BMPRⅡ^(+)neural precursor cells isolated and characterized from organotypic neurospheres:an in vitro model of human fetal spinal cord development

Roof plate secretion of bone morphogenetic proteins(BMPs)directs the cellular fate of sensory neurons during spinal cord development,including the formation of the ascending sensory columns,though their biology is not well understood.Type-ⅡBMP receptor(BMPRⅡ),the cognate receptor,is expressed by neural precursor cells during embryogenesis;however,an in vitro method of enriching BMPRⅡ^(+)human neural precursor cells(hNPCs)from the fetal spinal cord is absent.Immunofluorescence was undertaken on intact second-trimester human fetal spinal cord using antibodies to BMPRⅡand leukemia inhibitory factor(LIF).Regions of highest BMPRⅡ^(+)immunofluorescence localized to sensory columns.Parenchymal and meningeal-associated BMPRⅡ^(+)vascular cells were identified in both intact fetal spinal cord and cortex by co-positivity with vascular lineage markers,CD34/CD39.LIF immunostaining identified a population of somas concentrated in dorsal and ventral horn interneurons,mirroring the expression of LIF receptor/CD118.A combination of LIF supplementation and high-density culture maintained culture growth beyond 10 passages,while synergistically increasing the proportion of neurospheres with a stratified,cytoarchitecture.These neurospheres were characterized by BMPRⅡ^(+)/MAP2ab^(+/–)/βⅢ-tubulin^(+)/nestin^(–)/vimentin^(–)/GFAP^(–)/NeuN^(–)surface hNPCs surrounding a heterogeneous core ofβⅢ-tubulin^(+)/nestin^(+)/vimentin^(+)/GFAP^(+)/MAP2ab^(–)/NeuN^(–)multipotent precursors.Dissociated cultures from tripotential neurospheres contained neuronal(βⅢ-tubulin^(+)),astrocytic(GFAP+),and oligodendrocytic(O4+)lineage cells.Fluorescence-activated cell sorting-sorted BMPRⅡ^(+)hNPCs were MAP2ab^(+/–)/βⅢ-tubulin^(+)/GFAP^(–)/O4^(–)in culture.This is the first isolation of BMPRⅡ^(+)hNPCs identified and characterized in human fetal spinal cords.Our data show that LIF combines synergistically with high-density reaggregate cultures to support the organotypic reorganization of neurospheres,characterized by surface BMPRⅡ^(+)hNPCs.Our study has provided a new methodology for an in vitro model capable of amplifying human fetal spinal cord cell numbers for>10 passages.Investigations of the role BMPRⅡplays in spinal cord development have primarily relied upon mouse and rat models,with interpolations to human development being derived through inference.Because of significant species differences between murine biology and human,including anatomical dissimilarities in central nervous system(CNS)structure,the findings made in murine models cannot be presumed to apply to human spinal cord development.For these reasons,our human in vitro model offers a novel tool to better understand neurodevelopmental pathways,including BMP signaling,as well as spinal cord injury research and testing drug therapies.

A Two-Layer Encoding Learning Swarm Optimizer Based on Frequent Itemsets for Sparse Large-Scale Multi-Objective Optimization

Traditional large-scale multi-objective optimization algorithms(LSMOEAs)encounter difficulties when dealing with sparse large-scale multi-objective optimization problems(SLM-OPs)where most decision variables are zero.As a result,many algorithms use a two-layer encoding approach to optimize binary variable Mask and real variable Dec separately.Nevertheless,existing optimizers often focus on locating non-zero variable posi-tions to optimize the binary variables Mask.However,approxi-mating the sparse distribution of real Pareto optimal solutions does not necessarily mean that the objective function is optimized.In data mining,it is common to mine frequent itemsets appear-ing together in a dataset to reveal the correlation between data.Inspired by this,we propose a novel two-layer encoding learning swarm optimizer based on frequent itemsets(TELSO)to address these SLMOPs.TELSO mined the frequent terms of multiple particles with better target values to find mask combinations that can obtain better objective values for fast convergence.Experi-mental results on five real-world problems and eight benchmark sets demonstrate that TELSO outperforms existing state-of-the-art sparse large-scale multi-objective evolutionary algorithms(SLMOEAs)in terms of performance and convergence speed.

Assessment of Wet Season Precipitation in the Central United States by the Regional Climate Simulation of the WRFG Member in NARCCAP and Its Relationship with Large-Scale Circulation Biases

Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km,named WRFG,from the North American Regional Climate Change Assessment Program(NARCCAP)in simulating wet season precipitation over the Central United States for a period when observational data are available.The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer,although it tends to underestimate the magnitude of precipitation.This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation.Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor.The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between,leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains.The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence,for the development of moist convection as well.Therefore,a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios.

A semantic vector map-based approach for aircraft positioning in GNSS/GPS denied large-scale environment

Accurate positioning is one of the essential requirements for numerous applications of remote sensing data,especially in the event of a noisy or unreliable satellite signal.Toward this end,we present a novel framework for aircraft geo-localization in a large range that only requires a downward-facing monocular camera,an altimeter,a compass,and an open-source Vector Map(VMAP).The algorithm combines the matching and particle filter methods.Shape vector and correlation between two building contour vectors are defined,and a coarse-to-fine building vector matching(CFBVM)method is proposed in the matching stage,for which the original matching results are described by the Gaussian mixture model(GMM).Subsequently,an improved resampling strategy is designed to reduce computing expenses with a huge number of initial particles,and a credibility indicator is designed to avoid location mistakes in the particle filter stage.An experimental evaluation of the approach based on flight data is provided.On a flight at a height of 0.2 km over a flight distance of 2 km,the aircraft is geo-localized in a reference map of 11,025 km~2using 0.09 km~2aerial images without any prior information.The absolute localization error is less than 10 m.

FE65:a hub for neurodevelopment

FE65,initially identified as a binding partner of amyloid precursor protein(APP),is an adaptor protein enriched in the brain and regulated during development.FE65 belongs to the FE65 protein family.This family is comprised of three members,FE65,FE65 like-1(FE65L1),and FE65 like-2(FE65L2).

Spatial Differentiation and Convergence Trend of High-quality Development Level of China’s Tourism Economy

This paper aims to interpret the connotation of high-quality development of tourism economy(HQTE)from the perspective of the new development concepts of innovation,coordination,green,openness and sharing,and then to evaluate the spatial differenti-ation of China’s HQTE based on provincial panel data from 2009 to 2018.Specifically,we employ the spatial convergence model to ex-plore the absolute and conditionalβconvergence trends of HQTE in the whole country and the eastern,central and western regions of China.Our empirical results reveal that:1)within the decade,from 2009 to 2018,regions of China with the highest HQTE index is its eastern region followed by the central region and then the western region,but the fastest growing one is the western region of China fol-lowed by the central region and then the eastern region.2)Whether or not the spatial effect is included,there are absolute and condition-alβconvergence in HQTE in the whole country and aforementioned three regions.3)The degree of government attention as well as the level of economic development and location accessibility are the positive driving factors for the convergence of HQTE in the whole country and the three regions.The degree of marketization and human capital have not passed the significance test either in the whole country or in the three regions.The above conclusions could deepen the understanding of the regional imbalance and spatial conver-gence characteristics of HQTE,clarify the primary development objects,and accomplish the goal of China’s HQTE.

Large-Scale Multi-Objective Optimization Algorithm Based on Weighted Overlapping Grouping of Decision Variables

The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the interaction among decision variables is intricate,leading to large group sizes and suboptimal optimization effects;hence a large-scale multi-objective optimization algorithm based on weighted overlapping grouping of decision variables(MOEAWOD)is proposed in this paper.Initially,the decision variables are perturbed and categorized into convergence and diversity variables;subsequently,the convergence variables are subdivided into groups based on the interactions among different decision variables.If the size of a group surpasses the set threshold,that group undergoes a process of weighting and overlapping grouping.Specifically,the interaction strength is evaluated based on the interaction frequency and number of objectives among various decision variables.The decision variable with the highest interaction in the group is identified and disregarded,and the remaining variables are then reclassified into subgroups.Finally,the decision variable with the strongest interaction is added to each subgroup.MOEAWOD minimizes the interactivity between different groups and maximizes the interactivity of decision variables within groups,which contributed to the optimized direction of convergence and diversity exploration with different groups.MOEAWOD was subjected to testing on 18 benchmark large-scale optimization problems,and the experimental results demonstrate the effectiveness of our methods.Compared with the other algorithms,our method is still at an advantage.

A Large-Scale Group Decision Making Model Based on Trust Relationship and Social Network Updating

With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that considers the trust relationship among decisionmakers(DMs).In the process of consensusmeasurement:the social network is constructed according to the social relationship among DMs,and the Louvain method is introduced to classify social networks to form subgroups.In this study,the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights.In the process of consensus improvement:A feedback mechanism with four identification and two direction rules is designed to guide the consensus of the improvement process.Based on the trust relationship among DMs,the preferences are modified,and the corresponding social network is updated to accelerate the consensus.Compared with the previous research,the proposedmodel not only allows the subgroups to be reconstructed and updated during the adjustment process,but also improves the accuracy of the adjustment by the feedbackmechanism.Finally,an example analysis is conducted to verify the effectiveness and flexibility of the proposed method.Moreover,compared with previous studies,the superiority of the proposed method in solving the LGDM problem is highlighted.

Development and formation of wing cuticle based on transcriptomic analysis in Locusta migratoria during metamorphosis

Wings are an important flight organ of insects.Wing development is a complex process controlled by a series of genes.The flightless wing pad transforms into a mature wing with the function of migratory flight during the nymphto-adult metamorphosis.However,the mechanism of wing morphogenesis in locusts is still unclear.This study analyzed the microstructures of the locust wing pads at pre-eclosion and the wings after eclosion and performed the comparative transcriptome analysis.RNA-seq identified 25,334 unigenesand 3,430 differentially expressed genes(DEGs)(1,907 up-regulated and 1,523 down-regulated).The DEGs mainly included cuticle development(LmACPs),chitin metabolism(Lm Idgf4),lipid metabolism-related genes,cell adhesion(Integrin),zinc finger transcription factors(LmSalm,LmZF593 andLmZF521),and others.Functional analysis based on RNA interference and hematoxylin and eosin(H&E)staining showed that the three genes encoded zinc finger transcription factors are essential for forming wing cuticle and maintaining morphology in Locusta migratoria.Finally,the study found that the LmSalm regulates the expression of LmACPs in the wing pads at pre-eclosion,and LmZF593 and LmZF521 regulate the expression of LmIntegrin/LmIdgf4/LmHMT420 in the wings after eclosion.This study revealed that the molecular regulatory axis controls wing morphology in nymphal and adult stages of locusts,offering a theoretical basis for the study of wing development mechanisms in hemimetabolous insects.

Identification and Expression Profile of a Neuropeptide LFRFamide-Like Gene During Different Stages of Gonadal Development in the Cephalopod Sepia pharaonis

Neuropeptides are widely distributed in vertebrates and invertebrates,regulating a variety of physiological activities in the organisms,such as metabolism,feeding and reproduction.In this study,to explore the function of neuropeptide LFRFamide in Sepia pharaonis,the full-length cDNA of LFRFamide-like gene(named SpLFRFL,MG869822.1)was identified with rapid amplification of cDNA ends(RACE)method.The sequence of SpLFRFL was 860 bp in length and encoded 188 amino acids containing 4 different mature peptides:1 copy of PHTPFRFamide,NSLFRFamide,TIFRFamide,and 3 copies of GNLFRFamide.Multiple alignment and phylogenetic analysis results showed that SpLFRFL shared high identity with LFRFamides of Sepia officinalis and Sepiella japonica and had the closest relationship with them.Through quantitative Real-time PCR(qRT-PCR),it was found that the SpLFRFL gene was highly expressed in the optic lobe and brain at three different stages during gonad development in both genders.Moreover,the four mature peptides at a concentration of 0.01μmol L^(−1) could inhibit the protein synthesis in the Chinese hamster ovary cell strain-K1(CHOK1)induced by SpGnRH.These data suggest that SpLFRFL might be involved in the development and reproduction of S.pharaonis.The results can contribute to future studies on neuropeptide evolution and function and benefit the cuttlefish farming.

GAMYB transcription factor LoMYB65 from lily plays a vital role in pollen development

Lily(Lilium spp.)is an important horticultural crop,but its use is limited due to serious pollen contamination problems.There are many studies on pollen development in model plants,but few on flower crops such as lilies.Gibberellin(GA)is a large class of hormones and plays an important role in plant vegetative growth and reproductive development.GAMYB is a group of the R2R3-MYB family upregulated by gibberellin,and plays an important role in anther development.Here,we isolated a novel GAMYB,named LoMYB65,from lily,which was closely related to the AtMYB65 and AtMYB33 in Arabidopsis.Fluorescence quantitative PCR results showed that LoMYB65 was mainly expressed in lily anthers.LoMYB65 could be activated by 288μmol·L^(-1)GA3treatment and the LoMYB65 protein was located in the nucleus and cytoplasm,and had transactivation in yeast and tobacco leaf cells.The conserved motif within 226 amino acids of the C-terminal of LoMYB65 contributed to its transactivation.Overexpression of LoMYB65 caused dwarf phenotype,unnormal tapetum development,less seeds of siliques in transgenic Arabidopsis plants,the transgenic plants showed partly male sterile.Simultaneously,silencing of LoMYB65 with VIGS(Virus Induced Gene Silencing)in lily anthers caused unnormal pollen development and reduced the pollen amount.Overexpression of LoMYB65 in Arabidopsis and silencing of LoMYB65 in lily resulted in decreased pollen counts,so we speculate that LoMYB65 may be dose-dependent.Overall,these findings suggest that LoMYB65 may play an important role in anther development and pollen formation in lily.LoMYB65 may provide a useful candidate gene for pollenless breeding of lily.

Combining genome-wide association study and transcriptome analysis to identify molecular markers and genetic basis of population-asynchronous ovarian development in Coilia nasus

Coilia nasus,a migratory fish species found in the middle and lower reaches of the Yangtze River and along offshore areas of China,possesses considerable aquacultural and economic potential.However,the species faces challenges due to significant variation in the gonadal development rate among females,resulting in inconsistent ovarian maturation times at the population level,an extended reproductive period,and limitations on fish growth rate due to ovarian prematurity.In the present study,we combined genome-wide association study(GWAS)and comparative transcriptome analysis to investigate the potential single nucleotide polymorphisms(SNPs)and candidate genes associated with population-asynchronous ovarian development in C.nasus.Genotyping of the female population based on whole-genome resequencing yielded 2120695 high-quality SNPs,39 of which were suggestively associated with ovarian development.Of note,a significant SNP peak on LG21 containing 30 suggestively associated SNPs was identified,with cpne5a determined as the causal gene of the peak.Therefore,single-marker and haplotype association analyses were performed on cpne5a,revealing four genetic markers(P<0.05)and seven haplotypes(r2>0.9)significantly associated with the phenotype.Comparative transcriptome analysis of precociously and normally maturing individuals screened out 29 and 426 overlapping differentially expressed genes in the brain and ovary,respectively,between individuals of different body sizes.Integrating the GWAS and transcriptome analysis results,this study identified genes and pathways related to hypothalamic-pituitary-gonadal axis hormone secretion,extracellular matrix,angiogenesis,and gap junctions involved in population-asynchronous ovarian development.The insights gained from this study provide a basis for a deeper understanding of the molecular mechanisms underlying ovarian development in fish and may facilitate the genetic breeding of C.nasus strains exhibiting population-synchronous ovarian development in the future.

Robustness Study and Superior Method Development and Validation for Analytical Assay Method of Atropine Sulfate in Pharmaceutical Ophthalmic Solution

Background: The robustness is a measurement of an analytical chemical method and its ability to contain unaffected by little with deliberate variation of analytical chemical method parameters. The analytical chemical method variation parameters are based on pH variability of buffer solution of mobile phase, organic ratio composition changes, stationary phase (column) manufacture, brand name and lot number variation;flow rate variation and temperature variation of chromatographic system. The analytical chemical method for assay of Atropine Sulfate conducted for robustness evaluation. The typical variation considered for mobile phase organic ratio change, change of pH, change of temperature, change of flow rate, change of column etc. Purpose: The aim of this study is to develop a cost effective, short run time and robust analytical chemical method for the assay quantification of Atropine in Pharmaceutical Ophthalmic Solution. This will help to make analytical decisions quickly for research and development scientists as well as will help with quality control product release for patient consumption. This analytical method will help to meet the market demand through quick quality control test of Atropine Ophthalmic Solution and it is very easy for maintaining (GDP) good documentation practices within the shortest period of time. Method: HPLC method has been selected for developing superior method to Compendial method. Both the compendial HPLC method and developed HPLC method was run into the same HPLC system to prove the superiority of developed method. Sensitivity, precision, reproducibility, accuracy parameters were considered for superiority of method. Mobile phase ratio change, pH of buffer solution, change of stationary phase temperature, change of flow rate and change of column were taken into consideration for robustness study of the developed method. Results: The limit of quantitation (LOQ) of developed method was much low than the compendial method. The % RSD for the six sample assay of developed method was 0.4% where the % RSD of the compendial method was 1.2%. The reproducibility between two analysts was 100.4% for developed method on the contrary the compendial method was 98.4%.

A cell transcriptomic profile p ovides insights into adipocytes of porcine mammary gland across development

Background Studying the composition and developmental mechanisms in mammary gland is crucial for healthy growth of newborns. The mammary gland is inherently heterogeneous, and its physiological function dependents on the gene expression of multiple cell types. Most studies focused on epithelial cells, disregarding the role of neighboring adipocytes.Results Here, we constructed the largest transcriptomic dataset of porcine mammary gland cells thus far. The dataset captured 126,829 high-quality nuclei from physiological mammary glands across five developmental stages(d 90 of gestation, G90;d 0 after lactation, L0;d 20 after lactation, L20;2 d post natural involution, PI2;7 d post natural involution, PI7). Seven cell types were identified, including epithelial cells, adipocytes, endothelial cells, fibroblasts cells, immune cells, myoepithelial cells and precursor cells. Our data indicate that mammary glands at different developmental stages have distinct phenotypic and transcriptional signatures. During late gestation(G90), the differentiation and proliferation of adipocytes were inhibited. Meanwhile, partly epithelial cells were completely differentiated. Pseudo-time analysis showed that epithelial cells undergo three stages to achieve lactation, including cellular differentiation, hormone sensing, and metabolic activation. During lactation(L0 and L20), adipocytes area accounts for less than 0.5% of mammary glands. To maintain their own survival, the adipocyte exhibited a poorly differentiated state and a proliferative capacity. Epithelial cells initiate lactation upon hormonal stimulation. After fulfilling lactation mission, their undergo physiological death under high intensity lactation. Interestingly, the physiological dead cells seem to be actively cleared by immune cells via CCL21-ACKR4 pathway. This biological process may be an important mechanism for maintaining homeostasis of the mammary gland. During natural involution(PI2 and PI7), epithelial cell populations dedifferentiate into mesenchymal stem cells to maintain the lactation potential of mammary glands for the next lactation cycle.Conclusion The molecular mechanisms of dedifferentiation, proliferation and redifferentiation of adipocytes and epithelial cells were revealed from late pregnancy to natural involution. This cell transcriptomic profile constitutes an essential reference for future studies in the development and remodeling of the mammary gland at different stages.

A Golden2-like transcription factor, BnGLK1a, improves chloroplast development, photosynthesis, and seed weight in rapeseed

Enhancing photosynthetic efficiency is a major goal for improving crop yields under agricultural field conditions and is associated with chloroplast biosynthesis and development.In this study,we demonstrate that Golden2-like 1a(BnGLK1a)plays an important role in regulating chloroplast development and photosynthetic efficiency.Overexpressing BnGLK1a resulted in significant increases in chlorophyll content,the number of thylakoid membrane layers and photosynthetic efficiency in Brassica napus,while knocking down BnGLK1a transcript levels through RNA interference(RNAi)had the opposite effects.A yeast two-hybrid screen revealed that BnGLK1a interacts with the abscisic acid receptor PYRABACTIN RESISTANCE 1-LIKE 1-2(BnPYL1-2)and CONSTITUTIVE PHOTOMORPHOGENIC 9 SIGNALOSOME 5A subunit(BnCSN5A),which play essential roles in regulating chloroplast development and photosynthesis.Consistent with this,BnGLK1a-RNAi lines of B.napus display hypersensitivity to the abscisic acid(ABA)response.Importantly,overexpression of BnGLK1a resulted in a 10%increase in thousand-seed weight,whereas seeds from BnGLK1a-RNAi lines were 16%lighter than wild type.We propose that BnGLK1a could be a potential target in breeding for improving rapeseed productivity.Our results not only provide insights into the mechanisms of BnGLK1a function,but also offer a potential approach for improving the productivity of Brassica species.

BrrTCP4b interacts with BrrTTG1 to suppress the development of trichomes in Brassica rapa var. rapa

The number of trichomes significantly increased in CRISPR/Cas9-edited BrrTCP4b turnip(Brassica rapa var.rapa)plants.However,the underlying molecular mechanism remains to be uncovered.In this study,we performed the Y2H screen using BrrTCP4b as the bait,which unveiled an interaction between BrrTCP4b and BrrTTG1,a pivotal WD40-repeat protein transcription factor in the MYB-bHLH-WD40(MBW)complex.This physical interaction was further validated through bimolecular luciferase complementation and co-immunoprecipitation.Furthermore,it was found that the interaction between BrrTCP4b and BrrTTG1 could inhibit the activity of MBW complex,resulting in decreased expression of BrrGL2,a positive regulator of trichomes development.In contrast,AtTCP4 is known to regulate trichomes development by interacting with AtGL3 in Arabidopsis thaliana.Overall,this study revealed that BrrTCP4b is involved in trichome development by interacting with BrrTTG1 in turnip,indicating a divergence from the mechanisms observed in model plant A.thaliana.The findings contribute to our understanding of the regulatory mechanisms governing trichome development in the non-model plants turnip.

Large-scale spatial data visualization method based on augmented reality

Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for researchers'visual perceptions of the evolution and interaction of events in the space environment.Methods A time-series dynamic data sampling method for large-scale space was proposed for sample detection data in space and time,and the corresponding relationships between data location features and other attribute features were established.A tone-mapping method based on statistical histogram equalization was proposed and applied to the final attribute feature data.The visualization process is optimized for rendering by merging materials,reducing the number of patches,and performing other operations.Results The results of sampling,feature extraction,and uniform visualization of the detection data of complex types,long duration spans,and uneven spatial distributions were obtained.The real-time visualization of large-scale spatial structures using augmented reality devices,particularly low-performance devices,was also investigated.Conclusions The proposed visualization system can reconstruct the three-dimensional structure of a large-scale space,express the structure and changes in the spatial environment using augmented reality,and assist in intuitively discovering spatial environmental events and evolutionary rules.

The NAC transcription factor LuNAC61 negatively regulates fiber development in flax (Linum usitatissimum L.)

Flax is a crucial fiber crop that exhibits excellent textile properties and serves as a model plant for investigating phloem fiber development. The regulation of multiple genes significantly influences fiber development, notably involving NAC(NAM, ATAF1/2, CUC2) transcription factors in forming the fiber secondary cell wall(SCW).Overexpression of LuNAC61 in flax resulted in sparse top meristematic zone leaves and significantly reduced stem cellulose content. Scanning electron microscopy and staining observations revealed a significant reduction in fiber bundles. β-Glucuronidase(GUS) staining analysis demonstrated high activity of the LuNAC61 promoter in the bast fibers of the flax stem. Additionally, several members of the LuPLATZ and LuCesA families exhibited significant coexpression with LuNAC61. Subcellular localization indicated the presence of LuPLATZ24 protein in the nucleus and cytoplasm, LuNAC61 protein exclusively in the nucleus, and LuCesA10 in the nucleus and endoplasmic reticulum. LuPLATZ24 positively regulates LuNAC61, whereas LuNAC61 negatively affects LuCesA10, suggesting the involvement of a metabolic network in regulating flax fiber development. In conclusion, this study provides a critical opportunity for a comprehensive and in-depth analysis of the mechanisms governing flax fiber development and the potential use of biotechnology to enhance flax fiber yield.

Development of multi-functional anchorage support dynamic-static coupling performance test system and its application

In underground engineering with complex conditions,the bolt(cable)anchorage support system is in an environment where static and dynamic stresses coexist,under the action of geological conditions such as high stresses and strong disturbances and construction conditions such as the application of high prestress.It is essential to study the support components performance under dynamic-static coupling conditions.Based on this,a multi-functional anchorage support dynamic-static coupling performance test system(MAC system)is developed,which can achieve 7 types of testing functions,including single component performance,anchored net performance,anchored rock performance and so on.The bolt and cable mechanical tests are conducted by MAC system under different prestress levels.The results showed that compared to the non-prestress condition,the impact resistance performance of prestressed bolts(cables)is significantly reduced.In the prestress range of 50–160 k N,the maximum reduction rate of impact energy resisted by different types of bolts is 53.9%–61.5%compared to non-prestress condition.In the prestress range of 150–300 k N,the impact energy resisted by high-strength cable is reduced by76.8%–84.6%compared to non-prestress condition.The MAC system achieves dynamic-static coupling performance test,which provide an effective means for the design of anchorage support system.