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Synergistic effects of herbicidal rice husks and pyrolysis liquid from waste wood-based panels were studied relative to the germination of three common weed species in a tea plantation. The pyrolysis liquid consisted of various organic acids, phenols, alcohols, ketones, and nitrogen compounds, with organic acids accounting for up to 46.8% of the content. Three seeds of smooth crabgrass (Digitaria ischaemum), annual fleabane (Erigeron annuus), and hedge-parsley (Torilis scabra (Thunb.) DC) were treated with 2000 and 4000 L/ha of pyrolysis liquid, as well as 50, 100, and 200 m3/ha of pyrolysis liquid as a cover material. The pre-emergence herbicide tests demonstrated that the combination of rice husks and pyrolysis liquid effectively inhibited seed germination and aboveground biomass of the weeds. The weed control effect increased with the increase in the amount applied. The combination of rice husks (200 m3/ha) and pyrolysis liquid (4000 L/ha) exhibited the highest weed control efficacy, reducing seed germination and aboveground biomass by 69.1%, 79.5%, and 97.6% for smooth crabgrass, annual fleabane, and hedge-parsley, respectively. Discarded furniture materials and rice husks can both be used as sustainable materials for weed control, offering a fresh approach to the efficient utilization of waste materials.

Background: Hepatic immune tolerance might contribute to the development of therapeutic resistance to immunotherapy. However, addressing this issue is challenging since the efficacy of immunotherapy in the context of liver metastasis (LM) remains poorly studied. Here, we aimed to establish an LM common immune feature (LMCIF) score to quantify the characteristics of LM immunotolerance across cancer types for assisting clinical disease management. Methods: Large-scale clinical data were collected to identify the prognosis of LM. Multi-omics datasets of metastatic cancers with LM special immune-related pathways (LMSIPs) from the Molecular Signatures Database (MSigDB) were used to obtain an LMCIF cluster. Based on differential expression genes (DEGs), a novel LMCIF score for the LMCIF cluster was constructed. In addition, multi-omics, and immunohistochemistry (IHC) data from the public and in-house cohorts were used to explore the features of LM, and LMCIF score. Results: Patients with LM had a worse prognosis and significantly lower infiltration of immune cells than patients with metastasis to other organs when analyzed with combined clinical and RNA sequencing data. After extracting the LMCIF cluster from 373 samples by utilizing 29 LMSIPs and validating them in a microarray cohort, an LMCIF score was established to confirm the role of the immunosuppressive environment as a contributor to the poor prognosis of LM across cancer types. Moreover, this LMCIF score could be used to predict the immune response of cancer patients undergoing immunotherapy. Finally, we identified that the majority of the 31 LMCIF genes exhibited a negative correlation with TME cells in LM patients, one of them, KRT19, which possessed the strongest positive correlation with LMCIF score, was confirmed to have an immunosuppressive effect through IHC analysis. Conclusions: Our results suggest that LM across cancer types share similar immunological profiles that induce immunotolerance and escape from immune monitoring. The novel LMCIF score represents a common liver metastasis immune cluster for predicting immunotherapy response, the results of which might benefit clinical disease management.

Abstract Background Neutrophils play an essential role in Alzheimer’s disease (AD) pathology. However, the extent of their heterogeneity remains poorly explored, particularly in the context of developing novel therapies targeting these cells. Results We investigate the population structure of neutrophils purified from peripheral blood samples of AD mice. Utilizing single cell RNA sequencing, we comprehensively map neutrophil populations into six distinct clusters and find that the Neu-5 subset is specially enriched in AD mice. This subset exhibits fewer specific granules and a lower mature score. Gene ontology (GO) analysis reveals that genes involved in cytokine-mediated signaling are downregulated in the Neu-5 cluster. Furthermore, we identify the Ccrl2 gene is specifically upregulated in this subgroup, which is confirmed by flow cytometry in AD mice. Finally, immunohistochemical staining indicates that CCRL2 protein is increased in the brains of AD mice. Conclusions We identify a unique CCRL2 positive neutrophil cluster, that is specifically enriched in the peripheral blood of AD mice.

Benefited from its high process feasibility and controllable costs, binary-metal layered structured LiNi0.8Mn0.2O2 (NM) can effectively alleviate the cobalt supply crisis under the surge of global electric vehicles (EVs) sales, which is considered as the most promising next-generation cathode material for lithium-ion batteries (LIBs). However, the lack of deep understanding on the failure mechanism of NM has seriously hindered its application, especially under the harsh condition of high-voltage without sacrifices of reversible capacity. Herein, single-crystal LiNi0.8Mn0.2O2 is selected and compared with traditional LiNi0.8Co0.1Mn0.1O2 (NCM), mainly focusing on the failure mechanism of Co-free cathode and illuminating the significant effect of Co element on the Li/Ni antisite defect and dynamic characteristic. Specifically, the presence of high Li/Ni antisite defect in NM cathode easily results in the extremely dramatic H2/H3 phase transition, which exacerbates the distortion of the lattice, mechanical strain changes and exhibits poor electrochemical performance, especially under the high cutoff voltage. Furthermore, the reaction kinetic of NM is impaired due to the absence of Co element, especially at the single-crystal architecture. Whereas, the negative influence of Li/Ni antisite defect is controllable at low current densities, owing to the attenuated polarization. Notably, Co-free NM can exhibit better safety performance than that of NCM cathode. These findings are beneficial for understanding the fundamental reaction mechanism of single-crystal Ni-rich Co-free cathode materials, providing new insights and great encouragements to design and develop the next generation of LIBs with low-cost and high-safety performances.

Peanut (Arachis hypogaea L.) is a globally important oil crop. Web blotch is one of the most important foliar diseases affecting peanut, which results in serious yield losses worldwide. Breeding web blotch-resistant peanut varieties is the most effective and economically viable method for minimizing yield losses due to web blotch. In the current study, a bulked segregant analysis with next-generation sequencing was used to analyze an F2:3 segregating population and identify candidate loci related to web blotch resistance. Based on the fine-mapping of the candidate genomic interval using kompetitive allele-specific PCR (KASP) markers, we identified a novel web blotch resistance-related locus spanning approximately 169 kb on chromosome 16. This region included four annotated genes, of which only Arahy.35VVQ3 had a non-synonymous single nucleotide polymorphism in the coding region between the two parents. Two markers (Chr.16.12872635 and Chr.16.12966357) linked to this gene were shown to be co-segregated with the resistance of peanut web blotch by 72 randomly selected recombinant inbred lines (RIL), which could be used in marker-assisted breeding of resistant peanut varieties.

ABSTRACT To monitor the resistance rate and gain a deeper understanding of the resistance mechanisms, we conducted over a 2-year surveillance focusing on the Klebsiella pneumoniae associated with the clinical usage of ceftazidime-avibactam (CZA) in a teaching hospital. A total of 4,641 K. pneumoniae isolates were screened to identify the CZA resistance through antimicrobial susceptibility testing. Comprehensive analyses, including homology analysis, conjugation experiments, clone assays, and whole genome sequencing, were furtherly performed on the CZA-resistant strains. In total, four CZA-resistant K. pneumoniae (CZA-R-Kp) strains were separated from four patients, in which three of them received CZA treatment during the hospitalization, accounting for a 4% (3/75) resistance development rate of K. pneumoniae under CZA stress. All CZA-R-Kp isolates were found to possess variants of blaKPC-2. The identified mutations included blaKPC-33, blaKPC-86, and a novel variant designated as blaKPC-129, all of which were located in the Ω loop of the KPC enzyme. These mutations were found to impact the amino acid sequence and spatial structure of the enzyme’s active center, consequently affecting KPC carbapenemase activity. This study underscores the importance of active surveillance to monitor the emergence of resistance to CZA, highlighting the need for ongoing research to develop effective strategies for combating antimicrobial resistance. Understanding the mechanisms behind resistance is crucial in maintaining the efficacy of CZA, a vital tool in the battle against multidrug-resistant infections.IMPORTANCEAs an effective drug for the treatment of carbapenem-resistant Klebsiella pneumoniae, ceftazidime-avibactam (CZA) began to develop resistance in recent years and showed an increasing trend. In order to effectively monitor the resistance rate of CZA and understand its resistance mechanism, we monitored K. pneumoniae for more than 2 years to find CZA-resistant strains. Through comprehensive analysis of the selected CZA-resistant strains, it was found that all the CZA-resistant strains had mutation, which could affect the activity of KPC carbapenemase. This study highlights the importance of proactive surveillance to monitor the emergence of CZA resistance, which highlights the need for ongoing research to develop effective strategies to combat antimicrobial resistance. Understanding the mechanisms behind resistance is critical to maintaining the effectiveness of CZA, an important tool in the fight against multidrug-resistant infections.

The global spread of carbapenem-resistant Enterobacterales, particularly carbapenem-resistant Klebsiella pneumoniae (CRKP), poses a severe and ongoing public health threat because of high rates of illness and death (1). The production [...]

Abstract Background This study aims to decipher the genetic basis governing yield components and quality attributes of peanuts, a critical aspect for advancing molecular breeding techniques. Integrating genotype re-sequencing and phenotypic evaluations of seven yield components and two grain quality traits across four distinct environments allowed for the execution of a genome-wide association study (GWAS). Results The nine phenotypic traits were all continuous and followed a normal distribution. The broad heritability ranged from 88.09 to 98.08%, and the genotype-environment interaction effects were all significant. There was a highly significant negative correlation between protein content (PC) and oil content (OC). The 10× genome re-sequencing of 199 peanut accessions yielded a total of 631,988 high-quality single nucleotide polymorphisms (SNPs), with 374 significant SNP loci identified in association with the nine traits of interest. Notably, 66 of these pertinent SNPs were detected in multiple environments, and 48 of them were linked to multiple traits of interest. Five loci situated on chromosome 16 (Chr16) exhibited pleiotropic effects on yield traits, accounting for 17.64–32.61% of the observed phenotypic variation. Two loci on Chr08 were found to be strongly associated with protein and oil contents, accounting for 12.86% and 14.06% of their respective phenotypic variations, respectively. Linkage disequilibrium (LD) block analysis of these seven loci unraveled five nonsynonymous variants, leading to the identification of one yield-related candidate gene and two quality-related candidate genes. The correlation between phenotypic variation and SNP loci in these candidate genes was validated by Kompetitive allele-specific PCR (KASP) marker analysis. Conclusions Overall, molecular markers were developed for genetic loci associated with yield and quality traits through a GWAS investigation of 199 peanut accessions across four distinct environments. These molecular tools can aid in the development of desirable peanut germplasm with an equilibrium of yield and quality through marker-assisted breeding.

Abstract Background Bacterial wilt caused by Ralstonia solanacearum severely affects peanut (Arachis hypogaea L.) yields. The breeding of resistant cultivars is an efficient means of controlling plant diseases. Therefore, identification of resistance genes effective against bacterial wilt is a matter of urgency. The lack of a reference genome for a resistant genotype severely hinders the process of identification of resistance genes in peanut. In addition, limited information is available on disease resistance-related pathways in peanut. Results Full-length transcriptome data were used to generate wilt-resistant and -susceptible transcript pools. In total, 253,869 transcripts were retained to form a reference transcriptome for RNA-sequencing data analysis. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis of differentially expressed genes revealed the plant-pathogen interaction pathway to be the main resistance-related pathway for peanut to prevent bacterial invasion and calcium plays an important role in this pathway. Glutathione metabolism was enriched in wilt-susceptible genotypes, which would promote glutathione synthesis in the early stages of pathogen invasion. Based on our previous quantitative trait locus (QTL) mapping results, the genes arahy.V6I7WA and arahy.MXY2PU, which encode nucleotide-binding site-leucine-rich repeat receptor proteins, were indicated to be associated with resistance to bacterial wilt. Conclusions This study identified several pathways associated with resistance to bacterial wilt and identified candidate genes for bacterial wilt resistance in a major QTL region. These findings lay a foundation for investigation of the mechanism of resistance to bacterial wilt in peanut.

Abstract Reaumuria songarica, a drought‐resistant shrub, is widely distributed and plays a crucial role in the northern deserts of China. It is a key species for desert rehabilitation and afforestation efforts. Using the Maxent model to predict suitable planting areas for R. songarica is an important strategy for combating desertification. With 184 occurrence points of R. songarica and 13 environmental variables, the optimized Maxent model has identified the main limiting factors for its distribution. Distribution patterns and variation trends of R. songarica were projected for current and future climates (2030s, 2050s, 2070s, and 2090s) and different scenarios (ssp_126, ssp_370, and ssp_585). Results show that setting parameters to RM (regulation multiplier) = 4 and FC (feature combination) = LQHPT yields a model with good accuracy and high reliability. Currently, R. songarica is primarily suitable for desert control in eight provinces and autonomous regions, including Inner Mongolia, Xinjiang, Qinghai, and Ningxia. The total suitable planting area is 148.80 × 104 km2, representing 15.45% of China's land area. Precipitation (Precipitation of the wettest month, Precipitation of the warmest quarter, and Annual precipitation) and Ultraviolet‐B seasonality are the primary environmental factors limiting the growth and distribution of R. songarica. Mean temperature of the warmest quarter is the primary factor driving changes in the distribution of suitable areas for R. songarica under future climate scenarios. In future climate scenarios, the suitable planting area of R. songarica will shrink, and the distribution center will shift towards higher latitude, potentially indicate further desertification. The area of highly suitable habitat has increased, while moderately and less suitable habitat areas have decreased. Increased precipitation within R. songarica's water tolerance range is favorable for its growth and reproduction. With changes in the suitable cultivation area for R. songarica, priority should be given to exploring and utilizing its germplasm resources. Introduction and cultivation can be conducted in expanding regions, while scientifically effective measures should be implemented to protect germplasm resources in contracting regions. The findings of this study provide a theoretical basis for addressing desertification resulting from climate change and offer practical insights for the development, utilization, introduction, and cultivation of R. songarica germplasm resources.

Summary: Breast cancer (BC) is currently the most prevalent malignancy worldwide, and finding effective non-invasive biomarkers for routine clinical detection of BC remains a significant challenge. Here, we performed non-targeted and targeted metabolomics analysis on the screening, training and validation cohorts of serum samples from 1,947 participants. A metabolite biomarker model including glutamate, erythronate, docosahexaenoate, propionylcarnitine, and patient’s age was established for detecting BC. This model demonstrated better diagnostic performance than carbohydrate antigen 15-3 (CA15-3) and carcinoembryonic antigen (CEA) alone in discriminating BC from healthy controls both in the training and validation cohorts [area under the curve (AUC), 0.954; sensitivity, 87.1% and specificity, 93.5% for the training cohort and 0.834, 68.3%, and 85.2%, respectively, for the validation cohort 1]. This study has established a noninvasive approach for the detection of BC, which shows potential as a suitable supplement to the clinical screening methods currently employed for BC.

BackgroundWe aimed to elucidate the causal relationship between plasma metabolites and the vulnerability to Osteoarthritis (OA), encompassing both hip OA and knee OA.MethodsWe conducted a two-way two-sample Mendelian randomization (MR) analysis to investigate the association of 1,400 plasma metabolites with OA. The Inverse Variance Weighted (IVW) model served as the primary two-sample MR Analysis method, with supplementary analysis using the Weighted Median (WM) and MR Egger methods. To ensure the robustness of our findings, sensitivity analyses were performed, incorporating Cochran’s Q test, MR-Egger intercept test, MR-PRESSO, and Leave-One-Out analyses. To validate the identified metabolites, we utilized the Steiger test and linkage disequilibrium score regression.ResultsA total of 94 plasma metabolites were associated with osteoarthritis, with 60 associated with hip OA and 106 associated with knee OA. IVW analysis revealed that tryptophan levels showed the strongest positive association with hip OA (OR [95% CI]: 1.119 [1.024, 1.223]), while X-24757 levels exhibited the highest positive association with knee osteoarthritis (OR [95% CI]: 1.095 [1.032, 1.162]). Ethylparaben sulfate levels were found to have the greatest positive association with hip OA (OR [95% CI]: 1.118 [1.015, 1.231]). Notably, the plasma metabolite X-2475 showed a strong robust random effect across all three types of osteoarthritis. Metabolic pathway analysis revealed that the pathogenesis of osteoarthritis in the hip was mediated by acetylarginine, specifically in four important metabolic pathways: ethanol degradation (p = 0.044), amino sugar metabolism (p = 0.090), fatty acid biosynthesis (p = 0.095), and aspartate metabolism (p = 0.097816).ConclusionThere is a significant association between tryptophan levels and the risk of hip OA, as well as X-24757 levels and the risk of knee osteoarthritis. Additionally, X-24757 levels are also linked to the risk of hip OA. Moreover, this study has identified four crucial metabolic pathways in hip osteoarthritis, which are all regulated by acetylarginine. These findings provide valuable insights into potential biomarkers for OA and highlight potential pathways for its prevention and clinical intervention.

Urban populations, especially women, are vunerable to exposure to airborne pollution, particularly inhalable particulates (PM10). Thus, more accurate measurement of PM10 levels and evaluating their health effects is critical for guiding policy to improve human health. Previous studies obtained personal PM10 with time-weighted average by air filter-based sampling (AFS), which ignores individual differences and behavioral patterns. Here, we used nasal filters instead of AFS to obtain actual inhaled PM10 under short-term exposure for urban dwelling women during a severe haze event in Beijing in 2016. The levels of six heavy metals such as As, Cd, Ni, Cr, Pb, and Co in PM10 were investigated, and carcinogenic and non-carcinogenic risks evaluated based on an adjusted US EPA health risk assessment model. The health endpoints for urban dwelling women were further assessed through an exposure-reponse model. We found that the hourly inhaled dose of PM10 obtained through the nasal filter was about 2.5–17.6 times that obtained by AFS, which also resulted in 4.41–11.30 times more morbidity than estimated by AFS (p 18.8 μg/kg·h) and heavy metals (>2.2 ng/kg·h), and these populations are therefore at greatest risk of developing non-cancer (HI = 4.16) and cancer (Rt = 7.8 × 10−3) related morbities.

Abstract Background Pod shell thickness (PST) is an important agronomic trait of peanut because it affects the ability of shells to resist pest infestations and pathogen attacks, while also influencing the peanut shelling process. However, very few studies have explored the genetic basis of PST. Results An F2 segregating population derived from a cross between the thick-shelled cultivar Yueyou 18 (YY18) and the thin-shelled cultivar Weihua 8 (WH8) was used to identify the quantitative trait loci (QTLs) for PST. On the basis of a bulked segregant analysis sequencing (BSA-seq), four QTLs were preliminarily mapped to chromosomes 3, 8, 13, and 18. Using the genome resequencing data of YY18 and WH8, 22 kompetitive allele-specific PCR (KASP) markers were designed for the genotyping of the F2 population. Two major QTLs (qPSTA08 and qPSTA18) were identified and finely mapped, with qPSTA08 detected on chromosome 8 (0.69-Mb physical genomic region) and qPSTA18 detected on chromosome 18 (0.15-Mb physical genomic region). Moreover, qPSTA08 and qPSTA18 explained 31.1–32.3% and 16.7–16.8% of the phenotypic variation, respectively. Fifteen genes were detected in the two candidate regions, including three genes with nonsynonymous mutations in the exon region. Two molecular markers (Tif2_A08_31713024 and Tif2_A18_7198124) that were developed for the two major QTL regions effectively distinguished between thick-shelled and thin-shelled materials. Subsequently, the two markers were validated in four F2:3 lines selected. Conclusions The QTLs identified and molecular markers developed in this study may lay the foundation for breeding cultivars with a shell thickness suitable for mechanized peanut shelling.

Abstract Background The visual organ plays a crucial role in sensing environmental information. However, its mucosal surfaces are constantly exposed to selective pressures from aquatic or airborne pathogens and microbial communities. Although few studies have characterized the conjunctival-associated lymphoid tissue (CALT) in the ocular mucosa (OM) of birds and mammals, little is known regarding the evolutionary origins and functions of immune defense and microbiota homeostasis of the OM in the early vertebrates. Results Our study characterized the structure of the OM microbial ecosystem in rainbow trout (Oncorhynchus mykiss) and confirmed for the first time the presence of a diffuse mucosal-associated lymphoid tissue (MALT) in fish OM. Moreover, the microbial communities residing on the ocular mucosal surface contribute to shaping its immune environment. Interestingly, following IHNV infection, we observed robust immune responses, significant tissue damage, and microbial dysbiosis in the trout OM, particularly in the fornix conjunctiva (FC), which is characterized by the increase of pathobionts and a reduction of beneficial taxa in the relative abundance in OM. Critically, we identified a significant correlation between viral-induced immune responses and microbiome homeostasis in the OM, underscoring its key role in mucosal immunity and microbiota homeostasis. Conclusions Our findings suggest that immune defense and microbiota homeostasis in OM occurred concurrently in early vertebrate species, shedding light on the coevolution between microbiota and mucosal immunity. Video Abstract