Functional knee brace use for 21 h leads to a longer duration to achieve peak vertical ground reaction forces and the removal of the brace after 17.5 h results in faster loading of the knee joint.

PURPOSE: To investigate the landing strategies used after discontinuing and continuing the use of a functional knee brace (FKB) while performing a drop jump. METHODS: Following published methodology and power analysis, 23 uninjured male athletes, mean age of 19.4 ± 3.0 years, performed seven tests, during three test conditions (nonbraced, braced and removed brace or continued brace use), over 6 days of 12 testing sessions (S) for a total of 38.5 h. Each subject was provided with a custom-fitted FKB. This study focuses on the single leg drop jump kinetics during S12 when subjects were randomly selected to remove the FKB after 17.5 h or continued use of FKB. The time to peak vertical ground reaction forces (PVGRF) and PVGRF were recorded on landing in eight trials. RESULTS: After brace removal, a significantly shorter mean time to PVGRF was recorded (9.4 ± 22.9 msec (3.9%), p = 0.005, 95% confidence interval (95% CI): -168.1, 36.1), while continued brace use required a nonsignificant (n.s.) longer mean duration to achieve PVGRF (19.4 ± 53.6 msec (8.9%), n.s., 95% CI: -49.7, 73.4). No significant mean PVGRF difference was found in brace removal (25.3 ± 65.8 N) and continued brace use (25.1 ± 23.0 N). CONCLUSION: Removal of FKB after 17.5 h of use led to a significantly shorter time to achieve PVGRF, while continued brace use for 21 h required a longer duration to achieve PVGRF, suggesting faster and slower knee joint loading, respectively. Understanding the concerns associated with the use of FKB and the kinetics of the knee joint will assist clinicians in counselling athletes about the risks and benefits of using an FKB. LEVEL OF EVIDENCE: Level II.

Study protocol for Vascular Access outcome measure for function: a vaLidation study In hemoDialysis (VALID) : A multi-center, multinational validation study to assess the accuracy and feasibility of measuring vascular access function in clinical practice.

BACKGROUND: A functioning vascular access (VA) is crucial to providing adequate hemodialysis (HD) and considered a critically important outcome by patients and healthcare professionals. A validated, patient-important outcome measure for VA function that can be easily measured in research and practice to harvest reliable and relevant evidence for informing patient-centered HD care is lacking. Vascular Access outcome measure for function: a vaLidation study In hemoDialysis (VALID) aims to assess the accuracy and feasibility of measuring a core outcome for VA function established by the international Standardized Outcomes in Nephrology (SONG) initiative. METHODS: VALID is a prospective, multi-center, multinational validation study that will assess the accuracy and feasibility of measuring VA function, defined as the need for interventions to enable and maintain the use of a VA for HD. The primary objective is to determine whether VA function can be measured accurately by clinical staff as part of routine clinical practice (Assessor 1) compared to the reference standard of documented VA procedures collected by a VA expert (Assessor 2) during a 6-month follow-up period. Secondary outcomes include feasibility and acceptability of measuring VA function and the time to, rate of, and type of VA interventions. An estimated 612 participants will be recruited from approximately 10 dialysis units of different size, type (home-, in-center and satellite), governance (private versus public), and location (rural versus urban) across Australia, Canada, Europe, and Malaysia. Validity will be measured by the sensitivity and specificity of the data acquisition process. The sensitivity corresponds to the proportion of correctly identified interventions by Assessor 1, among the interventions identified by Assessor 2 (reference standard). The feasibility of measuring VA function will be assessed by the average data collection time, data completeness, feasibility questionnaires and semi-structured interviews on key feasibility aspects with the assessors. DISCUSSION: Accuracy, acceptability, and feasibility of measuring VA function as part of routine clinical practice are required to facilitate global implementation of this core outcome across all HD trials. Global use of a standardized, patient-centered outcome measure for VA function in HD research will enhance the consistency and relevance of trial evidence to guide patient-centered care. TRIAL REGISTRATION: Clinicaltrials.gov: NCT03969225. Registered on 31st May 2019.

The influence of neighbourhood equity on parkrunners in a British city.

Physical activity benefits both physical and mental health. Specific events may augment participation in physical activity at a population level. Parkrun is a popular, free, weekly, timed 5 km run or walk in public spaces located in five continents. However, these events may be distributed inequitably, possibly reinforcing inequities in health. As a prelude to a comprehensive analysis of a larger dataset, we explore a hypothesis that participation in parkrun is influenced by the socio-economic characteristics of both parkrunners and their park. Two parkruns, 4.5 km apart, were selected in the city of Sheffield in the United Kingdom. Defined by indices of multiple deprivation, Castle parkrun is located in an economically deprived neighbourhood and Hallam parkrun is in a prosperous area of the city. Parkrunners were defined by applying these same indices to the neighbourhood of home registration. Results: (i) the prosperous Hallam catchment area produced over five times more parkrun participants than Castle; (ii) compared with Castle, Hallam parkrun attracted more participants from both catchment areas; (iii) consequently, Hallam parkrun had seven times more participants than Castle parkrun. Conclusion: establishing parkruns in deprived areas is a necessary but not sufficient prerequisite for equity of participation in this heath promoting activity.

Parkruns are popular, free, weekly, timed 5 km runs or walks in public places across the world. They contribute to both mental and physical health. But they could also increase health inequality. Participants may already have the better health generally associated with above average incomes and home life in attractive neighbourhoods. Our pilot study compares two parkruns in the British city of Sheffield; one located in the city's poorer East End, the other in the richer West End.

C-SEQer: An Open-Source de Novo Glycan Identification Tool in C+.

Glycans play an important role in many biochemical processes, including protein function and cell signaling. Mass spectrometry (MS) provides the potential for high-throughput, high-sensitivity analysis of glycans but relies heavily on computational interpretation of experimental results. Open-source, stand-alone algorithms for de novo glycan MS analysis are few. One such algorithm, Sweet-SEQer, is available in Python. Glycan analysis of mass spectra can easily involve high volumes of data where Python's performance in time and memory is a noticeable bottleneck. This manuscript describes C-SEQer, a new implementation of the Sweet-SEQer algorithm in C++, which produces the same output as the original algorithm in approximately 15-fold less time with substantially less memory usage. The implementation is freely available with an MIT license.

A web-based system for creating, viewing, and editing precursor mass spectrometry ground truth data.

BACKGROUND: Mass spectrometry (MS) uses mass-to-charge ratios of measured particles to decode the identities and quantities of molecules in a sample. Interpretation of raw MS depends upon data processing algorithms that render it human-interpretable. Quantitative MS workflows are complex experimental chains and it is crucial to know the performance and bias of each data processing method as they impact accuracy, coverage, and statistical significance of the result. Creation of the ground truth necessary for quantitatively evaluating MS1-aware algorithms is difficult and tedious task, and better software for creating such datasets would facilitate more extensive evaluation and improvement of MS data processing algorithms. RESULTS: We present JS-MS 2.0, a software suite that provides a dependency-free, browser-based, one click, cross-platform solution for creating MS1 ground truth. The software retains the first version's capacity for loading, viewing, and navigating MS1 data in 2- and 3-D, and adds tools for capturing, editing, saving, and viewing isotopic envelope and extracted isotopic chromatogram features. The software can also be used to view and explore the results of feature finding algorithms. CONCLUSIONS: JS-MS 2.0 enables faster creation and inspection of MS1 ground truth data. It is publicly available with an MIT license at github.com/optimusmoose/jsms.

Quantitative Evaluation of Ion Chromatogram Extraction Algorithms.

Extracted ion chromatograms (XIC) are the fundamental signal unit in mass spectrometry. There are many algorithms for analyzing raw mass spectrometry data tasked with distinguishing real isotopic signals from noise. While one or more of the available algorithms are typically chained together for end-to-end mass spectrometry analysis, analysis of each algorithm in isolation provides a specific measurement of the strengths and weaknesses of each approach. Though qualitative opinions on extraction algorithm performance abound, quantitative performance has never been publicly ascertained. Quantitative evaluation has not occurred partly due to the lack of an available quantitative ground truth MS1 data set. Using a recently published, manually extracted XICs as ground truth data, we evaluate the quality of popular XIC algorithms, including MaxQuant, MZMine2, and several methods from XCMS. The manually curated data set comprises 48 human proteins stratified over 6 abundance orders of magnitude. Signals in the sample were manually curated into XIC using a commercial tool for visually identifying XIC and isotopic envelopes. XIC algorithms were applied to the manually extracted data using a grid search of possible parameters. Performance varied greatly between different parameter settings, though nearly all algorithms with parameter settings optimized with respect to the number of true positives recovered over 10 000 XICs.

Identifying critically important vascular access outcomes for trials in haemodialysis: an international survey with patients, caregivers and health professionals.

BACKGROUND: Vascular access outcomes reported across haemodialysis (HD) trials are numerous, heterogeneous and not always relevant to patients and clinicians. This study aimed to identify critically important vascular access outcomes. METHOD: Outcomes derived from a systematic review, multi-disciplinary expert panel and patient input were included in a multilanguage online survey. Participants rated the absolute importance of outcomes using a 9-point Likert scale (7-9 being critically important). The relative importance was determined by a best-worst scale using multinomial logistic regression. Open text responses were analysed thematically. RESULTS: The survey was completed by 873 participants [224 (26%) patients/caregivers and 649 (74%) health professionals] from 58 countries. Vascular access function was considered the most important outcome (mean score 7.8 for patients and caregivers/8.5 for health professionals, with 85%/95% rating it critically important, and top ranked on best-worst scale), followed by infection (mean 7.4/8.2, 79%/92% rating it critically important, second rank on best-worst scale). Health professionals rated all outcomes of equal or higher importance than patients/caregivers, except for aneurysms. We identified six themes: necessity for HD, applicability across vascular access types, frequency and severity of debilitation, minimizing the risk of hospitalization and death, optimizing technical competence and adherence to best practice and direct impact on appearance and lifestyle. CONCLUSIONS: Vascular access function was the most critically important outcome among patients/caregivers and health professionals. Consistent reporting of this outcome across trials in HD will strengthen their value in supporting vascular access practice and shared decision making in patients requiring HD.

A Peptide-Level Fully Annotated Data Set for Quantitative Evaluation of Precursor-Aware Mass Spectrometry Data Processing Algorithms.

Modern label-free quantitative mass spectrometry workflows are complex experimental chains for devising the composition of biological samples. With benchtop and in silico experimental steps that each have a significant effect on the accuracy, coverage, and statistical significance of the study result, it is crucial to understand the efficacy and biases of each protocol decision. Although many studies have been conducted on wet lab experimental protocols, postacquisition data processing methods have not been adequately evaluated in large part due to a lack of available ground truth data. In this study, we provide a novel ground truth data set for mass spectrometry data analysis at the precursor (MS1) signal level comprised of isolated peptide signals from UPS2, a popular complex standard for proteomics analysis, requiring more than 1000 h of manual curation. The data set consists of more than 62 million points with 1,294,008 grouped into 57,518 extracted ion chromatograms and those grouped into 14,111 isotopic envelopes. This data set can be used to evaluate many aspects of mass spectrometry data processing, including precursor mapping and signal extraction algorithms.

XNet: A Bayesian Approach to Extracted Ion Chromatogram Clustering for Precursor Mass Spectrometry Data.

Liquid chromatography mass spectrometry is a popular technique for high throughput analysis of biological samples. Identification and quantification of molecular species via mass spectrometry output requires postexperimental computational analysis of the raw instrument output. While tandem mass spectrometry remains a primary method for identification and quantification, species-resolved precursor data provides a rich source of unexploited information. Several algorithms have been proposed to resolve raw precursor signals into species-resolved isotopic envelopes. Many methods are particularly dependent on user parameters, and because they lack a means to optimize parameters, tend to perform poorly. To this end we present XNet, a parameter-less Bayesian machine learning approach to isotopic envelope extraction through the clustering of extracted ion chromatograms. We evaluate the performance of XNet and other prevalent methods on a quantitative ground truth data set. XNet is publicly available with an Apache license.

Conversations with 100 Scientists in the Field Reveal a Bifurcated Perception of the State of Mass Spectrometry Software.

Mass spectrometry is an important tool used by many scientists throughout the world. Nonetheless, feedback on the strengths and limitations of current software is often restricted to anecdote rather than formal inquiry. Over the course of 100 interviews over the state of mass spectrometry software, surprising patterns coalesced on several topics: perception of the frontier, perception of software quality, and differences between commercial and nonprofit environments. Most notably, interviews suggested a substantial schism between user satisfaction with current software and developer perceptions of software quality. Scientists' anonymized responses are presented and summarized into their suggestions for improving the state of the art.

Quantitative Evaluation of Algorithms for Isotopic Envelope Extraction via Extracted Ion Chromatogram Clustering.

LC-MS precursor (MS1) data are used increasingly often in conjunction with MS/MS data for the quantification, validation, and other computational mass spectrometry tasks. The efficacy of MS1 data on downstream tasks is dependent on the coverage and accuracy of the MS1 isotopic envelope extraction algorithms that delineate them from the dense backgrounds common in complex samples. Although several algorithms for extracted ion chromatogram (XIC) clustering exist, their performance has not yet been quantified, in part due to the difficulty of obtaining, isolating, and running some algorithms and in part due to the lack of quantitative MS1 ground truth. Using a newly available manually annotated ground truth data set, we measure the performance of several popular XIC clustering algorithms in time, coverage, and accuracy of resulting isotopic envelopes. We intend this work to provide a benchmark against which future algorithms can be scored.

Time-lapse imaging algorithms rank human preimplantation embryos according to the probability of live birth.

RESEARCH QUESTION: Can blastocysts leading to live births be ranked according to morphokinetic-based algorithms? DESIGN: Retrospective analysis of 781 single blastocyst embryo transfers, including all patient clinical factors that might be potential confounders for the primary outcome measure of live birth, was weighed using separate multi-variable logistic regression models. RESULTS: There was strong evidence of effect of embryo rank on odds of live birth. Embryos were classified A, B, C or D according to calculated variables; time to start (tSB) and duration (dB{tB - tSB}) of blastulation. Embryos of rank D were less likely to result in live birth than embryos of rank A (odds ratio [OR] 0.3046; 95% confidence interval [CI] 0.129, 0.660; P < 0.005). Embryos ranked B were less likely to result in live birth than those ranked A (OR 0.7114; 95% Cl 0.505, 1.001; P < 0.01), and embryos ranked C were less likely to result in live birth than those ranked A (OR 0.6501, 95% Cl 0.373, 1.118; P < 0.01). Overall, the LRT (Likelihood Ratio Test) p-value for embryo rank shows that there is strong evidence that embryo rank is informative as a whole in discriminating between live birth and no live birth outcomes (p = 0.0101). The incidence of live birth was 52.5% from rank A, 39.2% from rank B, 31.4% from rank C and 13.2% from rank D. CONCLUSIONS: Time-lapse imaging morphokinetic-based algorithms for blastocysts can provide objective hierarchical ranking of embryos for predicting live birth and may have greater discriminating power than conventional blastocyst morphology assessment.

Novel application of the matched case-control design to compare food supply chains during an Escherichia coli O157 outbreak, United Kingdom, 2016.

There is a need for innovative methods to investigate outbreaks of food-borne infection linked to produce with a complex distribution network. The investigation of a large outbreak of Escherichia coli O157 PT34 infection in the United Kingdom in 2016 indicated that catering venues associated with multiple cases had used salad leaves sourced from one supplier. Our aim was to investigate whether catering venues linked to cases were more likely to have used salad leaves from this supplier. We conducted a matched case-control study, with catering venues as the units of analysis. We compared venues linked to cases to those without known linked cases. We included 43 study pairs and obtained information on salad leaf products received by each venue. The odds of a case venue being supplied with salad leaves by Supplier A were 7.67 times (95% confidence interval: 2.30-25.53) those of control venues. This association provided statistical evidence to support the findings of the other epidemiological investigations undertaken for this outbreak. This is a novel approach which is labour-intensive but which addresses the challenge of investigating exposures to food across a complex distribution network.

JS-MS: a cross-platform, modular javascript viewer for mass spectrometry signals.

BACKGROUND: Despite the ubiquity of mass spectrometry (MS), data processing tools can be surprisingly limited. To date, there is no stand-alone, cross-platform 3-D visualizer for MS data. Available visualization toolkits require large libraries with multiple dependencies and are not well suited for custom MS data processing modules, such as MS storage systems or data processing algorithms. RESULTS: We present JS-MS, a 3-D, modular JavaScript client application for viewing MS data. JS-MS provides several advantages over existing MS viewers, such as a dependency-free, browser-based, one click, cross-platform install and better navigation interfaces. The client includes a modular Java backend with a novel streaming.mzML parser to demonstrate the API-based serving of MS data to the viewer. CONCLUSIONS: JS-MS enables custom MS data processing and evaluation by providing fast, 3-D visualization using improved navigation without dependencies. JS-MS is publicly available with a GPLv2 license at github.com/optimusmoose/jsms.

Probabilistic Generation of Mass Spectrometry Molecular Abundance Variance for Case and Control Replicates.

Shotgun differential mass spectrometry, the untargeted discovery of statistically significant differences between two or more samples, is a popular application with potential to advance biomarker detection, disease diagnostics, and other health objectives. Although many methods have been proposed, few have been quantitatively evaluated. The lack of ground truth data for shotgun difference detection limits quantitative evaluation and algorithmic advancement. While public mass-spectrometry data sets of single samples abound, data sets with more than one sample are rare, and data sets with the thousands of samples necessary to capture the complexity of real world populations are nonexistent due to technological and cost limitations. We present MSabundanceSIM, novel software for simulating any number of molecular samples based on one or a few real world data sets. The software uses a probabilistic model to generate case and control populations, with intuitive user parameters for tuning. We demonstrate variability by comparing to a real world data set over a range of abundances with differing biological and experimental variation coefficients. MSabundanceSIM is implemented in Ruby, is freely available, requires no external dependencies, and is suitable for a range of applications.

LC-MS alignment in theory and practice: a comprehensive algorithmic review.

Liquid chromatography-mass spectrometry is widely used for comparative replicate sample analysis in proteomics, lipidomics and metabolomics. Before statistical comparison, registration must be established to match corresponding analytes from run to run. Alignment, the most popular correspondence approach, consists of constructing a function that warps the content of runs to most closely match a given reference sample. To date, dozens of correspondence algorithms have been proposed, creating a daunting challenge for practitioners in algorithm selection. Yet, existing reviews have highlighted only a few approaches. In this review, we describe 50 correspondence algorithms to facilitate practical algorithm selection. We elucidate the motivation for correspondence and analyze the limitations of current approaches, which include prohibitive runtimes, numerous user parameters, model limitations and the need for reference samples. We suggest and describe a paradigm shift for overcoming current correspondence limitations by building on known liquid chromatography-mass spectrometry behavior.

Live births after embryo selection using morphokinetics versus conventional morphology: a retrospective analysis.

The increasing corpus of clinical studies using time-lapse imaging for embryo selection demonstrates considerable variation in study protocols and only limited-sized study cohorts. Outcome measures are based on implantation or clinical pregnancy; some predict blastulation from early cleavage-stage data, and few have evaluated live birth. Erroneously, most studies treat the embryos as independent variables and do not include patient or treatment variables in the statistical analyses. In this study, cohort size was 14,793 patients and 23,762 cycles. The incidence of live birth (n = 973 deliveries) after embryo selection by objective morphokinetic algorithms was compared with conventional embryology selection parameters (n = 6948 deliveries). A 19% increase in the incidence of live birth was observed when morphokinetic data were used to select embryos for the patient cohort aged younger than 38 years (OR 1.19 with 95% CI 1.06 to 1.34) using their own eggs, and an increase of 37% for oocyte recipients aged over 37 years (OR 1.370; 95% Cl 0.763 to 2.450). This is the largest study of the prospective use of time-lapse imaging algorithms in IVF reporting on live birth outcome, although the nature of purely a closed system versus standard incubation could not be assessed.

Jasmonate signalling drives time-of-day differences in susceptibility of Arabidopsis to the fungal pathogen Botrytis cinerea.

The circadian clock, an internal time-keeping mechanism, allows plants to anticipate regular changes in the environment, such as light and dark, and biotic challenges such as pathogens and herbivores. Here, we demonstrate that the plant circadian clock influences susceptibility to the necrotrophic fungal pathogen, Botrytis cinerea. Arabidopsis plants show differential susceptibility to B. cinerea depending on the time of day of inoculation. Decreased susceptibility after inoculation at dawn compared with night persists under constant light conditions and is disrupted in dysfunctional clock mutants, demonstrating the role of the plant clock in driving time-of-day susceptibility to B. cinerea. The decreased susceptibility to B. cinerea following inoculation at subjective dawn was associated with faster transcriptional reprogramming of the defence response with gating of infection-responsive genes apparent. Direct target genes of core clock regulators were enriched among the transcription factors that responded more rapidly to infection at subjective dawn than subjective night, suggesting an influence of the clock on the defence-signalling network. In addition, jasmonate signalling plays a crucial role in the rhythmic susceptibility of Arabidopsis to B. cinerea with the enhanced susceptibility to this pathogen at subjective night lost in a jaz6 mutant.

Controlling for confounding variables in MS-omics protocol: why modularity matters.

As the field of bioinformatics research continues to grow, more and more novel techniques are proposed to meet new challenges and improvements upon solutions to long-standing problems. These include data processing techniques and wet lab protocol techniques. Although the literature is consistently thorough in experimental detail and variable-controlling rigor for wet lab protocol techniques, bioinformatics techniques tend to be less described and less controlled. As the validation or rejection of hypotheses rests on the experiment's ability to isolate and measure a variable of interest, we urge the importance of reducing confounding variables in bioinformatics techniques during mass spectrometry experimentation.

JAMSS: proteomics mass spectrometry simulation in Java.

UNLABELLED: Countless proteomics data processing algorithms have been proposed, yet few have been critically evaluated due to lack of labeled data (data with known identities and quantities). Although labeling techniques exist, they are limited in terms of confidence and accuracy. In silico simulators have recently been used to create complex data with known identities and quantities. We propose Java Mass Spectrometry Simulator (JAMSS): a fast, self-contained in silico simulator capable of generating simulated MS and LC-MS runs while providing meta information on the provenance of each generated signal. JAMSS improves upon previous in silico simulators in terms of its ease to install, minimal parameters, graphical user interface, multithreading capability, retention time shift model and reproducibility. AVAILABILITY AND IMPLEMENTATION: The simulator creates mzML 1.1.0. It is open source software licensed under the GPLv3. The software and source are available at https://github.com/optimusmoose/JAMSS.