With the continuous transformation of the digital era and the ongoing collaboration of interdisciplinary fields, specialized applications of artificial intelligence(AI)have already made significant strides in the field of medicine. Given the precision required in ophthalmology and its high demands for intelligent solutions, particularly in the realm of nursing care, this study aims to explore the clinical practices and current status of AI in ophthalmic nursing based on a comprehensive review of domestic literature. Employing a scoping review framework, the research questions were formulated, and relevant studies were retrieved from Wanfang, the China National Knowledge Infrastructure(CNKI), VIP, PubMed, and Web of Science. The search spanned from January 2013 to December 2023. In accordance with inclusion and exclusion criteria, literature screening was conducted, and data extraction was performed on selected articles. A total of 20 articles were included in the review. The development of AI in ophthalmic nursing in China is relatively recent and not yet comprehensive. Continuous innovation in new technologies and projects is required by nursing professionals to effectively integrate with the advancements in intelligent medical care.

ObjectiveTo investigate and analyze an outbreak of rotavirus infectious diarrhea in a prison in Chongqing Municipality, to provide a basis for adult rotavirus surveillance and prevention, and to explore the public health problems in special settings. MethodsA retrospective survey was conducted to collect and analyze data on individual cases with diarrheal disease on-site. The clinical characteristics, as well as the temporal, spatial and geographical distribution patterns of the epidemic were described. Multi-pathogen detection tests were conducted both on diarrhea cases and environmental samples, with viral genotyping performed on positive samples. A case-control analysis was performed to identify the causes of the outbreak, and an SEIR model was adopted to predict the outbreak trend and evaluate the effectiveness of interventions. ResultsA total of 65 cases were found among the inmates, with an attack rate of 2.03%. The predominant clinical manifestations included diarrhea (89.23%), watery stool (73.85%), and dehydration (18.46%). The epidemic curve indicated a “human-to-human” transmission pattern, with an average incubation period of 5‒6 days. The attack rates among chefs in the main canteen (80.00%, 8/10) and caterers (28.33%, 17/60) were significantly higher than those of other inmates （P<0.05）. Multi-pathogen polymerase chain reaction (PCR) testing detected positive for group A rotavirus, with the viral genotyping identified as G9P [8] strain. Factors such as unprotected "bare-handed" food distribution among cases with diarrhea (OR=9.512, 95%CI: 4.261‒21.234) and close contact with diarrhea cases (OR=3.656, 95%CI: 1.719‒7.778) were the possible cause of the outbreak. The SEIR model (r₀=5, α=0.3, β₁=0.08, β₂=0.04) was constructed using prison inmates as susceptible population, aiming at fitting the initial transmission trend of the outbreak, and the epidemic rate declined rapidly after intervention measures were implemented (r_t≈0). ConclusionThis rare rotavirus infection diarrhea outbreak among adults in confined settings suggests that the construction of public health prevention and control systems in prison may be overlooked. Cross infection during meal processing and distribution in the canteens of such settings is likely to be the cause of the outbreak. Given the potential neglect of public heath system construction in special settings, it is imperative to enhance the surveillance and monitoring of rotavirus and other intestinal multi-pathogens among adults, as well as the construction of public health prevention and control systems in these special settings.

Objective To construct a predictive model for cerebral small vessel disease (CSVD) MRI burden based on β2-microglobulin (β2-MG) and lipoprotein(a) [Lp(a)], analyze its predictive value, and validate the model. Methods A total of 138 CSVD patients admitted to Anhui No.2 Provincial People’s Hospital from February 2023 to August 2024 were enrolled. Patients were divided into a low-burden group (n=63) and a moderate/severe burden group (n=75) according to the CSVD MRI burden scoring criteria. The related clinical data were compared between the two groups. Binary logistic regression analysis was used to identify independent factors for CSVD moderate/severe MRI burden. A nomogram predictive model was constructed based on these factors and its performance was evaluated. Results The proportions of male patients, as well as those with a history of diabetes or hypertension, were significantly higher in the moderate/severe burden group than those in the low burden group. Additionally, the age of patients in the moderate/severe burden group was significantly older, and the levels of β2-MG, Lp(a), and homocysteine (Hcy) were higher than those in the low burden group (P＜0.01). Binary logistic regression analysis revealed that hypertension, diabetes, β2-MG, and Lp(a) were independent factors for CSVD moderate/severe MRI burden (P＜0.05). The nomogram predictive model based on these four factors had a cut-off value of 0.467 0, with an area under curve (AUC) of 0.838 7 (95%CI 0.760 8-0.916 6) in the training set (n＝97) and 0.854 1 (95%CI 0.742 1-0.966 1) in the internal validation set (n＝41) . The calibration curve demonstrated good agreement between predicted and observed values. Decision curve analysis (DCA) indicated that the nomogram model had good clinical utility. Conclusions The nomogram model based on β2-MG and Lp(a) has high predictive performance in assessing the risk of CSVD moderate/severe MRI burden, with good discrimination and calibration.

Programmed cell death (PCD) is characterized as a cell death pathway governed by specific gene-encoding requirements, plays crucial roles in the homeostasis and innate immunity of organisms, and serves as both a pathogenic mechanism and a therapeutic target for a variety of human diseases. Z-DNA-binding protein 1 (ZBP1) functions as a cytosolic nucleic acid sensor, utilizing its unique Zα domains to detect endogenous or exogenous nucleic acids and its receptor-interacting protein homotypic interaction motif (RHIM) domains to sense or bind specific signaling molecules, thereby exerting regulatory effects on various forms of PCD. ZBP1 is involved in apoptosis, necroptosis, pyroptosis, and PANoptosis and interacts with molecules, such as receptor-interacting protein kinase 3 (RIPK3), to influence cell fate under various pathological conditions. It plays a crucial role in regulating PCD during infections, inflammatory and neurological diseases, cancers, and other conditions, affecting disease onset and progression. Targeting ZBP1-associated PCD may represent a viable therapeutic strategy for related pathological conditions. This review comprehensively summarizes the regulatory functions of ZBP1 in PCD and its interactions with several closely associated signaling molecules and delineates the diseases linked to ZBP1-mediated PCD, along with the potential therapeutic implications of ZBP1 in these contexts. Ongoing research on ZBP1 is being refined across various disease models, and these advancements may provide novel insights for studies focusing on PCD, potentially leading to new therapeutic options for related diseases.

Based on the viewpoint of "sweat pore-qi and liquid-kidney collaterals"， it is believed that children's nephrotic syndrome is caused by the core mechanism of sweat pore constraint and closure， qi and liquid imbalance， and kidney collaterals impairment， and it is proposed that the treatment principle is to nourish the sweat pore， regulate qi and fluid， and supplement the kidney and unblock the collaterals. In clinic， guided by sequential therapy and according to the different disease mechanism characteristics of the four stages， including early stage of the disease， hormone induction stage， hormone reduction stage， hormone maintenance stage， the staged dynamic identification and treatment was applied. For early stage of the disease with edema due to yang deficiency， modified Zhenwu Decoction （真武汤） was applied to warm yang and drain water； for hormone induction stage with yin deficiency resulting in effulgent fire， modified Zhibai Dihuang Pill （知柏地黄丸） plus Erzhi Pill （二至丸） was used to enrich yin and reduce fire； for hormone reduction stage with qi and yin deficiency， modified Shenqi Dihuang Decoction （参芪地黄汤） was used to boost qi and nourish yin； for hormone maintenance stage， modified Shenqi Pill （肾气丸） was used to supplement yin and yang. Meanwhile， the treatment also attaches importance to the combination of vine-based or worm medicinals to dredge collaterals， so as to providing ideas for clinical treatment.

Objective To explore the sleep quality and mental fatigue level in elderly patients with cerebrovascular small disease(CSVD).Methods A total of 222 patients aged over 65 years old hospitalized due to chronic diseases in Department of Neurology of the Affiliated Jiangning Hospi-tal of Nanjing Medical University from August 2022 to June 2024 were recruited prospectively and continuously.According to the CSVD score,they were divided into a CSVD group(CSVD score≥1,148 cases)and a non-CSVD group(CSVD score=0,74 cases).All the patients were evaluated by sleep quality,fatigue and neuropsychological scale when they were fully cooperated and in good condition.Subsequently,the patients in the CSVD group were further assigned into a good sleep subgroup(117 cases)and a poor sleep subgroup(31 patients).Results The CSVD group had significantly higher total score of Pittsburgh sleep quality index(PSQI),sleep quality score,sleep disturbance score,total score of self-rating fatigue,and mental fatigue score than the non-CSVD group(P＜0.01).The sleep quality score,sleep disturbance score,and mental fatigue score were risk factors for CSVD(P＜0.05).The mental fatigue score was significantly higher in the CSVD patients with poor sleep than those with good sleep(4.13±1.15 vs 2.50±1.92,P＜0.01).Conclusion Elderly CSVD patients were more likely to have decreased sleep quality and mental fatigue,and among them,those with poor sleep quality are prone to having mental fatigue than those with good sleep.

Objective:To investigate the correlation between mutations in KRAS, NRAS, BRAF, and PIK3 CA and the clinical characteristics of elderly colorectal cancer(CRC)patients. Methods:Paraffin-embedded tissue samples were obtained from 191 elderly CRC patients who consulted at Huadong Hospital, affiliated to Fudan University, between January 2022 and July 2023.Following deoxyribonucleic acid(DNA)extraction, the amplification refractory mutation system polymerase chain reaction(ARMS-PCR)was employed to detect the mutation profiles of KRAS, NRAS, BRAF, and PIK3 CA.Concurrently, serum samples collected prior to radical resection were analyzed for carcinoembryonic antigen(CEA), carbohydrate antigen 19-9(CA19-9), and carbohydrate antigen 72-4(CA72-4)using electrochemical luminescence.A comparative analysis of the clinical characteristics and preoperative serological tumor marker concentrations among patients with different gene mutations was conducted to elucidate their correlation. Results:A total of 191 elderly CRC patients were enrolled in the study, with ages ranging from 60 to 94 years(mean age 72.1±7.8 years), including 112 males.The mutation rate of KRAS, NRAS, BRAF, and PIK3 CA, as determined by combined detection, was found to be 49.21%(94/191)among elderly CRC patients. KRAS exhibited the highest mutation rate at 35.08%, with statistically significant differences observed in gender, primary site, degree of differentiation, and neurovascular invasion between patients with and without KRAS mutations( P<0.05 for all comparisons).The BRAF mutation rate was 8.90%, and significant differences in gender, age, primary site, and degree of differentiation were also noted between patients with and without BRAF mutations( P<0.05 for all).The mutation rates for NRAS and PIK3 CA were 2.62% and 5.24%, respectively, with no statistically significant differences in the clinical characteristics of patients across different groups( P>0.05 for all).Additionally, the proportion of patients over the age of 90 in the double mutation group was significantly higher( P<0.01).Significant differences in serum CA19-9 concentrations were observed among the various mutation types( P<0.05). Conclusions:There are notable differences in age, gender, primary site, degree of differentiation, and neurovascular invasion among elderly CRC patients with varying mutation statuses of KRAS, NRAS, BRAF, and PIK3 CA.Patients with double mutations exhibited higher concentrations of CA19-9 in preoperative serum.

Objective:To observe the pregnancy outcomes of patients with unexplained recurrent spontaneous abortion (URSA) after interventional treatment or expectant treatment.Methods:This prospective study followed up 398 patients with recurrent spontaneous abortion from March 2017 to September 2022 in seven hospitals. Among them, 267 patients were diagnosed with URSA, including 124 patients who were initially diagnosed in the interventional treatment hospital and 143 patients who were initially diagnosed in the expectant treatment hospital. All URSA patients were followed up for 33 months. Ongoing pregnancy rates were observed as main outcome indicators.Results:A total of 127 patients became pregnant, and 107 of them had sustained pregnancies, the ongoing pregnancy rate was 84.25% (107/127). The ongoing pregnancy rate was 86.11% (31/36) in the interventional treatment group and 83.52% (76/91) in the expectant treatment group, with no significant difference ( P>0.05). During the follow-up, the ongoing pregnancy rates in the interventional treatment hospital and the expectant treatment hospital were 75.71% (53/70) and 94.74% (54/57), respectively, with a significant difference ( P<0.05). The ongoing pregnancy rate after interventional treatment in the interventional treatment hospital was 82.76% (24/29), which was similar to the 94.00% (47/50) after expectant treatment in the expectant treatment hospital ( P>0.05). Conclusion:The ongoing pregnancy rate of interventional treatment for URSA patients has not been significantly improved, suggesting that it may not be necessary to carry out this treatment.

Objective:To evaluate the service capability and operational efficiency of surgical departments in a hospital using data analysis models such as entropy weight TOPSIS and Boston matrix analysis, for references for optimizing medical resource allocation, promoting refined management and sustainable development of the hospital.Methods:The operational data of 24 surgical departments (A~X) in a tertiary public hospital in 2023 from its information system were extracted. The number of doctors, actual number of open beds, and average length of stay etc., were served as evaluation indicators. The TOPSIS and rank sum ratio methods were used to evaluate the medical service capabilities, the data envelopment analysis (DEA) was used to analyze operational efficiency, and Boston matrix analysis was used for departmental classification.Results:In terms of medical service capabilities, the top 5 departments were F, S, K, D, and C ( Ci>0.41), all of which were in the excellent category; The bottom three departments were L, N, and G ( Ci<0.04), all of which were in the poor range. From the perspective of operational efficiency, 8 departments had achieved strong DEA effectiveness, while the remaining 16 departments were non DEA effective, resulting in resource redundancy or insufficient output. According to the Boston Matrix analysis, 8 departments (stars) had strong medical service capabilities and high operational efficiency; 6 departments (cash cows) had poor medical service capabilities but high operational efficiency, and 8 departments (dogs) had poor medical service capabilities and operational efficiency; 2 departments (question marks) had strong medical service capabilities but low operational efficiency. Conclusions:This study comprehensively applied multiple data models to objectively and comprehensively evaluate the service capabilities and operational efficiency of surgical departments. Hospitals could develop corresponding resource allocation optimization strategies based on the Boston matrix classification results, combined with the disease characteristics and business scale configuration of each department.