Search Results (54)

To enhance the precision of regional agricultural drought resilience evaluation, a convolutional neural network optimized with Adam with weight decay (AdamW–CNN) was constructed. Based on local agricultural economic development regulations and utilizing the Driving Force–Pressure–State–Impact–Response (DPSIR) conceptual model, sixteen indicators of agricultural drought resilience were selected. Subsequently, data preprocessing was conducted for Qiqihar City, Heilongjiang Province, China, which encompasses an area of 42,400 km². The drought resilience was accurately assessed based on the developed AdamW–CNN model from 2000 to 2021 in the study area. The key driving factors behind the spatiotemporal evolution of drought resilience were identified using gray relational analysis, and the future evolution trend of agricultural drought resilience was revealed through Ridge regression analysis improved by the Kepler optimization algorithm (KOA–Ridge). The results indicated that the agricultural drought resilience in Qiqihar City exhibited a trend of initial fluctuations, followed by a significant increase in the middle phase, and then stable development in the later stage. Precipitation, investment in the primary industry, grain output per unit of cultivated area, per capita cultivated land area, and the proportion of effective irrigation area were the primary driving factors in the study area. By simulating the drought resilience index of four typical regions and analyzing its evolution, it was found that the AdamW–CNN model, combined with the KOA–Ridge model, has greater advantages over the RMSProp-CNN model and the CNN model in terms of fit, stability, reliability, and evaluation accuracy. These findings provide a robust model for measuring agricultural drought resilience, offering valuable insights for regional drought prevention and management. Full article

Abnormalities in epidermal keratinocyte proliferation are a characteristic feature of a range of dermatological conditions. These include hyperproliferative states in psoriasis and dermatitis as well as hypoproliferative states in chronic wounds. This emphasises the importance of investigating the proliferation kinetics under conditions of healthy skin and identifying the key regulators of epidermal homeostasis, maintenance, and recovery following wound healing. Animal models contribute to our understanding of human epidermal self-renewal. Human skin xenografting overcomes the ethical limitations of studying human skin during regeneration. The application of this approach has allowed for the identification of a single population of stem cells and both slowly and rapidly cycling progenitors within the epidermal basal layer and the mapping of their location in relation to rete ridges and hair follicles. Furthermore, we have traced the dynamics of the proliferation pattern reorganization that occurs during epidermal regeneration, underlining the role of YAP activity in epidermal relief formation. Full article

Ecosystem water use efficiency (WUE) is a key indicator of the coupling between carbon and water cycles. With the increasing frequency of extreme climate events, WUE may also show trends of extremization. Understanding the dominant drivers behind extreme WUE variations is crucial for assessing the impact of climate variability on WUE. We investigate the main drivers and regional sensitivity of extreme WUE variations across seven geographical regions in China. The results reveal that extreme WUE variations are collectively influenced by gross primary productivity (GPP) and evapotranspiration (ET) (43.72%). GPP controls extreme WUE variations in 36.00% of the areas, while ET controls 20.17%. Furthermore, as the climate shifts from arid to humid regions, the area where GPP dominates extreme WUE variations increases, while the area dominated by ET decreases, suggesting a relationship with precipitation. Ridge regression analysis shows that vapor pressure deficit (VPD) is the primary driver of interannual WUE variation in China, with an average relative contribution of 38.64% and an absolute contribution of 0.025 gC·m⁻²·mm⁻¹·a⁻¹. We studied the changes in WUE and its driving mechanisms during extreme disaster events, providing a perspective focused on extreme conditions. In the future, these results may help regulate the carbon–water cycle in different regions, such as by guiding vegetation planting and land use planning based on the spatial characteristics of the dominant factors influencing extreme WUE variations to improve vegetation WUE. Full article

Cilia are highly specialized cellular projections emanating from the cell surface, whose defects contribute to a spectrum of diseases collectively known as ciliopathies. Intraflagellar transport protein 88 (IFT88) is a crucial component of the intraflagellar transport-B (IFT-B) subcomplex, a protein complex integral to ciliary transport. The absence of IFT88 disrupts the formation of ciliary structures; thus, animal models with IFT88 mutations, including the oak ridge polycystic kidney (ORPK) mouse model and IFT88 conditional allelic mouse model, are frequently employed in molecular and clinical studies of ciliary functions and ciliopathies. IFT88 plays a pivotal role in a variety of cilium-related processes, including organ fibrosis and cyst formation, metabolic regulation, chondrocyte development, and neurological functions. Moreover, IFT88 also exhibits cilium-independent functions, such as spindle orientation, planar cell polarity establishment, and actin organization. A deeper understanding of the biological events and molecular mechanisms mediated by IFT88 is anticipated to advance the development of diagnostic and therapeutic strategies for related diseases. Full article

Mycoplasma bovis (M. bovis) has caused huge economic losses to the cattle industry. The interaction between M. bovis and host cells is elucidated by screening and identifying the target protein of M. bovis adhesin on the surface of the host cell membrane. However, the response mechanism of embryonic bovine lung (EBL) cells to M. bovis infection is not yet fully understood. Additionally, it is necessary to further explore whether infection with M. bovis induces oxidative stress and mitochondrial damage in EBL cells. In this study, oxidation reaction, mitochondrial membrane potential, mitochondrial structure, and apoptosis ability of EBL cells infected with M. bovis were assessed at different times (12, 24, 48 h post-infection; hpi). Then, the differential proteomic analysis of M. bovis-infected EBL cells at 12 h and 24 h was performed with uninfected cells as the control. The results showed that M. bovis infection reduced the antioxidant capacity of EBL cells, increased ROS levels, and decreased mitochondrial membrane potential. The mitochondrial membrane of EBL cells was damaged, and the ridge arrangement was disordered after infection by transmission electron microscopy. With the increase in infection time, the mitochondrial matrix partially dissolved and spilled. The apoptosis rate of EBL cells increased with the increase in infection time of M. bovis. Furthermore, proteomic analysis identified 268 and 2061 differentially expressed proteins (DEPs) at 12 hpi and 24 hpi, respectively, compared with the uninfected cells. According to GO analysis, these DEPs were involved in the mitosis and negative regulation of cell growth. Additionally, the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated the following pathways were linked to mitochondrial damage or cell growth regulation, including glycolysis/gluconeogenesis, pentose phosphate pathway, oxidative phosphorylation, AMPK, cGMP-PKG, cAMP, calcium, Wnt, Phospholipase D, apoptosis, MAPK, cell cycle, Ras, PI3K-Akt, mTOR, HIF-1. PPI results indicated that YWHAZ, PIK3CA, HSP90AB1, RAP1A, TXN, RAF1, MAPK1, PKM, PGK1, and GAPDH might be involved in mitochondrial pathway apoptosis induced by M. bovis infection. This study offers helpful data toward understanding the response of mitochondria of EBL cells to M. bovis infection. Full article

The evaporation of soil water drives the upward movement of salt and its accumulation on the surface, which ultimately leads to soil salinization in agroecosystems. With the rapid development of remote sensing technology, the soil water and salt transport can be monitored accurately. Based on Landsat 8 satellite imagery and ERA5-Land reanalysis datasets, this study explored the variation characteristics of soil water and salt in the northeast Tibetan Plateau from 2013 to 2023, inferred by geostatistical methods like ridge regression, windowed cross correlation, and machine learning algorithms. The results show that the negative correlation effect between deep soil moisture (100–289 cm) and soil salinization is stronger. Moreover, soil water and salt also have a time lag effect compared with instant responses, meaning that the soil salinization caused by deep soil moisture may require longer transport times. As the potential driving factors, an increase in soil organic carbon and runoff is beneficial for alleviating salinization while abundant runoff also promotes soil humidification. This study has elucidated the specific regulation of soil salinization by soil moisture within different profiles, which is beneficial for understanding the ecological balance of soil water and soil salt in agroecosystems. Full article

Straw mulching cultivation technology can improve the soil environment of farmland, and it is applied in the dry farming area of Northwestern China. There are few studies on the effect of corn straw mulching on the soil temperature and yield of potato fields in dry land in Northwestern China. In this paper, three treatments, black film ridge (HM), corn straw mulching mechanized no-tillage planting (JG) and no-covering open field flat planting (CK), were set up in the period of 2022 to 2023. A field plot experiment was carried out to determine the soil temperature, growth index, and yield data during the key growth period. The statistical analysis results show that JG and HM significantly increased the potato yield, by 12.27~18.30% and 13.09~18.10%, compared with CK, but there was no significant difference between JG and HM. The yield was significantly positively correlated with tuber weight per plant at the tuber expansion stage, starch accumulation stage, and harvest stage (0.47 *~0.60 **), and significantly negatively correlated with the number of tubers at the harvest stage (−0.54 *). Compared with CK, HM increased the average soil temperature over the whole growth period by 0.27~0.92 °C. In 2022, the increase in the 5 cm soil layer in the tuber expansion period was the largest, reaching 0.83 °C. In 2023, the increase in the 5 cm soil layer in the starch accumulation period was the largest, reaching 3.08 °C. JG reduced the soil temperature over the whole growth period by 0.52 °C, and the 20 cm soil layer in the tuber formation period decreased the most, reaching 1.45 °C, which aggravated the soil temperature change over the whole growth period (the amplitude was 4.13~4.53 °C). The temperature difference between day and night in different growth periods in 2022 was 2.14~5.41 °C, and the soil temperature in some growth periods in 2022 even exceeded that with HM. The results showed that JG could regulate soil temperature and optimize the relationship between tuber weight per plant, tuber number per plant, and biomass allocation during tuber formation, which are beneficial for the improvement of the potato yield in the dry farming area of Northwestern China. Full article

In the era of digitalization, the large availability of data and innovations in machine learning algorithms provide new potential to improve the prediction of energy efficiency in buildings. The building sector research in the Kingdom of Saudi Arabia (KSA) lacks actual/measured data-based studies as the existing studies are predominantly modeling-based. The results of simulation-based studies can deviate from the actual energy performance of buildings due to several factors. A clearer understanding of building energy performance can be better established through actual data-based analysis. This study aims to predict the energy efficiency of residential buildings in the KSA using supervised machine learning algorithms. It analyzes residential energy trends through data collected from an energy audit of 200 homes. It predicts energy efficiency using five supervised machine learning algorithms: ridge regression, least absolute shrinkage and selection operator (LASSO) regression, a least angle regression (LARS) model, a Lasso-LARS model, and an elastic net regression (ENR) model. It also explores the most significant explanatory energy efficiency variables. The results reveal that the ENR model outperforms other models in predicting energy consumption. This study offers a new and prolific avenue for the research community and other building sector stakeholders, especially regulators and policymakers. Full article

Poly(p-dioxanone) (PPDO) is crystallized with amorphous poly(p-vinyl phenol) (PVPh) and tannic acid (TA) as co-diluents to regulate and induce dendritic-ringed PPDO spherulites, with spoke- or sector-bands, aiming for convenience of analyses on interior lamellar assembly. Morphologies and interior lamellar arrangement leading to the peculiar rings on individual dendrites are evaluated by using polarized-light microscopy (PLM) and scanning electron microscope (SEM). Combinatory microbeam small-/wide-angle X-ray scattering (SAXS/WAXS) analyses further confirm the unique assembly patterns in periodic cycles. Alternate gratings are packed with periodic ridges composed of feather-like branches and the valley is featured with some embossed textures. The periodic gratings in the ringed spokes resemble those in nature’s structured coloration and are proven to display light-interference iridescence. Full article

In recent decades, drought has intensified along with continuous global warming, significantly impacting terrestrial vegetation. High atmospheric water demand, indicated by vapor pressure deficit (VPD), and insufficient soil moisture (SM) are considered the primary factors causing drought stress in vegetation. However, the influences of VPD and SM on the autumn phenology are still unknown. Using satellite observations and meteorological data, we examined the impacts of VPD and SM on the end of the growing season (EOS) across the Northern Hemisphere (>30°N) from 1982 to 2022. We found that VPD and SM were as important as temperature, precipitation, and radiation in controlling the variations in the EOS. Moreover, the EOS was predominantly influenced by VPD or SM in more than one-third (33.8%) of the study area. In particular, a ridge regression analysis indicated that the EOS was more sensitive to VPD than to SM and the other climatic factors, with 25% of the pixels showing the highest sensitivity to VPD. In addition, the effects of VPD and SM on the EOS varied among biome types and climate zones. VPD significantly advanced the EOS in 25.8% of temperate grasslands, while SM had the greatest impact on advancing the EOS in 17.7% of temperate coniferous forests. Additionally, 27.7% of the midlatitude steppe (BSk) exhibited a significant negative correlation between VPD and the EOS, while 19.4% of the marine west coast climate (Cfb) showed a positive correlation between SM and the EOS. We also demonstrated that the correlation between VPD and the EOS was linearly affected by VPD and the leaf area index, while the correlation between SM and the EOS was affected by SM, precipitation, and the leaf area index. Our study highlights the importance of VPD and SM in regulating autumn phenology and enhances our understanding of terrestrial ecosystem responses to climate change. Full article

Forming ridges in no-tillage farming (FRNF) is an important conservation tillage practice in the purple soil region of China. Whether FRNF will enhance ecosystem services remains unclear. There is a lack of a systematic quantitative research about the effect of FRNF on ecosystem services. We collected 611 data entries from 21 previous publications to quantitatively evaluate the effects of FRNF on runoff and sediment loss, soil physicochemical properties and biomass. The results showed that compared with conventional tillage, (1) FRNF reduced runoff and sediment loss by 49% and 73%, respectively, due to the blocking effect of the ridge-ditch structure; (2) FRNF increased the concentrations of soil organic carbon, total nitrogen, available nitrogen, available phosphorus and available potassium by 15%, 14%, 30%, 58% and 17%, respectively; (3) FRNF decreased soil bulk density on the ridges by 11% and increased soil moisture content in the furrows by 28%, while it had insignificant effects on soil bulk density in the furrows and soil moisture content on the ridges; and (4) FRNF increased aboveground and belowground biomass (maize, oilseed rape, potato, sweet potato and wheat) by 23% and 63%, respectively. Overall, these results highlighted the importance of FRNF in regulating soil erosion, physicochemical properties and biomasses in the purple soil region of China. The implementation of FRNF in this region could significantly improve the ecosystem services in agro-ecosystems. Full article

Sunflower (Helianthus annuus) is a globally significant field crop, and disease resistance is crucial for ensuring yield stability and crop quality. Verticillium dahliae is a notorious soilborne pathogen that causes Verticillium Wilt (VW) and threatens sunflower production worldwide. In this study, we conducted a comprehensive assessment of sunflower resistance to V. dahliae across 231 sunflower cultivar lines, from the Sunflower Association Mapping (SAM) population. We employed EMMAX and ridge regression best linear unbiased prediction (rrBLUP) and identified 148 quantitative trait loci (QTLs) and 23 putative genes associated with V. dahliae resistance, including receptor like kinases, cell wall modification, transcriptional regulation, plant stress signalling and defense regulation genes. Our enrichment and quantitative real-time PCR validation results highlight the importance of membrane vesicle trafficking in the sunflower immune system for efficient signaling and defense upon activation by V. dahliae. This study also reveals the polygenic architecture of V. dahliae resistance in sunflowers and provides insights for breeding sunflower cultivars resistant to VW. This research contributes to ongoing efforts to enhance crop resilience and reduce yield losses due to VW, ultimately benefiting sunflower growers and the agricultural sector. Full article

In the global food industry, fermented dairy products are valued for their unique flavors and nutrients. Lactococcus lactis is crucial in developing these flavors during fermentation. Meeting diverse consumer flavor preferences requires the careful selection of fermentation agents. Traditional assessment methods are slow, costly, and subjective. Although electronic-nose and -tongue technologies provide objective assessments, they are mostly limited to laboratory environments. Therefore, this study developed a model to predict the electronic sensory characteristics of fermented milk. This model is based on the genomic data of Lactococcus lactis, using the DBO (Dung Beetle Optimizer) optimization algorithm combined with 10 different machine learning methods. The research results show that the combination of the DBO optimization algorithm and multi-round feature selection with a ridge regression model significantly improved the performance of the model. In the 10-fold cross-validation, the R² values of all the electronic sensory phenotypes exceeded 0.895, indicating an excellent performance. In addition, a deep analysis of the electronic sensory data revealed an important phenomenon: the correlation between the electronic sensory phenotypes is positively related to the number of features jointly selected. Generally, a higher correlation among the electronic sensory phenotypes corresponds to a greater number of features being jointly selected. Specifically, phenotypes with high correlations exhibit from 2 to 60 times more jointly selected features than those with low correlations. This suggests that our feature selection strategy effectively identifies the key features impacting multiple phenotypes, likely originating from their regulation by similar biological pathways or metabolic processes. Overall, this study proposes a more efficient and cost-effective method for predicting the electronic sensory characteristics of milk fermented by Lactococcus lactis. It helps to screen and optimize fermenting agents with desirable flavor characteristics, thereby driving innovation and development in the dairy industry and enhancing the product quality and market competitiveness. Full article

Exploring the relationship between topography and forest multifunctionality enhances understanding of the mechanisms maintaining forest multifunctionality and proves beneficial for managing overall forest functions across different landscapes. Leveraging census data from a 20 ha subtropical forest plot, we investigated the topographic variations in individual functions, multifunctionality, and their interrelationships. Our results revealed that relative to lower elevations, higher elevations had higher woody productivity, sapling growth, and recruitment that drove higher average forest multifunctionality (FMA). However, forest multifunctionality at the 50% threshold level (FMt50) had no significant difference between high and low elevations. Compared with the valley and slope, higher woody productivity, higher sapling recruitment, and higher soil organic carbon stock drove higher forest multifunctionality (FMA and FMt50) in the ridge. These results indicate the ridge serves as a forest multifunctionality “hotspot” within the Tiantong 20 hm² plot. Additionally, relative to the low elevation, the degree of synergy among functions at the high elevation was significantly lower, indicating difficulties in attaining high forest multifunctionality at the high elevation. Our work underscores the importance of topography in regulating subtropical forest multifunctionality and relationships between forest functions at a local scale, suggesting that future forest management strategies (such as regulating synergistic or trade-off relationships between functions) should give particular attention to topographic conditions. Full article

Salt accumulation in bare strips under film-mulched drip irrigation is a global concern as it adversely affects soil quality and hinders sustainable agricultural development in arid and semi-arid regions. This study aims to investigate the spatial distribution of soil moisture and salt under various planting patterns and assess the lateral salt accumulation effect in bare strips. Seven treatments were implemented based on the local cotton planting pattern, including the local classical planting pattern (LTP), mulch width of 220 cm (WFM-220), spacing of 90 cm (SFM-90), mulch width of 40 cm (WFM-40), spacing of 10 cm (SFM-10), ridge tillage (TFM-RT), and ditching (TFM-D), varying in mulch width, spacing, and tillage method in bare strips. Additionally, the performance of the HYDRUS-2D model was evaluated by comparing simulated and observed values using field data. The results revealed that (I) the WFM-220 cm treatment exhibited the best water content retention under mulched film, with lower salt accumulation in the surface bare strip (0–20 cm soil layer); (II) all treatments with narrow rows showed desalination effects in the 0–40 cm soil layer, with salt content reductions ranging from approximately 13% to 38% compared to the initial values; (III) under the LTP treatment, the lateral salt discharge effect in the bare strip of the 0–40 cm soil layer was the best, regardless of mulch width and spacing, with a salt accumulation rate up to three times higher than the initial value, and even up to four times higher in the 0–10 cm layer; (IV) the TFM-RT treatment exhibited the best salt accumulation ability on the surface bare strip; and (V) the HYDRUS-2D model proved to be an effective tool for studying the dynamic regulation mechanism of water and salt with root mean square error values ranging from 0.079 to 0.106 cm³·cm⁻³ for soil water content and from 0.044 to 0.079 dS·m⁻¹ for electrical conductivity, indicating good agreement between simulations and observations. Full article