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Abstract Background A clear understanding of public perceptions of the social determinants of health remains lacking. This paper aimed to describe the relationship between income and urbanicity levels and public views of the determinants of health in eight middle-and high-income countries that varied across multiple characteristics. Methods We conducted a cross-sectional online survey in Brazil, China, Germany, Egypt, India, Indonesia, Nigeria, and the United States. Respondents were asked to select what they considered to be most important for health out of a list of ten determinants. We stratified the results by income and urbanicity levels and tested significance of differences between groups using two-tailed χ2 tests. Multivariable logistic regression models tested associations between demographic factors and the likelihood of respondents selecting the genetics, healthcare, income and wealth, or social support determinants. Results Here we show 8753 respondents across eight countries. Rankings of determinants are similar across income groups, except for two determinants. Respondents in the highest income group rank genetics in higher proportions (32.4%, 95%CI: 29.0%,35.8%) compared to other income groups. Conversely, those in lowest income group rank social support more frequently (27.9%, 95%CI: 25.3%,30.7%) than other income groups. Those living in urban settings rank healthcare in higher proportions (61.2%, 95%CI: 59.0%,63.4%) compared to non-urban respondents; meanwhile, higher proportions (26.6%, 95%CI: 24.9%,28.3%) of non-urban respondents rank social support as important for health compared to urban respondents. Conclusion Demographic factors play a role in shaping public views of what affects health. Advancing public understanding about determinants of health requires tailoring public health messaging to account for socioeconomic position within a population.

Abstract Friedreich’s ataxia is a degenerative and progressive multisystem disorder caused by mutations in the highly conserved frataxin (FXN) gene that results in FXN protein deficiency and mitochondrial dysfunction. While gene therapy approaches are promising, consistent induction of therapeutic FXN protein expression that is sub-toxic has proven challenging, and numerous therapeutic approaches are being tested in animal models. FXN (hFXN in humans, mFXN in mice) is proteolytically modified in mitochondria to produce mature FXN. However, unlike endogenous hFXN, endogenous mFXN is further processed into N-terminally truncated, extra-mitochondrial mFXN forms of unknown function. This study assessed mature exogenous hFXN expression levels in the heart and liver of C57Bl/6 mice 7–10 months after intravenous administration of a recombinant adeno-associated virus encoding hFXN (AAVrh.10hFXN) and examined the potential for hFXN truncation in mice. AAVrh.10hFXN induced dose-dependent expression of hFXN in the heart and liver. Interestingly, hFXN was processed into truncated forms, but found at lower levels than mature hFXN. However, the truncations were at different positions than mFXN. AAVrh.10hFXN induced mature hFXN expression in mouse heart and liver at levels that approximated endogenous mFXN levels. These results suggest that AAVrh.10hFXN can likely induce expression of therapeutic levels of mature hFXN in mice.

Abstract Substantial literature documents the impact of mass traumatic events on post-traumatic stress disorder (PTSD) in populations. However, the trajectory of PTSD in the US population during the pandemic and the association between assets, Covid-19 related stressors, and PTSD over time remains unclear. The Covid-19 and Life Stressors Impact on Mental Health and Well-Being (CLIMB) is a nationally representative, longitudinal panel of US adults in Spring 2020 (N = 1270), 2021 (N = 1182), and 2022 (N = 1091). Using the four-item PC-PTSD-4, we assessed the prevalence of probable PTSD in the US population over three years. Using generalized estimating equations (GEE) and logistic regression at each wave, we estimated associations of demographics, assets, and stressors with probable PTSD. Here we report that the overall prevalence of PTSD decreases from 22.2% in 2020 to 16.8% in 2022 (p = 0.02). Persons with household incomes below $20,000 report higher prevalence of probable PTSD compared to other income groups. The GEE model shows higher odds of probable PTSD among persons with household incomes below $20,000 (OR = 2.17 (95%CI: 1.35,3.50)) relative to $75,000 or more; and high stressor scores (OR = 2.33 (95%CI: 1.72,3.15)) compared to low stressor scores. High stressor scores are associated with higher odds of probable PTSD in 2020 (OR = 2.69 (95%CI: 1.56,4.66)), 2021 (OR = 4.58 (95%CI: 2.52,8.30)), and 2022 (OR = 3.89 (95%CI: 2.05,7.38)) compared to low stressor scores. This analysis highlights the pandemic’s prolonged influence on population mental health, particularly among persons with fewer economic assets and those experiencing more pandemic-related stressors. Reducing mental health disparities requires interventions to address inequities.

Abstract Our sense of hearing is mediated by cochlear hair cells, of which there are two types organized in one row of inner hair cells and three rows of outer hair cells. Each cochlea contains 5–15 thousand terminally differentiated hair cells, and their survival is essential for hearing as they do not regenerate after insult. It is often desirable in hearing research to quantify the number of hair cells within cochlear samples, in both pathological conditions, and in response to treatment. Machine learning can be used to automate the quantification process but requires a vast and diverse dataset for effective training. In this study, we present a large collection of annotated cochlear hair-cell datasets, labeled with commonly used hair-cell markers and imaged using various fluorescence microscopy techniques. The collection includes samples from mouse, rat, guinea pig, pig, primate, and human cochlear tissue, from normal conditions and following in-vivo and in-vitro ototoxic drug application. The dataset includes over 107,000 hair cells which have been identified and annotated as either inner or outer hair cells. This dataset is the result of a collaborative effort from multiple laboratories and has been carefully curated to represent a variety of imaging techniques. With suggested usage parameters and a well-described annotation procedure, this collection can facilitate the development of generalizable cochlear hair-cell detection models or serve as a starting point for fine-tuning models for other analysis tasks. By providing this dataset, we aim to give other hearing research groups the opportunity to develop their own tools with which to analyze cochlear imaging data more fully, accurately, and with greater ease.

Abstract Background Mutations in the NMDA receptor are known to disrupt glutamatergic signaling crucial for early neurodevelopment, often leading to severe global developmental delay/intellectual disability, epileptic encephalopathy, and cerebral palsy phenotypes. Both seizures and movement disorders can be highly treatment-refractory. Results We describe a targeted ABA n-of-1 treatment trial with intrathecal MgSO4, rationally designed based on the electrophysiologic properties of this gain of function mutation in the GRIN1 NMDA subunit. Conclusion Although the invasive nature of the trial necessitated a short-term, non-randomized, unblinded intervention, quantitative longitudinal neurophysiologic monitoring indicated benefit, providing class II evidence in support of intrathecal MgSO4 for select forms of GRIN disorders.

Abstract Introduction It is important to study apathy in Alzheimer's disease (AD) to better understand its underlying neurobiology and develop effective interventions. In the current study, we sought to examine the relationships between longitudinal apathy and regional tau burden in cognitively impaired older adults from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Methods Three hundred and nineteen ADNI participants with mild cognitive impairment (MCI) or AD dementia underwent flortaucipir (FTP) tau positron emission tomography (PET) imaging and clinical assessment with the Neuropsychiatric Inventory (NPI) annually. Longitudinal NPI Apathy (NPI‐A) scores were examined in relation to baseline tau PET signal in three a priori selected regions implicated in AD and AD‐related apathy (supramarginal gyrus, entorhinal cortex [EC] and rostral anterior cingulate cortex [rACC]). Secondary models were adjusted for global cognition (Mini‐Mental State Examination score) and cortical amyloid (florbetapir PET). Results Higher baseline supramarginal gyrus and EC tau burden were each significantly associated with greater NPI‐A over time, while rACC tau was associated with higher NPI‐A but did not predict its trajectory over time. These results were retained for supramarginal and EC tau after adjusting models for global cognition and cortical amyloid. Discussion Our findings suggest that baseline in vivo tau burden in parietal and temporal brain regions affected in AD, and less so in a medial frontal region involved in motivational control, is associated with increasing apathy over time in older adults with MCI and AD dementia. Future work studying emergent apathy in relation to not only core AD pathology but also circuit level dysfunction may provide additional insight into the neurobiology of apathy in AD and opportunities for intervention. Highlights Tau (Flortaucipir PET) in regions implicated in AD was associated with increasing apathy over time Cortical amyloid was also found to be a robust predictor of the trajectory of apathy Evidence of synergy between regional tau and amyloid in overall higher levels of apathy

Introduction: The social determinants of health (SDoH) shape both the risk of mental disorders and access to treatment. There is ample evidence detailing the decline in mental health during the Covid-19 pandemic. However, there is a gap in our understanding of the association between disruptions to SDoH and adverse psychological indicators in different contexts. Methods: Data were collected through a multi-country, random, anonymous, opt-in, cross-sectional online survey in eight geographically diverse countries—Brazil, China, Germany, Egypt, India, Indonesia, Nigeria, and the United States. We documented the relationship between experiencing self/family job loss, financial problems, and food/supplies shortages and adverse mental health indicators—depression symptoms and probable posttraumatic stress disorder (PTSD). Results: Almost one-third of respondents who experienced at least one disruption had depression symptoms (32.3%, 95% CI: 30.3%–34.4%). This was consistent across countries, except Indonesia. Reporting at least one Covid-19 related SDoH disruption had 1.26 (95% CI: 1.14-1.39) times the risk of depression symptoms compared to respondents reporting no Covid-19 related SDoH disruptions. Across countries, experiencing at least one Covid-19 related SDoH disruption had significantly increased risk of depression symptoms, except for China, Egypt, and Indonesia. The prevalence of probable PTSD among respondents who reported at least one SDoH disruption was 8.4% (95% CI: 7.3%–9.5%). The prevalence was comparably elevated within countries, except for China. Reporting at least one SDoH disruption was associated with greater odds of probable PTSD in the overall adjusted model (OR=2.87, 95% CI: 2.31-3.59) and in the models for countries except for China and Indonesia. Conclusion: Disruptions to SDoH due to the pandemic were associated with an elevated burden of symptoms of depression and probable PTSD across geographically diverse countries, with a few exceptions particularly in China. This highlights the need to account for the broader consequences of mitigation policies that potentially have an impact on the health of populations.

Deep brain stimulation has been investigated as a potential treatment for cognitive impairments in Alzheimer’s disease. Here the authors carry out post hoc analysis of multi-center cohorts to investigate the anatomical and functional correlates of effective deep brain stimulation, and find that stimulating circuit of Papez, fornix and bed nucleus of the stria terminalis, and a multi-region functional network, were associated with clinical improvement.

Abstract INTRODUCTION Methylphenidate has been shown to improve apathy in patients with Alzheimer's disease (AD). The authors evaluated the impact of methylphenidate on neuropsychiatric symptoms (NPS) of AD, excluding apathy, using data from the Apathy in Dementia Methylphenidate Trial 2 (ADMET 2) study. METHODS A secondary analysis was conducted on data from the ADMET 2 study to determine the effect of methylphenidate on Neuropsychiatric Inventory (NPI) scores outside of apathy. Caregiver scores were compared from baseline to month 6 in 199 participants receiving methylphenidate (20 mg/day) or placebo regarding the presence or absence of individual neuropsychiatric symptoms, emergence of new symptoms, and individual domain scores. RESULTS No clinically meaningful improvement was observed in any NPI domain, excluding apathy, in participants treated with methylphenidate compared to placebo after 6 months. A statistical difference between groups was appreciated in the domains of elation/euphoria (P = 0.044) and appetite/eating disorders (P = 0.014); however, these findings were not considered significant. DISCUSSION Methylphenidate is a selective agent for symptoms of apathy in patients with AD with no meaningful impact on other NPS. Findings from this secondary analysis are considered exploratory and multiple limitations should be considered when interpreting these results, including small sample size and use of a single questionnaire. HIGHLIGHTS Methylphenidate was not associated with significant improvement on the Neuropsychiatric Inventory in domains outside of apathy. Methylphenidate did not show a statistically significant emergence of new neuropsychiatric symptoms (NPS) throughout the 6‐month treatment period compared to placebo. Methylphenidate appears to be a highly selective agent for apathy in Alzheimer's disease, potentially supporting catecholaminergic dysfunction as the driving force behind this presentation of symptoms.

Our sense of hearing is mediated by sensory hair cells, precisely arranged and highly specialized cells subdivided into outer hair cells (OHCs) and inner hair cells (IHCs). Light microscopy tools allow for imaging of auditory hair cells along the full length of the cochlea, often yielding more data than feasible to manually analyze. Currently, there are no widely applicable tools for fast, unsupervised, unbiased, and comprehensive image analysis of auditory hair cells that work well either with imaging datasets containing an entire cochlea or smaller sampled regions. Here, we present a highly accurate machine learning-based hair cell analysis toolbox (HCAT) for the comprehensive analysis of whole cochleae (or smaller regions of interest) across light microscopy imaging modalities and species. The HCAT is a software that automates common image analysis tasks such as counting hair cells, classifying them by subtype (IHCs versus OHCs), determining their best frequency based on their location along the cochlea, and generating cochleograms. These automated tools remove a considerable barrier in cochlear image analysis, allowing for faster, unbiased, and more comprehensive data analysis practices. Furthermore, HCAT can serve as a template for deep learning-based detection tasks in other types of biological tissue: With some training data, HCAT's core codebase can be trained to develop a custom deep learning detection model for any object on an image.

Abstract Background The application of advanced imaging in pediatric research trials introduces the challenge of how to effectively handle and communicate incidental and reportable findings. This challenge is amplified in underserved populations that experience disparities in access to healthcare as recommendations for follow-up care may be difficult to coordinate. Therefore, the purpose of the present report is to describe the process for identifying and communicating findings from a research MRI to low-income Latino children and families. Methods Latino adolescents (n = 86) aged 12–16 years old with obesity and prediabetes underwent a research MRI (3 Tesla Philips Ingenia®) as part of a randomized controlled diabetes prevention trial. The research MRIs were performed at baseline and 6 months to assess changes in whole-abdominal fat distribution and organ fat in response to the intervention. An institutional pathway was developed for identifying and reporting findings to participants and families. The pathway was developed through a collaborative process with hospital administration, research compliance, radiology, and the research team. All research images were reviewed by a board-certified pediatric radiologist who conveyed findings to the study pediatrician for determination of clinical actionability and reportability to children and families. Pediatric sub-specialists were consulted as necessary and a primary care practitioner (PCP) from a free community health clinic agreed to receive referrals for uninsured participants. Results A total of 139 images (86 pre- and 53 post-intervention) were reviewed with 31 findings identified and 23 deemed clinically actionable and reportable. The only reportable finding was severely elevated liver fat (> 10%, n = 14) with the most common and concerning incidental findings being horseshoe kidney (n = 1) and lung lesion (n = 1). The remainder (n = 7) were less serious. Of youth with a reportable or incidental finding, 18 had a PCP but only 7 scheduled a follow-up appointment. Seven participants without a PCP were referred to a safety-net clinic for follow-up. Conclusions With the increased utilization of high-resolution imaging in pediatric research, additional standardization is needed on what, when, and how to return incidental and reportable findings to participants, particularly among historically underrepresented populations that may be underserved in the community. Trial registration Preventing Diabetes in Latino Youth, NCT02615353

The recent advances in creating pluripotent stem cells from somatic cells and differentiating them into a variety of cell types is allowing us to study them without the caveats associated with disease-related changes. We generated induced Pluripotent Stem Cells (iPSCs) from eight Alzheimer’s disease (AD) patients and six controls and used lentiviral delivery to differentiate them into excitatory glutamatergic neurons. We then performed RNA sequencing on these neurons and compared the Alzheimer’s and control transcriptomes. We found that 621 genes show differences in expression levels at adjusted p < 0.05 between the case and control derived neurons. These genes show significant overlap and directional concordance with genes reported from a single-cell transcriptome study of AD patients; they include five genes implicated in AD from genome-wide association studies and they appear to be part of a larger functional network as indicated by an excess of interactions between them observed in the protein–protein interaction database STRING. Exploratory analysis with Uniform Manifold Approximation and Projection (UMAP) suggests distinct clusters of patients, based on gene expression, who may be clinically different. Our research outcomes will enable the precise identification of distinct biological subtypes among individuals with Alzheimer’s disease, facilitating the implementation of tailored precision medicine strategies.

Abstract We performed a comprehensive analysis of the transcriptional changes occurring during human induced pluripotent stem cell (hiPSC) differentiation to cardiomyocytes. Using single cell RNA-seq, we sequenced > 20,000 single cells from 55 independent samples representing two differentiation protocols and multiple hiPSC lines. Samples included experimental replicates ranging from undifferentiated hiPSCs to mixed populations of cells at D90 post-differentiation. Differentiated cell populations clustered by time point, with differential expression analysis revealing markers of cardiomyocyte differentiation and maturation changing from D12 to D90. We next performed a complementary cluster-independent sparse regression analysis to identify and rank genes that best assigned cells to differentiation time points. The two highest ranked genes between D12 and D24 (MYH7 and MYH6) resulted in an accuracy of 0.84, and the three highest ranked genes between D24 and D90 (A2M, H19, IGF2) resulted in an accuracy of 0.94, revealing that low dimensional gene features can identify differentiation or maturation stages in differentiating cardiomyocytes. Expression levels of select genes were validated using RNA FISH. Finally, we interrogated differences in cardiac gene expression resulting from two differentiation protocols, experimental replicates, and three hiPSC lines in the WTC-11 background to identify sources of variation across these experimental variables.