Objective To investigate the utility of combining breast mass growth orientation quantification with the S-Detect technique for predicting axillary lymph node(ALN)metastasis in breast cancer.Methods Data was collected from 163 breast cancer patients admitted to our hospital between March 2023 and October 2024,who were categorized into metastatic(n=62)and non-metastatic(n=101)groups based on ALN pathology results.All patients underwent routine preoperative ultrasound and S-Detect examination.Univariate and multivariate regression analyses were performed to assess the correlation between each observational index and ALN metastasis.Significant indexes were identified through screening,leading to the establishment of a logistic regression prediction model.The predictive value of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Results The univariate analysis revealed statistically significant differences(P<0.05)in the maximum diameter of the mass,border characteristics,margin features,calcification patterns,orientation angle,and blood flow between the two groups.Multifactorial analysis demonstrated that calcification,border characteristics,orientation angle,margin features,and maximum diameter independently influenced the prediction of axillary lymph node(ALN)status in breast cancer patients(P<0.05).Consequently,a logistic regression prediction model was constructed as follows:Y=-7.995+2.299×maximal diameter+1.171×border+2.137×margin+1.397×calcication+0.034×orientation angle.The area under curve(AUC)for this combined prediction model was 0.869 which significantly outperformed each independent influencing factor alone(P<0.05),indicating good agreement between this joint prediction model and pathological results(Kappa=0.701,P<0.05).Conclusions Quantification of the orientation angle of a breast mass aids in predicting axillary lymph node(ALN)metastasis and enhances the interpretation and application of non-parallel orientations.The combination of quantifying growth orientation based on breast mass with artificial intelligence S-Detect technique demonstrates promising predictive value for ALN metastasis in breast cancer,providing a reference basis for personalized treatment.

Objective To investigate the utility of combining breast mass growth orientation quantification with the S-Detect technique for predicting axillary lymph node(ALN)metastasis in breast cancer.Methods Data was collected from 163 breast cancer patients admitted to our hospital between March 2023 and October 2024,who were categorized into metastatic(n=62)and non-metastatic(n=101)groups based on ALN pathology results.All patients underwent routine preoperative ultrasound and S-Detect examination.Univariate and multivariate regression analyses were performed to assess the correlation between each observational index and ALN metastasis.Significant indexes were identified through screening,leading to the establishment of a logistic regression prediction model.The predictive value of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Results The univariate analysis revealed statistically significant differences(P<0.05)in the maximum diameter of the mass,border characteristics,margin features,calcification patterns,orientation angle,and blood flow between the two groups.Multifactorial analysis demonstrated that calcification,border characteristics,orientation angle,margin features,and maximum diameter independently influenced the prediction of axillary lymph node(ALN)status in breast cancer patients(P<0.05).Consequently,a logistic regression prediction model was constructed as follows:Y=-7.995+2.299×maximal diameter+1.171×border+2.137×margin+1.397×calcication+0.034×orientation angle.The area under curve(AUC)for this combined prediction model was 0.869 which significantly outperformed each independent influencing factor alone(P<0.05),indicating good agreement between this joint prediction model and pathological results(Kappa=0.701,P<0.05).Conclusions Quantification of the orientation angle of a breast mass aids in predicting axillary lymph node(ALN)metastasis and enhances the interpretation and application of non-parallel orientations.The combination of quantifying growth orientation based on breast mass with artificial intelligence S-Detect technique demonstrates promising predictive value for ALN metastasis in breast cancer,providing a reference basis for personalized treatment.

Objective To evaluate the predictive value of dual-modality ultrasound,incorporating conventional ultrasound and ultrasound elastography,in combination with S-Detect for cervical lymph node metastasis(CLNM)in patients with papillary thyroid carcinoma(PTC).Methods A retrospective analysis was conducted on the clinical data of 135 patients diagnosed with PTC who received treatment at the First Affiliated Hospital of Shihezi University between November 2023 and August 2024.For all patients,clinical baseline characteristics,conventional ultrasound findings,ultrasound elastography results,and S-Detect analysis data were collected.Independent predictors of CLNM in PTC were identified,and predictive models were developed.Receiver operating characteristic(ROC)curves were generated to compare the area under the curve(AUC)of the models.The most effective predictive model was selected to construct a risk probability nomogram,and the predictive performance and clinical applicability of this nomogram were subsequently evaluated.Results Age,maximum nodule diameter,boundary characteristics,capsular invasion,transverse-sectional morphological findings assessed by S-Detect,and ECI-based elasticity grading were identified as independent predictors of CLNM in PTC(all P<0.05).The AUC of the predictive model constructed using these six variables was 0.890(95%CI:0.835～0.945).The calibration curve demonstrated strong agreement between predicted and observed outcomes,and decision curve analysis indicated that the nomogram provided a favorable net clinical benefit within a threshold probability range of 2%to 91.5%.Conclusions Age,maximum nodule diameter,boundary characteristics,capsular invasion,sonographic features assessed by S-Detect in the transverse plane,and ECI-based elasticity grading are independent predictors of CLNM in PTC.A nomogram model incorporating these parameters demonstrates effective performance in predicting the likelihood of CLNM.

Objective To evaluate the predictive value of dual-modality ultrasound,incorporating conventional ultrasound and ultrasound elastography,in combination with S-Detect for cervical lymph node metastasis(CLNM)in patients with papillary thyroid carcinoma(PTC).Methods A retrospective analysis was conducted on the clinical data of 135 patients diagnosed with PTC who received treatment at the First Affiliated Hospital of Shihezi University between November 2023 and August 2024.For all patients,clinical baseline characteristics,conventional ultrasound findings,ultrasound elastography results,and S-Detect analysis data were collected.Independent predictors of CLNM in PTC were identified,and predictive models were developed.Receiver operating characteristic(ROC)curves were generated to compare the area under the curve(AUC)of the models.The most effective predictive model was selected to construct a risk probability nomogram,and the predictive performance and clinical applicability of this nomogram were subsequently evaluated.Results Age,maximum nodule diameter,boundary characteristics,capsular invasion,transverse-sectional morphological findings assessed by S-Detect,and ECI-based elasticity grading were identified as independent predictors of CLNM in PTC(all P<0.05).The AUC of the predictive model constructed using these six variables was 0.890(95%CI:0.835～0.945).The calibration curve demonstrated strong agreement between predicted and observed outcomes,and decision curve analysis indicated that the nomogram provided a favorable net clinical benefit within a threshold probability range of 2%to 91.5%.Conclusions Age,maximum nodule diameter,boundary characteristics,capsular invasion,sonographic features assessed by S-Detect in the transverse plane,and ECI-based elasticity grading are independent predictors of CLNM in PTC.A nomogram model incorporating these parameters demonstrates effective performance in predicting the likelihood of CLNM.

Objective:To investigate the current situation of knowledge, attitude and practice of medical personnel in areas with high incidence of fever with thrombocytopenia syndrome (SFTS) in Anhui Province, in order to provide a scientific basis for conducting systematic training for medical personnel.Methods:From July to August 2024, a multi-stage random sampling method was used to select medical personnel from village, township, county, and city level medical institutions in high incidence areas of SFTS in Anhui Province (Hefei City, Liu'an City, Chuzhou City, Xuancheng City) for an online questionnaire survey on their knowledge, attitude, and practice status. The survey included demographic data, knowledge, attitude, and practice related to SFTS, and a binary logistic regression model was used to analyze the influencing factors of SFTS knowledge qualification rate.Results:A total of 2 718 valid questionnaires were collected, with an effective response rate of 99.60% (2 718/2 729). Among them, 1 384 were males, accounting for 50.92%. The majority were medical personnel aged 41 to 50 years old, with undergraduate degrees, junior professional titles, working in township health centers or community health service centers, as clinical physicians, and with a working experience of no more than 10 years. They accounted for 31.97% (869/2 718), 50.48% (1 372/2 718), 35.54% (966/2 718), 38.52% (1 047/2 718), 62.33% (1 694/2 718), and 30.61% (832/2 718), respectively. The overall correct rates of medical personnel's relevant knowledge, attitude and practice were 77.52% (31 605/40 770), 94.53% (12 847/13 590) and 89.73% (12 194/13 590), respectively. There were statistically significant differences in the knowledge qualification of medical personnel of different genders, ages, education levels, professional titles, hospital levels, job positions, and years of work experience ( P < 0.05). The results of binary logistic regression analysis showed that professional title, hospital level, work position, and work experience were the influencing factors of knowledge qualification rate ( P < 0.05). Conclusions:Medical personnel have a relatively positive attitude and high level of practice towards SFTS, but their knowledge level still needs to be improved. It is recommended to provide targeted knowledge training for medical personnel in different positions to promote early detection, diagnosis, and treatment of SFTS.

Objective:To investigate the current situation of knowledge, attitude and practice of medical personnel in areas with high incidence of fever with thrombocytopenia syndrome (SFTS) in Anhui Province, in order to provide a scientific basis for conducting systematic training for medical personnel.Methods:From July to August 2024, a multi-stage random sampling method was used to select medical personnel from village, township, county, and city level medical institutions in high incidence areas of SFTS in Anhui Province (Hefei City, Liu'an City, Chuzhou City, Xuancheng City) for an online questionnaire survey on their knowledge, attitude, and practice status. The survey included demographic data, knowledge, attitude, and practice related to SFTS, and a binary logistic regression model was used to analyze the influencing factors of SFTS knowledge qualification rate.Results:A total of 2 718 valid questionnaires were collected, with an effective response rate of 99.60% (2 718/2 729). Among them, 1 384 were males, accounting for 50.92%. The majority were medical personnel aged 41 to 50 years old, with undergraduate degrees, junior professional titles, working in township health centers or community health service centers, as clinical physicians, and with a working experience of no more than 10 years. They accounted for 31.97% (869/2 718), 50.48% (1 372/2 718), 35.54% (966/2 718), 38.52% (1 047/2 718), 62.33% (1 694/2 718), and 30.61% (832/2 718), respectively. The overall correct rates of medical personnel's relevant knowledge, attitude and practice were 77.52% (31 605/40 770), 94.53% (12 847/13 590) and 89.73% (12 194/13 590), respectively. There were statistically significant differences in the knowledge qualification of medical personnel of different genders, ages, education levels, professional titles, hospital levels, job positions, and years of work experience ( P < 0.05). The results of binary logistic regression analysis showed that professional title, hospital level, work position, and work experience were the influencing factors of knowledge qualification rate ( P < 0.05). Conclusions:Medical personnel have a relatively positive attitude and high level of practice towards SFTS, but their knowledge level still needs to be improved. It is recommended to provide targeted knowledge training for medical personnel in different positions to promote early detection, diagnosis, and treatment of SFTS.

OBJECTIVE To identify tortoiseshell glue and antler glue in Qichong zuogui granules,and determine the contents of 12 chemical components.METHODS Identification and content determination were performed by using liquid chromatography-tandem mass spectrometry(LC-MS/MS)method.The identification was performed on Hypersil GOLD column with a mobile phase consisted of acetonitrile-0.1％formic acid solution(gradient elution);the electrospray ion source was used to scan in the positive ion multi-reaction detection mode.The mass charge ratio(m/z)631.3→546.4,631.3→921.4 was the detection ion pair for tortoiseshell glue,and the m/z 765.4→554.0,765.4→733.0 was the detection ion pair for antler glue.The determination method for 12 chemical components was as follows:Accucore C18 column,methanol-0.1％formic acid as mobile phase(gradient elution);scanning range of positive and negative ions was m/z 100→1 000 with the electric spray ion source and single ion detection scanning mode.RESULTS Average retention times of the molecular ion peaks for characteristic peptide segments of tortoiseshell glue and antler glue were 6.28 and 6.77 min,respectively;the linear relationship of 12 chemical components was good within their respective concentration ranges,such as astragaloside Ⅳ,calycosin-7-O-β-D-glucoside,calycosin,chlorogenic acid,ferulic acid,betaine,amygdalin,rutin,hydroxysafflor yellow A,hyperoside,loganin,cyasterone(r＞0.999);RSDs for precision,stability(24 h)and reproducibility tests were all less than 5％.The average sample recovery rates ranged from 98.04％to 101.08％.The average contents of 12 components were 1.83,25.73,13.76,56.71,23.80,49.82,807.49,15.01,317.02,60.21,202.71 and 17.70 μg/g,respectively.CONCLUSIONS In this study,tortoiseshell glue and antler glue in Qixiong zuogui granules are identified,and the contents of 12 chemical components therein are determined.This provides a reference for the quality control of this granule.

Pelvic organ prolapse (POP), whose etiology is influenced by genetic and clinical risk factors, considerably impacts women's quality of life. However, the genetic underpinnings in non-European populations and comprehensive risk models integrating genetic and clinical factors remain underexplored. This study constructed the first polygenic risk score (PRS) for POP in the Chinese population by utilizing 20 disease-associated variants from the largest existing genome-wide association study. We analyzed a discovery cohort of 576 cases and 623 controls and a validation cohort of 264 cases and 200 controls. Results showed that the case group exhibited a significantly higher PRS than the control group. Moreover, the odds ratio of the top 10% risk group was 2.6 times higher than that of the bottom 10%. A high PRS was significantly correlated with POP occurrence in women older than 50 years old and in those with one or no childbirths. As far as we know, the integrated prediction model, which combined PRS and clinical risk factors, demonstrated better predictive accuracy than other existing PRS models. This combined risk assessment model serves as a robust tool for POP risk prediction and stratification, thereby offering insights into individualized preventive measures and treatment strategies in future clinical practice.
Humans ; Female ; Pelvic Organ Prolapse/epidemiology* ; Middle Aged ; Risk Assessment/methods* ; China/epidemiology* ; Multifactorial Inheritance ; Aged ; Risk Factors ; Genome-Wide Association Study ; Genetic Predisposition to Disease ; Case-Control Studies ; Adult ; Polymorphism, Single Nucleotide ; Genetic Risk Score ; East Asian People

Objective To identify flavonoid glycosides with quorum sensing inhibitory activity from Epimedium brevicornum and evaluate their bioactivity. Methods The minimum inhibitory concentrations （MICs） of five major flavonoid glycosides （baohuoside, icariin, epimedin A/B/C） and the extract of E. brevicornum were firstly determined. Subsequently, the inhibitory effects on the production of purple pigments in Chromobacterium violaceum CV026 were measured. Additionally, the biofilm formation and chitin quantification of Pseudomonas aeruginosa PAO1 were assessed. Results The extract of E. brevicornum and its primary components exhibited significant quorum sensing inhibitory activity. Particularly, icariin and epimedin C demonstrated superior inhibitory activity. Conclusion E. brevicornum demonstrates the ability to inhibit the quorum sensing system of Chromobacterium violaceum CV026 and Pseudomonas aeruginosa PAO1. Furthermore, icariin and epimedin C （100 μg/ml） show promise for development into novel drugs for quorum sensing inhibitor.

Thermal analysis technology has emerged as a pivotal tool for the identification and quality control of traditional Chinese medicine （TCM） owing to its advantages of high sensitivity and capability for simultaneous multi-parameter detection. The application progress on thermogravimetric analysis （TGA）, differential thermal analysis （DTA）, and differential scanning calorimetry （DSC） in four key areas: authenticity identification of herbal medicines, optimization of processing techniques, evaluation of extract thermal stability, and construction of quality evaluation systems were summarized. Thermal analysis technology enables rapid authentication of medicinal materials by establishing a thermal fingerprint. When integrated with hyphenated techniques （e.g., FTIR and GC-MS）, it facilitates in-depth analysis of compositional differences in complex matrices. In Future, the development of thermal analysis databases and multi-technology integration will be expected to further promote the standardization of TCM quality control.