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Background Aneurysm treatments are crucial to minimize the rupture risk. The underlying molecular processes mediating cellular remodeling, endothelialization, and aneurysm healing following endovascular treatment are poorly understood. The current study aims to explore circulating miRNA as a treatment and outcome-associated biomarkers in patients undergoing endovascular treatment. Methods Patients undergoing endovascular interventions for unruptured intracranial aneurysms, using either flow diverter placement or coil embolization, were enrolled. Blood samples were collected before the intervention and during a follow-up period between 6 and 18 months. Total mRNA/miRNA was isolated from plasma, followed by RNA-seq analysis. Gene Ontology analysis was used to identify pathways linked to altered miRNA expression. Results Twenty-three patients participated, with 13 (56.5%) undergoing flow diversion and 10 (43.5%) coil embolization. The median follow-up sample collection time was 10.70 months (SEM ± 1.32). No significant differences in angiographic occlusion were noted between intervention groups. Differentially expressed miRNAs were not identified between groups at baseline. However, at follow-up, 39 miRNAs were upregulated and 41 were downregulated, independent of intervention. Notably, three miRNAs (miR-4746-5p, miR-4685-3p, and miR-490-3p) were downregulated in the flow diversion group compared to the coil embolization group. Bioinformatics analysis revealed associations with upregulated fluid shear stress, p53, adherens junction pathways, along with downregulated apoptosis pathways. Conclusions This study suggests that fluid shear stress and apoptosis may influence aneurysm healing or thromboembolic events in flow diverter-treated patients. Further research is warranted to elucidate the functional significance of these findings in treatment outcomes, providing valuable insights for improved patient care in intracranial aneurysm management.

Background: Secondary prevention after percutaneous coronary interventions (PCIs) is still challenging and lipoprotein(a) [Lp(a)] is believed to be a residual risk factor in this setting. However, the effect of Lp(a) in case of well-controlled low-density lipoprotein cholesterol (LDL-C) is still unclear. The interaction between Lp(a) and LDL-C has been studied in primary prevention but still needs to be investigated in secondary prevention. Hypothesis: Achieving adequate LDL-C control after PCI may reduce the cardiovascular (CV) risk associated with Lp(a). Methods: A retrospective study of consecutive patients who underwent PCI and reached their LDL-C target levels (<70mg/dL) at three academic centers sites between 2006 and 2017. All included patients must have an Lp(a) measurement before the PCI intervention. Clinical outcomes on 10-year follow-up were collected by reviewing the electronic patients' records. The primary outcomes included all-cause mortality (ACM) and major adverse CV events (MACE) including non-fatal MI, ischemic stroke, coronary revascularization, and CV death. Kaplan-Meier curves were created to compare the survival probabilities among patients with high Lp(a) (≥50mg/dL) versus those with low Lp(a) (<50mg/dL). Univariate and multivariate Cox regression analyses were performed to quantify the association of elevated Lp(a) with outcomes and control for potential confounders. Results: In total, 878 patients (median age = 68 years, 74% males) were included in the analysis. Of them, 242 (27.6%) had high Lp(a) ≥50mg/dL. Kaplan Meier analyses did not reveal any significant difference in survival probabilities across the Lp(a) groups for any of the outcomes (Figure 1). The results were consistent in univariate (MACE, HR: 1.08 [95%CIs 0.85-1.35]; ACM, HR: 0.97 [95% CI 0.76-1.23]) and multivariate analyses (MACE, HR: 1.14, [95% CIs 0.90-1.45]; ACM, HR: 1.08 [95% CI 0.84-1.39]). Conclusion: These findings suggest that, in patients who underwent PCI and achieved an LDL-C target of <70 mg/dL, elevated Lp(a) levels were not associated with and increased risk of MACE or mortality. Controlling the LDL-C should still be the cornerstone in secondary prevention after PCI, however, larger prospective studies are still warranted to validate our results.

Background: Major adverse cardiovascular events (MACE), including myocardial infarction, acute coronary syndrome, ischemic heart disease requiring revascularization, stroke, and heart failure, have been documented as significant contributors to mortality in cancer survivors. Coronary artery calcium (CAC) can predict MACE in non-cancer populations, while calcium in the aorta (CA) has not been evaluated as a prognostic marker. Every patient diagnosed with cancer undergoes a standard-of-care Positron Emission Tomography-Computed Tomography (PET-CT) or a chest CT before the initiation of chemotherapy. Hypothesis: To determine whether the CAC or CA of patients with Hodgkin's or non-Hodgkin's lymphoma, derived from standard-of-care PET-CT/chest CT, can predict the incidence of MACE. Methods: Patients treated with anthracycline-based chemotherapy, diagnosed and followed from January 1, 2013, through June 30, 2023, were included. Patients who did not undergo a PET-CT or CT, and/or developed MACE before treatment initiation were excluded. Univariate and multivariate adjusted Cox regression models were employed to assess whether the presence of CAC, CA, or CAC-CA was associated with the development of MACE. Calcium was retrospectively quantified using TeraRecon software (Durham NC) and categorized as: 0, 1-99, and >100. Outcome analyses was estimated using the Kaplan-Meier method. Results: 326 patients were included, mean age of 55 years (range: 52-60), predominantly male 201 (61%) and white 314 (96%), CAC was found in 89 patients and CA in 140. In the univariate regression model, a statistically significant association was found with values >100 for CA, CAC and CAC-CA with the risk of MACE. (Fig 1a/b/c). CAC equal to 0 demonstrated a significant protective effect against MACE. (Fig 1a). In the multivariable analysis, these associations persisted even after adjusting for comorbidities. (Table 1). Conclusion: CAC, CA and CAC/CA >100 in the standard-of-care CT/PET CT are predictors of MACE in lymphoma patients undergoing anthracycline treatment, a CAC equal to 0 has protective effect, these relationships remained statistically significant after adjusting for comorbidities.

Abstract Glioblastoma (GBM) is an aggressive form of cancer, comprising ≈80% of malignant brain tumors. However, there are no effective treatments for GBM due to its heterogeneity and the presence of the blood‐brain barrier (BBB), which restricts the delivery of therapeutics to the brain. Despite in vitro models contributing to the understanding of GBM, conventional 2D models oversimplify the complex tumor microenvironment. Organ‐on‐a‐chip (OoC) models have emerged as promising platforms that recapitulate human tissue physiology, enabling disease modeling, drug screening, and personalized medicine. There is a sudden increase in GBM‐on‐a‐chip models that can significantly advance the knowledge of GBM etiology and revolutionize drug development by reducing animal testing and enhancing translation to the clinic. In this review, an overview of GBM‐on‐a‐chip models and their applications is reported for drug screening and discussed current challenges and potential future directions for GBM‐on‐a‐chip models.

BACKGROUND: Packed red blood cell (pRBC) transfusions in patients undergoing surgery for cancer are given to treat anemia or acute hemorrhage. Evidence indicates that pRBC transfusions are associated with poor perioperative and oncological outcomes. The ARCA-1 (Perioperative Care in the Cancer Patient-1) study was designed to test the association between perioperative pRBC transfusions and postoperative morbidity and mortality in patients undergoing cancer surgery. The primary hypothesis of our study was that perioperative pRBC transfusions have a negative impact on postoperative morbidity and 1-year mortality. METHODS: ARCA-1 was an international multicenter prospective observational cohort study. Participating centers enrolled a minimum of 30 consecutive adult patients with cancer who underwent surgery with curative intent. The primary end point was all-cause mortality 1 year after major cancer surgery. Secondary end points were rates of perioperative blood product use, 1-year cancer-specific mortality, overall survival, and 30-day morbidity and mortality. We performed a propensity score matching analysis to adjust for selection bias. A multivariable logistic regression model was fitted to estimate the effects of significant covariates on 1-year mortality, cancer-related mortality, and overall survival. RESULTS: A total of 1079 patients were included in the study. The rate of perioperative pRBC transfusions was 21.1%. Preoperative comorbidities, including anemia, American Society of Anesthesiologists (ASA) score of III to IV, a history of coronavirus disease 2019 (COVID-19), myocardial infarction, stroke, need for dialysis, history of blood transfusions, and metastatic disease were statistically significantly more frequent in transfused patients compared to nontransfused patients. The 1-year mortality rate was higher in transfused patients before (19.7% vs 6.5%; P < .0001) and after (17.4% vs 13.2%; P = .29) propensity score matching. 1-year mortality was 1.97 times higher in transfused than in no-transfused patients (odd ratio [OR], 1.97; 95% confidence interval [CI], 1.13–3.41). The odds of 1-year cancer mortality for patients who had perioperative pRBCs was 1.82 times higher (OR, 1.82; 95% CI, 0.97–3.43) compared to those who did not receive perioperative pRBC transfusion. The effect of perioperative pRBC transfusion on overall survival was also significant (hazard ratio [HR], 1.85; 95% CI, 1.15–2.99). Transfused patients also had a higher rate of 30-day postoperative mortality before (3.5% vs 0.7%; P = .0009) and after propensity score matching (4.2% vs 1.8%; P = .34). CONCLUSIONS: This international, multicenter observational study showed that perioperative pRBC transfusion was associated with an increased mortality risk.

Abstract Seizure localization is important for managing drug‐resistant focal epilepsy. Here, the capability of a novel deep learning‐based source imaging framework (DeepSIF) for imaging seizure activities from electroencephalogram (EEG) recordings in drug‐resistant focal epilepsy patients is investigated. The neural mass model of ictal oscillations is adopted to generate synthetic training data with spatio‐temporal‐spectra features similar to ictal dynamics. The trained DeepSIF model is rigorously validated using computer simulations and in a cohort of 33 drug‐resistant focal epilepsy patients with high‐density (76‐channel) EEG seizure recordings, by comparing DeepSIF estimates with surgical resection outcome and seizure onset zone (SOZ). These findings show that the trained DeepSIF model outperforms other methods in estimating the spatial and temporal information of origins of ictal activities. It achieves a high spatial specificity of 96% and a low spatial dispersion of 3.80 ± 5.74 mm when compared to the resection region. The source imaging results also demonstrate good coverage of SOZ, with an average distance of 10.89 ± 10.14 mm (from the SOZ to the reconstruction). These promising results suggest that DeepSIF has significant potential for advancing noninvasive imaging of the origins of ictal activities in patients with focal epilepsy, aiding management of intractable epilepsy.

Abstract Background Major adverse cardiovascular events (MACE), commonly defined as acute myocardial infarction, acute coronary syndrome/ischemic heart disease requiring revascularization, stroke, and heart failure, represent a significant cause of mortality among patients with cancer. With increased rates of both cancer and cancer survivorship, the identification of new predictive markers for the development of MACE in this population is crucial for implementing effective preventive and risk-mitigation strategies. Purpose To determine whether the presence of calcifications in the coronary arteries (CAC) or aorta (CA) of lymphoma patients, as reported in standard-of-care PET-CT (Positron Emission Tomography-Computed Tomography) or chest CT (Computed Tomography) scan, can predict the occurrence of MACE. Methods A Retrospective analysis was conducted on a cohort of patients diagnosed with Hodgkin or non-Hodgkin lymphoma and treated with anthracycline-based chemotherapy. Patients were diagnosed from January 1, 2013, and followed through to June 30, 2023. The reference point for the study was the radiologist’s report of the PET-CT or chest CT conducted before the initiation of anthracycline therapy. Patients who did not undergo a PET-CT or CT before the start of treatment, and/or developed MACE before treatment initiation were excluded. Univariate and multivariate adjusted Cox regression models were employed to assess whether the presence of CA and CAC was associated with the development of MACE. Associations with outcomes were evaluated using the Kaplan-Meier method and Cox regression. Results 326 patients were included with a mean age of 55 years (range: 52-60), predominantly male 201 (61%) and white 314 (96%), CAC was reported in 75 patients (23%) and CA in 18 (6%). In the univariate regression model, a statistically significant association was found between the presence of both CA and CAC with the risk of MACE. CAC showed a stronger association with the development of MACE than CA (HR: 3.7 [1-7.9], p=0.0005 vs HR: 2.9 [1- 8.5], p=0.050). In multivariable analysis CAC emerged as the strongest predictor of MACE (HR: 2.9 [1.3 – 6.4], p=0.01), after accounting for hypertension, diabetes, dyslipidemia, and GFR &lt;60 (Table 1), while the association with CA attenuated (HR: 2.01 [0.7-6.5], p=0.2010) and was no longer significant (Table 2). Conclusion CAC in the standard-of-care PET/-CT scans was a predictor of MACE in lymphoma patients treated with anthracyclines, while the association with CA weakened in multivariable analyses and was likely underpowered given the small number of patients with CA. If replicated, this finding warrants closer surveillance of this group of patients and can be considered as a non-invasive cardiovascular risk marker.