AntDAS-GCMS: A New Comprehensive Data Analysis Platform for GC-MS-Based Untargeted Metabolomics with the Advantage of Addressing the Time Shift Problem.

Over the years, a number of state-of-the-art data analysis tools have been developed to provide a comprehensive analysis of data collected from gas chromatography-mass spectrometry (GC-MS). Unfortunately, the time shift problem remains unsolved in these tools. Here, we developed a novel comprehensive data analysis strategy for GC-MS-based untargeted metabolomics (AntDAS-GCMS) to perform total ion chromatogram peak detection, peak resolution, time shift correction, component registration, statistical analysis, and compound identification. Time shift correction was specifically optimized in this work. The information on mass spectra and elution profiles of compounds was used to search for inherent landmarks within analyzed samples to resolve the time shift problem across samples efficiently and accurately. The performance of our AntDAS-GCMS was comprehensively investigated by using four complex GC-MS data sets with various types of time shift problems. Meanwhile, AntDAS-GCMS was compared with advanced GC-MS data analysis tools and classic time shift correction methods. Results indicated that AntDAS-GCMS could achieve the best performance compared to the other methods.

The Key Role of Plant Hormone Signaling Transduction and Flavonoid Biosynthesis Pathways in the Response of Chinese Pine (Pinus tabuliformis) to Feeding Stimulation by Pine Caterpillar (Dendrolimus tabulaeformis).

In nature, plants have developed a series of resistance mechanisms to face various external stresses. As understanding of the molecular mechanisms underlying plant resistance continues to deepen, exploring endogenous resistance in plants has become a hot topic in this field. Despite the multitude of studies on plant-induced resistance, how plants respond to stress under natural conditions remains relatively unclear. To address this gap, we investigated Chinese pine (Pinus tabuliformis) using pine caterpillar (Dendrolimus tabulaeformis) under natural conditions. Healthy Chinese pine trees, approximately 10 years old, were selected for studying induced resistance in Huangtuliangzi Forestry, Pingquan City, Chengde City, Hebei Province, China. Pine needles were collected at 2 h and 8 h after feeding stimulation (FS) via 10 pine caterpillars and leaf clipping control (LCC), to simulate mechanical damage caused by insect chewing for the quantification of plant hormones and transcriptome and metabolome assays. The results show that the different modes of treatments significantly influence the contents of JA and SA in time following treatment. Three types of differentially accumulated metabolites (DAMs) were found to be involved in the initial response, namely phenolic acids, lipids, and flavonoids. Weighted gene co-expression network analysis indicated that 722 differentially expressed genes (DEGs) are positively related to feeding stimulation and the specific enriched pathways are plant hormone signal transduction and flavonoid biosynthesis, among others. Two TIFY transcription factors (PtTIFY54 and PtTIFY22) and a MYB transcription factor (PtMYB26) were found to be involved in the interaction between plant hormones, mainly in the context of JA signal transduction and flavonoid biosynthesis. The results of this study provide an insight into how JA activates, serving as a reference for understanding the molecular mechanisms of resistance formation in conifers responding to mandibulate insects.

Six-Transmembrane Epithelial Antigen of Prostate 3 Promotes Hepatic Insulin Resistance and Steatosis.

Nonalcoholic fatty liver disease (NAFLD) is a clinicopathological syndrome characterized by excessive deposition of fatty acids in the liver. Further deterioration leads to nonalcoholic steatohepatitis, cirrhosis, and hepatocellular carcinoma, creating a heavy burden on human health and the social economy. Currently, there are no effective and specific drugs for the treatment of NAFLD. Therefore, it is important to further investigate the pathogenesis of NAFLD and explore effective therapeutic targets for the prevention and treatment of the disease. Six-transmembrane epithelial antigen of prostate 3 (STEAP3), a STEAP family protein, is a metalloreductase. Studies have shown that it can participate in the regulation of liver ischemia-reperfusion injury, hepatocellular carcinoma, myocardial hypertrophy, and other diseases. In this study, we found that the expression of STEAP3 is upregulated in NAFLD. Deletion of STEAP3 inhibits the development of NAFLD in vivo and in vitro, whereas its overexpression promotes palmitic acid/oleic acid stimulation-induced lipid deposition in hepatocytes. Mechanistically, it interacts with transforming growth factor beta-activated kinase 1 (TAK1) to regulate the progression of NAFLD by promoting TAK1 phosphorylation and activating the TAK1-c-Jun N-terminal kinase/p38 signaling pathway. Taken together, our results provide further insight into the involvement of STEAP3 in liver pathology.

AntDAS-DDA: A New Platform for Data-Dependent Acquisition Mode-Based Untargeted Metabolomic Profiling Analysis with Advantage of Recognizing Insource Fragment Ions to Improve Compound Identification.

Data-dependent acquisition (DDA) mode in ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) can provide massive amounts of MS1 and MS/MS information of compounds in untargeted metabolomics and can thus facilitate compound identification greatly. In this work, we developed a new platform called AntDAS-DDA for the automatic processing of UHPLC-HRMS data sets acquired under the DDA mode. Several algorithms, including extracted ion chromatogram extraction, feature extraction, MS/MS spectrum construction, fragment ion identification, and MS1 spectrum construction, were developed within the platform. The performance of AntDAS-DDA was investigated comprehensively with a mixture of standard and complex plant data sets. Results suggested that features in complex sample matrices can be extracted effectively, and the constructed MS1 and MS/MS spectra can benefit in compound identification greatly. The efficiency of compound identification can be improved by about 20%. AntDAS-DDA can take full advantage of MS/MS information in multiple sample analyses and provide more MS/MS spectra than single sample analysis. A comparison with advanced data analysis tools indicated that AntDAS-DDA may be used as an alternative for routine UHPLC-HRMS-based untargeted metabolomics. AntDAS-DDA is freely available at http://www.pmdb.org.cn/antdasdda.

Identification of Oak-Barrel and Stainless Steel Tanks with Oak Chips Aged Wines in Ningxia Based on Three-Dimensional Fluorescence Spectroscopy Combined with Chemometrics.

With the increased incidence of wine fraud, a fast and reliable method for wine certification has become a necessary prerequisite for the vigorous development of the global wine industry. In this study, a classification strategy based on three-dimensional fluorescence spectroscopy combined with chemometrics was proposed for oak-barrel and stainless steel tanks with oak chips aged wines. Principal component analysis (PCA), partial least squares analysis (PLS-DA), and Fisher discriminant analysis (FDA) were used to distinguish and evaluate the data matrix of the three-dimensional fluorescence spectra of wines. The results showed that FDA was superior to PCA and PLS-DA in classifying oak-barrel and stainless steel tanks with oak chips aged wines. As a general conclusion, three-dimensional fluorescence spectroscopy can provide valuable fingerprint information for the identification of oak-barrel and stainless steel tanks with oak chips aged wines, while the study will provide some theoretical references and standards for the quality control and quality assessment of oak-barrel aged wines.

Blue and white light modulation of a flexible electroluminescent device based on phosphors.

Flexibility, certain mechanical strength, and color modulation are significant elements for flexible optoelectronic devices. However, it is laborious to fabricate a flexible electroluminescent device with balanceable flexibility and color modulation. Here, we mix a conductive nonopaque hydrogel and phosphors to fabricate a flexible alternating current electroluminescence (ACEL) device with color modulation ability. This device realizes flexible strain based on polydimethylsiloxane and carboxymethyl cellulose/polyvinyl alcohol ionic conductive hydrogel. The color modulation ability is achieved by varying the voltage frequency applied on the electroluminescent phosphors. The color modulation could realize blue and white light modulation. Our electroluminescent device exhibits great potential in artificial flexible optoelectronics.

Maillard reaction products and guaiacol as production process and raw material markers for the authentication of sesame oil.

BACKGROUND: Sesame oil has an excellent flavor and is widely appreciated. It has a higher price than other vegetable oils because of the high price of its raw materials, and different processing techniques also result in products of different quality levels, which can command different prices. In the market, there is a persistent problem of adulteration of sesame oil, driven by economic interests. The screening of volatile markers used to distinguish the authenticity of sesame oil raw materials and production processes is therefore very important. RESULTS: In this work, six markers related to the production processes and raw materials of sesame oil were screened by gas chromatography-tandem mass spectrometry (GC-MS/MS) combined with chemometric analysis. They were 3-methyl-2-butanone, 2-ethyl-5-methyl-pyrazine, guaiacol, 2,6-dimethyl-pyrazine, 5-methyl furfural, and ethyl-pyrazine. The concentration of these markers in sesame oil is between 10 and1000 times that found in other vegetable oils. However, only 3-methyl-2-butanone and 2-ethyl-5-methyl-pyrazine differed significantly as the result of the use of different production processes. Except for guaiacol, which was mainly derived from raw materials, the other five compounds mentioned above all result from the Maillard reaction during thermal processing. The six compounds mentioned above are sufficient to distinguish fraud involving sesame oil raw materials and production processes, and can identify accurately adulteration levels of 30% concentration. CONCLUSION: In this study, the classification markers can identify the adulteration of sesame oil accurately. These six compounds are therefore important for the authenticity of sesame oil and provide a theoretical basis for the rapid and accurate identification of the authenticity of sesame oil. © 2021 Society of Chemical Industry.

Phylogenetically divergent bacteria consortium from neutral activated sludge showed heightened potential on bioleaching spent lithium-ion batteries.

Recycling of spent lithium-ion batteries (LIBs) has become a global issue because of the potential environment risks raised by spent LIBs as well as high valuable metal content remaining in them. Although bioleaching is an environmentally friendly method to recover metals from spent LIBs, the commonly utilized bioleaching bacterial consortia or strains enriched/isolated from acidic environments cannot be applied at large scales owing to their long leaching cycle and poor tolerance to organic compounds. Here, two bioleaching consortia were enriched in 60 days from neutral activated sludge and were identified phylogenetically divergent from the documented bioleaching bacteria. The results showed that the novel consortia shortened the leaching cycle almost by half when compared to the previous reported consortia or strains, of which one consortium dominated by Acidithiobacillus ferrooxidans displayed high bioleaching efficiency on LiMn2O4, as 69.46% lithium (Li) and 67.60% manganese (Mn) were leached out in seven days. This consortium was further domesticated using cathodic materials for 100 days and proved consisted of three mixotrophs and two chemoautotrophs, three of which were novel species from the genera Sulfobacillus and Leptospirillum. More genes coding for proteins that utilize organic compounds were annotated in the metagenomic assembled genomes (MAGs) than previously reported. A mutualistic relationship between mixotrophs and chemoautotrophs was suggested to help the consortium surviving under either organic- rich or shortage environments. The results discovered that novel bioleaching bacteria with shorter leaching cycle and higher tolerance to organics could be enriched from non-acidic environments, which showed high potential for the metal recovering from spent LIBs or other organic-rich environments.

Fluorescent sensor based on quantum dots and nano-porphyrin for highly sensitive and specific determination of ethyl carbamate in fermented food.

BACKGROUND: Ethyl carbamate (EC) is a potentially toxic carcinogen produced during fermentation and storage of fermented foods, and many countries have set thresholds for its content in food. Therefore, sensitive, rapid and accurate detection of EC is meaningful to ensure the quality of fermented food. RESULTS: This study introduces a CdTe quantum dots/nano-5,10,15,20-tetrakis (4-methoxyphenyl)-porphyrin (nano TPP-OCH3 ) fluorescence sensor system detection of EC. The specificity of this sensing mainly relies on a photo-induced electron transfer and electrostatic force interaction between EC and nano TPP-OCH3 . This sensor presented a linear range of 10 to 1000 µg L-1 (R2  = 0.9903) with a low detection limit of 7.14 µg L-1 . Meanwhile, the recovery (91.19-101.09%) and precision [relative standard deviation (RSD) = 0.64-3.05%] of the sensor for the analysis of fermented food (yellow rice wine, soy sauce, Chinese spirits, Pu-erh tea) samples were good and could meet the requirements of practical detection. Moreover, the detection results of fermented food (yellow rice wine, soy sauce, Chinese spirits, Pu-erh tea) samples by this sensor are basically consistent with those of high-performance liquid chromatography with fluorescence detector (HPLC-FLD). CONCLUSION: This method was expected to provide a potential platform for sensitive and accurate detection of EC in food safety monitoring, which would provide knowledge of the flavor and quality related to fermented food. © 2021 Society of Chemical Industry.

Differentiating Westlake Longjing tea from the first- and second-grade producing regions using ultra high performance liquid chromatography with quadrupole time-of-flight mass spectrometry-based untargeted metabolomics in combination with chemometrics.

There are numerous articles published for geographical discrimination of tea. However, few research works focused on the authentication and traceability of Westlake Longjing green tea from the first- and second-grade producing regions because the tea trees are planted in a limited growing zone with identical cultivate condition. In this work, a comprehensive analytical strategy was proposed by ultrahigh performance liquid chromatography-quadrupole time-of-flight mass spectrometry-based untargeted metabolomics coupled with chemometrics. The automatic untargeted data analysis strategy was introduced to screen metabolites that expressed significantly among different regions. Chromatographic features of metabolites can be automatically and efficiently extracted and registered. Meanwhile, those that were valuable for geographical origin discrimination were screened based on statistical analysis and contents in samples. Metabolite identification was performed based on high-resolution mass values and tandem mass spectra of screened peaks. Twenty metabolites were identified, based on which the two-way encoding partial least squares discrimination analysis was built for geographical origin prediction. Monte Caro simulation results indicated that prediction accuracy was up to 99%. Our strategy can be applicable for practical applications in the quality control of Westlake Longjing green tea.

Disordered Metabolic Profiling in Plasma and Tissues of Mice Infected with Artemisinin-Sensitive and -Resistant Plasmodium berghei K173 Determined by 1H NMR Spectroscopy.

Artemisinin resistance has inevitably emerged in several malaria-endemic areas and led to an incremental clinical failure rate for artemisinin-based combination therapy (ACT), which is strongly recommended by the World Health Organization (WHO). Genetically resilient malaria parasites have evolved antimalarial drug-evasion mechanisms; meanwhile, the metabolic cross-talk between the malaria parasites and the host is of significance during the invasion. The intention of this work, therefore, is to propose a feasible method to discover the systematic metabolic phenotypes of mice invaded with artemisinin-sensitive or -resistant Plasmodium berghei K173 when compared with healthy mice. Biological samples, including plasma, liver, spleen, and kidney, of mice collected after euthanasia at day 7 were subjected to 1H nuclear magnetic resonance spectroscopy. Multivariable data analysis was utilized to estimate the metabolic characteristics of these samples from uninfected and infected mice. In contrast with healthy mice, both sensitive and resistant malaria-parasite-infected models displayed distinct metabolic profiles. Parasite invasion significantly changed the glycolysis, Kreb's cycle, and amino acid metabolism in plasma and tissues. Decreased N, N-dimethylglycine and glycine levels in plasma from the artemisinin-sensitive P. berghei-infected group and increased lactate, lipid, and aspartate in the artemisinin-resistant P. berghei-infected group were observed, respectively. In the liver, the artemisinin-sensitive group up-regulated the glutamate level and down-regulated glutamine. Artemisinin-resistant parasite exposure decreased ethanol and allantoin levels. The levels of myo-inositol and valine in the spleen were increased due to artemisinin-sensitive P. berghei infection, together with decreased trimethylamine N-oxide, phosphocholine, ß-glucose, and acetoacetic acid. In the artemisinin-resistant group, the spleen showed a remarkably increased phosphocholine content along with decreased dimethylglycine and arginine levels. In the kidney, artemisinin-sensitive P. berghei K173 caused increased lysine, glutamate, creatine, and 2-hydroxybutyrate as well as decreased ethanol. Artemisinin-resistant P. berghei led to low glycerophosphorylcholine and high acetate, betaine, and hypoxanthine. Mutual and specific altered metabolites and, accordingly, metabolic pathways induced by the infection of artemisinin-sensitive or -resistant P. berghei were therefore screened out. This should be considered a preliminary study to establish a direct relationship with the host metabolic background and artemisinin resistance.

Tanshinol alleviates impaired bone formation by inhibiting adipogenesis via KLF15/PPARγ2 signaling in GIO rats.

Glucocorticoid (GC)-induced osteoporosis (GIO) is characterized by impaired bone formation, which can be alleviated by tanshinol, an aqueous polyphenol isolated from Salvia miltiorrhiza Bunge. In this study we investigated the molecular mechanisms underlying GC-induced modulation of osteogenesis as well as the possibility of using tanshinol to interfere with GIO. Female SD rats aged 4 months were orally administered distilled water (Con), prednisone (GC, 5 mg·kg-1·d-1), GC plus tanshinol (Tan, 16 mg·kg-1·d-1) or GC plus resveratrol (Res, 5 mg·kg-1·d-1) for 14 weeks. After the rats were sacrificed, samples of bone tissues were collected. The changes in bone formation were assessed using Micro-CT, histomorphometry, and biomechanical assays. Expression of Kruppel-like factor 15 (KLF15), peroxisome proliferator-activated receptor γ 2 (PPARγ 2) and other signaling proteins in skeletal tissue was measured with Western blotting and quantitative RT-PCR. GC treatment markedly increased the expression of KLF15, PPARγ2, C/EBPα and aP2, which were related to adipogenesis, upregulated FoxO3a pathway proteins (FoxO3a and Gadd45a), and suppressed the canonical Wnt signaling (ß-catenin and Axin2), which was required for osteogenesis. Thus, GC significantly decreased bone mass and bone quality. Co-treatment with Tan or Res effectively counteracted GC-impaired bone formation, suppressed GC-induced adipogenesis, and restored abnormal expression of the signaling molecules in GIO rats. We conclude that tanshinol counteracts GC-decreased bone formation by inhibiting marrow adiposity via the KLF15/PPARγ2/FoxO3a/Wnt pathway.

AntDAS: Automatic Data Analysis Strategy for UPLC-QTOF-Based Nontargeted Metabolic Profiling Analysis.

High-quality data analysis methodology remains a bottleneck for metabolic profiling analysis based on ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry. The present work aims to address this problem by proposing a novel data analysis strategy wherein (1) chromatographic peaks in the UPLC-QTOF data set are automatically extracted by using an advanced multiscale Gaussian smoothing-based peak extraction strategy; (2) a peak annotation stage is used to cluster fragment ions that belong to the same compound. With the aid of high-resolution mass spectrometer, (3) a time-shift correction across the samples is efficiently performed by a new peak alignment method; (4) components are registered by using a newly developed adaptive network searching algorithm; (5) statistical methods, such as analysis of variance and hierarchical cluster analysis, are then used to identify the underlying marker compounds; finally, (6) compound identification is performed by matching the extracted peak information, involving high-precision m/z and retention time, against our compound library containing more than 500 plant metabolites. A manually designed mixture of 18 compounds is used to evaluate the performance of the method, and all compounds are detected under various concentration levels. The developed method is comprehensively evaluated by an extremely complex plant data set containing more than 2000 components. Results indicate that the performance of the developed method is comparable with the XCMS. The MATLAB GUI code is available from http://software.tobaccodb.org/software/antdas .

Method for multi-task learning fusion network traffic classification to address small sample labels.

In the context of the proliferated evolution of network service types and the expeditious augmentation of network resource deployment, the requisition for copious labeled datasets to facilitate superior performance in traffic classification methods, particularly those hinging on deep learning, is imperative. Nonetheless, the procurement and annotation of such extensive datasets necessitate considerable temporal and human resource investments. In response to this predicament, this work introduces a methodology, termed MTEFU, leveraging a deep learning model-based multi-task learning algorithm, strategically designed to mitigate the reliance on substantial labeled training samples. Multiple classification tasks, encompassing duration, bandwidth size, and business traffic category, are incorporated, with a shared parameter strategy implemented amongst tasks to assure the transference of information across disparate tasks. Employing CNN, SAE, GRU, and LSTM as multi-task learning classification models, training validation and experimental testing were conducted on the QUIC dataset. A comparative analysis with single-task and ensemble learning methods reveals that, in the context of predicting network traffic types, the accuracy derived from the multi-task learning strategy, even with a mere 150 labeled samples, can emulate the 94.67% accuracy achieved through single-task learning with a fully labeled dataset of 6139 samples.

Self-Powered and Self-Recovered Mechanoluminescent Electronic Skins for Detecting and Distinguishing Diverse External Stimuli.

The concept of simulating external mechanical stimuli to generate luminescence has been a long-standing aspiration in real-time dynamic visualization. However, creating self-power and self-restoring mechanoluminescent electronic skins for artificial sensors poses significant challenges. In this study, we introduce a cutting-edge triboelectric-mechanoluminescent electronic skin (TMES) that exhibits a remarkable response to multiple external stimuli. This advancement is achieved by integrating a mechanoluminescent intermediate layer within a triboelectric nanogenerator (TENG). When pressure is applied to TMES, the maximum detection voltage can reach hundreds of volts and the maximum correlation sensitivity is 11.76 V/N. Moreover, we incorporate luminescence materials into mechanoluminescence layer, and the maximum absolute sensitivity SR can reach 1.41%. The device can not only distinguish between external stimuli such as pressing and bending but also continuously track external mechanical stimuli. A 4 × 4 matrix and motion prediction of 8 different postures were established to further demonstrate the significant advantages of the developed device in spatial detection. The versatility and performance of the TMES hint at its vast potential in areas such as human-computer interaction and wearable electronics, paving the way for more intuitive and dynamic technological interfaces.

A novel comprehensive strategy for high-thoroughly studying released compounds during the combustion process of herbs. A case study for Artemisia argyi Levl. et Vant.

The comprehensive study of compound variations in released smoke during the combustion process is a great challenge in many scientific fields related to analytical chemistry like traditional Chinese medicine, environment analysis, food analysis, etc. In this work, we propose a new comprehensive strategy for efficiently and high-thoroughly characterizing compounds in the online released complex smokes: (i) A smoke capture device was designed for efficiently collecting chemical constituents to perform gas chromatography-mass spectrometry (GC-MS) based untargeted analysis. (ii) An advanced data analysis tool, AntDAS-GCMS, was used for automatically extracting compounds in the original acquired GC-MS data files. Additionally, a GC-MS data analysis guided instrumental parameter optimizing strategy was proposed for the optimization of parameters in the smoke capture device. The developed strategy was demonstrated by the study of compound variations in the smoke of traditional Chinese medicine, Artemisia argyi Levl. et Vant. The results indicated that more than 590 components showed significant differences among released smokes of various moxa velvet ratios. Finally, about 88 compounds were identified, of which phenolic compounds were the most abundant, followed by aromatics, alkenes, alcohols and furans. In conclusion, we may provide a novel approach to the studies of compounds in online released smoke.

TNIP3 protects against pathological cardiac hypertrophy by stabilizing STAT1.

Pathological cardiac hypertrophy is one of the major risk factors of heart failure and other cardiovascular diseases. However, the mechanisms underlying pathological cardiac hypertrophy remain largely unknown. Here, we identified the first evidence that TNFAIP3 interacting protein 3 (TNIP3) was a negative regulator of pathological cardiac hypertrophy. We observed a significant upregulation of TNIP3 in mouse hearts subjected to transverse aortic constriction (TAC) surgery and in primary neonatal rat cardiomyocytes stimulated by phenylephrine (PE). In Tnip3-deficient mice, cardiac hypertrophy was aggravated after TAC surgery. Conversely, cardiac-specific Tnip3 transgenic (TG) mice showed a notable reversal of the same phenotype. Accordingly, TNIP3 alleviated PE-induced cardiomyocyte enlargement in vitro. Mechanistically, RNA-sequencing and interactome analysis were combined to identify the signal transducer and activator of transcription 1 (STAT1) as a potential target to clarify the molecular mechanism of TNIP3 in pathological cardiac hypertrophy. Via immunoprecipitation and Glutathione S-transferase assay, we found that TNIP3 could interact with STAT1 directly and suppress its degradation by suppressing K48-type ubiquitination in response to hypertrophic stimulation. Remarkably, preservation effect of TNIP3 on cardiac hypertrophy was blocked by STAT1 inhibitor Fludaradbine or STAT1 knockdown. Our study found that TNIP3 serves as a novel suppressor of pathological cardiac hypertrophy by promoting STAT1 stability, which suggests that TNIP3 could be a promising therapeutic target of pathological cardiac hypertrophy and heart failure.

A novel chromatographic peak alignment method coupled with trilinear decomposition for three dimensional chromatographic data analysis to obtain the second-order advantage.

The alignment of chromatographic peaks and deconvolution of overlapped peaks still remain challenges in the field of complex sample analysis. In this paper, we highlight a strategy that employs a new time shift alignment method derived from the well-known Rank Minimization method for aligning chromatographic peak shifts among samples and then uses trilinear decomposition methodology to interpret the overlapped chromatographic peaks in order to quantify analytes of interest. The performance of this novel strategy for chromatographic data analysis was evaluated using simulated chromatographic data as well as real chromatographic data. The results indicate that the new time shift alignment method can accurately correct time shifts in test samples even in the presence of unexpected interferences, and thus the low-rank trilinearity of the same analyte can be obtained, which will be helpful for trilinear decomposition to achieve the second-order advantage. Moreover, the results showed that this new alignment method is more automated in comparison with the Rank Minimization method and will be suitable for the alignment of the time shifts of analytes that are completely overlapped by coeluted interferences.

The impact of Ag nanoparticles on methane emission in two typical paddy soils.

Numerous applications of Ag nanoparticles (AgNPs) have increased the likelihood of their release and accumulation in agroecosystem. Thus far, few studies have evaluated the impacts of AgNPs to soil methane emissions and the microbial dynamics. In this study, microcosmic experiments were conducted to investigate the responses of methanogenic processes from two paddy soils (Cambisols and Ultisols) subjected to four AgNPs doses (0.1, 1, 10 and 50 mg/kg). The results showed that 0.1 and 1 mg/kg AgNPs had no significant effects on CH4 emissions, but 50 mg/kg AgNPs increased soil CH4 emissions in both paddy soils. The aggravation effect of AgNPs on CH4 emissions was more apparent in Ultisols compared to Cambisols paddy soils. Real-time PCR suggested that 50 mg/kg AgNPs significantly increased the ratio of methanogenic to bacterial gene for both paddy soils. Amplicon sequencing indicated that methanogenic community was clustered into a separate group after 50 mg/kg AgNPs exposure. Structural equation model illustrated that Methanosarcinales was both significantly responded to AgNPs in Cambisols and Ultisols soils; however, Methanocellales significantly responded to AgNPs only in Cambisols soils. Subsequently, uncontrolled use of AgNPs may account as an environmental risk due to the potentially increased soil CH4 emissions in paddy ecosystems.