OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

BACKGROUND:Currently,there are many modeling methods for pelvic organ prolapse animal models,and the commonly used methods are vaginal balloon dilatation,oophorectomy and the combination of the two.There is no study comparing the three modeling methods in detail.OBJECTIVE:To construct and validate a rat animal model of pelvic organ prolapse using three different methods and to identify the advantages and disadvantages of various models.METHODS:Seventy-two 8-week SPF-grade female Sprague-Dawley rats were selected and randomly divided into four groups,namely,vaginal balloon dilatation group,ovariectomy group,ovariectomy combined with vaginal balloon dilatation group(the combined group),and the sham-operated group(no ovariectomy and no vaginal dilatation).The vaginal wall tissues of rats were collected at 4,8 and 12 weeks after the operation for hematoxylin-eosin staining,Masson staining,EVG staining and immunohistochemical staining of α-smooth muscle actin,Vimentin and matrix metalloproteinase 9 detection,and the pelvic floor muscle tissues were taken at 4,8 and 12 weeks after the operation for hematoxylin-eosin staining,Masson staining and EVG staining.RESULTS AND CONCLUSION:(1)Hematoxylin-eosi staining showed that there was no significant difference in the decrease of vaginal epithelial layer thickness in the vaginal balloon dilatation group compared with the sham-operated group,(P＞0.05),while the thickness of the vaginal epithelial layer was significantly reduced in the ovariectomy group and the ovariectomy combined with vaginal balloon dilation group(P＜0.001),and the reduction was more significant in the ovariectomy combined with vaginal balloon dilation group,remained stable at 8 weeks after surgery and lasted until 12 weeks.(2)The changes in the content of collagen fibers and elastic fibers in the vaginal wall stained by Masson and EVG staining were the same as the changes in the thickness of the vaginal epithelial layer stained by hematoxylin-eosin,and there were no changes in collagen fibers and elastic fibers in the pelvic floor muscle tissues of the treatment groups.(3)At 4,8 and 12 weeks after treatment,there was no significant difference in the expression levels of α-smooth muscle actin,Vimentin and matrix metalloproteinase 9 in the vaginal wall tissue of the balloon dilation group compared with the control group(P＞0.05),whereas the expression levels of α-smooth muscle actin and Vimentin were significantly decreased in the ovariectomy group and ovariectomy combined with vaginal balloon dilation group(P＜0.01)and the expression of matrix metalloproteinase 9 showed a significant increase(P＜0.01),with a more pronounced increase in the ovariectomy combined with vaginal balloon dilation group,and the increase reached a stable state at 8 weeks after surgery and could persist up to 12 weeks.To conclude,vaginal balloon dilatation could not maintain the degeneration of pelvic organ prolapse formed by the vaginal wall for a long period,and both ovariectomy and the combined method can be used.Ovariectomy combined with vaginal balloon dilatation can significantly accelerate and aggravate the formation of typical histological features of pelvic organ prolapse in vaginal wall tissues,effectively shorten the experimental period,and improve the efficiency.These effects reach a stable state at 8 weeks after surgery and can be sustained up to 12 weeks,which is practical and convenient for the study of pelvic organ prolapse animal models.

BACKGROUND:Type 2 diabetes mellitus is a secondary causative factor for osteoporosis.As highly heterogeneous innate immune cells,macrophages may be polarized in a hyperglycemic environment,which affects osteogenesis-angiogenesis coupling.This may be a research target for improving bone quality in patients with type 2 diabetic osteoporosis.OBJECTIVE:To explore the role of modulating macrophage M1/M2 polarization to influence osteogenesis-angiogenesis coupling in type 2 diabetic osteoporosis and to summarize the effects of commonly used anti-glucose and anti-osteoporosis drugs and bone biorepair materials on bone osteogenesis-angiogenesis coupling by regulating macrophage M1/M2 polarization.METHODS:The keywords of"macrophage polarization,type 2 diabetes,osteoporosis,osteogenesis-angiogenesis coupling"in Chinese and"macrophages,macrophage polarization,osteogenesis-angiogenesis coupling"in English were used to search for relevant literature in CNKI and PubMed,respectively.Seventy-nine pieces of literature were screened and analyzed.RESULTS AND CONCLUSION:(1)Type 2 diabetes mellitus causes the body to be in a hyperglycemic environment and increases the secretion of inflammatory-related factors in the body,which promotes macrophage polarization towards M1 and decreases the number of M2 macrophages.(2)In type 2 diabetes,promoting M2 macrophage polarization is beneficial for osteogenesis-angiogenesis coupling.(3)Some anti-glycemic drugs,active ingredients in traditional Chinese medicine and bone biorepair materials can improve type 2 diabetic osteoporosis by regulating macrophage M1/M2 polarization,reducing M1/M2 ratio,and promoting osteogenesis-angiogenesis coupling.

OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

AIM: To evaluate the efficacy and safety of 3% diquafosol sodium eye drops in children wearing orthokeratology lenses and with dry eye disease(DED)or at risk of DED.METHODS: Randomized controlled trials. Children with DED or at risk of DED were randomly assigned in a 1:1 ratio to receive either 3% diquafosol sodium eye drops 6 times daily or a blank control at Chongqing Aier Children's Eye Hospital from November 2023 to November 2024. The primary endpoint was the change in the Dry Eye Questionnaire-5(DEQ-5)score from baseline at 12 wk. Secondary assessments included non-invasive breakup time(NIBUT), tear meniscus height, Schirmer's test, corneal fluorescein staining score, and axial length.RESULTS: A total of 80 participants(80 eyes)were enrolled(40 in each group), the average age of the participants was 11.11±1.88 years, with 43 females(54%)and 37 males(46%), and all completed the trial. After 12 wk, the DEQ-5 scores for the diquafosol sodium group and the blank control group were 1.88±2.02 and 2.88±2.79, respectively(P=0.079). The diquafosol sodium group demonstrated a significant improvement in DEQ-5 dryness symptom scores(-0.33±0.66 vs. 0.05±0.81, P=0.023)and NIBUT(6.18±3.73 vs. -1.09±4.40 s, P<0.001)at 12 wk. Additionally, the diquafosol sodium group showed no axial length elongation, in contrast to the blank control group, which exhibited elongation(0.00±0.08 vs. 0.05±0.10 mm, P=0.013). No other significant differences were found in the secondary endpoints. No adverse events occurred during the trial.CONCLUSION: Although no statistically significant improvements were noted in the overall DEQ-5 scores, the 3% diquafosol sodium eye drops significantly improved dryness symptoms and NIBUT when compared to the blank control group.

ObjectiveTo investigate the effect of Toxoplasma gondii infection on copper metabolism in the kidneys of mice. MethodsA total of 80 7-8-week-old C57BL/6 female mice were randomly divided into four groups of 20 mice in each group after one week of adaptation， including Control group， Cu group， TgCtwh6 group and Cu+TgCtwh6 group. Mice that were not infected and fed with normal diet and water were used as the Control group； Mice fed with 1 g/kg of copper chloride processing diet and 0.1% copper chloride water for 60 consecutive days were used as Cu group； Mice infected with 25-30 TgCtwh6 cysts （one of the predominant genotype Chinese 1 in China） fed with normal diet and water were used as the TgCtwh6 group； mice infected with 25-30 TgCtwh6 cysts and fed with a processed diet containing 1 g/kg of copper chloride and water with 0.1% copper chloride for 60 consecutive days were used as the Cu+TgCtwh6 group. ICP-MS was used to determine the changes in copper content in kidney tissues. Hematoxylin-eosin （HE） staining was used to observe the pathological changes of mouse kidney tissue. The number of apoptotic cells was observed by PI staining. Western blot was used to detect the protein expression levels of glutathione peroxidase 4 （GPX4） and superoxide dismutase （SOD1， SOD2）. RT-qPCR was used to detect the mRNA expression of cuproptosis-related genes. ResultsPathological manifestations such as inflammatory cell infiltration in the Cu group and TgCtwh6 group were seen under the microscope， and the inflammatory infiltrating cells of the renal interstitial were reduced in the Cu+TgCtwh6 group， and the pathological manifestations

Objective To analyze the clinical and therapeutic characteristics of Epstein-Barr virus (EBV)-negative posttransplant lymphoproliferative disease (PTLD) with diffuse large B-cell lymphoma (DLBCL) in the context of specific cases and literature. Methods A case of EBV-negative DLBCL (GCB type) after kidney transplantation is reported. The patient was a 45-year-old male who underwent living-related kidney transplantation in 2016 and has been receiving triple immunosuppressive therapy with tacrolimus, mycophenolate mofetil and methylprednisolone since then. In 2024, the patient presented with intermittent fever, night sweats and gastrointestinal symptoms. The diagnosis was confirmed by endoscopic pathology, immunohistochemical staining and positron emission tomography/computed tomography. The R-CDOP regimen (rituximab + cyclophosphamide + liposomal doxorubicin + vincristine + dexamethasone) was used for treatment. Results The patient was diagnosed with EBV-negative DLBCL (GCB type, Ann Arbor stage Ⅳ B). After 4 cycles of R-CDOP chemotherapy, the efficacy assessment was partial remission, and the transplant kidney function remained stable. Conclusions For EBV-negative PTLD after kidney transplantation, it is necessary to break through the "virus-dependent" diagnostic thinking. In clinical practice, the focus should be on protecting the transplant kidney, and individualized treatment plans should be developed for patients.

BACKGROUND:Currently,there are many modeling methods for pelvic organ prolapse animal models,and the commonly used methods are vaginal balloon dilatation,oophorectomy and the combination of the two.There is no study comparing the three modeling methods in detail.OBJECTIVE:To construct and validate a rat animal model of pelvic organ prolapse using three different methods and to identify the advantages and disadvantages of various models.METHODS:Seventy-two 8-week SPF-grade female Sprague-Dawley rats were selected and randomly divided into four groups,namely,vaginal balloon dilatation group,ovariectomy group,ovariectomy combined with vaginal balloon dilatation group(the combined group),and the sham-operated group(no ovariectomy and no vaginal dilatation).The vaginal wall tissues of rats were collected at 4,8 and 12 weeks after the operation for hematoxylin-eosin staining,Masson staining,EVG staining and immunohistochemical staining of α-smooth muscle actin,Vimentin and matrix metalloproteinase 9 detection,and the pelvic floor muscle tissues were taken at 4,8 and 12 weeks after the operation for hematoxylin-eosin staining,Masson staining and EVG staining.RESULTS AND CONCLUSION:(1)Hematoxylin-eosi staining showed that there was no significant difference in the decrease of vaginal epithelial layer thickness in the vaginal balloon dilatation group compared with the sham-operated group,(P＞0.05),while the thickness of the vaginal epithelial layer was significantly reduced in the ovariectomy group and the ovariectomy combined with vaginal balloon dilation group(P＜0.001),and the reduction was more significant in the ovariectomy combined with vaginal balloon dilation group,remained stable at 8 weeks after surgery and lasted until 12 weeks.(2)The changes in the content of collagen fibers and elastic fibers in the vaginal wall stained by Masson and EVG staining were the same as the changes in the thickness of the vaginal epithelial layer stained by hematoxylin-eosin,and there were no changes in collagen fibers and elastic fibers in the pelvic floor muscle tissues of the treatment groups.(3)At 4,8 and 12 weeks after treatment,there was no significant difference in the expression levels of α-smooth muscle actin,Vimentin and matrix metalloproteinase 9 in the vaginal wall tissue of the balloon dilation group compared with the control group(P＞0.05),whereas the expression levels of α-smooth muscle actin and Vimentin were significantly decreased in the ovariectomy group and ovariectomy combined with vaginal balloon dilation group(P＜0.01)and the expression of matrix metalloproteinase 9 showed a significant increase(P＜0.01),with a more pronounced increase in the ovariectomy combined with vaginal balloon dilation group,and the increase reached a stable state at 8 weeks after surgery and could persist up to 12 weeks.To conclude,vaginal balloon dilatation could not maintain the degeneration of pelvic organ prolapse formed by the vaginal wall for a long period,and both ovariectomy and the combined method can be used.Ovariectomy combined with vaginal balloon dilatation can significantly accelerate and aggravate the formation of typical histological features of pelvic organ prolapse in vaginal wall tissues,effectively shorten the experimental period,and improve the efficiency.These effects reach a stable state at 8 weeks after surgery and can be sustained up to 12 weeks,which is practical and convenient for the study of pelvic organ prolapse animal models.

BACKGROUND:Type 2 diabetes mellitus is a secondary causative factor for osteoporosis.As highly heterogeneous innate immune cells,macrophages may be polarized in a hyperglycemic environment,which affects osteogenesis-angiogenesis coupling.This may be a research target for improving bone quality in patients with type 2 diabetic osteoporosis.OBJECTIVE:To explore the role of modulating macrophage M1/M2 polarization to influence osteogenesis-angiogenesis coupling in type 2 diabetic osteoporosis and to summarize the effects of commonly used anti-glucose and anti-osteoporosis drugs and bone biorepair materials on bone osteogenesis-angiogenesis coupling by regulating macrophage M1/M2 polarization.METHODS:The keywords of"macrophage polarization,type 2 diabetes,osteoporosis,osteogenesis-angiogenesis coupling"in Chinese and"macrophages,macrophage polarization,osteogenesis-angiogenesis coupling"in English were used to search for relevant literature in CNKI and PubMed,respectively.Seventy-nine pieces of literature were screened and analyzed.RESULTS AND CONCLUSION:(1)Type 2 diabetes mellitus causes the body to be in a hyperglycemic environment and increases the secretion of inflammatory-related factors in the body,which promotes macrophage polarization towards M1 and decreases the number of M2 macrophages.(2)In type 2 diabetes,promoting M2 macrophage polarization is beneficial for osteogenesis-angiogenesis coupling.(3)Some anti-glycemic drugs,active ingredients in traditional Chinese medicine and bone biorepair materials can improve type 2 diabetic osteoporosis by regulating macrophage M1/M2 polarization,reducing M1/M2 ratio,and promoting osteogenesis-angiogenesis coupling.

AIM: To investigate the distribution characteristics of pathogens in patients with post-traumatic infectious endophthalmitis(PTIE)and their relationship with serum levels of macrophage inflammatory protein 1α(MIP-1α), heat shock protein 70(HSP70), and soluble triggering receptor expressed on myeloid cells 1(sTREM-1).METHODS:A total of 157 patients with PTIE from the Handan City Eye Hospital(The Third Hospital of Handan)from May 2023 to May 2025 were selected as the study group. They were divided into a good prognosis group and a poor prognosis group based on their uncorrected visual acuity at discharge. Meanwhile, 157 patients with ocular trauma but without endophthalmitis during the same period were selected as control group 1, and 157 healthy volunteers who underwent physical examinations during the same period were selected as control group 2. Aqueous humor and vitreous fluid samples were collected from the study group to detect the distribution of pathogens. The levels of serum MIP-1α, HSP70, and sTREM-1 were measured using the enzyme-linked immunosorbent assay. Multivariate Logistic regression analysis was performed to identify risk factors for poor prognosis. The predictive value of serum MIP-1α, HSP70, and sTREM-1 levels for poor prognosis was evaluated using receiver operating characteristic(ROC)and decision curve analysis(DCA).RESULTS: The general data of the participants in the three groups was comparable. A total of 173 pathogens were detected in the 157 patients with PTIE, with Gram-positive bacteria being the predominant type. The levels of serum MIP-1α and sTREM-1 in the study group were higher than those in control groups 1 and 2, while the level of HSP70 was lower than those in control groups 1 and 2(all P<0.05). There were no significant differences in the levels of serum MIP-1α, HSP70, and sTREM-1 between control groups 1 and 2(all P>0.05). In the poor prognosis group, the time of wound suture was ≥24 h, the wound location was in zones II/III, the type of trauma was rupture, the proportion of rupture injuries, and the levels of serum C-reactive protein, MIP-1α, and sTREM-1 were higher than those in the good prognosis group, while the level of HSP70 was decreased(all P<0.001). Multivariate Logistic regression analysis showed that the time of wound suture, wound location, type of trauma, C-reactive protein, MIP-1α, HSP70, and sTREM-1 were risk factors for poor visual prognosis in patients with PTIE(all P<0.05). The ROC curve results showed that the combined prediction of serum MIP-1α, HSP70, and sTREM-1 for poor visual prognosis in PTIE patients had an AUC value of 0.965, which was significantly higher than that of individual predictions(ZMIP-1α, ZHSP70, ZsTREM-1=3.628, 4.705, 3.930, all P<0.05). Additionally, the DCA curve showed that the combined prediction had a higher net benefit rate than individual predictions in the high-risk threshold range of 0.03-0.97.CONCLUSION:Gram-positive bacteria are the predominant type of pathogenic bacteria in patients with PTIE, with elevated levels of serum MIP-1α and sTREM-1 and decreased levels of HSP70. The combined detection of these three factors has a high predictive efficacy for visual prognosis in patients.