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• A paper-based multi-biocatalyst platform was successfully constructed. • Nanoporous gold with unique properties was used as supporting material. • Three different markers can be integrally detected by the multi-biocatalyst platform. • The reliable detection of L. monocytogenes was successfully realized. As biomarkers for pathogenic Listeria monocytogenes , the detection of gene hly , acetoin, and listeriolysin O (LLO) is of great significance for preventing L. monocytogenes infection and diagnosing Listeriosis. Here, a portable paper-based multi-biocatalyst platform was constructed to identify L. monocytogenes by detecting multiple biomarkers at different levels: gene hly (nucleic acid), acetoin (small molecule metabolite), and LLO (protein). The integrating detections of the three biomarkers were successfully performed by two different modified working electrodes on a single paper-based multi-biocatalyst platform. The sensitive and reliable identification of L. monocytogenes was achieved using the portable paper-based multi-biocatalyst platform with wider detection range (from 1.0 × 104 to 1.0 × 109 CFU mL−1) and lower detection limit (104 CFU mL−1). Additionally, the simpler detection procedure and shorter detection time (2 h) endows the portable platform a better detection performance compared with National Food Safety Standard Method (China-GB 4789.30-2016). Moreover, the results detected by the portable platform in spiked samples were consistent with that obtained by the real-time quantitative polymerase chain reaction method, indicating a good application potential. These unique characteristics suggest that the portable platform provides a reliable identification method for L. monocytogenes. [ABSTRACT FROM AUTHOR]

The end Permian to Middle Triassic interval (∼252–242 Ma) witnessed the largest marine mass extinction and the most delayed recovery in the Phanerozoic. The nature and mechanism of these biotic and environmental changes remain unclear. This special issue focuses on the Triassic marine sediments in South China, which provide unique documentation of the collapse and recovery of marine ecosystems. Six papers focus on biotic changes and their ecological significance in Early and Middle Triassic times, documenting evidence from bivalves, marine reptiles, stromatolites, hybodontid teeth, vertebrate coprolites, and other putative fossils. Two papers study conodont biostratigraphy across the Permian-Triassic boundary (PTB) and Induan-Olenekian boundary. Two papers reconstruct the palaeoenvironments of the Early Triassic Chaohu Fauna and Middle Triassic Luoping Biota. Two further papers present new marine δ13C records and biomarker data and link them to volcanic eruptions in Early Triassic times. These new findings are important for understanding the co-evolution between biotic and environmental changes in the aftermath of Permian-Triassic boundary mass extinction. [ABSTRACT FROM AUTHOR]

Chemometric methods have unique advantages regarding comprehensive consideration of multiple parameters and the classification of samples or variables. Classification of oil spill sources was carried out by using chemometric techniques, such as Repeatability Limit, hierarchical cluster analysis (HCA), Student's t -test and Principal component analysis (PCA) Biplot. In addition, this paper takes the fingerprint identification of a Dalian "7.16″ oil spill accident as an example to illustrate the effectiveness of chemometric techniques in oil identification. PCA scores plot (explaining 82.77% of variance accounted for three PCs) showed that samples belong to four clusters and result of HCA method further confirmed that. The residual oil in Jinshatan Beach and Haibei Square may be caused by the explosion of Dalian "7–16" oil pipeline accident. The use of chemometric techniques is significant in providing independent validation for classifying the types of spilled oil in the investigation of oil spill pollution. The results will be of great significance to improve the accuracy and efficiency of oil spill identification based on oil fingerprint. • Origin based classification of oil residue by GC-MS and chemometrics method. • Multivariate and multiway analysis are mainly used in oil fingerprint methods. • Dalian "7.16″ oil spill accident provide a case platform for chemometric techniques. • It involved a principal component and hierarchical cluster analysis. [ABSTRACT FROM AUTHOR]

The origin of thirteen major oil fields in Zhu III sub-basin, Pearl River Mouth Basin, was studied by using the results of Rock-Eval pyrolysis on 340 samples and biomarker analysis on 18 source rock samples and 33 oil samples. The two possible source rock intervals have different biomarker assemblages and were deposited in different environments. The Eocene Wenchang Formation (E 2 w, 49.5–35 Ma) is characterized by high hopane/sterane ratio (>37.84), high 4-methyl sterane index (0.28–1.06), low gammacerane index (<0.09), low extended tricyclic terpane ratio [ETR = (C 28 + C 29 )/(C 28 + C 29 + Ts), 0.13–0.20] and bicadinane/C 30 hopane (<0.02), which was deposited in fresh-brackish water and dominated by algae. On the contrary, Oligocene Eenping Formation (E 3 e, 35–30 Ma) has high gammacerane index (>0.10), high bicadinane/C 30 hopane (up to 73.62) but low hopane/sterane ratio (<12.50), and it was deposited in relative saline water environment with significant high terrestrial plant debris input. Because of complex geologic settings, oils have different distribution. By using oil-source correlation analysis and hierarchical cluster analysis, two source-related oil groups were identified. Oils found in the Wenchang A depression and Yangjiang uplift, which are classified to oil group 1, were derived from E 3 e. Oils found in the Wenchang B depression and Shenhu uplift, which are classified to oil group 2, were derived from both E 2 w and E 3 e source rocks. But the Qionghai uplift received supply from both the Wenchang A and B depression. This distribution pattern is also proven by using a simple three-dimensional model called PathWay™. An explanation was put forward in this paper about the oils in Zhu III sub-basin and four potential petroleum accumulations were roughly predicted where no well drilled. [ABSTRACT FROM AUTHOR]

In the brackish water sedimentary environment of the Junggar Basin in Xinjiang, the organic-rich shale and shale oil formation with relatively low maturity, is characterized by relatively high abundance of C 28 regular steranes. However, the biogenic source of organic matter and favorable sedimentary environment for the type of source rock has been thoroughly classified. In this paper, organic geochemical and petrological, analyses of the Lucaogou Formation shale in the Jimusaer Sag, Junggar Basin in the north of Xinjiang Uygur Autonomy Region were carried out. The source rocks in the Lucaogou Formation are mainly composed of two types of maceral including lamalginite (cyanobacteria) and telalginite (green algae), with the former predominantly fueling the high C 28 regular sterane content. Petrological, organic and inorganic geochemical analyses suggest that the lamalginite was developed in low-salinity water while the telalginite was developed in high-salinity water. Based on geochemical and organic petrological characteristics, both the lamalginite and telalginite have good hydrocarbon-generating potential, but in the lower thermal evolution stage of the Lucaogou Formation source rock, telalginite have higher hydrocarbon-generating rate. • Lamalginite (cyanobacteria) is the primary source of C 28 regular steranes. • The lamalginite (cyanobacteria) is more developed when the salinity is low and the telalginite (green algae) is more developed when the salinity is high. • In the lower thermal evolution stage of the Lucaogou Formation source rock, the lamalginite (cyanobacteria) has lower hydrocarbon-generating rate than the telalginite (green algae). [ABSTRACT FROM AUTHOR]

Due to the similarity of the biomarker characteristics of the source rocks of different layers, the progress of the oil source research of the Yanchang Formation in the Ordos Basin is difficult and slow, which highlights the shortcomings of traditional research methods. Given this, this paper uses the gas chromatography-mass spectrometry analysis results of a large volume of samples of the Yanchang Formation in the basin as the dataset, and performs an exploratory application of the factor analysis (FA, a multivariate statistical method) to analyze the molecular geochemical characteristics of organic matter, with an aim to find features that have not been noticed in the past, and give a reasonable explanation for the oil source. The findings are summarized as below: with the help of multivariate (31 molecular geochemical parameters are introduced), FA can quantify many geochemical properties of samples well, which brings convenience to research. Based on the results, it was found that parameters such as C 26 TT/C 25 TT, sterane/hopane, and ΣC 19-26 TT/C 30 αβ can effectively distinguish the samples of different areas and layers, and it is further believed that the Chang 9 source rock has higher contributions to adjacent layers (mainly the Chang 8–Chang 10 oil groups) in areas where it is abundant (mainly the Wuqi-Zhidan area), while in the other areas and layers, oil is mostly attributed to the Chang 7 source rock. •Conventional oil-source research methods are inadequate when facing the Yanchang Fm. of Ordos Basin. •Exploratively combine factor analysis methods to analyze a large amount of GC-MS data. •Factor analysis effectively reveals differences in petroleum geochemistry among different source rocks. • This research has the potential value of promoting the development of petroleum geochemistry technology. [ABSTRACT FROM AUTHOR]

• Identification of highly-reliable and easierly-detectable biomarkers capable of secreting into blood, urine and saliva by integrating transcriptomics and proteomics data at the system biology level. • Obtainment of the effective candidate biomarkers ESM1, CTHRC1, AZGP1 for colorectal cancer capable of secreting into blood, urine and saliva. • Spanning the huge gap between transcriptome and proteomics. • Easily to be applied to identify biomarkers of other types of tumors. Colorectal cancer is one of the top leading causes of cancer mortality worldwide, especially in China. However, most of the current treatments are invasive and can only be applied to very few cancers. The earlier a malignant tumor is diagnosed, the higher the patient's survival rate. In this study, we proposed a computational framework to identify highly-reliable and easierly-detectable biomarkers capable of secreting into blood, urine and saliva by integrating transcriptomics and proteomics data at the system biology level. First, a large number of transcriptome data were processed to identify candidate biomarkers for colorectal cancer. Second, three classified models are constructed to predict biomarkers for colorectal cancer capable of secreting into blood, urine and saliva, which are effective disease diagnosis media to facilitate clinical screening. Then biological functions and molecular mechanisms of the candidate biomarkers of colorectal cancer are inferred utilizing multi-source biological knowledge and literature mining. Furthermore, the classification power of different combinations of candidate biomarkers is verified by machine learning models. In addition, the targeted drugs of the predicted biomarkers are further analyzed to provide assistance for clinical treatment of colorectal cancer. In this paper, our proposed computational model not only provides the effective candidate biomarkers ESM1, CTHRC1, AZGP1 for colorectal cancer capable of secreting into blood, urine and saliva, but also helps to understand the molecular mechanism of colorectal cancer. This computational framework can span the huge gap between transcriptome and proteomics, which can easily be applied to the biomarker research for other types of tumor. [ABSTRACT FROM AUTHOR]