Toad skin (Bufo bufo gargarizans Cantor), known as Chan Pi in traditional Chinese medicine, has long been recognized for its therapeutic potential, particularly in cancer treatment. While the pharmacological activities of small molecules in toad skin such as bufadienolides have been extensively studied, peptides—another class of bioactive molecules—remain largely unexplored. In this study, we employed a peptidomics-based approach combined with in silico screening and experimental validation to identify novel bioactive peptides with potential anticancer properties from toad skin extracts. Approximately 2500 distinct peptides were identified using both database searching and de novo sequencing. Computational screening with two predictive models identified 26 candidate peptides with bioactivity scores exceeding 0.75. Among them, three peptides with potential anti-lung cancer activity were synthesized for in vitro evaluation against NSCLC cell lines, A549 and H1975. Peptide STPECLLGMWK exerts selective anti-proliferative effects on TKI resistant H1975 lung cancer cells in a dose-dependent manner. These findings provide new insights into the peptide composition of toad skin extracts and highlight their potential as a source of novel anticancer agents, laying the groundwork for future cancer therapeutics development.

The development of novel ferroptosis inhibitor reprensents a promising strategy for neurodegenerative diseases, driving the urgent need for developing therapeutic agents that can effectively modulating ferroptosis. In this study, we designed and synthesized a series of novel C2-functionalized quinazolinone derivatives. Systematic screening identified compounds 8f and 8h as selective ferroptosis inhibitor in HT-22 cell. Compound 8h exhibited superior neuroprotective activity in vitro and in zebrafish model in vivo. Preliminary mechanistic studies revealed that compound 8h exerted synergistic effects through dual activation of Steap4 and glutathione peroxidase 4 (GPX4), thereby maintaining iron metabolism homeostasis, clearing phospholipid hydroperoxides, and attenuating lipid peroxidation and reactive oxygen species accumulation. Overall, this work is the first to report the 2-benzoyl-quinazolinones scaffold as effective ferroptosis inhibitor. Compound 8h, in particular, emerges as a promising candidate warranting further development for the treatment of Parkinson's disease (PD).

Objectives Free triiodothyronine (FT3) and free thyroxine (FT4) are important diagnostic markers for assessing thyroid function. However, their accurate quantification remains challenging due to low serum concentrations. Significant variability exists among current assay methods for measuring FT3 and FT4. This study aims to establish a candidate Reference Measurement Procedure (cRMP) for simultaneous quantification of serum FT3 and FT4 based on isotope-dilution liquid chromatography-tandem mass spectrometry (ID-LC-MS/MS) technology.Methods A convenient and reusable equilibrium dialysis (ED) device was utilized to separate free thyroid hormones from their protein-bound counterparts in serum. Key dialysis parameters, including temperature, pH, membrane type, and duration, were optimized to ensure consistent and reliable performance. The dialysate containing FT3 and FT4 was directly quantified by ID-LC-MS/MS. The method underwent systematic validation, comparative analysis with existing assays, and a comprehensive uncertainty assessment.Results The developed cRMP demonstrated limits of quantification (LoQ) of 1.54 pmol/L for FT3 and 3.22 pmol/L for FT4, and with an imprecision of less than 3 %. No interference from endogenous analogs was observed, and the method showed good consistency in interlaboratory comparison. In contrast, chemiluminescent immunoassay results exhibited poor agreement with and the cRMP.Conclusions This study developed a highly precise, accurate, specific, and sensitive ID-LC-MS/MS-based cRMP for the simultaneous measurement of FT3 and FT4 in human serum. This method provides a reliable tool for standardizing routine thyroid function tests.

High-affinity anti-double-stranded DNA (anti-dsDNA) antibodies serve as essential biomarkers for systemic lupus erythematosus (SLE), exhibiting particularly strong correlations with active disease manifestations and renal pathology. However, conventional detection methods require urea treatment to quantify these antibodies, necessitated by the heterogeneity of endogenous antibodies, which complicates assay procedures and compromises accuracy. In this study, a novel ratiometric electrochemical (EC) biosensor for the direct detection of high-affinity anti-dsDNA antibodies in serum without additional sample processing has been developed. This biosensor conducted by a novel T(6-4)T dimer dsDNA capture probe and integrated with a self-assembled 4-mercaptophenylboronic acid@gold nanoparticles@6-ferrocenyl-1-hexanethiol (4-MPBA@AuNPs@6-(Fc)HT) composite signal tag. Leveraging the highly specific of the T(6-4)T dimer dsDNA capture probe and multi-amplification capability of 4-MPBA@AuNPs@6-(Fc)HT, the platform exhibited non-specific interferences, higher sensitivity (limit of detection:1.60 IU/mL), and efficient preparation. Clinical serum analysis showed good correlation with indirect immunofluorescence (IIF) (r = 0.629, p < 0.001), superior diagnostic performance (AUC = 0.893 vs. IIF AUC = 0.900) in differentiating SLE patient from healthy control (CON). Notably, EC results correlated more strongly with renal impairment (r = 0.426, p < 0.01) than IIF (r = 0.321, p > 0.05), highlighting its superior clinical utility for monitoring disease. This strategy provides a robust and straightforward approach for serum high-affinity anti-dsDNA antibodies detection, offering significant potential for SLE diagnosis and progression monitoring.

BackgroundChemotherapy-induced nausea and vomiting (CINV) remains a prevalent and debilitating side effect of cancer treatment with limited therapeutic options. Dingxiang Shidi Decoction (DXSD), a classical Chinese herbal formula, has demonstrated clinical efficacy in CINV management. However, its active components and mechanism of action require systematic investigation.ObjectiveThis study aims to elucidate the pharmacologically active constituents of DXSD and their anti-CINV mechanisms.MethodsWe employed advanced analytical techniques including UPLC-MS/MS and GC-MS to analyze the chemical components of DXSD. Network pharmacology techniques were applied to explore its pharmacological mechanisms. And molecular docking simulation was conducted to further refine the drug-target interaction.ResultsA total of 292 chemical compounds were identified in DXSD, comprising 165 water-soluble components, 56 volatile components, and 84 network database entries. By integrating 564 drug targets with 888 CINV disease targets, we identified 143 potential therapeutic targets. Further protein-protein interaction (PPI) network analysis revealed 12 key active ingredients and 13 key therapeutic targets. Enrichment analysis suggested that DXSD may reduce inflammation, modulate neurotransmitter stimulation in the gastrointestinal tract, and regulate cellular proliferation and differentiation. Notably, key active ingredients, predominantly aromatic compounds such as sabinene, (-)-α-cubebene, α-copaene, β-caryophyllene, aromandendrene, γ-muurolene, (-)-α-muurolene, α-phellandrene, α-terpinene, γ-terpinene, (+)-δ-cadinene, and Gomisin B, demonstrated significant binding affinity with multiple targets, particularly AKT1, BCL2, EGFR, MTOR, and STAT3.ConclusionsThis study reveals the active components and therapeutic mechanisms of DXSD against CINV, supporting its clinical application and demonstrating the potential of aromatherapy as an effective treatment strategy.

BACKGROUND:Lupus nephritis (LN), a severe complication of systemic lupus erythematosus (SLE), lacks effective therapies because of its complex pathogenesis. PANoptosis, an integrated cell death pathway that combines apoptosis, pyroptosis, and necroptosis, has been implicated in inflammatory diseases; however, its role in LN and potential as a therapeutic target remain unexplored. Total glucosides of paeony (TGP), a traditional Chinese medicine derived from Paeonia lactiflora Pall, has shown promise in LN treatment due to its immunomodulatory and anti-inflammatory properties. Nevertheless, the mechanisms underlying its renoprotective effects, particularly its potential regulation of PANoptosis, are poorly understood. PURPOSE:This study investigated the role of PANoptosis in LN pathogenesis and elucidated the therapeutic mechanisms of TGP, focusing on ZBP1-mediated podocytes PANoptosis. METHODS:Four mRNA microarray datasets of renal tissues from patients with LN and LN mouse models were obtained from the GEO database, and were performed with gene set enrichment analysis (GSEA) to identify PANoptosis-related pathways. Renal pathology was assessed using HE staining and proteinuria detection. Cell death was evaluated in vivo using TUNEL staining and in vitro through flow cytometry and LDH release assay. The protein levels of ZBP1 and PANoptosis markers were detected by immunoblotting and immunohistochemistry (IHC). RESULTS:PANoptosis-related pathways were significantly enriched in LN kidneys. TGP treatment suppressed podocytes PANoptosis and alleviated renal injury in MRL/lpr mice. Mechanistically, TGP inhibited PANoptosis by regulating the STAT2-ZBP1 axis, with ZBP1 identified as a pivotal regulator. ZBP1 overexpression attenuated the therapeutic effects of TGP, confirming its central role in LN pathogenesis. CONCLUSION:This study reveals ZBP1-mediated podocytes PANoptosis as a key mechanism in LN and establishes TGP as a promising therapeutic agent targeting this pathway. These findings provide a novel, clinically translatable strategy for LN treatment.

Background Diabetic nephropathy (DN) is the most intractable complication of diabetes. Despite decades of research, accurate diagnostic markers and effective therapeutic drugs are still elusive. Abnormal copper metabolism is also implicated in diabetes and its complications. This study aims to identify copper metabolism-related biomarkers and potential drugs for DN. Methods DN datasets and copper metabolism-related genes (CMGs) were obtained from Gene Expression Omnibus (GEO) and GeneCards. Differentially expressed CMGs (DE-CMGs) were identified using the limma package and the Venn algorithm. Functional enrichment analysis and protein-protein interaction (PPI) network were performed to identify candidate hub genes. The single gene with an area under the receiver operating characteristic (ROC) curve > 0.7 was identified as a potential diagnostic biomarker of DN. Finally, these biomarkers were validated by quantitative real-time polymerase chain reaction (qRT-PCR) in high-glucose-treated human proximal tubular (HK-2) cells. These validated hub genes were used to construct a combined prediction model, confirmed by additional GSE30528 and GSE30529 datasets. The correlation analysis between the expression level of the hub genes and the estimated glomerular filtration rate (eGFR) was carried out. Additionally, immune cell infiltration and potential target drugs were investigated for these biomarkers. Results Five hub genes associated with copper metabolism, namely CD36, CCL2, CASP3, LPL, and APOC3, were identified as biomarkers for the early diagnosis of DN. Utilizing multiple biomarkers enhanced diagnostic accuracy and specificity. CD36, CCL2, and CASP3 correlated negatively with eGFR levels, while LPL and APOC3 correlated positively. Additionally, these hub genes were significantly linked to various immune cell types, including macrophages M1 and M2, T cells, gamma delta resting dendritic cells, neutrophils, and NK cells. Furthermore, 15 agents targeting these biomarkers were retrieved from the DrugBank database. Conclusion Our study identified key genes possibly related to copper metabolism in the pathological mechanism of DN that could serve as novel targets for the diagnosis and therapy of DN.

Background Diabetic nephropathy (DN) is a common and severe microvascular complication of diabetes. Mitochondrial dysfunction and immune inflammation are important factors in the pathogenesis of DN. However, the specific mechanisms and their intricate interactions in DN remain unclear. Besides, there are no effective specific predictive or diagnostic biomarkers for DN so far. Therefore, this study aims to elucidate the role of mitochondrial-related genes and their possibility as predictive or diagnostic biomarkers, as well as their crosstalk with immune infiltration in the progression of DN. Methods Based on the GEO database and limma R package, the differentially expressed genes (DEGs) of DN were identified. Mitochondrial-related DEGs (MitoDEGs) were then obtained by intersecting these DEGs with mitochondria-related genes from the MitoCarta 3.0 database. Subsequently, the candidate hub genes were further screened by gene co-expression network analysis (WGCNA), and verified mRNA levels of these genes by real-time quantitative PCR (qRT-PCR) in high-glucose-treated human proximal tubular (HK-2) cells. The verified hub genes were utilized to construct a combined diagnostic model for DN, with its diagnostic efficacy assessed across the GSE30122 and GSE96804 datasets. Additionally, the immune infiltration pattern in DN was assessed with the CIBERSORT algorithm, and the Nephroseq v5 database was used to analyze the correlation between hub genes and clinical features of DN. Results Seven mitochondria-related candidate hub genes were screened from 56 MitoDEGs. Subsequently, the expression levels of six of them, namely EFHD1, CASP3, AASS, MPC1, NT5DC2, and BCL2A1, exhibited significant inter-group differences in the HK-2 cell model. The diagnostic model based on the six genes demonstrated good diagnostic efficacy in both training and validation sets. Furthermore, correlation analysis indicated that EFHD1 and AASS, downregulated in DN, are positively correlated with eGFR and negatively with serum creatinine. Conversely, CASP3, NT5DC2, and BCL2A1, upregulated in DN, show opposite correlations. In addition, spearman analysis revealed that the six hub genes were significantly associated with the infiltration of immune cells, including M1 and M2 macrophages, mast cells, resting NK cells, gamma delta T cells, and follicular helper T cells. Conclusion This study elucidated the characteristics of mitochondria-related genes and their correlation with immune cell infiltration in DN, providing new insights for exploring the pathogenesis of DN and facilitating the identification of new potential biomarkers and therapeutic targets.

A candidate reference measurement procedure (RMP) for serum theophylline via isotope dilution liquid chromatography-tandem mass spectrometry (LC-MS/MS) was developed. With a single-step precipitation pretreatment and a 6-min gradient elution, the method achieved baseline separation of theophylline and its analogs on a C18-packed column. A bracketing calibration method was used to ensure repeatable signal intensity and high measurement precision. The intra-assay and inter-assay imprecisions were 1.06

Objectives: This study aimed to investigate the substance basis and pharmacological mechanism of Dingxiang Shidi Decoction in preventing and treating Chemotherapy-Induced Nausea and Vomiting (CINV). Methods: We employed advanced analytical techniques including UPLC-MS/MS and GC-MS to analyze the chemical components of Dingxiang Shidi Decoction. Network pharmacology and molecular docking techniques were applied to explore its pharmacological mechanisms. Results: Our study established a comprehensive chemical composition database for Dingxiang Shidi Decoction, integrating UPLC-MS/MS qualitative components, GC-MS qualitative components, and network database entries, comprising 292 chemical compounds. Furthermore, we elucidated potential pharmacologically active components and pathways associated with alleviating CINV symptoms by Dingxiang Shidi Decoction. These pathways include inflammation reduction, modulation of neurotransmitter stimulation in the gastrointestinal tract, and regulation of cellular proliferation and differentiation. Notably, key active ingredients, predominantly aromatic compounds such as sabinene, (-)-α-cubebene, α-copaene, β-caryophyllene, aromandendrene, γ-muurolene, (-)-α-muurolene, α-phellandrene, α-terpinene, γ-terpinene, (+)-δ-cadinene, and Gomisin B, demonstrate significant binding affinity with multiple targets, notably AKT1, BCL2, EGFR, MTOR, and STAT3. Conclusions: This study sheds light on the substance basis and pharmacological mechanisms of Dingxiang Shidi Decoction in CINV treatment, providing valuable insights for its clinical application and suggesting aromatherapy as a promising therapeutic approach. These findings provide insights into the multifaceted pharmacological mechanisms of Dingxiang Shidi Decoction and its potential applications in clinical settings for the treatment of chemotherapy-induced nausea and vomiting.

OBJECTIVES:Serum cystatin C (CysC) is a reliable and ideal endogenous marker for accurately assessing early changes in glomerular filtration rate (GFR), surpassing the limitations of creatinine-based estimated GFR. To improve the precision of GFR calculation, the development of strategies for accurately measuring serum CysC is crucial. METHODS:In this study, the full-length CysC pure product and fully recombinant 15N-labeled CysC internal standard were subjected to protein cleavage. Subsequently, an LC-MS/MS method was developed for the absolute quantification of serum CysC. The traceability of the method was assigned calibrator using the amino acid reference measurement procedure (RMP). It involved calibrating the instrument using an amino acid reference material with known amino acid concentrations for calibration and comparison purposes. RESULTS:The total imprecision of the method was determined to be ≤8.2 %, and a lower functional limit of quantification (LLoQ) was achieved. The recoveries ranged from 97.36 to 103.26 %. The relative bias between this candidate RMP for measurement of ERM-DA471-IFCC and the target value was 1.74 %. The linearity response was observed within the concentration range of 0.21-10.13 mg/L, with a high R2 value of 0.999. The results obtained using our method was consistent with those obtained using other certified RMPs. CONCLUSIONS:With the establishment of this highly selective and accurate serum CysC measurement method, it is now possible to assess the correlation between immunoassay results of serum CysC and the intended target when discrepancies are suspected in the clinical setting.

Digoxin, a cardiac glycoside, is widely used in the treatment of cardiovascular diseases. Due to its narrow therapeutic range, precise monitoring of its blood concentration is essential. A reference measurement procedure (RMP) is pivotal for ensuring result accuracy and comparability. The RMP for serum digoxin by ID-LC-MS/MS was optimized with sample pre-treatment and detection processes, and the bracketing calibration method was used, which facilitates more accurate measurement, especially for extreme concentrations. The performance of this optimized RMP was thoroughly evaluated. The limit of detection (LoD) was 0.05 ng/mL (0.06 nmol/L) and the lowest limit of quantification (LLoQ) was 0.10 ng/mL (0.13 nmol/L). The intra- and inter-assay imprecisions were 2.24

Objectives: The accuracy of blood glucose measurement in clinical laboratories is vital for diabetes diagnosis. Trueness Verification Plan was carried out and analyzed for evaluating the standardization of serum glucose among clinical laboratories. Methods: Trueness verification samples were distributed to clinical laboratories for three days measurement, and their target values were assigned by two certified reference laboratories. The relative bias, coefficient of variation (CV), and total error (TE) for each clinical laboratory were calculated and analyzed. Moreover, the Six Sigma metrics and Quality Goal Index were utilized to reflect the measurement quality of the clinical laboratories. Results: The pass rates evaluated by bias, CV, and TE ranged from 45.2 % to 64.8 %, 96.8 %-98.9 %, and 83.9 %-97.1 % over the six years. The matched systems used in clinical laboratories demonstrated better accuracy than the un-matched systems. The pass rate by bias of hexokinase method is 53.1 %-78.6 %, while the glucose oxidase method is 29.2 %-52.2 %. Overall, 74.2 %-85.7 % of clinical laboratories achieved an acceptable level (both sigma>3), and 35.2 %-61.4 % of laboratories reached a "world-class" level (both sigma>6). Conclusions: The quality for serum glucose measurement has been greatly improved. However, standardization among clinical systems still needs to be further promoted.

Background The advent of targeted cancer therapies has led to a decline in prostate cancer (PCa) incidence and mortality rates. Nevertheless, challenges persist due to the long-term single-agent therapeutic insensitivity and resistance encountered in PCa treatment. Therefore, there is an urgent need for novel drug targets to address these challenges in PCa therapy. Method We analyzed 731 plasma proteins and PCa summary GWAS data from Prostate Cancer Association Group to investigate cancer associated genomic alterations (control: case = 61 106: 79 148). Cis-acting Mendelian randomization and Bayesian analysis was applied to reveal the causality between protein and PCa. Additionally, protein-protein interaction (PPI) was performed to discover the potential coactions between identified target proteins and established drug targets approved by FDA for the treatment of PCa. Furthermore, we utilized Alpha Fold 2 to predict the 3D complex structure between identified proteins and established drug targets. Finally, these findings were validated using data from UK Biobank and the European Bioinfomatics Institute, and six promising target proteins were categorized into three tiers. Results Six potential causal proteins including MSMB, IGF2R, KDELC2, TNFRSF10B, GSTP1, and SPINT2 were discovered through drug target Mendelian randomization analysis. Among them, MSMB (Odds ratio (OR) = 0.81; 95% confidence interval (CI) : 0.80–0.82; P = 2.52×10− 148), IGF2R (OR = 0.92; 95% CI: 0.90–0.94; P = 4.57×10− 10), KDELC2 (OR = 0.89; 95% CI: 0.86–0.93; P = 1.89×10− 8), TNFRSF10B (OR = 0.74; 95% CI: 0.65–0.83; P = 2.41×10− 7), and GSTP1 (OR = 0.82; 95% CI: 0.75–0.90; P = 4.22×10− 5) were inversely associated with PCa risk, and upregulate level of SPINT2 (OR = 1.05; 95% CI: 1.03–1.05; P = 1.49×10− 6) increased PCa risk. None of six proteins had reverse causality. MSMB and KDELC2 shared the same variant with PCa by co-localization analysis (PPH4 > 0.8). During external validation, five proteins were replicated in at least one dataset except IGF2R. Conclusions Our study has highlighted that a constellation of plasma proteins including MSMB, KDELC2, GSTP1, and TNFRSF10B have been identified as potential drug targets for PCa, which might provide valuable insights for the rational design of novel drugs in PCa therapy.

Liver cancer, a prominent contributor to cancer-related deaths, necessitates timely identification for successful intervention. In recent years, long non-coding RNAs (lncRNAs) have gained attention as potential biomarkers for liver cancer, and accurate quantification of lncRNA is essential for early diagnosis of liver cancer. However, existing methods for lncRNA detection rely on amplification and labeling techniques, resulting in semi-quantitative or qualitative outcomes. DNA-peptide technology offers a promising alternative. It has successfully translated nucleic acid quantification into peptide quantification, particularly in the context of miRNA analysis. However, the intricate structure of long-chain lncRNAs presents a challenge not encountered with miRNAs, making the design and acquisition of specific DNA-peptide probes for direct quantification more difficult. In this study, a strategy for lncRNA quantification was developed using a DNA-peptide probe coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based quasi-targeted proteomics. The inherent structural complexity of long-chain lncRNAs was overcome by designing DNA-peptide probes based on their unique sequence segments, enabling direct quantification without the need for amplification. Highly upregulated in liver cancer (HULC) was identified as a target lncRNA through bioinformatics analysis using GEO2R online software. Subsequently, the target lncRNA (i.e., HULC), which had been biotinylated and bound to streptavidin agarose beforehand, was hybridized with the probe. Following trypsin digestion, the reporter peptide was released and quantified using LC-MS/MS. Finally, this method was applied to analyze HULC levels in liver cancer cell lines and serum samples, enabling quantitative assessment and early diagnosis. The results demonstrated that liver cancer diagnostics could be enhanced through the integration of mass spectrometry and DNA-peptide probe technology for lncRNA quantification.

Advanced glycation end products (AGEs), derived from the non-enzymatic glycation reaction, are defined as glycotoxins in various diseases including aging, diabetes and kidney injury. Exploring AGEs as potential biomarkers for these diseases holds paramount significance. Nevertheless, the high chemical structural similarity and great heterogeneity among AGEs present a formidable challenge when it comes to the comprehensive, simultaneous, and accurate detection of multiple AGEs in biological samples. In this study, an UPLC/MS/MS method for simultaneous quantification of 20 free AGEs in human serum was firstly established and applied to quantification of clinical samples from individuals with kidney injury. Simple sample preparation method through protein precipitation without derivatization was used. Method performances including imprecision, accuracy, sensitivity, linearity, and carryover were systematically validated. Intra- and inter- imprecision of 20 free AGEs were 1.93-5.94 % and 2.30-8.55 %, respectively. The method accuracy was confirmed with good recoveries ranging from 96.40 % to 103.25 %. The LOD and LOQ were 0.1-3.13 ng/mL and 0.5-6.25 ng/mL, respectively. Additionally, the 20 free AGEs displayed excellent linearity (R-2 >0.9974) across a wide linear range (1.56-400 ng/mL). Finally, through simultaneous quantitation of 20 Free AGEs in 100 participants including kidney injury patient and healthy controls, we identified six free AGEs, including N-6-carboxyethyl-L-arginine (CEA), N-6-carboxymethyl-L-lysine (CML), methylglyoxal-derived hydroimidazolones (MG-H), N-6-formyl-lysine, N-6-carboxymethyl-L-arginine (CMA), and glyoxal-derived hydroimidazolone (G-H), could well distinguish kidney injury patients and healthy individuals. Among them, the levels of four free AGEs including CML, CEA, MG-H, and G-H strongly correlate with traditionally clinical markers of kidney disease. The high area under the curve (AUC) values (AUC=0.965) in receiver operating characteristic (ROC) curve indicated that these four free AGEs can be served as combined diagnostic biomarkers for the diagnosis of kidney disease.

BACKGROUND:During pregnancy, the fetus needs to obtain a lot of nutrients from the mother, but the micronutrient deficiencies in pregnancy are not clear at present, and there is no reliable basis for nutrient intake and supplement. The purpose of this study was to understand the levels of essential elements in whole blood of pregnant women during various pregnancy stages at different ages and in different regions, to evaluate the deficiency of essential elements in Chinese pregnant women, and to explore the feasibility of using the elemental pattern to characterize maternal status.METHODS:Whole blood samples of 11222 healthy pregnant women enrolled in different areas of China from Jan-Dec 2019, were analyzed for concentrations of six essential elements including Mn, Cu, Zn, Ca, Mg, and Fe, using the inductively coupled plasma mass spectrometer. A retrospective comparative study during different pregnancy periods at different ages and in different regions in whole blood essential elements content from non-pregnant normal women and pregnant normal women was developed using multivariate statistical analysis. Principal component analysis evaluation elemental pattern was used to characterize pregnancy status of pregnant women.RESULTS:In general, the levels of six essential elements in whole blood of pregnant women can satisfy the needs of normal physiological activities. With the development of pregnancy, the contents of Cu and Mn increased, while the contents of Fe and Mg decreased, and the contents of Zn and Ca have no noteworthy change. At the same gestation stage, the Cu content in whole blood of elderly pregnant women was higher. There were some differences in whole blood essential elements content of pregnant women in different regions. Principal component analysis and heat map analysis showed the feasibility of using bioinformatics research strategies to identify different pregnancies.CONCLUSIONS:There are differences in the content of whole blood essential elements of women at different stages of pregnancy in different regions. It was found that there was no obvious deficiency in whole blood essential elements levels of pregnant women in recent years. The pattern of essential elements has a certain application potential in the evaluation of pregnancy and pregnant women's health status.

We developed and evaluated two-level, namely 2017011 and 2017012, serum-based reference materials (RMs) for 17 beta-estradiol (17 β-E2) by the reference method of isotope dilution liquid chromatography tandem mass spectrometry (ID-LC-MS/MS) from the remaining serum samples after routine clinical tests, to help improve clinical routine testing and provide the traceability of results. This paper describes the development process of these RMs. The National Metrology Institute of Japan (NMIJ) certified reference material (CRM) 6004-a was used as the primary RM for the measurement of 17 β-E2. These serum-based RMs showed satisfactory homogeneity and stability. They also assessed the commutability between the reference method and the three routine clinical immunoassay systems. Besides, a collaborative study was carried out in five reference laboratories, all of which had been accredited by the China National Accreditation Service for Conformity Assessment (CNAS) in accordance with ISO/WD 15725-1. Statistical analysis of raw results and uncertainty assessment obtained certified values: 2017011 was 445.2 ± 39.0 pmol/L, and 2017012 was 761.9 ± 35.5 pmol/L.

Background: Blood glucose is an important monosaccharide functioning as the main source of energy for the human body. The accurate measurement of blood glucose is crucial for the screening, diagnosis, and monitoring of diabetes and diabetes-associated diseases. To assure the reliability and traceability of blood glucose measurements, we developed a reference material (RM) for use in human serum at two different concentrations, which were certified by the National Institute of Metrology (NIM) as GBW(E)091040 and GBW(E)091043.Methods: Raw serum samples were collected from residual samples after clinical testing, filtered, and repackaged under mild stirring. The homogeneity and stability of the samples were examined according to ISO Guide 35: 2017. Commutability was evaluated in compliance with CLSI EP30-A. Value assignment was carried out in six certified reference laboratories using the JCTLM-listed reference method for serum glucose. Moreover, the RMs was further applied in a trueness verification program.Results: The developed RMs was homogeneous and commutable enough for clinical use. They were also stable for 24 h at 2-8 degrees C or 20-25 degrees C and for at least 4 years at - 70 degrees C. The certified values were 5.20 +/- 0.18 mmol/L and 8.18 +/- 0.19 mmol/L (k = 2) for GBW(E)091040 and GBW(E)091043, respectively. The pass rates were evaluated by bias, coefficient of variation (CV), and total error (TE) for 66 clinical laboratories in the trueness verification program were 57.6%, 98.5%, and 89.4% of GBW(E)091040, and 51.5%, 98.5%, and 90.9% of GBW(E)091043, respectively.Conclusion: The developed RM could be used for the standardization of reference and clinical systems with satisfactory performance and traceable values, providing strong support for the accurate measurement of blood glucose.

Background: The underlying pathogenic genes and effective therapeutic agents of Alzheimer's disease (AD) are still elusive. Meanwhile, abnormal copper metabolism is observed in AD brains of both human and mouse models. Objective: To investigate copper metabolism-related gene biomarkers for AD diagnosis and therapy. Methods: The AD datasets and copper metabolism-related genes (CMGs) were downloaded from GEO and GeneCards database, respectively. Differentially expressed CMGs (DE-CMGs) performed through Limma, functional enrichment analysis and the protein-protein interaction were used to identify candidate key genes by using CytoHubba. And these candidate key genes were utilized to construct a prediction model by logistic regression analysis for AD early diagnosis. Furthermore, ROC analysis was conducted to identify a single gene with AUC values greater than 0.7 by GSE5281. Finally, the single gene biomarker was validated by quantitative real-time polymerase chain reaction (qRT-PCR) in AD clinical samples. Additionally, immune cell infiltration in AD samples and potential therapeutic drugs targeting the identified biomarkers were further explored. Results: A polygenic prediction model for AD based on copper metabolism was established by the top 10 genes, which demonstrated good diagnostic performance (AUC values). COX11, LDHA, ATOX1, SCO1, and SOD1 were identified as blood biomarkers for AD early diagnosis. 20 agents targeting biomarkers were retrieved from DrugBank database, some of which have been proven effective for the treatment of AD. Conclusions: The five blood biomarkers and copper metabolism-associated model can differentiate AD patients from non-demented individuals and aid in the development of new therapeutic strategies.