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• Fatty acid content of indigenous seed oils by easy trans-esterification method and GC–MS analysis. • Indigenous South African seed oils are mostly of expected quality and authenticity. • Qualitative and quantitative variation demonstrated for commercially available essential oils. • Industry will benefit from implementation of available SANS standards. South Africa produces a number of indigenous, economically important seed and essential oils. These oils are sold at high prices, which may encourage malpractices such as the adulteration of products, by blending with other less expensive oils, and manipulation of the oil composition of inferior oils by adding specific compounds. Oils produced from wild-harvested plant material, which are typically variable in composition, can influence the batch-to-batch consistency of the oils, both qualitatively and quantitatively. These differences impact on their organoleptic and therapeutic properties. The aim of this study was to investigate the chemical composition of commercially available indigenous fixed oils and essential (volatile) oils, and to compare the levels of characteristic chemical constituents to those reported for authentic oils, to determine the need for compositional guidelines. Selected indigenous seed (n = 24) and essential oils (n = 28), purchased from online suppliers, were chemically characterised using gas chromatography coupled with mass spectrometry and flame ionisation detection. The relative concentrations of four major fatty acids, namely palmitic, stearic, oleic and linoleic acids, varied in the seed oils of Adansonia digitata, Sclerocarya birrea, Citrullus lanatus and Schinziophyton rautanenii. However, the ranges mostly correspond to those reported in literature and to that given in available South African National Standards. One sample each of Adansonia digitata and Citrullus lanatus contained considerably different levels of the four major fatty acids and the cyclopropane fatty acid, dihydrosterculic acid, compared to the other samples in the set. Overall, the main compounds for the five commercial essential oil sample sets were found to vary quantitatively mostly, but were strikingly different in some instances. The chemical profile of one Agathosma betulina sample was found to correspond with that of Agathosma crenulata. Artemisia afra samples contained a compound that may be santolinyl acetate at levels of up to 36.0 %, a compound that was not reported in all authentic oils of the same species. Eriocephalus punctulatus samples contained linalyl acetate at up to 11.9 %, but it was absent from authentic oils investigated in a previous study. Citronellyl acetate and phenyl ethyl alcohol were present in the Pelargonium graveolens samples, but were not reported in a previous study of commercial samples. Lippia javanica samples displayed chemotypic variation, which was also reported in a separate study for the species. A minor degree of qualitative variation was observed in some samples for the essential oils, with compounds absent or present. For the first time, the lack of compositional information that can have a direct impact on consumers is highlighted. As the composition directly impacts on the safety, quality and efficacy of these oils, highlighting the need for producers to follow and provide standardised protocols is suggested. A gas chromatographic profile of seed and essential oils, with semi-quantitative percentage areas and reliable identification of the major constituents present, is recommended as a minimum requirement for quality control. Adherence to this guideline can assist to ensure quality, consistency and authenticity of seed and essential oil products produced and marketed in South Africa. Quality control measures, and where possible, material standardisation, is of paramount importance. The standardisation of preselected plant materials used for essential oil production through cloning and cultivation are key to ensuring chemical consistency and consumer safety. [ABSTRACT FROM AUTHOR]

• ABUS is a 3D volume imaging technique for screening dense breasts, with similar diagnostic accuracy as handheld Ultrasound. • Adequate training, systematic quality checks and a learning curve are crucial in improving scans quality and reading times. • Recognizing ABUS unique artefacts and pitfalls is key in delivering state of the art exams and reports. • Large multicentric trials are needed to establish the feasibility of ABUS as an additional screening tool for dense breasts. [ABSTRACT FROM AUTHOR]

• AS LNA qPCR can accurately identify VP1-E 295 K containing samples in sPV2 batches. • The developed AS LNA qPCR for E 295 K mutation is highly sensitive. • LNA probes used are highly specific in targeting known mutations. • AS LNA qPCR is likely applicable to other vaccine strains, serotypes, and mutations. Sabin Inactivated Poliovirus Vaccine (sIPV) has become one of the preferred vaccination options for the last step in the Poliovirus eradication program. Sequencing of poliovirus samples is needed during the manufacturing of poliovirus vaccines to assure the safety and immunogenicity of these vaccines. Next-generation sequencing analysis is the current costly and time-consuming gold standard for monitoring the manufacturing processes. We developed a low-cost and quick, highly sensitive, and allele-specific locked nucleic acid-probe-based reverse transcription quantitative PCR alternative that can accurately detect mutations in poliovirus vaccine samples during process development, scaling up, and release. Using the frequently in vitro occurring and viral replication-impacting VP1-E 295 K mutation as a showcase, we show that this technology can accurately detect E 295 K mutations in poliovirus 2 samples to similar levels as NGS. The qPCR technology was developed employing a synthetic dsDNA fragment-based standard curve containing mixes of E 295 K-WT (wildtype) and Mut (mutant) synthetic dsDNA fragments ranging from 1 × 107 copies/µL to 1 × 102 copies/µL to achieve a linear correlation with R2 > 0.999, and PCR efficiencies of 95–105 %. Individual standard concentration levels achieved accuracies of ≥92 % (average 96 %) and precisions of ≤17 % (average 3.3 %) RSD. Specificity of locked nucleic acid (LNA)-probes was confirmed in the presence and absence of co-mutations in the probe-binding region. Application of the developed assay to Sabin Poliovirus type 2 production run samples, illustrated a linear relationship with an R2 of 0.994, and an average accuracy of 97.2 % of the variant (allele)-specific AS LNA qPCR result, compared to NGS. The assay showed good sensitivity for poliovirus samples, containing E 295 K mutation levels between 0 % and 95 % (quantification range). In conclusion, the developed AS LNA qPCR presents a valuable low-cost, and fast tool, suitable for the process development and quality control of polio vaccines. [ABSTRACT FROM AUTHOR]

This study aimed to assess the shifting patterns of the mediastinum, including the target volume and the isocenter point during the postoperative radiotherapy (PORT) process of non-small cell lung cancer (NSCLC), and to observe the occurrence of radiation injury. Additionally, we investigated the significance of mid-term assessment during the implementation of the PORT process. We established coordinate axes based on bone anatomy and measured the mediastinum's three-dimensional direction and the shift of the isocenter point's shift in the PORT process. Statistical analysis was performed using Wilcoxon, Kruskal-Wallis, and the Chi-square test. P < 0.05 was considered statistically significant. In this study, the analysis of patients revealed that the shift of anterior and posterior mediastinum (X), left and right mediastinum (Y), upper and lower mediastinum (Z), anterior and posterior isocenter point (X i), and the left and right isocenter points (Y i) in the PORT process were 0.04–0.53, 0.00–0.84, 0.00–1.27, 0.01–0.86, and 0.00–0.66 cm, respectively. The shift distance of the mediastinum was Z > Y > X, and the shift distance of the isocenter point was X i > Y i. According to the ROC curve, the cut-off values were 0.263, 0.352, 0.405, 0.238, and 0.258, respectively, which were more significant than the cut-off values in 25 cases (25%), 30 cases (30%), 30 cases (30%), 17 cases (17%), and 15 cases (15%). In addition, there was a significant difference in the shift of the mediastinum and the isocenter point (all P = 0.00). Kruskal-Wallis test showed no statistically significant difference between mediastinal shift and resection site in X, Y, and Z directions (P = 0.355, P = 0.239, P = 0.256), surgical method (P = 0.241, P = 0.110, P = 0.064). There was no significant difference in the incidence of RE and RP in PORT patients (P > 0.05). No III–IV RP occurred. However, the incidence of ≥ grade III RE in the modified plan cases after M-S was significantly lower than in the original PORT patients, 0% and 7%, respectively (P = 0.000). In conclusion, this study provides evidence that mediastinal shift is a potential complication during the PORT process for patients with N2 stage or R1–2 resection following radical resection of NSCLC. This shift affects about 20–30% of patients, manifesting as actual radiation damage to normal tissue and reducing the local control rate. Therefore, mid-term repositioning of the PORT and revision of the target volume and radiation therapy plan can aid in maintaining QA and QC during the treatment of NSCLC patients and may result in improved patient outcomes. [ABSTRACT FROM AUTHOR]

Mitochondrial protein import is a fundamental mitochondrial process that can be disrupted by a wide variety of stressors, making it an inclusive readout of overall mitochondrial function. Many mitochondrial quality control (MQC) pathways that maintain overall mitochondrial function monitor the integrity of mitochondrial protein import. Recent work has many revealed novel modulators of mitophagy, mitochondrial-derived vesicles, and the mitochondrial unfolded protein response that sense impaired mitochondrial protein import. Failure of protein import is a mechanistic step that helps trigger MQC responses. Mitochondrial quality control (MQC) mechanisms are required to maintain a functional proteome, which enables mitochondria to perform a myriad of important cellular functions from oxidative phosphorylation to numerous other metabolic pathways. Mitochondrial protein homeostasis begins with the import of over 1000 nuclear-encoded mitochondrial proteins and the synthesis of 13 mitochondrial DNA-encoded proteins. A network of chaperones and proteases helps to fold new proteins and degrade unnecessary, damaged, or misfolded proteins, whereas more extensive damage can be removed by mitochondrial-derived vesicles (MDVs) or mitochondrial autophagy (mitophagy). Here, focusing on mechanisms in mammalian cells, we review the importance of mitochondrial protein import as a sentinel of mitochondrial function that activates multiple MQC mechanisms when impaired. Mitochondrial quality control (MQC) mechanisms are required to maintain a functional proteome, which enables mitochondria to perform a myriad of important cellular functions from oxidative phosphorylation to numerous other metabolic pathways. Mitochondrial protein homeostasis begins with the import of over 1000 nuclear-encoded mitochondrial proteins and the synthesis of 13 mitochondrial DNA-encoded proteins. A network of chaperones and proteases helps to fold new proteins and degrade unnecessary, damaged, or misfolded proteins, whereas more extensive damage can be removed by mitochondria-derived vesicles (MDVs) or mitochondrial autophagy (mitophagy). Here, focusing on mechanisms in mammalian cells, we review the importance of mitochondrial protein import as a sentinel of mitochondrial function that activates multiple MQC mechanisms when impaired. [ABSTRACT FROM AUTHOR]

Over the last few decades, there has been a constant increase in sow litter size, the consequences of which include parturition duration extension, an increase in the percentage of stillborn and hypoxic piglets, and increased variation in piglet birth weight, which reduces their vitality. As such, it seems clear that further increasing sow fertility will generate difficulties and costs in rearing numerous litters with low birth weights. Therefore, the current study aimed to analyze the genetic background of sow hyperprolifcacy using a genome-wide association study (GWAS). The research included 144 sows in the maternal component, divided into two equal groups. The first group (control) consisted of females giving birth to the optimal number of piglets in their third and fourth litters (14–16), while the second group (cases) included those with excessive litter size (>16). The analyzed sows were genotyped using Illumina's PorcineSNP60v2 BeadChip microarray, comprising 64,232 single nucleotide polymorphisms (SNPs). Statistical analysis using R included quality control of genotyping data and GWAS analysis based on five logistic regression models (dominant, codominant, overdominant, recessive, and log-additive) with a single SNP marker as the explanatory variable. On this basis, one SNP (SIRI0000069) was identified on chromosome seven within the EFCAB11 (EF-hand calcium binding domain 11) gene that had a statistically significant effect on sow hyperprolificacy. Additionally, ten SNPs (INRA0007631 , ALGA0011600 , ALGA0043433 , ALGA0043428 , M1GA0010535 ALGA00443338 , ALGA0087116 , MARC0056787 , ALGA0112928 , and ALGA0089047) had a relationship with the analyzed feature at a level close to significance, set at 1−5. These SNPs appear important since they are located on chromosomes on which a large number of quantitative trait loci (QTLs) and SNPs associated with reproductive characteristics, including litter size, have been identified. • Numerous piglets of hyperprolific sows generate additional costs for rearing them. • Sow hyperprolificacy decreases piglets survival rate during and after parturition. • SNP SIRI000069 have significant (p ≤ 0.05) relationship with excessive sow prolificacy. • Within this SNP sows with AA genotype are more likely to give birth to a surplus litter. • EFCAB11 gene is potentially related with litter size in sows. [ABSTRACT FROM AUTHOR]

This paper discusses the challenging issues that reliability practitioners face in conducting destructive tests that lead to completely censored lifetimes, especially in estimating the defect rate of products. Manufacturers need to measure the defect rate for quality control purposes, but obtaining enough defective devices for accurate estimation is not easy when the defect rate is relatively low. To address the issues, a Bayesian approach for estimating the defect rate is proposed in this paper. The proposed method is devised to make up for the heavy computational burdens of the Metropolis-Hastings algorithm. To quantify the uncertainty in the Bayesian estimation, a nonparametric bootstrap technique is employed to construct a credible interval for the defect rate. The performance of the proposed method is evaluated through a variety of Monte Carlo simulation studies. The efficiency of the proposed Bayesian estimation procedure is validated using a real-world dataset of return-springs in DC motor systems under an accelerated destructive degradation test. • Estimate the defect rate of products in conducting destructive tests with completely censored lifetime data. • Propose a computationally efficient Bayesian estimator of an analytical form for the defect rate with masking. • Propose a nonparametric bootstrap technique to construct a credible interval for the defect rate. • The proposed method is validated using accelerated destructive degradation testing data of return-springs. [ABSTRACT FROM AUTHOR]

• Deep sequencing and variant analysis used to assess genetic drift in live, attenuated T1 vaccines. • Drift in some commercial vaccine batches reveals deviations from standard production protocols. • Genome variant analysis proposed as a new tool for T1 vaccine batch quality compliance. Vaccination is the most cost-effective tool to control contagious bovine pleuropneumonia. The vaccines currently used in Africa are derived from a live strain called T1, which was attenuated by passage in embryonated eggs and broth culture. The number of passages is directly correlated to the degree of attenuation of the vaccinal strains and inversely correlated to their immunogenicity in cattle. Current quality control protocols applied to vaccine batches allow the assessment of identity, purity, and titers, but cannot assess the level of genetic drift form the parental vaccine strains. Deep sequencing was used to assess the genetic drift generated over controlled in vitro passages of the parental strain, as well as on commercial vaccine batches. Signatures of cloning procedures were detected in some batches, which imply a deviation from the standard production protocol. Deep sequencing is proposed as a new tool for the identity and stability control of T1 vaccines. [ABSTRACT FROM AUTHOR]

With the purported future of oncological care being precision medicine, the hunt for predictive biomarkers has become a focal point. A potential source lies in radiological imaging, which has motivated the field of radiomics for the last decade [1–4]. Radiomics research, however, has been hampered by inconsistent methodology, despite efforts to establish standard features [5]. The release of the open-source PyRadiomics toolkit [6] was a significant and necessary step to standardize radiomics analysis, but the collation and distribution of publically available radiomics datasets remains poorly organized within the community. As a result, significant overhead remains when dealing with multiple training, testing, and validation datasets from both internal and external sources. Further, a recent study has raised the question of whether radiomic features with high predictive value are surrogates for tumour volume measurements [7]. There is a need for standard methodology for radiomic feature extraction, as well as large, publicly available radiomic datasets that have undergone rigorous processing to benchmark analyses. In this study, we have developed a reproducible, automated, open-source processing pipeline to generate analysis-ready radiomics data. We showcase the pipeline's capabilities by processing and analyzing the largest publicly available head and neck cancer (HNC) dataset, RADCURE [8], and compare three previously published radiomics models [1,7,9] using the resulting data. Data outputs have been made available via https://www.orcestra.ca/, a web-app that hosts processed 'omics data. Our proposed pipeline leverages three main tools: Med-ImageTools [10], PyRadiomics [6], and ORCESTRA [11]. While the former two are imaging-specific, we have modified ORCESTRA to work with clinical radiological data. The proposed pipeline was developed using the RADCURE [12] dataset. It consists of 3,346 HNC CT image volumes, corresponding radiotherapy structure sets (RTSTRUCT) containing primary gross tumour volume (GTVp) contours, and clinical data. The Med-ImageTools library was used to generate complete file lists for each CT acquisition, associate these with the correct RTSTRUCT, and load both as Simple ITK [13] images. For each GTVp, preprocessing, quality checking, and radiomic feature extraction was performed using PyRadiomics. Extraction settings from the RADCURE prognostic modelling challenge [8] were applied. Feature extraction was repeated with two negative control samples for each CT, either by shuffling voxel index values or randomly generating voxel values within the range of values in the original CT [7] (Figure 1). [Display omitted] The standard for data organization on ORCESTRA [11] is the MultiAssayExperiment R object [14], designed to harmonize multiple experimental assays from an overlapping patient set. To leverage this for radiomics, each set of extracted features becomes an experiment, with clinical data included as the primary metadata describing each patient. To demonstrate the pipeline's utility, we replicated previously published survival analysis models with the training and test cohorts from the RADCURE challenge subset [8]. Coefficients from the MW2018 [7] and Kwan [9] models were used to calculate prognostic index values for the test cohort. For comparison, we fit a Cox model to the RADCURE training cohort using the same radiomic signature and applied it to the test cohort. A univariate model for GTVp Mesh Volume was also tested. All models were compared using the concordance index. We processed 2,949 patients with GTVp contours, for a total of 2,988 GTVps from patients with varying primary tumour sites. We extracted 1,317 radiomic features from the CT and the negative control volume for each GTVp. For the 37 patients with multiple GTVps, features were extracted independently for each contour. The final data object containing all of these features, along with the clinical data and PyRadiomics configuration file, are available at https://www.orcestra.ca/radiomicset/10.5281/zenodo.8332910. The pipeline implementation is published at https://github.com/BHKLAB-DataProcessing/RADCUREradiomics. Results from our radiomics analysis are available in Table 1. The subset of 2400 GTVs was split into training and test cohorts based on the 'RADCURE-challenge' label in the clinical data. The Kwan model was tested with the oropharynx patients only. Model performance is similar whether the features were extracted from the CT or negative control samples, signaling that the radiomic signature is likely highly correlated with tumour volume, a known confounder of radiomics analysis. This is confirmed by the comparable performance of the univariable volume model. [Display omitted] This standardized architecture framework and the publicly available processed RADCURE dataset can be used to benchmark new datasets or radiomics models semi-automatically. Future work will include organ at risk and nodal targets in the RADCURE dataset and the production of ORCESTRA objects for other publicly available HNC datasets. We anticipate that this pipeline and the RADCURE objects generated could be a standard testing benchmark for future radiomics analyses and publications. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by dysregulation of the expression and processing of the amyloid precursor protein (APP). Protein quality control systems are dedicated to remove faulty and deleterious proteins to maintain cellular protein homeostasis (proteostasis). Identidying mechanisms underlying APP protein regulation is crucial for understanding AD pathogenesis. However, the factors and associated molecular mechanisms regulating APP protein quality control remain poorly defined. In this study, we show that mutant APP with its mitochondrialtargeting sequence ablated exhibited predominant endoplasmic reticulum (ER) distribution and led to aberrant ER morphology, deficits in locomotor activity, and shortened lifespan. We searched for regulators that could counteract the toxicity caused by the ectopic expression of this mutant APP. Genetic removal of the ribosome-associated quality control (RQC) factor RACK1 resulted in reduced levels of ectopically expressed mutant APP. By contrast, gain of RACK1 function increased mutant APP level. Additionally, overexpression of the ER stress regulator (IRE1) resulted in reduced levels of ectopically expressed mutant APP. Mechanistically, the RQC related ATPase VCP/p97 and the E3 ubiquitin ligase Hrd1 were required for the reduction of mutant APP level by IRE1. These factors also regulated the expression and toxicity of ectopically expressed wild type APP, supporting their relevance to APP biology. Our results reveal functions of RACK1 and IRE1 in regulating the quality control of APP homeostasis and mitigating its pathogenic effects, with implications for the understanding and treatment of AD. [ABSTRACT FROM AUTHOR]

The availability of analytical methods for the characterization of lipid nanoparticles (LNPs) for in-vivo intracellular delivery of nucleic acids is critical for the fast development of innovative RNA therapies. In this study, analytical protocols to measure (i) chemical composition, (ii) drug loading, (iii) particle size, concentration, and stability as well as (iv) structure and morphology were evaluated and compared based on a comprehensive characterization strategy linking key physical and chemical properties to in-vitro efficacy and toxicity. Furthermore, the measurement protocols were assessed either by testing the reproducibility and robustness of the same technique in different laboratories, or by a correlative approach, comparing measurement results of the same attribute with orthogonal techniques. The characterization strategy and the analytical measurements described here will have an important role during formulation development and in determining robust quality attributes ultimately supporting the quality assessment of these innovative RNA therapeutics. [Display omitted] [ABSTRACT FROM AUTHOR]

Burn registers provide important data that can track injury trends and evaluate services. Burn registers are concentrated in high-income countries, but most burn injuries occur in low- and middle-income countries where surveillance data are limited. Injury surveillance guidance recommends utilisation of existing routinely collected data where data quality is adequate, but there is a lack of guidance on how to achieve this. Our aim was to develop a rigorous and reproducible method to establish an electronic burn register from existing routinely collected data that can be implemented in low resource settings. Data quality of handwritten routinely collected records (register books) from a tertiary government hospital burn unit in Mysore, India was assessed prior to digitisation. Process mapping was conducted for burn patient presentations. Register and casualty records were compared to assess the case ascertainment rate. Register books from February 2016 to February 2022 were scanned and anonymised. Scans were quality checked and stored securely. An online data entry form was developed. All data underwent double verification. Process mapping suggested data were reliable, and case ascertainment was 95%. 1930 presentations were recorded in the registers, representing 0.84% of hospital all-cause admissions. 388 pages were scanned with 4.4% requiring rescanning due to quality problems. Two-step verification estimated there to be errors remaining in 0.06% of fields following data entry. We have described, using the example of a newly established electronic register in India, methods to assess the suitability and reliability of existing routinely collected data for surveillance purposes, to digitise handwritten data, and to quantify error during the digitisation process. The methods are likely to be of particular interest to burn units in countries with no active national burns register. We strongly recommend mobilisation of resources for digitisation of existing high quality routinely collected data as an important step towards developing burn surveillance systems in low resource settings. • We detail how to use routinely collected data for a new electronic burn register. • Methods include how to assess data quality, digitise data, and complete verification. • Process mapping should be used to detail potential sources of selection bias. • Two-step verification yielded very low error rates (6 errors in 10,000 fields). • Data presented utilising these methods would adhere to STROBE and RECORD guidance. [ABSTRACT FROM AUTHOR]

The present work proposes a novel method for determining the influence of the machining tolerances on the effective contact area of Hirth joints. The proposed method is based on a general Finite Element Model (FEM) capable to simulate any meshing condition of Hirth joints including positioning and machining tolerances using the Monte Carlo method. The FEM was developed based on an accurate measurement campaign of several Hirth joints which allowed to determine the geometric parameters affecting the meshing and the related ranges of variation. The machining reference surfaces and the sequence of technological processes which produce the Hirth joint starting from a raw disc were identified through contactless measurement techniques. The related machining tolerances were measured by employing a high-precision Coordinate Measuring Machine (CMM). A mean value and a standard deviation were associated with each geometrical parameter of the joint. The proposed method can be used for the preliminary design and the quality check of the Hirth joint. In particular, the Prussian blue test, which represents the typical test used to verify the joint's compliance with the technical specification, was simulated. The results highlight the reduction of the effective contact area of the Hirth joint due to the presence of manufacturing tolerances, which can lead to worse mechanical performances and early failure, and could be used to define the machining tolerances limit of Hirth joints. • The manufacturing tolerances of standard Hirth joints were measured. • Optical and contact-based measuring machines were used. • The geometric parameters relevant for the contact were determined. • A parametric finite element model was used to simulate several contact conditions. • The influence of the manufacturing tolerances on the contact area was quantified. [ABSTRACT FROM AUTHOR]

The paper offers a comprehensive exploration of 3D printing silicon carbide, covering its advantages over traditional manufacturing, potential applications across industries, environmental considerations, and the market's perspective. This holistic approach provides valuable insights into the expanding applications of silicon carbide ceramics and underscores the significance of this technology in various sectors. While 3D printing of silicon carbide offers many advantages, including precision and customization, it also faces several significant challenges related to material properties, process optimization, post-processing, cost, quality control, and environmental considerations. Addressing these challenges is essential for the widespread adoption and success of silicon carbide 3D printing technology across various industries. [ABSTRACT FROM AUTHOR]

The standards within the global steel industry are constantly advancing, necessitating increasingly rigorous quality control protocols during the continuous casting process. Central to the challenges faced in this domain are persistent defects such as central segregation, V-shaped segregation, and center porosity, which significantly impede the production of high-caliber steel products. The discipline of electromagnetic metallurgy has emerged as a critical solution in reducing these defects, thereby enhancing the efficiency and stability of continuous casting operations. Its demonstrated effectiveness has led to its widespread implementation across global and domestic steel production industries. This paper aims to deliver a comprehensive examination of electromagnetic metallurgy's impact on the final stages of solidification in continuous casting, along with its contributions to the heating and purification processes within the tundish. Additionally, it will explore the potential advancements and applications of this technology in the evolving sphere of continuous casting. [ABSTRACT FROM AUTHOR]

During B cell development, pre-B cell receptor (pre-BCR), comprising the immunoglobulin heavy chain (HC) and surrogate light chain (SLC), plays a crucial role. The expression of pre-BCR serves as a certification of HC quality, confirming its ability to associate with the SLC and light chain (LC). In mice lacking SLC, the absence of this quality control mechanism leads to a distorted repertoire of HCs in the spleen and bone marrow. In this study, we conducted a comparative analysis of the immunoglobulin gene repertoire in peripheral blood cells of both wild-type mice and pre-BCR–deficient mice. Our findings reveal differences not only in the μ HC repertoire but also in the α HC and κ LC repertoires of the pre-BCR–deficient mice. These results suggest that the pre-BCR–mediated quality check of HC influences the selection of class-switched HC and LC repertoires. To further explore the impact of pre-BCR deficiency, we immunized these mice with thymus-dependent antigens and compared the antigen-responding repertoires. Our observations indicate that the affinity maturation pathways remain consistent between wild-type mice and pre-BCR–deficient mice, albeit with variations in the degree of maturation. • Antibody repertoires of peripheral blood of pre-BCR–deficient mice were analyzed. • Lack of pre-BCR distorts heavy and light chain repertoires. • Affinity maturation proceeds along the same pathways but to a different degree. [ABSTRACT FROM AUTHOR]

Quality control testing and analytics are critical for the development and manufacture of cell and gene therapies, and flow cytometry is a key quality control and analytical assay that is used extensively. However, the technical scope of characterization assays and safety assays must keep apace as the breadth of cell therapy products continues to expand beyond hematopoietic stem cell products into producing novel adoptive immune therapies and gene therapy products. Flow cytometry services are uniquely positioned to support the evolving needs of cell therapy facilities, as access to flow cytometers, new antibody clones and improved fluorochrome reagents becomes more egalitarian. This report will outline the features, logistics, limitations and the current state of flow cytometry within the context of cellular therapy. [ABSTRACT FROM AUTHOR]

Contamination is one major contributor to the degradation of proton exchange membrane (PEM) fuel cell performance and lifetime. Aiming to evaluate the tolerance of PEM doped with radical scavenger additives to metal ions contamination, iron (Fe) ion was selected in this work as a representative of impurities that could come from current metal bipolar plates and directly introduced into the membrane. It has been found that the membrane additives could not only provide durability benefits but also enhance Fe3+ contamination tolerance without any performance loss. These scientific findings provide valuable guidelines for membrane developers and PEM fuel cell manufacturers on quality control (QC) considerations during the production of fuel cell components. The composite PEM with additives can improve durability as well as enhance Fe3+ contamination tolerance without performance loss. [Display omitted] • Study of effects of Fe3+ in membranes on PEMFC performance and durability. • Negative effect of Fe3+ on the cell performance at the beginning of cell activation. • Additives in PEM enhanced Fe3+ contamination tolerance. [ABSTRACT FROM AUTHOR]

Analysis of circulating cell-free DNA (ccfDNA) isolated from liquid biopsies is rapidly being implemented into clinical practice. However, diagnostic accuracy is significantly impacted by sample quality and standardised approaches for assessing the quality of ccfDNA are not yet established. In this study we evaluated the application of nucleic acid "spike-in" control materials to aid quality control (QC) and standardisation of cfDNA isolation for use in in vitro diagnostic assays. We describe an approach for the design and characterisation of in-process QC materials, illustrating it with a spike-in material containing an exogenous Arabidopsis sequence and DNA fragments approximating to ccfDNA and genomic DNA lengths. Protocols for inclusion of the spike-in material in plasma ccfDNA extraction and quantification of its recovery by digital PCR (dPCR) were assessed for their suitability for process QC in an inter-laboratory study between five expert laboratories, using a range of blood collection devices and ccfDNA extraction methods. The results successfully demonstrated that spiking plasmid-derived material into plasma did not deleteriously interfere with endogenous ccfDNA recovery. The approach performed consistently across a range of commonly-used extraction protocols and was able to highlight differences in efficiency and variability between the methods, with the dPCR quantification assay performing with good repeatability (generally CV <5%). We conclude that initial findings demonstrate that this approach appears "fit for purpose" and spike-in recovery can be combined with other extraction QC metrics for monitoring the performance of a process over time, or in the context of external quality assessment. [Display omitted] • Circulating cell-free DNA (ccfDNA) extraction is a key step in liquid biopsy tests. • Role of DNA spike-in for ccfDNA extraction QC evaluated in interlaboratory study. • Digital PCR measured recovery of spike-in with high precision. • Spike-in recovery reflected performance and correlated with alternative QC metrics. • Study demonstrates utility of DNA spike-in within a suite of ccfDNA QC approaches. [ABSTRACT FROM AUTHOR]

Protein folding, quality control, maturation, and trafficking are essential processes for proper cellular homeostasis. Around one-third of the human proteome is targeted to the endoplasmic reticulum (ER), the organelle that serves as entrance into the secretory pathway. Successful protein trafficking is paramount for proper cellular function and to that end there are many ER resident proteins that ensure efficient secretion. Here, biochemical and cell biological analysis was used to determine that TTC17 is a large, soluble, ER-localized protein that plays an important role in secretory trafficking. Transcriptional analysis identified the predominantly expressed protein isoform of TTC17 in various cell lines. Further, TTC17 localizes to the ER and interacts with a wide variety of chaperones and cochaperones normally associated with ER protein folding, quality control, and maturation processes. TTC17 was found to be significantly upregulated by ER stress and through the creation and use of TTC17-/- cell lines, quantitative mass spectrometry identified secretory pathway wide trafficking defects in the absence of TTC17. Notably, trafficking of insulinlike growth factor type 1 receptor, glycoprotein nonmetastatic melanoma protein B, clusterin, and UDP-glucose:glycoprotein glucosyltransferase 1 were significantly altered in H4 neuroglioma cells. This study defines a novel ER trafficking factor and provides insight into the protein-protein assisted trafficking in the early secretory pathway. [ABSTRACT FROM AUTHOR]

Preexposure to mild stress often improves cellular tolerance to subsequent severe stress. Severe ethanol stress (10% v/v) causes persistent and pronounced translation repression in Saccharomyces cerevisiae. However, it remains unclear whether preexposure to mild stress can mitigate translation repression in yeast cells under severe ethanol stress. We found that the translational activity of yeast cells pretreated with 6% (v/v) ethanol was initially significantly repressed under subsequent 10% ethanol but was then gradually restored even under severe ethanol stress. We also found that 10% ethanol caused the aggregation of Ded1, which plays a key role in translation initiation as a DEAD-box RNA helicase. Pretreatment with 6% ethanol led to the gradual disaggregation of Ded1 under subsequent 10% ethanol treatment in wild-type cells but not in fes1Δhsp104Δ cells, which are deficient in Hsp104 with significantly reduced capacity for Hsp70. Hsp104 and Hsp70 are key components of the bi-chaperone system that play a role in yeast protein quality control. fes1Δhsp104Δ cells did not restore translational activity under 10% ethanol, even after pretreatment with 6% ethanol. These results indicate that the regeneration of Ded1 through the bi-chaperone system leads to the gradual restoration of translational activity under continuous severe stress. This study provides new insights into the acquired tolerance of yeast cells to severe ethanol stress and the resilience of their translational activity. [ABSTRACT FROM AUTHOR]

In recent years, the food industry has faced a number of complex challenges related to both quality control and sustainability. Ensuring consumer safety and satisfaction remains a cornerstone of the food industry, supported by stringent standards that address the risks of contamination and spoilage. However, variability in raw materials, processing techniques and storage conditions are just some of the factors that affect quality in the food industry. To manage this high variability, it is essential to analyse the production process and factors that most influence food quality, aiming to predict and minimise food waste, thereby ensuring a sustainable process. This convergence of quality control and sustainability goals provides fertile ground for machine learning applications. By improving defect detection, process optimisation, resource allocation and predictive maintenance, these models help to improve product quality and reduce environmental impact. This article aims to explore the various applications of machine learning models in the food industry, where the variability of raw materials and the difficulty of controlling production and environmental factors challenge the use of traditional methods. The quality control and sustainability of an industrial corn cakes production process is used as a case study. [ABSTRACT FROM AUTHOR]

Mitochondrial dysfunction is implied as a crucial factor in age-related chronic kidney disease. It is confirmed that Gli-like transcription factor 1 (GLIS1) is involved in age-related renal fibrosis, however, the correlation between mitochondrial disturbances and GLIS1-driven kidney aging are not clearly clarified. Thus, we investigated the regulatory mechanism of GLIS1 in the homeostasis of mitochondrial quality control both in vivo and in vitro. The lower expression of GLIS1 was identified in natural and accelerated kidney aged models, accompanied by the dysfunctions of mitochondrial quality control, including enhanced mitochondrial fission, reduced mitochondrial biogenesis and mitophagy, whereas, GLIS1 could maintain mitochondrial stability by interacting with peroxisome proliferator-activated receptor γ coactivator-1α (PGC1-α). Additionally, the over-expressed GLIS1 inhibited extracellular matrix accumulation and alleviated renal fibrosis while siGLIS1 inhibited PGC1-α transcription, as well as affecting its mitochondria-protective functions. Collectively, we demonstrated that GLIS1 mediated mitochondrial quality control through targeting PGC1-α in kidney aging, which might be a promising therapeutic target for attenuating cell senescence and age-related renal fibrosis. [Display omitted] • Mitochondrial homeostasis was impaired in kidney aging. • GLIS1 maintained the mitochondrial homeostasis by targeting PGC-1α in kidney aging. • PGC-1α functionally maintain mitochondrial homeostasis. [ABSTRACT FROM AUTHOR]

Yeastolate is often used as a media supplement in industrial mammalian cell culture or as a major media component for microbial fermentations. Yeastolate variability can significantly affect process performance, but analysis is technically challenging because of its compositional complexity. However, what may be adequate for manufacturing purposes is a fast, inexpensive screening method to identify molecular variance and provide sufficient information for quality control purposes, without characterizing all the molecular components. Here we used Size Exclusion Chromatography (SEC) and chemometrics as a relatively fast screening method for identifying lot-to-lot variance (with Principal Component Analysis, PCA) and investigated if Partial Least Squares, PLS, predictive models which correlated SEC data with process titer could be obtained. SEC provided a relatively fast measure of gross molecular size hydrolysate variability with minimal sample preparation and relatively simple data analysis. The sample set comprised of 18 samples from 12 unique source lots of an ultra-filtered yeastolate (10 kDa molecular weight cut-off) used in a mammalian cell culture process. SEC showed significant lot-to-lot variation, at 214 and 280 nm detection, with the most significant variation, that correlated with process performance, occurring at a retention time of ∼6 min. PCA and PLS regression correlation models provided fast identification of yeastolate variance and its process impact. The primary drawback is the limited column lifetime (<300 injections) caused by the complex nature of yeastolate and the presence of zinc. This limited long term reproducibility because these age-related, non-linear changes in chromatogram peak positions and shapes were very significant. • Shows how to use Size Exclusion Chromatography (SEC) for screening lot-to-lot hydrolysate variance. • Uses Multivariate Data Analysis to correlate variance with process performance. • Identifies the critical limitation for method implementation. [ABSTRACT FROM AUTHOR]

Endoplasmic reticulum (ER)-associated degradation (ERAD) is a protein quality control process that eliminates misfolded proteins from the ER. DnaJ homolog subfamily C member 10 (ERdj5) is a protein disulfide isomerase family member that accelerates ERAD by reducing disulfide bonds of aberrant proteins with the help of an ER-resident chaperone BiP. However, the detailed mechanisms by which ERdj5 acts in concert with BiP are poorly understood. In this study, we reconstituted an in vitro system that monitors ERdj5-mediated reduction of disulfide-linked J-chain oligomers, known to be physiological ERAD substrates. Biochemical analyses using purified proteins revealed that J-chain oligomers were reduced to monomers by ERdj5 in a stepwise manner via trimeric and dimeric intermediates, and BiP synergistically enhanced this action in an ATP-dependent manner. Single-molecule observations of ERdj5-catalyzed J-chain disaggregation using highspeed atomic force microscopy, demonstrated the stochastic release of small J-chain oligomers through repeated actions of ERdj5 on peripheral and flexible regions of large J-chain aggregates. Using systematic mutational analyses, ERAD substrate disaggregation mediated by ERdj5 and BiP was dissected at the molecular level. [ABSTRACT FROM AUTHOR]

In this work, concentration prediction models applicable to a very wide range of concentrations for personalized tablet manufacturing were developed using near-infrared (NIR) spectroscopy. Tablet manufacturing experiments were conducted, and NIR spectral data of the tablets were obtained. To search for an appropriate development method for the prediction models applicable to a very wide range of concentrations, three typical active pharmaceutical ingredients (APIs) were selected and two modeling methods were applied, namely, partial least squares (PLS) regression and extreme g radient boosting (XGBoost). The prediction models developed using the two methods were evaluated according to widely used criteria. The results showed that the model accuracy obtained using PLS regression was higher than that obtained using XGBoost. The modeling method using PLS regression was also applied to other typical APIs and inorganic compounds. These results indicate that the model accuracy was affected by the heat resistance of the compound. In addition, this modeling method could be useful in developing prediction models for ion-binding inorganic compounds and in suggesting the presence of metallic foreign matter in tablets. [Display omitted] ● Concentration prediction models for tablets were developed using NIR spectroscopy. ● Tablet manufacturing experiments were performed to collect the NIR spectral data. ● Two modeling methods were applied to the prediction model development. ● Model accuracy using PLS regression was higher than that using XGBoost. ● PLS-based approach could be useful for detecting metallic foreign matter in tablets. [ABSTRACT FROM AUTHOR]

Involved node radiation therapy (INRT) was introduced in the European Organisation for Research and Treatment of Cancer/Lymphoma Study Association/Fondazione Italiana Linfomi H10 trial, a large multicenter trial in early-stage Hodgkin Lymphoma. The present study aimed to evaluate the quality of INRT in this trial. A retrospective, descriptive study was initiated to evaluate INRT in a representative sample encompassing approximately 10% of all irradiated patients in the H10 trial. Sampling was stratified by academic group, year of treatment, size of the treatment center, and treatment arm, and it was done proportional to the size of the strata. The sample was completed for all patients with known recurrences to enable future research on relapse patterns. Radiation therapy principle, target volume delineation and coverage, and applied technique and dose were evaluated using the EORTC Radiation Therapy Quality Assurance platform. Each case was reviewed by 2 reviewers and, in case of disagreement also by an adjudicator for a consensus evaluation. Data were retrieved for 66 of 1294 irradiated patients (5.1%). Data collection and analysis were hampered more than anticipated by changes in archiving of diagnostic imaging and treatment planning systems during the running period of the trial. A review could be performed on 61 patients. The INRT principle was applied in 86.6%. Overall, 88.5% of cases were treated according to protocol. Unacceptable variations were predominately due to geographic misses of the target volume delineations. The rate of unacceptable variations decreased during trial recruitment. The principle of INRT was applied in most of the reviewed patients. Almost 90% of the evaluated patients were treated according to the protocol. The present results should, however, be interpreted with caution because the number of patients evaluated was limited. Individual case reviews should be done in a prospective fashion in future trials. Radiation therapy Quality Assurance tailored to the clinical trial objectives is strongly recommended. [ABSTRACT FROM AUTHOR]

A high-quality and widely accepted UK EQ-5D-5L value set is urgently required to enable the latest version of EQ-5D scored using recent UK public preferences to inform policy including health technology assessments submitted to the National Institute for Health and Care Excellence. This article outlines the study protocol for the generation of a new EQ-5D-5L UK value set. Twelve hundred interviews will be undertaken using the composite time trade-off elicitation technique for 102 health states (86 from the international EQ-5D-5L valuation protocol, plus 16 with best predictive performance in an extended design used in the Native American EQ-5D-5L valuation). The sample will be UK adults (age ≥18 years) proportionately representative across England, Wales, Scotland, and Northern Ireland, representative for age, sex, ethnicity, and socioeconomic group, with inclusion of participants with/without health problems. Participants will choose to be interviewed via videoconference (by Zoom) or in-person in a central venue. Data quality will be rigorously assessed. The value set will be generated using tobit random effects and heteroscedastic tobit models (with censoring at −1) using all data, excluding time trade-off values highlighted by participants as ones they would reconsider and data from interviewers failing protocol compliance. Quality and acceptance will be achieved by public involvement, regular Steering Group meetings, independent assessment of data quality at 4 time points, and final endorsement of data and analyses. This study will produce a UK value set for the EQ-5D-5L for use in prospective and retrospective data sets containing EQ-5D-5L data. • The existing EQ-5D-5L value set for England was not accepted for use by the National Institute for Health and Care Excellence (NICE) because of concerns raised during independent quality assurance. This new study has been designed to resolve previous issues of concern with the quality and reliability of collected data and analysis methods, with involvement of NICE and policy partners (National Health Service England, Department of Health and Social Care) throughout study design and study conduct. • The project protocol and statistical analysis plan has been reviewed and approved by the Steering Group and independent Quality Control team. The study design has been informed by the international EQ-5D-5L valuation protocol that has been successfully used in 27 studies worldwide, but deviates from this for health state selection and choice of elicitation technique in response to concerns raised by experts on behalf of NICE. • The study benefits from regular Steering Group meetings that consist of representatives from NICE and policy partners, as well as international experts, EuroQol members, and scientific leaders; public involvement via the NICE public involvement program; independent assessment of data quality at 4 time points by a Quality Control team; and final endorsement of data and analyses by the Quality Control team and Steering Group. [ABSTRACT FROM AUTHOR]

Although there are several studies comparing organic and conventional milk characteristics, very few focused on dairy processed products such as cheese. Thus, this study aimed for a detailed controlled examination of gross composition, minerals, and the fatty acid profile of organic (ORG) and conventional (CON) Italian cheeses from parallel production. Four Italian cheese types were analyzed: Latteria (ORG, n = 9; CON, n = 10); Asiago Protected Designation of Origin (PDO) fresco (ORG, n = 9; CON, n = 9); Caciotta (ORG, n = 8; CON, n = 8); and Mozzarella Traditional Specialty Guaranteed (TSG; ORG, n = 14; CON, n = 14). Cheese samples were collected from September 2020 to August 2021. Gross composition, minerals, and fatty acids were determined using infrared spectroscopy. Within each cheese type, paired ORG and CON samples were compared using a nonparametric Wilcoxon signed-rank test. Latteria showed lower PUFA, n-3, and n-6 content, and greater Fe, K, C10:0, C12:0, and C16:0 content in ORG than in CON. Asiago PDO fresco showed lower protein and Zn content and greater salt, ash, and Na content in ORG than in CON. Caciotta showed lower ash, n-3, and n-6 content and greater K, C4:0, C8:0, C10:0, C14:0, and C16:0 content in ORG than in CON. Mozzarella TSG showed lower fat and, therefore, fatty acid content, and greater moisture, ash, and Mg content in ORG than in CON. In conclusion, few significant differences in chemical composition were observed between ORG and CON cheeses, regardless of the type considered. Moreover, Asiago PDO fresco showed fewer significant differences between ORG and CON compared with Latteria, Caciotta, and Mozzarella TSG. [ABSTRACT FROM AUTHOR]

In the last few years, subways have rapidly spread in many countries and have replaced different modes of commuting in some important areas. Despite the fact that passengers only spend a short time in the subway, pollution in the subway is devastating to human health and can cause various diseases, including respiratory diseases. With the development of artificial intelligence (AI), more and more scholars are keen to use this technology to predict and monitor pollution focuses, which in turn can screen the air quality in subways. This paper reviews the application of AI in prediction and control of indoor air quality (IAQ) in subways during 2010–2022. The results show that most of the prediction studies analyzed were conducted for PM 10 and PM 2.5 , and most of the control studies were conducted to optimize the subway ventilation system. Fewer studies have been conducted on the prediction of other air pollutants and on IAQ control facilities. This study attempts to provide guidelines for future AI to manage IAQ in subways. [ABSTRACT FROM AUTHOR]

Mitochondrial quality control (MQC) plays a crucial role in maintaining mitochondrial health. Mitochondrial dynamics and mitophagy are two intricate processes of the MQC machinery acting at the organelle level to orchestrate mitochondrial homeostasis. Here, we discuss how viruses perturb these two processes to facilitate their infections and emphasize the rationale and challenges of therapeutically targeting MQC for treating viral diseases. [ABSTRACT FROM AUTHOR]

[Display omitted] Multi-attribute methods employing mass spectrometry are applied throughout the biopharmaceutical industry for product and process characterization purposes but are not yet widely accepted as a method for batch release and stability testing under the good manufacturing practice (GMP) regime, due to limited experience and level of comfort with the technical, compliance and regulatory aspects of its implementation at quality control (QC) laboratories. This article is the second part of a two-tiered publication aiming at providing guidance for implementation of the multi-attribute method by peptide mapping liquid chromatography mass spectrometry (MAM) in a QC laboratory. The first part [1] focuses on technical considerations, while this second part provides considerations related to GMP compliance and regulatory aspects. This publication has been prepared by a group of industry experts representing 14 globally acting major biotechnology companies under the umbrella of the European Federation of Pharmaceutical Industries and Associations (EFPIA) Manufacturing & Quality Expert Group (MQEG). [ABSTRACT FROM AUTHOR]

Metabolomics holds great promise for uncovering insights around biological processes impacting disease in human epidemiological studies. Metabolites can be measured across biological samples, including plasma, serum, saliva, urine, stool, and whole organs and tissues, offering a means to characterize metabolic processes relevant to disease etiology and traits of interest. Metabolomic epidemiology studies face unique challenges, such as identifying metabolites from targeted and untargeted assays, defining standards for quality control, harmonizing results across platforms that often capture different metabolites, and developing statistical methods for high-dimensional and correlated metabolomic data. In this review, we introduce metabolomic epidemiology to the broader scientific community, discuss opportunities and challenges presented by these studies, and highlight emerging innovations that hold promise to uncover new biological insights. The rapidly emerging field of metabolomic epidemiology presents unique opportunities to gain mechanistic insights into disease risk and identify biomarkers that may inform prevention and screening strategies. Challenges include dealing with batch effects and drift, the sensitivity of metabolites to environmental exposures and the handling and processing of samples, metabolite identification, harmonizing metabolites across different platforms, analyzing high-dimensional data, the complex correlation structure of metabolites, and integrating metabolomics with other 'omic data types. We provide a broad introduction to the field for scientists from cross-disciplinary backgrounds, discussing technological, study design, quality control, and statistical considerations, opportunities and challenges in the field, and emerging innovations that hold promise to uncover new biological insights. [ABSTRACT FROM AUTHOR]

Damaged lysosomes are replaced, removed, and/or repaired by lysosomal quality control pathways. Lysosomal stress stimulates transcription factor EB (TFEB)/TFE3-mediated transcriptional upregulation of lysosomal biogenesis and exocytosis. Lysophagy degrades damaged lysosomes as a whole, whereas microautophagy degrades selective lysosomal membrane proteins. The endosomal sorting complex required for transport (ESCRT) machineries repair small lysosomal membrane pores by direct membrane sealing. The phosphoinositide-initiated membrane tethering and lipid transport (PITT) pathway repairs damaged lysosomes through direct lipid transfer at endoplasmic reticulum–lysosome membrane contact sites. Often deregulated in aging and diseases, lysosomal quality control pathways provide promising therapeutic targets for lysosomal related diseases, aging, infectious diseases, and cancer. Lysosomes are essential catabolic organelles with an acidic lumen and dozens of hydrolytic enzymes. The detrimental consequences of lysosomal leakage have been well known since lysosomes were discovered during the 1950s. However, detailed knowledge of lysosomal quality control mechanisms has only emerged relatively recently. It is now clear that lysosomal leakage triggers multiple lysosomal quality control pathways that replace, remove, or directly repair damaged lysosomes. Here, we review how lysosomal damage is sensed and resolved in mammalian cells, with a focus on the molecular mechanisms underlying different lysosomal quality control pathways. We also discuss the clinical implications and therapeutic potential of these pathways. [ABSTRACT FROM AUTHOR]

There are several studies that show high defect rates of transducers in clinical use. The purpose of the present study was to investigate whether image quality and the risk for misdiagnosis is affected by using defective transducers. Four defective transducers with varying degrees of defect severity, still in clinical use, were selected. Forty artifact-affected clinical images from each transducer were compared with images acquired from fully functional transducers, of the same model, in an observer study where four experienced radiologists rated each of the 320 images. The rating tasks included if the artifacts were detectable, if the possible artifacts might affect the diagnosis, how well structural details were reproduced and, finally, an assessment of overall image quality. The artifacts in the images were detectable for three of the four transducers (p < 0.05), and in 121 of 640 assessments of the images from the defective transducers the observers were confident that the artifacts could affect the diagnosis. All four faulty transducers were assessed to have decreased ability to resolve structural details (p < 0.05), and three of the four transducers were assessed to have worse overall image quality (p < 0.05). The present study shows that image quality and the risk of misdiagnosis can be affected by using defective transducers. This highlights the importance of frequent quality control of the transducers to avoid decreased image quality and even misdiagnosis. [ABSTRACT FROM AUTHOR]

Protein quality control (PQC) mechanisms are essential for degradation of misfolded or dysfunctional proteins. An essential part of protein homeostasis is recognition of defective proteins by PQC components and their elimination by the ubiquitin–proteasome system, often concentrating on protein termini as indicators of protein integrity. Changes in amino acid composition of C-terminal ends arise through protein disintegration, alternative splicing, or during the translation step of protein synthesis from premature termination or translational stop-codon read-through. We characterized reporter protein stability using light-controlled exposure of the random C-terminal peptide collection (CtPC) in budding yeast revealing stabilizing and destabilizing features of amino acids at positions −5 to −1 of the C terminus. The (de)stabilization properties of CtPC-degrons depend on amino acid identity, position, as well as composition of the C-terminal sequence and are transferable. Evolutionary pressure toward stable proteins in yeast is evidenced by amino acid residues underrepresented in cytosolic and nuclear proteins at corresponding C-terminal positions, but over-represented in unstable CtPC-degrons, and vice versa. Furthermore, analysis of translational stop-codon read-through peptides suggested that such extended proteins have destabilizing C termini. PQC pathways targeting CtPC-degrons involved the ubiquitin–protein ligase Doa10 and the cullin–RING E3 ligase SCFDas1 (Skp1–Cullin–Fbox protein). Overall, our data suggest a proteome protection mechanism that targets proteins with unnatural C termini by recognizing a surprisingly large number of C-terminal sequence variants. [ABSTRACT FROM AUTHOR]

Quality control in longitudinal cohort studies is critical for valid epidemiologic inference. Conditional studentized residuals (CSRs) derived from linear mixed effects models offer efficient individual-specific quality control. We present the utility of CSRs for outlier detection in an applied example using data from the Chronic Kidney Disease in Children cohort. Longitudinal linear mixed effects models with glomerular filtration rate (GFR) as the outcome were fit for observations prior to kidney replacement therapy, stratified by nonglomerular or glomerular diagnosis, and for a subset after receiving a kidney transplant. For each model, CSRs were calculated and values ≥±5 were considered potential outliers for further investigation. A total of 1096 participants contributed 6881 annual measures of GFR across the two diagnostic groups and after transplant. In all models, the fixed effects captured progressive GFR decline. CSRs provided measures of individual-level deviations from the modeled trajectories (random + fixed effects) and were easily visualized in longitudinal plots. A total of 38 potential outliers from 32 participants were detected and further investigated for quality control. This example demonstrated how longitudinal models can provide CSRs to detect individual-specific outliers. CSRs should be considered as part of quality control for longitudinal epidemiologic studies. [ABSTRACT FROM AUTHOR]

Since December 2019, global batch recalls of metformin pharmaceutical products have highlighted an urgent need to control N -nitrosodimethylamine (NDMA) contamination to demonstrate patient safety and maintain supply of this essential medicine. Due to their formulation, the metformin extended-release products present difficult analytical challenges for conventional sample preparation procedures, such as artefactual (in-situ) NDMA formation, gelling, and precipitation. To overcome these challenges, a new version of dispersive liquid-liquid microextraction (DLLME) termed dispersant-first DLLME (DF-DLLME) was developed and optimized for the analysis of NDMA in metformin extended-release products using a detailed Design of Experiments (DoE) to optimize sample preparation. Gas chromatography-high resolution accurate mass-mass spectrometry (GC-HRAM-MS) combined with automated DF-DLLME were successfully applied to monitor the NDMA levels of two different metformin extended-release AstraZeneca products to ultra-trace levels (parts per billion). The additional benefits associated with DF-DLLME, which include automation, time/costs saving, and greener sample preparation, make this novel technique easier to transfer from a development to Quality Control (QC) environment. In addition, this also offers an attractive candidate for the wider platform analysis of N -nitrosamines in pharmaceutical drug products. [ABSTRACT FROM AUTHOR]

Quality control is a critical aspect in today's fast-paced and competitive business landscape. The increasing digital transformation of manufacturing companies allows for the implementation of even proactive quality control strategies. This, however, requires the proper integration and analysis of shop floor data, regarding monitoring, diagnosis, and prognostics. This is to support defect recognition and recuperation, along with potential system reconfiguration based on knowledge extraction and human experience integration. Digital twins, being virtual replicas of physical assets, support real-time monitoring, analysis, and optimization. However, quality-related aspects may not be related to monitored parameters, thus solely data-driven models may not be accurate enough for proactive quality control. In this work, a hybrid digital twin is proposed, where data-driven models are used to finetune the behaviour of the digital twin based on its physics model. A use case concerning an industrial asset and the heat transfer to a steel bar is investigated with the results presented and commented on. [ABSTRACT FROM AUTHOR]

Anomalous Sound Detection by Deep Learning could be used to automatically detect malfunctions in mechanical products from their operating sounds. With many normal sounds but very few anomalous sounds available for training, one-class classification methods applied to sound spectrograms are the most suitable methods. Among them, the Masked Autoencoder for Distribution Estimation (MADE) method showed state-of-the-art results with transient anomalous sounds but poor results with sustained anomalous sounds. The loss of the spectro-temporal structure in the inputs possibly explaining this issue, we have modified a method recently designed for 2D image completion, taking advantage of the full spectro-temporal structure of the inputs. When evaluated on industrial data, this new method outperforms a baseline Autoencoder method and the original MADE method. [ABSTRACT FROM AUTHOR]

Ensuring high product quality is crucial in modern industry, as low-quality products can lead to negative consequences like financial losses, resource wastage, and harm to a company's reputation. Although in high volume production advanced inspection technologies are in place, small and medium-sized enterprises (SMEs) still often rely only on manual visual inspection by human operators to identify defective or improperly assembled products resulting in long cycle times, high error rates, and increased costs. To address mentioned issues, recently advanced automated optical inspection systems (AOIs) have been developed that employ Convolutional Neural Networks (CNN) such as YOLO (You Only Look Once). While YOLO has been effectively applied to identify defects across a range of industrial uses, the potential of YOLOv8 for real-time detection of correct and incorrect assembly in automated production lines lacks research. The research presented here aimed to develop an automated optical inspection system using a camera and a CNN-based model, Yolov8, to ensure the product quality of the assembled parts in real-time. Three algorithms were developed using Python, RT Toolbox 2, and TIA Portal v17 to facilitate communication between the developed model, robot, and PLC as well as assembly and carry out quality control processes. The system's performance was evaluated through three sets of experiments, each consisting of 50 instances. The collected data were then evaluated by means of statistical analysis methods. The study's results revealed that Yolov8 with AOIs resulted in a high accuracy as well as macro and micro recall, precision and F1-Score of 98%. Moreover, this low-cost and real-time approach holds significant potential for adoption in SMEs' production lines for inspecting parts. [ABSTRACT FROM AUTHOR]

In today's VUCA-defined age, accelerated by the rapid digital transformation brought on by the COVID-19 pandemic, the business sector needs to be able to adapt to expected and unexpected changes. Consistently improving the product quality and managing the whole product life cycle, starting from the new product development (NPD) process, and the related data, are important aspects of keeping a company competitive in a global landscape. This paper highlights the growing potential of Industry 4.0, particularly the digital thread (DTH) and digital twin (DT), in addressing these challenges. The research revealed existing gaps in clarity and practical guidelines for digital twin prototypes (DTP) and DTH in the existing literature. Moreover, additional issues within product life cycle management (PLM) were stated, regarding frequent data loss and the complexity of product audits in the perspective of a continuous improvement. Therefore, a definition and novel framework for DTP and DTH implementation was proposed, after analyzing and comparing state of the art literature. This framework is additionally based on product audits carried out during the design stage of the product development process using requirements engineering and quality control information added within the suggested framework. Preliminary tests with DTP and DTH commercial off-the-shelves and prototype solutions were carried out with a consumer product. The tests enabled delivering a better understanding of DTPs, their potential, and their implications for decision-making and implementation. [ABSTRACT FROM AUTHOR]

Quality constitutes the cutting-edge of contemporary industry, much more sharpened with the emergence of Industry 4.0. Yet, the assurance of delivering high-quality products remains a challenging problem that requires cautious controls and timely actions through the entire phases of the production cycle. To that end, zero-defect manufacturing (ZDM) has given prominence to a comprehensive methodology that ensures quality control and defects eradication at every phase of the procedure, prioritizing the continuous supervision of each distinctive component to satisfy the corresponding quality assurance standards. Continuous supervision and detection of possible flaws are subjective to exploiting high-tech sensors for high-precision monitoring and assessment. Considering the above, adopting active vision technology can further enhance the promising capabilities of ZDM. The paper highlights the active vision's benefits to the ZDM strategy and introduces a practical framework for applying such technology through the different stages. Innovations and challenges that have to be taken into consideration are also discussed. [ABSTRACT FROM AUTHOR]

The aim of this research is to explore the potential of Mixed Reality (MR) technologies for Operator Support in order to progress towards Industry 4.0 (I4.0) particularly for SMEs. Through a series of interventions and interviews conducted with local SMEs, potential use cases and their drawbacks have been identified. From this, insights were derived that serve as a starting point for conducting further experiments with MR technology in the smart manufacturing laboratory at the THUAS in Delft. The intervention consisted of a free form workshop in which the participants get 'tinkering' time to explore MR in their own work environment. The various levels of awareness were assessed in three stages: during an introductory interview, and after an instruction meeting and some 'tinkering'. The study took place in the period from January 2022 to July 2022 with 10 local SMEs in the Netherlands. The results show that for all SMEs the awareness and understanding increased. The use cases identified by operators themselves concerned Quality Control, Diagnostics, Instruction, Specification and Improvement of Operations. Drawbacks foreseen related to Ergonomic Concerns, Resistance from operators, Technical considerations, Unavailability of MR device and an insufficient digital infrastructure to support MR in full extent. The use case most promising to the participants was further developed into a physical prototype for an 'assisted assembly cell' by which the aspects of ergonomics and the mentioned technical considerations could be analysed. [ABSTRACT FROM AUTHOR]

No system is perfect or free of errors. For companies to reach zero defects in a highly volatile and uncertain environment, emerging technologies, as well as human involvement, are needed. The tenant is to measurement-assist the manufacturing system to predict and prevent deviations in dynamic conditions. This article reviews the Measurement-assisted manufacturing (MAM) literature with the aim to (i) reveal key technologies and processes for MAM, (ii) identify current practices and their weaknesses, and (iii) propose future directions. Results show that despite MAM and Zero-Defect Manufacturing (ZDM) being treated separately, they are deeply interrelated and combining both strategies can lead to true sustainability. The literature indicated that future work must be placed in 'hardware' as instrument operation and equipment maintenance, and 'software', as data analytics and geometry assurance strategies. [ABSTRACT FROM AUTHOR]

Aesthetic quality control (AQC) is an essential step in smart factories to ensure that product quality meets the desired standards. This operation includes assessing factors such as color, texture, and shape. In the context of AQC, bias can arise when the criteria used to evaluate the aesthetics of a product are subjective and influenced by personal preferences. Bias can also occur due to the background or other objective factors like the geometry of the material. This work will focus on applying an adversarial learning strategy to a pre-trained DL architecture for improving the generalization performance of a predictive model tailored explicitly for solving AQC task classification. Experimental results on a benchmark AQC dataset highlighted the robustness of the proposed methodology for learning only relevant components related to quality classes rather than other confusing traits, enabling the mitigation of the identified bias. [ABSTRACT FROM AUTHOR]

Computer Vision (CV) provides computers with the ability to perceive, analyze, and understand the content of images and videos. The applications are numerous and range from medical diagnosis to industrial quality control and special effects. CV uses different technologies and techniques to extract relevant information from a large number of images acquired via Machine Vision (MV) components. In industry, CV and MV are combined for trustworthy inspection of high-end products, quality control, and data collection applications. In this article, first, we present the CV and MV with a focus on the convenient artificial intelligence tools that may bused, such as machine & deep learning, and also the common color recognition methods. Second, we consider two industrial applications of artificial vision, especially CV, in real-time quality control to review their scientific valorization based on the primary findings of the studies carried out. Finally, we critically analyzed their findings to identify shortcomings, make recommendations, and open up new horizons for future research. [ABSTRACT FROM AUTHOR]

Laboratories across the world are successfully using quality indicators (QIs) to monitor their performance. We aimed to analyze the effectiveness of using the peer group comparison and statistical tools such as sigma metrics for periodic evaluation of QIs and identify potential errors in the preanalytical, analytical, and postanalytical phases. We evaluated the monthly QIs for 1 year. A total of 11 QIs were evaluated across the three phases of the total testing process, using percentage variance, and sigma metric analysis. Our study observed that based on sigma metric analysis, the performance was good for all the QIs except for the number of samples with the inappropriate specimen hemolyzed samples, clotted samples, and turnaround time (Sigma value < 3). The percentage variance of QIs in all the phases was plotted in a Pareto chart, which helped us in identifying turnaround time and internal quality control performance are the key areas that contribute to almost 80% of the errors among all the QIs. Laboratory performance evaluation using QIs and sigma metric analysis helped us in identifying and prioritizing the corrective actions in the key areas of the total testing process. [ABSTRACT FROM AUTHOR]

Genotype data from dairy cattle selection programs have greatly facilitated GWAS to identify variants related to economic traits. Results can enhance the accuracy of genomic prediction, analyze more complex models that go beyond additive effects, elucidate the genetic architecture of a trait, and finally, decipher the underlying biology of traits. The entire process, comprising data generation, quality control, statistical analyses, interpretation of association results, and linking results to biology should be designed and executed to minimize the generation of false-positive and false-negative associations and misleading links to biological processes. This review aims to provide general guidelines for data analysis that address data quality control, association tests, adjustment for population stratification, and significance evaluation to improve the reliability of conclusions. We also provide guidance on post-GWAS strategy and the interpretation of results. These guidelines are tailored to dairy cattle, which are characterized by long-range linkage disequilibrium, large half-sib families, and routinely collected phenotypes, requiring different approaches than those applied in human GWAS. We discuss common limitations and challenges that have been overlooked in the analysis and interpretation of GWAS to identify candidate sequence variants in dairy cattle. [ABSTRACT FROM AUTHOR]

Today, endovascular treatment (EVT) is the therapy of choice for strokes due to acute large vessel occlusion, irrespective of prior thrombolysis. This necessitates fast, coordinated multi-specialty collaboration. Currently, in most countries, the number of physicians and centres with expertise in EVT is limited. Thus, only a small proportion of eligible patients receive this potentially life-saving therapy, often after significant delays. Hence, there is an unmet need to train a sufficient number of physicians and centres in acute stroke intervention in order to allow widespread and timely access to EVT. To provide multi-specialty training guidelines for competency, accreditation and certification of centres and physicians in EVT for acute large vessel occlusion strokes. The World Federation for Interventional Stroke Treatment (WIST) consists of experts in the field of endovascular stroke treatment. This interdisciplinary working group developed competency – rather than time-based – guidelines for operator training, taking into consideration trainees' previous skillsets and experience. Existing training concepts from mostly single specialty organizations were analysed and incorporated. The WIST establishes an individualized approach to acquiring clinical knowledge and procedural skills to meet the competency requirements for certification of interventionalists of various disciplines and stroke centres in EVT. WIST guidelines encourage acquisition of skills using innovative training methods such as structured supervised high-fidelity simulation and procedural performance on human perfused cadaveric models. WIST multispecialty guidelines outline competency and quality standards for physicians and centres to perform safe and effective EVT. The role of quality control and quality assurance is highlighted. The World Federation for Interventional Stroke Treatment (WIST) establishes an individualized approach to acquiring clinical knowledge and procedural skills to meet the competency requirements for certification of interventionalists of various disciplines and stroke centres in endovascular treatment (EVT). WIST guidelines encourage acquisition of skills using innovative training methods such as structured supervised high-fidelity simulation and procedural performance on human perfused cadaveric models. WIST multispecialty guidelines outline competency and quality standards for physicians and centers to perform safe and effective EVT. The role of quality control and quality assurance is highlighted. The WIST 2023 Guidelines are published simultaneously in Europe (Adv Interv Cardiol 2023). • Widespread and timely interventional stroke treatment requires multiple specialties. • Training requirements for interventional stroke treatment are outlined. • Special emphasis rests on simulator and human cadaver training. • The pathway for an operator to reach WIST certification is specified. [ABSTRACT FROM AUTHOR]