Citations

Abstract This study explored the role of the ubiquitin-proteasome system (UPS) in dominantly inherited Alzheimer’s disease (DIAD) by examining changes in cerebrospinal fluid (CSF) levels of UPS proteins along with disease progression, AD imaging biomarkers (PiB PET, tau PET), neurodegeneration imaging measures (MRI, FDG PET), and Clinical Dementia Rating® (CDR®). Using the SOMAscan assay, we detected subtle increases in specific ubiquitin enzymes associated with proteostasis in mutation carriers (MCs) up to two decades before the estimated symptom onset. This was followed by more pronounced elevations of UPS-activating enzymes, including E2 and E3 proteins, and ubiquitin-related modifiers. Our findings also demonstrated consistent correlations between UPS proteins and CSF biomarkers such as Aβ42/40 ratio, total tau, various phosphorylated tau species to total tau ratios (ptau181/T181, ptauT205/T205, ptauS202/S202, ptauT217/T217), and MTBR-tau243, alongside Neurofilament light chain (NfL) and the CDR®. Notably, a positive association was observed with imaging markers (PiB PET, tau PET) and a negative correlation with markers of neurodegeneration (FDG PET, MRI), highlighting a significant link between UPS dysregulation and neurodegenerative processes. The correlations suggest that the increase in multiple UPS proteins with rising tau levels and tau-tangle associated markers, indicating a potential role for the UPS in relation to misfolded tau/neurofibrillary tangles (NFTs) and symptom onset. These findings indicate that elevated CSF UPS proteins in DIAD MCs could serve as early indicators of disease progression and suggest a link between UPS dysregulation and amyloid plaque, tau tangles formation, implicating the UPS as a potential therapeutic target in AD pathogenesis.

Mixed invasive ductal and lobular carcinoma (MDLC) is a rare histologic subtype of breast cancer displaying both E-cadherin positive ductal and E-cadherin negative lobular morphologies within the same tumor, posing challenges with regard to anticipated clinical management. It remains unclear whether these distinct morphologies also have distinct biology and risk of recurrence. Our spatially resolved transcriptomic, genomic, and single-cell profiling revealed clinically significant differences between ductal and lobular tumor regions including distinct intrinsic subtype heterogeneity – e.g., MDLC with triple-negative breast cancer (TNBC) or basal ductal and estrogen receptor positive (ER+) luminal lobular regions, distinct enrichment of cell cycle arrest/senescence and oncogenic (ER and MYC ) signatures, genetic and epigenetic CDH1 inactivation in lobular but not ductal regions, and single-cell ductal and lobular subpopulations with unique oncogenic signatures further highlighting intraregional heterogeneity. Altogether, we demonstrated that the intratumoral morphological/histological heterogeneity within MDLC is underpinned by intrinsic subtype and oncogenic heterogeneity which may result in prognostic uncertainty and therapeutic dilemma.

Medical researchers are increasingly utilizing advanced LLMs like ChatGPT-4 and Gemini to enhance diagnostic processes in the medical field. This research focuses on their ability to comprehend and apply complex medical classification systems for breast conditions, which can significantly aid plastic surgeons in making informed decisions for diagnosis and treatment, ultimately leading to improved patient outcomes. Fifty clinical scenarios were created to evaluate the classification accuracy of each LLM across five established breast-related classification systems. Scores from 0 to 2 were assigned to LLM responses to denote incorrect, partially correct, or completely correct classifications. Descriptive statistics were employed to compare the performances of ChatGPT-4 and Gemini. Gemini exhibited superior overall performance, achieving 98% accuracy compared to ChatGPT-4’s 71%. While both models performed well in the Baker classification for capsular contracture and UTSW classification for gynecomastia, Gemini consistently outperformed ChatGPT-4 in other systems, such as the Fischer Grade Classification for gender-affirming mastectomy, Kajava Classification for ectopic breast tissue, and Regnault Classification for breast ptosis. With further development, integrating LLMs into plastic surgery practice will likely enhance diagnostic support and decision making.

Importance Sudden death and cardiac arrest frequently occur without explanation, even after a thorough clinical evaluation. Calcium release deficiency syndrome (CRDS), a life-threatening genetic arrhythmia syndrome, is undetectable with standard testing and leads to unexplained cardiac arrest. Objective To explore the cardiac repolarization response on an electrocardiogram after brief tachycardia and a pause as a clinical diagnostic test for CRDS. Design, Setting, and Participants An international, multicenter, case-control study including individual cases of CRDS, 3 patient control groups (individuals with suspected supraventricular tachycardia; survivors of unexplained cardiac arrest [UCA]; and individuals with genotype-positive catecholaminergic polymorphic ventricular tachycardia [CPVT]), and genetic mouse models (CRDS, wild type, and CPVT were used to define the cellular mechanism) conducted at 10 centers in 7 countries. Patient tracings were recorded between June 2005 and December 2023, and the analyses were performed from April 2023 to December 2023. Intervention Brief tachycardia and a subsequent pause (either spontaneous or mediated through cardiac pacing). Main Outcomes and Measures Change in QT interval and change in T-wave amplitude (defined as the difference between their absolute values on the postpause sinus beat and the last beat prior to tachycardia). Results Among 10 case patients with CRDS, 45 control patients with suspected supraventricular tachycardia, 10 control patients who experienced UCA, and 3 control patients with genotype-positive CPVT, the median change in T-wave amplitude on the postpause sinus beat (after brief ventricular tachycardia at ≥150 beats/min) was higher in patients with CRDS ( P < .001). The smallest change in T-wave amplitude was 0.250 mV for a CRDS case patient compared with the largest change in T-wave amplitude of 0.160 mV for a control patient, indicating 100% discrimination. Although the median change in QT interval was longer in CRDS cases ( P = .002), an overlap between the cases and controls was present. The genetic mouse models recapitulated the findings observed in humans and suggested the repolarization response was secondary to a pathologically large systolic release of calcium from the sarcoplasmic reticulum. Conclusions and Relevance There is a unique repolarization response on an electrocardiogram after provocation with brief tachycardia and a subsequent pause in CRDS cases and mouse models, which is absent from the controls. If these findings are confirmed in larger studies, this easy to perform maneuver may serve as an effective clinical diagnostic test for CRDS and become an important part of the evaluation of cardiac arrest.

3553 Background: Immuno-STATs are modular fusion proteins designed for the selective activation of tumor antigen specific CD8+ T cells. CUE-102, the second Immuno-STAT in clinical trials, is composed of a human leukocyte antigen (HLA) complex, HLA-A*0201, a peptide epitope derived from the Wilms Tumor 1 (WT1) protein, and 4 molecules of reduced affinity human interleukin-2 (IL-2). In preclinical studies CUE-102 binds, activates and expands WT1-specific CD8+ T cells with the potential to enhance anti-tumor immunity in patients with WT1+ cancers. Here we present the results of the dose-finding portion (Part A) of the CUE-102-01 study. Methods: CUE-102-01 is a 2 part phase 1 study. HLA-A*02:01 positive patients with WT1+ advanced colorectal (CRC), gastric (GA) and gastroesophageal junction (GEJ), pancreatic (PDAC) or ovarian (OvCa) tumors refractory to standard therapies were eligible for participation. WT1 status is determined by IHC via central testing. CUE-102 monotherapy was administered intravenously every three weeks in doses ranging from 1 mg/kg to 8 mg/kg following 3+3 design rules with a Bayesian Logistic Regression Model overlay. Dose levels that exhibit an immune or tumor response may be expanded to further characterize activity and toxicity as allowed by safety rules. Results: Dose escalation was successfully completed in 28 patients with CRC (17), PDAC (6), GA/GEJ (3) and OvCa (2). No DLTs were observed. Three dose levels (2, 4 and 8 mg/kg) exhibited evidence of immune activity and were expanded up to 9 patients each for further evaluation. CUE-102 was well-tolerated with > 96% of treatment-related adverse events (TRAEs) grade ≤2. The most common TRAEs, were fatigue, infusion reactions, nausea and vomiting. There were no cases of CRS Grade ≥ 2. Preliminary PK data demonstrate dose dependent increases in exposure across the dose range assessed. Preliminary analysis of patient samples demonstrates selective expansion of WT1-specific CD8+ T cells. Stable disease of ≥ 6 weeks (range 6-36 weeks), as determined by RECIST 1.1, has been observed in 10 of 23 patients (DCR 43.5%). Conclusions: CUE-102 is a novel T cell engager that demonstrates acceptable tolerability, favorable PK, and supportive preliminary PD readouts. No DLTs or drug-related SAEs have been observed in doses up to 8 mg/kg as of the data cut-off. Adverse events have been manageable and consistent with the CUE-102 mechanism of action and underlying disease. Early signs of disease stabilization and anti-tumor activity in late-stage patients are encouraging. Part B is a dose expansion that further evaluates safety, PK/PD, recommended phase 2 dose (RP2D), antitumor efficacy and is currently enrolling patients. Clinical trial information: NCT05360680 .

Abstract Hub regions in the brain, recognized for their roles in ensuring efficient information transfer, are vulnerable to pathological alterations in neurodegenerative conditions, including Alzheimer’s disease (AD). Computational simulations and animal experiments have hinted at the theory of activity-dependent degeneration as the cause of this hub vulnerability. However, two critical issues remain unresolved. First, past research has not clearly distinguished between two scenarios: hub regions facing a higher risk of connectivity disruption (targeted attack) and all regions having an equal risk (random attack). Second, human studies offering support for activity-dependent explanations remain scarce. We refined the hub disruption index to demonstrate a hub disruption pattern in functional connectivity in autosomal dominant AD that aligned with targeted attacks. This hub disruption is detectable even in preclinical stages, 12 years before the expected symptom onset and is amplified alongside symptomatic progression. Moreover, hub disruption was primarily tied to regional differences in global connectivity and sequentially followed changes observed in amyloid-beta positron emission tomography cortical markers, consistent with the activity-dependent degeneration explanation. Taken together, our findings deepen the understanding of brain network organization in neurodegenerative diseases and could be instrumental in refining diagnostic and targeted therapeutic strategies for AD in the future.

Abstract Background Hypercontractile phenotype (HP) of the left ventricle (LV) is an actionable therapeutic target in patients with chronic coronary syndromes (CCS) or heart failure (HF), but its clinical recognition remains difficult. Objectives To assess the clinical variables associated with the HP. Methods In a prospective, observational, multicenter study, we recruited 5,122 patients (age 65 ± 11 years, 2974 males, 58%) with CCS and/or HF with preserved ejection fraction (EF). Systolic blood pressure (SBP) was measured. We assessed wall motion score index (WMSI), LV end-diastolic volume (EDV), end-systolic volume (ESV), EF, force (SBP/ESV), stroke volume (SV), arterial elastance (SBP/SV), and ventricular-arterial coupling (VAC, as SV/ESV). Univariable and multivariable logistic regression analysis assessed independent factors associated with the highest force sextile. Results For all the studied patients, force was 4.51 ± 2.11 mmHg/ml, with the highest sextile (Group 6) > 6.36 mmHg/ml. By multivariable logistic regression model, the highest sextile of force was associated with age > 65 years (OR 1.62, 95% CI 1.36–1.93, p < 0.001), hypertension (OR 1.76, 95% CI 1.40–2.21, p < 0.001), female sex (OR 4.52, 95% CI 3.77–5.42, p < 0.001), absence of beta-blocker therapy (OR 1.41, 95% CI 1.16–1.68), rest SBP ≥ 160 mmHg (OR 2.81, 95% CI 2.21–3.56, p < 0.001), high heart rate (OR 2.08, 95% CI 1.61–2.67, p < 0.001), and absence of prior myocardial infarction (OR 1.34, 95% CI 1.07–1.68, p = 0.012). Patients in the highest sextile of force showed lower values of WMSI, SV, EDV, and ESV, and higher values of arterial elastance and VAC. Conclusions HP of the LV with high force was clinically associated with advanced age, female sex, high resting SBP, and the absence of 𝛽-blocker therapy. By transthoracic echocardiography, HP was associated with a small heart with reduced EDV, reduced SV despite high EF, and higher arterial elastance.

Background and Objectives: Large language models (LLMs) are emerging as valuable tools in plastic surgery, potentially reducing surgeons’ cognitive loads and improving patients’ outcomes. This study aimed to assess and compare the current state of the two most common and readily available LLMs, Open AI’s ChatGPT-4 and Google’s Gemini Pro (1.0 Pro), in providing intraoperative decision support in plastic and reconstructive surgery procedures. Materials and Methods: We presented each LLM with 32 independent intraoperative scenarios spanning 5 procedures. We utilized a 5-point and a 3-point Likert scale for medical accuracy and relevance, respectively. We determined the readability of the responses using the Flesch–Kincaid Grade Level (FKGL) and Flesch Reading Ease (FRE) score. Additionally, we measured the models’ response time. We compared the performance using the Mann–Whitney U test and Student’s t-test. Results: ChatGPT-4 significantly outperformed Gemini in providing accurate (3.59 ± 0.84 vs. 3.13 ± 0.83, p-value = 0.022) and relevant (2.28 ± 0.77 vs. 1.88 ± 0.83, p-value = 0.032) responses. Alternatively, Gemini provided more concise and readable responses, with an average FKGL (12.80 ± 1.56) significantly lower than ChatGPT-4′s (15.00 ± 1.89) (p < 0.0001). However, there was no difference in the FRE scores (p = 0.174). Moreover, Gemini’s average response time was significantly faster (8.15 ± 1.42 s) than ChatGPT’-4′s (13.70 ± 2.87 s) (p < 0.0001). Conclusions: Although ChatGPT-4 provided more accurate and relevant responses, both models demonstrated potential as intraoperative tools. Nevertheless, their performance inconsistency across the different procedures underscores the need for further training and optimization to ensure their reliability as intraoperative decision-support tools.