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Retinal fundus diseases can lead to irreversible visual impairment without timely diagnoses and appropriate treatments. Single disease-based deep learning algorithms had been developed for the detection of diabetic retinopathy, age-related macular degeneration, and glaucoma. Here, we developed a deep learning platform (DLP) capable of detecting multiple common referable fundus diseases and conditions (39 classes) by using 249,620 fundus images marked with 275,543 labels from heterogenous sources. Our DLP achieved a frequency-weighted average F1 score of 0.923, sensitivity of 0.978, specificity of 0.996 and area under the receiver operating characteristic curve (AUC) of 0.9984 for multi-label classification in the primary test dataset and reached the average level of retina specialists. External multihospital test, public data test and tele-reading application also showed high efficiency for multiple retinal diseases and conditions detection. These results indicate that our DLP can be applied for retinal fundus disease triage, especially in remote areas around the world. Systems for automatic detection of a single disease may miss other important conditions. Here, the authors show a deep learning platform can detect 39 common retinal diseases and conditions.

PurposeTo determine the expressions of SARS-CoV-2 receptor angiotensin-converting enzyme 2 (ACE2) and type II transmembrane serine protease (TMPRSS2) genes in human and mouse ocular cells and comparison to other tissue cells.MethodsHuman conjunctiva and primary pterygium tissues were collected from pterygium patients who underwent surgery. The expression of ACE2 and TMPRSS2 genes was determined in human primary conjunctival and pterygium cells, human ocular and other tissue cell lines, mesenchymal stem cells as well as mouse ocular and other tissues by reverse transcription-polymerase chain reaction (RT-PCR) and SYBR green PCR.ResultsRT-PCR analysis showed consistent expression by 2 ACE2 gene primers in 2 out of 3 human conjunctival cells and pterygium cell lines. Expression by 2 TMPRSS2 gene primers could only be found in 1 out of 3 pterygium cell lines, but not in any conjunctival cells. Compared with the lung A549 cells, similar expression was noted in conjunctival and pterygium cells. In addition, mouse cornea had comparable expression of Tmprss2 gene and lower but prominent Ace2 gene expression compared with the lung tissue.ConclusionConsidering the necessity of both ACE2 and TMPRSS2 for SARS-CoV-2 infection, our results suggest that conjunctiva would be less likely to be infected by SARS-CoV-2, whereas pterygium possesses some possibility of SARS-CoV-2 infection. With high and consistent expression of Ace2 and Tmprss2 in cornea, cornea rather than conjunctiva has higher potential to be infected by SARS-CoV-2. Precaution is necessary to prevent possible SARS-CoV-2 infection through ocular surface in clinical practice.

Neuromyelitis optica spectrum disorder (NMOSD) is a rare, disabling inflammatory disease of the central nervous system (CNS). Aquaporin-4 (AQP4)-specific T cells play a key role in the pathogenesis of NMOSD. In addition to immune factors, T cells recognizing the AQP4 epitope showed cross-reactivity with homologous peptide sequences in C. perfringens proteins, suggesting that the gut microbiota plays an integral role in the pathogenicity of NMOSD. In this review, we summarize research on the involvement of the gut microbiota in the pathophysiology of NMOSD and its possible pathogenic mechanisms. Among them, Clostridium perfringens and Streptococcus have been confirmed to play a role by multiple studies. Based on this evidence, metabolites produced by gut microbes, such as short-chain fatty acids (SCFAs), tryptophan (Trp), and bile acid (BA) metabolites, have also been found to affect immune cell metabolism. Therefore, the role of the gut microbiota in the pathophysiology of NMOSD is very important. Alterations in the composition of the gut microbiota can lead to pathological changes and alter the formation of microbiota-derived components and metabolites. It can serve as a biomarker for disease onset and progression and as a potential disease-modifying therapy.

The axonal growth capacity of retinal ganglion cells decreases dramatically within the first day of birth, and the axonal regeneration after injury in mature mammals is very limited. Here, this study aimed to delineate the transcriptomic changes associated with altered axonal growth capacity and to identify the key genes associated with axonal regeneration by the RNA sequencing (RNA-Seq) analysis. The whole retinas from the mice of embryonic day (E) 20, postnatal day (P) 1 and P3 were collected at 6 hours after optic nerve crush (ONC). Differentially expressed genes (DEGs) for ONC or ages were identified by the RNA-Seq analysis. K-means analysis was conducted for the clustering of DEGs based on expression patterns. Enrichment of functions and signaling pathways analysis were performed based on Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) database, and Gene Set Enrichment analysis (GSEA). Quantitative real time polymerase chain reaction (qRT-PCR) was used to validate the DEGs selected from the RNA-Seq analysis. In total, 5,408 DEGs were identified for ages, and 2,639 DEGs in neonatal mouse retina after ONC. K-means analysis revealed 7 clusters in age-DEGs and 11 clusters in ONC-DEGs. The GO, KEGG and GSEA pathway analyses identified significantly enrichment of DEGs in the visual perception and phototransduction for the age effect, and the break repair, neuron projection guidance, and immune system pathway for the ONC. PPI analysis identified hub genes in the axon-related gene cluster. The expressions of Mlc1, Zfp296, Atoh7, Ecel1, Creb5, Fosb, and Lcn2, thought to be involved in RGC death and axonal growth were validated by qRT-PCR. This study, for the first time, delineated the gene expression changes following ON injury in embryonic and neonatal mice, providing a new resource of age- and injury-driven data on axonal growth capacity.

Optic neuropathies refer to a group of ocular disorders with abnormalities or dysfunction of the optic nerve, sharing a common pathophysiology of retinal ganglion cell (RGC) death and axonal loss. RGCs, as the retinal neurons in the central nervous system, show limited capacity in regeneration or recovery upon diseases or after injuries. Critically, there is still no effective clinical treatment to cure most types of optic neuropathies. Recently, stem cell therapy was proposed as a potential treatment strategy for optic neuropathies. Adult stem cells, including mesenchymal stem cells and hematopoietic stem cells, have been applied in clinical trials based on their neuroprotective properties. In this article, the applications of adult stem cells on different types of optic neuropathies and the related mechanisms will be reviewed. Research updates on the strategies to enhance the neuroprotective effects of human adult stem cells will be summarized. This review article aims to enlighten the research scientists on the diversified functions of adult stem cells and consideration of adult stem cells as a potential treatment for optic neuropathies in future clinical practices.

Social media intervention may enhance HIV prevention among men who have sex with men, but the effect of this intervention in resource-limited settings remains unclear. This randomized controlled trial evaluated whether a social media intervention grounded in the information-motivation-behavioral skills (IMB) model could be beneficial for HIV prevention among men who have sex with men in resource-limited settings. Participants were recruited in Nanning, China, between April 2023 and April 2024. Eligible participants were randomly assigned to either the social media intervention group or the routine HIV prevention services control group. Participants in the intervention group received a 3-month social media intervention, which included completing video-based tasks. Baseline surveys were conducted, followed by follow-up surveys every 3 months, for a total of 2 follow-ups. Outcomes included HIV testing uptake, high-risk behavior, AIDS-related knowledge, safe sex self-efficacy, and attitude. A total of 180 eligible men who have sex with men were enrolled (90 per group). Follow-up rates were 97.8% (88/90) and 95.5% (86/90) for the intervention and control groups, respectively. At the follow-ups, the intervention group demonstrated significantly higher uptake of HIV testing, a lower proportion of participants reporting high-risk sexual behaviors, and higher condom use self-efficacy compared to the control group (all P<.05). After controlling for sociodemographic variables, generalized estimating equations analysis revealed that the intervention group had significantly higher odds of HIV testing (risk ratio [RR] 1.739, 95% CI 1.110-2.730), HIV self-testing (RR 2.306, 95% CI 1.593-3.340), and consistent condom use (RR 2.457, 95% CI 1.636-3.690) than the control group. Cochran-Armitage trend tests within the intervention group revealed that with increasing intervention duration, both HIV testing and HIV self-testing significantly increased, while high-risk sexual behaviors significantly decreased (all P<.05). The social media intervention guided by the IMB model demonstrated a positive effect on expanding HIV testing coverage, reducing high-risk behavior, enhancing AIDS-related knowledge, and improving safer sex self-efficacy among men who have sex with men in resource-limited settings. These findings provide valuable guidance for future HIV prevention and control efforts targeting this population.

A retinopathy of prematurity (ROP) diagnosis currently relies on indirect ophthalmoscopy assessed by experienced ophthalmologists. A deep learning algorithm based on retinal images may facilitate early detection and timely treatment of ROP to improve visual outcomes. To develop a retinal image-based, multidimensional, automated, deep learning platform for ROP screening and validate its performance accuracy. A total of 14 108 eyes of 8652 preterm infants who received ROP screening from 4 centers from November 4, 2010, to November 14, 2019, were included, and a total of 52 249 retinal images were randomly split into training, validation, and test sets. Four main dimensional independent classifiers were developed, including image quality, any stage of ROP, intraocular hemorrhage, and preplus/plus disease. Referral-warranted ROP was automatically generated by integrating the results of 4 classifiers at the image, eye, and patient levels. DeepSHAP, a method based on DeepLIFT and Shapley values (solution concepts in cooperative game theory), was adopted as the heat map technology to explain the predictions. The performance of the platform was further validated as compared with that of the experienced ROP experts. Data were analyzed from February 12, 2020, to June 24, 2020. A deep learning algorithm. The performance of each classifier included true negative, false positive, false negative, true positive, F1 score, sensitivity, specificity, receiver operating characteristic, area under curve (AUC), and Cohen unweighted κ. A total of 14 108 eyes of 8652 preterm infants (mean [SD] gestational age, 32.9 [3.1] weeks; 4818 boys [60.4%] of 7973 with known sex) received ROP screening. The performance of all classifiers achieved an F1 score of 0.718 to 0.981, a sensitivity of 0.918 to 0.982, a specificity of 0.949 to 0.992, and an AUC of 0.983 to 0.998, whereas that of the referral system achieved an F1 score of 0.898 to 0.956, a sensitivity of 0.981 to 0.986, a specificity of 0.939 to 0.974, and an AUC of 0.9901 to 0.9956. Fine-grained and class-discriminative heat maps were generated by DeepSHAP in real time. The platform achieved a Cohen unweighted κ of 0.86 to 0.98 compared with a Cohen κ of 0.93 to 0.98 by the ROP experts. In this diagnostic study, an automated ROP screening platform was able to identify and classify multidimensional pathologic lesions in the retinal images. This platform may be able to assist routine ROP screening in general and children hospitals.

PurposeThis study aims to evaluate and compare the diagnostic reasoning of five large language models (LLMs) in complex neuro-ophthalmological cases. We assessed the performance of GPT-o1 Pro, GPT-4o, Google Gemini, Grok 2 and DeepSeek in handling clinical scenarios related to neuro-ophthalmology.Method18 clinical scenarios, derived from six complex neuro-ophthalmological cases, were presented to five LLMs: GPT-o1 Pro, GPT-4o, Google Gemini, Grok 2 and DeepSeek. The responses generated by these models were evaluated using the Revised-IDEA (R-IDEA) assessment tool. R-IDEA scores for high-quality responses ranged from 6 to 10, with ‘Excellent’ responses defined as those scoring between 8 and 10. In addition, the simplicity of each response was evaluated based on word count using a readability tool.ResultGPT-o1 Pro (8.80) significantly outperformed GPT-4o (6.80) and Grok 2 (6.94) in the R-IDEA scores (p=0.001). It achieved 100% high-quality responses, compared with 72.2% for GPT-4o, 77.8% for Grok 2 and 83.3% for both Gemini and DeepSeek (p=0.175). Regarding ‘Excellent’ responses, GPT-o1 Pro achieved 88.9% of its responses rated as Excellent, significantly outperforming the other models: 27.8% for GPT-4o, 38.9% for Grok 2 and 55.6% for both Gemini and DeepSeek (p=0.003). GPT-o1 Pro used the fewest words, showing significant differences compared with GPT-4o (p<0.001) and Gemini (p=0.032).ConclusionThe study underscores the superior clinical reasoning capabilities of ChatGPT-o1 Pro in neuro-ophthalmology compared with other LLMs, highlighting its potential for enhancing diagnostic processes in this complex field.

Background HIV post-exposure prophylaxis (PEP) and pre-exposure prophylaxis (PrEP) are effective yet underutilized HIV prevention modalities. This study aims to evaluate the awareness-to-use cascade for PEP and PrEP, and to examine the transition from PEP to PrEP among men who have sex with men (MSM). We will discuss the rationale for using PrEP after PEP use. Methods With an observational, longitudinal study design, MSM were recruited from five cities in Guangxi, China. Participants completed questionnaires every 3 months and were tracked for 12 months. Descriptive statistics summarized the awareness, use, cascade and transition of PEP and PrEP. The effect of PEP use on PrEP use was analyzed using Generalized Estimating Equations. Results A total of 363 eligible MSM were recruited, and 350 participants completed at least one follow-up visit. Overall, at baseline, 96.7% were aware of PEP, and 15.2% used it. 76.0% were aware of PrEP, and 5.2% used it. According to baseline and follow-up surveys, of the 68 participants who used PEP, 29.4% reported initiating PrEP after a PEP course; of these, 60.0% did so after a single course. The median number of PEP uses before transitioning was 1 (interquartile range [IQR]: 1 to 2.5). The median time interval for transitioning from PEP to PrEP was 11 months (IQR: 4 to 18 months). After adjusting for sociodemographic and sexual behavior factors, having previously used PEP is one of the main predictors of PrEP use (adjusted odds ratio [AOR] 5.45, 95% CI: 1.80–16.50). Conclusions Although awareness of PEP and PrEP among MSM in Guangxi, China was high, the proportion of participants initiating PEP and PrEP remained low. It is recommended that effective support and screening for transitioning to PrEP be provided after a successful first use of PEP to promote the broader implementation of HIV prevention measures.

The temperature response of net CO₂ assimilation rate (A), the rate of whole-chain electron transport, the activity and activation state of Rubisco, and the pool sizes of ribulose-1,5-bisphosphate (RuBP) and 3-phosphoglyceric acid (PGA) were assessed in sweet potato (Ipomoea batatas) grown under greenhouse conditions. Above the thermal optimum of photosynthesis, the activation state of Rubisco declined with increasing temperature. Doubling CO₂ above 370 [micro]bar further reduced the activation state, while reducing CO₂ by one-half increased it. At cool temperature (<16°C), the activation state of Rubisco declined at CO₂ levels where photosynthesis was unaffected by a 90% reduction in O₂ content. Reduction of the partial pressure of CO₂ at cool temperature also enhanced the activation state of Rubisco. The rate of electron transport showed a pronounced temperature response with the same temperature optimum as A at elevated CO₂. RuBP pool size and the RuBP-to-PGA ratio declined with increasing temperature. Increasing CO₂ also reduced the RuBP pool size. These results are consistent with the hypothesis that the reduction in the activation state of Rubisco at high and low temperature is a regulated response to a limitation in one of the processes contributing to the rate of RuBP regeneration. To further evaluate this possibility, we used measured estimates of Rubisco capacity, electron transport capacity, and the inorganic phosphate regeneration capacity to model the response of A to temperature. At elevated CO₂, the activation state of Rubisco declined at high temperatures where electron transport capacity was predicted to be limiting, and at cooler temperatures where the inorganic phosphate regeneration capacity was limiting. At low CO₂, where Rubisco capacity was predicted to limit photosynthesis, full activation of Rubisco was observed at all measurement temperatures.