Screening and Identification of Cotton Verticillium Wilt Antagonistic Bacteria Strain 7-30

[Objective]The aim of this study was to screen the antagonistic spore-forming bacteria of Verticillium dahliae and identify its physiological and biochemical characteristics.[Method]Taking the cotton verticillium wilt pathogen Verticillium dahliae V-190 as the test microorganism,the antagonistic spore-forming bacteria were screened.Through the preliminary screening and secondary screening,an antagonistic bacteria strain 7-30 with stronger antibacterial activity was obtained,and its morphological characteristics,physiological and biochemical characteristics were also identified.[Result]84 antagonistic bacteria strains were isolated from soil in various places by the preliminary screening.Especially,18 strains with better antagonistic ability were screened again,so an antagonistic bacteria strain 7-30 with the diameter of inhibition zone 18.9 mm and stronger antibacterial activity was obtained.According to its morphological characteristics,physiological and biochemical characteristics,the antagonistic bacteria strain 7-30 was identified as Bacillus subtilis primarily.[Conclusion]The strain 7-30 was obtained as the antagonistic spore-forming bacteria of Verticillium dahliae.

Screening and Identification of Antagonistic Bacteria against Soil-borne Diseases of Tomato

[Objective] This study was conducted to screen resources for biological control of soil-borne diseases of tomato. [Method] Antagonistic bacteria against Ral- stonia solanacearum and Fusarium oxysporum were isolated and purified from soil samples by dilution plating and confronting incubation on PDA plates, then the antibacterial spectrum and metabolic secretions of the bacterial isolates were measured, and their species were identified by establishing phylogenetic trees with Neighbor-Joining method. [Result] From the 60 soil samples, 10 of 59 antagonistic bacteria isolates against R. solanacearum showed inhibition zone diameter 〉 25 mm, and 4 of 30 strains against F. oxysporum exhibited inhibition rate 〉 30%. The bacteriostatic substances and antibacterial spectrum analysis on above 14 isolates revealed that four strains N23-2, N58-2, NF59-3 and NF61-1 had good antago- nism against pathogenic bacteria and fungi; 12 strains produced cellulose, 11 strains produced proteases, and 6 strains produced siderophores. The molecular identification experiments indicated that four strains were members of Paenibacillus, three strains of Streptomyces, three strains of Pseudomonas strains, and four strains of Bacillus strains.

Isolation,Screening and Primary Identification of a Keratin-degrading Fungus

[Objective] The paper was to provide new germplasm sources for efficient and economical degradation and utilization of animal keratin.[Method] The keratin-degrading fungus was isolated,screened and primarily identified by using the combination method of traditional isolation and screening,solid culture-medium degradation and animal test.[Result] A strain of non-pathogenic filamentous fungi with high degradation efficiency was obtained,which was preliminarily identified to be a species in Mucoraceae.[Conclusion] The discovery of the strain enriched the family members of keratin-degrading fungus,and provided new germplasm resources for degradation and utilization of animal keratin.

Screening and identification of an antagonistic bacterium strain LHB02 and the optimization of its fermentation conditions

A strain LHB02 with strong antibacterial activity against some aquatic pathogens was screened from the coastal marine sediment in Fujian province, China. LHB02 was identified as Bacillus subtilis, based on its 16S rRNA sequence, together with the morphological, physiological and biochemical characteristics. The antagonistic activity of strain LHB02 and its optimal fermentation conditions were also investigated. The results showed that LHB02 had strong antagonistic activity against 3 species of vibrios： Vibrio harveyi,Vibrio alginolyticus and Vibrio anguillarum, and the optimum fermentation conditions for the strain LHB02 were as follows： KB culture medium （peptone 20 g, glycerol 10 mL, K2HPO4 1.5 g, MgSO 4 .7H2O 1.5 g, H2O 1 000 mL）; temperature, 28 ℃; pH ,7.0; culture time, 36 h; and inoculation amount, 1.5% （v/v）.

Screening and Identification of Myxobacterias with Antifungal Activity

[ Objective] The paper was to screen myxobacteria with antifungal activity, and identify its species. [ Method] 237 myxobacteria were isolated and pu- rified from 200 copies of soil samples collected from 23 provinces in China. The strains were fermented in four different media, and the fermentation products were extracted by methanol to obtain metabolites. With Candida albicans as the model, the secondary metabolites were carried out high-throughput screening. [ Result ] A strain of myxohacteria numbered ZJ2 was obtained after secondary screening, its secondary metabolites had activities against G. albicans. 16S rDNA cloning and sequencing results showed that ZJ2 was Myxococcus fidvus. [ Conclusion ] The secondary metabolites of ZJ2 strain had bioactive substances with significant inhibi- tion effect against the growth of C. albicans, which had potential pharmaceutical research and development value.

Isolation,Screening and Identification of Cellulose Decomposing Strains in Straw-amended Soil

[Objective]The aim was to isolate cellulose decomposing strains with high activity from straw-amended soil.[Method]Screening of CMC solid culture and shaking culture rescreening were carried out to obtain cellulose decomposing strains with high activity from the corn straw amended soil,which were analyzed by 16rDNA sequence analysis.[Result]A bacterium and a fungus with higher endonucleases activity were obtained through preliminary screening and secondary screening,a fungus with higher filter paper enzyme activity,and a bacterium（NO.5 strain） with higher of both filter paper enzyme activity and CMC enzyme activity were obtained.The result of 16S rDNA sequence analysis showed that the similarity was 100% between NO.5 strain and Bacillus subtilis.[Conclusion]NO.5 strain was identified as Bacillus subtilis.

Screening of SSR Core Primers for Purity Identification of Pepper(Capsicum) Hybrids

[Objective] This study aimed to screen a set of SSR core primers suitable for purity identification of pepper （Capsicum） hybrids. [Method] DNA fingerprint of 100 pepper hybrids was analyzed using 17 SSR primers. [Result] According to the polymorphism and heterozygosity, Hpms1-214, Es395 and Hpmsl-5 were determined as three preferred core primers for purity identification of pepper hybrids. By using these three preferred core primers, 97 pepper hybrids （accounting for 97%） had heterozygous band pattern with at least one primer. Es330, Es363, Epms923, Es120 and Es64 were determined as candidate core primers for purity identification of pepper hybrids. Specific primers of 14 varieties were obtained, which could be used to further screen parent-complementary primers of each pepper hybrid. [Con- clusion] This study laid the foundation for constructing standard DNA fingerprints for purity identification of pepper hybrids.

Screening and Molecular Identification of Strain that Produced Inulinase in Qinghai

The 46 strains that produced inulase were screened from rhizosphere soil where Jerusalem artichoke was planted in Qinghai.One strain with high inulinase productivity was obtained through further screening and the enzyme activity was6.67 U/ml.This inulinase was exonuclease.Through determination and analysis of the r DNA-ITS sequence,and analysis of morphology,the fungus was identified as Actinomucor elegans.

Screening and Identification of Antagonistic Bacterium ZG-10 against Spot Blotch Disease in Pakchoi

[ Objective] The purpose was to screen bacterium with antagonistic effect against pathogen of spot blotch disease in pakchoi in vegetable field. [Method] More than 200 strains of bacteria which could produce spore were isolated from soil in different places. Through screening and rescreening, the bacteria with higher antibacterial activity were conducted observation about thallus shapes and colony characters, a series of physiological and biochemical tests were performed. [Result] Rescreening results indicated that the strains including ZG-10, ZG-19, ZG-59, ZG-72 and ZG-31 had significant antibacterial activity, which had very high research value and good application prospect for biocontrol on spot blotch disease in pakchoi; the strain ZG-10 was identified to be Bacillus subtilis. [ Conclusion] The strain ZG-10 had biocontrol potential and good development prospect. This research laid certain basis for subsequent research and strated a new way for the application of antagonistic strain and proteinum polypeptide in agdculture.

Early identification of stroke through deep learning with multi-modal human speech and movement data

Early identification and treatment of stroke can greatly improve patient outcomes and quality of life.Although clinical tests such as the Cincinnati Pre-hospital Stroke Scale(CPSS)and the Face Arm Speech Test(FAST)are commonly used for stroke screening,accurate administration is dependent on specialized training.In this study,we proposed a novel multimodal deep learning approach,based on the FAST,for assessing suspected stroke patients exhibiting symptoms such as limb weakness,facial paresis,and speech disorders in acute settings.We collected a dataset comprising videos and audio recordings of emergency room patients performing designated limb movements,facial expressions,and speech tests based on the FAST.We compared the constructed deep learning model,which was designed to process multi-modal datasets,with six prior models that achieved good action classification performance,including the I3D,SlowFast,X3D,TPN,TimeSformer,and MViT.We found that the findings of our deep learning model had a higher clinical value compared with the other approaches.Moreover,the multi-modal model outperformed its single-module variants,highlighting the benefit of utilizing multiple types of patient data,such as action videos and speech audio.These results indicate that a multi-modal deep learning model combined with the FAST could greatly improve the accuracy and sensitivity of early stroke identification of stroke,thus providing a practical and powerful tool for assessing stroke patients in an emergency clinical setting.

Advancing healthcare through laboratory on a chip technology:Transforming microorganism identification and diagnostics

In a recent case report in the World Journal of Clinical Cases,emphasized the crucial role of rapidly and accurately identifying pathogens to optimize patient treatment outcomes.Laboratory-on-a-chip(LOC)technology has emerged as a transformative tool in health care,offering rapid,sensitive,and specific identification of microorganisms.This editorial provides a comprehensive overview of LOC technology,highlighting its principles,advantages,applications,challenges,and future directions.Success studies from the field have demonstrated the practical benefits of LOC devices in clinical diagnostics,epidemiology,and food safety.Comparative studies have underscored the superiority of LOC technology over traditional methods,showcasing improvements in speed,accuracy,and portability.The future integration of LOC with biosensors,artificial intelligence,and data analytics promises further innovation and expansion.This call to action emphasizes the importance of continued research,investment,and adoption to realize the full potential of LOC technology in improving healthcare outcomes worldwide.

Screening of the Gene for Chlorella Identification and Identification of oil-producing Microalgae

[Objective] The aim was to select suitable gene for Chlorella identification and to identify the oil-producing microalgae.[Method] Four candidate gene sequences,the nuclear genomic rDNA of the 18S rRNA gene,internal transcribed spacer（ITS）,internal transcribed spacer Ⅱ（ITS Ⅱ）and the chloroplast rbcL gene,were selected for Chlorella molecular identification.Through these four candidate genes,the genetic variability and distinguish ability between intra-species and inter-species was analyzed to choose the right genes for identification of the high oil-content Chlorella.On this basis,application of these gene segments were classified and identified for five fresh-water isolated Chlorella,which oil-content is more than 30%.[Result] ITS gene was a suitable gene because of its high variation and short fragment length,meanwhile its genetic distance intra-species（0.439 6±0.135 9）was larger than inter-species（0.045 7±0.084 3）.Its sequence length varied between different species whereas highly conserved in the same species.By the application of ITS sequences,respectively,five high oil-content stains were identified as one C.vulgaris,two strains of C.sorokiniana and two strains of algae Chlorella sp.[Conclusion] This study had provided reference for the establishment of identification gene pool of Chlorella.

High-throughput computational screening and in vitro evaluation identifies 5-(4-oxo-4H-3,1-benzoxazin-2-yl)-2-[3-(4-oxo-4H-3,1-benzoxazin-2-yl)phenyl]-1H-isoindole-1,3(2H)-dione(C3),as a novel EGFR—HER2 dual inhibitor in gastric tumors

Gastric cancers are caused primarily due to the activation and amplification of the EGFR or HER2 kinases resulting in cell proliferation,adhesion,angiogenesis,and metastasis.Conventional therapies are ineffective due to the intra-tumoral heterogeneity and concomitant genetic mutations.Hence,dual inhibition strategies are recommended to increase potency and reduce cytotoxicity.In this study,we have conducted computational high-throughput screening of the ChemBridge library followed by in vitro assays and identified novel selective inhibitors that have a dual impediment of EGFR/HER2 kinase activities.Diversity-based High-throughput Virtual Screening(D-HTVS)was used to screen the whole ChemBridge small molecular library against EGFR and HER2.The atomistic molecular dynamic simulation was conducted to understand the dynamics and stability of the protein-ligand complexes.EGFR/HER2 kinase enzymes,KATOIII,and Snu-5 cells were used for in vitro validations.The atomistic Molecular Dynamics simulations followed by solvent-based Gibbs binding free energy calculation of top molecules,identified compound C3(5-(4-oxo-4H-3,1-benzoxazin-2-yl)-2-[3-(4-oxo-4H-3,1-benzoxazin-2-yl)phenyl]-1H-isoindole-1,3(2H)-dione)to have a good affinity for both EGFR and HER2.The predicted compound,C3,was promising with better binding energy,good binding pose,and optimum interactions with the EGFR and HER2 residues.C3 inhibited EGFR and HER2 kinases with IC50 values of 37.24 and 45.83 nM,respectively.The GI50 values of C3 to inhibit KATOIII and Snu-5 cells were 84.76 and 48.26 nM,respectively.Based on these findings,we conclude that the identified compound C3 showed a conceivable dual inhibitory activity on EGFR/HER2 kinase,and therefore can be considered as a plausible lead-like molecule for treating gastric cancers with minimal side effects,though testing in higher models with pharmacokinetic approach is required.

Methodology of drug screening and target identification for new necroptosis inhibitors

Apoptosis has been considered as the only form of regulated cell death for a long time. However, a novel form of programmed cell death called necroptosis was recently reported. The process of necroptosis is regulated and plays a critical role in the occurrence and development of multiple human diseases. Thus,the study on the molecular mechanism of necroptosis and its effective inhibitors has been an attractive field for researchers. Herein, we introduce the molecular mechanism of necroptosis and focus on the literature about necroptosis drug screening in recent years. In addition, the identification of the critical drug targets of the necroptosis is also discussed.

Methods on Identification and Screening of Rice Genotypes with High Nitrogen Efficiency

In order to establish methods for indentification and screening of rice genotypes with high nitrogen （N） efficiency, N absorption efficiency （NAE）, N utilization efficiency （NUE） and N harvest index （NHI） in ten rice genotypes were investgated at the elongation, booting, heading and maturity stages under six N levels in a pot experiment with soil-sand mixtures at various ratios. NAE in various rice genotypes firstly increased, peaked under a medium nitrogen rate of 0.177 g/kg and then decreased, but NUE and NHI always decreased with increasing nitrogen levels. NAE in various rice genotypes ever increased with growing process and NUE indicated a descending tendency of elongation stage〉heading stage〉maturity stage〉booting stage. N level influenced rice NAE, NUE and NHI most, followed by genotype, and the both effects were significant at 0.01 level. In addition, the interaction effects of genotype and nitrogen level on rice NAE and NUE were significant at 0.01 level, but not significant on rice NHI. Because the maximum differences of NAE and NUE were found at the elongation stage, it was thought to be the most suitable stage for identification and screening these two paremeters. Therefore, the optimum conditions for identification and screening of rice NAE, NUE and NHI in a pot experiment were the nitrogen rate of 0.157 g/kg at the elongation stage, low nitrogen at the elongation stage, and the nitrogen rate of 0.277 g/kg at the maturity stage, respectively.

Screening, identification and desilication of a silicate bacterium

The strain Lv（1- z） isolated from the Henan bauxite was characterized by morphological observation, biochemical and physiological identification, and 16S rDNA sequence analysis. The influences of temperature, initial pH value, the volume of medium, shaking speed and illite concentration on the desilicating ability of the strain Lv（1- z） were investigated. The results show that the bacterium is a Gram-negative rod-shaped bacterium with oval endspores and thick capsule, but without flagellum. The biochemical and physiological tests indicate that the strain Lv（1- z） is similar to Bacillus rnucilaginosus. In GenBank the 16S rDNA sequence similarity of the strain Lv（1- z） and the B. rnucilaginosus YNUCC0001（AY571332） is more than 99%. Based on the above results, the strain Lv（1- z） is identified as B. rnucilaginosus. The optimum conditions for the strain L（1- z） to remove silicon from illite are as follows., temperature is 30℃ ;initial pH value is 7.5; medium volume in 200 mL bottle is 60 mL; shaking speed of rotary shaker is 220 r/m ; illite concentration is 1%.

Screening and Identification of Waterlogging Tolerance in Brassica napus Germplasm Resources

In order to evaluate,screen and identify waterlogging-tolerant Brassica napus resources and provide good germplasm materials for breeding of waterlogging-tolerant rape,608 B. napus germplasm materials from different sources were identified and screened for waterlogging-tolerant germplasms. The identification results showed that tested materials had dead seedling rates in the range of 0-100%,indicating that these rape germplasm materials varied extensively in waterlogging tolerance. Among the 608 materials,waterlogging-tolerant materials( grade I,relative dead seedling rate≤21%) accounted for 25. 49%; non-tolerant materials( grade Ⅳ + V,dead seedling rate≥61%) accounted for 29. 43%; and other materials had waterlogging tolerance between the two. The identification results of waterlogging tolerance in the 349 rape germplasm resource from the upper,middle and lower reaches of Yangtze River and Huang-Huai Basin showed that materials from the lower Yangtze River had the lowest average dead seedling rate of 38. 8%,which was remarkably lower than materials from other ecological regions,and waterlogging-tolerant materials among them accounted for 33. 6%,which was also remarkably higher than materials from other ecological regions. It could thus be seen that materials from the lower Yangtze River have stronger waterlogging tolerance than those from other ecological regions overall. In this study,24 highly-tolerant B. napus germplasms( dead seedling rate < 1%) were selected from the 608 B. napus germplasm materials,which could be used for breeding of waterlogging-tolerant rape and related fundamental research.

Identification and screening of nitrogenefficient cotton genotypes under low and normal nitrogen environments at the seedling stage

Background： Large quantities of nitrogen （N） fertilizer applied to cotton cropping systems support high yields but cause adverse environmental impacts such as N20 emission and water eutrophication. The development of cotton cultivars with higher N use efficiencies suitable for low-N conditions is therefore important for sustainable production. In this study, we evaluated 100 cotton genotypes in 2016 for N use efficiency and related traits at the seedling stage. Methods： Sand culture experiment was conducted with low N levels （0.01 g.kg i） or normal N levels （0.1 g.kg i）. We investigated plant height, SPAD value （soil plant analysis development chlorophyll meter）, dry weight, N accumulation, N utilization efficiency, and N uptake efficiency. Through descriptive statistics, principal component analysis and heatmap clustering analysis, we confirmed the evaluation index system of N-efficient genotypes and the classification of N-efficient genotypes. Results： Significant differences were observed among N levels and genotypes for all agronomic traits and N levels. Coefficients of variation varied greatly and ranged from 6.7N28.8 and 7.4N20.8 under low-N and normal-N treatment, respectively. All traits showed highly significant positive correlations with each other, except SPAD value. The principal components under both N levels were similar, showing that total dry weight, aboveground dry weight, total N accumulation, and N uptake efficiency were important components. We confirmed these four traits as suitable screening indexes for low N tolerance. Based on the results of heatmap clustering and scatter diagram analysis of N efficiency value, 10 genotypes were found low-N tolerant, in which five varieties were inefficient under both low and normal N conditions, while four varieties were found efficient under low-N conditions but inefficient under normal-N conditions. Only one variety was efficient under both low and normal-N conditions. Meanwhile, 20 genotypes were identified as low-N sensitive ones, in which 19 genotypes were inefficient under low-N conditions but efficient under normal-N conditions, one variety was inefficient under both low and normal-N conditions. Conclusion： We preliminarily identified Kashi as a low-N tolerant and N-efficient cotton genotype, and CCRI 64 as a low- N sensitive and N-inefficient cotton genotype. Further studies should be carried out to verify the yield and heritability effect of specific genotypes in the field.

Screening and Simple Identification of Drought-resistant Lines in Sugarcane Breeding

Six sugarcane plant lines were selected from seedlings owing to good performance in agronomic characters under drought conditions.A special test with drought stress to death under groove was carried out to select the best drought tolerant clones among them. The proportion of bound water to free water content in leaves,cell cytoplasm membrane permeability in leaves,yield components,etc.,which were regarded as reasonable indexes to identify drought resistance of sugarcane,were measured. The results showed that both YT06-868 and YT05-339 were winners. The two were high-class drought-resistant clones. On some measured indexes,both of them had higher values than ROC22( the main check variety) and on the other ones,they both had the same values as ROC22. The drought resistance of YT05-291 was moderate and between ROC22 and ROC16( the secondary check variety),while the others had poor drought-resistant according to these indexes.

A Local Sparse Screening Identification Algorithm with Applications

Extracting nonlinear governing equations from noisy data is a central challenge in the analysis of complicated nonlinear behaviors.Despite researchers follow the sparse identification nonlinear dynamics algorithm(SINDy)rule to restore nonlinear equations,there also exist obstacles.One is the excessive dependence on empirical parameters,which increases the difficulty of data pre-processing.Another one is the coexistence of multiple coefficient vectors,which causes the optimal solution to be drowned in multiple solutions.The third one is the composition of basic function,which is exclusively applicable to specific equations.In this article,a local sparse screening identification algorithm(LSSI)is proposed to identify nonlinear systems.First,we present the k-neighbor parameter to replace all empirical parameters in data filtering.Second,we combine the mean error screening method with the SINDy algorithm to select the optimal one from multiple solutions.Third,the time variable t is introduced to expand the scope of the SINDy algorithm.Finally,the LSSI algorithm is applied to recover a classic ODE and a bi-stable energy harvester system.The results show that the new algorithm improves the ability of noise immunity and optimal parameters identification provides a desired foundation for nonlinear analyses.