Targeted and untargeted serum NMR metabolomics to reveal initial kidney disease in diabetes mellitus.

Serum 1H NMR metabolomics has been used as a diagnostic tool for screening type 2 diabetes (T2D) with chronic kidney disease (CKD) as comorbidity. This work aimed to evaluate 1H NMR data to detect the initial kidney damage and CKD in T2D subjects, through multivariate statistical analysis. Clinical data and biochemical parameters were obtained for classifying five experimental groups using KDIGO guidelines: Control (healthy subjects), T2D, T2D-CKD-mild, T2D-CKD-moderate, and T2D-CKD-severe. Serum 1H NMR spectra were recorded to follow two strategies: one based on metabolite-to-creatinine (Met/Cr) ratios as targeted metabolomics, and the second one based on untargeted metabolomics from the 1H NMR profile. A prospective biomarkers panel of the early stage of T2D-CKD based in metabolite-to-creatinine ratio (ornithine/Cr, serine/Cr, mannose/Cr, acetate/Cr, acetoacetate/Cr, formate/Cr, and glutamate/Cr) was proposed. Later, a statistical model based on non-targeted metabolomics was used to predict initial CKD, and its metabolic pathway analysis allowed identifying the most affected pathways: phenylalanine, tyrosine, and tryptophan biosynthesis; valine, leucine, and isoleucine degradation; glyoxylate and dicarboxylate metabolism; glycine, serine, and threonine metabolism; and histidine metabolism. Nonetheless, further studies with a larger cohort are advised to precise ranges in metabolite-to-creatinine ratios and evaluate the prediction pertinency to detect initial CKD in T2D patients in both statistical models proposed.

Volcanic soil gas 4He/CO2 ratio: a useful geochemical tool for real-time eruption forecasting.

At many dormant volcanoes, magmatic gases are not channeled through preferential degassing routes as fumaroles and only percolate through the flanks of the volcano in a diffuse way. This type of volcanic gas emission provides valuable information, even though the soil matrix contains an important atmospheric component. This study aimed to demonstrate that chemical ratios such as He/CO2 in soil gases provide excellent information on the evolution of volcanic unrest episodes and help forecast the volcanic eruption onset. Before and during the occurrence of the October 2011-March 2012 submarine of El Hierro, Canary Islands, more than 8500 soil He analyses and diffuse CO2 emission measurements were performed. The results show that the soil He/CO2 emission ratio began increasing drastically one month before eruption onset, reaching the maximum value 10 days before. During the eruptive period, this ratio also showed a maximum value several days before the period with the highest magma emission rate. The He/CO2 ratio was also helpful in forecasting the eruption onset. We demonstrate that this tool can be applied in real-time during volcanic emergencies. Our results also encourage a reevaluation of the global He emission from the subaerial volcanism.

Toward MR protocol-agnostic, unbiased brain age predicted from clinical-grade MRIs.

The difference between the estimated brain age and the chronological age ('brain-PAD') could become a clinical biomarker. However, most brain age models were developed for research-grade high-resolution T1-weighted MRIs, limiting their applicability to clinical-grade MRIs from various protocols. We adopted a dual-transfer learning strategy to develop a model agnostic to modality, resolution, or slice orientation. We retrained a convolutional neural network (CNN) using 6281 clinical MRIs from 1559 patients, among 7 modalities and 8 scanner models. The CNN was trained to estimate brain age from synthetic research-grade magnetization-prepared rapid gradient-echo MRIs (MPRAGEs) generated by a 'super-resolution' method. The model failed with T2-weighted Gradient-Echo MRIs. The mean absolute error (MAE) was 5.86-8.59 years across the other modalities, still higher than for research-grade MRIs, but comparable between actual and synthetic MPRAGEs for some modalities. We modeled the "regression bias" in brain age, for its correction is crucial for providing unbiased summary statistics of brain age or for personalized brain age-based biomarkers. The bias model was generalizable as its correction eliminated any correlation between brain-PAD and chronological age in new samples. Brain-PAD was reliable across modalities. We demonstrate the feasibility of brain age predictions from arbitrary clinical-grade MRIs, thereby contributing to personalized medicine.

Feasibility of brain age predictions from clinical T1-weighted MRIs.

An individual's brain predicted age minus chronological age (brain-PAD) obtained from MRIs could become a biomarker of disease in research studies. However, brain age reports from clinical MRIs are scant despite the rich clinical information hospitals provide. Since clinical MRI protocols are meant for specific clinical purposes, performance of brain age predictions on clinical data need to be tested. We explored the feasibility of using DeepBrainNet, a deep network previously trained on research-oriented MRIs, to predict the brain ages of 840 patients who visited 15 facilities of a health system in Florida. Anticipating a strong prediction bias in our clinical sample, we characterized it to propose a covariate model in group-level regressions of brain-PAD (recommended to avoid Type I, II errors), and tested its generalizability, a requirement for meaningful brain age predictions in new single clinical cases. The best bias-related covariate model was scanner-independent and linear in age, while the best method to estimate bias-free brain ages was the inverse of a scanner-independent and quadratic in brain age function. We demonstrated the feasibility to detect sex-related differences in brain-PAD using group-level regression accounting for the selected covariate model. These differences were preserved after bias correction. The Mean-Average Error (MAE) of the predictions in independent data was ∼8 years, 2-3 years greater than reports for research-oriented MRIs using DeepBrainNet, whereas an R2 (assuming no bias) was 0.33 and 0.76 for the uncorrected and corrected brain ages, respectively. DeepBrainNet on clinical populations seems feasible, but more accurate algorithms or transfer-learning retraining is needed.

Accelerated Brain Aging Mediates the Association Between Psychological Profiles and Clinical Pain in Knee Osteoarthritis.

Chronic pain is driven by factors across the biopsychosocial spectrum. Previously, we demonstrated that magnetic resonance images (MRI)-based brain-predicted age differences (brain-PAD: brain-predicted age minus chronological age) were significantly associated with pain severity in individuals with chronic knee pain. We also previously identified four distinct, replicable, multidimensional psychological profiles significantly associated with clinical pain. The brain aging-psychological characteristics interface in persons with chronic pain promises elucidating factors contributing to their poor health outcomes, yet this relationship is barely understood. That is why we examined the interplay between the psychological profiles in participants having chronic knee pain impacting function, brain-PAD, and clinical pain severity. Controlling for demographics and MRI scanner, we compared the brain-PAD among psychological profiles at baseline (n = 164) and over two years (n = 90). We also explored whether profile-related differences in pain severity were mediated by brain-PAD. Brain-PAD differed significantly between profiles (ANOVA's omnibus test, P = .039). Specifically, participants in the profile 3 group (high negative/low positive emotions) had an average brain-PAD ∼4 years higher than those in profile- (low somatic reactivity), with P = .047, Bonferroni-corrected, and than those in profile 2 (high coping), with P = .027, uncorrected. Repeated measures ANOVA revealed no significant change in profile-related brain-PAD differences over time, but there was a significant decrease in brain-PAD for profile 4 (high optimism/high positive affect), with P = .045. Moreover, profile-related differences in pain severity at baseline were partly explained by brain-PAD differences between profile 3 and 1, or 2; but brain-PAD did not significantly mediate the influence of variations in profiles on changes in pain severity over time. PERSPECTIVE: Accelerated brain aging could underlie the psychological-pain relationship, and psychological characteristics may predispose individuals with chronic knee pain to worse health outcomes via neuropsychological processes.

Brain-predicted age difference estimated using DeepBrainNet is significantly associated with pain and function-a multi-institutional and multiscanner study.

ABSTRACT: Brain age predicted differences (brain-PAD: predicted brain age minus chronological age) have been reported to be significantly larger for individuals with chronic pain compared with those without. However, a debate remains after one article showed no significant differences. Using Gaussian Process Regression, an article provides evidence that these negative results might owe to the use of mixed samples by reporting a differential effect of chronic pain on brain-PAD across pain types. However, some remaining methodological issues regarding training sample size and sex-specific effects should be tackled before settling this controversy. Here, we explored differences in brain-PAD between musculoskeletal pain types and controls using a novel convolutional neural network for predicting brain-PADs, ie, DeepBrainNet. Based on a very large, multi-institutional, and heterogeneous training sample and requiring less magnetic resonance imaging preprocessing than other methods for brain age prediction, DeepBrainNet offers robust and reproducible brain-PADs, possibly highly sensitive to neuropathology. Controlling for scanner-related variability, we used a large sample (n = 660) with different scanners, ages (19-83 years), and musculoskeletal pain types (chronic low back [CBP] and osteoarthritis [OA] pain). Irrespective of sex, brain-PAD of OA pain participants was ∼3 to 4.7 years higher than that of CBP and controls, whereas brain-PAD did not significantly differ among controls and CBP. Moreover, brain-PAD was significantly related to multiple variables underlying the multidimensional pain experience. This comprehensive work adds evidence of pain type-specific effects of chronic pain on brain age. This could help in the clarification of the debate around possible relationships between brain aging mechanisms and pain.

Diffuse CO2 degassing precursors of the January 2020 eruption of Taal volcano, Philippines.

On January 12, 2020, Taal volcano in Philippines erupted, 43 years after its previous eruption in 1977. This eruption was preceded by diffuse CO2 degassing precursory signals. Significant temporal variations in diffuse CO2 emission from Taal Main Crater Lake (TMLC) were observed across the ~ 12 years reaching high CO2 degassing rates in 2011 and 2017, with values typical of plume degassing volcanoes. In addition to these CO2 surveys at the TCML, soil CO2 efflux continuous monitoring was implemented at Taal volcano since 2016 and a clear increasing trend of the soil CO2 efflux in 2017 was observed. These geochemical observations are most simply explained by magma recharge to the system, and represent the earliest warning precursor signals to the January 2020 eruptive activity.

Cross-Sectional Brain-Predicted Age Differences in Community-Dwelling Middle-Aged and Older Adults with High Impact Knee Pain.

Purpose: Knee OA-related pain varies in impact across individuals and may relate to central nervous system alterations like accelerated brain aging processes. We previously reported that older adults with chronic musculoskeletal pain had a significantly greater brain-predicted age, compared to pain-free controls, indicating an "older" appearing brain. Yet this association is not well understood. This cross-sectional study examines brain-predicted age differences associated with chronic knee osteoarthritis pain, in a larger, more demographically diverse sample with consideration for pain's impact. Patients and Methods: Participants (mean age = 57.8 ± 8.0 years) with/without knee OA-related pain were classified according to pain's impact on daily function (ie, impact): low-impact (n=111), and high-impact (n=60) pain, and pain-free controls (n=31). Participants completed demographic, pain, and psychosocial assessments, and T1-weighted magnetic resonance imaging. Brain-predicted age difference (brain-PAD) was compared across groups using analysis of covariance. Partial correlations examined associations of brain-PAD with pain and psychosocial variables. Results: Individuals with high-impact chronic knee pain had significantly "older" brains for their age compared to individuals with low-impact knee pain (p < 0.05). Brain-PAD was also significantly associated with clinical pain, negative affect, passive coping, and pain catastrophizing (p's<0.05). Conclusion: Our findings suggest that high impact chronic knee pain is associated with an older appearing brain on MRI. Future studies are needed to determine the impact of pain-related interference and pain management on somatosensory processing and brain aging biomarkers for high-risk populations and effective intervention strategies.

Using nuclear magnetic resonance urine metabolomics to develop a prediction model of early stages of renal disease in subjects with type 2 diabetes.

Type 2 diabetes mellitus (DM2) is a multimorbidity, long-term condition, and one of the worldwide leading causes of chronic kidney disease (CKD) -a silent disease, usually detected when non-reversible renal damage have already occurred. New strategies and more effective laboratory methods are needed for more opportune diagnosis of DM2-CKD. This study comprises clinical parameters and nuclear magnetic resonance (NMR)-based urine metabolomics data from 60 individuals (20-65 years old, 67.7% females), sorted in 5 experimental groups (healthy subjects; diabetic patients without any clinical sign of CKD; and patients with mild, moderate, and severe DM2-CKD), according to KDIGO. DM2-CKD produces a continuous variation of the urine metabolome, characterized by an increase/decrement of a group of metabolites that can be used to monitor CKD progression (trigonelline, hippurate, phenylalanine, glycolate, dimethylamine, alanine, 2-hydroxybutyrate, lactate, and citrate). NMR profiles were used to obtain a statistical model, based on partial least squares analysis (PLS-DA) to discriminate among groups. The PLS-DA model yielded good validation parameters (sensitivity, specificity, and area under the curve (AUC) of the receiver operating characteristic curve (ROC) plot: 0.692, 0.778 and 0.912, respectively) and, thus, it can differentiate between subjects with DM2-CKD in early stages, from subjects with a mild or severe condition. This metabolic signature exhibits a molecular variation associated to DM2-CKD, and data suggests it can be used to predict risk of DM2-CKD in patients without clinical signs of renal disease, offering a new alternative to current diagnosis methods.

High-resolution Digital Surface Model of the 2021 eruption deposit of Cumbre Vieja volcano, La Palma, Spain.

Identifying accurate topographic variations associated with volcanic eruptions plays a key role in obtaining information on eruptive parameters, volcano structure, input data for volcano processes modelling, and civil protection and recovery actions. The 2021 eruption of Cumbre Vieja volcano is the largest eruptive event in the recorded history for La Palma Island. Over the course of almost 3 months, the volcano produced profound morphological changes in the landscape affecting both the natural and the anthropic environment over an area of tens of km2. We present the results of a UAS (Unoccupied Aircraft System) survey consisting of >12,000 photographs coupled with Structure-from-Motion photogrammetry that allowed us to produce a very-high-resolution (0.2 m/pixel) Digital Surface Model (DSM). We characterised the surface topography of the newly formed volcanic landforms and produced an elevation difference map by differencing our survey and a pre-event surface, identifying morphological changes in detail. The present DSM, the first one with such a high resolution to our knowledge, represents a relevant contribution to both the scientific community and the local authorities.

Experimental Pain Phenotype Profiles in Community-dwelling Older Adults.

OBJECTIVES: Pain sensitivity and the brain structure are critical in modulating pain and may contribute to the maintenance of pain in older adults. However, a paucity of evidence exists investigating the link between pain sensitivity and brain morphometry in older adults. The purpose of the study was to identify pain sensitivity profiles in healthy, community-dwelling older adults using a multimodal quantitative sensory testing protocol and to differentiate profiles based on brain morphometry. MATERIALS AND METHODS: This study was a secondary analysis of the Neuromodulatory Examination of Pain and Mobility Across the Lifespan (NEPAL) study. Participants completed demographic and psychological questionnaires, quantitative sensory testing, and a neuroimaging session. A Principal Component Analysis with Varimax rotation followed by hierarchical cluster analysis identified 4 pain sensitivity clusters (the "pain clusters"). RESULTS: Sixty-two older adults ranging from 60 to 94 years old without a specific pain condition (mean [SD] age=71.44 [6.69] y, 66.1% female) were analyzed. Four pain clusters were identified characterized by (1) thermal pain insensitivity; (2) high pinprick pain ratings and pressure pain insensitivity; (3) high thermal pain ratings and high temporal summation; and (4) thermal pain sensitivity, low thermal pain ratings, and low mechanical temporal summation. Sex differences were observed between pain clusters. Pain clusters 2 and 4 were distinguished by differences in the brain cortical volume in the parieto-occipital region. DISCUSSION: While sufficient evidence exists demonstrating pain sensitivity profiles in younger individuals and in those with chronic pain conditions, the finding that subgroups of experimental pain sensitivity also exist in healthy older adults is novel. Identifying these factors in older adults may help differentiate the underlying mechanisms contributing to pain and aging.

Chronic Musculoskeletal Pain Moderates the Association between Sleep Quality and Dorsostriatal-Sensorimotor Resting State Functional Connectivity in Community-Dwelling Older Adults.

Aging is associated with poor sleep quality and greater chronic pain prevalence, with age-related changes in brain function as potential underlying mechanisms. Objective. The following cross-sectional study aimed to determine whether self-reported chronic musculoskeletal pain in community-dwelling older adults moderates the association between sleep quality and resting state functional brain connectivity (rsFC). Methods. Community-dwelling older individuals (mean age = 73.29 years) part of the NEPAL study who completed the Pittsburg Sleep Quality Index (PSQI) and a rsFC scan were included (n = 48) in the present investigation. To that end, we tested the effect of chronic pain-by-PSQI interaction on rsFC among atlas-based brain regions-of-interest, controlling for age and sex. Results and Discussion. A significant network connecting the bilateral putamen and left caudate with bilateral precentral gyrus, postcentral gyrus, and juxtapositional lobule cortex, survived global multiple comparisons (FDR; q < 0.05) and threshold-free network-based-statistics. Greater PSQI scores were significantly associated with greater dorsostriatal-sensorimotor rsFC in the no-pain group, suggesting that a state of somatomotor hyperarousal may be associated with poorer sleep quality in this group. However, in the pain group, greater PSQI scores were associated with less dorsostriatal-sensorimotor rsFC, possibly due to a shift of striatal functions toward regulation sensorimotor aspects of the pain experience, and/or aberrant cortico-striatal loops in the presence of chronic pain. This preliminary investigation advances knowledge about the neurobiology underlying the associations between chronic pain and sleep in community-dwelling older adults that may contribute to the development of effective therapies to decrease disability in geriatric populations.

Asociación entre el hiperparatiroidismo secundario a la deficiencia de vitamina D en el embarazo y la frecuencia de preeclampsia / Association between hyperparathyroidism secondary to vitamin D deficiency in pregnancy and the frequency of preeclampsia

Resumen OBJETIVO: Establecer si existe asociación entre el hiperparatiroidismo secundario a una deficiencia de vitamina D en el embarazo y la frecuencia de preeclampsia. MATERIALES Y MÉTODOS: Estudio de casos y controles, prospectivo y longitudinal efectuado en pacientes con y sin preeclampsia que entre el 1 de enero y el 30 de junio del 2021 acudieron al Hospital Universitario de la Universidad Autónoma de Nuevo León para la atención del parto. Criterios de inclusión: pacientes embarazadas con diagnóstico de preeclampsia en el último trimestre de la gestación con tensión arterial igual o mayor a 140-90 mmHg y proteinuria igual o mayor a 30 mg/dL. Para el grupo control: embarazadas sanas, sin diagnóstico de preeclampsia en el último trimestre de la gestación. Criterios de exclusión: tabaquismo, alcoholismo y drogadicción y quienes no aceptaron entrar al estudio o tuvieran diagnóstico de enfermedades médicas crónicas. RESULTADOS: Se estudiaron 90 pacientes divididas en dos grupos: con preeclampsia (n = 45) y sin ésta (control, n = 45). Se encontró una relación entre la deficiencia de vitamina D, la hipocalcemia y la preeclampsia; no así entre la paratohormona y la preeclampsia en los rangos internacionales de la primera. La preeclampsia se encontró con mayor frecuencia en pacientes de 12 a 15 años. CONCLUSIONES: El hiperparatiroidismo secundario a la deficiencia de vitamina D en el embarazo no se observó en pacientes con preeclampsia, quienes sí la padecieron tuvieron concentraciones de paratohormona en límites normales. Se encontró una relación entre la deficiencia de vitamina D, la hipocalcemia y la preeclampsia.

Abstract OBJECTIVE: To establish whether there is an association between hyperparathyroidism secondary to vitamin D deficiency in pregnancy and the frequency of preeclampsia. MATERIALSAND METHODS: Case-control, prospective, longitudinal study performed in patients with and without preeclampsia who between January 1 and June 30, 2021 attended the Hospital Universitario of the Universidad Autónoma de Nuevo Leon for delivery care. Inclusion criteria: pregnant patients with a diagnosis of preeclampsia in the last trimester of gestation with blood pressure equal to or greater than 140-90 mmHg and proteinuria equal to or greater than 30 mg/dL. For the control group: healthy pregnant women without a diagnosis of preeclampsia in the last trimester of gestation. Exclusion criteria: smoking, alcoholism and drug addiction and those who did not agree to enter the study or had a diagnosis of chronic medical diseases. RESULTS: We studied 90 patients divided into two groups: with preeclampsia (n = 45) and without preeclampsia (control, n = 45). A relationship was found between vitamin D deficiency, hypocalcemia, and preeclampsia; a relationship was not found between parathormone and preeclampsia in the international parathormone ranges. Preeclampsia was found more frequently in patients aged 12 to 15 years. CONCLUSIONS: Hyperparathyroidism secondary to vitamin D deficiency in pregnancy was not observed in patients with preeclampsia; those who had it had parathormone concentrations in normal limits. A relationship was found between vitamin D deficiency, hypocalcemia, and preeclampsia.

Resting-state functional connectivity patterns are associated with worst pain duration in community-dwelling older adults.

INTRODUCTION: An individual's chronic pain history is associated with brain morphometric alterations; but little is known about the association between pain history and brain function. OBJECTIVES: This cross-sectional study aimed at determining how worst musculoskeletal pain intensity (WPINT) moderated the association between worst musculoskeletal pain duration (WPDUR) and brain resting-state magnetic resonance imaging functional connectivity (RSFC) in community-dwelling older adults (60-94 years, 75% females, 97% right-handed). METHODS: Resting-state magnetic resonance imaging functional connectivity between region of interests was linearly regressed on WPDUR and WPINT. Predictions were compared with a control group's average RSFC (61-85 years, 47% females, 95% right-handed). RESULTS: Three significant patterns emerged: (1) the positive association between WPDUR and RSFC between the medial prefrontal cortex, in the anterior salience network (SN), and bilateral lateral Brodmann area 6, in the visuospatial network (VSN), in participants with more severe chronic pain, resulting in abnormally lower RSFC for shorter WPDUR; (2) the negative association between WPDUR and RSFC between right VSN occipitotemporal cortex (lateral BA37 and visual V5) and bilateral VSN lateral Brodmann area 6, independently of WPINT, resulting in abnormally higher and lower RSFC for shorter and longer WPDUR, respectively; and (3) the positive association between WPDUR and the left hemisphere's salience network-default mode network connectivity (between the hippocampus and both dorsal insula and ventral or opercular BA44), independently of WPINT, resulting in abnormally higher RSFC for longer WPDUR. CONCLUSION: Musculoskeletal effects on brain functional networks of general healthy individuals could accumulate until being observable at older ages. Results invite to examinations of these effects' impact on function and memory.

Psychological profiles in adults with knee OA-related pain: a replication study.

INTRODUCTION: Psychological factors have been associated with knee osteoarthritis pain severity and treatment outcomes, yet their combined contribution to phenotypic heterogeneity is poorly understood. In particular, empirically derived psychological profiles must be replicated before they can be targeted or considered for treatment studies. The objectives of this study were to (1) confirm previously identified psychological profiles using unsupervised clustering methods in persons with knee osteoarthritis pain, (2) determine the replicability of profiles using supervised machine learning in a different sample, and (3) examine associations with clinical pain, brain structure, and experimental pain. METHODS: Participants included two cohorts of individuals with knee osteoarthritis pain recruited as part of the multisite UPLOAD1 (n = 270, mean age = 56.8 ± 7.6, male = 37%) and UPLOAD2 (n = 164, mean age = 57.73 ± 7.8, male = 36%) studies. Similar psychological constructs (e.g. optimism, coping, somatization, affect, depression, and anxiety), sociodemographic and clinical characteristics, and somatosensory function were assessed across samples. UPLOAD2 participants also completed brain magnetic resonance imaging. Unsupervised hierarchical clustering analysis was first conducted in UPLOAD1 data to derive clusters, followed by supervised linear discriminative analysis to predict group membership in UPLOAD2 data. Associations among cluster membership and clinical variables were assessed, controlling for age, sex, education, ethnicity/race, study site, and number of pain sites. RESULTS: Four distinct profiles emerged in UPLOAD1 and were replicated in UPLOAD2. Identified psychological profiles were associated with psychological variables (ps < 0.001), and clinical outcomes (ps = 0.001-0.03), indicating good internal and external validation of the cluster solution. Significant associations between psychological profiles and somatosensory function and brain structure were also found. CONCLUSIONS: This study highlights the importance of considering the biopsychosocial model in knee osteoarthritis pain assessment and treatment.

Identification of Negative BOLD Responses in Epilepsy Using Windkessel Models.

Alongside positive blood oxygenation level-dependent (BOLD) responses associated with interictal epileptic discharges, a variety of negative BOLD responses (NBRs) are typically found in epileptic patients. Previous studies suggest that, in general, up to four mechanisms might underlie the genesis of NBRs in the brain: (i) neuronal disruption of network activity, (ii) altered balance of neurometabolic/vascular couplings, (iii) arterial blood stealing, and (iv) enhanced cortical inhibition. Detecting and classifying these mechanisms from BOLD signals are pivotal for the improvement of the specificity of the electroencephalography-functional magnetic resonance imaging (EEG-fMRI) image modality to identify the seizure-onset zones in refractory local epilepsy. This requires models with physiological interpretation that furnish the understanding of how these mechanisms are fingerprinted by their BOLD responses. Here, we used a Windkessel model with viscoelastic compliance/inductance in combination with dynamic models of both neuronal population activity and tissue/blood O2 to classify the hemodynamic response functions (HRFs) linked to the above mechanisms in the irritative zones of epileptic patients. First, we evaluated the most relevant imprints on the BOLD response caused by variations of key model parameters. Second, we demonstrated that a general linear model is enough to accurately represent the four different types of NBRs. Third, we tested the ability of a machine learning classifier, built from a simulated ensemble of HRFs, to predict the mechanism underlying the BOLD signal from irritative zones. Cross-validation indicates that these four mechanisms can be classified from realistic fMRI BOLD signals. To demonstrate proof of concept, we applied our methodology to EEG-fMRI data from five epileptic patients undergoing neurosurgery, suggesting the presence of some of these mechanisms. We concluded that a proper identification and interpretation of NBR mechanisms in epilepsy can be performed by combining general linear models and biophysically inspired models.

Age Differences in Multimodal Quantitative Sensory Testing and Associations With Brain Volume.

BACKGROUND AND OBJECTIVES: Somatosensory function is critical for successful aging. Prior studies have shown declines in somatosensory function with age; however, this may be affected by testing site, modality, and biobehavioral factors. While somatosensory function declines are associated with peripheral nervous system degradation, little is known regarding correlates with the central nervous system and brain structure in particular. The objectives of this study were to examine age-related declines in somatosensory function using innocuous and noxious stimuli, across 2 anatomical testing sites, with considerations for affect and cognitive function, and associations between somatosensory function and brain structure in older adults. RESEARCH DESIGN AND METHODS: A cross-sectional analysis included 84 "younger" (n = 22, age range: 19-24 years) and "older" (n = 62, age range: 60-94 years) healthy adults who participated in the Neuromodulatory Examination of Pain and Mobility Across the Lifespan study. Participants were assessed on measures of somatosensory function (quantitative sensory testing), at 2 sites (metatarsal and thenar) using standardized procedures, and completed cognitive and psychological function measures and structural magnetic resonance imaging. RESULTS: Significant age × test site interaction effects were observed for warmth detection (p = .018, η p 2 = 0.10) and heat pain thresholds (p = .014, η p 2 = 0.12). Main age effects were observed for mechanical, vibratory, cold, and warmth detection thresholds (ps < .05), with older adults displaying a loss of sensory function. Significant associations between somatosensory function and brain gray matter structure emerged in the right occipital region, the right temporal region, and the left pericallosum. DISCUSSION AND IMPLICATIONS: Our findings indicate healthy older adults display alterations in sensory responses to innocuous and noxious stimuli compared to younger adults and, furthermore, these alterations are uniquely affected by anatomical site. These findings suggest a nonuniform decline in somatosensation in older adults, which may represent peripheral and central nervous system alterations part of aging processes.

Arterial blood stealing as a mechanism of negative BOLD response: From the steady-flow with nonlinear phase separation to a windkessel-based model.

Blood Oxygen Level Dependent (BOLD) signal indirectly characterizes neuronal activity by measuring hemodynamic and metabolic changes in the nearby microvasculature. A deeper understanding of how localized changes in electrical, metabolic and hemodynamic factors translate into a BOLD signal is crucial for the interpretation of functional brain imaging techniques. While positive BOLD responses (PBR) are widely considered to be linked with neuronal activation, the origins of negative BOLD responses (NBR) have remained largely unknown. As NBRs are sometimes observed in close proximity of regions with PBR, a blood "stealing" effect, i.e., redirection of blood from a passive periphery to the area with high neuronal activity, has been postulated. In this study, we used the Hagen-Poiseuille equation to model hemodynamics in an idealized microvascular network that account for the particulate nature of blood and nonlinearities arising from the red blood cell (RBC) distribution (i.e., the Fåhraeus, Fåhraeus-Lindqvist and the phase separation effects). Using this detailed model, we evaluate determinants driving this "stealing" effect in a microvascular network with geometric parameters within physiological ranges. Model simulations predict that during localized cerebral blood flow (CBF) increases due to neuronal activation-hyperemic response, blood from surrounding vessels is reallocated towards the activated region. This stealing effect depended on the resistance of the microvasculature and the uneven distribution of RBCs at vessel bifurcations. A parsimonious model consisting of two-connected windkessel regions sharing a supplying artery was proposed to simulate the stealing effect with a minimum number of parameters. Comparison with the detailed model showed that the parsimonious model can reproduce the observed response for hematocrit values within the physiological range for different species. Our novel parsimonious model promise to be of use for statistical inference (top-down analysis) from direct blood flow measurements (e.g., arterial spin labeling and laser Doppler/Speckle flowmetry), and when combined with theoretical models for oxygen extraction/diffusion will help account for some types of NBRs.

Chronic Pain is Associated With Reduced Sympathetic Nervous System Reactivity During Simple and Complex Walking Tasks: Potential Cerebral Mechanisms.

BACKGROUND: Autonomic dysregulation may lead to blunted sympathetic reactivity in chronic pain states. Autonomic responses are controlled by the central autonomic network (CAN). Little research has examined sympathetic reactivity and associations with brain CAN structures in the presence of chronic pain; thus, the present study aims to investigate how chronic pain influences sympathetic reactivity and associations with CAN brain region volumes. METHODS: Sympathetic reactivity was measured as change in skin conductance level (ΔSCL) between a resting reference period and walking periods for typical and complex walking tasks (obstacle and dual-task). Participants included 31 people with (n = 19) and without (n = 12) chronic musculoskeletal pain. Structural 3 T MRI was used to determine gray matter volume associations with ΔSCL in regions of the CAN (i.e., brainstem, amygdala, insula, and anterior cingulate cortex). RESULTS: ΔSCL varied across walking tasks (main effect p = 0.036), with lower ΔSCL in chronic pain participants compared to controls across trials 2 and 3 under the obstacle walking condition. ΔSCL during typical walking was associated with multiple CAN gray matter volumes, including brainstem, bilateral insula, amygdala, and right caudal anterior cingulate cortex (p's < 0.05). The difference in ΔSCL from typical-to-obstacle walking were associated with volumes of the midbrain segment of the brainstem and anterior segment of the circular sulcus of the insula (p's < 0.05), with no other significant associations. The difference in ΔSCL from typical-to-dual task walking was associated with the bilateral caudal anterior cingulate cortex, and left rostral cingulate cortex (p's < 0.05). CONCLUSIONS: Sympathetic reactivity is blunted during typical and complex walking tasks in persons with chronic pain. Additionally, blunted sympathetic reactivity is associated with CAN brain structure, with direction of association dependent on brain region. These results support the idea that chronic pain may negatively impact typical autonomic responses needed for walking performance via its potential impact on the brain.