Citations

Background: Little is known about how silicone metacarpophalangeal (MCP) arthroplasty outcomes compare between rheumatoid arthritis (RA) and osteoarthritis (OA) patients. Methods: Using our single institutional data from 2000 to 2022, we propensity matched 46 primary silicone MCP arthroplasties in 33 OA patients 1:2 to 92 arthroplasties in 54 RA patients based on age, sex, body mass index, operative digit, and if the surgery was on the dominant hand. We used Kaplan-Meier estimates and cluster-robust Cox proportional hazard models to compare survival free from revision, all-cause reoperation, and development of coronal plane deviation >10°. Results: There was comparable 10-year survival free of revision (94% OA, 91% RA) and all-cause reoperation (91% OA, 87% RA), with no difference in risk for each outcome between groups. Revision in OA patients occurred early (mean 0.6 years) for recurrent deformity (n = 2) and periprosthetic joint infection (n = 1). Revision in the RA cohort occurred later (mean 6.3 years postoperatively) for recurrent deformity (n = 3) and dislocation (n = 1). Osteoarthritis patients had less coronal plane deviation at the final radiographic follow-up (6.5° vs 16.2°, P < .001), higher 10-year survival free from coronal deviation > 10° (79% vs 17%), and lower risk of progressive coronal deformity (hazard ratio 0.15, P < .001). Conclusions: Silicone MCP arthroplasty remains a durable option with low reoperation rates for RA and OA. Osteoarthritis patients experience less coronal deviation and late reoperation for deformity than RA patients, likely due to their more robust soft-tissue stabilizers and noninflammatory disease process.

Rotator cuff injuries are among the most common musculoskeletal conditions that affect shoulder function and can ultimately impact quality of life. While physical therapy is essential in the care of rotator cuff injuries, the ideal dose of therapeutic exercises continues to be a significant clinical dilemma because of the generalized nature of rehabilitation protocols. This pilot study proposes a machine learning approach to personalize rehabilitation using surface electromyography (sEMG) data collected from eight healthy individuals by testing four key shoulder movements: scaption, internal rotation, external rotation, and external rotation at 90° abduction. In this research, the XGBoost algorithm was used to model muscle activation patterns by achieving a high predictive accuracy (R2 = 0.5325; MSE = 0.0084 μV2). Because sEMG reliably measures superficial muscle activity, a linear programming model was used to divide a 60 min therapy session in a way that increases activation of superficial muscles (such as deltoid and trapezius) while reducing strain on deep muscles (such as supraspinatus and infraspinatus). Three optimization scenarios were tested by reflecting a different clinical goal: prioritizing superficial muscles, minimizing deep muscle strain, or balancing both. Optimized time allocations assigned more time to external rotation at 90° abduction and scaption. This research demonstrates the potential for data-driven methods to transform rotator cuff rehabilitation through personalized and evidence-based treatment plans. The results enhance clinical practice by enabling adaptive rehabilitation planning and show that machine learning can support decision-making in complex muscle activation analysis with strong performance and low latency.

Abstract Alzheimer’s disease (AD) emerges from multi-scale interactions between molecular pathology and disruptions in large-scale brain network dynamics. Understanding how these processes co-evolve and relate to disease stages is essential for advancing complex systems models of aging and AD, and for developing system-informed interventions. However, progress has been limited by a lack of large-scale longitudinal data. To address this, we examined the longitudinal relationship between subsystems of the default mode network (DMN) (posterior DMN, ventral DMN, anterior dorsal DMN) using task-free functional MRI (fMRI) and amyloid positron emission tomography (PET) imaging in a large longitudinal cohort spanning the clinico-biological spectrum of AD (n = 1,451; 2,763 time points) using mixed-effect models. We also assessed whether patterns of DMN connectivity predicted conversion to amyloid positivity, mild cognitive impairment (MCI), and dementia using Cox proportional hazards models. Our findings reveal a dynamic interplay between amyloid accumulation and connectivity within and between DMN subsystems, with both hyper- and hypoconnectivity emerging across DMN subsystems in association with increasing amyloid burden. Importantly, survival models showed that DMN connectivity patterns predicted conversion to critical stages of the disease, including not only conversion to MCI and dementia, but also conversion to amyloid positivity in otherwise clinically unimpaired individuals who were amyloid negative at baseline. These associations were independent of age, APOE4 status, sex, education, and in-scanner motion. These results support a model in which breakdowns in tightly regulated feedback loops governing DMN physiology represent a core systems-level pathophysiology of AD. Notably, this functional dyshomeostasis precedes detectable amyloidosis on imaging. Future studies should focus on the development of robust biomarkers of brain function that can be applied at the individual level, which could in turn help support the development of therapeutic approaches targeting system-level pathophysiology.

Abstract Background Alveolar macrophages (AMs) are central to host defense against Pneumocystis, mediating organism clearance while also contributing to lung inflammation. EphA2, a transmembrane receptor that binds fungal β-glucans, has emerged as a regulator of host–pathogen interactions, but its role in AM responses during Pneumocystis pneumonia (PCP) is unknown. Methods We evaluated AM inflammatory responses to Pneumocystis β-glucans in the presence and absence of EphA2. In vivo studies used a CD4-depleted mouse model of PCP comparing wild-type and EphA2-deficient (EphA2−/−) mice. Lung cytokine responses and organism burden were assessed. Additionally, EphA2 signaling was pharmacologically inhibited using ALW-II-41-27 during trimethoprim-sulfamethoxazole treatment. Results EphA2 deficiency significantly reduced AM proinflammatory cytokine responses to Pneumocystis β-glucans. In CD4-depleted PCP mice, EphA2−/− animals demonstrated decreased lung inflammatory cytokines, but increased organism burden compared to controls. Pharmacologic inhibition of EphA2 during antimicrobial therapy significantly suppressed lung inflammation. Conclusions EphA2 signaling plays a critical role in AM-mediated host defense against Pneumocystis by promoting inflammatory responses necessary for organism control. However, this pathway also contributes to lung inflammation. Targeting EphA2 may represent a novel strategy to modulate inflammation during severe PCP while preserving antimicrobial defense.

Abstract Skin biopsies analyzed with α-synuclein seed amplification assays (SAAs) are a simple way to clinically interrogate the presence of α-synuclein aggregates. We determined the accuracy of skin biopsy SAA in predicting the clinical diagnoses of Parkinson disease (PD), PD with dementia (PDD) and dementia with Lewy bodies (DLB). Blinded SAAs were performed in 3 independent laboratories. Subjects diagnosed with PD, PDD and DLB were analyzed together as group 1, clinically unaffected subjects as group 2 and those with risk factors for LBD as group 3. Punch biopsies were taken from the posterior neck and analyzed by the 3 labs in 6 separate SAAs. Pairwise agreement between labs and assays ranged from excellent (kappa 0.82) to moderate (kappa 0.40-0.68). Sensitivity across assays ranged between 50.0% and 61.3%; specificity ranged between 68.6% and 100%. Comparisons of group 1 vs group 2 produced the greatest specificities, between 77.3% and 100%. In 17 cases that subsequently came to autopsy, 93% of SAAs were positive in those at the neocortical LBD stage but in only &lt;10% of those at lower stages. Skin biopsy α-synuclein SAA may be useful as a diagnostic and progression biomarker in Lewy body dementia clinical trials.

ABSTRACT Circulating tumor DNA (ctDNA) as a liquid biopsy is an emerging tool used for diagnosis and disease monitoring, yet not all tumors shed DNA equally, thus currently limiting the clinical applicability of this tool. Our institution has developed and validated a droplet digital Polymerase Chain Reaction (ddPCR) ctDNA test for BRAF V600 mutation. We collected data on all BRAF mutated melanoma patients tested with the ddPCR BRAF assay at our institution over the years 2018–2024 and correlated the test results with clinical and radiological baseline parameters, with a focus on Positron Emission Tomography‐Computed Tomography (PET‐CT) data, incorporating both location of lesions and volume of disease. Linear and logistic regression modelling was used to assess possible associations between the baseline parameters and the ctDNA results. We identified 71 BRAF mutated melanoma patients, of which 65 had active disease on imaging studies and 43 had PET‐CT data available for analysis. Multivariate modelling has shown that patients were more likely to have a positive ctDNA result if they had elevated serum lactate dehydrogenase (LDH) (OR = 9.9), had a higher number of lesions on imaging studies (> 10 lesions: OR = 11.3), and if they were younger than 65 (OR = 11.8), with an AUC of 0.84. The PET‐CT calculated total metabolic tumor volume correlated with the quantitative ctDNA result with a Pearson r factor of 0.49. In conclusion, ctDNA ddPCR BRAF testing is easily obtained and might be especially beneficial for patients diagnosed with a clinically aggressive disease, based on elevated LDH, higher PET‐CT metabolic tumor volume, and younger age.