Brain Structures Research Articles

Neurobehavioral perspectives on autistic spectrum disorder

Understanding genetics and environmental influences in autism has been explored in greater depth in recent decades. However, the mechanism by which they converge that leads to autism still needs to be explored further. An autism diagnosis in DSM-5 results from a neurodevelopmental disorder hurting normal brain function, affecting communication and social interaction combined with restricted or repetitive patterns of behavior and interests. This paper reviews current work investigating how the underlying mechanism of the brain structure and function relates to the complex and aberrant behavioral manifestations of autism. Mapping this connection can provide us with a better understanding of autism signs and symptoms, making the process of accurate diagnosis more straightforward. As a complex neurobehavioral condition, autistic individuals process the environment and their interactions with others differently from those without autism. So, they make different perceptions and connections between themselves and the environment. Consequently, they will have difficulty communicating, forming relationships, and responding appropriately to their environment. It is this lifelong neurobehavioral dysfunction that prevents autistic individuals from adequately understanding what they perceive and the emotional expression of others. There will be differences in their mental states, how their brains work, and how their thinking processes will be affected by a neurodevelopmental disability.

Blood biomarkers of neurodegeneration associate differently with amyloid deposition, medial temporal atrophy, and cerebrovascular changes in APOE ε4-enriched cognitively unimpaired elderly.

Alzheimer's disease (AD) is characterized by the accumulation of amyloid-β (Aβ) plaques, neurofibrillary tau tangles, and neurodegeneration in the brain parenchyma. Here, we aimed to (i) assess differences in blood and imaging biomarkers used to evaluate neurodegeneration among cognitively unimpaired APOE ε4 homozygotes, heterozygotes, and non-carriers with varying risk for sporadic AD, and (ii) to determine how different cerebral pathologies (i.e., Aβ deposition, medial temporal atrophy, and cerebrovascular pathology) contribute to blood biomarker concentrations in this sample. Sixty APOE ε4 homozygotes (n = 19), heterozygotes (n = 21), and non-carriers (n = 20) ranging from 60 to 75 years, were recruited in collaboration with Auria biobank (Turku, Finland). Participants underwent Aβ-PET ([11C]PiB), structural brain MRI including T1-weighted and T2-FLAIR sequences, and blood sampling for measuring serum neurofilament light chain (NfL), plasma total tau (t-tau), plasma N-terminal tau fragments (NTA-tau) and plasma glial fibrillary acidic protein (GFAP). [11C]PiB standardized uptake value ratio was calculated for regions typical for Aβ accumulation in AD. MRI images were analysed for regional volumes, atrophy scores, and volumes of white matter hyperintensities. Differences in biomarker levels and associations between blood and imaging biomarkers were tested using uni- and multivariable linear models (unadjusted and adjusted for age and sex). Serum NfL concentration was increased in APOE ε4 homozygotes compared with non-carriers (mean 21.4 pg/ml (SD 9.5) vs. 15.5 pg/ml (3.8), p = 0.013), whereas other blood biomarkers did not differ between the groups (p > 0.077 for all). From imaging biomarkers, hippocampal volume was significantly decreased in APOE ε4 homozygotes compared with non-carriers (6.71ml (0.86) vs. 7.2ml (0.7), p = 0.029). In the whole sample, blood biomarker levels were differently predicted by the three measured cerebral pathologies; serum NfL concentration was associated with cerebrovascular pathology and medial temporal atrophy, while plasma NTA-tau associated with medial temporal atrophy. Plasma GFAP showed significant association with both medial temporal atrophy and Aβ pathology. Plasma t-tau concentration did not associate with any of the measured pathologies. Only increased serum NfL concentrations and decreased hippocampal volume was observed in cognitively unimpaired APOEε4 homozygotes compared to non-carriers. In the whole population the concentrations of blood biomarkers were affected in distinct ways by different pathologies.

Dynamic Mechanism of Cerebral Venous Disruption: Longitudinal Evidence From a Community-Based Cohort.

This study aims to investigate the temporal and spatial patterns of structural brain injury related to deep medullary veins (DMVs) damage. This is a longitudinal analysis of the population-based Shunyi cohort study. Baseline DMVs numbers were identified on susceptibility-weighted imaging. We assessed vertex-wise cortex maps and diffusion maps at both baseline and follow-up using FSL software and the longitudinal FreeSurfer analysis suite. We performed statistical analysis of global measurements and voxel/vertex-wise analysis to explore the relationship between DMVs number and brain structural measurements. A total of 977 participants were included in the baseline, of whom 544 completed the follow-up magnetic resonance imaging (age 54.97±7.83 years, 32% men, mean interval 5.56±0.47 years). A lower number of DMVs was associated with a faster disruption of white matter microstructural integrity, presented by increased mean diffusivity and radial diffusion (β=0.0001 and SE=0.0001 for both, P=0.04 and 0.03, respectively), in extensive deep white matter (threshold-free cluster enhancement P<0.05, adjusted for age and sex). Of particular interest, we found a bidirectional trend association between DMVs number and change in brain volumes. Specifically, participants with mild DMVs disruption showed greater cortical enlargement, whereas those with severe disruption exhibited more significant brain atrophy, primarily involving clusters in the frontal and parietal lobes (multiple comparison corrected P<0.05, adjusted for age, sex, and total intracranial volume). Our findings posed the dynamic pattern of brain parenchymal lesions related to DMVs injury, shedding light on the interactions and chronological roles of various pathological mechanisms.

The circulating proteome and brain health: Mendelian randomisation and cross-sectional analyses.

Decline in cognitive function is the most feared aspect of ageing. Poorer midlife cognitive function is associated with increased dementia and stroke risk. The mechanisms underlying variation in cognitive function are uncertain. Here, we assessed associations between 1160 proteins' plasma levels and two measures of cognitive function, the digit symbol substitution test (DSST) and the Montreal Cognitive Assessment in 1198 PURE-MIND participants. We identified five DSST performance-associated proteins (NCAN, BCAN, CA14, MOG, CDCP1), with NCAN and CDCP1 showing replicated association in an independent cohort, GS (N = 1053). MRI-assessed structural brain phenotypes partially mediated (8-19%) associations between NCAN, BCAN, and MOG, and DSST performance. Mendelian randomisation analyses suggested higher CA14 levels might cause larger hippocampal volume and increased stroke risk, whilst higher CDCP1 levels might increase intracranial aneurysm risk. Our findings highlight candidates for further study and the potential for drug repurposing to reduce the risk of stroke and cognitive decline.

Associations between brain morphology, inflammatory markers and symptoms of fatigue, depression or anxiety in active and remitted Crohn's disease.

Fatigue and psychosocial impairments are highly prevalent in IBD, especially during active disease. Disturbed brain-gut-interactions may contribute to these symptoms. This study examined associations between brain structure, faecal calprotectin and symptoms of fatigue, depression and anxiety in persons with Crohn's Disease (CD) in different disease states. In this prospective observational study, n=109 participants (n=67 persons with CD, n=42 healthy controls) underwent cranial magnetic resonance imaging, provided stool samples for analysis of faecal calprotectin and completed questionnaires to assess symptoms of fatigue, depression and anxiety. We analysed differences in grey matter volume (GMV) between patients and controls and associations between regional GMV alterations, neuropsychiatric symptoms and faecal calprotectin. Symptoms of fatigue, depression and anxiety were increased in patients with CD compared to controls, with highest scores in active CD. Patients exhibited regionally reduced GMV in cortical and subcortical sensorimotor regions, occipitotemporal and medial frontal areas. Regional GMV differences showed a significant negative association with fatigue, but not with depression or anxiety. Subgroup analyses revealed symptom-GMV-associations for fatigue in remitted, but not in active CD, while fatigue was positively associated with faecal calprotectin in active, but not remitted disease. Our findings support disturbed brain-gut-interactions in CD which may be particularly relevant for fatigue during remitted disease. Reduced GMV in the precentral gyrus and other sensorimotor areas could reflect key contributions to fatigue pathophysiology in CD. A sensorimotor model of fatigue in CD could also pave the way for novel treatment approaches.

Major brain injuries at term continue to influence DTI parameters in adolescents born very preterm: a 13-year follow-up study.

Major brain injuries in structural brain magnetic resonance imaging (MRI) at term affect concurrent diffusion tensor imaging (DTI) parameters in very preterm infants. White matter is known to gradually maturate along with increasing gestational age, which is characterized by increasing fractional anisotropy (FA) and decreasing mean diffusivity (MD). To study the difference between DTI parameters at term and 13 years in adolescents born very preterm with and without major pathologies in structural brain MRI at term. Adolescents born very preterm (gestational age <32 weeks and/or birth weight ≤1500 g) in 2004-2006 at Turku University Hospital, Finland were included. We evaluated FA and MD at term and 13 years in 18 regions of interest using the JHU-neonate-SS atlas to compare the differences in these parameters between adolescents with and without major injuries identified on MRI at term. A total of 24 adolescents underwent brain MRI including DTI both at term and 13 years. Adolescents with major brain injury pathologies (n = 6) in structural MRI at term had decreased FA in the left corpus callosum and right cingulate gyrus part, and increased MD in the left corpus callosum, right anterior limb of internal capsule, and right posterior limb of the internal capsule at 13 years, in comparison with adolescents without major brain injuries (n = 18) in structural MRI at term. Our findings suggest that major brain injuries identified on structural MRI at term affect brain maturation, with adverse effects in FA and MD still during adolescence.

MAPPING THYROID HORMONE ACTION IN THE HUMAN BRAIN.

Normal brain development, mood, and cognitive functions depend on thyroid hormone (TH) action. However, little is known about how TH mediates its actions in the human brain. This is because of limited access to human brains deprived of TH during fetal and early postnatal life, as well as from adults with altered thyroid status. One way to partially bypass these limitations is by using magnetic resonance imaging and spectroscopy, two neuroimaging techniques that provide detailed, non-invasive information on human brain structure and function. Another way is using human-induced pluripotent stem cells (hiPSCs)-derived three-dimensional in vitro systems, known as brain organoids, which allow for studying fundamental aspects of the early stages of human brain development. This narrative review focuses on neuroimaging and brain organoid studies. Neuroimaging of human brains performed in individuals with different thyroid conditions provides information on the volume, myelination, blood flow, neural activity, and connectivity of different areas. Such studies show that a suboptimal thyroid status can impact human brain development and its normal function throughout life. This is true not only for patients with sporadic congenital hypothyroidism, during pregnancy or early after birth, but also for adult patients with hypo- or hyperthyroidism and for patients carrying mutations that manifest as impaired sensitivity to TH-and even for normal individuals during aging. Studies using brain organoids generated from iPSCs of healthy individuals or patients with thyroid genetic conditions provide insights into how TH can impact the early development of the human cerebral cortex. The developmental alterations in children born to mothers with different degrees of gestational hypothyroidism or who developed hypothyroidism early in life are remarkable, affecting multiple brain regions and pathways, including the cerebral cortex, hippocampus, cerebellum, interhemispheric and corticospinal tracts, and associative nuclei. The data connecting such changes to poor neurological outcomes in adult patients with hypothyroidism represent an objective link between thyroid-specific functional brain alterations and behavior. Growing brain organoids require TH, proving critical for human neuro- and oligodendrogenesis. These models proved useful in screening drugs with potential therapeutics for patients with genetic thyroid diseases.

Deep learning-based super-resolution of structural brain MRI at 1.5T: application to quantitative volume measurement.

This study investigated the feasibility of using deep learning-based super-resolution (DL-SR) technique on low-resolution (LR) images to generate high-resolution (HR) MR images with the aim of scan time reduction. The efficacy of DL-SR was also assessed through the application of brain volume measurement (BVM). In vivo brain images acquired with 3D-T1W from various MRI scanners were utilized. For model training, LR images were generated by downsampling the original 1mm-2mm isotropic resolution images. Pairs of LR and HR images were used for training 3D residual dense net (RDN). For model testing, actual scanned 2mm isotropic resolution 3D-T1W images with one-minute scan time were used. Normalized root-mean-square error (NRMSE), peak signal-to-noise ratio (PSNR), and structural similarity (SSIM) were used for model evaluation. The evaluation also included brain volume measurement, with assessments of subcortical brain regions. The results showed that DL-SR model improved the quality of LR images compared with cubic interpolation, as indicated by NRMSE (24.22% vs 30.13%), PSNR (26.19 vs 24.65), and SSIM (0.96 vs 0.95). For volumetric assessments, there were no significant differences between DL-SR and actual HR images (p > 0.05, Pearson's correlation > 0.90) at seven subcortical regions. The combination of LR MRI and DL-SR enables addressing prolonged scan time in 3D MRI scans while providing sufficient image quality without affecting brain volume measurement.

Neurorestorative approaches for ischemic stroke.

Despite recent advances in acute stroke management, most patients experiencing a stroke will suffer from residual brain damage and functional impairment. Addressing those residual deficits would require neurorestoration, i.e., rebuilding brain tissue to repair the structural brain damage caused by stroke. However, there are major pathobiological, anatomical and technological hurdles making neurorestorative approaches remarkably challenging, and true neurorestoration after larger ischemic lesions could not yet be achieved. On the other hand, there has been steady advancement in our understanding of the limits of tissue regeneration in the adult mammalian brain as well as of the fundamental organization of brain tissue growth during embryo- and ontogenesis. This has been paralleled by the development of novel animal models to study stroke, advancement of biomaterials that can be used to support neurorestoration, and in stem cell technologies. This review gives a detailed explanation of the major hurdles so far preventing the achievement of neurorestoration after stroke. It will also describe novel concepts and advancements in biomaterial science, brain organoid culturing, and animal modeling that may enable the investigation of post-stroke neurorestorative approaches in translationally relevant setups. Finally, there will be a review of recent achievements in experimental studies that have the potential to be the starting point of research and development activities that may eventually bring post-stroke neurorestoration within reach.

Brain structure and connectivity mediate the association of lifestyle and cognition: the Maastricht study

Brain structure and connectivity mediate the association of lifestyle and cognition: the Maastricht study

Exploring Schizophrenia Classification Through Multimodal MRI and Deep Graph Neural Networks: Unveiling Brain Region-Specific Weight Discrepancies and Their Association With Cell-Type Specific Transcriptomic Features.

Schizophrenia (SZ) is a prevalent mental disorder that imposes significant health burdens. Diagnostic accuracy remains challenging due to clinical subjectivity. To address this issue, we explore magnetic resonance imaging (MRI) as a tool to enhance SZ diagnosis and provide objective references and biomarkers. Using deep learning with graph convolution, we represent MRI data as graphs, aligning with brain structure, and improving feature extraction, and classification. Integration of multiple modalities is expected to enhance classification. Our study enrolled 683 SZ patients and 606 healthy controls from 7 hospitals, collecting structural MRI and functional MRI data. Both data types were represented as graphs, processed by 2 graph attention networks, and fused for classification. Grad-CAM with graph convolution ensured interpretability, and partial least squares analyzed gene expression in brain regions. Our method excelled in the classification task, achieving 83.32% accuracy, 83.41% sensitivity, and 83.20% specificity in 10-fold cross-validation, surpassing traditional methods. And our multimodal approach outperformed unimodal methods. Grad-CAM identified potential brain biomarkers consistent with gene analysis and prior research. Our study demonstrates the effectiveness of deep learning with graph attention networks, surpassing previous SZ diagnostic methods. Multimodal MRI's superiority over unimodal MRI confirms our initial hypothesis. Identifying potential brain biomarkers alongside gene biomarkers holds promise for advancing objective SZ diagnosis and research in SZ.

Deciphering nociplastic pain: clinical features, risk factors and potential mechanisms.

Nociplastic pain is a mechanistic term used to describe pain that arises or is sustained by altered nociception, despite the absence of tissue damage. Although nociplastic pain has distinct pathophysiology from nociceptive and neuropathic pain, these pain mechanisms often coincide within individuals, which contributes to the intractability of chronic pain. Key symptoms of nociplastic pain include pain in multiple body regions, fatigue, sleep disturbances, cognitive dysfunction, depression and anxiety. Individuals with nociplastic pain are often diffusely tender - indicative of hyperalgesia and/or allodynia - and are often more sensitive than othersto non-painful sensory stimuli such as lights, odours and noises. This Review summarizes the risk factors, clinical presentation and treatment of nociplastic pain, and describes how alterations in brain function and structure, immune processing and peripheral factors might contribute to the nociplastic pain phenotype. This article concludes with a discussion of two proposed subtypes of nociplastic pain that reflect distinct neurobiological features and treatment responsivity.

Right thalamic volume mediates impact of the dopamine beta-hydroxylase gene on the endowment effect.

The endowment effect is a tendency that individuals overvalue items belonging to them relative to those items that do not. Previous studies showed a strong relation between the dopamine beta-hydroxylase (DBH) gene and the endowment effect (EE), and a link between EE and task-based functional MRI activation in multiple brain regions. However, the role of brain structure on EE remains unclear. In this study, we have explored whether regional brain volume mediate the effect of the DBH gene on EE. Results showed that rs1611115, single-nucleotide polymorphisms (SNPs) at DBH loci, were significantly associated with right thalamus volume and the endowment effect in males but not in female participants. Specifically, male DBH rs1611115 T-carriers had larger right thalamus volume compared to carriers of CC genotype and exhibited a greater endowment effect. Importantly, we found that right thalamus volume mediated the effect of rs1611115 on the endowment effect in male participants. This study demonstrated how thalamic volume plays an important mediating role between genetics and decision-making in humans.

Bipolar disorder staging and the impact it has on its management: an update.

The longitudinal course of bipolar disorder (BD) is associated with an active process of neuroprogression, characterized by structural brain alterations and progressive functional impairment. In the last decades, a growing need of a standardized staging model for BD arose, with the aim of a more appropriate definition of stage-specific clinical manifestations and the identification of more customized therapeutic tools. The authors review the literature on clinical aspects, neurobiological correlates and treatment issues related to BD progression. Thereafter, they address the definition, constructs, and evolution of the staging concept, focusing on the clinical applications of BD staging models available in literature. Although several staging models for BD have been proposed to date, their application in clinical practice is still relatively scant. This may have a detrimental impact on the clinical and therapeutic management of BD, in terms of early and proper diagnosis as well as tailored treatment interventions according to the different stages of illness. Future research efforts should tend to the integration of recent insights on neuroimaging and epigenetic markers, toward a standardized and multidimensional staging model.

Cross-Sectional Associations of Peripheral Hearing, Brain Imaging, and Cognitive Performance With Speech-in-Noise Performance: The Aging and Cognitive Health Evaluation in Elders Brain Magnetic Resonance Imaging Ancillary Study.

Population-based evidence in the interrelationships among hearing, brain structure, and cognition is limited. This study aims to investigate the cross-sectional associations of peripheral hearing, brain imaging measures, and cognitive function with speech-in-noise performance among older adults. We studied 602 participants in the Aging and Cognitive Health Evaluation in Elders (ACHIEVE) brain magnetic resonance imaging (MRI) ancillary study, including 427 ACHIEVE baseline (2018-2020) participants with hearing loss and 175 Atherosclerosis Risk in Communities Neurocognitive Study Visit 6/7 (2016-2017/2018-2019) participants with normal hearing. Speech-in-noise performance, as outcome of interest, was assessed by the Quick Speech-in-Noise (QuickSIN) test (range: 0-30; higher = better). Predictors of interest included (a) peripheral hearing assessed by pure-tone audiometry; (b) brain imaging measures: structural MRI measures, white matter hyperintensities, and diffusion tensor imaging measures; and (c) cognitive performance assessed by a battery of 10 cognitive tests. All predictors were standardized to z scores. We estimated the differences in QuickSIN associated with every standard deviation (SD) worse in each predictor (peripheral hearing, brain imaging, and cognition) using multivariable-adjusted linear regression, adjusting for demographic variables, lifestyle, and disease factors (Model 1), and, additionally, for other predictors to assess independent associations (Model 2). Participants were aged 70-84 years, 56% female, and 17% Black. Every SD worse in better-ear 4-frequency pure-tone average was associated with worse QuickSIN (-4.89, 95% confidence interval, CI [-5.57, -4.21]) when participants had peripheral hearing loss, independent of other predictors. Smaller temporal lobe volume was associated with worse QuickSIN, but the association was not independent of other predictors (-0.30, 95% CI [-0.86, 0.26]). Every SD worse in global cognitive performance was independently associated with worse QuickSIN (-0.90, 95% CI [-1.30, -0.50]). Peripheral hearing and cognitive performance are independently associated with speech-in-noise performance among dementia-free older adults. The ongoing ACHIEVE trial will elucidate the effect of a hearing intervention that includes amplification and auditory rehabilitation on speech-in-noise understanding in older adults. https://doi.org/10.23641/asha.25733679.

Investigating the neurobiology of maternal opioid use disorder and prenatal opioid exposure using brain organoid technology

Over the past two decades, Opioid Use Disorder (OUD) among pregnant women has become a major global public health concern. OUD has been characterized as a problematic pattern of opioid use despite adverse physical, psychological, behavioral, and or social consequences. Due to the relapsing–remitting nature of this disorder, pregnant mothers are chronically exposed to exogenous opioids, resulting in adverse neurological and neuropsychiatric outcomes. Collateral fetal exposure to opioids also precipitates severe neurodevelopmental and neurocognitive sequelae. At present, much of what is known regarding the neurobiological consequences of OUD and prenatal opioid exposure (POE) has been derived from preclinical studies in animal models and postnatal or postmortem investigations in humans. However, species-specific differences in brain development, variations in subject age/health/background, and disparities in sample collection or storage have complicated the interpretation of findings produced by these explorations. The ethical or logistical inaccessibility of human fetal brain tissue has also limited direct examinations of prenatal drug effects. To circumvent these confounding factors, recent groups have begun employing induced pluripotent stem cell (iPSC)-derived brain organoid technology, which provides access to key aspects of cellular and molecular brain development, structure, and function in vitro. In this review, we endeavor to encapsulate the advancements in brain organoid culture that have enabled scientists to model and dissect the neural underpinnings and effects of OUD and POE. We hope not only to emphasize the utility of brain organoids for investigating these conditions, but also to highlight opportunities for further technical and conceptual progress. Although the application of brain organoids to this critical field of research is still in its nascent stages, understanding the neurobiology of OUD and POE via this modality will provide critical insights for improving maternal and fetal outcomes.

Leveraging SO(3)-steerable convolutions for pose-robust semantic segmentation in 3D medical data

Convolutional neural networks (CNNs) allow for parameter sharing and translational equivariance by using convolutional kernels in their linear layers. By restricting these kernels to be SO(3)-steerable, CNNs can further improve parameter sharing and equivariance. These equivariant convolutional layers have several advantages over standard convolutional layers, including increased robustness to unseen poses, smaller network size, and improved sample efficiency. Despite this, most segmentation networks used in medical image analysis continue to rely on standard convolutional kernels. In this paper, we present a new family of segmentation networks that use equivariant voxel convolutions based on spherical harmonics. These SE(3)-equivariant volumetric segmentation networks, which are robust to data poses not seen during training, do not require rotation-based data augmentation during training. In addition, we demonstrate improved segmentation performance in MRI brain tumor and healthy brain structure segmentation tasks, with enhanced robustness to reduced amounts of training data and improved parameter efficiency. Code to reproduce our results, and to implement the equivariant segmentation networks for other tasks is available at &lt;a href='http://github.com/SCAN-NRAD/e3nn_Unet'&gt;http://github.com/SCAN-NRAD/e3nn_Unet&lt;/a&gt;.

Postnatal Brain Trajectories and Maternal Intelligence Predict Childhood Outcomes in Complex CHD

Objective: To determine whether early structural brain trajectories predict early childhood neurodevelopmental deficits in complex CHD patients and to assess relative cumulative risk profiles of clinical, genetic, and demographic risk factors across early development. Study Design: Term neonates with complex CHDs were recruited at Texas Children’s Hospital from 2005–2011. Ninety-five participants underwent three structural MRI scans and three neurodevelopmental assessments. Brain region volumes and white matter tract fractional anisotropy and radial diffusivity were used to calculate trajectories: perioperative, postsurgical, and overall. Gross cognitive, language, and visuo-motor outcomes were assessed with the Bayley Scales of Infant and Toddler Development and with the Wechsler Preschool and Primary Scale of Intelligence and Beery–Buktenica Developmental Test of Visual–Motor Integration. Multi-variable models incorporated risk factors. Results: Reduced overall period volumetric trajectories predicted poor language outcomes: brainstem ((β, 95% CI) 0.0977, 0.0382–0.1571; p = 0.0022) and white matter (0.0023, 0.0001–0.0046; p = 0.0397) at 5 years; brainstem (0.0711, 0.0157–0.1265; p = 0.0134) and deep grey matter (0.0085, 0.0011–0.0160; p = 0.0258) at 3 years. Maternal IQ was the strongest contributor to language variance, increasing from 37% at 1 year, 62% at 3 years, and 81% at 5 years. Genetic abnormality’s contribution to variance decreased from 41% at 1 year to 25% at 3 years and was insignificant at 5 years. Conclusion: Reduced postnatal subcortical–cerebral white matter trajectories predicted poor early childhood neurodevelopmental outcomes, despite high contribution of maternal IQ. Maternal IQ was cumulative over time, exceeding the influence of known cardiac and genetic factors in complex CHD, underscoring the importance of heritable and parent-based environmental factors.

Association between household size and risk of incident dementia in the UK Biobank study

Currently, the relationship between household size and incident dementia, along with the underlying neurobiological mechanisms, remains unclear. This prospective cohort study was based on UK Biobank participants aged ≥ 50 years without a history of dementia. The linear and non-linear longitudinal association was assessed using Cox proportional hazards regression and restricted cubic spline models. Additionally, the potential mechanisms driven by brain structures were investigated by linear regression models. We included 275,629 participants (mean age at baseline 60.45 years [SD 5.39]). Over a mean follow-up of 9.5 years, 6031 individuals developed all-cause dementia. Multivariable analyses revealed that smaller household size was associated with an increased risk of all-cause dementia (HR, 1.06; 95% CI 1.02–1.09), vascular dementia (HR, 1.08; 95% CI 1.01–1.15), and non-Alzheimer’s disease non-vascular dementia (HR, 1.09; 95% CI 1.03–1.14). No significant association was observed for Alzheimer’s disease. Restricted cubic splines demonstrated a reversed J-shaped relationship between household size and all-cause and cause-specific dementia. Additionally, substantial associations existed between household size and brain structures. Our findings suggest that small household size is a risk factor for dementia. Additionally, brain structural differences related to household size support these associations. Household size may thus be a potential modifiable risk factor for dementia.

Ultrasound Diagnosis and Near-Infrared Spectroscopy in the Study of Encephalopathy in Neonates Born under Asphyxia: Narrative Review

Ultrasound Diagnosis and Near-Infrared Spectroscopy in the Study of Encephalopathy in Neonates Born under Asphyxia: Narrative Review