Cooking Hand Multi-Tool

The purpose of this project was to devise a solution for Jorge Segura, a US Marine who was wounded in Afghanistan and had to have his non-dominant arm amputated above the elbow. His current prosthetic attachments are not suited to cooking tasks, so he needed a way to cook more effectively with either prosthetic attachments or accessibility devices. The main tasks that he needed help with was holding down food on cutting boards and stabilizing pots, pans, and bowls especially when stirring. After background research, exploring commercially available devices, and talking with our challenger, our solution was to design three prosthetic attachments with a quick-change wrist to enable Jorge to stabilize pots, pans, and bowls, as well as hold food down on a cutting board and switch between the attachments efficiently. The quick-change wrist operates in a twist-and-lock fashion, with the wrist inserts mating into the wrist receiver and locking into place with magnets on each component. The wrist receiver easily mates with Jorge’s current wrist so that he can efficiently and easily install our quick-change wrist into his existing wrist. The wrist is predominantly made from delrin to reduce weight and improve component machinability. The prototyping process for the wrist cost $144.58 to develop our functional prototypes, while the estimated mass production cost is only$13.99 per wrist assembly. The clamp attachment interfaces with Jorge’s current body powered prosthetic arm through a connector plate mounted on the attachment body. Jorge is able to engage the cable to open the clamp so that it can fit over various sizes of pots and bowls, and release the tension in the cable to allow it to close over the pot or bowl. The clamp is also fully adjustable, with a trifold face designed with springs to conform to different diameters, and an angled guide that is adjustable with thumb screws to allow Jorge to angle the trifold to fit on curved bowls. It also includes a set of angled and straight inner prongs that can be removed for easier cleaning. The clamp is predominantly made from aluminum to reduce weight, and has an estimated cost of $209.55 to develop our functional prototypes, while the estimated mass production cost is only$43.25 per clamp assembly. The sleeve attachment allows Jorge to stabilize shallow pans with long handles. The design includes a simple diamond-shaped opening to fit over a variety of pan sizes, and has no moving parts for simplicity. Made from a 3D printed core and sheet metal inserts and connections, the sleeve is relatively lightweight and easy to manufacture. Design development to make our sleeve prototypes cost $124.91, while the estimated mass production cost of one sleeve is only$8.05. The cutting tool attachment enables Jorge to secure various sizes of food onto a cutting board. It is made of clear acrylic to allow Jorge to receive visual feedback from what he is cutting. The design of the cutting tool attachment includes several ridges to allow for better grip, and a narrow slit on the base to allow for perpendicular knife cuts. The cutting tool has an estimated development cost of $70.86 for the prototypes, with an estimated mass production cost of$4.72 per assembly. For future manufacturing of the wrist, we recommend that the wrist inserts be made from aluminum instead of delrin to improve the strength of the epoxied and press-fit joints. This would increase the weight of the device and decrease the cost slightly. We recommend that future iterations of the clamp include a more robust prong design, and a more secure connection for the angle guides. To manufacture more copies of the sleeve, we recommend adding a key to both sides of the connecting rod to fully restrain the rotation of the connecting rod. This would increase the weight and cost of the sleeve marginally. Finally, for future iterations of the cutting tool we recommend looking into a solid construction cast from food-safe resin in order to improve cutting tool durability with respect to impact loads

The Status of the Healthcare Workforce in the State of Nebraska

https://digitalcommons.unmc.edu/coph_policy_reports/1019/thumbnail.jp

Correlation functions quantify super-resolution images and estimate apparent clustering due to over-counting

We present an analytical method to quantify clustering in super-resolution localization images of static surfaces in two dimensions. The method also describes how over-counting of labeled molecules contributes to apparent self-clustering and how the effective lateral resolution of an image can be determined. This treatment applies to clustering of proteins and lipids in membranes, where there is significant interest in using super-resolution localization techniques to probe membrane heterogeneity. When images are quantified using pair correlation functions, the magnitude of apparent clustering due to over-counting will vary inversely with the surface density of labeled molecules and does not depend on the number of times an average molecule is counted. Over-counting does not yield apparent co-clustering in double label experiments when pair cross-correlation functions are measured. We apply our analytical method to quantify the distribution of the IgE receptor (Fc{\epsilon}RI) on the plasma membranes of chemically fixed RBL-2H3 mast cells from images acquired using stochastic optical reconstruction microscopy (STORM) and scanning electron microscopy (SEM). We find that apparent clustering of labeled IgE bound to Fc{\epsilon}RI detected with both methods arises from over-counting of individual complexes. Thus our results indicate that these receptors are randomly distributed within the resolution and sensitivity limits of these experiments.Comment: 22 pages, 5 figure

The deubiquitinase (DUB) USP13 promotes Mcl-1 stabilisation in cervical cancer

Protein ubiquitination is a critical regulator of cellular homeostasis. Aberrations in the addition or removal of ubiquitin can result in the development of cancer and key components of the ubiquitination machinery serve as oncogenes or tumour suppressors. An emerging target in the development of cancer therapeutics are the deubiquitinase (DUB) enzymes that remove ubiquitin from protein substrates. Whether this class of enzyme plays a role in cervical cancer has not been fully explored. By interrogating the cervical cancer data from the TCGA consortium, we noted that the DUB USP13 is amplified in ~15% of cervical cancer cases. We confirmed that USP13 expression was increased in cervical cancer cell lines, cytology samples from patients with cervical disease and in cervical cancer tissue. Depletion of USP13 inhibited cervical cancer cell proliferation. Mechanistically, USP13 bound to, deubiquitinated and stabilised Mcl-1, a pivotal member of the anti-apoptotic BCL-2 family. Furthermore, reduced Mcl-1 expression partially contributed to the observed proliferative defect in USP13 depleted cells. Importantly, the expression of USP13 and Mcl-1 proteins correlated in cervical cancer tissue. Finally, we demonstrated that depletion of USP13 expression or inhibition of USP13 enzymatic activity increased the sensitivity of cervical cancer cells to the BH3 mimetic inhibitor ABT-263. Together, our data demonstrates that USP13 is a potential oncogene in cervical cancer that functions to stabilise the pro-survival protein Mcl-1, offering a potential therapeutic target for these cancers

Data Carpentry: Workshops to Increase Data Literacy for Researchers

In many domains the rapid generation of large amounts of data is fundamentally changing how research is done. The deluge of data presents great opportunities, but also many challenges in managing, analyzing and sharing data. However, good training resources for researchers looking to develop skills that will enable them to be more effective and productive researchers are scarce and there is little space in the existing curriculum for courses or additional lectures. To address this need we have developed an introductory two-day intensive workshop, Data Carpentry, designed to teach basic concepts, skills, and tools for working more effectively and reproducibly with data. These workshops are based on Software Carpentry: two-day, hands-on, bootcamp style workshops teaching best practices in software development, that have demonstrated the success of short workshops to teach foundational research skills. Data Carpentry focuses on data literacy in particular, with the objective of teaching skills to researchers to enable them to retrieve, view, manipulate, analyze and store their and other’s data in an open and reproducible way in order to extract knowledge from data

Determination of HIV status and identification of incident HIV infections in a large, community-randomized trial: HPTN 071 (PopART).

INTRODUCTION: The HPTN 071 (PopART) trial evaluated the impact of an HIV combination prevention package that included "universal testing and treatment" on HIV incidence in 21 communities in Zambia and South Africa during 2013-2018. The primary study endpoint was based on the results of laboratory-based HIV testing for> 48,000 participants who were followed for up to three years. This report evaluated the performance of HIV assays and algorithms used to determine HIV status and identify incident HIV infections in HPTN 071, and assessed the impact of errors on HIV incidence estimates. METHODS: HIV status was determined using a streamlined, algorithmic approach. A single HIV screening test was performed at centralized laboratories in Zambia and South Africa (all participants, all visits). Additional testing was performed at the HPTN Laboratory Center using antigen/antibody screening tests, a discriminatory test and an HIV RNA test. This testing was performed to investigate cases with discordant test results and confirm incident HIV infections. RESULTS: HIV testing identified 978 seroconverter cases. This included 28 cases where the participant had acute HIV infection at the first HIV-positive visit. Investigations of cases with discordant test results identified cases where there was a participant or sample error (mixups). Seroreverter cases (errors where status changed from HIV infected to HIV uninfected, 0.4% of all cases) were excluded from the primary endpoint analysis. Statistical analysis demonstrated that exclusion of those cases improved the accuracy of HIV incidence estimates. CONCLUSIONS: This report demonstrates that the streamlined, algorithmic approach effectively identified HIV infections in this large cluster-randomized trial. Longitudinal HIV testing (all participants, all visits) and quality control testing provided useful data on the frequency of errors and provided more accurate data for HIV incidence estimates

Electrical Monitoring of sp³ Defect Formation in Individual Carbon Nanotubes

Many carbon nanotube (CNT) applications require precisely controlled chemical functionalization that is minimally disruptive to electrical performance. A promising approach is the generation of sp³ hybridized carbon atoms in the sp²-bonded lattice. We have investigated the possibility of using a carboxylic acid functionalized diazonium reagent to introduce a defined number of sp³ defects into electrically-contacted CNTs. Having performed real-time measurements on individually-contacted CNTs, we show that the formation of an individual defect is accompanied by an upward jump in resistance of approximately 6 kΩ. Additionally, we observe downward jumps in resistance of the same size, indicating that some defects are unstable. Our results are explained by a two-step reaction mechanism. Isolated aryl groups, formed in the first step, are unstable and dissociate on the minute timescale. Stable defect generation requires a second step, the coupling of a second aryl group adjacent to the first. Additional mechanistic understanding is provided by a systematic investigation of the gate voltage dependence of the reaction, showing that defect formation can be turned on and off. In summary, we demonstrate an unprecedented level of control over sp³ defect formation in electrically-contacted CNTs, and prove that sp³ defects are minimally disruptive to the electrical performance of CNTs

Genome-wide admixture and association study of serum iron, ferritin, transferrin saturation and total iron binding capacity in African Americans

Iron is an essential component of many important proteins and enzymes, including hemoglobin, which is responsible for carrying oxygen to the cells. African Americans (AAs) have a greater prevalence of iron deficiency compared with European Americans. We conducted genome-wide admixture-mapping and association studies for serum iron, serum ferritin, transferrin saturation (SAT) and total iron binding capacity (TIBC) in 2347 AAs participating in the Jackson Heart Study (JHS). Follow-up replication analyses for JHS iron-trait associated SNPs were conducted in 329 AA participants in the Healthy Aging in Neighborhoods of Diversity across the Life Span study (HANDLS). Higher estimated proportions of global African ancestry were significantly associated with lower levels of iron (P = 2.4 × 10−5), SAT (P = 0.0019) and TIBC (P = 0.042). We observed significant associations (P < 5 × 10−8) between serum TIBC levels and two independent SNPs around TF on chromosome 3, the first report of a genome-wide significant second independent signal in this region, and SNPs near two novel genes: HDGFL1 on chromosome 6 and MAF on chromosome 16. We also observed significant associations between ferritin levels and SNPs near GAB3 on chromosome X. We replicated our two independent associations at TF and our association at GAB3 in HANDLS. Our study provides evidence for both shared and unique genetic risk factors that are associated with iron-related measures in AAs. The top two variants in TF explain 11.2% of the total variation in TIBC levels in AAs after accounting for age, gender, body mass index and background ancestry

Post hoc Analysis for Detecting Individual Rare Variant Risk Associations Using Probit Regression Bayesian Variable Selection Methods in Case-Control Sequencing Studies

Rare variants (RVs) have been shown to be significant contributors to complex disease risk. By definition, these variants have very low minor allele frequencies and traditional single-marker methods for statistical analysis are underpowered for typical sequencing study sample sizes. Multimarker burden-type approaches attempt to identify aggregation of RVs across case-control status by analyzing relatively small partitions of the genome, such as genes. However, it is generally the case that the aggregative measure would be a mixture of causal and neutral variants, and these omnibus tests do not directly provide any indication of which RVs may be driving a given association. Recently, Bayesian variable selection approaches have been proposed to identify RV associations from a large set of RVs under consideration. Although these approaches have been shown to be powerful at detecting associations at the RV level, there are often computational limitations on the total quantity of RVs under consideration and compromises are necessary for large-scale application. Here, we propose a computationally efficient alternative formulation of this method using a probit regression approach specifically capable of simultaneously analyzing hundreds to thousands of RVs. We evaluate our approach to detect causal variation on simulated data and examine sensitivity and specificity in instances of high RV dimensionality as well as apply it to pathway-level RV analysis results from a prostate cancer (PC) risk case-control sequencing study. Finally, we discuss potential extensions and future directions of this work