Syringe Pump

Our team was asked to design a syringe pump that would deliver fluid at a controlled flow rate to cells in a microfluidic device. The design process of our syringe pump proved to be a very dynamic one. The beginning research of both microfluidic devices and existing syringe pumps helped our team get an idea of ways we could implement existing aspects that work into our design. There were many existing devices that resembled the one that we were asked to make closely; however, due to our resources as students, we had to be a bit more creative in figuring out how to afford and assemble each component to the best of our abilities. Developing customer requirements was a huge step in the process of understanding what exactly you as our customer wanted to see delivered in our syringe pump. The main requirements of our pump were that it was able to deliver accurate shear stress values so that they could mimic those found in true physiology, that it was able to deliver an accurate flow rate to the device, that it was easily usable, and that it was compact to both fit in a desired location and have ease of mobility when needed to be moved to or from that location. Next, it was our job as the engineers to turn those requirements into quantitative engineering specifications that our device needed to meet via testing of the device once the prototype was finished. Once we determined what numbers needed to be hit to quantify the requirements set by you, we were able to create a network diagram of tasks in order to organize the design, manufacturing, and testing processes that we had ahead. Our design process then became a series of brainstorming via tools like a conjoint analysis, morphology, and Pugh matrices. We did these exercises in order to compile a multitude of ideas for each component of the pump to determine which combination of these ideas would produce the optimal pump that is attractive to the user and does the best job at meeting the customer specifications. We determined the main functions of our pump were inputting flow rate parameters on the interface, having a power source for the pushing mechanism, the physical pushing mechanism, and lastly the mechanism through which the fluid would be delivered into the tube. Ultimately, through the many exercises as well as iterations due to a multitude of realizations down the road, we settled upon using a stepper motor linear actuator for the pushing mechanism and a screen with buttons for the input from the user, powered by a 24 V DC Power Supply and connected by a needle attachment to the syringe. Next came acquiring the materials and aspects of the pump that were to be purchased from a manufacturer as well as designing the aspects that we were going to manufacture ourselves. The primary component of our design that we purchased was the FUYU stepper motor linear actuator, to which we programmed electrically and designed adapters to fit onto. Our electrical programming revolved around the Arduino UNO and the Sketch coding software. The chassis was our last component to design, and its main purpose was to keep the user safe from any potential harm from the pump and protect the pump from any water or other wear. When we had performed the Hazard Safety Assessment, we determined a lot of the risk involved the user having their hands in the pinch points as well as having the device fall on the user, both of which were mitigated by having a chassis that covered the pinch point and made the device more compact and mobile. Once we had those components designed, we determined how we would both manufacture and assemble the final prototype. These plans were surely dynamic as we changed materials and found new ways to better manufacture each piece. Critical changes included changing the chassis material from acrylic to polycarbonate, and thus changing the manufacturing process from laser jetting to water jetting to using a variety of saws to cut the pieces. Another critical change came after having manufactured the pusher block adapter, as we were sent back to the design process when the adapter did not perform the way we wanted it to. Additionally, the electrical side of our design manufacturing had to be iterated multiple times as we determined what was feasible and still effective for inputting the parameters. Our design changed from a 4 x 4 keypad to two buttons, one increasing the flow rate value and one decreasing the value. Once the prototype had been built, it was time to verify that we had made a device that met the customer specifications. We created protocols for how we would test these specifications and executed each of the four, the most time-consuming ones being the flow rate and shear stress tests. Our testing plans for shear stress included both an analytical COMSOL simulation through the solid model of the microfluidic device as well as physical testing of the velocity of the particles moving via the LabSmith Micro Particle Image Velocimetry microscope. The physical testing was to verify that our analytical model accurately displayed what velocity and thus shear stresses the cells in our microfluidic devices would be experiencing. Next, we tested flow rate via running water through our pump at specified flow rates for a given period of time, measuring the mass acquired on a sensitive scale to back-calculate what flow rate was actually being delivered. Additionally, we used a gauge to measure the displacement of our pusher block over a specified time to first ensure that the correct speed was being programmed to the motor. In terms of surface area testing, we simply used a ruler to measure the dimensions of the bottom of our chassis to verify it would fit in the desired location in the lab. Lastly, our ease of use testing included simply numbering the steps in the operations manual. Ultimately, our data showed that we did in fact create a pump that received an input and delivered a controllable flow rate and shear stress to the cells in the microfluidic devices, all while being compact and easily usable. After inputting a flow rate of 28.8 ml/hr, we measured the delivered flow rate to be 25.5 ml/hr, which was within our target percent error range of 15%. For shear stress, when entering a flow rate of 75.8 uL/hr, our physical testing showed a particle velocity of 295.6 um/s and our COMSOL velocity showed one of 358.91 um/s, putting these within range of our 20% error goal. We measured the bottom surface area of our pump to be 431.85 cm^2, which was well within our specification of 695 cm^2. Lastly, we measured 5 steps to program our device, which was our target specification. There were surely limitations to our data, as when flow rate decreased to smaller and smaller values it was increasingly harder to acquire data, and then additionally extremely difficult to have that data be accurate. Thus, at the flow rate of 0.76 uL/hr, which is the flow rate at which the pump will typically be used at, both the shear stress and flow rate specifications were not met via our testing. There are a multitude of reasons why our data may have been skewed, and we have plans for future testing to discover where errors might be introduced in our pump. Overall, our team learned much about the design process and grew as engineers while designing this syringe pump

How taphonomic alteration affects the detection and imaging of striations in stab wounds

Stabbing with a kitchen knife is a common methodof homicide in Europe. Serrated knives may leave tool mark-ings (striations) in tissues. Documentation of striations is nec-essary for their use as forensic evidence. Traditional methods(physical casting and photography) have significant limita-tions, and micro-computed tomography (micro-CT) has beentrialled in cartilage toBvirtually cast^wounds. Previous re-search has shown the proportion of striations in cartilage fallsfollowing decomposition. This project has investigated theeffects of taphonomic alteration and documentation methodsof striations in porcine skin. Fresh, decomposed, mummified,burnt and waterlogged stab wounds in a porcine analoguewere excised and imaged using photography, stereo-opticalmicroscopy and micro-CT. The proportion of striations ineach taphonomic group was determined from the images byindependent analysts. Striations were observed more frequent-ly in serrated blade wounds, although they were also identifiedin non-serrated blade wounds. The proportion of woundsshowing striations declined following decomposition. An in-versely proportional linear correlation between advancing de-composition and proportion of striations existed. Dehydration(mummification and burning) rendered serrated and non-serrated blade wounds indistinguishable. Water compositionaffected the preservation of striations. Identification ofstriations gradually declined after decomposition in tap water,but persisted to a point when left in brackish water. All threetechniques imaged striations; however, the optimum tech-nique was stereo-optical microscopy due to practical advan-tages and specific limitations affecting photography and mi-cro-CT. This study demonstrates the effects of taphonomicalteration on striations and suggests stereo-optical microscopyis the optimum method for their documentation

Genome-wide association identifies nine common variants associated with fasting proinsulin levels and provides new insights into the pathophysiology of type 2 diabetes.

OBJECTIVE: Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology. RESEARCH DESIGN AND METHODS: We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates. RESULTS: Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10(-8)). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10(-4)), improved β-cell function (P = 1.1 × 10(-5)), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10(-6)). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets. CONCLUSIONS: We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication

A database of chlorophyll a in Australian waters

Chlorophyll a is the most commonly used indicator of phytoplankton biomass in the marine environment. It is relatively simple and cost effective to measure when compared to phytoplankton abundance and is thus routinely included in many surveys. Here we collate 173, 333 records of chlorophyll a collected since 1965 from Australian waters gathered from researchers on regular coastal monitoring surveys and ocean voyages into a single repository. This dataset includes the chlorophyll a values as measured from samples analysed using spectrophotometry, fluorometry and high performance liquid chromatography (HPLC). The Australian Chlorophyll a database is freely available through the Australian Ocean Data Network portal (https://portal.aodn.org.au/). These data can be used in isolation as an index of phytoplankton biomass or in combination with other data to provide insight into water quality, ecosystem state, and relationships with other trophic levels such as zooplankton or fish

A database of chlorophyll a in Australian waters

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article.Chlorophyll a is the most commonly used indicator of phytoplankton biomass in the marine environment. It is relatively simple and cost effective to measure when compared to phytoplankton abundance and is thus routinely included in many surveys. Here we collate 173, 333 records of chlorophyll a collected since 1965 from Australian waters gathered from researchers on regular coastal monitoring surveys and ocean voyages into a single repository. This dataset includes the chlorophyll a values as measured from samples analysed using spectrophotometry, fluorometry and high performance liquid chromatography (HPLC). The Australian Chlorophyll a database is freely available through the Australian Ocean Data Network portal (https://portal.aodn.org.au/). These data can be used in isolation as an index of phytoplankton biomass or in combination with other data to provide insight into water quality, ecosystem state, and relationships with other trophic levels such as zooplankton or fish