BACKGROUND:Studies have shown that ischemia-induced cellular autophagy dysfunction is a key factor in brain injury.Autophagy related genes 6(ATG6),microtubule-associated protein 1 light chain(LC3),p62,and other autophagy key proteins are involved in the processes such as neuronal axonal degeneration,death,and intracellular homeostasis maintenance,playing an important role in the recovery of neural function. OBJECTIVE:To review the research progress in the role of cellular autophagy in cerebral ischemic injury and the regulatory mechanism of traditional Chinese medicine. METHODS:The first author used"ischemic stroke,brain tissue injury,cellular autophagy,signaling pathways,traditional Chinese medicine compounds,terpenoids,alkaloids,flavonoids,saponins,lignans,phthalates"as Chinese and English keywords respectively to search for literature on autophagy,cerebral ischemic injury,and the regulatory mechanisms of traditional Chinese medicine from China National Knowledge Infrastructure(CNKI)and PubMed databases from January 2016 to February 2024.Literature that is not highly relevant,repetitive,or outdated was excluded.A total of 1 746 relevant literature were retrieved,and 92 articles were ultimately included. RESULTS AND CONCLUSION:Numerous studies have confirmed that autophagy plays an important role in cerebral ischemic injury.Moderate autophagy can promote cell survival,while excessive autophagy exacerbates brain injury.Traditional Chinese medicine can regulate the expression of autophagy related proteins,inhibit neuronal necrosis and apoptosis,and exert neuroprotective effects at different stages of cerebral ischemia by regulating signaling pathways such as PI3K/Akt/mTOR,AMPK-mTOR,and mitogen activated protein kinase.

Ferroptosis, a programmed cell death modality discovered and defined in the last decade, is primarily induced by iron-dependent lipid peroxidation. At present, it has been found that ferroptosis is involved in various physiological functions such as immune regulation, growth and development, aging, and tumor suppression. Especially its role in tumor biology has attracted extensive attention and research. Breast cancer is one of the most common female tumors, characterized by high heterogeneity and complex genetic background. Triple negative breast cancer (TNBC) is a special type of breast cancer, which lacks conventional breast cancer treatment targets and is prone to drug resistance to existing chemotherapy drugs and has a low cure rate after progression and metastasis. There is an urgent need to find new targets or develop new drugs. With the increase of studies on promoting ferroptosis in breast cancer, it has gradually attracted attention as a treatment strategy for breast cancer. Some studies have found that certain compounds and natural products can act on TNBC, promote their ferroptosis, inhibit cancer cells proliferation, enhance sensitivity to radiotherapy, and improve resistance to chemotherapy drugs. To promote the study of ferroptosis in TNBC, this article summarized and reviewed the compounds and natural products that induce ferroptosis in TNBC and their mechanisms of action. We started with the exploration of the pathways of ferroptosis, with particular attention to the System X_c^--cystine-GPX4 pathway and iron metabolism. Then, a series of compounds, including sulfasalazine (SAS), metformin, and statins, were described in terms of how they interact with cells to deplete glutathione (GSH), thereby inhibiting the activity of glutathione peroxidase 4 (GPX4) and preventing the production of lipid peroxidases. The disruption of the cellular defense against oxidative stress ultimately results in the death of TNBC cells. We have also our focus to the realm of natural products, exploring the therapeutic potential of traditional Chinese medicine extracts for TNBC. These herbal extracts exhibit multi-target effects and good safety, and have shown promising capabilities in inducing ferroptosis in TNBC cells. We believe that further exploration and characterization of these natural compounds could lead to the development of a new generation of cancer therapeutics. In addition to traditional chemotherapy, we discussed the role of drug delivery systems in enhancing the efficacy and reducing the toxicity of ferroptosis inducers. Nanoparticles such as exosomes and metal-organic frameworks (MOFs) can improve the solubility and bioavailability of these compounds, thereby expanding their therapeutic potential while minimizing systemic side effects. Although preclinical data on ferroptosis inducers are relatively robust, their translation into clinical practice remains in its early stages. We also emphasize the urgent need for more in-depth and comprehensive research to understand the complex mechanisms of ferroptosis in TNBC. This is crucial for the rational design and development of clinical trials, as well as for leveraging ferroptosis to improve patient outcomes. Hoping the above summarize and review could provide references for the research and development of lead compounds for the treatment for TNBC.

ObjectiveTo explore the construction of a machine learning model for the diagnosis of traditional Chinese medicine （TCM） syndromes in chronic cough and the optimization of this model using the Voting ensemble algorithm. MethodsA retrospective analysis was conducted using clinical data from 921 patients with chronic cough treated at the Respiratory Department of Dongfang Hospital， Beijing University of Chinese Medicine. After standardized processing， 84 clinical features were extracted to determine TCM syndrome types. A specialized dataset for TCM syndrome diagnosis in chronic cough was formed by selecting syndrome types with more than 50 cases. The synthetic minority over-sampling technique （SMOTE） was employed to balance the dataset. Four base models， logistic regression （LR）， decision tree （dt）， multilayer perceptron （MLP）， and Bagging， were constructed and integrated using a hard voting strategy to form a Voting ensemble model. Model performance was evaluated using accuracy， recall， precision， F1-score， receiver operating characteristic （ROC） curve， area under the curve （AUC）， and confusion matrix. ResultsAmong the 921 cases， six syndrome types had over 50 cases each， phlegm-heat obstructing the lung （294 cases）， wind pathogen latent in the lung （103 cases）， cold-phlegm obstructing the lung （102 cases）， damp-heat stagnating in the lung （64 cases）， lung yang deficiency （54 cases）， and phlegm-damp obstructing the lung （53 cases）， yielding a total of 670 cases in the specialized dataset. High-frequency symptoms among these patients included cough， expectoration， odor-induced cough， throat itchiness， itch-induced cough， and cough triggered by cold wind. Among the four base models， the MLP model showed the best diagnostic performance （test accuracy： 0.9104； AUC： 0.9828）. Compared with the base models， the Voting ensemble model achieved superior performance with an accuracy of 0.9289 on the training set and 0.9253 on the test set， showing a minimal overfitting gap of 0.0036. It also achieved the highest AUC （0.9836） in the test set， outperforming all base models. The model exhi-bited especially strong diagnostic performance for damp-heat stagnating in the lung （AUC： 0.9984） and wind pathogen latent in the lung （AUC： 0.9970）. ConclusionThe Voting ensemble algorithm effectively integrates the strengths of multiple machine learning models， resulting in an optimized diagnostic model for TCM syndromes in chronic cough with high accuracy and enhanced generalization ability.

One of its primary surgical treatments of tricuspid regurgitation is tricuspid valve biological valve replacement. Catheter tricuspid valve-in-valve implantation is a novel interventional alternative for biological valve failure. The non-invasive lung fluid measuring device remote dielectric sensing (ReDSTM) has been increasingly incorporated into clinical practice as a means of monitoring chronic heart failure in recent years. This report describes the process and outcomes of the first instance of perioperative lung fluid volume evaluation following transcatheter tricuspid valve implantation utilizing ReDSTM technology. The patient has a short-term, substantial increase in postoperative lung fluid volume as compared to baseline.

Objective To assess the health risks of gaseous pollutants in the indoor air of hair and beauty salons in Jinan, and to provide technical support for strengthening the hygiene management of hair and beauty salons in Jinan and promoting the improvement of conditions. Methods Every year, indoor air samples were collected from 10-16 selected hair salons and beauty salons in Jinan, and relevant information on practitioners was also collected. According to the ^“Technical Guidelines for Environmental Health Risk Assessment of Chemicals^”, an assessment was conducted on the carcinogenic and non-carcinogenic risks of inhalation pathways of gaseous pollutants in the indoor air of hair salons and beauty salons. Results Benzene, toluene, xylene, formaldehyde, and ammonia were detected in the indoor air of hair salons and beauty salons. Formaldehyde, benzene, and ammonia all exceeded the standard in hair salons and beauty salons. The median risk values of formaldehyde and benzene for carcinogenesis in hair salons and beauty salons were both greater than 10^-6, with maximum values higher than 10^-4. The median chronic non-carcinogenic risk value of formaldehyde in the indoor air of hair salons and beauty salons was greater than 1. The median chronic non-carcinogenic risk values for benzene and ammonia were both less than 1, but the maximum risk value was greater than 1. Conclusion Benzene and formaldehyde in the indoor air of hair salons and beauty salons in Jinan City have carcinogenic and non-carcinogenic risks, while ammonia has non-carcinogenic risks, which should be paid attention to.

PURPOSE: Septic shock is associated with high mortality and poor outcomes among sepsis patients with coagulopathy. Although traditional statistical methods or machine learning (ML) algorithms have been proposed to predict septic shock, these potential approaches have never been systematically compared. The present work aimed to develop and compare models to predict septic shock among patients with sepsis. METHODS: It is a retrospective cohort study based on 484 patients with sepsis who were admitted to our intensive care units between May 2018 and November 2022. Patients from the 908th Hospital of Chinese PLA Logistical Support Force and Nanchang Hongdu Hospital of Traditional Chinese Medicine were respectively allocated to training (n=311) and validation (n=173) sets. All clinical and laboratory data of sepsis patients characterized by comprehensive coagulation indexes were collected. We developed 5 models based on ML algorithms and 1 model based on a traditional statistical method to predict septic shock in the training cohort. The performance of all models was assessed using the area under the receiver operating characteristic curve and calibration plots. Decision curve analysis was used to evaluate the net benefit of the models. The validation set was applied to verify the predictive accuracy of the models. This study also used Shapley additive explanations method to assess variable importance and explain the prediction made by a ML algorithm. RESULTS: Among all patients, 37.2% experienced septic shock. The characteristic curves of the 6 models ranged from 0.833 to 0.962 and 0.630 to 0.744 in the training and validation sets, respectively. The model with the best prediction performance was based on the support vector machine (SVM) algorithm, which was constructed by age, tissue plasminogen activator-inhibitor complex, prothrombin time, international normalized ratio, white blood cells, and platelet counts. The SVM model showed good calibration and discrimination and a greater net benefit in decision curve analysis. CONCLUSION The SVM algorithm may be superior to other ML and traditional statistical algorithms for predicting septic shock. Physicians can better understand the reliability of the predictive model by Shapley additive explanations value analysis.
Humans ; Shock, Septic/blood* ; Machine Learning ; Male ; Female ; Retrospective Studies ; Middle Aged ; Aged ; Sepsis/complications* ; ROC Curve ; Cohort Studies ; Adult ; Intensive Care Units ; Algorithms ; Blood Coagulation ; Critical Illness

OBJECTIVE: To investigate the effect of piperlongumine(PL) on the proliferation and ferroptosis of human adriamycin-resistant chronic myeloid leukemia K562/ADR cells, and to explore its possible molecular mechanism. METHODS: CCK-8 assay was used to detect the effect of PL on the survival rate of K562/ADR cells and to screen the appropriate drug concentration. After K562/ADR cells were treated with low, medium and high concentrations of PL(2, 4, and 6 μmol/L), EdU proliferation assay and plate colony formation assay were used to detect cell proliferation and colony formation ability. CCK-8 assay was used to detect the effects of different inhibitors (Fer-1, Z-VAD, Nec-1) combined with PL on cell proliferation. The intracellular Fe²⁺, ROS, malondialdehyde(MDA) and glutathine(GSH) contents were respectively detected by iron ion colorimetry, DCFH-DA fluorescent probe, MDA and GSH kits. RT-qPCR and Western blot were respectively used to detect the expression level of GPX4 mRNA and protein in cells. Bioinformatics websites predicted miRNA that could target and regulate GPX4 . RT-qPCR was used to detect the effects of different concentrations of PL on the expression levels of the predicted miRNA. Dual luciferase gene reporter assay was used to verify the targeting relationship between miR-214-3p and GPX4 . After treating cells with PL or PL+miR-214-3p inhibitor, the Fe²⁺, ROS, MDA, GSH centents and GPX4 protein expression levels in cells were detected. RESULTS: PL inhibited K562/ADR cell proliferation in a concentration-dependent manner（r =0.979）. Compared with the blank control group, the survival rate, EdU positive cells rate in low, medium and high concentration PL groups were significantly decreased (P < 0.01). Compared with the PL group alone, the survival rate of cells in the Z-VAD+PL group was increased slightly (P < 0.05). The cell survival rate was significantly increased in medium or high concentration PL+Fer-1 group (P < 0.01). Compared with blank control group, ROS expression level in low concentration PL group was slightly increased (P < 0.05), and GSH content was slightly decreased (P < 0.05). In medium and high concentration PL groups, the contents of Fe²⁺, ROS and MDA were significantly increased (P < 0.01), while the contents of GSH, expression of GPX4 mRNA and protein were significantly decreased(P < 0.01). Bioinformatics prediction and double luciferase reporter gene experiment confirmed the targeting relationship between GPX4 and miR-214-3p. Compared with the blank control group, the expression level of miR-214-3p in cells of medium and high concentration PL groups was significantly increased (P < 0.01). Compared with PL group alone, the intracellular Fe²⁺, ROS and MDA contents in PL+miR-214-3p inhibitor group were all decreased (P < 0.01), while GSH content and GPX4 protein expression levels were significantly increased (P < 0.01). CONCLUSION Medium and high concentrations of PL can inhibit the proliferation of K562/ADR cells by inducing ferroptosis, which is related to the regulation of miR-214-3p pathway.
Humans ; Ferroptosis/drug effects* ; MicroRNAs/metabolism* ; Dioxolanes/pharmacology* ; Cell Proliferation/drug effects* ; K562 Cells ; Phospholipid Hydroperoxide Glutathione Peroxidase ; Reactive Oxygen Species ; Doxorubicin/pharmacology* ; Signal Transduction ; Piperidones

Mitochondrial dysfunction in chondrocytes is a key pathogenic factor in osteoarthritis (OA), but directly modulating mitochondria in vivo remains a significant challenge. This study is the first to verify a correlation between mitochondrial dysfunction and the downregulation of the FOXO3 gene in the cartilage of OA patients, highlighting the potential for regulating mitophagy via FOXO3 gene modulation to alleviate OA. Consequently, we developed a chondrocyte-targeting CRISPR/Cas9-based FOXO3 gene-editing tool (FoxO3) and integrated it within a nanoengineered 'truck' (NETT, FoxO3-NETT). This was further encapsulated in injectable hydrogel microspheres (FoxO3-NETT@SMs) to harness the antioxidant properties of sodium alginate and the enhanced lubrication of hybrid exosomes. Collectively, these FoxO3-NETT@SMs successfully activate mitophagy and rebalance mitochondrial function in OA chondrocytes through the Foxo3 gene-modulated PINK1/Parkin pathway. As a result, FoxO3-NETT@SMs stimulate chondrocytes proliferation, migration, and ECM production in vitro, and effectively alleviate OA progression in vivo, demonstrating significant potential for clinical applications.