AIM: To study the clinical characteristics and influencing factors of retinopathy of prematurity(ROP), and to construct a nomogram model for predicting ROP in premature infants.METHODS: This retrospective study enrolled premature infants who underwent fundus examinations in the hospital from January 2022 to September 2025 for analysis. Fundus examinations were performed using the RetCam III system, and the occurrence of ROP was recorded. The data were split into a training set and a validation set at a ratio of 7:3. Univariate analysis was conducted using the Chi-square test and multivariate analysis was performed using binary Logistic regression on the training set data. Variables identified in the multivariate analysis were used to construct a nomogram, which was subsequently validated.RESULTS: The incidence of ROP(428 cases)among the 3 841 premature infants was 11.43%, with 138 cases(32.24%)in stage I, 151 cases(35.28%)in stage II, 103 cases(24.07%)in stage III, 33 cases(7.71%)in stage IV, and 3 cases(0.70%)in stage V. No statistically significant differences were found in the clinical data between the training and validation sets(all P>0.05). Multivariate analysis identified neonatal sepsis, mechanical ventilation, transfusion therapy, coagulation dysfunction, bronchopulmonary dysplasia(BPD), neonatal respiratory distress syndrome(NRDS), formula feeding, and non-invasive respiratory support duration >1 wk as risk factors for ROP(all P<0.05). Birth weight(1 500-2 499 g, ≥2 500 g), gestational age(32-34 wk, 35-36 wk), weight gain rate ≥20 g/d, and 5-minute Apgar score ≥8 were identified as protective factors(all P<0.05). The area under curve(AUC)of the nomogram prediction model was 0.890 in the training set and 0.907 in the validation set, with sensitivity of 80.67% and 82.81%, and specificity of 83.18% and 85.14%, respectively. The calibration curves in both sets approached the ideal curve, and the Hosmer-Lemeshow goodness-of-fit test indicated good agreement between the predicted and observed values(χ2=12.918, P=0.115; χ2=4.047, P=0.853). The decision curve analysis demonstrated high net benefits in both the training and validation sets.CONCLUSION: The incidence of ROP in premature infants was 11.43%. The nomogram model, constructed based on multivariate Logistic regression and integrating key risk and protective factors such as birth weight, gestational age, sepsis, and mechanical ventilation, demonstrates high predictive value, good calibration, and high net benefit. It can serve as an intuitive and effective tool for early individualized risk assessment of ROP in premature infants.

Objective To explore the risk factors for mineral and bone disorder in maintenance hemodialysis patients, and to construct and validate a nomogram prediction model. Methods A total of 306 patients undergoing maintenance hemodialysis at Shanghai Eighth People’s Hospital from January 2021 to May 2025 were selected as study subjects and randomly divided into a training set (n＝214) and a validation set (n＝92) in a 7∶3 ratio. In the training set, patients were divided into a normal bone mineral metabolism group and an abnormal bone mineral metabolism group, and related factors were compared between the two groups. The multivariate logistic regression analysis was used to identify the influencing factors of mineral and bone disorder in maintenance hemodialysis patients in the training set, and a nomogram prediction model was constructed. ROC curves were drawn to evaluate the ability of the nomogram model for predicting mineral and bone disorder in these patients. Calibration curves and Hosmer-Lemeshow goodness-of-fit test were used to analyze the consistency of the predictive probability of nomogram model and actual probability of mineral and bone disorder in these patients. The decision curve was used to assess the clinical benefit using nomogram prediction model. Results Among the 306 hemodialysis patients, 254 patients had mineral and bone disorder, accounting for 83.01%. Among the 214 patients in the training set, 177 had mineral and bone disorder, accounting for 82.71%. In the training set, age, gender, body mass index (BMI), hypertension rate, dialysis age, blood urea nitrogen (BUN), hemoglobin (Hb), albumin (ALB), alkaline phosphatase (ALP), serum creatinine (SCr), uric acid (UA), estimated glomerular filtration rate (eGFR), and rate of taking phosphate binders were statistically significant different between the two groups (P＜0.05). The multivariate logistic regression analysis showed higher age, female, hypertension, longer dialysis duration, decreased eGFR, and not taking phosphate binders were identified as risk factors for mineral and bone disorder in maintenance hemodialysis patients (P＜0.01). The nomogram prediction model was constructed. The area under the ROC curve of the model for mineral and bone disorder in the training set and validation set was 0.895 (95%CI 0.850-0.941) and 0.881 (95%CI 0.830-0.932), respectively, with maximum Youden indice of 0.650 and 0.600, sensitivity of 0.856 and 0.849, and specificity of 0.794 and 0.751. The Hosmer-Lemeshow test showed the nomogram prediction model had good consistency in predictive probabilities with actual probabilities in training set and validation set. The decision curve showed the nomogram model could bring clinical net benefits when the threshold probabilities in the training set and validation set were less than 0.96 and 0.91. Conclusions The nomogram prediction model constructed based on six independent risk factors including age, gender, hypertension, dialysis duration, eGFR, and using phosphate binders or not, shows good discrimination and calibration, with good clinical predictive ability, which could provide guidance for the management of maintenance hemodialysis patients.

The Expert Consensus on the Deployment of DeepSeek in Medical Institutions serves as a detailed guideline for the deployment of DeepSeek in medical institutions. It was developed by experts in the fields of healthcare， hospital management， medical information， health policy， law， and medical ethics from nearly 30 leading domestic medical and academic research institutions， based on relevant domestic and international laws and regulations as well as the practices of medical institutions. It aims to provide medical institutions with a scientific， standardized， and secure deployment guideline to ensure that the application of artificial intelligence （AI） technologies in healthcare， including but not limited to DeepSeek， conforms to the unique characteristics of the healthcare industry and effectively promotes the improvement of medical service levels. From the three aspects of pre-deployment evaluation， deployment implementation， and post-deployment management and monitoring， the key factors that medical institutions should consider when introducing DeepSeek were elaborated in detail， including medical demand compatibility， technical capabilities and infrastructure， legal and ethical risks， data preparation and management， model selection and optimization， system integration and training， performance monitoring and continuous optimization， risk management and emergency response， as well as compliance review and evaluation. This provides a comprehensive deployment framework for medical institutions to ensure the safety and effectiveness of technology applications.

Purpose: This study aimed to evaluate the contrast-enhanced ultrasound with Sonazoid (Sonazoid-CEUS) features of hepatocellular carcinoma (HCC) in patients with non-alcoholic fatty liver disease (NAFLD). Methods: In this retrospective study, patients who underwent surgical resection and were histopathologically diagnosed with NAFLD or cirrhosis-related HCC were included. All patients received Sonazoid-CEUS examinations within 1 week prior to hepatic surgery. The enhancement patterns of HCC lesions were evaluated and compared between the two groups according to the current World Federation for Ultrasound in Medicine and Biology guidelines. Multivariate logistic regression analysis was used to assess the correlations between Sonazoid-CEUS enhancement patterns and clinicopathologic characteristics. Results: From March 2022 to April 2023, a total of 151 patients with HCC were included, comprising 72 with NAFLD-related HCC and 79 with hepatitis B virus (HBV) cirrhosis–related HCC. On Sonazoid-CEUS, more than half of the NAFLD-related HCCs exhibited relatively early and mild washout within 60 seconds (54.2%, 39/72), whereas most HBV cirrhosis–related HCCs displayed washout between 60 and 120 seconds (46.8%, 37/79) or after 120 seconds (39.2%, 31/79) (P<0.001). In the patients with NAFLD-related HCC, multivariate analysis revealed that international normalized ratio (odds ratio [OR], 0.002; 95% confidence interval [CI], 0.000 to 0.899; P=0.046) and poor tumor differentiation (OR, 21.930; 95% CI, 1.960 to 245.319; P=0.012) were significantly associated with washout occurring within 60 seconds. Conclusion Characteristic Sonazoid-CEUS features are useful for diagnosing HCC in patients with NAFLD.

Addressing the enduring challenge of evaluating traditional Chinese medicines (TCMs), the integrated evidence chain-based effectiveness evaluation of TCMs (Eff-iEC) has emerged. This paper explored its capacity through a demonstration study that evaluated the effectiveness evidence of six commonly used anti-hepatic fibrosis Chinese patent medicines (CPMs), including Biejiajian Pill (BP), Dahuang Zhechong Pill (DZP), Biejia Ruangan Compound (BRC), Fuzheng Huayu Capsule (FHC), Anluo Huaxian Pill (AHP), and Heluo Shugan Capsule (HSC), using both Eff-iEC and the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system. The recognition of these CPMs within the TCM academic community was also assessed through their inclusion in relevant medical documents. Results showed that the evidence of BRC and FHC received higher assessments in both Eff-iEC and GRADE system, while the assessments for others varied. Analysis of community recognition revealed that Eff-iEC more accurately reflects the clinical value of these CPMs, exhibiting superior evaluative capabilities. By breaking through the conventional pattern of TCMs effectiveness evaluation, Eff-iEC offers a novel epistemology that better aligns with the clinical realities and reasoning of TCMs, providing a coherent methodology for clinical decision-making, new drug evaluations, and health policy formulation.

OBJECTIVES: To evaluate the association of GGN repeat polymorphism of androgen receptor (AR) with ovarian reserve and ovarian response in controlled ovarian stimulation (COS). METHODS: This genetic association study was conducted among a total of 361 women aged ≤40 years with basal FSH≤12 U/L undergoing the GnRH-agonist long protocol for COS in a university-affiliated IVF center. GGN repeat in the AR gene was analyzed with Sanger sequencing. The primary endpoint was the number of antral follicle counts (AFCs), and the secondary endpoints were stimulation days, total dose of gonadotropin (Gn) used, total number of retrieved oocytes, ovarian sensitivity index, and follicular output rate. RESULTS: The GGN repeat in exon 1 of the AR gene ranged from 13 to 24, and the median repeat length was 22. Based on the genotypes (S for GGN repeats <22, L for GGN repeats ≥22), the patients were divided into 3 groups: SS, SL, and LL. Generalized regression analysis indicated that the number of AFCs in group SS was significantly lower than those in group SL (adjusted β=1.8, 95% CI: 0.2-3.4, P=0.024) and group LL (adjusted β=1.5, 95% CI: 0.2-2.7, P=0.021). No significant difference was observed in the number of AFCs between group SL and group LL (P>0.05). Generalized regression analysis indicated no significant differences in ovarian stimulation parameters among the 3 groups, either before or after adjusting for confounding factors (P>0.05). CONCLUSIONS GGN repeat length on the AR gene is associated with AFC but not with ovarian response in Chinese women, indicating that AR gene polymorphisms may affect ovarian reserve.
Adult ; Female ; Humans ; Genotype ; Ovarian Follicle/cytology* ; Ovarian Reserve/genetics* ; Ovulation Induction/methods* ; Polymorphism, Genetic ; Receptors, Androgen/genetics* ; East Asian People/genetics*

Dysregulated RNA splicing is a well-recognized characteristic of colorectal cancer (CRC); however, its intricacies remain obscure, partly due to challenges in profiling full-length transcript variants at the single-cell level. Here, we employ high-depth long-read scRNA-seq to define the full-length transcriptome of colorectal epithelial cells in 12 CRC patients, revealing extensive isoform diversities and splicing alterations. Cancer cells exhibited increased transcript complexity, with widespread 3'-UTR shortening and reduced intron retention. Distinct splicing regulation patterns were observed between intrinsic-consensus molecular subtypes (iCMS), with iCMS3 displaying even higher splicing factor activities and more pronounced 3'-UTR shortening. Furthermore, we revealed substantial shifts in isoform usage that result in alterations of protein sequences from the same gene with distinct carcinogenic effects during tumorigenesis of CRC. Allele-specific expression analysis revealed dominant mutant allele expression in key oncogenes and tumor suppressors. Moreover, mutated PPIG was linked to widespread splicing dysregulation, and functional validation experiments confirmed its critical role in modulating RNA splicing and tumor-associated processes. Our findings highlight the transcriptomic plasticity in CRC and suggest novel candidate targets for splicing-based therapeutic strategies.
Humans ; Colorectal Neoplasms/metabolism* ; RNA Isoforms/metabolism* ; Single-Cell Analysis ; RNA Splicing ; Gene Expression Regulation, Neoplastic ; RNA, Neoplasm/metabolism* ; Transcriptome

In recent years, the rapid development of transportation and sports industries, coupled with the accelerated population aging in China, has led to a steady increase in the incidence of articular cartilage injuries, wear, and degenerative changes. Currently, the clinical treatment options for cartilage defects primarily include conservative therapies and surgical interventions, both of which have certain limitations. Cartilage tissue engineering (CTE), as a novel technology, provides an infinite prospect for cartilage regeneration and repair. Because of the abilities of scaffolds to mimic the natural cartilage structure, exhibit excellent biocompatibility and biomimetic mechanical properties, and promote cell adhesion and proliferation, scaffolds are considered effective delivery systems for growth factors, genes, and drugs. This review summarizes the clinical treatments for cartilage defects and their limitations, discusses the materials and preparation techniques of scaffolds used in CTE, with a particular focus on drug-loaded scaffold delivery systems in cartilage repair and regeneration, and offers a perspective on the future application of drug-loaded CTE. The aim is to provide theoretical guidance and new approaches for the repair of cartilage defects.
Tissue Engineering/methods* ; Humans ; Tissue Scaffolds ; Drug Delivery Systems/methods* ; Regeneration ; Cartilage, Articular/physiology* ; Animals ; Biocompatible Materials