Glaucoma is a group of optic nerve disorders characterized by progressive optic nerve atrophy and visual field defects, which can lead to irreversible blindness. Early diagnosis of glaucoma is essential for preventing visual loss. However, due to the absence of obvious early symptoms, the diagnosis of glaucoma remains challenging. Visual electrophysiological examinations, an objective approach for evaluating visual function, have the potential to be used in the early diagnosis of glaucoma. This review integrates the latest publications to introduce visual electrophysiological examination techniques, including electroretinography(ERG)and visual evoked potential(VEP). It also explores the mechanisms underlying these techniques and their application value in the early diagnosis of glaucoma. In addition, this review summarizes the advantages, limitations, and applicable scenarios of different visual electrophysiological techniques. Finally, the review provides an outlook on the development prospects of visual electrophysiological techniques in the early diagnosis of glaucoma. The findings of this review can assist clinicians in selecting appropriate diagnostic methods, promote the innovation and development of early visual electrophysiological diagnostic techniques for glaucoma, and contribute to reducing the risk of blindness caused by glaucoma.

Objective To construct a risk prediction model for healthcare-associated infection(HAI)in stroke pa-tients,accurately and effectively screen out potential high-risk groups,and formulate targeted preventive interven-tions to reduce the occurrence of infection.Methods Stroke patients in the"Henan Stroke Cohort"in 2019-2021 were selected as the study objects,and relevant clinical data were collected as the main analysis data for model con-struction and internal validation.The relevant data of stroke patients in three hospitals that had never participated in the cohort construction from January to September 2022 were randomly selected as a test set for external validation of the risk prediction model.The main analysis data were randomly divided into a training set and a test set,and a risk prediction model was constructed based on logistic regression,artificial neural network(ANN)algorithm,extreme gradient boosting algorithm and random forest algorithm,respectively.Multiple indicators were used to evaluate the prediction performance of the model,and the optimal model was externally validated based on the test set data.Results The infection rate of stroke patients was 20.6％in the main analysis data and 56.4％in the test set data.The accuracy of the risk prediction model based on logistic regression was 91.2％,the area under the re-ceiver operating characteristic(ROC)curve(AUC)was 0.938,the precision rate,recall rate,specificity,and the F1 score were 0.851,0.695,0.968,and 0.765,respectively.The accuracy rate,precision rate,specificity and AUC of the logistic risk prediction model and the ANN risk prediction model were all significantly better than other models,while the recall rate and F1 score of the logistic risk prediction model were slightly better than the ANN risk prediction model.The logistic risk prediction model had excellent prediction performance in external validation.Conclusion HAI risk prediction model of stroke patients based on logistic regression can better screen out high-risk stroke patients with infection risk,and can contribute to formulate targeted preventive interventions to reduce the occurrence of infection.

Objective To observe the efficacy and safety of Morinda officinalis oligosaccharides in the continuation treatment of mild and moderate depression.Methods An open,single-arm,multi-center design was adopted in our study.Adult patients with mild and moderate depression who had received acute treatment of Morinda officinalis oligosaccharides were enrolled and continue to receive Morinda officinalis oligosaccharides capsules for 24 weeks,the dose remained unchanged during continuation treatment.The remission rate,recurrence rate,recurrence time,and the change from baseline to endpoint of Hamilton Depression Scale(HAMD),Hamilton Anxiety Scale(HAMA),Clinical Global Impression-Severity(CGI-S)and Arizona Sexual Experience Scale(ASEX)were evaluated.The incidence of treatment-related adverse events was reported.Results The scores of HAMD-17 at baseline and after treatment were 6.60±1.87 and 5.85±4.18,scores of HAMA were 6.36±3.02 and 4.93±3.09,scores of CGI-S were 1.49±0.56 and 1.29±0.81,scores of ASEX were 15.92±4.72 and 15.57±5.26,with significant difference(P＜0.05).After continuation treatment,the remission rate was 54.59％(202 cases/370 cases),and the recurrence rate was 6.49％(24 cases/370 cases),the recurrence time was(64.67±42.47)days.The incidence of treatment-related adverse events was 15.35％(64 cases/417 cases).Conclusion Morinda officinalis oligosaccharides capsules can be effectively used for the continuation treatment of mild and moderate depression,and are well tolerated and safe.

ObjectiveDetection and quantification of RNA synthesis in cells is a widely used technique for monitoring cell viability, health, and metabolic rate.After exposure to environmental stimuli, both the internal reference gene and target gene would be degraded. As a result, it is imperative to consider the accurate capture of nascent RNA and the detection of transcriptional levels of RNA following environmental stimulation. This study aims to create a Click Chemistry method that utilizes its property to capture nascent RNA from total RNA that was stimulated by the environment. MethodsThe new RNA was labeled with 5-ethyluridine (5-EU) instead of uracil, and the azido-biotin medium ligand was connected to the magnetic sphere using a combination of “Click Chemistry” and magnetic bead screening. Then the new RNA was captured and the transcription rate of 16S rRNA was detected by fluorescence molecular beacon (M.B.) and quantitative reverse transcription PCR (qRT-PCR). ResultsThe bacterial nascent RNA captured by “Click Chemistry” screening can be used as a reverse transcription template to form cDNA. Combined with the fluorescent molecular beacon M.B.1, the synthesis rate of rRNA at 37℃ is 1.2 times higher than that at 15℃. The 16S rRNA gene and cspI gene can be detected by fluorescent quantitative PCR,it was found that the measured relative gene expression changes were significantly enhanced at 25℃ and 16℃ when analyzed with nascent RNA rather than total RNA, enabling accurate detection of RNA transcription rates. ConclusionCompared to other article reported experimental methods that utilize screening magnetic columns, the technical scheme employed in this study is more suitable for bacteria, and the operation steps are simple and easy to implement, making it an effective RNA capture method for researchers.

Diabetic retinopathy (DR) is a diabetic ocular complication that can lead to poor vision and blindness. This experiment aimed to investigate the ameliorative effect and its mechanism of Panax notoginseng saponins (PNS) eye drops on streptozotocin (STZ)-induced non-proliferative diabetic retinopathy (NPDR) in rats. All experiments were approved by the Animal Research Committee of Shanghai University of Traditional Chinese Medicine. Animal welfare and the animal experimental protocols were strictly consistent with related ethics regulations of Shanghai University of Traditional Chinese Medicine (No. PZSHUTCM 211115004). Diabetes mellitus was induced by a single intraperitoneal injection of STZ into rats. Two months later, PNS solution was dropped binocular twice per day at 6 h intervals at dose of 20, 40, and 80 mg·kg^-1 continuously for 1 month. The morphological structure and activation of microglia of the retina were observed by hematoxylin-eosin staining and immunohistochemical assay. The disruption of the blood-retina barrier (BRB) was conducted by the Evans blue dye leakage assay. The number of acellular capillaries in the retina was assessed by digesting and hematoxylin-eosin staining assay. The number of retinal leukocyte adhesion was observed by fluorescein isothiocyanate-coupled concanavalin A lectin labeling assay. The serum expression of inflammatory factors was measured using enzyme-linked immunosorbent assay. Western blot experiments were used to detect the expression of relevant proteins in retinal tissue and transcriptional activation of nuclear factor kappa-B (NF-κB). The results revealed that PNS eye drops significantly increased the thickness of the retina, decreased the number of acellular capillaries, and up-regulated the expression of the tight junction proteins claudin-1 and occludin, thereby alleviating BRB damage. In addition, PNS eye drops were also able to significantly reduce leukocyte adhesion and microglia activation, the expression of inflammatory factors in serum, and the nuclear translocation of retinal p65 proteins, effectively inhibiting the occurrence of retinal inflammation. The above results showed that PNS eye drops played a role in improving NPDR by inhibiting the activation of the NF-κB signaling pathway and reducing inflammation.

Objective To investigate the expression of Nanog and its regulatory relationship with MMP-2/MMP-9 proteins in esophageal squamous cell carcinoma(ESCC).Methods We detected Nanog and MMP-2/MMP-9 protein expressions in 127 ESCC tissues and 82 adjacent normal tissues using immunohistochemistry and explored their correlations with the clinicopathological parameters and prognosis of the patients.GEO database was utilized to analyze the pathways enriched with the stemness-related molecules including Nanog,and TIMER online tool was used to analyze the correlations among TβR1,MMP-2,and MMP-9 in esophageal cancer.Results Nanog and MMP-2/MMP-9 proteins were significantly upregulated in ESCC tissues and positively intercorrelated.Their expression levels were closely correlated with infiltration depth and lymph node metastasis of ESCC but not with age,gender,or tumor differentiation.The patients with high expressions of Nanog and MMP-2/MMP-9 had significantly shorter survival time.Bioinformatics analysis showed enrichment of stemness-associated molecules in the TGF-β signaling pathway,and the expressions of MMP-2/MMP-9 and TβR1 were positively correlated.In cultured ESCC cells,Nanog knockdown significantly decreased the expression of TβR1,p-Smad2/3,MMP-2,and MMP-9 and strongly inhibited cell migration.Conclusion The high expressions of Nanog,MMP-2,and MMP-9,which are positively correlated,are closely related with invasion depth,lymph node metastasis,and prognosis of ESCC.Nanog regulates the expressions of MMP-2/MMP-9 proteins through the TGF-β signaling pathway,and its high expression promotes migration of ESCC cells.

Objective:To investigate the diagnostic value of serum ferritin in intestinal failure-associated liver disease. Methods:Clinical data of adult patients with short bowel syndrome admitted to the Department of General Surgery of Jinling Hospital affiliated to Nanjing University from January 2019 to December 2022 were retrospectively analyzed to determine the correlation between serum ferritin and liver enzyme profiles by linear regression,to screen the potential risk factors of liver injury by multifactorial Logistic regression analysis,and to establish a prediction model for liver fibrosis. The area under the curve was also calculated to assess the accuracy of the model. Results:A total of 106 patients with short bowel syndrome were included,of whom 55 (51.9％) had elevated serum ferritin (SF). Linear regression analysis showed a positive correlation between serum ferritin and ALT (r=0.427,P<0.001),ALP (r=0.365,P<0.001),and γ-GT (r=0.423,P<0.001),and one-way Logistic regression analysis showed that the higher the level of serum ferritin,the more pronounced the difference was (SF>ULN) The one-way logistic regression analysis showed that the higher the serum ferritin level,the more significant the difference was[SF>ULN (upper limit of normal value of serum ferritin),P=0.033;SF>1.5×ULN,P=0.018;SF>2.5×ULN,P=0.006]. Multifactorial logistic regression analysis showed that PN dependence (OR=3.366,P=0.017) and serum ferritin>2.5 ULN (OR=3.292,P=0.014)were independent risk factors for intestinal failure-associated liver disease-liver fibrosis,and the receiver operating curve (ROC) of the subjects showed area under the curve of 74.8％,95％ CI:0.652～0.844. Conclusion:Serum ferritin can be used as a reliable clinical biomarker to help identify intestinal failure-associated liver disease.

Objective To investigate the expression of Nanog and its regulatory relationship with MMP-2/MMP-9 proteins in esophageal squamous cell carcinoma(ESCC).Methods We detected Nanog and MMP-2/MMP-9 protein expressions in 127 ESCC tissues and 82 adjacent normal tissues using immunohistochemistry and explored their correlations with the clinicopathological parameters and prognosis of the patients.GEO database was utilized to analyze the pathways enriched with the stemness-related molecules including Nanog,and TIMER online tool was used to analyze the correlations among TβR1,MMP-2,and MMP-9 in esophageal cancer.Results Nanog and MMP-2/MMP-9 proteins were significantly upregulated in ESCC tissues and positively intercorrelated.Their expression levels were closely correlated with infiltration depth and lymph node metastasis of ESCC but not with age,gender,or tumor differentiation.The patients with high expressions of Nanog and MMP-2/MMP-9 had significantly shorter survival time.Bioinformatics analysis showed enrichment of stemness-associated molecules in the TGF-β signaling pathway,and the expressions of MMP-2/MMP-9 and TβR1 were positively correlated.In cultured ESCC cells,Nanog knockdown significantly decreased the expression of TβR1,p-Smad2/3,MMP-2,and MMP-9 and strongly inhibited cell migration.Conclusion The high expressions of Nanog,MMP-2,and MMP-9,which are positively correlated,are closely related with invasion depth,lymph node metastasis,and prognosis of ESCC.Nanog regulates the expressions of MMP-2/MMP-9 proteins through the TGF-β signaling pathway,and its high expression promotes migration of ESCC cells.

Following the principles of evidence-based medicine,in accordance with the structure and drafting rules of standardized documents,based on literature research,according to the characteristics of chronic cough in children and issues that need to form a consensus,the TCM Guidelines for Diagnosis and Treatment of Chronic Cough in Children was formulated based on the Delphi method,expert discussion meetings,and public solicitation of opinions.The guideline includes scope of application,terms and definitions,eti-ology and diagnosis,auxiliary examination,treatment,prevention and care.The aim is to clarify the optimal treatment plan of Chinese medicine in the diagnosis and treatment of this disease,and to provide guidance for improving the clinical diagnosis and treatment of chronic cough in children with Chinese medicine.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.