Pterygium, a common ocular surface disorder characterized by the abnormal growth of conjunctival tissue onto the cornea, often necessitates surgical excision as its primary treatment. While effective, pterygium surgery is frequently associated with a spectrum of postoperative complications that significantly impact patient prognosis and quality of life. This comprehensive review systematically analyzes the classification, underlying pathophysiological mechanisms, and associated risk factors of these complications, with a particular focus on less commonly explored entities such as postoperative granuloma(PPG), corneal dellen, and scleral necrosis, alongside the more prevalent issue of recurrence. We delineate these complications based on their temporal presentation(early, intermediate, and late), and provide an in-depth analysis of general and specific contributing factors, including surgical trauma, individual patient characteristics, surgical technique, and perioperative management. Furthermore, this review synthesizes advancements in preventive strategies and therapeutic interventions, encompassing refined surgical techniques [e.g., femtosecond laser-assisted pterygium surgery(FLAPS), pterygium extended removal followed by extended conjunctival transplant(P.E.R.F.E.C.T.)technique, Tissue Tuck technique], judicious application of adjuvant therapies [e.g., mitomycin C(MMC), 5-fluorouracil(5-FU), corticosteroids, anti-vascular endothelial growth factor(VEGF)agents], and optimized postoperative care protocols. By consolidating current evidence and identifying future research priorities, this review aims to provide ophthalmologists with a valuable theoretical foundation to guide individualized surgical planning, dynamic postoperative management, and ultimately minimize complications and improve patient satisfaction.

Objective: To investigate the epidemiological characteristics and spatial-temporal clustering characteristics of scarlet fever in Jinhua City, Zhejiang Province from 2005 to 2023, so as to provide a reference for improving the prevention and control strategy of scarlet fever. Methods: The data of scarlet fever cases in Jinhua City from 2005 to 2023 were collected from the China Information System for Disease Control and Prevention, and descriptive epidemiological method was used to analyze the epidemiological characteristics of scarlet fever. The average annual percent change (AAPC) was calculated to analyze the trend of scarlet fever incidence from 2005 to 2023. The spatial-temporal clustering of scarlet fever was identified using spatial autocorrelation analysis and space-time scanning analysis. Results: A total of 1 494 scarlet fever cases were reported in Jinhua City from 2005 to 2023, and the average annual reported incidence rate was 1.41/100 000, with no significant change trend (AAPC=1.706%, P>0.05). There were two incidence peaks, from April to June and from November to January of the next year. There were 937 males and 557 females, with a male to female ratio of 1.68∶1. The age was mainly <10 years (1 391 cases, 93.11%), of which 3-<7 years was the high incidence age group (936 cases, 62.65%). There were 1 466 cases of preschool children, students, and scattered children, accounting for 98.13%. The average annual reported incidence of scarlet fever in Dongyang City, Pujiang County, and Yongkang City was 4.58/100 000, 3.04/100 000, and 1.99/100 000, respectively. The spatial autocorrelation analysis showed that there was a positive spatial correlation between the incidence of scarlet fever in Jinhua City from 2005 to 2023 (Moran's I=0.579, P<0.05), and the high-high clustering areas were mainly distributed in Dongyang City and Pujiang County. The spatial-temporal scanning analysis showed that there were 8 spatial-temporal clustering areas of scarlet fever in Jinhua City from 2005 to 2023. The class Ⅰ clustering area was 9 towns in Dongyang City, and the clustering period was from August 2013 to December 2022. There were 7 class Ⅱ clusters, covering some streets in Pujiang County, Dongyang City, Yongkang City, Yiwu City, and Pan'an County. Conclusions From 2005 to 2023, the incidence of scarlet fever in Jinhua City was relatively low, and children aged 3-<7 years had a high incidence, and there was a spatiotemporal clustering. The peak incidence was from April to June and from November to January of the next year. Dongyang City, Pujiang County, and Yongkang City had high incidence areas.

Objective: To analyze the epidemiological characteristics of leptospirosis in Jinhua City, Zhejiang Province, from 2007 to 2024, so as to provide a basis for improving the prevention and control strategies of leptospirosis. Methods: Data pertaining to leptospirosis cases in Jinhua City from 2007 to 2024 were collected through the Monitoring and Reporting Management System of the Chinese Disease Prevention and Control Information System. Descriptive epidemiological methods were used to analyze the distribution characteristics of leptospirosis in terms of time, region, population, interval from the onset of the disease to diagnosis and the outbreak of the epidemic. Results: A total of 81 cases of leptospirosis were reported in Jinhua City from 2007 to 2024, with an average annual reported incidence of 0.08/100 000. The peak incidence occurred from August to September, with 57 cases accounting for 70.37%. Leptospirosis cases were reported in 9 counties (cities, districts) in Jinhua City. Pan'an County reported the most cases, with 52 cases accounting for 64.20%. There were 54 male cases and 27 female cases, with a male-to-female ratio of 2∶1. The majority of cases were aged over 40 years, with 73 cases accounting for 90.12%. The average reported incidence of leptospirosis showed an upward trend with the increase of age (P<0.05), and the highest incidence of leptospirosis was at the 60-<80 age group (0.21/100 000). The majority of patients were farmers, with 77 cases accounting for 95.06%. The median interval from onset to diagnosis was 4.00 (interquartile range, 6.00) days. There were significant differences in the interval from onset to diagnosis among cases in Dongyang City compared with Pan'an County, Wuyi County, and Wucheng District, between Pan'an County and Jindong District, Wucheng District, and between Wuyi County and Wucheng District (all P<0.05). In 2007, one outbreak of leptospirosis was reported, which occurred in Jiuhe Township, Pan'an County, with 36 reported cases. Conclusions The reported incidence of leptospirosis in Jinhua City from 2007 to 2024 is generally low. The high-incidence period is from August to September, and Pan'an County is the high-incidence area. Males over 40 years and farmers are the key populations for prevention and control. It is recommended to strengthen epidemic surveillance and health education for high-risk populations.

BACKGROUND: Preclinical studies have indicated that Angong Niuhuang Pills (ANP) reduce cerebral infarct and edema volumes. This study aimed to investigate whether ANP safely reduces cerebral infarct and edema volumes in patients with moderate to severe acute ischemic stroke. METHODS: This randomized, double-blind, placebo-controlled pilot trial included patients with acute ischemic stroke with National Institutes of Health Stroke Scale (NIHSS) scores ranging from 10 to 20 in 17 centers in China between April 2021 and July 2022. Patients were allocated within 36 h after onset via block randomization to receive ANP or placebo (3 g/day for 5 days). The primary outcomes were changes in cerebral infarct and edema volumes after 14 days of treatment. The primary safety outcome was severe adverse events (SAEs) for 90 days. RESULTS: There were 57 and 60 patients finally included in the ANP and placebo groups, respectively for modified intention-to-treat analysis. The median age was 66.0 years, and the median NIHSS score at baseline was 12.0. The changes in cerebral infarct volume at day 14 were 0.3 mL and 0.4 mL in the ANP and placebo groups, respectively (median difference: -7.1 mL; interquartile range [IQR]: -18.3 to 2.3 mL, P = 0.30). The changes in cerebral edema volume of the ANP and placebo groups on day 14 were 11.4 mL and 4.0 mL, respectively ( median difference: 3.0 mL, IQR: -1.3 to 9.9 mL, P = 0.15). The rates of SAE within 90 days were similar in the ANP (3/57, 5%) and placebo (7/60, 12%) groups ( P = 0.36). Changes in serum mercury and arsenic concentrations were comparable. In patients with large artery atherosclerosis, ANP reduced the cerebral infarct volume at 14 days (median difference: -12.3 mL; IQR: -27.7 to -0.3 mL, P = 0.03). CONCLUSIONS: ANP showed a similar safety profile to placebo and non-significant tendency to reduce cerebral infarct volume in patients with moderate-to-severe stroke. Further studies are warranted to assess the efficacy of ANP in reducing cerebral infarcts and improving clinical prognosis. TRAIL REGISTRATION Clinicaltrials.gov , No. NCT04475328.
Aged ; Female ; Humans ; Male ; Middle Aged ; Double-Blind Method ; Drugs, Chinese Herbal/adverse effects* ; Ischemic Stroke/drug therapy* ; Pilot Projects ; Stroke/drug therapy* ; Treatment Outcome

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

Endometriosis （EMT） is a common disease with frequent occurrence and difficult to be cured in modern clinical practice of obstetrics and gynaecology. It is characterized by progressively worsening dysmenorrhoea， pelvic mass， and infertility. The incidence of EMT is growing and increasingly younger patients are diagnosed with this disease， which poses a serious threat to the reproductive and psychological health of women of childbearing age and adolescent females. However， the pathogenesis of EMT is still not completely clear， and the disease has a long course. Therefore， developing new therapies is an urgent clinical problem to be solved. Great progress has been achieved in the treatment of EMT with traditional Chinese medicine （TCM）， while the underlying mechanism remains in exploration. Programmed cell death （PCD） is a cell death mode mediated by a variety of bio-molecules with specific signaling cascades. The known PCD processes include apoptosis， pyroptosis， autophagy， ferroptosis， and cuproptosis， which all play a pivotal role in the development of EMT. Researchers have made achievements in the treatment of EMT with TCM， which regulates PCD via multiple pathways， routes， targets， and mechanisms. However， the progress in the regulation of PCD in the treatment of EMT with TCM remains to be reviewed. This paper reviews the research progress in the treatment of EMT with TCM from five PCD processes （apoptosis， pyroptosis， autophagy， ferroptosis， and cuproptosis）， with the aim of providing a theoretical basis for the clinical prevention and treatment of EMT.

Objective:To develop an artificial intelligence (AI) calculation system for the effective withdrawal time of colonoscopy and to evaluate its clinical application value.Methods:First, 17 118 colonoscopy pictures from Renmin Hospital of Wuhan University were used for training and testing to establish a deep convolutional neural network model to recognize various colonoscopy fields. Then this model was integrated with the internal and external recognition model and cecum recognition model developed by the research group to create an AI system for automatic calculation of the effective withdrawal time. Finally, 944 colonoscopy videos from the Endoscopy Center of Renmin Hospital of Wuhan University from July 1, 2020 to October 10, 2020 were included in a retrospective analysis. AI automatic computing system was used to calculate the effective withdrawal time, and 89 of them were manually calculated to evaluate the accuracy of the AI automatic computing system. The remaining 855 cases were divided into two groups according to AI calculations, namely, the effective withdrawal time <6 min group ( n=615) and the effective withdrawal time ≥6 min group ( n=240), and the differences in the overall detection rate of adenoma and polyp were compared and analyzed. Results:The accuracy of AI automatic calculation system for effective withdrawal time reached 92.1% (82/89). The overall adenoma detection rate in the group with effective withdrawal time ≥6 min was 37.5% (90/240), that in the group with effective withdrawal time <6 min was 19.0% (117/615), and the difference was statistically significant ( χ2=32.11, P<0.001). The overall polyp detection rate in the group with effective withdrawal time ≥6 min was 75.0% (180/240), and that in the group with effective withdrawal time <6 min was 45.2% (278/615), with statistical significance ( χ2=61.62, P<0.001). Conclusion:AI automatic computing system can accurately calculate the effective withdrawal time of colonoscopy, and can be used to monitor the effective withdrawal time of clinical colonoscopy. In addition, effective withdrawal time ≥6 min can effectively improve the detection rate of adenoma and polyps.

Objective To observe the mid-and long-term effects of Kegel training combined with Pilates training on urinary conti-nence recovery in different body mass index(BMI)male patients with urinary incontinence after prostatectomy.Methods From May,2023 to June,2024,48 patients in Beijing Bo'ai Hospital were recruited and divided into group A(<25 kg/m2,n=15),group B(25 to 30 kg/m2,n=18)and group C(>30 kg/m2,n=15)according to their BMI.All the groups performed Kegel training combined with Pilates training for two months,and followed up at six months from baseline.They were evaluated with one hour pad test,the number of daily urinary incontinence,In-ternational Consultation on Incontinence Questionnaire-Short Form(ICIQ-SF)and modified Oxford Rating Scale before treatment,and four weeks,eight weeks and six months after treatment.Results The intra-group effect,the inter-group effect and interaction effect were significant in the results of one hour pad test and the daily number of urinary incontinence(F>2.955,P<0.05).Post Hoc test showed that they were worse in group C than in groups A and B(P<0.05),and the number of daily urinary incontinence was more in group B than in group A(P<0.05).There was significant difference in the scores of ICIQ-SF and modified Ox-ford Rating Scale among groups in different time points after treatment(Z>10.476,P<0.05)except the score of ICIQ-SF four weeks after treatment(P>0.05),and they were the worst in group C.BMI(group A=1,group B=2,group C=3)was correlated with the results of one hour pad test(r=0.79,P<0.001),the number of daily uri-nary incontinence(r=0.68,P<0.001),and the scores of ICIQ-SF(r=0.68,P<0.001)and modified Oxford Rating Scale(r=-0.47,P=0.001)six months after treatment.Conclusion Kegel training combined with Pilates training could improve the urinary control in patients with urinary in-continence after prostatectomy.The decrease of BMI can promote the recovery of urinary control,and improve the symptoms of later urinary incontinence in mid-and long-term.

Diamond-Blackfan anemia(DBA),also known as congenital pure red cell aplasia,is a rare genetic disorder characterized by bone marrow failure,congenital anomalies,and severe red blood cell abnormalities.The rarity of the condition,and consequently limited patient pool and scarcity of research models,means that the pathogenic mechanisms associated with genetic mutations in DBA remain uncertain,and the clinical treatment options are limited.This review synthesizes the findings from zebrafish,mouse,and human cellular models of DBA mutations.We clarify the pathogenic mechanisms and monitor the progression of drugs into clinical trials,thereby aiding further in-depth explorations into the etiology and therapeutic advancements for DBA.

Objective:To establish a risk prediction model based on least absolute shrinkage and selection operator (LASSO) regression for procalcitonin (PCT), milk fat globule-epidermal growth factor 8 (MFG-E8) and CXC chemokine ligand 9 (CXCL9) in elderly patients with liver cancer after transcatheter arterial chemoembolization (TACE) .Methods:A total of 150 elderly patients with liver cancer who underwent TACE treatment in Shishi City Hospital, Fujian Province and 910th Hospital of the Chinese People's Liberation Army Joint Logistic Support Force from August 2020 to August 2023 were selected as the study subjects. Patients with infection after TACE were included in the infected group and those without infection were included in the non-infected group according to whether the patients had infection during the postoperative hospitalization. The baseline data of patients were collected and compared. LASSO regression was used to screen the factors that may affect the infection after TACE in elderly patients with liver cancer and binary logistic regression analysis was performed. According to the results of regression analysis, a nomogram model was constructed based on the regression analysis results and the nomogram was internally validated using Bootstrap and receiver operator characteristic (ROC) curves.Results:There were 18 cases of infection in 150 elderly patients with liver cancer after TACE, with an incidence of 12.00%. There were statistically significant differences in focal rupture and bleeding ( χ2=5.92, P=0.015), ascites ( χ2=6.70, P=0.010), skin or mucosal damage ( χ2=6.67, P=0.010) between the infected group ( n=18) and the non-infected group ( n=132). The levels of serum PCT [ (1.17±0.32 ) μg/L vs. (0.91±0.14) μg/L], MFG-E8 [ (194.29±45.85) pg/ml vs. (158.76±28.63) pg/ml] and CXCL9 [ (948.49±52.38) pg/ml vs. (886.05±50.07) pg/ml] were higher than those in the non-infected group, with statistically significant differences ( t=4.13, P<0.001; t=4.55, P<0.001; t=4.94, P<0.001). Four factors related to infection after TACE intervention in patients with liver cancer were finally selected by LASSO regression model, skin or mucosal damage, PCT, MFG-E8, CXCL9 levels. Binary logistic regression analysis showed that skin or mucosal damage ( OR=13.48, 95% CI: 1.29-140.47, P=0.030), high levels of serum PCT ( OR=1.13, 95% CI: 1.05-1.22, P=0.001), MFG-E8 ( OR=1.04, 95% CI: 1.01-1.07, P=0.003), CXCL9 ( OR=1.05, 95% CI: 1.02-1.08, P=0.001) were risk factors for infection after TACE in elderly patients with liver cancer. Based on skin or mucosa damage, PCT, MFG-E8 and CXCL9, a nomogram prediction model for postoperative infection in elderly patients with liver cancer after TACE intervention was established. Calibration curve showed that the C-index of postoperative infection predicted by the nomogram model in elderly patients with liver cancer after TACE intervention was 0.939, indicating the model had good discrimination. ROC curve analysis showed that the area under the curve (AUC) predicted by the nomogram model for infection after TACE intervention in elderly patients with liver cancer was 0.960 (95% CI: 0.926-0.995, P<0.001), which had certain predictive value. The specificity, sensitivity and Youden index were 0.864, 0.944 and 0.808, respectively. Conclusions:Skin or mucosal damage, high levels of serum PCT, CXCL9 and MFG-E8 are closely related to postoperative infection in elderly patients with liver cancer after TACE, and the prediction model constructed based on this has better predictive performance for postoperative infection.