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Coal mining in Shendong Mining area has an important impact on the local ecological environment, especially the growth of vegetation. In order to describe this effect quantitatively, this study uses a regional evapotranspiration model to calculate the Potential Net Primary Productivity (PNP,p) of the Shendong mining area. MODIS17A3 dataset (2001—2022) was used to characterize the Actual Net Primary Productivity (PNP,a), and combined with the monthly net primary productivity raster dataset of terrestrial ecosystems in China (PNP,al, 1988—2015), using GWR model construction correction method to correct PNP,al to obtain 1988—2000 PNP,a data, and using the difference between the two PNP,h to characterize the impact of coal mining. The effect of coal mining on vegetation PNP in Shendong mining area was evaluated. The results show that: ① the accuracy of PNP,al data corrected by GWR model is about 0.76, and the corrected PNP,al data has a strong spatial correlation with the MODIS17A3 dataset, which indicates the reliability of the accuracy of the corrected model; ② The overall PNP,a and PNP,h of Shendong mining area showed a trend of decreasing first and then recovering gradually, but the PNP of vegetation did not recover to the pre-mining level. The mean values of PNP,h before mining and PNP,h after mining are 21.50 g/m2 and −60.20 g/m2, respectively. PNP,h

Abstract Multi-drug resistant (MDR) bacterial infections are gradually increasing in the global scope, causing a serious burden to patients and society. The formation of bacterial biofilms, which is one of the key reasons for antibiotic resistance, blocks antibiotic penetration by forming a physical barrier. Nano/micro motors (MNMs) are micro-/nanoscale devices capable of performing complex tasks in the bacterial microenvironment by transforming various energy sources (including chemical fuels or external physical fields) into mechanical motion or actuation. This autonomous movement provides significant advantages in breaking through biological barriers and accelerating drug diffusion. In recent years, MNMs with high penetrating power have been used as carriers of antibiotics to overcome bacterial biofilms, enabling efficient drug delivery and improving the therapeutic effectiveness of MDR bacterial infections. Additionally, non-antibiotic antibacterial strategies based on nanomaterials, such as photothermal therapy and photodynamic therapy, are continuously being developed due to their non-invasive nature, high effectiveness, and non-induction of resistance. Therefore, multifunctional MNMs have broad prospects in the treatment of MDR bacterial infections. This review discusses the performance of MNMs in the breakthrough and elimination of bacterial biofilms, as well as their application in the field of anti-infection. Finally, the challenges and future development directions of antibacterial MNMs are introduced.

Abstract Background Light-harvesting chlorophyll a/b binding proteins (Lhcb) play crucial roles in plant growth, development, and the response to abiotic stress in higher plants. Previous studies have reported that Lhcb genes were involved in the phytochrome regulation and responded to different light and temperature conditions in Poaceae (such as maize). However, the evolution and functions of Lhcb genes remains poorly characterized in important Rosaceae species. Results In this investigation, we conducted a genome-wide analysis and identified a total of 212 Lhcb genes across nine Rosaceae species. Specifically, we found 23 Lhcb genes in Fragaria vesca, 20 in Prunus armeniaca, 33 in Malus domestica ‘Gala’, 21 in Prunus persica, 33 in Rosa chinensis, 29 in Pyrus bretschneideri, 18 in Rubus occidentalis, 20 in Prunus mume, and 15 in Prunus salicina. Phylogenetic analysis revealed that the Lhcb gene family could be classified into seven major subfamilies, with members of each subfamily sharing similar conserved motifs. And, the functions of each subfamily was predicted based on the previous reports from other species. The Lhcb proteins were highly conserved within their respective subfamilies, suggesting similar functions. Interestingly, we observed similar peaks in Ks values (0.1–0.2) for Lhcb genes in apple and pear, indicating a recent whole genome duplication event (about 30 to 45 million years ago). Additionally, a few Lhcb genes underwent tandem duplication and were located across all chromosomes of nine species of Rosaceae. Furthermore, the analysis of the cis-acting elements in the 2000 bp promoter region upstream of the pear Lhcb gene revealed four main categories: light response correlation, stress response correlation, hormone response correlation, and plant growth. Quantitative expression analysis demonstrated that Lhcb genes exhibited tissue-specific expression patterns and responded differently to low-temperature stress in Rosaceae species. Conclusions These findings shed light on the evolution and phylogeny of Lhcb genes in Rosaceae and highlight the critical role of Lhcb in pear’s response to low temperatures. The results obtained provide valuable insights for further investigations into the functions of Lhcb genes in Rosaceae, and these functional genes will be used for further fruit tree breeding and improvement to cope with the current climate changes.

Salt stress is one of the major environmental problems in agricultural production, severely limiting crops’ germination, growth and yield. Silicon (Si) is a widely recognized beneficial element in plants, which can promote plant growth especially under stressful conditions. With the emergence of nanotechnology in agriculture, silicon nanoparticles (SiNPs) have been shown to be a promising tool in nano-enabled agricultural production. However, the comparative effects of Si and SiNPs in alleviating salt stress in plants remain unclear, which would limit the application of SiNPs in agricultural practice. In this study, the effects of SiNPs and conventional Si (silicate) on tomato (a typical low-Si accumulator) seed germination, reactive oxygen species (ROS) content, antioxidant enzyme activity, and the expression of genes related to hormone metabolism were investigated. The results showed that SiNPs more effectively promoted seed germination percentage, fresh weight, and Si content than conventional Si. Simultaneously, SiNPs more significantly modulated the activities of antioxidant enzymes and alleviated salt stress-induced oxidative damage in tomato seeds. Moreover, exogenous SiNPs addition promoted the expression of genes responsible for gibberellin (GA) synthesis and abscisic acid (ABA) catabolism, while downregulating the expression of genes related to GA deactivation and ABA synthesis in tomato seeds under salt stress. Overall, our results indicate that SiNPs are more effective than conventional Si in promoting tomato seed germination under salt stress via modulating antioxidant enzyme activity and key endogenous hormone metabolism, which could be based on the higher accumulation of SiNPs in tomato seeds than conventional Si.

Abstract Polarons are entities of excess electrons dressed with local response of lattices, whose atomic-scale characterization is essential for understanding the many body physics arising from the electron-lattice entanglement, yet difficult to achieve. Here, using scanning tunneling microscopy and spectroscopy (STM/STS), we show the visualization and manipulation of single polarons in monolayer CoCl2, that are grown on HOPG substrate via molecular beam epitaxy. Two types of polarons are identified, both inducing upward local band bending, but exhibiting distinct appearances, lattice occupations and polaronic states. First principles calculations unveil origin of polarons that are stabilized by cooperative electron-electron and electron-phonon interactions. Both types of polarons can be created, moved, erased, and moreover interconverted individually by the STM tip, as driven by tip electric field and inelastic electron tunneling effect. This finding identifies the rich category of polarons in CoCl2 and their feasibility of precise control unprecedently, which can be generalized to other transition metal halides.

Colorectal cancer (CRC) is a common and deadly disease of the digestive system, but its targeted therapy is hampered by the lack of reliable and specific biomarkers. Hence, discovering new therapeutic targets and agents for CRC is an urgent and challenging task. Here we report that carnitine palmitoyltransferase 1A (CPT1A), a mitochondrial enzyme that catalyzes fatty acid oxidation (FAO), is a potential target for CRC treatment. We show that CPT1A is overexpressed in CRC cells and that its inhibition by a secolignan-type compound, 2,6-dihydroxypeperomin B (DHP-B), isolated from the plant Peperomia dindygulensis, suppresses tumor cell growth and induces apoptosis. We demonstrate that DHP-B covalently binds to Cys96 of CPT1A, blocks FAO, and disrupts the mitochondrial CPT1A-VDAC1 interaction, leading to increased mitochondrial permeability and reduced oxygen consumption and energy metabolism in CRC cells. We also reveal that CPT1A expression correlates with the survival of tumor-bearing animals and that DHP-B exhibits anti-CRC activity in vitro and in vivo. Our study uncovers the molecular mechanism of DHP-B as a novel CPT1A inhibitor and provides a rationale for its preclinical development as well as a new strategy for CRC targeted therapy.

Melon (Cucumis melo L.) is a valuable horticultural crop of the Cucurbitaceae family. Downy mildew (DM), caused by Pseudoperonospora cubensis, is a significant inhibitor of the production and quality of melon. Brassinolide (BR) is a new type of phytohormone widely used in cultivation for its broad spectrum of resistance- and defense-mechanism-improving activity. In this study, we applied various exogenous treatments (0.5, 1.0, and 2.0 mg·L−1) of BR at four distinct time periods (6 h, 12 h, 24 h, and 48 h) and explored the impact of BR on physiological indices and the genetic regulation of melon seedling leaves infected by downy-mildew-induced stress. It was mainly observed that a 2.0 mg·L−1 BR concentration effectively promoted the enhanced photosynthetic activity of seedling leaves, and quantitative real-time polymerase chain reaction (qRT-PCR) analysis similarly exhibited an upregulated expression of the predicted regulatory genes of photosystem II (PSII) CmHCF136 (MELO3C023596.2) and CmPsbY (MELO3C010708.2), thus indicating the stability of the PSII reaction center. Furthermore, 2.0 mg·L−1 BR resulted in more photosynthetic pigments (nearly three times more than the chlorophyll contents (264.52%)) as compared to the control and other treatment groups and similarly upregulated the expression trend of the predicted key enzyme genes CmLHCP (MELO3C004214.2) and CmCHLP (MELO3C017176.2) involved in chlorophyll biosynthesis. Meanwhile, the maximum contents of soluble sugars and starch (186.95% and 164.28%) were also maintained, which were similarly triggered by the upregulated expression of the predicted genes CmGlgC (MELO3C006552.2), CmSPS (MELO3C020357.2), and CmPEPC (MELO3C018724.2), thereby maintaining osmotic adjustment and efficiency in eliminating reactive oxygen species. Overall, the exogenous 2.0 mg·L−1 BR exhibited maintained antioxidant activities, plastid membranal stability, and malondialdehyde (MDA) content. The chlorophyll fluorescence parameter values of F0 (42.23%) and Fv/Fm (36.67%) were also noticed to be higher; however, nearly three times higher levels of NPQ (375.86%) and Y (NPQ) (287.10%) were observed at 48 h of treatment as compared to all other group treatments. Increased Rubisco activity was also observed (62.89%), which suggested a significant role for elevated carbon fixation and assimilation and the upregulated expression of regulatory genes linked with Rubisco activity and the PSII reaction process. In short, we deduced that the 2.0 mg·L−1 BR application has an enhancing effect on the genetic modulation of physiological indices of melon plants against downy mildew disease stress.

Summary: Background: Prognosis is crucial for personalized treatment and surveillance suggestion of the resected non-small-cell lung cancer (NSCLC) patients in stage I-III. Although the tumor-node-metastasis (TNM) staging system is a powerful predictor, it is not perfect enough to accurately distinguish all the patients, especially within the same TNM stage. In this study, we developed an intelligent prognosis evaluation system (IPES) using pre-therapy CT images to assist the traditional TNM staging system for more accurate prognosis prediction of resected NSCLC patients. Methods: 20,333 CT images of 6371 patients from June 12, 2009 to March 24, 2022 in West China Hospital of Sichuan University, Mianzhu People's Hospital, Peking University People's Hospital, Chengdu Shangjin Nanfu Hospital and Guangan Peoples' Hospital were included in this retrospective study. We developed the IPES based on self-supervised pre-training and multi-task learning, which aimed to predict an overall survival (OS) risk for each patient. We further evaluated the prognostic accuracy of the IPES and its ability to stratify NSCLC patients with the same TNM stage and with the same EGFR genotype. Findings: The IPES was able to predict OS risk for stage I-III resected NSCLC patients in the training set (C-index 0.806; 95% CI: 0.744–0.846), internal validation set (0.783; 95% CI: 0.744–0.825) and external validation set (0.817; 95% CI: 0.786–0.849). In addition, IPES performed well in early-stage (stage I) and EGFR genotype prediction. Furthermore, by adopting IPES-based survival score (IPES-score), resected NSCLC patients in the same stage or with the same EGFR genotype could be divided into low- and high-risk subgroups with good and poor prognosis, respectively (p

Recognizing the risk of fluvial bank erosion is an important challenge to ensure the early warning and prevention or control of bank collapse in river catchments, including in the Yangtze River. This study introduces a geomorphons-based algorithm to extract river bank erosion information by adjusting the flatness from multibeam echo-sounding data. The algorithm maps ten subaqueous morphological elements, including the slope, footslope, flat, ridge, peak, valley, pit, spur, hollow, and shoulder. Twenty-one flatness values were used to build an interpretation strategy for the subaqueous features of riverbank erosion. The results show that the bank scarp, which is the erosion carrier, is covered by slope cells when the flatness is 10°. The scour pits and bank scars are indicated by pit cells near the bank and hollow cells in the bank slope at a flatness of 0°. Fluvial subaqueous dunes are considered an important factor accelerating bank erosion, particularly those near the bank toe; the critical flatness of the dunes was evaluated as 3°. The distribution of subaqueous morphological elements was analyzed and used to map the bank erosion inventory. The analysis results revealed that the near-bank zone, with a relatively large water depth, is prone to form large scour pits and a long bank scarp. Arc collapse tends to occur at the long bank scarp to shorten its length. The varied assignment of flatness values among terrestrial, marine, and fluvial environments is discussed, concluding that diversified flatness values significantly enable fluvial subaqueous morphology recognition. Consequently, this study provides a reference for the flatness-based recognition of fluvial morphological elements and enhances the targeting of subaqueous signs and risks of bank failure with a range of multibeam bathymetric data.

Abstract Mammography is used to detect breast cancer (BC), but its sensitivity is limited, especially for dense breasts. Circulating cell-free DNA (cfDNA) methylation tests is expected to compensate for the deficiency of mammography. We derived a specific panel of markers based on computational analysis of the DNA methylation profiles from The Cancer Genome Atlas (TCGA). Through training (n = 160) and validation set (n = 69), we developed a diagnostic prediction model with 26 markers, which yielded a sensitivity of 89.37% and a specificity of 100% for differentiating malignant disease from normal lesions [AUROC = 0.9816 (95% CI: 96.09-100%), and AUPRC = 0.9704 (95% CI: 94.54–99.46%)]. A simplified 4-marker model including cg23035715, cg16304215, cg20072171, and cg21501525 had a similar diagnostic power [AUROC = 0.9796 (95% CI: 95.56–100%), and AUPRC = 0.9220 (95% CI: 91.02–94.37%)]. We found that a single cfDNA methylation marker, cg23035715, has a high diagnostic power [AUROC = 0.9395 (95% CI: 89.72–99.27%), and AUPRC = 0.9111 (95% CI: 88.45–93.76%)], with a sensitivity of 84.90% and a specificity of 93.88%. In an independent testing dataset (n = 104), the obtained diagnostic prediction model discriminated BC patients from normal controls with high accuracy [AUROC = 0.9449 (95% CI: 90.07–98.91%), and AUPRC = 0.8640 (95% CI: 82.82–89.98%)]. We compared the diagnostic power of cfDNA methylation and mammography. Our model yielded a sensitivity of 94.79% (95% CI: 78.72–97.87%) and a specificity of 98.70% (95% CI: 86.36–100%) for differentiating malignant disease from normal lesions [AUROC = 0.9815 (95% CI: 96.75–99.55%), and AUPRC = 0.9800 (95% CI: 96.6–99.4%)], with better diagnostic power and had better diagnostic power than that of using mammography [AUROC = 0.9315 (95% CI: 89.95–96.34%), and AUPRC = 0.9490 (95% CI: 91.7–98.1%)]. In addition, hypermethylation profiling provided insights into lymph node metastasis stratifications (p

It is challenging for a mobile robot to avoid moving obstacles in dynamic environments. Traditional velocity obstacle methods do not fully consider the obstacles moving with the speeds larger than the maximum speed of the robot. In this article, a new obstacle avoidance method, named the maximum-speed aware velocity obstacle (MVO) algorithm, is proposed for a mobile robot to avoid one or multiple high-speed obstacles. The proposed algorithm expands the velocity obstacle region into two parts, where one of the parts foresees collisions beyond the time horizon to ensure the feasible solutions of the current and the next control step. In practical applications, the perception capability of the robot is generally limited, and a non-holonomic robot can't move into any direction due to its kinematic constraints. In this article, the limited sensing field of view and non-holonomic kinematic constraints of the mobile robot are incorporated into the proposed MVO method. Moreover, continuity, safety, and computational complexity of the MVO approach are analyzed and presented. Extensive simulations and physical experiments are conducted to verify the efficacy of the MVO method, where a quadrotor and a differential-drive robot are used to perform dynamic obstacle avoidance.

In order to optimize the additive manufacturing process and find the process parameters affecting the mechanical properties of the parts, an additive manufacturing simulation model of Ti-6Al-4V titanium alloy was established, and the effects of ambient temperature, substrate thickness and wire temperature on the stress field and residual stress field were analyzed. The results show that the ambient temperature is inversely proportional to the residual stress of the cladding layer, while the substrate thickness and wire temperature are positively correlated to the residual stress of the cladding layer. When the ambient temperature increases from 0 °C to 600 °C, the maximum residual stress decreases by 36.0%, the maximum residual stress increases by 10.0% when the substrate thickness increases from 25 mm to 55 mm and the maximum residual stress increases by 7.48% when the temperature increases from 0 °C to 600 °C. The influence of the three parameters on the maximum residual stress is as follows: ambient temperature > substrate thickness > wire temperature. The research results can provide reference for stress control during actual manufacturing.

Determining the nutrient requirements of industrial hemp to increase the yield requires quantifying variations in soil nutrients and enzyme activities in different growth stages, along with relevant soil microbial response. This study investigated the effects of different growth stages of industrial hemp on rhizosphere soil nutrients, enzyme activities, and microbial communities. The results showed that with the increase in the growth stages, the pH and available phosphorus (AP) decreased, while the soil organic matter (SOM), available nitrogen (AN), and available potassium (AK) increased substantially, indicating that the demand for nutrients of industrial hemp was constantly changing. Proteobacteria, Acidobacteria, Ascomycota, and Basidiomycota were found to be the keystone taxa to adapt to the nutrient requirements of industrial hemp at different growth stages by regulating soil enzyme activity. Furthermore, using the redundancy analysis and Spearman’s correlation analysis, we found that microbial taxonomic composition was related to the variations in AN, AP, and pH. In general, we emphasized that the interaction between industrial hemp and soil is closely related to the growth stage, which increases plant adaptability and growth because of the change of soil microorganisms.

Long-term continuous monoculture cultivation harms soil physicochemical and microbial communities in agricultural practices. However, little has been reported on the effect of continuous cropping of industrial hemp on bacterial community and diversity in the rhizosphere soil. Our study investigated the changes in physicochemical properties and bacterial communities of industrial hemp rhizosphere soils in different continuous cropping years. The results showed that continuous cropping would reduce soil pH and available phosphorus (AP), while electrical conductivity (EC), available nitrogen (AN), and available potassium (AK) would increase. Soil bacterial diversity and richness index decreased with continuous cropping years. At the same time, continuous cropping marked Acidobacteria, Bacteroidetes, and Gemmatimonadetes increase, and the Proteobacteria and Actinobacteria decreased. Moreover, we found that pH, AK, and AP were the critical factors associated with the changes in the abundance and structure of the bacterial community. Overall, our study first reported the effect of continuous cropping on the rhizosphere soil microflora of industrial hemp. The results can provide a theoretical basis for revealing the obstacle mechanism of continuous cropping of industrial hemp and contribute to the sustainable cultivation of industrial hemp in the future.

The main task for real-time vehicle tracking is establishing associations with objects in consecutive frames. After occlusion occurs between vehicles during the tracking process, the vehicle is given a new ID when it is tracked again. In this study, a novel method to track vehicles between video frames was constructed. This method was applied on driving recorder sensors. The neural network model was trained by YOLO v3 and the system collects video of vehicles on the road using a driving data recorder (DDR). We used the modified Deep SORT algorithm with a Kalman filter to predict the position of the vehicles and to calculate the Mahalanobis, cosine, and Euclidean distances. Appearance metrics were incorporated into the cosine distances. The experiments proved that our algorithm can effectively reduce the number of ID switches by 29.95% on the model trained on the BDD100K dataset, and it can reduce the number of ID switches by 32.16% on the model trained on the COCO dataset.