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Abstract The tumor microenvironment (TME) facilitates tumor development through intricate intercellular signaling, thereby supporting tumor growth and suppressing the immune response. Thyroid hormone receptor interactor 13 (TRIP13), an AAA+ ATPase, modulates the conformation of client macromolecules, consequently influencing cellular signaling pathways. TRIP13 has been implicated in processes such as proliferation, invasion, migration, and metastasis during tumor progression. Recent studies have revealed that TRIP13 also plays a role in immune response suppression within the TME. Thus, inhibiting these functions of TRIP13 could potentially enhance immune responses and improve the efficacy of immune checkpoint inhibition. This review summarizes the recent research progress of TRIP13 and discusses the potential of targeting TRIP13 to improve immune‐based therapies for patients with cancer.

This study investigates the complex interaction of biophysical and meteorological factors that drive evapotranspiration (ET) in saline environments. Leveraging a total of 182 cloud-free Landsat 5/8 time-series data from 1988 to 2019, we employed the Surface Energy Balance System (SEBS) model to quantify ET and investigate its relationships with soil salinity, vegetation cover, groundwater depth, and landscape metrics. We validated the predicted ET at two experimental sites using ET observation calculated by a water balance model. The result shows an R2 of 0.78 and RMSE of 0.91 mm for the SEBS predicted ET, indicating high accuracy of the ET estimation. We detected abandoned saline farmland patches across Hetao and extracted the normalized difference vegetation index (NDVI), salinization index (SI), and the predicted ET for analysis. The results indicate that ET is negatively correlated with SI with a Pearson correlation coefficient (r) up to −0.7, while ET is positively correlated with NDVI (r = 0.4). In addition, we designed a control-variable experiment in the Yichang subdistrict to investigate the effects of groundwater depth, land aggregation index, soil salinity index, and the area of abandoned saline farmland patches on ET. The results indicate that increased NDVI could significantly enhance ET, while smaller saline farmland patches exhibited greater sensitivity to groundwater recharge, with higher averaged ET than larger patches. Moreover, we analyzed factor importance using Lasso regression and Random Forest (RF) regression. The result shows that the ranking of the importance of the features is consistent for both methods and for all the features, with NDVI being the most important (with an RF importance score of 0.4), followed by groundwater table depth (GWTD), and the influence of the surface area of abandoned saline farmland being the weakest. We found that smaller patches of abandoned saline farmland were more sensitive to changes in groundwater levels induced by nearby irrigation, affecting their averaged ET more dynamically than larger patches. Decreasing patch size over time indicates ongoing changes in land management and ecological conditions. This study, through a multifactor analysis of ET in abandoned saline farmland and its intrinsic factors, provides a reference for evaluating the dry drainage efficiency of abandoned saline farmland in a dry drainage system.

The risk of algal blooms in landscape water bodies replenished by reclaimed water (RW) prompted the scientific management of RW discharge issues. Mathematical models are concise and convincing methods to stimulate algal growth and calculate thresholds for water quality control. This study presented three types of models, including one-parameter models, multiple-parameter models, and ecosystem dynamic models. Key influencing factors (such as nutrient concentration, light intensity, temperature, biotic processes, specific hydraulic conditions, etc.) are taken into consideration in these models. The work provided feasible methods for the management of reclaimed water to prevent water bloom outbreaks.

Phytolacca americana, introduced to China in the 20th century for its medicinal properties, has posed a significant ecological and agricultural challenge. Its prolific fruit production, high reproductive coefficient, adaptability, and toxic roots and fruits have led to the formation of monoculture communities, reducing native species diversity and posing threats to agriculture, human and animal health, and local ecosystems. Understanding its potential distribution patterns at a regional scale and its response to climate change is essential for effective monitoring, management, and control. In this study, we utilized the Maxent model to simulate potential habitat areas of P. americana across three timeframes (current, 2050s, and 2070s) under three climate change scenarios (SSP126, SSP245, and SSP585). Leveraging data from 556 P. americana sites across China, we employed ROC curves to assess the prediction accuracy. Our findings highlight key environmental factors influencing P. americana’s geographical distribution, including the driest month’s precipitation, the coldest month’s minimum temperature, the wettest month’s precipitation, isothermality, and temperature annual range. Under current climate conditions, P. americana potentially inhabits 280.26 × 104 km2 in China, with a concentration in 27 provinces and cities within the Yangtze River basin and its southern regions. While future climate change scenarios do not drastically alter the total suitable area, the proportions of high and low-suitability areas decrease over time, shifting towards moderate suitability. Specifically, in the SSP126 scenario, the centroid of the predicted suitable area shifts northeastward and then southwestward. In contrast, in the SSP245 and SSP585 scenarios, the centroid shifts northward.

Current knowledge on the fish gut microbiota has largely been obtained from experiments on laboratory-reared animals. Here, the crucian carp (Carassius auratus) with a mean weight of 159.9 ± 11.4 g (mean ± SD) were collected from their natural habitats (i.e., Wuhu lake and Poyang lake, China), and the gut microbiota were analysed by using the next-generation sequencing of 16S rRNA gene. We obtained more than 430,000 high-quality reads, which constituted more than 1200 operational taxonomy units (OTUs), revealing extremely diverse microbes in the fish gut. Proteobacteria, Fusobacteria, Bacteroidetes and Firmicutes were detected as the prominent phyla (each > 1% of total abundance) within the gut microbiota, regardless of the host habitat or the gut segment (i.e., foregut vs. hindgut). Although the microbes in the hindgut were more diverse (OTU number, Shannon and Chao1; One-way Anova, p > 0.05) than in the foregut, the host habitat had a significant role in shaping the community structures (MRPP, ANOSIM, PERMANOVA, p < 0.01). Interestingly, we also detected a set of common OTUs, whereby genera Aeromonas and Cetobacterium might comprise the core gut microbiota of crucian carp.

Weather disturbances, difficult backgrounds, the shading of fruit and foliage, and other elements can significantly affect automated yield estimation and picking in small target apple orchards in natural settings. This study uses the MinneApple public dataset, which is processed to construct a dataset of 829 images with complex weather, including 232 images of fog scenarios and 236 images of rain scenarios, and proposes a lightweight detection algorithm based on the upgraded YOLOv7-tiny. In this study, a backbone network was constructed by adding skip connections to shallow features, using P2BiFPN for multi-scale feature fusion and feature reuse at the neck, and incorporating a lightweight ULSAM attention mechanism to reduce the loss of small target features, focusing on the correct target and discard redundant features, thereby improving detection accuracy. The experimental results demonstrate that the model has an mAP of 80.4% and a loss rate of 0.0316. The mAP is 5.5% higher than the original model, and the model size is reduced by 15.81%, reducing the requirement for equipment; In terms of counts, the MAE and RMSE are 2.737 and 4.220, respectively, which are 5.69% and 8.97% lower than the original model. Because of its improved performance and stronger robustness, this experimental model offers fresh perspectives on hardware deployment and orchard yield estimation.

The effects of invasive species on the local community (e.g., structure and stability) are highly environmentally dependent. Invasions of amphibious species usually take place in both xeric and humid environments, yet they are relatively poorly understood. In this study, we analyzed the communities that were dominated by Alternanthera philoxeroides using ecological niche and interspecific association. A total of 66 species and 67 species were recorded in the xeric environment and humid environment, respectively. In both environments, species in family Gramineae, such as Echinochloa crusgalli and Cynodon dactylon, exhibited a higher level of importance values and greater ecological niche widths. The interspecific association and stability of the dominant species were weak and the dominant species were relatively independent of each other. In the xeric environment, A. philoxeroides was more compatible with E. crusgalli and C. dactylon in terms of ecological niche requirements and habitat suitability. In humid habitats, A. philoxeroides had a greater correlation with E. crusgalli, C. dactylon, and Persicaria lapathifolia, suggesting a higher possibility of concomitant occurrence. Overall, we suggested that during the revegetation after A. philoxeroides invasion, E. crusgalli and C. dactylon can be the alternative plants. Meanwhile, alternative control measures for A. philoxeroides invasion in agricultural fields should give more consideration to the use of plants with economic or ecological value.

In this study, based on the lumped-parameter theory and the Lagrange approach, a novel and generalized bending-torsional-axial coupled dynamic model for analyzing the load sharing behavior in the herringbone planetary gear train (HPGT) is presented by taking into account the actual structure of herringbone gears, manufacturing errors, time-dependent meshing stiffness, bearing deflections, and gyroscopic effects. The model can be applied to the analysis of the vibration of the HPGT with any number of planets and different types of manufacturing errors in different floating forms. The HPGT equivalent meshing error is analyzed and derived for the tooth profile errors and manufacturing eccentric errors of all components in the HPGT system. By employing the variable-step Runge–Kutta approach to calculate the system dynamic response, in conjunction with the presented calculation approach of the HPGT load sharing coefficient, the relationships among manufacturing errors, component floating, and load sharing are numerically obtained. The effects of the combined errors and single error on the load sharing are, respectively, discussed. Meanwhile, the effects of the support stiffness of the main components in the HPGT system on load sharing behavior are analyzed. The results indicate that manufacturing errors, floating components, and system support stiffness largely influence the load sharing behavior of the HPGT system. The research has a vital guiding significance for the design of the HPGT system.

This present study mainly focuses on the influence of low-calcium circulating fluidized bed fly ash (LCFA) on the mechanical property and microstructure of cement-based materials under different curing conditions. The mechanical properties test was conducted by changing variable parameters, such as LCFA content, the internal mixing ratio of LCFA and fly ash (FA), and dry and water curing conditions. Further, the hydration products and pore structure were analyzed using XRD, FT-IR, TG-DTG, NI, SEM, and BET micro-testing technology. The strength development law of LCFA on cement-based materials is discussed. The research results show that LCFA has a certain degree of self-hardening and can be used as a cementitious material in cement-based materials. Still, the loose and porous microstructure of LCFA leads to higher water requirements, which reduces the fluidity of cement-based pastes. Water curing is favorable for promoting the development of LCFA on the long-term compressive strength of cement-based materials. When the LCFA was added to the cement, the optimal substitution ratio was 20%, and the compressive strength at 91 days reached 101 MPa. In the case of compounding LCFA and FA, when the internal mixing ratio of LCFA/FA was 3 and the total content was 20%, the mechanical properties were the highest, and the compressive strength at 91 days was 92 MPa. The microscopic analysis result shows that the cumulative hydration heat of the samples decreased significantly with the increase of dosage of LCFA. The main hydration products of cement-based materials mixed with LCFA were AFt, C-S-H gel, and Ca(OH)2. AFt and C-S-H gels are critical to the strength development of OPC-LCFA samples. The active Al2O3 and active SiO2 in LCFA were involved in hydration reactions to promote the formation of C-A-H and C-S-H gel and effectively promote the development of the mechanical properties. Overdosages of LCFA would reduce the ettringite formation rate. FA is not conducive to AFt formation in the hydration process of OPC-FA samples.

Salinization in arid or semiarid regions with water logging limits cropland yield, threatening food security. The highest level of farmland salinization, that is, abandoned salinized farmland, is a tradeoff between inadequate drainage facilities and sustainable farming. The evolution of abandoned salinized farmlands is closely related to the development of cropping systems. However, detecting abandoned salinized farmland using time-series remote sensing data has not been investigated well by previous studies. In this study, a novel approach was proposed to detect the dynamics of abandoned salinized farmland using time-series multispectral and thermal imagery. Thirty-two years of temporal Landsat imagery (from 1988 to 2019) was used to assess the evolution of salinization in Hetao, a two-thousand-year-old irrigation district in northern China. As intermediate variables of the proposed method, the crop-specific planting area was retrieved via its unique temporal vegetation index (VI) pattern, in which the shape-model-fitting technology and the K-means cluster algorithm were used. The desert area was stripped from the clustered non-vegetative area using its distinct features in the thermal band. Subsequently, the abandoned salinized farmland was distinguished from the urban area by the threshold-based saline index (SI). In addition, a regression model between electrical conductance (EC) and SI was established, and the spatial saline degree was evaluated by the SI map in uncropped and unfrozen seasons. The results show that the cropland has constantly been expanding in recent decades (from 4.7 × 105 ha to 7.1 × 105 ha), while the planting area of maize and sunflower has grown and the area of wheat has decreased. Significant desalinization progress was observed in Hetao, where both the area of salt-affected land (salt-free area increased approximately 4 × 105 ha) and the abandoned salinized farmland decreased (reduced from 0.45 × 105 ha to 0.19 × 105 ha). This could be mainly attributed to three reasons: the popularization of water-saving irrigation technology, the construction of artificial drainage facilities, and a shift in cropping patterns. The decrease in irrigation and the increase in drainage have deepened the groundwater table in Hetao, which weakens the salt collection capacity of the abandoned salinized farmland. The results demonstrate the promising possibility of reutilizing abandoned salinized farmland via a leaching campaign where the groundwater table is sufficiently deep to stop salinization.

Cycloaddition reactions such as intramolecular Diels–Alder (IMDA) are extremely important in constructing multicyclic scaffolds with diverse bioactivities. Using MycB as a biomarker, three new polyketides – Chaetolivacines A (1), B (3), and C (4) – with one known compound Myceliothermophin E (2) comprising of decalin and 4-hydroxy-2-pyridones were obtained from the culture of Chaetomium olivaceum SD-80A under the guidance of gene mining. The structures of these compounds were established using detailed 1D, 2D NMR, and high-resolution electron spray ionization mass spectroscopy (HRESIMS) analysis. The relative and absolute configurations of the compounds 1, 3, and 4 were elucidated by NOESY and ECD. The biosynthesis pathways of these compounds were proposed, which involves in three key genes ChaA [polyketide synthase-non-ribosomal peptide synthetases (PKS-NRPS)], ChaB, and ChaC. Compounds 1–4 were tested for their antimicrobial activities, and compounds 2 and 3 showed moderate bioactivity against Staphylococcus aureus (SA) and methicillin-resistant S. aureus (MRSA) with MIC values of 15.8 and 27.1 μM. The results showed that configuration of C-21 in 3 and 4 is important for anti-SA and anti-MRSA activities. This study reveals the significant potential of the genus Chaetomium in producing new PKS-NRPS, therefore increasing the speed in the mining for new sources of antimicrobial agents.

Abstract Several E3 ubiquitin ligases have been confirmed that they are related to the tumorigenesis. This study aims to find the tongue cancer‐related E3 ubiquitin ligase. The E3 ubiquitin ligase library was screened. The effect of candidate molecule on tongue cancer was validated through cell viability, cell proliferation, colony formation, invasive assay in vitro, and the xenograft model in vivo. The E3 ubiquitin ligase RNF135 significantly promoted the expression of PTEN and TP53 in SCC25 cells. The overexpression of RNF135 inhibited the viability, proliferation, and invasion of SCC25 cells. Knockdown of RNF135 had the opposite effects. Furthermore, RNF135 regulates the tumorigenesis activity of SCC25 cells in vivo. Our results demonstrated that RNF135 had the potential to affect the development of the tongue cancer in vitro. The further in vivo study is helpful to fully understand the role of it.

Soil organic matter (SOM) refers to all carbon-containing organic matter in soil and is one of the most important indicators of soil fertility. The hyperspectral inversion analysis of SOM traditionally relies on laboratory chemical testing methods, which have the disadvantages of being inefficient and time-consuming. In this study, 69 soil samples were collected from the Honghu farmland area and a mining area in northwest China. After pretreatment, 10 spectral indicators were obtained. Ridge regression, kernel ridge regression, Bayesian ridge regression, and AdaBoost algorithms were then used to construct the SOM hyperspectral inversion model based on the characteristic bands, and the accuracy of the models was compared. The results showed that the AdaBoost algorithm based on a grid search had the best accuracy in the different regions. For the mining area in northwest China, R p 2 = 0.91, R M S E p = 0.22, and M A E p = 0.2. For the Honghu farmland area, R p 2 = 0.86, R M S E p = 0.72, and M A E p = 0.56. The detection of SOM content using hyperspectral technology has the characteristics of a high detection precision and high speed, which will be of great significance for the rapid development of precision agriculture.

Fallows are widespread in dryland cropping systems. However, timely information about their spatial extent and location remains scarce. To overcome this lack of information, we propose to classify fractional cover data from Sentinel-2 with biased support vector machines. Fractional cover images describe the land surface in intuitive, biophysical terms, which reduces the spectral variability within the fallow class. Biased support vector machines are a type of one-class classifiers that require labelled data for the class of interest and unlabelled data for the other classes. They allow us to extrapolate in-situ observations collected during flowering to the rest of the growing season to generate large training data sets, thereby reducing the data collection requirements. We tested this approach to monitor fallows in the northern grains region of Australia and showed that the seasonal fallow extent can be mapped with >92% accuracy both during the summer and winter seasons. The summer fallow extent can be accurately mapped as early as mid-December (1–4 months before harvest). The winter fallow extent can be accurately mapped from mid-August (2–4 months before harvest). Our method also detected emergence dates successfully, indicating the near real-time accuracy of our method. We estimated that the extent of fallow fields across the northern grains region of Australia ranged between 50% in winter 2017 and 85% in winter 2019. Our method is scalable, sensor independent and economical to run. As such, it lays the foundations for reconstructing and monitoring the cropping dynamics in Australia.

The concept of harvesting ambient energy as an alternative power supply for electronic systems like remote sensors to avoid replacement of depleted batteries has been enthusiastically investigated over the past few years. Wind energy is a potential power source which is ubiquitous in both indoor and outdoor environments. The increasing research interests have resulted in numerous techniques on small-scale wind energy harvesting, and a rigorous and quantitative comparison is necessary to provide the academic community a guideline. This paper reviews the recent advances on various wind power harvesting techniques ranging between cm-scaled wind turbines and windmills, harvesters based on aeroelasticities, and those based on turbulence and other types of working principles, mainly from a quantitative perspective. The merits, weaknesses, and applicability of different prototypes are discussed in detail. Also, efficiency enhancing methods are summarized from two aspects, that is, structural modification aspect and interface circuit improvement aspect. Studies on integrating wind energy harvesters with wireless sensors for potential practical uses are also reviewed. The purpose of this paper is to provide useful guidance to researchers from various disciplines interested in small-scale wind energy harvesting and help them build a quantitative understanding of this technique.