Because of its benign nature and rarity, circumscribed choroidal hemangioma (CCH) often receives limited attention, leading to a high rate of misdiagnosis and a lack of standardized treatment protocols. We provide a thorough clarification of the demographics, clinical features, diagnosis, management, and prognosis of CCH. We conducted a systematic search of the PubMed, EMBASE, and Ovid databases up to December, 2023, to identify relevant studies. The study included 106 studies encompassing 3854 patients with CCH. The demographic profile revealed a male preponderance (62 %, 95 % CI 61-64 %) and a peak incidence in the working-age population (30-50 years, 48 %, 95 % CI 39-57 %), with the right eye being involved in 50 % of cases (95 % CI 48-53 %). Clinically, the most common symptom was decreased vision (90 %, 95 % CI 78-99 %), followed by blurred vision, visual field defect, and metamorphopsia. Fundus examination frequently revealed an orange-colored tumor (80 %, 95 % CI 58-96 %) located subfoveally (48 %, 95 % CI 42-53 %), often accompanied by subretinal fluid (SRF) (84 %, 95 % CI 78-89 %) and sometimes exudative retinal detachment (69 %, 95 % CI 51-85 %). The proportion of correctly diagnosed CCH upon first presentation was 13 % (95 % CI 3-26 %), with CCH commonly misdiagnosed as unspecified choroidal tumors, choroidal metastasis, and central serous chorioretinopathy. Photodynamic therapy (PDT) was the most widely researched treatment, taking up 18 % (95 % CI 8-31 %), followed by observation, transpupillary thermotherapy (TTT), and laser photocoagulation. When no treatment was applied, 33 % of patients experienced visual acuity improvement, which increased to 76 % (95 % CI 58-90 %) with radiotherapy and 58 % (95 % CI 50-67 %) with PDT. In terms of tumor shrinkage, radiotherapy was most effective (100 %), with PDT close behind (95 % CI 96-100 %), and TTT at 63 % (95 % CI 45-80 %). PDT led to SRF resolution in 89 % (95 % CI 77-97 %) of patients and cystoid macular edema (CME) resolution in 73 % (95 % CI 38-97 %), while radiotherapy achieved the highest efficacy with 100 % SRF resolution (95 % CI: 99-100 %) and 100 % CME resolution (95 % CI: 83-100 %). Complication rates were highest with radiotherapy (14 %, 95 % CI 5-25 %) and PDT (9 %, 95 % CI 4-16 %). First-line treatment failure rates were highest for TTT (71 %, 95 % CI 44-92 %) and laser (70 %, 95 % CI 28-99 %), with radiotherapy showing the lowest rate (0 %, 95 % CI 0-2 %). Recurrence rates were highest for laser (68 %, 95 % CI 17-100 %) and TTT (62 %, 95 % CI 26-93 %), whereas radiotherapy had the lowest recurrence rate (0 %, 95 % CI 0-1 %). CCH predominantly affects the working-age male population, often leading to vision impairment and SRF. The diagnosis of CCH remains challenging, with low accuracy and frequent misdiagnoses. While PDT is the most widely researched treatment, radiotherapy offers superior outcomes in visual acuity, tumor shrinkage, and resolution of SRF and CME, though it carries higher complication rates. This study highlights the need for improved diagnostic accuracy and a balanced approach to treatment.

KIF1A, a microtubule-based motor protein responsible for axonal transport, is linked to a group of neurological disorders known as KIF1A-associated neurological disorder (KAND). Current therapeutic options for KAND are limited. Here, we introduced the clinically relevant KIF1A(R11Q) variant into the Caenorhabditis elegans homolog UNC-104, resulting in uncoordinated animal behaviors. Through genetic suppressor screens, we identified intragenic mutations in UNC-104’s motor domain that rescued synaptic vesicle localization and coordinated movement. We showed that two suppressor mutations partially recovered motor activity in vitro by counteracting the structural defect caused by R11Q at KIF1A’s nucleotide-binding pocket. We found that supplementation with fisetin, a plant flavonol, improved KIF1A(R11Q) worms’ movement and morphology. Notably, our biochemical and single-molecule assays revealed that fisetin directly restored the ATPase activity and processive movement of human KIF1A(R11Q) without affecting wild-type KIF1A. These findings suggest fisetin as a potential intervention for enhancing KIF1A(R11Q) activity and alleviating associated defects in KAND.

Background Dysregulation of cholesterol metabolism has been recognized as a critical driver in the pathogenesis of hepatic disorders, particularly hepatocellular carcinoma (HCC) and metabolic dysfunction-associated steatotic liver disease (MASLD). However, the causal relationships between circulating proteins involved in cholesterol homeostasis and the progression of these hepatopathologies remain insufficiently explored, warranting further mechanistic investigation. Methods This study utilized Mendelian randomization (MR) to identify the role of cholesterol metabolism-related proteins in HCC and MASLD. We systematically investigated the causal associations of these proteins with HCC and MASLD and their roles in disease progression using circulating proteomic databases and bioinformatics tools. In addition, network-based drug repositioning techniques and molecular docking experiments were utilized to assess the interactions of the above biomarkers with known drugs to discover drugs with potential therapeutic effects. Results MR analysis identified several proteins linked with significant risk for HCC and MASLD. Notably, apolipoprotein E (APOE) expression was significantly increased in tissues from HCC and MASLD patients, closely correlating with elevated disease risk. Meta-analysis demonstrated a significant causal relationship between APOE and increased risk of HCC (OR: 1.710, 95% CI 1.220–2.400; P < 0.01) and MASLD (OR: 1.490, 95% CI 1.280–1.740; P < 0.01). Additionally, network analysis revealed extensive interactions between APOE and other disease-related proteins, suggesting that APOE may contribute to liver disease progression through its influence on complex protein networks. Conclusion Our findings delineate a novel mechanistic involvement of cholesterol regulatory proteins, with APOE demonstrating pathogenic significance in both HCC and MASLD. This investigation substantially provides new insights into the molecular mechanisms of these liver diseases and highlights potential therapeutic targets.

Background: The utilization of immunotherapeutic approaches in the operable settings has demonstrated promising efficacy and safety in preventing postoperative recurrence and improving patients’ survival across various cancer types. To delineate the developmental trajectory and future directions of this specialized field, a comprehensive bibliometric analysis is necessary. Materials and methods: A total of 541 high-quality publications focusing on the convergence of immunotherapy and surgery were manually extracted from 6973 papers published between 2015 and 2024 in the Web of Science Core Collection. Traditional bibliometric analysis was conducted utilizing VOSviewer, CiteSpace, and the Bibliometrix R package to identify contributions at national and institutional levels, journal impact, and pivotal keywords. The integration of large language model (LLM)-driven text embeddings alongside BERTopic-based semantic modeling enabled a comprehensive synthesis of themes and illuminated prospective directions within this field. Furthermore, advanced dimensionality reduction techniques such as Uniform Manifold Approximation and Projection and t-distributed Stochastic Neighbor Embedding were employed to visualize clustering outcomes and interpret the semantic distances among these academic publications. Results: The distribution of publications over time indicated a growing interest in the integration of immunotherapy and surgery. China and the United States were leaders in publication volume and academic influence, while the “ Journal for Immunotherapy of Cancer ” stands out as a key resource. Clustering based on LLM-driven embedding vectors identified five categories of papers, the thematic classification of which was presented in a hierarchical structure. Further in-depth analysis revealed the optimal utilization patterns of immune checkpoint inhibitors (ICIs) vary across different cancer types. Neoadjuvant ICIs are effective for triple negative breast cancer, non-small cell lung cancer, melanoma, and deficient mismatch repair colon cancer. Adjuvant mRNA vaccines are viable for pancreatic ductal adenocarcinoma and melanoma, while oncolytic virus demonstrate enhanced efficacy alongside manageable toxicity in perioperative settings. Conclusion: This bibliometric analysis, which integrates LLM-driven modeling with manual thematic synthesis, has elucidated the developmental trajectory and future directions of the field concerning the combination of immunotherapy and surgery.

Background: Age-related macular degeneration (AMD) represents a significant clinical concern, particularly in aging populations, and recent advancements in artificial intelligence (AI) have catalyzed substantial research interest in this domain. Despite the growing body of literature, there remains a need for a comprehensive, quantitative analysis to delineate key trends and emerging areas in the field of AI applications in AMD. This bibliometric analysis sought to systematically evaluate the landscape of AI-focused research on AMD to illuminate publication patterns, influential contributors, and focal research trends. Methods: Using the Web of Science Core Collection (WoSCC), a search was conducted to retrieve relevant publications from 1992 to 2023. This analysis involved an array of bibliometric indicators to map the evolution of AI research in AMD, assessing parameters such as publication volume, national/regional and institutional contributions, journal impact, author influence, and emerging research hotspots. Visualization tools, including Bibliometrix, CiteSpace and VOSviewer, were employed to generate comprehensive assessments of the data. Results: A total of 1,721 publications were identified, with the USA leading in publication output and the University of Melbourne as the most prolific institution. The journal Investigative Ophthalmology & Visual Science published the highest number of articles, and Schmidt-Eerfurth emerged as the most active author. Keyword and clustering analyses, along with citation burst detection, revealed three distinct research stages within the field from 1992 to 2023. Presently, research efforts are concentrated on developing deep learning (DL) models for AMD diagnosis and progression prediction. Prominent emerging themes include early detection, risk stratification, and treatment efficacy prediction. The integration of large language models (LLMs) and vision-language models (VLMs) for enhanced image processing also represents a novel research frontier. Conclusions: This bibliometric analysis provides a structured overview of prevailing research trends and emerging directions in AI applications for AMD. These findings furnish valuable insights to guide future research and foster collaborative advancements in this evolving field.

Background Metabolic reprogramming, especially lipid metabolism, is crucial in cancer progression and treatment resistance. Apolipoproteins are crucial targets for research as they regulate autophagy, oxidative stress, and chemoresistance. A systematic bibliometric and bioinformatics approach is necessary to identify trends and elucidate the molecular mechanisms linking apolipoproteins to cancer. Methods A systematic bibliometric analysis was conducted using the Web of Science Core Collection and PubMed. VOSviewer, CiteSpace, and the Bibliometrix R package were employed to analyze and visualize co-authorship networks, keyword trends, and other key metrics. Bioinformatics analysis integrated protein–protein interaction network construction, hub gene identification, and enrichment analysis using R-based pipelines. Results China has led the international research on apolipoproteins and cancer since 2015. Research has shifted from molecular studies to clinical applications, highlighting the roles of apolipoproteins in cancer risk, progression, and prognosis. Bioinformatic analysis identified key genes represented by APOA1 (apolipoprotein A1), APOE (apolipoprotein E), APOA2 (apolipoprotein A2), and ALB (Albumin) as central regulators in lipid localization, cholesterol metabolism, insulin resistance, and the peroxisome proliferator-activated receptors (PPARs) signaling pathways. Conclusions This study combines bibliometric and bioinformatic approaches to explore apolipoprotein research in cancer. The research trend revealed apolipoproteins with the most research potential in a specific cancer type, as confirmed in the clinical trials. Bioinformatic research found the key genes regulating several essential lipid-related pathways. This article clearly outlined the research landscape and frontiers of this field by combining various databases and methods, highlighting the significant potential of apolipoproteins in the development of novel cancer medications.