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Abstract Plant genebanks contain large numbers of germplasm accessions that likely harbor useful alleles or genes absent in commercial plant breeding programs. Broadening the genetic base of commercial alfalfa germplasm with these valuable genetic variations can be achieved by screening the extensive genetic diversity in germplasm collections and enabling maximal recombination among selected genotypes. In this study, we assessed the genetic diversity and differentiation of germplasm pools selected in northern U.S. latitudes (USDA Plant Hardiness Zone 7 or below) originating from Eurasian germplasm. The germplasm evaluated included four BASE populations (C0) from different geographical origins (Central Asia, Northeastern Europe, Balkans-Turkey-Black Sea, and Siberia/Mongolia), 20 cycle-one populations (C1) derived from each of the four BASE populations selected across five locations in the U.S. and Canada, and four commercial cultivars. Using a panel of 3,000 Diversity Array Technologies (DArTag) marker loci, we retrieved 2,994 target SNPs and approximately 12,000 microhaplotypes. Microhaplotypes exhibited higher genetic diversity values than target SNPs. Principal component analysis and discriminant analysis of principal components revealed significant population structure among the alfalfa populations based on geographical origin, while the check cultivars formed a central cluster. Inbreeding coefficients (FIS) ranged from − 0.1 to 0.006, with 27 out of 28 populations showing negative FIS values, indicating an excess of heterozygotes. Interpopulation genetic distances were calculated using Rho pairwise distances (FST adapted for autotetraploid species) and analysis of molecular variance (AMOVA) parameters. All BASE populations showed lower Rho values compared to C1 populations and check cultivars. AMOVA revealed that most of the genetic diversity was among individuals within populations, especially in BASE populations (92.7%). This study demonstrates that individual plants in BASE populations possess high genetic diversity, low interpopulation distances, and minimal inbreeding, characteristics that are essential for base-broadening selection. The populations developed in this project serve as valuable sources of novel alleles for North American alfalfa breeding programs, offering breeders access to diverse, regionally adapted pools for improving various alfalfa traits.

Two rare-earth-induced peroxo-polyoxotungstates (peroxo-POTs), namely, two-dimensional [Ln2(H2O)4(OH)P2W6(O2)4O23]3− (2D-Ln2, Ln = Pr, Sm) and one-dimensional [Ln(H2O)4P4W6(O2)6(OH)4O24]5− (1D-Ln, Ln = Gd, Tb, Dy, Ho), were successfully prepared by similar synthesis methods based on that used to synthesize {P3W6(O2)6} clusters. However, although the original {P3W6(O2)6} building block remained, a completely new structure was achieved in these two lanthanide-based peroxo-POT derivatives that was induced by the rare-earth cations. 2D-Ln2 was composed of {P2W6(O2)4} polyanion units linked by replacing {PW3(O2)3} with {PW3(O2)2}, while 1D-Ln was composed of two symmetric {P2W3(O2)3} cores connected by rare-earth cations. Furthermore, the proton conductivities of 2D-Ln2 and 1D-Ln were investigated. At 65 °C and 95% relative humidity (RH), 2D-Pr2 and 1D-Tb exhibited conductivities of 2.62 × 10−3 and 2.78 × 10−3 S∙cm−1, respectively, while the conductivities of their corresponding Nafion membranes were considerably higher, with values of 1.65 × 10−1 and 1.44 × 10−1 S∙cm−1, respectively, under the same conditions.

Abstract Salvia hispanica L. (Chia), a member of the Lamiaceae, is an economically important crop in Mesoamerica, with health benefits associated with its seed fatty acid composition. Chia varieties are distinguished based on seed color including mixed white and black (Chia pinta) and black (Chia negra). To facilitate research on Chia and expand on comparative analyses within the Lamiaceae, we generated a chromosome‐scale assembly of a Chia pinta accession and performed comparative genome analyses with a previously published Chia negra genome assembly. The Chia pinta and Chia negra genome sequences were highly similar as shown by a limited number of single nucleotide polymorphisms and extensive shared orthologous gene membership. However, there is an enrichment of terpene synthases in the Chia pinta genome relative to the Chia negra genome. We sequenced and analyzed the genomes of 20 Chia accessions with differing seed color and geographic origin revealing population structure within S. hispanica and interspecific introgressions of Salvia species. As the genus Salvia is polyphyletic, its evolutionary history remains unclear. Using large‐scale synteny analysis within the Lamiaceae and orthologous group membership, we resolved the phylogeny of Salvia species. This study and its collective resources further our understanding of genomic diversity in this food crop and the extent of interspecies hybridizations in Salvia.

Alfalfa biomass can be fractionated into leaf and stem components. Leaves comprise a protein-rich and highly digestible portion of biomass for ruminant animals, while stems constitute a high fiber and less digestible fraction, representing 50 to 70% of the biomass. However, little attention has focused on stem-related traits, which are a key aspect in improving the nutritional value and intake potential of alfalfa. This study aimed to identify molecular markers associated with four morphological traits in a panel of five populations of alfalfa generated over two cycles of divergent selection based on 16-h and 96-h in vitro neutral detergent fiber digestibility in stems. Phenotypic traits of stem color, presence of stem pith cells, winter standability, and winter injury were modeled using univariate and multivariate spatial mixed linear models (MLM), and the predicted values were used as response variables in genome-wide association studies (GWAS). The alfalfa panel was genotyped using a 3K DArTag SNP markers for the evaluation of the genetic structure and GWAS. Principal component and population structure analyses revealed differentiations between populations selected for high- and low-digestibility. Thirteen molecular markers were significantly associated with stem traits using either univariate or multivariate MLM. Additionally, support vector machine (SVM) and random forest (RF) algorithms were implemented to determine marker importance scores for stem traits and validate the GWAS results. The top-ranked markers from SVM and RF aligned with GWAS findings for solid stem pith, winter standability, and winter injury. Additionally, SVM identified additional markers with high variable importance for solid stem pith and winter injury. Most molecular markers were located in coding regions. These markers can facilitate marker-assisted selection to expedite breeding programs to increase winter hardiness or stem palatability.

Breeding programs around the world continually collect data on large numbers of individuals. To be able to combine data collected across regions, years, and experiments, research communities develop standard operating procedures for data collection and measurement. One such method is a crop ontology, or a standardized vocabulary for collecting data on commonly measured traits. The ontology is also computer readable to facilitate the use of data management systems such as databases. Blueberry breeders and researchers across the United States have come together to develop the first standardized crop ontology in blueberry (Vaccinium spp.). We provide an overview and report on the construction of the first blueberry crop ontology and the 178 traits and methods included within. Researchers of Vaccinium species—such as other blueberry species, cranberry, lingonberry, and bilberry—can use the described crop ontology to collect phenotypic data of greater quality and consistency, interoperability, and computer readability. Crop ontologies, as a shared data language, benefit the entire worldwide research community by enabling collaborative meta-analyses that can be used with genomic data for quantitative trait loci, genome-wide association studies, and genomic selection analysis.

Objective To compare the supply data of red blood cells(RBCs) from 18 blood centers in China before and after the outbreak of COVID-19 during 2018 to 2021. Methods Eight indicators related to RBCs supply from 18 blood centers in China during 2018-2021 were collected retrospectively, including the storage of total amount of qualified RBCs (referred to as the total amount of storage), the distribution of total amount of RBCs (referred to as the total amount of distribution), the distribution amount of RBCs per 1 000 population (referred to as the amount of distribution per 1 000 population), the distribution amount of RBCs from 400 mL original blood per 1 000 population [referred to as the amount of distribution per 1 000 population (400 mL)], the average daily distribution amount of RBCs (referred to as the average daily distribution amount), the average daily storage amount of RBCs (referred to as the average daily storage amount), the average storage days of RBCs when distribute (referred to as the RBC storage days), and the expired amount of RBCs (referred to as the expired amount). Based on the outbreak time of COVID-19, the data of 2018 and 2019 were the pre-pandemic group, and the data of 2020 and 2021 were the post-pandemic group. Results Data on RBCs supply in 18 blood centers from 2018 to 2021(comparison of the pre-pandemic group and the post-pandemic group): the amount of distribution per 1 000 population (median 14.68 U>13.92 U) decreased, the amount of distribution per 1 000 population (400 mL) (median 10.16 U>9.21 U) decreased, and the difference was statistically significant (P99 084.08 U) decreased, the amount of distribution per 1 000 population (median 15.04 U>12.19 U) decreased, the amount of distribution per 1000 population (400 mL) (median 10.11 U>8.94 U), the average daily distribution amount(322.66 U>270.73 U) decreased and RBC storage days (median 10.50 d324.46 U), the average daily inventory (median 3 222.00 U0.00 U) decreased, the difference has statistical significance (P

Annual medic (Medicago spp.) germplasm was collected from the Crimean Peninsula of Ukraine in 2008 to fill gaps in geographic coverage in the United States department of Agriculture, Agricultural Research Service, National Plant Germplasm System (NPGS) temperate-adapted forage legume collection. A total of 102 accessions across 10 Medicago species were collected. To assess genetic diversity, population structure, and to confirm taxonomic identities, the collections were phenotypically and genetically characterized. Phenotyping included the use of 24 descriptor traits while genetic characterization was accomplished using a 3K Diversity Array Technologies (DArTag) panel developed for alfalfa (Medicago sativa L.). For both field and molecular characterizations, a reference set of 92 geographically diverse and species-representative accessions were obtained from the NPGS collection. Phenotypic descriptors showed consistency among replicated plants within accessions, some variation across accessions within species, and evident distinctions between species. Because the DArTag panel was developed for cultivated alfalfa, the transferability of markers to the species being evaluated was limited, resulting in an average of ~1,500 marker loci detected per species. From these loci, 448 markers were present in 95% of the samples. Principal component and phylogenetic analysis based on a larger set of 2,396 selected markers clustered accessions by species and predicted evolutionary relationships among species. Additionally, the markers aided in the taxonomic identity of a few accessions that were likely mislabeled. The genotyping results also showed that sampling individual plants for these mostly self-pollinating species is sufficient due to high reproducibility between single (n=3) and pooled (n=7) biological replicate leaf samples. The phenotyping and the 2,396 Single Nucleotide Polymorphism (SNP) marker set were useful in estimating population structure in the Crimean and reference accessions, highlighting novel and unique genetic diversity captured in the Crimean accessions. This research not only demonstrated the utility of the DArTag marker panel in evaluating the Crimean germplasm but also highlighted its broader application in assessing genetic resources within the Medicago genus. Furthermore, we anticipate that our findings will underscore the importance of leveraging genetic resources and advanced genotyping tools for sustainable crop improvement and biodiversity conservation in annual medic species.

Small public breeding programmes have many barriers to adopting technology, particularly creating and using genetic marker panels for genomic-based decisions in selection. Here we report the creation of a DArTag panel of 3,000 loci distributed across the tetraploid genome of blueberry (Vaccinium corymbosum) for use in molecular breeding and genomic prediction. The creation of this marker panel brings cost-effective and rapid genotyping capabilities to public and private breeding programmes. The open access provided by this platform will allow genetic data sets generated on the marker panel to be compared and joined across projects, institutions and countries. This genotyping resource has the power to make routine genotyping a reality for any breeder of blueberry.

Accurate measurement of a Radar Cross-Section (RCS) is a critical technical challenge in assessing the stealth performance and scattering characteristics of radar targets. Traditional RCS measurement methods are limited by high costs, sensitivity to environmental conditions, and difficulties in distinguishing local scattering features of targets. To address these challenges, this paper proposes a novel RCS measurement method based on enhanced imaging and scattering center extraction. This method integrates sub-aperture imaging with image fusion techniques to improve imaging quality and enhance the detail of target scattering characteristics. Additionally, an improved sequence CLEAN algorithm is employed to effectively suppress sidelobe effects and ensure the accuracy of scattering center extraction. Experimental results demonstrate that this method achieves higher precision in RCS measurement of complex targets and is particularly effective in environments with strong interference, where it successfully separates the scattering contributions of the target from those of the interference sources. This method offers a new technological approach for precise RCS measurement of radar stealth targets in the future.

BackgroundLower extremity motor dysfunction is one of the most severe consequences after stroke, restricting functional mobility and impairing daily activities. Growing evidence suggests that repetitive transcranial magnetic stimulation (rTMS) can improve stroke patients’ lower extremity motor function. However, there is still controversy about the optimal rTMS protocol. Therefore, we compared and analyzed the effects of different rTMS protocols on lower extremity motor function in stroke patients using network meta-analysis (NMA).MethodsWe systematically searched CNKI, WanFang, VIP, CBM, PubMed, Embase, Web of Science, and Cochrane Library databases (from origin to 31 December 2023). Randomized controlled trials (RCTs) or crossover RCTs on rTMS improving lower extremity motor function in stroke patients were included. Two authors independently completed article screening, data extraction, and quality assessment. RevMan (version 5.4) and Stata (version 17.0) were used to analyze the data.ResultsA total of 38 studies with 2,022 patients were eligible for the NMA. The interventions included HFrTMS-M1, LFrTMS-M1, iTBS-Cerebellum, iTBS-M1, dTMS-M1, and Placebo. The results of NMA showed that LFrTMS-M1 ranked first in FMA-LE and speed, and HFrTMS-M1 ranked first in BBS, TUGT, and MEP amplitude. The subgroup analysis of FMA-LE showed that HFrTMS-M1 was the best stimulation protocol for post-stroke time > 1 month, and LFrTMS-M1 was the best stimulation protocol for post-stroke time ≤ 1 month.ConclusionConsidering the impact of the stroke phase on the lower extremity motor function, the current research evidence shows that HFrTMS-M1 may be the preferred stimulation protocol to improve the lower extremity motor function of patients for post-stroke time > 1 month, and LFrTMS-M1 for post-stroke time ≤ 1 month. However, the above conclusion needs further analysis and validation by more high-quality RCTs.Systematic Review Registration:www.crd.york.ac.uk/prospero/, identifier (CRD42023474215).

The development of mobile networks has led to the emergence of challenges such as high delays in storage, computing and traffic management. To deal with these challenges, fifth-generation networks emphasize the use of technologies such as mobile cloud computing and mobile edge computing. Mobile Edge Cloud Computing (MECC) is an emerging distributed computing model that provides access to cloud computing services at the edge of the network and near mobile users. With offloading tasks at the edge of the network instead of transferring them to a remote cloud, MECC can realize flexibility and real-time processing. During computation offloading, the requirements of Internet of Things (IoT) applications may change at different stages, which is ignored in existing works. With this motivation, we propose a task offloading method under dynamic resource requirements during the use of IoT applications, which focuses on the problem of workload fluctuations. The proposed method uses a learning automata-based offload decision-maker to offload requests to the edge layer. An auto-scaling strategy is then developed using a long short-term memory network which can estimate the expected number of future requests. Finally, an Asynchronous Advantage Actor-Critic algorithm as a deep reinforcement learning-based approach decides to scale down or scale up. The effectiveness of the proposed method has been confirmed through extensive experiments using the iFogSim simulator. The numerical results show that the proposed method has better scalability and performance in terms of delay and energy consumption than the existing state-of-the-art methods.

Blueberry (Vaccinium spp.) is one of the most economically important berry crops worldwide. Validation of genetic mapping studies is often hindered by asynchronous marker technology. The development of a standardized genotyping platform that targets a specific set of polymorphic loci can be a practical solution to unify the scientific and breeding community toward blueberry improvement. The objective of this study was to develop and evaluate a targeted genotyping platform for cultivated blueberries that is affordable, reproducible, and sufficiently high density to warrant large-scale adoption for genomic studies. The Flex-Seq platform was developed in a two-step procedure that resulted in 22,000 loci that yielded 194,365 single nucleotide polymorphisms when assessed in a diversity set of 192 samples including cultivated and other related wild Vaccinium species. Locus recovery averaged 89.4% in the cultivated polyploid blueberry (northern highbush [NHB], southern highbush [SHB], and rabbiteye [RE]) and on average 88.8% were polymorphic. While recovery of these loci was lower in the other Vaccinium species assayed, recovery remained high and ranged between 60.8% and 70.4% depending on the taxonomic distance to the cultivated blueberry targeted in this platform. NHB had the highest mean number of variants per locus at 9.7, followed by RE with 9.1, SHB with 8.5, and a range between 7.7 and 8.5 in other species. As expected, the total number of unique-in-state haplotypes exceeded the total number of variants in the domesticated blueberries. Phylogenetic analysis using a subset of the SNPs and haplotypes mostly conformed to known relationships. The platform also offers flexibility about the number of loci, depth of sequencing for accurate dosage calling, loci and haplotype reconstruction from increased fragment length. This genotyping platform will accelerate the development and improvement of blueberry cultivars through genomic-assisted breeding tools.

Summary: Objective: To compare the characteristics of conventional laparoscopic pyeloplasty (LP) and robotic-assisted laparoscopic pyeloplasty (RALP) in infants and young children with ureteropelvic junction obstruction (UPJO). Methods: We performed a retrospective study of patients (age: 0–36 months) who underwent dismembered pyeloplasty (Anderson-Hynes) with the fourth-generation RALP or traditional LP between April 2020 and December 2020. Results: A total of 33 patients with UPJO were enrolled: 12 underwent RALP (9 left side; 3 right side) and 21 underwent LP (18 left side; 3 right side). In the RALP group, the median patient age was 17 months (range: 5–36 months). In the LP group, the median patient age was 9 months (range: 2–36 months) (P = 0.182). The mean operation times were 120.25 ± 37.54 min (RALP) and 156.10 ± 51.11 min (LP) (P = 0.042), and the mean lengths of hospital stay were 6.42 ± 1.62 days (RALP) and 8.19 ± 2.25 days (LP) (P = 0.023). Removal of the drainage tube was performed after 3.08 ± 0.69 days (RALP) and after 4.76 ± 1.81 days (LP) (P = 0.001). The postoperative pain showed no significant difference. The mean hospitalization costs were 61464.75 ± 2800.53 yuan (RALP) and 22169.52 ± 3442.15 yuan (LP) (P

Small public breeding programmes have many barriers to adopting technology, particularly creating and using genetic marker panels for genomic-based decisions in selection. Here we report the creation of a DArTag panel of 3,000 loci distributed across the alfalfa (Medicago sativa L.) genome for use in molecular breeding and genomic insight. The creation of this marker panel brings cost-effective and rapid genotyping capabilities to alfalfa breeding programmes. The open access provided by this platform will allow genetic data sets generated on the marker panel to be compared and joined across projects, institutions and countries. This genotyping resource has the power to make routine genotyping a reality for any breeder of alfalfa.

The sweetpotato weevil, Cylas formicarius elegantulus (Summers) (Coleoptera: Brentidae), is one of the most destructive pests of sweetpotato worldwide. Genomic analyses of sweetpotato weevils can provide insights into their genetic diversity, population structure, and dispersal as well as provide information to support management strategies. Adult sweetpotato weevils were collected by various methods from Ipomoea batatas L. (sweetpotato) or I. coccinea L. (red morning glory) in the U.S. states of Georgia, Hawaii, South Carolina, and Texas. Genomic DNA was extracted from individual weevil specimens and sequenced using Illumina NovaSeq. A total of 181 GB of 150 base pair (bp) paired-end reads were generated for 40 specimens. Mitochondrial genomes were assembled for each specimen via reference mapping and annotated using Geneious Prime. Full mitochondrial genome sequences range from 17,141 to 17,152 bp with an average GC content of 21.8% and average coverage of 3307 × . A maximum likelihood phylogenetic analysis considering the mitochondrial protein coding genes is provided. Mitochondrial genomes and assembled reads are deposited in NCBI GenBank, providing 40 mitogenomes of C. formicarius elegantulus collected in the U.S.

Iridoid compounds are an important class of natural products. Here, the authors report on the discovery and engineering of nepetalactol-related short chain reductases and their application for the biosynthesis of nepetalactol or nepetalactone stereoisomers, as a versatile system for the production of the iridoid natural product scaffold.

Objective To investigate the main causes of blood donor deferral in domestic blood center. Methods The causes of donor deferral were classified into 12 categories as previous medical history, drug use, alcohol consumption, menstrual period, underweight, abnormal blood pressure, abnormal body temperature, abnormal hemoglobin (Hb), lipemic blood, positive hepatitis B surface antigen (HBsAg), elevated alanine aminotransferase (ALT) and others according to the comparison indicators of Asia-Pacific Blood Network (APBN) and the national standard Blood Donor Health Examination Requirements. The relevant data of the top 3 causes of donor deferral, voluntarily reported by the members of Practice Comparison Working Group of China’s Mainland Blood Collection and Supply Institutions from 2014 to 2019, were collected and a histogram was generated. Results The median donor deferral rate of 20 domestic blood centers from 2014 to 2019 was 12.14%, with the lowest at 0.18% and highest at 32.32%, respectively. The top three causes for donor deferral were elevated ALT, abnormal Hb and abnormal blood pressure in year 2014, 2015, 2018 and 2019; elevated ALT, lipemic blood and abnormal blood pressure in 2016; elevated ALT, abnormal Hb, and lipemic blood in 2017. Conclusion The main causes of donor deferral were elevated ALT, abnormal Hb, abnormal blood pressure and lipemic blood.

Objective To explore the recruitment and retention strategy of blood donors by investigating the age composition of blood donors in some areas of China, so as to promote blood donation and enhance clinical blood supply. Methods Through the working platform of Practice Comparison Working Group of China’s Mainland Blood Collection and Supply Institutions, the average age and age composition of blood donors from 22 blood centers were collected, and statistical analysis was conducted after eliminating invalid data. Results The median average age of blood donors during the survey year was 30.02.The median age in 2.89% of the blood centers was lower than 25. The average age of different genders was statistically significant only in 2018(P

An efficient transmission line model of high-speed cables is established, to predict its response at a high-frequency region (up to 20 GHz). Especially, an appropriate conformal mapping technique is applied to formulate the per-unit-length parameters of high-speed cables. Moreover, the skin and proximity effects of the conducting wires and the outer shield are derived in the closed form. As a result, the AC resistance/ inductance of all the conducting materials due to the skin and proximity effects are accurately incorporated for both layered and unlayered conductors. Furthermore, the mixed-mode S-parameters are precisely predicted for both balanced and unbalanced transmission line cables in the high-frequency region. In addition, the effects of the nonuniformities and cable geometry deformation on the mode conversions are also investigated. The proposed model is firstly validated with commercial software tools, COMSOL, FEKO, and HFSS; then, we further performed physical measurements to verify our new algorithm.

Neural networks (NNs) have been widely adopted in various application domains. Deeper NNs greatly enhance the output accuracy, but complex NNs with more parameters incur intensive memory accesses, and the data usually need to be partitioned since it may exceed the on-chip storage. However, there is no research considering the partition and scheduling co-design of the NNs. In this paper, we propose a sparse NN data partition and loop scheduling scheme. We establish the compression efficiency model of the matrix sparse algorithm and design a partition selection method based on sparsity characteristics analyzed by the compression efficiency model. Further, we design a loop scheduling scheme based on the proper partition size. The experiment results show that the average memory access of each layer can be compressed to 68% of the original, and the throughput of the AlexNet, VGG and VGG19 is increased to an average of 1.66 times.

In contrast to common bean, tepary bean is highly adapted to heat and drought. Here, the authors assemble the genomes of tepary bean landrace and wild accession, discuss the possible mechanism for resilience to heat stress, and reveal a reduced disease resistance gene repertoire.

Cornelia de Lange syndrome (CdLS) is a rare genetic disease involving multiorgan systems that varies in clinical manifestations. Female genital abnormalities in patients with CdLS are rarely reported, and current guidelines for CdLS contain little information related to female genital abnormalities. We report a case of classic CdLS with an NIPBL gene pathogenic variant in a 4.5-year-old girl who experienced recurrent urinary tract infections (UTIs) with vesical tenesmus. Urogenital physical and imaging examinations revealed external vaginal orifice obstruction and bilateral vesicoureteral reflux (VUR). Vaginal diaphragm-like tissue resection and vaginal orifice plasty were performed on this patient. The symptoms of urination disorders and recurrent UTIs, as well as VUR grading, improved after relieving the vaginal obstruction during the operation. For female CdLS patients, especially those with VUR, it is necessary to check for genital abnormalities and perform timely treatment, which is of great significance in improving urination disorder symptoms, reducing resistance during voiding, decreasing the occurrence of secondary VUR, and controlling recurrent UTIs.

Question answering over knowledge bases (KBQA) is a challenging task in natural language processing. It requires machines to answer natural language questions based on large-scale knowledge bases. Recent years have witnessed remarkable success of neural network models on many natural language processing tasks, including KBQA. In this paper, we first review the recent advances of deep learning methods on solving simple questions in two streams, the information extraction style and semantic parsing style. We then introduce how to extend the neural architectures to answer more complex questions with iteration and decomposition techniques, and summarize current research challenges.

Magnetic tunnel junctions have been widely used in various applications, such as magnetic sensors and magnetic random-access memories. In the practical application of MTJs, they are usually used in series toward high sensitivity and high stability, especially for sensor applications. In this paper, serial MTJs devices on 8 in. wafers were fabricated. The temperature dependence of the tunnel magnetoresistance ratio, resistances in parallel and antiparallel configurations, and dynamic conductance were systematically investigated. The results of serial MTJs devices are consistent with a single MTJ device. This research suggests that serial MTJs can be directly used to investigate the magnetic tunneling properties of MTJ stacks.

The dynamic response of curved steel beams has long been a research focus in curved bridges. The formula for the dynamic response under a moving load was derived according to the basic principles of the precise integration method. Combined with the necessary conditions of this method, the stiffness matrix of a variable-curvature beam was obtained using matrix inversion, and the mass matrix of the structure was obtained using the concentrated mass method. The dynamic response of the structure was obtained by applying moving loads and masses at different speeds to the curved beam. Finite element simulation and laboratory curved-beam models of the variable-curvature steel beam were established. By comparing the laboratory measurement results against the theoretical data obtained in this study, we propose that our theory has practical engineering significance. It can be used as a theoretical basis for the study of variable curvature steel beam structures and for guiding the construction of curved beams.

This work presents a monolithically integrated temperature and humidity sensor based on microelectromechanical systems technology. The temperature sensor working on the “bi-metallic” effect has the advantages of wide temperature range, high sensitivity, and fast detection. The humidity sensor has a polyimide parallel plate capacitive structure with the microporous array on the upper electrode designed for high sensitivity and fast response. Numerical analysis and COMSOL simulation showed that the temperature detection sensitivity is 0.2 mV/°C in the range of 193–393 K and humidity sensitivity is 0.405 pF/% relative humidity (RH) with the response time of 34 s in the humidity range of 0%–100% RH. The integrated temperature and humidity sensor has the advantages of small dimension, wide detection range, high precision, and fast response.

Colon adenocarcinoma (COAD) is one of the most common malignant tumors and has high migration and invasion capacity. In this study, we attempted to establish a multigene signature for predicting the prognosis of COAD patients. Weighted gene co-expression network analysis and differential gene expression analysis methods were first applied to identify differentially co-expressed genes between COAD tissues and normal tissues from the Cancer Genome Atlas (TCGA)-COAD dataset and GSE39582 dataset, and a total of 309 overlapping genes were screened out. Then, our study employed TCGA-COAD cohort as the training dataset and an independent cohort by merging the GES39582 and GSE17536 datasets as the testing dataset. After univariate and multivariate Cox regression analyses were performed for these overlapping genes and overall survival (OS) of COAD patients in the training dataset, a 13-gene signature was constructed to divide COAD patients into high- and low-risk subgroups with significantly different OS. The testing dataset exhibited the same results utilizing the same predictive signature. The area under the curve of receiver operating characteristic analysis for predicting OS in the training and testing datasets were 0.789 and 0.868, respectively, which revealed the enhanced predictive power of the signature. Multivariate Cox regression analysis further suggested that the 13-gene signature could independently predict OS. Among the 13 prognostic genes, NAT1 and NAT2 were downregulated with deep deletions in tumor tissues in multiple COAD cohorts and exhibited significant correlations with poorer OS based on the GEPIA database. Notably, NAT1 and NAT2 expression levels were positively correlated with infiltrating levels of CD8+ T cells and dendritic cells, exhibiting a foundation for further research investigating the antitumor immune roles played by NAT1 and NAT2 in COAD. Taken together, the results of our study showed that the 13-gene signature could efficiently predict OS and that NAT1 and NAT2 could function as biomarkers for prognosis and the immune response in COAD.

Long non-coding RNAs (lncRNAs) were reported to have the potential in maintaining genome instability, but the identification of lncRNAs related to genome instability and their prognostic value have not been largely explored in colon cancer. In this study, we obtained 155 genome instability-associated lncRNAs based on somatic mutation profiles in colon cancer from The Cancer Genome Atlas (TCGA) database. Functional enrichment analysis revealed the possible roles of genes co-expressed with those lncRNAs involved in some cancer, genome instability and immune related biological processes. Combined with overall survival data, a seven-lncRNA signature was established for prognosis prediction. According to the risk score calculated by this signature, high-risk patients characterized by high somatic mutation count, high microsatellite instability, significantly poorer clinical outcomes and specific tumor immune infiltration status compared with low-risk patients. The lncRNA signature was validated to be an independent prognostic indicator with good predictive performance in TCGA cohort. Furthermore, the prognostic value of the ZNF503-AS1 in lncRNA signature was confirmed in another independent dataset from Gene Expression Omnibus database. In summary, the genome instability-associated lncRNA signature in this study could be a promising tool for effectively predicting survival outcomes in colon cancer.

In order to explore the influence of interlayer between dielectric layer and channel layer on performance of thin film transistors (TFTs), the single layer titanium doped zinc oxide (TiZO) TFTs and the dual layer indium tin oxide (ITO)/TiZO TFTs were fabricated successfully in this work. The effects of interlayer thickness on the performance of TFTs were studied and the optimal thickness condition was obtained. The experimental results indicate that the introduction of interlayer contributes to the improvement of TFT characteristics. In addition, the dual-layer ITO/TiZO TFTs also present a good uniformity, which is suitable for large-area display applications.

In recent years, compute-in-memory (CIM) has been extensively studied to improve the energy efficiency of computing by reducing data movement. At present, CIM is frequently used in data-intensive computing. Data-intensive computing applications, such as all kinds of neural networks (NNs) in machine learning (ML), are regarded as ‘soft’ computing tasks. The ‘soft’ computing tasks are computations that can tolerate low computing precision with little accuracy degradation. However, ‘hard’ tasks aimed at numerical computations require high-precision computing and are also accompanied by energy efficiency problems. Numerical computations exist in lots of applications, including partial differential equations (PDEs) and large-scale matrix multiplication. Therefore, it is necessary to study CIM for numerical computations. This article reviews the recent developments of CIM for numerical computations. The different kinds of numerical methods solving partial differential equations and the transformation of matrixes are deduced in detail. This paper also discusses the iterative computation of a large-scale matrix, which tremendously affects the efficiency of numerical computations. The working procedure of the ReRAM-based partial differential equation solver is emphatically introduced. Moreover, other PDEs solvers, and other research about CIM for numerical computations, are also summarized. Finally, prospects and the future of CIM for numerical computations with high accuracy are discussed.

A novel VDMOS with Step Floating Islands VDMOS (S-FLI VDMOS) is proposed for the first time in this letter, in order to optimize the breakdown voltage (BV) and the specific on-resistance (Ron,sp). The innovative terminal technology of Breakdown Point Transfer (BPT) is applied to S-FLI VDMOS, which transfers the breakdown point from the high electric field region to the low electric field region, and the S-FLI VDMOS structure uses multiple layers of charge compensation blocks to generate multiple electric field peaks in the drift region in order to optimize the electric field distribution. In the TCAD simulation, the BV of the proposed S-FLI VDMOS is improved to 326 V, which is higher than that of 281 V for the conventional Si VDMOS with the same drift region length of 15 μm, and the Ron,sp is reduced from 21.54 mΩ·cm2 for the conventional Si VDMOS to 7.77 mΩ·cm2 for the S-FLI VDMOS. Compared with the conventional Si VDMOS, the current density of the effective current conduction path is increased when the forward bias is applied to the proposed device.

Calotropis gigantea produces specialized secondary metabolites known as cardenolides, which have anticancer and antimalarial properties. Although transcriptomic studies have been conducted in other cardenolide-producing species, no nuclear genome assembly for an Asterid cardenolide-producing species has been reported to date. A high-quality de novo assembly was generated for C. gigantea, representing 157,284,427 bp with an N50 scaffold size of 805,959 bp, for which quality assessments indicated a near complete representation of the genic space. Transcriptome data in the form of RNA-sequencing libraries from a developmental tissue series was generated to aid the annotation and construction of a gene expression atlas. Using an ab initio and evidence-driven gene annotation pipeline, 18,197 high-confidence genes were annotated. Homologous and syntenic relationships between C. gigantea and other species within the Apocynaceae family confirmed previously identified evolutionary relationships, and suggest the emergence or loss of the specialized cardenolide metabolites after the divergence of the Apocynaceae subfamilies. The C. gigantea genome assembly, annotation, and RNA-sequencing data provide a novel resource to study the cardenolide biosynthesis pathway, especially for understanding the evolutionary origin of cardenolides and the engineering of cardenolide production in heterologous organisms for existing and novel pharmaceutical applications.

Abstract Background Recent advances in omics technology have produced a large amount of liver-related data. A comprehensive and up-to-date source of liver-related data is needed to allow biologists to access the latest data. However, current liver-related data sources each cover only a specific part of the liver. It is difficult for them to keep pace with the rapid increase of liver-related data available at those data resources. Integrating diverse liver-related data is a critical yet formidable challenge, as it requires sustained human effort. Results We present LiverWiki, a first wiki-based database that integrates liver-related genes, homolog genes, gene expressions in microarray datasets and RNA-Seq datasets, proteins, protein interactions, post-translational modifications, associated pathways, diseases, metabolites identified in the metabolomics datasets, and literatures into an easily accessible and searchable resource for community-driven sharing. LiverWiki houses information in a total of 141,897 content pages, including 19,787 liver-related gene pages, 17,077 homolog gene pages, 50,251 liver-related protein pages, 36,122 gene expression pages, 2067 metabolites identified in the metabolomics datasets, 16,366 disease-related molecules, and 227 liver disease pages. Other than assisting users in searching, browsing, reviewing, refining the contents on LiverWiki, the most important contribution of LiverWiki is to allow the community to create and update biological data of liver in visible and editable tables. This integrates newly produced data with existing knowledge. Implemented in mediawiki, LiverWiki provides powerful extensions to support community contributions. Conclusions The main goal of LiverWiki is to provide the research community with comprehensive liver-related data, as well as to allow the research community to share their liver-related data flexibly and efficiently. It also enables rapid sharing new discoveries by allowing the discoveries to be integrated and shared immediately, rather than relying on expert curators. The database is available online at http://liverwiki.hupo.org.cn /.

The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread to more than 100 countries. Children approved to be susceptible to SARS-CoV-2 infection. Preventing and controlling the epidemic while ensuring orderly flows of pediatric surgery clinical work has proven to be a big challenge for both patients and clinicians during the epidemic. Based on the transmission characteristics of SARS-CoV-2 and the requirements for prevention and control of COVID-19, the authors proposed some concrete measures and practical strategies of managing emergency, limited-term, and elective pediatric surgeries during the epidemic period.

Grafting is a well-established agricultural practice in cherry production for clonal propagation, altered plant vigor and architecture, increased tolerance to biotic and abiotic stresses, precocity, and higher yield. Mobile molecules, such as water, hormones, nutrients, DNAs, RNAs, and proteins play essential roles in rootstock-scion interactions. Small RNAs (sRNAs) are 19 to 30-nucleotides (nt) RNA molecules that are a group of mobile signals in plants. Rootstock-to-scion transfer of transgene-derived small interfering RNAs enabled virus resistance in nontransgenic sweet cherry scion. To determine whether there was long-distance scion-to-rootstock transfer of endogenous sRNAs, we compared sRNAs profiles in bud tissues of an ungrafted 'Gisela 6' rootstock, two sweet cherry 'Emperor Francis' scions as well as their 'Gisela 6' rootstocks. Over two million sRNAs were detected in each sweet cherry scion, where 21-nt sRNA (56.1% and 55.8%) being the most abundant, followed by 24-nt sRNAs (13.1% and 12.5%). Furthermore, we identified over three thousand sRNAs that were potentially transferred from the sweet cherry scions to their corresponding rootstocks. In contrast to the sRNAs in scions, among the transferred sRNAs in rootstocks, the most abundant were 24-nt sRNAs (46.3% and 34.8%) followed by 21-nt sRNAs (14.6% and 19.3%). In other words, 21-nt sRNAs had the least transferred proportion out of the total sRNAs in sources (scions) while 24-nt had the largest proportion. The transferred sRNAs were from 574 cherry transcripts, of which 350 had a match from the Arabidopsis thaliana standard protein set. The finding that "DNA or RNA binding activity" was enriched in the transcripts producing transferred sRNAs indicated that they may affect the biological processes of the rootstocks at different regulatory levels. Overall, the profiles of the transported sRNAs and their annotations revealed in this study facilitate a better understanding of the role of the long-distance transported sRNAs in sweet cherry rootstock-scion interactions as well as in branch-to-branch interactions in a tree.

Gene expression is controlled at transcriptional and post-transcriptional levels including decoding of messenger RNA (mRNA) into polypeptides via ribosome-mediated translation. Translational regulation has been intensively studied in the model dicot plant Arabidopsis thaliana, and in this study, we assessed the translational status [proportion of steady-state mRNA associated with ribosomes] of mRNAs by Translating Ribosome Affinity Purification followed by mRNA-sequencing (TRAP-seq) in rice (Oryza sativa), a model monocot plant and the most important food crop. A survey of three tissues found that most transcribed rice genes are translated whereas few transposable elements are associated with ribosomes. Genes with short and GC-rich coding regions are overrepresented in ribosome-associated mRNAs, suggesting that the GC-richness characteristic of coding sequences in grasses may be an adaptation that favors efficient translation. Transcripts with retained introns and extended 5′ untranslated regions are underrepresented on ribosomes, and rice genes belonging to different evolutionary lineages exhibited differential enrichment on the ribosomes that was associated with GC content. Genes involved in photosynthesis and stress responses are preferentially associated with ribosomes, whereas genes in epigenetic regulation pathways are the least enriched on ribosomes. Such variation is more dramatic in rice than that in Arabidopsis and is correlated with the wide variation of GC content of transcripts in rice. Taken together, variation in the translation status of individual transcripts reflects important mechanisms of gene regulation, which may have a role in evolution and diversification.

Transposons are ubiquitous genomic components that play pivotal roles in plant gene and genome evolution. We analyzed two genome sequences of common bean (Phaseolus vulgaris) and identified a new CACTA transposon family named pvCACTA1. The family is extremely abundant, as more than 12,000 pvCACTA1 elements were found. To our knowledge, this is the most abundant CACTA family reported thus far. The computational and fluorescence in situ hybridization (FISH) analyses indicated that the pvCACTA1 elements were concentrated in terminal regions of chromosomes and frequently generated AT-rich 3 bp target site duplications (TSD, WWW, W is A or T). Comparative analysis of the common bean genomes from two domesticated genetic pools revealed that new insertions or excisions of pvCACTA1 elements occurred after the divergence of the two common beans, and some of the polymorphic elements likely resulted in variation in gene sequences. pvCACTA1 elements were detected in related species but not outside the Phaseolus genus. We calculated the molecular evolutionary rate of pvCACTA1 transposons using orthologous elements that indicated that most transposition events likely occurred before the divergence of the two gene pools. These results reveal unique features and evolution of this new transposon family in the common bean genome.

In this work, magnetic CuFe2O4/Ag nanoparticles activated by porous covalent organic frameworks (COF) was fabricated to evaluate the heterogenous reduction of 4-nitrophenol (4-NP). The core-shell CuFe2O4/Ag@COF was successfully prepared by polydopamine reduction of silver ions on CuFe2O4 nanoparticles, followed by COF layer condensation. By integrating the intrinsic characteristics of the magnetic CuFe2O4/Ag core and COF layer, the obtained nanocomposite exhibited features of high specific surface area (464.21 m2 g-1), ordered mesoporous structure, strong environment stability, as well as fast magnetic response. Accordingly, the CuFe2O4/Ag@COF catalyst showed good affinity towards 4-NP via π-π stacking interactions and possessed enhanced catalytic activity compared with CuFe2O4/Ag and CuFe2O4@COF. The pseudo-first-order rate constant of CuFe2O4/Ag@COF (0.77 min-1) is 3 and 5 times higher than CuFe2O4/Ag and CuFe2O4@COF, respectively. The characteristics of bi-catalytic CuFe2O4/Ag and the porous COF shell of CuFe2O4/Ag@COF made a contribution to improve the activity of 4-NP reduction. The present work demonstrated a facile strategy to fabricate COF-activated nano-catalysts with enhanced performance in the fields of nitrophenolic wastewater treatment.

A new and hydrophilic molecularly imprinted polymer (MIP) selective for olaquindox was prepared by bulk polymerisation using methacrylic acid as the functional monomer and ethylene glycol dimethacrylate as the crosslinker. The synthesised polymer was characterised by Fourier-transform infrared and static adsorption experiments. Results showed that the MIP had good recognition and selective ability for olaquindox. A novel method based on molecularly imprinted solid-phase extraction coupled with high-performance liquid chromatography was developed for the separation and determination of trace olaquindox in feed samples. Under selected experimental conditions, the detection limit (signal-to-noise ratio = 3) was 42.2 ng/g, and the relative standard deviation (RSD) for five replicate extractions of 50 µg/l olaquindox was 4.9%. The method provided high recoveries ranging from 89.8% to 93.1% at three spiked levels with < 5% RSDs. This method was successfully applied for the analysis of olaquindox in feed.

A facile approach was successfully developed for synthesis of cellulose nanocrystals (CNC)-supported magnetic CuFe2O4@Ag@ZIF-8 nanospheres which consist of a paramagnetic CuFe2O4@Ag core and porous ZIF-8 shell. The CuFe2O4 nanoparticles (NPs) were first prepared in the presence of CNC and dispersant. Ag NPs were then deposited on the CuFe2O4/CNC composites via an in situ reduction directed by dopamine polymerization (PDA). The CuFe2O4/CNC@Ag@ZIF-8 nanocomposite was characterized by TEM, FTIR, XRD, N2 adsorption-desorption isotherms, VSM, and XPS. Catalytic studies showed that the CuFe2O4/CNC@Ag@ZIF-8 catalyst had much higher catalytic activity than CuFe2O4@Ag catalyst with the rate constant of 0.64 min−1. Because of the integration of ZIF-8 with CuFe2O4/CNC@Ag that combines the advantaged of each component, the nanocomposites were demonstrated to have an enhanced catalytic activity in heterogeneous catalysis. Therefore, these results demonstrate a new method for the fabrication of CNC-supported magnetic core-shell catalysts, which display great potential for application in biocatalysis and environmental chemistry.

Common bean (Phaseolus vulgaris L.) fixes atmospheric nitrogen (N2) through symbiotic nitrogen fixation (SNF) at levels lower than other grain legume crops. An understanding of the genes and molecular mechanisms underlying SNF will enable more effective strategies for the genetic improvement of SNF traits in common bean. In this study, transcriptome profiling was used to identify genes and molecular mechanisms underlying SNF differences between two common bean recombinant inbred lines that differed in their N-fixing abilities. Differential gene expression and functional enrichment analyses were performed on leaves, nodules and roots of the two lines when grown under N-fixing and non-fixing conditions. Receptor kinases, transmembrane transporters, and transcription factors were among the differentially expressed genes identified under N-fixing conditions, but not under non-fixing conditions. Genes up-regulated in the stronger nitrogen fixer, SA36, included those involved in molecular functions such as purine nucleoside binding, oxidoreductase and transmembrane receptor activities in nodules, and transport activity in roots. Transcription factors identified in this study are candidates for future work aimed at understanding the functional role of these genes in SNF. Information generated in this study will support the development of gene-based markers to accelerate genetic improvement of SNF in common bean.