Near-infrared monitoring of roller compacted ribbon density: investigating sources of variation contributing to noisy spectral data

The aim of this study was to highlight how variability in roller compacted ribbon quality can impact on NIR spectral measurement and to propose a simple method of data selection to remove erroneous spectra. The use of NIR spectroscopy for monitoring ribbon envelope density has been previously demonstrated, however to date there has been limited discussion as to how spectral data sets can contain erroneous outliers due to poor sample presentation to the NIR probes. In this study compacted ribbon of variable quality was produced from three separate blends of microcrystalline cellulose (MCC)/lactose/magnesium stearate at 8 Roll Force settings (2–16 kN/cm). The three blends differed only in the storage conditions of MCC prior to blending and compaction. MCC sublots were stored at ambient (41% RH/20 °C), low humidity (11% RH/20 °C) and high humidity (75% RH/40 °C) conditions prior to blending. Ribbon envelope density was measured and ribbon NIR spectral data was acquired at line using a multi-probe spectrometer (MultiEye™ NIR). Initial inspection of the at-line NIR spectral data set showed a large degree of variability which indicated that some form of data cleaning was required. The source of variability in spectral measurements was investigated by subjective visual examination and by statistical analysis. Spectral variability was noted due to the storage conditions of MCC prior to compaction, Roll Force settings and between individual ribbon samples sampled at a set Roll Force/Blend combination. Variability was also caused by ribbon presentation to probes, such as differences in the presentation of broken, curved and flat intact ribbons. Based on the subjective visual examination of data, a Visual Discard method was applied and was found to be particularly successful for blends containing MCC stored at ambient and low humidity. However the Visual Discard method of spectra cleaning is subjective and therefore a non-subjective method capable of screening for erroneous probe readings was developed. For this data set a Trimmed Mean method was applied to set a limit on how data is cleaned from the data set allowing for the removal of a faulty probe reading (25% of data) or a poor sample (33% of data). The 33% Trimmed Mean reduced the impact of spectral variation or misreads between samples or probes and was found to be as successful as the Visual Discard method at cleaning the data set prior to development of the calibration equation

Inverting the model of genomics data sharing with the NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space

The NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL; https://anvilproject.org) was developed to address a widespread community need for a unified computing environment for genomics data storage, management, and analysis. In this perspective, we present AnVIL, describe its ecosystem and interoperability with other platforms, and highlight how this platform and associated initiatives contribute to improved genomic data sharing efforts. The AnVIL is a federated cloud platform designed to manage and store genomics and related data, enable population-scale analysis, and facilitate collaboration through the sharing of data, code, and analysis results. By inverting the traditional model of data sharing, the AnVIL eliminates the need for data movement while also adding security measures for active threat detection and monitoring and provides scalable, shared computing resources for any researcher. We describe the core data management and analysis components of the AnVIL, which currently consists of Terra, Gen3, Galaxy, RStudio/Bioconductor, Dockstore, and Jupyter, and describe several flagship genomics datasets available within the AnVIL. We continue to extend and innovate the AnVIL ecosystem by implementing new capabilities, including mechanisms for interoperability and responsible data sharing, while streamlining access management. The AnVIL opens many new opportunities for analysis, collaboration, and data sharing that are needed to drive research and to make discoveries through the joint analysis of hundreds of thousands to millions of genomes along with associated clinical and molecular data types

Colonoscopy Standardization: Insurance Verification and Direct Access

Outline Background Problem Scope Approach Progress Recommendation

Histochemistry: Live and in Color

Histochemistry—chemistry in the context of biological tissue—is an invaluable set of techniques used to visualize biological structures. This field lies at the interface of organic chemistry, biochemistry, and biology. Integration of these disciplines over the past century has permitted the imaging of cells and tissues using microscopy. Today, by exploiting the unique chemical environments within cells, heterologous expression techniques, and enzymatic activity, histochemical methods can be used to visualize structures in living matter. This review focuses on the labeling techniques and organic fluorophores used in live cells

Adaptive Background Correction of Crystal Image Datasets:Towards Automated Process Control

Improving the data descriptor calculation of crystal’s physical properties requires sophisticated imaging techniques and algorithms. It has been possible to construct 2D population balance models benefiting from characteristic measurements of both crystal’s length and width, compared to the single representative sizes used in 1D models. Our aim is to ameliorate the procedure of determining shape (and not only size) factors, in an automated fashion and directly from the process, for implementation in future models. Here, approaches suitable for real-time applications were employed including engineered imaging sensors and adaptive algorithms. We described the latter in detail for varying 2D image datasets. Their basic concept is similar. Each is applicable to an entire dataset, thus demonstrating efficacy for a variety of particle environments. While the challenge of particle segmentation for higher concentrations was not scrutinized here, this approach reduced processing time, steps and supervision, for the benefit of certain applications requiring process monitoring and automation

Serum neurofilament light chain in hereditary transthyretin amyloidosis: validation in real-life practice

Neurofilament light chain (NfL) has emerged as a sensitive biomarker in hereditary transthyretin amyloid polyneuropathy (ATTRv-PN). We hypothesise that NfL can identify conversion of gene carriers to symptomatic disease, and guide treatment approaches. Serum NfL concentration was measured longitudinally (2015–2022) in 59 presymptomatic and symptomatic ATTR variant carriers. Correlations between NfL and demographics, biochemistry and staging scores were performed as well as longitudinal changes pre- and post-treatment, and in asymptomatic and symptomatic cohorts. Receiver-operating analyses were performed to determine cut-off values. NfL levels correlated with examination scores (CMTNS, NIS and MRC; all p p p 64.5 pg/ml (sensitivity= 91.9%, specificity = 88.5%), whereas asymptomatic patients could only be discriminated from sensory or sensorimotor converters or symptomatic individuals by a NfL concentration >88.9 pg/ml (sensitivity = 62.9%, specificity = 96.2%) However, an NfL increment of 17% over 6 months could discriminate asymptomatic from sensory or sensorimotor converters (sensitivity = 88.9%, specificity = 80.0%). NfL reduced with treatment by 36%/year and correlated with TTR suppression (r = 0.64, p = .008). This data validates the use of serum NfL to identify conversion to symptomatic disease in ATTRv-PN. NfL levels can guide assessment of disease progression and response to therapies.</p

Momentary Influences on Self-Regulation in Two Populations With Health Risk Behaviors: Adults Who Smoke and Adults Who Are Overweight and Have Binge-Eating Disorder.

Introduction: Self-regulation has been implicated in health risk behaviors and is a target of many health behavior interventions. Despite most prior research focusing on self-regulation as an individual-level trait, we hypothesize that self-regulation is a time-varying mechanism of health and risk behavior that may be influenced by momentary contexts to a substantial degree. Because most health behaviors (e.g., eating, drinking, smoking) occur in the context of everyday activities, digital technologies may help us better understand and influence these behaviors in real time. Using a momentary self-regulation measure, the current study (which was part of a larger multi-year research project on the science of behavior change) used ecological momentary assessment (EMA) to assess if self-regulation can be engaged and manipulated on a momentary basis in naturalistic, non-laboratory settings. Methods: This one-arm, open-label exploratory study prospectively collected momentary data for 14 days from 104 participants who smoked regularly and 81 participants who were overweight and had binge-eating disorder. Four times per day, participants were queried about momentary self-regulation, emotional state, and social and environmental context; recent smoking and exposure to smoking cues (smoking sample only); and recent eating, binge eating, and exposure to binge-eating cues (binge-eating sample only). This study used a novel, momentary self-regulation measure comprised of four subscales: momentary perseverance, momentary sensation seeking, momentary self-judgment, and momentary mindfulness. Participants were also instructed to engage with Laddr, a mobile application that provides evidence-based health behavior change tools via an integrated platform. The association between momentary context and momentary self-regulation was explored via mixed-effects models. Exploratory assessments of whether recent Laddr use (defined as use within 12 h of momentary responses) modified the association between momentary context and momentary self-regulation were performed via mixed-effects models. Results: Participants (mean age 35.2; 78% female) in the smoking and binge-eating samples contributed a total of 3,233 and 3,481 momentary questionnaires, respectively. Momentary self-regulation subscales were associated with several momentary contexts, in the combined as well as smoking and binge-eating samples. For example, in the combined sample momentary perseverance was associated with location, positively associated with positive affect, and negatively associated with negative affect, stress, and tiredness. In the smoking sample, momentary perseverance was positively associated with momentary difficulty in accessing cigarettes, caffeine intake, and momentary restraint in smoking, and negatively associated with temptation and urge to smoke. In the binge-eating sample, momentary perseverance was positively associated with difficulty in accessing food and restraint in eating, and negatively associated with urge to binge eat. While recent Laddr use was not associated directly with momentary self-regulation subscales, it did modify several of the contextual associations, including challenging contexts. Conclusions: Overall, this study provides preliminary evidence that momentary self-regulation may vary in response to differing momentary contexts in samples from two exemplar populations with risk behaviors. In addition, the Laddr application may modify some of these relationships. These findings demonstrate the possibility of measuring momentary self-regulation in a trans-diagnostic way and assessing the effects of momentary, mobile interventions in context. Health behavior change interventions may consider measuring and targeting momentary self-regulation in addition to trait-level self-regulation to better understand and improve health risk behaviors. This work will be used to inform a later stage of research focused on assessing the transdiagnostic mediating effect of momentary self-regulation on medical regimen adherence and health outcomes. Clinical Trial Registration: ClinicalTrials.gov, Identifier: NCT03352713