Insulin Nucleation Using Voltage Clamping and Current Clamping Techniques

Crystallization of proteins is the prerequisite to obtaining three-dimensional molecular structures; by X-ray crystallography. The knowledge of protein structures is foundational and could pave ways to the understanding of a protein’s functions. However, obtaining single crystals is challenging and often a bottleneck let alone the need of satisfactory diffraction quality. In this thesis, quartz nanopipettes are used to spatially confine the location of nucleation and crystal growth at a nanometer scale. Current and voltage clamping techniques are employed to induce phase transition and subsequent crystal formation via external controls. Throughout the process, we can monitor and control the electrical current/potential that controls mass transport for local concentration adjustment

Greater Wheeling Regional Plan: Action Plan for Economic Development

The Wheeling Region has a long and rich history. However, the passage of time and the change that it has brought has not always been beneficial to the region. As a result, leaders in the region have begun a process to reevaluate and reinvent the Wheeling area and improve the regional economy. In this report, we discuss these strategies and recommend actions to further the Wheeling region’s economic development

Anisotropic dehydration of hydrogel surfaces

Efforts to develop tissue-engineered skin for regenerative medicine have explored natural, synthetic, and hybrid hydrogels. The creation of a bilayer material, with the stratification exhibited by native skin is a complex problem. The mechanically robust, waterproof epidermis presents the stratum corneum at the tissue/air interface, which confers many of these protective properties. In this work we explore the effect of high temperatures on alginate hydrogels, which are widely employed for tissue engineering due to their excellent mechanical properties and cellular compatibility. In particular, we investigate the rapid dehydration of the hydrogel surface which occurs following local exposure to heated surfaces with temperatures in the range 100-200 oC. We report the creation of a mechanically strengthened hydrogel surface, with improved puncture resistance and increased coefficient of friction, compared to the unheated surface. The use of a mechanical restraint during heating promoted differences in the rate of mass loss; the rate of temperature increase within the hydrogel, in the presence and absence of restraint, is simulated and discussed. It is hoped that the results will be of use in the development of processes suitable for preparing skin-like analogues; application areas could include wound healing and skin restoration

Oliveros Virus: A Novel Arenavirus from Argentina

AbstractDuring the past few decades several newly recognized rodent-borne arenaviruses have been shown to be associated with severe hemorrhagic fever cases in South America. Changes in ecology and farming practices throughout the region have increased the concern over the potential public health threat posed by such emerging virus diseases. Oliveros (OLV) virus is a recently discovered arenavirus of the rodentBolomys obscurusin Argentina. Genetic analysis of the small genomic RNA segment, which encodes the nucleocapsid protein and the envelope glycoproteins, shows that Oliveros is a novel, phylogenetically distinct member of theArenaviridaefamily which differs in nucleotide sequence from the previously characterized members by approximately 35% or more. Despite this level of diversity, OLV virus possesses the same ambisense genome structure and many overall RNA and protein features in common with other arenaviruses. These data represent an important first step in the development of specific immunological and PCR diagnostic reagents to allow assessment of the prevalence and disease potential of this virus

Mechanical properties of alginate hydrogels manufactured using external gelation

Alginate hydrogels are commonly used in biomedical applications such as scaffolds for tissue engineering, drug delivery, and as a medium for cell immobilization. Multivalent cations are often employed to create physical crosslinks between carboxyl and hydroxyl moieties on neighbouring polysaccharide chains, creating hydrogels with a range of mechanical properties. This work describes the manufacture and characterisation of sodium alginate hydrogels using the divalent cations Mg2+, Ca2+ and Sr2+ to promote gelation via non-covalent crosslinks. The gelation time and Young’s modulus are characterised as a function of cation and alginate concentrations. The implications of this work towards the use of environmental elasticity to control stem cell differentiation are discussed

Statistics of heart failure and mechanical circulatory support in 2020

Heart failure is increasing in prevalence, with approximately 26 million patients affected worldwide. This represents a significant cause of morbidity and mortality. Statistics regarding heart failure patient age, hospitalization likelihood, and mortality differ significantly by country. Heart failure patients are typically classified by ejection fraction, with distinct phenotypes associated with reduced ejection fraction (rEF) or preserved ejection fraction (pEF). Heart failure has a significant financial impact related to hospitalization, medication, and procedural expenses. The costs of heart failure also extend to the reduced quality of life conferred by heart failure symptoms. Management of heart failure includes a variety of interventions, including mechanical circulatory support (MCS). MCS, including left ventricular assist devices (LVADs), right ventricular assist devices (RVADs) and extracorporeal membrane oxygenation (ECMO), has been a means of managing end stage heart failure. Given the relative scarcity of transplant organs, the utilization of MCS, particularly as a bridge to transplantation (BTT) has grown significantly. In this review, we discuss statistics related to heart failure and MCS. We evaluate how patients are classified and examine global trends and regional differences. We then address MCS therapies, the costs associated with heart failure, the impact of heart failure on patient quality of life, and data regarding morbidity and mortality

Managing active learning processes in large first year physics classes: The advantages of an integrated approach

Turning lectures into interactive, student-led question and answer sessions is known to increase learning, but enabling interaction in a large class seems aninsurmountable task. This can discourage adoption of this new approach – who has time to individualize responses, address questions from over 200 students and encourage active participation in class? An approach adopted by a teaching team in large first-year classes at a research-intensive university appears to provide a means to do so. We describe the implementation of active learning strategies in a large first-year undergraduate physics unit of study, replacing traditional, content-heavy lectures with an integrated approach to question-driven learning. A key feature of our approach is that it facilitates intensive in-class discussions by requiring students to engage in preparatory reading and answer short written quizzes before every class. The lecturer uses software to rapidly analyze the student responses and identify the main issues faced by the students before the start of each class. We report the success of the integration of student preparation with this analysis and feedback framework, and the impact on the in-class discussions. We also address some of the difficulties commonly experienced by staff preparing for active learning classes

Engineering biofilms for biocatalysis

Biofilm, friend not foe: Single species biofilms can be engineered to form robust biocatalysts with greater catalytic activity and significantly improved catalytic longevity than purified and immobilised enzymes. We report the engineering, structural analysis and biocatalytic capability of a biofilm that can mediate the conversion of serine and haloindoles to halotryptophans

Effects of wildfire on sea otter ( Enhydra lutris ) gene transcript profiles

Wildfires have been shown to impact terrestrial species over a range of temporal scales. Little is known, however, about the more subtle toxicological effects of wildfires, particularly in downstream marine or downwind locations from the wildfire perimeter. These down‐current effects may be just as substantial as those effects within the perimeter. We used gene transcription technology, a sensitive indicator of immunological perturbation, to study the effects of the 2008 Basin Complex Fire on the California coast on a sentinel marine species, the sea otter ( Enhydra lutris ). We captured sea otters in 2008 (3 mo after the Basin Complex Fire was controlled) and 2009 (15 mo after the Basin Complex Fire was controlled) in the adjacent nearshore environment near Big Sur, California. Gene responses were distinctly different between Big Sur temporal groups, signifying detoxification of PAH s, possible associated response to potential malignant transformation, and suppression of immune function as the primary responses of sea otters to fire in 2008 compared to those captured in 2009. In general, gene transcription patterns in the 2008 sea otters were indicative of molecular reactions to organic exposure, malignant transformation, and decreased ability to respond to pathogens that seemed to consistent with short‐term hydrocarbon exposure.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109779/1/mms12151.pd

Predicting feed intake using modelling based on feeding behaviour in finishing beef steers.

Current techniques for measuring feed intake in housed cattle are both expensive and time-consuming making them unsuitable for use on commercial farms. Estimates of individual animal intake are required for assessing production efficiency. The aim of this study was to predict individual animal intake using parameters that can be easily obtained on commercial farms including feeding behaviour, liveweight and age. In total, 80 steers were used, and each steer was allocated to one of two diets (40 per diet) which consisted of (g/kg; DM) forage to concentrate ratios of either 494:506 (MIXED) or 80:920 (CONC). Individual daily fresh weight intakes (FWI; kg/day) were recorded for each animal using 32 electronic feeders over a 56-day period, and individual DM intakes (DMI; kg/day) subsequently calculated. Individual feeding behaviour variables were calculated for each day of the measurement period from the electronic feeders and included: total number of visits to the feeder, total time spent at the feeder (TOTFEEDTIME), total time where feed was consumed (TIMEWITHFEED) and average length of time during each visit to the feeder. These feeding behaviour variables were chosen due to ease of obtaining from accelerometers. Four modelling techniques to predict individual animal intake were examined, based on (i) individual animal TOTFEEDTIME relative expressed as a proportion of the dietary group (GRP) and total GRP intake, (ii) multiple linear regression (REG) (iii) random forests (RF) and (iv) support vector regressor (SVR). Each model was used to predict CONC and MIXED diets separately, giving eight prediction models, (i) GRP_CONC, (ii) GRP_MIXED, (iii) REG_CONC, (iv) REG_MIXED, (v) RF_CONC, (vi) RF_MIXED, (vii) SVR_CONC and (viii) SVR_MIXED. Each model was tested on FWI and DMI. Model performance was assessed using repeated measures correlations (R2_RM) to capture the repeated nature of daily intakes compared with standard R2, RMSE and mean absolute error (MAE). REG, RF and SVR models predicted FWI with R2_RM = 0.1–0.36, RMSE = 1.51–2.96 kg and MAE = 1.19–2.49 kg, and DMI with R2_RM = 0.13–0.19, RMSE = 1.15–1.61 kg and MAE = 0.9–1.28 kg. The GRP models predicted FWI with R2_RM = 0.42–0.49, RMSE = 2.76–3.88 kg and MAE = 2.46–3.47 kg, and DMI with R2_RM = 0.32–0.44, RMSE = 0.32–0.44 kg, MAE = 1.55–2.22 kg. Whilst more simplistic GRP models showed higher R2_RM than regression and machine learning techniques, these models had larger errors, likely due to individual feeding patterns not being captured. Although regression and machine learning techniques produced lower errors associated with individual intakes, overall precision of prediction was too low for practical use