Objective: To assess the association between the metabolic score for insulin resistance index (METS-IR) and overactive bladder (OAB) in the US population，so as to explore the potential of METS-IR as a predictive tool for OAB risk and to provide insights for early screening and intervention strategies. Methods: Based on the data from the National Health and Nutrition Examination Survey (NHANES) 2005-2018，a cross-sectional design was employed，and multivariate logistic regression models were used to analyze the association between METS-IR and OAB. METS-IR was analyzed both as a continuous variable and categorized into quartiles. To further validate the association between METS-IR and OAB across diverse populations，subgroup analyses were conducted in participants stratified by clinical characteristics. Smooth curve fitting was employed to test the linearity of the METS-IR-OAB relationship. Results: Elevated METS-IR was associated with an increased risk of OAB (P<0.001)，and this positive correlation remained stable when METS-IR was categorized into quartiles (P<0.001). Subgroup analyses revealed that the association between METS-IR and OAB was more pronounced in females，participants younger than 55 years，and non-diabetic individuals (P<0.05). Furthermore，smooth curve fitting confirmed a linear positive correlation between METS-IR and OAB，with this linear relationship observed in both diabetic and non-diabetic groups. Conclusion: This study，based on the NHANES 2005-2018 database，found a linear positive correlation between METS-IR and OAB.

BACKGROUND:Tissue flossing is a new injury prevention tool and auxiliary exercise training strategy.Tissue flossing can increase joint range of motion,improve athletic performance,and relieve pain,and is increasingly widely used in the field of sports and rehabilitation. OBJECTIVE:To review the mechanism of tissue flossing and its application in sports and rehabilitation to provide a reference for follow-up research. METHODS:"Tissue flossing;compression tissue flossing;floss band;voodoo flossband;blood flow restriction;shearing of fascia;musculoskeletal rehabilitation;sport injury"were used as Chinese and English search terms to search on the databases of CNKI,WanFang,VIP,PubMed and EBSCO databases.Relevant articles from January 2000 to October 2022 were retrieved,and 86 articles were finally included according to inclusion and exclusion criteria. RESULTS AND CONCLUSION:Tissue flossing intervention can improve lower limb joint motion,improve sprint and jump performance,promote joint injury rehabilitation,and relieve pain subjectively.However,tissue flossing intervention did not improve the range of motion of the upper limb.There is still controversy on the acute enhancement of lower limb muscle strength.It has a good tendency to improve lower limb balance and stability and improve mental state,but more studies are needed to confirm.The possible mechanisms of tissue flossing intervention are mainly fascia shear,pain gating,blood flow restriction and reperfusion,and compression.Tissue flossing is a useful treatment option that can provide important contributions in the future in the areas of sports training,sports injury prevention and rehabilitation,but more long-term in-depth studies are needed.

BACKGROUND:The specific mechanism of Gushukang,as a Chinese traditional patent medicine for the treatment of postmenopausal osteoporosis of kidney deficiency and blood stasis,needs further studies. OBJECTIVE:To investigate the effect of Gushukang on serum sex hormones,bone microstructure and estrogen receptor in postmenopausal osteoporosis. METHODS:Firstly,network pharmacological analysis was performed.The active ingredients and action targets of Gushukang and the targets of postmenopausal osteoporosis were obtained respectively.Cytoscape was used to construct the active ingredient-target network.STRING database and Cytoscape were used for protein-protein interaction analysis and screening of core targets.DAVID database was used for Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses of intersection targets.Then the ovariectomized Sprague-Dawley rats were used in the animal experiment.Gushukang was administered by gavage for 3 months.The serum estrogen level was detected by ELISA,the bone microstructure was detected by microCT,and the protein expression of estrogen receptor α and estrogen receptor β in bone tiusse was detected by western blot. RESULTS AND CONCLUSION:The network pharmacological research results identified 132 active ingredients and 150 targets of Gushukang and 1155 targets of postmenopausal osteoporosis.After intersections with 1155 postmenopausal osteoporosis targets,87 targets of active ingredients of Gushukang against postmenopausal osteoporosis were obtained.By constructing the active ingredient-target network,it was found that the active ingredients at the core were quercetin,kaempferol,luteolin,naringin and isorhamnetin,and the targets at the core were NCOA2,ESR2,AR,F2,ESR1 and PTGS1.The final targets obtained after the protein-protein interaction analysis and screening included MAPK8,ESR1,JUN,R3C1,RELA and FOS,of which ESR1 was the common core target obtained from the two analyses.KEGG enrichment analysis showed estrogen,tumor necrosis factor,apoptosis and other signaling pathways.Therefore,animal experiments focused on the effect of Gushukang on different subtypes of estrogen receptors in the estrogen signaling pathway.The results showed that in the Gushukang group,bone microstructure was significantly improved,serum estrogen level had no significant change,but the protein expression of estrogen receptor α and β in bone tissue was significantly increased.All the findings indicate that the mechanism of Gushukang in the treatment of postmenopausal osteoporosis may be related to its hormone-like effect and the enhancement of estrogen receptor expression.

Objectives:To develop and validate predictive models for esophageal squamous cell carcinoma (ESCC) using circulating cell-free DNA (cfDNA) terminal motif analysis. The goal was to improve the non-invasive detection of early-stage ESCC and its precancerous lesions.Methods:Between August 2021 and November 2022, we prospectively collected plasma samples from 448 individuals at the Department of Endoscopy, Cancer Hospital, Chinese Academy of Medical Sciences for cfDNA extraction, library construction, and sequencing. We analyzed 201 cases of ESCC, 46 high-grade intraepithelial neoplasia (HGIN), 46 low-grade intraepithelial neoplasia (LGIN), 176 benign esophageal lesions, and 29 healthy controls. Participants, including ESCC patients and control subjects, were randomly assigned to a training set ( n=284) and a validation set ( n=122). The training cohort underwent z-score normalization of cfDNA terminal motif matrices and a selection of distinctive features differentiated ESCC cases from controls. The random forest classifier, Motif-1 (M1), was then developed through principal component analysis, ten-fold cross-validation, and recursive feature elimination. M1's efficacy was then validated in the validation and precancerous lesion sets. Subsequently, individuals with precancerous lesions were included in the dataset and participants were randomly allocated to newly formed training ( n=243), validation ( n=105), and test ( n=150) cohorts. Using the same procedure as M1, we trained the Motif-2 (M2) random forest model with the training cohort. The M2 model's accuracy was then confirmed in the validation cohort to establish the optimal threshold and further tested by performing validation in the test cohort. Results:We developed two cfDNA terminal motif-based predictive models for ESCC and associated precancerous conditions. The first model, M1, achieved a sensitivity of 90.0%, a specificity of 77.4%, and an area under the curve (AUC) of 0.884 in the validation cohort. For LGIN, HGIN, and T1aN0 stage ESCC, M1's sensitivities were 76.1%, 80.4%, and 91.2% respectively. Notably, the sensitivity for jointly predicting HGIN and T1aN0 ESCC reached 85.0%. Both the predictive accuracy and sensitivity increased in line with the cancer's progression ( P＜0.001). The second model, M2, exhibited a sensitivity of 87.5%, a specificity of 77.4%, and an AUC of 0.857 in the test cohort. M2's sensitivities for detecting precancerous lesions and ESCC were 80.0% and 89.7%, respectively, and it showed a combined sensitivity of 89.4% for HGIN and T1aN0 stage ESCC. Conclusions:Two predictive models based on cfDNA terminal motif analysis for ESCC and its precancerous lesions are developed. They both show high sensitivity and specificity in identifying ESCC and its precancerous stages, indicating its potential for early ESCC detection.

Objective:To evaluate the effects of antibiotics alone and combined with Longqing tablets and antibiotics on stent-related symptoms (SRS), urinary tract infection (UTI), and quality of life in patients who underwent ureteroscopic lithotripsy (URL) with indwelling ureteral stents.Methods:The clinical data of 160 patients who underwent URL with indwelling ureteral stents in the Department of Urology, Xuanwu Hospital, Capital Medical University from January 2022 to December 2023 were retrospectively analyzed. According to the postoperative application of antibiotics and Longqing tablets, they were divided into two groups: control group and observation group, with 80 cases in each group. The control group took Levofloxacin tablets orally, and the observation group took Longqing tablets combined with Levofloxacin tablets orally. The SRS of the two groups was compared according to the degree of urinary tract irritation symptoms, low back pain, and dysuria. UTI was evaluated by the incidence of fever, hematuria, pyuria, positive rate of urine culture, and specific bacterial classes. The Chinese version of the ureteral stent symptom questionnaire (USSQ) and the quality of life score were evaluated in the two groups. Normally distributed quantitative data were expressed as mean ± standard deviation ( ± s), and the t-test was used for comparison between groups; non-normally distributed quantitative data were expressed as median (interquartile range) [ M( Q1, Q3)], and the non-parametric test was used for comparison between groups. Count data were expressed as the number of cases and percentage, and the Chi-square test was used for comparison between groups. Results:Among the 160 patients, 141 (88.13%) developed SRS, including 71 cases (88.75%) in the control group, and 70 cases (87.50%) in the observation group, there was no significant difference between the two groups ( P=0.724). In terms of SRS, the urinary tract irritation symptom scores [3.0 (1.0, 5.0) points vs 5.0 (3.0, 7.0) points], low back pain scores [1.5 (1.0, 2.0) points vs 2.5 (2.0, 3.0) points] and dysuria scores [1.5 (1.0, 2.0) points vs 3.5 (2.5, 4.0) points] of the observation group were significantly lower than those of the control group, the differences were statistically significant ( P<0.05). The Chinese version of USSQ showed that the urinary tract symptoms of the observation group were significantly relieved compared with the control group [15(12, 19) points vs 22 (15, 28) points], and the difference was statistically significant ( P=0.037). In terms of UTI, the incidence of fever (6.25% vs 7.50%), the incidence of hematuria (20.00% vs 22.50%), the incidence of pyuria (30.00% vs 33.75%), and positive rate of urine culture (11.25% vs 15.00%) between the two groups were not statistically significant ( P> 0.05), but the number was reduced to a certain extent. There was no statistically significant difference in the scores of physiological function, emotional function and social function between the two groups before surgery ( P> 0.05); however, the scores of the above three items in both groups were improved 2 weeks after surgery, and the improvement of the observation group was significantly higher than that of the control group, with statistical significance ( P<0.01). Conclusion:Longqing tablets combined with antibiotics are more effective in improving SRS in patients who receive URL and have indwelling ureteral stents than antibiotics alone, and can prevent UTI and improve the quality of life to a certain extent.

Objectives:To develop and validate predictive models for esophageal squamous cell carcinoma (ESCC) using circulating cell-free DNA (cfDNA) terminal motif analysis. The goal was to improve the non-invasive detection of early-stage ESCC and its precancerous lesions.Methods:Between August 2021 and November 2022, we prospectively collected plasma samples from 448 individuals at the Department of Endoscopy, Cancer Hospital, Chinese Academy of Medical Sciences for cfDNA extraction, library construction, and sequencing. We analyzed 201 cases of ESCC, 46 high-grade intraepithelial neoplasia (HGIN), 46 low-grade intraepithelial neoplasia (LGIN), 176 benign esophageal lesions, and 29 healthy controls. Participants, including ESCC patients and control subjects, were randomly assigned to a training set ( n=284) and a validation set ( n=122). The training cohort underwent z-score normalization of cfDNA terminal motif matrices and a selection of distinctive features differentiated ESCC cases from controls. The random forest classifier, Motif-1 (M1), was then developed through principal component analysis, ten-fold cross-validation, and recursive feature elimination. M1's efficacy was then validated in the validation and precancerous lesion sets. Subsequently, individuals with precancerous lesions were included in the dataset and participants were randomly allocated to newly formed training ( n=243), validation ( n=105), and test ( n=150) cohorts. Using the same procedure as M1, we trained the Motif-2 (M2) random forest model with the training cohort. The M2 model's accuracy was then confirmed in the validation cohort to establish the optimal threshold and further tested by performing validation in the test cohort. Results:We developed two cfDNA terminal motif-based predictive models for ESCC and associated precancerous conditions. The first model, M1, achieved a sensitivity of 90.0%, a specificity of 77.4%, and an area under the curve (AUC) of 0.884 in the validation cohort. For LGIN, HGIN, and T1aN0 stage ESCC, M1's sensitivities were 76.1%, 80.4%, and 91.2% respectively. Notably, the sensitivity for jointly predicting HGIN and T1aN0 ESCC reached 85.0%. Both the predictive accuracy and sensitivity increased in line with the cancer's progression ( P＜0.001). The second model, M2, exhibited a sensitivity of 87.5%, a specificity of 77.4%, and an AUC of 0.857 in the test cohort. M2's sensitivities for detecting precancerous lesions and ESCC were 80.0% and 89.7%, respectively, and it showed a combined sensitivity of 89.4% for HGIN and T1aN0 stage ESCC. Conclusions:Two predictive models based on cfDNA terminal motif analysis for ESCC and its precancerous lesions are developed. They both show high sensitivity and specificity in identifying ESCC and its precancerous stages, indicating its potential for early ESCC detection.

Objective:To evaluate artificial intelligence constructed by deep convolutional neural network (DCNN) for the site identification in upper gastrointestinal endoscopy.Methods:A total of 21 310 images of esophagogastroduodenoscopy from the Cancer Hospital of Chinese Academy of Medical Sciences from January 2019 to June 2021 were collected. A total of 19 191 images of them were used to construct site identification model, and the remaining 2 119 images were used for verification. The performance differences of two models constructed by DCCN in the identification of 30 sites of the upper digestive tract were compared. One model was the traditional ResNetV2 model constructed by Inception-ResNetV2 (ResNetV2), the other was a hybrid neural network RESENet model constructed by Inception-ResNetV2 and Squeeze-Excitation Networks (RESENet). The main indices were the accuracy, the sensitivity, the specificity, positive predictive value (PPV) and negative predictive value (NPV).Results:The accuracy, the sensitivity, the specificity, PPV and NPV of ResNetV2 model in the identification of 30 sites of the upper digestive tract were 94.62%-99.10%, 30.61%-100.00%, 96.07%-99.56%, 42.26%-86.44% and 97.13%-99.75%, respectively. The corresponding values of RESENet model were 98.08%-99.95%, 92.86%-100.00%, 98.51%-100.00%, 74.51%-100.00% and 98.85%-100.00%, respectively. The mean accuracy, mean sensitivity, mean specificity, mean PPV and mean NPV of ResNetV2 model were 97.60%, 75.58%, 98.75%, 63.44% and 98.76%, respectively. The corresponding values of RESENet model were 99.34% ( P<0.001), 99.57% ( P<0.001), 99.66% ( P<0.001), 90.20% ( P<0.001) and 99.66% ( P<0.001). Conclusion:Compared with the traditional ResNetV2 model, the artificial intelligence-assisted site identification model constructed by RESENNet, a hybrid neural network, shows significantly improved performance. This model can be used to monitor the integrity of the esophagogastroduodenoscopic procedures and is expected to become an important assistant for standardizing and improving quality of the procedures, as well as an significant tool for quality control of esophagogastroduodenoscopy.

Objective:To compare the efficacy of robot-assisted and conventional fluoroscopy-guided percutaneous vertebroplasty (PVP) combined with pediculoplasty in treating symptomatic chronic thoracolumbar osteoporotic vertebral fracture (SCOVF) without neurological symptoms.Methods:A retrospective cohort study was used to analyze the clinical data of 120 patients with thoracolumbar SCOVF without neurological symptoms, who were admitted to Honghui Hospital Affiliated to Xi′an Jiaotong University from January 2015 to January 2020. The patients included 34 males and 86 females, aged 63-85 years [(72.9±5.7)years]. All patients were treated with PVP combined with pediculoplasty. A total of 87 patients were treated with robot-assisted and C-arm X-ray machine guided puncture (robot group) and 33 patients with C-arm X-ray machine fluoroscopic-guided puncture (conventional group). The operation time, amount of bone cement injection and puncture accuracy were compared between the two groups. The results of vertebral body index, Cobb angle, visual analogue scale (VAS), and Oswestry disability index (ODI) were also compared before operation, at 1 day and 1 year after operation and at the final follow-up. Complications such as bone cement leakage and displacement were observed.Results:All patients were followed up for 24-36 months [(29.4±3.4)months]. The operation time was (85.2±10.5)minutes in the robot group, significantly longer than (37.2±3.7)minutes in the conventional group ( P<0.01). The amount of bone cement injection was (5.0±0.7)ml in the robot group, significantly less than (5.3±0.8)ml in the conventional group ( P<0.05). The puncture accuracy in the robot group was 95.4% (83/87), significantly higher than 81.8% (27/33) in the conventional group ( P<0.01). There were no significant differences in vertebral body index, Cobb angle, VAS or ODI between the two groups before operation (all P>0.05). The values of vertebral body index were 87.1±4.5, 86.9±4.3, 86.8±4.3 in the robot group at 1 day after operation, 1 year after operation and the final follow up, respectively, which were significantly higher than 83.6±4.4, 84.1±3.8, 84.4±3.9 in the conventional group (all P<0.01). There were no significant differences in Cobb angle or ODI between the two groups at 1 day after operation, 1 year after operation or the final follow-up (all P>0.05). The values of VAS were (2.9±1.0)points, (1.8±0.7)points, (1.8±0.7)points in the robot group at 1 day after operation, 1 year after operation and the final follow-up, respectively, which were significantly lower than (4.4±1.1)points, (3.1±0.8)points, (3.0±0.9)points in the conventional group (all P<0.01). The bone cement leakage occurred in 7 patients in the robot group [8.0%(7/87)] and in 10 in the conventional group [30.3%(10/33)] ( P<0.01). No delayed bone cement displacement [0.0%(0/87)] occurred in the robot group from 1 day after operation to the final follow-up, but 3 patients [9.1%(3/33)] were noted in the conventional group ( P<0.05). Conclusion:Both robot-assisted and conventional fluoroscopy-guided PVP combined with pediculoplasty have satisfactory effect for SCOVF patients without neurological impairment, but the robot-assisted one has the advantages of higher puncture accuracy, more satisfactory vertebral height recovery, more rapid pain relief, lower incidence of bone cement leakage and effective avoidance of cement displacement.

Abstract OBJECTIVE To construct an intelligent medical supply chain management platform and explore the closed-loop management model of the entire medical supply chain process. METHODS Identify the problems in the traditional drug supply chain management model of medical institutions and propose the idea of building an intelligent medical supply chain management platform. At the same time, systematically introduce the architecture and management of this platform and evaluates its application effect. RESULT After the implementation of the platform, notable enhancements had been observed in the hospital drug supply chain regarding information and intelligence. Moreover, the work efficiency of the hospital drug supply chain had been improved, facilitated the interconnection of drug information between medical institutions, designated medical security information platforms, and pharmaceutical enterprises. Furthermore, the platform had successfully facilitated "resource sharing and technical support" among these three entities, enabling comprehensive traceability of the entire drug supply chain within the region. CONCLUSION Building an intelligent medical supply chain management platform based on internet information technology can help promote digital reform in hospitals, strengthen pharmaceutical management levels, improve medical service quality and has widespread application value within the industry.

Objective:To compare the abilities of different neural networks to generate pseudo-computed tomography (CT) images from magnetic resonance imaging (MRI) images and to explore the feasibility of pseudo-CT for clinical radiotherapy planning.Methods:A total of 29 brain cancer patients with planning CT and diagnostic MRI were selected. 23 of these patients were used for training neural networks and 6 for testing pseudo-CT images. Cycle-consistent generative adversarial network (cycleGAN), contrastive learning for unpaired image-to-image translation (CUT), and improved network denseCUT proposed in this study were applied to generate pseudo-CT images from MRI images. The pseudo-CT images were imported into a clinical treatment planning system to verify the feasibility of applying this method to radiotherapy planning.Results:The comparison between the generated pseudo-CT images and real CT images showed that the mean absolute errors were (72.0±6.9), (72.5±8.0), and (64.6±7.3) HU for the cycleGAN, CUT, and denseCUT, respectively. Meanwhile, the structure similarity indices were 0.91±0.01, 0.91±0.01, and 0.93±0.01, respectively. The peak signal-to-noise ratios were (28.5±0.7), (28.5±0.7), and (29.5±0.7) dB, respectively. The 2%/2 mm γ passing rates were 98.05%, 97.92%, and 98.31% for the cycleGAN, CUT, and denseCUT, respectively.Conclusions:DenseCUT can generate more accurate pseudo-CT images and the pseudo-CT can meet the demand for the dose calculation of IMRT plan.