e13622 Background: Traditional methods for capturing patient-reported outcomes (PROs) are often time-consuming and may lead to underreporting of symptoms by physicians. With advancements in artificial intelligence (AI), particularly large language models (LLMs) like GPT-4, there is potential to revolutionize this aspect of patient care. Methods: This study developed and tested a GPT-4-based web application for monitoring cancer treatment toxicity in breast cancer patients. The application utilized 35 items from the PRO-CTCAE scale to create an interactive form for patients to report treatment-related symptoms. Upon form completion, a natural language summary of the patient’s responses was generated using the GPT-4 API for physician review. Nine radiation oncologists (5 attendings, 4 residents) evaluated the summaries of virtual patients using the adapted Physician Documentation Quality Index (PDQI-9). PDQI-9 consists of 9 items scored using a 5-point Likert scale (1 -not at all- to 5. -extremely-). IRB approval was not required because this study did not use real patient data, in accordance with the 2018 Revised Common Rule Requirements of the NIH. All data used were researcher-generated and non-identifiable. Results: The mean time for textual summary generation was 7 (5.7-9.2) seconds. The AI-Symptom Summarization Tool (ASST) mean scores were 4.25 for accuracy and 4 for thoroughness. Usefulness, organization, comprehensibility, concision, synthesis quality and consistency were all rated between 3 and 4. Overall score was 42/50. No hallucinations (false information made up by the LLM) were found. Conclusions: The GPT-4-based application for cancer treatment toxicity monitoring demonstrates significant promise in enhancing the quality and efficiency of patient care. By automating the documentation of patient-reported symptoms, this tool could allow physicians to focus more time on patient interaction and individualized care. As AI technologies continue to evolve, their integration into clinical practice must be approached with caution, emphasizing augmentation over replacement and the importance of verification to maintain trust in these new tools.

INTRODUCTION:Brain arteriovenous malformations (bAVMs) are vascular abnormalities that can be treated with embolization or radiotherapy to prevent the risk of future rupture. In this study, we use hand-crafted radiomics and deep learning techniques to predict favorable vs. unfavorable outcomes following Gamma Knife radiosurgery (GKRS) of bAVMs and compare their prediction performances.METHODS:One hundred twenty-six patients seen at one academic medical center for GKRS obliteration of bAVMs over 15 years were retrospectively reviewed. Forty-two patients met the inclusion criteria. Favorable outcomes were defined as complete nidus obliteration demonstrated on cerebral angiogram and asymptomatic recovery. Unfavorable outcomes were defined as incomplete obliteration or complications relating to the AVM that developed after GKRS. Outcome predictions were made using a random forest model with hand-crafted radiomic features and a fine-tuned ResNet-34 convolutional neural network (CNN) model. The performance was evaluated by using a ten-fold cross-validation technique.RESULTS:The average accuracy and area-under-curve (AUC) values of the Random Forest Classifier (RFC) with radiomics features were 68.5 ±9.80% and 0.705 ±0.086, whereas those of the ResNet-34 model were 60.0 ±11.9% and 0.694 ±0.124. Four radiomics features used with RFC discriminated unfavorable response cases from favorable response cases with statistical significance. When cropped images were used with ResNet-34, the accuracy and AUC decreased to 59.3 ± 14.2% and 55.4 ±10.4%, respectively.CONCLUSIONS:A hand-crafted radiomics model and a pre-trained CNN model can be fine-tuned on pre-treatment MRI scans to predict clinical outcomes of AVM patients undergoing GKRS with equivalent prediction performance. The outcome predictions are promising but require further external validation on more patients.

BACKGROUND:Tetraspanin CD151 is highly expressed in endothelia and reinforces cell adhesion, but its role in vascular inflammation remains largely unknown.METHODS:In vitro molecular and cellular biological analyses on genetically modified endothelial cells, in vivo vascular biological analyses on genetically engineered mouse models, and in silico systems biology and bioinformatics analyses on CD151-related events.RESULTS:Endothelial ablation of Cd151 leads to pulmonary and cardiac inflammation, severe sepsis, and perilous COVID-19, and endothelial CD151 becomes downregulated in inflammation. Mechanistically, CD151 restrains endothelial release of proinflammatory molecules for less leukocyte infiltration. At the subcellular level, CD151 determines the integrity of multivesicular bodies/lysosomes and confines the production of exosomes that carry cytokines such as ANGPT2 (angiopoietin-2) and proteases such as cathepsin-D. At the molecular level, CD151 docks VCP (valosin-containing protein)/p97, which controls protein quality via mediating deubiquitination for proteolytic degradation, onto endolysosomes to facilitate VCP/p97 function. At the endolysosome membrane, CD151 links VCP/p97 to (1) IFITM3 (interferon-induced transmembrane protein 3), which regulates multivesicular body functions, to restrain IFITM3-mediated exosomal sorting, and (2) V-ATPase, which dictates endolysosome pH, to support functional assembly of V-ATPase.CONCLUSIONS:Distinct from its canonical function in strengthening cell adhesion at cell surface, CD151 maintains endolysosome function by sustaining VCP/p97-mediated protein unfolding and turnover. By supporting protein quality control and protein degradation, CD151 prevents proteins from (1) buildup in endolysosomes and (2) discharge through exosomes, to limit vascular inflammation. Also, our study conceptualizes that balance between degradation and discharge of proteins in endothelial cells determines vascular information. Thus, the IFITM3/V-ATPase-tetraspanin-VCP/p97 complexes on endolysosome, as a protein quality control and inflammation-inhibitory machinery, could be beneficial for therapeutic intervention against vascular inflammation.

This study explores using GPT-4 for radiation toxicity monitoring in prostate cancer treatments. Two methods were tested: a summarization method and a chatbot interface. Surveyed radiation oncologists preferred the summarization method for its accuracy and potential for adoption (median rating 8 vs 4, p =.002). Both methods saved time.

We establish in vivo Perturb-seq in orthotopic GBM models as a platform for simultaneous functional genomic discovery and characterization of therapeutic targets, revealing an underappreciated role for Prkdc in GBM tumors in vivo that is targetable using small molecules. These tools are adaptable for a wide range of disease models and treatment modalities.

Next-generation sequencing (NGS) to identify potential targets is becoming a common approach to refractory tumors. We describe a patient with a CIC-DUX4 sarcoma that harbored a patched homolog 1 (PTCH1) mutation, a mutation not previously reported in so-called Ewing family tumors. PTCH1 is part of the hedgehog signaling pathway. Basal cell carcinomas (BCC) commonly have PTCH1 mutations, and those with PTCH1 mutations are often responsive to therapy with the hedgehog pathway inhibitor vismodegib. The effect of any mutation in a gene important in cell growth and division is likely dependent upon the background biochemistry of the cell. In the current case, vismodegib was not effective. This case is the first report of a PTCH1 mutation in an Ewing family tumor and demonstrates that the utility of targeting a potential mutation may depend upon many factors, including other mutations in the signaling pathway, and importantly, also the background biochemistry of the malignant cell that may prevent effective treatment targeting.

Rationale: Cardiac microvascular leakage and inflammation are triggered during myocardial infarction (MI) and contribute to heart failure. Hypoxia-inducible factor 2α ( Hif2α ) is highly expressed in endothelial cells (ECs) and rapidly activated by myocardial ischemia, but its impact in microvascular endothelial barrier function during MI is unclear. Objective: To test our hypothesis that the expression of Hif2α in ECs regulates cardiac microvascular permeability in infarcted hearts, which is through its binding partner aryl hydrocarbon nuclear translocator. (ARNT). Methods and Results: Experiments were conducted with mice carrying an inducible EC-specific Hif2α -knockout ( ecHif2α -/- ) mutation, with mouse cardiac microvascular endothelial cells (CMVECs) isolated from the hearts of ecHif2α -/- mice after the mutation was induced, and with human CMVECs and umbilical-vein endothelial cells transfected with ecHif2α siRNA. After MI induction, echocardiographic assessments of cardiac function were significantly lower, while measures of cardiac microvascular leakage (Evans blue assay), plasma IL6 levels, and cardiac neutrophil accumulation and fibrosis (histology) were significantly greater, in ecHif2α -/- mice than in control mice, and RNA-sequencing analysis of heart tissues from both groups indicated that the expression of genes involved in vascular permeability and collagen synthesis was enriched in ecHif2α -/- hearts. In cultured ECs, ec Hif2α deficiency was associated with declines in endothelial barrier function (electrical cell impedance assay) and the reduced abundance of tight-junction proteins, as well as an increase in the expression of inflammatory markers, all of which were largely reversed by the overexpression of ARNT. We also found that ARNT, but not Hif2α, binds directly to the IL6 promoter and suppresses IL6 expression. Conclusions: Endothelial HIF-2a protects from hypoxia-induced cardiac microvascular barrier dysfunction, promotes inflammation damage and represents a potential therapeutic target for cardioprotection, and prevention of fibrosis following acute ischemic injury.

Abstract Aims Sleep disturbance is an important factor in the pathophysiology and progression of psychiatric disorders, but whether it is a cause, or a downstream effect is still not clear. Methods To investigate causal relationships between three sleep-associated traits and seven psychiatric diseases, we used genetic variants related to insomnia, chronotype and sleep duration to perform a two-sample bidirectional Mendelian randomisation analysis. Summary-level data on psychiatric disorders were extracted from the Psychiatric Genomics Consortium. Effect estimates were obtained by using the inverse-variance-weighted (IVW), weights modified IVW, weighted-median methods, MR-Egger regression, MR pleiotropy residual sum and outlier (MR-PRESSO) test and Robust Adjusted Profile Score (RAPS). Results The causal odds ratio (OR) estimate of genetically determined insomnia was 1.33 (95% confidence interval (CI) 1.22–1.45; p = 5.03 × 10−11) for attention-deficit/hyperactivity disorder (ADHD), 1.31 (95% CI 1.25–1.37; p = 6.88 × 10−31) for major depressive disorder (MDD) and 1.32 (95% CI 1.23–1.40; p = 1.42 × 10−16) for post-traumatic stress disorder (PTSD). There were suggestive inverse associations of morningness chronotype with risk of MDD and schizophrenia (SCZ). Genetically predicted sleep duration was also nominally associated with the risk of bipolar disorder (BD). Conversely, PTSD and MDD were associated with an increased risk of insomnia (OR = 1.06, 95% CI 1.03–1.10, p = 7.85 × 10−4 for PTSD; OR = 1.37, 95% CI 1.14–1.64; p = 0.001 for MDD). A suggestive inverse association of ADHD and MDD with sleep duration was also observed. Conclusions Our findings provide evidence of potential causal relationships between sleep disturbance and psychiatric disorders. This suggests that abnormal sleep patterns may serve as markers for psychiatric disorders and offer opportunities for prevention and management in psychiatric disorders.

BackgroundObservational studies have shown an inverse association between circulating linoleic acid (LA) and risk of ischemic stroke (IS).ObjectiveThe aim of this study was to explore whether genetic variants predicting levels of circulating LA are associated with IS and its subtypes using a two-sample Mendelian randomization (MR) analysis.MethodsLA-related single-nucleotide polymorphisms (SNPs) were selected from a genome-wide association study of 8,631 participants, and summary statistics of IS and IS subtypes were obtained from the MEGASTROKE consortium. MR analysis was performed using the inverse-variance weighted (IVW) method complemented with other approaches, including weighted-median, weighted-mode, MR Pleiotropy RESidual Sum and Outlier test and MR-Egger regression, to test for the robustness of the association. Moreover, we conducted bidirectional MR analysis to assess the impact of IS-associated SNPs on circulating LA levels. Odds ratios (ORs) with 95% confidence intervals (95% CIs) were calculated.ResultsWe found that genetically predicted circulating LA levels were inversely associated with the risk of IS by the IVW method (OR = 0.98, 95% CI: 0.97–0.99, and P = 0.003). Subgroup analyses showed a statistically significant association between LA and risk of large artery stroke (LAS; OR = 0.95, 95% CI: 0.92–0.98, and P = 0.004), but not for other IS subtypes. The results were stable in sensitivity analyses, and no evidence of reverse association between LA and risk of IS, or LAS was observed.ConclusionOur study supports a potential inverse association of genetically predicted circulating LA levels with risk of IS, particularly LAS.

Endothelial cells line the innermost layer of arterial, venous, and lymphatic vascular tree and accordingly are subject to hemodynamic, stretch, and stiffness mechanical forces. Normally quiescent, endothelial cells have a hemodynamic set point and become "activated" in response to disturbed hemodynamics, which may signal impending nutrient or gas depletion. Endothelial cells in the majority of tissue beds are normally inactivated and maintain vessel barrier functions, are anti-inflammatory, anti-coagulant, and anti-thrombotic. However, under aberrant mechanical forces, endothelial signaling transforms in response, resulting cellular changes that herald pathological diseases. Endothelial cell metabolism is now recognized as the primary intermediate pathway that undergirds cellular transformation. In this review, we discuss the various mechanical forces endothelial cells sense in the large vessels, microvasculature, and lymphatics, and how changes in environmental mechanical forces result in changes in metabolism, which ultimately influence cell physiology, cellular memory, and ultimately disease initiation and progression.

Aging is a major risk factor of high incidence and increased mortality of acute respiratory distress syndrome (ARDS) and COVID-19. We repot that aging impairs the intrinsic FoxM1-dependent endothelial regeneration and vascular repair program and causes persistent lung injury and high mortality following sepsis. Therapeutic gene transduction of FOXM1 in vascular endothelium or treatment with FDA-approved drug Decitabine was sufficient to reactivate FoxM1-dependent lung endothelial regeneration in aged mice, reverse aging-impaired resolution of inflammatory injury, and promote survival. In COVID-19 lung autopsy samples, FOXM1 expression was not induced in vascular endothelial cells of elderly patients in contrast to mid-age patients. Thus, Decitabine reactivation of FoxM1-dependent vascular repair represents a potential effective therapy for elderly COVID-19 and non-COVID-19 ARDS patients.

Ground truth dataset of human aortic endothelial cells expressing Laconic (GFP channel) and stained with Hoechst (nuclei).

Abstract Single-cell motility is spatially heterogeneous and driven by metabolic energy. Direct linking cell mobility to cell metabolism is technically challenging but biologically important. Here we implemented a single-cell metabolic imaging assay to measure glycolysis in individual endothelial cells using genetically-encoded biosensors capable of deciphering metabolic heterogeneity with subcellular resolution. We observed that cellular glycolysis fuels endothelial activation, migration and contraction and that the high lactate production sites co-localize with active cytoskeletal remodeling within an endothelial cell. Mechanistically, we found RhoA induces endothelial glycolysis for the phosphorylation of cofilin and myosin light chain in order to reorganize the cytoskeleton and thus control cell mobility; RhoA activation triggers a glycolytic burst through the translocation of a glucose transporter SLC2A3/GLUT3 to fuel the cellular contractile machinery, as demonstrated across multiple endothelial types. Together, our results discovered that Rho-GTPase signaling coordinates energetic metabolism with cytoskeleton remodeling to regulate the motility of single endothelial cells.

Background and Purpose: Linoleic acid (LA) is an essential fatty acid involved in eicosanoid synthesis. Epidemiological studies have suggested an inverse association between circulating LA levels and ischemic stroke (IS), however, it is unclear whether the observed association is causal or due to confounding or reverse causation. We conducted a Mendelian randomization (MR) to evaluate the potential causal relationship between circulating LA levels and risk of IS. Methods: Summary statistics for IS were obtained from the MEGASTROKE consortium, including 34,217 IS cases and 404,630 controls of European ancestry. Seventeen single nucleotide polymorphisms (SNPs) associated with circulating LA levels were used as instrumental variables (IVs) in the MR analysis, with another two SNP sets used in sensitivity analyses. We used the inverse-variance weighted method to evaluate the potential causal associations of circulating LA levels with IS, complemented with other MR approaches including weighted-median, weighted-mode, MR Pleiotropy RESidual Sum and Outlier test and MR-Egger regression. Results: Each 1-standard deviation increase of genetically-predicted LA levels was inversely associated with a 2% (95% confidence interval [CI], 1%-3%) reduction in IS incidence. Subgroup analyses showed significant causal associations for large artery stroke (OR, 0.95; 95% CI, 0.92-0.98; P =3.45х10 -4 ), but not for cardioembolic stroke (OR, 0.98; 95% CI, 0.96-1.00; P =0.05) and small vessel stroke (OR, 1.02; 95% CI, 0.99-1.05; P =0.11). Sensitivity analyses using two additional SNP sets as IVs produced consistent findings. Conclusions: Our study provides evidence for an inverse causal association of circulating LA levels with risk of IS, particularly large artery stroke. Further studies are warranted to clarify the underlying mechanism of LA in the prevention of IS.

Objective. To evaluate the telomere length (TL) in patients with RA relative to that in controls and to test whether TL is causally associated with risk of RA. Methods. Systematic review and meta-analysis of relevant literature was conducted to evaluate the association between TL and RA. Standardized mean differences with 95% CIs of TL in RA patients relative to controls were pooled using fixed or random-effects models. TL-related single-nucleotide polymorphisms were selected from a genome-wide association study of 37 684 individuals, and summary statistics of RA were obtained from a genome-wide association study meta-analysis including 14 361 RA patients and 43 923 controls. Mendelian randomization was performed using the inverse-variance weighted, weighted-median and likelihood-based methods. Sensitivity analyses were performed to test the robustness of the association. Results. In the meta-analysis of 911 RA patients and 2498 controls, we found that patients with RA had a significantly shorter TL compared with controls (standardized mean differences = -0.50; 95% CI -0.88, -0.11; P = 0.012). In the Mendelian randomization analysis, we found that genetically predicted longer TL was associated with a reduced risk of RA [odds ratio = 0.68; 95% CI 0.54, 0.86; P = 0.002 using the inverse-variance weighted method]. Sensitivity analyses using alternative Mendelian randomization approaches yielded similar findings, suggesting the robustness of the causal association. Conclusion. Our study provides evidence for a negative causal association of TL with risk of RA. Further studies are warranted to elucidate the underlying mechanism for the role of telomeres in the development of RA.