High-throughput sequencing and fatty acid profile analyses of the Black Amur bream (Megalobrama terminalis) reveal variation in dietary niche associated with geographic segregation.

Fish dietary niche is a core focus, and it reflects the diversity of resources, habitats, or environments occupied by a species. However, whether geographic segregation among different populations triggers dietary diversification and concomitant fish niche shift remains unknown. In the present study, we selected the Black Amur bream (Megalobrama terminalis) is a migratory fish species that plays an important role in the material transfer and energy cycling of river ecosystems, inhabiting southern China drainage with multiple geographic populations. Here, we utilized the combined analyses of 18S rDNA high-throughput sequencing in fish gut contents and fatty acid (FA) in muscle tissues to evaluate potential spatial patterns of habitat and resource use for M. terminalis in three rivers of southern China. Our results showed that prey items of the Xijiang (XR) population (Pearl River) exhibited the highest species diversity and richness among the three geographic populations. Moreover, diet composition of M. terminalis was affected by spatial differences associated with geographic segregation. Analyses of FA biomarkers indicated that the highest levels of C16:0, C18:3n-3, and C18:2n-6c were found in Wanquan (WS) population (Wanquan River). The XR population exhibited a distinct FA profile characterized by higher amounts of arachidonic acid (ARA) and docosahexaenoic acid (DHA). The Moyang (MY) population (Moyang River) acted as the linkage between WS and XR populations and consisted of middle levels of saturated FAs (SFAs) and polyunsaturated FAs (PUFAs). The XR population displayed a greater FA niche width compared with WS population. Furthermore, we observed a close positive relationship between the niche width and α-diversity indices of dietary resources for FA proflies. Our study provides valued information to develop different conservation strategies among different populations and improve fisheries management for M. terminalis and other endemic species in local rivers.

Meta-Analysis of the Effects of Overexpressed bZIP Transcription Factors in Plants under Drought Stress.

The bZIP (basic leucine zipper) transcription factors have been identified as key regulators of plant responses to drought stress, which limits plant growth and yield. Overexpression of bZIP genes has shown potential in enhancing drought tolerance in various plant species. However, the constrained types of individual studies and inconsistencies among experimental approaches has resulted in a lack of statistical significance and limited the extrapolation of bZIP transcription factor overexpression for plant improvement. We conducted a meta-analysis to evaluate ten measured parameters of drought tolerance in bZIP transcription factor-expressing plants as well as moderators affecting the performance of transgenic plants. The results showed that seven parameters, including survival rate as well as the content of regulatory substances (proline accumulation, H2O2 concentration, CAT activity, POD activity, SOD activity and MDA accumulation), were most affected while the impact on physiological status indicators is not significant. In addition, donor/recipient species, treatment medium, duration and methods of simulating drought stress all significantly impacted the degree of drought stress tolerance in plants to some extent among the considered moderators. The findings underscore the potential of bZIP transcription factors as key targets for genetic engineering approaches aimed at improving plant resilience to water scarcity.

Fish Gut Microbiome Analysis Provides Insight into Differences in Physiology and Behavior of Invasive Nile Tilapia and Indigenous Fish in a Large Subtropical River in China.

The gut microbiome is thought to play vital roles in host fitness and local adaptation to new environments, thereby facilitating the invasion of the host species. The Nile tilapia (Oreochromis niloticus) (NT) is an aggressive and omnivorous species that competes with native fishes for food resources, and it has successfully invaded much of the Pearl River basin in China. Here, we investigated the gut microbiomes of invasive Nile tilapia and indigenous black Amur bream (BA) in the same river section using high-throughput 16S rRNA gene sequencing. The results indicated that the gut microbiome of NT had several special characteristics, e.g., higher alpha diversity and greater niche breadth, compared with the bream. The gut microbiota of the small size of Nile tilapia (NTS) and small size of black Amur bream (BAS) groups were dominated by Proteobacteria, while those of the NTS and large size of Nile tilapia (NTL) and BAS and large size of black Amur bream (BAL). BAL and NTL were characterized by Firmicutes and Fusobacteriota, respectively. We found that Pseudomonas, Cetobacterium, Ralstonia, and Romboutsia were biomarkers of the NTS, NTL, BAS, and BAL groups, respectively. Moreover, the results collectively suggested that the clustering coefficients of BAL and NTL networks were greater than those of BAS and NTS networks, and BAS had the smallest network among the four groups. Positive interactions between two ASVs dominated the BAS, NTS, and NTL networks, while the proportion of negative interactions between two ASVs in the BAL network was remarkably increased. Low levels of interspecies competition in the NT gut microbiome would contribute to high diversity in the dietary niches and would also benefit the survival and local adaptation of the host. Our results identified specific biomarkers of gut microbial species in invasive Nile tilapia and provided useful information concerning how to monitor and manage invasive Nile tilapia populations.

LANet: Stereo matching network based on linear-attention mechanism for depth estimation optimization in 3D reconstruction of inter-forest scene.

The 3D reconstruction of forests provides a strong basis for scientific regulation of tree growth and fine survey of forest resources. Depth estimation is the key to the 3D reconstruction of inter-forest scene, which directly determines the effect of digital stereo reproduction. In order to solve the problem that the existing stereo matching methods lack the ability to use environmental information to find the consistency of ill-posed regions, resulting in poor matching effect in regions with weak texture, occlusion and other inconspicuous features, LANet, a stereo matching network based on Linear-Attention mechanism is proposed, which improves the stereo matching accuracy by effectively utilizing the global and local information of the environment, thereby optimizing the depth estimation effect. An AM attention module including a spatial attention module (SAM) and a channel attention module (CAM) is designed to model the semantic relevance of inter-forest scenes from the spatial and channel dimensions. The linear-attention mechanism proposed in SAM reduces the overall complexity of Self-Attention from O(n 2) to O(n), and selectively aggregates the features of each position by weighted summation of all positions, so as to learn rich contextual relations to capture long-range dependencies. The Self-Attention mechanism used in CAM selectively emphasizes interdependent channel maps by learning the associated features between different channels. A 3D CNN module is optimized to adjust the matching cost volume by combining multiple stacked hourglass networks with intermediate supervision, which further improves the speed of the model while reducing the cost of inferential calculation. The proposed LANet is tested on the SceneFlow dataset with EPE of 0.82 and three-pixel-error of 2.31%, and tested on the Forest dataset with EPE of 0.68 and D1-all of 2.15% both of which outperform some state-of-the-art methods, and the comprehensive performance is very competitive. LANet can obtain high-precision disparity values of the inter-forest scene, which can be converted to obtain depth information, thus providing key data for high-quality 3D reconstruction of the forest.

Gut microbiomes of cyprinid fish exhibit host-species symbiosis along gut trait and diet.

Teleost omnivorous fish that coexist partially sharing resources are likely to modify their gut traits and microbiome as a feedback mechanism between ecological processes and evolution. However, we do not understand how the core gut microbiome supports the metabolic capacity of the host and regulates digestive functions in specialized omnivorous fish gut traits. Therefore, we evaluated the gut microbiome of eight omnivorous fish from a single family (i.e., Cyprinidae) in the current study. We examined the correlation between host phylogeny, diet composition, and intestinal morphological traits related to the intestinal microbiome. The results indicated that cyprinid fish with similar relative gut lengths had considerable gut microbiome similarity. Notably, the SL (short relative gut length) group, as zoobenthos and zooplankton specialists, was abundant in Proteobacteria and was less abundant in Firmicutes than in the ML (medium relative gut length) and LL (long relative gut length) groups. These fish could extract nutrients from aquatic plants and algae. Additionally, we found the relative abundance of Clostridium and Romboutsia to be positively correlated with host relative gut length but negatively correlated with the relative abundance of Cetobacterium, Plesiomonas, Bacteroides, and Lactobacillus, and host-relative gut length. We also show a positive linear relationship between host gut microbiome carbohydrate metabolism and relative gut length, while the amino acid and lipid metabolism of the gut microbiome was negatively correlated with host-relative gut length. In addition, omnivorous species competing for resources improve their ecological adaptability through the specialization of gut length, which is closely related to variation in the synergy of the gut microbiome. Above all, specialized gut microbiota and associated gut morphologies enable fish to variably tolerate resource fluctuation and improve the utilization efficiency of nutrient extraction from challenging food resources.

Continuous Flat Pressing of MDF Quality Control Model Framework and Collaborative Programming Approach Based on Wood Fiber Hot Pressing Mechanism.

The increasing demand for forestry resources is driving the need for smarter systems capable of saving and protecting forests that can optimize agile forestry production. This study uses the continuous hot-pressing process of wooden medium-density fiberboard (MDF) to investigate the possibility of automatic quality control of the continuous flat pressing process. For this purpose, conceptual digital twin modeling for mechanism and sequence parameter control was conducted based on the cellular automata (CA) theory. A distributed coordination mode framework was constructed, and a craft control programming method was proposed for the quality control of MDF continuous flat pressing. Based on the MDF continuous flat press craft mechanism and control standards, a framework of five distributed flat press cooperative control mode elements for the cylinder array of the continuous panel system (CPS) was defined. To satisfy the distributed distance servo and pressure servo demands of the multi-stage hot pressing craft design, five kinds of synergy collaborative control modes of multiple rack groups were constructed using mode elements: For the four types of typical deviations in slab production, i.e., thickness, slope, depression, and bulge, a multi-zone mutual cooperative mode craft control sequence was programmed. According to the type and intensity of real-time deviation, the corresponding regulation sequence was applied. This effectively counteracts the deviation caused by the uncertainty interference due to the multi-field coupling effect in actual production. The application tests demonstrate that the adjustment and response time of the continuous flat press were greatly improved, and the quality superiority rate is controlled above 95%, thereby confirming the effectiveness of the control strategy.

Gut Microbiome Analyses of Wild Migratory Freshwater Fish (Megalobrama terminalis) Through Geographic Isolation.

Gut microbiome is considered as a critical role in host digestion and metabolic homeostasis. Nevertheless, the lack of knowledge concerning how the host-associated gut microbiome underpins the host metabolic capability and regulates digestive functions hinders the exploration of gut microbiome variation in diverse geographic population. In the present study, we selected the black Amur bream (Megalobrama terminalis) that inhabits southern China drainage with multiple geographic populations and relatively high digestive plasticity as a candidate to explore the potential effects of genetic variation and environmental discrepancy on fish gut microbiome. Here, high-throughput 16S rRNA gene sequencing was utilized to decipher the distinct composition and diversity of the entire gut microbiota in wild M. terminalis distributed throughout southern China. The results indicated that mainland (MY and XR) populations exhibited a higher alpha diversity than that of the Hainan Island (WS) population. Moreover, a clear taxon shift influenced by water temperature, salinity (SA), and gonadosomatic index (GSI) in the course of seasonal variation was observed in the gut bacterial community. Furthermore, geographic isolation and seasonal variation significantly impacted amino acid, lipid, and carbohydrate metabolism of the fish gut microbiome. Specifically, each geographic population that displayed its own unique regulation pattern of gut microbiome was recognized as a specific digestion strategy to enhance adaptive capability in the resident environment. Consequently, this discovery suggested that long-term geographic isolation leads to variant environmental factors and genotypes, which made a synergetic effect on the diversity of the gut microbiome in wild M. terminalis. In addition, the findings provide effective information for further exploring ecological fitness countermeasures in the fish population.

Research on Quantitative Evaluation of Remote Sensing and Statistics Based on Wireless Sensors and Farmland Soil Nutrient Variability.

The combination of wireless sensor networks and radio technology can form a new type of communication network. The emergence of wireless sensor networks has effectively solved the problems existing in radio technology, but traditional wireless sensor networks and radio technology networks cannot be directly applied to wireless sensors. On this basis, this paper studies the remote sensing of soil nutrient variability in agricultural land using wireless sensors. Due to traditional farmland management and agricultural systems, farmland soil nutrient variability has led to polarization: fertile soil has excess nutrients, reducing the use rate of chemical fertilizers and polluting high-quality farmland. Traditional farming methods can no longer meet the requirements, and modern technology must be used to comprehensively understand the spatiotemporal variability of soil nutrients during plant growth. Remote sensing technology has the advantages of accuracy, speed, economy, and regular monitoring. It provides new ideas and technical guarantees for soil quality evaluation in land development and consolidation projects. This paper also studies the use of statistical quantitative evaluation technology to carry out multidimensional statistical quantification of soil protection function evaluation at a given location. Finally, wireless sensor networks are used to analyze the relationship between several natural factors and quantitative estimation of soil protection. Based on wireless sensor technology, this paper studies the variability of farmland soil nutrients and statistical quantitative evaluation, hoping to lay a foundation for the development of agriculture and statistics.

The gut microbiome composition and degradation enzymes activity of black Amur bream (Megalobrama terminalis) in response to breeding migratory behavior.

Black Amur bream (Megalobrama terminalis), a dominant species, resides in the Pearl River basin, known for its high plasticity in digestive ability. During spawning season, M. terminalis individuals with large body size and high fertility undergo a spawn migratory phase, while other smaller individuals prefer to settlement over migration. It is well known that gut microbial community often underpins the metabolic capability and regulates a wide variety of important functions in fish. However, little was known about how the gut microbiomes affect fish breeding migration. To investigate the variations in the gut microbiome of M. terminalis during the migration, we used high-throughput 16S rRNA gene sequencing to reveal the distinct composition and diversity of the whole gut microbiome of migrated and nonmigrated population during period of peak reproduction, respectively. Our results indicated that nonmigrated population in estuary had a higher alpha diversity than that of migrated population in main stem. Additionally, an obvious abundant taxa shift between the gut microbiota community of nonmigrated and migrated M. terminalis was also observed. Change of dominant gut taxa from nonmigrated to migrated population was thought to be closely related to their degradation enzymes. Our results suggested that amino acid metabolism and lipid metabolism in migrated population were higher than that in nonmigrated population, providing a line of evidence for that M. terminalis change from partial herbivorous to partial carnivorous diet during breeding migration. We further concluded that, in order to digest foods of higher nutrition to supply energy to spawning migration, M. terminalis regulate activities of the gut microbiome and degradation enzymes, considered to be a key physiological strategy for reproduction.

Effect of hypoxia and air-breathing restricted on respiratory physiology of air-breathing loach (Paramisgurnus dabryanus).

This aim of this study was to determine the respiratory physiology response in the gill and gut of Paramisgurnus dabryanus under different breathing treatment patterns. The experimental design included the following three conditions: a control group without any stress treatments, an inhibited group with intestinal respiration inhibited, and an air-exposed group with gill respiration inhibited. The results indicated that the total static metabolic rate in the air-exposed group (188.92 ± 13.67 mg h-1 kg-1) was much higher than that of the other group after 7 days, decreased significantly after the first day of recovery (81.64 ± 7.85 mg h-1 kg-1). The air metabolic rate in the air-exposed group increased significantly after 7 days (P < 0.05). There was no significant difference among the groups. Histological observation on the gill and hindgut of P. dabryanus showed that the gill filament area of inhibited group became larger, while the gill structure of air exposed group showed some damage. The number of capillariesin the hindgut mucosal epithelial in air-exposed group showed a rapidly increase (P < 0.05). Likewise, the gas diffusion distance (1.24 ± 0.36 µm) became significantly shorter (P < 0.05). Lactate dehydrogenase activity of gill in the air-exposed group (846.68 ± 88.78 U mg-1 protein) significantly increased after 7 days whereas succinate dehydrogenase (1.02 ± 0.21 U mg-1 protein) and Na+/K+ ATPase (0.57 ± 0.20 U mg-1 protein) activity decreased significantly (P < 0.05). However, there was no significant change in the hindgut. After recovery, there was no significant difference in lactate dehydrogenase, succinate dehydrogenase, and Na+/K+ ATPase activity in the gill or hindgut in groups. P. dabryanus had a high viability in air-exposed condition. When recovery occurred under normoxic conditions, the physical levels of respiration returned back to the normal level quickly.

TRB3 regulates pulmonary interstitial fibrosis through the MAPK signaling pathway.

This study aims to investigate the effects of TRB3 on the EMT and MAPK signaling pathways in a bleomycin (BLM)-induced pulmonary fibrosis mouse model. TRB3 adenovirus vector with green fluorescent protein (GFP) and TRB3-siRNA adenovirus vector were constructed for overexpression and down-regulation of TRB3, respectively. The pulmonary fibrosis mouse model was induced by bleomycin, and then treated with adenovirus on the next day. The mice were randomly killed at the 7th (D7), 14th (D14) and 28th (D28) day, respectively. The lung tissues were collected for histopathologic observations, hydroxyproline determination, Immunohistochemistry, western blot and RT-qPCR to detect the expression of TRB3 and EMT-related proteins. Overexpression of TRB3 caused more severe pulmonary fibrosis (P<0.05), while downregulation of TRB3 significantly reduced pulmonary fibrosis (P<0.05). The expression of MAPK pathway-related and EMT-related genes and proteins was markedly upregulated by TRB3 overexpression (P<0.05), but prominently downregulated by TRB3-shRNA (P<0.05). In conclusion, exogenous regulation of TRB3 may have effects on bleomycin-induced pulmonary fibrosis in mice.

Data-Prefetching Scheme Based on Playback Delay and Positioning Satisfaction in Peer-To-Peer Video-On-Demand System.

As one of the most important applications in peer-to-peer (P2P) networks, the video-on-demand (VoD) system freely supports video cassette recorder (VCR) operation for users. However, the users may experience significant playback delay after frequent VCR operations in the VoD system, which will affect the quality of experience (QoE) of the users. Hence, selecting an appropriate data-prefetching strategy to support better VCR operation is an important approach to improve the QoE. This paper proposes a data-prefetching strategy (DSA) to determine the most suitable anchor interval by considering the playback delay and positioning satisfaction. According to the DSA, we use the multiple-attribute decision-making (MADM) theory to model the selection of intervals of prefetching data blocks (i.e., anchor interval) and the technique for ordering preference by similarity to an ideal solution (TOPSIS) algorithm to solve the MADM. The simulation results show that the DSA strategy obtains higher positioning satisfaction than the existing schemes, which is approximately 60% higher than the anchor points, popular parts of video, and user interests (API)-based method. Moreover, with the increase in network bandwidth, the DSA strategy can minimize the playback delay after VCR operation using relative few extra bandwidths.

Prediction of Soil Salinity Using Near-Infrared Reflectance Spectroscopy with Nonnegative Matrix Factorization.

As a key, yet difficult, issue currently in the quantitative remote sensing analysis of soil, the accurate and stable monitoring of soil salinity content (SSC) in situ should be studied and improved. The purpose of this study is to explore the method of fusing spectra outdoors with spectra indoors and improve the estimation precision of SSC based on near-infrared (NIR) reflectance hyper-spectra. First, samples of saline soil from the Yellow River delta of China were collected and analyzed. We measured three groups of sample spectra using a spectrometer: (1) situ-spectra, measured at sampling points in situ; (2) out-spectra, measured outdoors on air-dried samples; and, (3) lab-spectra, measured in a dark laboratory with the above air-dried samples. Second, four algorithms (multiplicative update, alternating least-squares, sparse affine non-negative matrix factorization (NMF), and gradient projection algorithms) of NMF were used to fuse the situ-spectra or out-spectra with the lab-spectra for the calibration of SSC. Finally, estimation models of SSC were built using the multiple linear regression method based on the first derivatives of the un-fused and fused spectra. The results indicate that using the NMF method to fuse the situ-spectra or out-spectra with the lab-spectra can heighten the correlation between SSC and the outdoor spectra in most wavelength ranges and improve the accuracy of the prediction model. The gradient projection algorithm shows the best performance with fewer variables and highest accuracy of the SSC model based on the NIR spectra.

[Relationship between soluble intercellular adhesion molecule-1 and severe pneumonia].

OBJECTIVE: It has been reported that soluble intercellular adhesion molecule-1 (sICAM-1) participates in many immune and inflammatory reactions. Its expression and role in severe pneumonia has not fully been understood. This study aimed to investigate the changes of sICAM-1 expression in severe pneumonia and the relationship between sICAM-1 and severe pneumonia in children. METHODS: Serum sICAM-1 levels were determined by the double antibody sand using ELISA in 50 children with severe pneumonia and 56 children with mild pneumonia. Fifty-two healthy children served as control group. RESULTS: Serum sICAM-1 levels in children with severe pneumonia (402.36 +/- 31.24 mu g/L) were remarkably higher than those in the mild pneumonia group (278.86 +/- 36.24 mu g/L) at the acute stage and higher than in the control group (180.74 +/- 21.46 mu g/L) (P < 0.01). Serum sICAM-1 levels in children with severe pneumonia decreased significantly at the recovery stage (198.56 +/- 12.63 mu g/L) (P < 0.01), which were not statistically different from those in the mild pneumonia group at the recovery stage and the control group. There were no significant differences in serum sICAM-1 levels among the severe pneumonia subgroups caused by different pathogens (bacteria, virus or Mycoplasma) at the acute stage. Serum sICAM-1 levels at the acute stage in children with severe pneumonia who were treated successfully were not significantly different from those in patients whose symptoms were partly improved. CONCLUSIONS: sICAM-1 might be involved in the inflammation course of severe pneumonia. It can severe as a marker of the diagnosis and the severity evaluation of severe pneumonia.