Search

The Chinese Christian community occupies an essential position in the pluralistic religious landscape of modern Singapore, which is known as a multicultural and multiracial immigrant society. Despite being a minority compared with Buddhists and Taoists in Singapore, the historical formation and contemporary existence of the Chinese Christian community in Singapore not only embodies religious diversity, but also contributes significantly to Singapore’s social development. This paper zooms into the founding and evolution of the Jubilee Church to see how Chinese Christians contributed to the revolutionary cause, took part in the anti-opium movement, and advanced educational activities in Singapore. Particularly, by establishing the Singapore Reading Room, participating in the founding of the Anti-Opium Society and the Chinese Kindergarten, the Jubilee Church played an important role in Singapore’s history, contributing to the modernization of Singapore in terms of advancing ideas, improving social order, and promoting education. We aim to shed light on how Chinese Christians were engaged in social activities, taking up significant roles in the transformation of the Chinese diaspora in Singapore. More importantly, we argue that these varied social engagements significantly impacted the development of Christianity. Through a detailed historical case study on the Jubilee Church, this paper proposes that social functions and religious evangelization are mutually constitutive, thus complicating our understanding of the entangled relationship among Chinese diaspora, Christianity, and motherland China.

Plants generate a range of physiological and molecular responses to sustain their growth and development when suffering heat stress. Avocado is a type of tropical fruit tree with high economic value. Most avocado cultivars delete, wither, or even die when exposed to heat stress for a long time, which seriously restricts the introduction and cultivation of avocados. In this study, samples of a heat-intolerant variety (‘Hass’) were treated under heat stress, and the transcriptomics and metabolomics were analyzed, with the expectation of providing information on the variety improvement and domestication of avocados. The differentially expressed genes identified using transcriptome analysis mainly involved metabolic pathways such as plant hormone signal transduction, plant–pathogen interaction, and protein processing in the endoplasmic reticulum. Combined transcriptome and metabolome analysis indicated that the down-regulation of Hass.g03.10206 and Hass.g03.10205 in heat shock-like proteins may result in the reduced Trehalose and Sinapoyl aldehyde content. Metabolomics analysis results indicated that the decrease in Trehalose and Sinapoyl aldehyde content may be an important factor for heat intolerance. These results provide important clues for understanding the physiological mechanisms of adaptation to heat stress in avocados.

Oncidium hybridum Lodd. is an important ornamental flower that is used as both a cut flower and a potted plant around the world; additionally, its pseudobulbs serve as essential carriers for floral organs and flower development. The NAM gene family is crucial for managing responses to various stresses as well as regulating growth in plants. However, the mechanisms by which NAM genes regulate the development of pseudobulbs remain unclear. In this study, a total of 144 NAM genes harboring complete structural domains were identified in O. hybridum. The 144 NAM genes were systematically classified into 14 distinct subfamilies via phylogenetic analysis. Delving deeper into the conserved motifs revealed that motifs 1–6 exhibited remarkable conservation, while motifs 7–10 presented in a few NAM genes only. Notably, NAM genes sharing identical specific motifs were classified into the same subfamily, indicating functional relatedness. Furthermore, the examination of occurrences of gene duplication indicated that the NAM genes display 16 pairs of tandem duplications along with five pairs of segmental duplications, suggesting their role in genetic diversity and potential adaptive evolution. By conducting a correlation analysis integrating transcriptomics and metabolomics at four stages of pseudobulb development, we found that OhNAM023, OhNAM030, OhNAM007, OhNAM019, OhNAM083, OhNAM047, OhNAM089, and OhNAM025 exhibited significant relationships with the endogenous plant hormones jasmonates (JAs), hinting at their potential involvement in hormonal signaling. Additionally, OhNAM089, OhNAM025, OhNAM119, OhNAM055, and OhNAM136 showed strong links with abscisic acid (ABA) and abscisic acid glucose ester (ABA-GE), suggesting the possible regulatory function of these NAM genes in plant growth and stress responses. The 144 NAM genes identified in this study provide a basis for subsequent research and contribute to elucidating the intricate molecular mechanisms of NAM genes in Oncidium and potentially in other species.

Stakeholder management is a crucial component in the implementation of off-site construction (OSC) projects, while stakeholder mapping serves as a practical technique to facilitate an in-depth understanding of different project stakeholders. Various topics have been explored in the OSC stakeholder management field, but research on OSC stakeholder analysis based on stakeholder mapping is still lacking. This study addresses this gap by developing two-dimensional (2D) and three-dimensional (3D) stakeholder mapping models. Data were collected from 167 stakeholders involved in OSC projects. The 2D model utilizes a power–interest matrix to classify 12 identified OSC stakeholder groups, while the 3D model further explores these groups by incorporating an additional dimension of stakeholder salience across different stages of project implementation. The results show that OSC stakeholders predominantly fall into the “key players” or “minimal effort” categories across various project stages. Key players include the client, modular manufacturer, main contractor, government, and designer, while the public and industry organizations generally require minimal effort. Additionally, stakeholders such as the supervision company, supplier, and subcontractor play key roles at specific stages, with varying levels of salience throughout the project lifecycle, reflecting shifts in their influence and involvement. The findings contribute to stakeholder management knowledge by providing an in-depth understanding of OSC stakeholders’ interrelationships during project implementation, especially through uncovered stakeholder mapping in the OSC field.

Effective supply and demand matching for construction materials is a crucial challenge in large-scale railway projects, particularly in complex and hazardous environments. We propose a two-stage stochastic programing model that incorporates environmental uncertainties, such as natural disasters, into the supply chain optimization process. The first stage determines optimal locations and capacities for material supply points, while the second stage addresses material distribution under uncertain demand. We further enhance the model’s efficiency with Benders decomposition algorithm. The performance of our model is rigorously compared with existing optimization approaches, demonstrating its superior capability in handling environmental uncertainties and complex logistical scenarios. This study provides a novel framework for optimizing supply chains in challenging environments, offering significant improvements over traditional models in both adaptability and robustness.

Improving drought tolerance in plants is essential for increasing crop yields under water-limited conditions. In this study, we investigated the functional role of the maize gene ZmDST44, which is targeted by the miRNA ZmmiR139. Our results indicate that ZmmiR139 regulates ZmDST44 by cleaving its mRNA, as confirmed by inverse expression patterns and 5′-RACE analysis. Overexpression of ZmDST44 in Arabidopsis, rice, and maize resulted in significant enhancements in drought tolerance. Transgenic plants exhibited reduced malondialdehyde (MDA) levels, increased proline accumulation, and upregulation of drought-responsive genes compared to wild-type plants. Transgenic Arabidopsis and rice showed improved drought resistance and higher post-drought recovery rates, and transgenic maize displayed lower sensitivity to drought stress. These findings suggest that ZmDST44 acts as a positive regulator of drought tolerance across different plant species and holds promise for developing drought-resistant crops through genetic engineering.

The SAUR (small auxin-up RNA) family constitutes a category of genes that promptly respond to the hormone auxin and play a pivotal role in diverse biological processes encompassing plant growth and the response to abiotic stress. Santalum album L., a semi-parasitic evergreen tree, is renowned for its economically valuable essential oils, positioning it among the most prized tree species. In this study, a meticulous identification and comprehensive analysis of 43 SAUR genes was conducted within S. album. Based on phylogenetic relationships, the SaSAUR genes were systematically categorized into five groups. A collinearity analysis revealed intriguing insights, disclosing 14 segmental duplications and 9 tandem duplications within the SaSAUR genes, emphasizing the pivotal role of duplication in the expansion of this gene family. Noteworthy variations in the expression levels of SaSAUR genes were observed by delving into the SaSAUR transcriptome data from various tissues, including leaves, roots, and heartwood, as well as under salt-stress conditions. Notably, SaSAUR08 and SaSAUR13 were significantly upregulated in heartwood compared with roots and leaves, while SaSAUR18 was markedly more expressed in roots compared with heartwood and leaves. Furthermore, SaSAUR27 and SaSAUR28 were found to respond closely to salt stress, hinting at their potential involvement in the salt-stress response mechanism. This research offers a comprehensive investigation of SAUR genes in S. album and establishes a foundation for future exploration of the SAUR gene family, particularly its relation to growth and salt-stress responses.

With the rapid development of the electric vehicle industry, the widespread utilization of lithium-ion batteries has made it imperative to address their safety issues. This paper focuses on the thermal safety concerns associated with lithium-ion batteries during usage by specifically investigating high-capacity lithium iron phosphate batteries. To this end, thermal runaway (TR) experiments were conducted to investigate the temperature characteristics on the battery surface during TR, as well as the changes in battery mass and expansion rate before and after TR. Meanwhile, by constructing a TR simulation model tailored to lithium iron phosphate batteries, an analysis was performed to explore the variations in internal material content, the proportion of heat generation from each exothermic reaction, and the influence of the heat transfer coefficient during the TR process. The results indicate that as the heating power increases, the response time of lithium-ion batteries to TR advances. Furthermore, the heat released from the negative electrode–electrolyte reaction emerges as the primary heat source throughout the entire TR process, contributing to 63.1% of the total heat generation.

Currently, cutting-edge, high-frequency current sources are limited by switching devices and wire materials, and the output current cannot take into account the demands of a high peak and low rise time at the same time. Based on the output demand of a current source, a non-inductive coil for providing high-frequency, high current sources with low rise times is designed. The coil is appropriately designed according to the principle of the ampere-turn method, where several turns of wire are utilized to linearly synthesize the current to obtain high-frequency currents with amplitudes up to 30 kA. However, the inductance formed after winding the coil could possess a hindering effect on the high-frequency current. In the present investigation, based on the law of energy conservation and utilizing the principle of transformer coupling, the inductor’s hindering effect on high-frequency currents is appropriately eliminated by consuming the stored energy of the inductor innovatively. Theoretical calculations and practical tests show that the inductance of a two-layer 28-turn coil is 42 times smaller than that of a two-layer, 28-turn perfect circular spiral PCB coil. The measured inductance is only 6.69 μH, the output current amplitude is calculated to be up to 33 kA with a rise time of 20 ns, and the output waveform corresponding to a 1 MHz square wave is not remarkably distorted. This effective design idea could be very helpful in solving the problem of high peak values and low rise times in high-frequency, high-current source output design.

It is essential to establish a digital twin scene, which helps to depict the dynamically changing geographical environment accurately. Digital twins could improve the refined management level of intelligent tunnel construction; however, research on geographical twin models primarily focuses on modeling and visual description, which has low analysis efficiency. This paper proposes a knowledge-guided intelligent analysis method for the geometric deformation of tunnel excavation profile twins. Firstly, a dynamic data-driven knowledge graph of tunnel excavation twin scenes was constructed to describe tunnel excavation profile twin scenes accurately. Secondly, an intelligent diagnosis algorithm for geometric deformation of tunnel excavation contour twins was designed by knowledge guidance. Thirdly, multiple visual variables were jointly used to support scene fusion visualization of tunnel excavation profile twin scenes. Finally, a case was selected to implement the experimental analysis. The experimental results demonstrate that the method in this article can achieve an accurate description of objects and their relationships in tunnel excavation twin scenes, which supports rapid geometric deformation analysis of the tunnel excavation profile twin. The speed of geometric deformation diagnosis is increased by more than 90% and the cognitive efficiency is improved by 70%. The complexity and difficulty of the deformation analysis operation are reduced, and the diagnostic analysis ability and standardization of the geographic digital twin model are effectively improved.

Recent studies have introduced transformer modules into convolutional neural networks (CNNs) to solve the inherent limitations of CNNs in global modeling and have achieved impressive performance. However, some challenges have yet to be addressed: first, networks with simple connections between the CNN and transformer perform poorly in small change areas; second, networks that only use transformer structures are prone to attaining coarse detection results and excessively generalizing feature boundaries. In addition, the methods of fusing the CNN and transformer have the issue of a unilateral flow of feature information and inter-scale communication, leading to a loss of change information across different scales. To mitigate these problems, this study proposes a full-scale connected CNN–Transformer network, which incorporates the Siamese structure, Unet3+, and transformer structure, used for change detection in remote sensing images, namely SUT. A progressive attention module (PAM) is adopted in SUT to deeply integrate the features extracted from both the CNN and the transformer, resulting in improved global modeling, small target detection capacities, and clearer feature boundaries. Furthermore, SUT adopts a full-scale skip connection to realize multi-directional information flow from the encoder to decoder, enhancing the ability to extract multi-scale features. Experimental results demonstrate that the method we designed performs best on the CDD, LEVIR-CD, and WHU-CD datasets with its concise structure. In particular, based on the WHU-CD dataset, SUT upgrades the F1-score by more than 4% and the intersection over union (IOU) by more than 7% compared with the second-best method.

The transformation of CO/CO2 hydrogenation into high-density sustainable aviation fuel (SAF) represents a promising pathway for carbon emission reduction in the aviation industry but also serves as a method for renewable energy assimilation. However, current hydrocarbon products synthesized through CO/CO2 often focus on various catalytic paths with high selectivity and high conversion rates rather than the synthesis of SAFs with complex components. This study undertakes a thermodynamic investigation into the direct or indirect synthesis of SAFs from CO/CO2 hydrogenation. By analyzing the synthesis of seven aviation fuels defined by the American Society for Testing and Materials (ASTM) D7566 standard, our study reveals a temperature-dependent reduction in the reaction driving force for all products. Specifically, for CO, ΔG transitions from approximately −88.6 J/(mol·K) at 50 °C to 26.7 J/(mol·K) at 500 °C, with the switch from negative to positive values occurring around 390 °C. Similarly, for CO2, ΔG values change from approximately −66.7 J/(mol·K) at 50 °C to 37.3 J/(mol·K) at 500 °C, with the transition point around 330 °C. The thermodynamic favorability for various hydrocarbon products synthesized is also examined, highlighting a transition at temperatures of around 250 °C, beyond which the thermodynamic drive for the synthesis of aromatic compounds increasingly surpasses that of cycloparaffin synthesis. Our findings also underscore that the products with a higher aromatic content yield a lower H2/CO2 ratio, thus reducing hydrogen consumption. The influence of cycloparaffin and aromatic proportions in the typical SAF products on the ΔG is also explored, revealing that an increase in cycloparaffin content in SAFs slightly elevates the ΔG, whereas an increase in aromatic content significantly reduces ΔG, thereby markedly enhancing the thermodynamic drive of the CO/CO2 hydrogenation reaction. These findings underscore the thermodynamic preference for synthesizing SAF with a higher proportion of aromatic compounds, shedding light on potential pathways for optimizing fuel synthesis to improve efficiency. Finally, the thermodynamic challenges and potential solutions involved in synthesizing SAFs via specific intermediate compounds are discussed, presenting opportunities for more strategic process schemes in industrial scenarios.

Pancreatic ductal adenocarcinoma (PDAC), one of the deadliest malignancies worldwide, is characteristic of the tumor microenvironments (TME) comprising numerous fibroblasts and immunosuppressive cells. Conventional therapies for PDAC are often restricted by limited drug delivery efficiency, immunosuppressive TME, and adverse effects. Thus, effective and safe therapeutics are urgently required for PDAC treatment. In recent years, hydrogels, with their excellent biocompatibility, high drug load capacity, and sustainable release profiles, have been developed as effective drug-delivery systems, offering potential therapeutic options for PDAC. This review summarizes the distinctive features of the immunosuppressive TME of PDAC and discusses the application of hydrogel-based therapies in PDAC, with a focus on how these hydrogels remodel the TME and deliver different types of cargoes in a controlled manner. Furthermore, we also discuss potential drug candidates and the challenges and prospects for hydrogel-based therapeutics for PDAC. By providing a comprehensive overview of hydrogel-based therapeutics for PDAC treatment, this review seeks to serve as a reference for researchers and clinicians involved in developing therapeutic strategies targeting the PDAC microenvironment.

Dalbergia odorifera is a valuable material used in the crafting of luxury furniture, and the chemical constituents from heartwood possess significant medicinal value. The WRKY gene family, one of the most extensively studied gene families, plays an important role in plants. However, a comprehensive genome-wide identification of the WRKY gene family in D. odorifera has not been reported yet. In this study, a total of 99 WRKY genes were identified in D. odorifera. The DoWRKY genes were categorized into three primary groups with five subgroups. A collinearity analysis revealed 38 segmental duplications and 3 tandem duplications within the DoWRKY genes, indicating the pivotal role of segmental duplication in gene family expansion. Through the analysis of DoWRKY transcriptomic data across diverse tissues and under wounding stress, we found that only eight genes were universally expressed, while a subset displayed distinct tissue-specific patterns. Notably, DoWRKY41 was exclusively expressed in leaves; DoWRKY04 was solely in roots; and DoWRKY17, DoWRKY28, DoWRKY47, and DoWRKY67 were uniquely in flowers. Furthermore, we identified 24 WRKY proteins that tightly respond to wounding stress (20 upregulated; 4 downregulated). This comprehensive investigation offered valuable insights into the WRKY gene family of D. odorifera, serving as a foundational resource for forthcoming explorations into the functional roles of these genes amid wounding stress.

The mechanism of long-term cognitive impairment after neonatal sepsis remains poorly understood, although long-lasting neuroinflammation has been considered the primary contributor. Necroptosis is actively involved in the inflammatory process, and in this study, we aimed to determine whether neonatal sepsis-induced long-term cognitive impairment was associated with activation of necroptosis. Rat pups on postnatal day 3 (P3) received intraperitoneal injections of lipopolysaccharide (LPS, 1 mg/kg) to induce neonatal sepsis. Intracerebroventricular injection of IL-1β-siRNA and necrostatin-1 (NEC1) were performed to block the production of IL-1β and activation of necroptosis in the brain, respectively. The Morris water maze task and fear conditioning test were performed on P28–P32 and P34–P35, respectively. Enzyme-linked immunosorbent assay (ELISA), quantitative real-time PCR (RT-PCR), and Western blotting were used to examine the expression levels of proinflammatory cytokines and necroptosis-associated proteins, such as receptor-interacting protein 1 (RIP1) and receptor-interacting protein 3 (RIP3). Sustained elevation of IL-1β level was observed in the brain after initial neonatal sepsis, which would last for at least 32 days. Sustained necroptosis activation was also observed in the brain. Knockdown of IL-1β expression in the brain alleviated necroptosis and improved long-term cognitive function. Direct inhibition of necroptosis also improved neurodevelopment and cognitive performance. This research indicated that sustained activation of necroptosis via IL-1β contributed to long-term cognitive dysfunction after neonatal sepsis.

In recent years, the diffusive gradients in the thin films (DGT) technique has also been increasingly applied to assess the bioavailability of heavy metals and organic pollutants in the soil. The combination of binding and diffusion phases made from different materials allows for the targeted determination of different target substances. This review briefly introduces the compositions and development of the DGT technique and analyzes the composition structure of DGT and the impact of environmental factors, such as pH, ion strength (IS), and dissolved organic matter (DOM), on the bioavailability evaluation of heavy metals and organic pollutants in soil. Finally, the application potential and broad application prospects of the DGT technique were expected. In addition, standardized DGT technique methods and calibration procedures are conducive to the establishment of a more stable and reliable measurement system to enhance the robustness of the DGT technique application in the soil.

Citrullus colocynthis (L.) Schrad. (Cucurbitaceae) is widely distributed in the desert areas of the world. The fruit bodies of C. colocynthis are recognized for their wide range of nutraceutical potential, as well as medicinal and pharmaceutical uses. The plant has been reported for various uses, such as asthma, bronchitis, cancer, colic, common cold, cough, diabetes, dysentery, and jaundice. The fruit has been extensively studied for its biological activities, which include insecticide, antitumor, and antidiabetic effects. Numerous bioactive compounds have been reported in its fruit bodies, such as essential oils, fatty acids, glycosides, alkaloids, and flavonoids. Of these, flavonoids or caffeic acid derivatives are the constituents associated with the inhibition of fungal or bacterial growth, whereas eudesmane sesquiterpenes or sesquiterpene lactones are most active against insects, mites, and nematodes. In this review, the scientific evidence for the biological activity of C. colocynthis against insecticide, cytotoxic, and antidiabetic effects is summarized.

WD repeat and HMG-box DNA binding protein 1 (WDHD1) is a highly conserved gene from yeast to humans. It actively participates in DNA replication, playing a crucial role in DNA damage repair and the cell cycle, contributing to centromere formation and sister chromosome segregation. Notably, several studies have implicated WDHD1 in the development and progression of diverse tumor types, including esophageal carcinoma, pulmonary carcinoma, and breast carcinoma. Additionally, the inhibitor of WDHD1 has been found to enhance radiation sensitivity, improve drug resistance, and significantly decrease tumor cell proliferation. This comprehensive review aims to provide an overview of the molecular structure, biological functions, and regulatory mechanisms of WDHD1 in tumors, thereby establishing a foundation for future investigations and potential clinical applications of WDHD1.

In this study, AlGaN/GaN nanochannel high-electron-mobility transistors (HEMTs) with tri-gate (TGN-devices) and dual-gate (DGN-devices) structures were fabricated and investigated. It was found that the peak value of the transconductance (Gm), current gain cut-off frequency (fT) and power gain cut-off frequency (fmax) of the TGN-devices were larger than that of the DGN-devices because of the enhanced gate control from the top gate. Although the TGN-devices and DGN-devices demonstrated flattened transconductance, fT and fmax profiles, the first and second transconductance derivatives of the DGN-devices were lower than those of the TGN-devices, implying an improvement in linearity. With the nanochannel width decreased, the peak value of the transconductance and the first and second transconductance derivatives increased, implying the predominant influence of sidewall gate capacitance on the transconductance and linearity. The comparison of gate capacitance for the TGN-devices and DGN-devices revealed that the gate capacitance of the tri-gate structure was not simply a linear superposition of the top planar gate capacitance and sidewall gate capacitance of the dual-gate structure, which could be attributed to the difference in the depletion region shape for tri-gate and dual-gate structures.

Low temperature is among the important factors affecting the distribution, survival, growth, and physiology of aquatic animals. In this study, coordinated transcriptomic responses to 10 °C acute cold stress were investigated in the gills, hearts, livers, and spleens of Japanese flounder (Paralichthys olivaceus), an important aquaculture species in east Asia. Histological examination suggested different levels of injury among P. olivaceus tissues after cold shock, mainly in the gills and livers. Based on transcriptome and weighted gene coexpression network analysis, 10 tissue-specific cold responsive modules (CRMs) were identified, revealing a cascade of cellular responses to cold stress. Specifically, five upregulated CRMs were enriched with induced differentially expressed genes (DEGs), mainly corresponding to the functions of “extracellular matrix”, “cytoskeleton”, and “oxidoreductase activity”, indicating the induced cellular response to cold shock. The “cell cycle/division” and “DNA complex” functions were enriched in the downregulated CRMs for all four tissues, which comprised inhibited DEGs, suggesting that even with tissue-specific responses, cold shock may induce severely disrupted cellular functions in all tissues, reducing aquaculture productivity. Therefore, our results revealed the tissue-specific regulation of the cellular response to low-temperature stress, which warrants further investigation and provides more comprehensive insights for the conservation and cultivation of P. olivaceus in cold water.

Pancreatic cancer is one of the most lethal malignant diseases due to its high invasiveness, early metastatic properties, rapid disease progression, and typically late diagnosis. Notably, the capacity for pancreatic cancer cells to undergo epithelial–mesenchymal transition (EMT) is key to their tumorigenic and metastatic potential, and is a feature that can explain the therapeutic resistance of such cancers to treatment. Epigenetic modifications are a central molecular feature of EMT, for which histone modifications are most prevalent. The modification of histones is a dynamic process typically carried out by pairs of reverse catalytic enzymes, and the functions of these enzymes are increasingly relevant to our improved understanding of cancer. In this review, we discuss the mechanisms through which histone-modifying enzymes regulate EMT in pancreatic cancer.

Electrocardiogram (ECG) is an efficient and simple method for the diagnosis of cardiovascular diseases and has been widely used in clinical practice. Because of the shortage of professional cardiologists and the popularity of electrocardiograms, accurate and efficient arrhythmia detection has become a hot research topic. In this paper, we propose a new multi-task deep neural network, which includes a shared low-level feature extraction module (i.e., SE-ResNet) and a task-specific classification module. Contextual Transformer (CoT) block is introduced in the classification module to dynamically model the local and global information of ECG feature sequence. The proposed method was evaluated on public CPSC2018 and PTB-XL datasets and achieved an average F1 score of 0.827 on the CPSC2018 dataset and an average F1 score of 0.833 on the PTB-XL dataset.

Salinity and alkalinity are among the important factors affecting the distribution, survival, growth and physiology of aquatic animals. Chinese sea bass (Lateolabrax maculatus) is an important aquaculture fish species in China that can widely adapt to diverse salinities from freshwater (FW) to seawater (SW) but moderately adapt to highly alkaline water (AW). In this study, juvenile L. maculatus were exposed to salinity change (SW to FW) and alkalinity stress (FW to AW). Coordinated transcriptomic responses in L. maculatus gills were investigated and based on the weighted gene co-expression network analysis (WGCNA), 8 and 11 stress-responsive modules (SRMs) were identified for salinity change and alkalinity stress, respectively, which revealed a cascade of cellular responses to oxidative and osmotic stress in L. maculatus gills. Specifically, four upregulated SRMs were enriched with induced differentially expressed genes (DEGs) for alkalinity stress, mainly corresponding to the functions of “extracellular matrix” and “anatomical structure”, indicating a strong cellular response to alkaline water. Both “antioxidative activity” and “immune response” functions were enriched in the downregulated alkaline SRMs, which comprised inhibited alkaline specific DEGs, revealing the severely disrupted immune and antioxidative functions under alkalinity stress. These alkaline-specific responses were not revealed in the salinity change groups with only moderately inhibited osmoregulation and induced antioxidative response in L. maculatus gills. Therefore, the results revealed the diverse and correlated regulation of the cellular process and stress response in saline-alkaline water, which may have arisen through the functional divergence and adaptive recruitment of the co-expression genes and will provide vital insights for the development of L. maculatus cultivation in alkaline water.

As a novel bio-inspired vision sensor, spike cameras offer significant advantages over conventional cameras with a fixed low sampling rate, recording fast-moving scenes by firing a continuous stream of spikes. Reconstruction methods including Texture from ISI (TFI), Texture from Playback (TFP), and Texture from Adaptive threshold (TFA) produce undesirable noise or motion blur. A spiking neural model distinguishes the dynamic and static spikes before reconstruction, but the reconstruction of motion details is still unsatisfactory even with the advanced TFA method. To address this issue, we propose a coarse-to-fine high-speed motion scene reconstruction (CFSR) method with a region-adaptive-based spike distinction (RASE) framework to reconstruct the full texture of natural scenes from the spike data. We utilize the spike distribution of dynamic and static regions to propose the RASE to distinguish the spikes of different moments. After distinction, the TFI, TFP, and patch matching are exploited for image reconstruction in different regions, respectively, which does not introduce unexpected noise or motion blur. Experimental results on the PKU-SPIKE-RECON dataset demonstrate that our CFSR method outperforms the state-of-the-art approaches in terms of objective and subjective quality.

Background: The dietary inflammatory index (DII) is thought to be related to many healthy events. However, the association between the DII and sarcopenia remains unclear. Methods: The meta-analysis was conducted to evaluate the effects of the DII on the risk of sarcopenia utilizing available studies. Up to September 2022, Cochrane, PubMed, Web of Science, Medline, and EMBASE databases were searched to evaluate the relationships between the DII and sarcopenia. A random‒effects model was used to calculate the effect size and 95% confidence intervals (CIs). Result: Eleven studies with 19,954 participants were included in our meta-analysis. The results indicated that a high DII increased the risk of sarcopenia (OR = 1.16, 95%CI [1.06, 1.27], p < 0.05). The result of the dose–response analysis showed that the risk of sarcopenia increased by 1.22 times for each 1-point increase in the DII score (OR = 1.22, 95%CI [1.12, 1.33], p < 0.05). Conclusion: The meta-analysis demonstrated that the DII is associated with sarcopenia. Considering some limitations in this study, more studies are needed to verify this relationship.

Non-coding RNAs (ncRNAs), including miRNAs, lncRNAs, circRNAs, and piRNAs, do not encode proteins. Nonetheless, they have critical roles in a variety of cellular activities—such as development, neurogenesis, degeneration, and the response to injury to the nervous system—via protein translation, RNA splicing, gene activation, silencing, modifications, and editing; thus, they may serve as potential targets for disease treatment. The activity of adult neural stem cells (NSCs) in the subgranular zone of the hippocampal dentate gyrus critically influences hippocampal function, including learning, memory, and emotion. ncRNAs have been shown to be involved in the regulation of hippocampal neurogenesis, including proliferation, differentiation, and migration of NSCs and synapse formation. The interaction among ncRNAs is complex and diverse and has become a major topic within the life science. This review outlines advances in research on the roles of ncRNAs in modulating NSC bioactivity in the hippocampus and discusses their potential applications in the treatment of illnesses affecting the hippocampus.

The distribution of heavy metals in the agricultural areas from a cattle-producing area near the Zhangbei Dam grassland, Hebei province, China, was investigated for providing the basis for the control of pollution in a rural farmland. Fifty-three surface soil samples including 28 soils of potato and 25 soils of oats were collected and analyzed for the distribution of Cd, Cu, Pb, Zn, Cr, As, Hg, and Ni. Furthermore, the ecological risk of soils contaminated with heavy metals was evaluated by employing the single factor index, the Nemerow comprehensive pollution index and geo-accumulation index, and potential ecological hazard index. The results showed that the contents of the eight heavy metals in soil planted with potato were below the risk screening values. The single factor index in soils planted with hulless oats showed that the concentrations of Cd, Hg, and Ni surpassed the Chinese screening limits by 8%, 4%, and 8%, respectively. According to the geo-accumulation index, 4% of samples reached the level of medium ecological risk for Cd. According to the results of ecological risk assessment, the studied soils generally showed a mild pollution degree. According to the health risks assessment results, the carcinogenic risks should be considered non-negligible. Arsenic is the dominant carcinogenic pollutant for human beings in the county. The main sources of pollution are mining and application of fertilizers.

Point cloud data are extensively used in various applications, such as autonomous driving and augmented reality since it can provide both detailed and realistic depictions of 3D scenes or objects. Meanwhile, 3D point clouds generally occupy a large amount of storage space that is a big burden for efficient communication. However, it is difficult to efficiently compress such sparse, disordered, non-uniform and high dimensional data. Therefore, this work proposes a novel deep-learning framework for point cloud geometric compression based on an autoencoder architecture. Specifically, a multi-layer residual module is designed on a sparse convolution-based autoencoders that progressively down-samples the input point clouds and reconstructs the point clouds in a hierarchically way. It effectively constrains the accuracy of the sampling process at the encoder side, which significantly preserves the feature information with a decrease in the data volume. Compared with the state-of-the-art geometry-based point cloud compression (G-PCC) schemes, our approach obtains more than 70–90% BD-Rate gain on an object point cloud dataset and achieves a better point cloud reconstruction quality. Additionally, compared to the state-of-the-art PCGCv2, we achieve an average gain of about 10% in BD-Rate.

Under some unexpected conditions, drive rods and control-rod assemblies may not be disconnected. If this situation is not detected, the control rod will be lifted out of the reactor core together with the upper reactor internals. This situation will seriously affect the follow-up work and reduce the economy and safety protection of the nuclear power plant. To ensure safety, the tripping status must be checked after tripping. Follow-up work can be carried out after checking and confirming that all drive rods are in the tripping status. There are many problems for traditional inspection methods, such as misjudgment, low accuracy, and labor consumption. This paper proposes a visual inspection system for the uncoupling state of the control-rod drive rod of the nuclear reactor. The proposed method is based on the fitting model of the ellipse parameter of the drive-rod head and the height of the drive rod. The ellipse of the drive-rod head is firstly accurately detected. Then, a mathematical model between the ellipse parameter and the height of the drive rod is established. The measurement error caused by the swing of the head of the drive rod is eliminated. The accurate measurement of the height difference before and after the tripping of the drive rod is computed. Finally, the status of the uncoupling of the drive rod is judged according to the difference. Many experiments are carried out with our developed system. The experimental results show that the proposed system realizes remote operation, ensures the quality of trip-status inspection, improves work efficiency, and reduces the workload of staff.

High-energy ball milling and spark plasma sintering (SPS) are used to create high-strength Ti-25Nb-6Zr biomedical alloys with β structures. The Ti-25Nb-6Zr alloy microstructure and mechanical properties were examined as a function of the sintering temperatures. The results showed that as the sintering temperature was raised, the densification process was expedited, and the comprehensive mechanical characteristics increased at first, then dropped slightly. Moreover, under high temperatures, the fracture morphology of the Ti-25Nb-6Zr biomedical alloys exhibited more dimples, indicating enhanced plasticity of the material. Evaluating the mechanical properties of the Ti-25Nb-6Zr biomedical alloy sintered at 1623 K indicated a high compressive strength of 1678.4 ± 5 MPa and an elongation of 12.4 ± 0.5%. The strengthening mechanisms are discussed in terms of the formation and distribution of bcc-Ti in the matrix as well as the homogeneous distribution of Nb and Zr. This research presents a new method for fabricating Ti-25Nb-6Zr biomedical alloys with high strength and low modulus values. The theoretical grounds for the development of high-performance Ti-Nb-Zr alloys will be laid by detailed research of this technology and its strengthening mechanisms.

Treatment of full-thickness articular cartilage defects with exposure of subchondral bone often seen in osteoarthritic conditions has long been a great challenge, especially with a focus on the feasibility of in situ cartilage regeneration through minimally invasive procedures. Osteoblasts that situate in the subchondral bone plate may be considered a potentially vital endogenous source of cells for cartilage resurfacing through direct reprogramming into chondrocytes. Microarray-based gene expression profiles were generated to compare tissue-specific transcripts between subchondral bone and cartilage of mice and to assess age-dependent differences of chondrocytes as well. On osteoblast cell lines established from mouse proximal tibial subchondral bone, sequential screening by co-transduction of transcription factor (TF) genes that distinguish chondrocytes from osteoblasts reveals a shortlist of potential reprogramming factors exhibiting combined effects in inducing chondrogenesis of subchondral bone osteoblasts. A further combinatorial approach unexpectedly identified two 3-TF combinations containing Sox9 and Sox5 that exhibit differences in reprogramming propensity with the third TF c-Myc or Plagl1, which appeared to direct the converted chondrocytes toward either a superficial or a deeper zone phenotype. Thus, our approach demonstrates the possibility of converting osteoblasts into two major chondrocyte subpopulations with two combinations of three genes (Sox9, Sox5, and c-Myc or Plagl1). The findings may have important implications for developing novel in situ regeneration strategies for the reconstruction of full-thickness cartilage defects.

Leonurine has been shown to have excellent anti-myocardial ischemia effects. Our previous studies suggested that cardiac protection by leonurine during myocardial ischemia appeared to be inextricably linked to its regulation of the liver. At present, however, there are few mechanistic studies of leonurine and its regulation of hepatic metabolism against ischemic injury. In this study, a metabolomics approach was developed to give a global view of the metabolic profiles of the heart and liver during myocardial ischemia. Principal component analysis and orthogonal partial least squares discrimination analysis were applied to filter differential metabolites, and a debiased sparse partial correlation analysis was used to analyze the correlation of the differential metabolites between heart and liver. As a result, a total of thirty-one differential metabolites were identified, six in the myocardial tissue and twenty-five in the hepatic tissue, involving multiple metabolic pathways including glycine, serine and threonine, purine, fatty acid, and amino acid metabolic pathways. Correlation analysis revealed a net of these differential metabolites, suggesting an interaction between hepatic and myocardial metabolism. These results suggest that leonurine may reduce myocardial injury during myocardial ischemia by regulating the metabolism of glycine, serine and threonine, purine, fatty acids, and amino acids in the liver and heart.

The use of green manure plants for soil restoration is a viable agricultural practice that can mitigate soil degradation and biodiversity loss caused by the long-term application of inorganic fertilizers. However, the effects of green manure on soil microbial communities, rice yield, and quality in the karst mountains are largely unknown. The effects of no chemical fertilizer, chemical fertilizer, chemical fertilizer + different Astragalus sinicus L. (Chinese milk vetch, CMV) treatments on the microbial community, soil enzyme activities, soil nutrient content, and crop yield were investigated through field experiments. A moderate application of chemical fertilizer with green manure can increase chlorophyll content, increase effective rice spikes, positive impact on rice yield, and increase crude protein, etc. Additional application of the moderate amount of CMV can increase alkali-hydrolyzable nitrogen and available phosphorus (a significant increase of 54.87–72.65%), improve microbial biomass carbon (MBC) and microbial biomass nitrogen (MBN) (CFMV2 significantly increased by 22.16%), improve soil urease and phosphatase activities, and the urease activity increased by 43.43–69.24% with CMV application compared to CK. Moreover, all bacterial communities were dominated by three major phyla (Proteobacteria, Chloroflexi, and Acidobacteria), where the application of chemical fertilizer with CMV increased the ratio of abundance of Proteobacteria and Acidobacteria in rice soils, and the effect of chemical fertilizer application on the dominant bacteria was regulated to some extent by additional green manure application, which may have a beneficial effect on rice yield. Therefore, we conclude that the rational use of chemical fertilizers with CMV (22,500 kg ha−1) in karst landscapes is one of the effective measures to achieve efficient and sustainable use of rice fields.

Recently, developing a cost-effective and high-performance catalyst is regarded as an urgent priority for hydrogen generation technology. In this work, ISOBAM-104 stabilized Co/Fe colloidal catalysts were prepared via a co-reduction method and used for the hydrogen generation from KBH4 hydrolysis. The obtained ISOBAM-104 stabilized Co10Fe90 colloidal catalysts exhibit an outstanding catalytic activity of 37,900 mL-H2 min−1 g-Co−1, which is far higher than that of Fe or Co monometallic nanoparticles (MNPs). The apparent activation energy (Ea) of the as-prepared Co10Fe90 colloidal catalysts is only 14.6 ± 0.7 kJ mol−1, which is much lower than that of previous reported noble metal-based catalysts. The X-ray photoelectron spectroscopy results and density functional theory calculations demonstrate that the electron transfer between Fe and Co atoms is beneficial for the catalytic hydrolysis of KBH4.

To develop a precise semantic segmentation method with an emphasis on the edges for automated segmentation of the arterial vessel wall and plaque based on the convolutional neural network (CNN) in order to facilitate the quantitative assessment of plaque in patients with ischemic stroke. A total of 124 subjects’ MR vessel wall images were used to train, validate, and test the model using deep learning. An end-to-end architecture network that can emphasize the edge information, namely the Edge Vessel Segmentation Network (EVSegNet) for automated segmentation of the arterial vessel wall, is proposed. The EVSegNet network consists of two workflows: one is implemented to achieve finely and multiscale segmentation by combining Dense Upsampling Convolution (DUC) and Hybrid Dilated Convolution (HDC) with different dilation rates modules, and the other utilizes edge information and is fused with another workflow to finally segment the vessel wall. The proposed network demonstrates robust segmentation of the vessel wall and better performance with a Dice (%) of 87.5, compared with the traditional U-net that has a Dice (%) of 81.0 and other U-net-based models on the test dataset. The results suggest that the proposed segmentation method with an emphasis on the edges improves segmentation accuracy effectively and will facilitate the quantitative assessment of atherosclerosis.

Parcel detection is crucial to achieving automatic sorting in intelligent logistics systems. Most parcels in logistics centers are currently detected manually, imposing low efficiency and high error rate, severely limiting logistics transportation efficiency. Therefore, there is an urgent need for automated parcel detection. However, parcels in logistics centers have challenges such as dense stacking, occlusion and background interference, making it difficult for existing methods to detect parcels accurately. To address the above problem, we developed an improved Faster R-CNN-based parcel detection model spurred by current deep-learning-based object detection trends. The proposed method first solves the false detection problem due to parcel mutual occlusion by augmenting Faster R-CNN with an edge detection branch and adding object edge loss to the loss function. Furthermore, the self-attention ROI Align module is proposed to address the problem of feature misalignment caused by the quantization rounding operation in the ROI Pooling module. The module uses an attention mechanism to filter and enhance the features and uses bilinear interpolation to calculate the feature pixel values, improving detection accuracy. The implementation of the proposed method was validated using parcel images collected in the field and the public dataset SKU110K and compared with four existing parcel detection methods. The results show that our method’s Recall, Precision, map@0.5 and Fps are 96.89%, 98.76%, 98.42% and 22.83%, respectively, which significantly improves the parcel detection accuracy.

Oxypeucedanin, a furanocoumarin extracted from many traditional Chinese herbal medicines, has a variety of pharmacological effects. However, the independent pharmacokinetic characteristics and bioavailability of this compound remains elusive. In this study, a rapid, sensitive, and selective method using ultra-high performance liquid chromatography–tandem mass spectrometry (UPLC/MS/MS) was developed for evaluating the intravenous and oral pharmacokinetics of oxypeucedanin. After intravenous administration of oxypeucedanin (2.5, 5, and 10 mg/kg), and intragastric administration of oxypeucedanin (20 mg/kg), blood samples were collected periodically from the tail vein. The plasma concentration-time curves were plotted, and the pharmacokinetic parameters were calculated using a non-compartmental model analysis. After intravenous administration of oxypeucedanin (single dosing at 2.5, 5, and 10 mg/kg) to rats, the pharmacokinetics fit the linear kinetics characteristics, which showed that some parameters including average elimination half-life (T1/2Z of 0.61~0.66 h), mean residence time (MRT of 0.62~0.80 h), apparent volume of distribution (VZ of 4.98~7.50 L/kg), and systemic clearance (CLZ of 5.64~8.55 L/kg/h) are dose-independent and the area under concentration-time curve (AUC) increased in a dose-proportional manner. Single oral administration of oxypeucedanin (20 mg/kg) showed poor and slow absorption with the mean time to reach the peak concentration (Tmax) of 3.38 h, MRT of 5.86 h, T1/2Z of 2.94 h, and a mean absolute bioavailability of 10.26% in rats. These results provide critical information for a better understanding of the pharmacological effect of oxypeucedanin, which will facilitate its research and development.

Steroidogenesis controls the conversion of cholesterol into steroid hormones through the complex cascade reaction of various enzymes, which play essential roles in sexual differentiation and gonadal development in vertebrates, including teleosts. Japanese flounder (Paralichthys olivaceus) and Chinese tongue sole (Cynoglossus semilaevis) are important marine cultured fishes in China and have remarkable sexual dimorphism with bigger females and sex reversal scenarios from female to neo-male. Several steroidogenic genes have been analyzed individually in the two species, but there is a lack of information on the coordinated interaction of steroidogenic gene regulation. Therefore, in this study, through genomic and transcriptomic analysis, 39 and 42 steroidogenic genes were systematically characterized in P. olivaceus and C. semilaevis genomes, respectively. Phylogenetic and synteny analysis suggested a teleost specific genome duplication origin for cyp19a1a/cyp19a1b, hsd17b12a/hsd17b12b, ara/arb and esr2a/esr2b but not for star/star2 and cyp17a1/cyp17a2. Comparative transcriptome analysis revealed conserved expression patterns for steroidogenic genes in P. olivaceus and C. smilaevis gonads; star/star2, cyp11a/cyp11c, cyp17a1/cyp17a2, cyp21a, hsd3b1, hsd11b and hsd20b were strongly expressed in testis, while cyp19a1a and hsd17b genes were highly expressed in ovaries. Only a few genes were differentially expressed between male and neo-male testis of both P. olivaceus and C. semilaevis, and even fewer genes were differentially regulated in the brains of both species. Network analysis indicated that cyp11c, cyp17a1 and hsd3b1 actively interacted with other steroidogenic genes in P. olivaceus and C. semilaevis, and may play a more sophisticated role in the steroid hormone biosynthesis cascade. The coordinated interaction of steroidogenic genes provided comprehensive insights into steroidogenic pathway regulation with a global biological impact, as well as sexual development in teleost species.

Accurate combined bundle adjustment (BA) is a fundamental step for the integration of aerial and terrestrial images captured from complementary platforms. In traditional photogrammetry pipelines, self-calibrated bundle adjustment (SCBA) improves the BA accuracy by simultaneously refining the interior orientation parameters (IOPs), including lens distortion parameters, and the exterior orientation parameters (EOPs). Aerial and terrestrial images separately processed through SCBA need to be fused using BA. Thus, the IOPs in the aerial–terrestrial BA must be properly treated. On one hand, the IOPs in one flight should be identical for the same images in physics. On the other hand, the IOP adjustment in the cross-platform-combined BA may mathematically improve the aerial–terrestrial image co-registration degree in 3D space. In this paper, the impacts of self-calibration strategies in combined BA of aerial and terrestrial image blocks on the co-registration accuracy were investigated. To answer this question, aerial and terrestrial images captured from seven study areas were tested under four aerial–terrestrial BA scenarios: the IOPs for both aerial and terrestrial images were fixed; the IOPs for only aerial images were fixed; the IOPs for only terrestrial images were fixed; the IOPs for both images were adjusted. The cross-platform co-registration accuracy for the BA was evaluated according to independent checkpoints that were visible on the two platforms. The experimental results revealed that the recovered IOPs of aerial images should be fixed during the BA. However, when the tie points of the terrestrial images are comprehensively distributed in the image space and the aerial image networks are sufficiently stable, refining the IOPs of the terrestrial cameras during the BA may improve the co-registration accuracy. Otherwise, fixing the IOPs is the best solution.

This work proposes the use of a robust geometrical segmentation algorithm to detect inherent shapes from dense point clouds. The points are first divided into voxels based on their connectivity and normal consistency. Then, the voxels are classified into different types of shapes through a multi-scale prediction algorithm and multiple shapes including spheres, cylinders, and cones are extracted. Next, a hybrid voting RANSAC algorithm is adopted to separate the point clouds into corresponding segments. The point–shape distance, normal difference, and voxel size are all considered as weight terms when evaluating the proposed shape. Robust voxels are weighted as a whole to ensure efficiency, while single points are considered to achieve the best performance in the disputed region. Finally, graph-cut-based optimization is adopted to deal with the competition among different segments. Experimental results and comparisons indicate that the proposed method can generate reliable segmentation results and provide the best performance compared to the benchmark methods.

High-resolution remote sensing images contain abundant building information and provide an important data source for extracting buildings, which is of great significance to farmland preservation. However, the types of ground features in farmland are complex, the buildings are scattered and may be obscured by clouds or vegetation, leading to problems such as a low extraction accuracy in the existing methods. In response to the above problems, this paper proposes a method of attention-enhanced U-Net for building extraction from farmland, based on Google and WorldView-2 remote sensing images. First, a Resnet unit is adopted as the infrastructure of the U-Net network encoding part, then the spatial and channel attention mechanism module is introduced between the Resnet unit and the maximum pool and the multi-scale fusion module is added to improve the U-Net network. Second, the buildings found on WorldView-2 and Google images are extracted through farmland boundary constraints. Third, boundary optimization and fusion processing are carried out for the building extraction results on the WorldView-2 and Google images. Fourth, a case experiment is performed. The method in this paper is compared with semantic segmentation models, such as FCN8, U-Net, Attention_UNet, and DeepLabv3+. The experimental results indicate that this method attains a higher accuracy and better effect in terms of building extraction within farmland; the accuracy is 97.47%, the F1 score is 85.61%, the recall rate (Recall) is 93.02%, and the intersection of union (IoU) value is 74.85%. Hence, buildings within farming areas can be effectively extracted, which is conducive to the preservation of farmland.

Skeletal muscle plays important roles in animal locomotion, metabolism, and meat production in farm animals. Current studies showed that non-coding RNAs, especially the circular RNA (circRNA) play an indispensable role in skeletal muscle development. Our previous study revealed that several differentially expressed circRNAs among fast muscle growing broilers (FMGB) and slow muscle growing layers (SMGL) may regulate muscle development in the chicken. In this study, a novel differentially expressed circPPP1R13B was identified. Molecular mechanism analysis indicated that circPPP1R13B targets miR-9-5p and negatively regulates the expression of miR-9-5p, which was previously reported to be an inhibitor of skeletal muscle development. In addition, circPPP1R13B positively regulated the expression of miR-9-5p target gene insulin like growth factor 2 mRNA binding protein 3 (IGF2BP3) and further activated the downstream insulin like growth factors (IGF)/phosphatidylinositol 3-kinase (PI3K)/AKT serine/threonine kinase (AKT) signaling pathway. The results also showed that the knockdown of circPPP1R13B inhibits chicken skeletal muscle satellite cells (SMSCs) proliferation and differentiation, and the overexpression of circPPP1R13B promotes the proliferation and differentiation of chicken SMSCs. Furthermore, the overexpression of circPPP1R13B could block the inhibitory effect of miR-9-5p on chicken SMSC proliferation and differentiation. In summary, our results suggested that circPPP1R13B promotes chicken SMSC proliferation and differentiation by targeting miR-9-5p and activating IGF/PI3K/AKT signaling pathway.

The fertility of female animals is negatively correlated with increasing chronological age. In aging broiler breeder hens, there is a decline in the functionality of the ovary and liver accompanied by hormonal or endocrine changes, a reduction in antioxidant capacity, and a decrease in folliculogenesis. Therefore, improving the reproductive function in aging breeder hens using dietary strategies is of great concern to the poultry breeder. This study evaluated the capacity of dietary quercetin (Q), vitamin E (VE), and their combination (Q + VE) to promote follicle development and attenuate organ inflammation by improving the antioxidant capacity of aging breeder hens. In this study, 400 broiler breeder hens (Tianfu broilers breeder hens, 435 days old) were allotted into four groups (100 birds each) with four replicates each (25 birds each). They were fed diets containing Q (0.4 g/kg), VE (0.2 g/kg), Q + VE (0.4 g/kg + 0.2 g/kg), and a basal diet for 10 weeks. The results showed that Q + VE improved the organ characteristics (p < 0.05), and also that Q + VE showed protective effects on the liver against injury, as well as increasing the antioxidant capacity of the liver, serum, and ovary (p < 0.05). Furthermore, liver lipid synthesis was increased remarkably, as indicated by the changes in triglyceride levels in hens fed Q + VE (p < 0.05). Levels of E2, FSH, and LH, their receptors, and mRNAs related to yolk precursor synthesis were increased by the Q + VE (p < 0.05). Therefore, the combination of quercetin and vitamin E synergistically promotes and regulates the transportation and exchange of synthetic substances among the liver–blood–ovary alliances to ensure the synchronous development and functional coordination between the liver and ovary in aging breeder hens.

Long non-coding RNAs (lncRNAs) and mRNAs are temporally expressed during chicken follicle development. However, follicle transcriptome studies in chickens with timepoints relating to changes in luteinizing hormone (LH) levels are rare. In this study, gene expression in Rohman layers was investigated at three distinct stages of the ovulatory cycle: zeitgeber time 0 (ZT0, 9:00 a.m.), zeitgeber time 12 (ZT12, 9:00 p.m.), and zeitgeber time 20 (ZT20, 5:00 a.m.) representing the early, middle, and LH surge stages, respectively, of the ovulatory cycle. Gene expression profiles were explored during follicle development at ZT0, ZT12, and ZT20 using Ribo-Zero RNA sequencing. The three stages were separated into two major stages, including the pre-LH surge and the LH surge stages. A total of 12,479 mRNAs and 7528 lncRNAs were identified among the three stages, and 4531, 523 differentially expressed genes (DEGs) and 2367, 211 differentially expressed lncRNAs (DELs) were identified in the ZT20 vs. ZT12, and ZT12 vs. ZT0, comparisons. Functional enrichment analysis revealed that genes involved in cell proliferation and metabolism processes (lipid-related) were mainly enriched in the ZT0 and ZT12 stages, respectively, and genes related to oxidative stress, steroids regulation, and inflammatory process were enriched in the ZT20 stage. These findings provide the basis for further investigation of the specific genetic and molecular functions of follicle development in chickens.

Skeletal muscle satellite cell growth and development is a complicated process driven by multiple genes. The PDZ and LIM domain 5 (PDLIM5) gene has been proven to function in C2C12 myoblast differentiation and is involved in the regulation of skeletal muscle development. The role of PDLIM5 in chicken skeletal muscle satellite cells, however, is unclear. In this study, in order to determine whether the PDLIM5 gene has a function in chicken skeletal muscle satellite cells, we examined the changes in proliferation and differentiation of chicken skeletal muscle satellite cells (SMSCs) after interfering and overexpressing PDLIM5 in cells. In addition, the molecular pathways of the PDLIM5 gene regulating SMSC proliferation and differentiation were analyzed by transcriptome sequencing. Our results show that PDLIM5 can promote the proliferation and differentiation of SMSCs; furthermore, through transcriptome sequencing, it can be found that the differential genes are enriched in the MAPK signaling pathway after knocking down PDLIM5. Finally, it was verified that PDLIM5 played an active role in the proliferation and differentiation of chicken SMSCs by activating the p38-MAPK signaling pathway. These results indicate that PDLIM5 may be involved in the growth and development of chicken skeletal muscle.

In the context of the problem of image blur and nonlinear reflectance difference between bands in the registration of hyperspectral images, the conventional method has a large registration error and is even unable to complete the registration. This paper proposes a robust and efficient registration algorithm based on iterative clustering for interband registration of hyperspectral images. The algorithm starts by extracting feature points using the scale-invariant feature transform (SIFT) to achieve initial putative matching. Subsequently, feature matching is performed using four-dimensional descriptors based on the geometric, radiometric, and feature properties of the data. An efficient iterative clustering method is proposed to perform cluster analysis on the proposed descriptors and extract the correct matching points. In addition, we use an adaptive strategy to analyze the key parameters and extract values automatically during the iterative process. We designed four experiments to prove that our method solves the problem of blurred image registration and multi-modal registration of hyperspectral images. It has high robustness to multiple scenes, multiple satellites, and multiple transformations, and it is better than other similar feature matching algorithms.

Most of the existing approaches to the extraction of buildings from high-resolution orthoimages consider the problem as semantic segmentation, which extracts a pixel-wise mask for buildings and trains end-to-end with manually labeled building maps. However, as buildings are highly structured, such a strategy suffers several problems, such as blurred boundaries and the adhesion to close objects. To alleviate the above problems, we proposed a new strategy that also considers the contours of the buildings. Both the contours and structures of the buildings are jointly learned in the same network. The contours are learnable because the boundary of the mask labels of buildings implicitly represents the contours of buildings. We utilized the building contour information embedded in the labels to optimize the representation of building boundaries, then combined the contour information with multi-scale semantic features to enhance the robustness to image spatial resolution. The experimental results showed that the proposed method achieved 91.64%, 81.34%, and 74.51% intersection over union (IoU) on the WHU, Aerial, and Massachusetts building datasets, and outperformed the state-of-the-art (SOTA) methods. It significantly improved the accuracy of building boundaries, especially for the edges of adjacent buildings. The code is made publicly available.

Three-dimensional (3D) building models play an important role in digital cities and have numerous potential applications in environmental studies. In recent years, the photogrammetric point clouds obtained by aerial oblique images have become a major source of data for 3D building reconstruction. Aiming at reconstructing a 3D building model at Level of Detail (LoD) 2 and even LoD3 with preferred geometry accuracy and affordable computation expense, in this paper, we propose a novel method for the efficient reconstruction of building models from the photogrammetric point clouds which combines the rule-based and the hypothesis-based method using a two-stage topological recovery process. Given the point clouds of a single building, planar primitives and their corresponding boundaries are extracted and regularized to obtain abstracted building counters. In the first stage, we take advantage of the regularity and adjacency of the building counters to recover parts of the topological relationships between different primitives. Three constraints, namely pairwise constraint, triplet constraint, and nearby constraint, are utilized to form an initial reconstruction with candidate faces in ambiguous areas. In the second stage, the topologies in ambiguous areas are removed and reconstructed by solving an integer linear optimization problem based on the initial constraints while considering data fitting degree. Experiments using real datasets reveal that compared with state-of-the-art methods, the proposed method can efficiently reconstruct 3D building models in seconds with the geometry accuracy in decimeter level.

Zearalenone (ZEA) is a nonsteroidal estrogenic mycotoxin found in several food commodities worldwide. ZEA causes reproductive disorders, genotoxicity, and testicular toxicity in animals. However, little is known about the functions of apoptosis and autophagy after exposure to ZEA in granulosa cells. This study investigated the effects of ZEA on chicken granulosa cells. The results show that ZEA at different doses significantly inhibited the growth of chicken granulosa cells by inducing apoptosis. ZEA treatment up-regulated Bax and downregulated Bcl-2 expression, promoted cytochrome c release into the cytosol, and triggered mitochondria-mediated apoptosis. Consequently, caspase-9 and downstream effector caspase-3 were activated, resulting in chicken granulosa cells apoptosis. ZEA treatment also upregulated LC3-II and Beclin-1 expression, suggesting that ZEA induced a high level of autophagy. Pretreatment with chloroquine (an autophagy inhibitor) and rapamycin (an autophagy inducer) increased and decreased the rate of apoptosis, respectively, in contrast with other ZEA-treated groups. Autophagy delayed apoptosis in the ZEA-treated cells. Therefore, autophagy may prevent cells from undergoing apoptosis by reducing ZEA-induced cytotoxicity. In addition, our results further show that the autophagy was stimulated by ZEA through PI3K-AKT-mTOR and MAPK signaling pathways in chicken granulosa cells.

The authors wish to make the following corrections to their paper [...]