Search

Patient-based real-time QC (PBRTQC) uses patient-derived data to assess assay performance. PBRTQC algorithms have advanced in parallel with developments in computer science and the increased availability of more powerful computers. The uptake of Artificial Intelligence in PBRTQC has been rapid, with many stated advantages over conventional approaches. However, until this review, there has been no critical comparison of these. The PBRTQC algorithms based on moving averages, regression-adjusted real-time QC, neural networks and anomaly detection are described and contrasted. As Artificial Intelligence tools become more available to laboratories, user-friendly and computationally efficient, the major disadvantages, such as complexity and the need for high computing resources, are reduced and become attractive to implement in PBRTQC applications. [ABSTRACT FROM AUTHOR]

L-Glutathione reduced (GSH) is a small molecule peptide found in large quantities in living organisms, particularly in animal liver cells. Its unique structure gives it great potential to act as an environmentally friendly and efficient corrosion inhibitor. The inhibition properties of GSH for mild steel in simulated concrete pore solutions (SCPS) containing chlorine was investigated by electrochemical tests and SEM-EDS surface analysis. According to the experimental results, GSH mainly blocked the cathodic corrosion reaction and has a corrosion inhibition efficiency of up to 92.3% at room temperature, enhancing the corrosion resistance of mild steel. The isothermal adsorption results indicate that the adsorption behavior of GSH on the surface follows the Langmuir isothermal adsorption model. Both quantum chemical calculations (QC) and molecular dynamics simulations (MD) show that GSH can be effectively adsorbed onto mild steel substrates, thus protecting the surface from erosion. Finally, the results of the above experiments and theoretical calculations are combined to elucidate the inhibitive mechanism: GSH molecules binds to the iron surface via the sulfur, nitrogen and oxygen atoms in the molecule, thus adsorbing to the iron surface in a tiled manner and forming a protective film to prevent the corrosive material from contacting the iron surface. [ABSTRACT FROM AUTHOR]

Recently significant effort has been invested in studying commonalities of human brain operation and advanced algorithms for machine learning to answer the question: Can the learning mechanisms, identified in the operation of the brain, be mimicked in artificial neural networks to enhance the learning efficiency with simultaneous reduction in complexity and power consumption.At the same time, machine learning algorithms, on their own, become increasingly complex, resulting in complex neural networks. To speed up the machine learning algorithms, research on 7G networks will be looking for new computing technologies, like quantum (q-) computing (QC), and new models for complex networks that will enable us to efficiently control/optimize the processes run on them.In this paper, under the umbrella of well-established complex networks theory, we provide a unified presentation of how quantum computing, implemented on near-future computers, can enable solving various problems in the above disciplines, otherwise difficult to solve by using classical (c-) approaches. The emphasis is on the commonalities in QC applications and modeling for the different systems listed above. For 7G network designers, the survey is expected to provide an insight into how much the research results in natural, QC based sciences can be integrated into new network paradigms to support above initiatives.

Cross-lingual question understanding involves identifying named entities and question intent in the target language based on corresponding texts from the source-language training dataset. However, relying solely on bilingual parallel corpora has limitations, especially for low-resource languages where such corpora are scarce or unavailable. This paper argues that current cross-lingual techniques hinder the effectiveness of various phrases, particularly noun phrases and interrogative phrases. To address this, a new code-switching data augmentation method called PBCS is introduced for zero-shot cross-lingual training. Unlike recent methods, this approach utilizes small bilingual phrase dictionaries instead of relying on a large bilingual parallel corpus. Moreover, a cross-lingual question understanding model, XQUM, is proposed. At the lower level, the model shares input features and hidden layer states to mitigate error accumulation. Additionally, at the top level, model performance is enhanced through a bi-directional correlation layer based on an iterative mechanism, specifically tailored for the given task. Experimental results on the MQUC and MTOD datasets demonstrate that XQUM significantly improves the accuracy of cross-lingual question understanding tasks. [ABSTRACT FROM AUTHOR]

Repeat-patient testing quality control (RPT-QC) is a version of statistical quality control (SQC) in which individual patient samples, rather than commercial control materials, are used. Whereas conventional SQC assumes control material stability and repeatedly measures the same lot of control material over time, RPT-QC uses a unique patient sample for each QC event and exploits the labile nature of patient samples under prescribed storage conditions for QC purposes. Advantages of RPT-QC include commutability, lower cost, and QC at concentrations of medical interest. Challenges include sample procurement and the establishment of control limits. The objective of this review is to compare and contrast the principles and procedures of RPT-QC and conventional SQC and to provide an overview of RPT-QC control limit establishment. [ABSTRACT FROM AUTHOR]

Background: The 2019 ASVCP Education Committee Forum for Discussion, presented at the annual ASVCP/ACVP meeting, identified a need to develop recommendations for teaching laboratory quality management principles in veterinary clinical pathology residency training programs. Objectives: To present a competency- based framework for teaching laboratory quality management principles in veterinary clinical pathology residency training programs, including entrustable professional activities (EPAs), domains of competence, individual competencies, and learning outcomes. Methods: A joint subcommittee of the ASVCP Quality Assurance and Laboratory Standards (QALS) and Education Committees executed this project. A draft guideline version was reviewed by the ASVCP membership and shared with selected ACVP committees in early 2022, and a final version was voted upon by the full QALS and Education Committees in late 2022. Results: Eleven domains of competence with relevant individual competencies were identified. In addition, suggested learning outcomes and resource lists were developed. Domains and individual competencies were mapped to six EPAs. Conclusions: This guideline presents a framework for teaching principles of laboratory quality management in veterinary clinical pathology residency training programs and was designed to be comprehensive yet practical. Guidance on pedagogical terms and possible routes of implementation are included. Recommendations herein aim to improve and support resident training but may require gradual implementation, as programs phase in necessary expertise and resources. Future directions include the development of learning milestones and assessments and consideration of how recommendations intersect with the American College of Veterinary Pathologists training program accreditation and certifying examination. [ABSTRACT FROM AUTHOR]

Representativeness and quality of collected meteorological data impact accuracy and precision of climate, hydrological, and biogeochemical analyses and predictions. We developed a comprehensive Quality Assurance (QA) and Quality Control (QC) statistical framework, consisting of three major phases: Phase I—Preliminary data exploration, i.e., processing of raw datasets, with the challenging problems of time formatting and combining datasets of different lengths and different time intervals; Phase II—QA of the datasets, including detecting and flagging of duplicates, outliers, and extreme data; and Phase III—the development of time series of a desired frequency, imputation of missing values, visualization and a final statistical summary. The paper includes two use cases based on the time series data collected at the Billy Barr meteorological station (East River Watershed, Colorado), and the Barro Colorado Island (BCI, Panama) meteorological station. The developed statistical framework is suitable for both real-time and post-data-collection QA/QC analysis of meteorological datasets.

Scientific datasets are growing rapidly and becoming critical to next-generation scientific discoveries. The validity of scientific results relies on the quality of data used and data are often subject to change, for example, due to observation additions, quality assessments, or processing software updates. The effects of data change are not well understood and difficult to predict. Datasets are often repeatedly updated and recomputing derived data products quickly becomes time consuming and resource intensive and may in some cases not even be necessary, thus delaying scientific advance. Despite its importance, there is a lack of systematic approaches for best comparing data versions to quantify the changes, and ad-hoc or manual processes are commonly used. In this article, we propose a novel hierarchical approach for analyzing data changes, including real-time (online) and offline analyses. We employ a variety of fast-to-compute numerical analyses, graphical data change representations, and more resource-intensive recomputations of a subset of the data product. We illustrate the application of our approach using three scientific diverse use cases, namely, satellite, cosmological, and x-ray data. The results show that a variety of data change metrics should be employed to enable a comprehensive representation and qualitative evaluation of data changes.

Based on the construction of berths No.9 and No.10 in the South Operation Area of Dalanping Port, Qinzhou Port, the quality control measures for underwater foundation treatment, caisson prefabrication, assembly and installation, surface structure construction, etc. were carried out through QC management methods according to the PDCA cycle in the construction of caisson gravity wharf. Feasible solutions have been proposed from six aspects: personnel, machinery, materials, methods, environment, and measurement, to address the instability of caissons caused by improper foundation treatment during the construction of gravity wharves, the large deviation of concrete component reinforcement protection layer that affects the service life of the structure, the unattractive overall shape of the wharf, and the structural safety caused by concrete cracking. It has improved the overall construction quality management level of the project, as well as the safety management level and economic benefits. [ABSTRACT FROM AUTHOR]

Abstract The rapid growth of biotherapeutic industry, with more and more complex molecules entering the market, forces the need for advanced analytical platforms that can quickly and accurately identify and quantify product quality attributes. Mass spectrometry has the potential to provide more detailed information about the quality attributes of complex products, and MS methods are more sensitive than UV methods for detection of impurities. The multi-attribute method (MAM), a liquid chromatography-mass spectrometry based analytical approach is an emerging platform which supports biotherapeutic characterization and cGMP testing. The main advantage lies in the ability to monitor multiple quality attributes in a single assay, both at the peptide and the intact level, facilitating streamlined biopharmaceutical production, from research and development to the QC environment. This review highlights the current landscape of the MAM approach with special attention given to increased analytical throughput, general requirements for QC in terms of instrumentation and software, regulatory requirements, and industry acceptance of the MAM platform. [ABSTRACT FROM AUTHOR]

Quality Control (QC) and Quality Assurance (QA) principles are essential for effective cervical cancer prevention. Being a crucial diagnostic step, colposcopy's sensitivity and specificity improvements are strongly advocated worldwide since inter- and intra-observer differences are the main limiting factors. The objective of the present study was the evaluation of colposcopy accuracy through the results of a QC/QA assessment from a survey in Italian tertiary-level academic and teaching hospitals. A web-based, user-friendly platform based on 100 colposcopic digital images was forwarded to colposcopists with different levels of experience. Seventy-three participants were asked to identify colposcopic patterns, provide personal impressions, and indicate the correct clinical practice. The data were correlated with a panel of experts' evaluation and with the clinical/pathological data of the cases. Overall sensitivity and specificity with the threshold of CIN2+ accounted for 73.7% and 87.7%, respectively, with minor differences between senior and junior candidates. Identification and interpretation of colposcopic patterns showed full agreement with the experts' panel, ranging from 50% to 82%, in some instances with better results from junior colposcopists. Colposcopic impressions correlated with a 20% underestimation of CIN2+ lesions, with no differences linked to level of experience. Our results demonstrate the good diagnostic performance of colposcopy and the need for improving accuracy through QC assessments and adhesion to standard requirements and recommendations. [ABSTRACT FROM AUTHOR]

The conventional successful business model of companies has been to increase productivity with high efficiency in order to provide good quality products to society. However, this business model is changing to focus on how to optimally manage corporate technology and resources to solve social issues. Therefore, it is necessary to promote three different types of activities to improve quality, productivity and sustainability that ensure the sustainability of each organization into the future. In this paper, we propose an SDQ Cube Template that expresses the strategy to promote SDGs (Sustainable Development Goals), DX (Digital transformation) and QC (Quality Control) initiatives in business processes. Additionally, we clarify the effectiveness of the proposed method by expressing practical business processes using the SDQ Cube template. [ABSTRACT FROM AUTHOR]

Quality indicators are tools for continuous improvement to enable the blood center to achieve its standards of the highest quality. Hence, they have to be established and monitored regularly for which NABH (National Accreditation Board for Hospitals) accreditation should be sought for. This study was undertaken to assess the Key Performance Indicators (KPI) through clinical audit quality control study of ten parameters, with a goal to improve and meet the benchmark as defined by NABH. All 10 Key Performance Indicators defined by NABH were analysed prospectively in a tertiary care blood centre of southern India. Parameters were compared to that of bench mark standards. Root cause analysis of all non-conformance parameters were done. Problem were identified and action taken to achieve KPI benchmarks in all deviations. Out of the ten KPI's which were studied, more than 50% meet the quality standards. The ones that did not meet the bench mark were TTI-HIV% which was 0.44%, TTI-Syphilis (RPR)% 0.26%, Number of units received back for discarding 5.96%, PRBC wastage% (on-shelf) was 2.11%, FFP, Cryoprecipitate wastage % (on-shelf) was 2.71%, the mean TAT for crossmatch of emergency PRBC blood was 18.3 min, 41.11% of FFP QC failure failed, Delay in transfusion time beyond 30 min after issue was 19.14%, Donor Deferral rate was 16.36% and TTI Outliers% No. of deviations beyond ± 2SD for HBsAg, HCV, HIV were 14.43%, 12.59% and17.73% respectively. Present study has helped to understand the flaws and problems faced by a tertiary care blood center in sustaining quality. It also actively captured and analysed multiple cross sections of non-conformances. [ABSTRACT FROM AUTHOR]

In the current economic situation of many companies, the need to reduce production time is a critical element. However, this cannot usually be carried out with a decrease in the quality of the final product. This article presents a possible solution for reducing the time needed for quality management. With the use of modern solutions such as optical measurement systems, quality control can be performed without additional stoppage time. In the case of single-point measurement with the Laser Doppler Vibrometer, the measurement can be performed quickly in a matter of milliseconds for each product. This article presents an example of such quality assurance measurements, with the use of fully non-contact methods, together with a proposed evaluation criterion for quality assessment. The proposed quality assurance algorithm allows the comparison of each of the products' modal responses with the ideal template and stores this information in the cloud, e.g., in the company's supervisory system. This makes the presented 3D Laser Vibrometry System an advanced instrumentation and data acquisition system which is the perfect application in the case of a factory quality management system based on the Industry 4.0 concept. [ABSTRACT FROM AUTHOR]

Given the wide variability in the quality of next-generation sequencing data submitted to public repositories, it is essential to identify methods that can perform quality control on these data sets when additional quality control data, such as mean tile data, are missing from public repositories. In this study, we present evidence that correlating counts of reads corresponding to pairs of motifs separated over specific distances on individual exons can be used as a proxy mean tile data in the data sets we analyzed and hence could be used when mean tile data are not available. As test data sets we use the Homo sapiens in vitro transcribed (IVT) data set, and a Drosophila melanogaster data set comprising wild and mutant types. We find that a FastQC analysis of the available parts of these data sets demonstrates that the per-tile sequencing quality is good for all the data sets apart from the mutant-type data where the mutant-r3 data are worse than the mutant-r2 data. Correspondingly, intra-exon motif correlations are reasonably large for all data sets except this latter case where the mutant-r2 correlations are low and the mutant-r3 correlations close to zero. We propose that these extremely low correlations are indicative of bias of technical origin, such as flowcell errors. In addition to this, the intra-exon motif correlations as a function of both guanosine-cytosine (GC) content parameters are somewhat higher and less dependent on the GC content parameters in the IVT-Plasmids messenger RNA (mRNA) selection free RNA-Seq sample (control) than in the other RNA-Seq samples that did undergo mRNA selection: both ribosomal depletion (IVT-Only) and PolyA selection (IVT-PolyA, wild type, and mutant). [ABSTRACT FROM AUTHOR]

Recent advances in single cell RNA sequencing (scRNA-seq) technologies have been invaluable in the study of the diversity of cancer cells and the tumor microenvironment. While scRNA-seq platforms allow processing of a high number of cells, uneven read quality and technical artifacts hinder the ability to identify and classify biologically relevant cells into correct subtypes. This obstructs the analysis of cancer and normal cell diversity, while rare and low expression cell populations may be lost by setting arbitrary high cutoffs for UMIs when filtering out low quality cells. To address these issues, we have developed a novel machine-learning framework that: 1. Trains cell lineage and subtype classifier using a gold standard dataset validated using marker genes 2. Systematically assess the lowest UMI threshold that can be used in a given dataset to accurately classify cells 3. Assign accurate cell lineage and subtype labels to the lower read depth cells recovered by setting the optimal threshold. We demonstrate the application of this framework in a well-curated scRNA-seq dataset of breast cancer patients and two external datasets. We show that the minimum UMI threshold for the breast cancer dataset could be lowered from the original 1500 to 450, thereby increasing the total number of recovered cells by 49%, while achieving a classification accuracy of >0.9. Our framework provides a roadmap for future scRNA-seq studies to determine optimal UMI threshold and accurately classify cells for downstream analyses. [ABSTRACT FROM AUTHOR]

Máy đo hoạt độ phóng xạ (dose calibrator) là thiết bị giữ vai trò vô cùng quan trọng trong khoa y học hạt nhân. Do đó, kiểm soát chất lượng (QC) cho dose calibrator là công việc thường xuyên, có đóng góp quyết định đến hiệu quả chẩn đoán và điều trị. Cơ quan Năng lượng Nguyên tử Quốc tế (The International Atomic Energy Agency), và Hiệp hội Vật lý Y khoa Hoa Kỳ (The American Association of Physicists in Medicine) đã đưa ra các hướng dẫn cho QC dose calibrator. Trong nghiên cứu sau đây, các hướng dẫn này được áp dụng để kiểm soát chất lượng cho dose calibrator được trang bị tại Phòng Thí nghiệm Vật lý Y khoa, thuộc trường Đại học Nguyễn Tất Thành. Các bài QC gồm: đo độ chính xác và độ chụm, độ tái lập, đáp ứng phông phóng xạ và đáp ứng tuyến tính. Kết quả kiểm tra cho thấy thiết bị hiện đang đáp ứng đầy đủ các tiêu chuẩn do Cơ quan Năng lượng Nguyên tử Quốc tế đưa ra. Phương pháp được mô tả trong nghiên cứu này có thể áp dụng để kiểm soát chất lượng cho các thiết bị tương tự tại các cơ sở y học hạt nhân.

Recent advances in single cell RNA sequencing (scRNA-seq) technologies have been invaluable in the study of the diversity of cancer cells and the tumor microenvironment. While scRNA-seq platforms allow processing of a high number of cells, uneven read quality and technical artifacts hinder the ability to identify and classify biologically relevant cells into correct subtypes. This obstructs the analysis of cancer and normal cell diversity, while rare and low expression cell populations may be lost by setting arbitrary high cutoffs for UMIs when filtering out low quality cells. To address these issues, we have developed a novel machine-learning framework that: 1. Trains cell lineage and subtype classifier using a gold standard dataset validated using marker genes 2. Systematically assess the lowest UMI threshold that can be used in a given dataset to accurately classify cells 3. Assign accurate cell lineage and subtype labels to the lower read depth cells recovered by setting the optimal threshold. We demonstrate the application of this framework in a well-curated scRNA-seq dataset of breast cancer patients and two external datasets. We show that the minimum UMI threshold for the breast cancer dataset could be lowered from the original 1500 to 450, thereby increasing the total number of recovered cells by 49%, while achieving a classification accuracy of >0.9. Our framework provides a roadmap for future scRNA-seq studies to determine optimal UMI threshold and accurately classify cells for downstream analyses.

Purpose: Research has shown that co-administration of preparations containing HQ and azelaic acid (AZ) or vitamin C (vit C) may be more effective than HQ alone. The aim of this study was to evaluate the stability of HQ in the presence of AZ and vit C as active ingredients in the extemporaneous preparations prepared with different techniques. Methods: Topical preparations containing HQ, vit C, and AZ were prepared using with aqueous and none-aqueous extemporaneous techniques. Some auxiliary antioxidants were used to stabilize vit C. Thermal stress condition was applied for stability evaluation. Digital images and HPLC analysis were performed to control the color changes and drug loss, respectively. Results: Severe color changes happened in some formulations and dark brown color appeared. Color change was directly attributed to vit C loss but not related to HQ loss. HQ ointment with no antioxidant, showed no loss after stress incubation. AZ was partially able to increase the HQ and vit C stability in a combination formulation, but this stabilizing effect in binary formulations of HQ and AZ was not seen. SMB enhanced vit C stability. Aqueous preparation methods decreased the stability of formulations significantly. It can be recommended that HQ, vit C, and AZ be formulated in separate dosage forms. Conclusion: Avoiding water incorporating or aqueous methods will enhance the stability of these formulations, as well. Intrinsic low stability of vit C in topical formulations may be enhanced using non-water incorporating or non-aqueous methods and utilizing SMB in suitable concentrations. [ABSTRACT FROM AUTHOR]

In this practitioner protocol, the optimization of the radiochemical synthesis of [18F]fluoroestradiol (FES) on the Synthra RNplus research automated platform is described in detail and a quality control (QC) summary of three validation productions is presented. In comparison with published synthesis methods developed on other platforms, the yield was considerably improved (40%–45% ndc). The other important improvement is the reduction of the required concentration of H2SO4 avoiding the production of high concentrations of acidic vapors that can deteriorate the module. Purification was achieved by solid phase extraction, and the required adaptation of an external heating plate to the module to evaporate the ethanol is also described. The product was obtained with high radiochemical purity and fulfilled all the requirements of current Good Manufacturing Practice (cGMP). The final product is formulated as a sterile, pyrogen‐free solution suitable for human injection. To the best of our knowledge, this is the first report of FES production using this type of module. [ABSTRACT FROM AUTHOR]

Patient-based real-time QC (PBRTQC) uses patient-derived data to assess assay performance. PBRTQC algorithms have advanced in parallel with developments in computer science and the increased availability of more powerful computers. The uptake of Artificial Intelligence in PBRTQC has been rapid, with many stated advantages over conventional approaches. However, until this review, there has been no critical comparison of these. The PBRTQC algorithms based on moving averages, regression-adjusted real-time QC, neural networks and anomaly detection are described and contrasted. As Artificial Intelligence tools become more available to laboratories, user-friendly and computationally efficient, the major disadvantages, such as complexity and the need for high computing resources, are reduced and become attractive to implement in PBRTQC applications.

Objectives: The quality control of serological assays remains controversial. The aim of this project was to describe the problems associated with a working model for controlling these assays and solutions, including using a source of well-defined targets and acceptable limits, a process to identify lot-to-lot reagent variation and an interpretation of the result that accounted for the clinical situation. False-negative results are problematic but can be reduced by identifying and comparing reagent lot variation with previous results., Methods: The components of the Quality Assurance strategy are the following: Lot-to-lot reagent and calibrator variation assessment; dynamic, big-data approach to determine accurate targets and acceptable limits for manufacturer-provided QC material; negative QC monitoring process; use of commutable EQA with a sufficient method subgroup size to assess bias; clinical assessment of any statistically flagged error; and provision of support to the clinician for the interpretation of results., Results: The model described has been used for twelve months, and acceptable variation has been maintained., Conclusions: The paper presents a solution that emphasizes the early detection of reagent lot variation and patient risk rather than instrument control. Reducing the risk of a false result to patients requires optimal assay quality control and an effective mechanism to support the clinician's use of these results in diagnosis and monitoring. The problems of serological assays are well-known, but there remain few integrated solutions in the literature., (Copyright © 2024 Elsevier B.V. All rights reserved.)

In the UK, the Institute of Physics and Engineering in Medicine (IPEM) provides guidance to Medical Physics departments on appropriate Quality Control (QC) tests to evaluate MRI scanners used in routine clinical practice. The method recommended for the rigorous annual assessment of the SNR produced by RF coils uses a sequence and regions of interest (ROIs) recommended by IPEM, and calculates SNR through a subtraction calculation (IPEM recommended Method). This method was compared to alternative methods proposed by NessAiver at the 2019 American Association of Physicists in Medicine meeting in their talk on RF coil testing. Comparisons were completed for sequences and regions of interest (ROIs) recommended by IPEM and NessAiver. Testing was performed at 1.5 T using the scanner’s integrated body coil and at 3.0 T using a peripheral Head/Neck coil. Calculation of SNR using the mean of the background noise, assessed using the NessAiver recommended sequence and ROIs (NessAiver Noise-Average Method), typically offered the lowest variability in SNR results. Additionally, the SNR results produced by the IPEM Recommended Method were less repeatable than those from the NessAiver Noise-Average Method (p

Quality Control (QC) and Quality Assurance (QA) principles are essential for effective cervical cancer prevention. Being a crucial diagnostic step, colposcopy’s sensitivity and specificity improvements are strongly advocated worldwide since inter- and intra-observer differences are the main limiting factors. The objective of the present study was the evaluation of colposcopy accuracy through the results of a QC/QA assessment from a survey in Italian tertiary-level academic and teaching hospitals. A web-based, user-friendly platform based on 100 colposcopic digital images was forwarded to colposcopists with different levels of experience. Seventy-three participants were asked to identify colposcopic patterns, provide personal impressions, and indicate the correct clinical practice. The data were correlated with a panel of experts’ evaluation and with the clinical/pathological data of the cases. Overall sensitivity and specificity with the threshold of CIN2+ accounted for 73.7% and 87.7%, respectively, with minor differences between senior and junior candidates. Identification and interpretation of colposcopic patterns showed full agreement with the experts’ panel, ranging from 50% to 82%, in some instances with better results from junior colposcopists. Colposcopic impressions correlated with a 20% underestimation of CIN2+ lesions, with no differences linked to level of experience. Our results demonstrate the good diagnostic performance of colposcopy and the need for improving accuracy through QC assessments and adhesion to standard requirements and recommendations.

This article aims to review the application of various quantum chemical methods (semi-empirical, density functional theory (DFT), second order Møller–Plesset perturbation theory (MP2)) in the studies of cyclodextrin host–guest complexes. The details of applied approaches such as functionals, basis sets, dispersion corrections or solvent treatment methods are analyzed, pointing to the best possible options for such theoretical studies. Apart from reviewing the ways that the computations are usually performed, the reasons for such studies are presented and discussed. The successful applications of theoretical calculations are not limited to the determination of stable conformations but also include the prediction of thermodynamic properties as well as UV–Vis, IR, and NMR spectra. It has been shown that quantum chemical calculations, when applied to the studies of CD complexes, can provide results unobtainable by any other methods, both experimental and computational. [ABSTRACT FROM AUTHOR]

Over the past few years, the implementation of mass spectrometry (MS) in QC laboratories has become a more common occurrence. The multi-attribute method (MAM), and emerging intact multi-attribute method (iMAM), are powerful analytical tools utilising liquid chromatography−mass spectrometry (LC-MS) methods that enable the monitoring of critical quality attributes (CQAs) in biotherapeutic proteins in compliant settings. Both MAM and iMAM are intended to replace or supplement several conventional assays with a single LC-MS method utilising MS data in combination with robust, semi-automated data processing workflows. MAM and iMAM workflows can also be implemented into current Good Manufacturing Practices environments due to the availability of CFR 11 compliant chromatography data system software. In this study, MAM and iMAM are employed for the analysis of 4 batches of a glucagon-like peptide-Fc fusion protein. MAM approach involved a first the discovery phase for the identification of CQAs and second, the target monitoring phase of the selected CQAs in other samples. New peak detection was performed on the data set to determine the appearance, absence or change of any peak. For native iMAM workflow both size exclusion and strong cation exchange chromatography were optimized for the identification and monitoring of CQAs at the intact level. [Display omitted] • The development and implementation of a MAM and iMAM method for the characterization of a GLP-Fc fusion protein. • Identification and monitoring of CQAs in commercial drug products. • New peak detection to identify modified and/or new species between samples analysed. • The proposed workflow offers site specific identification of critical quality attributes. • Versatile workflows that can be applied to additional biotherapeutic proteins. [ABSTRACT FROM AUTHOR]

When using HCl to remove oxidation from metal surfaces, there is a risk of significant corrosion to the metal substrate. As a common industrial practice, organic or polymer coatings in corrosive environments protect metals from corrosion by providing a barrier on the metal surface within the corrosive medium. However, the limited solubility of polymers in aqueous corrosive mediums restricts their effectiveness. Herein, a highly water-soluble polyfluorene derivative, Poly(9,9-bis{3′-[(N , N -dimethyl)- N -ethylammonium}-propyl]-2,7-fluorene dibromide) (PFDN-Br), was synthesized as a HCl corrosion inhibitor to solve the corrosion problem of Q235 steel. The protective performance of the synthesized coatings was evaluated through electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization (PDP) curves. The results of electrochemical testing demonstrate that the addition of PFDN-Br significantly reduces the corrosion rate of mild steel compared to the results without PFDN-Br. The average inhibition efficiency is 92.7 %. Additionally, the results of PDP indicate that PFDN-Br acts as a mixed-type corrosion inhibitor, with its adsorption on the surface of carbon steel following the Langmuir adsorption isotherm model. Quantum chemistry calculations (QC) and molecular dynamics simulations (MD) were employed to investigate the interaction mechanism between PFDN-Br and the surface. The excellent inhibitory performance of PFDN-Br may be attributed to its high-density side chains. This study provides insights into the development of polymer coatings with high water solubility and superior corrosion resistance. • Synthesized a highly water-soluble cationic Polyfluorene PFDN-Br. • PFDN-Br coating protects metals from acid corrosion. • After 10 h of immersion, PFDN-Br maintains a corrosion inhibition rate of 93 %. • The adsorption mechanism of PFDN-Br was elucidated through theoretical calculations. [ABSTRACT FROM AUTHOR]

• The implementation of the quality management software (UnityRT) in molecular virology/microbiology was evaluated. • UnityRT consolidated the capture, analysis, monitoring, and tracking of QC data, along with corrective actions. • Real-time QC monitoring can have a significant clinical impact. Quality control (QC) is one component of an overarching quality management system (QMS) that aims at assuring laboratory quality and patient safety. QC data must be acceptable prior to reporting patients' results. Traditionally, QC statistics, records, and corrective actions were tracked at the Johns Hopkins Molecular Virology Laboratory using Microsoft Excel. Unity Real-Time (UnityRT), a QMS software (Bio-Rad Laboratories), which captures and analyzes QC data by instrument and control lot per assay, was implemented and its impact on the workflow was evaluated. The clinical utility of real-time QC monitoring using UnityRT is highlighted with a case of subtle QC trending of HIV-1 quantitative control results. A comprehensive workflow analysis was performed, with a focus on Epstein Barr Virus (EBV) and BKV quantitative viral load testing (Roche cobas 6800). The number of QC steps and time to complete each step were assessed before and after implementing UnityRT. Our assessment of monthly QC data review revealed a total of 10 steps over 57 min when using Microsoft Excel, versus 6 steps over 11 min when using UnityRT. HIV-1 QC monitoring revealed subtle trending of the low positive control above the mean from November to December 2022, correlating with a change in the reagent kit lot. This associated with a shift in patients' results from positives below the lower limit of quantification to positives between 20 and 100 copies/mL. UnityRT consolidated QC analyses, monitoring, and tracking corrective actions. UnityRT was associated with significant time savings, which along with the interfaced feature of the QC capture and data analysis, have improved the workflow and reduced the risk of laboratory errors. The HIV-1 case revealed the value of the real-time monitoring of QC. [ABSTRACT FROM AUTHOR]

In the current economic situation of many companies, the need to reduce production time is a critical element. However, this cannot usually be carried out with a decrease in the quality of the final product. This article presents a possible solution for reducing the time needed for quality management. With the use of modern solutions such as optical measurement systems, quality control can be performed without additional stoppage time. In the case of single-point measurement with the Laser Doppler Vibrometer, the measurement can be performed quickly in a matter of milliseconds for each product. This article presents an example of such quality assurance measurements, with the use of fully non-contact methods, together with a proposed evaluation criterion for quality assessment. The proposed quality assurance algorithm allows the comparison of each of the products’ modal responses with the ideal template and stores this information in the cloud, e.g., in the company’s supervisory system. This makes the presented 3D Laser Vibrometry System an advanced instrumentation and data acquisition system which is the perfect application in the case of a factory quality management system based on the Industry 4.0 concept.

We present the design and analysis of noninverting single-spiral Ka-band (26.5–40 GHz) CMOS Wilkinson power dividers and their deriving quadrature couplers (QCs) and baluns. For the power dividers, a parallel capacitor is included at the input port (port 1) for input matching, and a parallel RC network is connected between the output ports (ports 2 and 3) for input matching and isolation. Noninverting single-spiral structure with transmission-line (TL) length of about λ/12 is adopted to achieve miniature area and small amplitude imbalance (AI) and phase difference (PD). To realize QC and balun, negative/positive phase-shift TLs with phase-shift of − 45°/45° and − 90°/90°, respectively, can be included at ports 2/3 of the power divider. Two power dividers and their deriving two QCs and two baluns are designed and implemented. Prominent result is obtained. For example, the miniature QC achieves excellent S11 of − 13.5 dB, S22 of − 14.5 dB, S33 of − 19.4 dB, S32 of − 10.5 dB, S21 of − 4.713 dB, and S31 of − 4.731 dB at 28 GHz. The corresponding AI and PD are 0.018 dB and − 0.1°, respectively. Moreover, S11 is smaller than − 10 dB from 10.4 GHz to over 50 GHz, corresponding to a fractional bandwidth (FBW) larger than 141.4%. The QC occupies a normalized chip area of 6.1 × 10–4 λ02, one of the smallest normalized chip areas ever reported for millimeter-wave QCs. [ABSTRACT FROM AUTHOR]

Quality control of genomic data is an essential but complicated multi-step procedure, often requiring separate installation and expert familiarity with a combination of different bioinformatics tools. Software incompatibilities, and inconsistencies across computing environments, are recurrent challenges, leading to poor reproducibility. Existing semi-automated or automated solutions lack comprehensive quality checks, flexible workflow architecture, and user control. To address these challenges, we have developed snpQT: a scalable, stand-alone software pipeline using nextflow and BioContainers, for comprehensive, reproducible and interactive quality control of human genomic data. snpQT offers some 36 discrete quality filters or correction steps in a complete standardised pipeline, producing graphical reports to demonstrate the state of data before and after each quality control procedure. This includes human genome build conversion, population stratification against data from the 1,000 Genomes Project, automated population outlier removal, and built-in imputation with its own pre- and post- quality controls. Common input formats are used, and a synthetic dataset and comprehensive online tutorial are provided for testing, educational purposes, and demonstration. The snpQT pipeline is designed to run with minimal user input and coding experience; quality control steps are implemented with numerous user-modifiable thresholds, and workflows can be flexibly combined in custom combinations. snpQT is open source and freely available at https://github.com/nebfield/snpQT. A comprehensive online tutorial and installation guide is provided through to GWAS (https://snpqt.readthedocs.io/en/latest/), introducing snpQT using a synthetic demonstration dataset and a real-world Amyotrophic Lateral Sclerosis SNP-array dataset.

Since its discovery by F.A.L Clowes, extensive research has been dedicated to identifying the functions of the quiescent center (QC). One of the earliest hypotheses was that it serves a key role in regeneration of the root meristem. Recent works provided support for this hypothesis and began to elucidate the molecular mechanisms underlying this phenomenon. There are two scenarios to consider when assessing the role of the QC in regeneration: one, when the damage leaves the QC intact; and the other, when the QC itself is destroyed. In the first scenario, multiple factors are recruited to activate QC cell division in order to replace damaged cells, but whether the QC has a role in the second scenario is less clear. Both using gene expression studies and following the cell division pattern have shown that the QC is assembled gradually, only to appear as a coherent identity late in regeneration. Similar late emergence of the QC was observed during the de novo formation of the lateral root meristem. These observations can lead to the conclusion that the QC has no role in regeneration. However, activities normally occurring in QC cells, such as local auxin biosynthesis, are still found during regeneration but occur in different cells in the regenerating meristem. Thus, we explore an alternative hypothesis, that following destruction of the QC, QC-related gene activity is temporarily distributed to other cells in the regenerating meristem, and only coalesce into a distinct cell identity when regeneration is complete. [ABSTRACT FROM AUTHOR]

Quality control of genomic data is an essential but complicated multi-step procedure, often requiring separate installation and expert familiarity with a combination of different bioinformatics tools. Dependency hell and reproducibility are recurrent challenges. Existing semi-automated or automated solutions lack comprehensive quality checks, flexible workflow architecture, and user control. To address these challenges, we have developed snpQT: a scalable, stand-alone software pipeline using nextflow and BioContainers, for comprehensive, reproducible and interactive quality control of human genomic data. snpQT offers some 36 discrete quality filters or correction steps in a complete standardised pipeline, producing graphical reports to demonstrate the state of data before and after each quality control procedure. This includes human genome build conversion, population stratification against data from the 1,000 Genomes Project, automated population outlier removal, and built-in imputation with its own pre- and post- quality controls. Common input formats are used, and a synthetic dataset and comprehensive online tutorial are provided for testing, educational purposes, and demonstration. The snpQT pipeline is designed to run with minimal user input and coding experience; quality control steps are implemented with default thresholds which can be modified by the user, and workflows can be flexibly combined in custom combinations. snpQT is open source and freely available at https://github.com/nebfield/snpQT. A comprehensive online tutorial and installation guide is provided through to GWAS (https://snpqt.readthedocs.io/en/latest/), introducing snpQT using a synthetic demonstration dataset and a real-world Amyotrophic Lateral Sclerosis SNP-array dataset.

• Next generation sequencing is a scalable solution to genotyping mutant mice. • Ratios of wild type and mutant sequence counts are used to call the genotype. • Hundreds of samples can be multiplexed into one sequencing experiment. • Amplification of high-homology genes can be easily filtered out during analysis. Genotyping of knockout alleles in mice is commonly performed by end-point PCR or gene-specific/universal cassette qPCR. Both have advantages and limitations in terms of assay design and interpretation of results. As an alternative method for high-throughput genotyping, we investigated next generation sequencing (NGS) of PCR amplicons, with a focus on CRISPR-mediated exon deletions where antibiotic selection markers are not present. By multiplexing the wild type and mutant-specific PCR reactions, the genotype can be called by the relative sequence counts of each product. The system is highly scalable and can be applied to a variety of different allele types, including those produced by the International Mouse Phenotyping Consortium and associated projects. One potential challenge with any assay design is locating unique areas of the genome, especially when working with gene families or regions of high homology. These can result in misleading or ambiguous genotypes for either qPCR or end-point assays. Here, we show that genotyping by NGS can negate these issues by simple, automated filtering of undesired sequences. Analysis and genotype calls can also be fully automated, using FASTQ or FASTA input files and an in-house Perl script and SQL database. [ABSTRACT FROM AUTHOR]

In the present study, 149 local earthquakes (0.6≤ML≤5.1), those that occurred in the Chamoli region of the Garhwal Himalaya and are recorded by a 12-station digital telemetry seismological network around the Tehri region, have been analyzed to estimate source parameters using Brune's (1970) point source circular model and the quality factor Qc, adopting the single back-scattering model given by Aki and Chouet (1975). Two data sets comprised of 86 local earthquakes (data set 1) in the magnitude range (0.6≤ML≤3.3) recorded during January 2009 to December 2014 and 63 local earthquakes (data set 2) in the magnitude range (0.7≤ML≤5.1) recorded during January–December 2017 have been used for this purpose. The source parameters, viz., seismic moment (Mo), source radii (r), and stress drop (∆σ), have been computed from the displacement spectra of SH-component of the S-wave, whereas the quality factor Qc has been estimated from the coda waves of 30-s window length of vertical component seismograms for giving the frequency-dependent attenuation relation for the region. Mo, r, and ∆σ vary from 1.2˟1011 to 7.9˟1013 Nm, 132 to 317 m, and 0.05 to 42.9 bars, respectively, for data set 1 and from 2.5˟1011 to 2.1˟1015 Nm, 45.7 to 365m, and 0.2 to 149 bars, respectively, for the data set 2. Low stress drops have been obtained for the majority of events of both the data sets. However, high stress drops, i.e., 307 bars and 480 bars, have also been observed for two small size earthquakes of the second data sets having a magnitude of ML~5.1 and ~4.9, respectively. The estimation of quality factor Qc has provided the frequency-dependent average attenuation relations, Qc=137f0.87 and Qc=120f0.99, for data set 1 and 2, respectively, for the region. [ABSTRACT FROM AUTHOR]

BackgroundThe primary rescue medication to treat acute asthma exacerbation is the short-acting β₂-adrenergic receptor agonist; however, there is variation in how well a patient responds to treatment. Although these differences might be due to environmental factors, there is mounting evidence for a genetic contribution to variability in bronchodilator response (BDR).ObjectiveTo identify genetic variation associated with bronchodilator drug response in Latino children with asthma.MethodsWe performed a genome-wide association study (GWAS) for BDR in 1782 Latino children with asthma using standard linear regression, adjusting for genetic ancestry and ethnicity, and performed replication studies in an additional 531 Latinos. We also performed admixture mapping across the genome by testing for an association between local European, African, and Native American ancestry and BDR, adjusting for genomic ancestry and ethnicity.ResultsWe identified 7 genetic variants associated with BDR at a genome-wide significant threshold (P < 5 × 10(-8)), all of which had frequencies of less than 5%. Furthermore, we observed an excess of small P values driven by rare variants (frequency,

Abstract Background Characterizing the behaviors of dynamic systems requires capturing them with high temporal and spatial resolution. Owing to its transparency and genetic tractability, the Arabidopsis thaliana root lends itself well to live imaging when combined with cell and tissue-specific fluorescent reporters. We developed a novel 4D imaging method that utilizes simple confocal microscopy and readily available components to track cell divisions in the root stem cell niche and surrounding region for up to 1 week. Results Using this method, we performed a direct measurement of cell division intervals within and around the root stem cell niche. The results reveal a short, steep gradient of cell division rates in proximal stem cells, with progressively more rapid cell division rates from quiescent center (QC), to cells in direct contact with the QC (initials), to their immediate daughters, after which division rates appear to become more homogeneous. Conclusions These results provide a baseline to study how perturbations in signaling could affect cell division patterns in the root meristem. This new setup further allows us to finely analyze meristematic cell division rates that lead to patterning.

This article aims to review the application of various quantum chemical methods (semi-empirical, density functional theory (DFT), second order Møller–Plesset perturbation theory (MP2)) in the studies of cyclodextrin host–guest complexes. The details of applied approaches such as functionals, basis sets, dispersion corrections or solvent treatment methods are analyzed, pointing to the best possible options for such theoretical studies. Apart from reviewing the ways that the computations are usually performed, the reasons for such studies are presented and discussed. The successful applications of theoretical calculations are not limited to the determination of stable conformations but also include the prediction of thermodynamic properties as well as UV–Vis, IR, and NMR spectra. It has been shown that quantum chemical calculations, when applied to the studies of CD complexes, can provide results unobtainable by any other methods, both experimental and computational.