Search

Abstract Background Powdery mildew is a devastating fungal disease that poses a significant threat to wheat yield and quality worldwide. Identifying resistance genes is highly advantageous for the molecular breeding of resistant cultivars. GRAS proteins are important transcription factors that regulate plant development and stress responses. Nonetheless, their roles in wheat-pathogen interactions remain poorly understood. Results In this study, we used bioinformatics tools to identify and analyze wheat GRAS family genes responsive to biotic stresses and elucidated the function of TaeSCL6 within this family. A total of 179 GRAS genes in wheat were unevenly distributed on 7 chromosomes, and classified into 12 subfamilies based on phylogenetic relationship analysis. Gene duplication analysis revealed 13 pairs of tandem repeats and 142 pairs of segmental duplications, which may account for the rapid expansion of the wheat GRAS family. Expression pattern analysis revealed that 75% of the expressed TaeGRAS genes are responsive to biotic stresses. Few studies have focused on the roles of HAM subfamily genes. Consequently, we concentrated our analysis on the members of the HAM subfamily. Fourteen motifs were identified in the HAM family proteins from both Triticeae species and Arabidopsis, indicating that these motifs were highly conserved during evolution. Promoter analysis indicated that the promoters of HAM genes contain several cis-regulatory elements associated with hormone response, stress response, light response, and growth and development. Both qRT-PCR and RNA-seq data analyses demonstrated that TaeSCL6 responds to Blumeria graminis infection. Therefore, we investigated the role of TaeSCL6 in regulating wheat resistance via RNA interference and barley stripe mosaic virus induced gene silencing. Wheat plants with silenced TaeSCL6 exhibited increased susceptibility to powdery mildew. Conclusions In summary, this study not only validates the positive role of TaeSCL6 in wheat resistance to powdery mildew, but also provides candidate gene resources for future breeding of disease-resistance wheat cultivars.

Abstract Hemolytic peptides are therapeutic peptides that damage red blood cells. However, therapeutic peptides used in medical treatment must exhibit low toxicity to red blood cells to achieve the desired therapeutic effect. Therefore, accurate prediction of the hemolytic activity of therapeutic peptides is essential for the development of peptide therapies. In this study, a multi-feature cross-fusion model, HemoFuse, for hemolytic peptide identification is proposed. The feature vectors of peptide sequences are transformed by word embedding technique and four hand-crafted feature extraction methods. We apply multi-head cross-attention mechanism to hemolytic peptide identification for the first time. It captures the interaction between word embedding features and hand-crafted features by calculating the attention of all positions in them, so that multiple features can be deeply fused. Moreover, we visualize the features obtained by this module to enhance its interpretability. On the comprehensive integrated dataset, HemoFuse achieves ideal results, with ACC, SP, SN, MCC, F1, AUC, and AP of 0.7575, 0.8814, 0.5793, 0.4909, 0.6620, 0.8387, and 0.7118, respectively. Compared with HemoDL proposed by Yang et al., it is 3.32%, 3.89%, 5.93%, 10.6%, 8.17%, 5.88%, and 2.72% higher. Other ablation experiments also prove that our model is reasonable and efficient. The codes and datasets are accessible at https://github.com/z11code/Hemo .

Background: Hyperbaric oxygen therapy (HBOT), which is widely used in clinical practice, is aimed at improving nerve function impairment after brain injury. Meanwhile, the effects of music therapy on brain function are unclear. This retrospective study was conducted to explore the application effect of HBOT combined with music therapy on patients suffering from aneurysmal subarachnoid hemorrhage (aSAH). Methods: For this retrospective study, 130 patients with aSAH after HBOT were selected from our hospital from June 2021 to June 2022. The patients were divided into the observation (n = 70) and control (n = 60) groups based on whether they received music therapy. Comparisons were made on general demographic data, blood flow rate in median cerebral artery (MCA), cerebral vasospasm (CVS), National Institutes of Health Stroke Scale (NIHSS), activities of daily living (ADL) score, Self-Rating Depressive Scale (SDS), and Self-Rating Anxiety Scale (SAS) of patients. Results: Baseline data between the two groups showed no statistically significant difference (P > 0.05). After management, patients in the observation group presented significantly lower SAS and SDS scores (P < 0.05), lower blood flow rate in MCA, CVS and NIHSS scores (P < 0.05), and higher ADL scores than the control group (P < 0.05). Conclusions: The combination of HBOT and music therapy can considerably improve cerebral neurological deficits, slow down cerebral arterial blood flow, promote the recovery of postoperative cerebral function in aSAH patients, and improve anxiety and depression and the patients’ ADL.

Abstract As a class of biologically active molecules with significant immunomodulatory and anti-inflammatory effects, anti-inflammatory peptides have important application value in the medical and biotechnology fields due to their unique biological functions. Research on the identification of anti-inflammatory peptides provides important theoretical foundations and practical value for a deeper understanding of the biological mechanisms of inflammation and immune regulation, as well as for the development of new drugs and biotechnological applications. Therefore, it is necessary to develop more advanced computational models for identifying anti-inflammatory peptides. In this study, we propose a deep learning model named DAC-AIPs based on variational autoencoder and contrastive learning for accurate identification of anti-inflammatory peptides. In the sequence encoding part, the incorporation of multi-hot encoding helps capture richer sequence information. The autoencoder, composed of convolutional layers and linear layers, can learn latent features and reconstruct features, with variational inference enhancing the representation capability of latent features. Additionally, the introduction of contrastive learning aims to improve the model's classification ability. Through cross-validation and independent dataset testing experiments, DAC-AIPs achieves superior performance compared to existing state-of-the-art models. In cross-validation, the classification accuracy of DAC-AIPs reached around 88%, which is 7% higher than previous models. Furthermore, various ablation experiments and interpretability experiments validate the effectiveness of DAC-AIPs. Finally, a user-friendly online predictor is designed to enhance the practicality of the model, and the server is freely accessible at http://dac-aips.online .

As the demand on the construction salt rock storage increases in China, the shallow suitable deposits have been gradually exhausted, as such, the utilization shift from shallow to deep salt deposits is an inevitable trend. In order to study the creep damage characteristics of surrounding rock under the coupling effect of three-dimensional in-situ stress and temperature during the actual operation of deep salt rock storage, the triaxial creep tests were carried out on deep salt rock specimens under different temperatures and stresses. Considering the influence of temperature and stress on the creep damage characteristic of deep salt rock, it is believed that the temperature damage is accompanied by the whole creep process, and the stress damage starts to play a role when the stress state reaches the yield limit. It is assumed that the damage variables relationship between temperature and stress satisfies Weibull distribution and negative exponential function respectively. A new viscoelastic-plastic creep damage model considering the temperature and stress coupling effect was proposed by introducing a fractional Abel dashpot to modify the Nishihara model. The proposed model not only has a simple form and clear physical meaning of parameters, which is convenient for the application of the model in numerical calculation and engineering practice. The results show that the steady-creep rate of deep salt rock is a function of deviatoric stress and temperature. The material parameter A= 32.39 MPa−4.83/h, activation free energy Q=7.84×104 kJ/mol and creep stress index n = 4.83 in the steady-state creep strain rate constitutive equation are fitted. The theoretical analytical solutions of the viscoelastic-plastic creep damage models under different temperatures and stresses are in good agreement with the corresponding experimental data, which verifies the correctness and accuracy of the model. The effects of temperature and stress on rock creep properties were verified by the fitting parameters of each mechanical body of the creep damage model, which proves the rationality of the established model. The theoretical model can not only accurately characterize the attenuation and steady-state creep stages of rocks, but also well describe the deformation characteristics of accelerated creep stages.

Background: Cuproptosis is a unique form of cell death that is dependent on copper, which is fundamentally different from other recognized forms of cell death. However, the molecular and immune characteristics in cuproptosis-defined subgroups of cholangiocarcinoma (CCA) remain to be further illustrated. Methods: We conducted a comprehensive investigation into the genetic and transcriptional variation, prognostic significance, and expression profiles of 16 cuproptosis-related genes (CRGs). To construct a prognostic signature based on differentially expressed genes between molecular subtypes, we employed LASSO and multivariate Cox regression analyses. We then assessed the values of this signature in prognostic prediction, immune infiltration, and therapeutic responses in CCA. The robustness of the signature was further validated in the GEO and IMvigor210 cohorts. Additionally, qRT-PCR and Western blotting (WB) were utilized to confirm the expression of the signature genes across different cell lines. Results: A total of 16 CRGs were analyzed revealed differentially expressed, and two CRG-related clusters were identified, which displayed contrasting survival times.Then, a robust cuproptosis-related risk model was established and was an independent prognostic factor for CCA, which was further validated across two external cohorts. Low-risk patients had a better overall survival than high-risk patients. The comprehensive results showed that a low-risk score was correlated with metabolism-related pathways, high infiltration of CD8 T cells, B cells, and M1 macrophages, active immunity and less aggressive phenotypes, high chemotherapeutic sensitivity, and more benefit from immunotherapy. In contrast, a high-risk score was associated with cancer and metastasis-related pathways, high infiltration of M2 macrophages, high expression of immune checkpoint genes, suppressive immunity and more aggressive phenotypes, and less benefit from chemotherapeutic and immunotherapy. In addition, the critical CRGs were further validated through qRT-PCR and WB. Conclusions: We developed a novel risk model for CCA patients, which serves as a promising biomarker for distinguishing prognosis as well as molecular and immune characteristics.

AimIn this study, we aimed to evaluate oral health strategies in rheumatoid arthritis (RA) patients with periodontitis.MethodsWe enrolled 110 RA patients with periodontitis who were diagnosed in a Grade A tertiary hospital into an oral health strategies program. The control and test groups comprised 55 cases each. The management effect was evaluated by self-care ability, oral health-related quality of life, RA-related clinical indicators, and the DAS28 score. The control group received routine nursing, whereas the test group was in a self-health management program for 3 months.ResultsAfter the intervention, compared to the control group, the test group showed better self-care ability, oral health-related quality of life score, RA-related clinical indicators, and DAS28 score (P < 0.05).ConclusionOur oral health strategies program slowed down the progression of the disease and can be popularized in patients.

Abstract The structural diversity of biological macromolecules in different environments contributes complexity to enzymological processes vital for cellular functions. Fluorescence resonance energy transfer and electron microscopy are used to investigate the enzymatic reaction of T4 DNA ligase catalyzing the ligation of nicked DNA. The data show that both the ligase–AMP complex and the ligase–AMP–DNA complex can have four conformations. This finding suggests the parallel occurrence of four ligation reaction pathways, each characterized by specific conformations of the ligase–AMP complex that persist in the ligase–AMP–DNA complex. Notably, these complexes have DNA bending angles of ≈0°, 20°, 60°, or 100°. The mechanism of parallel reactions challenges the conventional notion of simple sequential reaction steps occurring among multiple conformations. The results provide insights into the dynamic conformational changes and the versatile attributes of T4 DNA ligase and suggest that the parallel multiple reaction pathways may correspond to diverse T4 DNA ligase functions. This mechanism may potentially have evolved as an adaptive strategy across evolutionary history to navigate complex environments.

Federated learning (FL) is an emerging machine learning paradigm that enables the participants to train a global model without sharing the training data. Recently, FL has been widely deployed in industrial IoT scenarios because of its data privacy and scalability. However, the current FL architecture relies on a central server to orchestrate the FL process, thus incurring a risk of privacy leakage and single-point failure. To address this issue, we propose a fully decentralized FL architecture based on blockchain technology. Unlike existing blockchain-based FL systems that use blockchain for coordination or storage, we use blockchain as a trustable computing platform for model aggregation. Furthermore, we model the interaction between the FL task publisher and participants as a Stackelberg game and design a rewarding mechanism to incentivize participants to contribute to the FL task. We build a prototype system of the proposed decentralized FL architecture and implement an FL-based damaged package detection application to evaluate the proposed approach. Experimental results show that the blockchain-based decentralized FL is feasible in a practical industrial IoT scenario, and the incentive mechanism performs well with real application data.

Human history is also the history of the fight against viral diseases. From the eradication of viruses to coexistence, advances in biomedicine have led to a more objective understanding of viruses and a corresponding increase in the tools and methods to combat them. More recently, antiviral peptides (AVPs) have been discovered, which due to their superior advantages, have achieved great impact as antiviral drugs. Therefore, it is very necessary to develop a prediction model to accurately identify AVPs. In this paper, we develop the iAVPs-ResBi model using k-spaced amino acid pairs (KSAAP), encoding based on grouped weight (EBGW), enhanced grouped amino acid composition (EGAAC) based on the N5C5 sequence, composition, transition and distribution (CTD) based on physicochemical properties for multi-feature extraction. Then we adopt bidirectional long short-term memory (BiLSTM) to fuse features for obtaining the most differentiated information from multiple original feature sets. Finally, the deep model is built by combining improved residual network and bidirectional gated recurrent unit (BiGRU) to perform classification. The results obtained are better than those of the existing methods, and the accuracies are 95.07, 98.07, 94.29 and 97.50% on the four datasets, which show that iAVPs-ResBi can be used as an effective tool for the identification of antiviral peptides. The datasets and codes are freely available at https://github.com/yunyunliang88/iAVPs-ResBi.

Abstract Tertiary lymphoid structures (TLSs) play a crucial role in determining prognosis and response to immunotherapy in several solid malignancies. Nevertheless, the effect of TLS-associated gene signature based on The Cancer Genome Atlas (TCGA) cohort in patients with breast cancer (BRCA) remains controversial. Based on TCGA-BRCA dataset (n = 866), 9-gene was identified to construct an TLS signature and further analyzed its prognostic value. Then, we explored the relationship of this TLS signature with molecular subtype, immune microenvironment, tumor mutational burden (TMB). High-TLS signature patients had a better overall survival (OS) than low-TLS signature patients, consistent with the results in the METABRIC cohort. Multivariate analysis revealed that TLS signature remained an independent prognostic indicator for OS. In addition, we established a nomogram with the integration of TLS signature and other independent variables to predict individual risk of death. The comprehensive results showed that patients with high TLS signature benefit from immunotherapy; the signature was also correlated with inhibition of cell proliferation pathways, low TP53 mutation rate, high infiltration of B cells, CD8 + T cells, CD4 + T cells, and M1 macrophages. Therefore, TLS signature is a promising biomarker to distinguish the prognosis and immune microenvironment in BRCA.

Highlights A comprehensive summary of the representative promising applications of metal halide perovskite materials, including traditional optoelectronic devices (solar cells, light-emitting diodes, photodetectors, lasers), and cutting-edge technologies in terms of neuromorphic devices (artificial synapses and memristors) and pressure-induced emission. For each application, the fundamentals of the field, the current progress and the remaining challenges are provided, based on the up-to-date works.

ObjectivesThis study aims to measure the effect of Construction of Healthcare Consortium (CHC) on the allocation and equity of human resources (HR) for primary health care (PHC) in China, at the same time, it provides some data to support the government's policies improvement in the next stage.MethodsChanges in the equity of allocation of HR for PHC by population are demonstrated through a three-stage approach to inequality analysis that includes the Gini coefficient (G), the Theil index (T), the Concentration index (CI) and Concentration curves. Trends in resource allocation from 2021 to 2030 were projected using the GM (1, 1) model.ResultsThe average rate of growth in volume of HR for PHC accelerates following the release of CHC in the 2016. Whilst some regions have seen their G and T rise between 2012 and 2016, their levels of inequality of allocation for resource shave gradually declined in the years following 2016, but there are exceptions, with the regions of northeast and northwest seeing the opposite. Eastern and northern region accounted for a larger contribution to intra-regional inequality. Concentration index and concentration curves indicate HR for PHC is related to economic income levels. GM (1, 1) projects a growing trend in allocation of resources from 2021 to 2030, but different regions differ in the average rate of growth of resources.ConclusionsThe inequality of HR for PHC in China is low, however, the inequality between regions has not been eliminated. We still need to take a long-term view to monitor the impact of CHC on the allocation of HR for PHC and its equity in China.

In this study, a novel peroxydisulfate (PDS) activator (CF-nZVI-JE) was prepared via in-situ loading nano zero-valent iron (nZVI) on Juncus effusus (JE) followed with wrapping a layer of cellulose film (CF). The CF-nZVI-JE had the same 3D structure as the JE, being easy to separate from aqueous solution. The loaded nZVI existed single nanoparticles with a size of 60–100 nm except chain-type agglomeration of nanoparticles due to the stabilization of JE fibers. The activation performance of the CF-nZVI-JE for PDS was evaluated with Rhodamine B (Rh B) as a representative pollutant. Under the optimal activating conditions, the degradation rate of Rh B reached 99% within 30 min in the CF-nZVI-JE/PDS system. After five cycles, the degradation rate of Rh B was still over 85%, suggesting that the CF-nZVI-JE had good reusability. More interestingly, SO4·− and ·OH radicals were simultaneously detected in the CF-nZVI-JE/PDS system, but only SO4·− existed in the JE-ZVI/PDS system, suggesting the different activation mechanism. Meanwhile, the introduction of CF not only facilitated to the mineralization of Rh B but also significantly reduced the release amount of iron ions. Hence, the CF-nZVI-JE can be employed as a promising PDS activator for the treatment of organic wastewater. HIGHLIGHTS The prepared CF-nZVI-JE had the same 3D structure as JE, which can stabilize nZVI.; nZVI existed as single nanoparticles and chain-type agglomeration of nanoparticles.; Rh B degradation was involved in SO4−· and HO· in the CF-nZVI-JE/PDS system.; CF-nZVI-JE facilitated the mineralization of Rh B compared with the nZVI-JE.; CF prevented the leakage of nZVI and reduced the release amount of iron ions.;

Abstract Background Insights into the genetic basis of complex traits and disease in both human and livestock species have been achieved over the past decade through detection of genetic variants in genome-wide association studies (GWAS). A majority of such variants were found located in noncoding genomic regions, and though the involvement of numerous regulatory elements (REs) has been predicted across multiple tissues in domesticated animals, their evolutionary conservation and effects on complex traits have not been fully elucidated, particularly in ruminants. Here, we systematically analyzed 137 epigenomic and transcriptomic datasets of six mammals, including cattle, sheep, goats, pigs, mice, and humans, and then integrated them with large-scale GWAS of complex traits. Results Using 40 ChIP-seq datasets of H3K4me3 and H3K27ac, we detected 68,479, 58,562, 63,273, 97,244, 111,881, and 87,049 REs in the liver of cattle, sheep, goats, pigs, humans and mice, respectively. We then systematically characterized the dynamic functional landscapes of these REs by integrating multi-omics datasets, including gene expression, chromatin accessibility, and DNA methylation. We identified a core set (n = 6359) of ruminant-specific REs that are involved in liver development, metabolism, and immune processes. Genes with more complex cis-REs exhibited higher gene expression levels and stronger conservation across species. Furthermore, we integrated expression quantitative trait loci (eQTLs) and GWAS from 44 and 52 complex traits/diseases in cattle and humans, respectively. These results demonstrated that REs with different degrees of evolutionary conservation across species exhibited distinct enrichments for GWAS signals of complex traits. Conclusions We systematically annotated genome-wide functional REs in liver across six mammals and demonstrated the evolution of REs and their associations with transcriptional output and conservation. Detecting lineage-specific REs allows us to decipher the evolutionary and genetic basis of complex phenotypes in livestock and humans, which may benefit the discovery of potential biomedical models for functional variants and genes of specific human diseases.

The dirigent (DIR) gene is a key player in environmental stress response and has been identified in many multidimensional tube plant species. However, there are few studies on the StDIR gene in potato. In this study, we used genome-wide identification to identify 31 StDIR genes in potato. Among the 12 potato chromosomes, the StDIR gene was distributed on 11 chromosomes, among which the third chromosome did not have a family member, while the tenth chromosome had the most members with 11 members. 22 of the 31 StDIRs had a classical DIR gene structure, with one exon and no intron. The conserved DIR domain accounts for most of the proteins in the 27 StDIRs. The structure of the StDIR gene was analyzed and ten different motifs were detected. The StDIR gene was divided into three groups according to its phylogenetic relationship, and 22 duplicate genes were identified. In addition, four kinds of cis-acting elements were detected in all 31 StDIR promoter regions, most of which were associated with biotic and abiotic stress. The findings demonstrated that the StDIR gene exhibited specific responses to cold stress, salt stress, ABA, and drought stress. This study provides new candidate genes for improving potato’s resistance to stress.

Abstract The ultra‐dense deployment of unmanned aerial vehicles (UAVs) as mobile small cell base stations (SBS) is expected to support ultra‐high‐speed, ultra‐reliable, and ultra‐low‐latency wireless connections in sixth generation (6G) wireless cellular networks. Inevitably, the explosively increasing number of SBSs each with ever‐shrinking cell size will result in the spectrum scarcity and pose critical challenges to the spectrum management. Towards the centralized spectrum management system, a third‐party authority is employed to coordinate the spectrum sensing, sharing, and allocation among participants. However, a centralized authority is vulnerable to numerous security threats, such as single point of failure, denial of service attacks, and privacy disclosure, and cannot guarantee fair and efficient spectrum management without mutual trusts among participants. To address these problems, a novel framework of blockchain‐aided spectrum management is designed to securely record the spectrum auction data and spectrum allocation data in the decentralized spectrum sharing. Moreover, a trust management scheme is proposed to evaluate the trusts of all UAVs participating in the decentralized spectrum sharing, where the trust increase depends on legal use of spectrum allocation and honest report of spectrum sensing. In particular, it is shown that the proposed trust management can not only incentivize the UAVs to comply with the legal rule of spectrum sharing in blockchain, but also punish the malicious behaviour that either violates the spectrum sharing rule or provides misleading spectrum sensing results.

Abstract Background Cross-species comparison of transcriptomes is important for elucidating evolutionary molecular mechanisms underpinning phenotypic variation between and within species, yet to date it has been essentially limited to model organisms with relatively small sample sizes. Results Here, we systematically analyze and compare 10,830 and 4866 publicly available RNA-seq samples in humans and cattle, respectively, representing 20 common tissues. Focusing on 17,315 orthologous genes, we demonstrate that mean/median gene expression, inter-individual variation of expression, expression quantitative trait loci, and gene co-expression networks are generally conserved between humans and cattle. By examining large-scale genome-wide association studies for 46 human traits (average n = 327,973) and 45 cattle traits (average n = 24,635), we reveal that the heritability of complex traits in both species is significantly more enriched in transcriptionally conserved than diverged genes across tissues. Conclusions In summary, our study provides a comprehensive comparison of transcriptomes between humans and cattle, which might help decipher the genetic and evolutionary basis of complex traits in both species.

ObjectiveTo identify the correlation between finger-to-floor distance(FFD) and the spinal function indices and disease activity scores of ankylosing spondylitis (AS) via a multicentre case–control study, and to calculate the optimal cutoff value of FFD using statistical methods.MethodsPatients with AS and healthy individuals were recruited, and the FFD and other spinal mobility values were measured. The correlation between the FFD and the Bath Ankylosing Spondylitis Metric Index (BASMI), Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Bath Ankylosing Spondylitis Functional Index (BASFI) was analyzed using Spearman rank correlation analysis. Receiver operating characteristic (ROC) curves of FFD stratified by gender and age were drawn and their optimal cutoff values were determined.ResultsA total of 246 patients with AS and 246 healthy subjects were recruited. The FFD was strongly correlated with BASMI (r = 0.72, p

Abstract 2D materials are promising nanomaterials for future applications due to their predominant quantum effects and unique properties in optics, electrics, magnetics, and mechanics. However, explorations in unique properties and potential applications of novel 2D materials have been hampered by synthesis and their stability under ambient conditions. Recently, in the graphene, 2D β‐CuI is observed experimentally under ambient conditions. Here, it is shown that this 2D β‐CuI@graphene possesses unexpected piezoresistive effect and room‐temperature ferromagnetism. Moreover, this 2D β‐CuI crystal is likely to be stable in a wide range of temperature, that is, below 900 K. Theoretical studies reveal that the unexpected piezoresistive effect is mainly attributable to the convergence of the electrons on Cu and I atoms to the Fermi level with increasing strain. There is a magnetic moment that is ≈0.97 μB on the edge of β‐CuI nanocrystal created by an iodine vacancy, which is considered the origin of such strong room‐temperature ferromagnetism. Clearly, the 2D β‐CuI@graphene provides a promising nanomaterial in the nano‐sensors with low power consumption pressure and magnetic nano‐devices with a size down to atomic scale. The discovery in the present work will evoke various new 2D nanomaterials with novel properties in nanotechnology, biotechnology, sensor materials, and technologies.

The three distinct medicinal parts of Angelica sinensis (Oliv.) Diels (Ang) roots are the head, body, and tail (ARH, ARB, and ART, respectively). How endophytic fungi shape the differences in metabolic components among these parts remains unclear. We quantified the distribution of active components and endophytic fungi along the ARH, ARB, and ART and their relationships. Based on the metabolic components and their abundances detected via non-target metabolism, the different medicinal parts were distinguishable. The largest number of dominant metabolic components was present in ART. The difference between ART and ARH was the greatest, and ARB was in a transitional state. The dominant active molecules in ART highlight their effects in haemodynamics improvement, antibacterial, anti-inflammatory, and hormone regulation, while ARH and ARB indicated more haemostasis, blood enrichment, neuromodulation, neuroprotection and tranquilisation, hepatoprotection, and antitumour activities than that of ART. The ARHs, ARBs, and ARTs can also be distinguished from each other based on the endophytic fungi at the microbiome level. The most dominant endophytic fungi were distributed in ART; the differences between ART and ARH were the largest, and ARB was in a transition state, which is consistent with the metabolite distributions. Structural equation modelling showed that the endophytic fungi were highly indicative of the metabolic components. Correlation analysis further identified the endophytic fungi significantly positively correlated with important active components, including Condenascus tortuosus, Sodiomyces alcalophilus, and Pleotrichocladium opacum. The bidirectional multivariate interactions between endophytic fungi and the metabolic components shape their spatial variations along the longitudinal direction in the Ang root.

Covalent Organic Frameworks (COFs) have been widely developed in the fields of catalysis, energy storage, and transformation due to their excellent controllability, stability, and porosity, but the un-processable powder nature imposes limitations. Here, we report the designed synthesis of a liquid processable COF material (termed as COFNTC-Fe) in a variety of organic solvents and alkaline solutions via modulating the van der Waals force approach. Through increasing conjugate structure by extending the number of benzene rings in the reaction monomer, the newly developed COFNTC-Fe obtains lower inter-layer interactions and dissolves faster in the same solution compared with small conjugated materials, i.e., COFBTC-Fe. Our experiments along with molecular dynamics simulations reveal that the COFNTC-Fe can be more easily exfoliated to dissolve due to the smaller van der Waals force in the same solvent. Benefitting from the excellent liquid processability, the newly developed COFs can be directly added into Poly(9-vinylcarbazole) solution to form a uniform transport layer to obtain enhanced hole transport rate and more efficient blue light perovskite light-emitting diodes (perovskite LED) devices. This work, therefore, provides a new preparation approach toward liquid processable COF materials to broaden their applications.

Abstract As the COVID‐19 pandemic evolves and new variants emerge, the development of more efficient identification approaches of variants is urgent to prevent continuous outbreaks of SARS‐CoV‐2. Field‐effect transistors (FETs) with two‐dimensional (2D) materials are viable platforms for the detection of virus nucleic acids (NAs) but cannot yet provide accurate information on NA variations. Herein, 2D Indium selenide (InSe) FETs were used to identify SARS‐CoV‐2 variants. The device's mobility and stability were ensured by atomic layer deposition (ALD) of Al2O3. The resulting FETs exhibited sub‐fM detection limits ranging from 10–14 M to 10–8 M. The recognition of single‐nucleotide variations was achieved within 15 min to enable the fast and direct identification of two core mutations (L452R, R203M) in Delta genomes (p

Covalent organic polymers (COPs) have emerged as a unique class of luminescent polymers with pre-designed quasi-ordered architectures. However, their layered stacks and limited solubility preclude further processing for large-scale applications in devices, especially optoelectronic equipment. Herein, a universal strategy to adjust the electron donor–acceptor (D-A) moieties of the building blocks in COPs is proposed, achieved by in situ charge exfoliation of COP blocks into few-layer true solutions in (Lewis) acid and base media. The electron D-A moieties of the building blocks endow the COPs with the ability to accept or donate electrons, by altering the electron cloud distribution as well as the relative energy levels of the frontier molecular orbitals. The resultant soluble COPs can easily be processed into a uniform film by solution processing via the spin-coat method. The obtained COP-N achieves efficient and stable perovskite electroluminescence as a novel hole injection material on indium tin oxide, and the operating lifetime for a perovskite quantum dot light-emitting diodes device exceeds that of a poly(ethylene dioxythiophene):polystyrene sulphonate counterpart. This straightforward electronic regulation strategy provides a new avenue for the rational synthesis of processable reticular molecular polymers for practical electronic devices.

Abstract Understanding the configuration and properties of the simplest lithium‐ion crystal, the Li‐Cl crystal, is essential for developing Li‐based electrochemical energy storage and conversion devices. Under ambient conditions, LiCl in a 1:1 stoichiometry is the only known stable form of the Li‐Cl crystal, and the corresponding crystals are insulating. Here, using cryo‐electron microscopy (cryo‐EM) and X‐ray photoelectron spectroscopy (XPS), this work reports a novel abnormal 2D Li2Cl crystal in ultra‐thin reduced graphene oxide (rGO) membranes by simply soaking the rGO membrane in unsaturated LiCl solution under ambient conditions and showed its high‐resolution image. Unexpectedly, such Li2Cl crystal presents metallic properties rather than insulating properties. Using vacuum filtration of the unsaturated LiCl solution through rGO membranes, this work prepares the rGO membranes with high content Li2Cl, displaying a high areal capacitance of 220 mF cm−2. Remarkably, the Li2Cl‐rGO membranes also exhibit heterostructure property and piezoelectricity. For the excess Li and unique electrical characteristics, these Li2Cl‐rGO membranes can be used as a humidity sensor. These findings point to possibilities for creating new Li‐based materials and fabricating novel high‐performance electronic devices, transistors, and sensors.

Oxyanions-nitrate, bromate, and perchlorate in water bodies can do harms of different levels to human health. Photocatalytic reduction is one of the most promising and effective means to convert them into harmless ions. In this article, we discuss the photocatalytic mechanisms of TiO2 catalyst in nitrogen removal process. The factors determining the catalytic activity and the selectivity of nitrogen are elaborated. An overview of the pathway of photocatalysis toward bromate and perchlorate reduction is presented, and the reduction performance of different photocatalysts is evaluated. It is of vital importance to the development of low-cost photocatalytic materials and the use of their activities.

Abstract Background The early death and health problems of calves caused substantial economic losses in the dairy industry. As the immune system of neonates has not been fully developed, the absorption of maternal immunoglobulin (Ig) from colostrum is essential in protecting newborn calves against common disease organisms in their early life. The overwhelming majority of Ig in bovine whey is transported from the serum. Therefore, Ig concentration in the colostrum and serum of dairy cows are critical traits when estimating the potential disease resistance of its offspring. Results Colostrum, blood, and hair follicle samples were collected from 588 Chinese Holstein cows within 24 h after calving. The concentration of total IgG, IgG1, IgG2, IgA and IgM in both colostrum and serum were detected via ELISA methods. With GCTA software, genome-wide association studies (GWASs) were performed with 91,620 SNPs genotyped by GeneSeek 150 K (140,668 SNPs) chips. As a result, 1, 5, 1 and 29 significant SNPs were detected associated with the concentrations of colostrum IgG1, IgG2, IgA IgM, and serum IgG2 at the genome-wide level (P

BackgroundNon-Hodgkin lymphoma (NHL) is one of the dominant malignancies in the hematological system. This study estimated secular trends in NHL incidence and mortality from 1990 to 2019 and provided comprehensive evaluations of potential age, period, and cohort effects.MethodsAge-period-cohort (APC) model was used to analyze changes in NHL incidence and mortality with age, period, and birth cohort effects based on data from the Global Burden of Disease Study 2019.ResultsThe age-standardized incidence rates (ASIR) of NHL rose by 144.6% and age-standardized mortality rate (ASMR) rose by 27.5% from 1990 to 2019. Local drift for incidence was greater than 0 (p< 0.05) for both genders in each age group. Local drift for mortality rates were greater than 0 (p< 0.05) for males aged 20 to 89 years and females aged 60 to 84 years and less than 0 (p< 0.05) for females aged 20 to 50 years. Period rate ratio (RR) and cohort RR of NHL incidence in China showed an increasing trend, while the trend of male and female mortality was not consistent.ConclusionsNHL incidence and mortality rates have been increasing in China over the past three decades. Males and older individuals were at high risk for NHL. Thus, attention to the prevention and therapy of NHL would be essential to lessen the disease burden of NHL.

Abstract 2D materials van der Waals heterostructures (vdWHs) provide a revolutionary route toward high‐performance solar energy conversion devices beyond the conventional silicon‐based pn junction solar cells. Despite tremendous research progress accomplished in recent years, the searches of vdWHs with exceptional excitonic solar cell conversion efficiency and optical properties remain an open theoretical and experimental quest. Here, this study shows that the vdWH family composed of MoSi2N4 and WSi2N4 monolayers provides a compelling material platform for developing high‐performance ultrathin excitonic solar cells and photonics devices. Using first‐principle calculations, 51 types of MoSi2N4 and WSi2N4‐based [(Mo,W)Si2N4] vdWHs composed of various metallic, semimetallic, semiconducting, insulating, and topological 2D materials are constructed and classified. Intriguingly, MoSi2N4/(InSe, WSe2) are identified as Type II vdWHs with exceptional excitonic solar cell power conversion efficiency reaching well over 20%, which are competitive to state‐of‐the‐art silicon solar cells. The (Mo,W)Si2N4 vdWH family exhibits strong optical absorption in both the visible and UV regimes. Exceedingly large peak UV absorptions over 40%, approaching the maximum absorption limit of a freestanding 2D material, can be achieved in (Mo,W)Si2N4/α2‐(Mo,W)Ge2P4 vdWHs. The findings unravel the enormous potential of (Mo,W)Si2N4 vdWHs in designing ultimately compact excitonic solar cell device technology.

Summary: The preparation technology of unconventional low-dimensional Cu2O monocrystals, which exhibit specific crystal planes and present significantly unique interfacial and physicochemical properties, is attracting increasing attention and interest. Herein, by integrating a high-temperature oxidation process under vacuum and a pure-water incubation process under ambient conditions, we propose the self-assembled growth and synthesis of quasi-two-dimensional Cu2O monocrystals on reduced graphene oxide (rGO) membranes. The prepared Cu2O crystals have a single (110) crystal plane, regular rectangular morphology, and potentially well conductivity. Experimental and theoretical results suggest that this assembly is attributed to the pre-nucleation clusters aggregation and directional attachment of Cu and O on the rGO membranes in aqueous environment and cation-π interactions between the (110) crystal plane of Cu2O and rGO surface. Our findings offer a potential avenue for the discovery and design of advanced low-dimensional single-crystal materials with specific interfacial properties in a pure aqueous environment.

The tractor is the primary power device of the agricultural production process. For the problem that the traditional electro-hydraulic hitch control method for tractors cannot simultaneously meet the requirements of maintaining a constant ploughing depth and improving traction performance and electric tractor overall efficiency, this paper proposes a hydraulic cylinder pressure control method of the electro-hydraulic hitch system for electric tractors. We establish a tractor-implement system dynamic model, calculate the rear axle load of the tractor in real-time according to the actual working parameters under the premise of ensuring the constant ploughing depth, construct a traction performance objective optimization function, and use the genetic algorithm to solve the optimal hydraulic cylinder pressure value of the electro-hydraulic hitch system. Hardware-in-the-loop (HIL) simulation results show that the electric tractor under the traditional position control method and the hydraulic cylinder pressure control method has an average wheel slip of 18.50% and 16.93%, an average traction efficiency of 71.35% and 73.08%, and an average overall efficiency of 50.81% and 52.40%. The hydraulic cylinder pressure control method proposed in this paper reduces the wheel slip by 9.27%, increases the traction efficiency by 2.42%, improves the electric tractor overall efficiency by 3.13%, and reduces the electric tractor overall energy loss by 7.67% compared with the traditional position-control method. Therefore, the hydraulic cylinder pressure control method of the electro-hydraulic hitch system proposed in this paper can achieve the purpose of effectively improving tractor traction performance and reducing tractor energy loss while maintaining a constant ploughing depth. This study offers technological references for electric tractors to improve traction performance and reduce the overall energy loss of electric tractors.

Enhancer is a non-coding DNA fragment that can be bound with proteins to activate transcription of a gene, hence play an important role in regulating gene expression. Enhancer identification is very challenging and more complicated than other genetic factors due to their position variation and free scattering. In addition, it has been proved that genetic variation in enhancers is related to human diseases. Therefore, identification of enhancers and their strength has important biological meaning. In this paper, a novel model named iEnhancer-MFGBDT is developed to identify enhancer and their strength by fusing multiple features and gradient boosting decision tree (GBDT). Multiple features include k-mer and reverse complement k-mer nucleotide composition based on DNA sequence, and second-order moving average, normalized Moreau-Broto auto-cross correlation and Moran auto-cross correlation based on dinucleotide physical structural property matrix. Then we use GBDT to select features and perform classification successively. The accuracies reach 78.67% and 66.04% for identifying enhancers and their strength on the benchmark dataset, respectively. Compared with other models, the results show that our model is useful and effective intelligent tool to identify enhancers and their strength, of which the datasets and source codes are available at https://github.com/shengli0201/iEnhancer-MFGBDT1.

Abstract Worldwide use of elite sires has caused inbreeding accumulation and high frequencies of genetic defects in dairy cattle populations. In recent years, several genetic defect genes or haplotypes have been identified in Holstein cattle. A rapid and reliable microfluidic chip with Kompetitive allele‐specific PCR (KASP) assay was developed in our previous study for the detection of heterozygotes at eight genetic defect loci of bovine leukocyte adhesion deficiency (BLAD), Brachyspina syndrome (BS), complex vertebral malformation (CVM), Holstein haplotype 1 (HH1), Holstein haplotype 3 (HH3), Holstein haplotype 4 (HH4), Holstein haplotype 5 (HH5) and haplotype for cholesterol deficiency (HCD). This study aimed to extend that assay to include a newly identified genetic defect of Holstein haplotype 6 (HH6) and to estimate the frequencies of carriers for each of the nine genetic defects in six Chinese Holstein herds. Of the 1633 cows, carrier frequencies of the genetic defects were 6.92%, 5.76%, 4.46%, 4.30%, 3.62%, 2.94%, 1.86% and 0.37% for HH1, HH3, CVM, HH5, HCD, BS, HH6 and BLAD, respectively. No carrier was found for HH4. Notably, 27.43% of cows carried at least one genetic defect, while 2.27% and 0.12% of cows carried double and triple genetic defect alleles, respectively. The existence of genetic defects calls for routine molecular testing and effective management of genetic defects by avoiding carrier‐to‐carrier mating in production herds and eliminating or at least reducing the frequency of the defective alleles through marker‐assisted selection in breeding herds.

Abstract Background Characterization of the molecular mechanisms underlying hair follicle development is of paramount importance in the genetic improvement of wool-related traits in sheep and skin-related traits in humans. The Merino is the most important breed of fine-wooled sheep in the world. In this study, we systematically investigated the complexity of sheep hair follicle development by integrating transcriptome and methylome datasets from Merino sheep skin. Results We analysed 72 sequence datasets, including DNA methylome and the whole transcriptome of four gene types, i.e. protein-coding genes (PCGs), lncRNAs, circRNAs, and miRNAs, across four embryonic days (E65, E85, E105, and E135) and two postnatal days (P7 and P30) from the skin tissue of 18 Merino sheep. We revealed distinct expression profiles of these four gene types across six hair follicle developmental stages, and demonstrated their complex interactions with DNA methylation. PCGs with stage-specific expression or regulated by stage-specific lncRNAs, circRNAs, and miRNAs were significantly enriched in epithelial differentiation and hair follicle morphogenesis. Regulatory network and gene co-expression analyses identified key transcripts controlling hair follicle development. We further predicted transcriptional factors (e.g. KLF4, LEF1, HOXC13, RBPJ, VDR, RARA, and STAT3) with stage-specific involvement in hair follicle morphogenesis. Through integrating these stage-specific genomic features with results from genome-wide association studies (GWAS) of five wool-related traits in 7135 Merino sheep, we detected developmental stages and genes that were relevant with wool-related traits in sheep. For instance, genes that were specifically upregulated at E105 were significantly associated with most of wool-related traits. A phenome-wide association study (PheWAS) demonstrated that candidate genes of wool-related traits (e.g. SPHK1, GHR, PPP1R27, CSRP2, EEF1A2, and PTPN1) in sheep were also significantly associated with dermatological, metabolic, and immune traits in humans. Conclusions Our study provides novel insights into the molecular basis of hair follicle morphogenesis and will serve as a foundation to improve breeding for wool traits in sheep. It also indicates the importance of studying gene expression in the normal development of organs in understanding the genetic architecture of economically important traits in livestock. The datasets generated here are useful resources for functionally annotating the sheep genome, and for elucidating early skin development in mammals, including humans.

Lung adenocarcinoma (LUAD) is a typical disease regarded as having multi-stage progression. However, many existing methods often ignore the critical differences among these stages, thereby limiting their effectiveness for discovering key biological molecules and biological functions as signals at each stage. In this study, we propose a method to discover the evolution between biological molecules and biological functions by investigating the multi-stage biological molecules of LUAD. The method is based on the random walk algorithm and the Monte Carlo method to generate clusters as the modules, which were used as subgraphs of the differentiated biological molecules network in each stage. The connection between modules of adjacent stages is based on the measurement of the Jaccard coefficient. The online gene set enrichment analysis tool (DAVID) was used to obtain biological functions corresponding to the individual important modules. The core evolution network was constructed by combining the aforementioned two networks. Since the networks here are all dynamic, we also propose a strategy to visualize the dynamic information together in one network. Eventually, 12 core modules and 11 core biological functions were found through such evolutionary analyses. Among the core biological functions that we obtained, six functions are related to the disease, the biological function of neutrophil chemotaxis is not directly associated with LUAD but can serve as a predictor, two functions may serve as a predictive signal, and two functions need to be verified through more biological evidence. Compared with two alternative design methods, the method proposed in this study performed more efficiently.

The return to the Moon and the landing on Mars has emphasized the need for greater attention to the effects of partial gravity on human health. Here, we sought to devise a new type of simulated partial gravity apparatus that could more efficiently and accurately provide a partial gravity environment for rat hindlimbs. The new apparatus uses a pulley system and tail suspension to create the simulated partial gravity of the rat’s hind limbs by varying the weight in a balance container attached to the pulley system. An experiment was designed to verify the reliability and stability of the new apparatus. In this experiment, 25 seven-week-old male Wistar Hannover rats were randomly divided into five groups (n = 5 per group): hindlimb full weight-bearing control (1G), sham (1G), and the simulated gravity groups including Mars (3/8G), Moon (1/6G), and interplanetary space (microgravity: µG). The levels of partial gravity experienced by rat hindlimbs in the Mars and Moon groups were provided by a novel simulated partial gravity device. Changes in bone parameters [overall bone mineral density (BMD), trabecular BMD, cortical BMD, cortical bone thickness, minimum moment of area (MMA), and polar moment of area (PMA)] were evaluated using computed tomography in all rats at the proximal, middle, and distal regions of femur and tibia. Reduced gravity led to decreases in bone parameters (overall BMD, trabecular BMD, cortical BMD, MMA, and PMA) in the simulated gravity groups, mainly in distal femur and proximal tibia. The proximal tibia, MMA, and PMA findings indicated greater weakness in the µG group than in the Mars group. The sham group design also excluded the decrease in lower limb bone parameters caused by the suspension attachment of the rat’s tail. The new simulated partial gravity apparatus can provide a continuous and stable level of partial gravity. It offers a reliable and valuable model for studying the effects of extraterrestrial gravity environments on humans.

Abstract Background Our previous genome-wide association study (GWAS) on milk fatty acid traits in Chinese Holstein cows revealed, the SNP, BTB-01556197, was significantly associated with C10:0 at genome-wide level (P = 0.0239). It was located in the down-stream of 5-hydroxytryptamine receptor 1B (HTR1B) gene that has been shown to play an important role in the regulation of fatty acid oxidation. Hence, we considered it as a promising candidate gene for milk fatty acids in dairy cattle. In this study, we aimed to investigate whether the HTR1B gene had significant genetic effects on milk fatty acid traits. Results We re-sequenced the entire coding region and 3000 bp of 5′ and 3′ flanking regions of HTR1B gene. A total of 13 SNPs was identified, containing one in 5′ flanking region, two in 5′ untranslated region (UTR), two in exon 1, five in 3′ UTR, and three in 3′ flanking region. By performing genotype-phenotype association analysis with SAS9.2 software, we observed that 13 SNPs were significantly associated with medium-chain saturated fatty acids such as C6:0, C8:0 and C10:0 (P T) that reduced amino acid change from alanine to serine, we predicted that it altered the secondary structure of HTR1B protein with SOPMA. In addition, we predicted that three SNPs in promoter region, g.17307103A > T, g.17305206 T > G and g.17303761C > T, altered the binding sites of transcription factors (TFs) HMX2, PAX2, FOXP1ES, MIZ1, CUX2, DREAM, and PPAR-RXR by Genomatix. Of them, luciferase assay experiment further confirmed that the allele T of g.17307103A > T significantly increased the transcriptional activity of HTR1B gene than allele A (P = 0.0007). Conclusions In conclusion, our findings provided first evidence that the HTR1B gene had significant genetic effects on milk fatty acids in dairy cattle.

Abstract Background Genetic improvement of wool and growth traits is a major goal in the sheep industry, but their underlying genetic architecture remains elusive. To improve our understanding of these mechanisms, we conducted a weighted single-step genome-wide association study (WssGWAS) and then integrated the results with large-scale transcriptome data for five wool traits and one growth trait in Merino sheep: mean fibre diameter (MFD), coefficient of variation of the fibre diameter (CVFD), crimp number (CN), mean staple length (MSL), greasy fleece weight (GFW), and live weight (LW). Results Our dataset comprised 7135 individuals with phenotype data, among which 1217 had high-density (HD) genotype data (n = 372,534). The genotypes of 707 of these animals were imputed from the Illumina Ovine single nucleotide polymorphism (SNP) 54 BeadChip to the HD Array. The heritability of these traits ranged from 0.05 (CVFD) to 0.36 (MFD), and between-trait genetic correlations ranged from − 0.44 (CN vs. LW) to 0.77 (GFW vs. LW). By integrating the GWAS signals with RNA-seq data from 500 samples (representing 87 tissue types from 16 animals), we detected tissues that were relevant to each of the six traits, e.g. liver, muscle and the gastrointestinal (GI) tract were the most relevant tissues for LW, and leukocytes and macrophages were the most relevant cells for CN. For the six traits, 54 quantitative trait loci (QTL) were identified covering 81 candidate genes on 21 ovine autosomes. Multiple candidate genes showed strong tissue-specific expression, e.g. BNC1 (associated with MFD) and CHRNB1 (LW) were specifically expressed in skin and muscle, respectively. By conducting phenome-wide association studies (PheWAS) in humans, we found that orthologues of several of these candidate genes were significantly (FDR

Abstract Two-dimensional (2D) semiconductors are promising channel materials for next-generation field-effect transistors (FETs) thanks to their unique mechanical properties and enhanced electrostatic control. However, the performance of these devices can be strongly limited by the scattering processes between carriers and phonons, usually occurring at high rates in 2D materials. Here, we use quantum transport simulations calibrated on first-principle computations to report on dissipative transport in antimonene and arsenene n-type FETs at the scaling limit. We show that the widely-used approximations of either ballistic transport or simple acoustic deformation potential scattering result in large overestimation of the ON current, due to neglecting the dominant intervalley and optical phonon scattering processes. We additionally investigate a recently proposed valley engineering strategy to improve the device performance by removing the valley degeneracy and suppressing most of the intervalley scattering channels via an uniaxial strain along the zigzag direction. The method is applicable to other similar 2D semiconductors characterized by multivalley transport.

This study compared the effects of four forest canopies on throughfall chemistry in the Qinling Mountains, China. Rainfall and throughfall samples were collected in stands of Quercus aliena (Qa) var. Acuteserrata, Pinus tabulaeformis (Pt), P. armandii (Pa), and mixed broad-leaved (Mb) trees from 2009 to 2011. The results indicated that the pH of the rainfall, which was mildly acidic, increased as it passed through the forest canopy. The pH increased more within the broad-leaved forest canopy than the coniferous forest. Concentrations of decreased as rainfall passed through the Qa canopy but increased after passing through the other species. The concentrations of and Zn, Cd and Pb decreased as rainfall passed through the four canopies. The coniferous forest canopy was more effective than the broad-leaved forest in reducing in rainwater. The decreases in Cd concentrations were similar among the four canopies. The Pb concentration decreased the most among the heavy metals, and the order of the decrease was Qa > Pt > Pa > Mb. The results may provide a basis for the selection of tree species for afforestation in water sources in the Qinling Mountains and similar areas. HIGHLIGHTS The broad-leaved forest canopies increased acidic rainfall pH more than the coniferous forest canopies.; The coniferous forest canopies were more effective in reducing in the rainwater.; The order of canopy decreasing Pb concentrations was Quercus aliena > Pinus tabulaeformis > P. armandii > mixed broad-leaved trees.; The decreases in Cd concentrations were similar among the four canopies.;

Aboveground biomass (AGB) is an essential assessment of plant development and guiding agricultural production management in the field. Therefore, efficient and accurate access to crop AGB information can provide a timely and precise yield estimation, which is strong evidence for securing food supply and trade. In this study, the spectral, texture, geometric, and frequency-domain variables were extracted through multispectral imagery of drones, and each variable importance for different dimensional parameter combinations was computed by three feature parameter selection methods. The selected variables from the different combinations were used to perform potato AGB estimation. The results showed that compared with no feature parameter selection, the accuracy and robustness of the AGB prediction models were significantly improved after parameter selection. The random forest based on out-of-bag (RF-OOB) method was proved to be the most effective feature selection method, and in combination with RF regression, the coefficient of determination (R2) of the AGB validation model could reach 0.90, with root mean square error (RMSE), mean absolute error (MAE), and normalized RMSE (nRMSE) of 71.68 g/m2, 51.27 g/m2, and 11.56%, respectively. Meanwhile, the regression models of the RF-OOB method provided a good solution to the problem that high AGB values were underestimated with the variables of four dimensions. Moreover, the precision of AGB estimates was improved as the dimensionality of parameters increased. This present work can contribute to a rapid, efficient, and non-destructive means of obtaining AGB information for crops as well as provide technical support for high-throughput plant phenotypes screening.

The inter-organelle interactions, including the cytomembrane, endoplasmic reticulum, mitochondrion, lysosome, dictyosome, and nucleus, play the important roles in maintaining the normal function and homeostasis of cells. Organelle dysfunction can lead to a range of diseases (e.g., Alzheimer’s disease (AD), Parkinson’s disease (PD), and cancer), and provide a new perspective for drug discovery. With the development of imaging techniques and functional fluorescent probes, a variety of algorithms and strategies have been developed for the ever-improving estimation of subcellular structures, organelle interaction, and organelle-related drug discovery with accounting for the dynamic structures of organelles, such as the nanoscopy technology and molecular dynamics (MD) simulations. Accordingly, this work summarizes a series of state-of-the-art examples of the recent progress in this rapidly changing field and uncovering the drug screening based on the structures and interactions of organelles. Finally, we propose the future outlook for exciting applications of organelle-related drug discovery, with the cooperation of nanoscopy and MD simulations.

Objective An initial RNA-Sequencing study revealed that UDP-galactose-4-epimerase (GALE) was one of the most promising candidates for milk protein concentration in Chinese Holstein cattle. This enzyme catalyzes the interconversion of UDP-galactose and UDP-glucose, an important step in galactose catabolism. To further validate the genetic effect of GALE on milk protein traits, genetic variations were identified, and genotypes-phenotypes associations were performed. Methods The entire coding region and the 5′-regulatory region (5′-UTR) of GALE were re-sequenced using pooled DNA of 17 unrelated sires. Association studies for five milk production traits were performed using a mixed linear animal model with a population encompassing 1,027 Chinese Holstein cows. Results A total of three variants in GALE were identified, including two novel variants (g.2114 A>G and g.2037 G>A) in the 5′-UTR and one previously reported variant (g.3836 G>C) in an intron. All three single nucleotide polymorphisms (SNPs) were associated with milk yield (pC. Conclusion Overall, our findings provided new insights into the polymorphic variations in bovine GALE gene and their associations with milk protein concentration. The data indicate their potential uses for marker-assisted breeding or genetic selection schemes.

In the blockchain, the consensus mechanism plays a key role in maintaining the security and legitimation of contents recorded in the blocks. Various blockchain consensus mechanisms have been proposed. However, there is no technical analysis and comparison as a guideline to determine which type of consensus mechanism should be adopted in a specific scenario/application. To this end, this work investigates three mainstream consensus mechanisms in the blockchain, namely, Proof of Work (PoW), Proof of Stake (PoS), and Direct Acyclic Graph (DAG), and identifies their performances in terms of the average time to generate a new block, the confirmation delay, the Transaction Per Second (TPS) and the confirmation failure probability. The results show that the consensus process is affected by both network resource (computation power/coin age, buffer size) and network load conditions. In addition, it shows that PoW and PoS are more sensitive to the change of network resource while DAG is more sensitive to network load conditions.

Abstract Background Lack of comprehensive functional annotations across a wide range of tissues and cell types severely hinders the biological interpretations of phenotypic variation, adaptive evolution, and domestication in livestock. Here we used a combination of comparative epigenomics, genome-wide association study (GWAS), and selection signature analysis, to shed light on potential adaptive evolution in cattle. Results We cross-mapped 8 histone marks of 1300 samples from human to cattle, covering 178 unique tissues/cell types. By uniformly analyzing 723 RNA-seq and 40 whole genome bisulfite sequencing (WGBS) datasets in cattle, we validated that cross-mapped histone marks captured tissue-specific expression and methylation, reflecting tissue-relevant biology. Through integrating cross-mapped tissue-specific histone marks with large-scale GWAS and selection signature results, we for the first time detected relevant tissues and cell types for 45 economically important traits and artificial selection in cattle. For instance, immune tissues are significantly associated with health and reproduction traits, multiple tissues for milk production and body conformation traits (reflecting their highly polygenic architecture), and thyroid for the different selection between beef and dairy cattle. Similarly, we detected relevant tissues for 58 complex traits and diseases in humans and observed that immune and fertility traits in humans significantly correlated with those in cattle in terms of relevant tissues, which facilitated the identification of causal genes for such traits. For instance, PIK3CG, a gene highly specifically expressed in mononuclear cells, was significantly associated with both age-at-menopause in human and daughter-still-birth in cattle. ICAM, a T cell-specific gene, was significantly associated with both allergic diseases in human and metritis in cattle. Conclusion Collectively, our results highlighted that comparative epigenomics in conjunction with GWAS and selection signature analyses could provide biological insights into the phenotypic variation and adaptive evolution. Cattle may serve as a model for human complex traits, by providing additional information beyond laboratory model organisms, particularly when more novel phenotypes become available in the near future.

With the development of blockchain technology,more and more blockchain projects have appeared.Due to the closure property of the blockchain,different blockchains have become islands of value.The information interaction and value transfer problems between different blockchains need to be solved urgently.The cross-chain technology is to solve the cross-chain operation problems of assets and data between different chains.There are many attempts and developments on cross-chain technology in the past few years,and the major models of cross-chain include Hash lock,notary mechanism,side chain and relay technology,etc.The concept of each cross-chain technology was introduced,and the advantages and disadvantages of each cross-chain technology were summarized and analyzed.

Identifying epigenetic changes is essential for an in-depth understanding of phenotypic diversity and pigs as the human medical model for anatomizing complex diseases. Abnormal sperm DNA methylation can lead to male infertility, fetal development failure, and affect the phenotypic traits of offspring. However, the whole genome epigenome map in pig sperm is lacking to date. In this study, we profiled methylation levels of cytosine in three commercial pig breeds, Landrace, Duroc, and Large White using whole-genome bisulfite sequencing (WGBS). The results showed that the correlation of methylation levels between Landrace and Large White pigs was higher. We found that 1,040–1,666 breed-specific hypomethylated regions (HMRs) were associated with embryonic developmental and economically complex traits for each breed. By integrating reduced representation bisulfite sequencing (RRBS) public data of pig testis, 1743 conservated HMRs between sperm and testis were defined, which may play a role in spermatogenesis. In addition, we found that the DNA methylation patterns of human and pig sperm showed high similarity by integrating public data from WGBS and chromatin immunoprecipitation sequencing (ChIP-seq) in other mammals, such as human and mouse. We identified 2,733 conserved HMRs between human and pig involved in organ development and brain-related traits, such as NLGN1 (neuroligin 1) containing a conserved-HMR between human and pig. Our results revealed the similarities and diversity of sperm methylation patterns among three commercial pig breeds and between human and pig. These findings are beneficial for elucidating the mechanism of male fertility, and the changes in commercial traits that undergo strong selection.

Milk protein is one of the most important economic traits in the dairy industry. Yet, the regulatory network of miRNAs for the synthesis of milk protein in mammary is poorly understood. Samples from 12 Chinese Holstein cows with three high ( ≥ 3.5%) and three low ( ≤ 3.0%) phenotypic values for milk protein percentage in lactation and non-lactation were examined through deep small RNA sequencing. We characterized 388 known and 212 novel miRNAs in the mammary gland. Differentially expressed analysis detected 28 miRNAs in lactation and 52 miRNAs in the non-lactating period with a highly significant correlation with milk protein concentration. Target prediction and correlation analysis identified some key miRNAs and their targets potentially involved in the synthesis of milk protein. We analyzed for enrichments of GWAS signals in miRNAs and their correlated targets. Our results demonstrated that genomic regions harboring DE miRNA genes in lactation were significantly enriched with GWAS signals for milk protein percentage traits and that enrichments within DE miRNA targets were significantly higher than in random gene sets for the majority of milk production traits. This integrated study on the transcriptome and posttranscriptional regulatory profiles between significantly differential phenotypes of milk protein concentration provides new insights into the mechanism of milk protein synthesis, which should reveal the regulatory mechanisms of milk secretion.

To support the big-data processing needs of large-scale deployments of smart devices, there is significant interest in moving from cloud-computing to multi-agent (fog-computing) models, given these algorithms scalability and self-healing properties with respect to nodes and link failures. However, these algorithms are often based on the average consensus primitive, which is, unfortunately, vulnerable to data injection attacks. Recognizing this challenge, this work proposes three novel methods for detecting and localizing adversarial nodes using neural network (NN) models. The methods proposed are based on fully distributed algorithms, wherein each node locally updates its local states by exchanging information with its neighbors without supervision. Compared to the state-of-the-art, the proposed approach leverages the automatic learning characteristics of NN to reduce the dependence on pre-designed models and human expertise in complex internal attack scenarios. Simulation results show that the NN-based methods can significantly improve the attacker detection and localization performance.