Domain Adversarial Convolutional Neural Network Improves the Accuracy and Generalizability of Wearable Sleep Assessment Technology.

Wearable accelerometers are widely used as an ecologically valid and scalable solution for long-term at-home sleep monitoring in both clinical research and care. In this study, we applied a deep learning domain adversarial convolutional neural network (DACNN) model to this task and demonstrated that this new model outperformed existing sleep algorithms in classifying sleep-wake and estimating sleep outcomes based on wrist-worn accelerometry. This model generalized well to another dataset based on different wearable devices and activity counts, achieving an accuracy of 80.

Frequency of Acute Kidney Injury in Patients Admitted With Acute Stroke at Hayatabad Medical Complex, Peshawar.

Background Patients hospitalized with acute stroke are at risk of developing acute kidney injury (AKI), and when both conditions occur together, patient outcomes are often worse. The relationship between stroke type, patient characteristics, and the development of AKI is not fully understood, particularly in tertiary care settings in Pakistan, where healthcare resources and patient characteristics may differ from Western populations. Objective To determine the frequency of AKI and identify associated risk factors, including stroke type, severity, and comorbidities, in patients presenting with acute stroke at a tertiary care center in Pakistan, the Hayatabad Medical Complex, Peshawar.

Differential late-stage face processing in autism: a magnetoencephalographic study of fusiform gyrus activation.

Background: Autism is associated with alterations of social communication, such as during face-to-face interactions. This study aimed to probe face processing in autistics with normal IQ utilizing magnetoencephalography to examine event-related fields within the fusiform gyrus during face perception.

Methods: A case-control cohort of 22 individuals diagnosed with autism and 20 age-matched controls (all male, age 29.

Capacity building and enhancing knowledge of the healthcare providers on inappropriate practices and dispensing of antimicrobials.

This paper reports on the training programme, aimed for healthcare providers on the concepts of antimicrobial resistance (AMR) and build their understanding and knowledge on the causes and factors contributing to the AMR hence reducing the burden on the healthcare systems. A team of experts developed the curriculum and teaching material. A 2-day training workshop was conducted which included the pre- and post-knowledge assessment of the participants on AMR.

Antibiogram and Antibiotic Resistance Patterns in Bacterial Isolates from Hayatabad Medical Complex, Peshawar.

Background Empirical antibiotic therapy is facilitated by antibiograms as they provide local bacterial resistance data and patterns. Antibiograms are critical tools that offer comprehensive, institution-specific information on antimicrobial susceptibilities, enabling clinicians to make informed decisions about empirical treatment and guiding antimicrobial stewardship efforts. The rising incidence of multidrug-resistant (MDR) organisms is a significant challenge in countries like Pakistan.

Using large language models for safety-related table summarization in clinical study reports.

Objectives: The generation of structured documents for clinical trials is a promising application of large language models (LLMs). We share opportunities, insights, and challenges from a competitive challenge that used LLMs for automating clinical trial documentation.

Materials And Methods: As part of a challenge initiated by Pfizer (organizer), several teams (participant) created a pilot for generating summaries of safety tables for clinical study reports (CSRs).

Delays in latencies of median-nerve evoked magnetic fields in patients with succinic semialdehyde dehydrogenase deficiency.

Objective: Succinic semialdehyde dehydrogenase deficiency (SSADHD) is a genetic disorder resulting in abnormal regulation of γ-aminobutyric acid, lipid metabolism, and myelin biogenesis, leading to ataxia, seizures, and cognitive impairment. Since the myelin sheath is thinner in a murine model of SSADHD compared to a wild type, we hypothesized that this also holds for human brain. We tested whether the conduction velocity in the somatosensory pathway is accordingly delayed.

Characterizing directional dynamics of semantic prediction based on inter-regional temporal generalization.

The event-related potential/field component N400(m) has been widely used as a neural index for semantic prediction. It has long been hypothesized that feedback information from inferior frontal areas plays a critical role in generating the N400. However, due to limitations in causal connectivity estimation, direct testing of this hypothesis has remained difficult.

The caring competencies of nursing students: Comparing the four and two-year Bachelor of Nursing Programme.

The study was conducted to determine and compare the caring behaviours of nursing students in four-year BS Nursing (Bachelor of Science in nursing) and two-year Post- RN BSN (Registered nurse to Bachelor of Science in Nursing) programmes. A cross-sectional analytical study was conducted in the nursing institutes of KP from July to September 2022. The sample size was 383 calculated by using the Rao soft sample size calculator.

SciKit digital health package for accelerometry-measured physical activity: comparisons to existing solutions and investigations of age effects in healthy adults.

Introduction: Accelerometry has become increasingly prevalent to monitor physical activity due to its low participant burden, quantitative metrics, and ease of deployment. Physical activity metrics are ideal for extracting intuitive, continuous measures of participants' health from multiple days or weeks of high frequency data due to their fairly straightforward computation. Previously, we released an open-source digital health python processing package, SciKit Digital Health (SKDH), with the goal of providing a unifying device-agnostic framework for multiple digital health algorithms, such as activity, gait, and sleep.

Both stronger and weaker cerebro-cerebellar functional connectivity patterns during processing of spoken sentences in autism spectrum disorder.

Cerebellar differences have long been documented in autism spectrum disorder (ASD), yet the extent to which such differences might impact language processing in ASD remains unknown. To investigate this, we recorded brain activity with magnetoencephalography (MEG) while ASD and age-matched typically developing (TD) children passively processed spoken meaningful English and meaningless Jabberwocky sentences. Using a novel source localization approach that allows higher resolution MEG source localization of cerebellar activity, we found that, unlike TD children, ASD children showed no difference between evoked responses to meaningful versus meaningless sentences in right cerebellar lobule VI.

Biallelic MED27 variants lead to variable ponto-cerebello-lental degeneration with movement disorders.

MED27 is a subunit of the Mediator multiprotein complex, which is involved in transcriptional regulation. Biallelic MED27 variants have recently been suggested to be responsible for an autosomal recessive neurodevelopmental disorder with spasticity, cataracts and cerebellar hypoplasia. We further delineate the clinical phenotype of MED27-related disease by characterizing the clinical and radiological features of 57 affected individuals from 30 unrelated families with biallelic MED27 variants.

Sex-related patterns in the electroencephalogram and their relevance in machine learning classifiers.

Deep learning is increasingly being proposed for detecting neurological and psychiatric diseases from electroencephalogram (EEG) data but the method is prone to inadvertently incorporate biases from training data and exploit illegitimate patterns. The recent demonstration that deep learning can detect the sex from EEG implies potential sex-related biases in deep learning-based disease detectors for the many diseases with unequal prevalence between males and females. In this work, we present the male- and female-typical patterns used by a convolutional neural network that detects the sex from clinical EEG (81% accuracy in a separate test set with 142 patients).

Interference mitigation in intentional jammers aided non-uniform heterogeneous cellular networks.

Coverage and capacity are optimized in fifth generation (5G) networks by small base station (SBS) distribution in the coverage realm of macro base station (MBS). However, system performance is significantly reduced by inter-cell interference (ICI) because of the orthogonal frequency division multiple access assumption. In addition to ICI, this work considers intentional jammers' interference (IJI) due to the presence of jammers.

Exome sequencing in a Romanian Bardet-Biedl syndrome cohort revealed an overabundance of causal BBS12 variants.

Bardet-Biedl syndrome (BBS), is an emblematic ciliopathy hallmarked by pleiotropy, phenotype variability, and extensive genetic heterogeneity. BBS is a rare (~1/140,000 to ~1/160,000 in Europe) autosomal recessive pediatric disorder characterized by retinal degeneration, truncal obesity, polydactyly, cognitive impairment, renal dysfunction, and hypogonadism. Twenty-eight genes involved in ciliary structure or function have been implicated in BBS, and explain the molecular basis for ~75%-80% of individuals.

No Differences in Auditory Steady-State Responses in Children with Autism Spectrum Disorder and Typically Developing Children.

Auditory steady-state response (ASSR) has been studied as a potential biomarker for abnormal auditory sensory processing in autism spectrum disorder (ASD), with mixed results. Motivated by prior somatosensory findings of group differences in inter-trial coherence (ITC) between ASD and typically developing (TD) individuals at twice the steady-state stimulation frequency, we examined ASSR at 25 and 50 as well as 43 and 86 Hz in response to 25-Hz and 43-Hz auditory stimuli, respectively, using magnetoencephalography. Data were recorded from 22 ASD and 31 TD children, ages 6-17 years.

Atypical cortical processing of bottom-up speech binding cues in children with autism spectrum disorders.

Individuals with autism spectrum disorder (ASD) commonly display speech processing abnormalities. Binding of acoustic features of speech distributed across different frequencies into coherent speech objects is fundamental in speech perception. Here, we tested the hypothesis that the cortical processing of bottom-up acoustic cues for speech binding may be anomalous in ASD.

Predictive coding across the left fronto-temporal hierarchy during language comprehension.

We used magnetoencephalography (MEG) and event-related potentials (ERPs) to track the time-course and localization of evoked activity produced by expected, unexpected plausible, and implausible words during incremental language comprehension. We suggest that the full pattern of results can be explained within a hierarchical predictive coding framework in which increased evoked activity reflects the activation of residual information that was not already represented at a given level of the fronto-temporal hierarchy ("error" activity). Between 300 and 500 ms, the three conditions produced progressively larger responses within left temporal cortex (lexico-semantic prediction error), whereas implausible inputs produced a selectively enhanced response within inferior frontal cortex (prediction error at the level of the event model).

Magnetoencephalography and electroencephalography can both detect differences in cortical responses to vibrotactile stimuli in individuals on the autism spectrum.

Autism Spectrum (AS) is defined primarily by differences in social interactions, with impairments in sensory processing also characterizing the condition. In the search for neurophysiological biomarkers associated with traits relevant to the condition, focusing on sensory processing offers a path that is likely to be translatable across populations with different degrees of ability, as well as into animal models and across imaging modalities. In a prior study, a somatosensory neurophysiological signature of AS was identified using magnetoencephalography (MEG).