NK‐cell receptors NKp46 and NCR1 control human metapneumovirus infection

Natural killer (NK) cells are capable of killing various pathogens upon stimulation of activating receptors. Human metapneumovirus (HMPV) is a respiratory virus, which was discovered in 2001 and is responsible for acute respiratory tract infection in infants and children worldwide. HMPV infection is very common, infecting around 70% of all children under the age of five. Under immune suppressive conditions, HMPV infection can be fatal. Not much is known on how NK cells respond to HMPV. In this study, using reporter assays and NK‐cell cytotoxicity assays performed with human and mouse NK cells, we demonstrated that the NKp46‐activating receptor and its mouse orthologue Ncr1, both members of the natural cytotoxicity receptor (NCR) family, recognized an unknown ligand expressed by HMPV‐infected human cells. We demonstrated that MHC class I is upregulated and MICA is downregulated upon HMPV infection. We also characterized mouse NK‐cell phenotype in the blood and the lungs of HMPV‐infected mice and found that lung NK cells are more activated and expressing NKG2D, CD43, CD27, KLRG1, and CD69 compared to blood NK cells regardless of HMPV infection. Finally, we demonstrated, using Ncr1‐deficient mice, that NCR1 plays a critical role in controlling HMPV infection.     

NKp46 Receptor-Mediated Interferon-γ Production by Natural Killer Cells Increases Fibronectin 1 to Alter Tumor Architecture and Control Metastasis

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Participation in leisure activities among boys with attention deficit hyperactivity disorder

ADHD is a neural developmental disorder expressed in various life settings. Yet, previous studies have focused mainly on children's function in school and academic achievement. The purpose of the present study was, therefore, to examine participation patterns in outside formal school activities among boys with ADHD compared to typical boys. Participants included 25 boys aged 8–11 years with ADHD and 25 age-matched typical boys. All participants completed the Children's Assessment of Participation and Enjoyment (CAPE). Several aspects of participation were examined: diversity, intensity, enjoyment, place, and partners in 49 extra curricular activities. The findings indicate that boys with ADHD reported significant lower intensity rates of participation in most activity domains. Furthermore, boys with ADHD also reported higher diversity scores and lower enjoyment in ‘formal’ activities. Yet, no significant differences were found with regard to activity place and partners. These findings enhance the importance of providing therapy that refers to after school activities. Accordingly, CAPE can be useful for assessing boys with ADHD and planning appropriate intervention programs.     

Handwriting features of children with developmental coordination disorder – Results of triangular evaluation

Developmental coordination disorders (DCD) is one of the most common disorders affecting school-aged children. The study aimed to characterize the handwriting performance of children with DCD who write in Arabic, based on triangular evaluation.Participants included 58 children aged 11–12 years, 29 diagnosed with DCD based on the DSM-IV criteria and the M-ABC, and 29 matched typically developed controls. Children were asked to copy a paragraph on a sheet of paper affixed to a digitizer supplying objective measures of the handwriting process. The handwriting proficiency screening questionnaire (HPSQ) was completed by their teachers while observing their performance and followed by evaluation of their final written product.Results indicated that compared to controls, children with DCD required significantly more on-paper and in-air time per stroke while copying. In addition, global legibility, unrecognizable letters and spatial arrangement measures of their written product were significantly inferior. Significant group differences were also found between the HPSQ subscales scores. Furthermore, 82.8% of all participants were correctly classified into groups based on one discriminate function which included two handwriting performance measures.These study results strongly propose application of triangular standardized evaluation to receive better insight of handwriting deficit features of individual children with DCD who write in Arabic.     

Treatment of scabies and pediculosis: Facts and controversies

Unlike many other skin diseases, success or failure of therapy of ectoparasitic infestation depends much more on how to use the topical preparation and whom we treat than on which scabicide or pediculicides to use. The diagnosis of scabies should no longer rely on the rather uncommon and unpractical sign of finding a burrow or the number of parasites per infected patient. Most infested individuals have been shown to have several-fold more acari than the oft-quoted average of 12 adult acari per infected patient that appears in most of our textbooks (stemming from Mellanby's work). Contrary to what Mellanby taught us, we know that indirect transmission (ie, without personal contact) does occur. As to which agent to use, the winner remains undeclared at present. Although indirect contact transmission of hair lice has been clarified after thousands of years of infestation, there are still numerous questions, uncertainties, disagreements, and controversies on the subject; for example, we know that lice survive immersion in water but are probably not transmitted in swimming pools. There is no consensus on the best or most correct way to diagnose lice, nor is the problem of resistance resolved. We do not recommend a “no-nit” policy.     

Generation of an Anti-idiotypic Antibody as a Surrogate Ligand for Sulfamethazine in Immunoassay Procedures

We report the generation of an anti-idiotypic antibody, clone 12E12, against antisulfamethazine (SMZ) as a surrogate ligand for SMZ in immunoassay procedures. This has been achieved by using the primary monoclonal anti-SMZ antibody as an immunogen in hybridoma technology followed by screening of the resulting hybridromas for binding to the SMZ site of the primary anti-SMZ antibody. Characterization of a strong anti-idiotypic antibody of the betatype, clone 12E12, capable of mimicking SMZ, permitted the development of immunoassay formats for SMZ based on the idiotypic and anti-idiotypic approach and the direct measurement of SMZ content in diluted pig urine. The availability of the strong betatypic anti-idiotypic antibody acting as a surrogate ligand for SMZ enables antibodies to be labeled instead of ligands and offers interesting possibilities for the development of competitive type non-isotopic immunoassays for SMZ.     

Meeting the unmet needs of clinicians from AI systems showcased for cardiology with deep-learning–based ECG analysis

Despite their great promise, artificial intelligence (AI) systems have yet to become ubiquitous in the daily practice of medicine largely due to several crucial unmet needs of healthcare practitioners. These include lack of explanations in clinically meaningful terms, handling the presence of unknown medical conditions, and transparency regarding the system’s limitations, both in terms of statistical performance as well as recognizing situations for which the system’s predictions are irrelevant. We articulate these unmet clinical needs as machine-learning (ML) problems and systematically address them with cutting-edge ML techniques. We focus on electrocardiogram (ECG) analysis as an example domain in which AI has great potential and tackle two challenging tasks: the detection of a heterogeneous mix of known and unknown arrhythmias from ECG and the identification of underlying cardio-pathology from segments annotated as normal sinus rhythm recorded in patients with an intermittent arrhythmia. We validate our methods by simulating a screening for arrhythmias in a large-scale population while adhering to statistical significance requirements. Specifically, our system 1) visualizes the relative importance of each part of an ECG segment for the final model decision; 2) upholds specified statistical constraints on its out-of-sample performance and provides uncertainty estimation for its predictions; 3) handles inputs containing unknown rhythm types; and 4) handles data from unseen patients while also flagging cases in which the model’s outputs are not usable for a specific patient. This work represents a significant step toward overcoming the limitations currently impeding the integration of AI into clinical practice in cardiology and medicine in general.

For decades, researchers have been applying machine-learning (ML) algorithms to medical tasks with the goal of incorporating insights derived from data into real-world medical applications (1). Medical artificial intelligence (AI) can potentially be used to increase personalization, reduce physician cognitive load, aid decision-making, enable preventive medicine through predictions, automate analysis of medical images and health records, and much more (2–5). Recently, deep learning (DL), a branch of ML focusing on algorithms that can learn directly from raw data (e.g., physiological signals), has risen to prominence. Such algorithms are responsible for many of the current state-of-the-art results reported in the literature for medical AI tasks, with several works claiming to surpass a human doctor’s performance (5) in cases such as automatic diagnosis of breast cancer from mammography scans (6); of melanoma from skin images (7); of pathology from optical coherence tomography scans (8); assessing rehospitalization and in-hospital death risks via analysis of electronic health records (9); arrhythmia detection from electrocardiograms (ECG) analysis (10); and more. However, this slew of research successes has so far not led to widespread adoption of DL-based solutions in the day-to-day practice of medicine and in the healthcare industry in general. Over the past two years, the clinical community has responded to the recent results reported by AI researchers via several top-tier review and opinion papers (1, 2, 11–13), in which leading clinicians addressed some specific shortcomings in recent state-of-the-art medical AI solutions, which prevent them from being incorporated into clinical practice.Here, we consolidate the most frequently mentioned shortcomings voiced by leading physicians and researchers into what we term the “unmet needs” of clinicians from medical AI. We focus specifically on shortcomings that most critically prevent clinical adoption of medical AI solutions according to the recent medical literature. We formulate these unmet needs in a manner actionable by ML researchers. We define each unmet need accurately, demonstrate how it can be met for electrocardiogram (ECG) analysis tasks, and describe our contributions with respect to it. Our work goes beyond the usual search for better model architectures or improved accuracy and focus on the challenges of clinical usefulness. To clarify, although widespread adoption of AI in the clinic is also impeded by broad systemic issues such as regulatory, legal or ethical considerations, lack of standardized data formats, integration with existing infrastructure, and others, this work focuses only on the shortcomings of the AI systems themselves.     

A linked active transport system for Na+ and K+ in a glial cell line.

Ouabain (5 X 10(-4) M) induced a 6-fold increase in intracellular Na+ and a 65% loss of cellular K+ in C6 glial cells which was accompanied by a 12 mV decrease in the resting membrane potential. Following ouabain washout intracellular ion concentrations and the membrane potential returned to control levels suggesting that C6 is capable of active Na+ transport which is linked to uptake of K+. A portion of K+ uptake under steady-state conditions is also active since K+ influx was reduced 32% by ouabain. Five mM cyanide significantly increased cell Na+ and significantly decreased cell K+ and the membrane potential. The similarity in the ratio of Na+ gained/K+ lost (ouabain 1.24, cyanide 1.41) suggests that the two agents inhibit the same ion transport system. Decreased temperature had the paradoxical effect of increasing intracellular K+ while significantly decreasing both membrane potential and K+ influx. Part of this effect may be due to the marked reduction in K+ efflux at low temperature. At 6 degrees C cell loss of K+ was much less than loss of K+ with ouabain at 37 degrees C. The observation of a linked Na+-K+ transport system in C6 cell confirms the hypothesis that coupled active Na+-K+ exchange occurs in glial cells and suggests that ionic transport may regulate certain aspects of glial metabolism.