Anti-GM-CSF autoantibodies predict outcome of cryptococcal meningitis in patients not infected with HIV: A cohort study.

OBJECTIVES: To explore the seroprevalence of anti-granulocyte-macrophage colony-stimulating factor (GM-CSF) autoantibodies in non-HIV cryptococcal meningitis (CM) and assess its predictive value for survival. METHODS: This is a retrospective study of 12 years of non-HIV CM. We detected serum anti-GM-CSF autoantibodies, and evaluated the clinical features and outcomes, together with the exploration of prognostic factors for 2-week and 1-year survival. RESULTS: A total of 584 non-HIV CM cases were included. 301 of 584 patients (51.5%) were phenotypically healthy. 264 Cryptococcus isolates were obtained from cerebrospinal fluid (CSF) culture, of which 251 were identified as C. neoformans species complex and 13 as C. gattii species complex. Thirty-seven of 455 patients (8.1%) tested positive for serum anti-GM-CSF autoantibodies. Patients with anti-GM-CSF autoantibodies were more susceptible to C. gattii species complex infection (66.7% vs. 6.3%; p < 0.001) and more likely to develop pulmonary mass lesions with a diameter >3 centimetres (42.9% vs. 6.5%; p 0.001). Of 584 patients 16 (2.7%) died within 2 weeks, 77 of 563 patients (13.7%) died at 1 year, and 93 of 486 patients (19.1%) lived with disabilities at 1 year. Univariant Cox regression analysis found that anti-GM-CSF autoantibodies were associated with lower 1-year survival (HR, 2.66; 95% CI, 1.34-5.27; p 0.005). Multivariable Cox proportional hazards modelling revealed that CSF cryptococcal antigen titres ≥1:1280 were associated with both, reduced 2-week and 1-year survival rates (HR, 5.44; 95% CI, 1.23-24.10; p 0.026 and HR, 5.09; 95% CI, 1.95-13.26; p 0.001). DISCUSSION: Presence of serum anti-GM-CSF autoantibodies is predictive of poor outcomes, regardless of host immune status and the causative Cryptococcus species complex.

A comparative study on point cloud down-sampling strategies for deep learning-based crop organ segmentation.

The 3D crop data obtained during cultivation is of great significance to screening excellent varieties in modern breeding and improvement on crop yield. With the rapid development of deep learning, researchers have been making innovations in aspects of both data preparation and deep network design for segmenting plant organs from 3D data. Training of the deep learning network requires the input point cloud to have a fixed scale, which means all point clouds in the batch should have similar scale and contain the same number of points. A good down-sampling strategy can reduce the impact of noise and meanwhile preserve the most important 3D spatial structures. As far as we know, this work is the first comprehensive study of the relationship between multiple down-sampling strategies and the performances of popular networks for plant point clouds. Five down-sampling strategies (including FPS, RS, UVS, VFPS, and 3DEPS) are cross evaluated on five different segmentation networks (including PointNet + + , DGCNN, PlantNet, ASIS, and PSegNet). The overall experimental results show that currently there is no strict golden rule on fixing down-sampling strategy for a specific mainstream crop deep learning network, and the optimal down-sampling strategy may vary on different networks. However, some general experience for choosing an appropriate sampling method for a specific network can still be summarized from the qualitative and quantitative experiments. First, 3DEPS and UVS are easy to generate better results on semantic segmentation networks. Second, the voxel-based down-sampling strategies may be more suitable for complex dual-function networks. Third, at 4096-point resolution, 3DEPS usually has only a small margin compared with the best down-sampling strategy at most cases, which means 3DEPS may be the most stable strategy across all compared. This study not only helps to further improve the accuracy of point cloud deep learning networks for crop organ segmentation, but also gives clue to the alignment of down-sampling strategies and a specific network.

Multiomics analyses of Jining Grey goat and Boer goat reveal genomic regions associated with fatty acid and amino acid metabolism and muscle development.

Objective: Jining Grey Goat is a local Chinese goat breed that is well known for its high fertility and excellent meat quality but shows low meat production performance. Numerous studies have focused on revealing the genetic mechanism of its high fertility, but its highlighting meat quality and muscle growth mechanism still need to be studied. Methods: In this research, an integrative analysis of the genomics and transcriptomics of Jining Grey goats compared with Boer goats was performed to identify candidate genes and pathways related to the mechanisms of meat quality and muscle development. Results: Our results overlap among five genes (ABHD2, FN1, PGM2L1, PRKAG3, RAVER2) and detected a set of candidate genes associated with fatty acid metabolism (PRKAG3, HADHB, FASN, ACADM), amino acid metabolism (KMT2C, PLOD3, NSD2, SETDB1, STT3B, MAN1A2, BCKDHB, NAT8L, P4HA3) and muscle development (MSTN, PPARGC1A, ANKRD2). Several pathways have also been detected, such as the FoxO signaling pathway and Apelin signaling pathway that play roles in lipid metabolism, lysine degradation, N-glycan biosynthesis, valine, leucine and isoleucine degradation that involving with amino acid metabolism. Conclusion: The comparative genomic and transcriptomic analysis of Jining Grey Goat and Boer Goat revealed the mechanisms underlying the meat quality and meat productive performance of goats. These results provide valuable information for future breeding in goats.

Diagnostic Laboratory Features and Performance of an Aspergillus IgG Lateral Flow Assay in a Chronic Pulmonary Aspergillosis Cohort.

Chronic pulmonary aspergillosis (CPA) is a chronic and progressive fungal disease with high morbidity and mortality. Avoiding diagnostic delay and misdiagnosis are concerns for CPA patients. However, diagnostic practice is poorly evaluated, especially in resource-constrained areas where Aspergillus antibody testing tools are lacking. This study aimed to investigate the diagnostic laboratory findings in a retrospective CPA cohort and to evaluate the performance of a novel Aspergillus IgG lateral flow assay (LFA; Era Biology, Tianjin, China). During January 2016 and December 2021, suspected CPA patients were screened at the Center for Infectious Diseases at Huashan Hospital. A total of 126 CPA patients were enrolled. Aspergillus IgG was positive in 72.1% with chronic cavitary pulmonary aspergillosis, 75.0% with chronic necrotizing pulmonary aspergillosis, 41.7% with simple aspergilloma, and 30.3% with Aspergillus nodule(s). The cavitary CPA subtypes had significantly higher levels of Aspergillus IgG. Aspergillus IgG was negative in 52 patients, who were finally diagnosed by histopathology, respiratory culture, and metagenomic next-generation sequencing (mNGS). Sputum culture was positive in 39.3% (42/107) of patients and Aspergillus fumigatus was the most common species (69.0%, 29/42). For CPA cohort versus controls, the sensitivity and specificity of the LFA were 55.6% and 92.7%, respectively. In a subgroup analysis, the LFA was highly sensitive for A. fumigatus-associated chronic cavitary pulmonary aspergillosis (CCPA; 96.2%, 26/27). Given the complexity of the disease, a combination of serological and non-serological tests should be considered to avoid misdiagnosis of CPA. The novel LFA has a satisfactory performance and allows earlier screening and diagnosis of CPA patients. IMPORTANCE There are concerns on avoiding diagnostic delay and misdiagnosis for chronic pulmonary aspergillosis due to its high morbidity and mortality. A proportion of CPA patients test negative for Aspergillus IgG. An optimal diagnostic strategy for CPA requires in-depth investigation based on real-world diagnostic practice, which has been rarely discussed. We summarized the clinical and diagnostic laboratory findings of 126 CPA patients with various CPA subtypes. Aspergillus IgG was the most sensitive test for diagnosing CPA. However, it was negative in 52 patients, who were finally diagnosed by non-serological tests, including biopsy, respiratory culture, and metagenomic next-generation sequencing. We also evaluated a novel Aspergillus IgG lateral flow assay, which showed a satisfactory performance in cavitary CPA patients and was highly specific to Aspergillus fumigatus. This study gives a full picture of the diagnostic practice for CPA patients in Chinese context and calls for early diagnosis of CPA with combined approaches.

Identifying the Soybean microRNAs Related to Phytophthora sojae Based on RNA Sequencing and Bioinformatics Analysis.

Phytophthora root rot in soybeans is caused by a pathogen called Phytophthora sojae (P. sojae), which results in a significant decrease in soybean production within affected regions. MicroRNAs (miRNAs) are a class of small non-coding RNA molecules that play a key post-transcriptional regulatory role in eukaryotes. In this paper, the miRNAs that respond to P. sojae were analyzed from the gene level to complement the study of molecular resistance mechanisms in soybean. The study utilized high-throughput sequencing of soybean data to predict miRNAs that respond to P. sojae, analyze their specific functions, and verify regulatory relationships using qRT-PCR. The results showed that the miRNAs in soybean respond to P. sojae infection. MiRNAs can be transcribed independently, suggesting the presence of transcription factor binding sites in the promoter regions. Additionally, we performed an evolutionary analysis on conserved miRNAs that respond to P. sojae. Finally, we investigated the regulatory relationships among miRNAs, genes, and transcription factors, and identified five regulatory patterns. These findings lay the groundwork for future studies on the evolution of miRNAs responsive to P. sojae.

The Antibiotics Degradation and Its Mechanisms during the Livestock Manure Anaerobic Digestion.

Antibiotics are administered to livestock at subtherapeutic levels to promote growth, and their degradation in manure is slow. High antibiotic concentrations can inhibit bacterial activity. Livestock excretes antibiotics via feces and urine, leading to their accumulation in manure. This can result in the propagation of antibiotic-resistant bacteria and antibiotic resistance genes (ARGs). Anaerobic digestion (AD) manure treatment technologies are gaining popularity due to their ability to mitigate organic matter pollution and pathogens, and produce methane-rich biogas as renewable energy. AD is influenced by multiple factors, including temperature, pH, total solids (TS), substrate type, organic loading rate (OLR), hydraulic retention time (HRT), intermediate substrates, and pre-treatments. Temperature plays a critical role, and thermophilic AD has been found to be more effective in reducing ARGs in manure compared to mesophilic AD, as evidenced by numerous studies. This review paper investigates the fundamental principles of process parameters affecting the degradation of ARGs in anaerobic digestion. The management of waste to mitigate antibiotic resistance in microorganisms presents a significant challenge, highlighting the need for effective waste management technologies. As the prevalence of antibiotic resistance continues to rise, urgent implementation of effective treatment strategies is necessary.

Shifts in bacterial diversity characteristics during the primary and secondary fermentation stages of bio-compost inoculated with effective microorganisms agent.

Microbial inoculation was an effective way to improve product quality of composting and solve traditional composting shortage. However, the effect mechanism of microbial inoculation on compost microorganisms remains unclear. Here, Shifts in bacterial community, metabolic function and co-occurrence network during the primary and secondary fermentation stages of bio-compost inoculated with effective microorganisms (EM) agent were analyzed by high-throughput sequencing and network analysis. Microbial inoculation promoted organic carbon transformation in early stage of secondary fermentation (days 27 to 31). The beneficial biocontrol bacteria were main dominant genera at the second fermentation stage. Microbial inoculation can be good for the survival of beneficial bacteria. Inoculation with microbes promoted amino acid, carbohydrate and lipid metabolism, and inhibited energy metabolism and citrate cycle (TCA cycle). Microbial inoculation could enhance complexity of bacterial network and enhance mutual cooperation among bacteria during composting.

Diagnostic performance of noncultural methods for central nervous system aspergillosis.

BACKGROUND: Central nervous system (CNS) aspergillosis is an uncommon but fatal disease, the diagnosis of which is still difficult. OBJECTIVES: We aim to explore the diagnositic performance of noncultural methods for CNS aspergillosis. METHODS: In this retrospective study, all pathologically confirmed rhinosinusitis patients in whom cerebrospinal fluid (CSF) galactomannan (GM) test and metagenomic next-generation sequencing (mNGS) had been performed were included. We evaluated the diagnostic performances of CSF GM optical density indexes (ODI) at different cut-off values and compared performance with mNGS in patients with and without CNS aspergillosis, as well as in patients with different manifestations of CNS aspergillosis. RESULTS: Of the 21 proven and probable cases, one had positive culture result, five had positive mNGS results and 10 had a CSF GM ODI of >0.7. Sample concordance between mNGS and GM test was poor, but best diagnostic performance was achieved by combination of GM test (ODI of >0.7) and mNGS, which generated a sensitivity of 61.9% and specificity of 82.6%. Further investigation of combination diagnostic performances in different kind of CNS aspergillosis was also conducted. Lowest sensitivity (42.9%) was identified in abscess group, while increased sensitivity (60.0%) was achieved in abscess with encephalitis groups. Combination test exhibited the best performance for encephalitis patients who had only CSF abnormalities, in whom the sensitivity and specificity were 77.8% and 82.6%, respectively. CONCLUSIONS: In conclusion, combination of these two tests might be useful for diagnosis of CNS aspergillosis associated with fungal rhinosinusitis, especially in encephalitis patients.

Induction therapy with high-dose fluconazole plus flucytosine for human immunodeficiency virus-uninfected cryptococcal meningitis patients: Feasible or not?

BACKGROUND: Cryptococcal meningitis (CM) is increasingly recognised in human immunodeficiency virus (HIV)-uninfected patients with high mortality. The efficacy and safety profiles of induction therapy with high-dose fluconazole plus flucytosine remain unclear. METHODS: HIV-uninfected CM patients who received high-dose fluconazole (800 mg/d) for initial therapy in Huashan Hospital were included in this retrospective study from January 2013 to December 2018. Efficacy and safety of initial therapy, clinical outcomes and risk factors were evaluated. RESULTS: Twenty-seven (71.1%) patients who received high-dose fluconazole with flucytosine combination therapy and 11 (28.9%) having fluconazole alone for induction therapy were included. With a median duration of 42 days (IQR, 28-86), the successful response rate of initial therapy was 76.3% (29/38), while adverse drug reactions occurred in 14 patients (36.8%). The rate of persistently positive cerebrospinal fluid (CSF) culture results was 30.6% at 2 weeks, which was significantly associated with CSF CrAg titre >1:1280 (OR 9.56; 95% CI 1.40-103.65; p = .010) and CSF culture of Cryptococcus >3.9 log10 CFU/ml (OR 19.20; 95% CI 1.60-920.54; p = .011), and decreased to 8.6% at 4 weeks. One-year mortality was 15.8% (6/38), and low serum albumin (35 g/L) was found as an independent risk factor for 1-year mortality (HR 6.31; 95% CI 1.150-34.632; p = .034). CONCLUSIONS: Induction therapy with high-dose fluconazole (800 mg/d), combined with flucytosine, effectively treated HIV-uninfected CM and was well tolerated. Long-term fluconazole treatment with continued monitoring is beneficial for patients with persistent infection.

Exploring Soybean Flower and Pod Variation Patterns During Reproductive Period Based on Fusion Deep Learning.

The soybean flower and the pod drop are important factors in soybean yield, and the use of computer vision techniques to obtain the phenotypes of flowers and pods in bulk, as well as in a quick and accurate manner, is a key aspect of the study of the soybean flower and pod drop rate (PDR). This paper compared a variety of deep learning algorithms for identifying and counting soybean flowers and pods, and found that the Faster R-CNN model had the best performance. Furthermore, the Faster R-CNN model was further improved and optimized based on the characteristics of soybean flowers and pods. The accuracy of the final model for identifying flowers and pods was increased to 94.36 and 91%, respectively. Afterward, a fusion model for soybean flower and pod recognition and counting was proposed based on the Faster R-CNN model, where the coefficient of determinationR2 between counts of soybean flowers and pods by the fusion model and manual counts reached 0.965 and 0.98, respectively. The above results show that the fusion model is a robust recognition and counting algorithm that can reduce labor intensity and improve efficiency. Its application will greatly facilitate the study of the variable patterns of soybean flowers and pods during the reproductive period. Finally, based on the fusion model, we explored the variable patterns of soybean flowers and pods during the reproductive period, the spatial distribution patterns of soybean flowers and pods, and soybean flower and pod drop patterns.

Cerebrospinal fluid cytokine and chemokine patterns correlate with prognosis of HIV-uninfected cryptococcal meningitis: A prospective observational study.

The cerebrospinal fluid (CSF) immune responses in HIV-uninfected cryptococcal meningitis (CM) have not been well studied. In this study, we aimed to explore the phenotype of CSF immune response during the course of disease and to examine relationships between phenotypes and disease severity. We profiled the CSF immune response in 128 HIV-uninfected CM and 30 pulmonary cryptococcosis patients using a 27-plex Luminex cytokine kit. Principal component analyses (PCA) and logistic regression model were performed. Concentrations of 23 out of 27 cytokines and chemokines in baseline CSF were significantly elevated in CM patients compared with pulmonary cryptococcosis cases. In CM patients with Cryptococcus neoformans infection, IL-1ra, IL-9, and VEGF were significantly elevated in immunocompetent cases. Cytokine levels usually reached peaks within the first 2 weeks of antifungal treatment and gradually decreased over time. PCA demonstrated a co-correlated CSF cytokine and chemokine response consisting of Th1, Th2, and Th17 type cytokines. Prognostic analysis showed that higher scores for the PCs loading pro-inflammatory cytokines, IFN-γ, TNF-α, and IL-12; and anti-inflammatory cytokine, IL-4; and chemokines, Eotaxin, FGF-basis, and PDGF-bb; as well as lower scores for the PCs loading RANTES were associated with disease severity, as defined by a Glasgow Coma Scale of <15 or death. In conclusion, combined inflammatory responses in CSF involving both pro- and anti-inflammatory cytokines and chemokines are upregulated in HIV-uninfected CM, and associated with disease severity.

Construction of Chromosome Segment Substitution Lines and Inheritance of Seed-Pod Characteristics in Wild Soybean.

Genetic populations provide the basis for genetic and genomic research, and chromosome segment substitution lines (CSSLs) are a powerful tool for the fine mapping of quantitative traits, new gene mining, and marker-assisted breeding. In this study, 213 CSSLs were obtained by self-crossing, backcrossing, and marker-assisted selection between cultivated soybean (Glycine max [L.] Merr.) variety Suinong14 (SN14) and wild soybean (Glycine soja Sieb. et Zucc.) ZYD00006. The genomes of these 213 CSSLs were resequenced and 580,524 single-nucleotide polymorphism markers were obtained, which were divided into 3,780 bin markers. The seed-pod-related traits were analyzed by quantitative trait locus (QTL) mapping using CSSLs. A total of 170 QTLs were detected, and 32 QTLs were detected stably for more than 2 years. Through epistasis analysis, 955 pairs of epistasis QTLs related to seed-pod traits were obtained. Furthermore, the hundred-seed weight QTL was finely mapped to the region of 64.4 Kb on chromosome 12, and Glyma.12G088900 was identified as a candidate gene. Taken together, a set of wild soybean CSSLs was constructed and upgraded by a resequencing technique. The seed-pod-related traits were studied by bin markers, and a candidate gene for the hundred-seed weight was finely mapped. Our results have revealed the CSSLs can be an effective tool for QTL mapping, epistatic effect analysis, and gene cloning.

Automatic and Accurate Acquisition of Stem-Related Phenotypes of Mature Soybean Based on Deep Learning and Directed Search Algorithms.

The stem-related phenotype of mature stage soybean is important in soybean material selection. How to improve on traditional manual methods and obtain the stem-related phenotype of soybean more quickly and accurately is a problem faced by producers. With the development of smart agriculture, many scientists have explored soybean phenotypes and proposed new acquisition methods, but soybean mature stem-related phenotype studies are relatively scarce. In this study, we used a deep learning method within the convolutional neural network to detect mature soybean stem nodes and identified soybean structural features through a novel directed search algorithm. We subsequently obtained the pitch number, internodal length, branch number, branching angle, plant type spatial conformation, plant height, main stem length, and new phenotype-stem curvature. After 300 epochs, we compared the recognition results of various detection algorithms to select the best. Among them, YOLOX had a maximum average accuracy (mAP) of 94.36% for soybean stem nodes and scale markers. Through comparison of the phenotypic information extracted by the directed search algorithm with the manual measurement results, we obtained the Pearson correlation coefficients, R, of plant height, pitch number, internodal length, main stem length, stem curvature, and branching angle, which were 0.9904, 0.9853, 0.9861, 0.9925, 0.9084, and 0.9391, respectively. These results show that our algorithm can be used for robust measurements and counting of soybean phenotype information, which can reduce labor intensity, improve efficiency, and accelerate soybean breeding.

Spatial heterogeneity of particulate organic matter for the sorption of ciprofloxacin at the microstructure scale.

Particulate organic matter (POM) is a major antibiotic sorbent of the active soil organic carbon pool. Until now, the spatial heterogeneity of POM for ciprofloxacin (CFC) sorption at the microstructure scale has not been quantified. To our knowledge, this is the first study that combines a batch sorption experiment, NanoSIMS, and a 13C isotopic tracer to expound the distribution characteristics of CFC and the dominant sorption components of POM. Four POMs separated from soils (wetland, oil waste field, and farmlands) were utilized to study the sorption mechanisms using batch experiments. POM separated from the wetland was utilized for further study at the microstructure scale. The results revealed that the POM had a great CFC sorption capacity ranging from 65.20 mg g-1 to 77.51 mg g-1. Both the kinetics and NanoSIMS results showed that the sorption mechanisms included surface distribution and intra-particle diffusion. The microstructural distribution characteristics exhibited a marginal accumulation tendency and a surface accumulation effect. A combination of the NanoSIMS with the pH and salinity results explained that CFC adsorption was dominated by the organic components of POM. Overall, the present study demonstrates that the characteristics and organic components of the POM played a decisive role in the CFC-POM interactions. This study provides the first evidence of the vector potential of CFC rereleased into the environment during the POM turnover process.

Automatic and Accurate Calculation of Rice Seed Setting Rate Based on Image Segmentation and Deep Learning.

The rice seed setting rate (RSSR) is an important component in calculating rice yields and a key phenotype for its genetic analysis. Automatic calculations of RSSR through computer vision technology have great significance for rice yield predictions. The basic premise for calculating RSSR is having an accurate and high throughput identification of rice grains. In this study, we propose a method based on image segmentation and deep learning to automatically identify rice grains and calculate RSSR. By collecting information on the rice panicle, our proposed image automatic segmentation method can detect the full grain and empty grain, after which the RSSR can be calculated by our proposed rice seed setting rate optimization algorithm (RSSROA). Finally, the proposed method was used to predict the RSSR during which process, the average identification accuracy reached 99.43%. This method has therefore been proven as an effective, non-invasive method for high throughput identification and calculation of RSSR. It is also applicable to soybean yields, as well as wheat and other crops with similar characteristics.

Identification of Finely Mapped Quantitative Trait Locus and Candidate Gene Mining for the Three-Seeded Pod Trait in Soybean.

The three-seeded pod number is an important trait that positively influences soybean yield. Soybean variety with increased three-seeded pod number contributes to the seed number/plant and higher yield. The candidate genes of the three-seeded pod may be the key for improving soybean yield. In this study, identification and validation of candidate genes for three-seeded pod has been carried out. First, a total of 36 quantitative trait locus (QTL) were detected from the investigation of recombinant inbred lines including 147 individuals derived from a cross between Charleston and Dongning 594 cultivars. Five consensus QTLs were integrated. Second, an introgressed line CSSL-182 carrying the target segment for the trait from the donor parent was selected to verify the consensus QTL based on its phenotype. Third, a secondary group was constructed by backcrossing with CSSL-182, and two QTLs were confirmed. There were a total of 162 genes in the two QTLs. The mining of candidate genes resulted in the annotation of eight genes with functions related to pod and seed sets. Finally, haplotype analysis and quantitative reverse transcriptase real-time PCR were carried to verify the candidate genes. Four of these genes had different haplotypes in the resource group, and the differences in the phenotype were highly significant. Moreover, the differences in the expression of the four genes during pod and seed development were also significant. These four genes were probably related to the development process underlying the three-seeded pod in soybean. Herein, we discuss the past and present studies related to the three-seeded pod trait in soybean.

Assessment of Cavitation Erosion in a Water-Jet Pump Based on the Erosive Power Method.

Cavitation affects the performance of water-jet pumps. Cavitation erosion will appear on the surface of the blade under long-duration cavitation conditions. The cavitation evolution under specific working conditions was simulated and analyzed. The erosive power method based on the theory of macroscopic cavitation was used to predict cavitation erosion. The result shows that the head of the water-jet pump calculated using the DCM-SST turbulence model is 12.48 m. The simulation error of the rated head is 3.8%. The cavitation structure of tip leakage vortex was better captured. With the decrease of the net positive suction head, the position where the severe cavitation appears in the impeller domain gradually moves from the tip to the root. The erosion region obtained by the cavitation simulation based on the erosive power method is similar to the practical erosion profile in engineering. As the net positive suction head decreases, the erodible area becomes larger, and the erosion intensity increases.

[Isolation, identification and heavy metals biosorption of a lead and cadmium-tolerant strain].

Adding biological passivation agent during composting is one of the most effective ways to reduce the toxicity of heavy metals in contaminated livestock manure. To further improve biological passivation, we obtained a strain with high-heavy metal compounds tolerance to passivate heavy-metal contaminated manure and to characterize heavy-metal biosorption. High-tolerance microorganisms for lead and cadmium were isolated and screened from swine manure composting samples. The strain was identified by its morphology and molecular biology. After the influence of different pH, temperature and salt concentrations on growth of the strain were investigated, the optimal growth conditions were obtained for further analysis of its biosorption characteristics of lead and cadmium. The bacterium with tolerance to lead and cadmium termed SC19 was obtained, whose lead resistance was 600 mg/L and cadmium resistance was 120 mg/L. The isolate was further identified as Cedecea sp., and then its optimum pH was 7.0, temperature was 37 °C, and salt concentration was 0.5%. Lead removal was highest after 30 min of adsorption by the SC19 strain cultured for the stationary phase 36 h, and the maximum removal rate and biosorption capacity of lead were 60.7% and 329.13 mg/g, respectively. Meanwhile, cadmium removal was highest after 30 min of adsorption by the strain cultured for the logarithmic phase 8 h, and the maximum removal rate and biosorption capacity of cadmium were 51.0% and 126.19 mg/g, respectively. Fourier Transform InfraRed (FT-IR) results revealed that the biosorption process mainly happened on the surface of SC19 cell and many active groups on the cell surface could chelate the Pb²âº and Cd²âº. By comprehensive comparison, it was showed that strain SC19 shared a certain capacity of Pb²âº and Cd²âº biosorption, and the bacterium provided precious microbial germplasm resources for biological passivation of heavy metal contaminated manure.

[Effects of microbial agents on bacterial community composition during swine manure composting]. / å¾®ç”Ÿç‰©èŒå‰‚å¯¹çŒªç²ªå †è‚¥ä¸­ç»†èŒç¾¤è½ç»“æž„çš„å½±å“.

The process of swine manure and wheat straw aerobic composting was examined, with exogenous microbial agents being added in treatment group. The physicochemical properties were measured by conventional methods, and bacterial community characteristics were investigated by high throughput sequencing analysis. Exogenous microbial agents increased high-temperature duration, reduced pH value at the end of fermentation stage, augmented total nitrogen content, reduced C/N ratio. Results from principal component analysis showed that microbial agents affected the stability of bacterial community during composting. At the phylum level, the relative abundance of Firmicutes, Proteobacteria, and Chloroflexi was higher in the treatment group. At the class level, the relative abundance of Clostridia, Alphaproteobacteria, and Gammaproteobacteria in the treatment group were higher at the mesophilic and thermophilic phases. At the family level, Peptostreptococcaceae, Clostridiaceae_1, and Halanaerobiaceae of the Clostridia and Micromonosporaceae in the treatment group were higher at the mesophilic and thermophilic phases. Halocella was significantly positively correlated with exogenous microbial agents, while Ammoniibacillus was significantly negatively correlated with it. It suggested that microbial agents significantly changed the physicochemical properties and bacterial community structure during swine composting.

Responses of Soybean Genes in the Substituted Segments of Segment Substitution Lines Following a Xanthomonas Infection.

Bacterial blight, which is one of the most common soybean diseases, is responsible for considerable yield losses. In this study, a novel Xanthomonas vasicola strain was isolated from the leaves of soybean plants infected with bacterial blight under field conditions. Sequencing the X. vasicola genome revealed type-III effector-coding genes. Moreover, the hrpG deletion mutant was constructed. To identify the soybean genes responsive to HrpG, two chromosome segment substitution lines (CSSLs) carrying the wild soybean genome, but with opposite phenotypes following Xanthomonas inoculations, were used to analyze gene expression networks based on RNA sequencing at three time points after inoculations with wild-type Xanthomonas or the hrpG deletion mutant. To further identify the hub genes underlying soybean responses to HrpG, the genes located on the substituted chromosome segments were examined. Finally, a combined analysis with the QTLs for resistance to Xanthomonas identified 35 hub genes in the substituted chromosomal segments that may help regulate soybean responses to Xanthomonas and HrpG. Furthermore, two candidate genes in the CSSLs might play pivotal roles in response to Xanthomonas.