HIP: a method for high-dimensional multi-view data integration and prediction accounting for subgroup heterogeneity.

Epidemiologic and genetic studies in many complex diseases suggest subgroup disparities (e.g. by sex, race) in disease course and patient outcomes. We consider this from the standpoint of integrative analysis where we combine information from different views (e.g. genomics, proteomics, clinical data). Existing integrative analysis methods ignore the heterogeneity in subgroups, and stacking the views and accounting for subgroup heterogeneity does not model the association among the views. We propose Heterogeneity in Integration and Prediction (HIP), a statistical approach for joint association and prediction that leverages the strengths in each view to identify molecular signatures that are shared by and specific to a subgroup. We apply HIP to proteomics and gene expression data pertaining to chronic obstructive pulmonary disease (COPD) to identify proteins and genes shared by, and unique to, males and females, contributing to the variation in COPD, measured by airway wall thickness. Our COPD findings have identified proteins, genes, and pathways that are common across and specific to males and females, some implicated in COPD, while others could lead to new insights into sex differences in COPD mechanisms. HIP accounts for subgroup heterogeneity in multi-view data, ranks variables based on importance, is applicable to univariate or multivariate continuous outcomes, and incorporates covariate adjustment. With the efficient algorithms implemented using PyTorch, this method has many potential scientific applications and could enhance multiomics research in health disparities. HIP is available at https://github.com/lasandrall/HIP, a video tutorial at https://youtu.be/O6E2OLmeMDo and a Shiny Application at https://multi-viewlearn.shinyapps.io/HIP_ShinyApp/ for users with limited programming experience.

Parental Emotion Socialization of Sadness as a Correlate for Clinical Improvement: A Longitudinal Study of Adolescents with a Range of Nonsuicidal Self-Injury.

Engagement in nonsuicidal self-injury (NSSI) often begins in adolescence, and commonly occurs when a person is emotionally dysregulated. Parental emotion socialization (ES) plays a key role in shaping children's emotional expression, experience, and regulation. Longitudinal work is needed to understand how links between parental ES and adolescent clinical outcomes unfold over time. In this longitudinal study (N = 118; all assigned female at birth with a range of NSSI - from none to severe; age 12-17 years, Mage = 14.98 at the first assessment), for the Time 1 (T1) and Time 2 (T2) annual assessments; adolescents reported NSSI and adolescents and parents reported depressive symptoms. Parents (primarily mothers) reported on their supportive and unsupportive ES responses to youth expressions of sadness, anger, and happiness. We examined (1) concurrent relationships across time points, (2) longitudinal models (T1 to T2 change in parental ES and its associated T1 to T2 changes in adolescent clinical outcomes), and (3) prediction models (T1 parental ES predicting changes in adolescent clinical outcomes). Concurrent associations between parental supportive ES responses to sadness and anger were inversely related to adolescent's depressive symptoms and NSSI episodes. Longitudinal analyses showed that increases in unsupportive responses to sadness correspond with increases in depressive symptoms from T1 to T2. The findings underscore the importance of examining how parents respond to their children's emotions. Next steps are to investigate potential mechanisms of risk and consider interventions that enhance adaptive responses of parents to adolescents embroiled in negative emotional states.

Reducing thermal noise in high-resolution quantitative magnetic resonance imaging rotating frame relaxation mapping of the human brain at 3 T.

Quantitative maps of rotating frame relaxation (RFR) time constants are sensitive and useful magnetic resonance imaging tools with which to evaluate tissue integrity in vivo. However, to date, only moderate image resolutions of 1.6 x 1.6 x 3.6 mm3 have been used for whole-brain coverage RFR mapping in humans at 3 T. For more precise morphometrical examinations, higher spatial resolutions are desirable. Towards achieving the long-term goal of increasing the spatial resolution of RFR mapping without increasing scan times, we explore the use of the recently introduced Transform domain NOise Reduction with DIstribution Corrected principal component analysis (T-NORDIC) algorithm for thermal noise reduction. RFR acquisitions at 3 T were obtained from eight healthy participants (seven males and one female) aged 52 ± 20 years, including adiabatic T1ρ, T2ρ, and nonadiabatic Relaxation Along a Fictitious Field (RAFF) in the rotating frame of rank n = 4 (RAFF4) with both 1.6 x 1.6 x 3.6 mm3 and 1.25 x 1.25 x 2 mm3 image resolutions. We compared RFR values and their confidence intervals (CIs) obtained from fitting the denoised versus nondenoised images, at both voxel and regional levels separately for each resolution and RFR metric. The comparison of metrics obtained from denoised versus nondenoised images was performed with a two-sample paired t-test and statistical significance was set at p less than 0.05 after Bonferroni correction for multiple comparisons. The use of T-NORDIC on the RFR images prior to the fitting procedure decreases the uncertainty of parameter estimation (lower CIs) at both spatial resolutions. The effect was particularly prominent at high-spatial resolution for RAFF4. Moreover, T-NORDIC did not degrade map quality, and it had minimal impact on the RFR values. Denoising RFR images with T-NORDIC improves parameter estimation while preserving the image quality and accuracy of all RFR maps, ultimately enabling high-resolution RFR mapping in scan times that are suitable for clinical settings.

Prediction of tuberculosis clusters in the riverine municipalities of the Brazilian Amazon with machine learning.

OBJECTIVE: Tuberculosis (TB) is the second most deadly infectious disease globally, posing a significant burden in Brazil and its Amazonian region. This study focused on the "riverine municipalities" and hypothesizes the presence of TB clusters in the area. We also aimed to train a machine learning model to differentiate municipalities classified as hot spots vs. non-hot spots using disease surveillance variables as predictors. METHODS: Data regarding the incidence of TB from 2019 to 2022 in the riverine town was collected from the Brazilian Health Ministry Informatics Department. Moran's I was used to assess global spatial autocorrelation, while the Getis-Ord GI* method was employed to detect high and low-incidence clusters. A Random Forest machine-learning model was trained using surveillance variables related to TB cases to predict hot spots among non-hot spot municipalities. RESULTS: Our analysis revealed distinct geographical clusters with high and low TB incidence following a west-to-east distribution pattern. The Random Forest Classification model utilizes six surveillance variables to predict hot vs. non-hot spots. The machine learning model achieved an Area Under the Receiver Operator Curve (AUC-ROC) of 0.81. CONCLUSION: Municipalities with higher percentages of recurrent cases, deaths due to TB, antibiotic regimen changes, percentage of new cases, and cases with smoking history were the best predictors of hot spots. This prediction method can be leveraged to identify the municipalities at the highest risk of being hot spots for the disease, aiding policymakers with an evidenced-based tool to direct resource allocation for disease control in the riverine municipalities.

Deep transcranial magnetic stimulation for adolescents with treatment-resistant depression: A preliminary dose-finding study exploring safety and clinical effectiveness.

BACKGROUND: Transcranial magnetic stimulation (TMS) is an intervention for treatment-resistant depression (TRD) that modulates neural activity. Deep TMS (dTMS) can target not only cortical but also deeper limbic structures implicated in depression. Although TMS has demonstrated safety in adolescents, dTMS has yet to be applied to adolescent TRD. OBJECTIVE/HYPOTHESIS: This pilot study evaluated the safety, tolerability, and clinical effects of dTMS in adolescents with TRD. We hypothesized dTMS would be safe, tolerable, and efficacious for adolescent TRD. METHODS: 15 adolescents with TRD (Age, years: M = 16.4, SD = 1.42) completed a six-week daily dTMS protocol targeting the left dorsolateral prefrontal cortex (BrainsWay H1 coil, 30 sessions, 10 Hz, 3.6 s train duration, 20s inter-train interval, 55 trains; 1980 total pulses per session, 80 % to 120 % of motor threshold). Participants completed clinical, safety, and neurocognitive assessments before and after treatment. The primary outcome was depression symptom severity measured by the Children's Depression Rating Scale-Revised (CDRS-R). RESULTS: 14 out of 15 participants completed the dTMS treatments. One participant experienced a convulsive syncope; the other participants only experienced mild side effects (e.g., headaches). There were no serious adverse events and minimal to no change in cognitive performance. Depression symptom severity significantly improved pre- to post-treatment and decreased to a clinically significant degree after 10 treatment sessions. Six participants met criteria for treatment response. LIMITATIONS: Main limitations include a small sample size and open-label design. CONCLUSIONS: These findings provide preliminary evidence that dTMS may be tolerable and associated with clinical improvement in adolescent TRD.

Post-Implementation Outcomes of a Remote Patient Monitoring Program After Emergency Department Discharge.

To better communicate and improve post-visit outcomes, a remote patient monitoring (RPM) program was implemented for patients discharged from emergency departments (ED) across 10 hospitals. The solution was offered to patients at the time of ED discharge and staffed by a group of care coordinators to respond to questions/urgent needs. Of 107,477 consecutive patients offered RPM, 28,425 patients (26.4%) engaged with the program. Activated patients with RPM were less likely to return to the ED within 90 days of their index visit [19.8% compared to 23.6%, p<.001]. While activation rates were modest, we observed fewer return visits to the ED in patients using RPM, with a 16.2% lower hazard of returning in the next year. Future research is needed to understand methods to improve RPM activation, any causal effects of RPM activation on return ED visits, and external validation of these findings.

Prediction of tuberculosis clusters in the riverine municipalities of the Brazilian Amazon with machine learning / Predição de áreas de aglomeração de tuberculose nos municípios ribeirinhos da Amazônia brasileira com aprendizagem de máquina

ABSTRACT Objective: Tuberculosis (TB) is the second most deadly infectious disease globally, posing a significant burden in Brazil and its Amazonian region. This study focused on the "riverine municipalities" and hypothesizes the presence of TB clusters in the area. We also aimed to train a machine learning model to differentiate municipalities classified as hot spots vs. non-hot spots using disease surveillance variables as predictors. Methods: Data regarding the incidence of TB from 2019 to 2022 in the riverine town was collected from the Brazilian Health Ministry Informatics Department. Moran's I was used to assess global spatial autocorrelation, while the Getis-Ord GI* method was employed to detect high and low-incidence clusters. A Random Forest machine-learning model was trained using surveillance variables related to TB cases to predict hot spots among non-hot spot municipalities. Results: Our analysis revealed distinct geographical clusters with high and low TB incidence following a west-to-east distribution pattern. The Random Forest Classification model utilizes six surveillance variables to predict hot vs. non-hot spots. The machine learning model achieved an Area Under the Receiver Operator Curve (AUC-ROC) of 0.81. Conclusion: Municipalities with higher percentages of recurrent cases, deaths due to TB, antibiotic regimen changes, percentage of new cases, and cases with smoking history were the best predictors of hot spots. This prediction method can be leveraged to identify the municipalities at the highest risk of being hot spots for the disease, aiding policymakers with an evidenced-based tool to direct resource allocation for disease control in the riverine municipalities.

RESUMO Objetivo: A tuberculose (TB) é a segunda doença infecciosa que mais mata no mundo, representando um problema de saúde pública no Brasil, especialmente na região amazônica. Este estudo analisa a TB nos municípios ribeirinhos" com o objetivo de identificar aglomerados de alta incidência, também conhecidos como "hot spots". Posteriormente, utilizando aprendizagem de máquina, visamos prever estes aglomerados por meio de variáveis de vigilância epidemiológica. Assim buscamos auxiliar o ente público no combate à TB nesta região. Métodos: Dados da incidência de TB nos "municípios ribeirinhos" foram coletados entre os anos de 2019 e 2022 do Departamento de Informática do Ministério da Saúde. O índice de Moran foi utilizado para a determinação de autocorrelação espacial global, enquanto o método Getis-Ord GI* foi empregado para a autocorrelação espacial local. Variáveis referentes ao diagnóstico, tratamento e características socioeconômicas associadas aos casos foram utilizadas para a predição de aglomerados de alta incidência por meio de um modelo Random Forest. Resultados: Foram identificados aglomerados com alta incidência de TB a oeste e baixa incidência a leste. O total de seis variáveis de vigilância epidemiológica foi identificado como relevante para a predição. Nosso modelo Random Forest alcança uma área sob a curva da característica operacional do receptor (AUC-ROC) de 0,81. Conclusão: Municípios com altas porcentagens de casos recorrentes, mortes por TB, mudança do esquema de tratamento, casos novos e casos com história de tabagismo estão associados a aglomerados de alta incidência. Esperamos que este método de identificação de possíveis aglomerados de TB seja útil para o ente público no combate à doença na região.

Regional sex differences in neurochemical profiles of healthy mice measured by magnetic resonance spectroscopy at 9.4 tesla.

Objective: To determine sex differences in the neurochemical concentrations measured by in vivo proton magnetic resonance spectroscopy (1H MRS) of healthy mice on a genetic background commonly used for neurodegenerative disease models. Methods: 1H MRS data collected from wild type mice with C57BL/6 or related genetic backgrounds in seven prior studies were used in this retrospective analysis. To be included, data had to be collected at 9.4 tesla magnetic field using advanced 1H MRS protocols, with isoflurane anesthesia and similar animal handling protocols, and a similar number of datasets from male and female mice had to be available for the brain regions analyzed. Overall, 155 spectra from female mice and 166 spectra from male mice (321 in total), collected from six brain regions (brainstem, cerebellum, cortex, hippocampus, hypothalamus, and striatum) at various ages were included. Results: Concentrations of taurine, total creatine (creatine + phosphocreatine), ascorbate, glucose and glutamate were consistently higher in male vs. female mice in most brain regions. Striatum was an exception with similar total creatine in male and female mice. The sex difference pattern in the hypothalamus was notably different from other regions. Interaction between sex and age was significant for total creatine and taurine in the cerebellum and hippocampus. Conclusion: Sex differences in regional neurochemical levels are small but significant and age-dependent, with consistent male-female differences across most brain regions. The neuroendocrine region hypothalamus displays a different pattern of sex differences in neurochemical levels. Differences in energy metabolism and cellular density may underlie the differences, with higher metabolic rates in females and higher osmoregulatory and antioxidant capacity in males.

Population Pharmacokinetic Model of N-Acetylcysteine During Periods of Recurrent Hypoglycemia in Healthy Volunteers.

Recurrent hypoglycemia leads to impaired awareness of hypoglycemia where the blood glucose threshold that elicits the counterregulatory response is lowered. Hypoglycemia-induced oxidative stress is hypothesized to contribute to impaired awareness of hypoglycemia development and hypoglycemia-associated autonomic failure. Our group conducted a randomized, double-blinded, placebo-controlled, crossover study in healthy individuals undergoing experimentally induced recurrent hypoglycemia to evaluate the impact of intravenous N-acetylcysteine (NAC) during experimental hypoglycemia to preserve the counterregulatory response to subsequent hypoglycemia. The work presented herein aimed to characterize the NAC pharmacokinetics and its effects on oxidative stress. Whole blood and plasma samples were collected at specified time points during separate NAC and placebo infusions from 10 healthy volunteers. Samples were analyzed for NAC, cysteine, and glutathione (GSH) concentrations. A 2-compartment population NAC pharmacokinetic model was developed. Estimates for central compartment clearance and volume of distribution were 19.8 L/h, and 12.2 L, respectively, for a 70-kg person. Peripheral compartment clearance and volume of distribution estimates were 34.9 L/h and 13.1 L, respectively, for a 70-kg person. The PK parameters estimated here were different from those reported in the literature, suggesting a higher NAC clearance during hypoglycemic episodes. NAC leads to a significant increase in circulating cysteine concentration in a NAC concentration-dependent manner, suggesting rapid biotransformation. A transient decrease in plasma GSH was observed, supporting the hypothesis that NAC can act as a reducing agent displacing glutathione from the disulfide bond allowing for increased clearance and/or distribution of GSH.

Brain MRI detects early-stage alterations and disease progression in Friedreich ataxia.

Friedreich ataxia is a progressive neurodegenerative disorder characterized by cerebellar and spinal atrophy. However, studies to elucidate the longitudinal progression of the pathology in the brain are somewhat inconsistent and limited, especially for early-stage Friedreich ataxia. Using a multimodal neuroimaging protocol, combined with advanced analysis methods, we sought to identify macrostructural and microstructural alterations in the brain of patients with early-stage Friedreich ataxia to better understand its distribution patterns and progression. We enrolled 28 patients with Friedreich ataxia and 20 age- and gender-matched controls. Longitudinal clinical and imaging data were collected in the patients at baseline, 12, 24 and 36 months. Macrostructural differences were observed in patients with Friedreich ataxia, compared to controls, including lower volume of the cerebellar white matter (but not cerebellar grey matter), superior cerebellar peduncle, thalamus and brainstem structures, and higher volume of the fourth ventricle. Diffusion tensor imaging and fixel-based analysis metrics also showed microstructural differences in several brain regions, especially in the cerebellum and corticospinal tract. Over time, many of these macrostructural and microstructural alterations progressed, especially cerebellar grey and white matter volumes, and microstructure of the superior cerebellar peduncle, posterior limb of the internal capsule and superior corona radiata. In addition, linear regressions showed significant associations between many of those imaging metrics and clinical scales. This study provides evidence of early-stage macrostructural and microstructural alterations and of progression over time in the brain in Friedreich ataxia. Moreover, it allows to non-invasively map such brain alterations over a longer period (3 years) than any previous study, and identifies several brain regions with significant involvement in the disease progression besides the cerebellum. We show that fixel-based analysis of diffusion MRI data is particularly sensitive to longitudinal change in the cerebellar peduncles, as well as motor and sensory white matter tracts. In combination with other morphometric measures, they may therefore provide sensitive imaging biomarkers of disease progression for clinical trials.

Multiway sparse distance weighted discrimination.

Modern data often take the form of a multiway array. However, most classification methods are designed for vectors, i.e., 1-way arrays. Distance weighted discrimination (DWD) is a popular high-dimensional classification method that has been extended to the multiway context, with dramatic improvements in performance when data have multiway structure. However, the previous implementation of multiway DWD was restricted to classification of matrices, and did not account for sparsity. In this paper, we develop a general framework for multiway classification which is applicable to any number of dimensions and any degree of sparsity. We conducted extensive simulation studies, showing that our model is robust to the degree of sparsity and improves classification accuracy when the data have multiway structure. For our motivating application, magnetic resonance spectroscopy (MRS) was used to measure the abundance of several metabolites across multiple neurological regions and across multiple time points in a mouse model of Friedreich's ataxia, yielding a four-way data array. Our method reveals a robust and interpretable multi-region metabolomic signal that discriminates the groups of interest. We also successfully apply our method to gene expression time course data for multiple sclerosis treatment. An R implementation is available in the package MultiwayClassification at http://github.com/lockEF/MultiwayClassification.

Multimodal MRI improves diagnostic accuracy and sensitivity to longitudinal change in amyotrophic lateral sclerosis.

BACKGROUND: Recent advances in MRI acquisitions and image analysis have increased the utility of neuroimaging in understanding disease-related changes. In this work, we aim to demonstrate increased sensitivity to disease progression as well as improved diagnostic accuracy in Amyotrophic lateral sclerosis (ALS) with multimodal MRI of the brain and cervical spinal cord. METHODS: We acquired diffusion MRI data from the brain and cervical cord, and T1 data from the brain, of 20 participants with ALS and 20 healthy control participants. Ten ALS and 14 control participants, and 11 ALS and 13 control participants were re-scanned at 6-month and 12-month follow-ups respectively. We estimated cross-sectional differences and longitudinal changes in diffusion metrics, cortical thickness, and fixel-based microstructure measures, i.e. fiber density and fiber cross-section. RESULTS: We demonstrate improved disease diagnostic accuracy and sensitivity through multimodal analysis of brain and spinal cord metrics. The brain metrics also distinguished lower motor neuron-predominant ALS participants from control participants. Fiber density and cross-section provided the greatest sensitivity to longitudinal change. We demonstrate evidence of progression in a cohort of 11 participants with slowly progressive ALS, including in participants with very slow change in ALSFRS-R. More importantly, we demonstrate that longitudinal change is detectable at a six-month follow-up visit. We also report correlations between ALSFRS-R and the fiber density and cross-section metrics. CONCLUSIONS: Our findings suggest that multimodal MRI is useful in improving disease diagnosis, and fixel-based measures may serve as potential biomarkers of disease progression in ALS clinical trials.

ALS is a disease affecting the brain and spinal cord which leads to weakness and muscle wasting. It is important to be able to measure disease-related changes whilst clinical trials are ongoing to assess whether the treatments being tested are working. We imaged the brain and spinal cord of people with and without ALS at 3 time points over a year. We found changes in the brain and spine over time. This study demonstrates that brain imaging could be potentially used to assess changes in disease progression during clinical trials, giving an indication of whether the treatments being tested are having an effect.

Antisense Oligonucleotide Silencing Reverses Abnormal Neurochemistry in Spinocerebellar Ataxia 3 Mice.

OBJECTIVE: Spinocerebellar ataxia type 3 (SCA3) is the most common dominantly inherited ataxia, and biomarkers are needed to noninvasively monitor disease progression and treatment response. Anti-ATXN3 antisense oligonucleotide (ASO) treatment has been shown to mitigate neuropathology and rescue motor phenotypes in SCA3 mice. Here, we investigated whether repeated ASO administration reverses brainstem and cerebellar neurochemical abnormalities by magnetic resonance spectroscopy (MRS). METHODS: Symptomatic SCA3 mice received intracerebroventricular treatment of ASO or vehicle and were compared to wild-type vehicle-treated littermates. To quantify neurochemical changes in treated mice, longitudinal 9.4T MRS of cerebellum and brainstem was performed. Acquired magnetic resonance (MR) group means were analyzed by 2-way analysis of variance mixed-effects sex-adjusted analysis with post hoc Sidak correlation for multiple comparisons. Pearson correlations were used to relate SCA3 pathology and behavior. RESULTS: MR spectra yielded 15 to 16 neurochemical concentrations in the cerebellum and brainstem. ASO treatment in SCA3 mice resulted in significant total choline rescue and partial reversals of taurine, glutamine, and total N-acetylaspartate across both regions. Some ASO-rescued neurochemicals correlated with reduction in diseased protein and nuclear ATXN3 accumulation. ASO-corrected motor activity correlated with total choline and total N-acetylaspartate levels early in disease. INTERPRETATION: SCA3 mouse cerebellar and brainstem neurochemical trends parallel those in patients with SCA3. Decreased total choline may reflect oligodendrocyte abnormalities, decreased total N-acetylaspartate highlights neuronal health disturbances, and high glutamine may indicate gliosis. ASO treatment fully or partially reversed select neurochemical abnormalities in SCA3 mice, indicating the potential for these measures to serve as noninvasive treatment biomarkers in future SCA3 gene silencing trials. ANN NEUROL 2023;94:658-671.

Scyllo-inositol: Transverse relaxation time constant at 3 T and concentration changes associated with aging and alcohol use.

The goals of this study were to measure the apparent transverse relaxation time constant, T2 , of scyllo-inositol (sIns) in young and older healthy adults' brains and to investigate the effect of alcohol usage on sIns in young and older healthy adults' brains, using proton magnetic resonance spectroscopy (MRS) at 3 T. Twenty-nine young adults (age 21 ± 1 years) and 24 older adults (age 74 ± 3 years) participated in this study. MRS data were acquired from two brain regions (the occipital cortex and posterior cingulate cortex) at 3 T. The T2 of sIns was measured using a localization by adiabatic selective refocusing (LASER) sequence at various echo times, while the sIns concentrations were measured using a short-echo-time stimulated echo acquisition mode (STEAM) sequence. A trend towards lower T2 relaxation values of sIns in older adults was observed, although these were not significant. sIns concentration was higher with age in both brain regions and was significantly higher in the young when considering alcohol consumption of more than two drinks per week. This study shows that differences in sIns can be found in two distinct regions of the brain across two age groups, potentially reflecting normal aging. In addition, it is important to take into account alcohol consumption when reporting the sIns level in the brain.

Neurochemical correlates of synapse density in a Huntington's disease mouse model.

Striatal medium spiny neurons are highly susceptible in Huntington's disease (HD), resulting in progressive synaptic perturbations that lead to neuronal dysfunction and death. Non-invasive imaging techniques, such as proton magnetic resonance spectroscopy (1 H-MRS), are used in HD mouse models and patients with HD to monitor neurochemical changes associated with neuronal health. However, the association between brain neurochemical alterations and synaptic dysregulation remains unknown, limiting our ability to monitor potential treatments that may affect synapse function. We conducted in vivo longitudinal 1 H-MRS in the striatum followed by ex vivo analyses of excitatory synapse density of two synaptic circuits disrupted in HD, thalamo-striatal (T-S), and cortico-striatal (C-S) pathways, to assess the relationship between neurochemical alterations and changes in synapse density. We used the zQ175(Tg/0) HD mouse model as well as zQ175 mice lacking one allele of CK2α'(zQ175(Tg/0) :CK2α'(+/-) ), a kinase previously shown to regulate synapse function in HD. Longitudinal analyses of excitatory synapse density showed early and sustained reduction in T-S synapses in zQ175 mice, preceding C-S synapse depletion, which was rescued in zQ175:CK2α'(+/-) . Changes in T-S and C-S synapses were accompanied by progressive alterations in numerous neurochemicals between WT and HD mice. Linear regression analyses showed C-S synapse number positively correlated with 1 H-MRS-measured levels of GABA, while T-S synapse number positively correlated with levels of phosphoethanolamine and negatively correlated with total creatine levels. These associations suggest that these neurochemical concentrations measured by 1 H-MRS may facilitate monitoring circuit-specific synaptic dysfunction in the zQ175 mouse model and in other HD pre-clinical studies.

Hypoxia within subcutaneously implanted macroencapsulation devices limits the viability and functionality of densely loaded islets.

Introduction: Subcutaneous macroencapsulation devices circumvent disadvantages of intraportal islet therapy. However, a curative dose of islets within reasonably sized devices requires dense cell packing. We measured internal PO2 of implanted devices, mathematically modeled oxygen availability within devices and tested the predictions with implanted devices containing densely packed human islets. Methods: Partial pressure of oxygen (PO2) within implanted empty devices was measured by noninvasive 19F-MRS. A mathematical model was constructed, predicting internal PO2, viability and functionality of densely packed islets as a function of external PO2. Finally, viability was measured by oxygen consumption rate (OCR) in day 7 explants loaded at various islet densities. Results: In empty devices, PO2 was 12 mmHg or lower, despite successful external vascularization. Devices loaded with human islets implanted for 7 days, then explanted and assessed by OCR confirmed trends proffered by the model but viability was substantially lower than predicted. Co-localization of insulin and caspase-3 immunostaining suggested that apoptosis contributed to loss of beta cells. Discussion: Measured PO2 within empty devices declined during the first few days post-transplant then modestly increased with neovascularization around the device. Viability of islets is inversely related to islet density within devices.

Altered brain responses to noxious dentoalveolar stimuli in high-impact temporomandibular disorder pain patients.

High-impact temporomandibular disorder (TMD) pain may involve brain mechanisms related to maladaptive central pain modulation. We investigated brain responses to stimulation of trigeminal sites not typically associated with TMD pain by applying noxious dentoalveolar pressure to high- and low-impact TMD pain cases and pain-free controls during functional magnetic resonance imaging (fMRI). Fifty female participants were recruited and assigned to one of three groups based on the Diagnostic Criteria for Temporomandibular Disorders (DC/TMD) and Graded Chronic Pain Scale: controls (n = 17), low-impact (n = 17) and high-impact TMD (n = 16). Multimodal whole-brain MRI was acquired following the Human Connectome Project Lifespan protocol, including stimulus-evoked fMRI scans during which painful dentoalveolar pressure was applied to the buccal gingiva of participants. Group analyses were performed using non-parametric permutation tests for parcellated cortical and subcortical neuroimaging data. There were no significant between-group differences for brain activations/deactivations evoked by the noxious dentoalveolar pressure. For individual group mean activations/deactivations, a gradient in the number of parcels surviving thresholding was found according to the TMD pain grade, with the highest number seen in the high-impact group. Among the brain regions activated in chronic TMD pain groups were those previously implicated in sensory-discriminative and motivational-affective pain processing. These results suggest that dentoalveolar pressure pain evokes abnormal brain responses to sensory processing of noxious stimuli in high-impact TMD pain participants, which supports the presence of maladaptive brain plasticity in chronic TMD pain.

Spinal cord magnetic resonance imaging and spectroscopy detect early-stage alterations and disease progression in Friedreich ataxia.

Friedreich ataxia is the most common hereditary ataxia. Atrophy of the spinal cord is one of the hallmarks of the disease. MRI and magnetic resonance spectroscopy are powerful and non-invasive tools to investigate pathological changes in the spinal cord. A handful of studies have reported cross-sectional alterations in Friedreich ataxia using MRI and diffusion MRI. However, to our knowledge no longitudinal MRI, diffusion MRI or MRS results have been reported in the spinal cord. Here, we investigated early-stage cross-sectional alterations and longitudinal changes in the cervical spinal cord in Friedreich ataxia, using a multimodal magnetic resonance protocol comprising morphometric (anatomical MRI), microstructural (diffusion MRI), and neurochemical (1H-MRS) assessments.We enrolled 28 early-stage individuals with Friedreich ataxia and 20 age- and gender-matched controls (cross-sectional study). Disease duration at baseline was 5.5 ± 4.0 years and Friedreich Ataxia Rating Scale total neurological score at baseline was 42.7 ± 13.6. Twenty-one Friedreich ataxia participants returned for 1-year follow-up, and 19 of those for 2-year follow-up (cohort study). Each visit consisted in clinical assessments and magnetic resonance scans. Controls were scanned at baseline only. At baseline, individuals with Friedreich ataxia had significantly lower spinal cord cross-sectional area (-31%, P = 8 × 10-17), higher eccentricity (+10%, P = 5 × 10-7), lower total N-acetyl-aspartate (tNAA) (-36%, P = 6 × 10-9) and higher myo-inositol (mIns) (+37%, P = 2 × 10-6) corresponding to a lower ratio tNAA/mIns (-52%, P = 2 × 10-13), lower fractional anisotropy (-24%, P = 10-9), as well as higher radial diffusivity (+56%, P = 2 × 10-9), mean diffusivity (+35%, P = 10-8) and axial diffusivity (+17%, P = 4 × 10-5) relative to controls. Longitudinally, spinal cord cross-sectional area decreased by 2.4% per year relative to baseline (P = 4 × 10-4), the ratio tNAA/mIns decreased by 5.8% per year (P = 0.03), and fractional anisotropy showed a trend to decrease (-3.2% per year, P = 0.08). Spinal cord cross-sectional area correlated strongly with clinical measures, with the strongest correlation coefficients found between cross-sectional area and Scale for the Assessment and Rating of Ataxia (R = -0.55, P = 7 × 10-6) and between cross-sectional area and Friedreich ataxia Rating Scale total neurological score (R = -0.60, P = 4 × 10-7). Less strong but still significant correlations were found for fractional anisotropy and tNAA/mIns. We report here the first quantitative longitudinal magnetic resonance results in the spinal cord in Friedreich ataxia. The largest longitudinal effect size was found for spinal cord cross-sectional area, followed by tNAA/mIns and fractional anisotropy. Our results provide direct evidence that abnormalities in the spinal cord result not solely from hypoplasia, but also from neurodegeneration, and show that disease progression can be monitored non-invasively in the spinal cord.

Corrigendum: Assessment of cerebral and cerebellar white matter microstructure in spinocerebellar ataxias 1, 2, 3, and 6 using diffusion MRI.

[This corrects the article DOI: 10.3389/fneur.2020.00411.].

Relationship Between Hypoglycemia Awareness Status on Clarke/Gold Methods and Counterregulatory Response to Hypoglycemia.

Context: Impaired awareness of hypoglycemia (IAH) is characterized by the diminished ability to perceive symptoms of hypoglycemia. Gold and Clark questionnaires are commonly used to identify patients with IAH. The relationship between IAH status on questionnaires and a person's symptom and epinephrine responses to hypoglycemia are not well understood. Objective: We aimed to examine the relationship between hypoglycemia awareness status on Clarke and Gold questionnaires with both hormonal and symptomatic responses to experimental hypoglycemia. Methods: In this university medical center study, we examined data from 78 subjects with type 1 diabetes (T1D) who completed both questionnaires and underwent a hyperinsulinemic hypoglycemic clamp (target glucose 50 mg/dL). Results: Clarke and Gold scores were highly correlated with one another (r = 0.82) and each had a moderate negative relationship with epinephrine (Clarke: r = -0.51, Gold: r = -0.50) and total symptom response (Clarke: r = -0.59, Gold: r = -0.57). However, 32% of the subjects were classified inconsistently by Clark vs Gold. A clustering analysis was done to examine how disagreement between the 2 questionnaires on IAH classification relates to epinephrine and symptoms responses during hypoglycemia. Subjects who had partial loss of symptoms or of epinephrine response were more likely to be classified inconsistently. Conclusion: Our results show that IAH classification may be discordant between Clark and Gold questionnaires and that hypoglycemia awareness status on Clarke and Gold questionnaires poorly predicts hormonal and symptomatic responses to hypoglycemia in subjects with T1D and moderate blunting of symptoms or epinephrine.