Control Metrics Research Articles

Atypia of undetermined significance and ThyroSeq v3-positive call rates as quality control metrics for cytology laboratory performance.

The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) recommends an upper limit of 10% for atypia of undetermined significance (AUS). Recent data suggest that this category might be overused when the rate of cases with molecular positive results is low. As a quality metric, the AUS and positive call rates for this facility's cytology laboratory and each cytopathologist (CP) were calculated. A retrospective analysis of all thyroid cytology cases in a 4.5-year period was performed. Cases were stratified by TBSRTC, and molecular testing results were collected for indeterminate categories. The AUS rate was calculated for each CP and the laboratory. The molecular positive call rate (PCR) was calculated with and without the addition of currently negative to the positive results obtained from the ThyroSeq report. A total of 7535 cases were classified as nondiagnostic, 7.6%; benign, 69%; AUS, 17.5%; follicular neoplasm/suspicious for follicular neoplasm, 1.4%; suspicious for malignancy, 0.7%; and malignant, 3.8%. The AUS rate for each CP ranged from 9.9% to 36.8%. The overall PCR was 24% (range, 13%-35.6% per CP). When including cases with currently negative results, the PCR increased to 35.5% for the cytology laboratory (range, 13%-42.6% per CP). Comparison analysis indicates a combination of overcalling benign cases and, less frequently, undercalling of higher TBSRTC category cases. The AUS rate in the context of PCR is a useful metric to assess cytology laboratory and cytopathologists' performance. Continuous feedback on this metric could help improve the overall quality of reporting thyroid cytology.

BPI24-015: Reporting the False Negative Rate of Sentinel Lymph Node Biopsy for Melanoma SLNB: A Useful Quality Control Metric.

BPI24-015: Reporting the False Negative Rate of Sentinel Lymph Node Biopsy for Melanoma SLNB: A Useful Quality Control Metric.

Matrix Pontryagin principle approach to controllability metrics maximization under sparsity constraints

This study considers optimization problems for time-varying network topologies that maximize the controllability of linear network systems under sparsity constraints. The major theoretical differences from the existing findings on control node scheduling problems is that our method is based on the matrix-valued Pontryagin maximum principle applied to the controllability Lyapunov differential equation. This allows us to handle various controllability metrics that can only be approximated by existing methods. Finally, we perform a numerical evaluation of our proposed method and compare results with those of our previous approximation method.

CITEViz: interactively classify cell populations in CITE-Seq via a flow cytometry-like gating workflow using R-Shiny

BackgroundThe rapid advancement of new genomic sequencing technology has enabled the development of multi-omic single-cell sequencing assays. These assays profile multiple modalities in the same cell and can often yield new insights not revealed with a single modality. For example, Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-Seq) simultaneously profiles the RNA transcriptome and the surface protein expression. The surface protein markers in CITE-Seq can be used to identify cell populations similar to the iterative filtration process in flow cytometry, also called “gating”, and is an essential step for downstream analyses and data interpretation. While several packages allow users to interactively gate cells, they often do not process multi-omic sequencing datasets and may require writing redundant code to specify gate boundaries. To streamline the gating process, we developed CITEViz which allows users to interactively gate cells in Seurat-processed CITE-Seq data. CITEViz can also visualize basic quality control (QC) metrics allowing for a rapid and holistic evaluation of CITE-Seq data.ResultsWe applied CITEViz to a peripheral blood mononuclear cell CITE-Seq dataset and gated for several major blood cell populations (CD14 monocytes, CD4 T cells, CD8 T cells, NK cells, B cells, and platelets) using canonical surface protein markers. The visualization features of CITEViz were used to investigate cellular heterogeneity in CD14 and CD16-expressing monocytes and to detect differential numbers of detected antibodies per patient donor. These results highlight the utility of CITEViz to enable the robust classification of single cell populations.ConclusionsCITEViz is an R-Shiny app that standardizes the gating workflow in CITE-Seq data for efficient classification of cell populations. Its secondary function is to generate basic feature plots and QC figures specific to multi-omic data. The user interface and internal workflow of CITEViz uniquely work together to produce an organized workflow and sensible data structures for easy data retrieval. This package leverages the strengths of biologists and computational scientists to assess and analyze multi-omic single-cell datasets. In conclusion, CITEViz streamlines the flow cytometry gating workflow in CITE-Seq data to help facilitate novel hypothesis generation.

Insight into Metabolomic Profiling of Tinospora cordifolia: Recent Advances and Future Perspectives of Quality Control

Abstract The objective of this study was to offer a review of previous works on Tinospora cordifolia (TC) metabolomics with a highlight on the use of metabolomics in comparative evaluations between varieties and selection of optimum cultivation, collection, and extraction procedures, providing insights into pharmaceutical and food product quality monitoring. Scholarly databases were searched to gather relevant information on TC’s therapeutic usefulness, phytoconstituent studies, metabolomics, and applications. PubChem was used to learn the structures of several of the metabolites. The various medicinal properties of TC were extensively researched. The most essential portions of the plant in Ayurvedic medicines are the stems. Bioactive phytochemicals such as steroidal lactones, alkaloids, diterpenoids, and phenolic compounds are present in the roots and leaves. Metabolomic analysis revealed that, in addition to the season and geographical region of the sample collected, the metabolite profiles of TC also depend on the parts of the plant taken as a sample and also the plant’s stage of growth. The amounts of secondary metabolites differed between morpho/chemotypes within the TC species. Despite the fact that research on TC began several decades ago, the diversity of phytoconstituents was not appreciated because of a lack of reliable techniques for phytochemical fingerprinting. The uncovering of several novel metabolites was aided by advances in chromatography combined with mass spectrometry. To produce a full metabolomic profile, researchers used mutually complementary techniques. Following that, data analysis and searches against spectrum databases allowed for signal annotation and interpretation of metabolites in large quantities without separating them separately. The current review includes a critical assessment of metabolomic data and an overview of the technique’s various applications. It is vital to establish the metrics of quality control of herbal medicines in order to accomplish formulation purity assessments. Such information would assist us in determining the best geolocation for the plants and the best time to harvest them. Metabolomic investigation of TC-based herbal products is recommended for quality standards and the identification of novel bioactive components.

Abstract 4957: DNA quality control metrics in cryopreserved tissue outperform DNA extracted from FFPE tissue

Abstract Personalized cancer care requires molecular characterization of neoplasms. While the research community accepts frozen tissues as the gold standard analyte for molecular assays, the source of tissue for testing of tumor tissue in clinical cancer care comes primarily from formalin-fixed, paraffin-embedded tissue (FFPE). Specific to genomics assays, numerous studies have shown significant discordance in genetic information obtained from FFPE samples and frozen samples. To explain the discordance between FFPE samples and cryopreserved samples, a head-to-head comparison between FFPE and cryopreserved tissues was performed to analyze the DNA yield, DNA purity and DNA quality in terms of DNA length. Additionally, short-read sequencing was performed on matched samples and quality control metrics were compared between the two sample types. Matched human tumors (n = 50) were processed either by formalin fixation and paraffin embedding or placed in cryovials containing cryopreservation medium. These cryovials were cooled slowly to -80°C and stored in liquid nitrogen. DNA was extracted using the same protocol for both tissue types with the exception that tissues embedded in paraffin were first dewaxed followed by a multistep rehydration protocol. Samples were weighed and calibrated for mass. After the column purification and elution, sample concentration and purity were measured. DNA fragment length was measured on a fragment microelectrophoresis analyzer. Graded amounts of tumor tissue were used to determine the lowest starting material needed to extract 200 ng of DNA. The average of all the samples reached the minimal threshold of 200 ng. However,74% of FFPE specimens failed to meet the minimum 40 ng/mg, whereas only 21% were below the threshold in the cryopreserved samples. In the cryopreserved group, the average DNA yield was 222.1 ng/mg, whereas 52.8 ng/mg was obtained from FFPE tissue. For DNA purity in cryopreserved tissues, the 260/280 ratio was 1.76, and in FFPE tissues the mean was 1.78. The DNA Quality Number (DQN) is a measurement of DNA fragment length and the percentage that exceeds the threshold of 300 bp. For FFPE, the DQN was 4.4 compared to a DQN of 9.8 for the cryopreserved samples. Setting a higher threshold of DNA length to 40,000 bp and measuring the area under the curve (AUC), it was observed that cryopreserved samples were 9-fold higher in fragments greater than 40,000 bp. Cryopreserved cancer tissue provides superior quality assurance measurements of DNA over FFFPE. Treatment decisions based on molecular results demand accuracy and validity. The pathology community should support efforts to cryopreserve cancer biospecimens in the clinical setting to provide valid molecular testing results. The automatic pickling of tumor specimens in formalin is no longer an acceptable default. Citation Format: Jared James Barrott, Nikole O'Neal, Jeffrey Okojie, David Booker, Ken Dixon. DNA quality control metrics in cryopreserved tissue outperform DNA extracted from FFPE tissue [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4957.

Abstract 3218: Combination drug screen identifies novel epigenetic therapies to enhance menin inhibitor efficacy in KMT2A rearranged and NPM1 mutant AML

Abstract Background: Acute myeloid leukemia (AML) with KMT2A-rearrangements have a poor prognosis and so there is an urgent need for novel therapies. Menin inhibitors have shown promising anti-leukemic effects in KMT2A-rearranged and NPM1-mutated AML. However, the efficacy of menin inhibitors as single agents may be limited by the development of resistance mutations. Combining menin inhibitors with other epigenetic drugs may present a strategy to enhance their therapeutic potential. In this study, we performed a combination drug screen using an epigenetic drug library in KMT2A-rearranged (MV4;11) and NPM1-mutant (OCI-AML3) AML cell lines to identify synergistic therapies that can be used in conjunction with menin inhibitors. Methods: During assay optimization, MV4;11 and OCI-AML3 cells were treated with the menin inhibitor DSP-5336, and their viability was assessed. Quality control metrics were applied with Z’ values consistently greater than 0.5 for all assay plates and then the cells were subjected to a small molecule compound library screen containing a set of 932 epigenetic drugs. The screening process included a systematic evaluation of each drug's effect on cell viability in combination with the DSP-5336. Results: The combination drug screen demonstrated robust performance in both MV4;11 and OCI-AML3 cell lines, with reliable quality control metrics. Among the epigenetic drugs tested, five compounds were identified as potential hits that synergistically enhanced the efficacy of DSP-5336 across both cell lines.The five identified compounds exhibited enhanced anti-leukemic effects when combined with the menin inhibitor in either one of the cell lines. The targets of these drugs varied, including histone deacetylases, histone acetyltransferases and BRD4 inhibition, suggesting many alternate mechanisms of action involving epigenetic modulation. Remarkably, one of the 5 hits C301-3161, a KAT2A inhibitor, showed limited activity in either cell line alone but increased cell killing with DSP-5336 in both cell lines, highlighting its potential as a specific therapeutic for combining with DSP-5336 in AML patients. Conclusions: Our findings suggest combining menin inhibitors with other epigenetic drugs may improve AML treatment outcomes. The combination drug screen successfully identified four novel compounds that synergistically enhance menin inhibitor efficacy in both KMT2A-rearranged and NPM1-mutant AML cell lines. These compounds hold significant promise as potential therapeutic candidates for further investigation. Future studies should focus on elucidating the underlying mechanisms of action for each hit and evaluating their effects in preclinical animal models. Ultimately, this research may pave the way for the development of innovative combination therapeutic strategies for AML patients with KMT2A-rearragned and NPM1-mutant AML. Citation Format: Tulasigeri M. Totiger, Sana Chaudhry, Skye Montoya, Maurizio Affer, Anya K. Sondhi, Alexandra Chirino, Claude-Henry Volmar, Shaun Brothers, Justin Watts, Justin Taylor. Combination drug screen identifies novel epigenetic therapies to enhance menin inhibitor efficacy in KMT2A rearranged and NPM1 mutant AML [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3218.

Abstract 3100: Interactive analysis of drug testing data for functional precision oncology with Breeze 2.0

Abstract High throughput screening (HTS) is used to screen large numbers of small molecules in cell-based assays to predicting their potential therapeutic response and when applying approved drug libraries using HTS it becomes drug repurposing. The Drug Sensitivity and Resistance Testing (DSRT) platform established at FIMM has been extensively used in testing panels of approved and investigational drugs on cells, both conventional cell lines and primary cell models derived from cancer patient samples. The results help in deepen our understanding of drug efficacy in individual patients and across specific disease to guide future patient stratification. Breeze 2.0 is an open access, web-based platform for interactive analysis of drug screening data in real time. Breeze accepts raw data in a simple tabular format and generates detailed quality control metrics, plots, dose-response curve fits, drug response quantification in form of IC50/EC50/AUC and Drug Sensitivity Scores (DSS). Besides tabular results, Breeze generates interactive, informative, and intuitive visualizations, such as plate heatmaps, scatterplots, barplots, clustered heatmaps, circular plots, for further analysis. Based on manually-curated published datasets available through Breeze 2.0, users can instantly compare their drug response patterns with the existing DSRT profiles from patient samples, as well as cell lines. Importantly, Breeze 2.0 has integrated curated reference DSRT data tested on bone marrow samples from healthy control individuals, which plays a crucial role in understanding cancer-selective drug response by de-prioritizing generally toxic compounds. The end-users can select multiple healthy controls or relevant patient/cell line samples and choose the drugs of interest to visualize the overlaid dose responses, as well as response quantification metrics. Breeze 2.0 is built in R, PHP, MySQL and is freely accessible at https://breeze.fimm.fi/v2 Citation Format: Swapnil Potdar, Filipp Ianevski, Aleksandr Ianevski, Ziaurrehman Tanoli, Krister Wennerberg, Brinton Seashore-Ludlow, Olli Kallioniemi, Päivi Östling, Tero Aittokallio, Jani Saarela. Interactive analysis of drug testing data for functional precision oncology with Breeze 2.0 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3100.

Abstract 5024: Analytical performance of a genome-wide methylome enrichment platform to detect minimal residual disease from plasma-derived cell-free DNA

Abstract Introduction: Plasma-derived cell-free DNA (cfDNA) can be used to identify cancer signals, including minimal residual disease (MRD), in patients who have undergone curative cancer treatments. The cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) methodology is combined with custom algorithms that leverage differentially methylated regions (DMRs) found in cfDNA to distinguish between cancer and non-cancer signals. This novel non-degradative, tissue-agnostic approach was developed to bypass the limitations of bisulfite-sequencing and tissue-informed methods used in other liquid biopsy technologies. Here we present preliminary analytical performance metrics of an algorithm in development for detecting MRD. Methods: In the genome-wide methylome enrichment platform, plasma-derived cfDNA is subjected to standard library preparation, combined with DNA filler, denatured, and immunoprecipitated using an anti-5-mC antibody. Captured DNA is amplified and sequenced. For this study, a candidate algorithm comprised of differentially methylated regions (DMRs) and 12 cancer types was used to quantify cancer-specific methylation. Control samples from 12 non-cancer donors were used to establish a selected 95% true negative rate threshold. This threshold was used to determine assay sensitivity, which was evaluated using contrived cancer samples intended to mimic low-level circulating tumor DNA (ctDNA) representative of MRD. Samples were contrived by titrating fragmented DNA from three immortalized tumor-derived cell-lines into plasma-derived cfDNA in a titration series targeting <1% ctDNA levels. Cell-lines were of non-small cell lung cancer and head and neck squamous cell carcinoma origin; titration series were replicated for a total of 65 tests. Results: All non-cancer and contrived cancer samples met in-process quality control metrics. This included ≥98.5% methylation specificity and ≥80 million unique molecules. Limit of detection calculations at 95% sensitivity (LoD95) were <0.1%. Conclusions: Tissue-agnostic approaches for detecting cancer signals from plasma have significant benefit, especially in settings where tissue is not accessible for evaluation. However, these tests must have highly sensitive methods of cancer signal detection for clinical applications. Our preliminary analytical data demonstrates the use of a blood-based, tissue- agnostic genome-wide methylome enrichment platform utilizing non-degradative methodology combined with specific algorithms and DMRs for MRD quantification and prognostic prediction, using treatment-naïve plasma samples. Future studies in post-treatment and longitudinal samples are ongoing to evaluate the utility of this genome-wide methylome enrichment platform for cancer management. Citation Format: Shu Yi Shen, Iulia Cirlan, Felicia Vincelli, Ben Brown, Jun Min, Justin Burgener, Junjun Zhang, Yulia Newton, Margaret Gruca, Abel Licon, Jing Zhang, Anne-Renee Hartman, Alan Williams, Hestia Mellert, Daniel D. De Carvalho. Analytical performance of a genome-wide methylome enrichment platform to detect minimal residual disease from plasma-derived cell-free DNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5024.

Best practices recommendations for estimating dissipation rates from shear probes

As a part of the Scientific Committee on Oceanographic Research (SCOR) Working Group #160 “Analyzing ocean turbulence observations to quantify mixing” (ATOMIX), we have developed recommendations on best practices for estimating the rate of dissipation of kinetic energy, ε, from measurements of turbulence shear using shear probes. The recommendations provided here are platform-independent and cover the conceivable range of dissipation rates in the ocean, seas, and other natural waters. They are applicable to commonly deployed platforms that include vertical profilers, fixed and moored instruments, towed profilers, submarines, self-propelled ocean gliders, and other autonomous underwater vehicles. The procedure for preparing the shear data for spectral estimation is discussed in detail, as are the quality control metrics that should accompany each estimate of ε. The methods are illustrated using a high-quality ‘benchmark’ dataset, while potential pitfalls are demonstrated with a second dataset containing common faults.

The False-Positive Rate of Synovial Fluid Culture at a Single Clinical Laboratory Using Culture Bottles.

Introduction Synovial fluid (SF) cultures can yield false-positive or negative results when diagnosing periprosthetic joint infection (PJI). False-positives may arise during sample collection or from laboratory contamination. Understanding false-positive SF culture rates is crucial for interpreting PJI laboratory data, yet clinical laboratories rarely report these rates. This study aimed to define the false-positive SF culture rate at a major specialized clinical laboratory. Methods This study retrospectively analyzed prospectively collected data at a single clinical laboratory that receives SF for clinical testing for PJI. A total of 180,317 periprosthetic SF samples from the hip, knee, and shoulder were identified from January 2016 to December 2023, which met the inclusion criteria for this study. Samples were classified by both a modified 2018 International Consensus Meeting (ICM) score and an inflammation score that combined the SF-C-reactive protein, alpha-defensin, SF-white blood cell count, and SF-polymorphonuclear% into one standardized metric. Logistic regression was utilized to evaluate the impact of various collection-based characteristics on culture positivity, including inflammation biomarkers, the source joint, quality control metrics, and days of specimen transport to the laboratory. SF culture false-positivity was calculated based on the ICM category of "not-infected" or low inflammation score. Results Overall, 13.3% (23,974/180,317) of the samples were associated with a positive culture result: 12.5% for knee samples, 20.3% for hip samples, and 14.7% for shoulder samples. The false-positive SF culture rate among 131,949 samples classified as "not-infected" by the modified 2018 ICM definition was 0.47% (95%CI: 0.43 to 0.51%). Stratification by joint revealed a false-positive rate of 0.34% (95%CI: 0.31 to 0.38%) for knee samples, 1.24% (95%CI: 1.05 to 1.45%) for hip samples, and 3.02% (95%CI: 2.40 to 3.80%) for shoulder samples, with p < 0.0001 for all comparisons. The false-positive SF culture rate among 90,156 samples, representing half of all samples with the lowest standardized inflammation scores, was 0.47% (95%CI: 0.43 to 0.52%). Stratification by joint revealed a false-positive rate of 0.33% (95%CI: 0.29 to 0.37%) for knee samples, 1.45% (95%CI: 1.19 to 1.77%) for hip samples, and 3.09% (95%CI: 2.41 to 3.95%) for shoulder samples, with p<0.0001 for all comparisons. Multivariate logistic regression demonstrated the joint source (hip, shoulder) and poor sample quality as collection-based factors associated with a false-positive culture. Evaluation of a cohort of samples selected to minimize collection-based causes of false-positive culture demonstrated a false-positive rate of 0.30%, representing the ceiling limit for laboratory-based SF culture false-positivity. Conclusions This study utilizes two methods to estimate the false-positive SF culture rate at a single specialized clinical laboratory, demonstrating an overall false-positive rate of approximately 0.5%. Stratification of samples by source joint demonstrated that periprosthetic SF from the shoulder and hip have a substantially higher false-positive culture rate than that of the knee. The lowest false-positive SF culture rate (0.30%) was observed among samples from the knee-passing quality control. Culture positivity due to contamination at this specific laboratory is less than 0.30% because all specimens undergo identical processing.

Reuse of Orthopaedic Equipment: Barriers and Opportunities.

» Reuse of orthopaedic equipment is one of many potential ways to minimize the negative impact of used equipment on the environment, rising healthcare costs and disparities in access to surgical care.» Barriers to widespread adoption of reuse include concerns for patient safety, exposure to unknown liability risks, negative public perceptions, and logistical barriers such as limited availability of infrastructure and quality control metrics.» Some low- and middle-income countries have existing models of equipment reuse that can be adapted through reverse innovation to high-income countries such as the United States.» Further research should be conducted to examine the safety and efficacy of reusing various orthopaedic equipment, so that standardized guidelines for reuse can be established.

Advancements in Individual Tree Detection and Forest Structural Attributes Estimation From LiDAR Data: MSITD and SAFER Approaches

AbstractCurrently, the information on the structural attributes of forests, such as the diameter at breast height (DBH) and the aboveground biomass (AGB), is being used widely in various disciplines. In this study, we first proposed a novel tree detection algorithm called multi‐scale individual tree detection (MSITD) algorithm, which combines the strengths of raster‐based and point‐based approaches in order to detect individual trees from LiDAR data accurately. After tree detection, the DBH and AGB attributes were estimated using the ground control data and metrics extracted from LiDAR data, adopting the safe semi‐supervised regression (SAFER) algorithm specifically designed for addressing regression problems with limited sample data. The performances of these algorithms were evaluated within a 10‐fold nested cross‐validation approach, utilizing the LiDAR data available in the NEWFOR project. The evaluation of the obtained results revealed that both the MSITD algorithm and the SAFER algorithm demonstrate substantial superiority compared to the benchmark algorithms in tree detection, especially for the understory trees, and forest structural attributes estimation, respectively. On average, the MSITD algorithm exhibited a 13% better performance in terms of extraction rate and an 11% better performance in terms of matching rate compared to the benchmark individual tree detection algorithms. For forest structural attributes estimation, the SAFER algorithm provided superior predictions compared to the benchmark ML algorithms, with the average RMSE of 3.38 cm, MAE of 2.84 cm, and R2 of 0.59 for DBH and the average RMSE of 75.79 kg, MAE of 70.02 kg, and R2 of 0.56 for AGB.

Performance management in the Australian higher education system – A historically informed critique

This article aims to provide a historical perspective of neoliberalism and new public management practices in the Australian higher education system from the early 1980s to contemporary times. Drawing on historical and contemporary data sets and research articles, it evaluates historical changes in control systems and metrics applied to university teaching and research. From an audit culture framework, it examines the emerging rationales driving financially focused university governance. Organisational and individual audits of performance have become standard practice, couched in the conventional language of transparency, performance and accountability. Accounting-based performance measurement, control and audit are found to dominate university operations, fostering mass delivery of education, research outputs and knowledge commercialisation. Neoliberal performance management is shown to have dramatically altered accounting models and changed internal power relations, transforming university identities and roles into a commercialised corporate model pursuing a self-interested financial bottom line aided by a private sector performance control orientation.

Microarray-Based DNA Methylation Profiling: Validation Considerations for Clinical Testing

Microarray-based methylation profiling has emerged as a valuable tool for refining diagnoses and revealing novel tumor subtypes, particularly in central nervous system tumors. Despite the increasing adoption of this technique in clinical genomic laboratories, no technical standards have been published in establishing minimum criteria for test validation. A working group with experience and expertise in DNA-based methylation profiling tests on CNS tumors collaborated to develop practical discussion points and focus on important considerations for validating this test in clinical laboratory settings. We summarize our experiences in validating this methodology in a clinical setting. Specifically, we highlight the advantages and challenges associated with utilizing an in-house classifier compared to a third-party classifier. Additionally, we share our experiences in demonstrating the assay's sensitivity and specificity, establishing minimum sample criteria, and implementing quality control metrics. As methylation profiling for tumor classification expands to other tumor types and continues to evolve for various other applications, the critical considerations described here are expected to serve as a guidance for future efforts in establishing professional guidelines for this assay.

Exploring genetic counselors' experiences with non-paternity in clinical settings.

Non-paternity (NP) is a challenging dilemma faced by genetics providers and there is little consensus on whether this finding should be disclosed. Discussions in the literature are highly theoretical, with limited research regarding how disclosure decisions are enacted in practice. We explored genetic counselors' (GCs) clinical experiences with NP to understand if, how, and why this finding is communicated. Our semi-structured interviews with genetic counselors in the United States and Canada were analyzed using reflexive thematic analysis to analyze data inductively, describe themes, and present a meaningful interpretation of the data. Eighteen participants who responded to list-serv messages were interviewed. Our framework describes five salient themes: (1) GC-lab relationship: the GCs awareness of laboratory processes such as quality control metrics that can uncover NP findings and the way in which a finding of NP was disclosed by the laboratory had an impact on disclosure decisions. This triggered a decision-making trajectory that involved (2) consultation, (3) ethical reasoning, and (4) practical constraints. GCs frequently consulted other professionals during decision-making. These conversations impacted disclosure decisions with some consultations carrying greater weight than others. GCs weighed moral concepts of patient autonomy, medical relevance, and preventing harm to rationalize decisions. Access to patients and documentation requirements often dictated how disclosure occurred. Finally, once a decision had been made and enacted, GCs used the experience to reconsider their approach to (5) consenting in future cases, with some GCs altering their pre-test counseling to always include a discussion of NP. Although NP scenarios are frequently unique in context, our findings demonstrate several common decision-making factors GCs harness to navigate the identification of NP through clinical genetic testing.

An advanced exploration of functionalities as the underlying principles of construction control metrics

PurposeIn academics and industry, significant efforts have been made to lead planners and control teams in evaluating project performance and control. In this context, numerous control metrics have been devised and put into practice, often with little emphasis on analyzing their underlying concepts. To cover this gap, this research aims to identify and analyze a holistic list of control metrics and their functionalities in the construction industry.Design/methodology/approachA multi-step analytical approach was conducted to achieve the study’s objectives. First, a holistic list of control metrics and their functionalities in the construction industry was identified. Second, a quantitative analysis based on social network analysis (SNA) was implemented to discover the most important functionalities.FindingsThe results revealed that the most important control metrics' functionalities (CMF) could differ depending on the type of metrics (lagging and leading) and levels of control. However, in general, the most significant functionalities include managing project progress and performance, evaluating the look-ahead level’s performance, measuring the reliability and stability of workflow, measuring the make-ready process, constraint management and measuring the quality of construction flow.Originality/valueThis research will assist the project team in getting a comprehensive sensemaking of planning and control systems and their functionalities to plan and control different dynamic aspects of the project.

The Index of Intrusion Control (IIC): Capturing individual variability in intentional intrusion control in the laboratory

Intrusive memories can be downregulated using intentional memory control, as measured via the Think/No-Think paradigm. In this task, participants retrieve or suppress memories in response to an associated reminder cue. After each suppression trial, participants rate whether the association intruded into awareness. Previous research has found that repeatedly exerting intentional control over memory intrusions reduces their frequency. This decrease is often summarised with a linear index, which may miss more complex patterns characterising the temporal dynamics of intrusion control. The goal of this paper is to propose a novel metric of intrusion control that captures those dynamic changes over time as a single index. Results from a mega-analysis of published datasets revealed that the change in intrusion frequencies across time is not purely linear, but also includes non-linear dynamics that seem best captured by a log function of the number of suppression attempts. To capture those linear and non-linear dynamics, we propose the Index of Intrusion Control (IIC), which relies on the integral of intrusion changes across suppression attempts. Simulations revealed that the IIC best captured the linear and non-linear dynamics of intrusion suppression when compared with other linear or non-linear indexes of control, such as the regression slope or Spearman correlation, respectively. Our findings demonstrate how the IIC may therefore act as a more reliable metric to capture individual differences in intrusion control, and examine the role of non-linear dynamics characterizing the conscious access to unwanted memories.

Short- and Long-Term Effects on Glucose Control of Nonadherence to Insulin Therapy in People With Type 2 Diabetes An In Silico Study.

Strict adherence to multiple daily insulin (MDI) therapy is a cornerstone for the achievement of good glucose control in people with advanced type 2 diabetes (T2D). Here, we aim to in silico assess glucose control in T2D subjects with poor adherence to MDI therapy. We tuned the Padova T2D Simulator, originally describing early-stage T2D physiology, around advanced T2D people. One hundred in silico advanced T2D subjects were generated and equipped with optimal MDI therapy: specifically, basal and bolus insulin amounts and injection times were individualized for each subject by applying titration algorithms that iteratively update insulin dose based on glucose deviation from its target. Then, the effect of nonadhering to MDI therapy was assessed using standard glucose control metrics calculated in two 6-month 3-meal/day in silico scenarios: in Scenario 1, subjects received the optimal basal and prandial insulin bolus at each meal; in Scenario 2, subjects received optimal basal insulin and randomly delayed or skipped the prandial insulin bolus in 3 lunches during working days and 1 dinner during weekends. A statistically significant degradation was found in all glucose control outcome metrics in Scenario 2 versus Scenario 1: e.g., percent time above 180 mg/dL increased by 22.2% and glucose management index by 0.2%. Impaired adherence to MDI therapy in T2D leads to glucose control deteriorations in both short and long terms. Interestingly, short-term hyperglycemia seems being contrasted by residual endogenous insulin secretion, which statistically increased by 3-fold after delayed/skipped insulin boluses compared with optimal ones.

Optical Genome Mapping for Chromosomal Aberrations Detection-False-Negative Results and Contributing Factors.

Optical genome mapping (OGM) has been known as an all-in-one technology for chromosomal aberration detection. However, there are also aberrations beyond the detection range of OGM. This study aimed to report the aberrations missed by OGM and analyze the contributing factors. OGM was performed by taking both GRCh37 and GRCh38 as reference genomes. The OGM results were analyzed in blinded fashion and compared to standard assays. Quality control (QC) metrics, sample types, reference genome, effective coverage and classes and locations of aberrations were then analyzed. In total, 154 clinically reported variations from 123 samples were investigated. OGM failed to detect 10 (6.5%, 10/154) aberrations with GRCh37 assembly, including five copy number variations (CNVs), two submicroscopic balanced translocations, two pericentric inversion and one isochromosome (mosaicism). All the samples passed pre-analytical and analytical QC. With GRCh38 assembly, the false-negative rate of OGM fell to 4.5% (7/154). The breakpoints of the CNVs, balanced translocations and inversions undetected by OGM were located in segmental duplication (SD) regions or regions with no DLE-1 label. In conclusion, besides variations with centromeric breakpoints, structural variations (SVs) with breakpoints located in large repetitive sequences may also be missed by OGM. GRCh38 is recommended as the reference genome when OGM is performed. Our results highlight the necessity of fully understanding the detection range and limitation of OGM in clinical practice.