Colorectal cancer， a leading malignant gastrointestinal tumor globally in terms of incidence and mortality， has seen a consistent annual rise in newly diagnosed cases. While conventional therapies like radiotherapy， chemotherapy， and surgery are available， problems such as lack of early diagnosis， poor prognosis， and drug resistance remain significant burdens for patients. Given the complex and diverse pathogenesis of colorectal cancer， there is an urgent clinical need for safe， effective， reliable， and multi-targeted therapeutic strategies. The Hippo signaling pathway， closely linked to mechanisms like tumorigenesis， cancer cell invasion， migration， and drug resistance， extensively participates in the occurrence and development of colorectal cancer， so targeting the signaling pathway for cancer prevention and treatment has become a crucial research direction in recent years. Traditional Chinese medicine （TCM） offers multi-faceted， multi-pathway， and multi-target advantages and becomes an important therapy for colorectal cancer by enhancing patients' immunity， improving the life quality， and prolonging survival. Studies show that the active components of TCM， including flavonoids， terpenoids， phenols， alkaloids， quinones， lignans， and saponins， as well as TCM compounds such as modified Sijunzi decoction， Jiedu Sangen decoction， Jianpi Jiedu compound， and Quyu Jiedu decoction， exhibit significant targeting effects on the Hippo signaling pathway. These TCMs can exert an anti-colorectal cancer effect through various mechanisms， such as inducing cancer cell autophagy and apoptosis， inhibiting epithelial-mesenchymal transition， reversing drug resistance of the tumor， and blocking the cancer cell cycle. This paper reviewed and analyzed Chinese and international research on the action mechanisms of TCM in regulating the Hippo signaling pathway for the prevention and treatment of colorectal cancer with a comprehensive overview presentation， aiming to provide new references and ideas for the clinical application of TCM and the development of new pharmacological agents in the prevention and treatment of colorectal cancer.

Colorectal cancer， a leading malignant gastrointestinal tumor globally in terms of incidence and mortality， has seen a consistent annual rise in newly diagnosed cases. While conventional therapies like radiotherapy， chemotherapy， and surgery are available， problems such as lack of early diagnosis， poor prognosis， and drug resistance remain significant burdens for patients. Given the complex and diverse pathogenesis of colorectal cancer， there is an urgent clinical need for safe， effective， reliable， and multi-targeted therapeutic strategies. The Hippo signaling pathway， closely linked to mechanisms like tumorigenesis， cancer cell invasion， migration， and drug resistance， extensively participates in the occurrence and development of colorectal cancer， so targeting the signaling pathway for cancer prevention and treatment has become a crucial research direction in recent years. Traditional Chinese medicine （TCM） offers multi-faceted， multi-pathway， and multi-target advantages and becomes an important therapy for colorectal cancer by enhancing patients' immunity， improving the life quality， and prolonging survival. Studies show that the active components of TCM， including flavonoids， terpenoids， phenols， alkaloids， quinones， lignans， and saponins， as well as TCM compounds such as modified Sijunzi decoction， Jiedu Sangen decoction， Jianpi Jiedu compound， and Quyu Jiedu decoction， exhibit significant targeting effects on the Hippo signaling pathway. These TCMs can exert an anti-colorectal cancer effect through various mechanisms， such as inducing cancer cell autophagy and apoptosis， inhibiting epithelial-mesenchymal transition， reversing drug resistance of the tumor， and blocking the cancer cell cycle. This paper reviewed and analyzed Chinese and international research on the action mechanisms of TCM in regulating the Hippo signaling pathway for the prevention and treatment of colorectal cancer with a comprehensive overview presentation， aiming to provide new references and ideas for the clinical application of TCM and the development of new pharmacological agents in the prevention and treatment of colorectal cancer.

Fecal microbiota transplantation (FMT) technology originated in China during the Eastern Jin Dynasty and has rapidly developed over the past two decades, becoming a primary method for studying the causal relationship between gut microbiota and the occurrence and progression of diseases. At the same time, the therapeutic effects of FMT in the field of gastrointestinal diseases have gained widespread recognition and are gradually expanding into other disease areas. The FMT procedure is relatively complex, and there is currently no standardized method; its success is influenced by various factors, including the donor, recipient, processing of the fecal material, and the method of implantation. Given the increasingly recognized relationship between gut microbiota and various diseases, FMT has become a research hotspot in both scientific studies and clinical applications, achieving a series of significant advancements. To help researchers better understand this technology, this paper will outline the development history of FMT, summarize common operational methods in research and clinical settings, review its application progress, and look forward to future development directions.

ObjectiveThe central symptom of Parkinson’s disease (PD) is impaired motor function. Beta-band electrical activity in the motor network of the basal ganglia is closely related to motor function. In this study, we combined scalp electroencephalography (EEG), brain functional network, and clinical scales to investigate the effects of beta burst-period neural electrical activity on brain functional network characteristics, which may serve as a reference for clinical diagnosis and treatment. MethodsThirteen PD patients were included in the PD group, and 13 healthy subjects were included in the healthy control group. Resting-state EEG data were collected from both groups, and beta burst and non-burst periods were extracted. A phase synchronization network was constructed using weighted phase lag indices, and the topological feature parameters of phase synchronization network were compared between the two groups across different periods and four frequency bands. Additionally, the correlation between changes in network characteristics and clinical symptoms was analyzed. ResultsDuring the beta burst period, the topological characteristic parameters of phase synchronization network in all four frequency bands were significantly higher in PD patients compared to healthy controls. The average clustering coefficient of the phase synchronization network in the beta band during the beta burst period was negatively correlated with UPDRS-III scores. In the low gamma band during the non-burst period, the average clustering coefficient of phase synchronization network was positively correlated with UPDRS and UPDRS-III scores, while UPDRS-III scores were positively correlated with global efficiency and average degree. ConclusionThe brain functional network features of PD patients were significantly enhanced during the beta burst period. Moreover, the beta-band brain functional network characteristics during the beta burst period were negatively correlated with clinical scale scores, whereas low gamma-band functional network features during the non-burst period were positively correlated with clinical scale scores. These findings indicate that motor function impairment in PD patients is associated with the beta burst period. This study provides valuable insights for the diagnosis of PD.

Cistanches Herba(CH) is a famous tonic traditional Chinese medicine, with the effects of tonifying kidney Yang, nourishing kidney Yin, replenishing essence and blood, and moistening the intestines to relieve constipation. Modern pharmacological studies have shown that CH has anti-aging, anti-fatigue, immunomodulatory, neuroprotective, and anti-aging activities, serving as an ideal raw material for the development of pharmaceuticals and health products. In 2023, CH was added in the catalog of medicinal and food substances, which provided policy support for its application in conventional food products and expanding pathways for industrial diversification. To comprehensively understand current development status of CH products, this review systematically investigated professional databases including Yaozhi(https://db.yaozh.com), Chinese Pharmacopoeia, Compendium of National Standards for Chinese Patent Medicines, and Kezhuang and collected market survey data to thoroughly review the applications of CH as a primary ingredient in domestic and international Chinese patent medicines, health foods, cosmetics, and common food products. Furthermore, this review points out challenges in the current industrial development and future potential market prospects, aiming to provide guidance for the development and industrialization of CH-based pharmaceuticals and health products, thereby promoting the vigorous growth of the CH industry.
Drugs, Chinese Herbal/pharmacology* ; Humans ; Cistanche/chemistry* ; Animals ; Medicine, Chinese Traditional

Hearing loss is the most prevalent disabling disease. Cochlear implantation（CI） serves as the primary intervention for severe to profound hearing loss. This consensus systematically explores the value of genetic diagnosis in the pre-operative assessment and efficacy prognosis for CI. Drawing upon domestic and international research and clinical experience, it proposes an evidence-based medicine three-tiered prognostic classification system（Favorable, Marginal, Poor）. The consensus focuses on common hereditary non-syndromic hearing loss（such as that caused by mutations in genes like GJB2, SLC26A4, OTOF, LOXHD1） and syndromic hereditary hearing loss（such as Jervell & Lange-Nielsen syndrome and Waardenburg syndrome）, which are closely associated with congenital hearing loss, analyzing the impact of their pathological mechanisms on CI outcomes. The consensus provides recommendations based on multiple round of expert discussion and voting. It emphasizes that genetic diagnosis can optimize patient selection, predict prognosis, guide post-operative rehabilitation, offer stratified management strategies for patients with different genotypes, and advance the application of precision medicine in the field of CI.
Humans ; Cochlear Implantation ; Prognosis ; Hearing Loss/surgery* ; Consensus ; Connexin 26 ; Mutation ; Sulfate Transporters ; Connexins/genetics*

OBJECTIVE: To construct machine learning prediction model for sepsis-associated encephalopathy (SAE), and analyze the application value of the model on early identification of SAE risk in elderly septic patients. METHODS: Patients aged over 60 years with a primary diagnosis of sepsis admitted to intensive care unit (ICU) from 2008 to 2023 were selected from Medical Information Mart for Intensive Care-IV 2.2 (MIMIC-IV 2.2). Demographic variables, disease severity scores, comorbidities, interventions, laboratory indicators, and hospitalization details were collected. Key factors associated with SAE were identified using univariate Logistic regression analysis. The data were randomly divided into training and validation sets in a 7 : 3 ratio. Multivariable Logistic regression analysis was conducted in the training set and visualized using a nomogram model for prediction of SAE. The discrimination of the model was evaluated in the validation set using the receiver operator characteristic curve (ROC curve), and its calibration was assessed using calibration curve. Furthermore, multiple machine learning algorithms, including multi-layer perceptron (MLP), support vector machine (SVM), naive bayes (NB), gradient boosting machine (GBM), random forest (RF), and extreme gradient boosting (XGB), were constructed in the training set. Their predictive performance was subsequently evaluated on the validation set. Taking the XGB model as an example, the interpretability of the model through the SHapley Additive exPlanations (SHAP) algorithm was enhanced to identify the key predictive factors and their contributions. RESULTS: A total of 2 204 septic patients were finally enrolled, of whom 840 developed SAE (38.1%). A total of 21 variables associated with SAE were screened through univariate Logistic regression analysis. Multivariable Logistic regression analysis showed that endotracheal intubation [odds ratio (OR) = 0.40, 95% confidence interval (95%CI) was 0.19-0.88, P < 0.001], oxygen therapy (OR = 0.76, 95%CI was 0.53-0.95, P = 0.023), tracheotomy (OR = 0.20, 95%CI was 0.07-0.53, P < 0.001), continuous renal replacement therapy (CRRT; OR = 0.32, 95%CI was 0.15-0.70, P < 0.001), cerebrovascular disease (OR = 0.31, 95%CI was 0.16-0.60, P < 0.001), rheumatic disease (OR = 0.44, 95%CI was 0.19-0.99, P < 0.001), male (OR = 0.68, 95%CI was 0.54-0.86, P = 0.001), and maximum anion gap (AG; OR = 0.95, 95%CI was 0.93-0.97, P < 0.001) were associated with an decreased probability of SAE, and age (OR = 1.05, 95%CI was 1.03-1.06, P < 0.001), acute physiology score III (APSIII; OR = 1.02, 95%CI was 1.01-1.02, P < 0.001), Oxford acute severity of illness score (OASIS; OR = 1.04, 95%CI was 1.03-1.06, P < 0.001), and length of hospital stay (OR = 1.01, 95%CI was 1.01-1.02, P < 0.001) were associated with an increased probability of SAE. A nomogram model was constructed based on these variables. In the validation set, ROC curve analysis showed that the model achieved an area under the ROC curve (AUC) of 0.723, and the calibration curve showed good consistency between the predicted probability of the model and the observed probability. Among the machine learning algorithms, including MLP, SVM, NB, GBM, RF, and XGB, the SVM model and RF model demonstrated relatively good predictive performance, with AUC of 0.748 and 0.739, respectively, and the sensitivity was both exceeding 85%. The predictive performance of the XGB model was explained through SHAP analysis, and the results indicated that APSIII score (SHAP value was 0.871), age (SHAP value was 0.521), and OASIS score (SHAP value was 0.443) were important factors affecting the predictive performance of the model. CONCLUSIONS The machine learning-based SAE prediction model exhibits good predictive capability and holds significant application value for the early identification of SAE risk in elderly septic patients.
Humans ; Machine Learning ; Aged ; Sepsis-Associated Encephalopathy ; Sepsis/complications* ; Intensive Care Units ; Logistic Models ; Middle Aged ; Male ; ROC Curve ; Female ; Bayes Theorem ; Nomograms ; Support Vector Machine ; Algorithms

Hepatocellular carcinoma （HCC） is one of the most common malignant tumors with high incidence and mortality rates worldwide， which brings a huge burden to the physical and mental health and socio-economic life of patients. The adenosine monophosphate-activated protein kinase （AMPK） signaling pathway serves as the regulatory center of cellular energy metabolism and is closely associated with the biological activities of HCC cells， including autophagy， apoptosis， and angiogenesis， and it has become a hot topic in current cancer research. Traditional Chinese medicine drugs are abundant in natural components such as flavonoids， alkaloids， and phenols and have the characteristics of multiple targets， pathways， components， and hierarchies. By targeting the AMPK signaling pathway， these components can be used alone or in combination with conventional antitumor therapies to exert an anti-tumor effect on HCC from various aspects. This article reviews and summarizes the extracts of traditional Chinese medicine that target the AMPK signaling pathway for the prevention and treatment of HCC， in order to provide a theoretical basis and a reference for the clinical application of traditional Chinese medicine in the treatment of HCC and the development of related drugs.

In recent years,the incidence of heat-related diseases has been on a steady upward trend,which is closely associated with environmental factors such as climate change and air pollution.Exposure to a hot environment and/or strenuous physical activities can progress to heat stroke(HS),an acute disease that can lead to death.Current research indicates that gut injury occupies the most crucial initiating position in the pathophysiological changes and pathogenesis of HS.Probiotics can reduce the incidence and mortality of HS through maintaining the health of the gut microbiota,regulating the intestinal immune system,and other effects.In addition,the gut microbiota can construct axis systems to interact with multiple organs such as the liver,lungs,and brain,which is of great significance for alleviating the damage to distant organs caused by HS.This paper reviews the regulation of the gut microbiota by probiotics to improve the intestinal heat tolerance ability and barrier function,aiming to provide references for the prevention and treatment of heat stroke in clinical practice.