Quality Control Standards Research Articles

Stability of Volatile Organic Compounds in Thermal Desorption Tubes and in Solution.

Exhaled breath VOCs are often collected and stored in sorbent tubes before thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS) analysis. Information about the stability of VOCs during storage is needed to account for potential artifacts and monitor for losses. Additionally, information about the stability of VOC standards in solution is required to assess their performance as quality control and internal standards. We evaluated the stability of a standard mixture of 42 VOCs in dual-sorbent tubes containing Tenax® TA and Carbotrap 1TD over 60 days at commonly used storage conditions: room temperature (~21 °C), 4 °C, and -80 °C. The same 42 VOCs were also evaluated for their stability in methanol over 60 days while stored at -20 °C. All samples were analyzed using TD-GC-MS. During storage, most VOCs were stable on sorbent after 60 days: 36/42 (86%), 39/42 (93%), and 41/42 (98%) had not statistically changed for room temperature, 4 °C and -80 °C, respectively, based on Spearman rank correlation coefficients and linear regression analysis. The isotopically labelled VOCs tested here are good candidates for use as internal standards for pre-analysis or storage. Degradation of VOCs in solution was apparent after 60 days: 27/42 (64%) of VOCs had statistically decreased. The total VOC mixture had dropped to 90% of its original intensity after ~22 days and a subset of VOCs typically used as internal standards dropped to 90% in ~16 days. Analysts using similar mixtures should make a fresh solution at least every two weeks to ensure analytical accuracy. This study provides important insights into storage practices for both sorbent tubes and standard solutions, guiding analysts toward improved reliability and accuracy in exhaled breath analysis. &#xD.

A Comprehensive Review on the Chinese Herbal Medicine Quzhiqiao

Quzhiqiao is a Chinese herbal medicine widely used in Zhejiang Province of China, which originates from the cultivar Citrus aurantiun ‘Changshanhuyou’, named Changshanhuyou in Chinese. Citrus aurantiun ‘Changshanhuyou’ is a botanical variety of C. aurantium L., which is obtained after long-term domestication. It belongs to the Rutaceae family and mainly grows in Changshan County, Zhejiang Province, China. Quzhiqiao is an authentic Chinese medicinal material in the Zhejiang area with various pharmacological and curative effects. A comprehensive review and indepth analysis of scientific literature on Quzhiqiao was conducted, utilizing diverse electronic databases and additional sources. This review provides a comprehensive overview of its chemical components, standardized quality control, pharmacological activity, and mechanism of action, which also outlines future perspectives, highlighting the necessity for further research for harnessing the potential of the therapeutic use of Quzhiqiao.

Spectrophotometric and calculative determination methods of textile color-difference threshold considering the observing condition

Purpose This study aims to investigate the varying color-difference thresholds for textiles under various illuminants. Design/methodology/approach To determine color-difference thresholds, 108 fabric samples with widely ranging colors were spectrophotometrically measured and visually assessed under four illumination conditions (correlated color temperatures of 2,856 K and 6,504 K; illuminances of 100 lx and 2,000 lx). Findings The mean spectrophotometric color-difference threshold (solely based on the textile’s physical color attributes in machine vision) was 4.22 ΔE*ab; thus, a mechanically measured color difference between two textiles (regardless of illuminant) of less than 4.22 ΔE*ab indicated individuals’ inability to differentiate between two textiles. The calculated color-difference thresholds, which reflected the color differences perceived by people considering textiles’ physical color attributes and the environmental factors in which they were observed, were higher than the spectrophotometric thresholds. This meant that under various illuminants, people had greater difficulty perceiving color differences than mechanically measured spectrophotometric thresholds. Particularly, larger discrepancies between the two threshold types occurred under reddish illuminants of 2,856 K than under bluish-white illuminants of 6,504 K. Furthermore, the extent to which people perceived color differences as distinct from actual differences under illumination was larger for greenish-blue textiles than for textiles of other hues. Originality/value The determined spectrophotometric and calculative color-difference thresholds for textiles can help fashion companies predict consumers’ perceptions of the colors of their textile products under various illuminants and, accordingly, appropriately plan colors of products and create standards for color quality control.

Determination of the quantitative content of volatile components in ethanol-containing products

A method is proposed for correctly determining the quantitative content of volatile components, including ethyl alcohol, in alcohol-containing products. The method is based on the use of sample density measurement data and chromatographic data for determining the quantitative content of volatile compounds. It is shown that in a number of cases the difference between the values of the volumetric content of ethyl alcohol in alcoholic products, calculated according to the interstate standard GOST 3639 and according to the proposed method, exceeds by several times the declared measurement error limit of 0.1 % by volume. The results obtained can be used to update state, interstate and international standards for quality control and safety of alcoholic and alcohol-containing products.

Rapid Identification of Chemical Constituents in New Compound Aloe Capsule Based on UPLC-Q-Orbitrap-MS.

The chemical composition of the new compound aloe capsule (NCAC) has not been fully elucidated to date, which poses challenges for pharmacology, scientific, and rational drug use. In this study, a rapid and sensitive method was established to comprehensively study the constituents in the NCAC. The contents of the NCAC were analyzed by UPLC-Q-Orbitrap-MS and data postprocessing technology. Firstly, the extract was separated by UPLC system, and the fragment information was obtained under positive and negative ions and then compared with the characteristic fragments described in the literature, so as to achieve the purpose of rapid identification of the compound of NCAC. A total of 56 compounds including 21 chromones, 6 pyranones, 7 anthraquinones, 7 anthrone, 5 alkaloids, 4 amino acids, and 6 other components were detected in NCAC by comparing the retention time and mass spectrometry information and retrieving the reference literature. The UPLC-Q-Orbitrap-MS method was developed and utilized successfully to identify the major constituents in NCAC and would be helpful for improving the quality control standard of NCAC.

Quality control standardization, nutritional profiling, phytochemical analysis, and investigation into antioxidant and antimicrobial potential of Begonia palmata D. Don. leaves

Quality control standardization, nutritional profiling, phytochemical analysis, and investigation into antioxidant and antimicrobial potential of Begonia palmata D. Don. leaves

Revealing the formation mechanisms of key flavor components during the fermentation of bamboo shoots by combining flavoromics and metagenomics

Microbial metabolism plays a critical role in the flavor development of Guangxi fermented bamboo shoots (GFBS). To clarify the role of microorganisms in flavor formation and predict the metabolic pathways of key characteristic flavor compounds, this study employed metabolomics, Odor Activity Value (OAV), and Taste Activity Value (TAV) calculations, integrated with Partial Least Squares Discriminant Analysis (PLS-DA), to investigate changes in GFBS flavors—represented by volatile flavor compounds, organic acids, and free amino acids—across a 30-day fermentation period. Metagenomic datasets were used to identify taxonomic and functional changes in the microbial community. As a result, 26 characteristic flavor compounds (OAV or TAV > 1) were identified in mature GFBS, and 23 differential flavor compounds were identified at different fermentation stages using PLS-DA (VIP > 1.2). The top 10 microbial genera associated with these characteristic flavor compounds were identified, including Acinetobacter, Enterobacter, Raoultella, Enterococcus, Klebsiella, Lactococcus, Leuconostoc, Weissella, Lactiplantibacillus and Limosilactobacillus. Based on these findings, a predictive metabolic network of key flavor compounds in GFBS was constructed, providing a comprehensive understanding of the diverse metabolic roles of microorganisms during fermentation. This work lays a theoretical foundation for the standardized production and quality control of GFBS flavor.

Abstract 4138019: eQTL Analysis of the PAH Biomarker CCN2 Identifies a Novel SNP that Associates with Survival

Background: We recently determined that cellular communication network factor 2 (CCN2) (also known as IGFBP8) levels associate with metrics of severity, and survival, in pulmonary arterial hypertension (PAH). While genetic variants that modify CCN2 gene expression have been described, the variants across the genome that associate with CCN2 protein levels in human circulation remain unknown. Research Question: We sought to identify genetic variants associated with circulating levels of CCN2 and to determine those variants’ relationship with clinical severity and survival. Methods: Serum CCN2 was measured by ELISA in subjects from a national sample repository, the PAH Biobank. A genome wide association study (GWAS) for CCN2 (natural log transformed) was performed in White idiopathic PAH (IPAH) PAH Biobank participants (n = 768) using Illumina OMNI5 genotypes in plink after standard quality control. Subsequent exploration of the SNP of interest was conducted in a separate dataset of 687 White PAH participants (n=360 IPAH, n=313 APAH) linked to genetic and clinical data, including REVEAL 2.0 risk score assessment (divided into low, medium, and high-risk levels) and outcomes (the STRIDE (Sitaxsentan To Relieve Impaired Exercise) trials cohort). Results: In the PAH Biobank, using GWAS, we found CCN2 levels were significantly associated with rs9493157 (p = 2.8 x10 -12 ) ( Figure A ). rs9493157 is reported in the Genotype-Tissue Expression (GTEx) portal to be an eQTL for CCN2 expression in the left ventricle. In the STRIDE cohort, the hazard ratio (HR) for death was 1.33 (99% CI 1.03 to 1.72) for participants with one or more T alleles (p=0.027; ( Figure B )). On multivariate analysis, the HR for death was 1.28 (95% CI 0.99 to 1.66; p=0.060). Among subjects with the highest REVEAL2.0 risk, those with a T allele had worse survival than those no T allele, with best survival among those with low a REVEAL2.0 score and no T allele. Conclusions: In White PAH subjects, rs9493157 associates with human levels of serum CCN2, a known biomarker for PAH. While additional studies are warranted, the T allele associates with worse survival and may enhance the prognostic value of the REVEAL2.0 risk score.

Revolutionizing Cytology and Cytopathology with Natural Language Processing and Chatbot Technologies: A Narrative Review on Current Trends and Future Directions.

The application of chatbots and Natural Language Processing (NLP) in cytology and cytopathology is an emerging field, which is currently characterized by a limited but growing body of research. Here, a narrative review has been proposed utilizing a standardized checklist and quality control procedure for including scientific papers. This narrative review explores the early developments and potential future impact of these technologies in medical diagnostics. The current literature, comprising 11 studies (after excluding comments, letters, and editorials) suggests that chatbots and NLP offer significant opportunities to enhance diagnostic accuracy, streamline clinical workflows, and improve patient engagement. By automating the extraction and classification of medical information, these technologies can reduce human error and increase precision. They also promise to make patient information more accessible and facilitate complex decision-making processes, thereby fostering greater patient involvement in healthcare. Despite these promising prospects, several challenges need to be addressed for the full potential of these technologies to be realized. These include the need for data standardization, mitigation of biases in Artificial Intelligence (AI) systems, and comprehensive clinical validation. Furthermore, ethical, privacy, and legal considerations must be navigated carefully to ensure responsible AI deployment. Compared to the more established fields of histology, histopathology, and especially radiology, the integration of digital tools in cytology and cytopathology is still in its infancy. Building on the advancements in related fields, especially radiology's experience with digital integration, where these technologies already offer promising solutions in mentoring, second opinions, and education, we can leverage this knowledge to further develop chatbots and natural language processing in cytology and cytopathology. Overall, this review underscores the transformative potential of these technologies while outlining the critical areas for future research and development.

AI in Cytopathology: A Narrative Umbrella Review on Innovations, Challenges, and Future Directions.

The integration of artificial intelligence (AI) in cytopathology is an emerging field with transformative potential, aiming to enhance diagnostic precision and operational efficiency. This umbrella review seeks to identify prevailing themes, opportunities, challenges, and recommendations related to AI in cytopathology. Utilizing a standardized checklist and quality control procedures, this review examines recent advancements and future implications of AI technologies in this domain. Twenty-one review studies were selected through a systematic process. AI has demonstrated promise in automating and refining diagnostic processes, potentially reducing errors and improving patient outcomes. However, several critical challenges need to be addressed to realize the benefits of AI fully. This review underscores the necessity for rigorous validation, ongoing empirical data on diagnostic accuracy, standardized protocols, and effective integration with existing clinical workflows. Ethical issues, including data privacy and algorithmic bias, must be managed to ensure responsible AI applications. Additionally, high costs and substantial training requirements present barriers to widespread AI adoption. Future directions highlight the importance of applying successful integration strategies from histopathology and radiology to cytopathology. Continuous research is needed to improve model interpretability, validation, and standardization. Developing effective strategies for incorporating AI into clinical practice and establishing comprehensive ethical and regulatory frameworks will be crucial for overcoming these challenges. In conclusion, while AI holds significant promise for advancing cytopathology, its full potential can only be achieved by addressing challenges related to validation, cost, and ethics. This review provides an overview of current advancements, identifies ongoing challenges, and offers a roadmap for the successful integration of AI into diagnostic cytopathology, informed by insights from related fields.

OPTIMIZATION OF LC-MS/MS METHOD FOR THE SIMULTANEOUS DETERMINATION OF METFORMIN AND ROSIGLITAZONE IN HUMAN PLASMA WITH BOX-BEHNKEN DESIGN

Objective: The objective of this study was to develop a robust Liquid Chromatography – Tandem Mass Spectrometry (LC-MS/MS) methodology for the precise quantification of metformin and rosiglitazone in human plasma. Methods: A Design of Experiments (DOE) framework was utilized, specifically employing a Box-Behnken experimental design, to optimize critical parameters such as Capillary voltage, Cone voltage, Desolvation temperature, and Collision energy. Sample preparation involved protein precipitation using acetonitrile, simplifying the procedure. Chromatography was performed with a mobile phase of 0.1% formic acid and acetonitrile (60:40 V/V) to enhance sensitivity and reproducibility. Quantification was achieved through Multiple Reaction Monitoring (MRM) of the transition’s m/z 130.1 → m/z 60.1 for metformin, m/z 358.2 → m/z 134.9 for rosiglitazone, and m/z 206.3 → m/z 59.9 for phenformin. The methodology was validated according to regulatory guidelines. Results: The developed methodology demonstrated selectivity, linearity, accuracy, precision, recovery, and stability. The calibration curve showed linearity over the concentration range of 5 ng/ml to 1000 ng/ml for metformin and 1.5 ng/ml to 300 ng/ml for rosiglitazone. Accuracy and precision were within acceptable limits across calibration and quality control standards. Assessments of extraction recovery and matrix effects confirmed the robustness of the extraction procedure, with negligible interference from plasma components. Stability studies indicated that the method maintained acceptable limits for metformin and rosiglitazone concentrations under various storage and handling conditions. Conclusion: The validated Liquid Chromatography – Tandem Mass Spectrometry (LC-MS/MS) methodology provides a reliable and accurate platform for the quantification of metformin and rosiglitazone in human plasma. This method shows potential applications in pharmacokinetic studies and clinical research, ensuring consistent performance in routine analysis.

The clinical pathway in China county for lung cancer diagnosis and treatment (2024 edition)

Standardizing the diagnosis and treatment of lung cancer is a key measure to improve the survival rate of lung cancer patients and reduce the mortality rate. However, county hospitals generally face the problem of inaccessibility to advanced diagnostic and treatment technologies. Therefore, when developing quality control standards and clinical diagnosis and treatment specifications, it is necessary to combine the actual situation of county hospitals and formulate specific recommendations. The recommendations of treatment measures also need to consider the approval status of indications and whether it is included in the National Reimbursement Drug List (NRDL), to ensure the access to medicines. To address the above issues, based on the existing guidelines at home and abroad and the clinical work characteristics of county hospitals, the " the clinical pathway in China county for lung cancer diagnosis and treatment (2024 edition)" has been updated on the basis of the first edition. This pathway elaborated on the imaging diagnosis, pathological diagnosis, molecular testing, precision medicine, and developed different diagnosis and treatment processes for different types of lung cancer patients. Consistent with the first pathway, this update still divides the recommendations for diagnosis and treatment of clinical scenarios into basic strategies and optional strategies for elaboration. The basic strategies are the standards that county hospitals must meet, while the optional strategies provide more choices for hospitals, which are convenient for county doctors to put into clinical practice. All the recommended diagnostic and treatment plans strictly refer to existing guidelines and consensus. Compared to the first edition, based on the latest high-level evidence-based medicine and the approval status of indications, the pathway has updated the diagnosis and treatment recommendations for lung cancer under different pathological types, TNM classification, and molecular classification in basic and optional strategies.

A rapid protocol for distinguishing the quality of Sanshengyin and identifying potential markers by the “three-in-one” fingerprint profiles with antioxidant activity

It is imperative to establish a standardized model for the quality control of traditional prescriptions, exemplified by Sanshengyin (SSY). This study introduces a multi-component and multi-level "three-in-one" fingerprint quality evaluation system designed to predict the comprehensive quality of traditional Chinese medicine (TCM). Initially, a five-wavelength high-performance liquid chromatography (HPLC) fusion spectrum was developed to enhance the stability of SSY within the chromatographic system. Additionally, a quantification method was employed to streamline the calculation and visualization processes of ultraviolet (UV) and infrared (IR) spectral systems. Through this approach, chromatographic and spectral fingerprints were amalgamated into a holistic analytical strategy. The average linear quantitative fingerprint method (ALQFM) was employed to swiftly differentiate the grades of 17 sample batches. Additionally, six quality markers were identified for content determination. Correlation analysis between the total content of these quality markers and macroscopic quantitative similarity was conducted to assess the accuracy of ALQFM in evaluating the quality of TCM represented by SSY. Finally, the binary correlation analysis model was employed to investigate the correlation between antioxidant activity and fingerprint profiles, facilitating the prediction of potential bioactive compounds in SSY. This research offers a straightforward, cost-effective, and holistic approach for assessing the quality consistency of TCM. The method is recommended for adoption by medical institutions and enterprises to enhance the standardization of TCM quality control.

Survey on the current situation of human resources and basic configuration of the intensive care medicine in Xinjiang Production and Construction Corps from 2019 to 2021

To comprehensively understand the basic situation of critical care medicine in Xinjiang Production and Construction Corps in order to promote the standardization, specialization, and systematization of quality control in critical care medicine. A survey was conducted from January 1, 2019, to December 31, 2021, using a questionnaire to investigate the human resources and basic allocation of comprehensive intensive care medicine departments in Xinjiang Production and Construction Corps division level hospitals and surrounding second-class hospitals. The survey content includes: basic situation of medical units, intensive care unit (ICU) basic information, ICU personnel situation, ICU equipment configuration situation, ICU performance situation, etc. The survey questionnaire was distributed in March 2022, with dedicated ICU attending physicians or above designated by each ICU as the contact person for the survey. Sixteen questionnaires were distributed and returned, all of which were included from 16 comprehensive intensive care medicine departments in the Corps and surrounding areas, including 5 second class first class hospitals and 11 third class first class hospitals. There were 196 beds in 16 ICU units, and the ICU bed ratio (1.99% overall, 1.77% in third class first class hospitals) was lower than the 2%-8% stipulated in the Guidelines for the Construction and Management of Critical Care Medicine (Trial) issued by the National Health Commission. Only ICU beds in second class first class hospitals accounted for 2.65%, meeting this standard. The comprehensive ICU doctor-bed ratio in 16 hospitals was 0.55 : 1, third class first class hospitals was 0.60 : 1, and second class first class hospitals was 0.44 : 1, compared with 0.8 : 1 stipulated in the ministerial guidelines, there was a certain gap. Among the 108 doctors in 16 ICUs, only four have a master's degree or above. Associate senior and above professional and technical titles accounted for 27.78%, less than one third. Among the 334 nursing staff, there were no personnel with a master's degree or above, and only 10 personnel with associate senior or above professional and technical titles. From 2019 to 2021, there were 1 new master's degree personnel, 2 new senior professional and technical personnel, and 12 deputy senior professional and technical personnel. It indicating that the proportion of highly educated and experienced physicians and nurses were lower, team building lags behind, talent introduction were lower, and highly educated talents were scarce. The statistical analysis results of the absolute growth of core technology showed that the growth of core technology was slow, the progressiveness was insufficient, and the professional technical ability was insufficient. The construction of critical care majors and talent echelons in the Xinjiang Production and Construction Corps region is lagging behind, the overall professional level of the discipline is not high, and there is a lack of specialized personnel. Further improvement is needed in talent cultivation, technical development and training, medical quality management, and other aspects to ensure medical quality and safety.

Effects of Diversification Strategies on Organizational Competitiveness

The study examined the effects of diversification strategies on organizational competitiveness of selected manufacturing firms in Delta State. This study adopted a descriptive research design. The study's population included 100 personnel from the staff of the selected manufacturing firms in Delta State. The sampling technique that was used for the study is simple random technique. The sample size of 80 respondents for the study was determined using Taro Yamane’s formula. Data collected from the field survey were analyzed using descriptive statistics, correlation and multiple regression analyses. The researcher used self-developed questionnaire as instrument for data collection. Findings showed that product diversification strategy (ß = 0.431, p <0.05) and market diversification strategy (ß = 0.277, p<0.05) has significant positive effect on organizational competitiveness. Findings showed that 32% of the change in organizational competitiveness was brought about by the dimensions of diversification strategies. The study concluded that diversification strategies have positive effect on organizational competitiveness of selected manufacturing firms in Delta State. The study recommended that companies should maintain high standards of quality control for all products, including the newly diversified ones. Consistency in product quality is essential for building customer trust.

Quality control of eddy covariance fluxes of two ecosystem types with local flux-variance similarity functions in West Africa

Ecosystem capacity studies for carbon sequestration and water extraction are largely conditioned by Eddy Covariance (EC) measurement availability and quality. Our study aims at evaluating several procedures of EC data qualification. Indeed, quality control of EC data is generally ensured by stationarity and well-developed turbulence tests. The latter is based on integral turbulence characteristic (ITC) models. In this study, we revisited the quality control procedure using locally established ITC models for wind speed components and atmospheric scalars (temperature, humidity and carbon dioxide molar densities) in unstable and stable conditions. We also considered the interdependence of flux qualities because of the corrections applied to fluxes during their preprocessing. The analyses were carried out using one year of data collected above a woodland forest and mixed crop sites, both situated in Northern Benin, West Africa. From these analyzes we note that the quality flags vary depending on the use of local or existing ITC models. Also, the test of turbulence development on atmospheric scalars, previously neglected, is of great importance in the quality control of data. Thus, taking into account the ITC models associated with the atmospheric scalars established locally in the well-developed turbulence test as well as taking into account the interdependence of the flux quality have considerably improved the standard quality control procedure used in effectively filtering unrealistic flux data while keeping a considerable percentage of good and medium quality data.

Screening and Predictive Biomarkers for Down Syndrome Through Amniotic Fluid Metabolomics.

Down syndrome (DS) is a congenital disorder caused by the presence of an extra copy of all or part of chromosome 21. It is characterized by significant intellectual disability, distinct facial features, and growth and developmental challenges. The utilization of metabolomics to analyze specific metabolic markers in maternal amniotic fluid may provide innovative tools and screening methods for investigating the early pathophysiology of trisomy 21 at the functional level. Amniotic fluid samples were obtained via amniocentesis from 57 pregnancies with DS and 55 control pregnancies between 173/7 and 240/7weeks of gestation. The targeted metabolomics focused on 34 organic acids, 17 amino acids, and 5 acylcarnitine metabolites. The untargeted metabolomics analysis concentrated on lipid profiles and included 602 metabolites that met quality control standards. Principal Component Analysis, Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA), and false discovery rate (FDR) adjustments were applied. MetaboAnalystR 5.0 was used to perform the metabolic pathway analysis on the identified differential metabolites. Fifty differential metabolites, including L-glutamine, eight organic acids, and 41 lipids, were significantly altered in DS based on three criteria: VIP > 1 in the OPLS-DA model, FDR-adjusted p-value < 0.05, and |log2FC|>log2(1.5) from a volcano plot of all detected metabolites. An analysis of 212 differential metabolites, selected from both targeted and untargeted approaches (VIP > 1 in the OPLS-DA model and FDR-adjusted p-value < 0.05), revealed significant changes in nine metabolic pathways. Fourteen key metabolites were identified to establish a screening model for DS, achieving an area under the curve of 1.00. Our results underscore the potential of metabolomics approaches in identifying concise and reliable biomarker combinations that demonstrate promising screening performance in DS.

Disparities in SGLT2i utilization among heart failure patients with different ejection fraction in China: findings from chinese cardiovascular association database-heart failure center registry

Abstract Background Sodium-glucose cotransporter-2 inhibitors (SGLT2i) are recommended for heart failure (HF) patients regardless of left ventricular ejection fraction (LVEF). Although Chinese HF guidelines still recommend traditional renin–angiotensin–aldosterone system inhibitors, beta blockers, mineralocorticoid receptor antagonists, the Chinese Cardiovascular Association (CCA) HF Center Registry has launched a project to promote the guideline-directed medical therapy (GDMT) for HF patients in China. However, data on the utilization of GDMT in Chinese HF patients is scarce, especially SGLT2i. Purpose We aimed to investigate the usage status of SGLT2i in HF patients with different LVEFs and explore associated factors with SGLT2i adoption in hospitalized HF Chinese patients. Methods This is a retrospective real world study using data from the CCA Database-HF Center Registry. The study included HF patients hospitalized in 52 secondary or tertiary hospitals, including 26 accredited heart failure centers (HFC) and 26 non-accredited heart failure centers (NHFC). Centers that meet the 25 quality control standards established by CCA can be accredited as HFC. We evaluated the use rate of SGLT2i overall and by HF type, as well as the change of SGLT2i usage rate at discharge during the study period from 1st July 2022 to 31st March 2023. LASSO and multivariable logistic regression were also used to explore associated factors of SGLT2i adoption at discharge. Result We included 8,843 hospitalized HF patients: 5,326 (60.2%) were male, 2,980 (33.7%) HFrEF, 1,624 (18.4%) HFmrEF, 3,653 (41.3%) HFpEF and 586 (6.6%) lacked EF data. Overall, SGLT2i were adopted in 3,666 (41.5%) HF patients at discharge (58.1% in HFrEF, 45.3% in HFmrEF, 28.8% in HFpEF). Overall, the usage rate of SGLT2i at discharge rose from 35.2% to 50.2%. Specifically, for HFrEF patients, there was a rise from 56.2% to 64.4%. For HFmrEF and HFpEF patients, the usage rate increased from 37.5% to 54.4% and from 22.2% to 35.7%, respectively (Figure 1). The usage rate of SGLT2i was higher in HFC compared with NHFC (47.1% vs. 35.8%, p&amp;lt;0.001). In multivariable logistic regression, older age, new-onset heart failure, hospital location, etc. were associated with a lower usage rate of SGLT2i at discharge. In contrast, HFC, dilated cardiomyopathy, obesity, etc. were associated with a higher utilization rate of SGLT2i (Figure 2). HF classification by LVEF was also an independent influencing factor even after adjusting other factors; when HFrEF was used as a reference, the use rate of SGLT2i was lower in HFmrEF (OR 0.79, 95% CI 0.69 - 0.91) and HFpEF (OR 0.44, 95% CI 0.39 - 0.49). Conclusion In clinical practice in China, the usage rate of SGLT2i for HF treatment is increasing but needs to be further improved. Disparities exist in usage rates among HF patients with different LVEFs. Addressing this disparity necessitates a targeted approach, emphasizing increased utilization in HF patients regardless of LVEF.SGLT2i usage rate in HFFactors affecting SGLT2i adoption in HF

Performance of the polyurethane foam injection technique for road maintenance applications

Road infrastructure plays an important role in strengthening transportation and driving the economic advancement of countries. However, the increasing traffic volume has accelerated road deterioration, particularly at critical points like bridge-road junctions. Traditional repair methods involving demolition and reconstruction lead to extended closures and high costs. This study explores the polyurethane (PU) foam injection technique as an alternative solution, which can reduce both repair time and costs. The research evaluates the application of PU foam in various road projects across Thailand, highlighting its ability to repair pavement surfaces and structures, even in severely damaged areas. Despite its advantages, the use of PU foam faces challenges due to a lack of standardized quality control. This paper proposes a set of working guidelines for PU foam injection, aimed at key stakeholders such as the Department of Highways, the Department of Rural Roads, and the Department of Local Administration. The findings underline the importance of establishing standardized methods to ensure the long-term effectiveness of PU foam in road maintenance. Future research should focus on refining these guidelines for diverse road conditions to support the sustainable development of national transportation infrastructure.

SWQC: Efficient sequencing data quality control on the next-generation sunway platform

Sequencing data quality control can significantly prevent low-quality data from impacting downstream applications in bioinformatics. The enormous growth of biological sequencing data in recent years introduces new challenges to the efficiency of quality control processes and motivates the need for fast implementations on modern compute systems. The powerful next-generation heterogeneous Sunway platform holds significant potential for addressing this challenge. However, there are currently no dedicated quality control applications that can fully utilize its computational power. To bridge this gap, we introduce SWQC, a novel quality control application specifically designed for the Sunway platform. We present an efficient distributed FASTQ I/O framework for Sunway-based workstations and supercomputers to take advantage of fast SSDs and the parallel file system. In order to support both process-level and thread-level (CPE-level) parallelism to leverage the computational power, we refactor and optimize all standard quality control modules for the heterogeneous Sunway architecture. When using a single node, SWQC achieves speedups between 2 and 40 over highly optimized quality control applications executed on a high-end 48-core AMD server. Additionally, when using 16 nodes, SWQC achieves parallel efficiencies of 70% (for reading and writing a single file) and 95% (for reading one file and writing split files) compared to a single node. Overall, SWQC is able to perform quality control operations for a 140GB FASTQ file within only 70 s using a single Sunway node. It is publicly available at https://github.com/RabbitBio/SWQC.