THE APPLICATION OF COMPUTER VISION, MACHINE AND DEEP LEARNING ALGORITHMS UTILIZING MATLAB

MATLAB is a multi-paradigm proprietary programming language and numerical computing environment developed by MathWorks. Within MATLAB Integrated Development Environment (IDE) you can perform Computer-aided design (CAD), different matrix manipulations, plotting of functions and data, implementation algorithms, creation of user interfaces, and has the ability to interface with programs written in other languages1. Since, its launch in 1984 MATLAB software has not particularly been associated within the field of data science. In 2013, that changed with the launch of their new data science concentrated toolboxes that included Deep Learning, Image Processing, Computer Vision, and then a year later Statistics and Machine Learning. The main objective of my thesis was to research and explore the field of data science. More specifically pertaining to the development of an object recognition application that could be built entirely using MATLAB IDE and have a positive social impact on the deaf community. And in doing so, answering the question, could MATLAB be utilized for development of this type of application? To simultaneously answer this question while addressing my main objectives, I constructed two different object recognition protocols utilizing MATLAB_R2019 with the add-on data science tool packages. I named the protocols ASLtranslate (I) and (II). This allowed me to experiment with all of MATLAB data science toolboxes while learning the differences, benefits, and disadvantages of using multiple approaches to the same problem. The methods and approaches for the design of both versions was very similar. ASLtranslate takes in 2D image of American Sign Language (ASL) hand gestures as an input, classifies the image and then outputs its corresponding alphabet character. ASLtranslate (I) was an implementation of image category classification using machine learning methods. ASLtranslate (II) was implemented by using a deep learning method called transfer learning, done by fine-tuning a pre-trained convolutional neural network (CNN), AlexNet, to perform classification on a new collection of images

Using Real-World Data to Guide Ustekinumab Dosing Strategies for Psoriasis: A Prospective Pharmacokinetic-Pharmacodynamic Study.

Variation in response to biologic therapy for inflammatory diseases, such as psoriasis, is partly driven by variation in drug exposure. Real-world psoriasis data were used to develop a pharmacokinetic/pharmacodynamic (PK/PD) model for the first-line therapeutic antibody ustekinumab. The impact of differing dosing strategies on response was explored. Data were collected from a UK prospective multicenter observational cohort (491 patients on ustekinumab monotherapy, drug levels, and anti-drug antibody measurements on 797 serum samples, 1,590 measurements of Psoriasis Area Severity Index (PASI)). Ustekinumab PKs were described with a linear one-compartment model. A maximum effect (Emax ) model inhibited progression of psoriatic skin lesions in the turnover PD mechanism describing PASI evolution while on treatment. A mixture model on half-maximal effective concentration identified a potential nonresponder group, with simulations suggesting that, in future, the model could be incorporated into a Bayesian therapeutic drug monitoring "dashboard" to individualize dosing and improve treatment outcomes

Enhancing autophagy by redox regulation extends lifespan in <i>Drosophila</i>

Redox signalling is an important modulator of diverse biological pathways and processes, and operates through specific post-translational modification of redox-sensitive thiols on cysteine residues 1–4. Critically, redox signalling is distinct from irreversible oxidative damage and functions as a reversible ‘redox switch’ to regulate target proteins. H2O2 acts as the major effector of redox signalling, both directly and through intracellular thiol redox relays 5,6. Dysregulation of redox homeostasis has long been implicated in the pathophysiology of many age-related diseases, as well as in the ageing process itself, however the underlying mechanisms remain largely unclear 7,8. To study redox signalling by H2O2in vivo and explore its involvement in metabolic health and longevity, we used the fruit fly Drosophila as a model organism, with its tractable lifespan and strong evolutionary conservation with mammals 9. Here we report that inducing an endogenous redox-shift, by manipulating levels of the H2O2-degrading enzyme catalase, improves health and robustly extends lifespan in flies, independently of oxidative stress resistance and dietary restriction. We find that the catalase redox-shifted flies are acutely sensitive to starvation stress, which relies on autophagy as a vital survival mechanism. Importantly, we show that autophagy is essential for the lifespan extension of the catalase flies. Furthermore, using redox-inactive knock-in mutants of Atg4a, a major effector of autophagy, we show that the lifespan extension in response to catalase requires a key redox-regulatory cysteine residue, Cys102 in Atg4a. These findings demonstrate that redox regulation of autophagy can extend lifespan, confirming the importance of redox signalling in ageing and as a potential pro-longevity target.</jats:p

Fine-tuning autophagy maximises lifespan and is associated with changes in mitochondrial gene expression in Drosophila

Increased cellular degradation by autophagy is a feature of many interventions that delay ageing. We report here that increased autophagy is necessary for reduced insulin-like signalling (IIS) to extend lifespan in Drosophila and is sufficient on its own to increase lifespan. We first established that the well-characterised lifespan extension associated with deletion of the insulin receptor substrate chico was completely abrogated by downregulation of the essential autophagy gene Atg5. We next directly induced autophagy by over-expressing the major autophagy kinase Atg1 and found that a mild increase in autophagy extended lifespan. Interestingly, strong Atg1 up-regulation was detrimental to lifespan. Transcriptomic and metabolomic approaches identified specific signatures mediated by varying levels of autophagy in flies. Transcriptional upregulation of mitochondrial-related genes was the signature most specifically associated with mild Atg1 upregulation and extended lifespan, whereas short-lived flies, possessing strong Atg1 overexpression, showed reduced mitochondrial metabolism and up-regulated immune system pathways. Increased proteasomal activity and reduced triacylglycerol levels were features shared by both moderate and high Atg1 overexpression conditions. These contrasting effects of autophagy on ageing and differential metabolic profiles highlight the importance of fine-tuning autophagy levels to achieve optimal healthspan and disease prevention

Fine-tuning autophagy maximises lifespan and is associated with changes in mitochondrial gene expression in Drosophila

Increased cellular degradation by autophagy is a feature of many interventions that delay ageing. We report here that increased autophagy is necessary for reduced insulin-like signalling (IIS) to extend lifespan in Drosophila and is sufficient on its own to increase lifespan. We first established that the well-characterised lifespan extension associated with deletion of the insulin receptor substrate chico was completely abrogated by downregulation of the essential autophagy gene Atg5. We next directly induced autophagy by over-expressing the major autophagy kinase Atg1 and found that a mild increase in autophagy extended lifespan. Interestingly, strong Atg1 up-regulation was detrimental to lifespan. Transcriptomic and metabolomic approaches identified specific signatures mediated by varying levels of autophagy in flies. Transcriptional upregulation of mitochondrial-related genes was the signature most specifically associated with mild Atg1 upregulation and extended lifespan, whereas short-lived flies, possessing strong Atg1 overexpression, showed reduced mitochondrial metabolism and up-regulated immune system pathways. Increased proteasomal activity and reduced triacylglycerol levels were features shared by both moderate and high Atg1 overexpression conditions. These contrasting effects of autophagy on ageing and differential metabolic profiles highlight the importance of fine-tuning autophagy levels to achieve optimal healthspan and disease prevention

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Genetic Variation in OAS1 Is a Risk Factor for Initial Infection with West Nile Virus in Man

West Nile virus (WNV) is a re-emerging pathogen that can cause fatal encephalitis. In mice, susceptibility to WNV has been reported to result from a single point mutation in oas1b, which encodes 2′–5′ oligoadenylate synthetase 1b, a member of the type I interferon-regulated OAS gene family involved in viral RNA degradation. In man, the human ortholog of oas1b appears to be OAS1. The ‘A’ allele at SNP rs10774671 of OAS1 has previously been shown to alter splicing of OAS1 and to be associated with reduced OAS activity in PBMCs. Here we show that the frequency of this hypofunctional allele is increased in both symptomatic and asymptomatic WNV seroconverters (Caucasians from five US centers; total n = 501; OR = 1.6 [95% CI 1.2–2.0], P = 0.0002 in a recessive genetic model). We then directly tested the effect of this SNP on viral replication in a novel ex vivo model of WNV infection in primary human lymphoid tissue. Virus accumulation varied markedly among donors, and was highest for individuals homozygous for the ‘A’ allele (P<0.0001). Together, these data identify OAS1 SNP rs10774671 as a host genetic risk factor for initial infection with WNV in humans

A Phylogenetic Analysis of Human Immunodeficiency Virus Type 1 Sequences in Kiev: Findings Among Key Populations

Background: The human immunodeficiency virus (HIV) epidemic in Ukraine has been driven by a rapid rise among people who inject drugs, but recent studies have shown an increase through sexual transmission. Methods: Protease and reverse transcriptase sequences from 876 new HIV diagnoses (April 2013–March 2015) in Kiev were linked to demographic data. We constructed phylogenetic trees for 794 subtype A1 and 64 subtype B sequences and identified factors associated with transmission clustering. Clusters were defined as ≥2 sequences, ≥80% local branch support, and maximum genetic distance of all sequence pairs in the cluster ≤2.5%. Recent infection was determined through the limiting antigen avidity enzyme immunoassay. Sequences were analyzed for transmitted drug resistance mutations. Results Thirty percent of subtype A1 and 66% of subtype B sequences clustered. Large clusters (maximum 11 sequences) contained mixed risk groups. In univariate analysis, clustering was significantly associated with subtype B compared to A1 (odds ratio [OR], 4.38 [95% confidence interval {CI}, 2.56–7.50]); risk group (OR, 5.65 [95% CI, 3.27–9.75]) for men who have sex with men compared to heterosexual males; recent, compared to long-standing, infection (OR, 2.72 [95% CI, 1.64–4.52]); reported sex work contact (OR, 1.93 [95% CI, 1.07–3.47]); and younger age groups compared with age ≥36 years (OR, 1.83 [95% CI, 1.10–3.05] for age ≤25 years). Females were associated with lower odds of clustering than heterosexual males (OR, 0.49 [95% CI, .31–.77]). In multivariate analysis, risk group, subtype, and age group were independently associated with clustering (P < .001, P = .007, and P = .033, respectively). Eighteen sequences (2.1%) indicated evidence of transmitted drug resistance. Conclusions Our findings suggest high levels of transmission and bridging between risk groups

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]