Temporal dynamics of neonatal hypoxic-ischemic encephalopathy injuries on magnetic resonance imaging.

Moderate to severe perinatal hypoxic-ischemic encephalopathy occurs in ~ 1 to 3/1000 live births in high-income countries and is associated with a significant risk of death or neurodevelopmental disability. Detailed assessment is important to help identify high-risk infants, to help families, and to support appropriate interventions. A wide range of monitoring tools is available to assess changes over time, including urine and blood biomarkers, neurological examination, and electroencephalography.

Socioeconomic Status and Lifestyle Factors Differences in the Association Between Dietary Patterns and Metabolic Syndrome: Tehran Lipid and Glucose Study.

Socioeconomic status and lifestyle factors could potentially modify the association between diet and chronic diseases such as metabolic syndrome (MetS). This study aimed to investigate the combined effect of socioeconomic status, lifestyle factors, and dietary patterns on the MetS risk. During 8.

Role of dietary patterns in older adults with cognitive disorders: An umbrella review utilizing neuroimaging biomarkers.

Various dietary patterns (DPs) may benefit or harm cognitive status through their components. Publications assessing the impact of DPs on cognitive scores using neuropsychological tests have often led to less promising results. Recently, numerous meta-analyses and systematic reviews have utilized neuroimaging to identify more subtle brain-associated alterations related to cognition.

Phenotypic approaches for CNS drugs.

Central nervous system (CNS) drug development is plagued by high clinical failure rate. Phenotypic assays promote clinical translation of drugs by reducing complex brain diseases to measurable, clinically valid phenotypes. We critique recent platforms integrating patient-derived brain cells, which most accurately recapitulate CNS disease phenotypes, with higher throughput models, including immortalized cells, to balance validity and scalability.

Iron-Status Indicators and HFE Gene Polymorphisms in Individuals with Amyotrophic Lateral Sclerosis: An Umbrella Review of Meta-analyses and Systematic Reviews.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by the progressive loss of motor neurons. Recent meta-analyses and systematic reviews suggest that HFE gene polymorphisms and iron-associated biomarkers may play a key role in the risk and occurrence of ALS. This umbrella study aimed to explore the roles of HFE gene polymorphisms and iron-associated biomarkers in individuals with ALS.

Effects of coffee and tea consumption on glioma risk: An umbrella review of systematic reviews and meta-analyses.

Background: Coffee and tea are considered to have some effects on the risk of glioma as one of the most prevalent intracranial malignant tumors in adults. However, the precise effect of coffee and tea consumption on glioma is not obvious. This umbrella review aimed to evaluate the impact of tea and coffee consumption on glioma risk.

Exploring the efficacy and safety of cannabidiol in individuals with epilepsy: an umbrella review of meta-analyses and systematic reviews.

Background: Epilepsy ranks among the most prevalent neurological conditions worldwide. Cannabidiol (CBD) has received authorization for epilepsy treatment, yet utilizing CBD is linked to a variety of adverse events (AEs). This umbrella review aims to explore risk and frequency of AEs in epilepsy patients undergoing treatment with CBD.

Designing a model of emergency medical services preparedness in response to mass casualty incidents: a mixed-method study.

Background: Emergency medical services preparedness in mass casualty incidents is one of the most important concerns in emergency systems. A mass casualty incident is a sudden event with several injured individuals that overwhelms the local health care system. This study aimed to identify and validate the components of emergency medical services readiness in mass casualty incidents which ultimately led to designing a conceptual model.

Screw Stimulation Thresholds for Neuromonitoring in Minimally Invasive Oblique Lateral Lumbar Interbody Fusion (OLLIF): A Correlational Study.

Introduction: This study presents findings from an investigation into the correlation of neuromonitoring techniques in minimally invasive lumbar fusions and their open counterparts regarding acceptable thresholds for screw stimulation. The threshold for acceptable stimulation value for open surgery has been established. The study compared acceptable thresholds for open pedicle screws where there is more connection between the screw and the soft tissue.

The Link Between Vitamin D and the Risk of Aneurysmal Subarachnoid Hemorrhage: A Systematic Review.

Background: Vitamin D (VD) is one of the fat-soluble vitamins proposed to be associated with aSAH. According to the clinical evidence, this investigation explores the link between VD concentrations and clinical outcomes in aSAH patients.

Methods: This systematic review was executed based on the PRISMA 2020 statement.

Deep Learning for Generalized EEG Seizure Detection after Hypoxia-Ischemia-Preclinical Validation.

Brain maturity and many clinical treatments such as therapeutic hypothermia (TH) can significantly influence the morphology of neonatal EEG seizures after hypoxia-ischemia (HI), and so there is a need for generalized automatic seizure identification. This study validates efficacy of advanced deep-learning pattern classifiers based on a convolutional neural network (CNN) for seizure detection after HI in fetal sheep and determines the effects of maturation and brain cooling on their accuracy. The cohorts included HI-normothermia term ( = 7), HI-hypothermia term ( = 14), sham-normothermia term ( = 5), and HI-normothermia preterm ( = 14) groups, with a total of >17,300 h of recordings.

Deep-Learning Markerless Tracking of Infant General Movements using Standard Video Recordings.

Monitoring spontaneous General Movements (GM) of infants 6-20 weeks post-term age is a reliable tool to assess the quality of neurodevelopment in early infancy. Abnormal or absent GMs are reliable prognostic indicators of whether an infant is at risk of developing neurological impairments and disorders such as cerebral palsy (CP). Therapeutic interventions are most effective at improving neuromuscular outcomes if administered in early infancy.

Atlas-Free Automatic Segmentation of Sheep Brain MRI.

Automated 3D brain segmentation methods have been shown to produce fast, reliable, and reproducible segmentations from magnetic resonance imaging (MRI) sequences for the anatomical structures of the human brain. Despite the extensive experimental research utility of large animal species such as the sheep, there is limited literature on the segmentation of their brains relative to that of humans. The availability of automatic segmentation algorithms for animal brain models can have significant impact for experimental explorations, such as treatment planning and studying brain injuries.

2D Wavelet-Scalogram Deep-Learning for Seizures Pattern Identification in the Post-Hypoxic-Ischemic EEG of Preterm Fetal Sheep.

Neonatal seizures after an hypoxic-ischemic (HI) event in preterm newborns can contribute to neural injury and cause impaired brain development. Preterm neonatal seizures are often not detected or their occurrence underestimated. Therefore, there is a need to improve knowledge about preterm seizures that can help establish diagnostic tools for accurate identification of seizures and for determining morphological differences.

Simultaneous acute portal vein thrombosis and ST elevation myocardial infarction in a Covid-19 patient - Case report.

Background: Covid-19 infected patients without any risk factors and family history of a thrombotic event can be still at risks of developing thrombotic and/or other Covid-19-related complications, and therefore, there is a substantial need to study such cases.

Case Presentation: In this study, we present a 60-years-old Covid-19 patient with mild symptoms who was admitted to the hospital with simultaneous arterial and venous thrombotic event, with chief complaint of chest pain and vague abdominal pain. The patient was diagnosed with Covid-19 two weeks before admission to the ICU.

Visual transformer and deep CNN prediction of high-risk COVID-19 infected patients using fusion of CT images and clinical data.

Background: Despite the globally reducing hospitalization rates and the much lower risks of Covid-19 mortality, accurate diagnosis of the infection stage and prediction of outcomes are clinically of interest. Advanced current technology can facilitate automating the process and help identifying those who are at higher risks of developing severe illness. This work explores and represents deep-learning-based schemes for predicting clinical outcomes in Covid-19 infected patients, using Visual Transformer and Convolutional Neural Networks (CNNs), fed with 3D data fusion of CT scan images and patients' clinical data.

Emergency medical services preparedness in mass casualty incidents: A systematic review.

Objective: The role of emergency medical services (EMS) preparedness in mass casualty incidents (MCIs) is crucial. MCIs are increasing worldwide, and EMS must enhance preparedness for them. For this purpose, the main components of EMS preparedness should be identified.

Deep-learning-based markerless tracking of distal anatomical landmarks in clinically recorded videos for assessing infant movement patterns associated with neurodevelopmental status.

Abnormal patterns in infants' General Movements (GMs) are robust clinical indicators for the progression of neurodevelopmental disorders, including cerebral palsy. Availability of automated platforms for General Movements Assessments (GMA) could improve screening rate and allow identifying at-risk infants. While we have previously shown that deep-learning schemes can accurately track the longitudinal axes of infant limb movements (12 anatomical locations, 3 per limb), information about the distal limb segments' rotational movements is important for making an accurate clinical assessment, but has not previously been captured.

Emergency medical services preparedness in mass casualty incidents: A qualitative study.

Background And Aims: The effective response of emergency medical services in mass casualty incidents (MCIs) calls for sufficient preparation. The components of preparation must be determined first to achieve this goal. This study aimed to describe the elements of preparedness of emergency medical services for MCIs.