Project description:The use of imaging systems in protein crystallisation means that the experimental setups no longer require manual inspection to determine the outcome of the trials. However, it leads to the problem of how best to find images which contain useful information about the crystallisation experiments. The adoption of a deeplearning approach in 2018 enabled a four-class machine classification system of the images to exceed human accuracy for the first time. Underpinning this was the creation of a labelled training set which came from a consortium of several different laboratories. The MARCO classification model does not have the same accuracy on local data as it does on images from the original test set; this can be somewhat mitigated by retraining the ML model and including local images. We have characterized the image data used in the original MARCO model, and performed extensive experiments to identify training settings most likely to enhance the local performance of a MARCO-dataset based ML classification model.
Project description:The myelodysplastic syndromes (MDS) share their origin in the hematopoietic stem cell but have otherwise very heterogeneous biological and genetic characteristics. Clinical features are dominated by cytopenia and a substantial risk for progression to acute myeloid leukemia. According to the World Health Organization, MDS is defined by cytopenia, bone marrow dysplasia and certain karyotypic abnormalities. The understanding of disease pathogenesis has undergone major development with the implementation of next-generation sequencing and a closer integration of morphology, cytogenetics and molecular genetics is currently paving the way for improved classification and prognostication. True precision medicine is still in the future for MDS and the development of novel therapeutic compounds with a propensity to markedly change patients' outcome lags behind that for many other blood cancers. Treatment of higher-risk MDS is dominated by monotherapy with hypomethylating agents but novel combinations are currently being evaluated in clinical trials. Agents that stimulate erythropoiesis continue to be first-line treatment for the anemia of lower-risk MDS but luspatercept has shown promise as second-line therapy for sideroblastic MDS and lenalidomide is an established second-line treatment for del(5q) lower-risk MDS. The only potentially curative option for MDS is hematopoietic stem cell transplantation, until recently associated with a relatively high risk of transplant-related mortality and relapse. However, recent studies show increased cure rates due to better tools to target the malignant clone with less toxicity. This review provides a comprehensive overview of the current status of the clinical evaluation, biology and therapeutic interventions for this spectrum of disorders.
Project description:The human circadian system has a period of approximately 24 h and studies on the consequences of "chornodisruption" have greatly expanded. Lifestyle and environmental factors of modern societies (i.e., artificial lighting, jetlag, shift work, and around-the-clock access to energy-dense food) can induce disruptions of the circadian system and thereby adversely affect individual health. Growing evidence demonstrates a complex reciprocal relationship between metabolism and the circadian system, in which perturbations in one system affect the other one. From a nutritional genomics perspective, genetic variants in clock genes can both influence metabolic health and modify the individual response to diet. Moreover, an interplay between the circadian rhythm, gut microbiome, and epigenome has been demonstrated, with the diet in turn able to modulate this complex link suggesting a remarkable plasticity of the underlying mechanisms. In this view, the study of the impact of the timing of eating by matching elements from nutritional research with chrono-biology, that is, chrono-nutrition, could have significant implications for personalized nutrition in terms of reducing the prevalence and burden of chronic diseases. This review provides an overview of the current evidence on the interactions between the circadian system and nutrition, highlighting how this link could in turn influence the epigenome and microbiome. In addition, possible nutritional strategies to manage circadian-aligned feeding are suggested.
Project description:Long Covid has raised awareness of the potentially disabling chronic sequelae that afflicts patients after acute viral infection. Similar syndromes of post-infectious sequelae have also been observed after other viral infections such as dengue, but their true prevalence and functional impact remain poorly defined. We prospectively enrolled 209 patients with acute dengue (n = 48; one with severe dengue) and other acute viral respiratory infections (ARI) (n = 161), and followed them up for chronic sequelae up to one year post-enrolment, prior to the onset of the Covid-19 pandemic. Baseline demographics and co-morbidities were balanced between both groups except for gender, with more males in the dengue cohort (63% vs 29%, p<0.001). Except for the first visit, data on symptoms were collected remotely using a purpose-built mobile phone application. Mental health outcomes were evaluated using the validated SF-12v2 Health Survey. Almost all patients (95.8% of dengue and 94.4% of ARI patients) experienced at least one symptom of fatigue, somnolence, headache, concentration impairment or memory impairment within the first week of enrolment. Amongst patients with at least 3-months of follow-up, 18.0% in the dengue cohort and 14.6% in the ARI cohort experienced persistent symptoms. The median month-3 SF-12v2 Mental Component Summary Score was lower in patients who remained symptomatic at 3 months and beyond, compared to those whose symptoms fully resolved (47.7 vs. 56.0, p<0.001), indicating that patients who self-reported persistence of symptoms also experienced functionally worse mental health. No statistically significant difference in age, gender distribution or hospitalisation status was observed between those with and without chronic sequelae. Our findings reveal an under-appreciated burden of post-infection chronic sequelae in dengue and ARI patients. They call for studies to define the pathophysiology of this condition, and determine the efficacy of both vaccines as well as antiviral drugs in preventing such sequelae.
Project description:Molecular "fingerprints" encoding structural information are the workhorse of cheminformatics and machine learning in drug discovery applications. However, fingerprint representations necessarily emphasize particular aspects of the molecular structure while ignoring others, rather than allowing the model to make data-driven decisions. We describe molecular graph convolutions, a machine learning architecture for learning from undirected graphs, specifically small molecules. Graph convolutions use a simple encoding of the molecular graph-atoms, bonds, distances, etc.-which allows the model to take greater advantage of information in the graph structure. Although graph convolutions do not outperform all fingerprint-based methods, they (along with other graph-based methods) represent a new paradigm in ligand-based virtual screening with exciting opportunities for future improvement.
Project description:The past few decades have witnessed a rapid rise in nutrition-related disorders such as obesity in the United States and over the world. Traditional nutrition research has associated various foods and nutrients with obesity. Recent advances in genomics have led to identification of the genetic variants determining body weight and related dietary factors such as intakes of energy and macronutrients. In addition, compelling evidence has lent support to interactions between genetic variations and dietary factors in relation to obesity and weight change. Moreover, recently emerging data from other 'omics' studies such as epigenomics and metabolomics suggest that more complex interplays between the global features of human body and dietary factors may exist at multiple tiers in affecting individuals' susceptibility to obesity; and a concept of 'personalized nutrition' has been proposed to integrate this novel knowledge with traditional nutrition research, with the hope ultimately to endorse person-centric diet intervention to mitigate obesity and related disorders.
Project description:BackgroundAsthma is a heterogeneous disease and development of novel therapeutics requires an understanding of pathophysiologic phenotypes. The purpose of the ADEPT study was to correlate clinical features and biomarkers with molecular characteristics, by profiling asthma (NCT01274507). This report presents for the first time the study design, and characteristics of the recruited subjects.MethodsPatients with a range of asthma severity and healthy non-atopic controls were enrolled. The asthmatic subjects were followed for 12 months. Assessments included history, patient questionnaires, spirometry, airway hyper-responsiveness to methacholine, fractional exhaled nitric oxide (FENO), and biomarkers measured in induced sputum, blood, and bronchoscopy samples. All subjects underwent sputum induction and 30 subjects/cohort had bronchoscopy.ResultsMild (n = 52), moderate (n = 55), severe (n = 51) asthma cohorts and 30 healthy controls were enrolled from North America and Western Europe. Airflow obstruction, bronchodilator response and airways hyperresponsiveness increased with asthma severity, and severe asthma subjects had reduced forced vital capacity. Asthma control questionnaire-7 (ACQ7) scores worsened with asthma severity. In the asthmatics, mean values for all clinical and biomarker characteristics were stable over 12 months although individual variability was evident. FENO and blood eosinophils did not differ by asthma severity. Induced sputum eosinophils but not neutrophils were lower in mild compared to the moderate and severe asthma cohorts.ConclusionsThe ADEPT study successfully enrolled asthmatics across a spectrum of severity and non-atopic controls. Clinical characteristics were related to asthma severity and in general asthma characteristics e.g. lung function, were stable over 12 months. Use of the ADEPT data should prove useful in defining biological phenotypes to facilitate personalized therapeutic approaches.