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.

Background Gestational weight gain is closely related to maternal and infant health outcomes. Pregnant women are simultaneously exposed to four metals—lithium (Li), vanadium (V), uranium (U), and bismuth (Bi)—through inhalation of fine particulate matter and consumption of contaminated food and water. Existing studies suggest that exposure to these metals may be associated with gestational weight gain. However, no study has yet explored the complex relationships between exposure to mixtures of these four metals and weight gain at different stages of pregnancy. Objective To investigate the associations between mixed exposure to Li, V, U, and Bi in early pregnancy and the average weekly gestational weight gain during both early pregnancy and mid-to-late pregnancy. Methods This prospective study recruited eligible women in early pregnancy from an obstetrics clinic of a tertiary hospital in Jinan, China, between September 2021 and July 2023. Pre-pregnancy weight, current weight (at 11⁺⁰ to 13⁺⁶ weeks of gestation), and spot urine samples (≥5.0 mL) were collected at enrollment. Urinary concentrations of Li, V, Bi, and U were determined using inductively coupled plasma mass spectrometry. Participants were followed up in late pregnancy (≥28 weeks of gestation) to collect information on physical activity via questionnaire; weight measurements at the last antenatal visit (35⁺⁰ to 37⁺⁶ weeks of gestation) were obtained from the hospital information system. After adjusting for covariates, multiple linear regression and generalized additive models were used to assess the associations of individual metals with weekly weight gain in early pregnancy and in mid-to-late pregnancy. Bayesian kernel machine regression (BKMR) and quantile-based g-computation (Qgcomp) were applied to evaluate the joint effects of the metal mixture exposure on weekly weight gain at the two gestational stages. Results A total of 313 pregnant women were included. The geometric means of urinary Li, V, U, and Bi concentrations were 37.07, 0.20, 0.06, and 0.04 μg·L⁻¹, respectively; after creatinine adjustment, the corresponding values were 46.82, 0.25, 0.07, and 0.05 μg·g⁻¹ (Cr). The mean weekly gestational weight gain was (0.19±0.25) kg in early pregnancy and (0.53 ± 0.18) kg in mid-to-late pregnancy. Both multiple linear regression and generalized additive models showed that urinary V concentration was positively associated with average weekly gestational weight gain in early pregnancy, while no significant associations were found for other metals or for gestational weight gain in mid-to-late pregnancy. In the BKMR model with early-pregnancy weight gain as the outcome, V had the strongest association [posterior inclusion probability (PIP)=0.773]. When other metals were fixed at their medians, V showed a positive non-linear association with the outcome. A significant single-metal effect of V and its interaction with Li were observed. Compared with the 50th percentile of the metal mixture, the average weekly weight gain in early pregnancy increased by 0.016 (95%CI: 0.003, 0.029) and 0.018 (95%CI: 0.001, 0.036) at the 60th and 65th percentiles, respectively; conversely, at the 25th percentile, it decreased by 0.026 (95%CI: 0.002, 0.050). Overall, the joint effect of the metal mixture on early- pregnancy weight gain showed an upward trend. In the BKMR model for mid-to-late pregnancy gestational weight gain, all PIPs were<0.5, and no significant single-metal effects, interactions, or joint effects were identified. Qgcomp results confirmed a positive association between the metal mixture and early-pregnancy weight gain (b=0.031, 95%CI: 0.010, 0.051; P<0.01), with V contributing the highest positive weight (0.71). No significant association was found for weight gain in mid-to-late pregnancy (b=0.007, P=0.339). Conclusion Higher levels of co-exposure to the Li, V, Bi, and U metal mixture during early pregnancy may be associated with increased average weekly weight gain in early pregnancy. Among these metals, V exhibits a predominant role and appears to interact with Li. No association is observed between early-pregnancy metal mixture exposure and average weekly gestational weight gain in mid-to-late pregnancy. These findings suggest that monitoring and managing metal exposure during early pregnancy may be crucial for the rational regulation of gestational weight gain.

Primary osteoporosis （POP） is a metabolic bone disease characterized by reduced bone mass， degenerated bone microstructure， and increased bone fragility. Its pathogenesis involves the interaction of multiple factors such as genetics， aging， endocrine， and environment， which remain incompletely elucidated. Mitochondrial dysfunction can lead to insufficient adenosine triphosphate （ATP） production and abnormal accumulation of reactive oxygen species （ROS）， activating oxidative stress and inflammation pathways， thereby inhibiting osteoblast differentiation and promoting osteoclast activation， exacerbating the negative bone metabolism balance in POP. Mitochondrial autophagy， as the core mechanism of mitochondrial quality control， selectively identifies and clears damaged mitochondria to effectively reduce ROS accumulation and energy metabolism disorders， thus maintaining the balance between osteoblast and osteoclast differentiation. It plays a critical role in maintaining bone homeostasis and the prevention and treatment of POP. The traditional Chinese medicine （TCM） theory of Qi transformation shares similarities with the functions of mitochondria in energy generation and substance conversion. The pathological state of Qi deficiency and stagnation may be associated with mitochondrial autophagy dysfunction， and the pathogenic characteristics of combined phlegm and stasis align with the metabolic waste accumulation induced by obstructed autophagy flow. This article explores the correlation of the theory of Qi deficiency and stagnation with mitochondrial autophagy and elucidates its potential role in the pathogenesis of POP. Additionally， considering the pathogenesis features of POP， which involve deficiency causing stagnation and a mixture of deficiency and excess， this article proposes a novel therapeutic approach： tonifying Qi to support the body and unblocking collaterals to resolve stagnation from the perspective of mitochondrial autophagy. This article aims to provide theoretical support and research insights for further exploration of TCM in the prevention and treatment of POP.

Primary osteoporosis （POP） is a metabolic bone disease characterized by reduced bone mass， degenerated bone microstructure， and increased bone fragility. Its pathogenesis involves the interaction of multiple factors such as genetics， aging， endocrine， and environment， which remain incompletely elucidated. Mitochondrial dysfunction can lead to insufficient adenosine triphosphate （ATP） production and abnormal accumulation of reactive oxygen species （ROS）， activating oxidative stress and inflammation pathways， thereby inhibiting osteoblast differentiation and promoting osteoclast activation， exacerbating the negative bone metabolism balance in POP. Mitochondrial autophagy， as the core mechanism of mitochondrial quality control， selectively identifies and clears damaged mitochondria to effectively reduce ROS accumulation and energy metabolism disorders， thus maintaining the balance between osteoblast and osteoclast differentiation. It plays a critical role in maintaining bone homeostasis and the prevention and treatment of POP. The traditional Chinese medicine （TCM） theory of Qi transformation shares similarities with the functions of mitochondria in energy generation and substance conversion. The pathological state of Qi deficiency and stagnation may be associated with mitochondrial autophagy dysfunction， and the pathogenic characteristics of combined phlegm and stasis align with the metabolic waste accumulation induced by obstructed autophagy flow. This article explores the correlation of the theory of Qi deficiency and stagnation with mitochondrial autophagy and elucidates its potential role in the pathogenesis of POP. Additionally， considering the pathogenesis features of POP， which involve deficiency causing stagnation and a mixture of deficiency and excess， this article proposes a novel therapeutic approach： tonifying Qi to support the body and unblocking collaterals to resolve stagnation from the perspective of mitochondrial autophagy. This article aims to provide theoretical support and research insights for further exploration of TCM in the prevention and treatment of POP.

Objective:To analyze the efficacies of unilateral biportal endoscopy(UBE)and percutaneous endoscopic transforaminal discectomy(PETD)in treatment of lumbar disc herniation(LDH),and to explore the optimal selection of minimally invasive surgical approaches for the The LDH patients.Methods:A retrospective analysis was performed on the clinical data of 64 LDH patients who underwent surgery at Liwan Central Hospital of Guangzhou City in Guangdong Province,between January 2020 and June 2024.The surgical approaches were determined through physician-patient communication,and the patients were divided into UBE group(n=30)and PETD group(n=34).The materials of patients were recorded including gender,age,body mass index(BMI),percentages of affected segments,course of disease,duration of hospitalization,operation duration,intraoperative blood loss,numbers of intraoperative fluoroscopy,total incision length,and time to full weight-bearing(WB).The therapeutic outcomes were evaluated using Oswestry disability index(ODI),Visual Analog Scale(VAS)scores for low back pain and leg pain,MacNab criteria,and spinal canal areas at the affected segment.the postoperative complications of the patients in two groups were analyzed.Results:There were no statistically significant differences in age,gender composition ratio,BMI,course of disease,and percentages of affected segments of the patients between UBE group and PETD group(P＞0.05).Compared with PETD group,the intraoperative blood loss,total incision length,and time to full WB of the patients in UBE group were significantly increase(P＜0.01),while the number of intraoperative fluoroscopy time was decreased(P＜0.01).Compared with pre-operation,the ODI scores and VAS scores for low back and leg pain of the patients at final follow-up in both groups were decreased(P＜0.01),and the spinal canal areas at the affected segments of the patients were increased(P＜0.01).At final follow-up,compared with PETD group,the ODI score and VAS scores for low back and leg pain of patients in UBE group were decreased(P＜0.01),while the spinal canal areas at the affected segments of the patients was increased(P＜0.01).According to MacNab criteria,the percentages of excellent and good had no significant difference between two groups(P＞0.05).The incidence of complication showed no statistical difference between two groups(P＞0.05).Conclusion:Both UBE and PETD yield satisfactory outcomes in the treatment of single-segment LDH.PETD is less invasive and permits earlier time to full WB,whereas UBE provides more extensive decompression and superior long-term efficacy.The surgical approach selection should be individualized based on specific factors in the clinic.

Interferon regulatory factor 4 (IRF4) is a critical transcription factor that governs the differentiation of cluster of differentiation 4⁺ (CD4⁺) T cells. The pathogenesis and progression of psoriasis are primarily attributed to an immune imbalance stemming from the overproduction of interleukin-17A (IL-17A) by T lymphocytes. However, the role of IRF4 in psoriasis remains unexplored. In this study, we found that IRF4 activity is increased in the cutaneous lesions of patients with psoriasis in response to stimulation by IL-23A and IL-1β. This IRF4 elevation heightens its binding to the E1A binding protein p300 (EP300) promoter, triggering the transcription of downstream retinoic acid receptor-related orphan receptor-γt (RORγt) and increasing the secretion of IL-17A, thereby establishing the IL-1β/IL-23A-IRF4-EP300-RORC-IL-17A inflammatory cascade in psoriasis. The alleviation of imiquimod (IMQ)-induced psoriatic-like symptoms was achieved through the creation of a Irf4 ^-/- gene deletion mouse model and pharmacological inhibition using antisense oligonucleotides targeted for Irf4. This amelioration was accompanied by a decreased number of IL-17A-producing CD4⁺ T cells in the skin. The findings of this study suggest that IRF4 plays a crucial role in the promotion of inflammation and exacerbation of IMQ-induced psoriasiform dermatitis. Consequently, IRF4 targeting could be a promising therapeutic strategy.

Natural products (NPs) have long held a significant position in various fields such as medicine, food, agriculture, and materials. The chemical space covered by NPs is extensive but often underexplored. Therefore, high-throughput and efficient methodologies for the annotation and discovery of NPs are desired to address the complexity and diversity of NP-based systems. Mass spectrometry (MS) has emerged as a powerful platform for the annotation and discovery of NPs. MS databases provide vital support for the structural characterization of NPs by integrating extensive mass spectral data and sample information. Additionally, the released annotation methodologies, based on a variety of informatics tools, continuously improve the ability to annotate the structure and properties of compounds. This review examines the current mainstream databases and annotation methodologies, focusing on their advantages and limitations. Prospects for future technological advancements are then discussed in terms of novel applications and research objectives. Through a systematic overview, this review aims to provide valuable insights and a reference for MS-based NPs annotation, thereby promoting the discovery of novel natural entities.
Biological Products/chemistry* ; Mass Spectrometry/methods* ; Databases, Factual ; Drug Discovery/methods* ; Humans

Objective: To investigate the iodine nutrition status of children aged 8-10 in Guangming, Longhua and Yantian District of Shenzhen in 2023, and to explore the influencing factors of thyroid volume. To evaluate prevention strategies and to provide a scientific basis for the elimination of iodine deficiency disorders. Methods: Urine and household salt samples were randomly collected from 580 non-boarding students aged 8-10 years foriodine content detection. Thyroid volume was measured using a fully digital ultrasound imaging system, and goiter prevalence was calculated. Results: A total of 580 samples was tested. The median salt iodine concentration was 23.86 mg/kg, with 93.62% qualified iodized salt and 94.48% coverage rate. The median of urinary iodine was 265.00 μg/L, mainly distributed between 200 - < 300 μg/L and ≥300 μg/L. The proportion of children with ap⁃ propriate iodine was 20. 86% , and the proportion of children with insufficient or excessive urinary iodine levels was 10. 86% and 68. 28% of the total surveyed population , respectively. The median thyroid volume was 3. 27 mL , and the goiter rate was 1. 72% . Multiple linear regression analysis showed that age was the risk factor for thyroid volume (8=0 328, P<0.05). while urinary iodine was the protective factor for thyroid volume(B=-4.134x10-4,P<0.05). Conclusion The qualified iodized salt rate, median of urinary iodine,and goiter prevalence of 580 children aged 8 - 10 meet the elimination criteria for iodine deficiency disorders. Age and urinary iodine are closely related to thyroid volume change. The urinary iodine level of children is generally high and requires serious attention.

Objective: To explore the correlation between traditional Chinese medicine (TCM) constitution and depressive symptom among school aged children and adolescents, so as to provide evidences for informing constitution based regulation and prevention of depressive symptom. Methods: From June to December 2024, a total of 4 729 students aged 6-14 were recruited by cluster random sampling from 10 primary schools in Baoding (Hebei Province), Heze and Liaocheng (Shandong Province). General information, TCM constitution and depressive symptom were collected. Restricted cubic spline (RCS) models were used to analyze related factors and threshold effects of depressive symptom. Binary Logistic regression was applied to examine the association between depressive symptom and TCM constitution, with subgroup analyses conducted. Results: The detection rate of depressive symptom among the included children and adolescents was 25.82%. RCS analyses indicated non linear associations between depressive symptom and age (inflection point at 10 years old), bedtime (inflection point at 22:00), and wake up time (inflection point at 6:30 ) (all P non linearity <0.01). Linear associations were observed with body mass index (BMI) and sleep duration (all P non linearity > 0.05 ). After adjusting for covariates such as age, BMI and sleep status, binary Logistic regression analyses showed that Yin deficient constitution ( OR =1.26, 95% CI =1.09-1.45) and Phlegm-dampness constitution ( OR =1.42, 95% CI =1.11-1.82) were significantly associated with depressive symptom among children and adolescents (all P <0.05). Conclusions Depressive symptom among school aged children and adolescents is primarily associated with Yin deficiency and Phlegm dampness constitutions in TCM constitution. Active attention should be paid to susceptible TCM constitution among children and adolescents. Targeted health guidance and interventions should be implemented to improve TCM constitution health status for preventing the occurrence of depressive symptom.

Perinatal depression (PND) is a critical public health issue affecting maternal and offspring health. Digital health intervention platforms, leveraging advantages in accessibility, privacy, and cost-effectiveness, demonstrate good application in PND prevention and treatment. This review systematically searched literature and policy documents published between January 2018 and March 2025 in CNKI, PubMed, Web of Science and World Health Organization. It summarized the development trajectory of digital health intervention platforms and their current applications and effectiveness in PND prevention and treatment. Existing evidence was evaluated across dimensions of efficacy, systematicity, and practicality, identifying major challenges faced by these platforms. Studies indicate that while PND digital health intervention platforms have achieved preliminary success in alleviating PND symptoms, widespread issues persist, including incomplete service closed-loop systems, low user adherence, and insufficient sustainability. Future efforts should focus on optimizing intervention content and interactive design, advancing intelligent assessment and tiered intervention strategies, strengthening continuous monitoring and crisis response mechanisms, and constructing a multidisciplinary collaborative support system. These steps are essential for achieving efficient, intelligent, and sustainable development of digital health intervention platforms for PND.