Citations

Granulomatous inflammation is a rare but known filler-related complication that may present similarly to an active infectious process with pain, swelling, and erythema. This study describes hyaluronic acid filler-related delayed-onset nodule formation in a pair of 44-year-old and 56-year-old females who were ineffectively treated with numerous attempts of antibiotic regimens, incision and drainage (I&D) procedures, and low-dose hyaluronidase across several months despite multiple negative microbial cultures. After initiation of hyaluronidase therapy dosed to filler-related vascular occlusion guidelines, complete resolution of symptoms was achieved in both patients. These cases emphasize the relevance of considering delayed-onset nodules in the differential for filler complications that are culture-negative and unresponsive to antibiotic treatment and I&D. We propose complete dissolution with higher dosage hyaluronidase as a safe and effective treatment modality with respect to the current lack of defined guidelines for treating this complication.

Abstract Chromosome 5p15.33 harbors several independent association signals which demonstrate antagonistic pleiotropy across cancer types, with causal mechanisms largely unresolved. To identify functional variants and enhancer elements at this locus, we performed statistical fine-mapping followed by massively parallel reporter assays (MPRA) and proliferation based CRISPRi screens. This approach identified eight multi-cancer functional variants (MCFVs) across three GWAS signals. Targeting rs421629 (part of the CLPTM1L signal marked by rs465498) with CRISPRi revealed opposing effects on TERT expression in pancreatic versus lung cancer cells, consistent with the antagonistic pleiotropy observed for this signal. Furthermore, CRISPRi nominated an intronic CLPTM1L variable number tandem repeat (VNTR) as a potent enhancer. Long-read sequencing established VNTR polymorphisms as potential causal variants for the rs465498 signal. We showed that Hippo-pathway transcription factors mediate VNTR enhancer activity in lung and pancreatic cancer cells. Together, these findings indicate that cancer susceptibility at 5p15.33 may be mediated by both SNPs and VNTRs and provide an integrated framework for resolving complex pleiotropic loci.

Abstract Recent work on double descent has challenged classical bias–variance tradeoffs, showing that test error can decrease, increase sharply near the interpolation threshold, and then decrease again as model capacity grows. This phenomenon has been documented in regression and classification, but its relevance to survival analysis remains unclear. Survival data are subject to censoring, which obscures true event times, and widely used models such as the Cox proportional hazards model are optimized via partial likelihoods that emphasize ranking rather than calibrated risk estimation. It is therefore unknown whether double descent occurs in this setting, how censoring influences its manifestation, or how it interacts with standard performance metrics.We investigate these questions using synthetic survival data generated from Weibull hazards with controlled censoring, allowing systematic variation of model capacity from under to over parameterized regimes. While we verified double descent occurs in survival models, calibration plateaus and decouples from discrimination, even under strong $\ell_2$ regularization. This decoupling arises because the Cox partial likelihood optimizes rankings rather than magnitudes, producing extreme risk scores that break the Breslow estimator used to estimate survival probabilities. These results highlight limitations of discrimination-based model selection in survival analysis and underscore the need for calibration-aware evaluation in high-capacity prognostic models.

Robotic-assisted reverse shoulder arthroplasty has recently entered early limited clinical use, with the goal of improving the execution of preoperative plans and reducing malposition outliers that increase complication rates and health-care costs. This Innovation article reviews the rationale for this technology, explores its potential impact, examines key implementation challenges, and highlights the future directions needed to determine its ultimate value.

Abstract The therapeutic landscape for systemic immunoglobulin light chain (AL) amyloidosis has been revolutionized by daratumumab-based regimens, achieving 76% 5-year overall survival in the landmark ANDROMEDA trial. However, the current prognostic models were developed using patient populations treated with now-suboptimal therapies, creating a critical gap between risk stratification models and contemporary outcomes. This comprehensive review analyzes prognostic factors and progression biomarkers in AL, categorizing them into disease-specific (clone-related and organ-related) and patient-specific factors. Notably, traditional baseline biomarkers including difference between involved and uninvolved free light chains and bone marrow plasma cell burden are losing prognostic significance with effective clone-directed therapies. Emerging approaches show promise, including dynamic markers such as minimal residual disease by free light chain mass spectrometry, cardiac imaging parameters such as global longitudinal strain, and functional measures. There is an urgent need for validation studies and prognostic model refinement to identify patients at high risk who may benefit from interventions beyond anti–plasma cell therapy.