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Gene expression is orchestrated by a complex array of gene regulatory elements that govern transcription in a cell-type-specific manner. Though previously studied, the ability to utilize regulatory elements to identify disrupting variants remains largely elusive. To identify important factors within these regions, we generated enhancer–promoter interaction (EPI) networks and investigated the presence of disease-associated variants that fall within these regions. Our study analyzed six neuronal cell types across neural differentiation, allowing us to examine closely related cell types and across differentiation stages. Our results expand upon previous findings of cell-type specificity of enhancer, promoter, and transcription factor binding sites. Notably, we find that regulatory regions within EPI networks can identify the enrichment of variants associated with neuropsychiatric disorders within specific cell types and network sub-structures. This enrichment within sub-structures can allow for a better understanding of potential mechanisms by which variants may disrupt transcription. Together, our findings suggest that EPIs can be leveraged to better understand cell-type-specific regulatory architecture and used as a selection method for disease-associated variants to be tested in future functional assays. Combined with these future functional characterization assays, EPIs can be used to better identify and characterize regulatory variants’ effects on such networks and model their mechanisms of gene regulation disruption across different disorders. Such findings can be applied in practical settings, such as diagnostic tools and drug development.

We study the chaotic motion of a semi-classical optomechanical system coupled to a non-Markovian environment with a finite correlation time. By studying the emergence of chaos using the Lyapunov exponent with the changing non-Markovian parameter, we show that the non-Markovian environment can significantly enhance chaos. It is observed that a non-Markovian environment characterized by the Ornstein–Uhlenbeck type noise can modify the generation of chaos with different environmental memory times. As a comparison, the crossover properties from Markov to non-Markovian regimes are also discussed. Our findings indicate that the quantum memory effects on the onset of chaos may become a useful property to be investigated in quantum manipulations and control.

The mitochondrial distribution and morphology family 33 gene (MDM33) regulates mitochondrial homeostasis by mediating the mitochondrial fission process in yeast. The wheat head blight Fusarium graminearum contains an FgMdm33 protein that is orthologous to Saccharomyces cerevisiae Mdm33, albeit its function remains unknown. We have reported here the roles of FgMdm33 in regulating fungal morphogenesis, mitochondrial morphology, autophagy, apoptosis, and fungal pathogenicity. The ΔFgmdm33 mutants generated through a homologous recombination strategy in this study exhibited defects in terms of mycelial growth, conidia production, and virulence. Hyphal cells lacking FgMDM33 displayed elongated mitochondria and a dispensable respiratory-deficient growth phenotype, indicating the possible involvement of FgMDM33 in mitochondrial fission. The ΔFgmdm33 mutants displayed a remarkable reduction in the proteolysis of GFP-FgAtg8, whereas the formation of autophagic bodies in the hyphal cells of mutants was recorded under the induction of mitophagy. In addition, the transcriptional expression of the apoptosis-inducing factor 1 gene (FgAIF1) was significantly upregulated in the ΔFgmdm33 mutants. Cumulatively, these results indicate that FgMDM33 is involved in mitochondrial fission, non-selective macroautophagy, and apoptosis and that it regulates fungal growth, conidiation, and pathogenicity of the head blight pathogen.

The cell structure of a gasoline particulate filter (GPF) is made up of thousands of individual cells. Although the symmetric square cell structure of the GPF is commonly used internationally, several cell designs have been proposed to reduce the pressure drop in the GPF trapping process. The aim of this paper was to use AVL-Fire software to establish GPF models of different cell structures, mainly including the symmetric square cell structure, asymmetric square cell structure, and symmetric hexagonal cell structure, and analyze the GPF pressure drop characteristics of different cell structures according to the carrier structural parameters and altitude. The results show that compared with the pressure drop of the symmetric square cell structure, the pressure drop of the asymmetric cell structure with inlet/outlet side length ratios ranging from 1.1 to 1.4 is decreased by 4.61%, 9.07%, 12.19%, and 13.22%, respectively, and the pressure drop of the symmetric hexagonal cell structure is decreased by 33.17%. Both asymmetric and symmetric hexagonal cell structure GPFs can decrease the pressure drop during trapping by increasing the cell density. From 200 CPSI to 300 CPSI, the pressure drop of the asymmetric cell structure with inlet/outlet side length ratios ranging from 1.1 to 1.4 is decreased by 20.43%, 20.53%, 20.39%, and 18.56%, respectively, and the pressure drop of the symmetric hexagonal cell structure is decreased by 18.70%. The pressure drop values of GPFs with asymmetric and symmetric hexagonal cell structures show an increasing trend with an increasing filter wall thickness and inlet/outlet plug length. The pressure drop values of GPFs with asymmetric and symmetric hexagonal cell structures show an increasing trend with an increasing altitude, and the larger the inlet/outlet ratio, the more significant the increase in the pressure drop.

Ehrlichia chaffeensis infects and proliferates inside monocytes or macrophages and causes human monocytic ehrlichiosis (HME), an emerging life-threatening tick-borne zoonosis. After internalization, E. chaffeensis resides in specialized membrane-bound inclusions, E. chaffeensis-containing vesicles (ECVs), to evade from host cell innate immune responses and obtain nutrients. However, mechanisms exploited by host cells to inhibit E. chaffeensis growth in ECVs are still largely unknown. Here we demonstrate that host cells recognize E. chaffeensis Ech_1067, a penicillin-binding protein, and then upregulate the expression of PIT1, which is a phosphate transporter and transports phosphate from ECVs to the cytosol to inhibit bacterial growth. We found that host cells upregulate the PIT1 expression upon E. chaffeensis infection using transcriptome sequencing, qRT-PCR and Western blotting, and PIT1 is localized on the ECV membrane in infected THP-1 cells using confocal microscopy. Silence of PIT1 using shRNA enhances E. chaffeensis intracellular growth. Finally, we found that E. chaffeensis Ech_1067 induces the upregulation of PIT1 expression through the MyD88-NF-κB pathway using recombinant protein for stimulation and siRNA for silence. Our findings deepen the understanding of the innate immune responses of host cells to inhibit bacterial intracellular growth and facilitate the development of new therapeutics for HME.

The Beiluo River Basin, situated in the central region of the Loess Plateau, frequently experiences landslide geological disasters, posing a severe threat to local lives and property. Thus, establishing a detailed database of historical landslides and analyzing and revealing their development characteristics are of paramount importance for providing a foundation for geological hazard risk assessment. First, in this study, landslides in the Beiluo River Basin are interpreted using Google Earth and ZY-3 high-resolution satellite imagery. Combined with a historical landslide inventory and field investigations, a landslide database for the Beiluo River Basin is compiled, containing a total of 1781 landslides. Based on this, the geometric and spatial characteristics of the landslides are analyzed, and the relationships between the different types of landslides and landslide scale, stream order, and geomorphological types are further explored. The results show that 50.05% of the landslides have a slope aspect between 225° and 360°, 68.78% have a slope gradient of 16–25°, and 38.97% are primarily linear in profile morphology. Areas with a high landslide density within a 10 km radius are mainly concentrated in the loess ridge and hillock landform region between Wuqi and Zhidan Counties and in the loess tableland region between Fu and Luochuan Counties, with a significant clustering effect observed in the Fu County area. Loess–bedrock interface landslides are relatively numerous in the northern loess ridge and hillock landform region due to riverbed incision and the smaller thickness of loess in this area. Intra-loess landslides are primarily found in the southern loess tableland region due to headward erosion and the greater thickness of loess in this area. Loess–clay interface landslides, influenced by riverbed incision and the limited exposure of red clay, are mainly distributed in the northern part of the southern loess tableland region and on both sides of the Beiluo River Valley in Ganquan County. These results will aid in further understanding the development and spatial distribution of landslides in the Beiluo River Basin and provide crucial support for subsequent landslide susceptibility mapping and geological hazard assessment in the region.

Cerium-based materials (CeO2−x) are of significant interest in the development of vacancy-modulated resistive switching (RS) memory devices. However, the influence of grain boundaries on the performance of memristors is very limited. To fill this gap, this study explores the influence of grain boundaries in cerium-based thin film resistive random-access memory (RRAM) devices. Sm0.2Ce0.8O2−x (SDC20) thin films were deposited on (100)-oriented Nb-doped SrTiO3 (NSTO) and (110)-oriented NSTO substrates using pulsed laser deposition (PLD). Devices constructed with a Pt/SDC20/NSTO structure exhibited reversible and stable bipolar resistive switching (RS) behavior. The differences in conduction mechanisms between single-crystal and polycrystalline devices were confirmed, with single-crystal devices displaying a larger resistance window and higher stability. Combining the results of XPS and I–V curve fitting, it was confirmed that defects near the grain boundaries in the SDC-based memristors capture electrons, thereby affecting the overall performance of the RRAM devices.

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Due to the high content of impurities such as proteins in tamarind seed polysaccharide (TSP), they must be separated and purified before it can be used. TSP can disperse in cold water, but a solution can only be obtained by heating the mixture. Therefore, it is important to understand the dispersion and dissolution process of TSP at different temperatures to expand the application of TSP. In this study, pasting behavior and rheological properties as a function of temperature were characterized in comparison with potato starch (PS), and their relationship with TSP molecular features and microstructure was revealed. Pasting behavior showed that TSP had higher peak viscosity and stronger thermal stability than PS. Rheological properties exhibited that G′ and G′′ of TSP gradually increased with the increase in temperature, without exhibiting typical starch gelatinization behavior. The crystalline or amorphous structure of TSP and starch was disrupted under different temperature treatment conditions. The SEM results show that TSP particles directly transformed into fragments with the temperature increase, while PS granules first expanded and then broken down into fragments. Therefore, TSP and PS underwent different dispersion mechanisms during the dissolution process: As the temperature gradually increased, TSP possibly underwent a straightforward dispersion and was then dissolved in aqueous solution, while PS granules initially expanded, followed by disintegration and dispersion.

Photothermal therapy (PTT) is a promising cancer therapy modality with significant advantages such as precise targeting, convenient drug delivery, better efficacy, and minimal adverse effects. Photothermal therapy effectively absorbs the photothermal transducers in the near-infrared region (NIR), which induces the photothermal effect to work. Although PTT has a better role in tumor therapy, it also suffers from low photothermal conversion efficiency, biosafety, and incomplete tumor elimination. Therefore, the use of nanomaterials themselves as photosensitizers, the targeted modification of nanomaterials to improve targeting efficiency, or the combined use of nanomaterials with other therapies can improve the therapeutic effects and reduce side effects. Notably, noble metal nanomaterials have attracted much attention in PTT because they have strong surface plasmon resonance and an effective absorbance light at specific near-infrared wavelengths. Therefore, they can be used as excellent photosensitizers to mediate photothermal conversion and improve its efficiency. This paper provides a comprehensive review of the key role played by noble metal nanomaterials in tumor photothermal therapy. It also describes the major challenges encountered during the implementation of photothermal therapy.

Enzyme-production microorganisms typically occupy a dominant position in composting, where cellulolytic microorganisms actively engage in the breakdown of lignocellulose. Exploring strains with high yields of cellulose-degrading enzymes holds substantial significance for the industrial production of related enzymes and the advancement of clean bioenergy. This study was inclined to screen cellulolytic bacteria, conduct genome analysis, mine cellulase-related genes, and optimize cellulase production. The potential carboxymethylcellulose-hydrolyzing bacterial strain Z2.6 was isolated from the maturation phase of pig manure-based compost with algae residuals as the feedstock and identified as Bacillus velezensis. In the draft genome of strain Z2.6, 31 related cellulolytic genes were annotated by the CAZy database, and further validation by cloning documented the existence of an endo-1,4-β-D-glucanase (EC 3.2.1.4) belonging to the GH5 family and a β-glucosidase (EC 3.2.1.21) belonging to the GH1 family, which are predominant types of cellulases. Through the exploration of ten factors in fermentation medium with Plackett–Burman and Box–Behnken design methodologies, maximum cellulase activity was predicted to reach 2.98 U/mL theoretically. The optimal conditions achieving this response were determined as 1.09% CMC-Na, 2.30% salinity, and 1.23% tryptone. Validation under these specified conditions yielded a cellulose activity of 3.02 U/mL, demonstrating a 3.43-fold degree of optimization. In conclusion, this comprehensive study underscored the significant capabilities of strain Z2.6 in lignocellulolytic saccharification and its potentialities for future in-depth exploration in biomass conversion.

Sonodynamic therapy (SDT) has attracted significant attention in recent years as it is an innovative approach to tumor treatment. It involves the utilization of sound waves or ultrasound (US) to activate acoustic sensitizers, enabling targeted drug release for precise tumor treatment. This review aims to provide a comprehensive overview of SDT, encompassing its underlying principles and therapeutic mechanisms, the applications of nanomaterials, and potential synergies with combination therapies. The review begins by introducing the fundamental principle of SDT and delving into the intricate mechanisms through which it facilitates tumor treatment. A detailed analysis is presented, outlining how SDT effectively destroys tumor cells by modulating drug release mechanisms. Subsequently, this review explores the diverse range of nanomaterials utilized in SDT applications and highlights their specific contributions to enhancing treatment outcomes. Furthermore, the potential to combine SDT with other therapeutic modalities such as photothermal therapy (PTT) and chemotherapy is discussed. These combined approaches aim to synergistically improve therapeutic efficacy while mitigating side effects. In conclusion, SDT emerges as a promising frontier in tumor treatment that offers personalized and effective treatment options with the potential to revolutionize patient care. As research progresses, SDT is poised to play a pivotal role in shaping the future landscape of oncology by providing patients with a broader spectrum of efficacious and tailored treatment options.

Straw mulching is a key method for controlling soil and water losses. Mulching costs may be reduced by applying it in strips rather than over entire areas. However, the effect of different straw mulching methods on the effectiveness of reducing soil erosion is unclear. In this study, the effects of straw mulching strip length (covering 1/4, 1/2, 3/4, and 4/4 of the slope length) and coverage rate (0.2, 0.5, and 0.8 kg m−2) on interception, infiltration, runoff, and soil erosion were investigated at the plot scale using rainfall simulation experiments. The further complex correlations between these variables were analyzed using structural equation modeling (SEM). Bare slopes were used as a control group. The rainfall intensity was chosen to be 60 mm h−1. The results showed that (1) the modified Merriam interception model can describe the change in interception with time under straw mulching conditions well (R2 > 0.91, NSE > 0.75). (2) A total of 35.39–78.79% of the rainwater is converted into infiltration on straw-covered slopes, while this proportion is 36.75% on bare slopes. The proportion of rainwater converted to infiltration was greatest (78.79%) when the straw covered 3/4 of the slope length at a coverage rate of 0.5 kg m−2, which was the most conducive to rainwater harvesting on the slope. (3) Straw mulching protects the topsoil from the impact of raindrops and directly affects the sediment yield (direct effect = −0.44). Straw mulching can also indirectly affect sediment yield by increasing interception, reducing runoff, and decreasing the sediment carrying capacity of runoff (indirect effect = −0.83). Compared with bare slopes, straw covering at least 1/2 of the slope length can significantly reduce runoff yield, but straw covering only 1/4 of the slope length can significantly reduce sediment yield. Moreover, once the straw mulch slope length reaches 3/4 and the coverage rate reaches 0.5 kg m−2, further increases in mulch slope length and coverage rate will not significantly reduce the runoff and sediment yields. These results assessed the effectiveness of different straw mulching methods in controlling soil and water losses on sloping farmland.

Peatlands store large amounts of carbon in wetland ecosystems. The hydrological conditions within peatlands are important factors that affect the biochemical cycle and patterns of greenhouse gas emissions in these peatlands. This study was carried out in Changbai Mountain Jinchuan peatland to investigate variations in carbon dioxide and methane emissions in peat swamps that have undergone distinct saturation conditions. Three peatland types (high water levels (S1); medium water levels (S2); low water levels (S3)) at different flood depths were selected as specific sampling points. The static box and gas chromatography methods were used at different time periods (6:00; 12:00; and 18:00) from July to September. The discharge flux of CO2 and CH4 slowly increased with the increase in the water level. The results indicate similarity in the fluctuation trends between the fluxes of CO2 and CH4 in S1 and S2 to the fluctuations of water levels. During the entire growth season, the flux range of CO2 and CH4 was −695.329~859.907 mg m2h−1 and 259.981~147.155 mg m2h−1, respectively. Furthermore, there was variation in mutation characteristics between two gases, the CO2 exhibited larger mutation range (−7.08~3.40) than CH4 (−1.79~1.26). In terms of daily flux changes, CO2 showed an upward trend, while CH4 had a downward trend. These results indicate variations in saturation conditions tend to affect discharge of greenhouse gases, with subsequent effects on climate change. This study highlights potential theoretical support to reduce anthropogenic activities on peatlands. This can be achieved by undertaking measures to conserve peatlands and explore mitigation measures to minimize greenhouse gas emissions and hence impacts of climate change.

Ehrlichia chaffeensis infects human monocytes or macrophages and causes human monocytic ehrlichiosis (HME), an emerging life-threatening zoonosis. After internalization, E. chaffeensis resides in membrane-bound inclusions, E. chaffeensis-containing vesicles (ECVs), which have early endosome-like characteristics and fuse with early autophagosomes but not lysosomes, to evade host innate immune microbicidal mechanisms and obtain nutrients for bacterial intracellular growth. The mechanisms exploited by E. chaffeensis to modulate intracellular vesicle trafficking in host cells have not been comprehensively studied. Here, we demonstrate that E. chaffeensis type IV secretion system (T4SS) effector Etf-3 induces RAB15 upregulation in host cells and that RAB15, which is localized on ECVs, inhibits ECV fusion with lysosomes and induces autophagy. We found that E. chaffeensis infection upregulated RAB15 expression using qRT-PCR, and RAB15 was colocalized with E. chaffeensis using confocal microscopy. Silence of RAB15 using siRNA enhanced ECV maturation to late endosomes and fusion with lysosomes, as well as inhibited host cell autophagy. Overexpression of Etf-3 in host cells specifically induced RAB15 upregulation and autophagy. Our findings deepen the understanding of E. chaffeensis pathogenesis and adaptation in hosts as well as the function of RAB15 and facilitate the development of new therapeutics for HME.

The epoxy resin-based (ESB) intumescent flame-retardant coatings were modified with 1,4-butanediol diglycidyl ether (14BDDE) and butyl glycidyl ether (BGE) as diluents and T403 and 4,4′-diaminodiphenylmethane (DDM) as curing agents, respectively. The effects of different diluents and curing agents on the flame-retardant and mechanical properties, as well as the composition evolution of the coatings, were investigated by using large-plate combustion, the limiting oxygen index (LOI), vertical combustion, a cone calorimeter, X-ray diffraction, FTIR analysis, a N2 adsorption and desorption test, a scanning electron microscope (SEM), a tensile strength test, and a viscosity test. The results showed that the addition of 14BBDE and T403 promoted the oxidation of B4C and the formation of boron-containing glass or ceramics, increased the residual mass of char, densified the surface char layer, and increased the specific surface area of porous residual char. When their dosage was 30%, ESB-1T-3 coating exhibited the most excellent flame-retardant properties. During the 2 h large-plate combustion test, the backside temperature was only 138.72 °C, without any melting pits. In addition, the peak heat release rate (PHRR), total heat release rate (THR), total smoke production (TSP), and peak smoke production (PSPR) were reduced by 13.15%, 13.9%, 5.48%, and 17.45%, respectively, compared to the blank ESB coating. The LOI value reached 33.4%, and the vertical combustion grade was V-0. In addition, the tensile strength of the ESB-1T-3 sample was increased by 10.94% compared to ESB. In contrast, the addition of BGE and DDM promoted the combustion of the coating, affected the ceramic process of the coating, seriously affected the formation of borosilicate glass, and exhibited poor flame retardancy. The backside temperature reached 190.93 °C after 2 h combustion. A unified rule is that as the amount of diluent and curing agent increases, the flame retardancy improves while the mechanical properties decrease. This work provides data support for the preparation and process optimization of resin-based coatings.

Asarum (Asarum sieboldii Miq. f. seoulense (Nakai) C. Y. Cheng et C. S. Yang) is a medicinal plant that contains asarinin and sesamin, which possess extensive medicinal value. The adaptation and distribution of Asarum’s plant growth are significantly affected by altitude. Although most studies on Asarum have concentrated on its pharmacological activities, little is known about its growth and metabolites with respect to altitude. In this study, the physiology, ionomics, and metabolomics were investigated and conducted on the leaves and roots of Asarum along an altitude gradient, and the content of its medicinal components was determined. The results showed that soil pH and temperature both decreased along the altitude, which restricts the growth of Asarum. The accumulation of TOC, Cu, Mg, and other mineral elements enhanced the photosynthetic capacity and leaf plasticity of Asarum in high-altitude areas. A metabolomics analysis revealed that, at high altitude, nitrogen metabolism in leaves was enhanced, while carbon metabolism in roots was enhanced. Furthermore, the metabolic pathways of some phenolic substances, including syringic acid, vanillic acid, and ferulic acid, were altered to enhance the metabolism of organic acids. The study uncovered the growth and metabolic responses of Asarum to varying altitudes, providing a theoretical foundation for the utilization and cultivation of Asarum.

We aimed to compare the performance and interobserver agreement of radiologists manually segmenting images or those assisted by automatic segmentation. We further aimed to reduce interobserver variability and improve the consistency of radiomics features. This retrospective study included 327 patients diagnosed with prostate cancer from September 2016 to June 2018; images from 228 patients were used for automatic segmentation construction, and images from the remaining 99 were used for testing. First, four radiologists with varying experience levels retrospectively segmented 99 axial prostate images manually using T2-weighted fat-suppressed magnetic resonance imaging. Automatic segmentation was performed after 2 weeks. The Pyradiomics software package v3.1.0 was used to extract the texture features. The Dice coefficient and intraclass correlation coefficient (ICC) were used to evaluate segmentation performance and the interobserver consistency of prostate radiomics. The Wilcoxon rank sum test was used to compare the paired samples, with the significance level set at p < 0.05. The Dice coefficient was used to accurately measure the spatial overlap of manually delineated images. In all the 99 prostate segmentation result columns, the manual and automatic segmentation results of the senior group were significantly better than those of the junior group (p < 0.05). Automatic segmentation was more consistent than manual segmentation (p < 0.05), and the average ICC reached >0.85. The automatic segmentation annotation performance of junior radiologists was similar to that of senior radiologists performing manual segmentation. The ICC of radiomics features increased to excellent consistency (0.925 [0.888~0.950]). Automatic segmentation annotation provided better results than manual segmentation by radiologists. Our findings indicate that automatic segmentation annotation helps reduce variability in the perception and interpretation between radiologists with different experience levels and ensures the stability of radiomics features.

Pheasants are widely distributed in the southwest of China, but many of them are endangered due to habitat fragmentation and environmental changes. Genetic diversity is crucial for species to maintain their evolutionary potential, and thus it is important to develop universal genetic markers for facilitating the assessment of genetic diversity and planning effective conservation actions in these endangered species. In this study, 471 microsatellite loci which are common among eight pheasant species were screened based on genome data, and 119 loci were selected to develop microsatellite markers. After PCR amplifications and reaction condition optimizations, and validation of microsatellite loci in 14 species of 11 genera within Phasianidae. Finally, 49 potentially universal microsatellite markers in pheasant species were obtained. These microsatellite markers were successfully applied to assess the genetic diversity of 3 pheasant species. The Sichuan hill partridge (Arborophila rufipectus), blood pheasant (Ithaginis cruentus), buff-throated partridge (Tetraophasis szechenyii) and Sichuan hill partridge had a relatively low genetic diversity level. These 49 microsatellite loci are potentially universal microsatellite loci for pheasants and are of great significance to establish a shared platform in population genetics study of pheasants.

Tumors are a major public health issue of concern to humans, seriously threatening the safety of people’s lives and property. With the increasing demand for early and accurate diagnosis and efficient treatment of tumors, noninvasive optical imaging (including fluorescence imaging and photoacoustic imaging) and tumor synergistic therapies (phototherapy synergistic with chemotherapy, phototherapy synergistic with immunotherapy, etc.) have received increasing attention. In particular, light in the near-infrared second region (NIR-II) has triggered great research interest due to its penetration depth, minimal tissue autofluorescence, and reduced tissue absorption and scattering. Nanomaterials with many advantages, such as high brightness, great photostability, tunable photophysical properties, and excellent biosafety offer unlimited possibilities and are being investigated for NIR-II tumor imaging-guided synergistic oncotherapy. In recent years, many researchers have tried various approaches to investigate nanomaterials, including gold nanomaterials, two-dimensional materials, metal sulfide oxides, polymers, carbon nanomaterials, NIR-II dyes, and other nanomaterials for tumor diagnostic and therapeutic integrated nanoplatform construction. In this paper, the application of multifunctional nanomaterials in tumor NIR-II imaging and collaborative therapy in the past three years is briefly reviewed, and the current research status is summarized and prospected, with a view to contributing to future tumor therapy.

Lumpy skin disease virus (LSDV) infection, accompanied by loss of hide quality, poor reproductive efficiency, consistent degenerative emaciation, and milk yield reduction of animals, causes severe economic implications in endemic zones. The heterologous attenuated goat pox (GTPV) vaccine (AV41 strain) was used in China to prevent LSDV infection. Only a few LSDV detection methods that distinguish LSDV from GTPV vaccine strains have been reported before. For simple, rapid, and specific detection of LSDV, the real-time recombinase polymerase amplification (RPA) method was established with the specific primers and probes designed according to the conserved regions of ORF132 gene sequences. The assay could be finished within 20 min at a constant temperature (39 °C). This method had a limit of detection (LOD) of 15 copies/μL for LSDV and no cross-reaction with the nucleic acids of goat pox virus, infectious bovine rhinotracheitis virus, Pasteurella multocida, and bovine healthy tissue. Furthermore, 43 clinical samples were detected by this method and the real-time PCR recommended by the World Organisation for Animal Health (WOAH), with a kappa value, was 0.94. These results demonstrated that the real-time RPA method for detecting LSDV developed in this study was characterized by high sensitivity and specificity, which has wide application value in the clinical diagnosis and detection of LSDV in China.

Neogurelca montana (Rothschild & Jordan, 1915) is a species of the genus Neogurelca Hogenes & Treadaway, 1993, that was previously known from Sichuan, Yunnan, and Tibet, China. Recently, however, this species was also found in Beijing and Hebei. These populations differ from those in southwest China in body colour and the shape of the yellow patches of the hindwing—a paler body colour and triangular patches in the former and darker body colour and fan-like patches in the latter. Wing morphology, male and female genitalia, and molecular evidence (DNA barcodes) were analysed for the different localities of this species and three other Neogurelca species—N. hyas, N. himachala, and N. masuriensis. Our molecular data support the Beijing population of montana as a valid subspecies, which we describe as N. montana taihangensis ssp. nov. Wing and genital morphology confirm the molecular conclusions. We also collected larvae of the new subspecies in the Beijing suburbs and describe its life history and larval hosts and compare them with those of N. himachala.

The substrate in the aquatic environment plays a crucial role in nutrient deposition and recovery for the growth of aquatic organisms. In order to optimize the culture medium of Procambarus Clarkii, culture media from different sources were selected in this study to explore their effects on the growth and immune performance of red swamp crayfish. The results showed that the weight gain rate (WGR), body length growth rate (BLGR) and specific growth rate (SGR) in group I2 were the highest, followed by group I1 and group I3. The WGR and SGR of crayfish in the I1 and I2 groups were significantly higher than those in the I3 group (p < 0.05). The activities of acid phosphatase (ACP), alkaline phosphatase (AKP) and superoxide dismutase (SOD) were the highest in group I2, followed by group I3, and the lowest in group I1. The expression trends in growth-related genes, nuclear hormone receptor (E75), molt-inhibiting hormone (MIH) and chitinase genes were similar, and the expression levels in the I2 group were higher than those in the I1 and I3 groups. It was noted that the expression levels of E75 and MIH genes in the I2 group were significantly higher than those in the I3 group (p < 0.05). α diversity analysis of 16S rRNA data showed that there was no statistically significant difference in the abundance of intestinal flora among the three culture substrate groups. The β diversity in the Xitangni group, crayfish Tangni group and Shuitangni group was significantly different. These changes in microbiota suggest that using different substrates to culture crayfish leads to differences in gut microbiota diversity. To sum up, the growth in crayfish and immune performance influenced by the culture substrate condition and aquatic breeding sediment substrates, rather than crab pool and paddy field pond sediment substrates, showed a better effect.

Previous studies of mice infected with Babesia microti have shown that a single dose of tafenoquine administered orally is extremely effective at decreasing microscopically detectable parasitemia. However, a critical limitation of studies to date is the lack of data concerning the plasma levels of tafenoquine that are needed to treat babesiosis. In the current study, we begin to address this gap by examining the plasma levels of tafenoquine associated with the rapid reduction of B. microti patent parasitemia in a mouse model of babesiosis. In the current study, we infected BALB/c mice with 1 × 107 B. microti-infected red blood cells. Two days post-infection, mice were treated with 20 mg/kg of tafenoquine succinate or vehicle control administered orally by gavage. Parasitemia and plasma levels of tafenoquine were evaluated every 24 h post-treatment for 96 h. This allowed us to correlate blood plasma levels of tafenoquine with reductions in parasitemia in treated mice. Consistent with previous studies, a single oral dose of 20 mg/kg tafenoquine resulted in a rapid reduction in parasitemia. Plasma levels of tafenoquine 24 h post-administration ranged from 347 to 503 ng/mL and declined thereafter. This blood plasma tafenoquine level is similar to that achieved in humans using the current FDA-approved dose for the prevention of malaria.

Wintersweet (Chimonanthus praecox (L.) Link, Calycanthaceae) is an esteemed ornamental flowering shrub known for its distinct blooming period in winter, vibrant color petals, and captivating floral fragrance. Basic helix-loop-helix (bHLH) transcription factors (TFs) play pivotal roles as key regulators in secondary metabolites biosynthesis, growth, and development in plants. However, the systematic analysis of the bHLH family members and their role in the regulation of floral traits in Wintersweet remains insufficiently understood. To bridge this knowledge gap, we conducted a comprehensive genome-wide analysis of the C. praecox bHLH (CpbHLH) gene family, identifying a total of 131 CpbHLH genes across 11 chromosomes. Phylogenetic analysis classified these CpbHLH genes into 23 subfamilies, wherein most members within the same subfamily exhibited analogous intron/exon patterns and motif composition. Moreover, the expansion of the CpbHLH gene family was primarily driven by segmental duplication, with duplicated gene pairs experiencing purifying selection during evolution. Transcriptomic analysis revealed diverse expression patterns of CpbHLH genes in various tissues and distinct stages of Wintersweet flower development, thereby suggesting their involvement in a diverse array of physiological processes. Furthermore, yeast 2-hybrid assay demonstrated interaction between CpbHLH25 and CpbHLH59 (regulators of floral scent and color) as well as with CpbHLH112 and CpMYB2, suggesting potential coordinately regulation of secondary metabolites biosynthesis in Wintersweet flowers. Collectively, our comprehensive analysis provides valuable insights into the structural attributes, evolutionary dynamics, and expression profiles of the CpbHLH gene family, laying a solid foundation for further explorations of the multifaceted physiological and molecular roles of bHLH TFs in Wintersweet.

Due to their low cost, interference resistance, and concealment of vision sensors, vision-based landing systems have received a lot of research attention. However, vision sensors are only used as auxiliary components in visual landing systems because of their limited accuracy. To solve the problem of the inaccurate position estimation of vision-only sensors during landing, a novel data closed-loop pose-estimation algorithm with an implicit neural map is proposed. First, we propose a method with which to estimate the UAV pose based on the runway’s line features, using a flexible coarse-to-fine runway-line-detection method. Then, we propose a mapping and localization method based on the neural radiance field (NeRF), which provides continuous representation and can correct the initial estimated pose well. Finally, we develop a closed-loop data annotation system based on a high-fidelity implicit map, which can significantly improve annotation efficiency. The experimental results show that our proposed algorithm performs well in various scenarios and achieves state-of-the-art accuracy in pose estimation.

Background: Globally, 10–15% of maternal deaths are statistically attributable to preeclampsia. Compared with late-onset PE, the severity of early-onset PE remains more harmful with higher morbidity and mortality. Objective: To establish an early-onset preeclampsia prediction model by clinical characteristics, risk factors and routine laboratory indicators were investigated from pregnant women at 6 to 10 gestational weeks. Methods: The clinical characteristics, risk factors, and 38 routine laboratory indicators (6–10 weeks of gestation) including blood lipids, liver and kidney function, coagulation, blood count, and other indicators of 91 early-onset preeclampsia patients and 709 normal controls without early-onset preeclampsia from January 2010 to May 2021 in Peking University Third Hospital (PUTH) were retrospectively analyzed. A logistic regression, decision tree model, and support vector machine (SVM) model were applied for establishing prediction models, respectively. ROC curves were drawn; area under curve (AUCROC), sensitivity, and specificity were calculated and compared. Results: There were statistically significant differences in the rates of diabetes, antiphospholipid syndrome (APS), kidney disease, obstructive sleep apnea (OSAHS), primipara, history of preeclampsia, and assisted reproductive technology (ART) (p < 0.05). Among the 38 routine laboratory indicators, there were no significant differences in the levels of PLT/LYM, NEU/LYM, TT, D-Dimer, FDP, TBA, ALP, TP, ALB, GLB, UREA, Cr, P, Cystatin C, HDL-C, Apo-A1, and Lp(a) between the two groups (p > 0.05). The levels of the rest indicators were all statistically different between the two groups (p < 0.05). If only 12 risk factors of PE were analyzed with the logistic regression, decision tree model, and support vector machine (SVM), and the AUCROC were 0.78, 0.74, and 0.66, respectively, while 12 risk factors of PE and 38 routine laboratory indicators were analyzed with the logistic regression, decision tree model, and support vector machine (SVM), and the AUCROC were 0.86, 0.77, and 0.93, respectively. Conclusions: The efficacy of clinical risk factors alone in predicting early-onset preeclampsia is not high while the efficacy increased significantly when PE risk factors combined with routine laboratory indicators. The SVM model was better than logistic regression model and decision tree model in early prediction of early-onset preeclampsia incidence.

The results of high-precision asphalt concrete pavement crack identification can provide help for pavement maintenance. Therefore, methods of image feature enhancement and crack identification of asphalt concrete pavement cracks are proposed. First of all, we used an industrial CCD camera mounted on a vehicle to collect an asphalt concrete pavement crack image. Then, after using the NeighShrink algorithm to denoise the acquired image, a fractional differential image enhancement algorithm was designed based on image feature blocks to enhance the image features. On this basis, crack characteristics were segmented and processed by watershed algorithm. Through crack direction identification and crack parameter extraction, crack distribution direction, crack length and width and other parameters of asphalt concrete pavement were obtained in order to achieve accurate identification of asphalt concrete pavement cracks. The experiment found that this method can effectively remove noise information from asphalt concrete crack images; after applying this method, the image entropy value of each image was improved, with a minimum improvement of 0.38 and a maximum improvement of 1.98. The time consumed by this method in identifying cracks in asphalt concrete pavement varied between 1.4 s and 2.4 s. When identifying the length of cracks in asphalt concrete pavement, the maximum deviation value was only 0.47 mm; when identifying the width of cracks in asphalt concrete pavement, the maximum deviation value was only 0.31 mm. The above results indicate that by enhancing the image features of asphalt concrete cracks, this method achieves more accurate identification results for crack distribution direction, length and width values, with high identification efficiency and good application effect.

As a current research hotspot, graph convolution networks (GCNs) have provided new opportunities for tree species classification in multi-source remote sensing images. To solve the challenge of limited label information, a new tree species classification model was proposed by using the semi-supervised graph convolution fusion method for hyperspectral images (HSIs) and multispectral images (MSIs). In the model, the graph-based attribute features and pixel-based features are fused to deepen the correlation of multi-source images to improve accuracy. Firstly, the model employs the canonical correlation analysis (CCA) method to maximize the correlation of multi-source images, which explores the relationship between information from various sources further and offers more valuable insights. Secondly, convolution calculations were made to extract features and then map graph node fusion, which not only reduces redundancy features but also enhances compelling features. Finally, the relationship between representative descriptors is captured through the use of hyperedge convolution in the training process, and the dominant features on the graph are fully mined. The tree species are classified through two fusion feature operations, leading to improved classification performance compared to state-of-the-art methods. The fusion strategy can produce a complete classification map of the study areas.

MicroRNAs (miRNAs) and transfer RNA-derived small RNAs (tsRNAs) play critical roles in the regulation of different biological processes, but their underlying mechanisms in diabetes mellitus (DM) are still largely unknown. This study aimed to gain a better understanding of the functions of miRNAs and tsRNAs in the pathogenesis of DM. A high-fat diet (HFD) and streptozocin (STZ)-induced DM rat model was established. Pancreatic tissues were obtained for subsequent studies. The miRNA and tsRNA expression profiles in the DM and control groups were obtained by RNA sequencing and validated with quantitative reverse transcription-PCR (qRT-PCR). Subsequently, bioinformatics methods were used to predict target genes and the biological functions of differentially expressed miRNAs and tsRNAs. We identified 17 miRNAs and 28 tsRNAs that were significantly differentiated between the DM and control group. Subsequently, target genes were predicted for these altered miRNAs and tsRNAs, including Nalcn, Lpin2 and E2f3. These target genes were significantly enriched in localization as well as intracellular and protein binding. In addition, the results of KEGG analysis showed that the target genes were significantly enriched in the Wnt signaling pathway, insulin pathway, MAPK signaling pathway and Hippo signaling pathway. This study revealed the expression profiles of miRNAs and tsRNAs in the pancreas of a DM rat model using small RNA-Seq and predicted the target genes and associated pathways using bioinformatics analysis. Our findings provide a novel aspect in understanding the mechanisms of DM and identify potential targets for the diagnosis and treatment of DM.

A collision avoidance method that is specifically tailored for UAVs (unmanned aerial vehicles) operating in converging airspace is proposed. The method is based on ADS-B messages and it aims to detect and resolve conflicts between UAVs. The proposed method involves two main steps. First, a UAV conflict-sensing scheme is developed, which utilizes ADS-B information flow path and analyzes the message format information. Second, an unscented Kalman filter is used to predict UAV trajectories based on the acquired ADS-B information. The predicted information is then used to determine potential conflict scenarios, and different deconfliction strategies are selected accordingly. These strategies include speed regulation, direction regulation, and compound deconfliction, and are mathematically validated using the velocity obstacle method. The feasibility and effectiveness of the proposed method are evaluated through simulation, and it is concluded that the method can significantly improve the conflict resolution capability of UAV flights. This research provides a valuable contribution to the field of UAV collision avoidance, and can serve as a theoretical foundation for further advancements in this area.

Terpene synthase (TPS) plays a key role in the biosynthesis of terpenoids, which are the most important components of the volatile compounds of wintersweet (Chimonanthus praecox). In this study, 52 CpTPS genes were found in wintersweet which were divided into 5 subfamilies. We identified 146 SSRs in the CpTPS genes, and obtained 33 pairs of SSR primers with good polymorphism through amplification in 6 wintersweet samples. Then, these primers were amplified in 69 samples from China’s main wintersweet production areas. Through structural analysis, 69 samples were divided into 2 clusters, and were divided into 4 groups in a genetic cluster analysis, of which SH-33 and SW were separate groups. Through AMOVA analysis, it was found that the variation mainly occurred in the population, and that the gene flow between populations was Nm > 1, so it might lead to population differentiation. In other words, these findings provided useful information for the biosynthesis of terpenoids, the construction of a genetic linkage map, the detection of quantitative trait loci, marker-assisted selection and other aspects of wintersweet.

Climate change is altering the abundance and distributions of natural communities in mountainous ecosystems, but the variations of soil microbial communities and their driving factors along elevation gradients at high altitudinal mid-subtropical zones have received limited attention. Such information is needed for a comprehensive understanding of the ecosystem’s response to intensifying climate changes. In this study, using Illumina sequencing, we investigated the shift in soil microbial diversity and community composition at eight evergreen broadleaf forest sites, which ranged from a low of 550 to a high of 1038 m above sea level (m a.s.l.) on Wuyi Mountain in Southeast China. Significant (p < 0.05) differences were observed only in the community structure of bacteria and fungi between the low and high elevation levels of forests, but not in their alpha-diversity indices. Soil bacterial diversity was significantly correlated with plant Shannon index. Likewise, plant richness and diversity modified soil bacterial community structures along the two elevations and were the best predictors. Soil pH was the main edaphic factor driving the fungal diversity across elevations, whereas inconsistency in the fungal trophic mode did not allow the identification of a determinant factor for soil fungal community structure. The variations of the predominant fungal trophic guilds, such as the symbiotrophs and pathotrophs, along elevation gradients were due to the plant richness and diversity prevailing at the low and high elevation levels of forest sites. The findings of this study reveal the soil microbial community dynamics and the local regulators across elevations on Wuyi mountain.

The umbrella-species strategy has been proposed as an attainable tool to achieve multi-species and community conservation with limited investment. There have been many umbrella-related studies since the concept’s inception; thus, a summary of global study efforts and recommended umbrella species is important for understanding advances in the field and facilitating conservation applications. Here, we collated 213 recommended umbrella species of terrestrial vertebrates from 242 scientific articles published during 1984–2021 and analyzed their geographic patterns, biological features, and conservation statuses to identify global trends in the selection of umbrella species. We found a considerable geographic bias: most studies and, consequently, recommended umbrella species are from the Northern Hemisphere. There is also a strong taxonomic bias, with grouses (order Galliformes) and large carnivores being the most popular umbrella species and amphibians and reptiles being largely overlooked. In addition, wide-ranging and non-threatened species were frequently recommended as umbrella species. Given the observed biases and trends, we caution that appropriate species need to be chosen for each location, and it is important to confirm that popular, wide-ranging species are effective umbrella species. Moreover, amphibians and reptiles should be investigated for their potential as umbrella species. The umbrella-species strategy has many strengths and, if applied appropriately, may be one of the best options in today’s conservation research and funding landscape.

As a typical symbol-wise solution of asymmetric Slepian-Wolf coding problem, Distributed Arithmetic Coding (DAC) non-linearly partitions source space into disjoint cosets with unequal sizes. The distribution of DAC coset cardinalities, named the Coset Cardinality Spectrum (CCS), plays an important role in both theoretical understanding and decoder design for DAC. In general, CCS cannot be calculated directly. Instead, a numerical algorithm is usually used to obtain an approximation. This paper first finds that the contemporary numerical algorithm of CCS is theoretically imperfect and does not finally converge to the real CCS. Further, to solve this problem, we refine the original numerical algorithm based on rigorous theoretical analyses. Experimental results verify that the refined numerical algorithm amends the drawbacks of the original version.

With the widespread use of end devices, online multi-label learning has become popular as the data generated by users using the Internet of Things devices have become huge and rapidly updated. However, in many scenarios, the user data are often generated in a geographically distributed manner that is often inefficient and difficult to centralize for training machine learning models. At the same time, current mainstream distributed learning algorithms always require a centralized server to aggregate data from distributed nodes, which inevitably causes risks to the privacy of users. To overcome this issue, we propose a distributed approach for multi-label classification, which trains the models in distributed computing nodes without sharing the source data from each node. In our proposed method, each node trains its model with its local online data while it also learns from the neighbour nodes without transferring the training data. As a result, our proposed method achieved the online distributed approach for multi-label classification without losing performance when taking existing centralized algorithms as a reference. Experiments show that our algorithm outperforms the centralized online multi-label classification algorithm in F1 score, being 0.0776 higher in macro F1 score and 0.1471 higher for micro F1 score on average. However, for the Hamming loss, both algorithms beat each other on some datasets, and our proposed algorithm loses 0.005 compared to the centralized approach on average, which can be neglected. Furthermore, the size of the network and the degree of connectivity are not factors that affect the performance of this distributed online multi-label learning algorithm.

In order to solve the problem of manual labeling in semi-supervised tree species classification, this paper proposes a pixel-level self-supervised learning model named M-SSL (multisource self-supervised learning), which takes the advantage of the information of plenty multisource remote sensing images and self-supervised learning methods. Based on hyperspectral images (HSI) and multispectral images (MSI), the features were extracted by combining generative learning methods with contrastive learning methods. Two kinds of multisource encoders named MAAE (multisource AAE encoder) and MVAE (multisource VAE encoder) were proposed, respectively, which set up pretext tasks to extract multisource features as data augmentation. Then the features were discriminated by the depth-wise cross attention module (DCAM) to enhance effective ones. At last, joint self-supervised methods output the tress species classification map to find the trade-off between providing negative samples and reducing the amount of computation. The M-SSL model can learn more representative features in downstream tasks. By employing the feature cross-fusion process, the low-dimensional information of the data is simultaneously learned in a unified network. Through the validation of three tree species datasets, the classification accuracy reached 78%. The proposed method can obtain high-quality features and is more suitable for label-less tree species classification.

Background: Increasingly, studies have discovered that different fatty acids (Fas) are linked to colorectal cancer (CRC) risk. Methods: We systematically searched Embase and Medline databases to identify eligible studies that examined the associations of different types of Fas with CRC risk. The effect estimates and their 95% confidence intervals (Cis) were pooled using a random-effects model. Subgroup and sensitivity analyses were performed to examine the robustness of the study findings. Results: This study evaluated the associations of 28 dietary and 18 blood Fas with CRC risk by summarizing the most updated evidence from 54 observational and four Mendelian Randomization (MR) studies. The present findings suggested that high dietary intake of eicosapentaenoic acid (EPA), docosahexanoic acid (DHA), and docosapentaenoic acid (DPA) are related to low risk of CRC, while the n-6/n-3 PUFA ratio and trans-FA are related to high risk of CRC. The summary of all cohort studies found that a high intake of SFA and DHA was a protective factor for CRC, and a high intake of the n-6/n-3 PUFA ratio was a risk factor for CRC. In the subgroup analysis of cancer subsites, we found that the dietary intake of linoleic acid (LA) and trans-FA are risk factors, while DPA is a protective factor for colon cancer. High dietary DHA intake was associated with a lower risk of rectal cancer, while the dietary n-6/n-3 PUFA ratio was associated with a higher risk of rectal cancer. Meta-analysis of blood FA levels showed a significant reverse association between blood pentadecanoic acid and CRC risk, whilst other blood Fas showed no significant association with CRC risk. All included MR studies showed that high plasma arachidonic acid (AA) is associated with increased CRC risk. Conclusions: Current evidence on the dietary intake and blood levels of Fas in relation to CRC risk is less consistent. Future studies are needed to investigate how the metabolism of Fas contributes to CRC development.

Trehalose, as a non-reductive disaccharide, plays a vital role in plant growth and development and resistance to abiotic stress. Trehalose-6-phosphate synthase (TPS) is a key enzyme in the synthesis mechanism of trehalose and TPS1 genes play a crucial role in the response to abiotic stress in plants. However, it has rarely been reported that CaTPS1 responds to cold and salt stresses in pepper. To verify the function of CaTPS1 in response to cold and salt stresses, CaTPS1 was silenced by virus-induced gene silencing (VIGS). Subsequently, the expressions of CaTPS1, plant morphology and some physiological indexes were analyzed after cold and salt stresses in pepper. The results showed that the expression of CaTPS1 was significantly lower in CaTPS1-silenced (pTRV2-CaTPS1) plant than that in the non-VIGS (CK) and negative control (PTRV2-00) plants. The parameters of response to cold and salt stresses have changed accordingly. The chlorophyll content decreased, while the trehalose content, peroxidase (POD) activity, catalase (CAT) activity and ascorbate peroxidase (APX) activity increased in all treatments. However, these parameters of response to cold and salt stresses were significantly lower in pTRV2-CaTPS1 plant than in CK and PTRV2-00 plants. This study suggested that CaTPS1 was involved in the response to cold and salt stresses in pepper.

Aiming at the features of deformation caused by large diameter vertical two-layer pipe jacking in the soil-rock composite stratum, on-site monitoring and numerical analysis has been done based on an electric power tunnel project constructed with the pipe jacking method, in which the upper tunnel is located in the soil layer and the lower tunnel is partially located in the rock layer. The research shows that: (1) During upper pipe jacking construction, the maximum transverse and longitudinal ground settlements are about three times those of the lower pipe jacking construction, and the maximum horizontal lateral displacement is about 3.3 times the lower pipe jacking construction. (2) Total ground settlement increases rapidly with the reduction of vertical clear spacing of the upper and lower pipe, and the superimposed effect should be taken into consideration during the vertical arranged pipe-jacking construction. (3) The Peck formula, which is used to estimate lateral surface subsidence distribution, is modified to make it more applicable in the soil–rock composite stratum to calculate the ground settlement induced by the construction of pipe-jacking.

The authors of the published paper [...]

The performance of a drive system with a flux-switching permanent magnet (FSPM) motor was studied through tests on a commercial electric vehicle (CEV). A practical design and an optimization method for the FSPM motor were proposed for a light-duty CEV. The initial dimensions of the motor were calculated by theoretical equations referring to a permanent magnet synchronous motor. Then, optimization was conducted through a response surface methodology (RSM) and a genetic algorithm (GA) based on three-dimensional finite element analysis (3D-FEA). With the optimized parameters, a prototype of the FSPM drive system was manufactured and assembled into an actual CEV. The performance of the CEV was investigated on an automobile test platform. The experimental results show that the FSPM drive system could drive the CEV properly. The high-efficiency running time of the FSPM motor accounted for 84% of the total time tested, which shows great potential for practical application in CEVs. However, the experimental results also show that the FSPM motor faced problems of large speed deviation and high-temperature rise during the driving cycle test, which should be fully addressed for practical applications.

In the fiberglass industry, Pt–Rh bushings made of platinum and rhodium have very good characteristics, such as high temperature resistance, corrosion resistance, oxidation resistance, and creep resistance. In this paper, a semi-infinite lath structure model is constructed, and the expression of the surface temperature distribution of a Pt–Rh alloy plate with a circular through hole is obtained based on the non-Fourier heat conduction equation, complex function method and conformal mapping method. At the same time, the influence of the position of the circular through hole in the Pt–Rh bushing and the parameters of the incident light source (Non-diffusion incident wave number and relative thermal diffusion length) on the surface temperature distribution of the Pt–Rh bushing is studied by using this formula. It is found that: 1. heat concentration and fracture are occur easily at the through hole; 2. when the through hole is in the asymmetric center, the greater the asymmetry, the smaller the maximum temperature amplitude; 3. when the buried depth of the through hole increases, the maximum temperature amplitude decreases; 4. when the incident wave number and the relative thermal diffusion length of the incident light source are larger, the maximum temperature amplitude is smaller. The numerical results are almost consistent with those of ANSYS thermal simulation. The expression of the surface temperature distribution of the semi-infinite lath structure proposed in this paper can effectively reduce the loss of precious metal materials and the time of thermal simulation in the experimental process, as well as provide important significance for structural design, quality inspection, process optimization, and service life improvement of Pt–Rh bushings.

(1) Background: soil salinization has become a global problem that restricts agricultural production; thus, there is a need to explore the special survival strategies of halophytes in saline–alkali environments. (2) Methods: this study conducted a comparative analysis of the differences in metabolites and mineral elements between two indicator plants (Suaeda glauca and Suaeda salsa) in the study area. (3) Results: S. salsa leaves accumulated more total nitrogen (TN), total organic carbon (TOC), calcium (Ca), sodium (Na) and manganese (Mn). The Na/K analysis showed that S. salsa was more tolerant of saline–alkali environments than S. glauca. Metabolite analysis revealed a significant increase in added sugars in S. salsa compared with S. glauca and a significant accumulation of most organic acids associated with the TCA cycle, which suggests an enhancement in the flow of carbon from glycolysis to the TCA cycle. In addition, the content of phenolic substances, such as phenylpropane compounds and flavonols, also changed in saline–alkali environments, which may have promoted the metabolism of organic acids. (4) Conclusions: during the process of plant adaptation to salinity, the central metabolism of S. glauca was nitrogen metabolism, while that of S. salsa was organic acid metabolism.

Semi-supervised learning (SSL) is a popular research area in machine learning which utilizes both labeled and unlabeled data. As an important method for the generation of artificial hard labels for unlabeled data, the pseudo-labeling method is introduced by applying a high and fixed threshold in most state-of-the-art SSL models. However, early models prefer certain classes that are easy to learn, which results in a high-skewed class imbalance in the generated hard labels. The class imbalance will lead to less effective learning of other minority classes and slower convergence for the training model. The aim of this paper is to mitigate the performance degradation caused by class imbalance and gradually reduce the class imbalance in the unsupervised part. To achieve this objective, we propose FocalMatch, a novel SSL method that combines FixMatch and focal loss. Our contribution of FocalMatch adjusts the loss weight of various data depending on how well their predictions match up with their pseudo labels, which can accelerate system learning and model convergence and achieve state-of-the-art performance on several semi-supervised learning benchmarks. Particularly, its effectiveness is demonstrated with the dataset that has extremely limited labeled data.

YABBY is a specific transcription factor gene family in plants. It has the typical N-terminal C2C2-type zinc-finger domain and the C-terminal YABBY conservative structure domain, which play an important role in the development of the leaves and floral organs. The YABBY gene family directs leaf polarity in mango, playing an important role in maintaining species specificity. In this study, a total of seven YABBY genes were identified in the mango (Mangifera indica) genome. The seven YABBY family members possessed both typical C2C2 and YABBY domains. A phylogenetic tree was constructed based on the amino acid sequences of the 42 YABBY proteins of mango, Arabidopsis, apple, grape, and peach. The phylogenetic tree indicated that the members of the mango YABBY family could be divided into three subfamilies, including CRC, YAB5, and YAB3. Quantitative real-time PCR showed that the transcription levels of the MiYABBYs were significantly different under biotic and abiotic stresses. The transcription level of MiYABBY7 was significantly down-regulated at 0–72 h after Xanthomonas campestris pv. mangiferaeindicae infection, methyl jasmonate and salicylic acid stresses. The MiYABBY1 transcription level was significantly down-regulated at 0–72 h after Colletotrichum gloeosporioides infection. MiYABBYs were expressed specifically in different leaves and fruit, and MiYABBY6 was significantly up-regulated during leaf and fruit development. However, MiYABBY5 showed a contrary transcriptional pattern during leaf and fruit development. This is first report on the mango YABBY gene family at the genome-wide level. These results will be beneficial for understanding the biological functions and molecular mechanisms of YABBY genes.

Clarifying the distribution pattern and overlapping relationship of sympatric relative species in the spatio-temporal niche is of great significance to the basic theory of community ecology and integrated management of multi-species habitats in the same landscape. In this study, based on a 9-year dataset (2012–2021) from 493 camera-trap sites in the Gongga Mountain National Nature Reserve, we analyzed the habitat distributions and activity patterns of tufted deer (Elaphodus cephalophus) and sambar (Rusa unicolor). (1) Combined with 235 and 153 valid presence sites of tufted deer and sambar, the MaxEnt model was used to analyze the distribution of the two species based on 11 ecological factors. The distribution areas of the two species were 1038.40 km2 and 692.67 km2, respectively, with an overlapping area of 656.67 km2. Additionally, the overlap indexes Schoener’s D (D) and Hellinger’s-based I (I) were 0.703 and 0.930, respectively. (2) Based on 10,437 and 5203 independent captures of tufted deer and sambar, their daily activity rhythms were calculated by using the kernel density estimation. The results showed that the daily activity peak in the two species appeared at dawn and dusk; however, the activity peak in tufted deer at dawn and dusk was later and earlier than sambar, respectively. Our findings revealed the spatio-temporal niche relationship between tufted deer and sambar, contributing to a further understanding of the coexistence mechanism and providing scientific information for effective wild animal conservation in the reserve and other areas in the southeastern edge of the Qinghai–Tibetan Plateau.

Thanks to the development of deep learning, the use of data-driven methods to detect pavement distresses has become an active research field. This research makes four contributions to address the problem of efficiently detecting cracks and sealed cracks in asphalt pavements. First, a dataset of pavement cracks and sealed cracks is created, which consists of 10,400 images obtained by a vehicle equipped with a highway condition monitor, with 202,840 labeled distress instances included in these pavement images. Second, we develop a dense and redundant crack annotation method based on the characteristics of the crack images. Compared with traditional annotation, the method we propose generates more object instances, and the localization is more accurate. Next, to achieve efficient crack detection, a semi-automatic crack annotation method is proposed, which reduces the working time by 80% compared with fully manual annotation. Finally, comparative experiments are conducted on our dataset using 13 currently prevailing object detection algorithms. The results show that dense and redundant annotation is effective; moreover, cracks and sealed cracks can be efficiently and accurately detected using the YOLOv5 series model and YOLOv5s is the most balanced model with an F1-score of 86.79% and an inference time of 14.8ms. The pavement crack and sealed crack dataset created in this study is publicly available.

Omeprazole is commonly prescribed to obese patients and patients after laparoscopic sleeve gastrectomy (LSG). The pharmacokinetics of oral omeprazole after LSG are still unknown. Therefore, the aim of this study was to investigate the pharmacokinetics of oral omeprazole in obese patients before and after LSG. A total of 331 blood samples were collected from 62 obese patients preoperatively (visit 1) followed by 41 patients 7 days post-LSG (visit 2) and 20 patients 1 month post-LSG (visit 3). Population pharmacokinetic analysis was performed using NONMEM to characterize the effect of LSG on omeprazole absorption and disposition. A one-compartment model with 12 transit absorption compartments and linear elimination successfully described the data. Compared with pre-surgery, the oral omeprazole time to maximum plasma concentration (Tmax) was reduced and maximum plasma concentration (Cmax) was higher, but the apparent clearance (CL/F) and area under the plasma concentration–time curve (AUC) were unchanged 7 days and 1 month after surgery. In addition, the CYP2C19 genotype and liver function exhibited a significant influence on omeprazole CL/F. LSG increased the rate of omeprazole absorption but did not affect omeprazole exposure. A dose of 20 mg omeprazole once daily may be adequate for relieving gastrointestinal tract discomfort at short-term follow-up post-LSG.