Citations

Abstract Heterogeneous treatment effects (HTE) are key to precision medicine, but most real-world studies lack the scale and diversity needed to detect them. While multi-site analyses offer a potential solution, data-sharing constraints often prevent access to patient-level information across institutions. We introduce POLARIS, a federated framework for time-to-event target trial emulation. POLARIS converts each site’s weighted Cox risk function into a compact tensor shared once with the coordinating center, enabling lossless reproduction of pooled estimates without sharing patient-level data. We applied POLARIS across five U.S. health systems to study risk of gastrointestinal outcomes after GLP-1 receptor agonist (GLP-1RAs) initiation versus sodium-glucose cotransporter 2 inhibitors (SGLT2is) and dipeptidyl peptidase 4 inhibitors (DPP4is). Results showed that GLP-1RAs were consistently associated with higher risks of nausea and vomiting, particularly among men, individuals with higher baseline HbA1c (≥ 8.5%), and lipid therapy. POLARIS provides a scalable solution for distributed target trial emulation and fine-grained assessment of HTE across diverse health systems.

Over the past three decades, the emergence of recombinant antibodies has positioned them as the fastest-growing class of therapeutic proteins and as well as crucial reagents for both diagnostics and specific research applications. The industrial production of most therapeutic antibodies currently relies on mammalian cell lines, primarily Chinese Hamster Ovary (CHO) cells, which remain the gold standard in biopharmaceutical manufacturing due to their exceptionally high production yields, robustness, regulatory acceptance, and consistent product quality. Nevertheless, new approaches using specifically adapted expression systems are emerging. These new host organisms enable the production of antibodies with posttranslational modifications that closely resemble those found in the human system, without the need for animal-derived source materials. For diagnostic and research purposes, a broad range of production systems has been developed. These include Gram-negative and Gram-positive bacteria, yeasts, filamentous fungi, insect cell lines, and transgenic plants. Additionally, smaller single domain antibodies and bispecific fragments that do not require glycosylation can be successfully produced in bacteria for therapeutic applications. Some of these molecules have already been approved by regulatory authorities in the European Union and the United States, and several more are currently in clinical trials. This review therefore focuses on the broad and evolving landscape of recombinant antibody production systems and their applicability across various fields.

Abstract Background Babesia and Plasmodium are intraerythrocytic parasites that cause babesiosis and malaria, respectively. Significant associations between human blood group antigens and malaria are known; however, few studies have examined the relationship between blood group antigens and babesiosis. Study Design and Methods From June to August 2025, 100 Babesia polymerase chain reaction (PCR)− and 100 B. microti PCR+ human patient samples tested at a national reference laboratory underwent ABO and D phenotyping and red blood cell (RBC) genotyping of 37 antigens. Results The predicted phenotype of S‐s+ was found in 32% and 50% of Babesia − and B. microti + patients, respectively (χ 2 = 5.97, p = .015, odds ratio = 2.125, 95% confidence interval 1.18–3.78). Two B. microti + patients had the predicted phenotype of Fy(a‐b‐), meaning that Duffy is unlikely to be an essential invasion receptor. There were no statistically significant differences in ABO or D expression between the groups. Discussion Because multiple testing corrections were not applied to the statistical analyses, the S/s predicted phenotype results must be viewed as hypothesis‐generating. This may be the first study to link B. microti infection to human RBC S/s antigens, which are known to impact B. divergens and P. falciparum . Additional studies are needed to understand the impact of the babesiosis patient's blood type on B. microti infection and whether the transfusion of RBCs expressing specific antigens can impact the disease.

ABSTRACT Talquetamab is a GPRC5D × CD3 bispecific antibody approved for relapsed/refractory multiple myeloma (RRMM). This is the first real‐world study to comprehensively report muco‐cutaneous toxicities, infections, and efficacy of talquetamab in 151 patients across five countries with the longest follow‐up reported enabling better efficacy and toxicity estimates. The median age was 64 years; high‐risk cytogenetics were present in 42%; ECOG ≥ 2 in 22%; 12% had creatinine clearance < 30; and 55% would not have met MonumenTAL‐1 eligibility. Patients received a median of 6 prior lines of therapy, 53% were penta‐refractory, and 75% received prior BCMA therapy. Talquetamab was associated with skin toxicity in 39.7%, nail toxicity in 75.5%, dysgeusia in 60.4%, and oral toxicities in 62.9%, with grade ≥ 3 events uncommon (≤ 4%) and dose interruptions infrequent (9.6% for skin toxicity, 6.9% for dysgeusia, and 4.0% for oral toxicities). These findings underscore the need for improved supportive care for muco‐cutaneous toxicities. In multivariate analysis, only platelet count < 50 (HR 1.8, 95% CI 1.15–2.83) was associated with inferior PFS, while penta‐refractory status, absolute lymphocyte count < 0.4, and prior BCMA‐targeted therapy were not statistically significant. With a median follow‐up of 12.7 months, the overall response rate was 67.6%, median progression‐free survival was 7 months, and 12‐month overall survival was 65%. This study shows that talquetamab efficacy is maintained in a heavily pretreated real‐world population with high prior BCMA exposure and notable comorbidity burden.

Introduction Proton dose driven continuous scanning (DDCS) is a form of proton pencil beam scanning (PBS) in which the beam may remain on during transitions between successive spots. Mayo Clinic Florida (MCF) is preparing to commission a synchrotron-based proton therapy system designed for DDCS, incorporating novel irradiation control features. Given the novelty and complexity of this system, a systematic risk-based analysis was performed to inform upcoming commissioning strategies. Methods A prospective risk analysis was conducted using the American Association of Physicists in Medicine (AAPM) Task Group 100 (TG 100) framework. A comprehensive process map of the DDCS irradiation control workflow was developed. Failure modes and effects analysis (FMEA) was performed to identify potential delivery system failure modes and to score each failure mode based on occurrence, severity, and lack of detectability. Targeted mitigation and commissioning strategies were then developed to address the highest-risk items. Results Twenty-nine delivery system failure modes were identified. The highest-risk failure modes were specific to DDCS operation. Targeted commissioning strategies were defined, including scan path measurement and modeling, validation of move and flap dose, dose monitor collection efficiency testing, spot position monitor performance evaluation, and verification of control system intervention behavior. Incorporation of these strategies into the commissioning plan reduced the mean RPN by more than 50%. Discussion This work provides a detailed description of the MCF proton DDCS irradiation control system and uses a TG 100 based approach for identifying system-specific risks. As new systems incorporate technologies for which limited guidance exists, institutions must perform their own risk analyses to determine appropriate quality management strategies.

Background Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer (BC) and lacks effective treatment options. Polyphyllin B (PB), a saponin extracted from Paris formosana Hayata, has shown potential in cancer therapy. However, its anti-TNBC effects and mechanisms are not well studied. This study investigated the effects and underlying mechanisms of PB in TNBC. Methods CCK8 assay, Wound healing assay, Transwell migration experiments, and clonogenic assay were performed to assess the effects of PB in three TNBC cells lines. Iron level, lipid ROS, and MDA levels were assessed as ferroptosis markers. Mechanistic studies were conducted using molecular docking, Western blot, immunofluorescence, RT-qPCR, Nrf2 overexpression assays and establishment of a TNBC mouse model. Results PB treatment resulted in significant cell death and inhibited the migration of TNBC cells. Accumulation of iron and MDA suggested that PB induces ferroptosis. In vitro and in vivo , PB downregulated the expression of nuclear factor E2-related factor 2 (NRF2) and sequestosome-1 (P62) and upregulated the expression of Kelch-like ECH-associated protein 1 (KEAP1). Furthermore, it modulated the expression of key ferroptosis regulators, including acyl-CoA synthetase long-chain family member 4 (ACSL4) and glutathione peroxidase 4 (GPX4). In a TNBC mouse model, PB suppressed tumor growth and increased malondialdehyde accumulation. Conclusion PB inhibits cell proliferation and migration and induces ferroptosis in TNBC through the inactivation of NRF2. PB is a promising candidate for TNBC treatment that warrants further investigation.

Introduction Studies have revealed circadian rhythms affect many organ systems and time of injury can impact healing, lung function, and inflammation. We hypothesized operative time may impact post-operative risk. Accordingly, the aim of this study was to compare post-operative complications in patients whose surgery started and finished before 12pm (Group 1); after 12pm (Group 2); and started before 12pm and finished after 12pm (Group 3). Methods Patients from two previous prospective studies were included in this post-hoc analysis. Inclusion criteria were indication for lung resection surgery (confirmed or highly suspicious tumor), age ≥18 and ability to undergo cardiopulmonary exercise testing (CPET). Exclusion criterion was inability to perform surgery (either low predicted postoperative oxygen consumption or inoperability). All patients underwent pre-operative CPET and spirometry. Post-operative pulmonary (PPC) and cardiovascular complications (PCC) were prospectively assessed from the hospital stay up to 30 days. Results Data from 497 patients were analyzed. On comparison of groups, there were differences in BMI (highest in Group 3), surgery duration (lowest in Group 1) and frequency of lobectomies (lowest in Group 1). Incidence of PPC was lowest in Group 1 (n=17; 9%) compared to n=17 (21%) in Group 2 and n=37 (17%) in Group 3 (p=0.01). Incidence of PCC was lowest in Group 1 n=25 (13%) compared to n=19 (23%) in Group 2 and n=46 (21%) in Group 3 (p=0.05). Multivariate logistic regression adjusted for confounders (BMI, surgery duration and lobectomy) showed time of surgery after 12pm was independently associated with PPC with OR = 2.17 (95% CI 1.07-4.41); p=0.03. Conclusion Time of surgery may impact the incidence of PPC in lung resection surgery patients with highest risk in patients undergoing the surgery after 12pm.

ABSTRACT Age‐related changes in human hematopoietic stem cells (HSCs) often form the basis for clonal hematopoiesis (CH), which presages the development of overt myeloid neoplasm with variable risk. CH can also arise after exposure to chemotherapy, radiotherapy, or immune interventions. In this study, we performed clinico‐genomic profiling of therapy‐related CH (t‐CH) ( n = 67) versus de novo CH ( n = 123) from a multidisciplinary CHIP Clinic. The most enriched mutations in t‐CH were TET2 (26.2%), DNMT3A (22.4%), and TP53 (8.4%). Median latency period from the time of initial exposure to the diagnosis of t‐CH was 6.96 ± 1.10 years. Patients with t‐CH had inferior event‐free survival compared to de novo CH (median 29.9 months versus 122.1 months, p = 0.0045). Overall survival was also shorter in t‐CH versus de novo CH (median 55.3 months vs. 129.2 months, p = 0.043). Genes that imparted significantly increased risk for progression from t‐CH to overt therapy‐related myeloid neoplasm (t‐MN) included JAK2 (relative risk (RR) 9.42, p = 0.0001), RUNX1 (RR 7.11, p = 0.001), EZH2 (RR 7.11, p = 0.001), and TET2 (RR 13.4, p = 0.01). Clonal dynamic modeling of patients with t‐CH who progressed to overt t‐MN showed an increase in the relative clonal fraction and new clonal outgrowth. In the t‐CH cohort, higher mean variant allele frequency was observed in progressors versus non‐progressors (77.1% vs. 30.6%, p = 0.017). This study sheds light onto outcomes for CH based on differing clinical ontogeny and has implications for previvorship for secondary malignancies.

Abstract Functional magnetic resonance imaging (fMRI) data are inherently complex, characterized by high dimensionality, intricate inter-regional dependencies, and substantial individual variability across experimental paradigms. Traditional linear mixed models (LMMs) provide a principled framework that models population-level fixed effects while estimating variance components arising from subject-level random effects; however, they often fail to adequately capture nonlinear relationships inherent in neuroimaging data. To address these limitations, we introduce the nonlinear mixed model (NMM) approach, an innovative extension of the LMM framework that integrates neural networks to flexibly model complex fixed-effect relationships while preserving the random-effects structure to account for individual differences. NMM advances fMRI analysis by: (1) identifying robust functional connectivity (FC) patterns consistently observed across multiple paradigms; (2) leveraging SHapley Additive exPlanations (SHAP) analysis to provide post-hoc interpretability of the nonlinear fixed effects, quantifying how age, sex, and paradigm contribute to predicted FC and how these effects are distributed across large-scale brain networks; and (3) using subject-specific random effects as neural fingerprints that not only show systematic variability across attention and default mode systems but also predict standardized cognitive scores, demonstrating biological relevance. Applied to the Philadelphia Neurodevelopmental Cohort (PNC) across emotion, n-back, and resting-state paradigms, NMM achieved superior model fit relative to classical LMMs, as evidenced by lower mean squared error (MSE) in predicting FC. This framework offers a statistically rigorous and practically explainable approach for modeling large-scale FC from modest covariates while explicitly separating population-level effects from stable individual variability in functional brain organization.