Control Metrics Research Articles

The Hong Kong genome project: building genome sequencing capacity and capability for advancing genomic science in Hong Kong

Aim: The Hong Kong Genome Project (HKGP) is the first large-scale genome sequencing (GS) project in the Hong Kong Special Administrative Region. The Hong Kong Genome Institute (HKGI) is entrusted with the task of implementing the HKGP. With the aim to sequence 45,000-50,000 genomes in five years, it is the project’s goal to provide participants with more precise diagnosis and personalised treatment, and to drive the application and integration of genomic medicine into routine clinical care. Methods: The HKGI Laboratory’s hardware and software components were customised to tailor to the needs of the project. Sample handling and storage protocol, DNA extraction, and PCR-free GS workflow were developed and optimised. Quality control indicators and metrics for assessing the quality of samples, sequencing libraries and sequencing data were established. Results: The Laboratory is designed to facilitate a unidirectional GS workflow to minimise the risk of contamination. The Sample Manager system handles laboratory data generated from the HKGP samples and biobank. The Laboratory handles and analyses approximately 350-500 samples per week, the majority of which are whole blood. During the first 24 months since the launch of the HKGP, 12,937 participants and their family members (6,680 genomes) have been recruited and sequenced. The sequencing capacity of the Laboratory has been further enhanced to include the latest technologies, such as long-read sequencing and multi-omics in order to meet the target of the HKGP. Conclusion: HKGI Laboratory established a robust GS workflow for the HKGP. The clinical utility of GS will bring precision medicine into routine clinical practice.

Clinical Features, Cardiovascular Risk Profile, and Therapeutic Trajectories of Patients with Type 2 Diabetes Candidate for Oral Semaglutide Therapy in the Italian Specialist Care.

This study aimed to address therapeutic inertia in the management of type 2 diabetes (T2D) by investigating the potential of early treatment with oral semaglutide. A cross-sectional survey was conducted between October 2021 and April 2022 among specialists treating individuals with T2D. A scientific committee designed a data collection form covering demographics, cardiovascular risk, glucose control metrics, ongoing therapies, and physician judgments on treatment appropriateness. Participants completed anonymous patient questionnaires reflecting routine clinical encounters. The preferred therapeutic regimen for each patient was also identified. The analysis was conducted on 4449 patients initiating oral semaglutide. The population had a relatively short disease duration (42% < 5years), and a minority (15.6%) had a history of cardiovascular events. Importantly, oral semaglutide was started in subjects with various disease durations and background therapies. Notably, its initiation was accompanied by de-prescription of sulfonylureas, pioglitazone, DPP-4 inhibitors, and insulin. Choice of oral semaglutide was influenced by patient profiles and ongoing glucose-lowering regimens. Factors such as younger age, higher HbA1c, and ongoing SGLT-2 inhibitor therapy drove the choice of oral semaglutide with the aim of improving glycemic control. Projected glycemic effectiveness analysis revealed that oral semaglutide could potentially lead HbA1c to target in > 60% of patients, and more often than sitagliptin or empagliflozin. The study supports the potential of early implementation of oral semaglutide as a strategy to overcome therapeutic inertia and enhance T2D management.

Interrelated effects of age and parenthood on whole-brain controllability: protective effects of parenthood in mothers.

Controllability is a measure of the brain's ability to orchestrate neural activity which can be quantified in terms of properties of the brain's network connectivity. Evidence from the literature suggests that aging can exert a general effect on whole-brain controllability. Mounting evidence, on the other hand, suggests that parenthood and motherhood in particular lead to long-lasting changes in brain architecture that effectively slow down brain aging. We hypothesize that parenthood might preserve brain controllability properties from aging. In a sample of 814 healthy individuals (aged 33.9 ± 12.7 years, 522 females), we estimate whole-brain controllability and compare the aging effects in subjects with vs. those without children. We use diffusion tensor imaging (DTI) to estimate the brain structural connectome. The level of brain control is then calculated from the connectomic properties of the brain structure. Specifically, we measure the network control over many low-energy state transitions (average controllability) and the network control over difficult-to-reach states (modal controllability). In nulliparous females, whole-brain average controllability increases, and modal controllability decreases with age, a trend that we do not observe in parous females. Statistical comparison of the controllability metrics shows that modal controllability is higher and average controllability is lower in parous females compared to nulliparous females. In men, we observed the same trend, but the difference between nulliparous and parous males do not reach statistical significance. Our results provide strong evidence that parenthood contradicts aging effects on brain controllability and the effect is stronger in mothers.

A multifactorial evaluation of objective performance indicators and video analysis in the context of case complexity and clinical outcomes in robotic-assisted cholecystectomy.

The increased digitization in robotic surgical procedures today enables surgeons to quantify their movements through data captured directly from the robotic system. These calculations, called objective performance indicators (OPIs), offer unprecedented detail into surgical performance. In this study, we link case- and surgical step-specific OPIs to case complexity, surgical experience and console utilization, and post-operative clinical complications across 87 robotic cholecystectomy (RC) cases. Videos of RCs performed by a principal surgeon with and without fellows were segmented into eight surgical steps and linked to patients' clinical data. Data for OPI calculations were extracted from an Intuitive Data Recorder and the da Vinci ® robotic system. RC cases were each assigned a Nassar and Parkland Grading score and categorized as standard or complex. OPIs were compared across complexity groups, console attributions, and post-surgical complication severities to determine objective relationships across variables. Across cases, differences in camera control and head positioning metrics of the principal surgeon were observed when comparing standard and complex cases. Further, OPI differences across the principal surgeon and the fellow(s) were observed in standard cases and include differences in arm swapping, camera control, and clutching behaviors. Monopolar coagulation energy usage differences were also observed. Select surgical step duration differences were observed across complexities and console attributions, and additional surgical task analyses determine the adhesion removal and liver bed hemostasis steps to be the most impactful steps for case complexity and post-surgical complications, respectively. This is the first study to establish the association between OPIs, case complexities, and clinical complications in RC. We identified OPI differences in intra-operative behaviors and post-surgical complications dependent on surgeon expertise and case complexity, opening the door for more standardized assessments of teaching cases, surgical behaviors and case complexities.

Testing the effect of high-definition transcranial direct current stimulation of the insular cortex to modulate decision-making and executive control.

Previous neuroimaging evidence highlighted the role of the insular and dorsal anterior cingulate cortex (dACC) in conflict monitoring and decision-making, thus supporting the translational implications of targeting these regions in neuro-stimulation treatments for clinical purposes. Recent advancements of targeting and modeling procedures for high-definition tDCS (HD-tDCS) provided methodological support for the stimulation of otherwise challenging targets, and a previous study confirmed that cathodal HD-tDCS of the dACC modulates executive control and decision-making metrics in healthy individuals. On the other hand, evidence on the effect of stimulating the insula is still needed. We used a modeling/targeting procedure to investigate the effect of stimulating the posterior insula on Flanker and gambling tasks assessing, respectively, executive control and both loss and risk aversion in decision-making. HD-tDCS was applied through 6 small electrodes delivering anodal, cathodal or sham stimulation for 20 min in a within-subject offline design with three separate sessions. Bayesian statistical analyses on Flanker conflict effect, as well as loss and risk aversion, provided moderate evidence for the null model (i.e., absence of HD-tDCS modulation). These findings suggest that further research on the effect of HD-tDCS on different regions is required to define reliable targets for clinical applications. While modeling and targeting procedures for neuromodulation in clinical research could lead to innovative protocols for stand-alone treatment, or possibly in combination with cognitive training, assessing the effectiveness of insula stimulation might require sensitive metrics other than those investigated here.

A filter for tracking non-cooperative low-thrust satellites using surveillance radar data

Numerous satellites with electric propulsion perform long duration maneuvers during their orbit acquisition phase. This poses a challenge to space object cataloging activities if no information regarding the maneuver plan is known a priori. Various works have been devoted to maneuver detection and tracking of space objects using radar and optical surveillance data, but the special case of unknown dynamics, analogous to a maneuver spanning several days or months, has received less attention. Herein, we propose a methodology to maintain custody of uncooperative low-thrust spacecraft under the special characteristics of surveillance radar observations. Based on the stochastic hybrid systems framework, a multi-hypothesis algorithm leverages information derived from measurements and the dynamical characteristics of the object. The latter is accomplished in an efficient manner by means of a low-thrust control metric that relies on the Thrust Fourier Coefficients approximation. To improve filter robustness, the maneuver transition density is assumed to be uniform within the set of reachable states, whose outer bound is approximated via the proposed control measure. The algorithm is applied to the orbit acquisition phase of a LEO satellite using synthetic data from a simulated surveillance radar network, and its shown to be capable of maintaining custody throughout the entire three-month transfer.

Development of dynamic shading control for daylight measures in green buildings towards overall energy efficiency of lighting and air-conditioning systems

The introduction of daylight can improve buildings’ energy efficiency and bring benefit to occupant satisfaction. However, the introduction of daylight may accompany with excessive heat. Properly counterbalancing the energy consumption of air conditioning and lighting systems owing to the entry of daylight is a critical control target of dynamic shading adjustment in cooling season. Most dynamic shading control strategies in use only consider one single system. Additionally, for advanced control mode like performance-based control, the predictive model usually only examines the instantaneous effect of energy performance to determine the shading adjustment state, unable to quantify the overall influence of shading adjustment state on building energy consumption. In order to address this issue, special consideration is given to calculating the cumulative contribution of heat gains to cooling load in this study. An overall energy-efficient shading control metric is proposed and used as basis to develop optimized dynamic shading control strategy. An application example demonstrates that the SGR-Optimal control strategy can further save energy by 21.8% ~ 38.8% when compared to the Rule-based control strategy, thus allowing a better exploration of the energy efficiency potential of daylight measure.

Glycemic control metrics in a cohort of hospitalized patients with type 1 diabetes using hybrid closed-loop and advanced hybrid closed-loop systems

AimsTo describe Hybrid closed-loop (HCL) and advanced hybrid closed-loop (AHCL) performance in the hospital setting based on the continuous glucose monitoring (CGM) metrics description. MethodsThis was an observational study from a cohort of patients with T1D using HCL/AHCL with history of hospitalization. CGM metrics were analyzed during the hospital stay. CGM metrics sub-analysis of the population with active Automated Mode (AM) and SmartGuard (SG) during hospitalization and/or surgical procedure was performed. ResultsTwenty-four patients were included (50 % women; mean age, 49 years [inter-quartile range (IQR), 39–62 years]). During hospitalization 70.8 % patients achieved %Time in Range (TIR) between 70 and 180 mg/dL ≥ 70 %. The overall %TIR was 75.5 % (IQR, 67.3–81.5 %), % time below range (TBR) < 70 mg/dL was 2.1 % (IQR, 0.7–5.4 %) and %TBR < 54 mg/dL was 0 % (IQR, 0–5.4 %). Users of the AHCL with active SG achieved a non-significant higher %TIR during hospitalization (79 % [73.8.88 %] vs. 76 % [72.81 %], p = 0.312) and had a shorter stay (3[IQR, 2.4] vs. 6 days[IQR, 5.7], p = 0.045) compared to the users of the HCL with AM active. No device-related serious adverse events occurred for users of either system. ConclusionsHCL/AHCL systems with active AM/SG in patients with T1D in the hospital environment leads to %TIR > 70 % in ranges of 70–180 mg/dL in patients without increasing hypoglycemia.

Abstract 138: Treatment Initiation During The First Month Following Hypertension Diagnosis Improves Blood Pressure Control Up To 30 Months

Background: Adults with hypertension (HTN) have fewer cardiovascular events if controlled within the first 6 months after diagnosis, during which time they are excluded from many HTN control metrics. We compared BP control rates (BP &lt;140/90) from 6 to 42 months in adults with HTN who did or did not have treatment initiated during the first month following diagnosis, irrespective of subsequent treatment initiation or intensification (TI). Methods: A patient cohort from 5 diverse healthcare organizations, engaged in a quality improvement program, was identified with previously undiagnosed and untreated HTN. TI and BP control were assessed by measuring the period prevalence of visit BP control and TI on uncontrolled visits, then compared with the time since diagnosis (TSD) up to 42 months. Groups were stratified by treatment initiation status during the first month. Results: A prospective cohort of 14,328 newly diagnosed and untreated persons with HTN was identified, mean age 56.2±14.7 years. Patients with TI during the first month had higher rates of BP control at 6 (56.2% vs 46.2%, p&lt;0.001) through 30 months (65.9% vs 61.4%, p&lt;0.001) than those initially untreated. Patients initiated during the first month were less likely to receive additional intensifications (OR 0.68, 95% CI [0.63-0.74]). Conclusion: TI in the first month after diagnosis results in better BP control at 6 months, which has prognostic importance and coincides with the time when these individuals impact standard HTN control metrics. Of concern, TI during the first month after diagnosis was insufficient to achieve control rates ≥70% and lowered the probability of subsequent TI.

Glucose control during Ramadan in a pediatric cohort with type 1 diabetes on MiniMed standard and advanced hybrid closed‑loop systems: A pilot study

BackgroundHybrid closed-loop (HCL) systems have revolutionized the treatment of diabetes, enabling doctors to cope with challenging conditions that were previously almost impossible to manage or were very risky and difficult. AimsTo assess the efficacy and safety of a hybrid closed-loop (HCL) system during Ramadan fasting in a pediatric cohort with type 1 diabetes (T1D). Research design and methodsGlucose control outcomes in older children and adolescents aged 8–16 years with automated insulin delivery for T1D were analyzed during Ramadan and 1 month before Ramadan. Participants on MiniMed standard HCL (670G) or advanced HCL (780G) systems of Medtronic were categorized as fasting or nonfasting. ResultsThe average age of the 19 participants (8 and 11 were on standard and advanced HCL systems, respectively) was 11.35 ± 2 years. Eleven patients fasted during Ramadan. Pump setup and sensor statistics were the same during Ramadan and the month before; no significant difference was found between the two groups in terms of insulin and glucose control metrics, with practically the same coefficient of variation, time in range (TIR) and time spent in hypoglycemia, maintained within the international recommended targets. Total daily doses were paradoxically higher in patients who fasted during Ramadan (p = 0.01), without repercussions on glucose control metrics. ConclusionsStandard and advanced HCL use during Ramadan were safe and were associated with a maintained optimum TIR (>70 %) and no significant hypoglycemia in adolescents and older children with T1D.

Differences in Use of Clinical Decision Support Tools and Implementation of Aspirin, Blood Pressure Control, Cholesterol Management, and Smoking Cessation Quality Metrics in Small Practices by Race and Sex

Practice-level evidence is needed to clarify the value of population-based clinical decision support (CDS) tools in reducing racial and sex disparities in cardiovascular care. To evaluate the association between CDS tools and racial and sex disparities in the aspirin use, blood pressure control, cholesterol management, and smoking cessation (ABCS) care quality metrics among smaller primary care practices. This cross-sectional study used practice-level data from the Agency for Healthcare Research and Quality-funded EvidenceNOW initiative. The national initiative from May 1, 2015, to April 30, 2021, spanned 12 US states and focused on improving cardiovascular preventive care by providing quality improvement support to smaller primary care practices. A total of 576 primary care practices in EvidenceNOW submitted both survey data and electronic health record (EHR)-derived ABCS data stratified by race and sex. Practice-level estimates of disparities between Black and White patients and between male and female patients were calculated as the difference in proportions of eligible patients within each practice meeting ABCS care quality metrics. The association between CDS tools (EHR prompts, standing orders, and clinical registries) and disparities was evaluated by multiply imputed multivariable models for each CDS tool, adjusted for practice rurality, ownership, and size. Across the 576 practices included in the analysis, 219 (38.0%) had patient panels that were more than half White and 327 (56.8%) had panels that were more than half women. The proportion of White compared with Black patients meeting metrics for blood pressure (difference, 5.16% [95% CI, 4.29%-6.02%]; P < .001) and cholesterol management (difference, 1.49% [95% CI, 0.04%-2.93%] P = .04) was higher; the proportion of men meeting metrics for aspirin use (difference, 4.36% [95% CI, 3.34%-5.38%]; P < .001) and cholesterol management (difference, 3.88% [95% CI, 3.14%-4.63%]; P < .001) was higher compared with women. Conversely, the proportion of women meeting practice blood pressure control (difference, -1.80% [95% CI, -2.32% to -1.28%]; P < .001) and smoking cessation counseling (difference, -1.67% [95% CI, -2.38% to -0.95%]; P < .001) metrics was higher compared with men. Use of CDS tools was not associated with differences in race or sex disparities except for the smoking metric. Practices using CDS tools showed a higher proportion of men meeting the smoking counseling metric than women (coefficient, 3.82 [95% CI, 0.95-6.68]; P = .009). The findings of this cross-sectional study suggest that practices using CDS tools had small disparities that were not statistically significant, but CDS tools were not associated with reductions in disparities. More research is needed on effective practice-level interventions to mitigate disparities.

Masked transformer through knowledge distillation for unsupervised text style transfer

Abstract Text style transfer (TST) aims at automatically changing a text’s stylistic features, such as formality, sentiment, authorial style, humor, and complexity, while still trying to preserve its content. Although the scientific community has investigated TST since the 1980s, it has recently regained attention by adopting deep unsupervised strategies to address the challenge of training without parallel data. In this manuscript, we investigate how relying on sequence-to-sequence pretraining models affects the performance of TST when the pretraining step leverages pairs of paraphrase data. Furthermore, we propose a new technique to enhance the sequence-to-sequence model by distilling knowledge from masked language models. We evaluate our proposals on three unsupervised style transfer tasks with widely used benchmarks: author imitation, formality transfer, and polarity swap. The evaluation relies on quantitative and qualitative analyses and comparisons with the results of state-of-the-art models. For the author imitation and the formality transfer task, we show that using the proposed techniques improves all measured metrics and leads to state-of-the-art (SOTA) results in content preservation and an overall score in the author imitation domain. In the formality transfer domain, we paired with the SOTA method in the style control metric. Regarding the polarity swap domain, we show that the knowledge distillation component improves all measured metrics. The paraphrase pretraining increases content preservation at the expense of harming style control. Based on the results reached in these domains, we also discuss in the manuscript if the tasks we address have the same nature and should be equally treated as TST tasks.

Monitoring Both Extended and Tryptic Forms of Stable Isotope-Labeled Standard Peptides Provides an Internal Quality Control of Proteolytic Digestion in Targeted Mass Spectrometry-Based Assays

Targeted mass spectrometry (MS)-based proteomic assays, such as multiplexed multiple reaction monitoring (MRM)-MS assays, enable sensitive and specific quantification of proteotypic peptides as stoichiometric surrogates for proteins. Efforts are underway to expand the use of MRM-MS assays in clinical environments, which requires a reliable strategy to monitor proteolytic digestion efficiency within individual samples. Towards this goal, extended stable isotope-labeled standard (SIS) peptides (hE), which incorporate native proteolytic cleavage sites, can be spiked into protein lysates prior to proteolytic (trypsin) digestion, and release of the tryptic SIS peptide (hT) can be monitored. However, hT measurements alone cannot monitor the extent of digestion and may be confounded by matrix effects specific to individual patient samples; therefore, they are not sufficient to monitor sample-to-sample digestion variability. We hypothesized that measuring undigested hE, along with its paired hT, would improve detection of digestion issues compared to only measuring hT. We tested the ratio of the SIS pair measurements, or hE/hT, as a quality control (QC) metric of trypsin digestion for two MRM assays: a direct-MRM (398 targets) and an immuno-MRM (126 targets requiring immunoaffinity peptide enrichment) assay, with extended SIS peptides observable for 54% (216) and 62% (78) of the targets, respectively. We evaluated the quantitative bias for each target in a series of experiments that adversely affected proteolytic digestion (e.g., variable digestion times, pH, and temperature). We identified a subset of SIS pairs (36 for the direct-MRM, 7 for the immuno-MRM assay) for which the hE/hT ratio reliably detected inefficient digestion that resulted in decreased assay sensitivity and unreliable endogenous quantification. The hE/hT ratio was more responsive to a decrease in digestion efficiency than a metric based on hT measurements alone. For clinical-grade MRM-MS assays, this study describes a ready-to-use QC panel and also provides a road map for designing custom QC panels.

Evaluating cPILOT Data toward Quality Control Implementation.

Multiplexing enables the monitoring of hundreds to thousands of proteins in quantitative proteomics analyses and increases sample throughput. In most mass-spectrometry-based proteomics workflows, multiplexing is achieved by labeling biological samples with heavy isotopes via precursor isotopic labeling or isobaric tagging. Enhanced multiplexing strategies, such as combined precursor isotopic labeling and isobaric tagging (cPILOT), combine multiple technologies to afford an even higher sample throughput. Critical to enhanced multiplexing analyses is ensuring that analytical performance is optimal and that missingness of sample channels is minimized. Automation of sample preparation steps and use of quality control (QC) metrics can be incorporated into multiplexing analyses and reduce the likelihood of missing information, thus maximizing the amount of usable quantitative data. Here, we implemented QC metrics previously developed in our laboratory to evaluate a 36-plex cPILOT experiment that encompassed 144 mouse samples of various tissue types, time points, genotypes, and biological replicates. The evaluation focuses on the use of a sample pool generated from all samples in the experiment to monitor the daily instrument performance and to provide a means for data normalization across sample batches. Our results show that tracking QC metrics enabled the quantification of ∼7000 proteins in each sample batch, of which ∼70% had minimal missing values across up to 36 sample channels. Implementation of QC metrics for future cPILOT studies as well as other enhanced multiplexing strategies will help yield high-quality data sets.

Nf-core/clipseq - a robust Nextflow pipeline for comprehensive CLIP data analysis.

Crosslinking and immunoprecipitation (CLIP) technologies have become a central component of the molecular biologists' toolkit to study protein-RNA interactions and thus to uncover core principles of RNA biology. There has been a proliferation of CLIP-based experimental protocols, as well as computational tools, especially for peak-calling. Consequently, there is an urgent need for a well-documented bioinformatic pipeline that enshrines the principles of robustness, reproducibility, scalability, portability and flexibility while embracing the diversity of experimental and computational CLIP tools. To address this, we present nf-core/clipseq - a robust Nextflow pipeline for quality control and analysis of CLIP sequencing data. It is part of the international nf-core community effort to develop and curate a best-practice, gold-standard set of pipelines for data analysis. The standards enabled by Nextflow and nf-core, including workflow management, version control, continuous integration and containerisation ensure that these key needs are met. Furthermore, multiple tools are implemented ( e.g. for peak-calling), alongside visualisation of quality control metrics to empower the user to make their own informed decisions based on their data. nf-core/clipseq remains under active development, with plans to incorporate newly released tools to ensure that pipeline remains up-to-date and relevant for the community. Engagement with users and developers is encouraged through the nf-core GitHub repository and Slack channel to promote collaboration. It is available at https://nf-co.re/clipseq.

A novel 6-day cycle surgical pathology rotation improves resident satisfaction and maintains Accreditation Council for Graduate Medical Education (ACGME) milestone performance

Surgical pathology residency training in the United States lags behind other specialties in quality control and graduated responsibility to train independent pathologists capable of seamlessly entering practice after training. We observed that our traditional 3-day-cycle surgical pathology cycle (day 1–grossing; day 2 –biopsies/frozens/preview; day 3 – sign-out) consistently and negatively impacted resident education by reducing preview time, case follow-up, immunohistochemical stain (IHC) interpretation, and molecular study integration. We aimed to create a modern surgical pathology rotation that improved performance and outcomes. We innovated our rotation to enhance resident education and ensure graduated responsibility. A novel 6-day cycle was created composed of 2 grossing days, 1 frozens/biopsies/preview days, 2 dedicated sign-out days, and 1 frozens/biopsies/case completion day. Residents completed surveys before implementing the new rotation and 6 months after implementation to track self-assessment of Accreditation Council for Graduate Medical Education (ACGME) milestone performance and internal quality control metrics. Clinical Competency Committee (CCC) annual evaluations were assessed in paired PGY levels pre- and post-intervention. After implementation, there was a statistically significant improvement in self-assessment of levels 4 and 5 of ACGME milestones and improved satisfaction of quality metrics, including time for previewing, reviewing IHC, graduated responsibility, and perceived readiness for independent practice. CCC evaluations showed overall maintained performance levels, with trends towards improvements in junior resident classes. Our 6-day cycle adequately fulfills the current demands of our sizeable academic center's surgical pathology training and can be a model for pathology residencies looking to modernize their surgical pathology rotations and resident education.

An Analysis of the Effect of ABCA4 p.Asn1868Ile Genotypes on Retinal Structure in 26,558 Participants in the UK Biobank.

To determine whether the ABCA4 retinopathy-associated variant p.Asn1868Ile (c.5603A>T) is associated with retinal structure or subclinical disease among the general population. UK Biobank participants of European ancestry with available spectral-domain optical coherence tomography (OCT) passing quality control metrics and exome sequencing data were included. Regression analyses using both linear and recessive models tested for the association between the p.Asn1868Ile variant and total retinal thickness, clinically relevant segmented layer thicknesses, and visual acuity. Further regression analyses were performed with automated quality control metrics to determine if the p.Asn1868Ile variant is associated with poor quality or abnormal scans. Retinal layer segmentation and sequencing data for the p.Asn1868Ile variant were available for 26,558 participants, following exclusions. We identified no significant association between the p.Asn1868Ile variant and retinal thickness, any of the segmented layers, or visual acuity. There was also no significant difference for homozygous p.Asn1868Ile when tested under the assumption of a recessive model. No association was identified for any of the quality control metrics, and a χ2 test showed that participants with the p.Asn1868Ile variant were not more likely to be excluded during quality control due to poor quality scans (P = 0.56). The p.Asn1868Ile variant does not appear to affect the retinal structure or have pathogenic or subclinical effects on its own within the general population. The variant is likely to require other specific cis- or trans-acting modifying factors to cause ABCA4 retinopathy.

Identification of Key Elements in Prostate Cancer for Ontology Building via a Multidisciplinary Consensus Agreement.

Clinical data collection related to prostate cancer (PCa) care is often unstructured or heterogeneous among providers, resulting in a high risk for ambiguity in its meaning when sharing or analyzing data. Ontologies, which are shareable formal (i.e., computable) representations of knowledge, can address these challenges by enabling machine-readable semantic interoperability. The purpose of this study was to identify PCa-specific key data elements (KDEs) for standardization in clinic and research. A modified Delphi method using iterative online surveys was performed to report a consensus agreement on KDEs by a multidisciplinary panel of 39 PCa specialists. Data elements were divided into three themes in PCa and included (1) treatment-related toxicities (TRT), (2) patient-reported outcome measures (PROM), and (3) disease control metrics (DCM). The panel reached consensus on a thirty-item, two-tiered list of KDEs focusing mainly on urinary and rectal symptoms. The Expanded Prostate Cancer Index Composite (EPIC-26) questionnaire was considered most robust for PROM multi-domain monitoring, and granular KDEs were defined for DCM. This expert consensus on PCa-specific KDEs has served as a foundation for a professional society-endorsed, publicly available operational ontology developed by the American Association of Physicists in Medicine (AAPM) Big Data Sub Committee (BDSC).

Development and initial testing of EcoToxChip, a novel toxicogenomics tool for environmental management and chemical risk assessment.

New approach methods (NAMs) are increasingly important to help accelerate the pace of ecological risk assessment and offer more ethical, affordable, and efficient alternatives to traditional toxicity tests. In the present study, we describe the development, technical characterization and initial testing of a toxicogenomics tool, EcoToxChip (384-well qPCR array), to support chemical management and environmental monitoring for three laboratory model species - fathead minnow (Pimephales promelas), African clawed frog (Xenopus laevis), and Japanese quail (Coturnix japonica). Chip design, including gene selection, was informed by a diverse end-user group and quality control metrics (e.g. primer assay, reverse transcription and PCR efficiency) performed well based on a priori established criteria. Correlation with RNAseq data provided additional confidence in this novel toxicogenomics tool. While the present study represents an initial testing of only 24 EcoToxChips for each of the model species, the results provide increased confidence in the robustness/reproducibility of EcoToxChips for evaluating perturbations in gene expression associated with chemical exposure and thus, this NAM, combined with early-life stage toxicity testing, could augment current efforts for chemical prioritization and environmental management.

Glycated Albumin Correlates With Time-in-Range Better Than HbA1c or Fructosamine.

Intermediate-term glycemic control metrics may represent a viable alternative to continuous glucose monitoring (CGM) in patients without access to CGM. This work aimed to compare the relationship between CGM parameters and glycated albumin (GA), glycated hemoglobin A1c (HbA1c), and fructosamine for 24 weeks. We conducted exploratory comparative analyses of CGM subgroup data from a previously published 24-week prospective study of assay performance in 8 US clinics. Participants included 34 individuals with type 1 (n = 18) and type 2 diabetes (n = 16) undergoing changes to improve glycemic control (n = 22; group 1) or with stable diabetes therapy (n = 12; group 2). Main outcome measures included Pearson correlations between CGM and glycemic indices and receiver operating characteristic (ROC) analysis of glycemic index values predictive of time in range (TIR) greater than 70%. At weeks 4 and 8, GA correlations with TIR were higher than HbA1c correlations in group 1. In group 2, GA correlations with TIR were statistically significant, whereas HbA1c correlations were not. In both groups over the first 12 weeks, GA correlations with TIR were higher than fructosamine-TIR correlations. In the ROC analysis, GA predicted a TIR greater than 70% during weeks 2 to 24 (area under the curve >0.80); HbA1c was predictive during weeks 12 to 24. Cutoff values for TIR greater than 70% were 17.5% (sensitivity and specificity, 0.88) for GA and 7.3% (0.86) for HbA1c. GA is the most accurate predictor of TIR over 8 weeks compared with other glycemic indices, which may assist in clinical evaluation of changes in treatment where CGM is not possible and it is too early to use HbA1c (NCT02489773).