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The moisture content (MC) and acidity content (AC) of the fermented grains used in liquor production directly affect the liquor quality and yield; as such, they are important indicators used to evaluate the quality of fermented grains. In this study, extreme gradient enhancement algorithm (XGBoost), partial least square regression (PLSR), and extreme learning machine (ELM) models were developed based on spectral data collected by near-infrared (NIR) hyperspectral imaging (HSI) technology. First, PLSR models were established after SNV and MSC algorithms preprocessed the HSI data, and the best preprocessing method was determined (MC: SNV; AC: MSC). Then, the competitive adaptive reweighting sampling (CARS) algorithm and principal component analysis (PCA), both combined with the successive projection algorithm (SPA), were used to extract the characteristic wavelengths from the full-band spectral data. Ultimately, the XGBoost model developed using the characteristic wavelengths extracted by CARS-SPA most accurately predicted the MC (RPD = 6.4167, RP2 = 0.9757, RMSEP = 0.0442 g·100 g−1) and AC (RPD = 13.0308, RP2 = 0.9941, RMSEP = 0.0216 mmol·10 g−1). The results showed that the XGBoost model could more accurately predict the MC and AC of the fermented grains from hyperspectral images of the grains, providing an effective method for the rapid analysis of raw materials used in the fermentation of liquor. [ABSTRACT FROM AUTHOR]

Starch and alcohol serve as pivotal indicators in assessing the quality of lees fermentation. In this paper, two hyperspectral imaging (HSI) techniques (visible–near‐infrared (Vis–NIR) and NIR) were utilized to acquire separate HSI data, which were then fused and analyzed toforecast the starch and alcohol contents during the fermentation of lees. Five preprocessing methods were first used to preprocess the Vis–NIR, NIR, and the fused Vis–NIR and NIR data, after which partial least squares regression models were established to determine the best preprocessing method. Following, competitive adaptive reweighted sampling, successive projection algorithm, and principal component analysis algorithms were used to extract the characteristic wavelengths to accurately predict the starch and alcohol levels. Finally, support vector machine (SVM)‐AdaBoost and XGBoost models were built based on the low‐level fusion (LLF) and intermediate‐level fusion (ILF) of single Vis–NIR and NIR as well as the fused data. The results showed that the SVM‐AdaBoost model built using the LLF data afterpreprocessing by standard normalized variable was most accurate for predicting the starch content, with an RP2$\ R_P^2$ of 0.9976 and a root mean square error of prediction (RMSEP) of 0.0992. The XGBoost model built using ILF data was most accurate for predicting the alcohol content, with an RP2$R_P^2$ of 0.9969 and an RMSEP of 0.0605. In conclusion, the analysis of fused data from distinct HSI technologies facilitates rapid and precise determination of the starch and alcohol contents in fermented grains. [ABSTRACT FROM AUTHOR]

BACKGROUND: Wheat is one of the key ingredients used to make Chinese liquor, and its saccharification power and protein content directly affect the quality of the liquor. In pursuit of a non‐destructive assessment of wheat components and the optimization of raw material proportions in liquor, this study introduces a precise predictive model that integrates hyperspectral imaging (HSI) with stacked ensemble learning (SEL). RESULTS: This study extracted hyperspectral information from 14 different varieties of wheat and employed various algorithms for preprocessing. It was observed that multiplicative scatter correction (MSC) emerged as the most effective spectral preprocessing method. The feature wavelengths were extracted from the preprocessed spectral data using three different feature extraction methods. Then, single models (support vector machine (SVM), backpropagation neural network (BPNN), random forest (RF), and gradient boosting tree (XGBoost)) and a SEL model were developed to compare the prediction accuracies of the SEL model and the single models based on the full‐band spectral data and the characteristic wavelengths. The findings indicate that the MSC–competitive adaptive reweighted sampling–SEL model demonstrated the highest prediction accuracy, with Rp2 (test set‐determined coefficient) values of 0.9308 and 0.9939 for predicting the saccharification power and protein content and root mean square error of the test set values of 0.0081 U and 0.0116 g kg−1, respectively. CONCLUSION: The predictive model established in this study, integrating HSI and SEL models, accurately detected wheat saccharification power and protein content. This validation underscores the practical potential of the SEL model and holds significant importance for non‐destructive component analysis of raw materials used in liquor. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Flower colour, as an important morphological marker, plays an essential role in improving the identification efficiency of the purity seed in hybrid production. However, the molecular mechanism of white‐flower trait has not been reported in pumpkin (Cucurbita moschata D.). In this study, we obtained a white‐flower mutant (wf) through the ethyl methane sulfonate (EMS) mutagenesis of inbred line N87 (yellow flower). F2 populations were then constructed by crossing wf mutant and N87 plant to fine map the genes controlling white‐flower trait in pumpkin. Phenotypic identification revealed that carotenoid content significantly decreased in the petals of wf mutants compared with N87 plants. Genetic analysis indicated that the white flower mutant trait was controlled by a single recessive gene, Cmowf. Using bulked segregant analysis and KASP phenotyping, Cmowf was mapped to a 762 kb region on chromosome 14 containing three annotated genes. Among them, a nonsynonymous single‐nucleotide polymorphisms mutation was identified only in CmoCh14G005820 gene, which encoded a DUF1997 family protein. Compared with CmoDUF1997 amino acid sequences between the wf mutants and N87 plants, the critical amino acid mutations (early termination of amino acids) occurred in wf mutants, so CmoCh14G005820 was predicted as a potential candidate for controlling the white‐flower trait. RNA‐sequencing analysis revealed that the expression of CmoCh14G005820 and most genes involved in carotenoid biosynthesis was significantly downregulated in wf mutants, whereas the expression of several genes responsible for carotenoid degradation was upregulated in wf mutants. This finding suggested that carotenoid metabolism may participate in the formation of flower colour in pumpkin. Overall, our results provided a theoretical basis for understanding the genetic mechanisms underlying white‐flower formation in pumpkin. [ABSTRACT FROM AUTHOR]

N1-methyladenosine (m1A) is a post-transcriptionally modified RNA molecule that plays a pivotal role in the regulation of various biological functions and activities. Especially in cancer cell invasion, proliferation and cell cycle regulation. Over recent years, there has been a burgeoning interest in investigating the m1A modification of RNA. Most studies have focused on the regulation of m1A in cancer enrichment areas and different regions. This review provides a comprehensive overview of the methodologies employed for the detection of m1A modification. Furthermore, this review delves into the key players in m1A modification, known as the "writers," "erasers," and "readers." m1A modification is modified by the m1A methyltransferases, or writers, such as TRMT6, TRMT61A, TRMT61B, TRMT10C, NML, and, removed by the demethylases, or erasers, including FTO and ALKBH1, ALKBH3. It is recognized by m1A-binding proteins YTHDF1, TYHDF2, TYHDF3, and TYHDC1, also known as "readers". Additionally, we explore the intricate relationship between m1A modification and its regulators and their implications for the development and progression of specific types of cancer, we discuss how m1A modification can potentially facilitate the discovery of novel approaches for cancer diagnosis, treatment, and prognosis. Our summary of m1A methylated adenosine modification detection methods and regulatory mechanisms in various cancers provides useful insights for cancer diagnosis, treatment, and prognosis. Cgy29QUiz7vJ-gsCtujnZr Video Abstract [ABSTRACT FROM AUTHOR]

N4-acetylcytidine (ac4C) is a highly conserved chemical modification widely found in eukaryotic and prokaryotic RNA, such as tRNA, rRNA, and mRNA. This modification is significantly associated with various human diseases, especially cancer, and its formation depends on the catalytic activity of N-acetyltransferase 10 (NAT10), the only known protein that produces ac4C. This review discusses the detection techniques and regulatory mechanisms of ac4C and summarizes ac4C correlation with tumor occurrence, development, prognosis, and drug therapy. It also comments on a new biomarker for early tumor diagnosis and prognosis prediction and a new target for tumor therapy. 1XB-Umo82HmUCTng4dZDNe Video Abstract [ABSTRACT FROM AUTHOR]

The protein and fat contents are important indicators for the quality evaluation of brewing sorghum, and a rapid and non-destructive testing method is urgently required to accurately detect them. Hyperspectral imaging (HSI) technology has been widely used in the assessment of the composition of various foods. In this study, different preprocessing methods were used to process the spectral data and determine the optimal preprocessing method. The characteristic spectra were extracted by three combination algorithms, namely, uninformative variable elimination-successive projections algorithm (UVE-SPA), competitive adaptive reweighted sampling-successive projections algorithm (CARS-SPA), and principal component analysis-successive projections algorithm (PCA-SPA). Four models (cascade forest (CF), the backpropagation-genetic algorithm (BP-GA), support vector regression (SVR), and partial least square regression (PLSR)) were established to predict the protein and fat contents based on the full spectrum, the feature spectrum, and fusion data (the integration of the feature spectrum with its corresponding texture features). A comparative analysis revealed that the BP-GA and CF models based on the visible light characteristic spectra extracted by PCA-SPA and UVE-SPA were the best models for predicting the protein and fat contents, respectively; they had respective RPD values of 5.1716 and 12.9724 and respective AB_RMSE values of 0.0916 and 0.0243 g/100 g. The overall results show that HSI combined with machine learning algorithms can rapidly and non-destructively predict the protein and fat contents of sorghum. [ABSTRACT FROM AUTHOR]

Scorodite (FeAsO4·2H2O) is an ideal material for the fixation of arsenic that has attracted considerable research interest in recent decades. However, the position of the H atom in the scorodite crystal structure, water molecular configuration, surface morphology, and chemical state of the surface atoms have not been reported. In this work, density functional theory (DFT) is used to optimize the scorodite crystal structure, and the atomic bonding is analyzed. At the same time, a surface model is constructed to calculate the configuration and electronic structure of the surface atoms for different coordination groups. The results show that the tetrahedral [AsO4] and octahedral [FeO4(2H2O)] groups in the scorodite crystal structure have good stability(geometry configuration), and the covalent bond strength between the As atom and the bridged oxygen atom (Ob) is greater than that between the Ob atom and the Fe atom. The water molecules in the crystal structure do not seriously deform and ionize. The configuration of the water molecules remains stable through electrostatic interactions (Ow–Fe) and hydrogen bonding (H–Ob). The Fe atoms on the surface of scorodite can coordinate with OH and H2O, while the As atoms can only form a stable coordination with OH. When an Fe atom on the surface coordinates with two H2O atoms, the Fe atom will shrink to the inside of the bulk. With the increase in the hydroxylation number of the Fe atom, the bonding strength between the Fe atom and the Ob atom decreases. Different surface configurations do not affect the stability(geometry configuration) of the [AsO4] structure. In addition, the surface water molecular layer has a very weak effect on the surface coordination configuration. By contrast, in the surface configuration of the (W + OH) structure, the change in the surface atomic layer spacing is the smallest. [ABSTRACT FROM AUTHOR]

BACKGROUND: The purity of sorghum varieties is an important indicator of the quality of raw materials used in the distillation of liquors. Different varieties of sorghum may be mixed during the acquisition process, which will affect the flavor and quality of liquor. To facilitate the rapid identification of sorghum varieties, this study proposes a sorghum variety identification model using hyperspectral imaging (HSI) technology combined with convolutional neural network (AlexNet). RESULTS: First, the watershed algorithm, which was modified with the extended‐maxim transform, was used to segment the hyperspectral images of a single sorghum grain. The isolated forest algorithm was used to eliminate abnormal spectral data from the complete spectral data. Secondly, the AlexNet model of sorghum variety identification was established based on the two‐dimensional gray image data of sorghum grain in group 1. The effects of different preprocessing methods and different convolution kernel sizes on the performance of the AlexNet model were discussed. The eigenvalues of the last layer of the AlexNet model were visualized using the t‐distributed random neighborhood embedding method, which is used to evaluate the separability of features extracted by the AlexNet model. The performance differences between the optimal AlexNet model and traditional machine learning models for sorghum variety identification were compared. Finally, the varieties of sorghum grains in groups 2 and 3 were identified based on the optimal AlexNet model, and the average accuracy values of the test set reached 95.62% and 95.91% respectively. CONCLUSION: The results in this study demonstrated that HSI combined with the AlexNet model could provide a feasible technical approach for the detection of sorghum varieties. © 2022 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

The analysis of the surface chemical behavior of pyrite is highly crucial in the fields of environmental conservation, metal extraction, and flotation separation. In this paper, the mechanism of atomic reconstruction on the pyrite surface and the adsorption behavior of O2 on a reconstructed surface are calculated by density functional theory (DFT). Different reconstruction surfaces were constructed by deleting S and Fe atoms on the (100) surface of pyrite. In addition, the geometric configuration, formation energy, binding energy, cohesion energy, and surface electronic properties of the reconstruction surface were calculated. The adsorption energies and geometric configurations of O2 on different reconstructed surfaces were also determined. The results show that under Fe-poor conditions, the charge of Fe atoms increases, and S atoms form Sn on the reconstructed surface. The binding energy between the Sn and the substrate (ideal surface) is lower, which is similar to the Sn adsorption on the substrate surface with the Fe atom as the site. Sn has high cohesive energy and is resistant to being attacked by oxidants, which leads to structural collapse, and a low affinity for O2. Under S-poor conditions, the –[Fe–S]n– plane structure formed on the reconstructed surface. The –[Fe–S]n– structure stably bonds to the substrate by an Fe–S bond, and exhibits strong binding energy. However, the –[Fe–S]n– structure has low cohesive energy and exhibits thermodynamic instability. In contrast, O2 shows a strong affinity for the –[Fe–S]n– structure, indicating that the deficiency of the S atom promotes the surface oxidation reaction. The mechanism of atomic reconstruction on the surface of pyrite is of utmost importance for understanding its surface chemical behavior. [ABSTRACT FROM AUTHOR]

It is widely recognized that combining alginate with graphene oxide (GO) is an effective method in improving the properties of alginate fiber. However, how the lateral size of GO influences the properties of the composite fiber is still unclear. In this work, GO was separated into four kinds of different lateral sizes with the assistance of centrifugation and high-power ultrasound. The tensile strength of calcium alginate/graphene oxide (CaAlg/GO) composite fiber increased with the lateral size of GO. Surprisingly, the combination of large and small GO performed the superior reinforcement effect. The tensile strength and Young's modulus increased from 407.66 MPa and 13.87 GPa to 556.97 MPa and 20.57 GPa, respectively. In addition, the water absorption ability of CaAlg/GO composite fiber reduced with the decreasing of the lateral size of GO. With significantly improved mechanical properties and fine biocompatibility, the CaAlg/GO composite fibers may have potential applications in the biotechnological, biomedical, and tissue engineering areas. [ABSTRACT FROM AUTHOR]

Polyacrylonitrile (PAN) fiber is soft and comfortable, but its poor strength compared to other synthetic fibers has limited it wide range of applications. This study effectively improved the strength of PAN fibers by adding graphene oxide (GO) and polyvinyl alcohol (PVA) during PAN spinning. The composite fibers were prepared via gel spinning and subsequent hot drawing process. The results show that the PVA molecular chains embedded into the PAN molecular chain significantly improved the mechanical properties of the hybrid fiber. At the same time, the defect reduced the UV resistance and thermal stability of the hybrid fibers only when the PVA molecular was introduced in the PAN. Surprisingly, after the recomposition of GO in the above mixed polymer system, the interaction between the GO and matrix not only improved the mechanical properties of the fiber, but also enhanced the UV resistance and thermal stability. In addition, when the amount of GO was 0.3 wt%, the crystallinity of the GO/PVA/PAN composite fiber reached the maximum and the tensile strength was the highest. This strategic approach suggests an effective method to prepare graphene-based ternary composites fibers with high strength and novel functional characteristics. [ABSTRACT FROM AUTHOR]

The moisture content and distribution of Daqu significantly influences the quality of Daqu products. This work presents the visualization of the moisture content in Daqu using a combination of spectral and spatial information from hyperspectral imaging. The least squares support vector machine (LS-SVM) and partial least squares regression (PLSR) methods were adopted to establish the predictive models based on the full wavelengths and the 29 feature wavelengths combined with color features, respectively. The best prediction model was PLSR ( R p 2 = 0.9823 , RMSEP = 0.0109) based on feature wavelengths. The results showed that the combination of spectral and spatial information of hyperspectral imaging can accurately predict the moisture content in Daqu during different fermentation processes, and the visualization of the distribution map of moisture content in Daqu provided a more convenient and understandable assessment of moisture content. This work presents a novel, rapid, and nondestructive approach for moisture content detection in Daqu, and provides theoretical support and basis for intelligent adjustment of temperature, humidity and other environmental parameters of Daqu fermentation. [ABSTRACT FROM AUTHOR]

Objective: To study the risk factors and prediction models of multidrug resistance in patients with tuberculosis and diabetes and those with a history of tuberculosis treatment.Methods: A total of 256 tuberculosis patients with diabetes who were registered in Luoyang city, Henan Province, from January 2018 to December 2021. Logistic regression analysis was performed to analyse the risk factors for multidrug resistance. ROC curves were used to analyse the predictive model for multidrug resistance.Results: Age < 65 years old, HbA1c, and a history of tuberculosis treatment were independent risk factors for multidrug resistance in patients with tuberculosis and diabetes (P < 0.05). The area under the ROC curve of predictive model for MDR was 0.878 (95% CI (0.824, 0.932)). Age < 65 years old and HbA1c were independent risk factors for MDR in patients with TB and diabetes with a history of TB treatment. The area under the ROC curve of predictive model for MDR was 0.920 [95% CI (0.831, 0.999)].Conclusion: The predictive model had certain prediction value for the risk of multidrug resistance in patients with tuberculosis and diabetes. [ABSTRACT FROM AUTHOR]

Purpose: Beta-lactamase-producing Klebsiella pneumoniae is common in the clinic, but research associated with the co-existence of KPC-2, LAP-2, and CTX-M-65 in K. pneumoniae is still rare. In this study, the phenotypic and genetic characteristics of a multidrug-resistant K. pneumoniae strain SJ25 co-harboring blaKPC-2, blaLAP-2, and blaCTX-M-65 with rare ST1469 were investigated. Methods and Results: Antimicrobial susceptibility testing revealed that strain SJ25 was resistant to various common antibiotics, except ciprofloxacin, fosfomycin, colistin, and tigecycline. Whole-genome analysis revealed that strain SJ25 carries a variety of antimicrobial resistance genes and virulence determinants. Plasmid analysis confirmed that the blaKPC-2 and blaCTX-M-65 genes were located on an ~136 kb transferrable IncFII/IncR plasmid and that blaLAP-2 was located on an untypeable plasmid. Conclusion: Our findings emphasized the need for continuous surveillance of β-lactamase-bearing K. pneumoniae in the clinic to control potential dissemination and outbreak. [ABSTRACT FROM AUTHOR]

Sorghum is a type of brewing material. The starch content of different kinds of mixed sorghum affect the quality and yield of liquor. Therefore, an accurate and efficient detection of its starch content is of great significance to obtain high‐quality and high‐yield of liquor. Based on the data of single visible light (Vis), near‐infrared (NIR), and Vis and NIR fusion, this study develops a genetic algorithm optimization BP neural network (GA‐BPNN) model and a particle swarm optimization support vector machine model. It is deduced that the model based on the data from the Vis and NIR fusion has the highest performance in predicting the starch content of mixed sorghum. For the prediction of amylose, the GA‐BPNN model developed after using the Pearson correlation coefficient to select the characteristic wavelength for fusion, has the highest performance (RMSEP =.0298 and Rp2=.9948). For the prediction of amylopectin, the GA‐BPNN model developed after fusion of spectral features extracted by principal component analysis, has the highest performance (RMSEP =.0213 and Rp2=.9985). In conclusion, the hyperspectral imaging combined with data fusion can rapidly and accurately detect the starch content of mixed sorghum. Practical Applications: As the single raw material of Maotai‐flavor liquor and the main raw material of Luzhou‐flavor liquor, the amylopectin content of sorghum directly affects the quality of liquor. Its amylose content also affects the yield of liquor. Because the different varieties of sorghum have different amylose and amylopectin content, liquor manufacturers often use several mixed varieties of sorghum as a brewing material. In order to ensure the quality and yield of liquor, it is particularly crucial to detect the amylose and amylopectin content variables of blended sorghum. The traditional sorghum starch content determination methods, such as the chemical detection methods and near infrared spectroscopy, have the disadvantages of destructiveness, low efficiency, and low detection accuracy. In the process of liquor brewing, the traditional detection methods cannot guide the timely adjustment of brewing process parameters. The hyperspectral imaging technology is widely used in food material detection, due to its fast and nondestructive advantages. The data fusion technology can fuse data from different sources of the same object to be detected, in order to obtain more comprehensive data for the development of accurate prediction models. This study uses the hyperspectral imaging combined with data fusion in order to quickly and accurately predicts the starch content (amylose, amylopectin) of mixed sorghum, which has a guiding significance for the timely adjustment of process parameters in the brewing process of liquor. In addition, it provides an accurate method for the component detection of other grains. [ABSTRACT FROM AUTHOR]

Pumpkin is a popular vegetable crop and exhibits a broad diversity in fruit shape and size. Fruit-related traits are the decisive factors determining consumer acceptance and market value of pumpkin cultivar. As a result, deciphering the genetic basis of fruit-related traits is of great importance for pumpkin breeding. To address this problem, a F2 population was generated by two Cucurbita moschata inbred lines with contrasting fruit shapes, and genotyping by sequencing approach was used to construct a genetic map and localize the QTLs underlying the fruit-related traits in this study. The results showed that a high-quality genetic map was constructed for pumpkin, which comprised of 2413 bins and spanned a total length of 2252.10 cM with an average genetic distance of 0.94 cM. Thirty significant QTLs with moderate or small effects were identified for seven fruit-related traits, including fruit length, fruit diameter, fruit shape index, fruit weight, fruit flesh thickness, seed cavity size, and total soluble solids content. Co-locations were observed between the QTLs underlying different traits, demonstrating that pleiotropic effect plays an important role in genetic control of fruit-related traits. The identified QTLs provide valuable information for further fine mapping of the related genes and pumpkin breeding programs with the aim of improving fruit quality. [ABSTRACT FROM AUTHOR]

Plant height is an important indicator in the ideal plant model and contributes to optimizing yield and lodging resistance. The emergence of a dwarfing phenotype provides an opportunity for plant height improvement. In a previous study, we identified a dwarf mutant Si1 in pumpkin (Cucurbita moschata D.) obtained by ethyl methane sulfonate (EMS) mutagenesis of the inbred line N87. Phenotype identification for Si1 revealed a decrease in cell size and shorter internodes than those of wild type. Genetic analysis revealed that the dwarf mutant trait was controlled by a single recessive gene, CmaSI1. By bulked segregant analysis (BSA) and subsequent fine mapping, we mapped the CmaSI1 locus to a 463 kb region on chromosome 8 that contained 28 annotated genes in the F2 population. Only one nonsynonymous single nucleotide polymorphism (SNP) in CmoCh08G006170 was obtained according to whole-genome resequencing of the two parents. CmoCh08G006170, a homolog of Arabidopsis gibberellin 3-beta hydroxylase (GA3ox), is a key enzyme in the regulation of bioactive gibberellins (GAs). RNA-seq analysis and qRT-PCR showed that the expression level of CmoCh08G006170 in stems of Si1 was changed compared with that of wild type. The dwarf phenotype could be restored by exogenous GA3 treatment, suggesting that Si1 is a GA-deficient mutant. The above results demonstrated that CmoCh08G006170 may be the candidate gene controlling the dwarf phenotype. This study provides an important theoretical basis for the genetic regulation of vine length and crop breeding in pumpkin. [ABSTRACT FROM AUTHOR]

Mobile colistin resistance (mcr) genes represent an emerging threat to public health. Reports on the prevalence, antimicrobial profiles, and clonality of MCR-9-producing Enterobacter cloacae complex (ECC) isolates on a national scale in China are limited. We screened 3,373 samples from humans, animals, and the environment and identified eleven MCR-9-positive ECC isolates. We further investigated their susceptibility, epidemiology, plasmid profiles, genetic features, and virulence potential. Ten strains were isolated from severe bloodstream infection cases, especially three of them were recovered from neonatal sepsis. Enterobacter hormaechei was the most predominant species among the MCR-9-producing ECC population. Moreover, the co-existence of MCR-9, CTX-M, and SHV-12 encoding genes in MCR-9-positive isolates was globally observed. Notably, mcr-9 was mainly carried by IncHI2 plasmids, and we found a novel ~187 kb IncFII plasmid harboring mcr-9 , with low similarity with known plasmids. In summary, our study presented genomic insights into genetic characteristics of MCR-9-producing ECC isolates retrieved from human, animal, and environment samples with one health perspective. This study is the first to reveal NDM-1- and MCR-9-co-producing ECC from neonatal sepsis in China. Our data highlights the risk for the hidden spread of the mcr-9 colistin resistance gene. [ABSTRACT FROM AUTHOR]

In this study, micron-sized two-dimensional graphene oxide (GO) was combined with chitosan fibres, followed by immersion into dopamine lye (DA lye) through a solution complex to increase the tensile strength of fibre from 252.22 to 411.62 MPa and Young's modulus from 18.95 to 25.67 GPa. GO sheets endue an effective stress transmission mechanism to chitosan fibre when such composite fibres are subjected to external forces. Self-polymerised poly-dopamine (PDA) formed a coating on the chitosan fibre surface, crosslinking the chitosan molecular, and thereby effectively offsetting the influence of intramolecular hydrogen bonds. Furthermore, the composite fibre exhibited an excellent antibacterial rate of > 99.9% and negligible toxicity to human fibroblasts, indicating its superior biocompatibility. The multiple van der Waals forces enhanced interfacial interactions between the GO surface and chitosan matrix, and the crosslinking and adhesion effect of the PDA coating to the chitosan fibre considerably improved the mechanical properties of the composite fibre. The results of this study can provide a guideline for bulk preparation and replication for synthesising high mechanical performance and multiple functional GO/natural polymer composite fibres, which can be used in many applications, such as biomedical and medical materials. [ABSTRACT FROM AUTHOR]

Cereal crops play an important role in preventing chronic diseases and regulating human functions due to their rich phytochemicals. However, an increasing number of cases of cereal‐crop adulteration are occurring, affecting the nutrition of food and threatening food safety. Therefore, this study used hyperspectral imaging (HSI) and a back‐propagation neural network (BPNN) to establish the variety identification model of different grain shapes, colors, and sizes. This model can conduct a quantitative and qualitative analysis of samples rapidly and nondestructively, because HSI can collect spectral information and spatial information of samples. Meanwhile, the Watershed algorithm was used to identify cereal varieties by particles, and the model identification performance was verified by the unlabeled test sets. The results show that the data extraction success rate of the new watershed algorithm reached 98%, and the comprehensive identification accuracy of the model reached 90%. In addition, the cereal in the training set can be changed to identify other cereal crops, thereby providing a method of rapid and nondestructive adulteration detection of cereals. Practical Applications: Cereal crops play an important role in preventing chronic diseases and regulating human functions due to their rich phytochemicals. However, an increasing number of cases of cereal‐crop adulteration are occurring, affecting the nutrition of food and threatening food safety. Therefore, this study used hyperspectral imaging (HSI) and a back‐propagation neural network (BPNN) to establish the variety identification model of different grain shapes, colors, and sizes. This model can conduct a quantitative and qualitative analysis of samples rapidly and nondestructively, because HSI can collect spectral information and spatial information of samples at the same time. The spectral information was used for qualitative analysis, while spatial information was used for quantitative analysis, so this model can realize the rapid and nondestructive detection of different varieties of cereals. And we can also change the training‐set data to realize the variety identification of other varieties of crops, which provides guidance for the method detecting the adulteration of cereal crops. [ABSTRACT FROM AUTHOR]

N -Acyl- N , O -acetals are key components in a variety of bioactive natural products. Furthermore, they are synthetic equivalents of unstable N -acylimines and building blocks in organic synthesis. Tremendous efforts have been made in the synthesis of such acetals, these methods can be broadly classified into two categories: electrochemical oxidation and chemical methods. Herein, we will summarize progress in the preparation of these subunits, which may aid the development of new synthetic methods for N -acyl- N , O -acetals. 1 Introduction 2 Synthetic Methods for Preparing N -Acyl- N , O -acetals 2.1 Electrochemical Oxidation 2.2 Chemical Methods 2.3 Other Methods 3 Summary and Outlook [ABSTRACT FROM AUTHOR]

The total acid content of Daqu during fermentation directly influences the quality of the Daqu. Hyperspectral imaging (HSI) was used to rapidly and accurately detect the total acid content of Daqu. The performances of two spectral ranges obtained by two hyperspectral cameras for Daqu total acid content were compared. Different pretreatment methods were used to build the partial least squares regression (PLSR) model, and the optimal pretreatment for the corresponding spectra was determined. A combination of principal component analysis (PCA) and successive projection algorithm (SPA) was used to select the feature wavelengths. The PCA algorithm optimized by SPA was more accurate than the PCA algorithm alone when extracting the feature wavelengths. PLSR, backpropagation neural network (BP), and the backpropagation‐genetic algorithm (BP‐GA) model were developed to predict the total acid content of the Daqu samples by using the full wavelengths and feature wavelengths, respectively. The predictive performance of each model was compared and analyzed. The optimal model was the MSC + PCA‐SPA+BP‐GA model (Rc2 = 0.8832, RMSEC = 0.1163, Rp2 = 0.9724, RMSEP = 0.0593, RPD = 4.2860, AB_RMSE = 0.0570). In addition, the distribution of total acid content within the region of interest (ROI) of Daqu samples was visualized at different fermentation stages using the optimized model. These results show that HSI technology can rapidly and precisely detect the total acid content of Daqu and visualize the content distribution, which provides important technical support for upgrading and transforming the liquor. Practical Applications: Daqu is the saccharifying agent, leavening agent, and aroma‐generating agent of liquor brewing. During the fermentation process, the total acid content is an important indicator for the quality evaluation of Daqu. Therefore, it is highly significant to detect the total acid content in Daqu quickly and accurately. The HSI technique is widely used to detect the contents of various substances in food. In this study, the HSI technique combining the PCA‐SPA and BP‐GA algorithms was established to detect the total acid content of Daqu, and a satisfactory result was obtained, showing that HSI technology combined with an optimized algorithm could be used to realize rapid and accurate detection of the total acid content of Daqu. In addition, the predictive model proposed in this study is not only applicable for detecting other food substances but also this method has great potential for real‐time indicators detection in winery for future work. [ABSTRACT FROM AUTHOR]

To evaluate the quality of Daqu, the change of moisture content during the fermentation process is an important indicator. To improve the accuracy of measuring the moisture content, we studied a measuring method that used a near‐infrared hyperspectral imaging technique. In the process of using multigranularity cascade forest algorithm to do deep learning on the detection task, two improvements were made to improve detection accuracy. One was to establish a multigranularity cascade forest model with various scanning window combinations to solve the problem of distribution offset in the prediction results. The other was to do continuum removal processing to obtain enhanced spectral data from the sample spectral data. The results showed that the multigranularity cascade forest was markedly better than a support vector machine and a backpropagation neural network. The coefficient of determination of the prediction set (R2) and root mean square error of the Prediction set reached 0.9977 and 0.0021, respectively. The study results indicated that the hyperspectral imaging technique could achieve highly accurate detection and distribution visualization of the moisture content of Daqu during the fermentation process. Practical applications: Daqu, a flavoring agent and fermentation starter, plays a vital role in the solid‐state liquor brewing process. During the fermentation process, moisture content is an important indicator for quality evaluation of Daqu. Therefore, it is highly important to detect the moisture content in Daqu quickly and accurately. The hyperspectral imaging technique, as an emerging detection technology, has advantages that traditional detection methods do not have, so that the disadvantages of traditional detection can be overcome. In our study, the hyperspectral imaging technique could achieve high‐precision detection of the moisture content of Daqu during the fermentation process, indicating that hyperspectral technology could be used to detect Daqu moisture content. Moreover, this method has great potential for real‐time indicators detection in winery for future work. [ABSTRACT FROM AUTHOR]

Daqu, a Chinese liquor fermentation starter, contains all kinds of microorganisms and enzymes for Chinese liquor fermentation. The moisture content of Daqu significantly influence on the reproduction of microorganisms in Daqu. This work presents for the first time that determination of moisture content of Daqu with hyperspectral imaging. The characteristic spectrum of water is extracted based on comparative experiments with varying moisture content. The molds based on the full bands and feature bands were established by the support vector regression (SVR) method, which is used to predict moisture content of Daqu during fermentation process. The performance of the model based on the feature bands (R2 = 0.9870, root mean square error (RMSE) = 0.0091) is comparable to the full bands and the dimensions of the spectral information were significantly reduced. This work presents a novel, rapid and nondestructive approach for detecting the moisture content in Daqu and lays a foundation for the application of hyperspectral imaging. [ABSTRACT FROM AUTHOR]

The dissemination of Klebsiella pneumoniae carbapenemases (KPCs) among Gram-negative bacteria is an important threat to global health. However, KPC-producing bacteria from environmental samples are rarely reported. This study aimed to elucidate the underlying resistance mechanisms of three carbapenem-resistant Aeromonas taiwanensis isolates recovered from river sediment samples. Pulsed-field gel electrophoresis (PFGE) and whole genome sequencing (WGS) analysis indicated a close evolutionary relationship among A. taiwanensis isolates. S1-PFGE, Southern blot and conjugation assays confirmed the presence of bla KPC–2 and qnrS2 genes on a non-conjugative plasmid in these isolates. Plasmid analysis further showed that pKPC-1713 is an IncP-6 plasmid with a length of 53,205 bp, which can be transformed into DH5α strain and mediated carbapenems and quinolones resistance. The plasmid backbone of p1713-KPC demonstrated 99% sequence identity to that of IncP-6-type plasmid pKPC-cd17 from Aeromonas spp. and IncP-6-type plasmid: 1 from Citrobacter freundii at 74% coverage. A 14,808 bp insertion sequence was observed between merT gene and hypothetical protein in p1713-KPC, which include the quinolone resistance qnrS2 gene. Emergence of plasmid-borned bla KPC and qnrS2 genes from A. taiwanensis isolates highlights their possible dissemination into the environment. Therefore, potential detection of such plasmids from clinical isolates should be closely monitored. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Chemistry is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Hydroxyl radicals (ṖOH) generated from a UV/O3 solution reaction is used to efficiently etch graphene oxide nanosheets under moderate conditions. Reduced holey graphene oxide is directly used as a supercapacitor electrode material and exhibits high specific capacitance (224 F g−1 at a current density of 1 A g−1) and high volumetric capacitance (up to 206 F cm−3). [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Chemistry is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: A novel avian-origin influenza A (H7N9) virus emerged and spread among humans in Eastern China in 2013. Prophylactic treatment with antibiotics and probiotics for secondary infection is as important as antiviral treatment. This study aims to assess the ability of probiotic treatment to restore internal homeostasis under antibiotic pressure and to reduce/ameliorate the risk of secondary infections resulting from infection with the H7N9 virus. Methods: This is a retrospective study in archival samples. Between April 1 and May 10, 2013, 113 stool, sputum, and blood specimens were collected and analyzed by denaturing gradient gel electrophoresis (DGGE) to determine the composition of the patient microbiomes. Microbial diversity was calculated using Gel-Pro analyzer and Past software. Cluster analysis of DGGE pattern profiles was employed to create a phylogenetic tree for each patient, and multidimensional scaling (MDS) and principal component analysis (PCA) were performed to visualize relationships between individual lanes. Results: Five patients had secondary infections, including Klebsiella pneumonia, Acinetobacter baumanii and Candida albicans infection. The DGGE profiles of fecal samples obtained at different time points from the same individual were clearly different, particularly for patients with secondary infections. Shannon’s diversity index and evenness index were lower in all infected groups compared to the control group. After B. subtilis and E. faecium or C. butyricum administration, the fecal bacterial profiles of patients who had not been treated with antibiotics displayed a trend of increasing diversity and evenness. C. butyricum failed to reduce/ameliorate secondary infection in H7N9-infected patients, but administration of B. subtilis and E. faecium appeared to reduce/ameliorate secondary infection in one patient. Conclusion: H7N9 infection might decrease intestinal microbial diversity and species richness in humans. C. butyricum failed to reduce/ameliorate secondary infection in H7N9-infected patients. B. subtilis and E. faecium may also play a role in reducing/ameliorating secondary infection in these patients. [ABSTRACT FROM AUTHOR]

Staphylococcus cohnii subsp. cohnii belongs to the family Staphylococcaceae in the order Bacillales, class Bacilli and phylum Firmicutes. The increasing relevance of S. cohnii to human health prompted us to determine the genomic sequence of Staphylococcus cohnii subsp. cohnii strain hu-01, a multidrug-resistant isolate from a hospital in China. Here we describe the features of S. cohnii subsp. cohnii strain hu-01, together with the genome sequence and its annotation. This is the first genome sequence of the species Staphylococcus cohnii. [ABSTRACT FROM AUTHOR]

Aiming at solving the existing issues in purity identification of Cucurbita moschata hybrids by SSR, such as complex operation and difficult application in production practice, in this study, a simple SSR-based method was established for purity identification of Cucurbita moschata hybrids. By using the established simple method, without grinding, freezing, centrifugation and drying, the genomic DNA extraction process is shorter than 3 min. compared with the conventional method, PCR detection system and silver staining in polyacrylamide gel electrophoresis of the established method are more time-saving and cost-saving. The whole detection process is shorter than 4 h, and 480 samples can be detected with this method by one person in one day. In addition, the detection result exhibits a coincidence rate of 99% with field identification. The simple SSR-based method established in this study can provide basis for large-scale rapid purity identification of Cucurbita moschata hybrids. [ABSTRACT FROM AUTHOR]

Liver cirrhosis occurs as a consequence of many chronic liver diseases that are prevalent worldwide. Here we characterize the gut microbiome in liver cirrhosis by comparing 98 patients and 83 healthy control individuals. We build a reference gene set for the cohort containing 2.69 million genes, 36.1% of which are novel. Quantitative metagenomics reveals 75,245 genes that differ in abundance between the patients and healthy individuals (false discovery rate < 0.0001) and can be grouped into 66 clusters representing cognate bacterial species; 28 are enriched in patients and 38 in control individuals. Most (54%) of the patient-enriched, taxonomically assigned species are of buccal origin, suggesting an invasion of the gut from the mouth in liver cirrhosis. Biomarkers specific to liver cirrhosis at gene and function levels are revealed by a comparison with those for type 2 diabetes and inflammatory bowel disease. On the basis of only 15 biomarkers, a highly accurate patient discrimination index is created and validated on an independent cohort. Thus microbiota-targeted biomarkers may be a powerful tool for diagnosis of different diseases. [ABSTRACT FROM AUTHOR]

Background: Chrysomya megacephala (Fabricius), a prevalent necrophagous blowfly that is easily mass reared, is noted for being a mechanical vector of pathogenic microorganisms, a pollinator of numerous crops, and a resource insect in forensic investigation in the postmortem interval. In the present study, in order to comprehensively understand the physiological and biochemical functions of C. megacephala, we performed RNA-sequencing and digital gene expression (DGE) profiling using Solexa/Illumina sequencing technology. Methodology/Principal Findings: A total of 39,098,662 clean reads were assembled into 27,588 unigenes with a mean length of 768 nt. All unigenes were searched against the Nt database, Nr database, Swiss-Prot, Cluster of Orthologous Groups (COG) and Kyoto Encyclopedia of Genes and Genome (KEGG) with the BLASTn or BLASTx algorithm (E-value<0.00001) for annotations. In total, 7,081 unigenes and 14,099 unigenes were functionally classified into 25 COG categories and 240 KEGG pathways, respectively. Furthermore, 20,216 unigenes were grouped into 48 sub-categories belonging to 3 main Gene Ontology (GO) categories (ontologies). Using the transcriptome data as references, we analyzed the differential gene expressions between a soybean oil-fed group (SOF) and a lard oil-fed group (LOF), compared to the negative control group (NC), using the DGE approach. We finally obtained 1,566 differentially expressed genes in SOF/NC, and 1,099 genes in LOF/NC. For further analysis, GO and KEGG functional enrichment were performed on all differentially expressed genes, and a group of differentially expressed candidate genes related to lipometabolism were identified. Conclusions/Significance: This study provides a global survey of C. megacephala and provides the basis for further research on the functional genomics of this insect. [ABSTRACT FROM AUTHOR]

By adding different amount of zinc into the artificial medium of the insect larvae, the zinc-induced apoptosis of the larvae haemocytes of the herbivorous insect Spodoptera litura Fabricius was investigated with flow cytometer. The results showed that the increase of zinc dose in the artificial feed led to the accumulations of zinc in the larval hemolymph and fat body, and more zinc was accumulated in fat body than in hemolymph. The apoptosis of hemocytes was significantly induced at high zinc concentration (1000 mg·kg-1) in the insect diet, and the apoptosis rate was 63.63%, which was remarkably higher than that at control and lower concentrations (50–500 mg·kg-1). This suggests that the high dose of zinc in the artificial diet of S. litura larvae could induce the apoptosis of the larval hemocytes of S. litura. [ABSTRACT FROM AUTHOR]

Reduced graphene oxide/SiO2 (RGO/SiO2) serving as a novel spherical support for Ziegler-Natta (Z-N) catalyst is reported. The surface and interior of the support has a porous architecture formed by RGO/SiO2 sandwich structure. The sandwich structure is like a brick wall coated with a graphene layer of concreted as skeleton which could withstand external pressures and endow the structure with higher support stabilities. After loading the Z-N catalyst, the active components anchor on the surface and internal pores of the supports. When the ethylene molecules meet the active centers, the molecular chains grow from the surface and internal catalytic sites in a regular and well-organized way. And the process of the nascent molecular chains filled in the sandwich structure polymerization could ensure the graphene disperse uniformly in the polymer matrix. Compared with traditional methods, the porous spherical graphene support of this strategy has far more advantages and could maintain an intrinsic graphene performance in the nanocomposites. [ABSTRACT FROM AUTHOR]

Bacterial translocation (BT) is thought to play an important role in the development of liver cirrhosis, but the mechanisms have not been fully explored. This study aims to investigate the distribution of Treg (CD3+CD4+CD25+Foxp3+), Th17 (CD3+CD4+IL-17+), and Th1 (CD3+CD4+IFN-γ+) cells in the intestinal lamina propria, liver and blood and to explore their relationships with BT. Cirrhotic rats with ascites were induced by CCl4. We found that there were lower levels of total protein and albumin, lower albumin/globulin ratio, lower body weight and higher spleen weight and ascites volume in cirrhotic rats with than without BT. We found that BT may cause increase of Treg cells in the proximal small intestine and decrease of Th17 cells in the whole intestine and blood in cirrhotic rats. It may also aggravate the CCl4-induced decrease in Th1 cells in the whole intestine, liver, caecum, and blood and the CCl4-induced increase in Th17 cells in the liver and Tregs in the distal small intestine, colon, and liver. Our data suggest that BT may aggravate liver injury and decrease liver function via an interaction with CD4+ T Cells. The results of this study may be helpful for the development of new treatments for liver cirrhosis. [ABSTRACT FROM AUTHOR]