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Objective: The ultra-high pressure (UHP) pretreatment combined with hot air drying (HAD) process of Chinese yam (CY) was established and optimized in this study, in order to shorten the drying time of CY and improve its quality. Methods: The drying time, rehydration ratio (RR), color difference value, polysaccharide and total phenol content (TPC) were used as indicators to investigate the effects of different UHP pressure, holding time and drying temperature conditions on CY processing by single factor experiment, the weight coefficient of five indicators and the comprehensive score under different conditions were calculated by the CRITIC method, using the comprehensive score as the response value to optimize the processing technology of UHP pretreatment combined with HAD by response surface methodology. Results: UHP pretreatment could significantly shorten the drying time (P

This study investigated the differences in the physicochemical indexes, volatile flavor substances and microbial community composition of three different colored Daqu (black, yellow and white). Physicochemical analyses showed that the acidity, moisture content and saccharifying power of black Daqu were intermediate between those of yellow and white Daqu, white Daqu had the highest saccharifying power, fermenting power, and esterifying power, and yellow Daqu contained the highest starch content. Flavor substance analysis indicated significant differences in the contents of ethyl caproate, ethyl acetate, phenylethyl alcohol, 1-hexanol and furfural among the three types of Daqu. Microbial community structure analysis revealed that Bacillus and Scopulibacillus were the dominant bacteria, and Thermomyces and Thermoascus were the major fungi in all three types of Daqu. Redundancy analysis (RDA) suggested that Bacillus and Thermomyces had a positive correlation with fermenting power, esterifying power and saccharifying power. Spearman correlation analysis showed that Scopulibacillus, Virgibacillus and Aspergillus were positively correlated with most key flavor compounds. This study provides reference data for the rational application of Daqu in the production of Jiang-flavor Baijiu and is of great value for the standardization of Jiang-flavor Baijiu production.

Abstract Changes in diet causing ecological stress pose a significant challenge to animal survival. In response, the gut microbiota, a crucial part of the host’s digestive system, exhibits patterns of change reflective of alterations in the host’s food component. The impact of temporal dietary shifts on gut microbiota has been elucidated through multidimensional modeling of both food component and macronutrient intake. However, the broad distribution of wild generalist and the intricate complexity of their food component hinder our capacity to ascertain the degree to which their gut microbiota assist in adapting to spatial dietary variations. We examined variation in patterns of the gut microbial community according to changes in diet and in a colobine monkey with a regional variable diet, the golden snub-nosed monkey (Rhinopithecus roxellana). Specifically, we analyse the interactions between variation in food component, macronutrient intake and the gut microbial community. We compared monkeys from four populations by quantifying food component and macronutrient intake, and by sequencing 16S rRNA and the microbial macro-genomes from the faecal samples of 44 individuals. We found significant differences in the diets and gut microbial compositions, in nutrient space and macronutrient intake among some populations. Variations in gut microbiota composition across distinct populations mirror the disparities in macronutrient intake, with a notable emphasis on carbohydrate. Geographical differences in the diet among of golden snub-nosed monkey populations will result in macronutrient intake variation, with corresponding differences in macronutrient intake driving regional differences in the compositions and abundances of gut microbiota. Importantly, the gut microbiota associated with core digestive functions does not vary, with the non-core gut microbiota fluctuating in response to variation in macronutrient intake. This characteristic may enable species heavily reliant on gut microbiota for digestion to adapt to diet changes. Our results further the understanding of the roles gut microbiota play in the formation of host dietary niches.

Abstract N6-methyladenosine (m6A) is a prevalent mRNA modification known for its implications in various cancer types, yet its role in chromophobe renal cell carcinoma (chRCC) remains largely unexplored. In this study, we performed m6A-SEAL-seq and RNA-seq analyses on tissues from three chRCC subjects, aiming to uncover m6A alterations in chRCC. Our findings revealed reduced expression levels of four m6A regulators in chRCC tissues and highlighted differences in m6A levels compared to normal tissues. Furthermore, we identified specific genes and cancer-related pathways affected by these differences, including notable candidates like NOTCH1 and FGFR1, implicated in chRCC development. Additionally, we developed a predictive model based on the expression level of m6A associated genes, demonstrating promising prognostic capabilities for patient survival prediction. Overall, our study provides valuable insights into the role of m6A in chRCC and its potential as a prognostic indicator.

Abstract In the process of tension wire construction of transmission lines, the key state quantities such as tension, inclination and spatial position of the traction walking plate directly affect the construction safety. At present, the construction personnel use visual observation to obtain the state quantity of traction walking plate in the process of tension wire construction. This monitoring method is not only inefficient, and there are personal subjective factors of judgment errors. For this reason, this paper develops a kind of intelligent traction walking plate for tension wire construction, based on the principle of resistance strain type and gyroscope to obtain the tension and inclination of the traction walking plate, respectively, using two front cameras and two rear cameras to obtain the spatial position of the traction walking plate, and finally completing the real‐time transmission of the monitoring data through the Lora technology. The developed intelligent traction walking plate was applied in Shandong Heze Yongfeng 220 kV transmission line project on 11 October 2020, which improved the construction efficiency by 15.71% while ensuring the construction safety.

Abstract Maternal overnutrition during lactation predisposes offspring to develop metabolic diseases and exacerbates the relevant syndromes in males more than females in later life. The hypothalamus is a heterogenous brain region that regulates energy balance. Here we combined metabolic trait quantification of mother and offspring mice under low and high fat diet (HFD) feeding during lactation, with single nucleus transcriptomic profiling of their offspring hypothalamus at peak lacation to understand the cellular and molecular alterations in response to maternal dietary pertubation. We found significant expansion in neuronal subpopulations including histaminergic (Hdc), arginine vasopressin/retinoic acid receptor-related orphan receptor β (Avp/Rorb) and agouti-related peptide/neuropeptide Y (AgRP/Npy) in male offspring when their mothers were fed HFD, and increased Npy-astrocyte interactions in offspring responding to maternal overnutrition. Our study provides a comprehensive offspring hypothalamus map at the peak lactation and reveals how the cellular subpopulations respond to maternal dietary fat in a sex-specific manner during development.

Adoption among nonhuman primates (hereafter primates) has been widely reported, particularly in chimpanzees, renowned for their higher intelligence and well-developed cognition. In contrast to adoption in other Old World monkeys, this case of adoption in golden snub-nosed monkeys (Rhinopithecus roxellana) involves two infants associated with three units characterized by distinct social structures and reproductive functions. Consequently, this case extends beyond traditional hypotheses on allomaternal care and adoption—such as enhancing the fitness of adoptive mothers, fostering maternal behaviors, and improving fitness through social and individual interactions—to necessitate an association with the complex social structure characterized by hierarchical, multilevel composition, akin to human society, and intense sexual selection that frequently results in infanticide. Specifically, adopting an infant with a genetic link to the dominant male of the adopting female may reduce the risk of infanticide against her offspring that do not share a biological link with the dominant male. This adoption pattern suggests that golden snub-nosed monkeys may possess more sophisticated intelligence and cognition, characteristics supported by more developed brain structure and facial muscles than the other Old World monkeys.

The evolutionary development and phylogenetic division between Asian and African cercopithecoids (Cercopithecidae) have attracted significant attention in genetics, molecular biology, behavior, and morphology. However, less emphasis has been placed on how they have evolved morphologically after divergence, approximately 10 million years ago (mya) for Colobinae and 5–7 mya for Cercopithecinae, corresponding to the significant variation and diversity in landscape, climate, habitat, and ecologies between the two continents. This study examines whether such variation and diversity have been reflected in dental morphology. Our findings reveal substantial differences between Hylobatidae and Cercopithecidae, as well as between Colobinae and Cercopithecinae, indicating that size-adjusted dental variation mainly reveals the diversity associated with evolution and phylogenetic inertia. Interestingly, despite the earlier divergence of Afro-Asian colobines, their Euclidean Distance is comparable to that of Afro-Asian cercopithecines. This implies that latecomers (macaques) demonstrate equivalent diversity to colobines due to their extensive dispersion and broader adaptative radiation on the same continent. Colobinae exhibit more developed premolar and molar regions. However, when post-canine teeth are considered alone, Colobinae present a significantly larger molar size than Asian Cercopithecinae but not with the African Cercopihecinae. This contradicts the hypothesis that folivorous primates (Colobinae) have larger post-canine molars than frugivorous ones (Cercopithecinae). The considerable molar size in African Cercopithecinae must be associated with their more protrusive and larger facial structure rather than a specific dietary preference, being less diverse than their Asian counterparts—a trait that has evolved phylogenetically. This study also paves the way for further exploration of facial and cranial differences between the continental groups of Cercopithecinae and Colobinae, delving deeply into diversity variation due to geographical and climatic adaptations.

Genetic diversity is an essential indicator that echoes the natural selection and environmental adaptation of a species. Isolated small populations are vulnerable to genetic drift, inbreeding, and limited gene flow; thus, assessing their genetic diversity is critical in conservation. In this study, we studied the genetic diversity of black-and-white snub-nosed monkeys (Rhinopithecus bieti) using neutral microsatellites and five adaptive major histocompatibility complex (MHC) genes. Two DQA1 alleles, two DQB1 alleles, two DRB1 alleles, two DRB5 alleles, and three DPB1 alleles were isolated from a population. The results indicate that neutral microsatellites demonstrate a high degree of heterozygosity and polymorphism, while adaptive MHC genes display a high degree of heterozygosity and moderate polymorphism. The results also show that balancing selection has prominently influenced the MHC diversity of the species during evolution: (1) significant positive selection is identified at several amino acid sites (primarily at and near antigen-binding sites) of the DRB1, DRB5, and DQB1 genes; (2) phylogenetic analyses display the patterns of trans-species evolution for all MHC loci. This study provides valuable genetic diversity insights into black-and-white snub-nosed monkeys, which dwell at the highest altitude and have experienced the harshest environmental selection of all primates globally since the Pleistocene. Such results provide valuable scientific evidence and a reference for making or amending conservation strategies for this endangered primate species.

As a new non thermal pretreatment technology, pulsed electric field (PEF) has excellent characteristics such as short time consumption, low energy consumption and green environmental protection. In this paper, the mechanism of pulsed electric field and its application as pretreatment technology in the field of fruit and vegetable drying, such as hot air drying, freeze drying, microwave drying, osmotic drying, spray drying and vacuum drying, are reviewed. Compared with untreated, PEF pretreatment can improve the dehydration rate, reduce production costs, improve the retention rate of nutrients in the sample, and make the quality of dried products better. However, PEF has some problems, such as the specificity between the parameters and the processing matrix, and the safety of the pretreated food. In the future, it is necessary to strengthen the parameter matching and safety research of PEF, so as to provide new ideas and references for the in-depth research of PEF pretreatment in the field of fruit and vegetable drying.

Soil analysis using near-infrared spectroscopy has shown great potential to be an alternative to traditional laboratory analysis, and there is continuously increasing interest in building large-scale soil spectral libraries (SSLs). However, due to issues such as high non-linearity in soil spectral data and complexity in soil spatial variation, the establishment of robust prediction models for soil spectral libraries remains a challenge. This study aimed to investigate the performance of deep learning algorithms, including long short-term memory (LSTM) and LSTM–convolutional neural networks (LSTM–CNN) integrated models, to predict the soil organic matter (SOM) of a provincial-scale SSL, and compare it to the normally used local weighted regression (LWR) model. The Hebei soil spectral library (HSSL) contains 425 topsoil samples (0–20 cm), of which every 3 soil samples were collected from dry land, irrigated land, and paddy fields, respectively, in different counties of Hebei Province, China. The results show that the accuracy of the validation dataset rank as follows: LSTM–CNN (R2p = 0.96, RMSEp = 1.66 g/kg) > LSTM (R2p = 0.83, RMSEp = 3.42 g/kg) > LWR (R2p = 0.82, RMSEp = 3.79 g/kg). The LSTM–CNN model performed the best, mainly due to its comprehensive ability to effectively extract spatial and temporal features. Meanwhile, the LSTM model achieved higher accuracy than the LWR model, owing to its built-in memory unit and its advantage of faster feature band extraction. Thus, it was suggested to use deep learning algorithms for SOM predictions in SSLs. However, their performance on larger-scale SSLs such as continental/global SSLs still needs to be further investigated.

Summary: Glycome in urine could be promising biomarkers for detecting pregnancy diagnosis and sex noninvasively for animals, especially for rare species. We explore the applicability of grouping golden snub-nosed monkeys by sex or diagnosing pregnancy based on their urinary glycopatterns, which are determined via lectin microarray combining mass spectrometry analysis. Sprague-Dawley rats are used to verify whether this approach and whether the glycomic biomarkers can be generalized to other mammalian species. The results show that, for both species, lectin microarray combining mass spectrometry can distinguish individuals’ pregnancy status and sex; significant differences are found in the types, amounts, and terminal modification of glycans between pregnant and non-pregnant females and between females and males. This indicates the approach could be generalized to other mammalian species to group sex and detect pregnancy, yet the glycopatterns appear to be species-specific and markers developed from one species may not be directly applicable to another.

This article explores the crucial first steps in enforcing the black soils protection law in China, presents the governance rationale for safeguarding black soil, and ultimately devises an effective governance system for the same. The article contends that black soils conservation necessitates a shift towards scientific management grounded in legislation and advocates for the establishment of a protection and governance system, including firming up the government's central role, executing scientific and technological initiatives, setting up inter-regional protection mechanisms, innovating management techniques, and exploring land-scale management.

Unmanned aerial vehicles (UAVs) have broad applications. However, their use for wildlife surveys in rugged mountains with dense vegetation is uncommon. Therefore, developing appropriately designed methods, selecting suitable facilities, establishing effective monitoring processes, and managing databases that align with a region’s distinctive geographic landscapes, environments, ecology, and habitats are essential. This study focuses on the Giant Panda National Park in China’s densely vegetated Qinling Mountains to carry out surveys using UAVs to assess the Sichuan snub-nosed monkey population size (Rhinopithecus roxellana) over an area of 30,000 ha. The results indicate that eight distinct groups were identified, totaling 648–755 individuals. Thus, this study offers proof-of-principle for using UAVs for surveying wildlife in remote mountainous regions with complex landscapes and dense vegetation and demonstrates how UAVs can be used in animal monitoring and conservation. Furthermore, the study highlights the broader potential application of UAVs in other remote mountainous regions, where animal demographic information is urgently needed to establish database-driven conservation strategies.

Objective: The present study was to explore the protective effects of the anthocyanidin extract of Hippophae rhamnoides L. (HRAE) against hydrogen peroxide (H2O2) induced by oxidative damage in H1299 cells and its mechanism. Methods: The H2O2-induced oxidative damage in H1299 cells was established. MTT assay was used to detect the cell viability of HRAE. Then the content of reactive oxygen species (ROS) was measured by fluorescence probe DCFH-DA. The contents of superoxide dismutase (SOD), catalase (CAT), glutathion peroxidase (GSH-Px), and malondialdehyde (MDA) were determined respectively by kit. Also the expression of proteins heme oxygenase-1 (HO-1), NAD(P)H quinine oxidoreductase 1 (NQO1), Kelch-like epichlorohydrin-associated protein 1 (Keap1) and nuclear factor-erythroid 2-related factor 2 (Nrf2) were tested. At last, the research collaboratory for structural bioinformatics (RCSB) protein data bank and AutoDock software were used to verify the molecular docking between epicatechin and Nrf2, the key target protein of oxidative stress. Results: MTT assay showed that HRAE had no effect on cell viability in the range of 0~800µg/mL (P>0.05). Compared with model group, MDA level was decreased, while SOD, CAT and GSH-Px protein expression levels increased significantly in drug administration group (P

IntroductionHumic substances (HSs), components of plant biostimulants, are known to influence plant physiological processes, nutrient uptake and plant growth, thereby increasing crop yield. However, few studies have focused on the impact of HS on overall plant metabolism, and there is still debate over the connection between HS’ structural characteristics and their stimulatory actions.MethodsIn this study, two different HSs (AHA, Aojia humic acid and SHA, Shandong humic acid) screened in a previous experiment were chosen for foliar spraying, and plant samples were collected on the tenth day after spraying (62 days after germination) to investigate the effects of different HSs on photosynthesis, dry matter accumulation, carbon and nitrogen metabolism and overall metabolism in maize leaf.Results and discussionThe results showed different molecular compositions for AHA and SHA and a total of 510 small molecules with significant differences were screened using an ESI-OPLC-MS techno. AHA and SHA exerted different effects on maize growth, with the AHA inducing more effective stimulation than the SHA doing. Untargeted metabolomic analysis revealed that the phospholipid components of maize leaves treated by SHA generally increased significantly than that in the AHA and control treatments. Additionally, both HS-treated maize leaves exhibited different levels of accumulation of trans-zeatin, but SHA treatment significantly decreased the accumulation of zeatin riboside. Compared to CK treatment, AHA treatment resulted in the reorganization of four metabolic pathways: starch and sucrose metabolism, TCA cycle, stilbenes, diarylheptanes, and curcumin biosynthesis, and ABC transport, SHA treatment modified starch and sucrose metabolism and unsaturated fatty acid biosynthesis. These results demonstrate that HSs exert their function through a multifaceted mechanism of action, partially connected to their hormone-like activity but also involving hormoneindependent signaling pathways.

Abstract Maternal caretaking and transport of dead infants are widespread among nonhuman primates, having been reported in numerous species of monkeys and apes. By contrast, accounts of such behaviors toward dead juveniles are scarce. Here, we describe responses by the mother and other group members to the death of a juvenile in a wild, multi-level group of Sichuan snub-nosed monkeys (Rhinopithecus roxellana). Following the juvenile’s fatal accident, his mother transported and cared for the corpse for four days. Immature monkeys belonging to the same one-male unit, and some individuals from other social units also showed interest in and tended the corpse. Comparisons of this case with those involving the deaths of infants and an adult female in the same population highlight possible effects of physiological, psychological and emotional factors in primate thanatological responses, and provide an additional perspective on the origin and evolution of compassionate acts.

Summary: Tactical deception can be beneficial for social animals during intra-specific competition. However, the use of tactical deception in wild mammals is predicted to be rare. We tested whether a food-provisioned free-ranging band of golden snub-nosed monkeys (Rhinopithecus roxellana) use alarm calls in a functionally deceptive manner to gain access to food resources, whether the rate of deceptive alarm calls varies among individuals, and whether there are any counter-deception behaviors. We used a hexagonal camera array consisting of 10 cameras to record videos during feeding, which allowed us to identify individual alarm callers. We found evidence that these monkeys use deceptive alarms and that adult females were more likely to use such calls than other individuals. The monkeys increased their rates of response to alarm calls when competition for food was high. However, we found no direct evidence of any counter-deception strategies.

Shift of ingestive behavior is an important strategy for animals to adapt to change of the environment. We knew that shifts in animal dietary habits lead to changes in the structure of the gut microbiota, but we are not sure about if changes in the composition and function of the gut microbiota respond to changes in the nutrient intake or food items. To investigate how animal feeding strategies affect nutrient intakes and thus alter the composition and digestion function of gut microbiota, we selected a group of wild primate group for the study. We quantified their diet and macronutrients intake in four seasons of a year, and instant fecal samples were analyzed by high-throughput sequencing of 16S rRNA and metagenomics. These results demonstrated that the main reason that causes seasonal shifts of gut microbiota is the macronutrient variation induced by seasonal dietary differences. Gut microbes can help to compensate for insufficient macronutrients intake of the host through microbial metabolic functions. This study contributes to a deeper understanding of the causes of seasonal variation in host-microbial variation in wild primates.

Quantifying canopy light interception provides insight into the effects of plant spacing, canopy structure, and leaf orientation on radiation distribution. This is essential for increasing crop yield and improving product quality. Canopy light interception can be quantified using 3-dimensional (3D) plant models and optical simulations. However, virtual 3D canopy models (VCMs) have often been used to quantify canopy light interception because realistic 3D canopy models (RCMs) are difficult to obtain in the field. This study aims to compare the differences in light interception between VCMs and RCM. A realistic 3D maize canopy model (RCM) was reconstructed over a large area of the field using an advanced unmanned aerial vehicle cross-circling oblique (CCO) route and the structure from motion-multi-view stereo method. Three types of VCMs (VCM-1, VCM-4, and VCM-8) were then created by replicating 1, 4, and 8 individual realistic plants constructed by CCO in the center of the corresponding RCM. The daily light interception per unit area (DLI), as computed for the 3 VCMs, exhibited marked deviation from the RCM, as evinced by the relative root mean square error (rRMSE) values of 20.22%, 17.38%, and 15.48%, respectively. Although this difference decreased as the number of plants used to replicate the virtual canopy increased, rRMSE of DLI for VCM-8 and RCM still reached 15.48%. It was also found that the difference in light interception between RCMs and VCMs was substantially smaller in the early stage (48 days after sowing [DAS]) than in the late stage (70 DAS). This study highlights the importance of using RCM when calculating light interception in the field, especially in the later growth stages of plants.

Gut microbiota deficient mice demonstrate enhanced glucose clearance, but which tissues are responsible for this improvement are still unclear. Here the authors report that brown adipose tissue contributes to the enhanced glucose clearance in gut microbiota depleted mice and that this response is dissociated from adaptive thermogenesis.

Summary: Evolutionary and historical development and current profiles are essential to generating a tangible conservation strategy. It is also critical to distinguish the regions with vigorous potential growth from those meeting evolutionary development bottlenecks and those whose development has been severely devastated. We used two sizeable national data repositories of terrestrial fauna and flora of China to approach the issues. The results indicate that the Southwest and Coastal regions have the most significant terrestrial faunal-floral biodiversity (TFFB). Thus, they should be prioritized in conservation for great potential promotions. Although there has been remarkable evolutionary development, the Central region has been severely devastated. A solution is to uphold a balanced association between social-economic development and TFFB sustainability. As for the Northeast and the western Northwest, there is no need to invest heavily in conservation measures. This study sheds light on exploring more practical conservation strategies regionally, nationally, and globally to achieve pragmatic goals.

The prediction of soil properties at different depths is an important research topic for promoting the conservation of black soils and the development of precision agriculture. Mid-infrared spectroscopy (MIR, 2500–25000 nm) has shown great potential in predicting soil properties. This study aimed to explore the ability of MIR to predict soil organic matter (OM) and total nitrogen (TN) at five different depths with the calibration from the whole depth (0–100 cm) or the shallow layers (0–40 cm) and compare its performance with visible and near-infrared spectroscopy (vis-NIR, 350–2500 nm). A total of 90 soil samples containing 450 subsamples (0–10 cm, 10–20 cm, 20–40 cm, 40–70 cm, and 70–100 cm depths) and their corresponding MIR and vis-NIR spectra were collected from a field of black soil in Northeast China. Multivariate adaptive regression splines (MARS) were used to build prediction models. The results showed that prediction models based on MIR (OM: RMSEp = 1.07–3.82 g/kg, RPD = 1.10–5.80; TN: RMSEp = 0.11–0.15 g/kg, RPD = 1.70–4.39) outperformed those based on vis-NIR (OM: RMSEp = 1.75–8.95 g/kg, RPD = 0.50–3.61; TN: RMSEp = 0.12–0.27 g/kg; RPD = 1.00–3.11) because of the higher number of characteristic bands. Prediction models based on the whole depth calibration (OM: RMSEp = 1.09–2.97 g/kg, RPD = 2.13–5.80; TN: RMSEp = 0.08–0.19 g/kg, RPD = 1.86–4.39) outperformed those based on the shallow layers (OM: RMSEp = 1.07–8.95 g/kg, RPD = 0.50–3.93; TN: RMSEp = 0.11–0.27 g/kg, RPD = 1.00–2.24) because the soil sample data of the whole depth had a larger and more representative sample size and a wider distribution. However, prediction models based on the whole depth calibration might provide lower accuracy in some shallow layers. Accordingly, it is suggested that the methods pertaining to soil property prediction based on the spectral library should be considered in future studies for an optimal approach to predicting soil properties at specific depths. This study verified the superiority of MIR for soil property prediction at specific depths and confirmed the advantage of modeling with the whole depth calibration, pointing out a possible optimal approach and providing a reference for predicting soil properties at specific depths.

The effects of pulsed electric fields (PEF) and blanching pretreatments on frying kinetics, oil content, color, texture, acrylamide (AA) content, and microstructure have been investigated in this paper. The total PEF pretreatment duration was tPEF = 0.2 s with an intensity of E = 1 kV/cm; blanching was studied at 85 °C for 5 min. The results demonstrated that pretreatment significantly reduced the moisture ratio and oil content by 25% and 40.33%, respectively. The total color change ΔE value of the pretreated samples was lower than that of the untreated samples. In addition, pretreatment increased the hardness of the sample after frying, and the AA content in the fried samples pretreated with PEF + blanching was reduced by approximately 46.10% (638 μg/kg). Finally, fried sweet potato chips obtained by the combined pretreatment exhibited a smoother and flatter cross-sectional microstructure.

As a precious soil resource, black soils in Northeast China are currently facing severe land degradation. Visible and near-infrared spectroscopy (vis-NIR, 350–2500 nm) and mid-infrared spectroscopy (MIR, 2500–25,000 nm) have shown great potential to predict soil properties. However, there is still limited research on using MIR in situ. The aim of this study was to explore the feasibility of in situ MIR for the prediction of soil total nitrogen (TN) and total phosphorus (TP) and to compare its performance with the use of laboratory MIR, as well as the use of in situ and laboratory vis-NIR. A total of 450 samples from 90 soil profiles, along with their in situ and laboratory spectra of MIR and vis-NIR, were collected in a field with ten different tillage and management practices in a typical black soil area of Northeast China. Partial least square regression (PLSR), random forest (RF) and multivariate adaptive regression splines (MARS) were used to generate the calibrations between the spectra and the two properties. The results showed that both MIR and vis-NIR were able to predict the TN whether in laboratory or in situ conditions, but neither of them could predict the TP quantitatively since there was no sensitive band on both spectra regarding the TP. The prediction accuracy of the TN with laboratory spectra was higher than that with in situ spectra, for both vis-NIR and MIR. The optimal prediction accuracy of the TN with laboratory MIR (RMSE = 0.11 g/kg, RPD = 3.12) was higher than that of laboratory vis-NIR (RMSE = 0.14 g/kg, RPD = 2.45). The optimal prediction accuracy of in situ MIR (RMSE = 0.20 g/kg, RPD = 1.80) was lower than that of in situ vis-NIR (RMSE = 0.16 g/kg, RPD = 2.14). The prediction performance of the spectra followed laboratory MIR > laboratory vis-NIR > in situ vis-NIR > in situ MIR. The performance of in situ MIR was relatively poor, mainly due to the fact that MIR was more influenced by soil moisture. This study verified the feasibility of in situ MIR for soil property prediction and provided an approach for obtaining rapid soil information and a reference for soil research and management in black soil areas.

The management of crop residue covering is a vital part of conservation tillage, which protects black soil by reducing soil erosion and increasing soil organic carbon. Accurate and rapid classification of corn residue-covered types is significant for monitoring crop residue management. The remote sensing technology using high spatial resolution images is an effective means to classify the crop residue-covered areas quickly and objectively in the regional area. Unfortunately, the classification of crop residue-covered area is tricky because there is intra-object heterogeneity, as a two-edged sword of high resolution, and spectral confusion resulting from different straw mulching ways. Therefore, this study focuses on exploring the multi-scale feature fusion method and classification method to classify the corn residue-covered areas effectively and accurately using Chinese high-resolution GF-2 PMS images in the regional area. First, the multi-scale image features are built by compressing pixel domain details with the wavelet and principal component analysis (PCA), which has been verified to effectively alleviate intra-object heterogeneity of corn residue-covered areas on GF-2 PMS images. Second, the optimal image dataset (OID) is identified by comparing model accuracy based on the fusion of different features. Third, the 1D-CNN_CA method is proposed by combining one-dimensional convolutional neural networks (1D-CNN) and attention mechanisms, which are used to classify corn residue-covered areas based on the OID. Comparison of the naive Bayesian (NB), random forest (RF), support vector machine (SVM), and 1D-CNN methods indicate that the residue-covered areas can be classified effectively using the 1D-CNN-CA method with the highest accuracy (Kappa: 96.92% and overall accuracy (OA): 97.26%). Finally, the most appropriate machine learning model and the connected domain calibration method are combined to improve the visualization, which are further used to classify the corn residue-covered areas into three covering types. In addition, the study showed the superiority of multi-scale image features by comparing the contribution of the different image features in the classification of corn residue-covered areas.

Abstract Maize–soybean intercropping systems are widely used in developing countries, but few studies have been performed to optimize such systems. The effects of strip width and orientation on photosynthetically active radiation (PAR) distribution characteristics were therefore determined to gain a better understanding of crop productivity in maize–soybean intercropping systems. A series of intercropping experiments incorporating different strip orientations and widths were conducted. In addition, an improved radiation transmission model was used to simulate PAR interception by the maize and soybean crops. We found that more PAR was intercepted by the soybean plants than by the maize plants when the strip orientation angle increased from 0° to 90° in the maize–soybean intercropping systems. This result was obtained in most of the main maize production areas, including those with different latitudes. The effect of strip widths within the intercropping systems also had a significant effect on PAR interception. The relative fraction of PAR intercepted ranged from 39.4% to 86% for soybean and 105.8% to 169.3% for maize. The effect of soybean strip width on leaf PAR interception was greater than that of maize strip width. These results are not only of fundamental biological importance but they also have important implications for agriculture in terms of the optimization of production in intercropping systems.

Summary: Caloric restriction is a robust intervention to increase lifespan. Giving less food (calorie restriction [CR]) or allowing free access to a diluted diet with indigestible components (calorie dilution [CD]) are two methods to impose restriction. CD does not generate the same lifespan effect as CR. We compare responses of C57BL/6 mice with equivalent levels of CR and CD. The two groups have different responses in fat loss, circulating hormones, and metabolic rate. CR mice are hungrier, as assessed by behavioral assays. Although gene expression of Npy, Agrp, and Pomc do not differ between CR and CD groups, CR mice had a distinctive hypothalamic gene-expression profile with many genes related to starvation upregulated relative to CD. While both result in lower calorie intake, CR and CD are not equivalent procedures. Increased hunger under CR supports the hypothesis that hunger signaling is a key process mediating the benefits of CR.

Specific emitter identification is a technique of extracting the radio frequency fingerprints of the received electromagnetic signal only using external feature measurements to determine the specific emitter that transmits the signal. In recent years, the related theories and practical applications of specific emitter identification have been continuously improved, and research on radio frequency fingerprinting feature extraction methods has made great progress. Based on the domestic and foreign academic achievements, this paper systematically reviews the status quo of the fingerprint feature extraction method of specific emitter identification. In addition, a new feature classification framework is proposed based on the inherent logic of fingerprint feature extraction. The classification framework combines the description characteristics of different radio frequency fingerprinting features and the correlation between them. It divides the existing radio frequency features into two main categories: direct measurement features and dimensionality reduction transform features, which have three levels. Finally, this paper analyzes and explores several potential research directions of fingerprint feature extraction, aiming to benefit the research and application of specific radiation source identification.

Abstract Background The primary aim of this study was to observe the effect of 5-ALA-mediated photodynamic therapy on oral squamous cell carcinoma in vitro. Methods SCC25 cells were divided into the observation group and the blank control group. Different concentrations of 5-ALA and SCC25 cells were co-incubated for different times, and the concentration of protoporphyrin IX was detected by flow cytometry. SCC25 cells were divided into the 5-ALA group (100 mg/L), the laser irradiation group alone, the 5-ALA plus laser irradiation group, and the blank control group (0 mg/L 5-ALA), and the methyl thiazolyl tetrazolium (MTT) solution method was used (each group was incubated for 4, 8 and 12 h in turn). The cell survival rate was calculated. Using annexin V-fluorescein isothiocyanate/propidium iodide method, the apoptosis of SCC25 cells was detected by flow cytometry. Results The level of protoporphyrin IX in SCC25 cells increased with increased concentrations of 5-ALA and length of incubation. However, after 12 h, protoporphyrin IX level in SCC25 cells was gradually stabilized, and similar effect was obtained with 100 mg/L or more 5-ALA, indicating that the level of protoporphyrin IX in SCC25 cells was determined by 5-ALA concentration and incubation time. 5-ALA plus laser irradiation exerted an inhibitory effect on the growth of SCC25 cells, which was highly associated with drug dose and incubation time. Compared with the control group, laser irradiation alone or 5-ALA alone had no effect on the apoptosis of SCC25 cells. Different concentrations of 5-ALA combined with laser irradiation showed a remarkable effect of apoptosis, and a higher apoptosis rate was seen with higher drug concentrations. Conclusion 5-ALA-mediated photodynamic therapy affects the growth of SCC25 cells in vitro, which may provide a new idea for the clinical treatment of oral squamous cell carcinoma.

In mammal herbivores, fiber digestion usually occurs predominantly in either the foregut or the hindgut. Reports of mechanisms showing synergistic function in both gut regions for the digestion of fiber and other nutrients in wild mammals are rare because it requires integrative study of anatomy, physiology, and gut microbiome. Colobine monkeys (Colobinae) are folivorous, with high-fiber foods fermented primarily in their foreguts. A few colobine species live in temperate regions, so obtaining energy from fiber during the winter is essential. However, the mechanisms enabling this remain largely unknown. We hypothesized that such species possess specialized mechanisms to enhance fiber digestion in the hindgut and studied microbial and morphological digestive adaptations of golden snub-nosed monkeys (GSMs), Rhinopithecus roxellana. which is a temperate forest colobine from central China that experiences high-thermal-energy demands while restricted to a fibrous, low-energy winter diet. We tested for synergistic foregut and hindgut fiber digestion using comparisons of morphology, microbiome composition and function, and digestive efficiency. We found that the GSM colon has a significantly greater volume than that of other foregut-fermenting colobines. The microbiomes of the foregut and hindgut differed significantly in composition and abundance. However, while digestive efficiency and the expression of microbial gene functions for fiber digestion were higher in the foregut than in the hindgut, both gut regions were dominated by microbial taxa producing enzymes to enable active digestion of complex carbohydrates. Our data suggest that both the GSM foregut and hindgut facilitate fiber digestion and that an enlarged colon is likely an adaptation to accommodate high throughput of fiber-rich food during winter.

A variety of inbred mouse strains have been used for research in metabolic disorders. Despite being inbred, they display large inter-individual variability for many traits like food intake and body weight. However, the relationship between dietary macronutrients and inter-individual variation in body weight and food intake of different mouse strains is still unclear. We investigated the association between macronutrient content of the diet and variations in food intake, body composition, and glucose tolerance by exposing five different mouse strains (C57BL/6, BALB/c, C3H, DBA/2, and FVB) to 24 different diets with variable protein, fat, and carbohydrate contents. We found only increasing dietary fat, but not protein or carbohydrate had a significant association (positive) with variation in both food intake and body weight. The highest variation in both body weight and food intake occurred with 50% dietary fat. However, there were no significant relationships between the variation in fat and lean mass with dietary protein, fat, or carbohydrate levels. In addition, none of the dietary macronutrients had significant impacts on the variation in glucose tolerance ability in C57BL/6 mice. In conclusion, the variations in food intake and body weight changes increased with the elevation of dietary fat levels.

High-throughput estimation of phenotypic traits from UAV (unmanned aerial vehicle) images is helpful to improve the screening efficiency of breeding maize. Accurately estimating phenotyping traits of breeding maize at plot scale helps to promote gene mining for specific traits and provides a guarantee for accelerating the breeding of superior varieties. Constructing an efficient and accurate estimation model is the key to the application of UAV-based multiple sensors data. This study aims to apply the ensemble learning model to improve the feasibility and accuracy of estimating maize phenotypic traits using UAV-based red-green-blue (RGB) and multispectral sensors. The UAV images of four growth stages were obtained, respectively. The reflectance of visible light bands, canopy coverage, plant height (PH), and texture information were extracted from RGB images, and the vegetation indices were calculated from multispectral images. We compared and analyzed the estimation accuracy of single-type feature and multiple features for LAI (leaf area index), fresh weight (FW), and dry weight (DW) of maize. The basic models included ridge regression (RR), support vector machine (SVM), random forest (RF), Gaussian process (GP), and K-neighbor network (K-NN). The ensemble learning models included stacking and Bayesian model averaging (BMA). The results showed that the ensemble learning model improved the accuracy and stability of maize phenotypic traits estimation. Among the features extracted from UAV RGB images, the highest accuracy was obtained by the combination of spectrum, structure, and texture features. The model had the best accuracy constructed using all features of two sensors. The estimation accuracies of ensemble learning models, including stacking and BMA, were higher than those of the basic models. The coefficient of determination (R2) of the optimal validation results were 0.852, 0.888, and 0.929 for LAI, FW, and DW, respectively. Therefore, the combination of UAV-based multisource data and ensemble learning model could accurately estimate phenotyping traits of breeding maize at plot scale.

As the important components of modern facility agriculture, both plastic greenhouses and mulching films have been widely utilized in agriculture production. Due to the similarity of spectral signatures, it remains a challenging task to separate plastic greenhouses and mulching films from each other. Meanwhile, deep learning has achieved great performance in many computer vison tasks, and has become a research hotspot in remote sensing image analysis. However, deep learning has been rarely studied for the accurate mapping of agricultural plastic covers, especially for the long-neglected issue of the separation between plastic greenhouses and mulching films. Therefore, this study aims to propose a deep learning model to detect and separate plastic greenhouses and mulching films from very high resolution (VHR) remotely sensed data, providing the agricultural plastic covered maps for relevant decision-makers. In specific, the proposed model is a dilated and non-local convolutional neural network (DNCNN), which consists of several multi-scale dilated convolution blocks and a non-local feature extraction module. The former contains a series of dilated convolutions with various dilated rates, which is to aggregate multi-level spatial features hence to account for the scale variations of land objects. While the latter utilizes a non-local module to extract the global and contextual features to further enhance the inter-class separability. Experimental results from Shenxian, China and Al-Kharj, Saudi Arabia show that the DNCNN in this study obtains a high accuracy with an overall accuracy of 89.6% and 92.6%, respectively. Compared to standard convolution, the inclusion of dilated convolution could raise the classification accuracy by 2.7%. In addition, ablation analysis shows that the non-local feature extraction module could also improve the classification accuracy by about 2%. This study demonstrates that the proposed DNCNN yields an effective approach for the accurate agricultural plastic cover mapping from VHR remotely sensed imagery.

In this study, Python Surface Energy Balance System (PySEBS) software was developed in the Python 2.7 programming language for continuous calculation of actual evapotranspiration (ETa) at regional scales. The software is based on the Surface Energy Balance System (SEBS) model, which uses basic meteorological data, MODIS remote sensing data, and Digital Elevation Model (DEM) data as the original input data and finally outputs daily-scale ETa in the form of raster data with a spatial resolution of 1 km × 1 km. To verify the reliability of the PySEBS model, the ETa of spring maize during the growing season in Jilin Province, China, from 2001 to 2020 was calculated and analyzed in this study and compared with the results of similar studies by others. The findings showed that the PySEBS model has a reasonable accuracy in estimating ETa within ±15% and is a robust model that can achieve the continuous calculation of ETa at a regional scale. Therefore, PySEBS software is a useful tool for regional irrigation scheduling and water resources management.

Exploring the effects of straw return and environmental factors on the spatiotemporal variation of soil organic matter (SOM) in black soil regions is essential for soil carbon sequestration research. However, studies seldom quantified the effects of long-term straw return on a long-term SOM variation at a regional scale in typical black soil areas. The case was conducted in one of the three major black soil regions in the Northern Hemisphere, where the straw return policy has been implemented for a long time. The study obtained the SOM spatial distribution in 2007, 2009, 2012, 2015, and 2018 with approximately 9000 samples and analyzed the effects of soil types, texture, elevation, and human management on the spatiotemporal variation. The results indicated that from the 1980s to 2007, before the straw return policy implementation, the mean SOM content decreased from 24.38 g kg−1 to 18.94 g kg−1. In contrast, the mean SOM content gradually increased from 2007 to 2018 after implementing straw return practices. In addition, the area of SOM within 20–30 g kg−1 increased gradually, with 32.2%, 40.5%, 50.2%, 49.4%, and 60.5% in 2007, 2009, 2012, 2015, and 2018, respectively. Surprisingly, the SOM within 30–40 g kg−1 emerged in 2018. The results indicated that returning straw to the field might promote SOM accumulation. However, the SOM contents in Phaezems (19.25–21.82 g kg−1) were lower than that in natural Phaezems (40–60 g kg−1), indicating severe degradation. The clay content positively correlated to SOM and was a major explanatory variable for the response of SOM to straw return. Straw return practices are promising measures in the black soil region and are worth exploring more effective approaches to allow straw return to play a better role.