Citations

Opioid use disorders (OUDs) pose a substantial global health burden, with methadone maintenance treatment (MMT) widely adopted as an intervention; however, MMT is associated with immunosuppression, metabolic disturbances, and dysbiosis of the gut microbiota. Despite the potential of acupuncture in reducing methadone dosages and opioid addiction, the underlying biological mechanisms remain unclear. Therefore, we aimed to integrate clinical trial data with multi-omics analysis, including single-cell sequencing, transcriptomics, metabolomics, and metagenomics, to evaluate the effects of acupuncture in patients undergoing MMT. We collected peripheral blood mononuclear cells, plasma, and fecal samples from 48 MMT participants in a randomized, placebo-controlled trial. Participants were divided into acupuncture ( n = 25) and sham-acupuncture ( n = 23) groups. After 8 weeks of intervention, 84% of patients in the acupuncture group achieved ≥20% reduction in methadone dosage, compared to 39% in the sham-acupuncture group ( P < 0.01). Our findings revealed that acupuncture may activate the defense response to viruses, with altered immune cell functions in classical monocytes correlating with clinical responses to reduced methadone doses. Acupuncture might ameliorate intestinal microbial disruptions caused by OUD by up-regulating Bilophila and modulating bile acid metabolism. Furthermore, acupuncture up-regulated galectin-9 (LGALS9)-mediated intercellular communication between classical monocytes and other immune subsets. To further validate the mechanistic link between bile acid metabolism and immune regulation, we conducted in vitro experiments using THP-1 monocytes treated with cholic acid. The results showed that bile acid exposure suppressed galectin-9 and IFN-γ expression, while low-dose bile acid (simulating acupuncture effects) partially reversed this effect. These findings support a bile acid–galectin–interferon axis that may be modulated by acupuncture in OUD. Collectively, our results provide clinical and mechanistic evidence supporting acupuncture as a potential adjunct therapy to mitigate the adverse effects of long-term opioid use.

Background/Objectives: Facial analysis is critical for preoperative planning in facial plastic surgery, but traditional methods can be time consuming and subjective. This study investigated the potential of Artificial Intelligence (AI) for objective and efficient facial analysis in plastic surgery, with a specific focus on Multimodal Large Language Models (MLLMs). We evaluated their ability to analyze facial skin quality, volume, symmetry, and adherence to aesthetic standards such as neoclassical facial canons and the golden ratio. Methods: We evaluated four MLLMs—ChatGPT-4o, ChatGPT-4, Gemini 1.5 Pro, and Claude 3.5 Sonnet—using two evaluation forms and 15 diverse facial images generated by a Generative Adversarial Network (GAN). The general analysis form evaluated qualitative skin features (texture, type, thickness, wrinkling, photoaging, and overall symmetry). The facial ratios form assessed quantitative structural proportions, including division into equal fifths, adherence to the rule of thirds, and compatibility with the golden ratio. MLLM assessments were compared with evaluations from a plastic surgeon and manual measurements of facial ratios. Results: The MLLMs showed promise in analyzing qualitative features, but they struggled with precise quantitative measurements of facial ratios. Mean accuracy for general analysis were ChatGPT-4o (0.61 ± 0.49), Gemini 1.5 Pro (0.60 ± 0.49), ChatGPT-4 (0.57 ± 0.50), and Claude 3.5 Sonnet (0.52 ± 0.50). In facial ratio assessments, scores were lower, with Gemini 1.5 Pro achieving the highest mean accuracy (0.39 ± 0.49). Inter-rater reliability, based on Cohen’s Kappa values, ranged from poor to high for qualitative assessments (κ > 0.7 for some questions) but was generally poor (near or below zero) for quantitative assessments. Conclusions: Current general purpose MLLMs are not yet ready to replace manual clinical assessments but may assist in general facial feature analysis. These findings are based on testing models not specifically trained for facial analysis and serve to raise awareness among clinicians regarding the current capabilities and inherent limitations of readily available MLLMs in this specialized domain. This limitation may stem from challenges with spatial reasoning and fine-grained detail extraction, which are inherent limitations of current MLLMs. Future research should focus on enhancing the numerical accuracy and reliability of MLLMs for broader application in plastic surgery, potentially through improved training methods and integration with other AI technologies such as specialized computer vision algorithms for precise landmark detection and measurement.

Objective To pool data from prospective clinical trials investigating combined stereotactic ablative radiotherapy (SABR) with immune checkpoint inhibitors (ICI) in patients with metastatic cancers. Methods and analysis PubMed, Scopus and EMBASE were queried for full-length articles of prospective clinical trials involving patients with metastatic solid tumours. Random-effects meta-analysis was performed with the Knapp-Hartung method. Multilevel regression analyses with primary cancers used as random effects and pairwise comparisons with two-tailed test adjusted with Benjamini-Hochberg method were performed. Regression coefficients (β) were calculated to assess the correlation between dose and outcomes. Results We identified 30 trials and 35 individual treatment arms with a total of 951 patients with at least one outcome metric reported. Large heterogeneity was identified for all outcomes measured (I 2 range: 75%–86%). The pooled rate of grade 3+ treatment-related adverse events was 18% (95% CI 11% to 24%). The progression-free survival (PFS) and overall survival (OS) at 6 months were 27% (95% CI 19% to 36%) and 67% (95% CI 59% to 76%), respectively. On multilevel regression, we identified improvement in 6-month PFS (β=0.6, p=0.003) and OS (β=1.6, p=0.04) with increasing BED10Gy doses. Combined-target ICI correlated with better 6-month OS when compared with αPD-1/PD-L1 alone. Conclusion We report a safety profile of combined ICI with SABR in patients with metastatic cancer that is comparable to that of ICI alone. We identified higher doses of radiotherapy and dual-target ICI to be associated with better OS at 6 months. Large heterogeneity and the lack of a control group limit the interpretation of our findings.

Abstract Gliomas are highly malignant brain tumors with poor prognosis and short survival. Nicotinamide adenine dinucleotide (NAD+) plays a critical role in cancer progression, yet anti-cancer therapies targeting NAD+ synthesis have had limited clinical success due to an incomplete understanding of its mechanisms. Here, we demonstrate the essential role of the NAD+ synthase nicotinamide mononucleotide adenylyltransferase (NMNAT) in glioma progression and its novel contribution to nuclear atypia. Analysis of the patient glioma transcriptomics dataset (GAPIA) indicated a strong correlation between high NMNAT transcription levels and poorer disease-free survival in low grade glioma (LGG) and glioblastoma multiforme (GBM). Utilizing quantitative statistical analysis to assess the size and circularity of about 3 million cells in glioma tissue samples from 19 patients, we identified the significant association between NMNAT1 protein level and increased nuclear atypia in different types of gliomas. Mechanistic studies in human glioma cells and a Drosophila glial neoplasia model revealed that NMNAT enhances glioma growth by promoting NAD+-dependent post-translational modifications poly(ADP-ribosyl)ation (PARylation) and deacetylation of p53, thereby attenuating the pro-apoptotic activity of p53. Additionally, NMNAT1 disrupts nuclear lamina integrity by altering lamin A/C distribution, further contributing to nuclear atypia and glioma progression. These findings uncover a novel tumorigenic mechanism involving NMNAT's regulation of nuclear architecture and NAD+-mediated metabolic signaling pathways, highlighting its roles in glioma growth and nuclear atypia. This study underscores NMNAT as a potential therapeutic target in glioma treatment. Citation Format: Jiaqi Liu, Xianzun Tao, Yi Zhu, Xiang Gao, Tijana Canic, Kai Ruan, Zoraida Diaz-Perez, Sakir Humayun Gultekin, Priyamvada Rai, Qunfeng Dong, Grace Zhai. NMNAT-mediated NAD+ metabolism promotes glioma growth by modulating p53 post-translational modifications and nuclear atypia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_2):Abstract nr LB060.

Abstract Background: Although colorectal cancer survival rates are improving, the risk of incident type 2 diabetes mellitus (T2D) among Asian, Native Hawaiian, and Pacific Islander (ANHPI) ethnic groups is poorly understood. This study aims to identify high-risk groups and quantify the risk across different periods. Methods: Using the SEER–Medicare database, colorectal cancer survivors who were ANHPI were matched to non-Hispanic White (NHW) survivors at a ratio of 1:3. Multivariable Cox regression models computed HRs and 95% confidence intervals (CI) for incident T2D. Results: The study included 6,463 NHW and 2,901 ANHPI colorectal cancer survivors diagnosed between 2000 and 2017. Among them, 715 NHW and 484 ANHPI developed T2D during 39,097 and 10,769 person-years of follow-up, respectively. ANHPI colorectal cancer survivors had an elevated T2D risk compared with NHW across all follow-up periods (HRoverall: 1.84, 95% CI, 1.51–2.25; HR1–5 years: 1.83, 95% CI, 1.45–2.30). Southeast and East Asians demonstrated the highest T2D risks. Colon cancer was linked to early postdiagnosis T2D risk, whereas rectal cancer was associated with later risk. No significant association was observed for Native Hawaiians and Pacific Islanders. Conclusions: ANHPI colorectal cancer survivors face a greater risk of T2D, particularly among Southeast and East Asians. These findings highlight the need for evidence-based survivorship strategies to prevent T2D and reduce ethnic disparities. Impact: This is the first study to examine T2D risk among ANHPI colorectal cancer survivors, providing critical insights to inform tailored diabetes prevention and survivorship care.

Abstract While tissue-resident memory CD8+ T cells (TRM cells) provide superior frontline defense against pathogens, the molecular mechanisms governing their persistence and functional regulation remain poorly defined. Our study reveals that the costimulatory receptors CD27 and ICOS coordinately sustain PD-1high CD8+ TRM cell populations following resolution of acute influenza infection. These costimulatory signals serve as critical targets for PD-1/PD-L1 blockade, thereby facilitating the rejuvenation of PD-1high TRM cells and influencing the progression of fibrotic sequelae during the memory phase. Mechanistic dissection identifies the nuclear receptor Nur77 (NR4A1) as the convergent transcriptional hub downstream of CD27/ICOS, governing proliferative renewal and maintenance of PD-1high TRM cells. Therapeutic administration of a CD27 agonist not only amplified this TRM cell subset in late-stage memory but also conferred cross-protective immunity against heterosubtypic viral challenges. Clinically, the expression of CD27 and ICOS is enriched in CD8+ T cells within the lung tissues of patients with pulmonary fibrosis. Collectively, our findings establish the "CD27/ICOS-NR4A1-Proliferation" axis as a linchpin of PD-1/PD-L1-mediated TRM cell homeostasis, revealing druggable targets for intercepting infection-associated fibrotic progression.

Background: Anatomically accurate illustrations are imperative in medical education, serving as crucial tools to facilitate comprehension of complex anatomical structures. While traditional illustration methods involving human artists remain the gold standard, the rapid advancement of Generative Artificial Intelligence (GAI) models presents a new opportunity to automate and accelerate this process. This study evaluated the potential of GAI models to produce craniofacial anatomy illustrations for educational purposes. Methods: Four GAI models, including Midjourney v6.0, DALL-E 3, Gemini Ultra 1.0, and Stable Diffusion 2.0 were used to generate 736 images across multiple views of surface anatomy, bones, muscles, blood vessels, and nerves of the cranium in both oil painting and realistic photograph styles. Four reviewers evaluated the images for anatomical detail, aesthetic quality, usability, and cost-effectiveness. Inter-rater reliability analysis assessed evaluation consistency. Results: Midjourney v6.0 scored highest for aesthetic quality and cost-effectiveness, and DALL-E 3 performed best for anatomical detail and usability. The inter-rater reliability analysis demonstrated a high level of agreement among reviewers (ICC = 0.858, 95% CI). However, all models showed significant flaws in depicting crucial anatomical details such as foramina, suture lines, muscular origins/insertions, and neurovascular structures. These limitations were further characterized by abstract depictions, mixing of layers, shadowing, abnormal muscle arrangements, and labeling errors. Conclusions: These findings highlight GAI’s potential for rapidly creating craniofacial anatomy illustrations but also its current limitations due to inadequate training data and incomplete understanding of complex anatomy. Refining these models through precise training data and expert feedback is vital. Ethical considerations, such as potential biases, copyright challenges, and the risks of propagating inaccurate information, must also be carefully navigated. Further refinement of GAI models and ethical safeguards are essential for safe use.

Précis: 240-degree and 360-degree goniotomy (GT) demonstrated similar efficacy in intraocular pressure (IOP) reduction, both outperforming 120-degree GT in patients with juvenile open angle glaucoma (JOAG) at postoperative 6-month follow-up. Objective: To compare the surgical efficacy and safety of 120-degree, 240-degree, and 360-degree GT for patients with JOAG. Patients and Methods: This multicenter retrospective study included 102 eyes of 102 patients with JOAG, who underwent GT with a follow-up of at least 6 months. Patients were categorized into 3 groups: (1) 120-degree GT, (2) 240-degree GT, and (3) 360-degree GT. IOP, glaucoma medications, and complications were recorded at baseline and the final visit. Complete success and qualified success were defined as a postoperative IOP ≤21 mm Hg without and with medications, respectively. Results: Mean age of the participants was 24.4 ± 7.9 years. After a mean follow-up of 8.1 ± 2.7 months, complete success rates were similar between the 240-degree GT (45.2%) and the 360-degree GT (63.2%; P = 0.135), and both were superior to 120-degree GT (18.2%; P < 0.05). Qualified success rates among patients in the 120-degree, 240-degree, and 360-degree GT groups were 93.9%, 96.8%, and 100%, respectively, and showed no statistically significant difference (P = 0.292). 360-degree GT required fewer medications than 240-degree GT and 120-degree GT (P < 0.05), with no significant difference in medications between 120-degree GT and 240-degree GT (P > 0.05). Hyphema was the most common postoperative complication, with a significantly higher incidence in the 360-degree GT (68.4%) compared with the 240-degree GT (41.9%) and 120-degree GT (33.3%; P < 0.05). Conclusions: 240-degree and 360-degree GT showed similar efficacy in IOP reduction and were superior to 120-degree GT. More extensive GT may provide better outcomes in JOAG.

Abstract Objective The rapid evolution of the COVID-19 virus has led to the development of different vaccine shots, each designed to combat specific variants and enhance overall efficacy. While vaccines have been crucial in controlling the spread of the virus, they can also cause adverse events (AEs). Understanding these relationships is vital for vaccine safety monitoring and surveillance. Methods In our study, we collected data from the Vaccine Adverse Event Reporting System (VAERS) and social media platforms (Twitter and Reddit) to extract relationships between COVID-19 vaccine shots and adverse events. The dataset comprised 771 relation pairs, enabling a comprehensive analysis of adverse event patterns. We employed state-of-the-art GPT models, including GPT-3.5 and GPT-4, alongside traditional models such as Recurrent Neural Networks (RNNs) and BioBERT, to extract these relationships. Additionally, we used two sets of post-processing rules to further refine the extracted relations. Evaluation metrics including precision, recall, and F1-score were used to assess the performance of our models in extracting these relationships accurately. Results The most commonly reported AEs following the primary series of COVID-19 vaccines include arm soreness, fatigue, and headache, while the spectrum of AEs following boosters is more diverse. In relation extraction, fine-tuned GPT-3.5 with Sentence-based Relation Identification achieved the highest precision of 0.94 and a perfect recall of 1, resulting in an impressive F1 score of 0.97. Conclusion This study advances biomedical informatics by showing how large language models and deep learning models can extract relationships between vaccine shots and adverse events from VAERS and social media. These findings improve vaccine safety monitoring and clinical practice by enhancing our understanding of post-vaccination symptoms. The study sets a precedent for future research in natural language processing and biomedical informatics, with potential applications in pharmacovigilance and clinical decision-making.