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Although disintegrated dolomite, widely distributed across the globe, has conventionally been a focus of research in underground engineering, the issue of slope stability issues in disintegrated dolomite strata is gaining increasing prominence. This is primarily due to their unique properties, including low strength and loose structure. Current methods for evaluating slope stability, such as basic quality (BQ) and slope stability probability classification (SSPC), do not adequately account for the poor integrity and structural fragmentation characteristic of disintegrated dolomite. To address this challenge, an analysis of the applicability of the limit equilibrium method (LEM), BQ, and SSPC methods was conducted on eight disintegrated dolomite slopes located in Baoshan, Southwest China. However, conflicting results were obtained. Therefore, this paper introduces a novel method, SMRDDS, to provide rapid and accurate assessment of disintegrated dolomite slope stability. This method incorporates parameters such as disintegrated grade, joint state, groundwater conditions, and excavation methods. The findings reveal that six slopes exhibit stability, while two are considered partially unstable. Notably, the proposed method demonstrates a closer match with the actual conditions and is more time-efficient compared with the BQ and SSPC methods. However, due to the limited research on disintegrated dolomite slopes, the results of the SMRDDS method tend to be conservative as a safety precaution. In conclusion, the SMRDDS method can quickly evaluate the current situation of disintegrated dolomite slopes in the field. This contributes significantly to disaster risk reduction for disintegrated dolomite slopes.

Compound pollution at industrial sites impedes urban development, especially when there is a lack of understanding about the spatial variations of internal pollution in industrial areas producing light-weight materials. In this study, spatial distribution and ecological risks of potentially toxic elements (PTEs), volatile organic compounds (VOCs), and petroleum hydrocarbons (C10–40) in the soil and groundwater of an Al/Cu (aluminum/copper) industrial site have been analyzed comprehensively. Results revealed the progressive clustering of pollutants in different soil layers, which indicated varying levels of penetration and migration of pollutants from the surface downward. Furthermore, severity of pollution varied according to pollutant type, with Cu (5–10,228 mg kg−1) often exceeding the background levels significantly (>40). Cd (0.03–2.60 mg kg−1) and Hg (0.01–3.73 mg kg−1) were found at elevated concentrations in deeper soil layers, suggesting distinct variations of PTEs across different soil depths. Among the more hazardous VOCS, polychlorinated biphenyls (1.80–234 μg kg−1) were particularly prevalent in the deeper layers of soil. Petroleum hydrocarbons (C10–40) were widely detected (6–582 mg kg−1), showing significant migration potential from surface to deep soil. These findings suggest that prolonged industrial activities lead to deep-seated accumulation of pollutants, which also impacts the groundwater, contributing to long-term dispersion of contaminants. Furthermore, multivariate statistical analysis indicated certain positive correlations among the distribution of Cu, Pb and petroleum hydrocarbons, indicating possible coupling of these pollutants. Severe Cu pollution caused an ecological risk in the surface soil layer (covering >20 % area of high pollution site, contributing >40 % ecological risk). While the Hg and Cd posed significant risks in the deeper soil layers, showing higher risk coefficients and mobility. The study provides crucial insights into the transformation of urban areas with a history of industrial uses into community spaces and highlights the risks posed by the remaining pollutants.

Neuropathic pain results from damage to nerves or the brain, and is characterized by symptoms such as allodynia, spontaneous pain, and hyperalgesia. The causes of this type of pain are intricate, which can make it difficult to treat. Sodium aescinate (SA), a natural extract from horse chestnut tree seeds, has been shown to act as a neuroprotector by inhibiting microglia activation. This study aims to explore the therapeutic potential of SA for neuropathic pain and the molecular mechanisms regulated by SA treatment. Through in vivo animal models and experiments, we found that SA treatment significantly reduced mechanical allodynia and heat hyperalgesia in neuropathic pain models. Additionally, SA inhibited O-GlcNAc-transferase (OGT)-induced O-GlcNAcylation (O-GlcNAc) modification in neuropathic pain mice. OGT overexpression could impede the therapeutic effects of SA on neuropathic pain. Further investigation revealed that Toll-like receptor 3 (TLR3), stabilized by OGT-induced O-GlcNAc modification, could activate the Mitogen activated protein kinase (MAPK) signaling pathway. Further in vivo experiments demonstrated that TLR3-mediated p38 mitogen-activated protein kinase (p38MAPK) activation is involved in SA-mediated relief of neuropathic pain. In conclusion, this study uncovers a novel molecular pathway deactivated by SA treatment in neuropathic pain.

Study region: Inner Mongolia Autonomous Region, North China Study focus: Sensible heat flux (H) quantifies the intensity of water evapotranspiration, making the factors influencing H pivotal to water consumption. North China's semi-arid grasslands are characterized by widespread grazing and strong wind conditions. Grazing strategy modifies surface air heat transfer resistance via vegetation and consequently alters H. Nevertheless, the majority of studies overlook the impact of the observed variables' time scale on H estimation. This paper employs a ''big-leaf'' model to estimate H, incorporating both grazing management strategy and data time scale, validated using the Bowen ratio, and attempted to analyze the factors that affect H. New hydrological insights for the region: Aerodynamic characteristics estimated from daily data typically exceed estimates derived from hourly data. The influence of surface radiative temperature and air temperature on H outweighs that of aerodynamic resistance, whereas aerodynamic resistance accounts for the disparity in estimating H between daily and hourly data. In grazing-prohibited grasslands, the daily H values estimated by the Big Leaf model closely match those obtained from the Bowen ratio. When estimating the hourly H value for grazing prohibited and grazing grasslands, the increase was 25.95 w/m2 and 52.27 w/m2 compared to the daily scale, respectively. For the estimation of water and heat fluxes across different regions, the temporal scale of input data is a pivotal factor.

Globally, water scarcity threatens food security, especially in arid and semi-arid food-producing regions, such as the Hetao Irrigation District (HID), where the water consumption during the non-growth season (spring irrigation, autumn irrigation) accounts for more than 30 % of the total irrigation volume. Meanwhile, mapping the characteristics of spatial and temporal evolution of the area of cropland irrigated in the spring and autumn and the pattern of water consumption is crucial for strengthening the management of agricultural water use. Evaporation and infiltration of irrigation water are difficult to capture in time due to insufficient timeliness or accuracy of single remote sensing data. This study integrates seven remote sensing datasets (Landsat5, Landsat7, Landsat8, HJ-1A/B, GF-1, Sentinel-2 and MODIS) for the first time to build a high spatial-temporal resolution dataset, and combines the water index NDWI and MNDWI to extract the maximum water range formed after irrigation by manually adjusting the threshold method. In addition to the global land use/cover dataset (GLC FCS30–1985_2020), the cropland layer was superimposed to accurately identify the cropland spring irrigation and autumn irrigation range from 2000 to 2021 in the HID. In the past 20 years, spring-irrigated (SI) areas increased by 1012.60 km2 (+49.96 %), and the autumn-irrigated (AI) areas decreased by 512.63 km2 (-11.02 %). Combined with the quantity of water diversion and displacement, the characteristics of irrigation water consumption in the non-growth season were further analysed. The results showed that the water consumption of spring irrigation increased by 0.67×108 m3 (+22.26 %), and that of autumn irrigation increased by 4.34×108 m3 (+38.82 %). The decrease of autumn- irrigated area and the increase of water consumption were mainly related to the stability of autumn irrigation water, imperfect irrigation and drainage conditions and insufficient field water management. In 2020­2021, the area of non-growth “autumn irrigation - spring irrigation” repeated irrigation is about 1271.52 km2, which can be used as a key control area. This study provides a theoretical basis and direction for rational water use in non-growth seasons of irrigation districts.

Abstract N6‐methyladenosine (m6A) is the most abundant modification of RNA in eukaryotic cells. Previous studies have shown that m6A is pivotal in diverse diseases especially cancer. m6A corelates with the initiation, progression, resistance, invasion, and metastasis of cancer. However, despite these insights, a comprehensive understanding of its specific roles and mechanisms within the complex landscape of cancer is still elusive. This review begins by outlining the key regulatory proteins of m6A modification and their posttranslational modifications (PTMs), as well as the role in chromatin accessibility and transcriptional activity within cancer cells. Additionally, it highlights that m6A modifications impact cancer progression by modulating programmed cell death mechanisms and affecting the tumor microenvironment through various cancer‐associated immune cells. Furthermore, the review discusses how microorganisms can induce enduring epigenetic changes and oncogenic effect in microorganism‐associated cancers by altering m6A modifications. Last, it delves into the role of m6A modification in cancer immunotherapy, encompassing RNA therapy, immune checkpoint blockade, cytokine therapy, adoptive cell transfer therapy, and direct targeting of m6A regulators. Overall, this review clarifies the multifaceted role of m6A modification in cancer and explores targeted therapies aimed at manipulating m6A modification, aiming to advance cancer research and improve patient outcomes.

Abstract In this paper, the tribological characteristics of an oil-soluble magnetic fluid additive under mixed lubrication are studied by experiments and numerical simulation. [bmim][FeCl4] is dissolved in CF10W-40 lubricating oil as a magnetic liquid additive, and its friction coefficient is tested by a point contact friction tester at different temperatures, rotational speeds and magnetic field intensities. The transition condition of lubrication state is obtained through analyzing the Stribeck curves based on the experiments, and the strength model of boundary film is established accordingly. A mixed lubrication model is established by substituting the boundary film strength model and the surface roughness model into the hydrodynamic lubrication model based on Reynolds equation. The results show that the magnetic solution as an additive can obviously reduce friction and wear, and the effect is more obvious under the condition of magnetic field. The boundary film strength model can accurately reflect the transition characteristics of lubrication state in the presence of boundary film, and the mixed lubrication model based on boundary film strength model can more precisely reflect the tribological characteristics of friction pairs, so this study provides a new theoretical method for the related research on the influence of boundary film on lubrication characteristics.

The spatial and temporal variations of net surface radiation (Rn) are critical for comprehending ecological environments. Nonetheless, the intricate interplay among Rn dynamics, vegetation growth, climate, and natural factors remains inadequately elucidated. In this study, we estimated net surface radiation based on Landsat data and ERA5 meteorological data in the Google Earth Engine (GEE) platform, which closely matched the observable spatial distribution (R2 = 0.96), with an average growth rate of 0.15 MJ m−2 mth−1. Trend analyses and spatial autocorrelation were used to explore the spatial and temporal changes in net radiation from 2000 to 2020, the global Moran's index for net radiation was found to exceed 0.76, with fluctuating increases, showing a highly positive spatial distribution of Rn. Local Moran's I predominantly fell into two categories: ‘High-High’ and ‘Low-Low’, with the first increasing in range and the latter decreasing. Combining GeoDetector and PLS-SEM analyses, temperature and vegetation emerge as predominant drivers of net surface radiation variation within the study area, each contributing more than 17% to Rn change. Furthermore, interactions between any two factors typically exhibits nonlinear enhancement. PLS-SEM underscores the influence of vegetation and climate on Rn, with other factors indirectly affecting net radiation changes by influencing vegetation growth.

Background: Breast cancer is a highly malignant disease worldwide, but there are currently no sufficient molecular biomarkers to predict patient prognosis and guide radiotherapy. The tumor microenvironment (TME) is an important factor affecting tumor biological function, and changes in its composition are equally relevant to tumor progression and prognosis during radiotherapy. Methods: Here, we performed bioinformatic analyses using data obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases to screen for molecular biomarkers related to the TME that may influence radiotherapy sensitivity. By combining immune scores and stromal scores and performing weighted coexpression network analysis (WGCNA), we identified key modules and hub genes to construct competing endogenous RNA (ceRNA) networks. Then, key pathways and genes were identified using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Furthermore, we explored the effect of THBS2 on the malignant phenotype of breast cancer through cellular experiments. Results: Genes in the PI3K-AKT pathway in the blue module were significantly enriched. Among the hub genes in the blue module, COL1A1, COL1A2, COL6A3, THBS2 and PDGFRB were negatively associated with RT sensitivity. Cellular experiments confirmed that knockdown of THBS2 inhibited the proliferation and invasion of breast cancer cells. Conclusion: These findings may provide new insights into the mechanisms of radiotherapy sensitivity in breast cancer patients, offering hope for the discovery of new therapeutic targets.

BackgroundKlebsiella pneumoniae is a common Gram-negative bacterium. Blood infection caused by K. pneumoniae is one of the most common causes of human sepsis, which seriously threatens the life of patients. The immune status of peripheral blood mononuclear cells (PBMCs) based on single-cell RNA sequencing (scRNA-seq) in acute stage and recovery stage of sepsis caused by K. pneumoniae bloodstream infection has not been studied.MethodsA total of 13 subjects were included in this study, 3 healthy controls, 7 patients with K. pneumoniae bloodstream infection in the acute stage (4 patients died), and 3 patients in the recovery stage. Peripheral blood of all patients was collected and PBMCs were isolated for scRNA-seq analysis. We studied the changes of PBMCs components, signaling pathways, differential genes, and cytokines in acute and recovery stages.ResultsDuring K. pneumoniae acute infection we observed a decrease in the proportion of T cells, most probably due to apoptosis and the function of T cell subtypes was disorder. The proportion of monocytes increased in acute stage. Although genes related to their phagocytosis function were upregulated, their antigen presentation capacity-associated genes were downregulated. The expression of IL-1β, IL-18, IFNGR1 and IFNGR2 genes was also increased in monocytes. The proportion of DCs was depleted during the acute stage and did not recover during sepsis recovery. DCs antigen presentation was weakened during the acute stage but recovered fast during the recovery stage. pDCs response to MCP-1 chemokine was weakened, they recovered it quickly during the recovery stage. B cells showed apoptosis both in the acute stage and recovery stage. Their response to complement was weakened, but their antigen presentation function was enhanced. The proportion of NK cells stable during all disease’s stages, and the expression of IFN-γ gene was upregulated.ConclusionThe proportion of PBMCs and their immune functions undergo variations throughout the course of the disease, spanning from the acute stage to recovery. These findings provide new insights into the mechanism of PBMCs immune function during K. pneumoniae bloodstream infection sepsis and recovery and sets the basis for further understanding and treatment.

ABSTRACTAccurate identification and classification of forage grass are pivotal in optimizing forage resources and breeding superior forage varieties. Given the low accuracy in forage image identification and classification, and the loss of some features from preprocessing, we proposed an innovative approach that integrates preprocessing operations directly into the model instead of preceding feature analysis. We captured near-ground hyperspectral imagery of forage in the field and applied two deep learning models – Squeeze and Excitation ResNet (SEResNet) and Convolution Block Attention Module ResNet (CBAMResNet). These models not only harness the automatic learning capabilities of the ResNet deep network but also employ channel attention and a channel-plus-space dual attention mechanism to filter and label important features. This approach enhances data extraction and analysis, strengthen the correlation between the channel and space dimensions while eliminating redundancy and noise. We compared the performance of the proposed methods with the current popular methods by six evaluation parameters, including overall accuracy (OA), average accuracy (AA), Kappa coefficient, etc. Experiment results show the OA of SEResNet and CBAMResNet are 96.57% and 98.35% respectively. The experiments demonstrate the feasibility of incorporating preprocessing into the network and the effectiveness of the new idea for the classification research of forage.

The microplastic pollution in freshwater system is gradually becoming more severe, which has led to increasing attention on the distribution and potential harmful effects of microplastics. Moreover, microplastics may have an impact on river ecology and pose risks to ecosystems. Therefore, it is important to reveal this process. This study aimed to explore correlations between microplastics and free-living microorganisms in an urban drinking water source of Xiangjiang River by using multivariate statistical analysis. The results indicated that the abundance of microplastics (size 50 μm to 5 mm) in surface water and sediments ranged from 0.72 to 18.6 (mean ± SD: 7.32 ± 2.36) items L−1 and 26.3–302 (150 ± 75.6) items kg−1 dry weight (dw), respectively, suggesting potential microplastic pollution despite the protected status as a drinking water source. Higher microplastic abundances were observed in urban areas and the downstream of wastewater plants, with mostly granular shape, transparent and black color as well as 50–100 μm in size. The multivariate statistical analysis presented that the abundance of microplastics is not significantly correlated with water indicators, due to the complexity of the abundance data. The water indicators showed an obvious correlation with microplastics in colors of transparent and black, and smaller sizes of 50–100 μm. This is also true for microplastics and microorganisms in water and sediment. Proteobacteria was the main prokaryote in water and sediments, being positively correlated with 50–100 μm microplastics; while Chloroplastida was the dominated eukaryotes, presenting a weak correlation with smaller-size microplastics. Overall, when considering the properties of microplastics such as shape, color and size, the potential correlations with water indicators and microorganisms were more evident than abundance. This study provides new insights into the multivariate statistical analysis, explaining the potential correlations among microplastic properties, microorganisms and environmental factors in a river system.

Abstract Background Early availability of pathogen identification in urinary tract infections (UTIs) has critical importance in disease management. Metagenomic next-generation sequencing (mNGS) has the potential to transform how acute and serious infections are diagnosed by offering unbiased and culture-free pathogen detection. However, clinical experience with application of the mNGS test is relatively limited. Methods We therefore established a MinION-based mNGS pathogens diagnostic platform and evaluated its potential for clinical implementation in UTIs with clinical samples. 213 urine samples from patients with suspected UTIs were included and subjected to mNGS testing using the MinION platform. mNGS results were compared to the gold standard of clinical culture and composite standard of combining clinical testing, confirmatory qPCR testing, and clinical adjudication by doctors. Results The mNGS exhibited a sensitivity of 81.4% and a specificity of 92.3%, along with a positive predictive value of 96.6%, a negative predictive value of 64.9%, and an overall accuracy of 84.4%, all of which were determined based on the gold standard of routine culture results. When assessed against the composite standard, the sensitivity and specificity both increased to 89.9% and 100%, respectively, while the accuracy rose to 92.4%. Notably, the positive predictive value and negative predictive value also saw improvements, reaching 100% and 76.8%, respectively. Moreover, this diagnostic platform successfully identified dsDNA viruses. Among the 65 culture-negative samples, the viral detection rate reached 33.8% (22/65) and was subsequently validated through qPCR. Furthermore, the automatic bioinformatics pipeline we developed enabled one-click analysis from data to results, leading to a significant reduction in diagnosis time. Conclusion These results demonstrate that the pathogen detection performance of mNGS is sufficient for diagnostic testing in clinical settings. As the method is generally unbiased, it can improve diagnostic testing of UTIs and other microbial infections.

ObjectiveTo determine the extent to which the regional brain volumes associated with slow gait speed can inform subsequent cognitive decline in older adults from the Rush Memory and Aging Project.ApproachWe utilized deformation-based morphometry (DBM) in a whole-brain exploratory approach to identify the regional brain volumes associated with gait speed assessed over a short distance during an in-home assessment. We created deformation scores to summarize the gait-associated regions and entered the scores into a series of longitudinal mixed effects models to determine the extent to which deformation predicted change in cognition over time, controlling for associations between gait and cognition.ResultsIn 438 older adults (81 ± 7; 76% female), DBM revealed that slower gait speed was associated with smaller volumes across frontal white matter, temporal grey matter, and subcortical areas and larger volumes in the ventricles during the same testing cycle. When a subset was followed over multiple (5 ± 2) years, slower gait speed was also associated with annual declines in global cognition, executive functioning, and memory abilities. Several of the gait-related brain structures were associated with these declines in cognition; however, larger ventricles and smaller medial temporal lobe volumes proved most robust and attenuated the association between slow gait and cognitive decline.ConclusionRegional brain volumes in the ventricles and temporal lobe associated with both slow gait speed and faster cognitive decline have potential to improve risk stratification for cognitive decline in older adults.

The microstructural characteristics and mechanical properties of friction stir lap welding (FSLW) of thin Al-clad Al (1.5 mm) and ultra-thin Al-clad mild steel (0.7 mm) sheets are experimentally investigated. Optical microscopic observation confirms that the FSLW joints are successfully fabricated without noticeable joining defects, such as cracks and hooks. The material flow is correlated with the silicon (Si) element distribution in the stir zone (SZ). The distribution of Si indicates that material flow is asymmetrical between the advancing side (AS) and the retreating side (RS) of the SZ. The tensile test result shows that all the FSLW joints fracture from the Al-clad Al side of the joints. During the fatigue tests, two different crack propagation modes (vertical crack in the Al-clad Al loading side; horizontal crack in the Al-clad mild steel loading side) are observed simultaneously due to the combined effect of the asymmetric geometry of the FSLW joint and the different loading configurations. The results of fatigue tests suggest that the asymmetric microstructure of the joint retards the propagation of a vertical crack in the Al-clad Al loading side for the RS-loaded FSLW joint. As a result, the fatigue life of the RS-loaded FSLW joint becomes clearly higher than that of the AS-loaded FSLW joint.

Forkhead box M1 (FOXM1) plays a critical role in development physiologically and tumorigenesis pathologically. However, insufficient efforts have been dedicated to exploring the regulation, in particular the degradation of FOXM1. Here, the ON-TARGETplus siRNA library targeting E3 ligases was used to screen potential candidates to repress FOXM1. Of note, mechanism study revealed that RNF112 directly ubiquitinates FOXM1 in gastric cancer, resulting in a decreased FOXM1 transcriptional network and suppressing the proliferation and invasion of gastric cancer. Interestingly, the well-established small-molecule compound RCM-1 significantly enhanced the interaction between RNF112 and FOXM1, which further promoted FOXM1 ubiquitination and subsequently exerted promising anticancer effects in vitro and in vivo. Altogether, we demonstrate that RNF112 suppresses gastric cancer progression by ubiquitinating FOXM1 and highlight the RNF112/FOXM1 axis serves as both prognosis biomarker and therapeutic target in gastric cancer.

The Loess Plateau is an important grain-producing area and energy base in China and is an area featuring dramatic changes in both surface and underground processes. However, the associations between surface deformation and groundwater storage changes in different landscape types in the region are still unclear. Based on Sentinel-1 and GRACE (Gravity Recovery and Climate Experiment) data, this study monitored and verified the surface deformation and groundwater storage changes in different landscape types, such as those of the Kubuqi Desert, Hetao Irrigation District, Jinbei Mining Area, and Shendong Mining Area, in the Loess Plateau of China from 2020 to 2021. Through time series and cumulative analysis using the same spatial and temporal resolution, the associations between these two changes in different regions are discussed. The results show that: (1) the surface deformation rates in different landscape types differ significantly. The minimum surface deformation rate in the Kubuqi Desert is −5~5 mm/yr, while the surface deformation rates in the Hetao Irrigation District, the open-pit mine recovery area in the Jinbei Mining Area, and the Shendong Mining Area are −60~25 mm/yr, −25~25 mm/yr, and −95.33~26 mm/yr, respectively. (2) The regional groundwater reserves all showed a decreasing trend, with the Kubuqi Desert, Hetao Irrigation District, Jinbei Mining Area, and Shendong Mining Area declining by 359.42 mm, 103.30 mm, 45.60 mm, and 691.72 mm, respectively. (3) The surface elasticity deformation had the same trend as the temporal fluctuation in groundwater storage, and the diversion activity was the main reason why the temporal surface deformation in the Hetao Irrigation District lagged behind the change in groundwater storage by 1~2 months. The measure of “underground water reservoirs in coal mines” slows down the rate of collapse of coal mine roof formations, resulting in the strongest time-series correlation between mild deformation of the surface of the Shendong mine and changes in the amount of groundwater reserves (R = 0.73). This study analyzes the associations between surface deformation and groundwater storage changes in different landscape areas of the Loess Plateau of China and provides new approaches to analyzing the dynamic associations between the two and the causes of changes in both variables.

Abstract In this paper, the surface texture parameters and distribution patterns are studied by numerical simulation and experiment. First, a three-dimensional micro-textured CFD fluid lubrication model with cavitation effect is established, and different texture arrays are designed to study the influence of different distribution modes on bearing capacity, friction coefficient and pressure distribution of the oil film. Then, the simulation results are further analyzed and verified by the visualized plane slider experimental platform, and the formation rules of cavitation bubbles in the micro-textured array, as well as the influences of the surface shape and different distribution modes of the micro-textured array on the cavitation bubbles are discussed. The results show that the existence of cavitation is one of the main reasons for the microtexture to increase the bearing capacity of the oil film, which cannot be ignored in the simulation study. The texture array with single symmetric orientation is the best to improve the oil film bearing capacity, and the bearing performance is the best when the texture inclination angle is 26.6°.The friction coefficient of the asymmetrically oriented textured array is 29.4% lower than that of the non-textured sample.The results in the experiment are consistent with the simulation.

The transfer process and variation characteristics of water and heat fluxes play an important role in both the ecosystem function and the climatic patterns of arid and semi-arid areas. However, both water (latent heat flux, Fe) and heat (sensible heat flux, Fh) fluxes, and the factors impacting each, operate on different time scales. Therefore, the wavelet transformation was used to reconstruct water and heat flux data measured by an eddy covariance system installed in Horqin sandy land, China. The distribution and response regularity of water and heat fluxes in response to control factors were then analysed across different time scales. The results indicated that the responses of Fe and Fh to controlling factors were similar on 30 min and daily scales, to which the energy terms of net radiation (Fn) and available energy (Fa) showed an extremely significant positive contribution. Removing the interference of the energy terms, Fe and Fh are strongly correlated with the vapour pressure deficit (VPD) and air temperature (Ta) at the daily scale. The water conditions of VPD and relative humidity (RH) were the main influencing factors at the monthly scale. At the seasonal scale, Fe was positively correlated with Fa and Fn but negatively correlated with soil heat flux (Fg), RH and wind speed (WS). On the contrary, Fh was positively correlated with RH but negatively correlated with Fn. At the annual scale, Fe and Fh showed a significant positive correlation with all factors. By the increasing time scale, the cross-correlations between various hydroclimatic processes become better. Generally, at the daily and annual scales, there is a high correlation between Fe, Fh and the control factors, and a pronounced periodicity is exhibited. Another factor that is known to cause such effects is the so-called long-term persistence (or else long-range dependence or the Hurst phenomenon). These results suggest that the time scales of flux and impacting factors should be considered when undertaking water and heat flux analyses of sandy land and other ecosystems. HIGHLIGHTS Latent and sensible heat fluxes in sandy land vary in response to various influencing factors at different time scales.; The same period latent heat flux was less than sensible heat flux, indicating that the energy was mainly used to heat the surface air and make the surface temperature rise rapidly.; Wavelet coherence of water heat flux and energy component showed highly consistent daily and annual common periods.;

The effect of uniaxial tensile stress on the galvanic corrosion behavior of a dissimilar joint of stainless steel alloys is investigated in 0.5 M Na2SO4 electrolyte solution at room temperature. The experimental stress-corrosion test results reveal that the application of uniaxial tensile stress causes a decrease in the corrosion potential and an increase in the corrosion rate compared to the nonstressed specimen. A numerical model is established and validated using the results from the experimental stress-corrosion tests. Consequently, a series of case studies is presented to investigate the galvanic corrosion behavior of the joint under some applied tensile strains.

ObjectiveInfluenza B virus (IBV) is highly contagious, spreads rapidly, and causes seasonal epidemic respiratory disease in the human population, especially in immunocompromised people and young children. Clinical manifestations in this high-risk population are often more severe than in immunocompetent hosts and sometimes atypical. Therefore, rapid, and accurate detection of IBV is important.MethodsAn amplified luminescent proximity homogeneous assay linked immunosorbent assay (AlphaLISA) was developed for detection of IBV by optimizing the ratio of IBV antibody-labeled receptor beads, streptavidin-conjugated donor beads and biotinylated IBV antibody, as well as the optimal temperature and time conditions for incubation. Assay sensitivity, specificity and reproducibility were evaluated. A total of 228 throat swab samples and inactivated influenza B virus were tested by AlphaLISA and lateral flow colloidal gold-based immunoassay (LFIA).ResultsAlphaLISA produced the best results for detection of inactivated influenza B virus when IBV antibody-labeled acceptor beads were 50 μg/ mL, streptavidin-conjugated donor beads were 40 μg/mL, and biotinylated IBV antibody was 0.5 μg/mL at 37°C for 15–10 min. Under these conditions, AlphaLISA had a limit of detection of 0.24 ng/mL for the detection of influenza B nucleoprotein, did not cross react with other common respiratory viruses, and showed good reproducibility with inter-assay coefficient of variation (CV) and intra-assay CV

IntroductionOlder Black adults experience a high burden of depressive symptoms and cerebrovascular disease but the specific neurobiological substrates underlying the association between late-life depressive symptoms and brain integrity are understudied, particularly in within-group designs.MethodsUsing the Center for Epidemiologic Studies Depression Scale and diffusion-tensor imaging, within-Black variation in the association between late-life depressive symptoms and white matter structural integrity was examined in 297 older Black participants without dementia that were enrolled across three epidemiological studies of aging and dementia. Linear regression models were used to test associations with DTI metrics (fractional anisotropy, trace of the diffusion tensor) as the outcomes and depressive symptoms as the predictor, while adjusting for age, sex, education, scanner, serotonin-reuptake inhibitor use, total volume of white-matter hyperintensities normalized by intracranial volume, and presence of white-matter hyperintensities at the voxel level.ResultsHigher level of self-reported late-life depressive symptoms was associated with greater diffusion-tensor trace (reduced white matter integrity) in connections between commissural pathways and contralateral prefrontal regions (superior and middle frontal/dorsolateral prefrontal cortex), association pathways connecting dorsolateral prefrontal cortex with insular, striatal and thalamic regions, and association pathways connecting the parietal, temporal and occipital lobes and the thalamus.DiscussionThis study demonstrated a discernable pattern of compromised white matter structural integrity underlying late-life depressive symptoms within older Black adults.

Abstract Grass community classification is the basis for the development of animal husbandry and dynamic monitoring of environment, which has become a critical problem to further strengthen the intelligent management of grassland. Compared with grass survey based on satellite remote sensing, the visible near infrared (NIR) hyperspectral not only monitor dynamically in a short distance, but also have high dimensions and detailed spectral information in each pixel. However, the hyperspectral labeled sample for classification is expensive and manual selection is more subjective. In order to solve above limitations, we proposed a visible-NIR hyperspectral classification model for grass based on multivariate smooth mapping and extreme active learning (MSM–EAL). Firstly, MSM is used to preprocess and reconstruct the spectrum. Secondly, by jointing XGBoost and active learning (AL), the advanced samples with the largest amount of information are actively selected to improve the performance of target classification. Innovation lies in: (1) MSM global enhanced preprocessing spectral reconstruction algorithm is proposed, in which isometric feature mapping is effectively applied to the grass hyperspectral for the first time. (2) EAL framework is constructed to solve the issue of high cost and small number for hyperspectral labeled samples, at the same time, enhance the physical essence behind spectral classification more intuitively. A field hyperspectral collection platform is assembled to establish nm resolution visible-NIR hyperspectral dataset of grass, Grass1, containing 750 samples, which to verify the effectiveness of the model. Experiments on the Grass1 dataset confirmed that compared with the full spectrum, the time consumption of MSM was reduced by 9.471 s with guaranteed overall accuracy (OA). Comparing EAL with AL, and other classification algorithms, EAL improves OA 22.2% over AL, and XAL has the best performance value on Kappa, Macro, Recall and F1-score, respectively. Altogether, the lightweight MSM–EAL model realizes intelligent and real-time classification, providing a new method for obtaining high-precision inter group classification of grass.

The microstructure, tensile properties, and fatigue behavior of friction stir welding (FSW) joints of multilayer AA3003-clad AA6013 are experimentally investigated. Linear butt welding is performed using a concave tool equipped with a columnar threaded pin at a rotating speed of 600 rpm and a transverse speed of 200 mm/min. The microstructures of FSW joints were observed using a field emission scanning electron microscope equipped with an electron backscatter diffraction system and an energy dispersive spectrometer. The microstructural characterization in the stir zone (SZ) reveals grain refinement, precipitate refinement, zigzag line, and the AA3003-clad layer fragments due to material mixing. The tensile test result of all-weld joints shows that the tensile strength of the SZ is significantly higher than that of base metal, while the cross-weld joints show a typical ductile fracture in the base metal. The result of fatigue tests shows that all the cross-weld joints fracture from the SZ. Analysis of the fatigue failure mechanism indicates that the crack causing the fatigue fracture originates from the AA3003-clad layer fragments in the advancing side of the SZ. The fatigue analysis also confirms that surface roughness and zigzag line are not the cause of the final fatigue fracture of the cross-weld joint for the present study.

Smart drug delivery, through which the drug molecules are delivered according to the requests of human biological rhythms or by maximizing drug therapeutic effects, is highly desired in pharmaceutics. Many biomacromolecules have been exploited for this application in the past few decades, both in industry and laboratories. Biphasic release, with an intentional pulsatile release and a following extended release stage, represents a typical smart drug delivery approach, which aims to provide fast therapeutic action and a long time period of effective blood drug concentration to the patients. In this study, based on the use of a well-known biomacromolecule, i.e., cellulose acetate (CA), as the drug (acetaminophen, ATP)-based sustained release carrier, a modified coaxial electrospraying process was developed to fabricate a new kind of core–shell nanoparticle. The nanoparticles were able to furnish a pulsatile release of ATP due to the shell polyvinylpyrrolidone (PVP). The time cost for a release of 30% was 0.32 h, whereas the core–shell particles were able to provide a 30.84-h sustained release of the 90% loaded ATP. The scanning electron microscope and transmission electron microscope results verified in terms of their round surface morphologies and the obvious core–shell double-chamber structures. ATP presented in both the core and shell sections in an amorphous state owing to its fine compatibility with CA and PVP. The controlled release mechanisms of ATP were suggested. The disclosed biomacromolecule-based process–structure–performance relationship can shed light on how to develop new sorts of advanced nano drug delivery systems.

Dissimilar stainless steels 316L (SUS316L) and SUS410 in a cylindrical butt configuration are solid-state joined along the cylinder axis by electrically assisted pressure joining (EAPJ). In EAPJ, different electric current densities are applied during compressive plastic deformation to investigate the effect of electric current density on joint performance. The microstructure analysis confirms that solid-state joints without macro- and micro-defects are fabricated through elemental diffusion and recrystallization during EAPJ. The effect of electric current density on the formation of martensite and subsequently on the variation of hardness is revealed by the grain average image quality maps and their relevant area distribution. The results of quasi-static tensile tests show that the fracture behavior of the joint is strongly affected by the applied electric current density. The fatigue behavior of joints with a higher tensile strength (SUS410 base metal fracture) is also evaluated by the S–N curve under a certain confidence level using two-parameter Weibull distribution. Finally, the fracture mechanism is investigated by examining the fracture surfaces from fatigue failure. The fracture morphology under high stress level exhibits a mixed fracture mode of base metal and interface fracture, while the fracture under low stress level exhibits interface fracture.

Gastric cancer is one of most lethal diseases across the world. However, the underlying mechanism of gastric cancer carcinogenesis and development is still not fully known. Forkhead box M1 (FOXM1) belongs to the FOX family and has crucial roles in transactivation of multiple oncogenes in several cancer types, including gastric cancer. Recent studies have also shown the non-transcriptional function of FOXM1 via protein–protein interactions. Human telomerase reverse transcriptase (hTERT) is the core subunit of telomerase that facilitates cancer initiation and progression by maintaining cell immortalization, promoting cell proliferation and inhibiting cell apoptosis. However, the relationship between FOXM1 and hTERT in gastric cancer is still unclear. In our study, we found that FOXM1 and hTERT were convergent to the cell cycle-related pathways and they were positively related with advanced gastric cancer stages and poor outcomes. Simultaneous high levels of FOXM1 and hTERT predicted the worst prognosis. FOXM1 could increase hTERT protein rather than mRNA levels in a non-transcriptional manner. Mechanistically, FOXM1 interrupted the interaction between the E3 ligase MKRN1 and hTERT and decreased hTERT protein degradation. Further studies revealed that FOXM1 interacted with hTERT through its DNA-binding domain (DBD) region. Finally, we found that hTERT played important roles in FOXM1-mediated activation of the Wnt/β-catenin pathway to promote gastric cancer cell proliferation. Taken together, we found a novel non-classical function of FOXM1 to increase hTERT protein stability. Targeting the FOXM1-hTERT pathway may be a potential therapeutic strategy in treating gastric cancer.

Point-of-care technologies (POCT) that enable early disease detection and therapeutic monitoring are crucial for the next generation of diagnostics and personalized medicine. Meanwhile, there is a global need for low-cost POCT that makes advanced diagnostic tools accessible to resource-limited settings. Recently, several mobile imaging platforms for single-molecule and particle detection have been developed, which greatly improve the detection sensitivity of molecular assays. This review highlights emerging technologies that achieve single-molecule and particle optical detection on true portable platforms. Miniature, high-sensitivity imaging devices based on smartphones, single-board computers (i.e., Raspberry Pi systems), lab-on-a-chip systems, and 3D-printed microscopy platforms are discussed.

High-quality T1-weighted (T1w) and diffusion tensor imaging (DTI) brain templates that are representative of the individuals under study enhance the accuracy of template-based neuroimaging investigations, and when they are also located in a common space they facilitate optimal integration of information on brain morphometry and diffusion characteristics. However, such multimodal templates have not been constructed for the brain of older adults. The purpose of this work was threefold: (A) to introduce an iterative method for construction of multimodal T1w and DTI templates that aims at maximizing the quality of each template separately as well as the spatial matching between templates, (B) to use this method to develop T1w and DTI templates of the older adult brain in a common space, and (C) to evaluate the performance of the method across iterations and compare it to the performance of state-of-the-art approaches based on multichannel registration. It was demonstrated that more iterations of the proposed method enhanced the characteristics and spatial matching of the resulting T1w and DTI templates. The templates of the older adult brain generated by the final iteration of the proposed method provided better delineation of brain structures, higher discriminability between tissues, and higher image sharpness near the cortex compared to templates generated with approaches employing multichannel registration. In addition, the spatial matching between the T1w and DTI templates constructed by the proposed method approximated the template alignment achieved with methods employing multichannel registration. Finally, when using the templates generated by the proposed method as references for spatial normalization of older adult T1w and DTI data, both the intra-modality inter-subject normalization precision and the inter-modality spatial matching were higher in most metrics than those achieved with templates constructed with other methods. Overall, the present work brought new insights into multimodal template construction, generated much-needed high quality T1w and DTI templates of the older adult brain in a common space, and conducted a thorough, quantitative evaluation of available multimodal template construction methods.

We previously found that, among human parainfluenza virus type 3 (HPIV3) proteins, the interaction of nucleoprotein (N) and phosphoprotein (P) provides the minimal requirement for the formation of cytoplasmic inclusion bodies (IBs), which are sites of RNA synthesis, and that acetylated α-tubulin enhances IB fusion and viral replication. In this study, using immunoprecipitation and mass spectrometry assays, we determined that vimentin (VIM) specifically interacted with the N-P complex of HPIV3, and that the head domain of VIM was responsible for this interaction, contributing to the inhibition of IB fusion and viral replication. Furthermore, we found that VIM promoted the degradation of α-tubulin acetyltransferase 1 (α-TAT1), through its head region, thereby inhibiting the acetylation of α-tubulin, IB fusion, and viral replication. In addition, we identified a 20-amino-acid peptide derived from the head region of VIM that participated in the interaction with the N-P complex and inhibited viral replication. Our findings suggest that VIM inhibits the formation of HPIV3 IBs by downregulating α-tubulin acetylation via enhancing the degradation of α-TAT1. Our work sheds light on a new mechanism by which VIM suppresses HPIV3 replication.

In recent years, grassland monitoring has shifted from traditional field surveys to remote-sensing-based methods, but the desired level of accuracy has not yet been obtained. Multi-temporal hyperspectral data contain valuable information about species and growth season differences, making it a promising tool for grassland classification. Transformer networks can directly extract long-sequence features, which is superior to other commonly used analysis methods. This study aims to explore the transformer network’s potential in the field of multi-temporal hyperspectral data by fine-tuning it and introducing it into high-powered grassland detection tasks. Subsequently, the multi-temporal hyperspectral classification of grassland samples using the transformer network (MHCgT) is proposed. To begin, a total of 16,800 multi-temporal hyperspectral data were collected from grassland samples at different growth stages over several years using a hyperspectral imager in the wavelength range of 400–1000 nm. Second, the MHCgT network was established, with a hierarchical architecture, which generates a multi-resolution representation that is beneficial for grass hyperspectral time series’ classification. The MHCgT employs a multi-head self-attention mechanism to extract features, avoiding information loss. Finally, an ablation study of MHCgT and comparative experiments with state-of-the-art methods were conducted. The results showed that the proposed framework achieved a high accuracy rate of 98.51% in identifying grassland multi-temporal hyperspectral which outperformed CNN, LSTM-RNN, SVM, RF, and DT by 6.42–26.23%. Moreover, the average classification accuracy of each species was above 95%, and the August mature period was easier to identify than the June growth stage. Overall, the proposed MHCgT framework shows great potential for precisely identifying multi-temporal hyperspectral species and has significant applications in sustainable grassland management and species diversity assessment.

Pixel-level information of remote sensing images is of great value in many fields. CNN has a strong ability to extract image backbone features, but due to the localization of convolution operation, it is challenging to directly obtain global feature information and contextual semantic interaction, which makes it difficult for a pure CNN model to obtain higher precision results in semantic segmentation of remote sensing images. Inspired by the Swin Transformer with global feature coding capability, we design a two-branch multi-scale semantic segmentation network (TMNet) for remote sensing images. The network adopts the structure of a double encoder and a decoder. The Swin Transformer is used to increase the ability to extract global feature information. A multi-scale feature fusion module (MFM) is designed to merge shallow spatial features from images of different scales into deep features. In addition, the feature enhancement module (FEM) and channel enhancement module (CEM) are proposed and added to the dual encoder to enhance the feature extraction. Experiments were conducted on the WHDLD and Potsdam datasets to verify the excellent performance of TMNet.

Abstract Management of breast cancer in limited-resource settings is hindered by a lack of low-cost, logistically sustainable approaches toward molecular and cellular diagnostic pathology services that are needed to guide therapy. To address these limitations, we have developed a multimodal cellphone-based platform—the EpiView-D4—that can evaluate both cellular morphology and molecular expression of clinically relevant biomarkers directly from fine-needle aspiration (FNA) of breast tissue specimens within 1 h. The EpiView-D4 is comprised of two components: (1) an immunodiagnostic chip built upon a “non-fouling” polymer brush-coating (the “D4”) which quantifies expression of protein biomarkers directly from crude cell lysates, and (2) a custom cellphone-based optical microscope (“EpiView”) designed for imaging cytology preparations and D4 assay readout. As a proof-of-concept, we used the EpiView-D4 for assessment of human epidermal growth factor receptor-2 (HER2) expression and validated the performance using cancer cell lines, animal models, and human tissue specimens. We found that FNA cytology specimens (prepared in less than 5 min with rapid staining kits) imaged by the EpiView-D4 were adequate for assessment of lesional cellularity and tumor content. We also found our device could reliably distinguish between HER2 expression levels across multiple different cell lines and animal xenografts. In a pilot study with human tissue (n = 19), we were able to accurately categorize HER2-negative and HER2-positve tumors from FNA specimens. Taken together, the EpiView-D4 offers a promising alternative to invasive—and often unavailable—pathology services and may enable the democratization of effective breast cancer management in limited-resource settings.

Rotavirus is the main pathogen causing acute viral gastroenteritis. Accurate and rapid diagnosis of rotavirus infection is important to determine appropriate treatment, prevention of unnecessary antibiotics use and control of infection spread. In this study, we established a rapid, accurate, and sensitive amplified luminescent proximity homogeneous assay linked immunosorbent assay (AlphaLISA) for detecting rotavirus and evaluated its efficacy in human stool samples. Our results demonstrated that the sensitivity of AlphaLISA (5−8) significantly exceeded that of the immunochromatographic assay (ICA, 5−4) for rotavirus antigen detection. The intra-assay and inter-assay coefficients of variation were 2.99–3.85% and 5.27–6.51%, respectively. Furthermore, AlphaLISA was specific for rotavirus and did not cross-react with other common diarrhea viruses. AlphaLISA and real-time reverse transcription polymerase chain reaction (RT-qPCR, which is considered a gold standard for detecting diarrhea viruses) tests showed consistent results on 235 stool samples, with an overall consistency rate of 97.87% and a kappa value of 0.894 (P < 0.001). The overall consistency rate of ICA compared with RT-qPCR was 95.74%. AlphaLISA showed better consistency with RT-qPCR than the routinely used ICA for rotavirus detection in stool samples. The AlphaLISA method can be used in clinical practice for the rapid, accurate, and sensitive detection of rotavirus infection.

Metagenomic next-generation sequencing (mNGS) is a novel useful strategy that is increasingly used for pathogens detection in clinic. Some emerging mNGS technologies with long-read ability are useful to decrease sequencing time and increase diagnosed accuracy, which is of great significance in rapid pathogen diagnosis. Reliable DNA extraction is considered critical for the success of sequencing; hence, there is thus an urgent need of gentle DNA extraction method to get unbiased and more integrate DNA from all kinds of pathogens. In this study, we systematically compared three DNA extraction methods (enzymatic cell lysis based on MetaPolyzyme, mechanical cell lysis based on bead beating, and the control method without pre–cell lysis, respectively) by assessing DNA yield, integrity, and the microbial diversity based on long-read nanopore sequencing of urine samples with microbial infections. Compared with the control method, the enzymatic-based method increased the average length of microbial reads by a median of 2.1-fold [Inter Quartile Range (IQR), 1.7–2.5; maximum, 4.8) in 18 of the 20 samples and the mapped reads proportion of specific species by a median of 11.8-fold (Inter Quartile Range (IQR), 6.9–32.2; maximum, 79.27]. Moreover, it provided fully (20 of 20) consistent diagnosed results to the clinical culture and more representative microbial profiles (P < 0.05), which all strongly proves the excellent performance of enzymatic-based method in long-read mNGS–based pathogen identification and potential diseases diagnosis of microbiome related.

Lap joining of dissimilar steel S45C and aluminum 6061-T6 alloy sheets in the solid state is conducted by means of electrically assisted pressure joining (EAPJ). During joining, electric current is applied to a specimen assembly under continuously compressive plastic deformation. Additional holding time at the elevated temperature is also applied by periodically applying electric current after the completion of compressive deformation to enhance the diffusion between the steel and aluminum alloy sheets. Microstructural analysis confirms the solid-state joining and shows that the microstructure of the joint strongly depends on the process parameters. Quasi-static lap shear tensile testing shows that joint strength increases with increasing electric current density and with increasing holding time at the elevated temperature. Fracture surface morphology suggests that brittle fracture occurs at the interface between the steel and aluminum alloy, with some amount of intermetallic compound sticking to the steel side. The present study confirms that the EAPJ concept is applicable to the joining of steel and aluminum alloy in solid state.

Abstract Purpose Soil microorganisms play an indispensable role in the material and energy cycle of grassland ecosystems. The abundance of these organisms vary according to environmental factors, such as time of year and soil depth. There have been few studies on the transformation of soil microbial communities in degraded typical steppe according to these temporal and spatial changes. In this study, we analyze the community structure and diversity of soil bacteria and fungi, and the impact of these changing temporal and spatial factors upon the community structure. Methods From May to September 2018, we collected 90 soil samples from different depths (10, 20, and 30 cm) from the typical degraded steppe area of Xilingol. We carried out studies on soil physical and chemical properties and soil microbial diversity using high-throughput sequencing technology. Results We found that depth significantly affected abundance and diversity of bacteria and fungi. Bacteria and fungi diversity at 10 cm was higher than that at 20 cm and 30 cm. The abundance of Acidobacteria, Proteobacteria, Actinomycetes, Ascomycetes, and Basidiomycetes varies significantly with depth. In addition, soil pH increased significantly with increasing depth, while soil organic matter (SOM), available nitrogen (AN), volume water content of soil (VWC), and soil temperature (ST) decreased significantly with increasing depth. Finally, the depth, total organic carbon (TOC), and AN had a significant impact on the bacterial and fungal communities’ abundance (p < 0.05). Conclusions Spatial heterogeneity (in soil depth) is more significant than the time of year (month) in predicting changes in microbial community composition and soil properties. SOM, VWC, and the abundance of Proteobacteria and Actinomycetes positively correlate with soil depth, while pH and the abundance of Acidobacteria, Ascomycetes, and Basidiomycetes negatively correlate with soil depth. We speculate that SOM and VWC account for the variations in the abundance of Acidobacteria and Proteobacteria, while pH causes variations in the abundance of Actinomycetes, Ascomycetes and Basidiomycota.

Urinary tract infections (UTIs) are among the most common acquired bacterial infections in humans. The current gold standard method for identification of uropathogens in clinical laboratories is cultivation. However, culture-based assays have substantial drawbacks, including long turnaround time and limited culturability of many potential pathogens. Nanopore sequencing technology can overcome these limitations and detect pathogens while also providing reliable predictions of drug susceptibility in clinical samples. Here, we optimized a metagenomic nanopore sequencing (mNPS) test for pathogen detection and identification in urine samples of 76 patients with acute uncomplicated UTIs. We first used twenty of these samples to show that library preparation by the PCR Barcoding Kit (PBK) led to the highest agreement of positive results with gold standard clinical culture tests, and enabled antibiotic resistance detection in downstream analyses. We then compared the detection results of mNPS with those of culture-based diagnostics and found that mNPS sensitivity and specificity of detection were 86.7% [95% confidence interval (CI), 73.5–94.1%] and 96.8% (95% CI, 82.4–99.9%), respectively, indicating that the mNPS method is a valid approach for rapid and specific detection of UTI pathogens. The mNPS results also performed well at predicting antibiotic susceptibility phenotypes. These results demonstrate that our workflow can accurately diagnose UTI-causative pathogens and enable successful prediction of drug-resistant phenotypes within 6 h of sample receipt. Rapid mNPS testing is thus a promising clinical diagnostic tool for infectious diseases, based on clinical urine samples from UTI patients, and shows considerable potential for application in other clinical infections.

Analysis on a single-cell basis is both fundamental and meaningful in biomedical research and clinical practice. Flow cytometry is one of the most popular approaches in this field with broad applications in cell sorting, counting, and identification of rare cells. However, the complicated design and bulky size of conventional flow cytometry have restricted their applications mainly in centralized laboratories. With the recent development of smartphone devices, smartphone-based cytometry has been explored and tested for single-cell analysis. Compared with traditional cytometers, smartphone-based cytometric biosensors are more suitable for point-of-care (POC) uses, such as on-site disease diagnosis and personal health monitoring. In this review article, the history of traditional flow cytometry is introduced, and advances of smartphone-enabled cytometry are summarized in detail based on different working principles. Representative POC applications of smartphone cytometers are also discussed. The achievements demonstrated so far illustrate the potential of smartphone-based cytometric devices to transform single-cell measurement in general, with a significant impact in POC diagnostics, preventive medicine, and cell biology. Keywords: Flow cytometry, Smartphone, Point-of-care diagnostics, Single-cell analysis, Imaging, Microfluidics

Salinity is one of the main adverse environmental factors severely inhibiting rice growth and decreasing grain productivity. Developing rice varieties with salt tolerance (ST) is one of the most economical approaches to cope with salinity stress. In this study, the salt tolerance of 220 rice accessions from rice diversity panel l (RDP1), representing five subpopulations, were evaluated based on 16 ST indices at both seedling and reproductive stages under salt stress. An apparent inconsistency was found for ST between the two stages. Through a gene-based/tightly linked genome-wide association study with 201,332 single nucleotide polymorphisms (SNPs) located within genes and their flanking regions were used, a total of 214 SNPs related to 251 genes, significantly associated with 16 ST-related indices, were detected at both stages. Eighty-two SNPs with low frequency favorable (LFF) alleles in the population were proposed to hold high breeding potential in improving rice ST. Fifty-four rice accessions collectively containing all these LFF alleles were identified as donors of these alleles. Through the integration of meta-quantitative trait locus (QTL) for ST and the response patterns of differential expression genes to salt stress, thirty-eight candidate genes were suggested to be involved in the regulation of rice ST. In total, the present study provides valuable information for further characterizing ST-related genes and for breeding ST varieties across whole developmental stages through marker-assisted selection (MAS).

For the influence of boundary film on the lubrication state of sliding friction pairs, a boundary film strength model was proposed that can comprehensively reflect the influences of film thickness, pressure, shear stress and temperature. The model parameters were obtained through fitting the test results. Then, a mixed lubrication model considering boundary film strength was established by coupling the boundary film strength model with the hydrodynamic lubrication model and the asperity contact model. The calculation program was developed using the Fortran language, which can effectively capture the tribological characteristics and action ratios of the fluid, boundary film and dry friction components. Simultaneously, the mixed lubrication model was applied to the journal bearing. A parametric analysis was performed to investigate the influences of different working conditions on lubrication performance. Under current operating conditions, the results show that: when the speed is above 200 r/min or the viscosity is higher than 0.09 Pa·s, the boundary film breakdown rate is almost 0 and the friction coefficient is lower than 0.02; when the roughness is reduced from 1.8 μm to 0.8 μm, the ultimate load of the journal bearing rises from 27 MPa to 36 MPa, an increase of about 33%; when the load exceeds 36 MPa or the temperature is higher than 100 °C, more than 25% of the boundary film breaks and the dry friction component accounts for more than 60% of the total friction, which leads to a sudden increase in the friction coefficient. Hence, the study of mixed lubrication considering boundary film strength provides theoretical guidance for accurately reflecting the actual lubrication state and improving the mechanical energy efficiency of friction pairs.

Forests are the most important part of terrestrial ecosystems. In the context of China’s industrialization and urbanization, mining activities have caused huge damage to the forest ecology. In the Ulan Mulun River Basin (Ordos, China), afforestation is standard method for reclamation of coal mine degraded land. In order to understand, manage and utilize forests, it is necessary to collect local mining area’s tree information. This paper proposed an improved Faster R-CNN model to identify individual trees. There were three major improved parts in this model. First, the model applied supervised multi-policy data augmentation (DA) to address the unmanned aerial vehicle (UAV) sample label size imbalance phenomenon. Second, we proposed Dense Enhance Feature Pyramid Network (DE-FPN) to improve the detection accuracy of small sample. Third, we modified the state-of-the-art Alpha Intersection over Union (Alpha-IoU) loss function. In the regression stage, this part effectively improved the bounding box accuracy. Compared with the original model, the improved model had the faster effect and higher accuracy. The result shows that the data augmentation strategy increased AP by 1.26%, DE-FPN increased AP by 2.82%, and the improved Alpha-IoU increased AP by 2.60%. Compared with popular target detection algorithms, our improved Faster R-CNN algorithm had the highest accuracy for tree detection in mining areas. AP was 89.89%. It also had a good generalization, and it can accurately identify trees in a complex background. Our algorithm detected correct trees accounted for 91.61%. In the surrounding area of coal mines, the higher the stand density is, the smaller the remote sensing index value is. Remote sensing indices included Green Leaf Index (GLI), Red Green Blue Vegetation Index (RGBVI), Visible Atmospheric Resistance Index (VARI), and Normalized Green Red Difference Index (NGRDI). In the drone zone, the western area of Bulianta Coal Mine (Area A) had the highest stand density, which was 203.95 trees ha−1. GLI mean value was 0.09, RGBVI mean value was 0.17, VARI mean value was 0.04, and NGRDI mean value was 0.04. The southern area of Bulianta Coal Mine (Area D) was 105.09 trees ha−1 of stand density. Four remote sensing indices were all the highest. GLI mean value was 0.15, RGBVI mean value was 0.43, VARI mean value was 0.12, and NGRDI mean value was 0.09. This study provided a sustainable development theoretical guidance for the Ulan Mulun River Basin. It is crucial information for local ecological environment and economic development.

Background: The artificial fluorinated group of compounds polyfluoroalkyl chemicals (PFCs) has been applied extensively in daily life for decades, and is present in food, drinking water, and indoor dust. The nephrotoxicity of PFCs has been widely studied for its characteristics of being mainly excreted through passing urine and affecting urodynamics. This work aimed to investigate the relationship between PFCs and the occurrence of urge urinary incontinence (UUI) in the United States (US) population. Methods: There were 3157 eligible female participants retrieved from the National Health and Nutrition Examination Survey (NHANES) between 2007 and 2014. A logistic regression model was used to examine the relationship between UUI and eight kinds of PFCs. The dose–response relationship was investigated through restricted cubic spline analysis in this retrospective study. Results: Of the 3157 eligible female participants, 913 self-reported a history of UUI. Total PFCs, perfluorohexane sulfonic acid (PFHS), 2-(N-methyl-perfluorooctane sulfonamido) acetate (MPAH), and perfluorononanoic acid (PFNA) correlated positively with the occurrence of UUI after adjusting for age, race, education, vigorous recreational activities, hypertension, diabetes, body mass index (BMI), creatinine, and estimated glomerular filtration rate (eGFR). Based on the results of sub-group analysis, the increasing tertiles contained odds ratios [OR; 95% confidence intervals (CI)] of 1.25 (95% CI, 1.03–1.51, p = 0.026) and 1.56 (95% CI, 1.29–1.89, p

To date, utilization of feed grains is increasing, which competes for human food. It is imperative to develop and utilize unconventional feed materials. Broussonetia papyrifera L. (B. papyrifera) is a good feeding material with high crude protein, crude fat, and low crude fiber, which is widely distributed in China. In this study, 12 Dorper ♂×Hu ♀ crossbred weaned male lambs were seleted into four groups based on the feed that ratio of the B. papyrifera fermented feed in the total mixed diet (0%, 6%, 18%, and 100%), to character the lambs’ longissimus dorsi (LD) fatty acids, morphology and transcriptome. Results showed that the muscle fiber’s diameter and area were the smallest in the 100% group. The highest content of beneficial fatty acids and the lowest content of harmful fatty acids in group 18%. RNA-seq identified 443 differentially expressed genes (DEGs) in the LD of lambs from 4 groups. Among these genes, 169 (38.1%) were up-regulated and 274 (61.9%) were down-regulated. The DEGs were mostly enriched in in fatty acid metabolism, arginine and proline metabolism, and PPAR signaling pathways. Our results provide knowledge to understand effect of different ratios of B. papyrifera fermented feed on sheep meat quality traits, also a basis for understanding of the molecular regulation mechanism of B. papyrifera fermented feed affecting on sheep meat quality.

Coal wall spalling is regarded as a key technical problem influencing safe and efficient mining of large-mining-height working faces while the distribution of abutment pressure within the limit equilibrium zone (LEZ) influences coal wall spalling within a large-mining-height working face. This research attempted to explore the distribution characteristics of abutment pressure within the LEZ in a large-mining-height working face. For this purpose, the influences of the orientation of joints on mechanical characteristics of coal with joints and on the distribution of abutment pressure within the LEZ in the large-mining-height working face were analysed by theoretical analysis and numerical simulation. Research results show that the damage variable of coal with joints first rises, then decreases, and finally increases with increasing dip angle of the joints; as the azimuth of the joints increases, the damage variable first declines, then increases; the damage variable gradually declines with increasing joint spacing; an increase in the dip angle of joints corresponds to first reduction, then growth, and a final decrease of the abutment pressure at the same position in front of the coal walls; on certain conditions, the abutment pressure at the same position within the LEZ first rises, then declines as the azimuth of joints increases; with the growth of the joint spacing, the abutment pressure at the same position within the LEZ rises. The dip angle and azimuth of joints marginally affect the abutment pressure within the LEZ.

Active DNA demethylation is an important epigenetic process that plays a key role in maintaining normal gene expression. In plants, active DNA demethylation is mediated by DNA demethylases, including ROS1, DME, DML2, and DML3. In this study, the available bisulfite sequencing and mRNA sequencing data from ros1 and rdd mutants were analyzed to reveal how the active DNA demethylation process shapes the DNA methylation patterns of Arabidopsis nucleotide-binding leucine-rich repeat (NLR) genes, a class of important plant disease resistance genes. We demonstrate that the CG methylation levels of three NLR genes (AT5G49140, AT5G35450, and AT5G36930) are increased in the ros1 mutants relative to the wild-type plants, whereas the CG methylation level of AT2G17050 is decreased. We also observed increased CG methylation levels of AT4G11170 and AT5G47260 and decreased CG methylation levels of AT5G38350 in rdd mutants. We further found that the expression of three NLR genes (AT1G12280, AT1G61180, and AT4G19520) was activated in both ros1 and rdd mutants, whereas the expression of another three NLR genes (AT1G58602, AT1G59620, and AT1G62630) was repressed in these two mutants. Quantitative reverse transcriptase–polymerase chain reaction detection showed that the expression levels of AT1G58602.1, AT4G19520.3, AT4G19520.4, and AT4G19520.5 were decreased in the ros1 mutant; AT3G50950.1 and AT3G50950.2 in the rdd mutant were also decreased in expression compared to Col-0, whereas AT1G57630.1, AT1G58602.2, and AT5G45510.1 were upregulated in the rdd mutant relative to Col-0. These results indicate that some NLR genes are regulated by DNA demethylases. Our study demonstrates that each DNA demethylase (ROS1, DML2, and DML3) exerts a specific effect on the DNA methylation of the NLR genes, and active DNA demethylation is part of the regulation of DNA methylation and transcriptional activity of some Arabidopsis NLR genes.

The application of titanium alloy micro-gears in microelectromechanical systems has been severely restricted, as the graphite mold is prone to abrasion or even to crack at high temperatures, mainly due to the forming load. We aimed to manufacture Ti-6Al-4V alloy micro-gears through hot extrusion under an electric field and to clarify the influence of holding time on the extrusion force. The results suggest that the formed gears had a complete filling and clear tooth profile. Moreover, the contact resistance and current density caused a gradient temperature distribution inside the billet, resulting in a carburized layer and inhomogeneous β grains. The extrusion force increased with an increased holding time, which can be ascribed to the increase in the thickness of the carburized layer and the β grain size. Among these two factors, β grain size played a leading role in the extrusion force. Continuous dynamic recrystallization dominated the deformation in a single β phase, and the misorientation of the transformed α laths from β grains followed the Burgers orientation relationship. This study may pave the way for the extrusion forming of other titanium alloy micro-components.

The mechanical properties of agricultural materials can provide the basis for the design and optimisation of agricultural machinery. There are currently very few studies on the mechanical properties of tiger nut tubers, which is not conducive to the design and development of machinery for their harvesting and processing. To obtain the mechanical parameters of tiger nut tubers, this study investigated the effects of variety (Zhong Yousha 1 and Zhong Yousha 2), moisture content (8%, 16%, 24%, 32% and 40%), contact material (steel, aluminium, plexiglass and polyurethane), release height (170 mm, 220 mm, 270 mm and 320 mm), loading speed (5 mm/min, 10 mm/min, 15 mm/min and 20 mm/min), compression direction (vertical and horizontal) on the friction, collision and compression mechanical properties of the tubers. The results were as follows: Both moisture content and contact material had a significant effect (p < 0.01) on the sliding friction coefficient (0.405–0.652) of the tubers; both variety and moisture content had a significant effect (p < 0.01) on the angle of repose (27.96–36.09°); contact material, moisture content, release height and variety all had a significant effect (p < 0.01) on the collision recovery coefficient (0.376–0.672) of tubers; variety, loading speed, moisture content and compression direction all had significant effects (p < 0.01) on the damage force (87.54–214.48 N), deformation (1.25–6.12 mm) and damage energy (82.38–351.08 mJ) of the tubers; only moisture content and compression direction had significant effects (p < 0.01) on the apparent elastic modulus (12.17–120.88 MPa) of the tubers. The results of this study can provide a reference for the design and optimisation of machinery for the harvesting and processing of tiger nut tubers.

This paper presents a newly developed segmentation algorithm for high-resolution remote sensing imagery. The new method is based on binary merge tree (BMT) and mainly comprises two parts, which are BMT construction and tree node selection. The first part is initialized by super-pixels, which are iteratively merged through using the well-known multi-resolution segmentation approach to complete BMT construction. The primary contribution of this paper resides in the second part, in which a new tree node selection criterion is developed. The new criterion is formulated by using spectral variance and class label cues in order to better describe intra-segment homogeneity. To validate the proposed strategy, four multispectral scenes captured by two Chinese satellites, ZiYuan-3 and GaoFen-2, were adopted for segmentation experiments. The results indicated that our method out-performed some state-of-the-art algorithms in terms of segmentation accuracy.