Citations

Abstract Heart failure (HF) is a major cause of hospitalization and mortality worldwide. Ventricular assist devices (VADs) represent an alternative to cardiac transplantation for advanced HF. The main FDA-approved VAD (HeartMate III, Abbott), while effective, requires major cardiac surgery to insert the inflow cannula into the cardiac apex, and is associated with numerous co-morbidities and re-hospitalizations related to continuous flow and an external drive line and power supply. Mi-VAD, Inc. aspires to improve outcomes and quality of life with a miniature, minimally invasive, pulsatile, transcutaneously-powered VAD that is implanted above the aortic valve and/or the pulmonary valve and offering a wide range of hemodynamic support suitable for both advanced-stage and less advanced HF. Through its unique placement, there is the potential for right ventricular and biventricular cardiac assist for patients with restrictive cardiomyopathy and HFpEF for whom current VAD therapy is ineffective. Mi-VAD, Inc. has achieved proof of concept with its prototype, providing pulsatile ECG gated cardiac assist up to 10L/minute. Following initial bench top performance testing and in vivo efficacy and safety studies future work will focus on the development of wireless charging capability and conducting GLP builds for verification, regulatory clearance and commercialization. Additional technical development will focus on AI-driven hemodynamic optimization using multimodal physiologic sensing towards patient-specific digital twin of the Mi-VAD platform.

Abstract Accurate assessment of left-ventricular ejection fraction (EF) is a critical metric in diagnosing and managing heart failure; however, methods of assessment remain resource intensive, not widely available in low-acuity or remote settings and are intermittent in nature. This study explores the potential of a novel framework, cardiac electromechanical fingerprinting (cEMF) using synchronized electrocardiography (ECG) and seismocardiography (SCG) collected from a wearable sensing patch as a low-cost, non-invasive, continuous estimate of EF that can be used for rapid point of care screening. A machine learning pipeline was developed to process raw ECG and SCG data to derive EF. Signals were cleaned using band-pass filtering, NeuroKit2-based ECG cleaning and fiducial detection of critical electromechanical events. We extracted an ECG-SCG feature space consisting of heart-rate variability metrics, ECG morphological characterization, SCG timing intervals, spectral and entropy-based features. The top thirty most important features for EF were used to train and evaluate several regressor models. The best performing model was the Gaussian Process Regressor with an MAE of 5.43. Our findings demonstrate the promise of producing clinically relevant cardiac function measures, such as EF, from wearable electromechanical signals. Future work using larger datasets and complementary physiological signals such as phonocardiogram (PCG) may significantly strengthen EF% estimation and other cardiac functions for clinical applicability.

ABSTRACT Primary plasma cell leukemia (pPCL) is a rare and aggressive plasma cell disorder with inferior outcomes compared with multiple myeloma (MM). However, studies describing outcomes after first progression and subsequent lines of therapy remain limited. We retrospectively analyzed 104 patients with pPCL who progressed after first‐line therapy treated at one comprehensive cancer center between 2006 and 2024. Clinical characteristics, treatments, time to next treatment (TTNT), and overall survival (OS) were assessed using Kaplan–Meier methods. All pPCL patients received novel agent–based induction. At the time of analysis, 63% had died; median OS was 39 months. High‐risk cytogenetics were present in 71%. The median TTNT after first‐line therapy was 10 months. Symptomatic progression occurred in 29% of patients and was associated with significantly inferior subsequent OS (13 vs. 34 months) compared with those experiencing asymptomatic biochemical progression. The TTNT progressively shortened with subsequent lines of therapy (3rd line: 6 months; 4th line: 4 months; 5th line: 3 months). Notable exceptions included pPCL patients with t (11;14) treated with anti‐BCL‐2‐based regimens, who achieved a median TTNT of 13 months. Additionally, 24 patients received anti‐BCMA CAR T‐cell therapy. With a median follow‐up of 21 months, their median TTNT was 32 months. pPCL is characterized by frequent disease progression and diminishing response duration with successive therapeutic lines. Symptomatic progression portends particularly poor outcomes. Anti‐BCL‐2‐based therapy in t (11;14) disease and anti‐BCMA CAR T‐cell therapy appear to provide more durable disease control and represent important advances for the management of progressed pPCL.

Background Invasive micropapillary carcinoma (IMPC) of the breast is associated with a high propensity for lymphovascular invasion and lymph node metastasis. However, whether chemotherapy is associated with improved survival outcomes in these patients remains unclear. Methods This retrospective study analyzed IMPC patients from the SEER database (2010–2018) (n=1,150) and an external validation cohort from Nanjing Drum Tower Hospital (n=199). Propensity score matching assessed chemotherapy’s impact on overall survival (OS) and breast cancer-specific survival (BCSS) in the SEER cohort. A risk stratification model was developed and validated using the external cohort. Results In the SEER cohort, chemotherapy was associated with significantly improved OS (HR = 0.517, 95% CI 0.293-0.910, P = 0.020) but not BCSS. A risk model incorporating marital status, tumor size, subtype, and radiotherapy history identified high- and low-risk groups. Chemotherapy was associated with significantly better OS only for high-risk patients (internal training cohort: HR = 0.577, 95% CI 0.349-0.952, P = 0.029; internal validation cohort: HR = 0.213, 95% CI 0.070-0.647, P = 0.003). External validation consistently confirmed poorer prognosis for high-risk patients (HR = 2.969, 95% CI 1.028-8.571, P = 0.035) and verified the model’s ability to identify patients with differential OS associations with chemotherapy: chemotherapy was associated with better OS in high-risk patients (HR = 0.163, 95% CI 0.031-0.868, P = 0.016), but not in low-risk patients (HR = 0.793, 95% CI 0.153-4.103, P = 0.782). Conclusions Chemotherapy was associated with improved prognosis particularly in high-risk patients with IMPC. However, chemotherapy decisions should be made cautiously for low-risk patients, taking into account a comprehensive assessment of clinical and pathological factors.

Objective: To develop a predictive model for pathological complete response (pCR) after total neoadjuvant therapy (TNT) to inform selection for watch-and-wait (W/W). Summary Background Data: Patient selection for W/W after TNT for locally advanced rectal cancer remains challenging. Methods: An ensemble of tabular foundation models was fine-tuned in adults with clinical stage II or III microsatellite stable primary rectal adenocarcinoma undergoing TNT and total mesorectal excision (TNT+TME) from 2018-2023 to predict pCR, using pre-TNT, post-TNT and pre-TME variables. This model was externally validated on patients having TNT and W/W (TNT+W/W) to predict persistent clinical complete response (pcCR; the absence of local regrowth, distant metastases, or persistent near-cCR). Area under the receiver operator curve (AUROC), area under the precision-recall curve (AUPRC), and Brier score were calculated with 95% confidence intervals (CI). Results: Among 308 patients that underwent TNT+TME (median age 56; 40% female), the model predicted pCR with an AUROC 0.71 (95% CI 0.65-0.77), AUPRC 0.44 (95% CI 0.35-0.57), and was well calibrated with a Brier score of 0.17 (95% CI 0.15-0.20). At external validation in a cohort of 83 patients that are being managed with TNT+W/W (median age 57; 37% female), the model predicted pcCR with an AUROC 0.69 (95% CI 0.57-0.82), AUPRC 0.90 (95% CI 0.82-0.96), and Brier score of 0.30 (95% CI 0.26-0.33), improving to 0.17 with recalibration. Conclusions: This novel predictive model demonstrated good discrimination and calibration for pCR after TNT+TME with utility in TNT+W/W for pcCR after appropriate recalibration, supporting its application for W/W patient selection.

INTRODUCTION: Alcohol-associated hepatitis (AH) is a severe condition with high short-term mortality. Identifying key predictors of poor outcomes is critical for guiding therapeutic strategies. Mean arterial pressure (MAP), a key determinant of tissue perfusion and systemic hemodynamics, may play a pivotal role in prognosis. METHODS: We analyzed a multicenter, prospective cohort of 323 patients hospitalized with AH, with validation in an independent cohort of 290 patients. Survival was evaluated using Kaplan-Meier curves and compared with the log-rank (Mantel-Cox) test. Cox proportional hazards models were used to estimate hazard ratios for mortality, adjusted for Model for end stage liver disease score. Mechanistic insights were explored through assessment of cardiovascular biomarkers. RESULTS: A baseline MAP <80 mm Hg was associated with significantly higher mortality at both 28 days (27.3% vs 8.0%) and 90 days (40.3% vs 15.6%; P < 0.001 for both). This association persisted after adjusting for Model for end stage liver disease score, age, and baseline hepatic encephalopathy. The incidence of infections during follow-up was similar across MAP groups (27.6% vs 22.8%), but acute kidney injury occurred more frequently in the MAP <80 mm Hg group (62% vs 38%, P < 0.001). In the validation cohort, patients with MAP <80 mm Hg also demonstrated significantly lower 28-day transplant-free survival. Although B-type natriuretic peptide and plasma renin levels were altered in patients with AH, they did not correlate with MAP values. DISCUSSION: A baseline MAP <80 mm Hg is an independent predictor of short-term and mid-term mortality in patients with AH. Strategies aimed at restoring hemodynamic stability may improve outcomes in this high-risk population.

PURPOSE EGFR alterations occur in a subset of biliary tract cancers (BTCs) and are often linked to disease progression and poor prognosis, yet targeted approaches remain underexplored. ERRFI1 , encoding the epidermal growth factor receptor (EGFR) inhibitor MIG6, is mutated in various cancers, including BTC, representing a potential predictive biomarker. We investigated whether loss of ERRFI1 function may enhance sensitivity to EGFR-targeted tyrosine kinase inhibitors (TKIs), presenting a potential therapeutic opportunity. METHODS This is a retrospective multicenter study of patients with BTC harboring ERRFI1 alterations. Data were extracted from electronic health records following institutional approval. ERRFI1 alterations were classified based on the alteration type, variant allele frequencies were documented, and coalterations were analyzed. Treatment outcomes including response, time to progression (TTP), overall survival (OS), safety profiles, and tumor marker kinetics were noted. RESULTS Fourteen BTC patients with ERRFI1 mutations were identified in our database; the median age was 50 years, 64% were males; all cases were intrahepatic cholangiocarcinomas. Common coalterations included IDH1 (36%), TP53 (29%), and ARID1A (29%). All patients received gemcitabine-cisplatin as first-line treatment, and 79% received immune checkpoint inhibitors. Eight patients (57%) received EGFR TKIs. Best responses to EGFR therapy included three partial responses (2 responses lasting >20 months), four stable diseases, and one progressive disease. The median TTP was 7 months (95% CI, 6 to 21 months). Treatment was well-tolerated: toxicities included rash (n = 2), transaminitis (n = 1), and diarrhea (n = 1). The median OS was 20 months (95% CI: 8-36 months); 50% remained alive at last follow-up. CONCLUSION ERRFI1 mutations represent actionable biomarkers in BTC, with EGFR-targeted therapy demonstrating meaningful clinical benefit in this heavily pretreated population. These findings support integration of ERRFI1 testing into routine molecular profiling of BTC and other EGFR-driven malignancies.

TAR DNA binding protein 43 (TDP-43) pathology is a defining pathological hallmark of multiple neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). A major feature of TDP-43 pathology is its nuclear depletion, leading to the aberrant inclusion of cryptic exons during RNA splicing. STMN2 and UNC13A have emerged as prominent TDP-43 splicing targets, but the broader impact of TDP-43–dependent cryptic splicing on neuronal function remains unclear. Here, we report previously unidentified TDP-43 splicing targets critical for membrane excitability and synaptic function, including KALRN , RAP1GAP , SYT7 , and KCNQ2 . Using human stem cell–derived neurons, we showed that TDP-43 reduction induces cryptic splicing and down-regulation of these genes, resulting in impaired excitability and synaptic transmission. In postmortem brains from patients with FTD, these cryptic splicing events occurred selectively in neurons with TDP-43 pathology. Suppressing individual cryptic splicing events using antisense oligonucleotides partially restored neuronal function, and combined targeting almost fully rescued the synaptic deficit caused by TDP-43 loss. Together, our findings provide evidence that cryptic splicing in these synaptic and membrane excitability genes is not only a downstream marker but instead a direct driver of neuronal dysfunction, establishing a mechanistic link between TDP-43 pathology and neurodegeneration in ALS and FTD.