Intravitreal anti-vascular endothelial growth factor(anti-VEGF)therapy has been widely used, but the variability in its therapeutic efficacy limits individualized treatment. In recent years, the application of artificial intelligence(AI)has opened up new avenues for personalized treatment response prediction, and its core branches include machine learning(ML)and deep learning(DL). This review systematically retrieved and analyzed 41 relevant studies published up to April 2025. Comprehensive analysis reveals that AI predictive models are evolving from forecasting single endpoints(such as visual acuity or central retinal thickness)to integrating multi-dimensional endpoints(encompassing anatomical, functional, and treatment demand parameters)and generating predictive imaging outputs. In terms of technical approaches, DL models(28 studies, accounting for 68.3%)dominate this field due to their robust image interpretation capabilities, while ML models(10 studies, 24.4%)retain significant value in the analysis of structured clinical data. Cross-disease comparisons indicate that research efforts are most concentrated on age-related macular degeneration(ARMD)and diabetic macular edema(DME), with shared conceptual frameworks for model construction, yet distinct anatomical and functional indicators are prioritized for each disease. Currently, the field confronts several key challenges, including insufficient prospective clinical validation, limited model interpretability(the “black box problem”), and a scarcity of high-quality multi-center datasets. Moving forward, it is imperative to advance real-world validation and develop explainable AI techniques to expedite the clinical translation of these predictive models.

Objective:To investigate the related factors of kidney injury in patients with masked hypertension (MHT).Methods:This study was a cross-sectional study. A total of 311 MHT patients who visited Dongguan Liaobu Community Health Service from June 1,2022 to June 1, 2023 were enrolled in the study. The complete blood biochemistry, urinary microalbumin and 24-hour urinary protein tests were conducted, and the risk factors of renal injury in MHT patients were analyzed with multivariate logistic regression.Results:The age of the 311 enrolled patients was(48.8±9.2)years, with 192 males(61.7%) There were 73 cases with microalbuminuria (MAU), accounting for 23.47% (73/311); and 28 cases of positive 24-hour urine total protein (24-hour UTP), accounted for 9.00% (28/311). Multivariate logistic regression analysis showed that fasting blood glucose level and mean nocturnal systolic blood pressure were independent risk factors of positive MAU in MHT patients ( OR=1.577, 95% CI: 1.049-2.370, P=0.030; OR=1.024, 95% CI: 1.001-1.047, P=0.038), while older age was a protective factor of MAU ( OR=0.965, 95% CI: 0.935-0.997, P=0.030); mean nocturnal systolic pressure, 24-hour mean systolic pressure and mean diurnal systolic pressure were independent risk factors of positive 24-hour UTP in MHT patients ( OR=1.031,95% CI: 1.000-1.064, P=0.049; OR=1.048,95% CI: 1.008-1.091, P=0.020; OR=1.042,95% CI: 1.003-1.083, P=0.035). Conclusion:Older age, fasting blood glucose, mean nocturnal systolic pressure, 24-hour mean systolic pressure and mean diurnal systolic pressure are associated with the renal injury in MHT patients.

Objective:To develop and validate clinical predictive models for identifying poor short-term response to recombinant human growth hormone(rhGH) treatment in children with short stature.Methods:A retrospective analysis was conducted on 118 children diagnosed with growth hormone deficiency or idiopathic short stature who were treated at the First Affiliated Hospital of Zhengzhou University and two other hospitals between January 1, 2020, and January 1, 2024. A poor response to rhGH was defined as a height increase of less than 0.2 standard deviation score(SDS) after 6 months of rhGH treatment. LASSO regression was used to identify predictive variables from baseline and follow-up data. Two logistic regression models were conducted: Model A(incorporating baseline variables only) and model B(incorporating both baseline and follow-up variables), and nomograms were created for visualization. External data and internal resampling were used for dual validation of the models, and their performance was compared.Results:A total of 118 children with short stature were included. Six baseline predictive variables(diagnosis, initial height SDS, bone age, bone age-chronological age difference, rhGH dose, and gender) and one follow-up variable(height SDS after 3 months of rhGH treatment) were identified. Area under the curve values for Model A and Model B were 0.753(95% CI 0.696-0.811) and 0.930(95% CI 0.891-0.975), respectively. Calibration curves, decision curve analysis, and other evaluation metrics demonstrated good discrimination and clinical utility for both models. Model B, incorporating the 3-month follow-up variable, showed superior predictive performance compared to Model A. Conclusions:The clinical prediction models developed in this study(Model A and Model B) are practical and reliable tools for quantitatively, conveniently, and intuitively identifying children with short stature at risk of poor response to rhGH treatment.

Objective:To investigate the related factors of kidney injury in patients with masked hypertension (MHT).Methods:This study was a cross-sectional study. A total of 311 MHT patients who visited Dongguan Liaobu Community Health Service from June 1,2022 to June 1, 2023 were enrolled in the study. The complete blood biochemistry, urinary microalbumin and 24-hour urinary protein tests were conducted, and the risk factors of renal injury in MHT patients were analyzed with multivariate logistic regression.Results:The age of the 311 enrolled patients was(48.8±9.2)years, with 192 males(61.7%) There were 73 cases with microalbuminuria (MAU), accounting for 23.47% (73/311); and 28 cases of positive 24-hour urine total protein (24-hour UTP), accounted for 9.00% (28/311). Multivariate logistic regression analysis showed that fasting blood glucose level and mean nocturnal systolic blood pressure were independent risk factors of positive MAU in MHT patients ( OR=1.577, 95% CI: 1.049-2.370, P=0.030; OR=1.024, 95% CI: 1.001-1.047, P=0.038), while older age was a protective factor of MAU ( OR=0.965, 95% CI: 0.935-0.997, P=0.030); mean nocturnal systolic pressure, 24-hour mean systolic pressure and mean diurnal systolic pressure were independent risk factors of positive 24-hour UTP in MHT patients ( OR=1.031,95% CI: 1.000-1.064, P=0.049; OR=1.048,95% CI: 1.008-1.091, P=0.020; OR=1.042,95% CI: 1.003-1.083, P=0.035). Conclusion:Older age, fasting blood glucose, mean nocturnal systolic pressure, 24-hour mean systolic pressure and mean diurnal systolic pressure are associated with the renal injury in MHT patients.

Objective:To develop and validate clinical predictive models for identifying poor short-term response to recombinant human growth hormone(rhGH) treatment in children with short stature.Methods:A retrospective analysis was conducted on 118 children diagnosed with growth hormone deficiency or idiopathic short stature who were treated at the First Affiliated Hospital of Zhengzhou University and two other hospitals between January 1, 2020, and January 1, 2024. A poor response to rhGH was defined as a height increase of less than 0.2 standard deviation score(SDS) after 6 months of rhGH treatment. LASSO regression was used to identify predictive variables from baseline and follow-up data. Two logistic regression models were conducted: Model A(incorporating baseline variables only) and model B(incorporating both baseline and follow-up variables), and nomograms were created for visualization. External data and internal resampling were used for dual validation of the models, and their performance was compared.Results:A total of 118 children with short stature were included. Six baseline predictive variables(diagnosis, initial height SDS, bone age, bone age-chronological age difference, rhGH dose, and gender) and one follow-up variable(height SDS after 3 months of rhGH treatment) were identified. Area under the curve values for Model A and Model B were 0.753(95% CI 0.696-0.811) and 0.930(95% CI 0.891-0.975), respectively. Calibration curves, decision curve analysis, and other evaluation metrics demonstrated good discrimination and clinical utility for both models. Model B, incorporating the 3-month follow-up variable, showed superior predictive performance compared to Model A. Conclusions:The clinical prediction models developed in this study(Model A and Model B) are practical and reliable tools for quantitatively, conveniently, and intuitively identifying children with short stature at risk of poor response to rhGH treatment.

Objective:This study aimed to explore the challenges faced by colleges and universities in performing their institutional responsibilities set forth by the Ethical Review Measures of Life Science and Medical Research Involving Human Participants (hereinafter referred to as the Measures), demonstrate the key points and main challenges in standardizing the ethical review and ethical management of colleges and universities, to provide a possible reference for daily working practices.Methods:Based on the interpretation of the policy document, combined with practical experiences in ethical review and ethical management, this paper summarized identified problems faced and proposed feasible practical suggestions.Results:The Measures strengthen the ethical review norms for life science and medical research involving human participants by reaffirming the responsibility of institutions. Colleges and universities might face some challenges and more systematic design is needed.Conclusions:The ethical review and ethical management work at colleges and universities need further consideration, top-down design model should be developed, to set work priorities, and at the same time, more innovative ways should be adopted to facilitate ethical review reliance and coordinate more streamlined review of cooperative research, and improve the quality and efficiency of ethical review promptly.

Lycophytes and seed plants constitute the typical vascular plants. Lycophytes have been thought to have no paleo-polyploidization although the event is known to be critical for the fast expansion of seed plants. Here, genomic analyses including the homologous gene dot plot analysis detected multiple paleo-polyploidization events, with one occurring approximately 13-15 million years ago (MYA) and another about 125-142 MYA, during the evolution of the genome of Selaginella moellendorffii, a model lycophyte. In addition, comparative analysis of reconstructed ancestral genomes of lycophytes and angiosperms suggested that lycophytes were affected by more paleo-polyploidization events than seed plants. Results from the present genomic analyses indicate that paleo-polyploidization has contributed to the successful establishment of both lineages-lycophytes and seed plants-of vascular plants.
Evolution, Molecular ; Genome, Plant ; Genomics ; Phylogeny ; Polyploidy ; Selaginellaceae/genetics*

Objective Summarize and share the working practice of Investigator Research Ethics and Research Integrity Training conducted at Peking University Human Research Protection Program (PKU HRPP) ,to further explore continuing quality improvement of investigator ethical training at university level .Methods Conduct systematic review of the archiving files of PKU HRPP investigator training activities during 2012-2018 ,summarize feedback information from investigators to i-dentify possible experiences for sharing and space for improvement .Results There are some positive experiences for sharing a-bout the training mechanism and practices at PKU HRPP .Conclusions Based on the previous ethical training work and experi-ences at PKU HRPP ,possible proposals for continuing quality improvement may including :strengthening the requirements of ethical training of investigators ,encouraging and recognizing ethical training conducted by research teams ,emphasizing training Quality and the promotion of sharing and mutual recognition mechanisms for ethical training .

Objective To explore the management of human genetic resources in our university,propose relevant suggestions for promoting the appropriate protection and scientific management of human genetic resources.Methods Based on the existing regulations and policies,discuss the potential problems relevant to how to strengthen management of human genetic resources in China at institute level.Results Main problems identified including the management scope of human genetic resources is not clear,the inconsistence of application materials,the informed consent and its process involved in biobank and lack of the management of whole process of human genetic resources exploration.Conclusions With the rapid development of biotechnology,the economic value and strategic significance of human genetic resources have become increasingly prominent.Enhancement of training and whole process management,as well as the improvement of informed consent for biobank play important roles in effectively improve the protection of human genetic resources.

With dramatic decline of genome sequencing cost,high-throughput sequencing technologies have been applied in clinical laboratory field,and play an increasingly important role in clinical diagnosis and treatment in complex diseases.Based on omics techniques,clinical laboratory data recording patient's diagnosis information has become the important independent medical research resources of the major health industry.Because these data include the patient's identity information,there are a series of ethical issues to be solved,such as protection of patients' informed consent right,patient privacy protection,information security protection,when carrying out the medical health big data research.Based on these problems,it proposed clinical laboratory data should be standard extraction,establishment of clinical laboratory data base for teaching,training,in order to improve the utilization of medical resources.Moreover,it is best to implement the written informed consent during the process of sample collection,informing the patient the data collected in diagnosis and treatment process may be used in related research in future.