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.

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.

Autophagy is the essential mechanism for cell adaptation and survival. Under normal physiological conditions, autophagy activates hair follicle stem cells, induces the transition of hair follicles from the telogen phase to the anagen phase, and maintains the hair growth cycle. Moreover, autophagy can protect dermal papilla cells from damage under pathological conditions. Intervention in autophagy can slow the progress of hair loss due to the existence of impaired autophagy in androgenetic alopecia and alopecia areata. The review summarizes the role of autophagy in hair cycle regulation, cell homeostasis maintenance, and hair regeneration, providing new insights into therapeutic options targeting follicular autophagy signaling pathways.

Objective:To analyze the correlation between sex hormone levels and micropenis after mild hypospadias surgery in children.Methods:A case control study was carried out.The clinical data of 71 children aged 1 to 13 years who underwent mild hypospadias surgery at the First Affiliated Hospital of Xinxiang Medical University from April 2022 to April 2024 were analyzed.Preoperatively, the children were divided into a mild hypospadias group (Group A) and a mild hypospadias with micropenis group (Group B) based on the stretched penile length (SPL).Prolactin, follicle-stimulating hormone (FSH), luteinizing hormone (LH), progesterone, and testosterone (TES) levels of the 2 groups were measured.Multivariate Logistic regression analysis was used to construct a risk prediction model.The discrimination capability of the model was evaluated using the receiver operating characteristic (ROC) curve.SPL and sex hormone levels were measured again 6 months after surgery.The children were divided into a normal penile group (Group AA) and a micropenis group (Group BB) after mild hypospadias according to SPL.Multivariate Logistic regression analysis was used to construct a risk prediction model, which was evaluated using the ROC curve.Results:The levels of FSH, LH and TES in group A before the operation were 3.28(2.02, 4.46) IU/L, 0.53(0.25, 0.79) IU/L and 25.24(17.94, 36.67) ng/dL, respectively, and those in group B were 1.42(1.10, 1.84) IU/L, 0.14(0.09, 0.23) IU/L and 15.73 (12.92, 17.00) ng/dL, respectively.The difference was all statistically significant (all P<0.05).Multivariate Logistic regression analysis showed statistical significance ( OR=0.515, 95% CI: 0.271-0.977; OR=0.035, 95% CI: 0.002-0.542; OR=0.883, 95% CI: 0.796-0.980).The area under the ROC curve (AUC) of the prediction model was 0.906, with a sensitivity of 75.00% and a specificity of 95.74%.The levels of FSH, LH and TES in the postoperative AA group were 2.97 (1.88, 4.28) IU/L, 0.46 (0.23, 0.78) IU/L and 20.92 (17.34, 33.27) ng/dL, respectively.The median levels of FSH, LH and TES in the BB group were 1.52 (1.27, 1.82) IU/L, 0.17 (0.12, 0.26) IU/L and 15.08(11.68, 16.68) ng/dL, respectively.The difference was all statistically significant (all P<0.05).Multivariate Logistic regression analysis showed statistical significance ( OR=0.484, 95% CI: 0.236-0.992; OR=0.061, 95% CI: 0.004-0.939; OR=0.891, 95% CI: 0.795-0.999).The AUC of the prediction model constructed was 0.877, with a sensitivity of 94.12% and a specificity of 68.52%. Conclusions:Lower FSH, LH and TES levels are risk factors for the micropenis after mild hypospadias surgery, and preoperative hormone levels have higher predictive value.

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 analyze and compare the efficacy of DNA barcode,i.e.,Cytochrome b(Cytb)and 12S ribosomal RNA(12S rRNA)gene sequences,in the species identification of wildlife.Methods DNA extraction,quantification,PCR amplification of Cytb and 12S rRNA gene fragments,Sanger sequencing,and sequence alignment analysis were performed on ten wildlife samples.Results Both gene fragments were successfully amplified in six samples,while Cytb alone was successfully amplified in 1 sample,and 12S rRNA alone in 3 samples.Sequence analysis indicated that Cytb enabled species-level identification for 6 samples(Gallinula chloropus,Streptopelia orientalis,Phasianus colchicus,Falco naumanni,Myiopsitta monachus and Lynx lynx)and genus-level identification for 1 sample(Lepus).In contrast,12S rRNA achieved species-level identificaggion for 8 samples(Gallinula chloropus,Lepus sinensis,Phasianus colchicus,Myiopsitta monachus,Muntiacus reevesi,Macaca mulatta and Lynx lynx),representing seven species,and genus-level identification for 1 sample(Falco).However,by combining Cytb and 12S rRNA,all samples could be identified to the species level.Conclusion When applying DNA barcodes to wildlife identification,the Cytb and 12S rRNA gene regions analyzed here can effectively identify common species such as Gallinula chloropus and Streptopelia orientalis,but face difficulties in distinguishing closely related species within the same genus.Therefore,when conducting wildlife species identification,it is recommended to use two or more DNA barcode markers.

Objective To analyze the risk factors of fluconazole resistance in Candida tropicalis(C.tropicalis)urinary tract infection(UTI),and evaluate the efficacy of different treatment regimens.Methods Patients with C.tropicalis UTI at Xiangya Hospital of Central South University from January 2021 to December 2023 were in-cluded for single center retrospective study.The minimum inhibitory concentration(MIC)of fluconazole was deter-mined by microbroth dilution.Patients were divided into a fluconazole-resistant group and a fluconazole-sensitive group based on fluconazole resistance.Risk factors for fluconazole resistance were analyzed based on clinical data,and therapeutic efficacy in patients in fluconazole-resistant group was analyzed.Results A total of 198 patients were included in the study.133(67.2％)C.tropicalis strains were detected to be sensitive to fluconazole,while 65(32.8％)strains were resistant,and 63.1％(n=41)had MIC values ≥128 μg/mL.Compared with fluconazole-sensitive group,fluconazole-resistant group had a higher proportion of pulmonary infection(P=0.019).Pulmonary infection(OR=3.282)was a risk factor for fluconazole resistance in C.tropicalis UTI,while urinary system ob-struction(OR=0.269)was a protective factor for fluconazole resistance in C.tropicalis UTI.There was no statis-tically significant difference in the usage rate of different antimicrobial agent types between the two groups(all P＞0.05).The therapeutic efficacy analysis showed that the effective rates of treatment with fluconazole dosage regi-mens of ≤200 mg/d,≥400 mg/d,and fluconazole monotherapy against fluconazole-resistant strains were 66.7％(6/9),83.3％(5/6),and 100％(6/6),respectively.For patients treated with monotherapy using other drugs or with multidrug sequential treatment regimens,the treatment effective rate was 60.0％(3/5).The proportion of pa-tients in the effective treatment group who removed their urinary catheters after detecting C.tropicalis was higher than that in the ineffective treatment group(P＜0.001).Conclusion The fluconazole resistance of C.tropicalis is related to urinary tract obstruction and concurrent pulmonary infection.When treating UTI caused by fluconazole-resistant strains,the catheter should be removed as early as possible.In addition to increasing the dosage of flucon-azole,other antifungal drugs such as flucytosine alone or sequential treatment with multiple drugs can also be con-sidered.

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.