Sex Differences in Human Brain Structure at Birth.

Background: Sex differences in human brain anatomy have been well-documented, though remain significantly underexplored during early development. The neonatal period is a critical stage for brain development and can provide key insights into the role that prenatal and early postnatal factors play in shaping sex differences in the brain.

Methods: Here, we assessed on-average sex differences in global and regional brain volumes in 514 newborns aged 0-28 days (236 birth-assigned females and 278 birth-assigned males) using data from the developing Human Connectome Project.

Molecular and micro-architectural mapping of gray matter alterations in psychosis.

The psychosis spectrum encompasses a heterogeneous range of clinical conditions associated with abnormal brain development. Detecting patterns of atypical neuroanatomical maturation across psychiatric disorders requires an interpretable metric standardized by age-, sex- and site-effect. The molecular and micro-architectural attributes that account for these deviations in brain structure from typical neurodevelopment are still unknown.

Machine learning in small sample neuroimaging studies: Novel measures for schizophrenia analysis.

Novel features derived from imaging and artificial intelligence systems are commonly coupled to construct computer-aided diagnosis (CAD) systems that are intended as clinical support tools or for investigation of complex biological patterns. This study used sulcal patterns from structural images of the brain as the basis for classifying patients with schizophrenia from unaffected controls. Statistical, machine learning and deep learning techniques were sequentially applied as a demonstration of how a CAD system might be comprehensively evaluated in the absence of prior empirical work or extant literature to guide development, and the availability of only small sample datasets.

Brain tumour microstructure is associated with post-surgical cognition.

Brain tumour microstructure is potentially predictive of changes following treatment to cognitive functions subserved by the functional networks in which they are embedded. To test this hypothesis, intra-tumoural microstructure was quantified from diffusion-weighted MRI to identify which tumour subregions (if any) had a greater impact on participants' cognitive recovery after surgical resection. Additionally, we studied the role of tumour microstructure in the functional interaction between the tumour and the rest of the brain.

Tumour-infiltrated cortex participates in large-scale cognitive circuits.

The extent to which tumour-infiltrated brain tissue contributes to cognitive function remains unclear. We tested the hypothesis that cortical tissue infiltrated by diffuse gliomas participates in large-scale cognitive circuits using a unique combination of intracranial electrocorticography (ECoG) and resting-state functional magnetic resonance (fMRI) imaging in four patients. We also assessed the relationship between functional connectivity with tumour-infiltrated tissue and long-term cognitive outcomes in a larger, overlapping cohort of 17 patients.

Disease trajectories in older adults with non-AD pathologic change and comparison with Alzheimer's disease pathophysiology: A longitudinal study.

Based on the 'AT(N)' system, individuals with normal amyloid biomarkers but abnormal tauopathy or neurodegeneration biomarkers are classified as non-Alzheimer's disease (AD) pathologic change. This study aimed to assess the long-term clinical and cognitive trajectories of individuals with non-AD pathologic change among older adults without dementia, comparing them to those with normal AD biomarkers and AD pathophysiology. Analyzing Alzheimer's Disease Neuroimaging Initiative data, we evaluated clinical outcomes and conversion risk longitudinally using mixed effects models and multivariate Cox proportional hazard models.

Applications of machine learning and deep learning in SPECT and PET imaging: General overview, challenges and future prospects.

The integration of positron emission tomography (PET) and single-photon emission computed tomography (SPECT) imaging techniques with machine learning (ML) algorithms, including deep learning (DL) models, is a promising approach. This integration enhances the precision and efficiency of current diagnostic and treatment strategies while offering invaluable insights into disease mechanisms. In this comprehensive review, we delve into the transformative impact of ML and DL in this domain.

Multipredictor risk models for predicting individual risk of Alzheimer's disease.

Background: Early prevention of Alzheimer's disease (AD) is a feasible way to delay AD onset and progression. Information on AD prediction at the individual patient level will be useful in AD prevention. In this study, we aim to develop risk models for predicting AD onset at individual level using optimal set of predictors from multiple features.

Network analysis of inflammation and symptoms in recent onset schizophrenia and the influence of minocycline during a clinical trial.

Attempts to delineate an immune subtype of schizophrenia have not yet led to the clear identification of potential treatment targets. An unbiased informatic approach at the level of individual immune cytokines and symptoms may reveal organisational structures underlying heterogeneity in schizophrenia, and potential for future therapies. The aim was to determine the network and relative influence of pro- and anti-inflammatory cytokines on depressive, positive, and negative symptoms.

Characterizing Subcortical Structural Heterogeneity in Autism.

Autism presents with significant phenotypic and neuroanatomical heterogeneity, and neuroimaging studies of the thalamus, globus pallidus and striatum in autism have produced inconsistent and contradictory results. These structures are critical mediators of functions known to be atypical in autism, including sensory gating and motor function. We examined both volumetric and fine-grained localized shape differences in autism using a large (=3145, 1045-1318 after strict quality control), cross-sectional dataset of T1-weighted structural MRI scans from 32 sites, including both males and females (assigned-at-birth).

Intra-operative applications of augmented reality in glioma surgery: a systematic review.

Background: Augmented reality (AR) is increasingly being explored in neurosurgical practice. By visualizing patient-specific, three-dimensional (3D) models in real time, surgeons can improve their spatial understanding of complex anatomy and pathology, thereby optimizing intra-operative navigation, localization, and resection. Here, we aimed to capture applications of AR in glioma surgery, their current status and future potential.

Potential cognitive and neural benefits of a computerised cognitive training programme based on Structure Learning in healthy adults: study protocol for a randomised controlled trial.

Background: Cognitive flexibility refers to the capacity to shift between conceptual representations particularly in response to changes in instruction and feedback. It enables individuals to swiftly adapt to changes in their environment and has significant implications for learning. The present study focuses on investigating changes in cognitive flexibility following an intervention programme-Structure Learning training.

Study protocol: How does cognitive flexibility relate to other executive functions and learning in healthy young adults?

Background: Cognitive flexibility (CF) enables individuals to readily shift from one concept or mode of practice/thoughts to another in response to changes in the environment and feedback, making CF vital to optimise success in obtaining goals. However, how CF relates to other executive functions (e.g.

Inflammatory subgroups of schizophrenia and their association with brain structure: A semi-supervised machine learning examination of heterogeneity.

Objective: Immune system dysfunction is hypothesised to contribute to structural brain changes through aberrant synaptic pruning in schizophrenia. However, evidence is mixed and there is a lack of evidence of inflammation and its effect on grey matter volume (GMV) in patients. We hypothesised that inflammatory subgroups can be identified and that the subgroups will show distinct neuroanatomical and neurocognitive profiles.

Pharmacological treatment of neuropsychiatric symptoms of dementia: a network meta-analysis.

Background: Pharmacological treatments are very common to be used for alleviating neuropsychiatric symptoms (NPS) in dementia. However, decision on drug selection is still a matter of controversy.

Aims: To summarise the comparative efficacy and acceptability of currently available monotherapy drug regimens for reducing NPS in dementia.

Disease trajectories in elders with suspected non-Alzheimer's pathophysiology and its comparison with Alzheimer's disease pathophysiology: a longitudinal study.

Background: According to the new 'AT(N)' system, those with a normal amyloid biomarker but with abnormal tauopathy or biomarkers of neurodegeneration or neuronal injury, have been labeled suspected non-Alzheimer's pathophysiology (SNAP). We aimed to estimate the long-term clinical and cognitive trajectories of SNAP individuals in non-demented elders and its comparison with individual in the Alzheimer's disease (AD) pathophysiology using 'AT(N)' system.

Methods: We included individuals with available baseline cerebrospinal fluid (CSF) Aβ (A), CSF phosphorylated tau examination (T) and 18F-uorodeoxyglucose PET or volumetric magnetic resonance imaging (N) from the Alzheimer's Disease Neuroimaging Initiative database.

Identifying modifiable factors and their joint effect on dementia risk in the UK Biobank.

Previous hypothesis-driven research has identified many risk factors linked to dementia. However, the multiplicity and co-occurrence of risk factors have been underestimated. Here we analysed data of 344,324 participants from the UK Biobank with 15 yr of follow-up data for 210 modifiable risk factors.

Protocol for the Psychosis Immune Mechanism Stratified Medicine (PIMS) trial: a randomised double-blind placebo-controlled trial of single-dose tocilizumab in patients with psychosis.

Introduction: Evidence suggests a potentially causal role of interleukin 6 (IL-6), a pleiotropic cytokine that generally promotes inflammation, in the pathogenesis of psychosis. However, no interventional studies in patients with psychosis, stratified using inflammatory markers, have been conducted to assess the therapeutic potential of targeting IL-6 in psychosis and to elucidate potential mechanism of effect. Tocilizumab is a humanised monoclonal antibody targeting the IL-6 receptor to inhibit IL-6 signalling, licensed in the UK for treatment of rheumatoid arthritis.

Brain network mapping and glioma pathophysiology.

Adult diffuse gliomas are among the most difficult brain disorders to treat in part due to a lack of clarity regarding the anatomical origins and mechanisms of migration of the tumours. While the importance of studying networks of glioma spread has been recognized for at least 80 years, the ability to carry out such investigations in humans has emerged only recently. Here, we comprehensively review the fields of brain network mapping and glioma biology to provide a primer for investigators interested in merging these areas of inquiry for the purposes of translational research.

A Phenome-wide Association and Mendelian Randomization Study for Alzheimer's Disease: A Prospective Cohort Study of 502,493 Participants From the UK Biobank.

Background: Considerable uncertainty remains regarding associations of multiple risk factors with Alzheimer's disease (AD). We aimed to systematically screen and validate a wide range of potential risk factors for AD.

Methods: Among 502,493 participants from the UK Biobank, baseline data were extracted for 4171 factors spanning 10 different categories.

HUMANISE: Human-Inspired Smart Management, towards a Healthy and Safe Industrial Collaborative Robotics.

The workplace is evolving towards scenarios where humans are acquiring a more active and dynamic role alongside increasingly intelligent machines. Moreover, the active population is ageing and consequently emerging risks could appear due to health disorders of workers, which requires intelligent intervention both for production management and workers' support. In this sense, the innovative and smart systems oriented towards monitoring and regulating workers' well-being will become essential.