Objective: To establish a progressive research strategy for “colonic components analysis - efficacy verification and mechanism exploration - gut microbiota”, screen pharmacodynamic substances, and investigate their mechanism via gut microbiota. Methods: The pharmacodynamics of Gegen Qinlian decoction (GQD) were assessed using a mouse model of dextran sulfate sodium-induced ulcerative colitis (UC). Ultra-performance liquid chromatography-quadrupole-orbitrap mass spectrometer was used to identify the prototype and metabolic components of GQD in the colon during UC. To analyze the structure and function of characteristic genera of GQD and its active components, 16S rRNA sequencing was performed. Results: We identified 67 prototypic and 14 metabolic components of GQD in the UC colon. The primary prototype components are flavonoids and alkaloids, including puerarin (PUE), baicalin (BAI), and berberine (BER). The metabolism was predominantly sulfonation. Efficacy verification showed that the main active components, puerarin, baicalin, and berberine, had good therapeutic effects on UC. The results of 16S rRNA gene sequencing showed that GQD improved UC by regulating the structure and function of the gut microbiota. The abundance of gut microbiota involved in the metabolism of the prototype components was influenced by the corresponding components. The function prediction results showed that PUE was the most comparable to GQD, with 24 consistent pathways. BAI and BER showed comparable gut microbiota regulation pathways. Characteristic pathways of BER include glucometabolic processes. Conclusion This study focused on the key issues in the gut microbiota pathway and developed a progressive research strategy to understand the transformation mechanisms of colonic components. This research systematically analyzed the active components and metabolic transformation of GQD in the colon during the pathological state of UC, as well as changes in the structure and function of the gut microbiota, clarified the mechanism of GQD and its active components in improving UC via the gut microbiota pathway.

Objective To study the changes and mechanism of skin stem cells in microgravity.Methods The skin stem cells of SD rats were used to establish a suspension culture system and compare the proliferation of skin stem cells with 1G gravity.Results The simulated microgravity significantly affected the velocity of skin stem cell sphere proliferation in suspension culture,which was about 12%higher than the 1G gravity group.Transcriptome sequencing showed that 1673 genes were up-regulated and 1409 genes were downregulated;Calcium signaling;cytokine-cytokine receptor interaction and PPAR pathway were different in the two environments.Conclusion Simulation of microgravity can affect the proliferation behavior of skin stem cells in suspension culture by regulating the expression of key signaling pathways,which provides an experimental basis for further research in spatial microgravity environ ment.

Objective:This study aims to explore the predictive value of T2-weighted imaging (T2WI), apparent diffusion coefficient (ADC), and early-delayed phases enhanced magnetic resonance imaging (DCE-MRI) radiomics prediction model in determining human epidermal growth factor receptor 2 status in breast cancer.Methods:A retrospective study was conducted, involving 187 patients with confirmed breast cancer by postsurgical pathology at Zhenjiang First People's Hospital during January 2021 and May 2023. Immunohistochemistry or fluorescence in situ hybridization was used to determine the HER-2 status of these patients, with 48 cases classified as HER-2 positive and 139 cases as HER-2 negative. The training set was used to construct the prediction models and the validation set was used to verify the prediction models. Layers of T2WI, ADC, and early-delayed phase DCE-MRI images were used to delineate the volumeof interest and 960 radiomic features were extracted from each case using Pyradiomic. After screening and dimensionality reduction by intraclass correlation coefficient, Pearson correlation analysis, least absolute shrinkage, and selection operator, the radiomics labels were established. Logistic regression analysis was used to construct the T2WI radiomics model, ADC radiomics model, DCE-2 radiomics model, DCE-6 radiomics model, and the joint sequence radiomics model to predict the HER-2 expression status of breast cancer, respectively. Based on the clinical, pathological, and MRI image characteristics of patients, univariate and multivariate logistic regression analysis wasused to construct a clinicopathological MRI feature model. The radscore of every patient and the clinicopathological MRI features which were statistically significant after screening were used to construct a nomogram model. The receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of each model and the decision curve analysis wasused to evaluate the clinical usefulness.Results:The T2WI, ADC, DCE-2, DCE-6, and joint sequence radiomics models, the clinicopathological MRI feature model, and the nomogram model were successfully constructed to predict the expression status of HER-2 in breast cancer. ROC analysis showed that in the training set and validation set, the areas under the curve (AUC) of the T2WI radiomics model were 0.797 and 0.760, of the ADC radiomics model were 0.776 and 0.634, of the DCE-2 radiomics model were 0.804 and 0.759, of the DCE-6 radiomics model were 0.869 and 0.798, of the combined sequence radiomics model were 0.908 and 0.847, of the clinicopathological MRI feature model were 0.703 and 0.693, and of the nomogram model were 0.938 and 0.859, respectively. In the training set, the combined sequence radiomics model outperformed the clinicopathological features model ( P＜0.001). In the training and validation sets, the nomogram outperformed the clinicopathological features model ( P＜0.05). In addition, the diagnostic performance of the nomogram was better than that of the four single-modality radiomics models in the training cohort ( P＜0.05) and was better than that of DCE-2 and ADC models in the validation cohort ( P＜0.05). Decision curve analysis indicated that the value of individualized prediction models was higher than clinical and pathological prediction models in clinical practice. The calibration curve showed that the multimodal radiomics model had a high consistency with the actual results in predicting HER-2 expression. Conclusions:T2WI, ADC and early-delayed phase DCE-MRI imaging histology models for HER-2 expression status in breast cancer are expected to provide a non-invasive virtual pathological basis for decision-making on preoperative neoadjuvant regimens in breast cancer.

Objective This study aims to establish a non-puerperal mastitis (NPM) rat model by simulating hyperprolactinemia and immune-inflammatory states, and to evaluate its local inflammatory characteristics in the mammary gland, thereby laying the foundation for research on the diagnosis and treatment of this clinically challenging disease. Methods Twelve SPF-grade Wistar female rats were evenly divided into a control group and a model group. During the experiment, the control group received no experimental treatment or medication. The model group received daily subcutaneous injections of 100 mg/kg metoclopramide hydrochloride for 7 consecutive days. Serum prolactin (PRL) levels were measured using ELISA on the 10th, 20th, and 30th days after the first injection. After 7 days of injections, 200 μL of lactating SD rat milk was mixed with 200 μL of complete Freund's adjuvant to prepare an oil-in-water emulsion, which was administered by multiple subcutaneous injections into the back of the Wistar rats for the initial immunization. Seven days after the initial immunization, the emulsion was injected subcutaneously into the third, fourth, and fifth mammary glands for the final immunization. After the final immunization, the rats were observed for 28 days for changes in mammary gland appearance, and the size of mammary nodules was calculated. On the 3rd, 7th, 14th, and 28th days, hematoxylin-eosin (HE) staining was used to analyze mammary tissue morphology. Immunohistochemistry was employed to detect CD138 expression levels. ELISA was used to measure the levels of interleukin (IL)-6, IL-1β, tumor necrosis factor (TNF)-α, and inducible nitric oxide synthase (iNOS) in mammary tissue to comprehensively assess the model. Results Rats in the model group exhibited mammary skin ulceration and foul odor at the ulcer sites. Palpation and ultrasound revealed the formation of mammary nodules. HE staining showed that on the 3rd day after the final immunization, normal ductal and lobular structures in the mammary glands disappeared, with significant infiltration of plasma cells. On the 7th day, ductal dilation, epithelial necrosis and detachment, and pronounced periductal plasma cell and lymphocyte (predominantly T-lymphocytes) infiltration were observed. On the 14th day, there was a proliferation of fibrofatty tissue, small blood vessels, and granulation tissue, with scattered plasma cells in the interstitium. By the 28th day, inflammatory cell infiltration and fibrous tissue proliferation were reduced, with granuloma formation. Serum PRL levels in the model group were significantly increased on the 10th day (P<0.05) and the 20th day (P<0.001). IL-6 and TNF-α levels in mammary tissue were higher in the model group compared to the control group on the 3rd, 7th, 14th, and 28th days (P<0.05). IL-1β levels were higher on the 3rd, 7th, and 14th days compared with the control group (P<0.01) but lower than the control group on the 28th day (P>0.05). iNOS levels were significantly higher on the 7th day after the final immunization (P<0.001). Conclusion A successful NPM model was established in rats, which exhibited typical pathological features such as local mammary masses, abscesses, ulcers, ductal dilation and plasma cell infiltration. This model can serve as a foundation for further research into the diagnosis and treatment of this clinically challenging disease.

Objective:This study aims to explore the predictive value of T2-weighted imaging (T2WI), apparent diffusion coefficient (ADC), and early-delayed phases enhanced magnetic resonance imaging (DCE-MRI) radiomics prediction model in determining human epidermal growth factor receptor 2 status in breast cancer.Methods:A retrospective study was conducted, involving 187 patients with confirmed breast cancer by postsurgical pathology at Zhenjiang First People's Hospital during January 2021 and May 2023. Immunohistochemistry or fluorescence in situ hybridization was used to determine the HER-2 status of these patients, with 48 cases classified as HER-2 positive and 139 cases as HER-2 negative. The training set was used to construct the prediction models and the validation set was used to verify the prediction models. Layers of T2WI, ADC, and early-delayed phase DCE-MRI images were used to delineate the volumeof interest and 960 radiomic features were extracted from each case using Pyradiomic. After screening and dimensionality reduction by intraclass correlation coefficient, Pearson correlation analysis, least absolute shrinkage, and selection operator, the radiomics labels were established. Logistic regression analysis was used to construct the T2WI radiomics model, ADC radiomics model, DCE-2 radiomics model, DCE-6 radiomics model, and the joint sequence radiomics model to predict the HER-2 expression status of breast cancer, respectively. Based on the clinical, pathological, and MRI image characteristics of patients, univariate and multivariate logistic regression analysis wasused to construct a clinicopathological MRI feature model. The radscore of every patient and the clinicopathological MRI features which were statistically significant after screening were used to construct a nomogram model. The receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of each model and the decision curve analysis wasused to evaluate the clinical usefulness.Results:The T2WI, ADC, DCE-2, DCE-6, and joint sequence radiomics models, the clinicopathological MRI feature model, and the nomogram model were successfully constructed to predict the expression status of HER-2 in breast cancer. ROC analysis showed that in the training set and validation set, the areas under the curve (AUC) of the T2WI radiomics model were 0.797 and 0.760, of the ADC radiomics model were 0.776 and 0.634, of the DCE-2 radiomics model were 0.804 and 0.759, of the DCE-6 radiomics model were 0.869 and 0.798, of the combined sequence radiomics model were 0.908 and 0.847, of the clinicopathological MRI feature model were 0.703 and 0.693, and of the nomogram model were 0.938 and 0.859, respectively. In the training set, the combined sequence radiomics model outperformed the clinicopathological features model ( P＜0.001). In the training and validation sets, the nomogram outperformed the clinicopathological features model ( P＜0.05). In addition, the diagnostic performance of the nomogram was better than that of the four single-modality radiomics models in the training cohort ( P＜0.05) and was better than that of DCE-2 and ADC models in the validation cohort ( P＜0.05). Decision curve analysis indicated that the value of individualized prediction models was higher than clinical and pathological prediction models in clinical practice. The calibration curve showed that the multimodal radiomics model had a high consistency with the actual results in predicting HER-2 expression. Conclusions:T2WI, ADC and early-delayed phase DCE-MRI imaging histology models for HER-2 expression status in breast cancer are expected to provide a non-invasive virtual pathological basis for decision-making on preoperative neoadjuvant regimens in breast cancer.

Carpal tunnel syndrome(CTS)is one of the most common peripheral nerve entrapment disorders,the elevated pressure in the carpal tunnel,high-intensity activities and obesity are the main causes,and the patients with mild to moderate CTS are more prevalent.The main pathogenesis of CTS involves the increasing of carpal tunnel pressure and impaired local blood oxygen supply leading to reduced nerve conduction.Currently,the clinical treatment methods for mild to moderate CTS mainly include surgical and nonsurgical treatments.Nonsurgical treatment is the preferable choice for the patients with mild to moderate CTS.The western medical treatment primarily rely on oral medications,but their long-term use is limited due to the certain adverse effects;the local blockade and extracorporeal shock wave therapies show better efficacy for the patients with frequent activities and severe symptoms;the traditional Chinese medicine treatment also becomes a choice for some CTS patients due to their advantages of less pain,lower medical costs,and significant effectiveness.This study reviews the recent advancements in the pathogenesis and treatment of mild to moderate CTS,in order to design the personalized treatment methods for the mild to moderate CTS patients based on their specific conditions in clinical settings and provide the references for precise treatment of the mild to moderate CTS patients.

Objective To investigate the affecting factors of postoperative restenosis in patients with Trans Atlantic Inter-Society Consensus-Ⅱ(TASC-Ⅱ)type C or D atherosclerosis obliterans(ASO)treated with endovascular intervention.Methods Eighty-one patients who underwent endovascular interventional treatment for ASO were included and were followed up continuously for two years after the procedure.Also,the pre-and post-treatment data of the restenosis group and the nonstenosis group were compared and statistically analyzed to clarify the affecting factors of restenosis as well as the value of the related factors in predicting the postoperative restenosis in the preoperative period.Results The incidence of restenosis in 81 patients was 40.74％within two years after the interventional treatment.The unifactorial results showed that the comparison of ankle brachial index(ABI),age,gender,smoking history,body mass index(BMI),procedure,number of stent placement,lesion length,hyperlipidemia,coronary heart disease,diabetes mellitus,and hypertension between the two groups was not statistically significant(P＞0.05);the comparison of blood biochemical indexes in the levels of hypersensitive C-reactive protein(hs-CRP),fibrinogen,neutrophil-lymphocyte ratio(NLR),homocysteine(Hcy),and cystatin C(Cys C)showed a difference of statistically significant(P＜0.05);binary logistic regression results for fibrinogen level,hs-CRP,NLR,Hey,and Cys C were all independent risk factors for postoperative restenosis[odds ratio(OR)=40.501,4.507,4.381,1.509,and 23.094,P＜0.05].The results of receiver operating characteristic(ROC)curves showed that hs-CRP,NLR,and Cys C could effectively predict ASO postoperative restenosis,with area under the curve(AUC)of 0.683,0.637,and 0.632,and cutoff values of 4.225,3.465,and 1.000,respectively(P＜0.05).Conclusion Post-interventional vascular restenosis in ASO patients is correlated with the levels of fibrinogen,hs-CRP,NLR,Hcy,and Cys C.Also,hs-CRP,NLR,and Cys C may be used as blood biochemical indexes to predict post-interventional vascular restenosis in ASO patients.

To investigate the mechanism of Wenshen Xuanbi Decoction (WSXB) in treating osteoarthritis (OA) via network pharmacology, bioinformatics analysis, and experimental verification. The active components and prediction targets of WSXB were obtained from the TCMSP database and Swiss Target Prediction website, respectively. OA-related genes were retrieved from GeneCards and OMIM databases.Protein-protein interaction and functional enrichment analyses were performed, resulting in the construction of the Herb-Component-Target network. In addition, differential genes of OA were obtained from the GEO database to verify the potential mechanism of WSXB in OA treatment. Subsequently, potential active components were subjected to molecular verification with the hub targets. Finally, we selected the most crucial hub targets and pathways for experimental verification in vitro. The active components in the study included quercetin, linolenic acid, methyl linoleate, isobergapten, and beta-sitosterol. AKT1, tumor necrosis factor (TNF), interleukin (IL)-6, GAPDH, and CTNNB1 were identified as the most crucial hub targets. Molecular docking revealed that the active components and hub targets exhibited strong binding energy. Experimental verification demonstrated that the mRNA and protein expression levels of IL-6, IL-17, and TNF in the WSXB group were lower than those in the KOA group (p < 0.05). WSXB exhibits a chondroprotective effect on OA and delays disease progression. The mechanism is potentially related to the suppression of IL-17 and TNF signaling pathways and the down-regulation of IL-6.

Risk assessment of clinical trials is of great significance to improve the quality of clinical trials. Through systematic comparative analysis of risk assessment tools for clinical trials in Britain, Germany and France, this paper found that the three countries’ risk assessment tools were consistent in terms of legal system guarantee and assessment process, but there were obvious differences in the basic risk classification and risk grading standards of clinical trials. Based on the experience of Britain, France and Germany, this paper proposed to improve the relevant regulations and documents of clinical trial risk management in China from the perspective of Chinese national conditions, further explore the factors affecting clinical trial risk, and develop and design clinical trial risk assessment tools with different discipline characteristics according to the specialties of the discipline to improve the quality and level of clinical trials.

BACKGROUND: Pancreatic β-cells elevate insulin production and secretion through a compensatory mechanism to override insulin resistance under metabolic stress conditions. Deficits in β-cell compensatory capacity result in hyperglycemia and type 2 diabetes (T2D). However, the mechanism in the regulation of β-cell compensative capacity remains elusive. Nuclear factor-Y (NF-Y) is critical for pancreatic islets' homeostasis under physiological conditions, but its role in β-cell compensatory response to insulin resistance in obesity is unclear. METHODS: In this study, using obese ( ob/ob ) mice with an absence of NF-Y subunit A (NF-YA) in β-cells ( ob , Nf-ya βKO) as well as rat insulinoma cell line (INS1)-based models, we determined whether NF-Y-mediated apoptosis makes an essential contribution to β-cell compensation upon metabolic stress. RESULTS: Obese animals had markedly augmented NF-Y expression in pancreatic islets. Deletion of β-cell Nf-ya in obese mice worsened glucose intolerance and resulted in β-cell dysfunction, which was attributable to augmented β-cell apoptosis and reactive oxygen species (ROS). Furthermore, primary pancreatic islets from Nf-ya βKO mice were sensitive to palmitate-induced β-cell apoptosis due to mitochondrial impairment and the attenuated antioxidant response, which resulted in the aggravation of phosphorylated c-Jun N-terminal kinase (JNK) and cleaved caspase-3. These detrimental effects were completely relieved by ROS scavenger. Ultimately, forced overexpression of NF-Y in INS1 β-cell line could rescue palmitate-induced β-cell apoptosis, dysfunction, and mitochondrial impairment. CONCLUSION Pancreatic NF-Y might be an essential regulator of β-cell compensation under metabolic stress.
Rats ; Mice ; Animals ; Reactive Oxygen Species/metabolism* ; Diabetes Mellitus, Type 2/metabolism* ; Insulin Resistance ; Insulin ; Insulin-Secreting Cells/metabolism* ; Apoptosis ; Stress, Physiological ; Transcription Factors/metabolism* ; Palmitates/pharmacology* ; Obesity/metabolism*