General Model for Predicting Response of Gas-Sensitive Materials to Target Gas Based on Machine Learning.

Gas sensors play a crucial role in various industries and applications. In recent years, there has been an increasing demand for gas sensors in society. However, the current method for screening gas-sensitive materials is time-, energy-, and cost-consuming. Consequently, an imperative exists to enhance the screening efficiency. In this study, we proposed a collaborative screening strategy through integration of density functional theory and machine learning. Taking zinc oxide (ZnO) as an example, the responsiveness of ZnO to the target gas was determined quickly on the basis of the changes in the electronic state and structure before and after gas adsorption. In this work, the adsorption energy and electronic and structural characteristics of ZnO after adsorbing 24 kinds of gases were calculated. These computed features served as the basis for training a machine learning model. Subsequently, various machine learning and evaluation algorithms were utilized to train the fast screening model. The importance of feature values was evaluated by the AdaBoost, Random Forest, and Extra Trees models. Specifically, charge transfer was assigned importance values of 0.160, 0.127, and 0.122, respectively, ranking as the highest among the 11 features. Following closely was the d-band center, which was presumed to exert influence on electrical conductivity and, consequently, adsorption properties. With 5-fold cross-validation using the Extra Tree accuracy, the 24-sample data set achieved an accuracy of 88%. The 72-sample data set achieved an accuracy of 78% using multilayer perceptron after 5-fold cross-validation, with both data sets exhibiting low standard deviations. This verified the accuracy and reliability of the strategy, showcasing its potential for rapidly screening a material's responsiveness to the target gas.

Construction of a high-resolution genetic map and identification of single nucleotide polymorphism markers relevant to flower stalk height in onion.

Introduction: Onion (Allium cepa L., 2n=16) is an economically and nutritionally important vegetable crop worldwide. Construction of a high-resolution genetic map and map-based gene mining in onion have lagged behind other vegetable crops such as tomato and pepper. Methods: In this study, we constructed a high-resolution genetic map of onion using 321 F2 individuals from a cross between two double haploid lines DH-1×DH-17 and employing specific length amplified fragment (SLAF)-seq technology. The genetic map containing 10,584 polymorphic SLAFs with 21,250 single nucleotide polymorphism (SNP) markers and 8 linkage groups was developed for onion, which spanned 928.32 cM, with an average distance of 0.09 cM between adjacent markers. Results: Using this map, we carried out QTL mapping of Ms locus related to the male-fertile trait and reproduced previous mapping results, which proved that this map was of good quality. Then, four QTLs (located on LG2, LG5, and LG8) were detected for flower stalk height, explaining 26.60% of the phenotypic variance. Among them, we proposed that 20 SLAF markers (in three QTLs) of flower stalk height trait were effective favorable allelic variant markers associated with heterosis. Discussion: Overall, the genetic map was structured using SLAF-seq based on DH lines, and it is the highest-quality and highest-resolution linkage map of onion to date. It lays a foundation for the fine mapping and candidate gene identification of flower stalk height, and provides new insights into the developmental genetic mechanisms in onion breeding.

Strong additive and synergistic effects of polyoxyethylene nonionic surfactant-assisted protein MALDI imaging mass spectrometry.

Protein MALDI imaging mass spectrometry (MALDI-IMS) holds a great promise to acquire spatial distribution information of proteins on biological tissue, but it suffers from the small number of proteins detected by direct MALDI-IMS detection. Ionic surfactants have been extensively used for protein extraction to improve the number of proteins detected in tissue samples by LC-MS analysis, but seldom by direct MALDI-IMS detection. Nonionic surfactants are milder than ionic surfactants and protein native structures are remained after extraction, which favors the spatial resolution of direct MALDI-IMS. However, nonionic surfactants are less effective than ionic surfactants. In this report, we utilized polyoxyethylene nonionic surfactants (PNS) to pre-incubate the tissue section, followed by the on-tissue trypsin digestion and then direct MALDI detection of in-situ formed peptides. For the first time, we observed that the additive effect of PNS and the synergistic effect of the mixed PNS in improving the number of peptides detected. Specifically, the peptides detected were 73.0-90.7% distinct when the different PNS (Tween 80 or Triton X-100 alone or their mixture) was used. Taking advantage of this additive effect, the 96 proteins including 12 transmembrane proteins were detected, corresponding to a ~10-fold improvement compared to MALDI-IMS without surfactant. When the mixed surfactants were used to replace Tween 80 and Triton X-100 alone, the optimized surfactant concentration decreased 20-100-fold and the number of peptides detected with m/z > 2500 Da was improved 15-fold. The additive and synergistic effects of PNS suggested that the interaction mode between each PNS and proteins is highly variable. Benefiting from the strong additive effect and diversity of PNS, further improvement of the number of proteins detected by MALDI-IMS is clearly feasible.

Complete chloroplast genome sequences of four Allium species: comparative and phylogenetic analyses.

The genus Allium is one of the largest monocotyledonous genera, containing over 850 species, and most of these species are found in temperate climates of the Northern Hemisphere. Furthermore, as a large number of new Allium species continue to be identified, phylogenetic classification based on morphological characteristics and a few genetic markers will gradually exhibit extremely low discriminatory power. In this study, we present the use of complete chloroplast genome sequences in genome-scale phylogenetic studies of Allium. We sequenced and assembled four Allium chloroplast genomes and retrieved five published chloroplast genomes from GenBank. All nine chloroplast genomes were used for genomic comparison and phylogenetic inference. The chloroplast genomes, ranging from 152,387 bp to 154,482 bp in length, exhibited conservation of genomic structure, and gene organization and order. Subsequently, we observed the expansion of IRs from the basal monocot Acorus americanus to Allium, identified 814 simple sequence repeats, 131 tandem repeats, 154 dispersed repeats and 109 palindromic repeats, and found six highly variable regions. The phylogenetic relationships of the Allium species inferred from the chloroplast genomes obtained high support, indicating that chloroplast genome data will be useful for further resolution of the phylogeny of the genus Allium.

Selection of Group-Specific Phthalic Acid Esters Binding DNA Aptamers via Rationally Designed Target Immobilization and Applications for Ultrasensitive and Highly Selective Detection of Phthalic Acid Esters.

Phthalic acid esters (PAEs) are ubiquitous in the environment, and some of them are recognized as endocrine disruptors that cause concerns on ecosystem functioning and public health. Due to the diversity of PAEs in the environment, there is a vital need to detect the total concentration of PAEs in a timely and low-cost way. To fulfill this requirement, it is highly desired to obtain group-specific PAE binders that are specific to the basic PAE skeleton. In this study, for the first time we have identified the group-specific PAE-binding aptamers via rationally designed target immobilization. The two target immobilization strategies were adopted to display either the phthalic ester group or the alkyl chain, respectively, at the surface of the immobilization matrix. The former enabled the rapid enrichment of aptamers after four rounds of selection. The top 100 sequences are cytosine-rich (44.7%) and differentiate from each other by only 1-4 nucleotides at limited locations. The top two aptamers all display the nanomolar dissociation constants to both the immobilized target and the free PAEs [dibutyl phthalate (DBP), butyl benzyl phthalate (BBP), bis(2-ethylhexyl) phthalate (DEHP)]. We further demonstrate the applications of the aptamers in the development of high-throughput PAE assays and DEHP electrochemical biosensors with exceptional sensitivity [limit of detection (LOD), 10 pM] and selectivity (>105-fold). PAE aptamers targeting one of the most sought for targets thus offer the promise of convenient, low-cost detection of total PAEs. Our study also provides insights on the aptamer selection and sensor development of highly hydrophobic small molecules.

Molecular cloning, characterization and expression analysis of CmAPX.

The RT PCR and RACE methods were used to obtain the cDNA sequence of an APX gene of muskmelon after the leaves were induced with powdery mildew. The cDNA length of the APX gene is 1,047 bp with a 750 bp ORF encoded a 249 amino acid and the molecular weight of APX protein is 27.3 kDa. The analysis showed that the CmAPX genomic DNA contained 10 extrons and 9 introns. The identity of the amino acid sequence deduced from the cDNA with the APX family of other homologous members was about 74-97%. A Full-length of ORF was sub-cloned into prokaryotic expression vector pET24a. The recombinant proteins had high expression level in E. coli. Analysis of expression at mRNA level showed that CmAPX exhibited highly tissue-specific patterns of expression. The mRNA level and enzyme activities assays showed that CmAPX might play an important role in the pathogenesis of powdery mildew.

[Prokaryotic expression of OC-IdeltaD86 (Oryzacystatin-IdeltaD86) gene and analysis of its activity].

According to the amino acids sequence of OC-IdeltaD86 gene and Escherichia coli codon usage, we synthesized this gene by overlap extension PCR method with 7 oligonucleotides DNA fragments. The PCR fragment was inserted into pGEM-T-easy vector and the recombined plasmid was named pGEM-T-OC-IdeltaD86. Two oligonucleotides into which the BamH I and Xho I sites were introduced were designed and synthesized based on pGEM-T-OC-IdeltaD86 and pet21b, and the PCR fragment into which the BamH I and Xho I sites were introduced was obtained. After digesting it with BamH I and Xho I, OC-IdeltaD86 gene was cloned into the corresponding sites of pet21b and obtained prokaryotic expression vector pet21b-OC-IdeltaD86. OC-IdeltaD86 gene was expressed in E. coli (BL21(DE3)plysS) after IPTG(Isopropyl beta-D-1-thiogalactopyranoside) inducement for 5 hours. The fusion protein of OC-IdeltaD86:6His gene accounted for 11.4% of total protein and 16.4% of soluble protein, which had been successfully purified by Ni-NTA and concentrated by PEG20000. This protein can effectively inhibit papain activity in vitro and may be used in anti-nematode research in vivo.