Quality Control Procedures Research Articles

The effect of androgens on the risk of endometriosis sub-phenotypes and ovarian neoplasms: A Mendelian randomization study

Endometriosis is a complex gynecological pathology with a broad spectrum of symptoms, affecting around 10% of reproductive-aged women. Ovarian cancer (OC) is a heterogeneous disease for which we lack effective diagnostic and therapeutic strategies. The etiology and pathogenesis of both diseases remain ambiguous. Androgens in endometriosis could have a distinct role beyond serving as estrogen sources, whereas in the case of serous OC could be important in the formation of precursor lesions which ultimately lead to tumor formation. Here we performed two-sample Mendelian randomization (MR) analysis to examine the causal relationship between the androgen precursor - dehydroepiandrosterone sulphate (DHEAS), bioactive androgen - testosterone (T), androgen metabolite - androsterone sulphate, steroid hormone binding globulin (SHBG) and albumin and the risk of endometrioses of various sub-phenotypes and ovarian neoplasms across the benign-borderline-malignant spectrum. Stringent quality control procedures were followed to select eligible instrumental variables that were strongly associated with the selected exposures, sensitivity analyses were performed to assess the heterogeneities, horizontal pleiotropy, and stabilities of SNPs in endometriosis and ovarian neoplasms. We discovered an inverse association between genetically predicted levels of all androgens and risk of endometriosis, the same trend was most evident in the ovarian sub-phenotype. Total T levels were also inversely associated with peritoneal sub-phenotype of endometriosis. Likewise, T was causally associated with decreased risk of clear-cell OC, an endometriosis-associated OC subtype, and with malignant serous OC of both low- and high-grade, but with higher risk of their counterpart of low malignant potential. These findings support further investigation of androgen’s action at a molecular level in ovary-associated endometriotic lesions, clear cell ovarian tumors and serous precursor lesions.

Adolescent to young adult longitudinal development of subcortical volumes in two European sites with four waves.

Adolescent subcortical structural brain development might underlie psychopathological symptoms, which often emerge in adolescence. At the same time, sex differences exist in psychopathology, which might be mirrored in underlying sex differences in structural development. However, previous studies showed inconsistencies in subcortical trajectories and potential sex differences. Therefore, we aimed to investigate the subcortical structural trajectories and their sex differences across adolescence using for the first time a single cohort design, the same quality control procedure, software, and a general additive mixed modeling approach. We investigated two large European sites from ages 14 to 24 with 503 participants and 1408 total scans from France and Germany as part of the IMAGEN project including four waves of data acquisition. We found significantly larger volumes in males versus females in both sites and across all seven subcortical regions. Sex differences in age-related trajectories were observed across all regions in both sites. Our findings provide further evidence of sex differences in longitudinal adolescent brain development of subcortical regions and thus might eventually support the relationship of underlying brain development and different adolescent psychopathology in boys and girls.

Characterization and comparability study of a series of miniaturized neon plasma jets

During the development of new therapeutic devices, comprehensive experimental investigations are necessary in all phases of the process. This requires the provision of device prototypes with reproducible and comparable operating parameters. In the current study, such miniature neon plasma jet prototypes designated for medical applications have been manufactured, characterized, and compared. The multi-parametric characterization included measurements of energy, power, temperature, leakage current, effluent length, and relative as well as absolute radiation. The dissipated electrical power and the optical emission in the UV range were identified as parameters indicating definable tolerances to sort out a device with inadequate species output. A liquid phase model was used to investigate reactive species deposition into simple matrices. Based on these investigations, a quality control procedure for manufacturing new device series is proposed. In conclusion, our findings suggest a test concept of achieving reproducible and comparable plasma device characterization as a putative quality control measure for lab-scale plasma source production.

The analysis of approaches to assessing the sugar content of fruit and vegetable products

The relevance of this study is due to the growing interest of modern consumers in healthy eating, where fruit and vegetables play an important role, which should not only be aesthetically pleasing but also have high taste potential. The purpose of the article is to analyse and compare different approaches to assessing the sugar content of fruit and vegetable products, their effectiveness, and to substantiate areas for improvement. For this purpose, the author analysed the literature and regulatory and technical documents. Traditional methods for determining the sugar content are considered: total content, soluble solids content, and total soluble solids content. It has been established that the soluble solids content and the total soluble solids content of fruits cannot be equated and should be adjusted using an appropriate coefficient based on the percentage of sugars. It has been shown that the content of total soluble substances does not always correctly reflect the sugar content and does not correlate with the taste of sweetness of fruit and vegetables. The necessity of taking into account acidity, which significantly affects the perception of sweet taste, has been established. High acidity can inhibit the sweet taste of fruit and vegetables, even with a very high sugar content. It is proposed to use the ratio of sugar content to titratable acidity for a comprehensive assessment of the sugar content and taste of products. The necessity of using the BrimA and sweetness indices, which combine the indicators of sugars and acidity, as well as reflect the contribution of a single carbohydrate to the total sugar content of the product, is substantiated. These indices allow for a comprehensive assessment of sugar content and predict the sensory perception of fruit and vegetable raw materials. The absence of a single standardised approach and the need for comparative analysis to select optimal methods for measuring the sugar content of fruit and vegetable products are noted, so there is an urgent need to standardise such approaches to improve data comparison. The results of the article can be used to select the most informative methods of sugar content analysis. This will optimise quality control procedures and standardisation of measurements in the food industry

Advancement in Sustainable 3D Concrete Printing: A Review on Materials, Challenges, and Current Progress in Australia

Three-dimensional concrete printing (3DCP) is a sustainable and green approach for rapid construction with the ability to create complex shapes to preserve the intended aesthetic appearance for an affordable cost. Even after a decade of attempts, there are many limitations and challenges to applying this technology for constructions without borders. The lack of guidelines for mix designs, quality control procedures during extrusion, printing and building phases, compatibility of material with extruder, standard testing, and guidelines to verify suitability of mixture with respect to the application and exposure conditions and limited machine capacity are several areas to be addressed for applications without borders. The development of 3DCP applications as a sustainable and green technology is another challenging task due to high Portland cement consumption in 3DCP. However, reducing the high usage of ordinary Portland cement (OPC) with pozzolanic waste materials replacement and environmentally friendly cement indicates the direction of moving 3DCP into a sustainable pathway. The authors reviewed more than 200 refereed articles published on materials and techniques in 3DCP. Inconsistency in disseminating knowledge in research articles has hindered the creation of a monolithically connected chain of research efforts and findings in accelerating the development and adoption of this technology. This paper summarizes the common approach to developing 3DCP mix designs and identifies the key areas for the future development of materials and techniques and challenges to be addressed for the global adoption of 3DCP. The current progress and challenges in the context of Australia’s construction industry and future trends for the acceptance of 3DCP are also reviewed.

Evaluation and standarisation of Shatavaryadi Churna

Introduction-The Ayurvedic medical system has recently got a lot of medical and healthcare services in India. To evaluate the quality, safety, and effectiveness of the medicine, standards and purity of herbal formulation are crucial. However, pharmacopoeia testing is the protocol that all medicines must follow in order to be accepted globally. A compound herbal formulation called Shatvaryadi Churna is suggested for the treatment of a number of diseases. For the treatment of Timira Vyadhi, patal vyadhi, kancha vyadhi and many other raktaj vikara the formulation was documented in the Ayurvedic classic Yoga Ratnakar. Materials & methods- Shatavaryadi Churna was made by using the standard procedure with all aseptic precautions and as described in the Ayurvedic Pharmacopoeia for Churna Kalpana (Powder Preparation). The manufactured medication has been standardised by adhering to the approved pharmacopeial protocol for quality control procedures. Results- Organoleptic parameters, physiochemical evaluation, and microbiological load test was done these analytical values were within the expected limits.

Uncertainties of Drag Coefficient Estimates Above Sea Ice from Field Data

Surface turbulent exchanges play a key role on sea ice dynamics, on ocean and sea ice heat budgets and on the polar atmosphere. Uncertainties in parameterizations of surface turbulent fluxes are mostly held by the transfer coefficients and estimates of those transfer coefficients from field data are required for parameterization development. Measurement errors propagate through the computation of transfer coefficients and contribute to its total error together with the uncertainties in the empirical stability functions used to correct for stability effects. Here we propose a methodology to assess their contributions individually to each coefficient estimate as well as the total drag coefficient uncertainty and we apply this methodology on the example of the SHEBA campaign. We conclude that for most common drag coefficient values (between 1.0×10-3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$1.0\ imes 10^{-3}$$\\end{document} and 2.5×10-3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$2.5\ imes 10^{-3}$$\\end{document}), the relative total uncertainty ranges from 25 and 50%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document}. For stable or unstable conditions with a stability parameter |ζ|>1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$|\\zeta |>1$$\\end{document} on average, the total uncertainty in the neutral drag coefficient exceeds the neutral drag coefficient value itself, while for |ζ|<1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$|\\zeta |<1$$\\end{document} the total uncertainty is around 25%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document} of the drag coefficient. For closer-to-neutral conditions, this uncertainty is dominated by measurement uncertainties in surface turbulent momentum fluxes which should therefore be the target of efforts in uncertainty reduction. We also propose an objective data-screening procedure for field data, which consists of retaining data for which the relative error on neutral drag coefficient does not exceed a given threshold. This method, in addition to the commonly used flux quality control procedure, allows for a reduction of the drag coefficient dispersion compared to other data-screening methods, which we take as an indication of better dataset quality.

Computational validation of clonal and subclonal copy number alterations from bulk tumor sequencing using CNAqc

Copy number alterations (CNAs) are among the most important genetic events in cancer, but their detection from sequencing data is challenging because of unknown sample purity, tumor ploidy, and general intra-tumor heterogeneity. Here, we present CNAqc, an evolution-inspired method to perform the computational validation of clonal and subclonal CNAs detected from bulk DNA sequencing. CNAqc is validated using single-cell data and simulations, is applied to over 4000 TCGA and PCAWG samples, and is incorporated into the validation process for the clinically accredited bioinformatics pipeline at Genomics England. CNAqc is designed to support automated quality control procedures for tumor somatic data validation.

SIX SIGMA METRICS: INDICATOR OF QUALITY ASSURANCE FOR CLINICAL BIOCHEMSITRY

Introduction: In present scenario Quality is the important aspect of laboratory practices. Mostly internal and external quality control are utilized to maintain quality in laboratory. Quality assurance of laboratory services is the need of present time in health care which require Quality Planning, Quality Control (QC), Quality Assessment (QA) and Quality Improvement . Aims &amp; Objectives: 1. To quantify the defects and errors in analytical phase of laboratory testing by sigma metrics and to represent the calculated sigma value. 2. Application of six sigma test in laboratory with the IQC and EQAS to maintain quality laboratory services. Methodology: Study was conducted at Clinical Biochemistry Laboratory, GMC Akola. We run IQC samples on daily basis and EQAS samples are running on monthly basis. Retrospectively we utilized data of IQC and EQAS from January to October 2023 for 16 Biochemical Analytes. Sigma metrics for each parameter was calculated. Result: The sigma metrics for IQC indicated that 1 out of 16 analytes qualified six sigma quality performance. Of these 15 analytes performance with sigma metrics was beteween three and six. We found different sigma value like more than6 for only HDL cholesterol and more than 3 for Amylase, Total Bilirunbin, Creatinine, Cholesterol, Glucose, Phosphorus, total Protein , SGPT , TG, UA, Urea, SGOT, which is among the acceptable range of performance. Conclusion: In our study sigma value was highest for HDL cholesterol and other 15 analytes show sigma value between 3 to 6 which is acceptable range. Sigma analysis is a continuous procedure and by taking the help of method decision chart we can improve on decision on making in clinical chemistry laboratory regarding optimising QC procedure.

Australian Ocean surface waves dataset from SAR

AbstractIn this article, a regional ocean surface waves dataset from Sentinel‐1 A and B Synthetic Aperture Radar (SAR) satellites has been described. The ocean wave data have been extracted from the Sentinel‐1 level‐2 OCN (ocean) product as provided by the European Space Agency and downloadable for this region from the Copernicus Australasia regional data hub. The source OCN data have been produced by evolving versions of Sentinel‐1 Instrument Processing Facility (IPF). The structure of the source OCN NetCDF files changes over time and presents a challenge in performing long duration, time series analyses, including the examination of potential inconsistencies in OCN wave data, due to employment of different IPF versions over the duration of the satellite missions. Here, the input OCN wave data have been homogenized to a single, easily usable standard format after applying a quality assurance and control procedure that removes various inconsistencies in variables, coordinates, dimensions and land flag, and through the addition of new auxiliary variables. The new format has the desirable properties of being compact in size, consistent in structure, and scalable in temporal and spatial coverage. It is also convenient to use and offers opportunities to perform fast, multi‐year regional processing and analysis for calibration and validation studies and scientific applications. No re‐processing of Sentinel‐1 level‐1 data has been carried out in this work.

Direct voxel classification from x-ray projections for 3D pore detection applied to laser sintered parts

X-ray computed tomography (XCT) is a validated and frequently used tool to verify part geometry and to perform a non-destructive inspection of additive manufacturing parts. However, the acquisition of a large number of x-ray projections generates long inspection times. This conflicts with a high throughput of the production process and hinders the integration of XCT as an in-line quality control procedure for low-end parts. In this paper, we propose a method to obtain three-dimensional (3D) information of the internal pores from a limited view or limited angle scan. The method combines a forward projection model of a cone-beam x-ray system and a deep learning neural network to directly classify each individual voxel, based on the x-ray projections in order to avoid the reconstruction and segmentation step. Accompanying reconstruction artifacts for limited view and limited angle XCT scans are thereby reduced, while preserving 3D information of the pores, defects or inclusions inside the material. The method is validated on real x-ray projections of polymer laser sintered industrial parts and shows a significant reduction in the required x-ray projections, hence acquisition time.

Study of Pre-Analytical Errors in Laboratory &amp; Steps to Improve

Objectives: Pre-analytical errors decisively influence the total laboratory errors and consequently the diagnostic accuracy. The following were the objectives of the study. 1) To detect the percentage of pre-analytical errors in venous specimens in Laboratory. 2) To categorize these pre-analytical errors. 3) To formulate steps of corrective measures to avoid such type of errors. Study Design and Result: Type of Study - Retrospective study. Study period - 12 months (June 2015 to May 2016), documenting the frequency and type of pre-analytical errors. Results: Total number of pre-analytical errors detected in the period of 12 months’ study were 180. Improper timing of specimens, hemolyzed &amp; clotted specimens and improper requests were the major concerns followed by delay in specimen transport. Conclusion: Pre-analytical phase is an important component of Total Laboratory Quality. Pre-analytical errors are not inevitable and can be avoided or minimized with diligent application of quality control, continuing education, effective protocols, and standardized procedures for effective blood collection systems to ensure total Quality patient care.

Welding processes in the restoration of industrial and energy facilities

The research relevance is determined by the constant development and changes in the production environment and technological requirements to ensure increased safety, durability, and efficiency of industrial and energy facilities. The study aims to analyse methods and strategies for improving the efficiency of welding and joint quality control, to achieve greater stability and reliability of energy facilities. The methods used include observation, comparative and descriptive, monitoring, abstraction, and others. The study analysed various welding technologies and their impact on the quality of welded joints. Various methods of calculating welded structures concerning materials and technical requirements were considered. In addition, various methods of quality control of welded joints, including visual inspection and non-destructive testing, were investigated. The study determined that the correct choice of technology, calculations and quality control can improve the strength, reliability, safety, and economic feasibility of welded structures. The studied welding technologies and quality control methods used are more effective for use in specific conditions and there is no general solution. In addition, the proper application of these methods demonstrated that they can significantly reduce the recovery time and increase the overall productivity of the process of restoring industrial and energy facilities. Therefore, the optimal use of welding technologies and quality control methods can significantly improve the efficiency and durability of industrial and energy facilities. The practical significance of the study is to contribute to improving the safety, reliability, and efficiency of the rehabilitation of industrial and energy facilities by improving the quality control procedures for welded joints

Use of ultrasound and NIRs as tools for monitoring ice formation in superchilled meat

This study aimed to gain a deeper understanding of the ice crystal formation during the superchilling process (SC) of meat by using non-destructive methods. Ultrasound inspection was performed considering the ultrasonic pulse velocity (UPV), while Near Infrared Spectroscopy (NIR) measurements were carried out with a spectral range of 950–1650 nm. Signals from both methodologies were periodically taken during the controlled freezing of 8 beef cubic samples of (6 cm3). Obtained results revealed that both methods have the ability to detect the ice crystal formation during the SC process, and particularly during the period of thermal arrest. Hence, these results evidence that ultrasound inspection and NIR, combined with Multivariate Statistical Process Control charts, could be implemented as quality control procedures during the SC process of muscle foods, allowing a more accurate control of the process and thus, minimizing the potential deleterious effects of ice crystals formation in meat.

Genetic interactions of schizophrenia using gene-based statistical epistasis exclusively identify nervous system-related pathways and key hub genes.

Background: The relationship between genotype and phenotype is governed by numerous genetic interactions (GIs), and the mapping of GI networks is of interest for two main reasons: 1) By modelling biological robustness, GIs provide a powerful opportunity to infer compensatory biological mechanisms via the identification of functional relationships between genes, which is of interest for biological discovery and translational research. Biological systems have evolved to compensate for genetic (i.e., variations and mutations) and environmental (i.e., drug efficacy) perturbations by exploiting compensatory relationships between genes, pathways and biological processes; 2) GI facilitates the identification of the direction (alleviating or aggravating interactions) and magnitude of epistatic interactions that influence the phenotypic outcome. The generation of GIs for human diseases is impossible using experimental biology approaches such as systematic deletion analysis. Moreover, the generation of disease-specific GIs has never been undertaken in humans. Methods: We used our Indian schizophrenia case-control (case-816, controls-900) genetic dataset to implement the workflow. Standard GWAS sample quality control procedure was followed. We used the imputed genetic data to increase the SNP coverage to analyse epistatic interactions across the genome comprehensively. Using the odds ratio (OR), we identified the GIs that increase or decrease the risk of a disease phenotype. The SNP-based epistatic results were transformed into gene-based epistatic results. Results: We have developed a novel approach by conducting gene-based statistical epistatic analysis using an Indian schizophrenia case-control genetic dataset and transforming these results to infer GIs that increase the risk of schizophrenia. There were ∼9.5 million GIs with a p-value 1 10-5. Approximately 4.8 million GIs showed an increased risk (OR > 1.0), while ∼4.75 million GIs had a decreased risk (OR <1.0) for schizophrenia. Conclusion: Unlike model organisms, this approach is specifically viable in humans due to the availability of abundant disease-specific genome-wide genotype datasets. The study exclusively identified brain/nervous system-related processes, affirming the findings. This computational approach fills a critical gap by generating practically non-existent heritable disease-specific human GIs from human genetic data. These novel datasets can train innovative deep-learning models, potentially surpassing the limitations of conventional GWAS.

Improved resistive plate chambers for HL-LHC upgrade of CMS

In view of the High Luminosity LHC, the CMS Muon system will be upgraded to sustain its efficient muon triggering and reconstruction performance. Resistive Plate Chambers (RPC) are dedicated detectors for muon triggering due to their excellent timing resolution. The RPC system will be extended up to 2.4 in pseudorapidity. Before the LHC Long Shutdown 3, new RE3/1 and RE4/1 stations of the forward Muon system will be equipped with improved Resistive Plate Chambers (iRPC) having, compared to the present RPC system, a different design and geometry and 2D strip readout. This advanced iRPC geometry configuration allows the rate capability to improve and hence survive the harsh background conditions during the HL-LHC phase. Several iRPC demonstrator chambers were installed in CMS during the recently completed 2nd Long Shutdown to study the detector behaviour under real LHC conditions. This paper summarizes the iRPC project and its schedule, including the status of the iRPC production sites, details of the chamber quality control procedures and results of the commissioning of the demonstrator chambers.

Effective constituents and protective effect of Mudan granules against Schwann cell injury

Ethnopharmacological relevanceDiabetic peripheral neuropathy (DPN) is the most common complication of diabetes. Mudan granules (MD) is a Chinese patent medicine for treating DPN, which is composed of nine Chinese medicinal herbs, including the radix of Astragalus membranaceus (Fisch.) Bge. var. mongholicus (Bge.) Hsiao or Astragalus membranaceus (Fisch.) Bge. (Huangqi in Chinese), rhizome of Corydalis yanhusuo W.T. Wang (Yanhusuo), radix and rhizome of Panax notoginseng (Burk.) F. H. Chen (Sanqi), radix of Paeonia lactiflora Pall. or Paeonia veitchii Lynch (Chishao), radix and rhizome of Salvia miltiorrhiza Bge. (Danshen), rhizome of Ligusticum chuanxiong Hort. (Chuanxiong), flowers of Carthamus tinctorius L. (Honghua), lignum of Caesalpinia sappan L. (Sumu), and caulis of Spatholobus suberectus Dunn (Jixueteng). MD was reported to have a protective effect on Schwann cell (SC) that is considered as an important therapeutic target of DPN. However, the constituents of MD have not been reported, and the effective constituents and protective pathways for MD against SC injury remain unclear. Aim of the studyThis study aimed to identify the constituents in MD, and to investigate the effective constituents and protective pathways of MD against high-glucose/lipid injury in SC. Materials and methodsThe chemical constituents of MD were identified using ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS). Protective effect and effective constituents screening were performed in an in vitro SC injury model induced by high glucose and lipid levels. The protective pathways of MD and its effective constituents were investigated by western blotting assay of related proteins. ResultsA total of 136 constituents were identified in MD. MD downregulated the phosphorylation of extracellular-regulated protein kinases 1/2 (ERK1/2) and expression of cyclooxygenase-2 (COX-2) and upregulated the expression of sirtuin 2 (SIRT2). Seven effective constituents were screened out, including three from Sanqi [20(R)-ginsenoside Rh2, 20(S)-ginsenoside Rh2, and ginsenoside Rk3], one from Huangqi (astragaloside II), one from Danshen (danshensu), and two from Chuanxiong (chlorogenic and cryptochlorogenic acid). Six of the seven compounds, excluding danshensu, inhibited the phosphorylation of ERK1/2. Both astragaloside II and chlorogenic acid upregulated the expression of SIRT2, and cryptochlorogenic acid and danshensu downregulated the expression of COX-2. ConclusionsThe constituents of MD were firstly identified, and seven effective constituents were found. MD can protect SC against high-glucose and -lipid injury by downregulating ERK1/2 phosphorylation and COX-2 expression and upregulating SIRT2 expression. Seven effective constituents regulated the expression of these proteins. This study presented an important advance toward elucidating the chemical constituents, and the effective constituents and protective pathways of MD against high-glucose/lipid injury in SC, which is very helpful for investigating the action mechanism of MD on treating DPN, and could ultimately inform the development of effective quality control procedures for MD production.

Impact of Adjusted and Nonadjusted Surface Observations on the Cold Season Performance of the Canadian Precipitation Analysis (CaPA) System

Abstract The Canadian Precipitation Analysis System (CaPA) is an operational system that uses a combination of weather gauge and ground-based radar measurements together with short-term forecasts from a numerical weather model to provide near-real-time estimates of 6- and 24-h precipitation amounts. During the winter season, many gauge measurements are rejected by the CaPA quality control process because of the wind-induced undercatch for solid precipitation. The goal of this study is to improve the precipitation estimates over central Canada during the winter seasons from 2019 to 2022. Two approaches were tested. First, the quality control procedure in CaPA has been relaxed to increase the number of surface observations assimilated. Second, the automatic solid precipitation measurements were adjusted using a universal transfer function to compensate for the undercatch problem. Although increasing the wind speed threshold resulted in lower amounts and worse biases in frequency, the overall precipitation estimates are improved as the equitable threat score is improved because of a substantial decrease in the false alarm ratio, which compensates the degradation of the probability of detection. The increase of solid precipitation amounts using a transfer function improves the biases in both frequency and amounts and the probability of detection for all precipitation thresholds. However, the false alarm ratio deteriorates for large thresholds. The statistics vary from year to year, but an overall improvement is demonstrated by increasing the number of stations and adjusting the solid precipitation amounts for wind speed undercatch.

Impact of HY‐2B SMR radiance assimilation on CMA global medium‐range weather forecasts

AbstractThe Chinese second ocean dynamic environment satellite Haiyang‐2B (HY‐2B) was successfully launched on October 25, 2018, carrying a scanning microwave radiometer (SMR) to provide information about the ocean and atmosphere. For the first time, this study investigated the impact of radiance data from the HY‐2B SMR in the four‐dimensional variational (4DVar) data assimilation system of the Global Forecast System developed by the China Meteorology Administration (CMA‐GFS). Prior to the radiance assimilation, we evaluated the data quality and developed suitable quality control (QC) procedures for the HY‐2B SMR observations. In addition, the cloud liquid water path (CLWP) and ocean wind speed (OWS) were introduced as new bias correction (BC) predictors to remove the systematic bias originating from the forward operator in the CMA‐GFS 4DVar system. The assimilation effects of SMR observations were evaluated through one‐month cycling experiments. Verification with independent observations and reanalysis data has demonstrated that assimilating SMR clear‐sky radiance can greatly reduce the analysis errors for temperature and humidity, while indirectly improving the quality of wind analysis. Furthermore, significant improvements in geopotential height forecasts were found for days 1–5 in the lower troposphere of the tropical region.

Single-cell RNA-Seq Elucidates the Crosstalk Between Cancer Stem Cells and the Tumor Microenvironment in Hepatocellular Carcinoma.

Background: The challenge of systemic treatment for hepatocellular carcinoma (HCC) stems from the development of drug resistance, primarily driven by the interplay between cancer stem cells (CSCs) and the tumor microenvironment (TME). However, there is a notable dearth of comprehensive research investigating the crosstalk between CSCs and stromal cells or immune cells within the TME of HCC. Methods: We procured single-cell RNA sequencing (scRNA-Seq) data from 16 patients diagnosed with HCC. Employing meticulous data quality control and cell annotation procedures, we delineated distinct CSCs subtypes and performed multi-omics analyses encompassing metabolic activity, cell communication, and cell trajectory. These analyses shed light on the potential molecular mechanisms governing the interaction between CSCs and the TME, while also identifying CSCs' developmental genes. By combining these developmental genes, we employed machine learning algorithms and RT-qPCR to construct and validate a prognostic risk model for HCC. Results: We successfully identified CSCs subtypes residing within malignant cells. Through meticulous enrichment analysis and assessment of metabolic activity, we discovered anomalous metabolic patterns within the CSCs microenvironment, including hypoxia and glucose deprivation. Moreover, CSCs exhibited aberrant activity in signaling pathways associated with lipid metabolism. Furthermore, our investigations into cell communication unveiled that CSCs possess the capacity to modulate stromal cells and immune cells through the secretion of MIF or MDK, consequently exerting regulatory control over the TME. Finally, through cell trajectory analysis, we found developmental genes of CSCs. Leveraging these genes, we successfully developed and validated a prognostic risk model (APCS, ADH4, FTH1, and HSPB1) with machine learning and RT-qPCR. Conclusions: By means of single-cell multi-omics analysis, this study offers valuable insights into the potential molecular mechanisms governing the interaction between CSCs and the TME, elucidating the pivotal role CSCs play within the TME. Additionally, we have successfully established a comprehensive clinical prognostic model through bulk RNA-Seq data.