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.

Colorectal cancer is a common malignant tumor of the digestive system. In recent years， its incidence rate and mortality are increasing year by year. Due to the complex pathogenesis and poor prognosis of patients， colorectal cancer poses a serious threat to human physical and mental health. Currently， although Western medicine treatment methods can to some extent inhibit tumor growth and alleviate patient symptoms， postoperative recurrence， metastasis， multiple adverse reactions， and susceptibility to drug resistance are prominent issues， resulting in unsatisfactory overall treatment outcomes. Therefore， exploring more efficient and safe treatment methods has become an urgent task. The adenosine monophosphate-activated protein kinase （AMPK） signaling pathway plays a regulatory role in the growth， differentiation， apoptosis， and autophagy of colorectal cancer cells， and is widely involved in the occurrence and development of colorectal cancer. It is considered an important target for colorectal cancer treatment. Traditional Chinese medicine has unique advantages in the treatment of colorectal cancer， as it can exert its effects through multiple mechanisms and pathways. It can prevent postoperative recurrence and metastasis， reduce adverse reactions to radiotherapy and chemotherapy， and improve patients' quality of life. It has become a key means of treating colorectal cancer. Research has shown that active ingredients in traditional Chinese medicine such as flavonoids， polyphenols， terpenes， and esters， as well as traditional Chinese medicine compounds such as Qingjie Fuzheng Granules and some traditional Chinese medicine extracts， have significant regulatory effects on AMPK and its interaction signaling pathways. They exert their anti-colorectal cancer effects by inducing autophagy and apoptosis in colorectal cancer cells， promoting ferroptosis， inhibiting epithelial-mesenchymal transition， reversing drug resistance， and arresting the cell cycle. This article reviewed and summarized the relevant research on traditional Chinese medicine in the treatment of colorectal cancer in recent years， with a focus on the mechanism of traditional Chinese medicine in regulating the AMPK signaling pathway for the treatment of colorectal cancer. It is expected to provide ideas and references for the development of new drugs for clinical anti-colorectal cancer treatment.

Liver cancer， as a malignant tumor with high incidence and mortality worldwide， has shown a year-by-year increase in both incidence and mortality in China. Currently， Western medicine has achieved certain efficacy in the clinical management of liver cancer in terms of inhibiting tumor growth， alleviating patient symptoms， and delaying disease progression. However， its limitations cannot be ignored. Significant side effects， increasingly severe drug resistance， and limited improvement in patient survival collectively make the overall therapeutic outcomes fall short of ideal expectations. Therefore， exploring more effective and safer treatment strategies has become a critical issue that urgently needs to be addressed in the field of oncology. The adenosine monophosphate-activated protein kinase （AMPK）/mammalian target of rapamycin （mTOR） signaling pathway plays a central regulatory role in the physiological processes of liver cancer cells， including proliferation， differentiation， apoptosis， and autophagy， and is considered a key molecular target for anti-liver cancer therapy. Traditional Chinese medicine （TCM）， characterized by its multi-pathway and multi-mechanism synergistic effects， has become an important component of the current comprehensive treatment system for liver cancer. Among these， TCM monomeric compounds， owing to their well-defined chemical structures and precisely analyzable pharmacological mechanisms， represent an important breakthrough in anti-liver cancer drug development. Studies have shown that various TCM monomeric compounds， including flavonoids， alkaloids， polyphenols， saponins， terpenoids， and quinones， can regulate the AMPK/mTOR signaling pathway and its upstream and downstream protein expression. Through these mechanisms， they induce autophagy and apoptosis in liver cancer cells， inhibit aerobic glycolysis， reverse drug resistance， promote ferroptosis， block epithelial-mesenchymal transition， and inhibit angiogenesis， thereby effectively suppressing the growth and metastasis of liver cancer cells. Based on this， this article systematically reviews recent studies on TCM monomeric compounds in the treatment of liver cancer， and further analyzes in depth their mechanisms in regulating the AMPK/mTOR signaling pathway， so as to provide ideas and references for the development of new anti-liver cancer drugs.

Liver cancer， as a malignant digestive tract tumor with high incidence and mortality rates globally， has witnessed continuous increases in both incidence and mortality in recent years. Although modern medical treatment methods have achieved certain results in disease control， the treatment of liver cancer remains challenging due to the low early diagnosis rate， obvious toxic and side effects， and widespread drug resistance. Against this backdrop， exploring more efficient and safer treatment strategies is of utmost urgency. The Hippo cascade signaling pathway plays a crucial regulatory role in processes such as the proliferation， differentiation， apoptosis， and invasion of liver cancer cells. It is extensively involved in the occurrence and development of liver cancer， serving as an important target for anti-liver cancer treatment research. Traditional Chinese medicine （TCM） can exert anti-liver cancer effects through multiple approaches， mechanisms， and pathways. It has shown remarkable efficacy in preventing postoperative recurrence and metastasis of liver cancer， reducing adverse reactions of radiotherapy and chemotherapy， and improving the quality of life， thus becoming a key component of comprehensive liver cancer treatment. Studies have confirmed that the TCM active components including flavonoids， alkaloids， terpenoids， polyphenols， saponins， and quinones， as well as the TCM compound prescriptions such as compound Banmao capsules， Erzhu Jiedu decoction， Pianzaihuang， and Zhenggan prescription， can effectively regulate the Hippo signaling pathway. They exert significant anti-liver cancer effects through multiple mechanisms， such as inducing autophagy and apoptosis of liver cancer cells， improving macrophage polarization， blocking epithelial-mesenchymal transition， inhibiting glycolytic metabolism， promoting immune cell activation， reversing tumor drug resistance， and arresting the cell cycle. This study used "liver cancer" "Hippo" "signaling pathway" and "traditional Chinese medicine" as the main keywords to search multiple literature databases， including PubMed， CNKI， and VIP. By discussing and analyzing the mechanisms of TCM in regulating the Hippo signaling pathway for the treatment of liver cancer in the past five years， this paper aims to provide ideas and references for the research and development of new anti-liver cancer drugs in clinical practice.

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.

BACKGROUND:Research has shown that endoplasmic reticulum stress-induced autophagy of neurons in the ischemic penumbra is a key link in cerebral ischemia-reperfusion injury.Autophagy mediated by the dissociation and activation of endoplasmic reticulum transmembrane proteins PERK,IRE1 α,ATF6,and GRP78/BIP plays an important role in neuronal outcomes.Traditional Chinese medicine can regulate endoplasmic reticulum stress-autophagy,reduce neuronal damage or death,and exert neuroprotective effects.OBJECTIVE:To explore the role of endoplasmic reticulum stress-autophagy in cerebral ischemia-reperfusion injury and the research progress in the regulatory mechanisms of traditional Chinese medicine.METHODS:A literature retrieval was conducted in CNKI and PubMed for relevant literature related to endoplasmic reticulum stress,autophagy,cerebral ischemia-reperfusion injury,and regulation by traditional Chinese Medicine published from January 2015 to May 2024.The search terms were"cerebral ischemia-reperfusion injury,ischemic stroke,brain injury,endoplasmic reticulum stress,autophagy,traditional Chinese medicine,compounds,signaling pathways,saponins,polyphenols,alkaloids"in Chinese and English,respectively.Any literature that is inconsistent with the research content,outdated,or duplicated was excluded.A total of 1197 relevant literature were retrieved,and 71 articles were ultimately included.RESULTS AND CONCLUSION:(1)Numerous studies have suggested that endoplasmic reticulum stress-autophagy is closely related with cerebral ischemia-reperfusion injury.(2)The active ingredients and compound formulas of traditional Chinese medicine monomers can regulate the expression of endoplasmic reticulum stress-autophagy related proteins,alleviate neuronal damage,and exert neuroprotective effects by regulating signal pathways such as PERK-eIF2α-ATF4,IRE1α-ASK1-JNK,and IRE1α-XBP.

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

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.