Israeli pediatricians’ confidence level in diagnosing and treating children with skin disorders: a cross-sectional questionnaire pilot study

BackgroundPediatricians daily see large numbers of patients with skin disorders. However, they encounter limited guidance as a result of a marked deficiency in pediatric dermatologists. Hence, reevaluation of training opportunities during pediatric residency has become essential. Our aim was to evaluate the confidence level of pediatric residents and specialists in diagnosing and treating skin disorders in children and to determine career and training-related characteristics that influence it.MethodsConducted as a cross-sectional study, we administered a questionnaire to 171 pediatricians across Israel. We assessed respondents’ self-efficacy about their ability to diagnose and treat skin disorders and collected data regarding their previous dermatology training and preferred training methods.Results77.8% of respondents reported below or average self-efficacy scores in diagnosing and managing children with skin disorders. Older age (>40 years old; OR = 5.51, p = 0.019), treating a higher number of patients with skin disorders (OR = 2.96, p = 0.032), and having any training in dermatology, either during medical school or residency (OR = 7.16, p = 0.031, OR = 11.14, p = 0.003 respectively), were all significant parameters involved in pediatricians reporting high self-efficacy in skin disorder management.ConclusionMost pediatric residents and pediatricians have average or below-average confidence in managing pediatric skin disorders. We suggest incorporating dermatology rotations during pediatric residency to improve young pediatricians’ self-efficacy in managing skin disorders and ultimately help pediatricians provide better care for patients presenting with dermatological conditions. These findings can ultimately help refine a pilot program in dermatology that might be implemented during pediatric residency

Turning high-throughput structural biology into predictive inhibitor design

Peer reviewe

Turning high-throughput structural biology into predictive inhibitor design

A common challenge in drug design pertains to finding chemical modifications to a ligand that increases its affinity to the target protein. An underutilized advance is the increase in structural biology throughput, which has progressed from an artisanal endeavor to a monthly throughput of hundreds of different ligands against a protein in modern synchrotrons. However, the missing piece is a framework that turns high-throughput crystallography data into predictive models for ligand design. Here, we designed a simple machine learning approach that predicts protein–ligand affinity from experimental structures of diverse ligands against a single protein paired with biochemical measurements. Our key insight is using physics-based energy descriptors to represent protein–ligand complexes and a learning-to-rank approach that infers the relevant differences between binding modes. We ran a high-throughput crystallography campaign against the SARS-CoV-2 main protease (MPro), obtaining parallel measurements of over 200 protein–ligand complexes and their binding activities. This allows us to design one-step library syntheses which improved the potency of two distinct micromolar hits by over 10-fold, arriving at a noncovalent and nonpeptidomimetic inhibitor with 120 nM antiviral efficacy. Crucially, our approach successfully extends ligands to unexplored regions of the binding pocket, executing large and fruitful moves in chemical space with simple chemistry

Differential, Positional-Dependent Transcriptional Response of Antigenic Variation (var) Genes to Biological Stress in Plasmodium falciparum

1% of the genes of the human malaria causing agent Plasmodium falciparum belong to the heterogeneous var gene family which encodes P. falciparum erythrocyte membrane protein 1 (PFEMP1). This protein mediates part of the pathogenesis of the disease by causing adherence of infected erythrocytes (IE) to the host endothelium. At any given time, only one copy of the family is expressed on the IE surface. The cues which regulate the allelic exclusion of these genes are not known. We show the existence of a differential expression pattern of these genes upon exposure to biological stress in relation to their positional placement on the chromosome – expression of centrally located var genes is induced while sub-telomeric copies of the family are repressed - this phenomenon orchestrated by the histone deacetylase pfsir2. Moreover, stress was found to cause a switch in the pattern of the expressed var genes thus acting as a regulatory cue. By using pharmacological compounds which putatively affect pfsir2 activity, distinct changes of var gene expression patterns were achieved which may have therapeutic ramifications. As disease severity is partly associated with expression of particular var gene subtypes, manipulation of the IE environment may serve as a mechanism to direct transcription towards less virulent genes

Open science discovery of potent noncovalent SARS-CoV-2 main protease inhibitors

INTRODUCTION COVID-19 became a global pandemic partially as a result of the lack of easily deployable, broad-spectrum oral antivirals, which complicated its containment. Even endemically, and with effective vaccinations, it will continue to cause acute disease, death, and long-term sequelae globally unless there are accessible treatments. COVID-19 is not an isolated event but instead is the latest example of a viral pandemic threat to human health. Therefore, antiviral discovery and development should be a key pillar of pandemic preparedness efforts. RATIONALE One route to accelerate antiviral drug discovery is the establishment of open knowledge bases, the development of effective technology infrastructures, and the discovery of multiple potent antivirals suitable as starting points for the development of therapeutics. In this work, we report the results of the COVID Moonshot—a fully open science, crowdsourced, and structure-enabled drug discovery campaign—against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease (Mpro). This collaboration may serve as a roadmap for the potential development of future antivirals. RESULTS On the basis of the results of a crystallographic fragment screen, we crowdsourced design ideas to progress from fragment to lead compounds. The crowdsourcing strategy yielded several key compounds along the optimization trajectory, including the starting compound of what became the primary lead series. Three additional chemically distinct lead series were also explored, spanning a diversity of chemotypes. The collaborative and highly automated nature of the COVID Moonshot Consortium resulted in >18,000 compound designs, >2400 synthesized compounds, >490 ligand-bound x-ray structures, >22,000 alchemical free-energy calculations, and >10,000 biochemical measurements—all of which were made publicly available in real time. The recently approved antiviral ensitrelvir was identified in part based on crystallographic data from the COVID Moonshot Consortium. This campaign led to the discovery of a potent [median inhibitory concentration (IC50) = 37 ± 2 nM] and differentiated (noncovalent and nonpeptidic) lead compound that also exhibited potent cellular activity, with a median effective concentration (EC50) of 64 nM in A549-ACE2-TMPRSS2 cells and 126 nM in HeLa-ACE2 cells without measurable cytotoxicity. Although the pharmacokinetics of the reported compound is not yet optimal for therapeutic development, it is a promising starting point for further antiviral discovery and development. CONCLUSION The success of the COVID Moonshot project in producing potent antivirals, building open knowledge bases, accelerating external discovery efforts, and functioning as a useful information-exchange hub is an example of the potential effectiveness of open science antiviral discovery programs. The open science, patent-free nature of the project enabled a large number of collaborators to provide in-kind support, including synthesis, assays, and in vitro and in vivo experiments. By making all data immediately available and ensuring that all compounds are purchasable from Enamine without the need for materials transfer agreements, we aim to accelerate research globally along parallel tracks. In the process, we generated a detailed map of the structural plasticity of Mpro, extensive structure-activity relationships for multiple chemotypes, and a wealth of biochemical activity data to spur further research into antivirals and discovery methodologies. We hope that this can serve as an alternative model for antiviral discovery and future pandemic preparedness. Further, the project also showcases the role of machine learning, computational chemistry, and high-throughput structural biology as force multipliers in drug design. Artificial intelligence and machine learning algorithms help accelerate chemical synthesis while balancing multiple competing molecular properties. The design-make-test-analyze cycle was accelerated by these algorithms combined with planetary-scale biomolecular simulations of protein-ligand interactions and rapid structure determination

SARS-CoV-2 infects the human kidney and drives fibrosis in kidney organoids

Kidney failure is frequently observed during and after COVID-19, but it remains elusive whether this is a direct effect of the virus. Here, we report that SARS-CoV-2 directly infects kidney cells and is associated with increased tubule-interstitial kidney fibrosis in patient autopsy samples. To study direct effects of the virus on the kidney independent of systemic effects of COVID-19, we infected human induced pluripotent stem cell-derived kidney organoids with SARS-CoV-2. Single cell RNA-sequencing indicated injury and dedifferentiation of infected cells with activation of pro-fibrotic signaling pathways. Importantly, SARS-CoV-2 infection also led to increased collagen 1 protein expression in organoids. A SARS-CoV-2 protease inhibitor was able to ameliorate the infection of kidney cells by SARS-CoV-2. Our results suggest that SARS-CoV-2 can directly infect kidney cells and induce cell injury with subsequent fibrosis. These data could explain both acute kidney injury in COVID-19 patients and the development of chronic kidney disease in Long-COVID

An Open Resource for Non-human Primate Imaging.

Non-human primate neuroimaging is a rapidly growing area of research that promises to transform and scale translational and cross-species comparative neuroscience. Unfortunately, the technological and methodological advances of the past two decades have outpaced the accrual of data, which is particularly challenging given the relatively few centers that have the necessary facilities and capabilities. The PRIMatE Data Exchange (PRIME-DE) addresses this challenge by aggregating independently acquired non-human primate magnetic resonance imaging (MRI) datasets and openly sharing them via the International Neuroimaging Data-sharing Initiative (INDI). Here, we present the rationale, design, and procedures for the PRIME-DE consortium, as well as the initial release, consisting of 25 independent data collections aggregated across 22 sites (total = 217 non-human primates). We also outline the unique pitfalls and challenges that should be considered in the analysis of non-human primate MRI datasets, including providing automated quality assessment of the contributed datasets

Influence of Selective Laser Melting Machine Source on the Dynamic Properties of AlSi10Mg Alloy

Selective laser melting (SLM) AlSi10Mg alloy has been thoroughly investigated in terms of its microstructure and quasi-static properties, owing to its broad industrial applications. However, the effects of the SLM process on the dynamic behavior under impact conditions remain to be established. This research deals with the influences of manufacturing process parameters on the dynamic response of the SLM on AlSi10Mg at a high strain rate of 700 to 6700 s−1 by using a split Hopkinson pressure bar apparatus. Examinations were performed on vertically and horizontally built samples, processed individually by two manufacturers using a different laser scanning technique on the same powder composition. It was concluded that the fabrication technique does not influence the true stress–true strain dependency at strain rates of 700 to 2800 s−1. However, at higher strain rates (4000 to 6700 s−1), this study revealed different plastic behavior, which was associated only with the horizontally built samples. Moreover, this study found different failure demeanors at true strains exceeding 0.8. The dynamic response was correlated with the as-built microstructure and crystallographic texture, characterized using the electron backscattered diffraction technique

Nuclear factor-κB signaling and ezrin are essential for L1-mediated metastasis of colon cancer cells

Hyperactivation of β-catenin–T-cell-factor (TCF)-regulated gene transcription is a hallmark of colorectal cancer (CRC). The cell-neural adhesion molecule L1CAM (hereafter referred to as L1) is a target of β-catenin–TCF, exclusively expressed at the CRC invasive front in humans. L1 overexpression in CRC cells increases cell growth and motility, and promotes liver metastasis. Genes induced by L1 are also expressed in human CRC tissue but the mechanisms by which L1 confers metastasis are still unknown. We found that signaling by the nuclear factor κB (NF-κB) is essential, because inhibition of signaling by the inhibitor of κB super repressor (IκB-SR) blocked L1-mediated metastasis. Overexpression of the NF-κB p65 subunit was sufficient to increase CRC cell proliferation, motility and metastasis. Binding of the L1 cytodomain to ezrin – a cytoskeleton-crosslinking protein – is necessary for metastasis because when binding to L1 was interrupted or ezrin gene expression was suppressed with specific shRNA, metastasis did not occur. L1 and ezrin bound to and mediated the phosphorylation of IκB. We also observed a complex containing IκB, L1 and ezrin in the juxtamembrane region of CRC cells. Furthermore, we found that L1, ezrin and phosphorylated p65 are co-expressed at the invasive front in human CRC tissue, indicating that L1-mediated activation of NF-κB signaling involving ezrin is a major route of CRC progression