Exploration of defined 2-dimensional working electrode shapes through additive manufacturing

In this work, the electrochemical response of different morphologies (shapes) and dimensions of additively manufactured (3D-printing) carbon black (CB)/poly-lactic acid (PLA) electrodes are reported. The working electrodes (WE) are printed using standard non-conductive PLA based filament for the housing and commercial Protopasta (carbon black/PLA) filament for the electrode and connection parts. Discs, squares, equilateral triangles and six-point stars with varying working electrode (WE) widths from 2 to 10 mm are evaluated herein towards the well-known near-ideal outer sphere redox probe hexaamineruthenium(III) chloride (RuHex). The results obtained show that triangular and squared electrodes exhibit a faster heterogeneous electron transfer (HET) rate constant (k°) than those of discs and stars, the latter being the slowest one. The results reported here also show a trend between the WE dimension and the reversibility of the electrochemical reaction, which decreases as the WE size increases. It is also observed that the ratio of the geometrical and electroactive area (%realarea) decreases as the overall WE size increases. On the other hand, these four WE shapes were applied toward the well-known and benchmarking detection of ascorbic acid (AA), uric acid (UA), β-nicotinamide adenine dinucleotide (NADH) and dopamine (DA). Moreover, electroanalytical detection of real acetaminophen (ACOP) samples is also showcased. The different designs for the working electrode proposed in this manuscript are easily changed to any other desired shapes thanks to the additive manufacturing methodology, these four shapes being just an example of what additive manufacturing can offer to experimentalists and to electrochemists in particular. Additive manufacturing is shown here as a versatile and rapid prototyping tool for the production of novel electrochemical sensing platforms, with scope for this work to be able to impact a wide variety of electroanalytical applications

Regression with Empirical Variable Selection: Description of a New Method and Application to Ecological Datasets

Despite recent papers on problems associated with full-model and stepwise regression, their use is still common throughout ecological and environmental disciplines. Alternative approaches, including generating multiple models and comparing them post-hoc using techniques such as Akaike's Information Criterion (AIC), are becoming more popular. However, these are problematic when there are numerous independent variables and interpretation is often difficult when competing models contain many different variables and combinations of variables. Here, we detail a new approach, REVS (Regression with Empirical Variable Selection), which uses all-subsets regression to quantify empirical support for every independent variable. A series of models is created; the first containing the variable with most empirical support, the second containing the first variable and the next most-supported, and so on. The comparatively small number of resultant models (n = the number of predictor variables) means that post-hoc comparison is comparatively quick and easy. When tested on a real dataset – habitat and offspring quality in the great tit (Parus major) – the optimal REVS model explained more variance (higher R2), was more parsimonious (lower AIC), and had greater significance (lower P values), than full, stepwise or all-subsets models; it also had higher predictive accuracy based on split-sample validation. Testing REVS on ten further datasets suggested that this is typical, with R2 values being higher than full or stepwise models (mean improvement = 31% and 7%, respectively). Results are ecologically intuitive as even when there are several competing models, they share a set of “core” variables and differ only in presence/absence of one or two additional variables. We conclude that REVS is useful for analysing complex datasets, including those in ecology and environmental disciplines

Artificial intelligence-assisted loop mediated isothermal amplification (AI-LAMP) for rapid detection of SARS-CoV-2

Until vaccines and effective therapeutics become available, the practical solution to transit safely out of the current coronavirus disease 19 (CoVID-19) lockdown may include the implementation of an effective testing, tracing and tracking system. However, this requires a reliable and clinically validated diagnostic platform for the sensitive and specific identification of SARS-CoV-2. Here, we report on the development of a de novo, high-resolution and comparative genomics guided reverse-transcribed loop-mediated isothermal amplification (LAMP) assay. To further enhance the assay performance and to remove any subjectivity associated with operator interpretation of results, we engineered a novel hand-held smart diagnostic device. The robust diagnostic device was further furnished with automated image acquisition and processing algorithms and the collated data was processed through artificial intelligence (AI) pipelines to further reduce the assay run time and the subjectivity of the colorimetric LAMP detection. This advanced AI algorithm-implemented LAMP (ai-LAMP) assay, targeting the RNA-dependent RNA polymerase gene, showed high analytical sensitivity and specificity for SARS-CoV-2. A total of ~200 coronavirus disease (CoVID-19)-suspected NHS patient samples were tested using the platform and it was shown to be reliable, highly specific and significantly more sensitive than the current gold standard qRT-PCR. Therefore, this system could provide an efficient and cost-effective platform to detect SARS-CoV-2 in resource-limited laboratories.BBSRC (repurposing the LAMP prototypes produced in the grant BB/R012695/1 to be used for SARS-CoV-2 laboratory testing at The University of Lancaster); BBSRC (BB/M008681/1 and BBS/E/I/00001852); British Council (172710323 and 332228521); Brunel University London; University of Surrey

Effectiveness of manual therapies: the UK evidence report

<p>Abstract</p> <p>Background</p> <p>The purpose of this report is to provide a succinct but comprehensive summary of the scientific evidence regarding the effectiveness of manual treatment for the management of a variety of musculoskeletal and non-musculoskeletal conditions.</p> <p>Methods</p> <p>The conclusions are based on the results of systematic reviews of randomized clinical trials (RCTs), widely accepted and primarily UK and United States evidence-based clinical guidelines, plus the results of all RCTs not yet included in the first three categories. The strength/quality of the evidence regarding effectiveness was based on an adapted version of the grading system developed by the US Preventive Services Task Force and a study risk of bias assessment tool for the recent RCTs.</p> <p>Results</p> <p>By September 2009, 26 categories of conditions were located containing RCT evidence for the use of manual therapy: 13 musculoskeletal conditions, four types of chronic headache and nine non-musculoskeletal conditions. We identified 49 recent relevant systematic reviews and 16 evidence-based clinical guidelines plus an additional 46 RCTs not yet included in systematic reviews and guidelines.</p> <p>Additionally, brief references are made to other effective non-pharmacological, non-invasive physical treatments.</p> <p>Conclusions</p> <p>Spinal manipulation/mobilization is effective in adults for: acute, subacute, and chronic low back pain; migraine and cervicogenic headache; cervicogenic dizziness; manipulation/mobilization is effective for several extremity joint conditions; and thoracic manipulation/mobilization is effective for acute/subacute neck pain. The evidence is inconclusive for cervical manipulation/mobilization alone for neck pain of any duration, and for manipulation/mobilization for mid back pain, sciatica, tension-type headache, coccydynia, temporomandibular joint disorders, fibromyalgia, premenstrual syndrome, and pneumonia in older adults. Spinal manipulation is not effective for asthma and dysmenorrhea when compared to sham manipulation, or for Stage 1 hypertension when added to an antihypertensive diet. In children, the evidence is inconclusive regarding the effectiveness for otitis media and enuresis, and it is not effective for infantile colic and asthma when compared to sham manipulation.</p> <p>Massage is effective in adults for chronic low back pain and chronic neck pain. The evidence is inconclusive for knee osteoarthritis, fibromyalgia, myofascial pain syndrome, migraine headache, and premenstrual syndrome. In children, the evidence is inconclusive for asthma and infantile colic.</p