Expanding Kane's argument-based validity framework: What can validation practices in language assessment offer health professions education?

CONTEXT: One central consideration in health professions education (HPE) is to ensure we are making sound and justifiable decisions based on the assessment instruments we use on health professionals. To achieve this goal, HPE assessment researchers have drawn on Kane's argument-based framework to ascertain the validity of their assessment tools. However, the original four-inference model proposed by Kane - frequently used in HPE validation research - has its limitations in terms of what each inference entails and what claims and sources of backing are housed in each inference. The under-specification in the four-inference model has led to inconsistent practices in HPE validation research, posing challenges for (i) researchers who want to evaluate the validity of different HPE assessment tools and/or (ii) researchers who are new to test validation and need to establish a coherent understanding of argument-based validation. METHODS: To address these identified concerns, this article introduces the expanded seven-inference argument-based validation framework that is established practice in the field of language testing and assessment (LTA). We explicate (i) why LTA researchers experienced the need to further specify the original four Kanean inferences; (ii) how LTA validation research defines each of their seven inferences and (iii) what claims, assumptions and sources of backing are associated with each inference. Sampling six representative validation studies in HPE, we demonstrate why an expanded model and a shared disciplinary validation framework can facilitate the examination of the validity evidence in diverse HPE validation contexts. CONCLUSIONS: We invite HPE validation researchers to experiment with the seven-inference argument-based framework from LTA to evaluate its usefulness to HPE. We also call for greater interdisciplinary dialogue between HPE and LTA since both disciplines share many fundamental concerns about language use, communication skills, assessment practices and validity in assessment instruments.

Strong-Coupling Phases of Trions and Excitons in Electron-Hole Bilayers at Commensurate Densities.

We introduce density imbalanced electron-hole bilayers at a commensurate 2:1 density ratio as a platform for realizing novel phases of electrons, excitons, and trions. Through the independently tunable carrier densities and interlayer spacing, competition between kinetic energy, intralayer repulsion, and interlayer attraction yields a rich phase diagram. By a combination of theoretical analysis and numerical calculation, we find a variety of strong-coupling phases in different parameter regions, including quantum crystals of electrons, excitons, and trions. We also propose an "electron-exciton supersolid" phase that features electron crystallization and exciton superfluidity simultaneously. The material realization and experimental signature of these phases are discussed in the context of semiconductor transition metal dichalcogenide bilayers.

ZnMo-MOF as anti-CO hydrogen electrocatalyst enhance microbial electrosynthesis for CO/CO2 conversion.

Microbial electrosynthesis (MES) is an electrically driven technology that can be used for converting CO/CO2 into chemicals. The unique electronic and substrate properties of CO make it an important research target for MES. However, CO can poison the cathode and increase the overpotential of hydrogen evolution reaction (HER), thus reducing the electron transfer rate via H2. This work evaluated the effect of an anti-CO HER catalyst on the performance of MES for CO/CO2 conversion. ZnMo-metal-organic framework (MOF) materials with different calcination temperatures were synthesized. ZnMo-MOF-800 with Mo2C nanoparticles as active centers exhibited excellent resistance to CO toxicity. It also obtained the highest hydrogen evolution and enhanced electron transfer rate in CO atmosphere. MES with ZnMo-MOF-800 cathode and Clostridium ljungdahlii as biocatalyst obtained 0.31 g L-1 d-1 acetate yield, 0.1 g L-1 d-1 butyrate yield, and 0.09 g L-1 d-1 2,3-butanediol yield in CO/CO2, while Pt/C only get 0.076 g L-1 d-1 acetate yield, 0.05 g L-1 d-1 butyrate yield and 0.02 g L-1 d-1 2,3-butanediol yield. ZnMo-MOF-800 was conducive to biofilm formation, enabling it to better resist CO toxicity. This work provides new opportunities for constructing a highly efficient cathode with an anti-CO hydrogen evolution catalyst to enhance CO/CO2 conversion in MES.

Assessing trends in cytokine-CYP drug interaction and relevance to drug dosing.

The regulation of drug-metabolizing enzymes and transporters by cytokines has been extensively studied, in vitro and in clinic. Cytokine-mediated suppression of CYPs or drug transporters may increase or decrease the systemic clearance of drug substrates that are primarily cleared via these pathways; neutralization of cytokines by therapeutic proteins may thereby alter systemic exposures of such drug substrates. The FDA recommends evaluating such clinical drug interactions during clinical development and has provided labeling recommendations for therapeutic proteins. To determine the clinical relevance of these drug interactions to dose adjustments, trends in steady-state exposures (AUCss) of CYP-sensitive substrates co-administered with cytokine modulators as reported in the UW DIDB were extracted and examined for each of the CYPs. Co-administration of CYP3A (midazolam/simvastatin), CYP2C19 (omeprazole), or CYP1A2 (caffeine/tizanidine) substrates with anti-IL-6 and with anti-IL-23 therapeutics led to changes in systemic exposures of CYP substrates ranging from ~ -58% to ~35%; no significant trends were observed for CYP2D6 (dextromethorphan) and CYP2C9 (warfarin) substrates. Although none of these changes in systemic exposures have been reported as clinically meaningful, dose adjustment of midazolam for optimal sedation in acute care settings has been reported. Simulated concentration-time profiles of midazolam under conditions of elevated cytokine levels when co-administered with tocilizumab, suggest a ~6-7 fold increase in midazolam clearance suggesting potential implications of cytokine- CYP drug interactions on dose adjustments of sensitive CYP3A substrates in acute care settings. Additionally, this article also provides a brief overview of non-clinical and clinical assessments of cytokine-CYP drug interactions, in drug discovery and development. Significance Statement Significance statement: There has been significant progress in understanding cytokine-mediated drug interactions for CYP-sensitive substrates. This article provides an overview of the progress in this field, including a trend analysis of systemic exposures of CYP-sensitive substrates co-administered with anti-IL-x therapeutics. In addition, the review also provides a perspective of current methods used to assess these drug interactions during drug development, and a focus on individualized medicine, particularly in acute care settings.

Direct structural analysis of a single acyl carrier protein domain in fatty acid synthase from the fungus Saccharomyces cerevisiae.

Acyl carrier protein (ACP) is the work horse of polyketide (PKS) and fatty acid synthases (FAS) and acts as a substrate shuttling domain in these mega enzymes. In fungi, FAS forms a 2.6 MDa symmetric assembly with six identical copies of FAS1 and FAS2 polypeptides. However, ACP spatial distribution is not restricted by symmetry owing to the long and flexible loops that tether the shuttling domain to its corresponding FAS2 polypeptide. This symmetry breaking has hampered experimental investigation of substrate shuttling route in fungal FAS. Here, we develop a protein engineering and expression method to isolate asymmetric fungal FAS proteins containing odd numbers of ACP domains. Electron cryomicroscopy (cryoEM) observation of the engineered complex reveals a non-uniform distribution of the substrate shuttling domain relative to its corresponding FAS2 polypeptide at 2.9 Å resolution. This work lays the methodological foundation for experimental study of ACP shuttling route in fungi.

Human Alzheimer's disease reactive astrocytes exhibit a loss of homeostastic gene expression.

Astrocytes are one of the brain's major cell types and are responsible for maintaining neuronal homeostasis via regulating the extracellular environment, providing metabolic support, and modulating synaptic activity. In neurodegenerative diseases, such as Alzheimer's disease, astrocytes can take on a hypertrophic appearance. These reactive astrocytes are canonically associated with increases in cytoskeletal proteins, such as glial fibrillary acidic protein and vimentin. However, the molecular alterations that characterize astrocytes in human disease tissues have not been extensively studied with single cell resolution. Using single nucleus RNA sequencing data from normal, pathologic aging, and Alzheimer's disease brains, we identified the transcriptomic changes associated with reactive astrocytes. Deep learning-based clustering algorithms denoised expression data for 17,012 genes and clustered 15,529 astrocyte nuclei, identifying protoplasmic, gray matter and fibrous, white matter astrocyte clusters. RNA trajectory analyses revealed a spectrum of reactivity within protoplasmic astrocytes characterized by a modest increase of reactive genes and a marked decrease in homeostatic genes. Amyloid but not tau pathology correlated with astrocyte reactivity. To identify reactivity-associated genes, linear regressions of gene expression versus reactivity were used to identify the top 52 upregulated and 144 downregulated genes. Gene Ontology analysis revealed that upregulated genes were associated with cellular growth, responses to metal ions, inflammation, and proteostasis. Downregulated genes were involved in cellular interactions, neuronal development, ERBB signaling, and synapse regulation. Transcription factors were significantly enriched among the downregulated genes. Using co-immunofluorescence staining of Alzheimer's disease brain tissues, we confirmed pathologic downregulation of ERBB4 and transcription factor NFIA in reactive astrocytes. Our findings reveal that protoplasmic, gray matter astrocytes in Alzheimer's disease exist within a spectrum of reactivity that is marked by a strong loss of normal function.

Leveraging spatial transcriptomics data to recover cell locations in single-cell RNA-seq with CeLEry.

Single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of cellular heterogeneity in health and disease. However, the lack of physical relationships among dissociated cells has limited its applications. To address this issue, we present CeLEry (Cell Location recovEry), a supervised deep learning algorithm that leverages gene expression and spatial location relationships learned from spatial transcriptomics to recover the spatial origins of cells in scRNA-seq. CeLEry has an optional data augmentation procedure via a variational autoencoder, which improves the method's robustness and allows it to overcome noise in scRNA-seq data. We show that CeLEry can infer the spatial origins of cells in scRNA-seq at multiple levels, including 2D location and spatial domain of a cell, while also providing uncertainty estimates for the recovered locations. Our comprehensive benchmarking evaluations on multiple datasets generated from brain and cancer tissues using Visium, MERSCOPE, MERFISH, and Xenium demonstrate that CeLEry can reliably recover the spatial location information for cells using scRNA-seq data.

Atomic model for core modifying region of human fatty acid synthase in complex with Denifanstat.

Fatty acid synthase (FASN) catalyzes the de novo synthesis of palmitate, a 16-carbon chain fatty acid that is the primary precursor of lipid metabolism and an important intracellular signaling molecule. FASN is an attractive drug target in diabetes, cancer, fatty liver diseases, and viral infections. Here, we develop an engineered full-length human FASN (hFASN) that enables isolation of the condensing and modifying regions of the protein post-translation. The engineered protein enables electron cryo-microscopy (cryoEM) structure determination of the core modifying region of hFASN to 2.7 Å resolution. Examination of the dehydratase dimer within this region reveals that unlike its close homolog, porcine FASN, the catalytic cavity is close-ended and is accessible only through one opening in the vicinity of the active site. The core modifying region exhibits two major global conformational variabilities that describe long-range bending and twisting motions of the complex in solution. Finally, we solved the structure of this region bound to an anti-cancer drug, Denifanstat (i.e., TVB-2640), demonstrating the utility of our approach as a platform for structure guided design of future hFASN small molecule inhibitors.

Convergent Approaches to Delineate the Metabolic Regulation of Tumor Invasion by Hyaluronic Acid Biosynthesis.

Metastasis is the leading cause of breast cancer-related deaths and is often driven by invasion and cancer-stem like cells (CSCs). Both the CSC phenotype and invasion are associated with increased hyaluronic acid (HA) production. How these independent observations are connected, and which role metabolism plays in this process, remains unclear due to the lack of convergent approaches integrating engineered model systems, computational tools, and cancer biology. Using microfluidic invasion models, metabolomics, computational flux balance analysis, and bioinformatic analysis of patient data, the functional links between the stem-like, invasive, and metabolic phenotype of breast cancer cells as a function of HA biosynthesis are investigated. These results suggest that CSCs are more invasive than non-CSCs and that broad metabolic changes caused by overproduction of HA play a role in this process. Accordingly, overexpression of hyaluronic acid synthases (HAS) 2 or 3 induces a metabolic phenotype that promotes cancer cell stemness and invasion in vitro and upregulates a transcriptomic signature predictive of increased invasion and worse patient survival. This study suggests that HA overproduction leads to metabolic adaptations to satisfy the energy demands for 3D invasion of breast CSCs highlighting the importance of engineered model systems and multidisciplinary approaches in cancer research.

Fenfluramine provides clinically meaningful reduction in frequency of drop seizures in patients with Lennox-Gastaut syndrome: Interim analysis of an open-label extension study.

OBJECTIVE: This study was undertaken to evaluate the long-term safety and effectiveness of fenfluramine in patients with Lennox-Gastaut syndrome (LGS). METHODS: Eligible patients with LGS who completed a 14-week phase 3 randomized clinical trial enrolled in an open-label extension (OLE; NCT03355209). All patients were initially started on .2 mg/kg/day fenfluramine and after 1 month were titrated by effectiveness and tolerability, which were assessed at 3-month intervals. The protocol-specified treatment duration was 12 months, but COVID-19-related delays resulted in 142 patients completing their final visit after 12 months. RESULTS: As of October 19, 2020, 247 patients were enrolled in the OLE. Mean age was 14.3 ± 7.6 years (79 [32%] adults) and median fenfluramine treatment duration was 364 days; 88.3% of patients received 2-4 concomitant antiseizure medications. Median percentage change in monthly drop seizure frequency was -28.6% over the entire OLE (n = 241) and -50.5% at Month 15 (n = 142, p < .0001); 75 of 241 patients (31.1%) experienced ≥50% reduction in drop seizure frequency. Median percentage change in nondrop seizure frequency was -45.9% (n = 192, p = .0038). Generalized tonic-clonic seizures (GTCS) and tonic seizures were most responsive to treatment, with median reductions over the entire OLE of 48.8% (p < .0001, n = 106) and 35.8% (p < .0001, n = 186), respectively. A total of 37.6% (95% confidence interval [CI] = 31.4%-44.1%, n = 237) of investigators and 35.2% of caregivers (95% CI = 29.1%-41.8%, n = 230) rated patients as Much Improved/Very Much Improved on the Clinical Global Impression of Improvement scale. The most frequent treatment-emergent adverse events were decreased appetite (16.2%) and fatigue (13.4%). No cases of valvular heart disease (VHD) or pulmonary arterial hypertension (PAH) were observed. SIGNIFICANCE: Patients with LGS experienced sustained reductions in drop seizure frequency on fenfluramine treatment, with a particularly robust reduction in frequency of GTCS, the key risk factor for sudden unexpected death in epilepsy. Fenfluramine was generally well tolerated; VHD or PAH was not observed long-term. Fenfluramine may provide an important long-term treatment option for LGS.

An integrated virtual pathology education platform developed using Microsoft Power Apps and Microsoft Teams.

The transition towards digital pathology and an extensive selection of video conferencing platforms have helped provide continuity to education even during the COVID-19 pandemic. Innovative approaches for pathology education, will likely persist beyond the pandemic, as they have powerful didactic potential. While there is a wide selection of software for use as educational tools, an environment to access all resources with ease is clearly lacking. In this technical note, we highlight our customized educational applications built using a low-code approach. Our applications, developed with Microsoft Power Apps, serve both educational and examination purposes and are launched using Microsoft Teams. Building applications using a low-code approach has made our applications very specific to our use and enabled daily distanced education. Combined with existing features on Teams, such as file sharing, meeting scheduling, and messaging, the applications serve as a unique and customizable pathology educational platform.

Targeting STAT5 Signaling Overcomes Resistance to IDH Inhibitors in Acute Myeloid Leukemia through Suppression of Stemness.

Mutant isocitrate dehydrogenase 1 (IDH1) and IDH2 block the differentiation of acute myeloid leukemia (AML) cells through production of R-2-hydroxyglutarate (R-2-HG). IDH inhibitors can induce differentiation of AML cells by lowering R-2-HG but have limited clinical efficacy as single agents. Here, we performed a genome-wide CRISPR knockout screen in an Idh1-mutated hematopoietic progenitor cell line to identify genes that increased the differentiation response to ivosidenib, an IDH1 inhibitor. The screen identified C-type lectin member 5a (Clec5a), which encodes a spleen tyrosine kinase (SYK)-coupled surface receptor, as one of the top hits. Knockout of Clec5a and Syk rendered cells more sensitive to ivosidenib-induced differentiation through a reduction in STAT5-dependent expression of stemness-related genes, including genes in the homeobox (HOX) family. Importantly, direct inhibition of STAT5 activity was sufficient to increase the differentiation response to IDH inhibitors in primary human IDH1- and IDH2-mutated AML cells, including those harboring mutations in receptor tyrosine kinase (RTK) and MAPK genes that have been linked to drug resistance. In patient-derived xenograft models of IDH1-mutated AML, combination treatment with ivosidenib and the STAT5 inhibitor pimozide was superior to each agent alone in inducing differentiation in leukemic cells without compromising normal hematopoiesis. These findings demonstrate that STAT5 is a critical mediator of resistance to IDH inhibitors and provide the rationale for combining STAT5 and IDH inhibitors in the treatment of IDH-mutated AML. SIGNIFICANCE: A CRISPR knockout screen identifies a mechanism of resistance to IDH inhibitors in AML involving activated STAT5 signaling, suggesting a potential strategy to improve the clinical efficacy of IDH inhibitors.

SARS-CoV-2 impairs interferon production via NSP2-induced repression of mRNA translation.

Viruses evade the innate immune response by suppressing the production or activity of cytokines such as type I interferons (IFNs). Here we report the discovery of a mechanism by which the SARS-CoV-2 virus coopts an intrinsic cellular machinery to suppress the production of the key immunostimulatory cytokine IFN-ß. We reveal that the SARS-CoV-2 encoded nonstructural protein 2 (NSP2) directly interacts with the cellular GIGYF2 protein. This interaction enhances the binding of GIGYF2 to the mRNA cap-binding protein 4EHP, thereby repressing the translation of the Ifnb1 mRNA. Depletion of GIGYF2 or 4EHP significantly enhances IFN-ß production, which inhibits SARS-CoV-2 replication. Our findings reveal a target for rescuing the antiviral innate immune response to SARS-CoV-2 and other RNA viruses.

Postoperative Trapped Lung After Orthotopic Liver Transplantation is a Predictor of Increased Mortality.

Pleural effusions are a common complication of orthotopic liver transplantation (OLT), and chronic post-OLT pleural effusions have been associated with worse outcomes. Furthermore, "trapped lung" (TL), defined as a restrictive fibrous visceral pleural peel preventing lung re-expansion, may have prognostic significance. We performed a retrospective analysis of adult OLT recipients over a 9-year period at UCLA Medical Center. Post-OLT patients with persistent pleural effusions, defined by the presence of pleural fluid requiring drainage one to 12 months after OLT, were included for analysis. Outcomes for patients with and without TL were compared using univariate and multivariate analysis. Of the 1722 patients who underwent OLT, 117 (7%) patients met our criteria for persistent postoperative pleural effusion, and the incidence of TL was 21.4% (25/117). Compared to patients without TL, those with TL required more surgical pleural procedures (OR 59.8, 95%CI 19.7-181.4, p < 0.001), spent more days in the hospital (IRR 1.56, 95%CI 1.09-2.23, p = 0.015), and had a higher risk of mortality (HR 2.47, 95%CI 1.59-3.82, p < 0.001) following transplant. In sum, we found that post-OLT TL was associated with higher morbidity, mortality, and healthcare utilization. Future prospective investigation is warranted to further clarify the risk factors for developing postoperative pleural effusions and TL.

Astrocytic junctional adhesion molecule-A regulates T-cell entry past the glia limitans to promote central nervous system autoimmune attack.

Contact-mediated interactions between the astrocytic endfeet and infiltrating immune cells within the perivascular space are underexplored, yet represent potential regulatory check-points against CNS autoimmune disease and disability. Reactive astrocytes upregulate junctional adhesion molecule-A, an immunoglobulin-like cell surface receptor that binds to T cells via its ligand, the integrin, lymphocyte function-associated antigen-1. Here, we tested the role of astrocytic junctional adhesion molecule-A in regulating CNS autoinflammatory disease. In cell co-cultures, we found that junctional adhesion molecule-A-mediated signalling between astrocytes and T cells increases levels of matrix metalloproteinase-2, C-C motif chemokine ligand 2 and granulocyte-macrophage colony-stimulating factor, pro-inflammatory factors driving lymphocyte entry and pathogenicity in multiple sclerosis and experimental autoimmune encephalomyelitis, an animal model of CNS autoimmune disease. In experimental autoimmune encephalomyelitis, mice with astrocyte-specific JAM-A deletion (mGFAP:CreJAM-Afl/fl ) exhibit decreased levels of matrix metalloproteinase-2, reduced ability of T cells to infiltrate the CNS parenchyma from the perivascular spaces and a milder histopathological and clinical course of disease compared with wild-type controls (JAM-Afl/fl ). Treatment of wild-type mice with intraperitoneal injection of soluble junctional adhesion molecule-A blocking peptide decreases the severity of experimental autoimmune encephalomyelitis, highlighting the potential of contact-mediated astrocyte-immune cell signalling as a novel translational target against neuroinflammatory disease.

Assessment of Natural Language Processing Methods for Ascertaining the Expanded Disability Status Scale Score From the Electronic Health Records of Patients With Multiple Sclerosis: Algorithm Development and Validation Study.

BACKGROUND: The Expanded Disability Status Scale (EDSS) score is a widely used measure to monitor disability progression in people with multiple sclerosis (MS). However, extracting and deriving the EDSS score from unstructured electronic health records can be time-consuming. OBJECTIVE: We aimed to compare rule-based and deep learning natural language processing algorithms for detecting and predicting the total EDSS score and EDSS functional system subscores from the electronic health records of patients with MS. METHODS: We studied 17,452 electronic health records of 4906 MS patients followed at one of Canada's largest MS clinics between June 2015 and July 2019. We randomly divided the records into training (80%) and test (20%) data sets, and compared the performance characteristics of 3 natural language processing models. First, we applied a rule-based approach, extracting the EDSS score from sentences containing the keyword "EDSS." Next, we trained a convolutional neural network (CNN) model to predict the 19 half-step increments of the EDSS score. Finally, we used a combined rule-based-CNN model. For each approach, we determined the accuracy, precision, recall, and F-score compared with the reference standard, which was manually labeled EDSS scores in the clinic database. RESULTS: Overall, the combined keyword-CNN model demonstrated the best performance, with accuracy, precision, recall, and an F-score of 0.90, 0.83, 0.83, and 0.83 respectively. Respective figures for the rule-based and CNN models individually were 0.57, 0.91, 0.65, and 0.70, and 0.86, 0.70, 0.70, and 0.70. Because of missing data, the model performance for EDSS subscores was lower than that for the total EDSS score. Performance improved when considering notes with known values of the EDSS subscores. CONCLUSIONS: A combined keyword-CNN natural language processing model can extract and accurately predict EDSS scores from patient records. This approach can be automated for efficient information extraction in clinical and research settings.

Fenfluramine significantly reduces day-to-day seizure burden by increasing number of seizure-free days and time between seizures in patients with Dravet syndrome: A time-to-event analysis.

OBJECTIVE: The number, unpredictability, and severity of seizures experienced by patients with Dravet syndrome (DS) negatively impact quality of life (QOL) for patients, caregivers, and families. Metrics are needed to assess whether patients with residual seizures have moved meaningfully toward seizure freedom after treatment with new antiseizure medications. METHODS: We evaluated the time required postrandomization for each patient to experience the same number of seizures experienced during baseline (i.e., time-to-nth seizure), using a post hoc time-to-event (TTE) analysis of data from two Phase 3 placebo-controlled trials of adjunctive fenfluramine for DS (Study 1, N = 119; Study 2, N = 87). Patients aged 2-19 years were randomized to placebo or adjunctive fenfluramine (Study 1: .7 mg/kg/day or .2 mg/kg/day; Study 2: .4 mg/kg/day with stiripentol). Data were analyzed by Kaplan-Meier TTE curves and waterfall plots. RESULTS: The proportion of patients who never reached baseline seizure frequency was greater with fenfluramine than with placebo (Study 1: fenfluramine .7 mg/kg/day, 60%; fenfluramine .2 mg/kg/day, 31%; placebo, 13%; Study 2: fenfluramine .4 mg/kg/day, 58%; placebo, 2%). Median time-to-nth seizure was longer after fenfluramine than after placebo (Study 1: fenfluramine .7 mg/kg/day, 13 weeks; .2 mg/kg/day, 10 weeks; placebo, 7 weeks; Study 2: fenfluramine .4 mg/kg/day, 13 weeks; placebo, 5 weeks; p < .001). Longest duration of convulsive seizure-free days was increased in active groups versus the placebo group (Study 1: fenfluramine .7 and .2 mg/kg/day, 25.0 and 15.0 days; placebo, 9.5 days [p = .0001; p = .0352]; Study 2: fenfluramine .4 mg/kg/day, 22.0 days; placebo, 13.0 days [p = .004]). The most common adverse events included decreased appetite, pyrexia, upper respiratory tract infection, diarrhea, and fatigue. SIGNIFICANCE: These data demonstrate that fenfluramine can significantly reduce day-to-day seizure burden in patients with DS, providing prolonged periods of convulsive seizure-free days, which may help reduce the physical and emotional disease toll while improving health-related QOL for patients and caregivers.

Using machine learning to predict severe hypoglycaemia in hospital.

AIM: To predict the risk of hypoglycaemia using machine-learning techniques in hospitalized patients. METHODS: We conducted a retrospective cohort study of patients hospitalized under general internal medicine (GIM) and cardiovascular surgery (CV) at a tertiary care teaching hospital in Toronto, Ontario. Three models were generated using supervised machine learning: least absolute shrinkage and selection operator (LASSO) logistic regression; gradient-boosted trees; and a recurrent neural network. Each model included baseline patient data and time-varying data. Natural-language processing was used to incorporate text data from physician and nursing notes. RESULTS: We included 8492 GIM admissions and 8044 CV admissions. Hypoglycaemia occurred in 16% of GIM admissions and 13% of CV admissions. The area under the curve for the models in the held-out validation set was approximately 0.80 on the GIM ward and 0.82 on the CV ward. When the threshold for hypoglycaemia was lowered to 2.9 mmol/L (52 mg/dL), similar results were observed. Among the patients at the highest decile of risk, the positive predictive value was approximately 50% and the sensitivity was 99%. CONCLUSION: Machine-learning approaches can accurately identify patients at high risk of hypoglycaemia in hospital. Future work will involve evaluating whether implementing this model with targeted clinical interventions can improve clinical outcomes.

Structural Characterization of Endogenous Tuberous Sclerosis Protein Complex Revealed Potential Polymeric Assembly.

Tuberous sclerosis protein complex (pTSC) nucleates a proteinaceous signaling hub that integrates information about the internal and external energy status of the cell in the regulation of growth and energy consumption. Biochemical and cryo-electron microscopy studies of recombinant pTSC have revealed its structure and stoichiometry and hinted at the possibility that the complex may form large oligomers. Here, we have partially purified endogenous pTSC from fasted mammalian brains of rat and pig by leveraging a recombinant antigen binding fragment (Fab) specific for the TSC2 subunit of pTSC. We demonstrate Fab-dependent purification of pTSC from membrane-solubilized fractions of the brain homogenates. Negative stain electron microscopy of the samples purified from pig brain demonstrates rod-shaped protein particles with a width of 10 nm, a variable length as small as 40 nm, and a high degree of conformational flexibility. Larger filaments are evident with a similar 10 nm width and a ≤1 µm length in linear and weblike organizations prepared from pig brain. Immunogold labeling experiments demonstrate linear aggregates of pTSC purified from mammalian brains. These observations suggest polymerization of endogenous pTSC into filamentous superstructures.

Curriculum Innovation in Times of the COVID-19 Pandemic: The Thinking-Based Instruction Theory and Its Application.

At the beginning of 2020, to stop the spread of the coronavirus disease (COVID-19) to the campus, the Ministry of Education of China launched a policy "Suspension of classes without suspending schooling" for the spring semester of 2020. However, the drawbacks of online teaching (e.g., students' inadequate autonomous learning, the lack of effective online instruction) forced us to modify teaching strategies during this special period, especially developing courses that are suitable for student learning at home and improving their key competencies. In order to solve these problems, this study introduces some theoretical exploration and practical work of curriculum design under the guidance of thinking-based instruction theory (TBIT) during the pandemic. We firstly introduce TBIT, and elaborate on the curriculum design under the TBIT theoretical frame. Then we describe a series of TBIT-based micro-courses with the pandemic as background. A descriptive study is reported to illustrate the effects of three micro-courses. Results showed that, compared to national curricula, the TBIT-based micro-courses not only improved the course quality but also enhanced students' motivation and facilitated their online learning behavior (such as interactive communication) for the online courses. The current study has important implications for how to design effective and interesting online courses suitable under pandemic and capable of improving students' thinking abilities and key competencies.