Temporal Trends in Hippocampal Sclerosis Surgery: An Observational Study From a Tertiary Epilepsy Centre.

Objective: Temporal lobe epilepsy with hippocampal sclerosis (HS) is a surgically remediable syndrome. We determined temporal trends in the prevalence of hippocampal sclerosis surgeries and related factors.

Methods: We analysed a prospective cohort of adults who underwent epilepsy surgery at the NHNN, London, between 1990 and 2019.

Developing structured clinical review templates in an integrated respiratory team during COVID-19: a qualitative review.

Introduction: In response to the SARS-CoV-2 pandemic in March 2020 and required adherence to infection control measures and patient and staff safety, an integrated respiratory team (IRT) developed guideline-based templates to support the team in teleconsultation reviews of their patients. Patients had been diagnosed with sleep disordered breathing, chronic obstructive pulmonary disease, asthma, interstitial lung disease or had oxygen assessment needs.

Methods: Nine IRT members collaboratively developed content for the templates to assist in clinical reviews.

Parietal alpha stimulation causally enhances attentional information coding in evoked and oscillatory activity.

Background: Selective attention is a fundamental cognitive mechanism that allows people to prioritise task-relevant information while ignoring irrelevant information. Previous research has suggested key roles of parietal event-related potentials (ERPs) and alpha oscillatory responses in attention tasks. However, the informational content of these signals is less clear, and their causal effects on the coding of multiple task elements are yet unresolved.

A Hybrid Transformer-Convolutional Neural Network for Segmentation of Intracerebral Hemorrhage and Perihematomal Edema on Non-Contrast Head Computed Tomography (CT) with Uncertainty Quantification to Improve Confidence.

Intracerebral hemorrhage (ICH) and perihematomal edema (PHE) are key imaging markers of primary and secondary brain injury in hemorrhagic stroke. Accurate segmentation and quantification of ICH and PHE can help with prognostication and guide treatment planning. In this study, we combined Swin-Unet Transformers with nnU-NETv2 convolutional network for segmentation of ICH and PHE on non-contrast head CTs.

Style mixup enhanced disentanglement learning for unsupervised domain adaptation in medical image segmentation.

Unsupervised domain adaptation (UDA) has shown impressive performance by improving the generalizability of the model to tackle the domain shift problem for cross-modality medical segmentation. However, most of the existing UDA approaches depend on high-quality image translation with diversity constraints to explicitly augment the potential data diversity, which is hard to ensure semantic consistency and capture domain-invariant representation. In this paper, free of image translation and diversity constraints, we propose a novel Style Mixup Enhanced Disentanglement Learning (SMEDL) for UDA medical image segmentation to further improve domain generalization and enhance domain-invariant learning ability.

A cross-sectional survey of farmer reported prevalence and farm management practices associated with neonatal infectious arthritis ("joint ill") in lambs, on UK sheep farms.

Introduction: Neonatal infectious arthritis (NIA) is a bacterial disease of lambs in the first month of life. NIA is associated with poor animal welfare, economic losses, and prophylactic antibiotic use. Farmers report problems with NIA despite following current guidance on prevention.

Progression of the faecal microbiome in preweaning dairy calves that develop cryptosporidiosis.

Background: Cryptosporidiosis is a diarrheal disease that commonly affects calves under 6 weeks old. The causative agent, Cryptosporidium parvum, has been associated with the abundance of specific taxa in the faecal microbiome during active infection. However, the long-term impact of these microbiome shifts, and potential effects on calf growth and health have not yet been explored in depth.

Part-based processing, but not holistic processing, predicts individual differences in face recognition abilities.

This study aimed to assess the roles of part-based and holistic processing for face processing ability (FPA). A psychophysical paradigm in which the efficiency at recognizing isolated or combined facial parts was used (N = 64), and holistic processing was defined as the perceptual integration from multiple parts. FPA and object processing ability were measured using a battery of tasks.

Comparison of umbilical artery pulsatility index reference ranges.

Objective: To compare the accuracy of four published reference standards for the umbilical artery pulsatility index (UA-PI) in predicting small-for-gestational age (SGA), adverse neonatal outcomes and obstetric complications in pregnancies at risk for fetal growth restriction.

Methods: This was a secondary analysis of a prospective study of singleton pregnancies that underwent fetal growth assessment by ultrasound between 26 and 36 weeks' gestation. Pregnancies with estimated fetal weight or abdominal circumference < 20 percentile with UA-PI measurements available were included.

Evaluating data sharing statements in leading emergency medicine journals: A mixed methods review.

Background: Emergency medicine remains as the front line of healthcare, providing acute care to a diverse population during urgent and critical moments. Our objective was to systematically quantify the prevalence of data sharing statements (DSS) in high-impact emergency medicine journals and assess their implementation by contacting corresponding authors who indicated data available upon request.

Methods: We conducted a cross-sectional analysis to identify the prevalence and content of data sharing statements in clinical studies published in high impact emergency medicine journals between 2018 and 2023, followed by a hierarchical logistic regression analysis to identify variables impacting the incorporation of data sharing statements into emergency medicine studies.

Investigating Falls Risk Awareness in Hospitals Using the Self-Awareness of Falls Risk Measure (SAFRM): Empirical Research Quantitative.

Aim: The overarching aim of this study was to explore patients' falls risk awareness in hospitals using section A of the validated Self Awareness of Falls Risk Measure (SAFRM).

Design: Descriptive cross-sectional study design.

Setting: Three rural/regional hospitals in the State of Victoria, Australia.

Brain Hypertrophy in Patients With Mesial Temporal Lobe Epilepsy With Hippocampal Sclerosis and Its Clinical Correlates.

Background And Objectives: Mesial temporal lobe epilepsy (mTLE) is generally associated with focal brain atrophy, but little knowledge exists on possible disease-related hypertrophy of brain structures. We hypothesized that repeated seizures or adaptive plasticity may lead to focal brain hypertrophy and aimed to investigate associated clinical correlates.

Methods: In this cohort study, we included patients with mTLE undergoing detailed epilepsy evaluations and matched healthy volunteers (HVs) from 2 tertiary centers (discovery and validation cohorts).

SPECTRAL BRAIN GRAPH NEURAL NETWORK FOR PREDICTION OF ANXIETY IN CHILDREN WITH AUTISM SPECTRUM DISORDER.

Children with Autism Spectrum Disorder (ASD) frequently exhibit comorbid anxiety, which contributes to impairment and requires treatment. Therefore, it is critical to investigate co-occurring autism and anxiety with functional imaging tools to understand the brain mechanisms of this comorbidity. Multidimensional Anxiety Scale for Children, 2nd edition (MASC-2) score is a common tool to evaluate the daily anxiety level in autistic children.

Aperiodic and oscillatory systems underpinning human domain-general cognition.

Domain-general cognitive systems are essential for adaptive human behaviour, supporting various cognitive tasks through flexible neural mechanisms. While fMRI studies link frontoparietal network activation to increasing demands across various tasks, the electrophysiological mechanisms underlying this domain-general response to demand remain unclear. Here, we used MEG/EEG, and separated the aperiodic and oscillatory components of the signals to examine their roles in domain-general cognition across three cognitive tasks using multivariate analysis.

Alpha rhythm slowing in temporal lobe epilepsy across scalp EEG and MEG.

EEG slowing is reported in various neurological disorders including Alzheimer's, Parkinson's and Epilepsy. Here, we investigate alpha rhythm slowing in individuals with refractory temporal lobe epilepsy compared with healthy controls, using scalp EEG and magnetoencephalography. We retrospectively analysed data from 17 (46) healthy controls and 22 (24) individuals with temporal lobe epilepsy who underwent scalp EEG and magnetoencephalography recordings as part of presurgical evaluation.

Inherited Retinal Degenerations and Non-Neovascular Age-Related Macular Degeneration: Progress and Unmet Needs.

Inherited retinal degeneration (IRD) disease and age-related macular degeneration (AMD) are leading causes of irreversible vision loss and blindness. Although significant progress has advanced the field in the past 5 years, significant challenges remain. The current article reviews the accomplishments and research advances that have fueled the development of treatments for patients with IRD and AMD, including the first approved gene-augmentation treatment for RPE65-related retinal degeneration and complement inhibition therapies to slow progression of geographic atrophy (GA) in AMD.

AI-Powered Multimodal Modeling of Personalized Hemodynamics in Aortic Stenosis.

Aortic stenosis (AS) is the most common valvular heart disease in developed countries. High-fidelity preclinical models can improve AS management by enabling therapeutic innovation, early diagnosis, and tailored treatment planning. However, their use is currently limited by complex workflows necessitating lengthy expert-driven manual operations.

The dimensionality of neural coding for cognitive control is gradually transformed within the lateral prefrontal cortex.

Implementing cognitive control relies on neural representations that are inherently high-dimensional and distributed across multiple subregions in the prefrontal cortex (PFC). Traditional approaches tackle prefrontal representation by reducing it into a unidimensional measure (univariate amplitude) or using them to distinguish a limited number of alternatives (pattern classification). By contrast, representational similarity analysis (RSA) enables flexibly formulating various hypotheses about informational contents underlying the neural codes, explicitly comparing hypotheses, and examining the representational alignment between brain regions.

Protection against induced by OMV-based Meningococcal Vaccines are associated with cross-species directed humoral and cellular immune responses.

Limited protective immunologic responses to natural infection and a lack of knowledge about mechanisms of protection have hampered development of an effective vaccine. Recent studies in humans and mice have found meningococcal outer membrane vesicle-containing vaccines (OMV) induce cross species immune responses against gonococci and are associated with protection. The exact mechanisms or how humoral and cellular immunity are related to protection, remain unclear.

Construction and use of mental models: Organizing principles for the science of brain and mind.

As an organizing framework for questions of mind and brain, I discuss how the brain builds and uses mental models. Mental models provide a complex, structured description of some situation in the world. The role of perception is to build such a model for the current environment; knowledge provides many of the building blocks; in episodic memory, a previous model is reinstated; in cognitive control, the model dictates a choice of action.

Update on syphilis diagnostics.

Purpose Of Review: Syphilis is rising globally, with resultant increases in morbidity and mortality that disproportionately impact underserved populations. Appropriate screening and testing for syphilis with accurate, reliable, affordable, and timely assays is crucial for combating this epidemic. This review provides a brief overview of laboratory methods for syphilis diagnosis, with a focus on recent updates in diagnostics and directions for future research.

Calibrating Multi-modal Representations: A Pursuit of Group Robustness without Annotations.

Fine-tuning pre-trained vision-language models, like CLIP, has yielded success on diverse downstream tasks. However, several pain points persist for this paradigm: (i) directly tuning entire pre-trained models becomes both time-intensive and computationally costly. Additionally, these tuned models tend to become highly specialized, limiting their practicality for real-world deployment; (ii) recent studies indicate that pre-trained vision-language classifiers may overly depend on spurious features - patterns that correlate with the target in training data, but are not related to the true labeling function; and (iii) existing studies on mitigating the reliance on spurious features, largely based on the assumption that we can identify such features, does not provide definitive assurance for real-world applications.