ObjectiveTo investigate the present situation of input, output, outcome and impact of all registered community-based rehabilitation stations in Inner Mongolia in China, and analyze how the input predict the output, outcome and impact. MethodsFrom March 1st to April 30th, 2025, a questionnaire survey was conducted on all registered community-based rehabilitation stations in Inner Mongolia, covering four dimensions: input, output, outcome and impact. A total of 1 365 questionnaires were distributed. The input included four items: laws and policies, human resources, equipment and facilities, and rehabilitation information management. The output included two items: technical paths and benefits/effectiveness. The outcome included three items: coverage rates, rehabilitation interventions and functional results. The impact included two items: health and sustainability. Each item contained several questions, all of which were described in a positive way. Each question was scored from one to five. A lower score indicated that the situation of the community-based rehabilitation station was more in line with the content described in the question. Regression analysis was performed using the total score of each item of input dimension as independent variables, and the total scores of the output, outcome and impact dimensions as dependent variables. ResultsA total of 1 262 valid questionnaires were collected. The mean values of input, output, outcome and impact of community-based rehabilitation stations were 1.827 to 1.904, with coefficient of variation of 45.892% to 49.239%. The regression analysis showed that, rehabilitation information management, human resources, and laws and policies significantly predicted the output dimension (R² = 0.910, P < 0.001). Meanwhile, all four items in the input dimension predicted both the outcome (R² = 0.850, P < 0.001) and impact dimensions (R² = 0.833, P < 0.001). ConclusionInput, output, outcome and impact of the community-based rehabilitation stations in Inner Mongolia were generally in line with the content of the questions, although some imbalances were observed. Additionally, the input of community-based rehabilitation stations could significantly predict their output, outcome and impact.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

OBJECTIVE To optimize the forming process of Yindan huoxue tongyu granules， and evaluate the quality of the granules. METHODS Taking forming rate， angle of repose， moisture， moisture absorption rate and dissolution rate as indexes， single factor experiment combined with Plackett-Burman design was adopted to screen key process parameters； analytic hierarchy process combined with entropy weight method and Box-Behnken response surface method were used to optimize the molding process of Yindan huoxue tongyu granules， and the forming process was verified. The relative homogeneity index， bulk density， vibration density， Hausner ratio， angle of repose， moisture and hygroscopicity were used as secondary physical indexes to establish the physical fingerprints of 10 batches of Yindan huoxue tongyu granules to evaluate particle quality consistency. RESULTS The optimal molding process of Yindan huoxue tongyu granules was as follows： mannitol as the fixed excipient， the drug-assisted ratio was 1∶1（m/m） and the drying time was 1 h； 90% ethanol was used as wetting agent and the amount of it was 32%， the drying temperature was 70 ℃. The results of validation tests showed that the average comprehensive score was 97.45， which was close to the predicted value of 97.18. The similarities between the physical fingerprints of 10 batches of Yindan huoxue tongyu granules prepared by the optimal molding process and the reference physical fingerprint were all higher than 0.99. CONCLUSIONS The molding process is stable and feasible， and the quality of Yindan huoxue tongyu granules produced is stable and controllable.

Objective To compare the performance and efficacy of prognostic models constructed by different machine learning algorithms in predicting the survival period of lung transplantation (LTx) recipients. Methods Data from 483 recipients who underwent LTx were retrospectively collected. All recipients were divided into a training set and a validation set at a ratio of 7:3. The 24 collected variables were screened based on variable importance (VIMP). Prognostic models were constructed using random survival forest (RSF) and extreme gradient boosting tree (XGBoost). The performance of the models was evaluated using the integrated area under the curve (iAUC) and time-dependent area under the curve (tAUC). Results There were no significant statistical differences in the variables between the training set and the validation set. The top 15 variables ranked by VIMP were used for modeling and the length of stay in the intensive care unit (ICU) was determined as the most important factor. Compared with the XGBoost model, the RSF model demonstrated better performance in predicting the survival period of recipients (iAUC 0.773 vs. 0.723). The RSF model also showed better performance in predicting the 6-month survival period (tAUC _{6 months} 0.884 vs. 0.809, P = 0.009) and 1-year survival period (tAUC _{1 year} 0.896 vs. 0.825, P = 0.013) of recipients. Based on the prediction cut-off values of the two algorithms, LTx recipients were divided into high-risk and low-risk groups. The survival analysis results of both models showed that the survival rate of recipients in the high-risk group was significantly lower than that in the low-risk group (P<0.001). Conclusions Compared with XGBoost, the machine learning prognostic model developed based on the RSF algorithm may preferably predict the survival period of LTx recipients.

Objective To introduce the modeling method of pendulum-like modified rat abdominal heart heterotopic transplantation model and evaluate the quality of the model. Methods An operator without transplantation experience performed 15 consecutive models, recorded the time of each step, changes in body weight and modified Stanford scores, and calculated the surgical success rate, postoperative 1-week survival rate and technical success rate. Ultrasound examinations was performed in 1 week postoperatively. Results The times for donor heart acquisition, donor heart processing, recipient preparation and transplantation anastomosis were (14.3±1.4) min, (3.5±0.6) min, (13.6±2.1) min and (38.3±5.2) min respectively. The surgical success rate was 87% (13/15), and the survival rate 1 week after operative was 100% (13/13). The improved Stanford score indicated a technical success rate of 92% (12/13), and the postoperative 1-week ultrasound examination showed that grafts with Stanford scores ≥3 had detectable pulsation and blood flow signals. Conclusions The pendulum-like modified rat abdominal heart heterotopic transplantation improved model further optimizes the operational steps with a high success rate and stable quality, may be chosen as a modeling option for basic research in heart transplantation in the future.

AIM: To analyze the value of blue-on-yellow perimetry(B/Y)combined with macular ganglion cells inner plexiform layer(GCIPL)detection in the early diagnosis of open angle glaucoma.METHODS: A prospective case-control study was conducted to collect 100 patients(174 eyes)from May 2023 to May 2024 in Eye Hospital of Wenzhou Medical University as the case group, and 20 healthy volunteers(40 eyes)as the control group. The case group was divided into high intraocular pressure group, suspected glaucoma group, and early glaucoma group based on the examination results. All study subjects underwent comprehensive ophthalmic examination, white-on-white perimetry(W/W)and B/Y examination, and swept source optical coherence tomography(SS-OCT)was used to scan the optic disc and macula to obtain relevant parameters. The value of B/Y combined with macular GCIPL in the diagnosis of open angle glaucoma was analyzed.RESULTS: In the case group, 30 cases(52 eyes)were diagnosed with early primary open angle glaucoma, 46 cases(82 eyes)were suspected of open angle glaucoma, and 24 cases(40 eyes)were diagnosed with high intraocular pressure. The W/W mean defect(MD)and B/Y-MD values in the early glaucoma group were lower than those in the control group, high intraocular pressure group, and suspected glaucoma group. The W/W pattern standard deviation(PSD)and B/Y-PSD values were higher than those in the control group, high intraocular pressure group, and suspected glaucoma group(all P<0.05). The W/W-MD and B/Y-MD values in the suspected glaucoma group were lower than those in the control group and the high intraocular pressure group(all P<0.05). The B/Y-MD values in the high intraocular pressure group were lower than those in the control group(P<0.05). The parameters of GCIPL in the macular area of the early glaucoma group were lower than those of the control group, high intraocular pressure group, and suspected glaucoma group(all P<0.05). The minimum GCIPL in the macular area of the suspected glaucoma group, as well as the upper and lower temporal areas, were lower than those of the control group and the high intraocular pressure group(all P<0.05). The average, upper, lower, temporal, 5:00, 6:00, and 12:00 positions of the retinal nerve fiber layer(RNFL)parameters around the optic disc in the early glaucoma group were lower than those in the control group, high intraocular pressure group, and suspected glaucoma group(all P<0.05). The average and upper RNFL parameters in the suspected glaucoma group were lower than those in the control group and high intraocular pressure group. The rim area of the optic nerve head(ONH)parameters in the early glaucoma group was smaller than that in the control group, high intraocular pressure group, and suspected glaucoma group, while the horizontal and vertical cup-to-disc ratio was higher than those in the control group, high intraocular pressure group, and suspected glaucoma group; the rim area of the suspected glaucoma group was smaller than that of the control group and high intraocular pressure group, and the horizontal and vertical cup-to-disc ratio were higher than those of the control group and high intraocular pressure group(all P<0.05). Receiver operating characteristic(ROC)curve was drawn, and the results showed that visual field parameters, macular GCIPL parameters, and RNFL parameters had certain diagnosibility for early open angle glaucoma and suspected glaucoma. Decision curve was drawn, and the results showed that when the threshold was between 0 and 1.0, the net return rate of diagnosing early open angle glaucoma with the combination of B/Y and macular GCIPL parameters was higher than the individual diagnostic efficacy of each indicator.CONCLUSION: The combination of B/Y and macular GCIPL detection can be an important means for the early diagnosis of glaucoma.

AIM: To analyze the changes of retinal structure and function before and after panretinal photocoagulation(PRP)in patients with proliferative diabetic retinopathy(PDR).METHODS: Prospective study. Totally 98 cases(98 eyes)of PDR patients who underwent PRP in Eye Hospital of Wenzhou Medical University from January 2022 to May 2023 were included. Optical coherence tomography angiography(OCTA)was used to detect central retinal thickness(CRT), central macular thickness(CMT), subfoveal choroidal thickness(SFCT), foveal avascular zone(FAZ), deep vascular complex(DVC)blood flow density, superficial vascular complex(SVC)blood flow density before and at 1 wk, 1 and 3 mo after PRP. During the follow-up, 1 eye underwent vitrectomy, 2 eyes were lost to follow-up, and finally 95 eyes completed 1 a follow-up, with a loss rate of 3%. According to the visual prognosis at 1 a after treatment, the patients were divided into two groups: 73 eyes in good prognosis group and 22 eyes in poor prognosis group(including 9 eyes of visual disability and 13 eyes of visual regression). The changes in retinal structure and function before and after PRP treatment were compared between the two groups of patients, and the receiver operating characteristic(ROC)curve and decision curve were used to analyze the predictive value of retinal structure and function for PDR treatment.RESULTS: There were statistical significant differences in PDR staging, CRT, CMT, SFCT, DVC blood flow density, and SVC blood flow density between the two groups of patients before treatment(all P<0.05). At 1 wk, 1 and 3 mo after treatment, the FAZ area of both groups decreased compared to before treatment, while the blood flow density of DVC and SVC increased compared to before treatment(both P<0.05). However, there was no significant difference in the blood flow density of FAZ, DVC, and SVC between the two groups at 1 wk, 1 and 3 mo after treatment(all P>0.05). The CRT, CMT and SFCT of the two groups at 1 wk after treatment were higher than those before treatment(all P<0.05), but there were no significant differences between the two groups(all P>0.05). The CRT, CMT and SFCT at 1 and 3 mo after treatment were lower than those at 1 wk after treatment and before treatment in both groups. The CRT, CMT and SFCT in the poor prognosis group at 3 mo after treatment were higher than those at 1 mo after treatment, and were higher than those in the good prognosis group(all P<0.05). ROC analysis showed that, at 3 mo after laser treatment in PDR patients, the area under the curve of the CRT, CMT, and SFCT alone or in combination after treatment for 1 a was 0.788, 0.781, 0.783, and 0.902, respectively, and the combined prediction value was better(P<0.05). Decision curve analysis showed that the combined detection of CRT, CMT, and SFCT in PDR patients at 3 mo after treatment can improve the predictive value of visual prognosis.CONCLUSION: The optimal time for retinal structure and function recovery in PDR patients after PRP treatment is between 1 wk and 1 mo. OCTA measurement of CRT, CMT, and SFCT at 3 mo after treatment can predict the visual prognosis during the 1 a treatment period.

Patients with alcoholic cirrhosis often experience varying degrees of malnutrition， and the patients with malnutrition are more susceptible to complications such as infections and ascites， which may lead to a poor prognosis. Therefore， it is particularly important to conduct nutritional risk screening for patients in clinical practice， and appropriate nutritional assessment tools should be used to evaluate the nutritional status of patients and develop individualized nutritional supplementation regimens， thereby promoting disease recovery and improving prognosis and quality of life. This article elaborates on the specific methods for nutritional screening， assessment， and management in patients with alcoholic cirrhosis and points out that systematic nutritional screening and assessment can help to identify the patients with malnutrition in the early stage and provide timely intervention. Individualized nutritional supplementation regimens should be adjusted based on the conditions of patients， so as to meet their nutritional needs， promote the recovery of liver function， improve overall health status， and enhance long-term quality of life.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Methods: Seventy-five patients with atlas fracture were included from January 2015 to December 2020. Based on the anatomy of the fracture line, atlas fractures were divided into three types. Each type was divided into two subtypes according to the fracture displacement. Unweighted Cohen kappa coefficients were applied to evaluate the reliability and reproducibility. Results: According to the new classification, 17 cases of type A1, 12 of type A2, seven of type B1, 13 of type B2, 12 of type C1, and 14 of type C2 were identified. The K-values of the interobserver and intraobserver reliability were 0.846 and 0.912, respectively, for the new classification. The K-values of interobserver reliability for types A, B, and C were 0.843, 0.799, and 0.898, respectively. The K-values of intraobserver reliability for types A, B, and C were 0.888, 0.910, and 0.935, respectively. The mean K-values of the interobserver and intraobserver reliability for subtypes were 0.687 and 0.829, respectively. Conclusions The new classification of atlas fractures can cover nearly all atlas fractures. This system is the first to evaluate the severity of fractures based on the C1 articular facet and fracture displacement and strengthen the anatomy ring of the atlas. It is concise, easy to remember, reliable, and reproducible.