Electronic subsystems of a free-swimming robotic fish

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.Includes bibliographical references (p. 99).by Jamie L. Cho.M.Eng

Seeking information about assistive technology: Exploring current practices, challenges, and the need for smarter systems

Ninety percent of the 1.2 billion people who need assistive technology (AT) do not have access. Information seeking practices directly impact the ability of AT producers, procurers, and providers (AT professionals) to match a user's needs with appropriate AT, yet the AT marketplace is interdisciplinary and fragmented, complicating information seeking. We explored common limitations experienced by AT professionals when searching information to develop solutions for a diversity of users with multi-faceted needs. Through Template Analysis of 22 expert interviews, we find current search engines do not yield the necessary information, or appropriately tailor search results, impacting individuals’ awareness of products and subsequently their availability and the overall effectiveness of AT provision. We present value-based design implications to improve functionality of future AT-information seeking platforms, through incorporating smarter systems to support decision-making and need-matching whilst ensuring ethical standards for disability fairness remain

Noninvasive In Vivo Imaging to Evaluate Immune Responses and Antimicrobial Therapy against Staphylococcus aureus and USA300 MRSA Skin Infections

Staphylococcus aureus skin infections represent a significant public health threat because of the emergence of antibiotic-resistant strains such as methicillin-resistant S. aureus (MRSA). As greater understanding of protective immune responses and more effective antimicrobial therapies are needed, a S. aureus skin wound infection model was developed in which full-thickness scalpel cuts on the backs of mice were infected with a bioluminescent S. aureus (methicillin sensitive) or USA300 community-acquired MRSA strain and in vivo imaging was used to noninvasively monitor the bacterial burden. In addition, the infection-induced inflammatory response was quantified using in vivo fluorescence imaging of LysEGFP mice. Using this model, we found that both IL-1α and IL-1β contributed to host defense during a wound infection, whereas IL-1β was more critical during an intradermal S. aureus infection. Furthermore, treatment of a USA300 MRSA skin infection with retapamulin ointment resulted in up to 85-fold reduction in bacterial burden and a 53% decrease in infection-induced inflammation. In contrast, mupirocin ointment had minimal clinical activity against this USA300 strain, resulting in only a 2-fold reduction in bacterial burden. Taken together, this S. aureus wound infection model provides a valuable preclinical screening method to investigate cutaneous immune responses and the efficacy of topical antimicrobial therapies

Sensitivity of Mitochondrial Transcription and Resistance of RNA Polymerase II Dependent Nuclear Transcription to Antiviral Ribonucleosides

Ribonucleoside analogues have potential utility as anti-viral, -parasitic, -bacterial and -cancer agents. However, their clinical applications have been limited by off target effects. Development of antiviral ribonucleosides for treatment of hepatitis C virus (HCV) infection has been hampered by appearance of toxicity during clinical trials that evaded detection during preclinical studies. It is well established that the human mitochondrial DNA polymerase is an off target for deoxyribonucleoside reverse transcriptase inhibitors. Here we test the hypothesis that triphosphorylated metabolites of therapeutic ribonucleoside analogues are substrates for cellular RNA polymerases. We have used ribonucleoside analogues with activity against HCV as model compounds for therapeutic ribonucleosides. We have included ribonucleoside analogues containing 2′-C-methyl, 4′-methyl and 4′-azido substituents that are non-obligate chain terminators of the HCV RNA polymerase. We show that all of the anti-HCV ribonucleoside analogues are substrates for human mitochondrial RNA polymerase (POLRMT) and eukaryotic core RNA polymerase II (Pol II) in vitro. Unexpectedly, analogues containing 2′-C-methyl, 4′-methyl and 4′-azido substituents were inhibitors of POLRMT and Pol II. Importantly, the proofreading activity of TFIIS was capable of excising these analogues from Pol II transcripts. Evaluation of transcription in cells confirmed sensitivity of POLRMT to antiviral ribonucleosides, while Pol II remained predominantly refractory. We introduce a parameter termed the mitovir (mitochondrial dysfunction caused by antiviral ribonucleoside) score that can be readily obtained during preclinical studies that quantifies the mitochondrial toxicity potential of compounds. We suggest the possibility that patients exhibiting adverse effects during clinical trials may be more susceptible to damage by nucleoside analogs because of defects in mitochondrial or nuclear transcription. The paradigm reported here should facilitate development of ribonucleosides with a lower potential for toxicity

Brain structural covariance networks in obsessive-compulsive disorder: a graph analysis from the ENIGMA Consortium.

Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T1-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z-score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10-0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P < 0.0001), lower modularity (P < 0.0001), and lower small-worldness (P = 0.017). Detection of community membership emphasized lower network segregation in OCD compared to healthy controls. At the regional level, there were lower (rank-transformed) centrality values in OCD for volume of caudate nucleus and thalamus, and surface area of paracentral cortex, indicative of altered distribution of brain hubs. Centrality of cingulate and orbito-frontal as well as other brain areas was associated with OCD illness duration, suggesting greater involvement of these brain areas with illness chronicity. In summary, the findings of this study, the largest brain structural covariance study of OCD to date, point to a less segregated organization of structural covariance networks in OCD, and reorganization of brain hubs. The segregation findings suggest a possible signature of altered brain morphometry in OCD, while the hub findings point to OCD-related alterations in trajectories of brain development and maturation, particularly in cingulate and orbitofrontal regions

Nanoliter high throughput quantitative PCR

Understanding biological complexity arising from patterns of gene expression requires accurate and precise measurement of RNA levels across large numbers of genes simultaneously. Real time PCR (RT-PCR) in a microtiter plate is the preferred method for quantitative transcriptional analysis but scaling RT-PCR to higher throughputs in this fluidic format is intrinsically limited by cost and logistic considerations. Hybridization microarrays measure the transcription of many thousands of genes simultaneously yet are limited by low sensitivity, dynamic range, accuracy and sample throughput. The hybrid approach described here combines the superior accuracy, precision and dynamic range of RT-PCR with the parallelism of a microarray in an array of 3072 real time, 33 nl polymerase chain reactions (RT-PCRs) the size of a microscope slide. RT-PCR is demonstrated with an accuracy and precision equivalent to the same assay in a 384-well microplate but in a 64-fold smaller reaction volume, a 24-fold higher analytical throughput and a workflow compatible with standard microplate protocols

Allelic polymorphism in the T cell receptor and its impact on immune responses

In comparison to human leukocyte antigen (HLA) polymorphism, the impact of allelic sequence variation within T cell receptor (TCR) loci is much less understood. Particular TCR loci have been associated with autoimmunity, but the molecular basis for this phenomenon is undefined. We examined the T cell response to an HLA-B*3501-restricted epitope (HPVGEADYFEY) from Epstein-Barr virus (EBV), which is frequently dominated by a TRBV9*01 public TCR (TK3). However, the common allelic variant TRBV9*02, which differs by a single amino acid near the CDR2β loop (Gln55→His55), was never used in this response. The structure of the TK3 TCR, its allelic variant, and a nonnaturally occurring mutant (Gln55→Ala55) in complex with HLA-B*3501 revealed that the Gln55→His55 polymorphism affected the charge complementarity at the TCR-peptide-MHC interface, resulting in reduced functional recognition of the cognate and naturally occurring variants of this EBV peptide. Thus, polymorphism in the TCR loci may contribute toward variability in immune responses and the outcome of infection

Trans-ethnic Mendelian-randomization study reveals causal relationships between cardiometabolic factors and chronic kidney disease.

Funder: Government Department of BusinessFunder: Energy and Industrial Strategy (BEIS)Funder: Vice-Chancellor Fellowship from the University of BristolFunder: Shanghai Thousand Talents ProgramFunder: Academy of Medical Sciences (AMS) Springboard AwardFunder: BBSRC Innovation fellowshipFunder: NIHR Biomedical Research Centre at University Hospitals Bristol NHS Foundation Trust and the University of BristolBACKGROUND: This study was to systematically test whether previously reported risk factors for chronic kidney disease (CKD) are causally related to CKD in European and East Asian ancestries using Mendelian randomization. METHODS: A total of 45 risk factors with genetic data in European ancestry and 17 risk factors in East Asian participants were identified as exposures from PubMed. We defined the CKD by clinical diagnosis or by estimated glomerular filtration rate of 25 kg/m2. CONCLUSIONS: Eight cardiometabolic risk factors showed causal effects on CKD in Europeans and three of them showed causality in East Asians, providing insights into the design of future interventions to reduce the burden of CKD.This research has been conducted using the UK Biobank resource under Application Numbers ‘40135’ and ‘15825’. J.Z. is funded by a Vice-Chancellor Fellowship from the University of Bristol. This research was also funded by the UK Medical Research Council Integrative Epidemiology Unit [MC_UU_00011/1, MC_UU_00011/4 and MC_UU_00011/7]. J.Z. is supported by the Academy of Medical Sciences (AMS) Springboard Award, the Wellcome Trust, the Government Department of Business, Energy and Industrial Strategy (BEIS), the British Heart Foundation and Diabetes UK [SBF006\1117]. This study was funded/supported by the NIHR Biomedical Research Centre at University Hospitals Bristol NHS Foundation Trust and the University of Bristol (G.D.S., T.R.G. and R.E.W.). This study received funding from the UK Medical Research Council [MR/R013942/1]. J.Z., Y.M.Z. and T.R.G are funded by a BBSRC Innovation fellowship. J.Z. is supported by the Shanghai Thousand Talents Program. Y.M.Z. is supported by the National Natural Science Foundation of China [81800636]. H.Z. is supported by the Training Program of the Major Research Plan of the National Natural Science Foundation of China [91642120], a grant from the Science and Technology Project of Beijing, China [D18110700010000] and the University of Michigan Health System–Peking University Health Science Center Joint Institute for Translational and Clinical Research [BMU2017JI007]. N.F. is supported by the National Institutes of Health awards R01-MD012765, R01-DK117445 and R21-HL140385. R.C. is funded by a Wellcome Trust GW4 Clinical Academic Training Fellowship [WT 212557/Z/18/Z]. The Trøndelag Health Study (the HUNT Study) is a collaboration between HUNT Research Centre (Faculty of Medicine and Health Sciences, NTNU, Norwegian University of Science and Technology), Trøndelag County Council, Central Norway Regional Health Authority and the Norwegian Institute of Public Health. M.C.B. is supported by the UK Medical Research Council (MRC) Skills Development Fellowship [MR/P014054/1]. S.F. is supported by a Wellcome Trust PhD studentship [WT108902/Z/15/Z]. Q.Y. is funded by a China Scholarship Council PhD scholarship [CSC201808060273]. Y.C. was supported by the National Key R&D Program of China [2016YFC0900500, 2016YFC0900501 and 2016YFC0900504]. The China Kadoorie Biobank baseline survey and the first resurvey were supported by a grant from the Kadoorie Charitable Foundation in Hong Kong. The long-term follow-up is supported by grants from the UK Wellcome Trust [202922/Z/16/Z, 088158/Z/09/Z and 104085/Z/14/Z]. Japan-Kidney-Biobank was supported by AMED under Grant Number 20km0405210. P.C.H. is supported by Cancer Research UK [grant number: C18281/A19169]. A.K. was supported by DFG KO 3598/5–1. N.F. is supported by NIH awards R01-DK117445, R01-MD012765 and R21-HL140385. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health

A genome-scale metabolic model of Cupriavidus necator H16 integrated with TraDIS and transcriptomic data reveals metabolic insights for biotechnological applications

Exploiting biological processes to recycle renewable carbon into high value platform chemicals provides a sustainable and greener alternative to current reliance on petrochemicals. In this regard Cupriavidus necator H16 represents a particularly promising microbial chassis due to its ability to grow on a wide range of low-cost feedstocks, including the waste gas carbon dioxide, whilst also naturally producing large quantities of polyhydroxybutyrate (PHB) during nutrient-limited conditions. Understanding the complex metabolic behaviour of this bacterium is a prerequisite for the design of successful engineering strategies for optimising product yields. We present a genome-scale metabolic model (GSM) of C. necator H16 (denoted iCN1361), which is directly constructed from the BioCyc database to improve the readability and reusability of the model. After the initial automated construction, we have performed extensive curation and both theoretical and experimental validation. By carrying out a genome-wide essentiality screening using a Transposon-directed Insertion site Sequencing (TraDIS) approach, we showed that the model could predict gene knockout phenotypes with a high level of accuracy. Importantly, we indicate how experimental and computational predictions can be used to improve model structure and, thus, model accuracy as well as to evaluate potential false positives identified in the experiments. Finally, by integrating transcriptomics data with iCN1361 we create a condition-specific model, which, importantly, better reflects PHB production in C. necator H16. Observed changes in the omics data and in-silico-estimated alterations in fluxes were then used to predict the regulatory control of key cellular processes. The results presented demonstrate that iCN1361 is a valuable tool for unravelling the system-level metabolic behaviour of C. necator H16 and can provide useful insights for designing metabolic engineering strategies