Allergic diseases exhibited the characteristics of latent concealment and dynamic transmutation， which highly align with the pathogenic features of "latency and transformative change" described in the theory of latent pathogens. Based on the "latent pathogens with transformative potential" theory， this paper systematically explored the mechanisms of occurrence， transmission， and outcome of allergic diseases. It proposed that the insufficiency of kidney essence is the root cause enabling pathogens to lurk internally， leading to disease onset due to deficient healthy qi and lurking pathogens； the dysfunction of sanjiao serves as the pathway for pathogen stagnation， driving multi-system transmission； the accumulation of phlegm， stasis， and toxins constitutes the predicament of a protracted course， ultimately resulting in intractable pathological entanglement. Accordingly， a tiered intervention strategy is formulated，i.e. during the latency period， treatment should tonify the kidney and replenish essence to consolidate the foundation and halt the tendency of pathogens to lurk internally； during the transmission period， treatment should regulate sanjiao to intercept disease transmission and curb multi-system proliferation； during the protracted period， treatment should purge phlegm and resolve stasis to eliminate stubborn lesions， and break the vicious cycle of chronic accumulation and damage.

OBJECTIVE: To evaluate the efficacy and safety of Shexiang Tongxin Dropping Pill (STDP) in treating stable angina patients with phlegm-heat and blood-stasis syndrome by exercise duration and metabolic equivalents. METHODS: This multicenter, randomized, double-blind, placebo-controlled clinical trial enrolled stable angina patients with phlegm-heat and blood-stasis syndrome from 22 hospitals. They were randomized 1:1 to STDP (35 mg/pill, 6 pills per day) or placebo for 56 days. The primary outcome was the exercise duration and metabolic equivalents (METs) assessed by the standard Bruce exercise treadmill test after 56 days of treatment. The secondary outcomes included the total angina symptom score, Chinese medicine (CM) symptom scores, Seattle Angina Questionnaire (SAQ) scores, changes in ST-T on electrocardiogram and adverse events (AEs). RESULTS: This trial enrolled 309 patients, including 155 and 154 in the STDP and placebo groups, respectively. STDP significantly prolonged exercise duration with an increase of 51.0 s, compared to a decrease of 12.0 s with placebo (change rate: -11.1% vs. 3.2%, P<0.01). The increase in METs was significantly greater in the STDP group than in the placebo group (change: -0.4 vs. 0.0, change rate: -5.0% vs. 0.0%, P<0.01). The improvement of total angina symptom scores (25.0% vs. 0.0%), CM symptom scores (38.7% vs. 11.8%), reduction of nitroglycerin consumption (100.0% vs. 11.3%), and all domains of SAQ, were significantly greater with STDP than placebo (all P<0.01). The changes in Q-T intervals at 28 and 56 days from baseline were similar between the two groups (both P>0.05). Twenty-five participants (16.3%) with STDP and 16 (10.5%) with placebo experienced AEs (P=0.131), with no serious AEs observed. CONCLUSION STDP could improve exercise tolerance in patients with stable angina and phlegm-heat and blood stasis syndrome, with a favorable safety profile. (Registration No. ChiCTR-IPR-15006020).
Humans ; Double-Blind Method ; Drugs, Chinese Herbal/adverse effects* ; Male ; Female ; Middle Aged ; Angina, Stable/physiopathology* ; Aged ; Syndrome ; Treatment Outcome ; Placebos ; Tablets

Parkinson's disease (PD), a chronic and common neurodegenerative disease, is characterized by the progressive loss of dopaminergic neurons in the dense part of the substantia nigra and abnormal aggregation of alpha-synuclein. Type 2 diabetes mellitus (T2DM) is a metabolic disease characterized by chronic insulin resistance and deficiency in insulin secretion. Extensive evidence has confirmed shared pathogenic mechanisms underlying PD and T2DM, such as oxidative stress caused by insulin resistance, mitochondrial dysfunction, inflammation, and disorders of energy metabolism. Conventional drugs for treating T2DM, such as metformin and glucagon-like peptide-1 receptor agonists, affect nerve repair. Even drugs for treating PD, such as levodopa, can affect insulin secretion. This review summarizes the relationship between PD and T2DM and related therapeutic drugs from the perspective of insulin signaling pathways in the brain.
Humans ; Parkinson Disease/drug therapy* ; Diabetes Mellitus, Type 2/pathology* ; Signal Transduction/physiology* ; Receptor, Insulin/metabolism* ; Animals ; Insulin Resistance/physiology* ; Insulin/metabolism*

Neurodegenerative diseases encompass a diverse array of disorders that have a profoundly detrimental impact on human health, characterized by their intricate and multifaceted pathogenesis. In the recent past, a growing body of scientific research has begun to shed light on the critical involvement of the neuro-immune axis in the onset and advancement of these debilitating conditions. This comprehensive review article delves into the intricate composition of the neuro-immune axis, elucidating the complex mechanisms through which it exerts its influence in the context of neurodegenerative diseases. Furthermore, it explores the potential therapeutic applications of targeting the neuro-immune axis for the management and treatment of these diseases. This extensive examination aims to offer new perspectives and innovative strategies that could pave the way for more effective treatments for neurodegenerative diseases, thereby providing hope for those afflicted by these challenging conditions.
Humans ; Neurodegenerative Diseases/metabolism* ; Animals ; Neuroimmunomodulation/physiology*

Zebrafish is a relatively new experimental animal model with unique characteristics that enable its wide use in research on many human diseases.The exploration of anti-tumor drugs and other clinical treatments remain the focus of current research on cancer.Zebrafish characteristics,including rapid development,ease of observation,high genetic homology,and low-cost gene editing,make them highly useful for tumor research.By covering the applications of zebrafish in anti-tumor drug research and clinical studies,this review aims to provide valuable insights for the further utilization of zebrafish in cancer drug screening,assessment of drug activity and toxicity,and clinical research.

Cancer incidence in China has been rising steadily,with a particularly heavy burden from several high-prevalence malignancies.Medical examination for cancer plays a critical role in the early detection of cancer,precancerous lesions,and precursor conditions,thereby facilitating timely diagnosis and intervention.Such examination also addresses the growing demand for person-alized cancer screening services among diverse population groups.The development of evidence-based,context-specific cancer screening guidelines is essential to enhance the standardization,quality,and equity of preventive screening practices across the country,ultimately improving out-comes in early cancer detection and treatment.Guided by the Department of Medical Emergency Response of the National Health Commission,the Guidelines for Medical Examination for Cancer in Health Examination Agency(2025 Edition)were developed under the leadership of the National Cancer Center.A multidisciplinary panel of experts formulated the guidelines in accordance with the principles and methodology of the World Health Organization Handbook for Guideline Deve-lopment.The guidelines provide evidence-based recommendations on key clinical domains:target cancers and populations,overall screening workflow,screening protocols,diagnostic technolo-gies,result interpretation,follow-up procedures,and quality control.The primary objective is to standardize cancer screening practices in health examination agency and strengthen China's ca-pacity for prevention and control of high-burden cancers.

Objective: To assess the association between the metabolic score for insulin resistance index (METS-IR) and overactive bladder (OAB) in the US population，so as to explore the potential of METS-IR as a predictive tool for OAB risk and to provide insights for early screening and intervention strategies. Methods: Based on the data from the National Health and Nutrition Examination Survey (NHANES) 2005-2018，a cross-sectional design was employed，and multivariate logistic regression models were used to analyze the association between METS-IR and OAB. METS-IR was analyzed both as a continuous variable and categorized into quartiles. To further validate the association between METS-IR and OAB across diverse populations，subgroup analyses were conducted in participants stratified by clinical characteristics. Smooth curve fitting was employed to test the linearity of the METS-IR-OAB relationship. Results: Elevated METS-IR was associated with an increased risk of OAB (P<0.001)，and this positive correlation remained stable when METS-IR was categorized into quartiles (P<0.001). Subgroup analyses revealed that the association between METS-IR and OAB was more pronounced in females，participants younger than 55 years，and non-diabetic individuals (P<0.05). Furthermore，smooth curve fitting confirmed a linear positive correlation between METS-IR and OAB，with this linear relationship observed in both diabetic and non-diabetic groups. Conclusion: This study，based on the NHANES 2005-2018 database，found a linear positive correlation between METS-IR and OAB.

OBJECTIVE: To explore the feasibility of incorporating simple bedside indicators into death predictive model for elderly critically ill patients based on interpretability machine learning algorithms, providing a new scheme for clinical disease assessment. METHODS: Elderly critically ill patients aged ≥ 65 years who were hospitalized in the intensive care unit (ICU) of Tacheng People's Hospital of Ili Kazak Autonomous Prefecture from June 2017 to May 2020 were retrospectively selected. Basic parameters including demographic characteristics, basic vital signs and fluid intake and output within 24 hours after admission, as well acute physiology and chronic health evaluation II (APACHE II), Glasgow coma score (GCS) and sequential organ failure assessment (SOFA) were also collected. According to outcomes in hospital, patients were divided into survival group and death group. Four datasets were constructed respectively, namely baseline dataset (B), including age, body temperature, heart rate, pulse oxygen saturation, respiratory rate, mean arterial pressure, urine output volume, infusion volume, and crystal solution volume; B+APACHE II dataset (BA), B+GCS dataset (BG), and B+SOFA dataset (BS). Then three machine learning algorithms, Logistic regression (LR), extreme gradient boosting (XGboost) and gradient boosting decision tree (GBDT) were used to develop the corresponding mortality predictive models within four datasets. The feature importance histogram of each prediction model was drawn by SHapley additive explanation (SHAP) method. The area under curve (AUC), accuracy and F1 score of each model were compared to determine the optimal prediction model and then illuminate the nomogram. RESULTS: A total of 392 patients were collected, including 341 in the survival group and 51 in the death group. There were statistically significant differences in heart rate, pulse oxygen saturation, mean arterial pressure, infusion volume, crystal solution volume, and etiological distribution between the two groups. The top three causes of death were shock, cerebral hemorrhage, and chronic obstructive pulmonary disease. Among the 12 prognostic models trained by three machine learning algorithms, overall performance of prognostic models based on B dataset was behind, whereas the LR model trained by BA dataset achieved the best performance than others with AUC of 0.767 [95% confidence interval (95%CI) was 0.692-0.836], accuracy of 0.875 (95%CI was 0.837-0.903) and F1 score of 0.190. The top 3 variables in this model were crystal solution volume with first 24 hours, heart rate and mean arterial pressure. The nomogram of the model showed that the total score between 150 and 230 were advisable. CONCLUSION The interpretable machine learning model including simple bedside parameters combined with APACHE II score could effectively identify the risk of death in elderly patients with critically illness.
Humans ; Critical Illness ; Machine Learning ; Aged ; Algorithms ; Intensive Care Units ; Retrospective Studies ; APACHE ; Prognosis ; Organ Dysfunction Scores ; Hospital Mortality ; Male ; Female

By combing the mechanism of retrograde transmission of damp-heat epidemic to the pericardium,it is believed that the retrograde transmission of damp-heat epidemic to the pericardium is the transmission trend of damp-heat turbid epidemic evil from the lung wei or lung to the pericardium,and the turbid evil harming the clear is an important pathological mechanism leading to the retro-grade transmission of epidemic evil.Clinical treatment should be based on the theory of turbid evil harming the clear,and the lung qi should be disseminated to promote yang first to cut off the retrograde transmission of epidemic evil;if retrograde transmission occurs,phlegm and turbidity should be removed to promote yang,and be careful to prevent the separation of yin and yang.

By combing the mechanism of retrograde transmission of damp-heat epidemic to the pericardium,it is believed that the retrograde transmission of damp-heat epidemic to the pericardium is the transmission trend of damp-heat turbid epidemic evil from the lung wei or lung to the pericardium,and the turbid evil harming the clear is an important pathological mechanism leading to the retro-grade transmission of epidemic evil.Clinical treatment should be based on the theory of turbid evil harming the clear,and the lung qi should be disseminated to promote yang first to cut off the retrograde transmission of epidemic evil;if retrograde transmission occurs,phlegm and turbidity should be removed to promote yang,and be careful to prevent the separation of yin and yang.