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Not Just for Kids: A Systematic Review of Outcomes of the Thenar Flap
No full textIntroduction: Fingertip injuries are common and the thenar flap is a well-described technique used to maintain digital length. However, its use in patients over 30 years of age is generally discouraged due to concerns regarding postoperative joint contracture. The purpose of this review was to evaluate whether these concerns are substantiated.
Methods: A search of PubMed, Embase, and SCOPUS (1947–2025) identified 15 studies involving 519 flaps. Case reports and studies lacking functional outcome data were excluded. Bias was assessed using the MINORS instrument, and results were synthesized using Microsoft Excel.
Results: Joint contracture occurred in 32.4% of cases, all of which involved only the distal interphalangeal (DIP) joint. Active range of motion (AROM) at the metacarpophalangeal (MCP) and proximal interphalangeal (PIP) joints remained near normal and comparable to contralateral finger values. DIP joint AROM was reduced by 14.1° compared to contralateral fingers. Patients over 30 demonstrated a 3° greater PIP joint AROM than younger patients (p=0.02).
Conclusion: Our analysis of the literature shows that there is an elevated risk of DIP joint contracture after thenar flap reconstruction of a fingertip injury, but this risk was not significantly different in patients over age 30. Further investigation with larger studies and standardized outcomes assessment is recommended
Dual CDK4/6-PI3K/mTOR inhibition reinforces cytostatic programs and tumor control in preclinical models of primary and metastatic osteosarcoma
No full textOsteosarcoma (OS) in pediatric, adolescent, and young adult (AYA) patients is an aggressive bone cancer with limited treatment options. Dysregulation of the CDK4/6-cyclin D axis and the PI3K/mTOR pathway contributes to OS pathogenesis, providing a biological rationale for co-targeting these signaling nodes. However, pharmacologic CDK4/6 inhibition can trigger compensatory activation of the PI3K/mTOR pathway, restoring D-type cyclin expression and partially reactivating CDK4/6 signaling. Thus, dual inhibition of the CDK4/6 and PI3K/mTOR pathways not only addresses two parallel oncogenic drivers but may also prevent potential CDK4/6 inhibitor resistance mediated by feedback activation of PI3K/mTOR. In this study, we tested the hypothesis that coordinated targeting of these pathways would improve tumor control in preclinical OS models. In vitro sensitivity analyses using palbociclib and voxtalisib demonstrated additive to synergistic OS growth suppression, with palbociclib inducing G1 arrest and senescence, and the combination enhancing autophagy. Furthermore, the efficacy, tolerability, and mechanisms of palbociclib and voxtalisib, alone or in combination, were evaluated in molecularly defined primary treatment-naïve, and relapsed/metastatic OS models. In the relapsed/metastatic PDX77-TT2 model, short-term palbociclib exposure activated PI3K/mTOR signaling, whereas the combination of palbociclib and voxtalisib in long-term studies produced marked tumor suppression and extended survival. In the primary treatment-naïve PDX96 model, long-term palbociclib exposure generated a robust CDK4/6 pharmacodynamic response. The addition of voxtalisib reinforced autophagy, sustained CDK pathway inhibition, and improved overall tumor control. In an OS lung-colonization model, CDK4/6 inhibition alone markedly reduced OS lung nodules, with combination therapy providing comparable suppression. Dual CDK4/6-PI3K/mTOR inhibition achieves tumor control across various OS models, supporting the use of genomically guided, pathway-targeted strategies for pediatric and AYA OS
National Evaluation of the Management of Melanoma Patients with Multiple Positive Sentinel Lymph Nodes
No full textIntroduction: Clinical trials for melanoma patients demonstrated safety of observation in lieu of completion lymph node dissection (CLND) following positive sentinel lymph node (SLN) biopsy. Patients with two or more positive SLNs were infrequently included in the trials, leaving uncertainty about their management. We aimed to (1) assess national trends of CLND use in patients with two or more positive SLNs; (2) examine factors associated with CLND use; and (3) examine overall survival outcomes.
Methods: Patients with stage I-III melanoma who underwent SLN biopsy between 2012 and 2021 were identified from the National Cancer Database. Factors associated with CLND were assessed by hierarchical logistic regression. Overall survival was estimated using Cox proportional hazards models.
Results: Among 151,442 patients (median age 61 years; 41.3% female) who underwent SLN biopsy, 5440 (3.6%) had two or more positive SLNs. CLND in patients with two or more positive SLNs decreased from 73% in 2012 to 14% in 2021, while immunotherapy utilization increased from 38% in 2012 to 76% in 2021. Patients with two or more positive SLNs were more likely to undergo CLND if they had melanoma in the head/neck region (odds ratio [OR] 2.02, 95% confidence interval [CI] 1.39-2.95) or ulcerated lesions (OR 1.42, 95% CI 1.11-1.83). There was no difference in 3-year overall survival (70.5% for two or more positive SLNs with observation vs. 70.8% for two or more positive SLNs with CLND; hazard ratio 1.03, 95% CI 0.77-1.37) for observation vs. CLND.
Conclusion: Utilization of CLND declined for melanoma patients with two or more positive SLNs following major clinical trials, with no difference in overall survival for observation versus CLND. Evolving treatment recommendations have been rapidly incorporated into practice in the United States
Indiana's 2024 Behavioral Health and Human Services Workforce Snapshot: Licensed Social Workers
No full textThis document is a 2024 data snapshot of actively practicing Licensed Social Workers (LSWs) in Indiana within the Behavioral Health and Human Services workforce. It reports the total number of active LSWs (1,800) and identifies primary practice settings, with private practice representing the largest share. The document also highlights key services provided—notably mental health services, general counseling, case management, and telehealth—and identifies major populations served, particularly adults and individuals in recovery. Additional data are included on where LSWs obtained their qualifying education
Aberrant Splicing Burden Predicts Immune Infiltration and Prognosis in Head and Neck Squamous Cell Carcinomas
No full textBackground: The role of alternative splicing events (ASEs) in immune evasion and prognosis in head and neck squamous cell carcinoma (HNSC) is not well characterized.
Methods: Using The Cancer Genome Atlas data, we identified ASEs (using our novel algorithm OutSplice) and characterized associations between splice burden, immune infiltration (quantified by xCell) and prognosis with multivariable logistic regression and survival models.
Results: HSNC tumors with low splice burden and high immune infiltration had significantly better prognosis than tumors with high splice burden and low immune infiltration when controlling for age, pathologic stage, HPV status, and tumor mutational burden (hazard ratio = 0.61). High splice burden predicted decreased immune infiltration in HNSC, which was validated in five other cancer types and supported by murine models of oral squamous cell carcinoma.
Conclusions: High splicing burden, as defined by OutSplice, is a novel biomarker to predict poor both immune infiltration and prognosis in HNSC
Identification of cancer mini-drivers by deciphering selective landscape in the cancer genome
No full textCancer development is driven by somatic evolution and clonal selection. However, traditional selective pressure analysis methods have treated all sites within a gene equally, such a gene-level model oversimplifies the complexity of cancer evolution. In this study, we introduced CN/CS-calculator, a novel site-specific method that can capture selective pressures acting across different gene sites. By deciphering the interplay between the selection pattern and the function of a gene in oncogenesis, CN/CS-calculator uncovers a unique class of mini-driver genes, which exhibit weak positive selection, with certain critical sites providing context-dependent promoter effects on the fitness of cancer subclones while others are constrained by evolutionary conservation. Our method emphasizes the importance of site-specific analysis in uncovering how subtle evolutionary forces shape cancer biology. The refined understanding offers new insights into the mechanisms of cancer heterogeneity and molecular evolution, with potential implications for advancing therapeutic strategies and prognostic assessments
Distinct neural signatures in a sensorimotor synchronization-continuation task
No full textOptimal sensorimotor timing hinges on the generation, refinement, and employment of internal models to meet task demands. In finger tapping sensorimotor synchronization tasks, this occurs across and within tapping conditions that prompt externally-cued synchronization, followed by un-cued continuation. Theory suggests within each condition, initial behavioral performance is adjusted by internal models. However, whether distinct within- and between condition subprocesses are associated with activation of unique neural networks remains unknown. During fMRI, 100 neurotypical adults completed a finger tapping task with synchronization and continuation conditions. Rapid improvement in tapping accuracy occurred during the initial seconds of both synchronization and continuation conditions. Tapping performance in the first few seconds of each condition was marked by heightened functional activity across sensorimotor, prefrontal-parietal-temporal, and salience network regions compared to subsequent within-condition performance, suggesting rapid refinement of an internal model. Intensity of functional activity within the same regions correlated with task performance. Findings highlight dynamic processes supporting development and refinement of internal models for sensorimotor timing
Enhancing care in alcohol-associated liver disease through peer support for alcohol use disorder
No full textAlcohol use disorder (AUD) and alcohol-associated liver disease (ALD) are interconnected conditions that contribute significantly to global morbidity and mortality. Despite advances in medical management, care for individuals with AUD and ALD remains suboptimal due to persistent gaps in psychosocial support, stigma, and limited integration between behavioral health care including AUD treatment services and hepatology. Peer support, emotional, informational, and practical assistance provided by individuals with lived experience, has emerged as a promising, though underutilized, strategy to address these challenges. This review examines the evolving role of peer and patient support programs, including community-based groups such as Alcoholics Anonymous and SMART Recovery, structured interventions for transplant candidates, and the integration of peer navigators within medical settings. Evidence suggests that peer support fosters recovery by enhancing engagement, reducing isolation, and promoting self-efficacy. Technological innovations, including virtual platforms and mobile apps, are extending the reach of peer support, particularly in rural or underserved populations. In addition, culturally tailored and demographically specific models are increasingly being adopted to address the diverse needs of patients. However, several challenges persist, including variability in peer training, inconsistent oversight, and limited research specific to ALD populations. To maximize the impact of peer support, future efforts must focus on integrating these programs into clinical care, ensuring sustainable funding, and evaluating outcomes using standardized metrics. Peer support represents a critical opportunity to enhance the recovery experience for individuals with AUD and ALD by addressing the emotional and social dimensions of care often overlooked in traditional medical settings
The Relative Contribution of Amyloid, Tau, Neurodegeneration, and Vascular Disease to Cognition and Cognitive Decline: A Cross‐National Study
No full textBackground:
Recent in vivo biomarker advancements have led to biological diagnostic and staging criteria for AD based on amyloid(“A”), tau(“T”), and neurodegeneration(“N”). However, the contribution of comorbid vascular(“V”) pathology and the relative influence of ATNV on cognitive performance and decline remains unclear, though is necessary to guide personalized diagnosis, prognosis, and care. We assessed the relative contribution of neuroimaging‐based ATNV measures to cognition in cross‐national studies.
Method:
Amyloid PET, tau PET, MRI, cognitive testing, and clinical evaluations were obtained in two prospective cohort studies with similar designs: ADNI3 in the US (n = 508; mean age=71±7, female=55%, education(yrs)=16.5±2.3) and KBASE in South Korea (n = 165; age=73±8, female=64%, education(yrs)=11.0±4.6). Continuous ATNV predictors included A=cortical centiloids, T=meta‐temporal SUVR, N = AD‐signature cortical thickness, and V=white matter hyperintensity volume. Clinical diagnoses of cognitively unimpaired (CU), mild cognitive impairment (MCI), and dementia were determined by clinical consensus. Cognitive testing was obtained annually with up to 4 years of follow‐up, and factor scores in each cognitive domain were used as outcomes. Parallel cross‐sectional analyses were performed within each cohort. ANOVA was performed to compare ATNV across clinical diagnoses. Multivariable linear mixed‐effect models were used to assess the association of baseline ATNV predictors with baseline and longitudinal cognitive outcomes adjusting for age, sex, education, and APOE status.
Result:
A, T, N, and V as continuous (mean) and binary (frequency of positivity) variables increased with clinical disease severity in both ADNI and KBASE (Table 1). In ADNI, T and N were associated with lower intercepts in each cognitive domain, V was associated with visuospatial and executive function intercepts, and A with the memory intercept (Table 2). Higher baseline T was associated with decline in each domain, and A was associated with memory decline. In KBASE, T was associated with lower memory and visuospatial intercepts, and N with visuospatial and executive function intercepts (Table 3). No factors (ATNV) were associated with cognitive decline over time in KBASE.
Conclusion:
Among ATNV measures, T and N are most strongly associated with cognition in individuals in the US and South Korea. T is most predictive of future cognitive decline in individuals in the US, though not replicated in Korea
Deep‐Block: Large‐scale WGS Analysis for Alzheimer's Disease Risk Variant Detection Using Deep Learning
No full textBackground:
The large‐scale WGS data from the Alzheimer's Disease Sequencing Project (ADSP) presents opportunities to identify novel genetic factors for Alzheimer's disease (AD). Advanced Artificial Intelligence (AI)‐based approaches may facilitate analysis of the WGS data. In this study, we developed Deep‐Block, a deep learning framework, to analyze ADSP R4 data, comprising 36,361 participant genomes. Our framework aims to identify robust AD‐associated genetic loci while retaining important biological context in an efficient manner. By integrating attention‐based neural networks, Deep‐Block captures intricate, non‐linear interactions among millions of genetic variants.
Methods:
We performed quality control on ADSP R4 WGS data (N = 36,361), retaining 9,956,115 SNPs and 36,329 participants (99.91%). We segmented the genome into 48,959 linkage disequilibrium (LD) blocks and imputed un‐called SNPs using k‐Nearest Neighbors. TabNet was used for feature selection, designating blocks exceeding 2.0 standard deviations above mean accuracy as high‐importance, yielding 3,040 blocks. A dual‐model approach (TabNet and Random Forest) computed importance scores for each SNP, identifying 4,869 genetic markers evaluated for their association with AD risk.
Results:
Deep‐Block yielded an AUC of 0.70 on an independent test set (N = 3,000), substantially outperforming randomly selecting SNPs (AUC=0.50) by 40%. Chromosome 19 harbored the largest number of high‐priority variants, including the known APOE‐related markers. In total, 95.6% of quality‐filtered SNPs were incorporated, indicating thorough genomic coverage.
Conclusions:
Deep‐Block is able to identify complex genomic features in AD. Model training and validation converged consistently, with cross‐validation demonstrating stable performance in AD risk prediction. By integrating LD‐based segmentation with deep learning approaches, the framework manages and addresses the complexity of large‐scale WGS data. Although high‐performance computing can expedite analysis, the method remains feasible in various research environments. Future directions include expansion of Deep‐Block to multi‐ethnic populations and incorporating multi‐omics data which may yield deeper insights into the genetic architecture of AD. Functional validation will be important to elucidate the influence of identified variants on AD pathogenesis