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Yersinia pestis , the causative agent of plague, is a genetically monomorphic bacterial pathogen that evolved from Yersinia pseudotuberculosis approximately 7,400 years ago. We observed unusually frequent mutations in Y. pestis YPO0623, mostly resulting in protein translation termination, which implies a strong natural selection. These mutations were found in all phylogenetic lineages of Y. pestis , and there was no apparent pattern in the spatial distribution of the mutant strains. Based on these findings, we aimed to investigate the biological function of YPO0623 and the reasons for its frequent mutation in Y. pestis . Our in vitro and in vivo assays revealed that the deletion of YPO0623 enhanced the growth of Y. pestis in nutrient-rich environments and led to increased tolerance to heat and cold shocks. With RNA-seq analysis, we also discovered that the deletion of YPO0623 resulted in the upregulation of genes associated with the type VI secretion system (T6SS) at 26°C, which probably plays a crucial role in the response of Y. pestis to environment fluctuations. Furthermore, bioinformatic analysis showed that YPO0623 has high homology with a PLP-dependent aspartate aminotransferase in Salmonella enterica , and the enzyme activity assays confirmed its aspartate aminotransferase activity. However, the enzyme activity of YPO0623 was significantly lower than that in other bacteria. These observations provide some insights into the underlying reasons for the high-frequency nonsense mutations in YPO0623, and further investigations are needed to determine the exact mechanism.

The bacterium Yersinia pestis has developed various strategies to sense and respond to the complex stresses encountered during its transmission and pathogenic processes. PurR is a common transcriptional regulator of purine biosynthesis among microorganisms, and it modulates the transcription level of the pur operon to suppress the production of hypoxanthine nucleotide (IMP). This study aims to understand the functions and regulatory mechanisms of purR in Y. pestis. Firstly, we constructed a purR knockout mutant of Y. pestis strain 201 and compared certain phenotypes of the null mutant (201-ΔpurR) and the wild-type strain (201-WT). The results show that deleting purR has no significant impact on the biofilm formation, growth rate, or viability of Y. pestis under different stress conditions (heat and cold shock, high salinity, and hyperosmotic pressure). Although the cytotoxicity of the purR knockout mutant on HeLa and 293 cells is reduced, the animal-challenging test found no difference of the virulence in mice between 201-ΔpurR and 201-WT. Furthermore, RNA-seq and EMSA analyses demonstrate that PurR binds to the promoter regions of at least 15 genes in Y. pestis strain 201, primarily involved in purine biosynthesis, along with others not previously observed in other bacteria. Additionally, RNA-seq results suggest the presence of 11 potential operons, including a newly identified co-transcriptional T6SS cluster. Thus, aside from its role as a regulator of purine biosynthesis, purR in Y. pestis may have additional regulatory functions.

The bacterium Yersinia pestis has developed various strategies to sense and respond to the complex stresses encountered during its transmission and pathogenic processes. PurR is a common transcriptional regulator of purine biosynthesis among microorganisms, and it modulates the transcription level of the pur operon to suppress the production of hypoxanthine nucleotide (IMP). This study aims to understand the functions and regulatory mechanisms of purR in Y. pestis. Firstly, we constructed a purR knockout mutant of Y. pestis strain 201 and compared certain phenotypes of the null mutant (201-ΔpurR) and the wild-type strain (201-WT). The results show that deleting purR has no significant impact on the biofilm formation, growth rate, or viability of Y. pestis under different stress conditions (heat and cold shock, high salinity, and hyperosmotic pressure). Although the cytotoxicity of the purR knockout mutant on HeLa and 293 cells is reduced, the animal-challenging test found no difference of the virulence in mice between 201-ΔpurR and 201-WT. Furthermore, RNA-seq and EMSA analyses demonstrate that PurR binds to the promoter regions of at least 15 genes in Y. pestis strain 201, primarily involved in purine biosynthesis, along with others not previously observed in other bacteria. Additionally, RNA-seq results suggest the presence of 11 potential operons, including a newly identified co-transcriptional T6SS cluster. Thus, aside from its role as a regulator of purine biosynthesis, purR in Y. pestis may have additional regulatory functions.

Two new conjugated copolymers, PBDT-T6-TTF and PBDT-T12-TTF, were derived from a novel 4-fluorobenzoyl thienothi- ophene （TTF）. In addition, two types of benzodithiophene （BDT） units with 2,3-dihexylthienyl （T6） and 2,3-didodecylthienyl （T12） substituents, respectively, were successfully synthesized. The effect of the dual two-dimensional （2D） substitutions of the building blocks upon the optoelectronic properties of the polymers was investigated. Generally, the two polymers exhibited good solubility and broad absorption, showing similar optical band gaps of ~1.53 eV. However, PBDT-T6-TTF with its shorter alkyl chain length possessed a larger extinction coefficient in thin solid film. The highest occupied molecular orbital （HOMO） level of PBDT-T6-TTF was located at -5.38 eV while that of PBDT-T12-TTF was at -5.51 eV. In space charge-limited- current （SCLC） measurement, PBDT-T6-TTF and PBDT-T12-TTF displayed respective hole mobilities of 3.0~10-~ and 1.6x10 5 cm2 V-1 s-l. In polymer solar cells, PBDT-T6-TTF and PBDT-T12-TTF showed respective power conversion efficiencies （PCEs） of 2.86% and 1.67%. When 1,8-diiodooctane （DIO） was used as the solvent additive, the PCE of PBDT-T6-TTF was remarkably elevated to 4.85%, but the use of DIO for the PBDT-T12-TTF-blend film resulted in a lower PCE of 0.91%. Atomic force microscopy （AFM） indicated that the superior efficiency of PBDT-T6-TTF with 3% DIO （v/v） should be related to the better continuous phase separation of the blend film. Nevertheless, the morphology of the PBDT-T12-TTF deteriorated when the 3% DIO （v/v） was added. Our results suggest that the alkyl-chain length on the 2D BDT units play an important role in determining the optoelectronic properties of dual 2D BDT-TT-based polymers.

Carbon fiber materials possess high temperature resistance, friction resistance, thermal conductivity, and corrosion resistance. It is easy to process into various fabrics. Due to the preferred orientation of its graphite microcrystalline structure along the fiber axis, it has high strength and modulus along the fiber axis direction. Carbon fiber is lightweight, high specific strength, high modulus, which is mainly used in environmental governance, aerospace, etc. Polyacrylonitrile based activated carbon fiber materials have high strength, developed microstructure, narrow pore size distribution, high effective adsorption and desorption, good conductivity, and large specific surface area. They are often used as electrode materials, adsorption materials, catalytic, membrane separation etc. This work reviews the carbon fiber precursor materials, preparation methods, and applications in adsorption, membrane separation, catalysis, etc. The focus on the preparation method and application of polyacrylonitrile based activated carbon fibers. Finally, prospects are proposed for the current development status of carbon fiber materials.

Effective treatments for neurodegenerative diseases need to be developed. MiR132 is abundantly expressed in the brain, and it modulates neuron morphology and plays a key role in maintaining neuron survival. Regulating miR132 can effectively improve the symptoms of Alzheimer’s disease. It can also reduce cell death after cerebral hemorrhage, improve the microenvironment of hematoma lesions and provide a certain protective effect from brain damage after cerebral ischemia. MiR132 has great potential in the treatment of cerebral ischemia and Alzheimer’s disease. To prevent the decline of miR132 of miR132 levels in the blood, we used mouse and rat models of Alzheimer’s disease with ischemic brain injury, and then delivered Wheat germ agglutinin (WGA)-NPs-miR132 intranasally to treat neurological damage after cerebral ischemia. Synaptic protein expression levels in Alzheimer’s mouse models increased significantly after administration. We propose that, nasal delivery of WGA-NPs-miR132 is an interesting novel therapeutic approach for the treatment of neurodegenerative diseases.

The double poling (DP) technique in cross-country sit-skiing is primarily considered as an upper-body exercise. The upper limb muscle strength and motion economy are important factors accounting for DP performance in cross-country sit-skiing. The present study investigates how upper limb muscle strength predicts DP performance in cross-country sit-skiing. A total of 19 female non-disabled college students (age 23.2 ± 0.8 years, BMI 20.4 ± 2.2) performed 30-s and 3-min DP performance tests using a sit-skiing ergometer. Isokinetic muscle strength of the shoulder and elbow extensor were measured at the angular velocity of 30°/s, 60°/s, and 120°/s with an ISOMED2000 isokinetic system. A medium correlation was found between DP output power and isokinetic upper limb muscle strength (shoulder strength at all speeds, r  = 0.39–0.74, p  ≤ 0.1). Multiple regression analyses which were employed to predict power production in the 30-s and 3-min tests showed that shoulder extension strength at 60°/s accounted for 34% of the variation in the 30-s test, and 40% of the variance in the 3-min test. Muscle strength and biomechanical analysis of DP process indicated that upper limb extensor muscle strength and muscle coordination were important factors for the power output generation in sit-skiing DP. These results may use to guide special physical fitness training for paralympic cross-country sit-skiing.

Background The small YABBY plant-specific transcription factor has a prominent role in regulating plant growth progress and responding to abiotic stress. Results Here, a total of 16 PvYABBYs from switchgrass ( Panicum virgatum L.) were identified and classified into four distinct subgroups. Proteins within the same subgroup exhibited similar conserved motifs and gene structures. Synteny analyses indicated that segmental duplication contributed to the expansion of the YABBY gene family in switchgrass and that complex duplication events occurred in rice, maize, soybean, and sorghum. Promoter regions of PvYABBY genes contained numerous cis-elements related to stress responsiveness and plant hormones. Expression profile analysis indicated higher expression levels of many PvYABBY genes during inflorescence development and seed maturation, with lower expression levels during root growth. Real-time quantitative PCR analysis demonstrated the sensitivity of multiple YABBY genes to PEG, NaCl, ABA, and GA treatments. The overexpression of PvYABBY14 in Arabidopsis resulted in increased root length after treatment with GA and ABA compared to wild-type plants. Conclusions Taken together, our study provides the first genome-wide overview of the YABBY transcription factor family, laying the groundwork for understanding the molecular basis and regulatory mechanisms of PvYABBY14 in response to ABA and GA responses in switchgrass.

Leaf area index (LAI) is an essential vegetation parameter that represents the light energy utilization and vegetation canopy structure. As the only in-operation hyperspectral satellite launched by China, GF-5 is potentially useful for accurate LAI estimation. However, there is no research focus on evaluating GF-5 data for LAI estimation. Hyperspectral remote sensing data contains abundant information about the reflective characteristics of vegetation canopies, but these abound data also easily result in a dimensionality curse. Therefore, feature selection (FS) is necessary to reduce data redundancy to achieve more reliable estimations. Currently, machine learning (ML) algorithms have been widely used for FS. Moreover, the same ML algorithm is usually conducted for both FS and regression in LAI estimation. However, no evidence suggests that this is the optimal solution. Therefore, this study focuses on evaluating the capacity of GF-5 spectral reflectance for estimating LAI and the performances of different combination of FS and ML algorithms. Firstly, the PROSAIL model, which coupled leaf optical properties model PROSPECT and the scattering by arbitrarily inclined leaves (SAIL) model, was used to generate simulated GF-5 reflectance data under different vegetation and soil conditions, and then three FS methods, including random forest (RF), K-means clustering (K-means) and mean impact value (MIV), and three ML algorithms, including random forest regression (RFR), back propagation neural network (BPNN) and K-nearest neighbor (KNN) were used to develop nine LAI estimation models. The FS process was conducted twice using different strategies: Firstly, three FS methods were conducted to search the lowest dimension number, which maintained the estimation accuracy of all bands. Then, the sequential backward selection (SBS) method was used to eliminate the bands having minimal impact on LAI estimation accuracy. Finally, three best estimation models were selected and evaluated using reference LAI. The results showed that although the RF_RFR model (RF used for feature selection and RFR used for regression) achieved reliable LAI estimates (coefficient of determination (R2) = 0.828, root mean square error (RMSE) = 0.839), the poor performance (R2 = 0.763, RMSE = 0.987) of the MIV_BPNN model (MIV used for feature selection and BPNN used for regression) suggested using feature selection and regression conducted by the same ML algorithm could not always ensure an optimal estimation. Moreover, RF selection preserved the most informative bands for LAI estimation so that each ML regression method could achieve satisfactory estimation results. Finally, the results indicated that the RF_KNN model (RF used as feature selection and KNN used for regression) with seven GF-5 spectral band reflectance achieved the better estimation results than others when validated by simulated data (R2 = 0.834, RMSE = 0.824) and actual reference LAI (R2 = 0.659, RMSE = 0.697).

Lung cancer and asthma are both global health problems with significant economic consequences. Recent studies have demonstrated that asthma may be a risk factor for lung cancer. The present study aimed to explore the pathogenesis between these two diseases through a comprehensive analysis. Differentially expressed genes (DEGs) screened in the asthma-related GSE165934 dataset were analyzed to find relevant inflammatory pathways. Overlapping genes regulated by inflammatory pathways and lung cancer-DEGs from The Cancer Genome Atlas (TCGA) were obtained and subjected to survival and gene-wide mutation analyses, and nomogram construction to determine the hub gene. The hub gene was further analyzed through expression validation, immunoassays and functional experiments to investigate its role and mechanism in lung cancer. Functional enrichment analysis showed that 1,275 DEGs from GSE165934 were closely associated with the Toll-like receptor signaling pathway, and 8 overlapping genes were identified from 12 genes regulated by the Toll-like receptor signaling pathway and 3,134 TCGA-DEGs. After a series of bioinformatics analyses, it was found that triggering receptor expressed on myeloid cells 1 (TREM1) was the hub gene involved in the mechanism of asthma and lung cancer. TREM1 was also found to be a suppressor gene in lung cancer correlated with immune cells, immune checkpoint-related genes and tumor mutational burden score. Additionally, the results of Cell Counting Kit-8 and Transwell experiments demonstrated that overexpression of TREM1 could significantly inhibit the invasion, proliferation and migration of lung cancer cells. Reverse transcription-quantitative PCR and western blotting demonstrated that the overexpression of TREM1 could also significantly reduce the level of Toll-like receptor signaling pathway proteins. The present findings suggest that TREM1 is associated with the mechanism of asthma and lung cancer through its regulation of the Toll-like receptor signaling pathway. Furthermore, TREM1 may serve as a potential treatment target and prognostic indicator for patients with lung cancer.