ABSTRACT
BACKGROUND: A significant proportion of septic patients with acute lung injury (ALI) are recognized late due to the absence of an efficient diagnostic test, leading to the postponed treatments and consequently higher mortality. Identifying diagnostic biomarkers may improve screening to identify septic patients at high risk of ALI earlier and provide the potential effective therapeutic drugs. Machine learning represents a powerful approach for making sense of complex gene expression data to find robust ALI diagnostic biomarkers. METHODS: The datasets were obtained from GEO and ArrayExpress databases. Following quality control and normalization, the datasets (GSE66890, GSE10474 and GSE32707) were merged as the training set, and four machine learning feature selection methods (Elastic net, SVM, random forest and XGBoost) were applied to construct the diagnostic model. The other datasets were considered as the validation sets. To further evaluate the performance and predictive value of diagnostic model, nomogram, Decision Curve Analysis (DCA) and Clinical Impact Curve (CIC) were constructed. Finally, the potential small molecular compounds interacting with selected features were explored from the CTD database. RESULTS: The results of GSEA showed that immune response and metabolism might play an important role in the pathogenesis of sepsis-induced ALI. Then, 52 genes were identified as putative biomarkers by consensus feature selection from all four methods. Among them, 5 genes (ARHGDIB, ALDH1A1, TACR3, TREM1 and PI3) were selected by all methods and used to predict ALI diagnosis with high accuracy. The external datasets (E-MTAB-5273 and E-MTAB-5274) demonstrated that the diagnostic model had great accuracy with AUC value of 0.725 and 0.833, respectively. In addition, the nomogram, DCA and CIC showed that the diagnostic model had great performance and predictive value. Finally, the small molecular compounds (Curcumin, Tretinoin, Acetaminophen, Estradiol and Dexamethasone) were screened as the potential therapeutic agents for sepsis-induced ALI. CONCLUSION: This consensus of multiple machine learning algorithms identified 5 genes that were able to distinguish ALI from septic patients. The diagnostic model could identify septic patients at high risk of ALI, and provide potential therapeutic targets for sepsis-induced ALI.
Subject(s)
Acute Lung Injury , Sepsis , Humans , Consensus , Sepsis/complications , Acetaminophen , Acute Lung Injury/diagnosis , Acute Lung Injury/etiology , Machine Learning , rho Guanine Nucleotide Dissociation Inhibitor betaABSTRACT
The aim of this study was to assess the total concentration and speciation variation of heavy metals (Pb, Cd, Cu and Zn) during composting and vermicomposting of industrial sludge with different addition rations of rice husk biochar. Results indicated that pH, EC, total phosphorus (TP) and total potassium (TK) were increased and total organic carbon (TOC) and total nitrogen (TN) were decreased during the composting of industrial sludge with biochar compared with the control (sludge without biochar). The addition of earthworm to the biochar-amended sludge further decreased pH and TOC but highly enhanced the EC, TN, TP and TK. Comparatively lower concentrations of total and DTPA-extractable heavy metals were observed in biochar-amended sludge treatments mixed with earthworm in comparison with the biochar-amended sludge treatments without earthworm or the control. Sequential extraction methods demonstrated that vermicomposting of sludge with biochar converted more metals bound with exchangeable, carbonate and organic matter into the residual fraction in comparison with those composting treatments of sludge with biochar. As a result, the combination of rice husk biochar and earthworm accelerated the passivation of heavy metals in industrial sludge during vermicomposting. Rice husk biochar and earthworm can play a positive role in sequestering the metals during the treatment of industrial sludge. This research proposed a potential method to dispose the heavy metals in industrial sludge to transform waste into resource utilization.
Subject(s)
Metals, Heavy , Oligochaeta , Oryza , Soil Pollutants , Animals , Sewage , Soil Pollutants/analysis , Cadmium , Lead , Soil , Metals, Heavy/analysis , Charcoal , Phosphorus , Pentetic Acid , Nitrogen , PotassiumABSTRACT
Gastric cancer (GC) is one of the most common malignancies and has the second highest lethal rate in the world; thus, finding new medicines with high potency and low toxicity is urgent. Cudrania tricuspidata (Carr.) Bur. ex Lavallee (Moraceae) is a traditional medicinal herb that is considered to have antitumour efficacy. We extracted and isolated cudraxanthone L (CXL) from Cudrania tricuspidata and evaluated its anti-cancer efficacy. CXL treatment inhibited angiogenesis of chorioallantoic membrane (CAM) and repressed the cell viability of various human cancer cells, indicating it presented the antitumour potential. Among them, CXL presented the best inhibitory effects on MGC803 cells. In addition, the invasion, migration and clonogenicity were significantly repressed, S phase of the cell cycle was arrested, and apoptosis was induced when MGC803 cells were treated with CXL. The results of RNA sequencing, qRT-PCR and western blotting verified that CXL regulated the MAPK signalling pathway and induced apoptosis by FAS-mediated pathway. The in vivo data revealed that CXL arrested tumour growth without toxic effects and upregulated the protein levels in FAS-mediated pathway in MGC803 gastric cancer-bearing mice. In summary, we demonstrate CXL presents impactful anti-GC efficacy by regulating the MAPK signalling pathway and promoting the FAS-mediated pathway.
Subject(s)
Antineoplastic Agents, Phytogenic/therapeutic use , MAP Kinase Signaling System/drug effects , Stomach Neoplasms/drug therapy , Stomach Neoplasms/metabolism , Xanthones/therapeutic use , fas Receptor/metabolism , Animals , Antineoplastic Agents, Phytogenic/isolation & purification , Antineoplastic Agents, Phytogenic/pharmacology , Cell Survival/drug effects , Cell Survival/physiology , Dose-Response Relationship, Drug , Hep G2 Cells , Humans , MAP Kinase Signaling System/physiology , Male , Mice , Mice, Inbred BALB C , Mice, Nude , Moraceae , Stomach Neoplasms/pathology , Xanthones/isolation & purification , Xanthones/pharmacology , Xenograft Model Antitumor Assays/methodsABSTRACT
Cassia fistula L. which is known as "Golden Shower", is used as an ornamental plant due to its flowers, and fruit parts of this plant have a high medicinal value. There are few reports providing a comprehensive overview of the chemical composition of its fruit or explaining the differences between samples from different sources because of the complexity of its chemical components. The purpose of the present study was to establish a fingerprint evaluation system based on Similarity Analysis (SA), Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA) for the composition identification and quality control of this herb. Twelve samples from Xinjiang and Sichuan provinces in China and India were analyzed by HPLC, and there were fifteen common peaks in the twelve batches. Molecular weight and formula information can be derived from thirty-one peaks by UHPLC/LTQ-Orbitrap MSn, molecular structure information of twenty components was obtained, of which ten compounds were identified by comparison with standard materials. Samples of twelve batches were divided according to their similarity into four groups, which were basically consistent with three different C.fistula fruit-producing areas. Five compounds were finally considered to be chemical markers to determine the quality of this herb. A fingerprints method combined with chemometrics was established to differentiate the origin of the fruit of C. fistula which has the advantages of effectivity and convenience, laying the foundation for the quality evaluation of this herb from different sources.
Subject(s)
Cassia/chemistry , Drugs, Chinese Herbal/chemistry , Fruit/chemistry , Metabolome , China , Chromatography, High Pressure Liquid , Cluster Analysis , Flavanones/chemistry , Flavanones/isolation & purification , Kaempferols/chemistry , Kaempferols/isolation & purification , Molecular Structure , Principal Component Analysis , Senna Extract/chemistry , Senna Extract/isolation & purificationABSTRACT
The polycyclic aromatic hydrocarbons (PAHs) concentrations in the water, suspended particulate matter (SPM) and sediment from the middle reaches of Huai River were analyzed by a gas chromatograph-mass spectrometer (GC-MS). The mean concentrations for the sum of 16 PAHs (∑16 PAHs) in the water, SPM and sediment were 1204 ng/L, 3192 ng/g (dry weight; dw), and 7955 ng/g (dw), respectively. Along the vertical profiles of water columns, higher ∑16 PAHs levels were seen in surface and bottom water layers and co-located SPM. The PAHs distribution in water and SPM is found to be controlled by organic carbon. Based on the statistic correlations of the organic carbon normalized partition coefficients (lgKOC) and octanol-water partition coefficient (lgKOW), we observed that the calculated partition coefficients do not increase as large as that would be expected from the increase of hydrophobicity. The principal component analysis suggests that coal combustion and the petroleum refinery were the primary PAHs contributors in the studied water-SPM-sediment system. The high ecological risks of PAHs in studied system highlight the urgent needs for remedial actions.
Subject(s)
Environmental Monitoring , Polycyclic Aromatic Hydrocarbons/analysis , Water Pollutants, Chemical/analysis , China , Coal/analysis , Ecology , Gas Chromatography-Mass Spectrometry , Geologic Sediments/analysis , Geologic Sediments/chemistry , Particulate Matter/analysis , Petroleum/analysis , Principal Component Analysis , Risk Assessment , Rivers/chemistry , Water/analysis , Water Pollution, Chemical/statistics & numerical dataABSTRACT
In order to determine the scientificalness of traditionally processed Whitmania pigra, water extraction method and bionic extraction method were used respectively to extract the anticoagulating active components in W. pigra hanging dry products, talcum powder fried products and wine immersing-baked products. Activated partial thromboplastin time (APTT), prothrombin time (PT), thrombin time (TT), and antithrombin activity were selected as the activity indexes to evaluate the anticoagulant activities of different processed W. pigra. Then the contents of protein in different processed W. pigra were measured by Coomassie brilliant blue method to preliminarily explain the reason of anticoagulant activity changes. When water extraction method was used, the results of APTT, PT, TT and antithrombin activity showed that the anticoagulant activities of W. pigra were decreased both in talcum powder fried products and wine immersing-baked products, and the activity order was as follows: hanging dried products> wine immersing-baked products>talcum powder fried products. This order was same as the protein content order. While when bionic extraction was used, APTT was shortened in talcum powder fried products, but all the other results indicated the anticoagulant activities of W. pigra processed products were increased, and the activity order was as follows: wine immersing-baked products>talcum powder fried products>hanging dry products. As compared with water extraction, the bionic extraction was more similar to the absorption process of W. pigra in human digestive system after oral administration and was more scientific. Therefore, the traditional processing method can not only modify the taste and smell, but also enhance the anticoagulant activity of W. pigra.
Subject(s)
Anticoagulants/pharmacology , Leeches/chemistry , Animals , Antithrombins/pharmacology , Bionics , Humans , Partial Thromboplastin Time , Prothrombin Time , Thrombin Time , WaterABSTRACT
BACKGROUND: To evaluate the refractive outcomes for the correction of low to moderate astigmatism up to 1 year following small incision lenticule extraction (SMILE) surgery. METHODS: This retrospective study enrolled 98 eyes from 98 patients who underwent SMILE surgery for the correction of myopia and astigmatism. Only right eyes were included in this study to avoid the bias of orientation errors. The vector method was used to analyze the outcomes of astigmatism at 1 month, 6 months and 12 months after the procedure, including the double-angle plots, correction index (CI), index of success (IOS), angle of error (AofE) and magnitude of error (MofE). The effectiveness, safety, stability and predictability were also investigated during the 12-month follow-up. RESULTS: The preoperative cylinder ranged from -2.75 D to -0.25 D (average of -0.90±0.68 D), and the mean postoperative cylinder values were -0.24±0.29 D, -0.24±0.29 D, and -0.20±0.27 D at 1 month, 6 months, and 12 months, respectively. The mean astigmatism in vector form was -0.14 D×27.19° at 1 month, -0.13 D×27.29° at 6 months, and -0.10 D×28.63° at 12 months after surgery. The CI was 1.00±0.32 and IOS was 0.29±0.44 at the 12-month follow-up. Significant negative correlations were found between the CI and absolute target induced astigmatism (TIA) value, and positive correlations were found between the IOS and absolute AofE value (P<0.05). The MofE was limited within ±1.00 D at the 12-month follow-up. Fifty-six eyes (57.1%) gained one line in corrected distance visual acuity (CDVA) and five eyes (5.1%) gained two lines. There were no significant differences observed in the refractive outcomes among time points. CONCLUSIONS: SMILE surgery was effective and safe in correcting low to moderate astigmatism, and stable refractive outcomes were observed at the long-term follow-up. The undercorrection of astigmatism could possibly be influenced by attempted astigmatism correction preoperatively, the axis rotation during the surgery or wound healing postoperatively. This study suggested that nomograms should be adjusted in correcting astigmatism with SMILE surgery.