DNA Logic-A novel approach to semiconductor based genetics

In the coming years, genetic test results will be increasingly used as indicators that influence medical decision-making. With chronic disease on the rise and the continuing global spread of infectious disease, novel instruments able to detect relevant mutations in a point-of-care setting are being developed to facilitate this increased demand in personalized health care. However, diagnosis for such demand often requires laboratory facilities and skilled personnel, meaning that diagnostic tests are restricted by time and access. This thesis presents a novel configuration for Ion sensitive Field Effect Transistors (ISFETs) to be used as a threshold detector during nucleic acid base pairs match. ISFET-based inverters are used as reaction threshold detectors to convey the chemical reaction level to a logic output once a threshold has been reached. Using this method, novel DNA logic functions are derived for nucleotides allowing local digital computations. The thesis also presents business models that enable such technology to be utilised in point of care applications, and experiment as results and business models given for an HIV point of care example are proposed

Free Inside: A Program to Help Inmates Cope with Life in Prison at Maui Community Correctional Center

This article describes the quantitative results of a study conducted at Maui Community Correctional Center in Hawaii. The program, Free Inside, was evaluated to determine its effectiveness as a rehabilitative tool for inmates. Each of the participants engaged in twelve-week cycles of twice weekly, hour-long classes in yoga, meditation, and chi gung practice. The findings reveal an association between inmate participation and increased awareness, self-esteem, sense of hope, and compassion. The authors recommend that similar programming become a part of the inmate experience in an effort to help rehabilitate and better prepare inmates for re-entry

A simple and rapid method for calculating identity-by-descent matrices using multiple markers

A fast, partly recursive deterministic method for calculating Identity-by-Descent (IBD) probabilities was developed with the objective of using IBD in Quantitative Trait Locus (QTL) mapping. The method combined a recursive method for a single marker locus with a method to estimate IBD between sibs using multiple markers. Simulated data was used to compare the deterministic method developed in the present paper with a stochastic method (LOKI) for precision in estimating IBD probabilities and performance in the task of QTL detection with the variance component approach. This comparison was made in a variety of situations by varying family size and degree of polymorphism among marker loci. The following were observed for the deterministic method relative to MCMC: (i) it was an order of magnitude faster; (ii) its estimates of IBD probabilities were found to agree closely, even though it does not extract information when haplotypes are not known with certainty; (iii) the shape of the profile for the QTL test statistic as a function of location was similar, although the magnitude of the test statistic was slightly smaller; and (iv) the estimates of QTL variance was similar. It was concluded that the method proposed provided a rapid means of calculating the IBD matrix with only a small loss in precision, making it an attractive alternative to the use of stochastic MCMC methods. Furthermore, developments in marker technology providing denser maps would enhance the relative advantage of this method

Design of Turing Systems with Physics-Informed Neural Networks

Reaction-diffusion (Turing) systems are fundamental to the formation of spatial patterns in nature and engineering. These systems are governed by a set of non-linear partial differential equations containing parameters that determine the rate of constituent diffusion and reaction. Critically, these parameters, such as diffusion coefficient, heavily influence the mode and type of the final pattern, and quantitative characterization and knowledge of these parameters can aid in bio-mimetic design or understanding of real-world systems. However, the use of numerical methods to infer these parameters can be difficult and computationally expensive. Typically, adjoint solvers may be used, but they are frequently unstable for very non-linear systems. Alternatively, massive amounts of iterative forward simulations are used to find the best match, but this is extremely effortful. Recently, physics-informed neural networks have been proposed as a means for data-driven discovery of partial differential equations, and have seen success in various applications. Thus, we investigate the use of physics-informed neural networks as a tool to infer key parameters in reaction-diffusion systems in the steady-state for scientific discovery or design. Our proof-of-concept results show that the method is able to infer parameters for different pattern modes and types with errors of less than 10\%. In addition, the stochastic nature of this method can be exploited to provide multiple parameter alternatives to the desired pattern, highlighting the versatility of this method for bio-mimetic design. This work thus demonstrates the utility of physics-informed neural networks for inverse parameter inference of reaction-diffusion systems to enhance scientific discovery and design

Universal Reference RNA as a standard for microarray experiments

BACKGROUND: Obtaining reliable and reproducible two-color microarray gene expression data is critically important for understanding the biological significance of perturbations made on a cellular system. Microarray design, RNA preparation and labeling, hybridization conditions and data acquisition and analysis are variables difficult to simultaneously control. A useful tool for monitoring and controlling intra- and inter-experimental variation is Universal Reference RNA (URR), developed with the goal of providing hybridization signal at each microarray probe location (spot). Measuring signal at each spot as the ratio of experimental RNA to reference RNA targets, rather than relying on absolute signal intensity, decreases variability by normalizing signal output in any two-color hybridization experiment. RESULTS: Human, mouse and rat URR (UHRR, UMRR and URRR, respectively) were prepared from pools of RNA derived from individual cell lines representing different tissues. A variety of microarrays were used to determine percentage of spots hybridizing with URR and producing signal above a user defined threshold (microarray coverage). Microarray coverage was consistently greater than 80% for all arrays tested. We confirmed that individual cell lines contribute their own unique set of genes to URR, arguing for a pool of RNA from several cell lines as a better configuration for URR as opposed to a single cell line source for URR. Microarray coverage comparing two separately prepared batches each of UHRR, UMRR and URRR were highly correlated (Pearson's correlation coefficients of 0.97). CONCLUSION: Results of this study demonstrate that large quantities of pooled RNA from individual cell lines are reproducibly prepared and possess diverse gene representation. This type of reference provides a standard for reducing variation in microarray experiments and allows more reliable comparison of gene expression data within and between experiments and laboratories

CREB is a critical regulator of normal hematopoiesis and leukemogenesis

The cAMP-responsive element binding protein (CREB) is a 43-kDa nuclear transcription factor that regulates cell growth, memory, and glucose homeostasis. We showed previously that CREB is amplified in myeloid leukemia blasts and expressed at higher levels in leukemia stem cells from patients with myeloid leukemia. CREB transgenic mice develop myeloproliferative disease after 1 year, but not leukemia, suggesting that CREB contributes to but is not sufficient for leukemogenesis. Here, we show that CREB is most highly expressed in lineage negative hematopoietic stem cells (HSCs). To understand the role of CREB in hematopoietic progenitors and leukemia cells, we examined the effects of RNA interference (RNAi) to knock down CREB expression in vitro and in vivo. Transduction of primary HSCs or myeloid leukemia cells with lentiviral CREB shRNAs resulted in decreased proliferation of stem cells, cell- cycle abnormalities, and inhibition of CREB transcription. Mice that received transplants of bone marrow transduced with CREB shRNA had decreased committed progenitors compared with control mice. Mice injected with Ba/F3 cells expressing either Bcr-Abl wild-type or T315I mutation with CREB shRNA had delayed leukemic infiltration by bioluminescence imaging and prolonged median survival. Our results suggest that CREB is critical for normal myelopoiesis and leukemia cell proliferation

Emotional valence and arousal affect reading in an interactive way: neuroimaging evidence for an approach-withdrawal framework

A growing body of literature shows that the emotional content of verbal material affects reading, wherein emotional words are given processing priority compared to neutral words. Human emotions can be conceptualised within a two-dimensional model comprised of emotional valence and arousal (intensity). These variables are at least in part distinct, but recent studies report interactive effects during implicit emotion processing and relate these to stimulus-evoked approach-withdrawal tendencies. The aim of the present study was to explore how valence and arousal interact at the neural level, during implicit emotion word processing. The emotional attributes of written word stimuli were orthogonally manipulated based on behavioural ratings from a corpus of emotion words. Stimuli were presented during an fMRI experiment while 16 participants performed a lexical decision task, which did not require explicit evaluation of a word's emotional content. Results showed greater neural activation within right insular cortex in response to stimuli evoking conflicting approach-withdrawal tendencies (i.e., positive high-arousal and negative low-arousal words) compared to stimuli evoking congruent approach vs. withdrawal tendencies (i.e., positive low-arousal and negative high-arousal words). Further, a significant cluster of activation in the left extra-striate cortex was found in response to emotional than neutral words, suggesting enhanced perceptual processing of emotionally salient stimuli. These findings support an interactive two-dimensional approach to the study of emotion word recognition and suggest that the integration of valence and arousal dimensions recruits a brain region associated with interoception, emotional awareness and sympathetic functions

Reductive Elimination Leading to C-C Bond Formation in Gold(III) Complexes: A Mechanistic and Computational Study

The factors affecting the rates of reductive C-C cross-coupling reactions in gold(III) aryls were studied using complexes that allow easy access to a series of electronically modified aryl ligands, as well as to gold methyl and vinyl complexes, using the pincer compounds (C^N^C)AuR (R = C6F5, CH=CMe2, Me and p-C6H4X, where X = OMe, F, H, But, Cl, CF3, or NO2) as starting materials (C^N^C = 2,6-(4′-ButC6H3)2pyridine dianion). Protodeauration followed by addition of 1 equiv. SMe2 leads to the quantitative generation of the thioether complexes [(C^N-CH)AuR(SMe2)]+. Upon addition of a second SMe2 pyridine is displaced, which triggers reductive aryl-R elimination. The rates for these cross-couplings increase in the sequence k(vinyl) > k(aryl) >> k(C6F5) > k(Me). Vinyl-aryl coupling is particularly fast, 1.15 × 10–3 L mol–1 s–1 at 221 K, while both C6F5 and Me couplings encountered higher barriers for the C-C bond forming step. Using P(p-tol)3 in place of SMe2 greatly accelerates C–C couplings. Computational modelling shows that in the C^N bonded compounds displacement of N by a donor L is required before the aryl ligands can adopt a conformation suitable for C-C bond formation, so that elimination takes place from a four-coordinate intermediate. C-C bond formation is rate limiting. In the non-chelating case, reductive C(sp2)-C(sp2) elimination from three-coordinate cations [(Ar1)(Ar2)AuL]+ is almost barrierless, particularly if L = phosphine

The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain–behavior relationships after stroke

The goal of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well‐powered meta‐ and mega‐analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large‐scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided