Repetitive transcranial magnetic stimulation in Alzheimer's disease: effects on neural and synaptic rehabilitation.

Alzheimer's disease is a neurodegenerative disease resulting from deficits in synaptic transmission and homeostasis. The Alzheimer's disease brain tends to be hyperexcitable and hypersynchronized, thereby causing neurodegeneration and ultimately disrupting the operational abilities in daily life, leaving patients incapacitated. Repetitive transcranial magnetic stimulation is a cost-effective, neuro-modulatory technique used for multiple neurological conditions. Over the past two decades, it has been widely used to predict cognitive decline; identify pathophysiological markers; promote neuroplasticity; and assess brain excitability, plasticity, and connectivity. It has also been applied to patients with dementia, because it can yield facilitatory effects on cognition and promote brain recovery after a neurological insult. However, its therapeutic effectiveness at the molecular and synaptic levels has not been elucidated because of a limited number of studies. This study aimed to characterize the neurobiological changes following repetitive transcranial magnetic stimulation treatment, evaluate its effects on synaptic plasticity, and identify the associated mechanisms. This review essentially focuses on changes in the pathology, amyloidogenesis, and clearance pathways, given that amyloid deposition is a major hypothesis in the pathogenesis of Alzheimer's disease. Apoptotic mechanisms associated with repetitive transcranial magnetic stimulation procedures and different pathways mediating gene transcription, which are closely related to the neural regeneration process, are also highlighted. Finally, we discuss the outcomes of animal studies in which neuroplasticity is modulated and assessed at the structural and functional levels by using repetitive transcranial magnetic stimulation, with the aim to highlight future directions for better clinical translations.

Correlation between initial alkaline phosphatase levels and overall survival in newly diagnosed multiple myeloma patients.

Background: Alkaline phosphatase (ALP) reflects changes in the condition of multiple myeloma (MM) patients to some extent. However, the relationship of ALP in MM remains uncertain. Our study aimed to determine the association between initial ALP levels and overall survival in newly diagnosed MM patients. Methods: Clinical data from 202 newly diagnosed MM patients at Beijing Chaoyang Hospital between 2012 and 2016 were collected. Baseline characteristics, disease progression staging, serum markers, and patient survival data were recorded. The cut-off value for ALP was calculated based on patient survival data, and patients were divided into groups. Differences in patients' 3- and 5-year survival rates, liver function, bone disease and other indicators among different groups were compared. Independent risk factors influencing newly diagnosed MM patients were identified using COX regression analysis. Results: Patients were categorized into three groups based on ALP cut-off points: Group 1 (ALP <70 U/L), Group 2 (ALP 70 to <120 U/L), and Group 3 (ALP ≥120 U/L). Significant differences were observed in lactate dehydrogenase, serum calcium, white blood cell count, hemoglobin, and liver function indicators (including alanine aminotransferase, aspartate aminotransferase, albumin, and γ-glutamyl transferase) among different ALP groups (P<0.05). ALP levels varied significantly among patients with different bone disease grades (P<0.05). Median survival times for Groups 1, 2, and 3 were 25, 52, and 31 months, respectively. Group 2 exhibited significantly higher 3-year survival compared to the other two groups (P=0.006), while no significant difference was observed in 5-year survival among the three groups (P=0.51). Age, International Staging System staging, aspartate aminotransferase, ß2-microglobulin, ALP grading, and severe bone disease were identified as independent factors influencing survival in newly diagnosed patients (P<0.05). Conclusions: ALP levels are correlated with the prognosis of MM patients, and an ALP range of 70 to <120 U/L reflects a better survival expectation.

Case report: Dual-targeted BCMA and CS1 CAR-T-cell immunotherapy in recurrent and refractory extramedullary multiple myeloma.

Background: The development of CAR-T-cell immunotherapy has notably elevated the efficacy of treating multiple myeloma. Currently, a variety of targets, including BCMA, CS1, CD38, FcRH5, and GPRC5D, are being investigated. Despite these significant advancements, challenges such as antigen escape, limited persistence of CAR-T cells, and the intricate nature of the tumor microenvironment persist, leading to relapses following treatment. Case presentation: We report the case of a patient with recurrent and refractory multiple myeloma (RRMM) who developed a substantial extramedullary plasmacytoma in the muscles of the lower limb following multiple rounds of radiotherapy and chemotherapy. The patient underwent CAR-T-cell immunotherapy targeting BCMA and CS1; however, the tumor progressed despite treatment. Surgical resection of the extramedullary plasmacytoma was subsequently performed. Upon comparison of the tumor tissue with the adjacent tissue, increased expression of MYBL2 was noted in the tumor tissue, potentially contributing to the lack of improvement in extramedullary relapse after dual-targeted CAR-T cell therapy. Conclusions: In patients with recurrent and refractory multiple myeloma who underwent multiple cycles of chemotherapy and radiotherapy, dual-targeted CAR-T cell therapy aimed at BCMA and CS1 failed to effectively manage extramedullary relapse. Elevated expression of MYBL2 in multiple myeloma correlates with a poorer prognosis.

Construction of effective reproduction number of infectious disease individuals based on spatiotemporal discriminant search model: take hand-foot-mouth disease as an example.

OBJECTIVE: In order to facilitate the tracing of infectious diseases in a small area and to effectively carry out disease control and epidemiological investigations, this research proposes a novel spatiotemporal model to estimate effective reproduction number(Re)for infectious diseases, based on the fundamental concept of contact tracing. METHODS: This study utilizes the incidence of hand, foot, and mouth disease (HFMD) among children in Bishan District, Chongqing, China from 2015 to 2019. The study incorporates the epidemiological characteristics of HFMD and aims to construct a Spatiotemporal Correlation Discrimination of HFMD. Utilizing ARC ENGINE and C# programming for the creation of a spatio-temporal database dedicated to HFMD to facilitate data collection and analysis. The scientific validity of the proposed method was verified by comparing the effective reproduction number obtained by the traditional SEIR model. RESULTS: We have ascertained the optimal search radius for the spatiotemporal search model to be 1.5 km. Upon analyzing the resulting Re values, which range from 1.14 to 4.75, we observe a skewed distribution pattern from 2015 to 2019. The median and quartile Re value recorded is 2.42 (1.98, 2.72). Except for 2018, the similarity coefficient r of the years 2015, 2016, 2017, and 2019 were all close to 1, and p <0.05 in the comparison of the two models, indicating that the Re values obtained by using the search model and the traditional SEIR model are correlated and closely related. The results exhibited similarity between the Re curves of both models and the epidemiological characteristics of HFMD. Finally, we illustrated the regional distribution of Re values obtained by the search model at various time intervals on Geographic Information System (GIS) maps which highlighted variations in the incidence of diseases across different communities, neighborhoods, and even smaller areas. CONCLUSION: The model comprehensively considers both temporal variation and spatial heterogeneity in disease transmission and accounts for each individual's distinct time of onset and spatial location. This proposed method differs significantly from existing mathematical models used for estimating Re in that it is founded on reasonable scientific assumptions and computer algorithms programming that take into account real-world spatiotemporal factors. It is particularly well-suited for estimating the Re of infectious diseases in relatively stable mobile populations within small geographical areas.

The prognostic role of an optimal machine learning model based on clinical available indicators in HCC patients.

Although methods in diagnosis and therapy of hepatocellular carcinoma (HCC) have made significant progress in the past decades, the overall survival (OS) of liver cancer is still disappointing. Machine learning models have several advantages over traditional cox models in prognostic prediction. This study aimed at designing an optimal panel and constructing an optimal machine learning model in predicting prognosis for HCC. A total of 941 HCC patients with completed survival data and preoperative clinical chemistry and immunology indicators from two medical centers were included. The OCC panel was designed by univariate and multivariate cox regression analysis. Subsequently, cox model and machine-learning models were established and assessed for predicting OS and PFS in discovery cohort and internal validation cohort. The best OCC model was validated in the external validation cohort and analyzed in different subgroups. In discovery, internal and external validation cohort, C-indexes of our optimal OCC model were 0.871 (95% CI, 0.863-0.878), 0.692 (95% CI, 0.667-0.717) and 0.648 (95% CI, 0.630-0.667), respectively; the 2-year AUCs of OCC model were 0.939 (95% CI, 0.920-0.959), 0.738 (95% CI, 0.667-0.809) and 0.725 (95% CI, 0.643-0.808), respectively. For subgroup analysis of HCC patients with HBV, aged less than 65, cirrhosis or resection as first therapy, C-indexes of our optimal OCC model were 0.772 (95% CI, 0.752-0.792), 0.769 (95% CI, 0.750-0.789), 0.855 (95% CI, 0.846-0.864) and 0.760 (95% CI, 0.741-0.778), respectively. In general, the optimal OCC model based on RSF algorithm shows prognostic guidance value in HCC patients undergoing individualized treatment.

Deep learning enhancing guide RNA design for CRISPR/Cas12a-based diagnostics.

Rapid and accurate diagnostic tests are fundamental for improving patient outcomes and combating infectious diseases. The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) Cas12a-based detection system has emerged as a promising solution for on-site nucleic acid testing. Nonetheless, the effective design of CRISPR RNA (crRNA) for Cas12a-based detection remains challenging and time-consuming. In this study, we propose an enhanced crRNA design system with deep learning for Cas12a-mediated diagnostics, referred to as EasyDesign. This system employs an optimized convolutional neural network (CNN) prediction model, trained on a comprehensive data set comprising 11,496 experimentally validated Cas12a-based detection cases, encompassing a wide spectrum of prevalent pathogens, achieving Spearman's ρ = 0.812. We further assessed the model performance in crRNA design for four pathogens not included in the training data: Monkeypox Virus, Enterovirus 71, Coxsackievirus A16, and Listeria monocytogenes. The results demonstrated superior prediction performance compared to the traditional experiment screening. Furthermore, we have developed an interactive web server (https://crispr.zhejianglab.com/) that integrates EasyDesign with recombinase polymerase amplification (RPA) primer design, enhancing user accessibility. Through this web-based platform, we successfully designed optimal Cas12a crRNAs for six human papillomavirus (HPV) subtypes. Remarkably, all the top five predicted crRNAs for each HPV subtype exhibited robust fluorescent signals in CRISPR assays, thereby suggesting that the platform could effectively facilitate clinical sample testing. In conclusion, EasyDesign offers a rapid and reliable solution for crRNA design in Cas12a-based detection, which could serve as a valuable tool for clinical diagnostics and research applications.

The influencing factors of health status among low-income individuals living alone in Wuxi, China.

This study aimed to understand the health status of low-income individuals living alone and to identify influencing factors. Using systematic random sampling methods, low-income individuals living alone were randomly selected. Via telephone interviews, we gathered information about their general health status. A logistic regression model was used to analyze relevant factors about the physical health of this population. The study included 1583 low-income individuals living alone. The prevalence rate of all kinds of diseases in low-income living alone in this survey was 88.63%. The multifactorial logistic regression analysis revealed that the risk factors for illness in this population were age ≥ 60 (OR 1.842, 95% CI 1.135-2.926, P = 0.006), self-rated poor mental health (OR 2.538, 95% CI 1.128-3.828, P = 0.005), and self-rated poor hearing status (OR 2.781, 95% CI 1.586-3.647, P = 0.001). Being female (OR 0.469, 95% CI 0.178-0.821, P = 0.033) was identified as a protective factor. Low-income individuals living alone are a unique group who lack familial care and economic and social support, and are thus in a disadvantaged social position. Therefore, this population requires increased attention, especially regarding their physical health. Implementing targeted assistance policies to improve their health status and enhance their quality of life is essential.

Predicting Type 2 Diabetes Metabolic Phenotypes Using Continuous Glucose Monitoring and a Machine Learning Framework.

Type 2 diabetes (T2D) and prediabetes are classically defined by the level of fasting glucose or surrogates such as hemoglobin HbA1c. This classification does not take into account the heterogeneity in the pathophysiology of glucose dysregulation, the identification of which could inform targeted approaches to diabetes treatment and prevention and/or predict clinical outcomes. We performed gold-standard metabolic tests in a cohort of individuals with early glucose dysregulation and quantified four distinct metabolic subphenotypes known to contribute to glucose dysregulation and T2D: muscle insulin resistance, ß-cell dysfunction, impaired incretin action, and hepatic insulin resistance. We revealed substantial inter-individual heterogeneity, with 34% of individuals exhibiting dominance or co-dominance in muscle and/or liver IR, and 40% exhibiting dominance or co-dominance in ß-cell and/or incretin deficiency. Further, with a frequently-sampled oral glucose tolerance test (OGTT), we developed a novel machine learning framework to predict metabolic subphenotypes using features from the dynamic patterns of the glucose time-series ("shape of the glucose curve"). The glucose time-series features identified insulin resistance, ß-cell deficiency, and incretin defect with auROCs of 95%, 89%, and 88%, respectively. These figures are superior to currently-used estimates. The prediction of muscle insulin resistance and ß-cell deficiency were validated using an independent cohort. We then tested the ability of glucose curves generated by a continuous glucose monitor (CGM) worn during at-home OGTTs to predict insulin resistance and ß-cell deficiency, yielding auROC of 88% and 84%, respectively. We thus demonstrate that the prediabetic state is characterized by metabolic heterogeneity, which can be defined by the shape of the glucose curve during standardized OGTT, performed in a clinical research unit or at-home setting using CGM. The use of at-home CGM to identify muscle insulin resistance and ß-cell deficiency constitutes a practical and scalable method by which to risk stratify individuals with early glucose dysregulation and inform targeted treatment to prevent T2D.

Genome-wide identification and evolution of the SAP gene family in sunflower (Helianthus annuus L.) and expression analysis under salt and drought stress.

Stress-associated proteins (SAPs) are known to play an important role in plant responses to abiotic stresses. This study systematically identified members of the sunflower SAP gene family using sunflower genome data. The genes of the sunflower SAP gene family were analyzed using bioinformatic methods, and gene expression was assessed through fluorescence quantification (qRT-PCR) under salt and drought stress. A comprehensive analysis was also performed on the number, structure, collinearity, and phylogeny of seven Compositae species and eight other plant SAP gene families. The sunflower genome was found to have 27 SAP genes, distributed across 14 chromosomes. The evolutionary analysis revealed that the SAP family genes could be divided into three subgroups. Notably, the annuus variety exhibited amplification of the SAP gene for Group 3. Among the Compositae species, C. morifolium demonstrated the highest number of collinearity gene pairs and the closest distance on the phylogenetic tree, suggesting relative conservation in the evolutionary process. An analysis of gene structure revealed that Group 1 exhibited the most complex gene structure, while the majority of HaSAP genes in Group 2 and Group 3 lacked introns. The promoter analysis revealed the presence of cis-acting elements related to ABA, indicating their involvement in stress responses. The expression analysis indicated the potential involvement of 10 genes (HaSAP1, HaSAP3, HaSAP8, HaSAP10, HaSAP15, HaSAP16, HaSAP21, HaSAP22, HaSAP23, and HaSAP26) in sunflower salt tolerance. The expression of these 10 genes were then examined under salt and drought stress using qRT-PCR, and the tissue-specific expression patterns of these 10 genes were also analyzed. HaSAP1, HaSAP21, and HaSAP23 exhibited consistent expression patterns under both salt and drought stress, indicating these genes play a role in both salt tolerance and drought resistance in sunflower. The findings of this study highlight the significant contribution of the SAP gene family to salt tolerance and drought resistance in sunflower.

Identification of RBM15 as a prognostic biomarker in prostate cancer involving the regulation of prognostic m6A-related lncRNAs.

BACKGROUND: Long noncoding RNAs (lncRNAs) and N6-methyladenosine (m6A) modification of RNA play pivotal roles in tumorigenesis and cancer progression. However, knowledge regarding the expression patterns of m6A-related lncRNAs and their corresponding m6A regulators in prostate cancer (PCa) is limited. This study aimed to delineate the landscape of m6A-related lncRNAs, develop a predictive model, and identify the critical m6A regulators of prognostic lncRNAs in PCa. METHODS: Clinical and transcriptome data of PCa patients were downloaded from The Cancer Genome Atlas (TCGA) database. Prognostic m6A-related lncRNAs were subsequently identified through Pearson correlation and univariate Cox regression analyses. The prognostic lncRNAs were clustered into two groups by consensus clustering analysis, and a risk signature model was constructed using least absolute shrinkage and selection operator (LASSO) regression analysis of the lncRNAs. This model was evaluated using survival, clinicopathological, and immunological analyses. Furthermore, based on the constructed lncRNA-m6A regulatory network and RT-qPCR results, RBM15 was identified as a critical regulator of m6A-related lncRNAs. The biological roles of RBM15 in PCa were explored through bioinformatics analysis and biological experiments. RESULTS: Thirty-four prognostic m6A-related lncRNAs were identified and categorized into two clusters with different expression patterns and survival outcomes in PCa patients. Seven m6A lncRNAs (AC105345.1, AL354989.1, AC138028.4, AC022211.1, AC020558.2, AC004076.2, and LINC02666) were selected to construct a risk signature with robust predictive ability for overall survival and were correlated with clinicopathological characteristics and the immune microenvironment of PCa patients. Among them, LINC02666 and AC022211.1 were regulated by RBM15. In addition, RBM15 expression correlated with PCa progression, survival, and the immune response. Patients with elevated RBM15 expression were more susceptible to the drug AMG-232. Moreover, silencing RBM15 decreased the viability of PCa cells and promoted apoptosis. CONCLUSION: RBM15 is involved in the regulation of prognostic lncRNAs in the risk signature and has a robust predictive ability for PCa, making it a promising biomarker in PCa.

Broadening Horizons: Exploring the Cathepsin Family as Therapeutic Targets for Alzheimer's Disease.

Alzheimer's disease (AD) is an intricate neurodegenerative disorder characterized by the accumulation of misfolded proteins, including beta-amyloid (Aß) and tau, leading to cognitive decline. Despite decades of research, the precise mechanisms underlying its onset and progression remain elusive. Cathepsins are a family of lysosomal enzymes that play vital roles in cellular processes, including protein degradation and regulation of immune responses. Emerging evidence suggests that cathepsins may be involved in AD pathogenesis. Cathepsins can influence the activation of microglia and astrocytes, the resident immune cells in the brain. However, cathepsin dysfunction may lead to the accumulation of misfolded proteins, notably Aß and tau. In addition, dysregulated cathepsin activity may induce an exaggerated immune response, promoting chronic inflammation and neuronal dysfunction in patients with AD. By unraveling the classification, functions, and roles of cathepsins in AD's pathogenesis, this review sheds light on their intricate involvement in this devastating disease. Targeting cathepsin activity could be a promising and novel approach for mitigating the pathological processes that contribute to AD, providing new avenues for its treatment and prevention.

The clinical influence of complete remission with incomplete count recovery (CRi) on single-unit umbilical cord blood transplantation in patients with acute leukemia.

BACKGROUND: Recent evidence has indicated that measurable residual disease (MRD) markedly affects the prognosis of patients with acute leukemia post-transplantation. However, the prognostic relevance of complete remission with incomplete count recovery (CRi) before transplantation has not been extensively explored. METHODS: In this single-center, longitudinal study, we assessed the outcomes of 466 MRD-negative acute leukemia patients who underwent single-unit unrelated cord blood transplantation (sUCBT), including 117 patients with CRi. RESULTS: We observed that acute myeloid leukemia (AML) patients with CRi had a significantly lower cumulative incidence of both neutrophil (90.8% vs. 96.5%) and platelet engraftment (67.2% vs. 85.3%) and experienced increased transplant-related mortality (TRM) (100-day TRM: 14.2% vs. 5.3%; 1-year TRM: 20.6% vs. 11.3%; P = 0.024 and 0.063, respectively), mainly due to infection-related deaths, compared to those in complete remission (CR). Multivariate analysis revealed that CRi was an independent adverse predictor of both neutrophil and platelet engraftment and increased 100-day TRM in AML patients. However, CRi status did not affect relapse or reduce 5-year overall survival (OS), leukemia-free survival (LFS), or GVHD-free relapse-free survival (GRFS) in the AML cohort. Conversely, for patients with acute lymphoblastic leukemia (ALL), CRi did not impact engraftment, TRM, relapse or survival after sUCBT. CONCLUSIONS: Our findings underscore that CRi status before sUCBT portends poorer engraftment outcomes and a greater TRM in AML patients, although it does not significantly affect the prognosis of ALL patients.

A novel long noncoding RNA AK029592 contributes to thermogenic adipocyte differentiation.

Exploration of factors originating from brown adipose tissue that govern the thermogenic adipocyte differentiation is imperative for comprehending the regulatory framework underlying brown fat biogenesis and for devising therapeutic approaches for metabolic disorders associated with obesity. Prior evidence has illuminated the pivotal role of long noncoding RNAs (lncRNAs) in orchestrating thermogenesis within adipose tissue. Here, we aimed to explore and identify the critical lncRNA that could promote thermogenic adipocyte differentiation and to provide a novel strategy to treat obesity-related metabolic diseases in the future. In this study, through amalgamation with our previous lncRNA microarray data from small extracellular vesicles derived from BAT (sEV-BAT), we have identified sEV-BAT-enriched lncRNA AK029592 as a critical constituent of the thermogenic program, which actively fostered beige adipocyte differentiation and enhanced the thermogenic capacities of adipose tissue. Moreover, lncRNA AK029592 could sponge miR-199a-5p in adipocytes to stimulate thermogenic gene expression. Consequently, we concluded lncRNA AK029592 as a crucial lncRNA component of the thermogenic program that regulated beige adipocyte differentiation and white adipose tissue browning, thereby providing a novel therapeutic target and strategy in combating obesity and related metabolic diseases.

Pretreatment with Indole-3-Propionic Acid Attenuates Lipopolysaccharide-Induced Cardiac Dysfunction and Inflammation Through the AhR/NF-κB/NLRP3 Pathway.

Background: Patients with sepsis frequently develop septic cardiomyopathy, which is known to be closely related to excessive inflammatory responses. Indole-3-propionic acid (IPA) is a tryptophan metabolite with anti-inflammatory properties that have been demonstrated in various studies. In this study, we investigated the underlying mechanisms and therapeutic role of IPA in septic cardiomyopathy. Methods: To investigate the role of IPA in septic cardiomyopathy, we constructed a lipopolysaccharide (LPS)-induced rat model of septic cardiomyopathy, and treated rats with IPA. Inflammatory factors and the NF-κB/NLRP3 pathway were evaluated in myocardial tissues and cells after IPA treatment using RT-qPCR, ELISA, Western blotting, and immunohistochemistry. To further elucidate the role of the aryl hydrocarbon receptor (AhR), we detected changes in inflammatory mediators and the NF-κB/NLRP3 pathway in in vivo and in vitro models of septic cardiomyopathy, which were treated with the AhR antagonist CH-223191 and/or AhR agonist FICZ. Results: IPA supplementation improved cardiac dysfunction in rats with septic cardiomyopathy. IPA reduced inflammatory cytokine release and inhibited NF-κB/NLRP3 signaling pathway in myocardial tissue and in H9c2 cells. CH-223191 impaired the anti-inflammatory effect of IPA in LPS-treated cells, whereas FICZ exerted the same effect as IPA. IPA also exhibited anti-inflammatory activity by binding to the AhR. Our results indicated that IPA attenuated septic cardiomyopathy in rats via AhR/NF-κB/NLRP3 signaling. Conclusion: Our study revealed that IPA improved left heart dysfunction and myocardial inflammation caused by sepsis via AhR/NF-κB/NLRP3 signaling, suggesting that IPA is a potential therapy for septic cardiomyopathy.

Baicalin induces cell death of non-small cell lung cancer cells via MCOLN3-mediated lysosomal dysfunction and autophagy blockage.

BACKGROUND: Non-small cell lung cancer (NSCLC) accounts for 85 % of lung cancer, becoming the most mortality of all cancers globally. Blockage of autophagy in NSCLC represents a promising therapeutic strategy that inhibits angiogenesis and overcomes drug resistance. Natural ingredients in anti-tumor adjuvants are increasingly reported to promote cell death with less side effects and the potential to increase chemotherapeutic drugs sensitivity. Baicalin, a Scutellaria baicalensis-extracted flavonoid glycoside, is reported to induce death of NSCLC cells, however, its effects on autophagy in NSCLC cells remain unclear. PURPOSE: This study aimed to investigate the effect of baicalin on autophagic flux in NSCLC cells, unraveling the underlying mechanism including potential target and its role in cell death of NSCLC cells. METHODS: In vitro anti-cancer effects of baicalin were verified by evaluating proliferation, clone formation, cell cycle, and cell migration in three NSCLC cell lines (A549, H1299, and PC-9). In vivo anti-tumor efficacies of baicalin were evaluated in subcutaneous xenograft tumor model in nude mice. Autophagy characterization in NSCLC cells included autophagic marker detection by western blot and immunofluorescence staining, subcellular structure observation by TEM, lysosomal function by RNA-seq and fluorescence staining (LysoTracker®, LysoSensor®, and acridine orange). Based on RNA-seq and molecular biological verification using apoptotic, autophagic, and lysosomal inhibitors, potential target molecule of baicalin was verified via Ca2+ flux assay, MCOLN3 knockdown by shRNA, and virtual molecular docking. RESULTS: Baicalin inhibited NSCLC cell proliferation and migration, and suppressed tumor growth in vivo. Baicalin blocked the autophagic flux via activating the membranal cation channel MCOLN3 of lysosome, which disrupted its Ca2+ balance and induced lysosome dysfunction, leading to failure of autolysosome degradation. The cytoplasmic Ca2+ imbalance further resulted in depolarization of mitochondrial membrane potentials and ROS accumulation in NSCLC cells, mediating autophagy-related apoptosis. CONCLUSION: This study demonstrated that baicalin inhibited autolysosome degradation by activating MCOLN3, leading to dysfunction in lysosomal pH elevation, thereby inhibiting autophagy in NSCLC, leading to apoptotic death of NSCLC cells. These findings enriched the existing theories of cancer therapy based on autophagy inhibition and underlying mechanisms of flavonoids as antitumor agents, paving the way for their clinical application in future.

Fluoride induces hepatointestinal damage and vitamin B2 mitigation by regulating IL-17A and Bifidobacterium in ileum.

INTRODUCTION: Fluorosis is a global public health disease affecting more than 50 countries and 500 million people. Excessive fluoride damages the liver and intestines, yet the mechanisms and therapeutic approaches remain unclear. OBJECTIVES: To explore the mechanisms by which fluoride-induced intestinal-hepatic damage and vitamin B2 alleviation. METHODS: Fluoride and/or vitamin B2-treated IL-17A knockout and wild-type mouse models were established, the morphological and functional changes of liver and gut, total bile acid biosynthesis, metabolism, transport, and regulation of FXR-FGF15 signaling pathways were evaluated, the ileal microbiome was further analyzed by 16S rDNA sequence. Finally, Bifidobacterium supplementation mouse model was designed and re-examined the above indicators. RESULTS: The results demonstrated that fluoride induced hepatointestinal injury and enterohepatic circulation disorder by altering the synthesis, transporters, and FXR-FGF15 pathway regulation of total bile acid. Importantly, the ileum was found to be the most sensitive and fluoride changed ileal microbiome particularly by reducing abundance of Bifidobacterium. While vitamin B2 supplementation attenuated fluoride-induced enterohepatic circulation dysfunction through IL-17A and ileal microbiome, Bifidobacterium supplementation also reversed fluoride-induced hepatointestinal injury. CONCLUSION: Fluoride induces morphological and functional impairment of liver and gut tissues, as well as enterohepatic circulation disorder by altering total bile acid (TBA) synthesis, transporters, and FXR-FGF15 signaling regulation. Vitamin B2 attenuated fluoride-induced enterohepatic circulation disorder through IL-17A knockout and ileal microbiome regulation. The ileum was found to be the most sensitive to fluoride, leading to changes in ileal microbiome, particularly the reduction of Bifidobacterium. Furthermore, Bifidobacterium supplementation reversed fluoride-induced hepatointestinal injury. This study not only elucidates a novel mechanism by which fluoride causes hepatointestinal toxicity, but also provides a new physiological function of vitamin B2, which will be useful in the therapy of fluorosis and other hepatoenterological diseases.

High Ambipolar Mobility and Long-Range Carrier Transport in Violet Phosphorus Nanosheet.

Carrier transport capacity with high mobility and long-range diffusion length holds particular significance for the advancement of modern optoelectronic devices. Herein, we have unveiled the carrier dynamics and transport properties of a pristine violet phosphorus (VP) nanosheet by a transient absorption microscopy. Under the excitation (2.41 eV) above the exciton band, two photoinduced absorption peaks with the energy difference of approximately 520 meV emerge within a broadband transient absorption background which originates from the prompt generation of free carriers and the concomitant formation of excitons (lifetime of 467.21 ps). This observation is consistent with the established band-edge model of VP. Intriguingly, we have determined the ambipolar diffusion coefficient and mobility of VP to be approximately 47.32 cm2·s-1 and 1798 cm2·V-1·s-1, respectively, which further indicate a long-range carrier transport of approximately 2.10 µm. This work unveils the significant carrier transport capacity of VP, highlighting its potential for future optoelectronic and excitonic applications.

Inhibition of Macrophage Pyroptosis─A New Therapeutic Strategy to Alleviate T-2 Toxin-Induced Subacute Liver Injury by Directly Competing with the Key Target.

Multiple compounds are related to the development of liver injury, such as toxins, drugs, and environmental pollutants. Although there are reports that the T-2 toxin can cause liver injury, its toxic mechanism remains unclear, which further impedes the development of effective antidotes. In this study, CRISPR-Cas9 genome-wide screening technology was used to identify transformation-related protein 53 inducible nuclear protein 1 (trp53inp1) as a toxic target of the T-2 toxin. Mechanism studies have shown that the T-2 toxin induced pyroptosis of macrophages (J774A.1 cells) by activating the trp53inp1/NF-κB/NLRP3/GSDMD-N pathway, leading to a subacute liver injury. Also, the new drug berberine (BER) identified through virtual screening significantly alleviated the subacute liver injury by competitively binding trp53inp1 via His224; the effect was better than those of the positive control drugs N-acetylcysteine (NAC) and disulfiram (DSF). In summary, the above results indicate that trp53inp1 is a key target for T-2 toxin to induce subacute liver injury and that inhibiting macrophage pyroptosis is a new method for treating liver injury. In addition, this study provides a new method and strategy for the discovery of key disease targets and the search for effective drugs.

CMOS-compatible reconstructive spectrometers with self-referencing integrated Fabry-Perot resonators.

Miniaturized reconstructive spectrometers play a pivotal role in on-chip and portable devices, offering high-resolution spectral measurement through precalibrated spectral responses and AI-driven reconstruction. However, two key challenges persist for practical applications: artificial intervention in algorithm parameters and compatibility with complementary metal-oxide-semiconductor (CMOS) manufacturing. We present a cutting-edge miniaturized reconstructive spectrometer that incorporates a self-adaptive algorithm referenced with Fabry-Perot resonators, delivering precise spectral tests across the visible range. The spectrometers are fabricated with CMOS technology at the wafer scale, achieving a resolution of ~2.5 nm, an average wavelength deviation of ~0.27 nm, and a resolution-to-bandwidth ratio of ~0.46%. Our approach provides a path toward versatile and robust reconstructive miniaturized spectrometers and facilitates their commercialization.

[Role of reactive oxygen species/silent information regulator 1 in hyperoxia-induced bronchial epithelial cell injury]. / 活性氧簇/æ²‰é»˜ä¿¡æ¯è°ƒèŠ‚å› å­1在高氧致支气管上皮细胞损伤中的作用.

OBJECTIVES: To investigate the effect of reactive oxygen species (ROS)/silent information regulator 1 (SIRT1) on hyperoxia-induced mitochondrial injury in BEAS-2B cells. METHODS: The experiment was divided into three parts. In the first part, cells were divided into H0, H6, H12, H24, and H48 groups. In the second part, cells were divided into control group, H48 group, H48 hyperoxia+SIRT1 inhibitor group (H48+EX 527 group), and H48 hyperoxia+SIRT1 agonist group (H48+SRT1720 group). In the third part, cells were divided into control group, 48-hour hyperoxia+N-acetylcysteine group (H48+NAC group), and H48 group. The ROS kit was used to measure the level of ROS. Western blot and immunofluorescent staining were used to measure the expression levels of SIRT1 and mitochondria-related proteins. Transmission electron microscopy was used to observe the morphology of mitochondria. RESULTS: Compared with the H0 group, the H6, H12, H24, and H48 groups had a significantly increased fluorescence intensity of ROS (P<0.05), the H48 group had significant reductions in the expression levels of SIRT1 protein and mitochondria-related proteins (P<0.05), and the H24 and H48 groups had a significant reduction in the fluorescence intensity of mitochondria-related proteins (P<0.05). Compared with the H48 group, the H48+SRT1720 group had significant increases in the expression levels of mitochondria-related proteins and the mitochondrial aspect ratio (P<0.05), and the H48+EX 527 group had a significant reduction in the mitochondrial area (P<0.05). Compared with the H48 group, the H48+NAC group had a significantly decreased fluorescence intensity of ROS (P<0.05) and significantly increased levels of SIRT1 protein, mitochondria-related proteins, mitochondrial area, and mitochondrial aspect ratio (P<0.05). CONCLUSIONS: The ROS/SIRT1 axis is involved in hyperoxia-induced mitochondrial injury in BEAS-2B cells.