Integrated Assays of Genome-Wide Association Study, Multi-Omics Co-Localization, and Machine Learning Associated Calcium Signaling Genes with Oilseed Rape Resistance to Sclerotinia sclerotiorum.

Sclerotinia sclerotiorum (Ss) is one of the most devastating fungal pathogens, causing huge yield loss in multiple economically important crops including oilseed rape. Plant resistance to Ss pertains to quantitative disease resistance (QDR) controlled by multiple minor genes. Genome-wide identification of genes involved in QDR to Ss is yet to be conducted. In this study, we integrated several assays including genome-wide association study (GWAS), multi-omics co-localization, and machine learning prediction to identify, on a genome-wide scale, genes involved in the oilseed rape QDR to Ss. Employing GWAS and multi-omics co-localization, we identified seven resistance-associated loci (RALs) associated with oilseed rape resistance to Ss. Furthermore, we developed a machine learning algorithm and named it Integrative Multi-Omics Analysis and Machine Learning for Target Gene Prediction (iMAP), which integrates multi-omics data to rapidly predict disease resistance-related genes within a broad chromosomal region. Through iMAP based on the identified RALs, we revealed multiple calcium signaling genes related to the QDR to Ss. Population-level analysis of selective sweeps and haplotypes of variants confirmed the positive selection of the predicted calcium signaling genes during evolution. Overall, this study has developed an algorithm that integrates multi-omics data and machine learning methods, providing a powerful tool for predicting target genes associated with specific traits. Furthermore, it makes a basis for further understanding the role and mechanisms of calcium signaling genes in the QDR to Ss.

Graph Multi-Scale Permutation Entropy for Bearing Fault Diagnosis.

Bearing faults are one kind of primary failure in rotatory machines. To avoid economic loss and casualties, it is important to diagnose bearing faults accurately. Vibration-based monitoring technology is widely used to detect bearing faults. Graph signal processing methods promising for the extraction of the fault features of bearings. In this work, graph multi-scale permutation entropy (MPEG) is proposed for bearing fault diagnosis. In the proposed method, the vibration signal is first transformed into a visibility graph. Secondly, a graph coarsening method is used to generate coarse graphs with different reduced sizes. Thirdly, the graph's permutation entropy is calculated to obtain bearing fault features. Finally, a support vector machine (SVM) is applied for fault feature classification. To verify the effectiveness of the proposed method, open-source and laboratory data are used to compare conventional entropies and other graph entropies. Experimental results show that the proposed method has higher accuracy and better robustness and de-noising ability.

High-Throughput Recognition of Tumor Cells Using Label-Free Elemental Characteristics Based on Interpretable Deep Learning.

With cancer seriously hampering the increasing life expectancy of people, developing an instant diagnostic method has become an urgent objective. In this work, we developed a label-free laser-induced breakdown spectroscopy (LIBS) method for high-throughput recognition of tumor cells. LIBS spectra were straightly collected from cells dropped on a silicon substrate and built into a deep learning model for simultaneous classification of various cancers. To interpret the result of the deep learning algorithm, gradient-weighted class activation mapping was utilized to a one-dimensional convolution neural network (1D-CNN), and the saliency maps thus obtained amplified the differences between the spectra of cell lines. Overall results showed that the 1D-CNN algorithms achieved a mean sensitivity of 94.00%, a mean specificity of 98.47%, and a mean accuracy of 97.56%. Thus, the proposed method performed satisfactorily and is seen as an interpretable classification process for cancer cell lines.

Construction of classification models for pathogenic bacteria based on LIBS combined with different machine learning algorithms.

Bacteria, especially foodborne pathogens, seriously threaten human life and health. Rapid discrimination techniques for foodborne pathogens are still urgently needed. At present, laser-induced breakdown spectroscopy (LIBS), combined with machine learning algorithms, is seen as fast recognition technology for pathogenic bacteria. However, there is still a lack of research on evaluating the differences between different bacterial classification models. In this work, five species of foodborne pathogens were analyzed via LIBS; then, the preprocessing effect of five filtering methods was compared to improve accuracy. The preprocessed spectral data were further analyzed with a support vector machine (SVM), a backpropagation neural network (BP), and k-nearest neighbor (KNN). Upon comparing the capacity of the three algorithms to classify pathogenic bacteria, the most suitable one was selected. The signal-to-noise ratio and mean square error of the spectral data after applying a Savitzky-Golay filter reached 17.4540 and 0.0020, respectively. The SVM algorithm, BP algorithm, and KNN algorithm attained the highest classification accuracy for pathogenic bacteria, reaching 98%, 97%, and 96%, respectively. The results indicate that, with the support of a machine learning algorithm, LIBS technology demonstrates superior performance, and the combination of the two is expected to be a powerful tool for pathogen classification.

[A method of lung puncture path planning based on multi-level constraint].

Percutaneous pulmonary puncture guided by computed tomography (CT) is one of the most effective tools for obtaining lung tissue and diagnosing lung cancer. Path planning is an important procedure to avoid puncture complications and reduce patient pain and puncture mortality. In this work, a path planning method for lung puncture is proposed based on multi-level constraints. A digital model of the chest is firstly established using patient's CT image. A Fibonacci lattice sampling is secondly conducted on an ideal sphere centered on the tumor lesion in order to obtain a set of candidate paths. Finally, by considering clinical puncture guidelines, an optimal path can be obtained by a proposed multi-level constraint strategy, which is combined with oriented bounding box tree (OBBTree) algorithm and Pareto optimization algorithm. Results of simulation experiments demonstrated the effectiveness of the proposed method, which has good performance for avoiding physical and physiological barriers. Hence, the method could be used as an aid for physicians to select the puncture path.

The Exocyst Regulates Hydrolytic Enzyme Secretion at Hyphal Tips and Septa in the Banana Fusarium Wilt Fungus Fusarium odoratissimum.

Hyphal polarized growth in filamentous fungi requires tip-directed secretion, while additional evidence suggests that fungal exocytosis for the hydrolytic enzyme secretion can occur at other sites in hyphae, including the septum. In this study, we analyzed the role of the exocyst complex involved in the secretion in the banana wilt fungal pathogen Fusarium odoratissimum. All eight exocyst components in F. odoratissimum not only localized to the tips ahead of the Spitzenkörper in growing hyphae but also localized to the outer edges of septa in mature hyphae. To further analyze the exocyst in F. odoratissimum, we attempted single gene deletion for all the genes encoding the eight exocyst components and only succeeded in constructing the gene deletion mutants for exo70 and sec5; we suspect that the other 6 exocyst components are encoded by essential genes. Deletion of exo70 or sec5 led to defects in vegetative growth, conidiation, and pathogenicity in F. odoratissimum. Notably, the deletion of exo70 resulted in decreased activities for endoglucosidase, filter paper enzymes, and amylase, while the loss of sec5 only led to a slight reduction in amylase activity. Septum-localized α-amylase (AmyB) was identified as the marker for septum-directed secretion, and we found that Exo70 is essential for the localization of AmyB to septa. Meanwhile the loss of Sec5 did not affect AmyB localization to septa but led to a higher accumulation of AmyB in cytoplasm. This suggested that while Exo70 and Sec5 both take part in the septum-directed secretion, the two play different roles in this process. IMPORTANCE The exocyst complex is a multisubunit tethering complex (MTC) for secretory vesicles at the plasma membrane and contains eight subunits, Sec3, Sec5, Sec6, Sec8, Sec10, Sec15, Exo70, and Exo84. While the exocyst complex is well defined in eukaryotes from yeast (Saccharomyces cerevisiae) to humans, the exocyst components in filamentous fungi show different localization patterns in the apical tips of hyphae, which suggests that filamentous fungi have evolved divergent strategies to regulate endomembrane trafficking. In this study, we demonstrated that the exocyst components in Fusarium odoratissimum are localized not only to the tips of growing hyphae but also to the outer edge of the septa in mature hyphae, suggesting that the exocyst complex plays a role in the regulation of septum-directed protein secretion in F. odoratissimum. We further found that Exo70 and Sec5 are required for the septum-directed secretion of α-amylase in F. odoratissimum but with different influences.

Sugar and Glycerol Transport in Saccharomyces cerevisiae.

In Saccharomyces cerevisiae the process of transport of sugar substrates into the cell comprises a complex network of transporters and interacting regulatory mechanisms. Members of the large family of hexose (HXT) transporters display uptake efficiencies consistent with their environmental expression and play physiological roles in addition to feeding the glycolytic pathway. Multiple glucose-inducing and glucose-independent mechanisms serve to regulate expression of the sugar transporters in yeast assuring that expression levels and transporter activity are coordinated with cellular metabolism and energy needs. The expression of sugar transport activity is modulated by other nutritional and environmental factors that may override glucose-generated signals. Transporter expression and activity is regulated transcriptionally, post-transcriptionally and post-translationally. Recent studies have expanded upon this suite of regulatory mechanisms to include transcriptional expression fine tuning mediated by antisense RNA and prion-based regulation of transcription. Much remains to be learned about cell biology from the continued analysis of this dynamic process of substrate acquisition.

Hierarchical porous carbon aerogels as a versatile electrode material for high-stability supercapacitors.

Supercapacitors (SCs), as new energy storage devices with low cost and high performance, urgently require an electrode material with good pore structure and developed graphitization. Herein, we report a 3D hierarchical porous structured carbon aerogel (CA) obtained via dissolving-gelling and a subsequent carbonizing process. The gelling process was realized by using different types of anti-solvents. The carbon aerogel-acetic acid (CA-AA) has a specific surface area of 616.97 m2 g-1 and a specific capacitance of 138 F g-1 which is superior to cellulose-based active carbon. The CA was assembled into a SC, which showed excellent cycle stability. After charging and discharging 5000 times at the current density of 1 A g-1, the capacitance retention ratio of CA-AA reaches 102%. In addition, CA-AA has an energy density of 10.06 W h kg-1 when the power density is 181.06 W kg-1. It provides a choice for non-activation to effectively regulate the porous structure of biomass carbon materials.

The Effect of Cuelure on Attracting and Feeding Behavior in Zeugodacus tau (Walker) (Diptera: Tephritidae).

As a vital pest control strategy, trapping plays an important role in the system of monitoring, catching and killing fruit flies. Cuelure (4-(4-acetoxyphenyl)-2-butanone, CL) is a male lure that attracts Zeugodacus tau and also stimulates feeding in this species. In this study, the attraction of Z. tau to CL and its subsequent feeding behavior were investigated. Under the significant influence of age and time of day, the attraction of CL to Z. tau was found to be optimal when flies were 14 days old, and the number of flies trapped increased with trapping duration. It was determined that consumption can improve the mating success and female adult fertility of Z. tau. After the observation period, the mating success rate of flies that ingested CL was significantly higher than that of the control group and was maintained at a higher level. It was found that parental consumption of CL could accelerate the development of eggs and larvae, resulting in increased pupation and emergence rates. The results of this study will further clarify the dynamic relationship between pest and lure, and provide a research basis for navigating the integrated management of Z. tau in the field.

Effect of Ultraviolet-B Radiating Drosophila melanogaster as Host on the Quality of Trichopria drosophilae, a Pupal Parasitoid of Drosophila suzukii.

The pupal parasitoid, Trichopria drosophilae Perkins (Hymenoptera: Diapriidae), is an ectoparasitoid of the genus Drosophila with great potential for application in biological control based on its excellent control efficiency for Drosophila suzukii Matsumura (Diptera: Drosophilidae), and it has has even been commercialized by biofactories. Due to its characteristics of short life cycle, large number of offspring, easy rearing, rapid reproduction, and low cost, Drosophila melanogaster (Diptera: Drosophilidae) is currently being utilized as a host to mass produce T. drosophilae. To simplify the mass rearing process and omit the separation of hosts and parasitoids, ultraviolet-B (UVB) was used as an irradiation source to irradiate D. melanogaster pupae, and the effects on T. drosophilae were studied. The results showed that UVB radiation significantly reduces host emergence and affects the duration of parasitoid development (female: F0 increased from 21.50 to 25.80, F1 from 23.10 to 26.10; male: F0 decreased from 17.00 to 14.10, F1 from 17.20 to 14.70), which has great significance for the separation of hosts and parasitoids as well as of females and males. Of the various studied conditions, UVB irradiation was ideal when the host was supplied with parasitoids for 6 h. The selection test results showed that the female-to-male ratio of emerging parasitoids in this treatment was highest at 3.47. The no-selection test resulted in the highest rates of parasitization and parasitoid emergence rate, maximized inhibition of host development, and allowed the omission of the separation step. Finally, the results of the semi-field test showed that the parasitoids bred in this treatment could search for their hosts normally and could therefore be directly applied in the biological control of Drosophila pests in the field.

Optimization of machine learning classification models for tumor cells based on cell elements heterogeneity with laser-induced breakdown spectroscopy.

The rapid and accurate diagnosis of cancer is an important topic in clinical medicine. In the present work, an innovative method based on laser-induced breakdown spectroscopy (LIBS) combined with machine learning was developed to distinguish and classify different tumor cell lines. The LIBS spectra of cells were first acquired. Then the spectral pre-processing was performed as well as detailed optimization to improve the classification accuracy. After that, the convolutional neural network (CNN), support vector machine (SVM), and K-nearest neighbors were further compared for the optimized classification ability of tumor cells. Both the CNN algorithm and SVM algorithm have achieved impressive discrimination performances for tumor cells distinguishing, with an accuracy of 97.72%. The results show that the heterogeneity of elements in tumor cells plays an important role in distinguishing the cells. It also means that the LIBS technique can be used as a fast classification method for classifying tumor cells.

Jujube Shell Based-Porous Carbon Composites Double-Doped by MnO2 and Ti3C2Tx: The Effect of Double Pseudocapacitive Doping on Electrochemical Properties.

In this study, manganese-containing porous carbon was synthesized from jujube shells by two-step carbonization and activation and was then covered with Ti3C2Tx to obtain double-doped biomass composites. In order to improve the interfacial properties (surface tension and wettability) between Ti3C2Tx and porous carbon, the effects of two media (deionized water and acetone solution) on the electrochemical properties of the composites were compared. The acetone solution changed the surface rheology of Ti3C2Tx and porous carbon, and the decreased surface tension and the increased wettability contributed to the ordered growth of 2D-Ti3C2Tx on the surface of the porous carbon. Raman analysis shows the relatively higher graphitization degree of JSPC&Ti3C2Tx (acetone). Compared with JSPC&Ti3C2Tx, JSPC&Ti3C2Tx (acetone) can maintain better rectangle-like properties even at a higher scanning rate. Under the effect of the acetone solution, the pseudocapacitive ratio of JSPC&Ti3C2Tx (acetone) increased from 10.1% to 30.7%. At the current density of 0.5 A/g, the specific capacitance of JSPC&Ti3C2Tx (acetone) achieved 96.83 F/g, and the specific capacitance of 58.17 F/g was maintained even at the high current density (10 A/g), which shows excellent magnification. Under the condition of the current density of 10 A/g, JSPC&Ti3C2Tx (acetone) can obtain a power density of 52,000 W/kg while maintaining an energy density of 8.74 Wh/kg. After 2000 cycles, the symmetrical button battery assembled with this material can still have a capacitance retention rate of more than 90%. This method realized the deep utilization of green and low-cost raw materials by using biomass as the precursor of composite materials and promoted the further development of carbon-based supercapacitor electrode materials.

Anaerobic digestion of wood vinegar wastewater using domesticated sludge: Focusing on the relationship between organic degradation and microbial communities (archaea, bacteria, and fungi).

Thermochemical process of biomass is one of the promising renewable energy technologies; however, the by-product (wood vinegar wastewater) is rich in refractory organics, which is harmful to the environment and inhibits the conversion efficiency of microorganisms. Consequently, the dominant functional microbial communities corresponding to the various substrate were obtained through the continuous domestication, and the relationship between the dominant functional communities and the degradation of organic compounds was comprehensively analyzed. The bacterial community was absolutely dominant (approximately 85%), while archaea and fungi had similar relative abundance. The diversity showed that glucose was not conducive to the development of microbial diversity, while the substrate containing wood vinegar wastewater showed the opposite trend. The functional analysis revealed that the enrichment of bacteria associated with the hydrolysis and acidification of organics increased in the domestication process. Glucose facilitated hydrogen-trophic methanogenesis as the main methanogenic pathway in the methanogenic stage.

Development of Mo-Modified Pseudoboehmite Supported Ni Catalysts for Efficient Hydrogen Production from Formic Acid.

Formic acid (FA), as a safe and renewable liquid hydrogen storage material, has attracted extensive attention. In this paper, a series of Mo-modified pseudoboehmite supported Ni catalysts were developed and evaluated for efficient hydrogen production from formic acid. Pseudoboehmite (PB) as a catalyst carrier was used for the first time. Ni/PB and NiMo/PB possessed a mesostructure, and the pore size distribution was mainly concentrated between 2 and 20 nm. The oxygen vacancies caused by Mo enhanced Ni anchoring, thus inhibiting Ni sintering. Compared with Ni10/PB (7.62 nm), Ni10Mo1/PB had smaller Ni particles (5.08 nm). The Ni-O-Al solid solutions formed through the interaction of Ni with the PB improved the catalytic performance. Ni10Mo1/PB gave the highest conversion of 92.8% with a H2 selectivity of 98% at 300 °C, and the catalyst activity hardly decreased during the 50 h stability test. In short, Ni10Mo1/PB was a promising catalyst for hydrogen production from formic acid because of the oxygen vacancy anchoring effect as well as the formation of Ni-O-Al solid solutions which could effectively suppress the Ni sintering.

Comparison of methanogenic potential of wood vinegar with gradient loads in batch and continuous anaerobic digestion and microbial community analysis.

Anaerobic digestion (AD) of wood vinegar wastewater (WVWW) has considerable potential in energy recovery and sustainable development. WVWW contains abundant acetic acid and some refractory organics. Therefore, the batch and continuous AD of WVWW were investigated. The threshold value of the inhibitory concentration was obtained at a chemical oxygen demand (COD) of 4 g/L in batch AD. Three-dimensional electrolysis was adopted to improve the biodegradability of WVWW, and a reduction in the inhibitory rate from 38.2% to 4.9% and an increase in methane production by 53.8% were observed. The up-flow anaerobic sludge blanket reactor achieved an efficient conversion of methane at an organic loading rate (OLR) of <8.58 g COD/L·d. However, the OLR of 10.01 g COD/L·d decreased the methane production from 350.6 to 42.5 mL CH4/g CODfed. Aminicenantales, Acetobacterium, Anaerolineae, and SBR1031 were the dominant bacterial genera in continuous AD. Fewer genera with similar classifications were detected in the batch AD. In the archaea community, acetotrophic methanogens (Methanosaeta) dominated and increased continuously with increasing OLR. Microbial analysis revealed that toxic substances affected bacterial diversity and promoted the enrichment of Intestinimonas, Syntropobacter, and Propionicimonas at high OLRs. The continuous AD was most suitable for the energy recovery from WVWW.

Continuous Anaerobic Digestion of Wood Vinegar Wastewater From Pyrolysis: Microbial Diversity and Functional Genes Prediction.

Wood vinegar wastewater (WVWW) is the main by-product of biomass pyrolysis process, which is more suitable to use anaerobic digestion (AD) to achieve energy recovery due to its large amount of organic matter. In this study, the up-flow anaerobic sludge bed (UASB) reactor was used to investigate the continuous anaerobic transformation of WVWW with gradient concentrations (0.3, 0.675, 1, 2, 3, 4, 5, 6, and 7 g COD/L). Then, the changes of microbial community, diversity index and functional gene were analyzed in detail. The results revealed that WVWW showed good AD performance in continuous fermentation. WVWW of organic loading rate (OLR) of >8.58 g COD/L⋅d showed severe inhibition on biodegradability and methane production, which is mainly due to the toxic substances as compared with the control group. The bacterial communities were dominated by phyla of Chloroflexi, Firmicutes, Proteobacteria, Acidobacteria, Synergistetes, and Actinobacteria. The gene abundances related to energy production, carbohydrate transport and metabolism were relatively high, which are mainly responsible for carbon forms conversion and carbohydrate degradation. This study will provide a basis for the screening and enrichment of functional bacteria and genes.

Extraction of pulmonary Trachea by dynamic tubular edge contour algorithm.

BACKGROUND: One of the difficulties and hot topics in the field of computer vision and image processing is extraction of the high-level pulmonary trachea from patients' lung CT images. Current, common bronchial extraction methods are limited by the phenomenon of bronchial loss and leakage, and cannot extract the higher-level pulmonary trachea, which does not meet the requirements of guiding lung puncture procedures. METHODS: Based on the characteristic "tubular structure" (ring or semi-closed ring) of the pulmonary trachea in CT images, an algorithm based on dynamic tubular edge contour is proposed. In axial, coronal and sagittal CT images, the algorithm could extract the skeletal line of the pulmonary trachea and vessel-connecting region, perform elliptical fitting, extract the pulmonary trachea by the ratio of the ellipse's long and short axes, and obtain point cloud data of the pulmonary trachea in three directions. The point cloud data was fused to obtain a complete three-dimensional model of the pulmonary trachea. RESULTS: The algorithm was verified using CT data from "EXACT09", and could extract the pulmonary trachea to the 10-11 level, which effectively solves the problems of leakage and loss of the trachea. CONCLUSIONS: We have constructed a novel extraction algorithm of pulmonary trachea that can guide the doctors to decide the puncture path and avoid the large trachea, which has important theoretical and practical significance for reducing puncture complications and the mortality rate.