By employing the analytic hierarchy process(AHP), the CRITIC method(a weight determination method based on indicator correlations), and the AHP-CRITIC hybrid weighting method, the weight coefficients of evaluation indicators were determined, followed by a comprehensive score comparison. The grey correlation analysis was then performed to analyze the results calculated using the hybrid weighting method. Subsequently, a backpropagation-artificial neural network(BP-ANN) model was constructed to predict the extraction process parameters and optimize the extraction process for Shenxiong Huanglian Jiedu Granules(SHJG). In the extraction process, an L_9(3~4) orthogonal experiment was designed to optimize three factors at three levels, including extraction frequency, water addition amount, and extraction time. The evaluation indicators included geniposide, berberine, ginsenoside Rg_1 + Re, ginsenoside Rb_1, ferulic acid, and extract yield. Finally, the optimal extraction results obtained by the orthogonal experiment, grey correlation analysis, and BP-ANN method were compared, and validation experiments were conducted. The results showed that the optimal extraction process involved two rounds of aqueous extraction, each lasting one hour; the first extraction used ten times the amount of added water, while the second extraction used eight times the amount. In the validation experiments, the average content of each indicator component was higher than the average content obtained in the orthogonal experiment, with a higher comprehensive score. The optimized extraction process parameters were reliable and stable, making them suitable for subsequent preparation process research.
Drugs, Chinese Herbal/analysis* ; Neural Networks, Computer

Traditional Chinese medicine(TCM) decoction pieces are a core carrier for the inheritance and innovation of TCM, and their quality and safety are critical to public health and the sustainable development of the industry. Conventional quality control models, while having established a well-developed system through long-term practice, still face challenges such as relatively long inspection cycles, insufficient objectivity in characterizing complex traits, and urgent needs for improving the efficiency of integrating multidimensional quality information when confronted with the dual demands of large-scale production and precision quality control. With the rapid development of artificial intelligence, machine learning can deeply analyze multidimensional data of the morphology, spectroscopy, and chemical fingerprints of decoction pieces by constructing high-dimensional feature space analysis models, significantly improving the standardization level and decision-making efficiency of quality evaluation. This article reviews the research progress in the application of machine learning in the processing, production, and rapid quality evaluation of TCM decoction pieces. It further analyzes current challenges in technological implementation and proposes potential solutions, offering theoretical and technical references to advance the digital and intelligent transformation of the industry.
Machine Learning ; Drugs, Chinese Herbal/standards* ; Quality Control ; Medicine, Chinese Traditional/standards* ; Humans

Diabetic foot (DF) is one of the most serious chronic complications of diabetes. The incidence rate among global diabetes patients is as high as 15% to 25%, and about 50% of patients will develop contralateral foot ulcers within 5 years after the first unilateral ulcer. As a non-invasive prevention and control solution, the application progress of functional insoles is mainly reflected in the following aspects:(1) Material innovation. The application of new composite materials and smart materials has significantly enhanced the pressure reduction effect and comfort. (2) Structural optimization. The development of multi-layer design and local pressure reduction structure has achieved more precise pressure distribution regulation. (3) Manufacturing process. 3D printing and parametric design have enabled the personalized customization of functional insoles. (4) Intelligent monitoring. It integrates functions such as pressure sensing and temperature monitoring, achieving real-time monitoring and early warning of foot conditions. Clinical research has confirmed that personalized functional insoles could reduce the incidence of foot ulcers and shorten the healing time of ulcers. At present, the research hotspots mainly focus on the development of smart materials, the construction of multi-functional integration and remote monitoring systems. However, in-depth research is still needed in the aspects of biomechanical mechanisms, standardized evaluation systems and long-term efficacy assessment. The development of future functional insoles should focus on the coordinated advancement of "personalization-intelligence-standardization", with the aim of providing more effective solutions for the prevention and treatment of DF.
Humans ; Diabetic Foot/therapy* ; Foot Orthoses

OBJECTIVE: To construct a prediction model for fracture reduction fixator therapy using the multi-modal multi-label classification (MMC) method. METHODS: Medical record data of 818 orthopedic patients from 2019 to 2023 were collected. Medical image features were extracted using the VGG19 network, text features of TCM four diagnostic methods (Inspection, Auscultation & Olfaction, Inquiry, Palpation) were extracted via the MiniLM model, and clinical case features were extracted through a fully connected neural network. After fusing the multi-modal information, multi-label therapy prediction was achieved using a linear layer. RESULTS: Experimental results on the clinical multi-modal dataset showed that the MMC method performed excellently in terms of subset accuracy(SA), accuracy(Acc), precision, and F₁-score, reaching 0.661, 0.856, 0.897, and 0.899 respectively. When the image modality and text modality were removed, the model performance decreased by an average of 8.1% and 2.4% respectively, while the hamming loss(HL) increased by 21.1% and 5.6% respectively. CONCLUSION The fracture reduction fixator therapy prediction model constructed in this study can effectively fuse multi-modal data, accurately predict personalized treatment plans for patients, and significantly improve the accuracy and reliability of treatment decisions. It provides a new solution for the digitalization and intellectualization of Traditional Chinese Medicine(TCM) in fracture treatment and has important clinical application prospects.
Humans ; Female ; Male ; Middle Aged ; Fracture Fixation/methods* ; Adult ; Fractures, Bone/surgery* ; Neural Networks, Computer ; Medicine, Chinese Traditional ; Aged

OBJECTIVES: To analyze the clinical characteristics of diffuse panbronchiolitis (DPB) in children and to enhance the clinical diagnosis and treatment of this disease. METHODS: A retrospective analysis was conducted on the clinical data of 6 children diagnosed with DPB who were hospitalized at The First Affiliated Hospital of Guangzhou Medical University from January 2011 to December 2019. RESULTS: Among the 6 patients, there were 2 males and 4 females; the age at diagnosis ranged from 7 to 12 years. All patients presented with cough, sputum production, and exertional dyspnea, and all had a history of sinusitis. Two cases showed positive serum cold agglutinin tests, and 5 cases exhibited pathological changes consistent with chronic bronchiolitis. High-resolution chest CT in all patients revealed centrilobular nodules diffusely distributed throughout both lungs with a tree-in-bud appearance. Five patients received low-dose azithromycin maintenance therapy, but 3 showed inadequate treatment response. After empirical anti-tuberculosis treatment, non-tuberculous Mycobacteria were found in the bronchoalveolar lavage fluid. Follow-up over 2 years showed 1 case cured, 3 cases significantly improved, and 2 cases partially improved. CONCLUSIONS The clinical presentation of DPB is non-specific and can easily lead to misdiagnosis. In cases where DPB is clinically diagnosed but does not show improvement with low-dose azithromycin treatment, special infections should be considered.
Humans ; Male ; Female ; Bronchiolitis/drug therapy* ; Retrospective Studies ; Child ; Haemophilus Infections/diagnosis*

OBJECTIVES: To investigate the clinical features of children with STAT gene mutations, and to explore corresponding immunotherapy strategies. METHODS: A retrospective analysis was performed for the clinical data of 10 children with STAT gene mutations who were admitted to the Department of Pediatrics of the First Affiliated Hospital of Guangzhou Medical University, from October 2015 to October 2024. Exploratory immunotherapy was implemented in some refractory cases, and the changes in symptoms, imaging manifestations, and cytokine levels were assessed after treatment. RESULTS: For the 10 children, the main clinical manifestations were recurrent rash since birth (7/10), cough (8/10), wheezing (5/10), expectoration (4/10), and purulent nasal discharge (4/10). Genotyping results showed that there was one child with heterozygous loss-of-function (LOF) mutation in the STAT1 gene, four children with heterozygous LOF mutation in the STAT3 gene, and five children with heterozygous gain-of-function (GOF) mutation in the STAT3 gene. Two children with LOF mutation in the STAT3 gene showed decreased interleukin-6 levels and improved clinical symptoms and imaging findings after omalizumab treatment. Three children with GOF mutation in the STAT3 gene achieved effective disease control after treatment with methylprednisolone (0.5 mg/kg per day). Two children with GOF mutation in the STAT3 gene received treatment with JAK inhibitor and then showed some improvement in symptoms. CONCLUSIONS STAT gene mutation screening should be considered for children with recurrent rash and purulent respiratory tract infections. Targeted immunotherapy may improve prognosis in patients with no response to conventional treatment.
Humans ; Male ; Immunotherapy ; Female ; Child, Preschool ; Child ; Gain of Function Mutation ; Retrospective Studies ; Infant ; Loss of Function Mutation ; STAT Transcription Factors/genetics*

OBJECTIVE: To investigate the effects of low-dose irradiated autologous peripheral blood reinfusion (LDIAPBR) on a rat model of radiation-induced leukopenia. METHODS: The rats were randomly divided into four groups. In the LDIAPBR group, LDIAPBR was performed 1 day before modeling (10% of the total circulating blood volume was withdrawn, irradiated with 100 mGy ex vivo, and completely reinfused). Meanwhile, the normal group and model group only underwent blood withdrawal and reinfusion of the same proportion without blood irradiation. Except for the normal group, all groups were subjected to 1 Gy X-ray whole-body irradiation to establish a radiation-induced leukopenia rat model. The positive drug group received subcutaneous injection of rhG-CSF after modeling. It was monitored that the general condition of the rats, peripheral blood cell counts, immune organ indices, bone marrow nucleated cell counts and viability, and the pathological analysis of bone marrow sections was conducted. RESULTS: The LDIAPBR group exhibited significant improvements in overall condition compared to the model group. Notably, compared with the model group, peripheral blood leukocyte and lymphocyte counts were markedly higher in the LDIAPBR group. Furthermore, there was a significant increase in both the number and viability of nucleated cells in the bone marrow. Pathological examination of bone marrow sections revealed increased nucleated cell density and reduced cavity area in the LDIAPBR group. CONCLUSION LDIAPBR can effectively improve hematological parameters and bone marrow hematopoietic function in a rat model of radiation-induced leukopenia, providing a new approach for the prevention and treatment of radiation-related injuries.
Animals ; Leukopenia/prevention & control* ; Rats ; Blood Transfusion, Autologous ; Whole-Body Irradiation ; Radiation Injuries, Experimental/therapy*

OBJECTIVE: To explore the expression regulation of lipid metabolism gene ABHD5 in testes. METHODS: Differential gene analysis was performed by integrating databases of TCGA and GTEx to identify the target gene ABHD5. The expression trends of ABHD5 gene in testicular carcinoma tissue were analyzed. Human testis single-cell atlases were obtained from the Human Protein Atlas and Male Health Atlas databases to determine the expression distribution of ABHD5 across different testicular cell types. Additionally, the GTEx database was utilized to visualize the expression pattern of ABHD5 in the testis, thereby enhancing the understanding of its transcriptional profile. The relationship between ABHD5 expression and age was assessed through integrated database analysis. Western blotting and immunofluorescence were performed to detect differential expressions of ABHD5 in testicular tissues of young and aged mice respectively. RESULTS: The TCGA database indicated that the expression of ABHD5 in human testicular carcinoma tissue was significantly lower than that in normal testicular tissue which showed a negative correlation with patient survival. ABHD5 was highly expressed in germ cells of the testis reveaked from Human Protein Atlas and Male Health Atlas databases. The stability of ABHD5 protein was crucial for testicular tissue, and its expression decreased with age. Furthermore, Western blot and immunofluorescence staining demonstrated that ABHD5 expression in the testicular tissue of aged mice was significantly lower than that in young mice. CONCLUSION ABHD5 plays an important role in testicular tissue, and may be inseparable from testicular tumors and reproductive aging. However, its mechanism of action remains to be further studied.
Male ; Animals ; Mice ; Testis/metabolism* ; Humans ; Lipid Metabolism/genetics* ; 1-Acylglycerol-3-Phosphate O-Acyltransferase/metabolism* ; Testicular Neoplasms/metabolism*

BACKGROUND: Atrial fibrillation (AF) is a common cardiac arrhythmia in the elderly. This study aimed to evaluate urban-rural disparities in its prevalence and management in elderly Chinese. METHODS: Consecutive participants aged ≥ 65 years attending outpatient clinics were enrolled for AF screening using handheld single-lead electrocardiogram (ECG) from April 2017 to December 2022. Each ECG rhythm strip was reviewed from the research team. AF or uninterpretable single-lead ECGs were referred for 12-lead ECG. Primary study outcome comparison was between rural and urban areas for the prevalence of AF. The Student's t-test was used to compare mean values of clinical characteristics between rural and urban participants, while the Pearson's chi-square test was used to compare between-group proportions. Multivariate stepwise logistic regression analysis was performed to estimate the association between AF and various patient characteristics. RESULTS: The 29,166 study participants included 13,253 men (45.4%) and had a mean age of 72.2 years. The 7073 rural participants differed significantly (P ≤ 0.02) from the 22,093 urban participants in several major characteristics, such as older age, greater body mass index, and so on. The overall prevalence of AF was 4.6% (n = 1347). AF was more prevalent in 7073 rural participants than 22,093 urban participants (5.6% vs. 4.3%, P < 0.01), before and after adjustment for age, body mass index, blood pressure, pulse rate, cigarette smoking, alcohol consumption and prior medical history. Multivariate logistic regression analysis identified overweight/obesity (OR = 1.35, 95% CI: 1.17-1.54) in urban areas and cigarette smoking (OR = 1.62, 95% CI: 1.20-2.17) and alcohol consumption (OR = 1.42, 95% CI: 1.04-1.93) in rural areas as specific risk factors for prevalent AF. In patients with known AF in urban areas (n = 781) and rural areas (n = 338), 60.6% and 45.9%, respectively, received AF treatment (P < 0.01), and only 22.4% and 17.2%, respectively, received anticoagulation therapy (P = 0.05). CONCLUSIONS In China, there are urban-rural disparities in AF in the elderly, with a higher prevalence and worse management in rural areas than urban areas. Our study findings provide insight for health policymakers to consider urban-rural disparity in the prevention and treatment of AF.

BACKGROUND: Non-invasive computed tomography angiography (CTA)-based fractional flow reserve (CT-FFR) could become a gatekeeper to invasive coronary angiography. Deep learning (DL)-based CT-FFR has shown promise when compared to invasive FFR. To evaluate the performance of a DL-based CT-FFR technique, DeepVessel FFR (DVFFR). METHODS: This retrospective study was designed for iScheMia Assessment based on a Retrospective, single-center Trial of CT-FFR (SMART). Patients suspected of stable coronary artery disease (CAD) and undergoing both CTA and invasive FFR examinations were consecutively selected from the Beijing Anzhen Hospital between January 1, 2016 to December 30, 2018. FFR obtained during invasive coronary angiography was used as the reference standard. DVFFR was calculated blindly using a DL-based CT-FFR approach that utilized the complete tree structure of the coronary arteries. RESULTS: Three hundred and thirty nine patients (60.5 ±10.0 years and 209 men) and 414 vessels with direct invasive FFR were included in the analysis. At per-vessel level, sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of DVFFR were 94.7%, 88.6%, 90.8%, 82.7%, and 96.7%, respectively. The area under the receiver operating characteristics curve (AUC) was 0.95 for DVFFR and 0.56 for CTA-based assessment with a significant difference (P < 0.0001). At patient level, sensitivity, specificity, accuracy, PPV and NPV of DVFFR were 93.8%, 88.0%, 90.3%, 83.0%, and 95.8%, respectively. The computation for DVFFR was fast with the average time of 22.5 ± 1.9 s. CONCLUSIONS The results demonstrate that DVFFR was able to evaluate lesion hemodynamic significance accurately and effectively with improved diagnostic performance over CTA alone. Coronary artery disease (CAD) is a critical disease in which coronary artery luminal narrowing may result in myocardial ischemia. Early and effective assessment of myocardial ischemia is essential for optimal treatment planning so as to improve the quality of life and reduce medical costs.