Validation Protocol Research Articles

Development and validation of a real-time PCR assay protocol for the specific detection and quantification of pelagiphages in seawater samples

Earth is inhabited by numerous adaptations of cellular forms shaped by the persistent scrutiny of natural selection. Thus, as natural selection has fixed beneficial adaptations of functional traits, cellular life has conquered almost all environmental niches on our planet. However, cellular life succumbs in number and genetic diversity to viruses. Among all viruses, phages are highly prevalent in diverse environments, and due to their vast genetic diversity and abundance, their relevant role as significant players in several ecological processes is now fully recognized. Pelagiphages, bacteriophages infecting bacteria of the SAR11 clade, are the most abundant viruses in the oceans. However, the ecological contribution of pelagiphages on populations of Pelagibacterales remains largely underestimated. An essential aspect of estimating the impact of bacteriophages is their absolute and precise quantification, which provides relevant information about the host-virus interactions and the structure of viral assemblages. Consequently, due to its abundance and claimed influence in the biogeochemical cycling of elements, the accurate quantification of pelagiphages results in an essential task. This study describes the development and validation of a sensitive, specific, accurate and reproducible qPCR platform targeting pelagiphages. Moreover, this method allowed the detection and quantification of pelagiphages in the Gulf of California for the first time.

Patient decision aid for chemotherapy or exclusion in cisplatin-intolerant patients with locally-advanced cervical cancer (CECIL): protocol for development, validation and clinical testing

Patient decision aid for chemotherapy or exclusion in cisplatin-intolerant patients with locally-advanced cervical cancer (CECIL): protocol for development, validation and clinical testing

Study protocol for development and validation of a single tool to assess risks of stroke, diabetes mellitus, myocardial infarction and dementia: DemNCD-Risk

IntroductionCurrent efforts to reduce dementia focus on prevention and risk reduction by targeting modifiable risk factors. As dementia and cardiometabolic non-communicable diseases (NCDs) share risk factors, a single risk-estimating tool...

Protocol for development and validation of a prediction model for post-induction hypotension in elderly patients undergoing non-cardiac surgery: a prospective cohort study

IntroductionPost-induction hypotension (PIH) is a common event in elderly surgical patients and is associated with increased postoperative morbidity and mortality. This study aims to develop and validate a PIH prediction...

Reliability And Validity Of A Home-Based Protocol To Assess Physical Function: Preliminary Results

Reliability And Validity Of A Home-Based Protocol To Assess Physical Function: Preliminary Results

An Independent Examination of the Mindful Sport Performance Enhancement Protocol in National Collegiate Athletic Association Swimming and Diving

The mindful sport performance enhancement (MSPE) protocol is designed to enhance mindfulness, emotional regulation, and attentional awareness and control. The MSPE consists of trainer led group sessions teaching the concepts of mindfulness through discussion and meditation practice. However, little research has tested the MSPE protocol’s adaptability and generalizability to National Collegiate Athletic Association (NCAA) Division-I teams and practitioners independent of the MSPE protocol’s creators. Therefore, the aim of the present study was to test the efficacy of an adapted MSPE protocol. The adapted MSPE protocol was delivered to a NCAA Division I team while a second team participated as a potentially equivalent control group. Both teams completed measures of attentional control, flow, rumination, and mindful attention as primary outcome variables. Results revealed significant decreases in rumination and trait anxiety, as well as improvements in concentration control and focusing ability compared with the control group. Findings support the external validity of the MSPE protocol to adapt to independent practitioners and a previously unstudied combination of sport and level of competition.

Neurobiological characteristics of individuals who have committed sexual offenses: A systematic review

Sexual violence is recognized as one of the most serious forms of violence. Assessment of individuals with history of sexual offenses is essential to inform placement decisions (e.g., inpatient or outpatient treatment, foster or residential placement), guide legal dispositions, prevent their offenses, and provide the basis for treatment planning. Insights into the neurobiological characteristics in subtypes of sexual offenses are particularly important both to the advancement of its understanding and guide research clinical efforts. The goal of this systematic review is to synthesize the findings regarding the neurobiological characteristics of individuals who have committed sexual offenses, focusing on the identification of the factors that should be targeted in the assessment of these individuals. Studies related to the topic were obtained from multiple databases, through rigorous exclusion and inclusion criteria. Only empirical studies with quantitative methodologies were included. Aims, methodological aspects (sample and instruments), and main conclusions were extracted from each study. In general, this systematic review found psychophysiological, neuroimaging, and neurophysiological studies, which used neurobiological techniques to evaluate individuals who have committed sexual offenses. A substantial part of the studies examined the neuroimaging profile of individuals who have committed sexual offenses against children with or without pedophilic interests, suggesting anatomical changes and functional deficits. Overall, there is enough evidence to support the link between specific neurobiological characteristics and sexual offenses, with this link being mainly revealed by neuroimaging and endocrinology studies. The knowledge about neurobiological characteristics implicated in sexual offending can help developing more accurate and valid protocols for the evaluation of individuals involved in such offenses, thereby improving diagnosis and treatment.

Deep Insights of Learning-Based Micro Expression Recognition: A Perspective on Promises, Challenges, and Research Needs

Micro expression recognition (MER) is a very challenging area of research due to its intrinsic nature and fine-grained changes. In the literature, the problem of MER has been solved through handcrafted/descriptor-based techniques. However, in recent times, deep learning (DL) based techniques have been adopted to gain higher performance for MER. Also, rich survey articles on MER are available by summarizing the datasets, experimental settings, conventional and deep learning methods. In contrast, these studies lack the ability to convey the impact of network design paradigms and experimental setting strategies for DL based MER. Therefore, this paper aims to provide a deep insight into the DL-based MER frameworks with a perspective on promises in network model designing, experimental strategies, challenges, and research needs. Also, the detailed categorization of available MER frameworks is presented in various aspects of model design and technical characteristics. Moreover, an empirical analysis of the experimental and validation protocols adopted by MER methods is presented. The challenges mentioned earlier and network design strategies may assist the affective computing research community in forge ahead in MER research. Finally, we point out the future directions, research needs and draw our conclusions.

Surface EMG feature disentanglement for robust pattern recognition

Extracting robust features from surface electromyogram (sEMG) for accurate pattern recognition is a central research topic in biomechanics and human-machine interaction. Although related topics have been extensively investigated, the robustness of the recognition models over the inter-subject and inter-session signal variabilities remains challenging. From the perspective of feature projection, here we have proposed and validated the concept of sEMG feature disentanglement. We used an autoencoder-like architecture with specialized loss functions to explicitly decompose the sEMG features into the pattern-specific and subject-specific components. The former can be applied to robust sEMG pattern recognition, while the latter can be used as task-independent biometric identifiers. The proposed method was evaluated on data from twenty subjects with training and testing data acquired 3-25 days apart. The hand gesture recognition performance under the rigorous cross-subject and cross-day validation protocols demonstrates the proposed concept, showing a significant performance improvement over the state-of-the-art methods. Overall, this work provides a new insight into developing robust sEMG-based pattern recognition models. Moreover, it also indicates several exciting research directions in sEMG analysis, like task-independent sEMG biometric, sEMG privacy-preserving, and sEMG style-transfer.

Explainable Artificial Intelligence based Ensemble Machine Learning for Ovarian Cancer Stratification using Electronic Health Records

The purpose of this study is to show how ensemble learning-driven machine learning algorithms outperform individual machine learning algorithms at predicting ovarian cancer on a biomarker dataset. Additionally, this study provides model explanations using explainable Artificial Intelligence methods, The method involved gathering and combining 49 risk factors from 349 patients. We hypothesize that ensemble machine learning systems are superior to individual Machine Learning systems in predicting ovarian cancer. The Machine Learning system consists of five individual Machine Learning and five ensemble Machine Learning systems were trained using K-10 cross validation protocols. These training models were then used to predict the development of benign ovarian tumors and ovarian cancer tumors patients. The AUC and Accuracy metrics for ensemble machine learning increased by 19% and 16%. The MCC and Kappa scores for ensemble Machine Learning also increased over individual machine learning by 29% and 33%, respectively. As a result, we draw the conclusion that ensembled-based algorithms outperform individual machine learning in terms of ovarian carcinoma prediction.

(Invited) Electrolyser Manufacturing Scale-up Versus Design Development for Meeting Green H2 Targets

Cummins-Hydrogenics pioneered our MW-scale PEM electrolysis cell stack architecture in 2012 and has built and operated multiple sites since, including the 20 MW Bécancour facility for Air Liquide from 2020. Lessons learned from these projects provide a springboard for large-scale manufacturing and deployment of PEM electrolysers worldwide and Cummins has announced GW-scale manufacturing deployment in Europe, N America and Asia. This is required to meet the growing global demand for PEM electrolysers, which derives from the targets and subsidies for green hydrogen production announced by many governments.Concurrent to this manufacturing scale-up, significant work on cost reduction and technology advancement is ongoing resulting in anticipated cost decreases from catalyst loading (Ir<150g/MW), efficiency improvements (<46 kWh/kg) and higher current density, all of which need to be achieved for commercial viability. Driving down the Ir-loading of PEM electrolysers while increasing current densities will remain the primary driver of CapEx reductions in the short to medium term but the deployment of large-scale manufacturing also allows for significant economies of scale. Recycling and regeneration of used components will also become a larger issue and new processes need to be implemented for each stack component.Moving from a project-based design methodology to design for volume manufacturing, all while maintaining the fast pace of technology development, makes for significant challenges and can lead to processing waste and inefficiencies. Rigorous testing and validation protocols are needed across the industry in order to successfully scale-up while implementing technology improvements necessary to meet TCO targets. This talk will focus on the juxtaposition of these challenges and ways to mitigate future risks.

Test-retest reliability and construct validity of trunk extensor muscle force modulation accuracy.

Low back pain is associated with changes in trunk muscle structure and function and motor control impairments. Voluntary force modulation (FM) of trunk muscles is a unique and under-investigated motor control characteristic. One of the reasons for this paucity of evidence is the lack of exploration and publication on the reliability and validity of trunk FM protocols. The purpose of this study was to determine the within- and between-day test-retest reliability and construct validity for trunk extensor muscle FM. Twenty-nine healthy participants were tested under three FM conditions with different modulation rates. Testing was performed on a custom-built apparatus designed for trunk isometric force testing. FM accuracy relative to a fluctuating target force (20-50%MVF) was quantified using the root mean square error of the participant's generated force relative to the target force. Reliability and precision of measurement were assessed using the Intraclass Correlation Coefficient (ICC), standard error of measurement (SEM), minimal detectable difference (MDD95), and Bland-Altman plots. In a subset of participants, we collected surface electromyography of trunk and hip muscles. We used non-negative matrix factorization (NNMF) to identify the underlying motor control strategies. Within- and between-day test-retest reliability was excellent for FM accuracy across the three conditions (ICC range: 0.865 to 0.979). SEM values ranged 0.9-1.8 Newtons(N) and MDD95 ranged from 2.4-4.9N. Conditions with faster rates of FM had higher ICCs. NNMF analysis revealed two muscle synergies that were consistent across participants and conditions. These synergies demonstrate that the muscles primarily involved in this FM task were indeed the trunk extensor muscles. This protocol can consistently measure FM accuracy within and between testing sessions. Trunk extensor FM, as measured by this protocol, is not specific to any trunk muscle group but is the result of modulation by all the trunk extensor muscles.

Comparison of quantitative real-time PCR targeting &lt;i&gt;nuc&lt;/i&gt; gene and culture-based plate count methods for quantification of &lt;i&gt;Staphylococcus aureus&lt;/i&gt; in raw cow milk

Staphylococcal food poisoning (SFP) is caused by ingestion of enterotoxins produced by enterotoxigenic Staphylococcus aureus when the cell population exceeds 5 Log CFU per gram/ml of food. The Objectives of this study were to evaluate the performance of SYBR Green 1-based quantitative real-time PCR (qPCR) targeting the nuc gene for the quantification of S. aureus in milk and to compare the assay with the plate count method. The qPCR and the plate count were applied for the quantification of S. aureus in 92 naturally contaminated and artificially spiked bulk milk samples. Optimized standard curves were generated as the qPCR employed the absolute quantification method. The qPCR assay discriminates S. aureus from other Staphylococcus species with a large difference in quantification cycle (Cq) (Mean S. aureus Cq = 13.83± 0.93; other staphylococci Cq= 30.34 ± 2.65). The standard curve showed 91 % amplification efficiency and 0.98 coefficients of correlation (R2 ). The detection and quantification limit of the assay was 18 copies of the nuc gene. The precision of the assay as expressed by standard deviation was 0.12 – 0.3 for intra-assay and 0.29 – 0.5 for inter-assay variability. In artificially contaminated milk, the R2 between CFU ml-1 and S. aureus cell equivalent (SCE) ml-1 was 0.95, which implies, the estimation of CFU ml-1 in raw milk by qPCR is possible. A statistically significant (p&lt; 0.05) difference in S. aureus count was documented between qPCR and plate count. The average SCE (5.59 ±1.55 Log SCE ml-1) estimated by qPCR was one Log higher than CFU (4.46 ± 1.06 Log CFU ml-1) estimated by plate count. Furthermore, 28% of the samples with &lt; 5 Log ml-1 S. aureus by plate count had &gt; 5 Log ml-1 by qPCR. Hence, the qPCR is recommended for routine and research work for its advantage of rapid, sensitivity, and reliability. Further study on validation of the qPCR protocol in different food matrixes for quantification of foodborne pathogens and cost-benefit analysis of the assay is required.

On-Chip Reconstitution of Uniformly Shear-Sensing 3D Matrix-embedded Multicellular Blood Microvessel.

Preclinical human-relevant modeling of organ-specific vasculature offers a unique opportunity to recreate pathophysiological intercellular, tissue-tissue, and cell-matrix interactions for a broad range of applications. Here, we present a reliable, and simply reproducible process for constructing user-controlled long rounded extracellular matrix (ECM)-embedded vascular microlumens on-chip for endothelization and co-culture with stromal cells obtained from human lung. We demonstrate the critical impact of microchannel cross-sectional geometry and length on uniform distribution and magnitude of vascular wall shear stress, which is key when emulating in vivo-observed blood flow biomechanics in health and disease. In addition, we provide an optimization protocol for multicellular culture and functional validation of the system. Moreover, we show the ability to finely tune rheology of the three-dimensional natural matrix surrounding the vascular microchannel to match pathophysiological stiffness. In summary, we provide the scientific community with a matrix-embedded microvasculature on-chip populated with all-primary human-derived pulmonary endothelial cells and fibroblasts to recapitulate and interrogate lung parenchymal biology, physiological responses, vascular biomechanics, and disease biogenesis in vitro. Such a mix-and-match synthetic platform can be feasibly adapted to study blood vessels, matrix, and ECM-embedded cells in other organs and be cellularized with additional stromal cells.

An Improved Secure Authentication in Lightweight IoT

Internet of Things (IoT) has been widely accepted by users and with rapid development of cloud computing, users are able to access the IoT services in various environment, including smart home, healthcare and smart factory. However, users are insecure as their data is being transmitted via open communication channel. The previous research protocol does not resist insider attack which leads to insecure scheme. In this proposal, we propose an enhanced security measurement to resist insider attack. The proposed scheme expected to achieve security requirements and resist insider attack. The proposed scheme will be validated using the automated validation of internet security protocols and applications (AVISPA) simulation tool and we will compare the performance and security features of the existing scheme and the proposed scheme.

Flow Cytometry Method Validation Protocols.

Analytical method validation provides a means to ensure that data are credible and reproducible. This article will provide a brief introduction to analytical method validation as applied to cellular analysis by flow cytometry, along with practical procedures for four different types of validation. The first, Basic Protocol 1 (the limited validation protocol), is recommended for research and non-regulated laboratories. Next, Basic Protocol 2) presents a reasonable, fit-for-purpose validation approach appropriate for biopharma and research settings. Basic Protocol 3 addresses the type of validation performed in clinical laboratories for moderate-risk tests developed in house. Finally, Basic Protocol 4 describes the process that should be applied whenever a method is being transferred from one facility to another. All four validation plans follow the fit-for-purpose validation approach, in which the validation parameters are selected based on the intended use of the assay. These validation protocols represent the minimal requirement and may not be applicable for every intended use such as high-risk clinical assays or data to be used as a primary endpoint in a clinical trial. The recommendations presented here are consistent with the white papers published by the American Association of Pharmaceutical Scientists and the International Clinical Cytometry Society, as well as with Clinical Laboratory Standards Institute Guideline H62: Validation of Assays Performed by Flow Cytometry (CLSI, 2021). © 2023 Wiley Periodicals LLC. Basic Protocol 1: Limited validation Basic Protocol 2: Fit-for-purpose validation for biopharma and research settings Basic Protocol 3: Validation for moderate clinical risk laboratory developed tests Basic Protocol 4: Transfer validation.

Predicting risk of suicidal behaviour after initiation of selective serotonin reuptake inhibitors in children, adolescents and young adults: protocol for development and validation of clinical prediction models

IntroductionThere is concern regarding suicidal behaviour risk during selective serotonin reuptake inhibitor (SSRI) treatment among the young. A clinically useful model for predicting suicidal behaviour risk should have high predictive...

Validation through field data of LineCore, a lightweight Eddy-current sensor for the early detection of corrosion of ACSRs

Since 2014, Hydro-Québec is using LineCore technology for the early detection of corrosion in ACSRs. This paper features, for the first time, an extensive validation based on measures on in-lab prepared samples and metallographic analysis on field collected samples. The experimental validation protocol is presented which resulted in 21 cuts and thousands of zinc layer thickness measurements. Key finding is the very high variability of zinc layer thicknesses observed on all samples. Correlation between LineCore data and metallographic cuts is established. More specifically, LineCore measurement features a bias toward local minimum values of zinc thickness on the strands, which can be indicative of localized corrosion initiation. By sharing these results, the authors wish to initiate discussion that could help standardize the usage of this novel NDT technology for the assessment of transmission line conductors.

Validation protocol for the evaluation of space-borne lidar particulate back-scattering coefficient bbp

Introduction: Space-borne lidar measurements from sensors such as CALIOP were recently used to retrieve the particulate back-scattering coefficient, bbp, in the upper ocean layers at a global scale and those observations have a strong potential for the future of ocean color with depth-resolved observations thereby complementing the conventional ocean color remote sensed observations as well as overcoming for some of its limitations. It is critical to evaluate and validate the space-borne lidar measurements for ocean applications as CALIOP was not originally designed for ocean applications. Few validation exercises of CALIOP were published and each exercise designed its own validation protocol. We propose here an objective validation protocol that could be applied to any current and future space-borne lidars for ocean applications.Methods: We, first, evaluated published validation protocols for CALIOP bbp product. Two published validation schemes were evaluated in our study, by using in-situ measurements from the BGC-Argo floats. These studies were either limited to day- or nighttime, or by the years used or by the geographical extent. We extended the match-up exercise to day-and nighttime observations and for the period 2010–2017 globally. We studied the impact of the time and distance differences between the in-situ measurements and the CALIOP footprint through a sensitivities study. Twenty combinations of distance (from 9-km to 50-km) and time (from 9 h to 16 days) differences were tested.Results &amp;amp; Discussion: A statistical score was used to objectively selecting the best optimal timedistance windows, leading to the best compromise in term of number of matchups and low errors in the CALIOP product. We propose to use either a 24 h/9 km or 24 h/15 km window for the evaluation of space-borne lidar oceanic products.

Validation of New Quantitative Lung Ultrasound Protocol and Comparison With Lung Ultrasound Score in Patients With COVID-19

Validation of New Quantitative Lung Ultrasound Protocol and Comparison With Lung Ultrasound Score in Patients With COVID-19