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Lymphoid gene expression supports neuroprotective microglia function
No full textMicroglia, the innate immune cells of the brain, play a defining role in the progression of Alzheimer's disease (AD). The microglial response to amyloid plaques in AD can range from neuroprotective to neurotoxic. Here we show that the protective function of microglia is governed by the transcription factor PU.1, which becomes downregulated following microglial contact with plaques. Lowering PU.1 expression in microglia reduces the severity of amyloid disease pathology in mice and is linked to the expression of immunoregulatory lymphoid receptor proteins, particularly CD28, a surface receptor that is critical for T cell activation. Microglia-specific deficiency in CD28, which is expressed by a small subset of plaque-associated PU.1 microglia, promotes a broad inflammatory microglial state that is associated with increased amyloid plaque load. Our findings indicate that PU.1 CD28-expressing microglia may operate as suppressive microglia that mitigate the progression of AD by reducing the severity of neuroinflammation. This role of CD28 and potentially other lymphoid co-stimulatory and co-inhibitory receptor proteins in governing microglial responses in AD points to possible immunotherapy approaches for treating the disease by promoting protective microglial functions.No embarg
Characterization bacterial metabolites and peripheral immune cell populations in stable and progressive Alzheimer’s disease
Get PDFBackground: Alzheimer’s disease (AD) is the most common type of dementia which
results in debilitating memory loss as the disease advances. However, among older
adults with AD, some may experience rapid cognitive decline while others may
maintain a stable cognitive status for years. In addition to the amyloid plaques, tau
tangles, and neuronal inflammation characteristic of AD, there is strong evidence
of dysregulation in the peripheral immune system, including decreased naïve T cells
and increased memory T cells among older adults with AD. It is currently unknown
what underlies dysfunction in the peripheral immune system or whether changes in
peripheral immune cells are associated with cognitive decline.
Method: We have performed unbiased metabolomics and characterized stool
metabolites present in 35 AD versus 35 propensity matched healthy controls. In
our ongoing work, we are longitudinally characterizing resting peripheral immune
cell populations by flow cytometry and gut microbiome composition by metagenomic
sequencing.
Result: We have identified an increase in the metabolites methionine sulfone (1.46
fold, p<0.05), homocysteine (1.67 fold, p<0.05), and cysteine (1.33 fold, p<0.05) in
the stool of older adults with AD compared to controls. Among the population of AD
patients experiencing cognitive decline, determined by increasing ADAS-Cog score >6
points over one year (n = 7 declining vs n = 8 stable cognition), we have identified
increases in the bacterial genes responsible for methionine production at the point
of cognitive decline compared to previous timepoints and between patients with
decline versus stable cognition. In accordance with the role of methionine in promoting
immune cell proliferation and differentiation, we have compared the composition
of peripheral immune cells among adults with declining versus stable cognition and
identified a decrease in CD4+/CD62L+ naïve T cells (percent of CD4+ lymphocytes stable 0.3055 vs declining 0.0955, p = 0.0042) and increased effector memory CD4+ T
cells (percent of CD4+ lymphocytes, stable = 0.2375 vs declining = 0.4164, p = 0.0225).
Conclusion: This longitudinal clinical study identifies changes in stool metabolites
and resting peripheral T cell populations in AD patients and among AD patients with
cognitive decline. We propose that gut bacterial produced methionine acts to promote
peripheral immune differentiation and dysfunction, leading to cognitive decline in AD.No embarg
Comparative Multi-Omics Revealed a Spatially and Transcriptionally Distinct Subset of moDC/Macs as a Key Producer of IFN-β in DM Lesions, Contributing to UVB Photosensitivity
No full textAutoimmune skin diseases include conditions with varied clinical and pathological manifestations. While ultraviolet (UV) radiation is used therapeutically in psoriasis and vitiligo, it is a potent trigger in cutaneous lupus erythematosus (CLE) and dermatomyositis (DM). The molecular mechanisms underlying UV-induced photosensitivity in these diseases remain incompletely understood.
Using a multi-omics approach integrating single-cell RNA-seq, spatial transcriptomics, and proteomics, we identified a specialized subset of monocyte-derived dendritic cells/macrophages (moDC/Macs) preferentially enriched in DM skin as the main producers of IFN-β. Transcriptionally and spatially, moDC/Macs in the skin span a continuum. The IFN-β-producing subset were at the proinflammatory end, marked by high CD16 and an M1-like profile, and localized to immune aggregates overlapping with CXCL12⁺CCL19⁺ fibroblasts or adjacent to keratinocytes in niches defined by CCL2⁺CCL8⁺ fibroblasts.
Basal keratinocytes in non-lesional skin of both CLE and DM exhibited type I interferon (IFN-I) signatures, and IFN-β pre-treatment potentiated UVB-induced apoptosis and cytokine production in keratinocytes, suggesting a primed, hypersensitive state in photosensitive skin. moDC/Macs were also enriched in non-lesional DM skin. In healthy individuals, acute UVB exposure triggered moDC/Mac infiltration. When stimulated with supernatants from UVB-irradiated keratinocytes, moDC/Macs displayed heightened activation and produced monocyte-recruiting chemokines, establishing a feedforward loop between keratinocytes and IFN-β-producing moDC/Macs.
These findings uncovered heterogeneity and spatial location of moDC/Macs in skin, and suggest a mechanistic rationale for targeting moDC/Macs in photosensitive diseases, particularly DM.Interdisciplinary Graduate Program6 months2025-11-0
Assessment of Obstetric Providers' Practice Surrounding Vaccine Counseling and Administration for Non-Birthing Partners
No full textIntroduction: Society guidelines recommend caregivers of neonates, including both co-parents, be up to date on Tdap, COVID-19, and influenza vaccines before delivery to prevent primary transmission of vaccine-preventable diseases to the infant. However, only one third of reproductive-age individuals are up to date on recommended vaccinations. Pregnant individuals often receive recommended vaccines during prenatal care, but limited research has investigated if prenatal care can also provide opportunities to increase vaccination rates among non-birthing partners/co-parents.
Methods: We administered an anonymous survey to outpatient prenatal care providers, including Obstetricians, Family Medicine physicians, Certified Nurse Midwives, and Nurse Practitioners, to assess practice patterns and opinions regarding vaccine counseling and in-office vaccination for the non-birthing partners of pregnant patients.
Results: Of the 200 obstetric providers surveyed, 112 responded (56%). Of these, 42% (n=77) reported counseling non-birthing partners on vaccine recommendations less than half the time. Only 4% (n=4) of respondents report vaccinating non-birthing partners who are not already patients in their practice. Nearly half of providers who do not offer non-birthing partner vaccination had never considered the practice (46%, n=44). The majority of respondents desired more education on non-birthing partner vaccination (58%, n=55). Respondents identified multiple implementation barriers to vaccinating non-birthing partners, including difficulties with registration, staffing, and time constraints. If barriers were addressed, 68% (n=65) of providers expressed willingness to incorporate non-birthing partner vaccination into their practice.
Conclusions: This study demonstrates willingness of key stakeholders to incorporate non-birthing partner vaccination into prenatal care, a unique mechanism to increase parental vaccination rates and protect neonates from vaccine-preventable illness.No embarg
A novel NLP-based method and algorithm to discover RNA-binding protein (RBP) motifs, contexts, binding preferences, and interactions [preprint]
No full textThis article is a preprint. Preprints are preliminary reports of work that have not been certified by peer review.RNA-binding proteins (RBPs) are essential modulators in the regulation of mRNA processing. The binding patterns, interactions, and functions of most RBPs are not well-characterized. Previous studies have shown that motif context is an important contributor to RBP binding specificity, but its precise role remains unclear. Despite recent computational advances to predict RBP binding, existing methods are challenging to interpret and largely lack a categorical focus on RBP motif contexts and RBP-RBP interactions. There remains a need for interpretable predictive models to disambiguate the contextual determinants of RBP binding specificity . Here, we present a novel and comprehensive pipeline to address these knowledge gaps. We devise a Natural Language Processing-based decomposition method to deconstruct sequences into entities consisting of a central target -mer and its flanking regions, then use this representation to formulate the RBP binding prediction task as a weakly supervised Multiple Instance Learning problem. To interpret our predictions, we introduce a deterministic motif discovery algorithm designed to handle our data structure, recapitulating the established motifs of numerous RBPs as validation. Importantly, we characterize the binding motifs and binding contexts for 71 RBPs, with many of them being novel. Finally, through feature integration, transitive inference, and a new cross-prediction approach, we propose novel cooperative and competitive RBP-RBP interaction partners and hypothesize their potential regulatory functions. In summary, we present a complete computational strategy for investigating the contextual determinants of specific RBP binding, and we demonstrate the significance of our findings in delineating RBP binding patterns, interactions, and functions
iSPARC 2025 Annual Report to the Massachusetts Department of Mental Health
Get PDFIn fiscal year 2025, iSPARC continued to leverage the Massachusetts Department of Mental Health's (DMH) investment to rapidly translate research findings into their implementation within best practices for individuals with lived experience, their families, and the providers who serve them across the Commonwealth. This report highlights iSPARC’s achievements for FY 2025. We begin by describing Technical Assistance to DMH and its contracted providers, collaborations with DMH, with other entities in the Commonwealth, and with other state organizations. We then describe our achievements in Public Mental Health and Implementation Research that span the nation. Finally, we highlight the specific programs and ways in which the DMH contract supports these activities and our overall organizational structure.No embarg
Staff perspectives on implementing dialectical behavior therapy skills groups in the Veterans Health Administration
No full textReducing veteran suicide is a high priority for the Veterans Health Administration (VHA). While dialectical behavior therapy skills groups (DBT-SG) may be as effective as comprehensive DBT in reducing suicide attempt, barriers and facilitators to this innovation in VHA are not well known. In preparation for a hybrid Type 1 effectiveness-implementation trial, we conducted individual semistructured qualitative interviews with 35 VHA staff (therapists, suicide prevention coordinators, local and national leaders) and identified themes using rapid qualitative analysis (Hamilton, 2013). Five themes emerged: (a) While leadership noted wanting innovative suicide prevention, (b) knowledge of DBT varied widely across respondents. (c) Implementation challenges, especially after COVID-19, included staff shortage and burnout. (d) DBT-SG may require adaptation to fit the diversity of the veteran population, including Indigenous, homeless, and urban veterans, and (e) virtual DBT-SG options hold promise for expanding reach and access and must be implemented with appropriate risk management. Enthusiasm for DBT-SG was high, and implementation challenges in a stressed health care system were noted. DBT-SG, especially delivered virtually, holds promise for VHA and will need to be implemented with attention to staffing, provider needs, and veteran diversity. (PsycInfo Database Record (c) 2025 APA, all rights reserved).No embarg
Non-conscious detection of ST-segment elevation during physician ECG interpretation
No full textObjective: To investigate errors in the assessment of ST-elevation (STEs) myocardial infarctions on ECGs to determine if non-conscious processes successfully detect missed STEs, as evidenced by changes in how long and often physicians look at leads with STEs.
Materials and method: Eight experienced physicians interpreted 90 ECGs (45 STEs, 45 Normal) while eye movements were recorded. Physicians marked consciously recognized or considered STEs. No clinical context was provided.
Results: Physicians missed 18% of STEs. Eye-tracking showed longer (P = 0.02), more frequent (P = 0.02), and increased transitions (P = 0.02) to "missed" STE leads compared to Normal ECG leads.
Discussion: Non-conscious detection of STEs, including inter‑lead relationships, despite a lack of conscious recognition, suggests a sophisticated mechanism of wholistic detection, including culprit lesion sites by non-conscious processes.
Conclusion: Non-conscious detection of STEs supports non-conscious detection processing in medicine leading to more success than can be tracked by conscious report. Eye-tracking could enhance ECG interpretation and reduce diagnostic errors.No embarg
Differential tractography: an imaging marker for tissue degeneration in neurodegenerative diseases
No full textGM1 gangliosidosis is an ultra-rare inherited neurodegenerative lysosomal storage disorder caused by biallelic mutations in the gene. GM1 is uniformly fatal and has no approved therapies, although clinical trials investigating gene therapy as a potential treatment for this condition are underway. Novel outcome measures or markers demonstrating the longitudinal effects of GM1 and potential recovery due to therapeutic intervention are urgently needed to establish efficacy of potential therapeutics. One promising tool is differential tractography, a novel imaging modality utilizing serial diffusion tensor imaging to quantify longitudinal changes in white matter microstructure. In this study, we present the novel use of differential tractography in quantifying the progression of GM1 alongside age-matched neurotypical controls. We analysed 113 diffusion tensor imaging scans from 16 GM1 patients and 32 age-matched neurotypical controls to investigate longitudinal changes in white matter pathology. GM1 patients showed white matter degradation evident by both the number and size of fibre tract loss. In contrast, neurotypical controls showed longitudinal white matter improvements as evident by both the number and size of fibre tract growth. We also corroborated these findings by documenting significant correlations between clinical global impression scores of clinical presentations and our differential tractography derived metrics in our GM1 cohort. Specifically, GM1 patients who lost more neuronal fibre tracts also had a worse clinical presentation. This result demonstrates the utility of differential tractography as a marker for disease progression in GM1 patients with potential extension to other neurodegenerative diseases and therapeutic intervention.No embarg
Multiclass Arrhythmia Classification using Multimodal Smartwatch Photoplethysmography Signals Collected in Real-life Settings
No full textObjective: Smartwatches with photoplethysmographic (PPG) sensors are ideal for early atrial fibrillation (AF) detection through continuous monitoring. However, prior deep learning was limited either to controlled environments, to minimize motion artifacts, or to short duration data collection. Additionally, premature atrial/ventricular contractions (PAC/PVC), which often confound AF detection algorithms, remains understudied due to limited datasets. Current state-of-the-art methods achieve only 75% sensitivity for PAC/PVC class on minimally motion artifact corrupted PPG data, despite showing 97% AF detection accuracy.
Methods: We addressed the above limitations using data from the recently completed NIH-funded Pulsewatch clinical trial which collected over two weeks of smartwatch PPG data from 106 subjects. Our computationally efficient 1D bi-directional Gated Recurrent Unit deep learning model incorporated multi-modal inputs (1D PPG, accelerometer, and heart rate data) to classify normal sinus rhythm, AF, and PAC/PVC.
Results: Our model achieved an unprecedented 83% sensitivity for PAC/PVC detection while maintaining a high accuracy of 97.31% for AF detection, outperforming the best retrained state-of-the-art model by 20.81% and 2.55%, respectively. It was also 14 times more computationally efficient and 2.7 times faster. Testing on two external PPG datasets collected with a different smartwatch and a fingertip PPG sensor, our model demonstrated better generalizability with macro-averaged AUROC values of 96.22% and 94.17%, respectively.
Conclusion: A light-weight multimodal input deep learning model can accurately distinguish PAC/PVC from AF, reducing false positive detection of AF.
Significance: Accurate AF and PAC/PVC detection with minimal false positive detection can enhance clinical and public acceptance of smartwatch-based AF monitoring.No embarg