L-carnitine supplementation for muscle weakness and fatigue in children with neurofibromatosis type 1: A Phase 2a clinical trial.

Reduced muscle tone, muscle weakness, and physical fatigue can impact considerably on quality of life for children with neurofibromatosis type 1 (NF1). Human muscle biopsies and mouse models of NF1 deficiency in muscle show intramyocellular lipid accumulation, and preclinical data have indicated that L-carnitine supplementation can ameliorate this phenotype. The aim of this study is to examine whether daily L-carnitine supplementation is safe and feasible, and will improve muscle strength and reduce fatigue in children with NF1. A 12-week Phase 2a trial was conducted using 1000 mg daily oral levocarnitine tartrate supplementation. Recruited children were between 8 and 12 years old with a clinical diagnosis of NF1, history of muscle weakness and fatigue, and naïve to L-carnitine. Primary outcomes were safety (self-reporting, biochemical testing) and compliance. Secondary outcomes included plasma acylcarnitine profiles, functional measures (muscle strength, long jump, handwriting speed, 6-minute-walk test [6MWT]), and parent-reported questionnaires (PedsQL™, CBCL/6-18). Six children completed the trial with no self-reported adverse events. Biochemical tests for kidney and liver function were normal, and the average compliance was 95%. Plasma acylcarnitine levels were low, but within a range not clinically linked to carnitine deficiency. For strength measures, there was a mean 53% increase in dorsiflexion strength (95% confidence interval [CI] 8.89-60.75; p = 0.02) and mean 66% increase in plantarflexion strength (95% CI 12.99-134.1; p = 0.03). In terms of muscle performance, there was a mean 10% increase in long jump distance (95% CI 2.97-16.03; p = 0.01) and 6MWT distance (95% CI 5.88-75.45; p = 0.03). Comparison with the 1000 Norms Project data showed a significant improvement in Z-score for all of these measures. Parent reports showed no negative impact on quality of life, and the perceived benefits led to the majority of individuals remaining on L-carnitine after the study. Twelve weeks of L-carnitine supplementation is safe and feasible in children with NF1, and a Phase 3 trial should confirm the efficacy of treatment.

TClustVID: A novel machine learning classification model to investigate topics and sentiment in COVID-19 tweets.

COVID-19, caused by SARS-CoV2 infection, varies greatly in its severity but presents with serious respiratory symptoms with vascular and other complications, particularly in older adults. The disease can be spread by both symptomatic and asymptomatic infected individuals. Uncertainty remains over key aspects of the virus infectiousness (particularly the newly emerging variants) and the disease has had severe economic impacts globally. For these reasons, COVID-19 is the subject of intense and widespread discussion on social media platforms including Facebook and Twitter. These public forums substantially influence public opinions and in some cases can exacerbate the widespread panic and misinformation spread during the crisis. Thus, this work aimed to design an intelligent clustering-based classification and topic extracting model named TClustVID that analyzes COVID-19-related public tweets to extract significant sentiments with high accuracy. We gathered COVID-19 Twitter datasets from the IEEE Dataport repository and employed a range of data preprocessing methods to clean the raw data, then applied tokenization and produced a word-to-index dictionary. Thereafter, different classifications were employed on these datasets which enabled the exploration of the performance of traditional classification and TClustVID. Our analysis found that TClustVID showed higher performance compared to traditional methodologies that are determined by clustering criteria. Finally, we extracted significant topics from the clusters, split them into positive, neutral and negative sentiments, and identified the most frequent topics using the proposed model. This approach is able to rapidly identify commonly prevailing aspects of public opinions and attitudes related to COVID-19 and infection prevention strategies spreading among different populations.

A Deep Convolutional Neural Network Method to Detect Seizures and Characteristic Frequencies Using Epileptic Electroencephalogram (EEG) Data.

BACKGROUND: Diagnosing epileptic seizures using electroencephalogram (EEG) in combination with deep learning computational methods has received much attention in recent years. However, to date, deep learning techniques in seizure detection have not been effectively harnessed due to sub-optimal classifier design and improper representation of the time-domain signal. METHODS: In this study, we focused on designing and evaluating deep convolutional neural network-based classifiers for seizure detection. Signal-to-image conversion methods are proposed to convert time-domain EEG signal to a time-frequency represented image to prepare the input data for classification. We proposed and evaluated three classification methods comprising of five classifiers to determine which is more accurate for seizure detection. Accuracy data were then compared to previous studies of the same dataset. RESULTS: We found our proposed model and signal-to-image conversion method outperformed all previous studies in the most cases. The proposed FT-VGG16 classifier achieved the highest average classification accuracy of 99.21%. In addition, the Shapley Additive exPlanations (SHAP) analysis approach was employed to uncover the feature frequencies in the EEG that contribute most to improved classification accuracy. To the best of our knowledge, this is the first study to compute the contribution of frequency components to target seizure classification; thus allowing the identification of distinct seizure-related EEG frequency components compared to normal EEG measures. CONCLUSION: Thus our developed deep convolutional neural network models are useful to detect seizures and characteristic frequencies using EEG data collected from the patients and this model could be clinically applicable for the automated seizures detection.

Gene expression profiling of SARS-CoV-2 infections reveal distinct primary lung cell and systemic immune infection responses that identify pathways relevant in COVID-19 disease.

To identify key gene expression pathways altered with infection of the novel coronavirus SARS-CoV-2, we performed the largest comparative genomic and transcriptomic analysis to date. We compared the novel pandemic coronavirus SARS-CoV-2 with SARS-CoV and MERS-CoV, as well as influenza A strains H1N1, H3N2 and H5N1. Phylogenetic analysis confirms that SARS-CoV-2 is closely related to SARS-CoV at the level of the viral genome. RNAseq analyses demonstrate that human lung epithelial cell responses to SARS-CoV-2 infection are distinct. Extensive Gene Expression Omnibus literature screening and drug predictive analyses show that SARS-CoV-2 infection response pathways are closely related to those of SARS-CoV and respiratory syncytial virus infections. We validated SARS-CoV-2 infection response genes as disease-associated using Kaplan-Meier survival estimates in lung disease patient data. We also analysed COVID-19 patient peripheral blood samples, which identified signalling pathway concordance between the primary lung cell and blood cell infection responses.

Pathogenetic profiling of COVID-19 and SARS-like viruses.

The novel coronavirus (2019-nCoV) has recently emerged, causing COVID-19 outbreaks and significant societal/global disruption. Importantly, COVID-19 infection resembles SARS-like complications. However, the lack of knowledge about the underlying genetic mechanisms of COVID-19 warrants the development of prospective control measures. In this study, we employed whole-genome alignment and digital DNA-DNA hybridization analyses to assess genomic linkage between 2019-nCoV and other coronaviruses. To understand the pathogenetic behavior of 2019-nCoV, we compared gene expression datasets of viral infections closest to 2019-nCoV with four COVID-19 clinical presentations followed by functional enrichment of shared dysregulated genes. Potential chemical antagonists were also identified using protein-chemical interaction analysis. Based on phylogram analysis, the 2019-nCoV was found genetically closest to SARS-CoVs. In addition, we identified 562 upregulated and 738 downregulated genes (adj. P ≤ 0.05) with SARS-CoV infection. Among the dysregulated genes, SARS-CoV shared ≤19 upregulated and ≤22 downregulated genes with each of different COVID-19 complications. Notably, upregulation of BCL6 and PFKFB3 genes was common to SARS-CoV, pneumonia and severe acute respiratory syndrome, while they shared CRIP2, NSG1 and TNFRSF21 genes in downregulation. Besides, 14 genes were common to different SARS-CoV comorbidities that might influence COVID-19 disease. We also observed similarities in pathways that can lead to COVID-19 and SARS-CoV diseases. Finally, protein-chemical interactions suggest cyclosporine, resveratrol and quercetin as promising drug candidates against COVID-19 as well as other SARS-like viral infections. The pathogenetic analyses, along with identified biomarkers, signaling pathways and chemical antagonists, could prove useful for novel drug development in the fight against the current global 2019-nCoV pandemic.

Evaluating modified diets and dietary supplement therapies for reducing muscle lipid accumulation and improving muscle function in neurofibromatosis type 1 (NF1).

Neurofibromatosis type 1 (NF1) is a genetic disorder that affects a range of tissue systems, however the associated muscle weakness and fatigability can have a profound impact on quality of life. Prior studies using the limb-specific Nf1 knockout mouse (Nf1Prx1-/-) revealed an accumulation of intramyocellular lipid (IMCL) that could be rescued by a diet supplemented with L-carnitine and enriched for medium-chain fatty acids (MCFAs). In this study we used the Nf1Prx1-/- mouse to model a range of dietary interventions designed to reduce IMCL accumulation, and analyze using other modalities including in situ muscle physiology and lipid mass spectrometry. Histological IMCL accumulation was significantly reduced by a range of treatments including L-carnitine and high MCFAs alone. A low-fat diet did not affect IMCL, but did provide improvements to muscle strength. Supplementation yielded rapid improvements in IMCL within 4 weeks, but were lost once treatment was discontinued. In situ muscle measurements were highly variable in Nf1Prx1-/- mice, attributable to the severe phenotype present in this model, with fusion of the hips and an overall small hind limb muscle size. Lipidome analysis enabled segregation of the normal and modified chow diets, and fatty acid data suggested increased muscle lipolysis with the intervention. Acylcarnitines were also affected, suggestive of a mitochondrial fatty acid oxidation disorder. These data support the theory that NF1 is a lipid storage disease that can be treated by dietary intervention, and encourages future human trials.

A machine learning model to identify early stage symptoms of SARS-Cov-2 infected patients.

The recent outbreak of the respiratory ailment COVID-19 caused by novel coronavirus SARS-Cov2 is a severe and urgent global concern. In the absence of effective treatments, the main containment strategy is to reduce the contagion by the isolation of infected individuals; however, isolation of unaffected individuals is highly undesirable. To help make rapid decisions on treatment and isolation needs, it would be useful to determine which features presented by suspected infection cases are the best predictors of a positive diagnosis. This can be done by analyzing patient characteristics, case trajectory, comorbidities, symptoms, diagnosis, and outcomes. We developed a model that employed supervised machine learning algorithms to identify the presentation features predicting COVID-19 disease diagnoses with high accuracy. Features examined included details of the individuals concerned, e.g., age, gender, observation of fever, history of travel, and clinical details such as the severity of cough and incidence of lung infection. We implemented and applied several machine learning algorithms to our collected data and found that the XGBoost algorithm performed with the highest accuracy (>85%) to predict and select features that correctly indicate COVID-19 status for all age groups. Statistical analyses revealed that the most frequent and significant predictive symptoms are fever (41.1%), cough (30.3%), lung infection (13.1%) and runny nose (8.43%). While 54.4% of people examined did not develop any symptoms that could be used for diagnosis, our work indicates that for the remainder, our predictive model could significantly improve the prediction of COVID-19 status, including at early stages of infection.

Cancer Cell Dormancy in Metastasis.

Recurrent metastasis following extended periods of disease-free survival remains a common cause of morbidity and mortality for many cancer patients. Recurrence is thought to be mediated by tumor cells that escaped the primary site early in the disease course and colonize distant organs. In these locations, cells adapt to the local environment, entering a state of long-term dormancy in which they can resist therapy. Then, through mechanisms that are poorly understood, a proportion of these cells are reactivated and become proliferative, forming lethal metastases. Here, we discuss disseminated tumor cell dormancy in recurrent metastasis. We discuss mechanisms known to control entrance of cells into dormancy, highlighting the relevant microenvironments or "niches" in which these cells reside and mechanisms known to be involved in dormant cell reactivation. Finally, we consider emerging therapeutic approaches aimed at eradicating residual disease and preventing metastatic relapse.

The multiple faces of tryptophan in bone biology.

Osteoporosis is highly prevalent in older persons. While many advances have been made in the field of osteoporosis, current treatments have been affected by unexpected side effects and limited efficacy; therefore, new approaches to identify disease mechanisms and pathways are required. This review focuses on the influence of tryptophan metabolites, particularly kynurenines and serotonin on bone. The kynurenine (KYN) pathway is associated with osteoblastogenesis and can be linked to the pathophysiology of osteoporosis. The activity of osteoblasts is reduced by 3-hydroxykynurenine (3-HKYN), a product of KYN. In addition, decreasing concentrations of 3-hydroxyanthranilic acid with aging can be one of the causes of bone loss. In contrast, picolinic acid, an end-product of the KYN pathway, acts as a bone anabolic. On the other hand, gut-derived serotonin (GDS) inhibits bone formation, whereas brain-derived serotonin enhances bone formation and decreases bone resorption. Overall, understanding the exact mechanisms of action of tryptophan metabolites on bone could have great potential to develop effective treatments for osteoporosis and other bone diseases.

Tumor Cell Dormancy and Reactivation in Bone: Skeletal Biology and Therapeutic Opportunities.

In the advanced stages of many cancers, tumor cells disseminate from the primary site and colonize distant locations such as the skeleton. These disseminated tumor cells colonizing bone can evade treatments and survive for prolonged periods in a dormant state before becoming reactivated to form overt metastases. The precise interactions between tumor cells and the bone microenvironment that promote survival, dormancy, and reactivation are currently unknown; as a result, bone metastases remain incurable. In this review we discuss the unique cellular and microenvironmental features of endosteal bone that tumor cells engage with to persist and survive, and ultimately reactivate and proliferate. Specifically, we provide a detailed summary of current perspectives on the processes of tumor cell colonization of the skeleton, and the endosteal bone cells as critical controllers of the dormant cancer cell phenotype, as well as relevant microenvironmental effects such as hypoxia. Evidence for the role of the osteoclast in controlling dormant cancer cell reactivation in bone is highlighted, preceding a discussion of therapeutics targeting the bone microenvironment, including anti-RANK ligand and bisphosphonate therapies and their potential utility in preventing tumor cell reactivation in addition to protecting bone from tumor-induced destruction. © 2018 The Authors. JBMR Plus published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research.

Lipid storage myopathies: Current treatments and future directions.

Lipid storage myopathies (LSMs) are a heterogeneous group of genetic disorders that present with abnormal lipid storage in multiple body organs, typically muscle. Patients can clinically present with cardiomyopathy, skeletal muscle weakness, myalgia, and extreme fatigue. An early diagnosis is crucial, as some LSMs can be managed by simple nutraceutical supplementation. For example, high dosage l-carnitine is an effective intervention for patients with Primary Carnitine Deficiency (PCD). This review discusses the clinical features and management practices of PCD as well as Neutral Lipid Storage Disease (NLSD) and Multiple Acyl-CoA Dehydrogenase Deficiency (MADD). We provide a detailed summary of current clinical management strategies, highlighting issues of high-risk contraindicated treatments with case study examples not previously reviewed. Additionally, we outline current preclinical studies providing disease mechanistic insight. Lastly, we propose that a number of other conditions involving lipid metabolic dysfunction that are not classified as LSMs may share common features. These include Neurofibromatosis Type 1 (NF1) and autoimmune myopathies, including Polymyositis (PM), Dermatomyositis (DM), and Inclusion Body Myositis (IBM).

Developmental dosing with a MEK inhibitor (PD0325901) rescues myopathic features of the muscle-specific but not limb-specific Nf1 knockout mouse.

Neurofibromatosis Type 1 (NF1) is a common autosomal dominant genetic disorder While NF1 is primarily associated with predisposition for tumor formation, muscle weakness has emerged as having a significant impact on quality of life. NF1 inactivation is linked with a canonical upregulation Ras-MEK-ERK signaling. This in this study we tested the capacity of the small molecule MEK inhibitor PD0325901 to influence the intramyocellular lipid accumulation associated with NF1 deficiency. Established murine models of tissue specific Nf1 deletion in skeletal muscle (Nf1MyoD-/-) and limb mesenchyme (Nf1Prx1-/-) were tested. Developmental PD0325901 dosing of dams pregnant with Nf1MyoD-/- progeny rescued the phenotype of day 3 pups including body weight and lipid accumulation by Oil Red O staining. In contrast, PD0325901 treatment of 4 week old Nf1Prx1-/- mice for 8 weeks had no impact on body weight, muscle wet weight, activity, or intramyocellular lipid. Examination of day 3 Nf1Prx1-/- pups showed differences between the two tissue-specific knockout strains, with lipid staining greatest in Nf1MyoD-/- mice, and fibrosis higher in Nf1Prx1-/- mice. These data show that a MEK/ERK dependent mechanism underlies NF1 muscle metabolism during development. However, crosstalk from Nf1-deficient non-muscle mesenchymal cells may impact upon muscle metabolism and fibrosis in neonatal and mature myofibers.

Dietary intervention rescues myopathy associated with neurofibromatosis type 1.

Neurofibromatosis type 1 (NF1) is an autosomal dominant genetic disorder with complex symptomology. In addition to a predisposition to tumors, children with NF1 can present with reduced muscle mass, global muscle weakness, and impaired motor skills, which can have a significant impact on quality of life. Genetic mouse models have shown a lipid storage disease phenotype may underlie muscle weakness in NF1. Herein we confirm that biopsy specimens from six individuals with NF1 similarly manifest features of a lipid storage myopathy, with marked accumulation of intramyocellular lipid, fibrosis, and mononuclear cell infiltrates. Intramyocellular lipid was also correlated with reductions in neurofibromin protein expression by western analysis. An RNASeq profile of Nf1null muscle from a muscle-specific Nf1 knockout mouse (Nf1MyoD-/-) revealed alterations in genes associated with glucose regulation and cell signaling. Comparison by lipid mass spectrometry demonstrated that Nf1null muscle specimens were enriched for long chain fatty acid (LCFA) containing neutral lipids, such as cholesterol esters and triacylglycerides, suggesting fundamentally impaired LCFA metabolism. The subsequent generation of a limb-specific Nf1 knockout mouse (Nf1Prx1-/-) recapitulated all observed features of human NF1 myopathy, including lipid storage, fibrosis, and muscle weakness. Collectively, these insights led to the evaluation of a dietary intervention of reduced LCFAs, and enrichment of medium-chain fatty acids (MCFAs) with L-carnitine. Following 8-weeks of dietary treatment, Nf1Prx1-/- mice showed a 45% increase in maximal grip strength, and a 71% reduction in intramyocellular lipid staining compared with littermates fed standard chow. These data link NF1 deficiency to fundamental shifts in muscle metabolism, and provide strong proof of principal that a dietary intervention can ameliorate symptoms.

Limitations of the Pax7-creERT2 transgene for driving deletion of Nf1 in adult mouse muscle.

Neurofibromatosis Type 1 (NF1) is an autosomal dominant genetic disorder that results in a variety of characteristic manifestations. Prior studies have shown reduced muscle size and global skeletal muscle weakness in children with NF1. This associated weakness can lead to significant challenges impacting on quality of life. Pre-clinical studies using a muscle-specific NF1 knockout mouse have linked this weakness to an underlying primary metabolic deficiency in the muscle. However, the neonatal lethality of this strain prevents analysis of the role of NF1 in adult muscle. In this study, we present the characterization of an inducible muscle-specific NF1 knockout strain (Nf1Pax7i f/f ) produced by cross breeding the Pax7-CreERT2 strain with the conditional Nf1flox/flox line. Tamoxifen dosing of 8-week old Nf1Pax7i f/f mice led to recombination of the floxed allele in muscle, as detected by PCR. Detailed phenotypic analysis of treated adult mice over 8 weeks revealed no changes in bodyweight or muscle weight, no histological signs of myopathy, and no functional evidence of distress or impairment. Subsequent analysis using the Ai9 Cre-dependent tdTomato reporter strain was used to analyse labelling in embryos and in adult mice. Cell tracking studies identified a lower than expected rate of integration of recombined satellite cells into adult muscle. In contrast, a high persistent contribution of embryonic cells that were Pax7+ were found in adult muscle. These findings indicate important caveats with the use of the Pax7-CreER T2 strain and highlight a need to develop new tools for investigating the function of NF1 in mature muscle.

Inducible cell labeling and lineage tracking during fracture repair.

Mouse models incorporating inducible Cre-ERT2/LoxP recombination coupled with sensitive fluorescent reporter lines are being increasingly used to track cell lineages in vivo. In this study we use two inducible reporter strains, Ai9iCol2a1 (Ai9×Col2a1-creERT2) to track contribution of chondrogenic progenitors during bone regeneration in a closed fracture model and Ai9i UBC (Ai9×UBC-creERT2) to examine methods for inducing localized recombination. By comparing with Ai9 littermate controls as well as inducible reporter mice not dosed with tamoxifen, we revealed significant leakiness of the CreERT2 system, particularly in the bone marrow of both lines. These studies highlight the challenges associated with highly sensitive reporters that may be activated without induction in tissues where the CreERT2 fusion is expressed. Examination of the growth plate in the Ai9iCol2a1 strain showed cells of the osteochondral lineage (cell co-staining with chondrocyte and osteoblast markers) labeled with the tdTom reporter. However, no such labeling was noted in healing fractures of Ai9iCol2a1 mice. Attempts to label a single limb using intramuscular injection of 4-hydroxytamoxifen in the Ai9i UBC strain resulted in complete labeling of the entire animal, comparable to intraperitoneal injection. While a challenge to interpret, these data are nonetheless informative regarding the limitations of these inducible reporter models, and justify caution and expansive controls in future studies using such models.