Combined assembly of long and short sequencing reads improve the efficiency of exploring the soil metagenome.

BACKGROUND: Advances in DNA sequencing technologies have transformed our capacity to perform life science research, decipher the dynamics of complex soil microbial communities and exploit them for plant disease management. However, soil is a complex conglomerate, which makes functional metagenomics studies very challenging. RESULTS: Metagenomes were assembled by long-read (PacBio, PB), short-read (Illumina, IL), and mixture of PB and IL (PI) sequencing of soil DNA samples were compared. Ortholog analyses and functional annotation revealed that the PI approach significantly increased the contig length of the metagenomic sequences compared to IL and enlarged the gene pool compared to PB. The PI approach also offered comparable or higher species abundance than either PB or IL alone, and showed significant advantages for studying natural product biosynthetic genes in the soil microbiomes. CONCLUSION: Our results provide an effective strategy for combining long and short-read DNA sequencing data to explore and distill the maximum information out of soil metagenomics.

Dynamics of Verticillium dahliae race 1 population under managed agricultural ecosystems.

BACKGROUND: Plant pathogens and their hosts undergo adaptive changes in managed agricultural ecosystems, by overcoming host resistance, but the underlying genetic adaptations are difficult to determine in natural settings. Verticillium dahliae is a fungal pathogen that causes Verticillium wilt on many economically important crops including lettuce. We assessed the dynamics of changes in the V. dahliae genome under selection in a long-term field experiment. RESULTS: In this study, a field was fumigated before the Verticillium dahliae race 1 strain (VdLs.16) was introduced. A derivative 145-strain population was collected over a 6-year period from this field in which a seggregating population of lettuce derived from Vr1/vr1 parents were evaluated. We de novo sequenced the parental genome of VdLs.16 strain and resequenced the derivative strains to analyze the genetic variations that accumulate over time in the field cropped with lettuce. Population genomics analyses identified 2769 single-nucleotide polymorphisms (SNPs) and 750 insertion/deletions (In-Dels) in the 145 isolates compared with the parental genome. Sequence divergence was identified in the coding sequence regions of 378 genes and in the putative promoter regions of 604 genes. Five-hundred and nine SNPs/In-Dels were identified as fixed. The SNPs and In-Dels were significantly enriched in the transposon-rich, gene-sparse regions, and in those genes with functional roles in signaling and transcriptional regulation. CONCLUSIONS: Under the managed ecosystem continuously cropped to lettuce, the local adaptation of V. dahliae evolves at a whole genome scale to accumulate SNPs/In-Dels nonrandomly in hypervariable regions that encode components of signal transduction and transcriptional regulation.

Analysis on the Subdivision of Skilled Mowing Movements on Slopes.

Owing to the aging of the rural population in the hilly and mountainous areas of Japan, mowing on narrow ridges and steep slopes is done manually by the elderly-individuals over 65 years of age. Studies have shown that many accidents that occurred during mowing were caused by workers' unstable posture, especially when mowing on steep surfaces where there is a high risk of falling. It is necessary to analyze the body movements of mowing workers to elucidate the elements related to the risk of falls. Therefore, in this study, based on a high-precision motion-capture device and a series of experiments with elderly, skilled mowing workers, we focused on the movements of mowing. We sought to identify effective and safe mowing patterns and the factors that lead to the risk of falls. In various mowing styles, compared to the stride (S) and downward (D) mowing patterns, the basic (B) and moving (M) patterns were the most efficient; however, the risk of falls was also the highest among these patterns. While mowing, workers need to pay more attention to their arm strength and take appropriate measures to reduce the risk of falls according to their age and physique. The results can be used as data for the development of fall-detection systems and offer useful insights for the training of new mowing workers.

Research progress on multicomponent physical exercise for patients with neurocognitive impairment.

Neurocognitive impairment is a group of clinical syndromes characterized by impaired cognitive function and decreased motor ability. Non-pharmacological interventions such as physical exercise have advantages in the treatment of patients with neurocognitive impairment. Multicomponent exercise is a combination of various physical exercises, including strength training, endurance training, balance training and flexibility training, that can improve gait, balance and cardiopulmonary function by increasing muscle mass, strength and endurance in people with neurocognitive impairment, while also reducing the risk of falls in elders. This article reviews the benefits of multicomponent exercise for patients with neurocognitive impairment and its evaluation methods; also describes 4 intervention programs and their clinical application, to provide evidence for clinical practice and promote the application of multicomponent exercise in patients with neurocognitive impairment.

S-Nitrosylation of Akt by organic nitrate delays revascularization and the recovery of cardiac function in mice following myocardial infarction.

The effects of long-term nitrate therapy are compromised due to protein S-Nitrosylation, which is mediated by nitric oxide (NO). This study is to determine the role of Akt S-Nitrosylation in the recovery of heart functions after ischaemia. In recombinant Akt protein and in HEK293 cells, NO donor decreased Akt activity and induced Akt S-Nitrosylation, but was abolished if Akt protein was mutated by replacing cysteine 296/344 with alanine (Akt-C296/344A). In endothelial cells, NO induced Akt S-Nitrosylation, reduced Akt activity and damaged multiple cellular functions including proliferation, migration and tube formation. These alterations were ablated if cells expressed Akt-C296/344A mutant. In Apoe-/- mice, nitroglycerine infusion increased both Akt S-Nitrosylation and infarct size, reduced Akt activity and capillary density, and delayed the recovery of cardiac function in ischaemic hearts, compared with mice infused with vehicle. Importantly, these in vivo effects of nitroglycerine in Apoe-/- mice were remarkably prevented by adenovirus-mediated enforced expression of Akt-C296/344A mutant. In conclusion, long-term usage of organic nitrate may inactivate Akt to delay ischaemia-induced revascularization and the recovery of cardiac function through NO-mediated S-Nitrosylation.

Genome Sequence Data of MAT1-1 and MAT1-2 Idiomorphs from Verticillium dahliae.

Though Verticillium dahliae is an asexually reproducing fungus, it is considered heterothallic owing to the presence of only one of the two mating-type idiomorphs (MAT1-1 or MAT1-2) in individual isolates. But sexual reproduction has never been observed either in nature or in the laboratory. All of the genomic information in the literature thus far has therefore come from studies on isolates carrying only the MAT1-2 idiomorph. Herein, we sequenced and compared high-quality reference genomes of MAT1-1 strain S011 and MAT1-2 strain S023 obtained from the same sunflower field. The two genomic sequences displayed high synteny, and encoded similar number genes, a similarity especially notable among pathogenicity-related genes. Homolog analysis between these two genomes revealed that 80% of encoded genes are highly conserved (95% identity and coverage), but only 20% of the single copy genes were identical. These novel genome resources will support the analysis of the structure and function of the two idiomorphs and provide valuable tools to elucidate the evolution and potential mechanisms of sexual reproduction in V. dahliae.

Genome Sequence of Verticillium dahliae Race 1 Isolate VdLs.16 From Lettuce.

Verticillium dahliae is a widespread fungal pathogen that causes Verticillium wilt on many economically important crops and ornamentals worldwide. Populations of V. dahliae have been divided into two distinct races based upon differential host responses in tomato and lettuce. Recently, the contemporary race 2 isolates were further divided into an additional race in tomato. Herein, we provide a high-quality reference genome for the race 1 strain VdLs.16 isolated from lettuce in California, U.S.A. This resource will contribute to ongoing research that aims to elucidate the genetic basis of V. dahliae pathogenicity and population genomic diversity.

Flexible layer-structured Bi2Te3 thermoelectric on a carbon nanotube scaffold.

Inorganic chalcogenides are traditional high-performance thermoelectric materials. However, they suffer from intrinsic brittleness and it is very difficult to obtain materials with both high thermoelectric ability and good flexibility. Here, we report a flexible thermoelectric material comprising highly ordered Bi2Te3 nanocrystals anchored on a single-walled carbon nanotube (SWCNT) network, where a crystallographic relationship exists between the Bi2Te3 <[Formula: see text]> orientation and SWCNT bundle axis. This material has a power factor of ~1,600 µW m-1 K-2 at room temperature, decreasing to 1,100 µW m-1 K-2 at 473 K. With a low in-plane lattice thermal conductivity of 0.26 ± 0.03 W m-1 K-1, a maximum thermoelectric figure of merit (ZT) of 0.89 at room temperature is achieved, originating from a strong phonon scattering effect. The origin of the excellent flexibility and thermoelectric performance of the Bi2Te3-SWCNT material is attributed, by experimental and computational evidence, to its crystal orientation, interface and nanopore structure. Our results provide insight into the design and fabrication of high-performance flexible thermoelectric materials.

A novel sunshine duration-based photothermal time model interprets the photosensitivity of flower maturity of pecan cultivars.

Although it is well-known and established that light plays important roles in plant development, up to now, there is no substantial improvements in how to deal with the light factor of spring phenology under natural condition. By monitoring the local meteorologic data and mature dates of two types (male and female) of flower from four pecan cultivars during 9 years, it was found that the complementary pattern of growing degree day and sunshine duration helped to maintain a threshold of driving force related to the maturity of pecan flower during 9 years. A novel photothermal time model based on the linear combination of growing degree day and sunshine duration was then proposed and validated to interpret the variance of mature dates of pecan cultivars. Comparative analysis showed that the new model had made extremely significant improvements to the traditional thermal time model. In addition, this model introduced the conversion coefficient K, which quantified the effect of light on the flowering drive, and revealed the differences of base temperature among cultivars. This was the first time that sunshine duration instead of photoperiod was adopted to develop into a verified model on spring phenological event of tree species. It will help to model the spring phenologies of other tree species more reasonably.

Learning misclassification costs for imbalanced classification on gene expression data.

BACKGROUND: Cost-sensitive algorithm is an effective strategy to solve imbalanced classification problem. However, the misclassification costs are usually determined empirically based on user expertise, which leads to unstable performance of cost-sensitive classification. Therefore, an efficient and accurate method is needed to calculate the optimal cost weights. RESULTS: In this paper, two approaches are proposed to search for the optimal cost weights, targeting at the highest weighted classification accuracy (WCA). One is the optimal cost weights grid searching and the other is the function fitting. Comparisons are made between these between the two algorithms above. In experiments, we classify imbalanced gene expression data using extreme learning machine to test the cost weights obtained by the two approaches. CONCLUSIONS: Comprehensive experimental results show that the function fitting method is generally more efficient, which can well find the optimal cost weights with acceptable WCA.

Population genomics demystifies the defoliation phenotype in the plant pathogen Verticillium dahliae.

Verticillium dahliae is a broad host-range pathogen that causes vascular wilts in plants. Interactions between three hosts and specific V. dahliae genotypes result in severe defoliation. The underlying mechanisms of defoliation are unresolved. Genome resequencing, gene deletion and complementation, gene expression analysis, sequence divergence, defoliating phenotype identification, virulence analysis, and quantification of V. dahliae secondary metabolites were performed. Population genomics previously revealed that G-LSR2 was horizontally transferred from the fungus Fusarium oxysporum f. sp. vasinfectum to V. dahliae and is exclusively found in the genomes of defoliating (D) strains. Deletion of seven genes within G-LSR2, designated as VdDf genes, produced the nondefoliation phenotype on cotton, olive, and okra but complementation of two genes restored the defoliation phenotype. Genes VdDf5 and VdDf6 associated with defoliation shared homology with polyketide synthases involved in secondary metabolism, whereas VdDf7 shared homology with proteins involved in the biosynthesis of N-lauroylethanolamine (N-acylethanolamine (NAE) 12:0), a compound that induces defoliation. NAE overbiosynthesis by D strains also appears to disrupt NAE metabolism in cotton by inducing overexpression of fatty acid amide hydrolase. The VdDfs modulate the synthesis and overproduction of secondary metabolites, such as NAE 12:0, that cause defoliation either by altering abscisic acid sensitivity, hormone disruption, or sensitivity to the pathogen.

Comparative genomics reveals cotton-specific virulence factors in flexible genomic regions in Verticillium dahliae and evidence of horizontal gene transfer from Fusarium.

Verticillium dahliae isolates are most virulent on the host from which they were originally isolated. Mechanisms underlying these dominant host adaptations are currently unknown. We sequenced the genome of V. dahliae Vd991, which is highly virulent on its original host, cotton, and performed comparisons with the reference genomes of JR2 (from tomato) and VdLs.17 (from lettuce). Pathogenicity-related factor prediction, orthology and multigene family classification, transcriptome analyses, phylogenetic analyses, and pathogenicity experiments were performed. The Vd991 genome harbored several exclusive, lineage-specific (LS) genes within LS regions (LSRs). Deletion mutants of the seven genes within one LSR (G-LSR2) in Vd991 were less virulent only on cotton. Integration of G-LSR2 genes individually into JR2 and VdLs.17 resulted in significantly enhanced virulence on cotton but did not affect virulence on tomato or lettuce. Transcription levels of the seven LS genes in Vd991 were higher during the early stages of cotton infection, as compared with other hosts. Phylogenetic analyses suggested that G-LSR2 was acquired from Fusarium oxysporum f. sp. vasinfectum through horizontal gene transfer. Our results provide evidence that horizontal gene transfer from Fusarium to Vd991 contributed significantly to its adaptation to cotton and may represent a significant mechanism in the evolution of an asexual plant pathogen.

Genome-wide analysis of the gene families of resistance gene analogues in cotton and their response to Verticillium wilt.

BACKGROUND: Gossypium raimondii is a Verticillium wilt-resistant cotton species whose genome encodes numerous disease resistance genes that play important roles in the defence against pathogens. However, the characteristics of resistance gene analogues (RGAs) and Verticillium dahliae response loci (VdRLs) have not been investigated on a global scale. In this study, the characteristics of RGA genes were systematically analysed using bioinformatics-driven methods. Moreover, the potential VdRLs involved in the defence response to Verticillium wilt were identified by RNA-seq and correlations with known resistance QTLs. RESULTS: The G. raimondii genome encodes 1004 RGA genes, and most of these genes cluster in homology groups based on high levels of similarity. Interestingly, nearly half of the RGA genes occurred in 26 RGA-gene-rich clusters (Rgrcs). The homology analysis showed that sequence exchanges and tandem duplications frequently occurred within Rgrcs, and segmental duplications took place among the different Rgrcs. An RNA-seq analysis showed that the RGA genes play roles in cotton defence responses, forming 26 VdRLs inside in the Rgrcs after being inoculated with V. dahliae. A correlation analysis found that 12 VdRLs were adjacent to the known Verticillium wilt resistance QTLs, and that 5 were rich in NB-ARC domain-containing disease resistance genes. CONCLUSIONS: The cotton genome contains numerous RGA genes, and nearly half of them are located in clusters, which evolved by sequence exchanges, tandem duplications and segmental duplications. In the Rgrcs, 26 loci were induced by the V. dahliae inoculation, and 12 are in the vicinity of known Verticillium wilt resistance QTLs.

[Activation of TNF-α and signaling pathway in the hypothalamus of the rats subjected to chronic unpredictable mild stressors after middle cerebral artery occlusion].

This study was aimed to investigate the changes of the hypothalamic-pituitary-adrenal axis (HPAA) activity and the cytokines system in the hypothalamus of the depressive rats which were exposed to chronic unpredictable mild stressors (CUMS) after middle cerebral artery occlusion (MCAO). By means of qRT-PCR, ELISA and Western blot, mRNA and/or protein expressions of corticotropin releasing factor (CRF), tumor necrosis factors-α (TNF-α), suppressor of cytokines signaling 3 (SOCS3), phosphorylation of signal transducers and activators of transcription 3 (pSTAT3) were measured in the hypothalamus of rats. The results showed that, compared with control group, CUMS+MCAO group exhibited increased mRNA levels of CRF, TNF-α, SOCS3, as well as up-regulated CRF, TNF-α, SOCS3 and pSTAT3 protein expressions. Furthermore, there were correlations between CRF and TNF-α, TNF-α and SOCS3, SOCS3 and pSTAT3, respectively. These observations indicated the CRF system was activated in the post stroke depression (PSD) status. The TNF-α and its signaling pathway, STAT3/SOCS3, were up-regulated in mRNA and protein levels. In conclusion, this study presents the evidence which supports the hypothesis of signaling cross-talk between the CRF system and TNF-α signaling pathway after ischemic stroke and CUMS.

Evaluating the predictive value of initial lactate/albumin ratios in determining prognosis of sepsis patients.

Sepsis remains a significant clinical challenge owing to its complex pathophysiology and variable prognosis. The early identification of patients at a higher risk of poor outcomes can be crucial for improving treatment strategies. This study aimed to evaluate the predictive value of early serum lactate and albumin levels and the lactate/albumin (L/A) ratio for 28-day prognosis in patients with sepsis. Patients diagnosed with sepsis between January 2021 and December 2022 were evaluated using a retrospective cohort methodology. Inclusion followed the International Consensus on sepsis and septic shock (Sepsis-3) guidelines and patients were selected based on well-defined criteria. Variables such as lactate, albumin, and the L/A ratio were documented within the first 24 hours of admission. Statistical analyses were performed using various tools, including the nonparametric Mann-Whitney U test and receiver operating characteristic curves. A total of 301 patients were divided into the survival (n = 167) and death (n = 134) groups. Notable differences were detected in the incidence of pulmonary infection, shock, lactate, albumin, and the L/A ratio. The L/A ratio was identified as a key predictor with an area under the curve of 0.868, an optimal cutoff value of >0.17, a sensitivity of 56.21%, and a specificity of 94.18%. Significant disparities in mortality rates and survival times were observed for the lactate, albumin, and L/A levels. This study underscores the predictive value of early serum lactate and albumin levels and the L/A ratio for 28-day prognosis in patients with sepsis, with the L/A ratio showing a superior predictive capability. These findings highlight the importance of L/A ratio as a robust and precise marker for evaluating the future clinical course of patients with sepsis, potentially aiding early detection and management.

Blinding and blurring the multi-object tracker with adversarial perturbations.

Adversarial attack reveals a potential imperfection in deep models that they are susceptible to being tricked by imperceptible perturbations added to images. Recent deep multi-object trackers combine the functionalities of detection and association, rendering attacks on either the detector or the association component an effective means of deception. Existing attacks focus on increasing the frequency of ID switching, which greatly damages tracking stability, but is not enough to make the tracker completely ineffective. To fully explore the potential of adversarial attacks, we propose Blind-Blur Attack (BBA), a novel attack method based on spatio-temporal motion information to fool multi-object trackers. Specifically, a simple but efficient perturbation generator is trained with the blind-blur loss, simultaneously making the target invisible to the tracker and letting the background be regarded as moving targets. We take TraDeS as our main research tracker, and verify our attack method on other excellent algorithms (i.e., CenterTrack, FairMOT, and ByteTrack) on MOT-Challenge benchmark datasets (i.e., MOT16, MOT17, and MOT20). BBA attack reduced the MOTA of TraDeS and ByteTrack from 69.1 and 80.3 to -238.1 and -357.0, respectively, indicating that it is an efficient method with a high degrees of transferability.

On-Chip Micro Temperature Controllers Based on Freestanding Thermoelectric Nano Films for Low-Power Electronics.

Multidimensional integration and multifunctional component assembly have been greatly explored in recent years to extend Moore's Law of modern microelectronics. However, this inevitably exacerbates the inhomogeneity of temperature distribution in microsystems, making precise temperature control for electronic components extremely challenging. Herein, we report an on-chip micro temperature controller including a pair of thermoelectric legs with a total area of 50 × 50 µm2, which are fabricated from dense and flat freestanding Bi2Te3-based thermoelectric nano films deposited on a newly developed nano graphene oxide membrane substrate. Its tunable equivalent thermal resistance is controlled by electrical currents to achieve energy-efficient temperature control for low-power electronics. A large cooling temperature difference of 44.5 K at 380 K is achieved with a power consumption of only 445 µW, resulting in an ultrahigh temperature control capability over 100 K mW-1. Moreover, an ultra-fast cooling rate exceeding 2000 K s-1 and excellent reliability of up to 1 million cycles are observed. Our proposed on-chip temperature controller is expected to enable further miniaturization and multifunctional integration on a single chip for microelectronics.

Reconstructed Graph Neural Network With Knowledge Distillation for Lightweight Anomaly Detection.

The proliferation of Internet-of-Things (IoT) technologies in modern smart society enables massive data exchange for offering intelligent services. It becomes essential to ensure secure communications while exchanging highly sensitive IoT data efficiently, which leads to high demands for lightweight models or algorithms with limited computation capability provided by individual IoT devices. In this study, a graph representation learning model, which seamlessly incorporates graph neural network (GNN) and knowledge distillation (KD) techniques, named reconstructed graph with global-local distillation (RG-GLD), is designed to realize the lightweight anomaly detection across IoT communication networks. In particular, a new graph network reconstruction strategy, which treats data communications as nodes in a directed graph while edges are then connected according to two specifically defined rules, is devised and applied to facilitate the graph representation learning in secure and efficient IoT communications. Both the structural and traffic features are then extracted from the graph data and flow data respectively, based on the graph attention network (GAT) and multilayer perceptron (MLP) techniques. These can benefit the GNN-based KD process in accordance with the more effective feature fusion and representation, considering both structural and data levels across the dynamic IoT networks. Furthermore, a lightweight local subgraph preservation mechanism improved by the graph attention mechanism and downsampling scheme to better utilize the topological information, and a so-called global information alignment defined based on the self-attention mechanism to effectively preserve the global information, are developed and incorporated in a refined graph attention based KD scheme. Compared with four different baseline methods, experiments and evaluations conducted based on two public datasets demonstrate the usefulness and effectiveness of our proposed model in improving the efficiency of knowledge transfer with higher classification accuracy but lower computational load, which can be deployed for lightweight anomaly detection in sustainable IoT computing environments.

Extracellular vesicles of Bifidobacterium longum reverse the acquired carboplatin resistance in ovarian cancer cells via p53 phosphorylation on Ser15.

We previously found that the relative abundance of Bifidobacterium was increased after chemotherapy; however, the role of Bifidobacterium longum in chemotherapeutic drug resistance in ovarian cancer (OVC) remains unclear. This study aimed to understand the potential effects and mechanism of B. longum extracellular vesicles (B. longum-EVs) on carboplatin (CBP) resistance in OVC. Eight normal and 11 ovarian tissues were collected and the expression of B. longum genomic DNA and its association with acquired CBP resistance in OVC patients was determined. After isolating EVs by ultracentrifugation from B. longum (ATCC 15707), CBP-resistant A2780 cells were treated with PBS, CBP, B. longum-EVs, or CBP + B. longum-EVs, and subsequently analyzed by CCK-8, Edu staining, Annexin V/PI double staining, wound healing, and Transwell assays to detect cell viability, proliferation, apoptosis, migration, and invasion, respectively. MRP1, ATP7A, ATP7B, and p53 expression as well as p53 phosphorylation were measured by western blot analysis. S15A mutation of p53 was assessed to examine the potential role of p53 Ser15 phosphorylation in CBP-resistant OVC. B. longum levels were elevated and positively associated with CBP resistance in OVC patients. Only high concentrations of B. longum-EVs attenuated A2780 cell proliferation, apoptosis, migration, and invasion. B. longum-EVs exposure significantly enhanced the sensitivity of CBP-resistant A2780 cells to CBP and decreased the expression of drug resistance-related proteins. The effect of B. longum-EVs on reversing CBP resistance was completely inhibited by S15A mutation of p53. B. longum-EVs enhanced the sensitivity of OVC cells to CBP through p53 phosphorylation on Ser15.

Humic acids-based one-step fabrication of SERS substrates for detection of polycyclic aromatic hydrocarbons.

A facile one-step approach to fabricate substrates for surface-enhanced Raman scattering (SERS) detection of polycyclic aromatic hydrocarbons (PAHs) was explored by reduction of silver nitrate with humic acids (HAs). This simple process readily delivers silver nanoparticles (Ag NPs) decorated with HAs (HAs-Ag NPs), and an average diameter of 50 nm. More importantly, it compares favorably to Ag NPs prepared by the usual sodium citrate method, HAs-Ag NPs show excellent SERS activity for PAHs and display a remarkable capacity to absorb aromatic molecules through presumed π-π stacking interactions. Furthermore, the HAs-Ag NPs displayed good SERS stability, possibly due to the fact that HAs form loose coils or networks around the nanoparticles thus preventing aggregation. The investigation of qualitative and quantitative detection of PAHs on HAs-Ag NPs indicate that different PAHs can be distinguished easily from their discriminant SERS peaks, and the SERS responses exhibited a linear dependence on PAH concentrations over two orders of magnitude, with tens of nM detection limits. In addition, the HAs-Ag NPs performed well in the multicomponent analysis of PAH mixtures by the SERS technique without pre-separation.