Quality Control Tool Research Articles

Bringing Sustainable Development to the Corporate Level: Boards’ Cognitive Biases towards ESG and Relevant Debiasing Interventions

The proposed research is an attempt to view how internationally recognised principles of sustainable development can be implemented at the corporate level, in particular, how the company’s board of directors should respond to climate and environmental challenges. Specifically, the paper examines the problem of reducing board members' repeated cognitive biases towards such a mainstream governance concept as ESG (Environmental, Social and Corporate Governance). The research focuses on the five most well-known cognitive biases of a board towards ESG, often encountered and described conceptually in behavioural literature: over-optimism, status quo effect, confirmation bias, hyperbolic discounting, and groupthink. Subsequently, the paper draws recommendations for overcoming or mitigating these biases by introducing and describing several debiasing interventions and quality control tools. These tools are conditionally divided into three groups: changing incentives, optimising choice architecture, and debiasing training. The author believes that incorporating behavioural insights into an analysis of the board’s ESG commitment would bring a fresh perspective to this research area, which now is typically dominated by a rational choice framework. The paper combines theoretical analysis of the existing literature in law, behavioural economics and psychology with qualitative research application based on data obtained from first-hand observations, board empirical studies, questionnaires, and focus groups.

Changes in the Main Physicochemical Properties and Electrochemical Fingerprints in the Production of Sea Buckthorn Juice by Pectinase Treatment.

Enzymatic hydrolysis using pectinase is critical for producing high-yield and quality sea buckthorn juice. This study determined the optimal temperature, time, and enzyme dosage combinations to guide manufacturers. A temperature of 60 °C, hydrolysis time of 3 h, and 0.3% enzyme dosage gave 64.1% juice yield-25% higher than without enzymes. Furthermore, monitoring physicochemical properties reveals enzyme impacts on composition. Higher dosages increase soluble solids up to 15% and soluble fiber content by 35% through cell wall breakdown. However, excessive amounts over 0.3% decrease yields. Pectin concentration also declines dose-dependently, falling by 91% at 0.4%, improving juice stability but needing modulation to retain viscosity. Electrochemical fingerprinting successfully differentiates process conditions, offering a rapid quality control tool. Its potential for commercial inline use during enzymatic treatment requires exploration. Overall, connecting optimized parameters to measured effects provides actionable insights for manufacturers to boost yields, determine enzyme impacts on nutrition/functionality, and introduce novel process analytical technology. Further investigations of health properties using these conditions could expand sea buckthorn juice functionality.

Analytical Method for Quantifying Monoterpenoids (p-Cymene and Myrcene) in Nanoemulsions Using High-Performance Liquid Chromatography.

Myrcene and cymene, aromatic monoterpenes found in plants and essential oils, possess distinctive aromatic qualities. However, their volatility and limited solubility pose challenges in precise handling and formulation. Meanwhile, nanoemulsions emerge as promising drug delivery systems, improving the bioavailability and stability of these active ingredients. This article aimed to develop an HPLC method for the quantification of two monoterpenoids, p-cymene and myrcene, in nanoemulsions. The method used a Phenomenex® Synergi™ Fusion-RP column (150 mm × 4.6 mm id, 4 μm particle size) on an HPLC system with isocratic elution. The mobile phase was composed of acetonitrile and water (60:40, v/v) and was validated in terms of specificity, linearity, accuracy, precision, robustness, and selectivity. The method provided accurate and precise results with a correlation coefficient of 0.999 and RSD values of less than 2%. The method can be used for quality control of nanoemulsions containing these monoterpenoids and as a reference for future studies on their efficacy and stability. The study demonstrates the feasibility of using HPLC for the quantification of monoterpenoids in nanoemulsions and its potential as a quality control tool for nanoemulsion-based drug delivery systems. The method's accuracy, precision, and reliability, as evidenced by high correlation coefficients and low RSD values, underscore its suitability for ensuring the consistent formulation of these monoterpenoid-containing nanoemulsions, while also serving as a reference point for future research endeavors in this field.

Decoding the complexity of on-target integration: characterizing DNA insertions at the CRISPR-Cas9 targeted locus using nanopore sequencing

BackgroundCRISPR-Cas9 technology has advanced in vivo gene therapy for disorders like hemophilia A, notably through the successful targeted incorporation of the F8 gene into the Alb locus in hepatocytes, effectively curing this disorder in mice. However, thoroughly evaluating the safety and specificity of this therapy is essential. Our study introduces a novel methodology to analyze complex insertion sequences at the on-target edited locus, utilizing barcoded long-range PCR, CRISPR RNP-mediated deletion of unedited alleles, magnetic bead-based long amplicon enrichment, and nanopore sequencing.ResultsWe identified the expected F8 insertions and various fragment combinations resulting from the in vivo linearization of the double-cut plasmid donor. Notably, our research is the first to document insertions exceeding ten kbp. We also found that a small proportion of these insertions were derived from sources other than donor plasmids, including Cas9-sgRNA plasmids, genomic DNA fragments, and LINE-1 elements.ConclusionsOur study presents a robust method for analyzing the complexity of on-target editing, particularly for in vivo long insertions, where donor template integration can be challenging. This work offers a new tool for quality control in gene editing outcomes and underscores the importance of detailed characterization of edited genomic sequences. Our findings have significant implications for enhancing the safety and effectiveness of CRISPR-Cas9 gene therapy in treating various disorders, including hemophilia A.

Comparison of Multiple NIR Spectrometers for Detecting Low-Concentration Nitrogen-Based Adulteration in Protein Powders.

Protein adulteration is a common fraud in the food industry due to the high price of protein sources and their limited availability. Total nitrogen determination is the standard analytical technique for quality control, which is incapable of distinguishing between protein nitrogen and nitrogen from non-protein sources. Three benchtops and one handheld near-infrared spectrometer (NIRS) with different signal processing techniques (grating, Fourier transform, and MEM-micro-electro-mechanical system) were compared with detect adulteration in protein powders at low concentration levels. Whey, beef, and pea protein powders were mixed with a different combination and concentration of high nitrogen content compounds-namely melamine, urea, taurine, and glycine-resulting in a total of 819 samples. NIRS, combined with chemometric tools and various spectral preprocessing techniques, was used to predict adulterant concentrations, while the limit of detection (LOD) and limit of quantification (LOQ) were also assessed to further evaluate instrument performance. Out of all devices and measurement methods compared, the most accurate predictive models were built based on the dataset acquired with a grating benchtop spectrophotometer, reaching R2P values of 0.96 and proximating the 0.1% LOD for melamine and urea. Results imply the possibility of using NIRS combined with chemometrics as a generalized quality control tool for protein powders.

Technical note: development of a simulation framework, enabling the investigation of locally tuned single energy proton radiography

Range uncertainties remain a limitation for the confined dose distribution that proton therapy can offer. The uncertainty stems from the ambiguity when translating CT Hounsfield Units (HU) into proton stopping powers. Proton Radiography (PR) can be used to verify the proton range. Specifically, PR can be used as a quality-control tool for CBCT-based synthetic CTs. An essential part of the work illustrating the potential of PR has been conducted using multi-layer ionization chamber (MLIC) detectors and mono-energetic PR. Due to the dimensions of commercially available MLICs, clinical adoption is cumbersome. Here, we present a simulation framework exploring locally-tuned single energy (LTSE) proton radiography and corresponding potential compact PR detector designs. Based on a planning CT data set, the presented framework models the water equivalent thickness. Subsequently, it analyses the proton energies required to pass through the geometry within a defined ROI. In the final step, an LTSE PR is simulated using the MCsquare Monte Carlo code. In an anatomical head phantom, we illustrate that LTSE PR allows for a significantly shorter longitudinal dimension of MLICs. We compared PR simulations for two exemplary 30 × 30 mm2 proton fields passing the phantom at a 90° angle at an anterior and a posterior location in an iso-centric setup. The longitudinal distance over which all spots per field range out is significantly reduced for LTSE PR compared to mono-energetic PR. In addition, we illustrate the difference in shape of integral depth dose (IDD) when using constrained PR energies. Finally, we demonstrate the accordance of simulated and experimentally acquired IDDs for an LTSE PR acquisition. As the next steps, the framework will be used to investigate the sensitivity of LTSE PR to various sources of errors. Furthermore, we will use the framework to systematically explore the dimensions of an optimized MLIC design for daily clinical use.

Ultra‐high‐performance liquid chromatography method development for the quantification of Molnupiravir and its process‐related impurities using Box‐Behnken experimental design

AbstractMolnupiravir, a promising antiviral agent, has gained significant attention for its potential in treating viral infections, particularly in the context of the coronavirus disease 2019 pandemic. This study aimed to develop and validate an ultra‐high‐performance liquid chromatography (UHPLC) method for the quantification of Molnupiravir and its associated impurities (Imp‐I, Imp‐II, Imp‐III, and Imp‐IV). The method involved a systematic investigation of critical method parameters and their optimization using Quality by Design principles. The percentage of organic modifiers, column temperature, and flow rate were systematically optimized using the Box‐Behnken design. The developed method was assessed for specificity, system suitability, accuracy, precision, linearity, and detection limits. The results demonstrate strong specificity, with the analysis remaining accurate even in the presence of impurities. The developed method exhibits excellent precision, with repeatability and intermediate precision showing relative standard deviation values ranging from 0.78% to 1.14% for impurities and 0.82% to 1.91% for Molnupiravir. Furthermore, the method displays exceptional linearity, covering a wide range of concentrations. The linear regression analysis yields high coefficients of determination (r2, 9993–0.9997), confirming the linearity. The developed UHPLC method is well‐suited for the accurate and reliable analysis of Molnupiravir and its impurities, making it a valuable tool for quality control and pharmaceutical research applications.

A comparative study on vildagliptin brand and its generic equivalents using dissolution test as quality control measure tool

Market drugs including brand or generic with poor quality, don’t meet the acceptable standard guidelines. Vildagliptin is an important antidiabetic drugs used in monotherapy or in combinations protocols for treatment of diabetes mellites. The main goal of the current study is to assess the pharmaceutical equivalence of two marketed generics of vildagliptin 50 mg tablets compared to the branded product (Galvus 50 mg). The in vitro dissolution test was used as a quality control tool to obtain the dissolution profile of vildagliptin compared to the reference drug. The results revealed that all tested samples showed dissolution behavior like standard drug. Whole samples dissolution reached after 15 min in accordance with the standard. According to the similarity factors records, tested vildagliptin samples showed a comparable dissolution to the reference drug. The current work presents an in vitro protocol for quality evaluation of recently released generic drugs.

Nonsense-mediated mRNA decay pathway in plants under stress: general gene regulatory mechanism and advances.

Nonsense-mediated mRNA decay in eukaryotes is vital to cellular homeostasis. Further knowledge of its putative role in plant RNA metabolism under stress is pivotal to developing fitness-optimizing strategies. Nonsense-mediated mRNA decay (NMD), part of the mRNA surveillance pathway, is an evolutionarily conserved form of gene regulation in all living organisms. Degradation of mRNA-bearing premature termination codons and regulation of physiological RNA levels highlight NMD's role in shaping the cellular transcriptome. Initially regarded as purely a tool for cellular RNA quality control, NMD is now considered to mediate various aspects of plant developmental processes and responses to environmental changes. Here we offer a basic understanding of NMD in eukaryotes by explaining the concept of premature termination codon recognition and NMD complex formation. We also provide a detailed overview of the NMD mechanism and its role in gene regulation. The potential role of effectors, including ABCE1, in ribosome recycling during the translation process is also explained. Recent reports of alternatively spliced variants of corresponding genes targeted by NMD inArabidopsis thalianaare provided in tabular format. Detailed figures are also provided to clarify the NMD concept in plants. In particular, accumulating evidence shows that NMD can serve as a novel alternative strategy for genetic manipulation and can help design RNA-based therapies to combat stress in plants. A key point of emphasis is its function as a gene regulatory mechanism as well as its dynamic regulation by environmental and developmental factors. Overall, a detailed molecular understanding of the NMD mechanism can lead to further diverse applications, such as improving cellular homeostasis in living organisms.

Understanding the spatial and seasonal variation of the ground-level ozone in Southeast China with an interpretable machine learning and multi-source remote sensing

Ground-level ozone (O3) pollution poses significant threats to both human health and air quality. This study uses ground observations and satellite retrievals to explore the spatiotemporal characteristics of ground-level O3 in Zhejiang Province, China. We created data-driven machine learning models that include meteorological, geographical and atmospheric parameters from multi-source remote sensing products, achieving good performance (Pearson's r of 0.81) in explaining regional O3 dynamics. Analyses revealed the crucial roles of temperature, relative humidity, total column O3, and the distributions and interactions of precursor (volatile organic compounds and nitrogen oxides) in driving the varied O3 patterns observed in Zhejiang. Furthermore, the interpretable modeling quantified multifactor interactions that sustain high O3 levels in spring and autumn, suppress O3 levels in summer, and inhibit O3 formation in winter. This work demonstrates the value of a combined approach using satellite and machine learning as an effective novel tool for regional air quality assessment and control.

Development of new matrix reference materials for quantitative urine analysis in drug tests.

Accurate quantitative analyses require standardized methods to control and improve the analytical process in the laboratory. The availability of urine reference materials (RMs) may offer a feasible option to improve the accuracy of urine analysis and to control matrix effects. This paper presents the complete process of the development of matrix RMs in urine, including sample preparation, homogeneity, and stability studies, as well as uncertainty assessment. A freeze-drying process was developed, and freeze-dried human and pig urine samples were prepared and verified to have comparable homogeneity to liquid samples and higher stability than liquid human, pig, and artificial urine samples at 4℃ or room temperature and under extreme conditions. A total of 21 authentic urine samples from August 2022 were measured with freeze-dried RMs and spiked urine samples, and the reliability of the quantification of the RMs was compared. The freeze-dried human urine matrix RM appeared to be an excellent tool for daily quality control, as it showed high stability and gave the most consistent results with spiked samples.

Fusing hyperspectral imaging and electronic nose data to predict moisture content in Penaeus vannamei during solar drying.

The control of moisture content (MC) is essential in the drying of shrimp, directly impacting its quality and shelf life. This study aimed to develop an accurate method for determining shrimp MC by integrating hyperspectral imaging (HSI) with electronic nose (E-nose) technology. We employed three different data fusion approaches: pixel-, feature-, and decision-fusion, to combine HSI and E nose data for the prediction of shrimp MC. We developed partial least squares regression (PLSR) models for each method and compared their performance in terms of prediction accuracy. The decision fusion approach outperformed the other methods, producing the highest determination coefficients for both calibration (0.9595) and validation sets (0.9448). Corresponding root-mean square errors were the lowest for the calibration set (0.0370) and validation set (0.0443), indicating high prediction precision. Additionally, this approach achieved a relative percent deviation of 3.94, the highest among the methods tested. The findings suggest that the decision fusion of HSI and E nose data through a PLSR model is an effective, accurate, and efficient method for evaluating shrimp MC. The demonstrated capability of this approach makes it a valuable tool for quality control and market monitoring of dried shrimp products.

Librarian: A quality control tool to analyse sequencing library compositions.

Robust analysis of DNA sequencing data needs to include a set of quality control steps to ensure that technical bias is kept to a minimum. A metric easily obtained is the frequency of each of the nucleobases for each position across all sequencing reads. Here, we explore the differences in nucleobase compositions of various library types produced by standard experimental methodologies. We obtained the compositions of nearly 3000 publicly available datasets and subjected them to Uniform Manifold Approximation and Projection (UMAP) dimensionality reduction for a two-dimensional representation of their composition characteristics. We find that most library types result in a specific composition profile. We use this to give an estimate of how strongly the composition of a test library resembles the profiles of previously published libraries, and how likely the test sample is to be of a particular type. We introduce Librarian, a user-friendly web application and command line tool which enables checking base compositions of test libraries against known library types. Library preparation methods strongly influence the per position nucleobase content. By comparing test libraries to a database of previously published library types we can make predictions regarding the library preparation method. Librarian is a user-friendly tool to access this information for quality assurance purposes as discrepancies can flag potential irregularities very early on.

Dual-energy computed tomography quality control: Initial experiences with a semi-automatic analysis tool

PurposeA quality control (QC) system for dual-energy CT (DECT) was developed. The scope of the QC system was to monitor both the constancy of the CT images and the software used in calculating the DECT derived maps. Longitudinal analysis was based on a standard imaging protocol, a commercial multi-energy phantom, and a semi-automatic analysis tool. MethodsThe phantom consisted of an elliptical body section with round slots for interchangeable inserts. It was scanned with 90kVp/Sn150kVp, automatic tube current modulation, and 9.6 mGy CTDIvol. From the two conventional CT images, scanner manufacturer’s software was used to provide virtual monoenergetic images at two different energies, effective atomic number (Zeff) maps, and iodine concentration maps. The images were analyzed using an open-source tool allowing user-selected statistics of interest. The means and standard deviations of the phantom background and the iodine, calcium, and water inserts were recorded. The QC tool is available at github.com/tomakela/dectqatool. ResultsThe obtained results were generally highly consistent over time, except for the smaller diameter iodine inserts. A small change inZeff was observed after a DECT software update. The developed QC tool aided the analysis robustness: the segmentations were modifiable when needed, and small rotations or air bubbles in the water insert were easily corrected. ConclusionThe developed QC system provided easy-to-use workflow for constancy measurements. A small deviation due to change in the post-processing was detected. The proposed imaging protocol and analysis steps, and the reported measurement variations can aid in determining action levels for DECT QC.

Capillary electrokinetic chromatography for chiral separation of potential SARS-CoV-2 3CL protease inhibitors.

In this work, a capillary electrophoresis method was developed as a quality control tool to determine the enantiomeric purity of a series of five chiral compounds evaluated as potential severe acute respiratory syndrome coronavirus 2 3CL protease inhibitors. The first cyclodextrin tested, that is, highly sulfated-β-cyclodextrin, at 6% (m/v) in a 25mM phosphate buffer, using a capillary dynamically coated with polyethylene oxide, at an applied voltage of 15kV and a temperature of 25°C, was found to successfully separate the five derivatives. The limits of detection and quantification were calculated together with the greenness score of the method in order to evaluate the method in terms of analytical and environmental performance. In addition, it is noteworthy that simultaneously high-performance liquid chromatography separation of the enantiomers of the same compounds with two different columns, the amylose tris(3,5-dimethylphenylcarbamate)-coated and the cellulose tris(3,5-dichlorophenylcarbamate)-immobilized on silica stationary phases, was studied. Neither the former stationary phase nor the latter was able to separate all derivatives in a mobile phase consisting of n-heptane/propan-2-ol 80/20 (v/v).

Advancements in microneedle fabrication techniques: artificial intelligence assisted 3D-printing technology.

Microneedles (MNs) are micron-scale needles that are a painless alternative to injections for delivering drugs through the skin. MNs find applications as biosensing devices and could serve as real-time diagnosis tools. There have been numerous fabrication techniques employed for producing quality MN-based systems, prominent among them is the three-dimensional (3D) printing. 3D printing enables the production of quality MNs of tuneable characteristics using a variety of materials. Further, the possible integration of artificial intelligence (AI) tools such as machine learning (ML) and deep learning (DL) with 3D printing makes it an indispensable tool for fabricating microneedles. Provided that these AI tools can be trained and act with minimal human intervention to control the quality of products produced, there is also a possibility of mass production of MNs using these tools in the future. This work reviews the specific role of AI in the 3D printing of MN-based devices discussing the use of AI in predicting drug release patterns, its role as a quality control tool, and in predicting the biomarker levels. Additionally, the autonomous 3D printing of microneedles using an integrated system of the internet of things (IoT) and machine learning (ML) is discussed in brief. Different categories of machine learning including supervised learning, semi-supervised learning, unsupervised learning, and reinforced learning have been discussed in brief. Lastly, a brief section is dedicated to the biosensing applications of MN-based devices.

Novel quantitative immunohistochemistry method using histone H3, family 3B as the internal reference standard for measuring human epidermal growth factor receptor 2 expression in breast cancer.

Immunohistochemistry (IHC) is an essential technique in surgical and clinical pathology for detecting diagnostic, prognostic, and predictive biomarkers for personalized cancer therapy. However, the lack of standardization and reference controls results in poor reproducibility, and a reliable tool for IHC quantification is urgently required. The objective of this study was to describe a novel approach in which H3F3B (histone H3, family 3B) can be used as an internal reference standard to quantify protein expression levels using IHC. The authors enrolled 89 patients who had human epidermal growth factor receptor 2 (HER2)-positive breast cancer (BC). They used a novel IHC-based assay to measure protein expression using H3F3B as the internal reference standard. H3F3B was uniformly expressed at the protein level in all tumor regions in cancer tissues. HER2 expression levels were measured with the H-score using HALO software. Kaplan-Meier analysis indicated that, among patients who had HER2-positive BC in The Cancer Genome Atlas data set and the authors' data set, the subgroup with low HER2 expression had a significantly better prognosis than the subgroup with high HER2 expression. Furthermore, the authors observed that HER2 expression levels were precisely evaluated using the proposed method, which can classify patients who are at higher risk of HER2-positive BC to receive trastuzumab-based adjuvant therapy. Dual-color IHC with H3F3B is an excellent tool for internal and external quality control of HER2 expression assays. The proposed IHC-based quantification method accurately assesses HER2 expression levels and provides insights for predicting clinical prognosis in patients with HER2-positive BC who receive trastuzumab-based adjuvant therapy.

Pediatric intensive care unit admissions network-rationale, framework and method of operation of a nationwide collaborative pediatric intensive care research network in Germany.

The Pediatric Intensive Care Unit Admissions (PIA) network aims to establish a nationwide database in Germany to gather epidemiological, clinical, and outcome data on pediatric critical illness. The heterogeneity of pediatric patients in intensive care units (PICU) poses challenges in obtaining sufficient case numbers for reliable research. Multicentered approaches, such as patient registries, have proven effective in collecting large-scale data. However, Germany lacks a systematic registration system for pediatric intensive care admissions, hindering epidemiological and outcome assessments. The PIA network intends to address these gaps and provide a framework for clinical and epidemiological research in pediatric intensive care. The network will interconnect PICUs across Germany and collect structured data on diagnoses, treatment, clinical course, and short-term outcomes. It aims to identify areas for improvement in care, enable disease surveillance, and potentially serve as a quality control tool. The PIA network builds upon the existing infrastructure of the German Pediatric Surveillance Unit ESPED and utilizes digitalized data collection techniques. Participating units will complete surveys on their organizational structure and equipment. The study population includes patients aged ≥28 days admitted to participating PICUs, with a more detailed survey for cases meeting specific criteria. Data will be collected by local PIA investigators, anonymized, and entered into a central database. The data protection protocol complies with regulations and ensures patient privacy. Quarterly data checks and customized quality reports will be conducted to monitor data completeness and plausibility. The network will evaluate its performance, data collection feasibility, and data quality. Eligible investigators can submit proposals for data analyses, which will be reviewed and analyzed by trained statisticians or epidemiologists. The PIA network aims to improve pediatric intensive care medicine in Germany by providing a comprehensive understanding of critical illness, benchmarking treatment quality, and enabling disease surveillance.

Heated fibre-optic cable installed in compacted bentonite layers: numerical evaluation of influences of the compaction-induced variability on thermal conductivity estimation

Active heating of fibre-optic (FO) cable combined with distributed temperature sensing has been applied as a quality control tool for emplacing granulated bentonite buffer. For calibrating the tool, the FO cable is installed in specimens with known dry densities. Layer-by-layer compaction is often employed to prepare the specimens. Although the average dry density is guaranteed, some studies report possible variations in the dry density within a layer. In this study, heat transfer from a heated FO cable installed in granulated bentonite with different compaction-induced variabilities was numerically simulated. The reference case used homogeneous bentonite with an average dry density of 1.5 g cm −3 . For three other cases the granulated bentonite was filled in two, three and four layers, respectively, each of which had a distinct dry density gradient ranging from 1.3 to 1.7 g cm −3 . For each case, the FO cable placed at the centre of the container was numerically heated, and the thermal conductivity was calculated using temperature changes. In the cases where the FO cable was placed on the layer interface at which the dry density was discontinuous, the calculated apparent thermal conductivity was found to have been underestimated with an error of as much as 4%. In the other two cases, the thermal conductivities obtained were nearly identical to those corresponding to the average dry density. The influence of the compaction-induced variability in the dry density was found to be insignificant and the estimated thermal conductivity was essentially that of the bentonite represented by its average dry density. Thematic collection: This article is part of the Sustainable geological disposal and containment of radioactive waste collection available at: https://www.lyellcollection.org/topic/collections/radioactive

Detecting potential outliers in longitudinal data with time-dependent covariates.

Outliers can influence regression model parameters and change the direction of the estimated effect, over-estimating or under-estimating the strength of the association between a response variable and an exposure of interest. Identifying visit-level outliers from longitudinal data with continuous time-dependent covariates is important when the distribution of such variable is highly skewed. The primary objective was to identify potential outliers at follow-up visits using interquartile range (IQR) statistic and assess their influence on estimated Cox regression parameters. Study was motivated by a large TEDDY dietary longitudinal and time-to-event data with a continuous time-varying vitamin B12 intake as the exposure of interest and development of Islet Autoimmunity (IA) as the response variable. An IQR algorithm was applied to the TEDDY dataset to detect potential outliers at each visit. To assess the impact of detected outliers, data were analyzed using the extended time-dependent Cox model with robust sandwich estimator. Partial residual diagnostic plots were examined for highly influential outliers. Extreme vitamin B12 observations that were cases of IA had a stronger influence on the Cox regression model than non-cases. Identified outliers changed the direction of hazard ratios, standard errors, or the strength of association with the risk of developing IA. At the exploratory data analysis stage, the IQR algorithm can be used as a data quality control tool to identify potential outliers at the visit level, which can be further investigated.