after adjusting for covariates. Mediation analysis verified that depressive symptoms mediated the effect of family functioning on SMA (indirect effect = -0.22, 95%CI[-0.28, -0.17]). Furthermore, the interaction of family functioning and peer support was negatively related to depressive symptoms (ß= -0.03, 95% CI[-0.05, -0.01]) and the interaction of depressive symptoms and peer support was positively related to SMA (ß = 0.01, 95%CI[0.004, 0.02]). Additional analysis further confirmed that peer support decreased depressive symptoms among young adults from dysfunctional families, and increased SMA behaviors in individuals with depressive symptoms. CONCLUSION: Better family functioning and lower depressive symptoms may contribute to less social media addiction among Chinese university students. Peer support could moderate the mediating role of depressive symptoms on social media addiction in individuals with family dysfunction.

Feasibility of ultrasound radiomics based models for classification of liver fibrosis due to Schistosoma japonicum infection.

BACKGROUND: Schistosomiasis japonica represents a significant public health concern in South Asia. There is an urgent need to optimize existing schistosomiasis diagnostic techniques. This study aims to develop models for the different stages of liver fibrosis caused by Schistosoma infection utilizing ultrasound radiomics and machine learning techniques. METHODS: From 2018 to 2022, we retrospectively collected data on 1,531 patients and 5,671 B-mode ultrasound images from the Second People's Hospital of Duchang City, Jiangxi Province, China. The datasets were screened based on inclusion and exclusion criteria suitable for radiomics models. Liver fibrosis due to Schistosoma infection (LFSI) was categorized into four stages: grade 0, grade 1, grade 2, and grade 3. The data were divided into six binary classification problems, such as group 1 (grade 0 vs. grade 1) and group 2 (grade 0 vs. grade 2). Key radiomic features were extracted using Pyradiomics, the Mann-Whitney U test, and the Least Absolute Shrinkage and Selection Operator (LASSO). Machine learning models were constructed using Support Vector Machine (SVM), and the contribution of different features in the model was described by applying Shapley Additive Explanations (SHAP). RESULTS: This study ultimately included 1,388 patients and their corresponding images. A total of 851 radiomics features were extracted for each binary classification problems. Following feature selection, 18 to 76 features were retained from each groups. The area under the receiver operating characteristic curve (AUC) for the validation cohorts was 0.834 (95% CI: 0.779-0.885) for the LFSI grade 0 vs. LFSI grade 1, 0.771 (95% CI: 0.713-0.835) for LFSI grade 1 vs. LFSI grade 2, and 0.830 (95% CI: 0.762-0.885) for LFSI grade 2 vs. LFSI grade 3. CONCLUSION: Machine learning models based on ultrasound radiomics are feasible for classifying different stages of liver fibrosis caused by Schistosoma infection.

Microbial dysbiosis in systemic lupus erythematosus: a scientometric study.

Introduction: Systemic lupus erythematosus (SLE) is a chronic autoimmune disease. Mounting evidence suggests microbiota dysbiosis augment autoimmune response. This study aims to provide a systematic overview of this research field in SLE through a bibliometric analysis. Methods: We conducted a comprehensive search and retrieval of literature related to microbial researches in SLE from the Web of Science Core Collection (WOSCC) database. The retrieved articles were subjected to bibliometric analysis using VOSviewer and Bibliometricx to explore annual publication output, collaborative patterns, research hotspots, current research status, and emerging trends. Results: In this study, we conducted a comprehensive analysis of 218 research articles and 118 review articles. The quantity of publications rises annually, notably surging in 2015 and 2018. The United States and China emerged as the leading contributors in microbial research of SLE. Mashhad University of Medical Sciences had the highest publication outputs among the institutions. Frontiers in Immunology published the most papers. Luo XM and Margolles A were the most prolific and highly cited contributors among individual authors. Microbial research in SLE primarily focused on changes in microbial composition, particularly gut microbiota, as well as the mechanisms and practical applications in SLE. Recent trends emphasize "metabolites," "metabolomics," "fatty acids," "T cells," "lactobacillus," and "dietary supplementation," indicating a growing emphasis on microbial metabolism and interventions in SLE. Conclusion: This study provides a thorough analysis of the research landscape concerning microbiota in SLE. The microbial research in SLE mainly focused on three aspects: microbial dysbiosis, mechanism studies and translational studies (microbiota-based therapeutics). It identifies current research trends and focal points, offering valuable guidance for scholars in the field.

Goos-Hänchen shift in cryogenic defect photonic crystals composed of superconductor HgBa2Ca2Cu3O8+δ.

We explore theoretically Goos-Hänchen (GH) shift around the defect mode in superconducting defective photonic crystals (PCs) in cryogenic environment. The defective PCs are constructed by alternating semiconductors and superconductors. A defect mode arises in the photonic bandgap and sensitively depends on environment temperature and hydrostatic pressure. Reflection and transmission coefficient phases make an abruptly jump at the defect mode and giant GH shifts have been achieved around this mode. The maximum GH shift can get as high as 103λ (incident wavelength), which could be modulated by the values of temperature and hydrostatic pressure. This study may be utilized for pressure- or temperature-sensors in cryogenic environment.

Innovative Diagnosis and Therapeutic Modalities: Engineered Exosomes in Autoimmune Disease.

Autoimmune diseases refer to a group of conditions where the immune system produces an immune response against self-antigens, resulting in tissue damage. These diseases have profound impacts on the health of patients. In recent years, with the rapid development in the field of biomedicine, engineered exosomes have emerged as a noteworthy class of biogenic nanoparticles. By precisely manipulating the cargo and surface markers of exosomes, engineered exosomes have gained enhanced anti-inflammatory, immunomodulatory, and tissue reparative abilities, providing new prospects for the treatment of autoimmune diseases. Engineered exosomes not only facilitate the efficient delivery of bioactive molecules including nucleic acids, proteins, and cytokines, but also possess the capability to modulate immune cell functions, suppress inflammation, and restore immune homeostasis. This review mainly focuses on the applications of engineered exosomes in several typical autoimmune diseases. Additionally, this article comprehensively summarizes the current approaches for modification and engineering of exosomes and outlines their prospects in clinical applications. In conclusion, engineered exosomes, as an innovative therapeutic approach, hold promise for the management of autoimmune diseases. However, while significant progress has been made, further rigorous research is still needed to address the challenges that engineered exosomes may encounter in the therapeutic intervention process, in order to facilitate their successful translation into clinical practice and ultimately benefit a broader population of patients.

Assessment and Comparison of Early Developmental Toxicity of Six Per- and Polyfluoroalkyl Substances with Human Embryonic Stem Cell Models.

Per- and polyfluoroalkyl substances (PFAS) are extensively utilized in varieties of products and tend to accumulate in the human body including umbilical cord blood and embryos/fetuses. In this study, we conducted an assessment and comparison of the potential early developmental toxicity of perfluorooctanoic acid (PFOA), undecafluorohexanoic acid (PFHxA), heptafluorobutyric acid, perfluorooctanesulfonate (PFOS), perfluorohexanesulfonate, and perfluorobutyric acid at noncytotoxic concentrations relevant to human exposure using models based on human embryonic stem cells in both three-dimensional embryoid body (EB) and monolayer differentiation configurations. All six compounds influenced the determination of cell fate by disrupting the expression of associated markers in both models and, in some instances, even led to alterations in the formation of cystic EBs. The expression of cilia-related gene IFT122 was significantly inhibited. Additionally, PFOS and PFOA inhibited ciliogenesis, while PFOA specifically reduced the cilia length. Transcriptome analysis revealed that PFOS altered 1054 genes and disrupted crucial signaling pathways such as WNT and TGF-ß, which play integral roles in cilia transduction and are critical for early embryonic development. These results provide precise and comprehensive insights into the potential adverse health effects of these six PFAS compounds directly concerning early human embryonic development.

Social media addiction and academic engagement as serial mediators between social anxiety and academic performance among college students.

BACKGROUND: Social anxiety has been shown to affect college students' academic performance. However, the role of social media addiction and academic engagement in this association is unclear. METHODS: A total 2661 college students completed a self-report questionnaire including Liebowitz Social Anxiety Scale, the Bergen Social Media Addiction Scale, the Utrecht Student Work Engagement Scale for Students, and the grade point average. Hayes' PROCESS macro for SPSS was employed to test the serial mediation effect. RESULTS: Results indicated that social anxiety was negatively related to academic performance, only academic engagement played a single mediating role in the relationship between social anxiety and academic performance, meanwhile social media addiction and academic engagement acted as serial mediators between social anxiety on academic performance. CONCLUSIONS: Social media addiction and academic engagement can explain the potential mechanisms of the association between social anxiety and academic performance, which have implications for devising intervention strategies to enhance the mental health and academic outcomes of college students.

The mutation of NSUN5 R295C promotes preeclampsia by impairing decidualization through downregulating IL-11Rα.

Preeclampsia (PE) is a pregnancy-specific hypertensive disorder that severely impairs maternal and fetal health. However, its pathogenesis remains elusive. NOP2/Sun5 (NSUN5) is an RNA methyltransferase. This study discovered a significant correlation between rs77133388 of NSUN5 and PE in a cohort of 868 severe PE patients and 982 healthy controls. To further explore this association, the researchers generated single-base mutant mice (NSUN5 R295C) at rs77133388. The pregnant NSUN5 R295C mice exhibited PE symptoms. Additionally, compared to the controls, the decidual area of the placenta was significantly reduced in NSUN5 R295C mice, and their decidualization was impaired with a significantly decrease in polyploid cell numbers after artificially induced decidualization. The study also found a decrease in phosphorylated JAK2, STAT3, and IL-11Rα, Cyclin D3 expression in NSUN5 R295C mice. Overall, these findings suggest that NSUN5 mutation potentially alters decidualization through the IL-11Rα/JAK2/STAT3/Cyclin D3 pathway, ultimately impairing placental development and contributing to PE occurrence.

Transcriptomics analysis of LINC02202/XBP1 axis in melanoma: Implications for drug targeting and PD-1 monoclonal antibody efficacy.

Malignant melanoma (MM) is a highly aggressive and deadly form of skin cancer, primarily caused by recurrence and metastasis. Therefore, it is crucial to investigate the regulatory mechanisms underlying melanoma recurrence and metastasis. Our study has identified a potential targeted regulatory relationship between LINC02202, miR-526b-3p and XBP1 in malignant melanoma. Through the regulation of the miR-526b-3p/XBP1 signalling pathway, LINC02202 may play a role in tumour progression and immune infiltration and inhibiting the expression of LINC02202 can increase the efficacy of immunotherapy for melanoma. Our findings shed light on the impact of LINC02202/XBP1 on the phenotype and function of malignant melanoma cells. Furthermore, this study provides a theoretical foundation for the development of novel immunotherapy strategies for malignant melanoma.