A new method for the rapid identification of external water types in rainwater pipeline networks using UV-Vis absorption spectroscopy.

Ultraviolet-visible (UV-Vis) absorption spectroscopy, due to its high sensitivity and capability for real-time online monitoring, is one of the most promising tools for the rapid identification of external water in rainwater pipe networks. However, difficulties in obtaining actual samples lead to insufficient real samples, and the complex composition of wastewater can affect the accurate traceability analysis of external water in rainwater pipe networks. In this study, a new method for identifying external water in rainwater pipe networks with a small number of samples is proposed. In this method, the Generative Adversarial Network (GAN) algorithm was initially used to generate spectral data from the absorption spectra of water samples; subsequently, the multiplicative scatter correction (MSC) algorithm was applied to process the UV-Vis absorption spectra of different types of water samples; following this, the Variational Mode Decomposition (VMD) algorithm was employed to decompose and recombine the spectra after MSC; and finally, the long short-term memory (LSTM) algorithm was used to establish the identification model between the recombined spectra and the water source types, and to determine the optimal number of decomposed spectra K. The research results show that when the number of decomposed spectra K is 5, the identification accuracy for different sources of domestic sewage, surface water, and industrial wastewater is the highest, with an overall accuracy of 98.81%. Additionally, the performance of this method was validated by mixed water samples (combinations of rainwater and domestic sewage, rainwater and surface water, and rainwater and industrial wastewater). The results indicate that the accuracy of the proposed method in identifying the source of external water in rainwater reaches 98.99%, with detection time within 10 s. Therefore, the proposed method can become a potential approach for rapid identification and traceability analysis of external water in rainwater pipe networks.

Fast dentification of overlapping fluorescence spectra of oil species based on LDA and two-dimensional convolutional neural network.

Although most petroleum oil species can be identified by their fluorescence spectra, overlapping fluorescence spectra make identification difficult. This study aims to address the issue that fluorescence spectroscopy is ineffective in identifying overlapping oil species. In this study, an equivalent model of overlapping oil species with fluorescence spectra was established. The linear discriminant analysis (LDA)-assisted machine learning (ML) algorithms K nearest neighbor (KNN), decision tree (DT), and random forest (RF) improved the identification of fluorescent spectrally overlapping oil species for diesel-lubricant oils. The identification accuracies of two-dimensional convolutional neural network (2DCNN), LDA combined with the ML algorithms effectively all 100 %. Furthermore, Partial Least Squares Regression (PLSR) algorithm, Support Vector Regression (SVR) algorithm, DT regression algorithm, and RF regression algorithm were also used to identify the lubricant concentration in diesel-lubricant oils. The coefficient of determination of the DT was 1, and the root-mean-square error was 0, which identified the concentration of lubricant oils in them accurately and without error.

Exploring antithrombotic mechanisms and effective constituents of Lagopsis supina using an integrated strategy based on network pharmacology, molecular docking, metabolomics, and experimental verification in rats.

ETHNOPHARMACOLOGICAL RELEVANCE: Thrombosis is a common cause of morbidity and mortality worldwide. Lagopsis supina (Stephan ex Willd.) Ikonn.-Gal. ex Knorring is an ancient Chinese herbal medicine used for treating thrombotic diseases. Nevertheless, the antithrombotic mechanisms and effective constituents of this plant have not been clarified. AIM OF THE STUDY: This work aimed to elucidate the pharmacodynamics and mechanism of L. supina against thrombosis. MATERIALS AND METHODS: Systematic network pharmacology was used to explore candidate effective constituents and hub targets of L. supina against thrombosis. Subsequently, the binding affinities of major constituents with core targets were verified by molecular docking analysis. Afterward, the therapeutic effect and mechanism were evaluated in an arteriovenous bypass thrombosis rat model. In addition, the serum metabolomics analysis was conducted using ultra-high performance liquid chromatography coupled with Q-Exactive mass spectrometry. RESULTS: A total of 124 intersected targets of L. supina against thrombosis were predicted. Among them, 24 hub targets were obtained and their mainly associated with inflammation, angiogenesis, and thrombosis approaches. Furthermore, 9 candidate effective constituents, including (22E,24R)-5α,8α-epidioxyergosta-6,22-dien-3ß-ol, aurantiamide, (22E,24R)-5α,8α-epidioxyergosta-6,9 (11),22-trien-3ß-ol, lagopsinA, lagopsin C, 15-epi-lagopsin C, lagopsin D, 15-epi-lagopsin D, and lagopsin G in L. supina and 6 potential core targets (TLR-4, TNF-α, HIF-1α, VEGF-A, VEGFR-2, and CLEC1B) were acquired. Then, these 9 constituents demonstrated strong binding affinities with the 6 targets, with their lowest binding energies were all less than -5.0 kcal/mol. The antithrombotic effect and potential mechanisms of L. supina were verified, showing a positively associated with the inhibition of inflammation (TNF-α, IL-1ß, IL-6, IL-8, and IL-10) and coagulation cascade (TT, APTT, PT, FIB, AT-III), promotion of angiogenesis (VEGF), suppression of platelet activation (TXB2, 6-keto-PGF1α, and TXB2/6-keto-PGF1α), and prevention of fibrinolysis (t-PA, u-PA, PAI-1, PAI-1/t-PA, PAI-1/u-PA, and PLG). Finally, 14 endogenous differential metabolites from serum samples of rats were intervened by L. supina based on untargeted metabolomics analysis, which were closely related to amino acid metabolism, inflammatory and angiogenic pathways. CONCLUSION: Our integrated strategy based on network pharmacology, molecular docking, metabolomics, and in vivo experiments revealed for the first time that L. supina exerts a significant antithrombotic effect through the inhibition of inflammation and coagulation cascade, promotion of angiogenesis, and suppression of platelet activation. This paper provides novel insight into the potential of L. supina as a candidate agent to treat thrombosis.

Uncovering the pharmacological mechanisms of Patchouli essential oil for treating ulcerative colitis.

ETHNOPHARMACOLOGICAL RELEVANCE: Pogostemonis Herba has long been used in traditional Chinese medicine to treat inflammatory disorders. Patchouli essential oil (PEO) is the primary component of Pogostemonis Herba, and it has been suggested to offer curative potential when applied to treat ulcerative colitis (UC). However, the pharmacological mechanisms of PEO for treating UC remain to be clarified. AIM OF THE STUDY: To elucidate the pharmacological mechanisms of PEO for treating UC. METHODS AND RESULTS: In the present study, transcriptomic and network pharmacology approaches were combined to clarify the mechanisms of PEO for treating UC. Our results reveal that rectal PEO administration in UC model mice significantly alleviated symptoms of UC. In addition, PEO effectively suppressed colonic inflammation and oxidative stress. Mechanistically, PEO can ameliorate UC mice by modulating gut microbiota, inhibiting inflammatory targets (OPTC, PTN, IFIT3, EGFR, and TLR4), and inhibiting the PI3K-AKT pathway. Next, the 11 potential bioactive components that play a role in PEO's anti-UC mechanism were identified, and the therapeutic efficacy of the pogostone (a bioactive component) in UC mice was partially validated. CONCLUSION: This study highlights the mechanisms through which PEO can treat UC, providing a rigorous scientific foundation for future efforts to develop and apply PEO for treating UC.

Uncovering the mechanisms of Zhubi decoction against rheumatoid arthritis through an integrated study of network pharmacology, metabolomics, and intestinal flora.

ETHNOPHARMACOLOGICAL RELEVANCE: Zhubi Decoction (ZBD) is a modified formulation derived from the classic traditional Chinese medicine prescription "Er-Xian Decoction" documented in the esteemed "Clinical Manual of Chinese Medical Prescription". While the utilization of ZBD has exhibited promising clinical outcomes in treating rheumatoid arthritis (RA), the precise bioactive chemical constituents and the underlying mechanisms involved in its therapeutic efficacy remain to be comprehensively determined. AIM OF THE STUDY: This study aims to systematically examine ZBD's pharmacological effects and molecular mechanisms for RA alleviation. MATERIALS AND METHODS: Utilizing the collagen-induced arthritis (CIA) rat model, we comprehensively evaluated the anti-rheumatoid arthritis effects of ZBD in vivo through various indices, such as paw edema, arthritis index, ankle diameter, inflammatory cytokine levels, pathological conditions, and micro-CT analysis. The UPLC-MS/MS technique was utilized to analyze the compounds of ZBD. The potential therapeutic targets and signaling pathways of ZBD in the management of RA were predicted using network pharmacology. To analyze comprehensive metabolic profiles and identify underlying metabolic pathways, we conducted a serum-based widely targeted metabolomics analysis utilizing LC-MS technology. Key targets and predicted pathways were further validated using immunofluorescent staining, which integrated findings from serum metabolomics and network pharmacology analysis. Additionally, we analyzed the gut microbiota composition in rats employing 16 S rDNA sequencing and investigated the effects of ZBD on the microbiota of CIA rats through bioinformatics and statistical methods. RESULTS: ZBD exhibited remarkable efficacy in alleviating RA symptoms in CIA rats without notable side effects. This included reduced paw redness and swelling, minimized joint damage, improved the histopathology of cartilage and synovium, mitigated the inflammatory state, and lowered serum concentrations of cytokines TNF-α, IL-1ß and IL-6. Notably, the effectiveness of ZBD was comparable to MTX. Network pharmacology analysis revealed inflammation and immunity-related signaling pathways, such as PI3K/AKT, MAPK, IL-17, and TNF signaling pathways, as vital mediators in the effectual mechanisms of ZBD. Immunofluorescence analysis validated ZBD's ability to inhibit PI3K/AKT pathway proteins. Serum metabolomics studies revealed that ZBD modulates 170 differential metabolites, partially restored disrupted metabolic profiles in CIA rats. With a notable impact on amino acids and their metabolites, and lipids and lipid-like molecules. Integrated analysis of metabolomics and network pharmacology identified 6 pivotal metabolite pathways and 3 crucial targets: PTGS2, GSTP1, and ALDH2. Additionally, 16 S rDNA sequencing illuminated that ZBD mitigated gut microbiota dysbiosis in the CIA group, highlighting key genera such as Ligilactobacillus, Prevotella_9, unclassified_Bacilli, and unclassified_rumen_bacterium_JW32. Correlation analysis disclosed a significant link between 47 distinct metabolites and specific bacterial species. CONCLUSION: ZBD is a safe and efficacious TCM formulation, demonstrates efficacy in treating RA through its multi-component, multi-target, and multi-pathway mechanisms. The regulation of inflammation and immunity-related signaling pathways constitutes a crucial mechanism of ZBD's efficacy. Furthermore, ZBD modulates host metabolism and intestinal flora. The integrated analysis presents experimental evidence of ZBD for the management of RA.

Triterpenes from Ganoderma lucidum inhibit hepatocellular carcinoma by regulating enhancer-associated lncRNA in vivo.

ETHNOPHARMACOLOGICAL RELEVANCE: Ganoderma lucidum (G. lucidum) has been widely used as adjuvant of anti-tumor therapy for variety tumors. The bioactive ingredients of G. lucidum mainly include triterpenes, such as Ganoderic acid A, Ganoderic acid B, Ganoderenic acid A, Ganoderenic acid B, Ganoderenic acid D, and Ganoderic acid X. However, the effects and underlying mechanisms of G. lucidum are often challenging in hepatocellular carcinoma (HCC) treatment. AIM OF THE STUDY: To explore the potential role and mechanism of enhancer-associated lncRNAs (en-lncRNAs) in G. lucidum treated HCC through the in vivo and in vitro experiments. MATERIALS AND METHODS: Hepa1-6-bearing C57 BL/6 mice model were established to evaluate the therapeutic efficacy of G. lucidum treated HCC. Ki67 and TUNEL staining were used to detect the tumor cell proliferation and apoptosis in vivo. The Mouse lncRNA 4*180K array was implemented to identify the differentially expressed (DE) lncRNAs and mRNAs of G. lucidum treated tumor mice. The constructed lncRNA-mRNA co-expression network and bioinformatics analysis were used to selected core en-lncRNAs and its neighboring genes. The UPLC-MS method was used to identify the triterpenes of G. lucidum, and the in vitro experiments were used to verify which triterpene monomers regulated en-lncRNAs in tumor cells. Finally, a stable knockdown/overexpression cell lines were used to confirm the relationship between en-lncRNA and neighboring gene. RESULTS: Ki67 and TUNEL staining demonstrated G. lucidum significantly inhibited tumor growth, suppressed cell proliferation and induced apoptosis in vivo. Transcriptomic analysis revealed the existence of 126 DE lncRNAs high correlated with 454 co-expressed mRNAs in G. lucidum treated tumor mice. Based on lncRNA-mRNA network and qRT-PCR validation, 6 core lncRNAs were selected and considered high correlated with G. lucidum treatment. Bioinformatics analysis revealed FR036820 and FR121302 might act as enhancers, and qRT-PCR results suggested FR121302 might enhance Popdc2 mRNA level in HCC. Furthermore, 6 main triterpene monomers of G. lucidum were identified by UPLC-MS method, and in vitro experiments showed FR121302 and Popdc2 were significantly suppressed by Ganoderenic acid A and Ganoderenic acid B, respectively. The knock/overexpression results demonstrated that FR121302 activating and enhancing Popdc2 expression levels, and Ganoderenic acid A and Ganoderenic acid B dramatically suppressed FR121302 and decreased Popdc2 level in Hepa1-6 cells. CONCLUSIONS: Enhancer-associated lncRNA plays a crucial role as an enhancer during hepatocarcinogenesis, and triterpenes of G. lucidum significantly inhibited tumor cell proliferation and induced apoptosis by regulating en-lncRNAs. Our study demonstrated Ganoderenic acid A and Ganoderenic acid B suppressed en-lncRNA FR121302 may be one of the critical strategies of G. lucidum inhibit hepatocellular carcinoma growth.

In vivo and in vitro study on the regulatory mechanism of XiaoChaiHu decoction on PANoptosis in sepsis-induced cardiomyopathy.

ETHNOPHARMACOLOGICAL RELEVANCE: In accordance with the tenets of traditional Chinese medicine, sepsis is categorized into three distinct syndromes: heat syndrome, blood stasis syndrome, and deficiency syndrome. Xiaochaihu decoction (XCHD) has many functions, including the capacity to protect the liver, cholagogue, antipyretic, anti-inflammatory, and anti-pathogenic microorganisms. XCHD exerts the effect of clearing heat and reconciling Shaoyang. The XCHD contains many efficacious active ingredients, yet the mechanism of sepsis-induced cardiomyopathy (SIC) remains elusive. AIM OF THE STUDY: To investigate the molecular mechanisms underlying the protective effects of XCHD against SIC using an integrated approach combining network pharmacology and molecular biology techniques. MATERIALS AND METHODS: Network pharmacology methods identified the active ingredients, target proteins, and pathways affected by XCHD in the context of SIC. We conducted in vivo experiments using mice with lipopolysaccharide-induced SIC, evaluating cardiac function through echocardiography and histology. XCHD-containing serum was analyzed to determine its principal active components using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The effects of XCHD-containing serum on SIC were further tested in vitro in LPS-treated H9c2 cardiac cells. Protein expression levels were quantified via Western blotting and enzyme-linked immunosorbent assay (ELISA). Additionally, molecular docking was performed between the active components and ZBP1, a potential target protein. Overexpression of ZBP1 in H9c2 cells allowed for a deeper exploration of its role in modulating SIC-associated gene expression. RESULTS: UPLC-MS/MS identified 31 shared XCHD and XCHD-containing serum components. These included organic acids, terpenoids, and flavonoids, which have been identified as the active components of XCHD. Our findings revealed that XCHD alleviated LPS-induced myocardial injury, improved cardiac function, and preserved cardiomyocyte morphology in mice. In vitro studies, we demonstrated that XCHD-containing serum significantly suppressed the expression of inflammatory cytokines (IL-6, IL-1ß, and TNF-α) in LPS-induced H9c2 cells. Mechanistic investigations showed that XCHD downregulated genes associated with PANoptosis, a novel cell death pathway, suggesting its protective role in sepsis-damaged hearts. Conversely, overexpression of ZBP1 abolished the protective effects of XCHD and amplified PANoptosis-related gene expression. CONCLUSIONS: Our study provides the first evidence supporting the protective effects of XCHD against SIC, both in vitro and in vivo. The underlying mechanism involves the inhibition of ZBP1-initiated PANoptosis, offering new insights into treating SIC using XCHD.

Integration of network pharmacology and experimental verification to reveal the active components and molecular mechanism of modified Danzhi Xiaoyao San in the treatment of depression.

ETHNOPHARMACOLOGICAL RELEVANCE: Modified Danzhi Xiaoyao San (MDXS) is an effective clinical prescription for depression in China, which was deprived of Danzhi Xiaoyao San in the Ming Dynasty. MDSX has significant implications for the development of new antidepressants, but its pharmacological mechanism has been rarely studied. AIM OF THE STUDY: To reveal the active components and molecular mechanism of MDXS in treating depression through network pharmacology and experimental verification in vivo and in vitro. MATERIALS AND METHODS: UPLC-Q-TOF-MS/MS was used to identify the chemical components in the MDXS freeze-dried powder, drug-containing serum, and cerebrospinal fluid (CSF). Based on the analysis of prototype components in the CSF, the major constituents, potential therapeutic targets and possible pharmacological mechanisms of MDXS in treating depression were investigated using network pharmacological and molecular docking. Then corticosterone (CORT)-induced mice model of depression was established to investigate the antidepressant effects of MDXS. HT22 cells were cultured to verify the neuroprotective effects and core targets of the active components. RESULTS: There were 81 compounds in MDXS freeze-dried powder, 36 prototype components in serum, and 13 prototype components in CSF were identified, respectively. Network pharmacology analysis showed that these 13 prototype components in the CSF shared 190 common targets with depression, which were mainly enriched in MAPK and PI3K/AKT signaling pathways. PPI analysis suggested that AKT1 and MAPK1 (ERK1/2) were the core targets. Molecular docking revealed that azelaic acid (AA), senkyunolide A (SA), atractylenolide III (ATIII), and tokinolide B (TB) had the highest binding energy with AKT1 and MAPK1. Animal experiments verified that MDXS could reverse CORT-induced depression-like behaviors, improve synaptic plasticity, alleviate neuronal injury in hippocampal CA3 regions, and up-regulate the protein expression of p-ERK1/2 and p-AKT. In HT22 cells, azelaic acid, senkyunolide A, and atractylenolide III significantly protected the cell injury caused by CORT, and up-regulated the protein levels of p-ERK1/2 and p-AKT. CONCLUSIONS: These results suggested that MDXS may exert antidepressant effects partially through azelaic acid, senkyunolide A, and atractylenolide III targeting ERK1/2 and AKT.

An integrative pharmacology-based study on the efficacy and mechanism of essential oil of Chaihu Guizhi Decoction on influenza A virus induced pneumonia in mice.

ETHNOPHARMACOLOGICAL RELEVANCE: Chaihu Guizhi Decoction (CGD) has a long history of use in China for the treatment of influenza, which involves the use of a variety of aromatic herbs. Our previous studies have found that the contents of aromatic constituents in CGD affected the efficacy of treatment of influenza-infected mice, suggesting a clue that essential oil from CGD may play a relatively important role in ameliorating influenza induced pneumonia. AIM OF THE STUDY: To evaluate the anti-influenza potential of essential oil derived from Chaihu Guizhi Decoction (CGD-EO), to characterize and predict the key active components in CGD-EO, and to explore the mechanism of action of CGD-EO. MATERIALS AND METHODS: CGD-EO was obtained by steam distillation, and the components of the essential oil were characterized by gas chromatography-mass spectrometry (GC-MS) in conjunction with the retention index. The constituents absorbed into the blood of mice treated with CGD-EO were analyzed by headspace solid phase microextraction gas chromatography/mass spectrometry (HS-SPME-GC/MS). The potential anti-influenza active constituents and their possible action pathway were predicted by simulation using a network pharmacology approach. The protective effect of CGD-EO and its major components on H1N1/PR8-infected cells was determined using the CCK8 assay kit. Mice infected with influenza A virus H1N1/PR8 were administered different doses of CGD-EO orally and the body weights and lung weights were recorded. Mice with varying degrees of H1N1/PR8 infection were administered CGD-EO orally, and their daily weight, water consumption, and clinical indicators were recorded. Necropsies were conducted on days 3 and 5, during which lung weights were measured and lung tissues were preserved. Furthermore, the mRNA expression of the H1N1/PR8 virus and inflammatory factors in lung tissue was analyzed using RT-qPCR. RESULTS: (E)-cinnamaldehyde was the most abundant compound in the CGD-EO. The results of serum medicinal chemistry combined with network pharmacological analysis indicated that (E)-cinnamaldehyde and 3-phenyl-2-propenal may be potential active components of the CGD-EO anti-influenza, and may be involved in the NF-κB signalling pathway. In vitro studies have demonstrated that both CGD-EO and cinnamaldehyde exert a protective effect on MDCK cells infected with H1N1/PR8. In a 0.5 TCID50 H1N1/PR8-induced influenza model, mice treated with CGD-EO at a dose of 63.50 µg/kg exhibited a reduction in lung index, pathological lung lesions, and H1N1/PR8 viral gene levels. In addition, CGD-EO treatment was found to regulate the levels of inflammatory cytokines, including IL-6, TNF-α, and IFN-γ. Moreover, following three days of administration, an upregulation of NF-κB mRNA levels in mouse lung tissue was observed in response to CGD-EO treatment. CONCLUSIONS: The findings of our study indicate CGD-EO exerts a protective effect against H1N1-induced cytopathic lesions in vitro and is capable of alleviating H1N1-induced pneumonitis in mice. Moreover, it appears to be more efficacious in the treatment of mild symptoms of H1N1 infection. Studies have demonstrated that CGD-EO has antiviral potential to attenuate influenza-induced lung injury by modulating inflammatory cytokines and NF-κB signalling pathways during the early stages of influenza infection. It is possible that (E)-cinnamaldehyde is a potential active ingredient in the anti-influenza efficacy of CGD-EO.

Investigation of spatiotemporal distribution and formation mechanisms of ozone pollution in eastern Chinese cities applying convolutional neural network.

Severe ground-level ozone (O3) pollution over major Chinese cities has become one of the most challenging problems, which have deleterious effects on human health and the sustainability of society. This study explored the spatiotemporal distribution characteristics of ground-level O3 and its precursors based on conventional pollutant and meteorological monitoring data in Zhejiang Province from 2016 to 2021. Then, a high-performance convolutional neural network (CNN) model was established by expanding the moment and the concentration variations to general factors. Finally, the response mechanism of O3 to the variation with crucial influencing factors is explored by controlling variables and interpolating target variables. The results indicated that the annual average MDA8-90th concentrations in Zhejiang Province are higher in the northern and lower in the southern. When the wind direction (WD) ranges from east to southwest and the wind speed (WS) ranges between 2 and 3 m/sec, higher O3 concentration prone to occur. At different temperatures (T), the O3 concentration showed a trend of first increasing and subsequently decreasing with increasing NO2 concentration, peaks at the NO2 concentration around 0.02 mg/m3. The sensitivity of NO2 to O3 formation is not easily affected by temperature, barometric pressure and dew point temperature. Additionally, there is a minimum [Formula: see text] at each temperature when the NO2 concentration is 0.03 mg/m3, and this minimum [Formula: see text] decreases with increasing temperature. The study explores the response mechanism of O3 with the change of driving variables, which can provide a scientific foundation and methodological support for the targeted management of O3 pollution.

Impact of residual antibiotics on microbial decomposition of livestock manures in Eutric Regosol: Implications for sustainable nutrient recycling and soil carbon sequestration.

The land application of livestock manure has been widely acknowledged as a beneficial approach for nutrient recycling and environmental protection. However, the impact of residual antibiotics, a common contaminant of manure, on the degradation of organic compounds and nutrient release in Eutric Regosol is not well understood. Here, we studied, how oxytetracycline (OTC) and ciprofloxacin (CIP) affect the decomposition, microbial community structure, extracellular enzyme activities and nutrient release from cattle and pig manure using litterbag incubation experiments. Results showed that OTC and CIP greatly inhibited livestock manure decomposition, causing a decreased rate of carbon (28%-87%), nitrogen (15%-44%) and phosphorus (26%-43%) release. The relative abundance of gram-negative (G-) bacteria was reduced by 4.0%-13% while fungi increased by 7.0%-71% during a 28-day incubation period. Co-occurrence network analysis showed that antibiotic exposure disrupted microbial interactions, particularly among G- bacteria, G+ bacteria, and actinomycetes. These changes in microbial community structure and function resulted in decreased activity of urease, ß-1,4-N-acetyl-glucosaminidase, alkaline protease, chitinase, and catalase, causing reduced decomposition and nutrient release in cattle and pig manures. These findings advance our understanding of decomposition and nutrient recycling from manure-contaminated antibiotics, which will help facilitate sustainable agricultural production and soil carbon sequestration.

Quality control for serological testing.

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

Quantitative predictions of protein and total flavonoids content in Tartary and common buckwheat using near-infrared spectroscopy and chemometrics.

A rapid method was developed for determining the total flavonoid and protein content in Tartary buckwheat by employing near-infrared spectroscopy (NIRS) and various machine learning algorithms, including partial least squares regression (PLSR), support vector regression (SVR), and backpropagation neural network (BPNN). The RAW-SPA-CV-SVR model exhibited superior predictive accuracy for both Tartary and common buckwheat, with a high coefficient of determination (R2p = 0.9811) and a root mean squared error of prediction (RMSEP = 0.1071) for flavonoids, outperforming both PLSR and BPNN models. Additionally, the MMN-SPA-PSO-SVR model demonstrated exceptional performance in predicting protein content (R2p = 0.9247, RMSEP = 0.3906), enhancing the effectiveness of the MMN preprocessing technique for preserving the original data distribution. These findings indicate that the proposed methodology could efficiently assess buckwheat adulteration analysis. It can also provide new insights for the development of a promising method for quantifying food adulteration and controlling food quality.

Role of per- and polyfluoroalkyl substances in the cardiorenal system: Unraveling crosstalk from the network of pollutants and phenotypes.

Although per- and polyfluoroalkyl substances (PFAS) have been frequently linked to cardiovascular and renal disease separately, evidence remains scarce regarding their systematic effect. Therefore, we recruited 546 newly diagnosed acute coronary syndrome (ACS) patients and detected seven myocardial enzymes and six kidney function biomarkers. Twelve PFAS were also assessed with ultra-high-performance liquid chromatography-tandem mass spectrometry. Generalized linear model and restricted cubic spline model were applied to single pollutant analysis. Quantile g-computation was used for mixture analysis. Network model was utilized to identify central and bridge nodes of pollutants and phenotypes. In the present study, perfluorohexane sulfonic acid was positively associated with uric acid (UA) (ß= 0.04, 95% confidence interval (CI): 0.01, 0.07), and perfluorobutanoic acid was negatively associated with estimated glomerular filtration rate (ß= -0.04, 95% CI: -0.07, -0.01) but positively associated with UA (ß= 0.03, 95% CI: 0.01, 0.06). In mixture analysis, each quantile increase in the PFAS mixture was significantly associated with UA (ß= 0.08, 95% CI: 0.04, 0.11). Network analysis revealed that perfluorooctanoate, UA, and myoglobin were denoted as bridge nodes, and the first principal component of lactate dehydrogenase and creatine kinase- myocardial band was identified as the node with the highest strength and expected influence. This study investigates the systematic impact of PFAS exposure through cardiorenal interaction network, which highlights that PFAS may serve as an upstream approach in UA-modulated cardiorenal network to affect cardiorenal system comprehensively.

Integration of network pharmacology, UHPLC-Q exactive orbitrap HRMS technique and metabolomics to elucidate the active ingredients and mechanisms of compound danshen pills in treating hypercholesterolemic rats.

ETHNOPHARMACOLOGICAL RELEVANCE: Hypercholesterolemia (HLC) was a key risk factor for cardiovascular disease (CVD) characterized by elevated cholesterol levels, particularly LDL. While traditional Chinese medicine preparations Compound Danshen Pills(CDP) has been clinically used for hypercholesterolemia and coronary heart disease, its specific therapeutic effect on HLC remains understudied, necessitating further investigation into its mechanisms. AIM OF THE STUDY: The aim of this study was to explore the potential of CDP in treating HLC and elucidate its underlying mechanisms and active components. MATERIALS AND METHODS: A hypercholesterolemic lipemia rat model induced by a high-fat diet was employed. Network pharmacology combined with UHPLC-Q exactive orbitrap HRMS technique was used to predict the active components, targets and mechanisms of CDP for HLC. Histological analysis and serum biochemical assays were used to assess the therapeutic effect of CDP and its main active ingredient Sa B on hypercholesterolemic lipemia rat model. Immunofluorescence assays and western blotting were used to verify the mechanism of CDP and Sa B in the treatment of HLC. Metabolomics approach was used to demonstrate that CDP and Sa B affected the metabolic profile of HLC. RESULTS: Our findings demonstrated that both CDP and its main active ingredient Sa B significantly ameliorated hypercholesterolemic lipemic lesions, reducing levels of TC, LDL, AST, ALT, and ALP. Histological analysis revealed a decrease in lipid droplet accumulation and collagen fiber deposition in the liver, as well as reduced collagen fiber deposition in the aorta. Network pharmacology predicted potential targets such as PPARα and CYP27A1. Immunofluorescence assays and western blotting confirmed that CDP and Sa B upregulated the expression of Adipor1, PPARα and CYP27A1. Metabolomics analyses further indicated improvements in ABC transporters metabolic pathways, with differential metabolites such as riboflavin, taurine, and choline showed regression in levels after CDP treatment and riboflavin, L-Threonine, Thiamine, L-Leucine, and Adenosine showed improved expression after Sa B treatment. CONCLUSION: CDP and Sa B have been shown to alleviate high-fat diet-induced hypercholesterolemia by activating the PPAR pathway and improving hepatic lipid metabolism. Our study demonstrated, for the first time, the complex mechanism of CDP, Sa B in the treatment of hypercholesterolemia at the protein and metabolic levels and provided a new reference that could elucidate the pharmacological effects of traditional Chinese medicine on hypercholesterolemia from multiple perspectives.

Study on the underlying mechanism of Huachansu Capsule induced cardiotoxicity of normal rat by integrating transcriptomics, metabolomics and network toxicology.

ETHNOPHARMACOLOGICAL RELEVANCE: Huachansu Capsule (HCSc) is a simple enteric-coated capsule refined from the skin of the dried toad, a traditional medicinal herb. It has been used clinically for many years to treat a variety of malignant tumors with remarkable efficacy. To date, a number of main components of HCSc have been reported to be cardiotoxic, but the specific mechanism of cardiotoxicity is still unknown. AIM OF THE STUDY: The aim of this study was to elucidate the possible cardiotoxic symptoms caused by high-doses of HCSc and to further reveal the complex mechanisms by which it causes cardiotoxicity. MATERIALS AND METHODS: UPLC-Q-Exactive Orbitrap MS and network toxicology were used to identify and predict the potential toxic components, related signaling pathways. Then, we used acute and sub-acute toxicity experiments to reveal the apparent phenomenon of HCSc-induced cardiotoxicity. Finally, we combined transcriptomics and metabolomics to elucidate the potential mechanism of action, and verified the putative mechanism by molecular docking, RT-qPCR, and Western blot. RESULTS: We found 8 toad bufadienolides components may be induced cardiac toxicity HCSc main toxic components. Through toxicity experiments, we found that high dose of HCSc could increase a variety of blood routine indexes, five cardiac enzymes, heart failure indexes (BNP), troponin (cTnI and cTnT), heart rate and the degree of heart tissue damage, while low-dose of HCSc had no such changes. In addition, by molecular docking, found that 8 kinds of main toxic components and cAMP, AMPK, IL1ß, mTOR all can be a very good combination, especially in the cAMP. Meanwhile, RT-qPCR and Western blot results showed that HCSc could induce cardiotoxicity by regulating a variety of heart-related differential genes and activating the cAMP signaling pathway. CONCLUSIONS: In this study, network toxicology, transcriptomics and metabolomics were used to elucidate the complex mechanism of possible cardiotoxicity induced by high-dose HCSc. Animal experiments, molecular docking, Western blot and RT-qPCR experiments were also used to verify the above mechanism. These findings will inform further mechanistic studies and provide theoretical support for its safe clinical application.

Non-pharmacological interventions for reducing dental anxiety in pediatric dentistry: a network meta-analysis.

BACKGROUND: Child dental anxiety is a prevalent issue in the field of pediatric dentistry. At present, several non-pharmacological interventions are employed to mitigate anxiety during dental treatments for children. The objective of this study is to assess the effectiveness of diverse non-pharmacological interventions in reducing dental anxiety, as well as enhancing heart rate during pediatric dental treatments. To achieve this, we conducted a systematic review and a network meta-analysis (NMA) to compare the efficacy of various outcome indicators. METHODS: A thorough search was conducted in the databases of PubMed, Embase, Web of Science, Cochrane Library, Scopus, APA PsycInfo, CINAHL, and AMED to identify all eligible randomized controlled trials (RCTs) from the beginning of the databases up to August 1, 2024. The quality assessment was carried out using the Cochrane Collaboration's bias risk tool. The two outcome measures under consideration were dental anxiety and heart rate. Network graphs, league tables and SUCRA were constructed using R 4.2.3 software and Stata 16 software. This study is registered in PROSPERO under the registration number CRD42023467610. RESULTS: The study examined 12 different non-pharmacological approaches, drawing from a pool of 61 research studies involving 6,113 participants aged 4 to 16 years. The results of the network meta-analysis revealed that music (SUCRAs: 93.60%) proved to be the most effective measure in mitigating dental anxiety, followed by aromatherapy (SUCRAs: 78.58%) and game (SUCRAs: 70.99%). Moreover, hypnosis (SUCRAs: 98.80%), music (SUCRAs: 79.58%), and relaxation (SUCRAs: 72.41%) were identified as the top three interventions for decreasing heart rate. CONCLUSION: In this NMA, when contemplating dental anxiety outcomes, music is recommended as a priority. For heart rate outcomes, hypnosis may be a preferred measure. However, owing to the limited number of articles, the conclusion of this study still requires additional confirmation or correction through more high-quality primary studies in the future.

Early recurrence as a pivotal event in nasopharyngeal carcinoma: identifying predictors and key molecular signals for survivors.

PURPOSE: The duration of response to treatment is a significant prognostic indicator, with early recurrence (ER) often predicting poorer survival outcomes in nasopharyngeal carcinoma (NPC) survivors. This study seeks to elucidate the factors contributing to the onset of ER following radiotherapy in NPC survivors. METHODS: This investigation encompassed 2,789 newly diagnosed NPC patients who underwent radical intensity-modulated radiotherapy. Ordinal logistic regression analysis was employed to evaluate the independent predictors of earlier recurrence. A machine learning-based prediction model of NPC recurrence patterns was developed. Tumorous RNA-sequencing (in-house cohort: N = 192) and biological tipping point analysis were utilized to infer potential molecular mechanisms associated with ER. RESULTS: Our results demonstrated that ER within 24 months post-initial treatment was the optimal time frame for identifying early malignant progression in NPC survivors. The ER cohort (150 of 2,789, 5.38%) exhibited a notably short median overall survival of 48.6 months. Multivariate analyses revealed that male gender, T4 stage, local or regional residual disease, detectable pre- and post-radiotherapy EBV DNA, and the absence of induction chemotherapy were significant predictors of earlier recurrence. The machine learning-based predictive model further underscored the importance of tumor-related factors in NPC recurrence. Moreover, ER emerged as a pivotal stage in NPC progression, with 15 critical transition signals identified potentially associated with the negative modulation of the immune response. CONCLUSIONS: Our comprehensive analysis of NPC recurrence patterns has unveiled insights into the key factors driving ER and provided novel insights into potential early warning biomarkers and the mechanisms underlying NPC progression.

High free sugars, insulin resistance, and low socioeconomic indicators: the hubs in the complex network of non-communicable diseases in adolescents.

BACKGROUND: Noncommunicable diseases (NCDs) predominantly affect adults, but pathophysiological changes begin decades earlier, as a continuum, with initial events apparent in adolescence. Hence, early identification and intervention are crucial for the prevention and management of NCDs. We investigated the complex network of socioeconomic, behavioral, and metabolic factors associated with the presence of NCD in Brazilian adolescents. METHODS: We conducted a cross-sectional study nested within the São Luís segment of the Ribeirão Preto, Pelotas, and São Luís (RPS) cohort's consortium, focusing on 18-19-year-olds (n = 2515). Data were collected prospectively, from which we constructed a complex network with NCD-related factors/indicators as nodes and their co-occurrences as edges. General and sex-based models analyzed: socioeconomic status, behavioral (smoking, alcohol, and other drugs use, unhealthy diet, poor sleep, physical inactivity), and metabolic factors (overweight/obesity, elevated blood pressure, poor lipid profile). We also looked for NCDs in adolescence like asthma, abnormal spirometry, depression, suicide risk, and poor oral health. The network was characterized by degree, betweenness, eigenvector, local transitivity, Shannon entropy, and cluster coefficient. RESULTS: The adolescents had an average age of 18.3 years, 52.3% were female and 47.7% male. 99.8% of them have a diet rich in free sugars, 15% are overweight/obese and 72.3% had an elevated TyG index. High free sugar emerged as the central hub, followed by high TyG index (an early marker of insulin resistance) and low socioeconomic class. In males, low fiber intake and a high triglycerides/HDL ratio highlighted cardiometabolic concerns; in females, sedentary behavior and poor sleep marked metabolic and psychological challenges, along with caries in both sexes. CONCLUSIONS: Our findings provide insights into central health challenges during adolescence, such as high free sugars, insulin resistance, and low socioeconomic indicators, suggesting that interventions targeted at these central hubs could have a significant impact on their NCD network.

A weighted Bayesian integration method for predicting drug combination using heterogeneous data.

BACKGROUND: In the management of complex diseases, the strategic adoption of combination therapy has gained considerable prominence. Combination therapy not only holds the potential to enhance treatment efficacy but also to alleviate the side effects caused by excessive use of a single drug. Presently, the exploration of combination therapy encounters significant challenges due to the vast spectrum of potential drug combinations, necessitating the development of efficient screening strategies. METHODS: In this study, we propose a prediction scoring method that integrates heterogeneous data using a weighted Bayesian method for drug combination prediction. Heterogeneous data refers to different types of data related to drugs, such as chemical, pharmacological, and target profiles. By constructing a multiplex drug similarity network, we formulate new features for drug pairs and propose a novel Bayesian-based integration scheme with the introduction of weights to integrate information from various sources. This method yields support strength scores for drug combinations to assess their potential effectiveness. RESULTS: Upon comprehensive comparison with other methods, our method shows superior performance across multiple metrics, including the Area Under the Receiver Operating Characteristic Curve, accuracy, precision, and recall. Furthermore, literature validation shows that many top-ranked drug combinations based on the support strength score, such as goserelin and letrozole, have been experimentally or clinically validated for their effectiveness. CONCLUSIONS: Our findings have significant clinical and practical implications. This new method enhances the performance of drug combination predictions, enabling effective pre-screening for trials and, thereby, benefiting clinical treatments. Future research should focus on developing new methods for application in various scenarios and for integrating diverse data sources.