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Background and purpose: Nemaline myopathy (NEM) has been associated with mutations in 12 genes to date. However, for some patients diagnosed with NEM, definitive mutations are not identified in the known genes, suggesting that there are other genes involved. This study describes compound heterozygosity for rare variants in ryanodine receptor type 3 (RYR3) gene in one such patient. Methods and results: Clinical examination of the patient at 22 years of age revealed a long narrow face, high arched palate and bilateral facial weakness. She had proximal weakness in all four limbs, mild scapular winging but no scoliosis. Muscle biopsy revealed wide variation in fibre size with type 1 fibre predominance and atrophy. Abundant nemaline bodies were located in perinuclear and subsarcolemmal areas, and within the cytoplasm. No likely pathogenic mutations in known NEM genes were identified. Copy number variation in known NEM genes was excluded by NEM‐targeted comparative genomic hybridization array. Next‐generation sequencing revealed compound heterozygous missense variants in the RYR3 gene. RYR3 transcripts are expressed in human fetal and adult skeletal muscle as well as in human brain and cauda equina samples. Immunofluorescence of human skeletal muscle revealed a ‘single‐row’ appearance of RYR3, interspersed between the ‘double rows’ of ryanodine receptor type 1 (RYR1) at each A–I junction. Conclusion: The results suggest that variants in RYR3 may cause a recessive muscle disease with pathological features including nemaline bodies. We characterize the expression pattern of RYR3 in human skeletal muscle and brain, and the subcellular localization of RYR1 and RYR3 in human skeletal muscle. [ABSTRACT FROM AUTHOR]

Objective Primary central nervous system lymphoma (PCNSL) is an extremely rare condition in childhood. We report the first case of PCNSL in a child in Iran. Clinical presentation A nine-year-old boy was referred to Mofid Hospital with the history of headache of four months and seizure of 2 months duration. Magnetic resonance imaging of the brain revealed a hyper-intense lesion in left fronto-parietal area with secondary satellite lesions. Biopsy of the brain mass was performed. Pathologic findings showed brain lymphoma and immunohistochemistry confirmed this diagnosis. The treatment started with intrathecal and systemic chemotherapy in combination with radiotherapy. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to evaluate the electrophysiologic findings of Guillain Barre Syndrome (GBS) in children and their relation with clinical progress of the disease.Methods: Twenty-three children with GBS were evaluated between 2005 and 2007. Electrophysiologic evaluations were performed at admission and one month later.Findings: Five patients needed respirator, 15 were bedridden, 1 developed recurrence 6 months later, and 2 experienced chronic GBS. The most common findings included: decreased amplitude of muscle action potential (CMAP) (96%), increased distal latency (74%), increased F wave latency (69%), and decreased nerve conduction velocity (NCV) (61%). Sensory nerve conduction (evaluating sural nerve) was normal in 78% of the cases. These measures did not significantly change after 1 month.Conclusion: Electrodiagnostic evaluations are helpful at the primary stages of GBS for diagnosis. Fibrillation potentials and positive sharp waves showing denervation and axonal injury are presentative of longer duration of the disease and a worse prognosis. [ABSTRACT FROM AUTHOR]

Objective: To develop a framework for good clinical decision-making using machine learning (ML) models for interventional, patient-level decisions., Design: Grounded theory qualitative interview study., Setting: Primarily single-site at a major urban academic paediatric hospital, with external sampling., Participants: Sixteen participants representing physicians (n=10), nursing (n=3), respiratory therapists (n=2) and an ML specialist (n=1) with experience working in acute care environments were identified through purposive sampling. Individuals were recruited to represent a spectrum of ML knowledge (three expert, four knowledgeable and nine non-expert) and years of experience (median=12.9 years postgraduation). Recruitment proceeded through snowball sampling, with individuals approached to represent a diversity of fields, levels of experience and attitudes towards artificial intelligence (AI)/ML. A member check step and consultation with patients was undertaken to vet the framework, which resulted in some minor revisions to the wording and framing., Interventions: A semi-structured virtual interview simulating an intensive care unit handover for a hypothetical patient case using a simulated ML model and seven visualisations using known methods addressing interpretability of models in healthcare. Participants were asked to make an initial care plan for the patient, then were presented with a model prediction followed by the seven visualisations to explore their judgement and potential influence and understanding of the visualisations. Two visualisations contained contradicting information to probe participants' resolution process for the contrasting information. The ethical justifiability and clinical reasoning process were explored., Main Outcome: A comprehensive framework was developed that is grounded in established medicolegal and ethical standards and accounts for the incorporation of inference from ML models., Results: We found that for making good decisions, participants reflected across six main categories: evidence, facts and medical knowledge relevant to the patient's condition; how that knowledge may be applied to this particular patient; patient-level, family-specific and local factors; facts about the model, its development and testing; the patient-level knowledge sufficiently represented by the model; the model's incorporation of relevant contextual factors. This judgement was centred on and anchored most heavily on the overall balance of benefits and risks to the patient, framed by the goals of care. We found evidence of automation bias, with many participants assuming that if the model's explanation conflicted with their prior knowledge that their judgement was incorrect; others concluded the exact opposite, drawing from their medical knowledge base to reject the incorrect information provided in the explanation. Regarding knowledge about the model, we found that participants most consistently wanted to know about the model's historical performance in the cohort of patients in their local unit where the hypothetical patient was situated., Conclusion: Good decisions using AI tools require reflection across multiple domains. We provide an actionable framework and question guide to support clinical decision-making with AI., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2025. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ Group.)

Heart rate (HR) response to workout intensity reflects fitness and cardiorespiratory health. Physiological models have been developed to describe such heart rate dynamics and characterize cardiorespiratory fitness. However, these models have been limited to small studies in controlled lab environments and are challenging to apply to noisy-but ubiquitous-data from wearables. We propose a hybrid approach that combines a physiological model with flexible neural network components to learn a personalized, multidimensional representation of fitness. The physiological model describes the evolution of heart rate during exercise using ordinary differential equations (ODEs). ODE parameters are dynamically derived via a neural network connecting personalized representations to external environmental factors, from area topography to weather and instantaneous workout intensity. Our approach efficiently fits the hybrid model to a large set of 270,707 workouts collected from wearables of 7465 users from the Apple Heart and Movement Study. The resulting model produces fitness representations that accurately predict full HR response to exercise intensity in future workouts, with a per-workout median error of 6.1 BPM [4.4-8.8 IQR]. We further demonstrate that the learned representations correlate with traditional metrics of cardiorespiratory fitness, such as VO 2 max (explained variance 0.81 ± 0.003). Lastly, we illustrate how our model is naturally interpretable and explicitly describes the effects of environmental factors such as temperature and humidity on heart rate, e.g., high temperatures can increase heart rate by 10%. Combining physiological ODEs with flexible neural networks can yield interpretable, robust, and expressive models for health applications., (© 2023. The Author(s).)

Aim: A widespread outbreak of COVID-19 is followed by adverse effects on the mental health of the general population. Therefore, this study is an audit to investigate the activities of various organizations during the COVID-19 pandemic in Mazandaran Province, Iran., Methods: The aim of the study was to collect the data, the relevant officials in various organizations and units were contacted to collect the statistics of actions taken in psychology and psychiatry wards. Moreover, databases such as Google Scholar and Iranian resources were searched., Results: According to the results, different healthcare systems worked in parallel during the peak of the COVID-19 pandemic. For example, Mazandaran University of Medical Science [MAZUMS] Health Vice-Chancellor performed the following activities during this crisis: establishing a virtual crisis management working group, holding a provincial educational committee to train the crisis management teams, organizing virtual psychological intervention teams in the healthcare systems, and so forth. In addition, the mental health activities by Mazandaran Welfare Organization during the COVID-19 outbreak included providing hostelry free psychological counseling, quarantine boarding and rehabilitation centers, and providing harm prevention protocols of COVID-19, especially for marginalized regions. In the third level of medical centers, including hospitals, consultation-liaison psychiatry or psychiatrists and clinical psychologists, therapeutic interventions for comorbid psychiatric disorders with COVID-19 disease, and online workshops for mental health were conducted to reduce burnout of medical staff and nurses., Conclusion: This study can provide a good guideline for different service providers by using the experiences of other centers to achieve better results., (© 2022 The Authors. Neuropsychopharmacology Reports published by John Wiley & Sons Australia, Ltd on behalf of The Japanese Society of Neuropsychopharmacology.)

In outbred Western populations, most individuals with intellectual disability (ID) are sporadic cases, dominant de novo mutations (DNM) are frequent, and autosomal recessive ID (ARID) is very rare. Because of the high rate of parental consanguinity, which raises the risk for ARID and other recessive disorders, the prevalence of ID is significantly higher in near- and middle-east countries. Indeed, homozygosity mapping and sequencing in consanguineous families have already identified a plethora of ARID genes, but because of the design of these studies, DNMs could not be systematically assessed, and the proportion of cases that are potentially preventable by avoiding consanguineous marriages or through carrier testing is hitherto unknown. This prompted us to perform whole-exome sequencing in 100 sporadic ID patients from Iran and their healthy consanguineous parents. In 61 patients, we identified apparently causative changes in known ID genes. Of these, 44 were homozygous recessive and 17 dominant DNMs. Assuming that the DNM rate is stable, these results suggest that parental consanguinity raises the ID risk about 3.6-fold, and about 4.1 to 4.25-fold for children of first-cousin unions. These results do not rhyme with recent opinions that consanguinity-related health risks are generally small and have been "overstated" in the past., (© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

First, existing commercially available open-loop and closed-loop implantable neurostimulators are reviewed and compared in terms of their targeted application, physical size, system-level features, and performance as a medical device. Next, signal processing algorithms as the primary strength point of the closed-loop neurostimulators are reviewed, and various design and implementation requirements and trade-offs are discussed in details along with quantitative examples. The review results in a set of guidelines for algorithm selection and evaluation. Second, the implementation of an inductively-powered seizure-predicting microsystem for monitoring and treatment of intractable epilepsy is presented. The miniaturized system is comprised of two miniboards and a power receiver coil. The first board hosts a 24-channel neurostimulator system on chip fabricated in a [Formula: see text] CMOS technology and performs neural recording, on-chip digital signal processing, and electrical stimulation. The second board communicates recorded brain signals as well as signal processing results wirelessly. The multilayer flexible coil receives inductively-transmitted power. The system is sized at 2 × 2 × 0.7 [Formula: see text] and weighs 6 g. The approach is validated in the control of chronic seizures in vivo in freely moving rats.

THOC6 is a part of the THO complex, which is involved in coordinating mRNA processing with export. The THO complex interacts with additional components to form the larger TREX complex (transcription export complex). Previously, a homozygous missense mutation in THOC6 in the Hutterite population was reported in association with syndromic intellectual disability. Using exome sequencing, we identified three unrelated patients with bi-allelic mutations in THOC6 associated with intellectual disability and additional clinical features. Two of the patients were compound heterozygous for a stop and a missense mutation, and the third was homozygous for a missense mutation; the missense mutations were predicted to be pathogenic by in silico analysis and modeling. Clinical features of the three newly identified patients and those previously reported are reviewed; intellectual disability is moderate to severe, and malformations are variable including renal and heart defects, cleft palate, microcephaly, and corpus callosum dysgenesis. Facial features are variable and include tall forehead, short upslanting palpebral fissures +/- deep set eyes, and a long nose with overhanging columella. These subtle facial features render the diagnosis difficult to make in isolation with certainty. Our results expand the mutational and clinical spectrum of this rare disease, confirm that THOC6 is an intellectual disability causing gene, while providing insight into the importance of the THO complex in neurodevelopment., (© 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Hereditary spastic paraplegia (HSP) is a heterogeneous condition characterized by progressive spasticity and weakness in the lower limbs. It is divided into two major groups, complicated and uncomplicated, based on the presence of additional features such as intellectual disability, ataxia, seizures, peripheral neuropathy and visual problems. SPG56 is an autosomal recessive form of HSP with complicated and uncomplicated manifestations, complicated being more common. CYP2U1 gene mutations have been identified as responsible for SPG56. Intellectual disability, dystonia, subclinical sensory motor neuropathy, pigmentary degenerative maculopathy, thin corpus callosum and periventricular white-matter hyperintensities were additional features noted in previous cases of SPG56. Here we identified two novel mutations in CYP2U1 in two unrelated patients by whole exome sequencing. Both patients had complicated HSP with activity-induced dystonia, suggesting dystonia as an additional finding in SPG56. Two out of 14 previously reported patients had dystonia, and the addition of our patients suggests dystonia in a quarter of SPG56 patients. Developmental regression has not been reported in SPG56 patients so far but both of our patients developed motor regression in infancy., Competing Interests: Authors declare no conflict of interest., (Copyright © 2016 European Paediatric Neurology Society. Published by Elsevier Ltd. All rights reserved.)

Background: Epilepsy is a common disease of childhood, in which almost 25% of cases are resistant to common antiepileptic drugs. Uncontrolled epilepsy increases morbidity and mortality rates, adversely affects growth and development in these children and imposes heavy psychological stress and financial burdens on parents, health care and society, making it mandatory to find effective therapies for the condition. Our aim was to study the efficacy of levetiracetam, as an add-on therapy, in children suffering from refractory epilepsy., Materials and Methods: In this prospective add-on study, 45 children aged 0.6-15 years (median 5.9 years) with epilepsy not responding to most conventional or new antiepileptic drugs were treated by adding levetiracetam to their present antiepileptic regimen and followed for a minimum period of 12 weeks. The starting dose of 20mg/kg/day was increased at intervals of 1 week by 10mg/kg/day, if necessary, up to a maximum dose of 60mg/kg/day., Results: Four children (8.7%) became seizure free, in 4 (8.7%), seizure frequency increased, and in 8 (17.4%) and 13 (28.3%) patients, seizure frequency decreased by 75-99% and 50-74% respectively. Overall levetiracetam was effective in 54.3% of patients, decreasing seizure frequency to at least 50% of baseline seizure frequency. Variables such as sex, age, duration of disease, type and cause of seizure, EEG and imaging data, also type of epileptic syndrome showed no statistically significant correlations with these results., Conclusion: Levetiracetam can be used as an effective add-on treatment in children with refractory epilepsy.

Antibody to the common "a" determinant of hepatitis B surface antigen (HBsAg) protects against infection with hepatitis B virus. A number of variant surface antigens with amino acid substitutions within the "a" determinant have been described in patients around the world. Both wild type and variant HBsAgs were expressed in the yeast Pichia pastoris and the antigens were semi-purified and quantitated. The effect on antigenicity of these changes was investigated in a quantitative fashion using four monoclonal antibodies known to bind to different epitopes within the common "a" determinant. The results suggest that amino acid substitution of T131I, K141E and G145R and insertion of 3 amino acids between residues 123 and 124 markedly affect the antigenic structure of HBsAg. These substitutions and insertions in the viral envelope may lead to evasion of the virus neutralizing antibody response and also to reduce efficiency of detection by immunoassays used for diagnosis and blood-bank screening., (Copyright 2000 Wiley-Liss, Inc.)