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"Klein, Jennifer"
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Exploiting machine learning for end-to-end drug discovery and development
A variety of machine learning methods such as naive Bayesian, support vector machines and more recently deep neural networks are demonstrating their utility for drug discovery and development. These leverage the generally bigger datasets created from high-throughput screening data and allow prediction of bioactivities for targets and molecular properties with increased levels of accuracy. We have only just begun to exploit the potential of these techniques but they may already be fundamentally changing the research process for identifying new molecules and/or repurposing old drugs. The integrated application of such machine learning models for end-to-end (E2E) application is broadly relevant and has considerable implications for developing future therapies and their targeting.This Perspective describes the application of machine learning models in the design, synthesis and characterisation of molecules at different stages in the drug discovery and development process.
Journal Article
Natural Images from the Birthplace of the Human Eye
Here we introduce a database of calibrated natural images publicly available through an easy-to-use web interface. Using a Nikon D70 digital SLR camera, we acquired about six-megapixel images of Okavango Delta of Botswana, a tropical savanna habitat similar to where the human eye is thought to have evolved. Some sequences of images were captured unsystematically while following a baboon troop, while others were designed to vary a single parameter such as aperture, object distance, time of day or position on the horizon. Images are available in the raw RGB format and in grayscale. Images are also available in units relevant to the physiology of human cone photoreceptors, where pixel values represent the expected number of photoisomerizations per second for cones sensitive to long (L), medium (M) and short (S) wavelengths. This database is distributed under a Creative Commons Attribution-Noncommercial Unported license to facilitate research in computer vision, psychophysics of perception, and visual neuroscience.
Journal Article
The calmodulin redox sensor controls myogenesis
Muscle aging is accompanied by blunted muscle regeneration in response to injury and disuse. Oxidative stress likely underlies this diminished response, but muscle redox sensors that act in regeneration have not yet been characterized. Calmodulin contains multiple redox sensitive methionines whose oxidation alters the regulation of numerous cellular targets. We have used the CRISPR-Cas9 system to introduce a single amino acid substitution M109Q that mimics oxidation of methionine to methionine sulfoxide in one or both alleles of the CALM1 gene, one of three genes encoding the muscle regulatory protein calmodulin, in C2C12 mouse myoblasts. When signaled to undergo myogenesis, mutated myoblasts failed to differentiate into myotubes. Although early myogenic regulatory factors were present, cells with the CALM1 M109Q mutation in one or both alleles were unable to withdraw from the cell cycle and failed to express late myogenic factors. We have shown that a single oxidative modification to a redox-sensitive muscle regulatory protein can halt myogenesis, suggesting a molecular target for mitigating the impact of oxidative stress in age-related muscle degeneration.
Journal Article
Untangling the Complex Associations between Socioeconomic and Demographic Characteristics and Prenatal Detection and Outcomes in Congenital Heart Disease
Recent literature has established a strong foundation examining the associations between socioeconomic/demographic characteristics and outcomes for congenital heart disease. These associations are found beginning in fetal life and influence rates of prenatal detection, access to timely and appropriate delivery room and neonatal interventions, and surgical and other early childhood outcomes. This review takes a broad look at the existing literature and identifies gaps in the current body of research, particularly as it pertains to disparities in the prenatal detection of congenital heart disease within the United States. It also proposes further research and interventions to address these health disparities.
Journal Article
Deviant Cyber-Sexual Activities in Young Adults: Exploring Prevalence and Predictions Using In-Person Sexual Activities and Social Learning Theory
Technology has shifted some human interactions to the virtual world. For many young adults, sexual encounters now occur through virtual means, as social media, picture exchanges, sexually explicit Web sites, and video chatting have become popular alternative outlets for these activities to occur. This study used the self-report responses of 812 undergraduate students (282 men and 530 women), collected from an online survey. In addition to using 10 personal demographic control variables, this study used five sexual activity/relationship characteristics (number of sexual partners, relationship status, age to first use pornography, frequency of sexual activity/intercourse, and frequency of masturbation), and the four constructs of Akers’ social learning theory (identified as differential association, differential reinforcement, imitation/modeling, and definitions favorable) to predict a seven-item count of deviant cyber-sexual activities, and two measures of “sexting” behaviors. Gender, self-esteem, sexual orientation, race, and religion were strongly significant predictors in the models, but Akers’ four elements of social learning performed the strongest in predicting the two measures of sexting and the overall deviant cyber-sexual activities scale. This finding indicates that peer associations and peer reinforcements have a strong influence on individuals’ willingness to engage in deviant cyber-sexual activities. This study explored different avenues for young adults’ engagement in sexual deviancy and the results suggest that sexual behaviors performed in-person may not be the strongest predictors of online sexual behavior.
Journal Article
Effect of anaemia on the diagnosis of rheumatic heart disease using World Heart Federation criteria
There is overlap between pathological mitral regurgitation seen in borderline rheumatic heart disease using World Heart Federation echocardiography criteria and physiologic regurgitation found in normal children. One possible contributing factor is higher rates of anaemia in endemic countries.
To investigate the contribution of anaemia as a potential confounder in the diagnosis of rheumatic heart disease detected in echocardiographic screening.
A novel Server 2012 data warehouse tool was used to incorporate haematology and echocardiography databases. The study included a convenience sample of patients from 5 to 18 years old without structural or functional heart disease that had a haemoglobin value within 1 month prior to an echocardiogram. Echocardiogram images were reviewed to determine presence or absence of World Heart Federation criteria for rheumatic heart disease. The rate of rheumatic heart disease among anaemic and non-anaemic children according to gender- and age-based norms groups was compared.
Of the 935 patients who met the study inclusion criteria, 406 were classified as anaemic. There was no difference in the rate of echocardiograms meeting criteria for borderline rheumatic heart disease in anaemic (2.0%, 95% CI 0.6-3.3%) and non-anaemic children (1.3%, 95% CI 0.3-2.3%). However, there was a statistically significant increase in rates of mitral regurgitation of unclear significance among anaemic versus non-anaemic patients (8.6 versus 3.6%; p = 0.0012).
Anaemia does not increase the likelihood of meeting echocardiographic criteria for borderline rheumatic heart disease. Future studies should evaluate for the correlation between anaemia and mitral regurgitation in endemic settings.
Journal Article