The principle of treating different diseases with the same therapy is the essence of syndrome differentiation and treatment in traditional Chinese medicine （TCM）. It means that when the same pathogenic changes or the same symptoms appear in the development of different diseases， the same principles or methods can be used for treatment. Due to the complexity and high variability of viral pathogenicity， the precise and effective treatment of different types of viral pneumonia （VP） has always been a research focus and difficulty in modern medicine. VP belongs to the category of external-contraction febrile disease， warm disease， and epidemic in TCM. Haoqin Qingdantang （HQQDD） is a representative formula for clearing heat and dispelling dampness in warm diseases， and its intervention in VP caused by various viral infections has significant effects. This study， guided by the theory of treating different diseases with the same therapy， links the related studies on using HQQDD to treat different types of VP and finds that influenza virus pneumonia （IVP）， severe acute respiratory syndrome （SARS）， and COVID-19 all have a common pathogenic mechanism of dampness-heat at different stages of respective diseases. When these diseases are dominated by damp-heat factors， the use of HQQDD yields remarkable therapeutic effects. Modern pharmacological studies have confirmed that HQQDD can inhibit virus replication， reduce fever reactions， inhibit the expression of inflammatory mediators， and regulate immune balance. Moreover， the sovereign medicine in this formula has excellent antiviral activity， and the formula reflects rich scientific connotations of treating VP. According to the theory of treating different diseases with the same therapy and based on the effective treatment practice and modern pharmacological research of HQQDD for different types of VP， this paper mines the underlying TCM theory of treatment with the same therapy， explores the syndrome differentiation and treatment strategy and effect mechanism of this formula for different types of VP， and analyzes the treatment mechanism and characteristics， with the aim of providing evidence and reference for the clinical application and modern research of HQQDD.

Pneumonia is an infectious disease with high morbidity and mortality worldwide， and its damage to the body is not limited to the acute phase. The theory of combination of pathogenic factors emphasizes that the combination of new pathogens and residual pathogens in the body leads to the occurrence of diseases， which generalizes the causes of recurrence during pneumonia recovery. During the recovery stage of pneumonia， pathological changes such as disturbance of immune homeostasis， persistent low-grade inflammation， and microvascular damage continue to affect the body function， impair the health and quality of life of patients， and increase the risk of secondary infection. According to the theory of traditional Chinese medicine （TCM）， pneumonia is caused by deficiency， and Qi deficiency and blood stasis is the core pathogenesis in the recovery stage. At this time， the body is not full of healthy qi and still has residual pathogens， and thus it is susceptible to external pathogenic factors that lead to disease recurrence. As an important part of the TCM philosophy of treating disease before its onset， prevention of recurrence after recovery emphasizes the need for aftercare in the recovery stage to prevent disease recurrence. Based on the pathogenesis theory of combination of pathogenic factors and the pathogenesis of Qi deficiency and blood stasis， this paper discusses the effect and connotation of TCM in regulating immune inflammation and microvascular damage in preventing recurrence of pneumonia during the recovery stage， aiming to develop new ideas for effective prevention and treatment of pneumonia at this stage.

Objective To evaluate the performance of the artificial intelligence (AI)-enabled snail identification system for recognition of Oncomelania hupensis robertsoni and Tricula in schistosomiasis-endemic areas of Yunnan Province. Methods Fifty O. hupensis robertsoni and 50 Tricula samples were collected from Yongbei Township, Yongsheng County, Lijiang City, a schistosomiasis-endemic area in Yunnan Province in May 2024. A total of 100 snail sample images were captured with smartphones, including front-view images of 25 O. hupensis robertsoni and 25 Tricula samples (upward shell opening) and back-view images of 25 O. hupensis robertsoni and 25 Tricula samples (downward shell opening). Snail samples were identified as O. hupensis robertsoni or Tricula by schistosomiasis control experts with a deputy senior professional title and above according to image quality and morphological characteristics. A standard dataset for snail image classification was created, and served as a gold standard for recognition of snail samples. A total of 100 snail sample images were recognized with the AI-enabled intelligent snail identification system based on a WeChat mini program in smartphones. Schistosomiasis control professionals were randomly sampled from stations of schistosomisis prevention and control and centers for disease control and prevention in 18 schistosomiasis-endemic counties (districts, cities) of Yunnan Province, for artificial identification of 100 snail sample images. All professionals are assigned to two groups according the median years of snail survey experiences, and the effect of years of snail survey experiences on O. hupensis robertsoni sample image recognition was evaluated. A receiver operating characteristic (ROC) curve was plotted, and the sensitivity, specificity, accuracy, Youden’s index and the area under the curve (AUC) of the AI-enabled intelligent snail identification system and artificial identification were calculated for recognition of snail sample images. The snail sample image recognition results of AI-enabled intelligent snail identification system and artificial identification were compared with the gold standard, and the internal consistency of artificial identification results was evaluated with the Cronbach’s coefficient alpha. Results A total of 54 schistosomiasis control professionals were sampled for artificial identification of snail sample image recognition, with a response rate of 100% (54/54), and the accuracy, sensitivity, specificity, Youden’s index, and AUC of artificial identification were 90%, 86%, 94%, 0.80 and 0.90 for recognition of snail sample images, respectively. The overall Cronbach’s coefficient alpha of artificial identification was 0.768 for recognition of snail sample images, and the Cronbach’s coefficient alpha was 0.916 for recognition of O. hupensis robertsoni snail sample images and 0.925 for recognition of Tricula snail sample images. The overall accuracy of artificial identification was 90% for recognition of snail sample images, and there was no significant difference in the accuracy of artificial identification for recognition of O. hupensis robertsoni (86%) and Tricula snail sample images (94%) (χ² = 1.778, P > 0.05). There was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (88%) and downward shell openings (92%) (χ² = 0.444, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less (75%) and more than 6 years (90%) (χ² = 7.792, P < 0.05). The accuracy, sensitivity, specificity and AUC of the AI-enabled intelligent snail identification system were 88%, 100%, 76% and 0.88 for recognition of O. hupensis robertsoni snail sample images, and there was no significant difference in the accuracy of recognition of O. hupensis robertsoni snail sample images between the AI-enabled intelligent snail identification system and artificial identification (χ² = 0.204, P > 0.05). In addition, there was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (90%) and downward shell openings (86%) (χ² = 0.379, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less and more than 6 years (χ² = 5.604, P_adjusted < 0.025). Conclusions The accuracy of recognition of snail sample images is comparable between the AI-enabled intelligent snail identification system and artificial identification by schistosomiasis control professionals, and the AI-enabled intelligent snail identification system is feasible for recognition of O. hupensis robertsoni and Tricula in Yunnan Province.

Purpose: Human epidermal growth factor receptor 2 (HER2)-low breast cancer has the potential to emerge as a distinct subtype. Several studies have compared the differences between HER2-low and HER2-0 breast cancers, but no consensus has been reached.Additionally, a biomarker to predict pathological complete response (pCR) rates in patients with HER2-low breast cancer remains to be identified. Methods: We collected data from 777 patients across three centers, stratifying them into HER2-low and HER2-0 groups. We compared differences in survival and pCR rates between the two groups and investigated potential biomarkers that could reliably predict pCR. Results: The study found that patients with HER2-0 breast cancer had higher pCR rates compared to patients with HER2-low tumors (289 patients [30.1%] vs. 475 patients [18.1%], p < 0.0001). Survival analysis showed no significant advantage for HER2-low tumors over HER2-0 breast cancers. Binary logistic analysis revealed that androgen receptor (AR) expression predicts poorer pCR rates in both the overall patient group and the HER2-0 breast cancer group (overall patients: odds ratio [OR], 0.479; 95% confidence interval [CI], 0.250–0.917; p = 0.026 and HER2-0 patients: OR, 0.267; 95% CI, 0.080–0.892; p = 0.032). In contrast, programmed death ligand 1 (PD-L1) expression was associated with more favorable pCR rates in the overall patient group (OR, 3.199; 95% CI, 1.020–10.037; p = 0.046). Conclusion There is currently insufficient evidence to classify HER2-low breast cancer as a distinct subtype. Our study revealed that AR expression, along with negative PD-L1 expression, contributes to lower pCR rates.

Purpose: Human epidermal growth factor receptor 2 (HER2)-low breast cancer has the potential to emerge as a distinct subtype. Several studies have compared the differences between HER2-low and HER2-0 breast cancers, but no consensus has been reached.Additionally, a biomarker to predict pathological complete response (pCR) rates in patients with HER2-low breast cancer remains to be identified. Methods: We collected data from 777 patients across three centers, stratifying them into HER2-low and HER2-0 groups. We compared differences in survival and pCR rates between the two groups and investigated potential biomarkers that could reliably predict pCR. Results: The study found that patients with HER2-0 breast cancer had higher pCR rates compared to patients with HER2-low tumors (289 patients [30.1%] vs. 475 patients [18.1%], p < 0.0001). Survival analysis showed no significant advantage for HER2-low tumors over HER2-0 breast cancers. Binary logistic analysis revealed that androgen receptor (AR) expression predicts poorer pCR rates in both the overall patient group and the HER2-0 breast cancer group (overall patients: odds ratio [OR], 0.479; 95% confidence interval [CI], 0.250–0.917; p = 0.026 and HER2-0 patients: OR, 0.267; 95% CI, 0.080–0.892; p = 0.032). In contrast, programmed death ligand 1 (PD-L1) expression was associated with more favorable pCR rates in the overall patient group (OR, 3.199; 95% CI, 1.020–10.037; p = 0.046). Conclusion There is currently insufficient evidence to classify HER2-low breast cancer as a distinct subtype. Our study revealed that AR expression, along with negative PD-L1 expression, contributes to lower pCR rates.

OBJECTIVE: To explore the effect of bear bile powder (BBP) on acute lung injury (ALI) and the underlying mechanism. METHODS: The chemical constituents of BBP were analyzed by ultra-high-pressure liquid chromatography-mass spectrometry (UPLC-MS). After 7 days of adaptive feeding, 50 mice were randomly divided into 5 groups by a random number table (n=10): normal control (NC), lipopolysaccharide (LPS), dexamethasone (Dex), low-, and high-dose BBP groups. The dosing cycle was 9 days. On the 12th and 14th days, 20 µL of Staphylococcus aureus solution (bacterial concentration of 1 × 10^-7 CFU/mL) was given by nasal drip after 1 h of intragastric administration, and the mice in the NC group was given the same dose of phosphated buffered saline (PBS) solution. On the 16th day, after 1 h intragastric administration, 100 µL of LPS solution (1 mg/mL) was given by tracheal intubation, and the same dose of PBS solution was given to the NC group. Lung tissue was obtained to measure the myeloperoxidase (MPO) activity, the lung wet/dry weight ratio and expressions of CD14 and other related proteins. The lower lobe of the right lung was obtained for pathological examination. The concentrations of inflammatory cytokines including interleukin (IL)-6, tumour necrosis factor α (TNF-α ) and IL-1β in the bronchoalveolar lavage fluid (BALF) were detected by enzyme linked immunosorbent assay, and the number of neutrophils was counted. The colonic contents of the mice were analyzed by 16 sRNA technique and the contents of short-chain fatty acids (SCFAs) were measured by gas chromatograph-mass spectrometer (GC-MS). RESULTS: UPLC-MS revealed that the chemical components of BBP samples were mainly tauroursodeoxycholic acid and taurochenodeoxycholic acid sodium salt. BBP reduced the activity of MPO, concentrations of inflammatory cytokines, and inhibited the expression of CD14 protein, thus suppressing the activation of NF-κB pathway (P<0.05). The lung histopathological results indicated that BBP significantly reduced the degree of neutrophil infiltration, cell shedding, necrosis, and alveolar cavity depression. Moreover, BBP effectively regulated the composition of the intestinal microflora and increased the production of SCFAs, which contributed to its treatment effect (P<0.05). CONCLUSIONS BBP alleviates lung injury in ALI mouse through inhibiting activation of NF-κB pathway and decreasing expression of CD14 protein. BBP may promote recovery of ALI by improving the structure of intestinal flora and enhancing metabolic function of intestinal flora.
Animals ; Acute Lung Injury/pathology* ; Lipopolysaccharides ; Ursidae ; Gastrointestinal Microbiome/drug effects* ; Bile/chemistry* ; Lipopolysaccharide Receptors/metabolism* ; Powders ; Male ; Lung/drug effects* ; Mice ; Peroxidase/metabolism* ; Signal Transduction/drug effects* ; Cytokines/metabolism*

Senecavirus A (SVA) is a major viral pathogen causing disease in pigs, and effective monitoring of SVA infection is critical for disease control. In this study, we aimed to develop a reliable ELISA method for rapidly detecting neutralizing antibodies against SVA. We used HEK293F cells to express an SVA-specific porcine Fab antibody and verified the biological activity of the Fab antibody by indirect ELISA, immunofluorescence assay, virus neutralization test, and Western blotting. The Fab antibody was biotinylated and used as a competitive antibody to establish a competitive ELISA (C-ELISA) for detecting neutralizing antibodies against SVA. We then evaluated the C-ELISA in terms of sensitivity, specificity, repeatability, and result agreement rate with the VNT. The results showed that we successfully prepared an SVA-specific porcine Fab antibody, which showed high affinity for SVA. We named this antibody 1M33Fab and designated it as Bio-1M33Fab after biotin labeling. The assay conditions were optimized as follows: the coating concentration of SVA particles being 1 μg/mL, the working concentration of Bio-1M33Fab being 0.5 μg/mL, the optimal serum dilution of 1:10, and the optimal dilution of enzyme-labeled avidin being 1:30 000. At a percent inhibition (PI) of 47%, the assay demonstrated the highest sensitivity (96.88%) and specificity (100%), with no cross-reactivity observed with the positive sera of major porcine viral diseases. The intra-assay coefficient of variation ranged from 1.12% to 7.34%, while the inter-assay coefficient of variation ranged from 1.10% to 8.97%, indicating good repeatability. In the detection of 224 clinical pig serum samples, C-ELISA and VNT showed a result agreement rate of 93.75%. In conclusion, we successfully develop a C-ELISA method for detecting neutralizing antibodies against SVA by using a porcine-derived Fab antibody, which lays a foundation for the development of detection kits.
Animals ; Swine ; Antibodies, Neutralizing/immunology* ; Enzyme-Linked Immunosorbent Assay/methods* ; Immunoglobulin Fab Fragments/immunology* ; Antibodies, Viral/immunology* ; Picornaviridae/immunology* ; Humans ; HEK293 Cells ; Swine Diseases/diagnosis* ; Picornaviridae Infections/diagnosis*

Chronic heart failure （CHF）， as the terminal stage of various cardiovascular diseases， is characterized by a prolonged clinical course and recurrent exacerbations. The coexistence of CHF with anxiety and depression falls under the category of psycho-cardiological diseases. Studies have demonstrated that anxiety and depression are closely associated with adverse outcomes including elevated risks of cardiovascular events and increased mortality in CHF patients. The complex pathogenesis poses challenges to modern medical treatments， which often face limited efficacy and concurrent side effects. According to the theory of Shaoyang Pivot in traditional Chinese medicine （TCM）， this paper elucidates that obstructed Shaoyang Pivot—manifested as Qi transformation disorder， dysregulated fluid metabolism， and abnormal distribution of ministerial fire-serves as a critical pathological basis for CHF with anxiety and depression. Bupleuri Radix-based Formulas， such as Xiao Chaihu Tang， Chaihu Guizhi Tang， and Chaihu Jia Longgu Muli Tang， aim to harmonize lesser Yang to restore the Qi transformation， activate Yang to promote water excretion， and redistribute ministerial fire， thus effectively alleviating pathological states such as Qi stagnation， blood stasis， water retention， and phlegm-fire disturbing the heart in CHF patients with anxiety and depression. Consequently， they mitigate symptoms of this psycho-cardiological disease. Mechanism studies have revealed that Bupleuri Radix-based formulas exhibit multi-target effects， including modulation of neurotransmitters， suppression of inflammatory responses， regulation of lipid metabolism， protection of cardiomyocytes， and improvement of the endothelial function. By interpreting the TCM pathogenesis of CHF with anxiety and depression from the theory of Shaoyang Pivot， this paper delves into the therapeutic principles and mechanisms of Bupleuri Radix-based formulas， providing a theoretical foundation for optimizing TCM diagnosis and treatment strategies for psycho-cardiological diseases.

Objective To construct a model combining with traditional Chinese medicine(TCM)syndrome for predicting the risk of disease progression in patients with idiopathic membranous nephropathy(IMN)by machine learning methods,thus to quantitatively evaluating the value of TCM syndrome in the prediction of the risk of disease progression in IMN.Methods Monofactor analysis,recursive feature elimination(RFE)and multivariate binary Logistic regression analysis were used to screen the independent related factors affecting the risk of disease progression of IMN,and then a risk prediction model was constructed.A total of 102 patients with IMN were randomly assigned to the training set and the test set in a ratio of 65∶35,and then the comparison was conducted in the performance indicators of accuracy,sensitivity,specificity,F1 value,and area under the receiver operating characteristic(ROC)area under the curve(AUC)of the risk prediction model with or without the inclusion of the TCM syndrome information.Results Before the inclusion of TCM syndrome information,12 clinical characteristic variables for patients with MN were obtained after monofactor analysis combined with RFE screening,and they were age,hemoglobin quantification,urinary occult blood,24-hour urine protein quantification,urine protein-creatinine ratio,estimated glomerular filtration rate(eGFR),creatinine,uric acid,alanine transaminase,anti-phospholipase A2 receptor antibody(PLA2R-Ab),total cholesterol,and low-density lipoprotein cholesterd.A risk cholesterol prediction model containing the above variables was constructed.The multivariate binary Logistic regression analysis showed that the differences of the clinical variables mentioned above between the training-set group and test-set group were statistically significant,and the risk prediction model presented good sensitivity and predictability.Monofactor analysis combined with RFE screening was performed again after the inclusion of TCM syndrome information,and then 14 variables were obtained,which included blood stasis syndrome and dampness obstruction syndrome.The sensitivity and specificity of the model with the inclusion of the TCM syndrome information were significantly improved when compared with those without the inclusion of TCM syndrome information.Conclusion The results of the study initially indicate that TCM syndrome can be used as an important supplementary variable for predicting the risk of disease progression in IMN,and will provide a reference for intelligent diagnosis through the integration of traditional Chinese and western medicine information,and will supply the guidance for the treatment of IMN with TCM.

Objective To analyze the risk factors associated with central nervous system(CNS)infection in patients after neuroendoscopic hematoma removal combined with and microscopic hematoma removal,and to construct and validate a nomogram prediction model.Methods A total of 460 patients who underwent neuroendoscopic hematoma removal combined with microscopic hematoma removal at our hospital between January 2021 and December 2024 were retrospectively enrolled.The patients were assigned to a modeling cohort(n=322)and a validation cohort(n=138)in a 7∶3 ratio.Furthermore,the modeling cohort was divided into an infection group(n=68)and a non-infected group(n=254)according to whether CNS infection occurred.The independent predictors of central nervous system infection were identified by logistic regression analysis,and a nomogram prediction model was constructed accordingly.Results The overall incidence of CNS infection in the 460 patients was 20.65%(95/460).According to the logistic regression analysis,the independent risk factors for CNS infection in patients after neuroendoscopic and microscopic combined hematoma removal included a history of diabetes mellitus(odds ratio[OR]=3.431,95%CI:1.300-9.057),the Glasgow Coma Scale(GCS)score(OR=0.574,95%CI:0.462-0.711),cerebrospinal fluid leakage(OR=4.492,95%CI:1.430-14.116),operation duration(OR=1.011,95%CI:1.004-1.019),duration of drainage tube placement(OR=5.452,95%CI:2.423-12.268)and albumin(ALB)level(OR=0.778,95%CI:0.720-0.840)(P<0.05).Based on these risk factors,a nomogram prediction model was constructed,and the area under the receiver operating characteristic curve(AUC)of the predicted events in the modeling cohort and the validation cohort was 0.928(95%CI:0.895-0.960)and 0.918(95%CI:0.885-0.951),respectively.The calibration curve fitted well with the ideal curve(Hosmer-Lemeshow test,P>0.05),and the decision curve analysis demonstrated significant net benefit.Conclusion The nomogram model based on history of diabetes mellitus,GCS score,cerebrospinal fluid leakage,operation duration,duration of drainage tube placement,and ALB level demonstrates high predictive performance for CNS infection after neuroendoscopy-assisted microscopic hematoma removal.