Publications

OBJECTIVE: Neuropathic pain significantly impacts quality of life (QoL), mental health, and function. Targeted Muscle Reinnervation (TMR) is an intervention that can effectively treat and prevent neuropathic pain, but its effects on psychosocial outcomes remain underexplored. This study evaluates psychosocial outcomes following TMR surgery for neuropathic pain in both amputees (both primary pTMR and secondary sTMR) and non-amputees.

METHODS: In this prospective study, 46 patients (15 sTMR, 19 pTMR, 12 non-amputees) who underwent TMR for neuropathic pain management were assessed for psychosocial outcomes. Pre- and post-operative surveys measured pain catastrophizing (PROMIS), depression (PHQ-2), anxiety (GAD-2), sleep metrics (PROMIS Sleep Disturbance, sleep duration), and QoL (WHOQOL-2). Mean follow-up was 1.5 ± 0.8 years.

RESULTS: Pain catastrophizing significantly decreased across all groups (overall from 50.39 ± 6.24 to 42.41 ± 4.40, p < 0.001). Depression and Anxiety scores improved significantly in the non-amputee and pTMR groups, but not in sTMR patients. Sleep disturbance decreased significantly in all groups (from 59.67 ± 8.64 to 51.82 ± 8.01, p < 0.001), while sleep duration increased (from 5.32 ± 1.63 to 6.09 ± 1.29 hours, p < 0.001). QoL scores improved significantly across all groups (from 2.45 ± 0.87 to 3.43 ± 0.62, p < 0.001). Patients with psychiatric comorbidities (60.9%) showed similar improvements, despite having higher pre- and post-operative depression and anxiety scores.

CONCLUSIONS: Patients who underwent TMR for neuropathic pain management demonstrated improved psychosocial outcomes. Non-amputees and pTMR patients demonstrated greater improvements in depression and anxiety compared to sTMR patients. Sleep quality and duration improved substantially, a previously underreported benefit of TMR. Future, larger prospective studies should further validate relationship between neuropathic pain reduction through TMR and psychosocial outcomes.

BACKGROUND: Anhedonia-a core symptom of Major Depressive Disorder-is associated with poorer clinical outcomes, lower quality of life, and disrupted reward processing. However, putative relationships among self-reported anhedonia, well-being and anhedonic phenotypes (specifically, reward learning) remain largely unexplored. The main goal of the current study was to fill this gap in a large online adult community sample (N = 478).

METHODS: To evaluate how different approaches to assessing anhedonia may capture these relationships, we administered the Probabilistic Reward Task (PRT) to probe reward learning and two clinical scales: the Snaith-Hamilton Pleasure Scale (SHAPS) and the Dimensional Anhedonia Rating Scale (DARS). In a first step, the SHAPS was administered to identify anhedonic vs. non-anhedonic individuals, who then performed an online PRT.

RESULTS: Both scales were significantly associated with lower self-reported quality of life (QoL), as measured by the Quality of Life Enjoyment and Satisfaction Questionnaire Short Form (QLESQ-SF), with the SHAPS showing a stronger relationship to both QoL and reward learning. Follow-up computational modeling indicated the anhedonic group showed a significantly higher level of uncertainty while completing the PRT compared to the non-anhedonic group. Moreover, trial-by-trial analyses revealed group differences in PRT response patterns, such that anhedonic individuals were less likely to incorrectly indicate that they had seen the more frequently rewarded "rich" stimulus on trials that actually presented the less frequently rewarded "lean" stimulus.

CONCLUSIONS: Findings highlight the utility of combining subjective and behavioral measures to better understand the impact of anhedonia on daily functioning and reinforcement learning processes.

OBJECTIVE: Uveitis refers to the inflammation of the uveal tract of the eye (iris, ciliary body and choroid). In the developed world, it accounts for 10–15% of all cases of blindness. Anterior uveitis accounts is the most common form of uveitis. There is an unmet need for a topically administered non-steroidal drug to treat anterior uveitis.

METHODS: We tested two topical formulations of mycophenolate (MPA), an inhibitor of inosine monophosphate dehydrogenase (IMPDH) enzyme, as a potential steroid-sparing treatment for uveitis. We studied first the binding of MPA to a three-dimensional model of human IMPDH2 generated with AlphaFold 3. Next, we formulated mycophenolate sodium as an aqueous suspension and mycophenolate mofetil as an ointment. Permeability of mycophenolate through the corneal barrier was measured using a Franz cell assay using a goat eye cornea as the membrane. Drug concentration in the different compartments of the eye involved in anterior uveitis was measured using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Both formulations were tested for acute ocular irritation in vivo, and efficacy in a rabbit model of uveitis.

RESULTS: The AlphaFold 3 model of IMPDH2 offered a detailed map of the MPA binding site. MPA makes hydrogen bonds to main chain atoms of S276 and G326 and side chain atoms of S276, T333 and Q441 as well as hydrophobic interactions with S276, G415 and Y430. The computational analysis shed new insights on the mechanism of mycophenolate inhibition and allosteric regulation of the enzyme. Mycophenolate was stable over 6 months in both suspension and ointment. Topical application of mycophenolate sodium 1% and 2% suspension eye drop exhibited a drug flux of 81·81ug/cm2 and 140.42 ug/cm2, respectively, through the corneal barrier, greater than 11.01 ug/cm2 and 26.54 ug/cm2 achieved with mycophenolate mofetil 1% and 2% ointments, respectively. The formulations were non-irritant to eyes of New Zealand white rabbits. No systemic clinical signs of toxicity and necropsy findings were observed. Mycophenolate sodium 2% suspension-treated group showed significant reduction (p < 0.0010) in the uveitis score with reduced leukocyte counts in the anterior chamber compared to vehicle control and was not statistically different from positive control prednisone steroid (p = 0.44).

CONCLUSION: Topical mycophenolate sodium 2% suspension could emerge as an effective non-steroidal treatment for anterior uveitis and merits clinical evaluation.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12348-026-00569-y.

OBJECTIVES: To explore the complexities of eliminating race correction in clinical artificial intelligence (AI), the pitfalls of naive solutions, and to propose systematic strategies for equitable model development.

BACKGROUND AND SIGNIFICANCE: Race correction in clinical AI, as in traditional medicine, introduces biases with potentially harmful consequences. Simple removal of race from models is insufficient due to the lasting influence of historically biased data.

APPROACH: We analyze 4 standardized scenarios to demonstrate how race correction manifests in clinical AI: use of race-corrected variables, explicit inclusion of race, inference via proxy variables, and use of race-specific models.

RESULTS: For each scenario, the intuitive solution to removing race correction fails to eliminate bias, often due to legacy effects embedded in the data. More thoughtful approaches are required.

DISCUSSION: Ending race correction in clinical AI requires deliberate, context-sensitive interventions, inclusion of diverse stakeholders, and strategies to make model reasoning more transparent and auditable.

Multidrug resistance (MDR) of the pathogen Acinetobacter baumannii is a major challenge to global healthcare due to the limited treatment options. The emergence of MDR bacteria necessitates innovative therapeutic approaches, especially given the associated economic burden and the rapid spread of infections. Conventional treatments such as antibiotics and vaccines face significant obstacles. Antimicrobial peptides (AMPs) such as LL37 have potential as an alternative treatment due to their broad-spectrum activity and ability to target specific bacterial structures such as the outer membrane protein A (OmpA). The efficacy of AMPs can be enhanced by using nanobodies (Nbs) that bind to bacterial OmpA, guiding LL37 precisely to its target. In this study, A. baumannii OmpA (AbOmpA)-specific Nbs (NbO7 and NbO13) were efficiently isolated through magnetic-activated cell sorting-based screening of a yeast surface display library, eliminating the need for specialized equipment. Nbs exhibited specific, dose-dependent binding to the target. Conjugation of Nbs with LL37 effectively inhibited the growth of MDR A. baumannii. This approach leverages the natural antimicrobial properties of AMPs and enhances their specificity and effectiveness by targeting bacterial cell surface proteins. LL37-conjugated AbOmpA-Nbs present a promising therapeutic strategy against MDR A. baumannii and other resistant pathogens.IMPORTANCEMultidrug-resistant (MDR) Acinetobacter baumannii poses a major global health threat due to its resistance to nearly all available antibiotics and its persistence in hospital settings. This challenge underscores the urgent need for new therapeutic approaches beyond conventional drugs. In this study, we developed an innovative strategy that combines the human antimicrobial peptide LL37 with nanobodies (Nbs) targeting the outer membrane protein A (OmpA), a key virulence and survival factor of A. baumannii. OmpA-specific Nbs were efficiently isolated from a fully synthetic library using a simple, low-cost selection approach without animal immunization. When conjugated with LL37, these Nbs bound specifically to OmpA and strongly inhibited MDR A. baumannii growth in vitro. Our findings introduce a simple yet powerful platform for generating targeted Nb-peptide conjugates, offering strong potential for adaptation against other antibiotic-resistant pathogens and contributing to the development of next-generation biologics to overcome antibiotic limitations.

Clinical trials are contingent upon enrollment of participants who are willing to volunteer their time and effort. Many persons living with HIV (PLWH) are long-term survivors aging into midlife and thus, are at risk for medical co-morbidities such as cardiovascular disease (CVD). Many PLWH have a long-standing history of research participation, including therapeutic trials, which have informed the use of highly effective antiretroviral treatments. As increasing numbers of PLWH age, research participation remains essential to generate findings to inform clinical care and treatment guidelines for aging-associated diseases specific to this population. Our study shares findings from survey data that explored reasons for clinical research participation, including participation in a CVD risk study, among midlife PLWH. Four themes emerged from content analysis of the participant responses: health and wellness, research engagement, altruism, and personal benefit. Findings may inform strategies to enhance recruitment and retention strategies for research studies among midlife PLWH.

STUDY OBJECTIVES: We investigate a Mamba-based deep learning approach for sleep staging on signals from ANNE One (Sibel Health, Chicago, IL), a non-intrusive dual-module wireless wearable system measuring chest electrocardiography (ECG), triaxial accelerometry, and chest temperature, and finger photoplethysmography and finger temperature.

METHODS: We obtained wearable sensor recordings from 357 adults undergoing concurrent polysomnography (PSG) at a tertiary care sleep lab. Each PSG recording was manually scored and these annotations served as ground truth labels for training and evaluation of our models. PSG and wearable sensor data were automatically aligned using their ECG channels with manual confirmation by visual inspection. We trained a Mamba-based recurrent neural network architecture on these recordings. Ensembling of model variants with similar architectures was performed.

RESULTS: After ensembling, the model attains a 3-class (wake, non rapid eye movement [NREM] sleep, rapid eye movement [REM] sleep) balanced accuracy of 84.02%, F1 score of 84.23%, Cohen's κ of 72.89%, and a Matthews correlation coefficient (MCC) score of 73.00%; a 4-class (wake, light NREM [N1/N2], deep NREM [N3], REM) balanced accuracy of 75.30%, F1 score of 74.10%, Cohen's κ of 61.51%, and MCC score of 61.95%; a 5-class (wake, N1, N2, N3, REM) balanced accuracy of 65.11%, F1 score of 66.15%, Cohen's κ of 53.23%, MCC score of 54.38%.

CONCLUSIONS: Our Mamba-based deep learning model can successfully infer major sleep stages from the ANNE One, a wearable system without electroencephalography (EEG), and can be applied to data from adults attending a tertiary care sleep clinic.

BACKGROUND: Neurodevelopmental models regard impulsivity as a central risk factor for adolescent substance use. However, the practical utility of impulsivity in predicting substance use is complicated by variability among measures that encompass multiple methods and theoretical domains. Prior research has been constrained by cross-sectional designs, small sample sizes, and/or the use of a narrow subset of impulsivity measures.

METHOD: Leveraging the ABCD dataset (n = 11,868), we identified and replicated correlations among impulsivity measures and assessed their prospective longitudinal and concurrent predictive utility regarding adolescent substance use outcomes before 15 years old. We then used simulation to inform how associations between impulsivity and substance use vary across sampling strategies (population vs. high-risk cohorts) and sample sizes.

FINDINGS: Correlations between questionnaire and behavioral measures of impulsivity were small, and questionnaires significantly outperformed behavioral measures in predicting substance use initiation, largely due to the contribution of the CBCL externalizing scale. Predictions of substance use based on impulsivity were statistically detectable but small according to clinical standards (AUCs 0.6-0.76), exhibiting sensitivity to sample size and base rate of substance use, and thus, poor absolute predictive performance. Large samples (n > 1,000) were needed to achieve adequate power for impulsivity measures to predict substance use initiation.

CONCLUSION: These results support a significant but small contribution of impulsivity in predicting the onset of early adolescent substance use, indicating that these factors alone are insufficient for clinically deployable prediction. In community samples, large sample sizes are needed for reproducible impulsivity prediction of adolescent substance use.