The Expert Consensus on Clinical Application of Qinbaohong Zhike Oral Liquid in Treatment of Acute Bronchitis and Acute Attack of Chronic Bronchitis （GS/CACM 337-2023） was released by the China Association of Chinese Medicine on December 13^th， 2023. This expert consensus was developed by experts in methodology， pharmacy， and Chinese medicine in strict accordance with the development requirements of the China Association of Chinese Medicine （CACM） and based on the latest medical evidence and the clinical medication experience of well-known experts in the fields of respiratory medicine （pulmonary diseases） and pediatrics. This expert consensus defines the application of Qinbaohong Zhike oral liquid in the treatment of cough and excessive sputum caused by phlegm-heat obstructing lung， acute bronchitis， and acute attack of chronic bronchitis from the aspects of applicable populations， efficacy evaluation， usage， dosage， drug combination， and safety. It is expected to guide the rational drug use in medical and health institutions， give full play to the unique value of Qinbaohong Zhike oral liquid， and vigorously promote the inheritance and innovation of Chinese patent medicines.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Based on CT scan data,a bionic model of lumbar spine injuries with high biofidelity is developed and validated through cadaver experiments.Decoupling the constraint system that affects occupants during collisions due to inertial forces and the subsequent pressure exerted by the seat upon returning to position,a simulated fall experiment is designed.The simulated outcomes are trained and predicted using deep learning algorithms,and the accuracy of the trained neural network prediction model is verified.Key parameters are analyzed for correlation using principal component analysis and cross-reverse methods.The results shows that the predicted lumbar spine injury model obtained from training has high reliability(R2>0.9).Comprehensive analysis reveals that after experiencing axial impact,the L4 vertebral body bears the highest impact load and can be used as a representative measure of lumbar spine injury.Among the environmental variables,the axial force on the L4 lumbar spine is mainly affected by torso mass and fall height,both of which have positive correlations.Torso mass,fall height,and posture angle all have positive effects on internal energy.Conversely,torso mass and fall height have negative correlations with stress.These research findings provide a scientific basis for further elucidating lumbar spine injury mechanisms in intelligent cockpit environments,devising corresponding safety protection measures,and evaluating occupant safety in automobiles.

OBJECTIVE: As an age-related neurodegenerative disease, the prevalence of mild cognitive impairment (MCI) increases with age. Within the framework of traditional Chinese medicine, spleen-kidney deficiency syndrome (SKDS) is recognized as the most frequent MCI subtype. Due to the covert and gradual onset of MCI, in community settings it poses a significant challenge for patients and their families to discern between typical aging and pathological changes. There exists an urgent need to devise a preliminary diagnostic tool designed for community-residing older adults with MCI attributed to SKDS (MCI-SKDS). METHODS: This investigation enrolled 312 elderly individuals diagnosed with MCI, who were randomly distributed into training and test datasets at a 3:1 ratio. Five machine learning methods, including logistic regression (LR), decision tree (DT), naive Bayes (NB), support vector machine (SVM), and gradient boosting (GB), were used to build a diagnostic prediction model for MCI-SKDS. Accuracy, sensitivity, specificity, precision, F1 score, and area under the curve were used to evaluate model performance. Furthermore, the clinical applicability of the model was evaluated through decision curve analysis (DCA). RESULTS: The accuracy, precision, specificity and F1 score of the DT model performed best in the training set (test set), with scores of 0.904 (0.845), 0.875 (0.795), 0.973 (0.875) and 0.973 (0.875). The sensitivity of the training set (test set) of the SVM model performed best among the five models with a score of 0.865 (0.821). The area under the curve of all five models was greater than 0.9 for the training dataset and greater than 0.8 for the test dataset. The DCA of all models showed good clinical application value. The study identified ten indicators that were significant predictors of MCI-SKDS. CONCLUSION The risk prediction index derived from machine learning for the MCI-SKDS prediction model is simple and practical; the model demonstrates good predictive value and clinical applicability, and the DT model had the best performance. Please cite this article as: Ai YT, Zhou S, Wang M, Zheng TY, Hu H, Wang YC, Li YC, Wang XT, Zhou PJ. Development of a machine learning-based risk prediction model for mild cognitive impairment with spleen-kidney deficiency syndrome in the elderly. J Integr Med. 2025; 23(4): 390-397.
Humans ; Cognitive Dysfunction/diagnosis* ; Aged ; Male ; Female ; Machine Learning ; Spleen ; Aged, 80 and over ; Kidney ; Medicine, Chinese Traditional

The integration of multi-source data and the establishment of early warning indicator systems constitute pivotal elements for advancing surveillance and early warning capacities in respiratory infectious diseases. Given the multifaceted transmission mechanisms and complex contributing factors inherent in respiratory infectious diseases, surveillance datasets and associated early warning indicators demonstrate notable heterogeneity and sophisticated interrelationships. Furthermore, as surveillance and early warning requirements significantly vary across diverse epidemiological scenarios, accurate assessment of the value and applicability of distinct data types and indicators is imperative. This paper systematically reviews and synthesizes recent advancements in surveillance data and early warning indicators for respiratory infectious diseases, drawing on both domestic and international research. Particular attention is dedicated to analyzing the applicability and efficacy of various data types and indicators within multiple practical contexts, aiming to provide robust theoretical frameworks and methodological guidance to facilitate the development of resilient and efficient surveillance and early warning systems for respiratory infectious diseases.

With the rapid development of neuroelectrophysiology, neuroimaging and other technologies, a large amount of evidence has shown that the occurrence and development of idiopathic generalized epilepsy (IGE) are closely related to the cortical-subcortical neural network. This article intends to review the relevant research on how the cerebral cortex and subcortical structures such as the thalamus, basal ganglia, and cerebellum are involved in the cognitive impairment of IGE, as well as the important subcortical neural nuclei targets currently targeted in the treatment of drug-resistant epilepsy by neuromodulation, to evaluate the feasibility of neuromodulation therapy in clinical practice.

Objective:To evaluate the left atrial function in patients with hypertrophic cardiomyopathy（HCM）combined with heart failure with preserved ejection fraction（HFpEF）using four-dimensional automated left atrial quantification（4D Auto LAQ）technology，and to investigate the independent factors affecting patients with HCM combined with HFpEF.Methods:One hundred HCM patients with left ventricular ejection fraction（LVEF）≥ 50% who were admitted to the First Affiliated Hospital of Zhengzhou University from September 2023 to March 2025 were prospectively selected. There were 50 cases in the HFpEF group and 50 cases in the non-HF group. The clinical data and conventional ultrasound parameters of HCM patients were collected. The 4D Auto LAQ technology was applied to obtain the four-dimensional volume and strain parameters of the left atrium，including the minimum left atrial volume（LAVmin），the maximum left atrial volume（LAVmax），the maximum left atrial volume index（LAVImax），the pre-atrial contraction volume（LAVpreA），the left atrial emptying volume（LAEV），the left atrial ejection fraction（LAEF），the longitudinal and circumferential strains in the left atrial reservoir period（LASr，LASr-c），the longitudinal and circumferential strains in the left atrial conduit period（LAScd，LAScd-c），the longitudinal and circumferential strains in the left atrial contraction period（LASct，LASct-c），and the minimum left atrial volume index（LAVImin）. The differences in the above parameters between the two groups were compared. Univariate and multivariate Logistic regression analyses were used to analyze the independent influencing factors in HCM patients with HFpEF. The intraclass correlation coefficient was used to test the repeatability of the 4D Auto LAQ parameters.Results:Compared with the non-HF group，LAVmin，LAVmax，LAVpreA，LAVImin，and LAVImax increased，while LAEF，LASr，LAScd，LASct，LASr-c，LAScd-c，and LASct-c decreased in the HFpEF group（all P<0.05）. Multivariate Logistic regression analysis showed that LASr was the strongest independent influencing factor in patients with HCM combined with HFpEF（ OR=0.255， P=0.003）. The consistency test showed that the intraclass correlation coefficients of each parameters of 4D Auto LAQ were all>0.7，the consistency was good. Conclusions:4D Auto LAQ technology can be used to evaluate left atrial function in patients with HCM combined with HFpEF，and LASr is the strongest independent influence factor in patients with HCM combined with HFpEF.

Objective:To analyze the surveillance results of brucellosis in Shanxi Province, to gain a understanding of the epidemic characteristics and changing trend of brucellosis in Shanxi Province, and to provide scientific basis for formulating prevention and control strategies and measures for brucellosis.Methods:The surveillance data of brucellosis in Shanxi Province from Infectious Disease Reporting Information Management System of China Disease Prevention and Control Information System, and the active surveillance results of 5 national brucellosis surveillance sites from 2018 to 2023 were collected for descriptive analysis.Results:From 2018 to 2023, a total of 24 041 cases of human brucellosis were reported in Shanxi Province, with the number of cases increased from 2 800 in 2018 to 5 131 in 2023. The annual reported incidence was 11.22/100 000, ranging from 7.56/100 000 to 14.74/100 000, showing an overall upward trend (χ 2trend = 1 377.43, P < 0.001). The epidemic had affected all counties (cities and districts) in the province, mainly concentrated in Linfen City, Jinzhong City, Datong City, and Shuozhou City, with a total of 13 489 cases of human brucellosis reported, accounting for 56.11%. The population distribution was mainly composed of individuals aged 40 - 69 (17 682 cases), males (18 513 cases), farmers (20 295 cases), and household and unemployed individuals (1 017 cases). The onset of the disease showed obvious seasonality, with the peak time from March to August, accounting for 66.39% (15 961/24 041). A total of 14 130 occupational individuals were investigated at the surveillance sites, and 11 141 underwent serological tests, with a positive rate of 5.25% (585/11 141), including 299 new cases. The positive rate of serological tests was relatively high in Qinyuan County, at 8.51% (241/2 832). Etiological culture was conducted on 338 human blood samples, and 43 strains of Brucella were isolated, with a detection rate of 12.72%. All strains were Brucella melitensis, including 42 strains of Brucella melitensis biovar 3. Conclusions:The overall trend of human brucellosis epidemic in Shanxi Province from 2018 to 2023 is on the rise, and it is still at a high level. It is suggested to continue strengthening monitoring, study the epidemic situation in a timely manner, take comprehensive prevention and control measures, and effectively control the spread of brucellosis.

Shewanella oneidensis MR-1, a Gram-negative bacterium with a significant role in the adsorption and reduction of uranium in wastewater and a quorum-sensing effect, can be used to remove uranium from wastewater. Exogenous signaling molecules (acyl-homoserine lactones, AHLs) can be added to induce the quorum sensing behavior for rapid biofilm formation, thereby improving the removal efficiency of this bacterium for uranium. Extracellular polymeric substances (EPS), as the significant components of biofilm, play a key role in biofilm formation. To investigate the quorum sensing behavior induced by AHLs, we systematically investigated the effects of AHLs on the EPS secretion and biofilm properties of S. oneidensis MR-1 by regulating parameters such as AHL species, concentration, addition time point, and contact time. The results showed that the addition of 10 μmol/L N-butyryl-l-homoserine lactone (C4-HSL) after 6 h of culture and continued incubation to reach the time point of 72 h significantly promoted the secretion of EPSs, in which the content of extracellular proteins and extracellular polysaccharides was increased by 15.2% and 28.2%, respectively, compared with that of the control group. The biofilm electrodes induced by signaling molecules showed superior properties, which were evidenced by an increase of exceeding 20 μm in biofilm thickness, an increase of 33.9% in the proportion of living cells, enhanced electroactivity, and an increase of 10.7% in the uranium removal rate. The biofilm electrode was confirmed to immobilize uranium in wastewater mainly by electrosorption, physicochemical adsorption, and electro-reduction through characterization means such as X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared spectroscopy (FTIR). This study provides a new technical idea for the efficient recovery of uranium in wastewater and enriches the theoretical system of quorum sensing regulation of electroactive biofilms.
Biofilms/drug effects* ; Acyl-Butyrolactones/pharmacology* ; Quorum Sensing/drug effects* ; Uranium/metabolism* ; Shewanella/metabolism* ; Adsorption ; Uranium Compounds/metabolism* ; Wastewater/chemistry* ; Biodegradation, Environmental ; Extracellular Polymeric Substance Matrix/metabolism*

Objective:To evaluate the efficacy of multimodal prehabilitation in patients with refractory functional constipation undergoing Jinling procedure(modified Duhamel surgery).Methods:In this prospective randomized controlled trial,80 patients with refractory functional constipation scheduled for Jinling procedure at the Department of General Surgery,the General Hospital of Eastern Theater Command between January 2020 and December 2021 were enrolled.Participants were randomly assigned to either the observation group(n=40,multimodal prehabilitation)or control group(n=40,routine nursing care).Outcome measures included:time to first flatus,time to first ambulation,defecation volume on postoperative day 5,length of hospitalization,nutritional markers(hemoglobin,albumin,total protein at postoperative day 7),anxiety/depression scores(Hospital Anxiety and Depression Scale,HADS),and total complication rates.Results:Compared to controls,the first ventilation time(48.02±6.15)h,first ambulation time(49.92±5.58)h,defecation volume on the fifth day(234.50±51.03)mL,hospital stay(13.15±2.64)d,anxiety score(43.68±3.45)points,depression score(43.81±1.58)points,and the total incidence of postoperative complications(15%)were significantly lower in the observation group(all p values<0.05).By contrast,the serum levels of hemoglobin(115.60±11.60)g/l,albumin(41.19±5.79)g/L and total protein(61.64±4.94)g/L on day 7 post-operatively were significantly higher in the observation group than those in the control group(P<0.05).Conclusions:Multimodal prehabilitation enhances postoperative intestinal recovery,reduces complications,improves nutritional status,and shortens hospital stays in refractory functional constipation patients undergoing Jinling procedure,supporting its clinical adoption.