Neurophysiology of Resilience in Juvenile Fibromyalgia.

Objective: Juvenile fibromyalgia (JFM) is a chronic pain syndrome predominantly affecting adolescent girls. Resilience may be a protective factor in coping with pain, reducing affective burden, and promoting positive outlooks. Brain regions affected in JFM overlap with those linked to resilience, particularly in the default-mode network (DMN). We investigate the role of resilience on core somatic and affective symptoms in JFM and assess the neurophysiological substrates for the first time. Methods: Forty-one girls with JFM and 40 pain-free adolescents completed a resting-state fMRI assessment and self-report questionnaires. We used clustering analyses to group JFM participants based on resilience, and principal component analyses to summarize core somatic and affective symptoms. We estimated whole-brain and within-DMN connectivity and assessed differences between higher and lower resilience JFM groups and compared their connectivity patterns to pain-free participants. Results: The higher resilience JFM group had less affective (T=4.03; p<.001) but similar core somatic symptoms (T=1.05; p=.302) than the lower resilience JFM group. They had increased whole-brain (T's>3.90, pFDR's<.03) and within-DMN (T=2.20, p=.03) connectivity strength, and higher connectivity between DMN nodes and self-referential, regulatory, and reward-processing regions. Conversely, higher DMN-premotor connectivity was observed in the lower resilience group. Conclusion: JFM participants with higher resilience were protected affectively but not in core somatic symptoms. Greater resilience was accompanied by higher signal integration within the DMN, a network central to internally oriented attention and flexible attention shifting. Crucially, the connectivity pattern in highly resilient patients resembled that of pain-free adolescents, which was not the case for the lower resilience group.

Constructing Tunable Electrides on Monolayer Transition Metal Dichalcogenides.

Electrides have emerged as promising materials with exotic properties due to the presence of localized electrons detached from all atoms. Despite the continuous discovery of many new electrides, most of them are based on atypical compositions, and their applications require an inert surface structure to passivate reactive excess electrons. Here, we demonstrate a different route to attain tunable electrides. We first report that monolayer transition metal dichalcogenides (TMDCs) exhibit weak electride characteristics, which is the remainder of the electride feature of the transition metal sublattice. By introducing chalcogen vacancies, the enhanced electride characteristics are comparable to those of known electrides. Since the precise tailoring of the chalcogen vacancy concentration has been achieved experimentally, we proposed that TMDCs can be used to build electrides with controllable intensities. Furthermore, we demonstrate that the electride states at the chalcogen vacancy of monolayer TMDCs will play an important role in catalyzing hydrogen evolution reactions.

Dataset of breast thermography images for the detection of benign and malignant masses.

Thermographic image analysis is a subfield of diagnostic image processing aimed at detecting breast abnormalities in women at an early stage. It is a developing field of research and its effectiveness and scope require scientific assessment to be determined. An open-access dataset has been created for the scientific community to test and develop techniques for computational detection of normal and abnormal breast conditions from thermograms. This dataset is a valuable resource for researchers due to the scarcity of publicly available datasets of breast thermographic images. It includes thermographic images of the female chest area in three capture positions: anterior, left oblique and right oblique. The data set comes from 119 women ranging from 18 to 81 years of age. A table is attached to the dataset with the diagnosis of breast pathology, showing that 84 patients had benign pathology and 35 patients had malignant pathology. The diagnoses of women with healthy breast pathology are not included.

Technical Efficiency of Mexico's Public Health System in the Delivery of Obstetric Care, during 2012-2018.

The objective of this study was to evaluate the technical efficiency of Mexico's public health system in the delivery of obstetric care from 2012 to 2018. A multi-stage quantitative study of the public health institutions responsible for 95% of the system's obstetric services was conducted using data envelopment analysis. The efficiency of state-level productive units (decision-making units, or DMUs) was calculated and juxtaposed with the DMUs' maximum (0.82) and minimum (0.22) scores. Using the outcomes of the initial stage, the average technical efficiency of each institution at the national level was estimated and compared. The results were also utilized to estimate and compare the average efficiency of each state-level health system based on economic characteristics (state GDP per capita). Outputs included prenatal visits and deliveries, while inputs comprised gynecologists, exam rooms, and delivery rooms. Institutional efficiency ranged from 0.16 to 0.82, with an average of 0.417. The Ministry of Health (0.82) and the Mexican Social Security Institute (0.747) exhibited the highest efficiency scores, while the remaining institutions (Institute for Social Security and Services for State Workers [ISSSTE]; Mexican Petroleum [PEMEX]; the Secretary of National Defense [SEDENA]; and the Navy [SEMAR]) scored below the health system average. Of the 153 DMUs, 20% surpassed the maximum (0.82) and 40.6% fell below the minimum (0.22). These findings indicate that 80% of DMUs have unused operational capacity that could be utilized to enhance technical efficiency. No relationship was found between efficiency and the GDP of Mexico's 32 politico-administrative divisions. The efficiency gap between institutions (0.66) shows that while some DMUs are saturated (exhibiting high efficiency scores), the majority have unused operational capacity. Leveraging this untapped capacity could address the needs of vulnerable populations facing restricted access due to health system fragmentation.

Patterns of subregional cerebellar atrophy across epilepsy syndromes: An ENIGMA-Epilepsy study.

OBJECTIVE: The intricate neuroanatomical structure of the cerebellum is of longstanding interest in epilepsy, but has been poorly characterized within the current corticocentric models of this disease. We quantified cross-sectional regional cerebellar lobule volumes using structural magnetic resonance imaging in 1602 adults with epilepsy and 1022 healthy controls across 22 sites from the global ENIGMA-Epilepsy working group. METHODS: A state-of-the-art deep learning-based approach was employed that parcellates the cerebellum into 28 neuroanatomical subregions. Linear mixed models compared total and regional cerebellar volume in (1) all epilepsies, (2) temporal lobe epilepsy with hippocampal sclerosis (TLE-HS), (3) nonlesional temporal lobe epilepsy, (4) genetic generalized epilepsy, and (5) extratemporal focal epilepsy (ETLE). Relationships were examined for cerebellar volume versus age at seizure onset, duration of epilepsy, phenytoin treatment, and cerebral cortical thickness. RESULTS: Across all epilepsies, reduced total cerebellar volume was observed (d = .42). Maximum volume loss was observed in the corpus medullare (dmax = .49) and posterior lobe gray matter regions, including bilateral lobules VIIB (dmax = .47), crus I/II (dmax = .39), VIIIA (dmax = .45), and VIIIB (dmax = .40). Earlier age at seizure onset ( η ρ max 2 = .05) and longer epilepsy duration ( η ρ max 2 = .06) correlated with reduced volume in these regions. Findings were most pronounced in TLE-HS and ETLE, with distinct neuroanatomical profiles observed in the posterior lobe. Phenytoin treatment was associated with reduced posterior lobe volume. Cerebellum volume correlated with cerebral cortical thinning more strongly in the epilepsy cohort than in controls. SIGNIFICANCE: We provide robust evidence of deep cerebellar and posterior lobe subregional gray matter volume loss in patients with chronic epilepsy. Volume loss was maximal for posterior subregions implicated in nonmotor functions, relative to motor regions of both the anterior and posterior lobe. Associations between cerebral and cerebellar changes, and variability of neuroanatomical profiles across epilepsy syndromes argue for more precise incorporation of cerebellar subregional damage into neurobiological models of epilepsy.

Mapping gray and white matter volume abnormalities in early-onset psychosis: an ENIGMA multicenter voxel-based morphometry study.

INTRODUCTION: Regional gray matter (GM) alterations have been reported in early-onset psychosis (EOP, onset before age 18), but previous studies have yielded conflicting results, likely due to small sample sizes and the different brain regions examined. In this study, we conducted a whole brain voxel-based morphometry (VBM) analysis in a large sample of individuals with EOP, using the newly developed ENIGMA-VBM tool. METHODS: 15 independent cohorts from the ENIGMA-EOP working group participated in the study. The overall sample comprised T1-weighted MRI data from 482 individuals with EOP and 469 healthy controls. Each site performed the VBM analysis locally using the standardized ENIGMA-VBM tool. Statistical parametric T-maps were generated from each cohort and meta-analyzed to reveal voxel-wise differences between EOP and healthy controls as well as the individual-based association between GM volume and age of onset, chlorpromazine (CPZ) equivalent dose, and other clinical variables. RESULTS: Compared with healthy controls, individuals with EOP showed widespread lower GM volume encompassing most of the cortex, with the most marked effect in the left median cingulate (Hedges' g = 0.55, p = 0.001 corrected), as well as small clusters of lower white matter (WM), whereas no regional GM or WM volumes were higher in EOP. Lower GM volume in the cerebellum, thalamus and left inferior parietal gyrus was associated with older age of onset. Deficits in GM in the left inferior frontal gyrus, right insula, right precentral gyrus and right superior frontal gyrus were also associated with higher CPZ equivalent doses. CONCLUSION: EOP is associated with widespread reductions in cortical GM volume, while WM is affected to a smaller extent. GM volume alterations are associated with age of onset and CPZ equivalent dose but these effects are small compared to case-control differences. Mapping anatomical abnormalities in EOP may lead to a better understanding of the role of psychosis in brain development during childhood and adolescence.

Focal reactive nodular gliosis: an extremely rare retinal astrocytic tumor.

Focal reactive nodular gliosis (FRNG) is an extremely rare benign retinal reactive astrocytic tumor that results from the proliferation of well-differentiated glial cells secondary to a variety of retinal conditions. We describe a case of this tumor in a 64-year-old male in association with a chorioretinal scar he has had since childhood. The symptom was sudden painful vision loss. In the clinical examination, iris rubeosis, posterior synechiae, cataract, vitreous haze and a suspected fundus mass were showed. B-scan ultrasonography demonstrated a retinal mass consistent with choroidal melanoma. The magnetic resonance imaging (MRI) showed a well-circumscribed mass with T1 hyperintensity and T2 hypointensity. Enucleation was performed and histopathologic and immunohistochemical studies confirmed the diagnosis of FRNG.

Patterns of subregional cerebellar atrophy across epilepsy syndromes: An ENIGMA-Epilepsy study.

Objective: The intricate neuroanatomical structure of the cerebellum is of longstanding interest in epilepsy, but has been poorly characterized within the current cortico-centric models of this disease. We quantified cross-sectional regional cerebellar lobule volumes using structural MRI in 1,602 adults with epilepsy and 1,022 healthy controls across twenty-two sites from the global ENIGMA-Epilepsy working group. Methods: A state-of-the-art deep learning-based approach was employed that parcellates the cerebellum into 28 neuroanatomical subregions. Linear mixed models compared total and regional cerebellar volume in i) all epilepsies; ii) temporal lobe epilepsy with hippocampal sclerosis (TLE-HS); iii) non-lesional temporal lobe epilepsy (TLE-NL); iv) genetic generalised epilepsy; and (v) extra-temporal focal epilepsy (ETLE). Relationships were examined for cerebellar volume versus age at seizure onset, duration of epilepsy, phenytoin treatment, and cerebral cortical thickness. Results: Across all epilepsies, reduced total cerebellar volume was observed (d=0.42). Maximum volume loss was observed in the corpus medullare (dmax=0.49) and posterior lobe grey matter regions, including bilateral lobules VIIB (dmax= 0.47), Crus I/II (dmax= 0.39), VIIIA (dmax=0.45) and VIIIB (dmax=0.40). Earlier age at seizure onset (ηρ2max=0.05) and longer epilepsy duration (ηρ2max=0.06) correlated with reduced volume in these regions. Findings were most pronounced in TLE-HS and ETLE with distinct neuroanatomical profiles observed in the posterior lobe. Phenytoin treatment was associated with reduced posterior lobe volume. Cerebellum volume correlated with cerebral cortical thinning more strongly in the epilepsy cohort than in controls. Significance: We provide robust evidence of deep cerebellar and posterior lobe subregional grey matter volume loss in patients with chronic epilepsy. Volume loss was maximal for posterior subregions implicated in non-motor functions, relative to motor regions of both the anterior and posterior lobe. Associations between cerebral and cerebellar changes, and variability of neuroanatomical profiles across epilepsy syndromes argue for more precise incorporation of cerebellum subregions into neurobiological models of epilepsy.

In vivo white matter microstructure in adolescents with early-onset psychosis: a multi-site mega-analysis.

Emerging evidence suggests brain white matter alterations in adolescents with early-onset psychosis (EOP; age of onset <18 years). However, as neuroimaging methods vary and sample sizes are modest, results remain inconclusive. Using harmonized data processing protocols and a mega-analytic approach, we compared white matter microstructure in EOP and healthy controls using diffusion tensor imaging (DTI). Our sample included 321 adolescents with EOP (median age = 16.6 years, interquartile range (IQR) = 2.14, 46.4% females) and 265 adolescent healthy controls (median age = 16.2 years, IQR = 2.43, 57.7% females) pooled from nine sites. All sites extracted mean fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) for 25 white matter regions of interest per participant. ComBat harmonization was performed for all DTI measures to adjust for scanner differences. Multiple linear regression models were fitted to investigate case-control differences and associations with clinical variables in regional DTI measures. We found widespread lower FA in EOP compared to healthy controls, with the largest effect sizes in the superior longitudinal fasciculus (Cohen's d = 0.37), posterior corona radiata (d = 0.32), and superior fronto-occipital fasciculus (d = 0.31). We also found widespread higher RD and more localized higher MD and AD. We detected significant effects of diagnostic subgroup, sex, and duration of illness, but not medication status. Using the largest EOP DTI sample to date, our findings suggest a profile of widespread white matter microstructure alterations in adolescents with EOP, most prominently in male individuals with early-onset schizophrenia and individuals with a shorter duration of illness.

Interpretable surface-based detection of focal cortical dysplasias: a Multi-centre Epilepsy Lesion Detection study.

One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted 'gold-standard' subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in individuals with epilepsy.

Atlas of lesion locations and postsurgical seizure freedom in focal cortical dysplasia: A MELD study.

OBJECTIVE: Drug-resistant focal epilepsy is often caused by focal cortical dysplasias (FCDs). The distribution of these lesions across the cerebral cortex and the impact of lesion location on clinical presentation and surgical outcome are largely unknown. We created a neuroimaging cohort of patients with individually mapped FCDs to determine factors associated with lesion location and predictors of postsurgical outcome. METHODS: The MELD (Multi-centre Epilepsy Lesion Detection) project collated a retrospective cohort of 580 patients with epilepsy attributed to FCD from 20 epilepsy centers worldwide. Magnetic resonance imaging-based maps of individual FCDs with accompanying demographic, clinical, and surgical information were collected. We mapped the distribution of FCDs, examined for associations between clinical factors and lesion location, and developed a predictive model of postsurgical seizure freedom. RESULTS: FCDs were nonuniformly distributed, concentrating in the superior frontal sulcus, frontal pole, and temporal pole. Epilepsy onset was typically before the age of 10 years. Earlier epilepsy onset was associated with lesions in primary sensory areas, whereas later epilepsy onset was associated with lesions in association cortices. Lesions in temporal and occipital lobes tended to be larger than frontal lobe lesions. Seizure freedom rates varied with FCD location, from around 30% in visual, motor, and premotor areas to 75% in superior temporal and frontal gyri. The predictive model of postsurgical seizure freedom had a positive predictive value of 70% and negative predictive value of 61%. SIGNIFICANCE: FCD location is an important determinant of its size, the age at epilepsy onset, and the likelihood of seizure freedom postsurgery. Our atlas of lesion locations can be used to guide the radiological search for subtle lesions in individual patients. Our atlas of regional seizure freedom rates and associated predictive model can be used to estimate individual likelihoods of postsurgical seizure freedom. Data-driven atlases and predictive models are essential for evidence-based, precision medicine and risk counseling in epilepsy.

Volumetric and shape analysis of the hippocampus in temporal lobe epilepsy with GAD65 antibodies compared with non-immune epilepsy.

Glutamic acid decarboxylase 65 antibodies (anti-GAD65) have been found in patients with late-onset chronic temporal lobe epilepsy (TLE). No prior neuroimaging studies have addressed how they affect hippocampal volume and shape and how they relate to cognitive abnormalities. We aimed to investigate both brain structure and function in patients with isolated TLE and high anti-GAD65 levels (RIA ≥ 2000 U/ml) compared to 8 non-immune mesial TLE (niTLE) and 8 healthy controls (HC). Hippocampal subfield volume properties were correlated with the duration of the disease and cognitive test scores. The affected hippocampus of GAD-TLE patients showed no volume changes to matched HC whereas niTLE volumes were significantly smaller. Epilepsy duration in GAD-TLE patients correlated negatively with volumes in the presubiculum, subiculum, CA1, CA2-3, CA4, molecular layer and granule cell-molecular layer of the dentate nucleus. We found differences by advanced vertex-wise shape analysis in the anterior hippocampus of the left GAD-TLE compared to HC whereas left niTLE showed bilateral posterior hippocampus deformation. Verbal deficits were similar in GAD-TLE and niTLE but did not correlate to volume changes. These data might suggest a distinct expression of hippocampal structural and functional abnormalities based on the immune response.

Structural characterization of the Extended Frontal Aslant Tract trajectory: A ML-validated laterality study in 3T and 7T.

The Extended Frontal Aslant Tract (exFAT) is a recently described tractography-based extension of the Frontal Aslant Tract connecting Broca's territory to both supplementary and pre-supplementary motor areas, and more anterior prefrontal regions. In this study, we aim to characterize the microstructural properties of the exFAT trajectories as a means to perform a laterality analysis to detect interhemispheric structural differences along the tracts using the Human Connectome Project (HCP) dataset. To that end, the bilateral exFAT was reconstructed for 3T and 7T HCP acquisitions in 120 randomly selected subjects. As a complementary exploration of the exFAT anatomy, we performed a white matter dissection of the exFAT trajectory of two ex-vivo left hemispheres that provide a qualitative assessment of the tract profiles. We assessed the lateralization structural differences in the exFAT by performing: (i) a laterality comparison between the mean microstructural diffusion-derived parameters for the exFAT trajectories, (ii) a laterality comparison between the tract profiles obtained by applying the Automated Fiber Quantification (AFQ) algorithm, and (iii) a cross-validated Machine Learning (ML) classifier analysis using single and combined tract profiles parameters for single-subject classification. The mean microstructural diffusion-derived parameter comparison showed statistically significant differences in mean FA values between left and right exFATs in the 3T sample. The diffusion parameters studied with the AFQ technique suggest that the inferiormost half of the exFAT trajectory has a hemispheric-dependent fingerprint of microstructural properties, with an increased measure of tissue hindrance in the orthogonal plane and a decreased measure of orientational dispersion along the main tract direction in the left exFAT compared to the right exFAT. The classification accuracy of the ML models showed a high agreement with the magnitude of those differences.

Distinct Components in the Right Extended Frontal Aslant Tract Mediate Language and Working Memory Performance: A Tractography-Informed VBM Study.

The extended frontal aslant tract (exFAT) is a tractography-based extension of the frontal aslant tract (FAT) which has been shown to be related with language and working memory performance in healthy human adults, but whether those functional implications map to structurally separate regions along its trajectory is still an open question. We present a tractography-informed Voxel-Based Morphometry procedure capable of detecting local tract-specific structural differences in white matter regions and apply it in two maximum variation sampling studies by comparing local differences in diffusion-derived microstructural parameters and fiber density along the exFAT territory between top performers and bottom performers in language and working memory tasks. In the right hemisphere we were able to detect, without prior constraints, a vertical frontal aslant component approximating the original FAT trajectory whose fiber density was significantly correlated with language (but not working memory) performance and an anterior cluster component corresponding to a distinct anterior frontal aslant component whose fiber density was significantly correlated with working memory (but not language) performance. The reported sub-division of the exFAT territory describes a set of frontal connections that are compatible with previously reported results on the Broca's territory and frontal cortex hierarchical organization along an anterior-posterior gradient, suggesting that the exFAT could be part of a common neuroanatomical scaffold where language and working memory functions are integrated in the healthy human brain.

Default Mode Network structural alterations in Kocher-Monro trajectory white matter transection: A 3 and 7 tesla simulation modeling approach.

The Kocher-Monro trajectory to the cerebral ventricular system represents one of the most common surgical procedures in the field of neurosurgery. Several studies have analyzed the specific white matter disruption produced during this intervention, which has no reported adverse neurological outcomes. In this study, a graph-theoretical approach was applied to quantify the structural alterations in whole-brain level connectivity. To this end, 132 subjects were randomly selected from the Human Connectome Project dataset and used to create 3 independent 44 subjects groups. Two of the groups underwent a simulated left/right Kocher-Monro trajectory and the third was kept as a control group. For the right Kocher-Monro approach, the nodal analysis revealed decreased strength in the anterior cingulate gyrus of the transected hemisphere. The network-based statistic analysis revealed a set of right lateralized subnetworks with decreased connectivity strength that is consistent with a subset of the Default Mode Network, Salience Network, and Cingulo-Opercular Network. These findings could allow for a better understanding of structural alterations caused by Kocher-Monro approaches that could reveal previously undetected clinical alterations and inform the process of designing safer and less invasive cerebral ventricular approaches.