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BackgroundPatients with osteoporosis (OP) are often associated with decreased hand grip strength and increased risk of falling. It remains unclear whether there is a genetic causal between hand grip strength and OP, falling risk.MethodsThe Mendelian randomization study was used to investigate the genetic causal effect of low hand grip strength on total body bone mineral density (BMD) at different ages, OP, and falling risk. Genes for low hand grip strength, total body BMD at different ages, OP, and falling risk were obtained from published genome-wide association studies. Inverse variance weighted, MR‐Egger, and weighted median were applied to perform the MR analysis. The Cochran’s Q test, MR‐Egger intercept test, MR-PRESSO global test, and leave-one-out analysis were used to detect the pleiotropy or heterogeneity.ResultsThe results showed strong evidence that low hand grip strength was positively associated with OP (OR: 1.006, 95% CI: 1.003-1.010; P= 0.0001) and falling risk (OR: 1.069, 95% CI: 1.013-1.129; P= 0.0160), and could not directly affect the different ages of total body BMD (P> 0.05). There was no heterogeneity or horizontal pleiotropy in the sensitivity analysis (all P> 0.05).ConclusionThe study found a positive causal relationship between low hand grip strength and higher risk of OP and falling, which should be taken into account in the development of future prevention and screening strategies for OP and falling.

Abstract Respiratory diseases constitute a major health problem for ruminants, resulting in considerable economic losses throughout the world. Parainfluenza type 3 virus (PIV3) is one of the most important respiratory pathogens of ruminants. The pathogenicity and phylogenetic analyses of PIV3 virus have been reported in sheep and goats. However, there are no recent studies of the vaccination of sheep or goats against PIV3. Here, we developed a purified inactivated ovine parainfluenza virus type 3 (OPIV3) vaccine candidate. In addition, we immunized sheep with the inactivated OPIV3 vaccine and evaluated the immune response and pathological outcomes associated with OPIV3 TX01 infection. The vaccinated sheep demonstrated no obvious symptoms of respiratory tract infection, and there were no gross lesions or pathological changes in the lungs. The average body weight gain significantly differed between the vaccinated group and the control group (P

Abstract Background Bovine coronavirus (BCoV) is implicated in severe diarrhea in calves and contributes to the bovine respiratory disease complex; it shares a close relationship with human coronavirus. Similar to other coronaviruses, remarkable variability was found in the genome and biology of the BCoV. In 2022, samples of feces were collected from a cattle farm. A virus was isolated from 7-day-old newborn calves. In this study, we present the genetic characteristics of a new BCoV isolate. The complete genomic, spike protein, and nucleocapsid protein gene sequences of the BCoV strain, along with those of other coronaviruses, were obtained from the GenBank database. Genetic analysis was conducted using MEGA7.0 and the Neighbor-Joining (NJ) method. The reference strains’ related genes were retrieved from GenBank for comparison and analysis using DNAMAN. Results The phylogenetic tree and whole genome consistency analysis showed that it belonged to the GIIb subgroup, which is epidemic in Asia and America, and was quite similar to the Chinese strains in the same cluster. Significantly, the S gene was highly consistent with QH1 (MH810151.1) isolated from yak. This suggests that the strain may have originated from interspecies transmission involving mutations of wild strains. The N gene was conserved and showed high sequence identity with the epidemic strains in China and the USA. Conclusions Genetic characterization suggests that the isolated strain could be a new mutant from a wild-type lineage, which is in the same cluster as most Chinese epidemic strains but on a new branch.

To address the imbalance in the supply of grass resources caused by seasonality and regional factors, it is crucial to efficiently store and transport alfalfa. Exploring suitable grass feed processing techniques contributes to the stable transportation of grass blocks and long-term storage of nutritional components. The Central Composite Design response surface design was used to design experiments, with moisture content and compressive force as the test factors. Based on the experimental results, it was found that lower moisture content and a certain compressive force were beneficial for the stability, high density, and protein storage of alfalfa blocks. The microscopic examination of alfalfa particles revealed that a certain moisture content (15%) facilitates the formation of solid bridges between particles, leading to more stable alfalfa blocks. The final optimized process parameters were moisture content of 14.3% and compressive force of 34.8 kN. Under these conditions, the density of the molded alfalfa block was 1001 kg/m3, with R-CP at 96.96%, R-EE at 67.23%, and R-CF at 114.13%.

Abstract The combination of flexible sensors and deep learning has attracted much attention as an efficient method for the recognition of human postures. In this paper, an in situ polymerized MXene/polypyrrole (PPy) composite is dip-coated on a polydimethylsiloxane (PDMS) sponge to fabricate an MXene/PPy@PDMS (MPP) piezoresistive sensor. The sponge sensor achieves ultrahigh sensitivity (6.8925 kPa−1) at 0–15 kPa, a short response/recovery time (100/110 ms), excellent stability (5000 cycles) and wash resistance. The synergistic effect of PPy and MXene improves the performance of the composite materials and facilitates the transfer of electrons, making the MPP sponge at least five times more sensitive than sponges based on each of the individual single materials. The large-area conductive network allows the MPP sensor to maintain excellent electrical performance over a large-scale pressure range. The MPP sensor can detect a variety of human body activity signals, such as radial artery pulse and different joint movements. The detection and analysis of human motion data, which is assisted by convolutional neural network (CNN) deep learning algorithms, enable the recognition and judgment of 16 types of human postures. The MXene/PPy flexible pressure sensor based on a PDMS sponge has broad application prospects in human motion detection, intelligent sensing and wearable devices.

In this study, the wear characteristics of the die were tested and analyzed through compaction tests, and the distribution of wear depth along the direction toward the extrusion outlet was obtained. A discrete element method (DEM) model of the die’s wear process was established. The results show that the severe wear area is located near the stop position of the compression rod, forming a plow-shaped wear area along the extrusion direction, accompanied by fatigue peeling. The wear depth gradually decreases towards the extrusion outlet. The DEM model partially reveals the occurrence of the wear phenomenon, but the particle motion speed deviates from the actual situation. The maximum compression force value range during the DEM compression stage is within the actual maximum compression force value range, and the relative error range of the average maximum compression force is less than 2%. By verifying the formula to calibrate the model, the calibrated model is compared with the actual mold wear, and the predicted value is close to the actual test result. The DEM can be used to explore the wear mechanism and predict the die’s wear failure process, laying the foundation for optimizing die wear resistance design.

The crude protein (CP) content is an important determining factor for the quality of alfalfa, and its accurate and rapid evaluation is a challenge for the industry. A model was developed by combining Fourier transform infrared spectroscopy (FTIS) and chemometric analysis. Fourier spectra were collected in the range of 4000~400 cm−1. Adaptive iteratively reweighted penalized least squares (airPLS) and Savitzky–Golay (SG) were used for preprocessing the spectral data; competitive adaptive reweighted sampling (CARS) and the characteristic peaks of CP functional groups and moieties were used for feature selection; partial least squares regression (PLSR) and random forest regression (RFR) were used for quantitative prediction modelling. By comparing the combined prediction results of CP content, the predictive performance of airPLST-cars-PLSR-CV was the best, with an RP2 of 0.99 and an RMSEP of 0.053, which is suitable for establishing a small-sample prediction model. The research results show that the combination of the PLSR model can achieve an accurate prediction of the crude protein content of alfalfa forage, which can provide a reliable and effective new detection method for the crude protein content of alfalfa forage.

Researching the thermal characteristic parameters of alfalfa is of fundamental importance for accurately measuring heat transfer and distribution during the compression process. Therefore, the thermal characteristic parameters were measured using the transient plane heat source method. Additionally, the study examined the impact of moisture content and particle size on the thermal characteristic parameters of alfalfa. The experimental results indicated that the thermal conductivity of alfalfa increased with higher moisture content, and it decreased with the increase of particle size. Similarly, the specific heat capacity increased with higher water content, while the particle size had little effect on specific heat capacity. The thermal diffusion coefficient initially decreased and then stabilized with higher water content. Moreover, the influence of particle size on thermal diffusion coefficient was not significant. The obtained thermal characteristic parameters are valuable for investigating temperature changes during the densification process of alfalfa.

As the sheep industry rapidly moves towards modernization, digitization, and intelligence, there is a need to build breeding farms integrated with big data. By collecting individual information on sheep, precision breeding can be conducted to improve breeding efficiency, reduce costs, and promote healthy breeding practices. In this context, the accurate identification of individual sheep is essential for establishing digitized sheep farms and precision animal husbandry. Currently, scholars utilize deep learning technology to construct recognition models, learning the biological features of sheep faces to achieve accurate identification. However, existing research methods are limited to pattern recognition at the image level, leading to a lack of diversity in recognition methods. Therefore, this study focuses on the small-tailed Han sheep and develops a sheep face recognition method based on three-dimensional reconstruction technology and feature point matching, aiming to enrich the theoretical research of sheep face recognition technology. The specific recognition approach is as follows: full-angle sheep face images of experimental sheep are collected, and corresponding three-dimensional sheep face models are generated using three-dimensional reconstruction technology, further obtaining three-dimensional sheep face images from three different perspectives. Additionally, this study developed a sheep face orientation recognition algorithm called the sheep face orientation recognition algorithm (SFORA). The SFORA incorporates the ECA mechanism to further enhance recognition performance. Ultimately, the SFORA has a model size of only 5.3 MB, with accuracy and F1 score reaching 99.6% and 99.5%, respectively. During the recognition task, the SFORA is first used for sheep face orientation recognition, followed by matching the recognition image with the corresponding three-dimensional sheep face image based on the established SuperGlue feature-matching algorithm, ultimately outputting the recognition result. Experimental results indicate that when the confidence threshold is set to 0.4, SuperGlue achieves the best matching performance, with matching accuracies for the front, left, and right faces reaching 96.0%, 94.2%, and 96.3%, respectively. This study enriches the theoretical research on sheep face recognition technology and provides technical support.

Baling cellulosic biomass into round bales is an effective way to reduce the cost of storage and transportation. To improve the quality of bales and reduce the baling energy consumption, this paper introduces the steel roller layout parameters of the round baler into the biomass baling process. Alfalfa was used as an experimental material for five levels pitch value of roller circumferential layout baling experiments. The results showed that the introduction of chamber non-roundness (pitch value of roller circumferential layout) destroyed the formation of the entanglement high density ring cylindrical shell lamination of the outer layer of bales, which was beneficial to the compression of bales core material. When the pitch value was 30 mm, the maximum baling pressure, radial pressure transfer loss, and the baling energy consumption of baler were reduced by 30.4%, 33.4%, and 13.7%, respectively. When the pitch value was 60 mm, the relaxation ratio and radial density difference were reduced by 6.3% and 35.8%, respectively, and the radial density uniformity of alfalfa bale was increased by 32.0%. The experimental results provide a theoretical basis and technical support for the chamber structural optimization design of the round baler.

To reveal the action mechanism of vibration frequency in alfalfa opening compression, a self-developed vibration compression test system was used to evaluate the variation of compression force during alfalfa open compression. A faster vibration frequency yielded a smaller compression force required for compressing alfalfa into blocks. Compared with free vibration compression, vibration compression was beneficial to release the internal stress of alfalfa block, reduce the forming pressure, and stabilize the high density. In the range of test vibration frequency, when the frequency was 15 Hz, the residual internal stress release ratio of alfalfa block was the highest, and the stable density of alfalfa block was the largest. Considering the pressure and alfalfa block density comprehensively, the optimized vibration frequency was approximately 15 Hz.

Compression alfalfa into briquettes is an effective way to solve the problem of storage and transportation. In the process of compression, heat is generated, which raises the temperature in the material. The appropriate temperature can improve the quality of alfalfa briquettes. In this paper, the effect of assisted vibration frequency, moisture content, and particle size on the compression temperature were tested. The results showed that when the vibration was applied, the material particle temperature in the mold rose significantly, and the core particle temperature rose faster than the edge temperature. The vibration frequency was the most significant factor affecting heat transfer in the three studied factors. When the moisture content and particle size were constant, the heat transfer effect increased first and then decreased with the vibration frequency, and it had an optimal value at 17 Hz. When the vibration frequency and particle size were constant, the heat transfer effect increased first and then decreased with the moisture content. It had an optimal value of 20%. The experimental results explained the effect of vibration frequency, moisture content, and particle size on temperature variation during alfalfa compression and provided a basis for reasonable process parameters.

Accurate identification of individual animals plays a pivotal role in enhancing animal welfare and optimising farm production. Although Radio Frequency Identification technology has been widely applied in animal identification, this method still exhibits several limitations that make it difficult to meet current practical application requirements. In this study, we proposed ViT-Sheep, a sheep face recognition model based on the Vision Transformer (ViT) architecture, to facilitate precise animal management and enhance livestock welfare. Compared to Convolutional Neural Network (CNN), ViT is renowned for its competitive performance. The experimental procedure of this study consisted of three main steps. Firstly, we collected face images of 160 experimental sheep to construct the sheep face image dataset. Secondly, we developed two sets of sheep face recognition models based on CNN and ViT, respectively. To enhance the ability to learn sheep face biological features, we proposed targeted improvement strategies for the sheep face recognition model. Specifically, we introduced the LayerScale module into the encoder of the ViT-Base-16 model and employed transfer learning to improve recognition accuracy. Finally, we compared the training results of different recognition models and the ViT-Sheep model. The results demonstrated that our proposed method achieved the highest performance on the sheep face image dataset, with a recognition accuracy of 97.9%. This study demonstrates that ViT can successfully achieve sheep face recognition tasks with good robustness. Furthermore, the findings of this research will promote the practical application of artificial intelligence animal recognition technology in sheep production.

Head smut is a soil-borne fungal disease caused by Sporisorium reilianum that infects maize tassels and ears. This disease poses a tremendous threat to global maize production. A previous study found markedly different and stably heritable tassel symptoms in some maize inbred lines with Sipingtou blood after infection with S. reilianum. In the present study, 55 maize inbred lines with Sipingtou blood were inoculated with S. reilianum and classified into three tassel symptom types (A, B, and C). Three maize inbred lines representing these classes (Huangzao4, Jing7, and Chang7-2, respectively) were used as test materials to investigate the physiological mechanisms of tassel formation in infected plants. Changes in enzyme activity, hormone content, and protein expression were analyzed in all three lines after infection and in control plants. The activities of peroxidase (POD), superoxide dismutase (SOD), and phenylalanine-ammonia-lyase (PAL) were increased in the three typical inbred lines after inoculation. POD and SOD activities showed similar trends between lines, with the increase percentage peaking at the V12 stage (POD: 57.06%, 63.19%, and 70.28% increases in Huangzao4, Jing7, and Chang7-2, respectively; SOD: 27.01%, 29.62%, and 47.07% in Huangzao4, Jing7, and Chang7-2, respectively. These were all higher than in the disease-resistant inbred line Mo17 at the same growth stage); this stage was found to be key in tassel symptom formation. Levels of gibberellic acid (GA3), indole-3-acetic acid (IAA), and abscisic acid (ABA) were also altered in the three typical maize inbred lines after inoculation, with changes in GA3 and IAA contents tightly correlated with tassel symptoms after S. reilianum infection. The differentially expressed proteins A5H8G4, P09233, and Q8VXG7 were associated with changes in enzyme activity, whereas P49353, P13689, and P10979 were associated with changes in hormone contents. Fungal infection caused reactive oxygen species (ROS) and nitric oxide (NO) bursts in the three typical inbred lines. This ROS accumulation caused biofilm disruption and altered host signaling pathways, whereas NO signaling triggered strong secondary metabolic responses in the host and altered the activities of defense-related enzymes. These factors together resulted in the formation of varying tassel symptoms. Thus, interactions between S. reilianum and susceptible maize materials were influenced by a variety of signals, enzymes, hormones, and metabolic cycles, encompassing a very complex regulatory network. This study preliminarily identified the physiological mechanisms leading to differences in tassel symptoms, deepening our understanding of S. reilianum-maize interactions.

Abstract Background The outbreak of Lumpy skin disease (LSD) in cattle caused by LSD virus (LSDV) was first reported in August 2019 in China. Since then, several LSD outbreaks have been reported in seven different provinces of China. Until now, several Lumpy skin disease virus (LSDV) strains from China have been reported and sequenced including LSDV/Xinjiang/2019 (MN598005.1), China/GD01/2020 (MW355944.1), and LSDV/Hongkong/2021 (MW732649.1). In October 2020, more than 1,700 cattle imported from Chile arrived in Xilingol, Inner Mongolia, and were diagnosed with LSD. Currently, limited data on the origin of the virus is available. Methods Nucleotide sequences of the ORF11, ORF36, ORF74, ORF117, ORF126 genes and the complete genome of LSDV strains and isolates were downloaded from NCBI database. MEGA7.0 was used to perform phylogenetic analysis with Neighbor-Joining (NJ). DNASTAR software is used to analyze homologous comparison analysis with related genes of reference strains included in Genbank. Results Compared with other strains isolated from China, the results of full genome sequence analysis showed the LSDV/NMG/2020 strain belonged to the recombinant strains. The LSDV/NMG/2020 strain is different from the current LSDV field isolates in Africa, the Middle East, Europe, and the newly emerged LSDV Russia variants. Based on the identities of P32, RPO30, EEV, GPCR and LSDV117 genes (99.8%, 99%, 99.8%, 99% and 98.7%), the sub-cluster recombinant containing LSDV/NMG/2020 strain is phylogenetically closer to the Russia strain (Saratov/2017). Conclusions In this study, we reported a new isolated LSDV strain named LSDV/NMG/2020. The results of genomic characterization and phylogenetic analysis demonstrated that the LSDV/NMG/2020 isolate was a vaccine-like recombinant strain.

Abstract Background Rubella virus (RV) is the causative agent of rubella or German measles. Although most infections cause only mild self-limited measles-like illness, the infection in pregnant women can cause severe foetal malformation or even miscarriage, especially in the first 3 months of pregnancy. Therefore, it is of great practical significance to establish a simple and sensitive RV detection method. Methods The partial epitopes of the E1 and E2 proteins from Rubella Virus were selected as the target sites, the sequence of the selected antigenic sites of the E1 and E2 were linked by a linker. The expression plasmid P6T was constructed by inserting the gene into PET-32A + with a histidine Tag. The P6 protein was induced and expressed in Escherichia coli L21 (DE3) and purified by nickel column affinity. The protein P6 antigen was identified by Western blotting analysis, and an anti-P6 antibody ELISA was established to test known serum samples to evaluate the capability of this method. Results After purification, the concentration and purity of the protein P6 were 0.283 mg/mL and more than 80%, respectively. Western blotting analysis showed that the protein P6 could react with rubella virus positive serum. By ELISA, 36 negative sera and 58 positive sera were detected. The coincidence rate, specificity and sensitivity of the ELISA were 86.2%, 88.89% and 84.48%, respectively. The P6 ELISA with a kappa coefficient of 0.715, P

Due to the large number of waterborne bacteria presenting in drinking water, their rapid and accurate identification has become a global priority. The surface plasmon resonance (SPR) biosensor with prism (BK7)-silver(Ag)-MXene(Ti3T2Cx)-graphene- affinity-sensing medium is examined in this paper, in which the sensing medium includes pure water, vibrio cholera (V. cholera), and escherichia coli (E. coli). For the Ag-affinity-sensing medium, the maximum sensitivity is obtained by E. coli, followed by V. cholera, and the minimum is pure water. Based on the fixed-parameter scanning (FPS) method, the highest sensitivity is 246.2 °/RIU by the MXene and graphene with monolayer, and with E. coli sensing medium. Therefore, the algorithm of improved differential evolution (IDE) is obtained. By the IDE algorithm, after three iterations, the maximum fitness value (sensitivity) of the SPR biosensor achieves 246.6 °/RIU by using the structure of Ag (61 nm)-MXene (monolayer)-graphene (monolayer)-affinity (4 nm)-E. coli. Compared with the FPS and differential evolution (DE) algorithm, the highest sensitivity is more accurate and efficient, and with fewer iterations. The performance optimization of multilayer SPR biosensors provides an efficient platform.

The accurate identification of sheep is crucial for breeding, behavioral research, food quality tracking, and disease prevention on modern farms. As a result of the time-consuming, expensive, and unreliable problems of traditional sheep-identification methods, relevant studies have built sheep face recognition models to recognize sheep through facial images. However, the existing sheep face recognition models face problems such as high computational costs, large model sizes, and weak practicality. In response to the above issues, this study proposes a lightweight sheep face recognition model named LSR-YOLO. Specifically, the ShuffleNetv2 module and Ghost module were used to replace the feature extraction module in the backbone and neck of YOLOv5s to reduce floating-point operations per second (FLOPs) and parameters. In addition, the coordinated attention (CA) module was introduced into the backbone to suppress non-critical information and improve the feature extraction ability of the recognition model. We collected facial images of 63 small-tailed Han sheep to construct a sheep face dataset and further evaluate the proposed method. Compared to YOLOv5s, the FLOPs and parameters of LSR-YOLO decreased by 25.5% and 33.4%, respectively. LSR-YOLO achieved the best performance on the sheep face dataset, and the mAP@0.5 reached 97.8% when the model size was only 9.5 MB. The experimental results show that LSR-YOLO has significant advantages in recognition accuracy and model size. Finally, we integrated LSR-YOLO into mobile devices and further developed a recognition system to achieve real-time recognition. The results show that LSR-YOLO is an effective method for identifying sheep. The method has high recognition accuracy and fast recognition speed, which gives it a high application value in mobile recognition and welfare breeding.

Oncolytic viral therapy is a promising treatment approach for a variety of tumor forms. Although a number of studies have demonstrated that the pseudorabies virus (PRV) may be applied as an oncolytic carrier, the anti-colorectal cancer impact of the virus and the mechanism of its cytotoxic effect remain elusive. In this study, the replication capacity and cell activity of PRV attenuated live vaccines Bartha K61 and HB98 in HCT-8 cells in vitro were investigated. Next, the antitumor ability and safety were evaluated in a mouse model of HCT-8 tumor transplantation. Both PRV strains were able to suppress tumor growth and HB98 showed higher safety and efficiency than the Bartha K61 strain. Finally, flow cytometry and immunohistochemistry examination were performed to investigate its possible cytotoxic mechanism. The results showed that PRV inhibited tumor proliferation both in vitro and in vivo by inducing apoptosis. In summary, our study discovered for the first time that the live attenuated PRV has an oncolytic effect on HCT-8 cells with high efficacy and safety.

Spexin (SPX) is a novel peptide involved in glucose and lipid metabolism and suppresses hepatic total bile acid levels by inhibiting hepatic cholesterol 7α-hydroxylase 1 expression. As important mediators for glycolysis/gluconeogenesis and lipid metabolism, the effects of bile acids on SPX expression is yet to be understood. By using SMMC7721 and BEL-7402 cell lines, we screened the effects of bile acids and found that chenodeoxycholic acid (CDCA) and deoxycholic acid (DCA) can stimulate SPX gene transcription. Both CDCA and DCA were able to stimulate SPX mRNA expression in the liver but not colon and ileum in mice. In SMMC7721 and BEL-7402 cells, CDCA- and DCA-induced SPX promoter activity was mimicked by bile acid receptor FXR and TGR5 activation and suppressed by FXR and TGR5 silencing. Adenylate cyclase (AC)/cyclic adenosine monophosphate (cAMP) activators significantly increased SPX promoter activity whereas the inhibitors for AC/CAMP/protein kinase A (PKA) and mitogen-activated protein kinases (MAPK) pathway attenuated CDCA- and DCA-induced SPX transcription. Thus, CDCA and DCA stimulate SPX expression at the hepatic level through FXR and TGR5 mediated AC/cAMP/PKA and MAPK cascades.

In the arid grasslands of northern China, unreasonable grazing methods can reduce the water content and species numbers of grassland vegetation. This project uses solar-powered GPS collars to obtain track data for sheep grazing. In order to eliminate the trajectory data of the rest area and the drinking area, the kernel density analysis method was used to cluster the trajectory point data. At the same time, the vegetation index of the experimental area, including elevation, slope and aspect data, was obtained through satellite remote sensing images. Therefore, using trajectory data and remote sensing image data to establish a neural network model of grazing intensity of sheep, the accuracy of the model could be high. The results showed that the best input parameters of the model were the combination of vegetation index, sheep weight, duration, moving distance and ambient temperature, where the coefficient of determination R2=0.97, and the mean square error MSE = 0.73. The error of grazing intensity obtained by the model is the smallest, and the spatial-temporal distribution of grazing intensity can reflect the actual situation of grazing intensity in different locations. Monitoring the grazing behavior of sheep in real time and obtaining the spatial-temporal distribution of their grazing intensity can provide a basis for scientific grazing.

Recent studies have shown the effect of microRNAs on HSC activation and transformation, which is essential for the pathogenesis of liver fibrosis. In our study, we explored the role of miR-185 in liver fibrosis. Plasma miR-185 was detected in hepatitis B virus-related liver fibrosis patients (S2/3, n = 10) by Illumina HiSeq sequencing, and healthy volunteers were selected (n = 8) as the control group. We found that the plasma miR-185 level in fibrosis patients was significantly downregulated. CCl4-induced fibrosis tissues in mouse livers and TGF-β1-activated HSCs also presented downregulated miR-185 concomitant with an increased expression of RHEB and RICTOR. To explore the correlations, LX-2 cells were transiently transfected with miR-185 mimics. The expression levels of α-SMA, collagen I, and collagen III were decreased as well as RHEB and RICTOR. Inhibition of endogenous miR-185 increased fibrogenic activity. Furthermore, dual-luciferase reporter assays indicated that miR-185 inhibited the expression of RHEB and RICTOR by directly targeting their 3′ UTRs. Moreover, silencing RHEB and RICTOR suppressed α-SMA and collagen expression levels. In conclusion, miR-185 prevents liver fibrogenesis by inhibiting HSC activation via inhibition of RHEB and RICTOR. These results provide new insights into the mechanisms behind the anti-fibrotic effect of miR-185.

An attempt to introduce assistive vibration into the process of biomass briquetting was carried out, with a focus on lowering the energy requirement and improving product quality. The effects of assistive vibration on the surface morphology of briquettes using corn stalk and wheat straw as the experimental materials was investigated, and it was found that assistive vibration can increase the flow capacity of the material and improve the press transmission as well as the uniformity of internal stresses to facilitate the inner-layer-material compression and lower the springback of the compressed material. The biomass particles were still bonded primarily by mechanical interlocking and solid bridges, but the distribution range and size of the voids or gaps between adjacent particles were reduced, and the particles or fibers of thicker layer appeared to be “lying down” instead of “standing,” indicating a higher density of the product compared with the case of compaction without vibration assistance.

A genetic map is an important and valuable tool for quantitative trait locus (QTL) mapping, marker-assisted selection (MAS)-based breeding, and reference-assisted chromosome assembly. In this study, 112 F2 plants from a cross between Linum usitatissimum L. “DIANE” and “NY17” and parent plants were subjected to high-throughput sequencing and specific-locus amplified fragment (SLAF) library construction. After preprocessing, 61.64 Gb of raw data containing 253.71 Mb paired-end reads, each 101 bp in length, were obtained. A total of 192,797 SLAFs were identified, of which 23,115 were polymorphic, with a polymorphism rate of 11.99%. Finally, 2,339 SLAFs were organized into a linkage map consisting of 15 linkage groups (LGs). The total length of the genetic map was 1483.25 centimorgans (cM) and the average distance between adjacent markers was 0.63 cM. Combined with flax chromosome-scale pseudomolecules, 12 QTLs associating with 6 flax fiber-related traits were mapped on the chromosomal scaffolds. This high-density genetic map of flax should serve as a foundation for flax fine QTL mapping, draft genome assembly, and MAS-guided breeding. Ultimately, the genomic regions identified in this research could potentially be valuable for improving flax fiber cultivars, as well as for identification of candidate genes involved in flax fiber formation processes.Significance statementA high-density genetic map of flax was constructed, and QTLs were identified on the sequence scaffolds to be interrelated with fiber-related traits. The results of this study will not only provide a platform for gene/QTL fine mapping, map-based gene isolation, and molecular breeding for flax, but also provide a reference to help position sequence scaffolds on the physical map and assist in the process of assembling the flax genome sequence.

Studies have demonstrated that microRNA 185 may be a promising therapeutic target in liver cancer. However, its role in hepatocellular carcinoma is largely unknown. In this study, the proliferation of human HepG2 cells was inhibited by transfection of microRNA 185 mimics. Cell-cycle analysis revealed arrest at the G0/G1 phase. Transfection of HepG2 cells with microRNA 185 mimics significantly induced apoptosis. These data confirmed microRNA 185 as a potent cancer suppressor. We demonstrated that microRNA 185 was a compelling inducer of autophagy, for the first time. When cell autophagy was inhibited by chloroquine or 3-methyladenine, microRNA 185 induced more cell apoptosis. MicroRNA 185 acted as a cancer suppressor by regulating AKT1 expression and phosphorylation. Dual-luciferase reporter assays indicated that microRNA 185 suppressed the expression of target genes including RHEB , RICTOR , and AKT1 by directly interacting with their 3′-untranslated regions. Binding site mutations eliminated microRNA 185 responsiveness. Our findings demonstrate a new role of microRNA 185 as a key regulator of hepatocellular carcinoma via autophagy by dysregulation of AKT1 pathway.

The biomass extrusion process for making biomass briquettes or logs normally requires large amounts of energy to overcome the springback of the material and friction with the die surface. Also, the products readily expand and disintegrate because of the retention of internal stresses. In this study, tests on vibration-assisted compaction of biomass were performed as a method to reduce the energy requirement and to improve product quality. An experimental set-up was designed and manufactured by which vibration-assisted compaction was exerted on a die surface. Tests on compaction to form upgraded biomass logs with and without the assistance of vibration were conducted and compared. The results showed that the vibration applied on a die surface can reduce the compression energy requirements and improve product quality.