Surface-enhanced Raman scattering (SERS) technology, as an important analytical tool, has been widely applied in the field of chemical and biomedical sensing. Automated testing is often combined with biochemical analysis technologies to shorten the detection time and minimize human error. The present SERS substrates for sample detection are time-consuming and subject to high human error, which are not conducive to the combination of SERS and automated testing. Here, a novel honeycomb-inspired SERS microarray is designed for large-area automated testing of urease in saliva samples to shorten the detection time and minimize human error. The honeycomb-inspired SERS microarray is decorated with hexagonal microwells and a homogeneous distribution of silver nanostars. Compared with the other four common SERS substrates, the optimal honeycomb-inspired SERS microarray exhibits the best SERS performance. The RSD of 100 SERS spectra continuously collected from saliva samples is 6.56%, and the time of one detection is reduced from 5 min to 10 s. There is a noteworthy linear relationship with a R2 of 0.982 between SERS intensity and urease concentration, indicating the quantitative detection capability of the urease activity in saliva samples. The honeycomb-inspired SERS microarray, combined with automated testing, provides a new way in which SERS technology can be widely used in biomedical applications.

UNASSIGNED: We previously demonstrated the convergent validity of a fully automated voice recognition analogue of the Symbol Digit Modalities Test (VR-SDMT) for evaluating processing speed in people with multiple sclerosis (pwMS).
UNASSIGNED: We aimed to replicate these results in 54 pwMS and 18 healthy controls (HCs), demonstrating the VR-SDMT\'s reliability.
UNASSIGNED: Significant correlations were found between the VR-SDMT and the traditional oral SDMT in the multiple sclerosis (MS) (r = -0.771, p < 0.001) and HC (r = -0.785, p < 0.001) groups.
UNASSIGNED: Taken collectively, our two studies demonstrate the reliability and validity of the VR-SDMT for assessing processing speed in pwMS.

Ventilator is an important medical instrument which can replace the function of autonomous ventilation artificially. Its safety and reliability are related to the health and even life safety of patients. With the publishing of the new national standard and international standard for ventilators, higher requirements are put forward for the detection and evaluation. This study mainly introduces an automatic test system for ventilator performance. The test system is based on PF-300 air-flow analyzer of Imtmedical and standard simulation lung. The automatic switch module of simulation lung is developed, and the automatic test system of ventilator is designed using the software development platform based on Python. It can not only automatically test all ventilation control parameters and monitoring parameters of the ventilator, but also realize automatic data recording, form reports and data analysis, and improve the efficiency and quality of inspection, detection and quality control.

Cognitive flexibility in non-human primates is traditionally measured with the conceptual set shifting task (CSST). In our laboratory, Guinea baboons (N = 24) were continuously tested with a CSST task during approximately 10 years. Our task involved the presentation of three stimuli on a touch screen all made from 3 possible colours and 3 shapes. The subjects had to touch the stimulus containing the stimulus dimension (e.g., green) that was constantly rewarded until the stimulus dimension changed. Analysis of perseveration responses, scores and response times collected during the last two years of testing (approximately 1.6 million trials) indicate (1) that the baboons have developed an \"expert\" form of cognitive flexibility and (2) that their performance was age-dependent, it was at a developing stage in juveniles, optimal in adults, declining in middle-aged, and strongly impaired in the oldest age group. A direct comparison with the data collected by Bonté , Flemming & Fagot (2011) on some of the same baboons and same task as in the current study indicates that (3) the performance of all age groups has improved after 10 years of training, even for the now old individuals. All these data validate the use of non-human primates as models of human cognitive flexibility and suggest that cognitive flexibility in humans has a long evolutionary history.

Combinatorial interaction testing, which is a technique to verify a system with numerous input parameters, employs a mathematical object called a covering array as a test input. This technique generates a limited number of test cases while guaranteeing a given combinatorial coverage. Although this area has been studied extensively, handling constraints among input parameters remains a major challenge, which may significantly increase the cost to generate covering arrays. In this work, we propose a mathematical operation, called \"weaken-product based combinatorial join\", which constructs a new covering array from two existing covering arrays. The operation reuses existing covering arrays to save computational resource by increasing parallelism during generation without losing combinatorial coverage of the original arrays. Our proposed method significantly reduce the covering array generation time by 13-96% depending on use case scenarios.

BACKGROUND: The Concept 2 (C2) rowing ergometer is used worldwide for home-based training, official competitions, and performance assessment in sports and science. Previous studies reported a disparate underestimation of mechanical power output positively related to an unclearly defined stroke variability. The aim of this study was to quantify the accuracy of the C2 while controlling for the potentially influencing variables of the rowing stroke by using a test rig for air-braked rowing ergometers and thus excluding biological variability.
METHODS: A unique motorized test rig for rowing ergometers was employed. Accuracy was assessed as the difference in mechanical power output between C2 and a reference system during steady (i.e., minimal variations of stroke power within a series of 50 spacemark, no -strokes) and unsteady simulated rowing (i.e., persistent variations during measurement series) while manipulating the stroke variables shape, force, or rate.
RESULTS: During steady simulated rowing, differences between C2 and the reference system ranged 2.9-4.3%. Differences were not significantly affected by stroke shapes (P = 0.153), but by stroke rates ranging 22-28 min-1 (P < 0.001). During unsteady simulated rowing with alterations of stroke force and rate, mean differences of 2.5-3.9% were similar as during steady simulated rowing, but the random error increased up to 18-fold. C2 underestimated mechanical power output of the first five strokes by 10-70%. Their exclusion reduced mean differences to 0.2-1.9%.
CONCLUSIONS: Due to the enormous underestimation of the start strokes, the nominal accuracy of the C2 depends on the total number of strokes considered. It ranges 0.2-1.9%, once the flywheel has been sufficiently accelerated. Inaccuracy increases with uneven rowing, but the stroke shape has a marginal impact. Hence, rowers should row as even as possible and prefer higher stroke rates to optimize C2 readings. We recommend external reference systems for scientific and high-performance assessments, especially for short tests designs where the start strokes will have a major impact.

Chronic liver disease (CLD) is a significant health problem affecting millions of people worldwide. In Scotland, CLD is a major cause of premature mortality. Liver function tests (LFTs) are a panel of frequently requested blood tests which may indicate liver disease. However, LFTs commonly contain at least one abnormal result, and abnormalities are rarely investigated to the extent recommended by national guidelines. The intelligent Liver Function Testing (iLFT) pathway is a novel, automated system designed to improve early diagnosis of liver disease. Initial abnormal LFT results trigger a cascade of reflexive testing to help identify the cause of any liver dysfunction. Algorithms combine these results with demographic and clinical data (such as patient age, body mass index, and alcohol intake) and fibrosis estimates to produce an electronic diagnosis and management plan. The pilot trial demonstrated that iLFT increased diagnosis of liver disease whilst remaining cost-effective. As such, iLFT has been fully operational across our region (NHS Tayside, Scotland) since August 2018. In the first year, iLFT generated over 2000 diagnoses from 1824 patient samples with an abnormality in the initial LFTs. The majority of these patients could be safely managed in primary care. iLFT allows maximal value to be obtained from liver blood tests across biochemistry, virology, immunology, and hematology with only minor changes to working practices. \'Intelligent\', algorithm-led testing pathways break down the barrier between clinical and laboratory medicine and offer solutions to many of the challenges experienced in modern healthcare systems.

The Roche Cobas chemistry analyzer\'s hemolysis index (HI) check function can directly report hemoglobin (Hb) concentrations. We aimed to validate the HI check function for the measurement of plasma cell-free Hb.
Plasma samples (6 μl) were taken by the analyzer and diluted in normal saline to measure the absorbance for Hb at 570 and 600 nm. Hb concentrations were calculated based on the molar extinction coefficient. Imprecision, lower limit of quantification (LLOQ), and analytical measurement range (AMR) of the assay were evaluated. The accuracy was determined by comparing the results between the new method and an existing spectrophotometric method. We further studied interference of icterus and lipemia and carryover. The performance of the assay in proficiency testing was also evaluated. The reference range was transferred from the existing method.
Within-run and total CVs were 1.7%-4.2% and 2.1%-7.0%, respectively (n = 20). The LLOQ was 11 mg/dL (CV = 8.1%) with the upper limit of AMR of 506 mg/dL. The results of the new method correlated well with the existing reference assay: Y (new method) = 0.974 x (reference method) + 4.9, r = 0.9990, n = 52. Bilirubin with a concentration up to 60 mg/dL and lipemic index up to 389 did not show significant interference. No significant carryover was detected. The average standard deviation index in proficiency testing was 0.03 ± 0.29. The reference range was <22 mg/dL.
Plasma cell-free Hb measurement using the HI check function meets the analytical requirements of the plasma cell-free Hb assays. It is simple and cost-effective.

Liver function tests (LFTs) are frequently requested blood tests which may indicate liver disease. LFTs are commonly abnormal, the causes of which can be complex and are frequently under investigated. This can lead to missed opportunities to diagnose and treat liver disease at an early stage. We developed an automated investigation algorithm, intelligent liver function testing (iLFT), with the aim of increasing the early diagnosis of liver disease in a cost-effective manner.
We developed an automated system that further investigated abnormal LFTs on initial testing samples to generate a probable diagnosis and management plan. We integrated this automated investigation algorithm into the laboratory management system, based on minimal diagnostic criteria, liver fibrosis estimation, and reflex testing for causes of liver disease. This algorithm then generated a diagnosis and/or management plan. A stepped-wedged trial design was utilised to compare LFT outcomes in general practices in the 6 months before and after introduction of the iLFT system. Diagnostic outcomes were collated and compared.
Of eligible patients with abnormal LFTs, 490 were recruited to the control group and 64 were recruited to the intervention group. The primary diagnostic outcome was based on the general practitioner diagnosis, which agreed with the iLFT diagnosis in 67% of cases. In the iLFT group, the diagnosis of liver disease was increased by 43%. Additionally, there were significant increases in the rates of GP visits after diagnosis and the number of referrals to secondary care in the iLFT group. iLFT was cost-effective with a low initial incremental cost-effectiveness ratio of £284 per correct diagnosis, and a saving to the NHS of £3,216 per patient lifetime.
iLFT increases liver disease diagnoses, improves quality of care, and is highly cost-effective. This can be achieved with minor changes to working practices and exploitation of functionality existing within modern laboratory diagnostics systems.
There is a growing epidemic of advanced liver disease, this could be offset by early detection and management. Checking liver blood tests (LFTs) should be an opportunity to diagnose liver problems, but abnormal results are often incompletely investigated. In this study we were able to substantially increase the diagnostic yield of the abnormal LFTs using the automated intelligent LFT system. With the addition of referral recommendations and management plans, this strategy provides optimum investigation and management of LFTs and is cost saving to the NHS.

One factor hindering the widespread use of cognitive testing for people with multiple sclerosis (pwMS) is the need for a tester to administer tests.
To undertake a proof of concept study assessing the feasibility of a fully automated speech recognition version of the Symbol Digit Modalities Test (auto-SDMT) in detecting abnormalities in processing speed in pwMS.
A sample of 50 pwMS and 32 matched healthy control (HC) subjects was tested with the auto-SDMT and the Brief International Cognitive Assessment for MS (BICAMS).
The percentages of MS participants impaired on the auto-SDMT and the traditional oral SDMT were 34% and 32%, respectively. Excellent convergent validity was found between the two tests (MS: r = -0.806, p < 0.001 and HC: r = -0.629, p < 0.001). The auto-SDMT had a similar sensitivity and specificity to the traditional oral SDMT in predicting overall impairment on the BICAMS.
The auto-SDMT is a sensitive measure for detecting processing speed deficits in pwMS. The test, the first entirely computer administrated oral response version of the SDMT, uses speech recognition technology, thereby eliminating the need for a human tester. Replication of the results is required in a larger representative sample of pwMS.