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Previous research has consistently shown that high-fat diet (HFD) consumption can lead to the development of colonic inflammation. Neohesperidin (NHP), a naturally occurring flavanone glycoside in citrus fruits, has anti-inflammatory properties. However, the efficacy and mechanism of NHP in countering prolonged HFD-induced inflammation remains unclear. In this study, rats on HFD were intragastrically administered (i.g.) with NHP for 12 consecutive weeks. Results indicate that this natural compound is effective in reducing colorectal inflammation at doses of 40-80 mg/kg body weight (BW) by i.g. administration, with significant decreases in inflammation markers such as TNF-α and IL-1β levels. It also improved intestinal mucosal tissue integrity and reduced HFD-stimulated colorectal inflammation via the JAK2/STAT3 pathway. Furthermore, intestinal microbiota sequencing results show that NHP intervention significantly downregulated the Firmicutes/Bacteroidetes ratio. This ratio is closely related to the preventive role in the context of glycolipid metabolism disorder. Compared with fecal cultures of rats from the HFD group, after 48 h in vitro fermentation, those from the NHP group had distinct microbiota composition and notably higher concentrations of SCFAs. Collectively, these observations suggest that 80 mg/kg BW NHP possesses biological activities in downregulating HFD-induced colorectal inflammation by regulating intestinal flora and promoting SCFAs formation.

Photocatalytic hydrogen evolution using inexhaustible clean solar energy is considered as a promising strategy. In order to build an efficient photocatalytic hydrogen production system to satisfy the demands of practical applications, it is of great significance to design photocatalysts that offer high activity, low cost, and high stability. Herein, a series of cheap CdS/Ni(OH) 2 composite photocatalysts were designed and synthesized using the hydrothermal method. The introduction of a Ni(OH) 2 cocatalyst multiplied the reactive active site of cadmium sulfide and promoted the transfer of photoinduced electrons in a semiconductor. Therefore, CdS/Ni(OH) 2 composites demonstrate significantly better photocatalytic performance, and the hydrogen production rate of an optimal CdS/5%Ni(OH) 2 composite is 6.9 times higher than that of blank CdS. Furthermore, the stability test also showed that CdS/Ni(OH) 2 had good stability. This study aims to serve as a rewarding reference for the development of high-performance composite photocatalysts.

As unmanned aerial vehicle (UAV) technology expands into diverse applications, the demand for enhanced performance intensifies. Blockchain sharding technology offers promising avenues for improving data processing capabilities and security in drone networks. However, the inherent mobility of UAVs and their dynamic operational environment pose significant challenges to conventional sharding techniques, often resulting in communication latencies and data synchronization delays that compromise efficiency. This study presents a novel blockchain-based adaptive sharding framework specifically designed for UAV ecosystems. Our research extends beyond improving data transmission rates to encompass an enhanced Asynchronous Advantage Actor-Critic algorithm, tailored to address long-term optimization objectives in aerial networks. The proposed optimizations focus on dual objectives: enhancing data security while concurrently accelerating processing speeds. By addressing the limitations of traditional approaches, this work aims to facilitate seamless communication and foster innovation in UAV networks. The adaptive sharding framework, coupled with the refined A3C algorithm, presents a comprehensive solution to the unique challenges faced by mobile aerial systems in blockchain implementation.

Lupus nephritis (LN) is a severe form of systemic lupus erythematosus (SLE), characterized by inflammation in the renal glomeruli and tubules. Previous research has demonstrated that dihydroartemisinin (DHA) can reduce inflammatory damage in LN mouse models. Oxymatrine, which has similar biological properties to DHA, may also provide therapeutic benefits. This study aims to investigate the effects of oxymatrine on LN using a murine model and examines its molecular mechanisms through an analysis of microarray datasets from LN patients. The analysis identified differentially expressed genes (DEGs) in renal tissues, regulated by the transcription factor Yin Yang 1 (YY1), which was found to be significantly upregulated in LN patient kidneys. The results indicate that oxymatrine targets the YY1/IL-6/STAT3 signaling pathway. In cell models simulating renal inflammation, oxymatrine reduced YY1 expression and inhibited the secretion of inflammatory factors (IFs), thereby diminishing inflammation. YY1 is crucial in modulating IFs' secretion and contributing to LN pathogenesis. Additionally, oxymatrine's interaction with YY1, leading to its downregulation, appears to be a key mechanism in alleviating LN symptoms. These findings support oxymatrine as a promising therapeutic agent for LN, offering new avenues for treating this autoimmune kidney disorder.

Leptin plays an indispensable role in energy homeostasis, and its involvement in metabolic activities has been extensively explored in fish. We generated mutant lines of leptina (-5 bp) and leptinb (+8 bp) in zebrafish using CRISPR/Cas9 technology to explore the metabolic characteristics of lepa and lepb mutant zebrafish in response to high glucose nutritional stress induced by high levels of carbohydrates. The results were as follows: the body weight and food intake of adult zebrafish of the two mutant species were increased; the visceral fat accumulation, whole-body crude lipid, and crude protein contents of lepb -/- were increased; and the visceral fat accumulation and crude lipid in lepa -/- zebrafish were decreased. The blood glucose levels of the two mutant zebrafish were increased, the mRNA expression levels of glycolytic genes pk and gck were decreased in the two mutant zebrafish, and there were differences between lepa -/- and lepb -/- zebrafish. The expressions of glycogen synthesis and decomposition genes were inhibited and promoted, respectively. The expression of adipose synthesis genes in the liver and muscle was stimulated in lepb -/- zebrafish but suppressed in lepa -/- zebrafish. Lipolysis and oxidation genes were also stimulated in lepa -/- zebrafish livers, while the livers of lepb -/- zebrafish were stimulated but muscle was inhibited. In conclusion, the results indicate that lepa plays a major role in glucose metabolism, which is conducive to promoting glucose utilization and lipogenesis, while lepb mainly promotes lipolysis and oxidation, regulates protein generation, and plays a minor role in glucose metabolism.

Background: Non/low-caloric artificial sweeteners (NAS) are recognized as chemical additives substituting sugars to avoid caloric intake and subsequent sugar-derived diseases such as diabetes and hyperglycemia. Six NAS have been claimed safe and are authorized by the US Food and Drug Administration (FDA) for public use, with acceptable daily intake information available: aspartame, acesulfame-K, saccharin, sucralose, neotame, and advantame. However, the impacts of NAS on the gut microbiome have raised potential concerns, since sporadic research revealed NAS-induced microbial changes in the gastrointestinal tracts and alterations in the microbiome-host interactive metabolism., Methods: Given the fact that the gut microbiome influences kaleidoscopic physiological functions in host health, this review aimed to decipher the impacts of NAS on the gut microbiome by implementing a comprehensive two-stage literature analysis based on each NAS., Results: This review documented disturbed microbiomes due to NAS exposure to a maximal resolution of species level using taxonomic clustering analysis, and recorded metabolism alterations involved in gut microbiome-host interactions., Conclusions: The results elucidated that specific NAS exhibited discrepant impacts on the gut microbiome, even though overlapping on the genera and species were identified. Some NAS caused glucose tolerance impairment in the host, but the key metabolites and their underlying mechanisms were different. Furthermore, this review embodied the challenges and future directions of current NAS-gut microbiome research to inspire advanced examination of the NAS exposure-gut microbiome-host metabolism axis.

The development of efficient and environmentally friendly photocatalysts is crucial for addressing global energy and environmental challenges. Perylene diimide, an organic supramolecular material, holds great potential for applications in mineralized phenol. In this study, through the integration of different mass ratios of unmodified perylenimide (PDI-NH) into the self-assembly of amino acid-substituted perylenimide (PDI-COOH), a novel supramolecular organic heterojunction (PDICOOH/PDINH) was fabricated. The ensuing investigation focuses on its visible-light mineralized phenol properties. The results show that the optimal performance is observed with a composite mass fraction of 10%, leading to complete mineralization of 5 mg/L phenol within 5 h. The reaction exhibits one-stage kinetics with rate constants 13.80 and 1.30 times higher than those of PDI-NH and PDI-COOH, respectively. SEM and TEM reveal a heterogeneous interface between PDI-NH and PDI-COOH. Photoelectrochemical and Kelvin probe characterization confirm the generation of a built-in electric field at the interface, which is 1.73 times stronger than that of PDI-COOH. The introduction of PDI-NH promotes π-π stacking of PDI-COOH, while the built-in electric field facilitates efficient charge transfer at the interface, thereby enhancing phenol decomposition. The finding demonstrates that supramolecular heterojunctions have great potential as highly effective photocatalysts for environmental remediation applications.

Conjugated polymers (CPs) are widely used as conductive materials in various applications, with their conductive properties adjustable through chemical doping. While doping enhances the thermoelectric properties of CPs due to improved main-chain transport, overdoping can distort the polymer structure, increasing energy disorder and impeding intrinsic electrical transport. This study explored how different dopants affect the structural integrity and electrical transport properties of CPs. We found that dopants vary in their impact on CP structure, consequently altering their electrical transport capabilities. Specifically, ferric chloride (FeCl 3 )-doped indacenodithiophene- co -benzothiadiazole (IDTBT) shows superior electrical transport properties to triethyloxonium hexachloroantimonate (OA)-doped IDTBT due to enhanced backbone planarity and rigidity, which facilitate carrier transport and lower energetic disorder. These results highlight the critical role of dopant selection in optimizing CPs for advanced applications, suggesting that strategic dopant choices can significantly refine the charge transport characteristics of CPs, paving the way for their industrialization.

Wearable sensors for sweat trace metal monitoring have the challenges of effective sweat collection and the real-time recording of detection signals. The existing detection technologies are implemented by generating enough sweat through exercise, which makes detecting trace metals in sweat cumbersome. Generally, it takes around 20 min to obtain enough sweat, resulting in dallied and prolonged detection signals that cannot reflect the endogenous fluctuations of the body. To solve these problems, we prepared a multifunctional hydrogel as an electrolyte and combined it with a flexible patch electrode to realize real-time monitoring of sweat Zn 2+ . Such hydrogel has magnetic and porous properties, and the porous structure of hydrogel enables a fast absorption of sweat, and the magnetic property of the addition of fabricated Fe 3 O 4 NPs not only improves the conductivity but also ensures the adjustable internal structures of the hydrogel. Such a sensing platform for sweat Zn 2+ monitoring shows a satisfied linear relationship in the concentration range of 0.16-16 µg/mL via differential pulsed anodic striping voltammetry (DPASV) and successfully detects the sweat Zn 2+ of four volunteers during exercise and resting, displaying a promising path for commercial application.

To enhance the performance of micro-hemispherical gyroscopes, achieving low-damage and high-surface-quality trimming is essential. This enables greater stability and reliability for the gyroscopes. Current methods for reducing frequency split often come with drawbacks such as high cost, adverse effects on the Q-factor, or surface damage. In this paper, a chemical etching trimming method is proposed to reduce frequency split in micro-hemispherical resonators. This method allows for trimming with minimal damage, while also being cost-effective and easy to implement. The theoretical basis of this method was analyzed, followed by a simulation to determine the optimal trimming range and location on the resonator. The simulated Q-factor analysis before and after trimming preliminarily validated the method's low-damage characteristics. Ultimately, the frequency split of the resonator was reduced to below 1 Hz. Additionally, test results of the Q-factor and surface quality before and after trimming further confirmed that chemical etching offers effective low-damage trimming capabilities. The proposed method holds significant potential for improving the performance of micro-hemispherical resonator gyroscopes.

Herein, we simultaneously prepared borax-crosslinked starch-based hydrogels with enhanced mechanical properties and self-healing ability via a simple one-pot method. The focus of this work is to study the effects of the amylose/amylopectin ratio of starch on the grafting reactions and the performance of the resulting borax-crosslinked hydrogels. An increase in the amylose/ amylopectin ratio increased the gel fraction and grafting ratio but decreased the swelling ratio and pore diameter. Compared with hydrogels prepared from low-amylose starches, hydrogels prepared from high-amylose starches showed pronouncedly increased network strength, and the maximum storage modulus increased by 8.54 times because unbranched amylose offered more hydroxyl groups to form dynamic borate ester bonds with borate ions and intermolecular hydrogen bonds, leading to an enhanced crosslink density. In addition, all the hydrogels exhibited a uniformly interconnected network structure. Furthermore, owing to the dynamic borate ester bonds and hydrogen bonds, the hydrogel exhibited excellent recovery behavior under continuous step strain, and it also showed thermal responsiveness.

CdS quantum dots (CdS QDs) are regarded as a promising photocatalyst due to their remarkable response to visible light and suitable placement of conduction bands and valence bands. However, the problem of photocorrosion severely restricts their application. Herein, the CdS QDs-Co 9 S 8 hollow nanotube composite photocatalyst has been successfully prepared by loading Co 9 S 8 nanotubes onto CdS QDs through an electrostatic self-assembly method. The experimental results show that the introduction of Co 9 S 8 cocatalyst can form a stable structure with CdS QDs, and can effectively avoid the photocorrosion of CdS QDs. Compared with blank CdS QDs, the CdS QDs-Co 9 S 8 composite exhibits obviously better photocatalytic hydrogen evolution performance. In particular, CdS QDs loaded with 30% Co 9 S 8 (CdS QDs-30%Co 9 S 8 ) demonstrate the best photocatalytic performance, and the H 2 production rate reaches 9642.7 μmol·g -1 ·h -1 , which is 60.3 times that of the blank CdS QDs. A series of characterizations confirm that the growth of CdS QDs on Co 9 S 8 nanotubes effectively facilitates the separation and migration of photogenerated carriers, thereby improving the photocatalytic hydrogen production properties of the composite. We expect that this work will facilitate the rational design of CdS-based photocatalysts, thereby enabling the development of more low-cost, high-efficiency and high-stability composites for photocatalysis.

To analyze the potential mechanisms of growth differences in spotted seabass ( Lateolabrax maculatus ) fed a low-phosphorus diet, a total of 150 spotted seabass with an initial body weight of 4.49 ± 0.01 g were used (50 fish per tank) and fed a low-phosphorus diet for eight weeks. At the end of the experiment, five of the heaviest and five of the lightest fish were selected from each tank as fast-growing spotted seabass (FG) and slow-growing spotted seabass (SG), respectively, and their livers were analyzed by metabolomics and transcriptomics. The hepatic antioxidant capacity of the FG fed a low-phosphorus diet was significantly higher than that of the SG. A total of 431 differentially expressed genes (DEGs) were determined in the two groups, and most of the DEGs were involved in metabolism-related pathways such as steroid biosynthesis, glycolysis/gluconeogenesis, and protein digestion and absorption. Substance transport-related regulators and transporters were predominantly up-regulated. Furthermore, a large number of metabolites in the liver of FG were significantly up-regulated, especially amino acids, decanoyl-L-carnitine and dehydroepiandrosterone. The integration analysis of differential metabolites and genes further revealed that the interaction between protein digestion and absorption, as well as phenylalanine metabolism pathways were significantly increased in the liver of FG compared to those of the SG. In general, FG fed a low-phosphorus diet induced an enhancement in hepatic immune response, substance transport, and amino acid metabolism. This study provides new information on genetic mechanisms and regulatory pathways underlying differential growth rate and provides a basis for the foundation of efficient utilization of low-phosphorus diets and selective breeding programs for spotted seabass.

Most visual simultaneous localization and mapping (SLAM) systems are based on the assumption of a static environment in autonomous vehicles. However, when dynamic objects, particularly vehicles, occupy a large portion of the image, the localization accuracy of the system decreases significantly. To mitigate this challenge, this paper unveils DOT-SLAM, a novel stereo visual SLAM system that integrates dynamic object tracking through graph optimization. By integrating dynamic object pose estimation into the SLAM system, the system can effectively utilize both foreground and background points for ego vehicle localization and obtain a static feature points map. To rectify the inaccuracies in depth estimation from stereo disparity directly on the foreground points of dynamic objects due to their self-similarity characteristics, a coarse-to-fine depth estimation method based on camera-road plane geometry is presented. This method uses rough depth to guide fine stereo matching, thereby obtaining the 3 dimensions (3D)spatial positions of feature points on dynamic objects. Subsequently, by establishing constraints on the dynamic object's pose using the road plane and non-holonomic constraints (NHCs) of the vehicle, reducing the initial pose uncertainty of dynamic objects leads to more accurate dynamic object initialization. Finally, by considering foreground points, background points, the local road plane, the ego vehicle pose, and dynamic object poses as optimization nodes, through the establishment and joint optimization of a nonlinear model based on graph optimization, accurate six degrees of freedom (DoFs) pose estimations are obtained for both the ego vehicle and dynamic objects. Experimental validation on the KITTI-360 dataset demonstrates that DOT-SLAM effectively utilizes features from the background and dynamic objects in the environment, resulting in more accurate vehicle trajectory estimation and a static environment map. Results obtained from a real-world dataset test reinforce the effectiveness.

Chalcone (1,3-diaryl-2-propen-1-one) is an α, β-unsaturated ketone that serves as an active constituent or precursor of numerous natural substances, exhibiting a broad spectrum of pharmacological effects. In this study, the classical Claisen-Schmidt condensation method was used to synthesize the chalcone derivative 2',4'-dimethoxychalcone (DTC) and evaluate its pharmacological activity. By upregulating the expression of the epithelial cell marker E-cadherin and downregulating the expression of the mesenchymal cell marker vimentin, DTC was found to inhibit transforming growth factor-β1 (TGF-β1)-induced epithelial-mesenchymal transition (EMT) process in A549 cells, maintaining the cells' epithelial-like morphology and reducing the ability of the cells to migrate. Additionally, DTC demonstrated the ability to decrease the expression levels of nitric oxide (NO), tumor necrosis factor (TNF-α), interleukin-6 (IL-6), and interleukin-1β (IL-1β) in RAW264.7 cells, suggesting a possible anti-inflammatory effect. Furthermore, DTC was found to exhibit bacteriostatic activity against Staphylococcus aureus ( S. aureus ), Proteus vulgaris ( P. vulgaris ), methicillin-resistant Staphylococcus aureus (MRSA), and Candida albicans ( C. albicans ), indicating that this chemical may possess broad-spectrum antibacterial activity.

Pulmonary fibrosis (PF) is a disease characterised by diffuse nonspecific alveolar inflammation with interstitial fibrosis, which clinically manifests as dyspnoea and a significant decline in lung function. Many studies have shown that the epithelial-mesenchymal transition (EMT) plays a pivotal role in the pathogenesis of pulmonary fibrosis. Based on our previous findings, hypericin (Hyp) can effectively inhibit the process of the EMT to attenuate lung fibrosis. Therefore, a series of hyperoside derivatives were synthesised via modifying the structure of hyperoside, and subsequently evaluated for A549 cytotoxicity. Among these, the pre-screening of eight derivatives inhibits the EMT. In this study, we evaluated the efficacy of Z6, the most promising hyperoside derivative, in reversing TGF-β1-induced EMTs and inhibiting the EMT-associated migration of A549 cells. After the treatment of A549 cells with Z6 for 48 h, RT-qPCR and Western blot results showed that Z6 inhibited TGF-β1-induced EMTs in epithelial cells by supressing morphological changes in A549 cells, up-regulating E-cadherin ( p < 0.01, p < 0.001), and down-regulating Vimentin ( p < 0.01, p < 0.001). This treatment significantly reduced the mobility of transforming growth factor β1 (TGF-β1)-stimulated cells ( p < 0.001) as assessed by wound closure, while increasing the adhesion rate of A549 cells ( p < 0.001). In conclusion, our results suggest that hyperoside derivatives, especially compound Z6, are promising as potential lead compounds for treating pulmonary fibrosis, and therefore deserve further investigation.

The exceptional corrosion resistance and combined physical and chemical self-cleaning capabilities of superhydrophobic photocatalytic coatings have sparked significant interest among researchers. In this paper, we propose an economical and eco-friendly superhydrophobic epoxy resin coating that incorporates SiO 2 @CuO/HDTMS nanoparticles modified with Hexadecyltrimethoxysilane (HDTMS). The application of superhydrophobic coatings effectively reduces the contact area between the metal surface and corrosive media, leading to a decreased corrosion rate. Additionally, the incorporation of nanomaterials, exemplified by SiO 2 @CuO core-shell nanoparticles, improves the adhesion and durability of the coatings on aluminum alloy substrates. Experimental data from Tafel curve analysis and electrochemical impedance spectroscopy (EIS) confirm the superior corrosion resistance of the superhydrophobic modified aluminum alloy surface compared to untreated surfaces. Estimations indicate a significant reduction in corrosion rate after superhydrophobic treatment. Furthermore, an optical absorption spectra analysis of the core-shell nanoparticles demonstrates their suitability for photocatalytic applications, showcasing their potential contribution to enhancing the overall performance of the coated surfaces. This research underscores the promising approach of combining superhydrophobic properties with photocatalytic capabilities to develop advanced surface modification techniques for enhanced corrosion resistance and functional properties in diverse industrial settings.

Silicon photonic-based refractive index sensors are of great value in the detection of gases, biological and chemical substances. Among them, microring resonators are the most promising due to their compact size and narrow Lorentzian-shaped spectrum. The electric field in a subwavelength grating waveguide (SWG) is essentially confined in the low-refractive index dielectric, favoring enhanced analyte-photon interactions, which represents higher sensitivity. However, it is very challenging to further significantly improve the sensitivity of SWG ring resonator refractive index sensors. Here, a hybrid waveguide blocks double slot subwavelength grating microring resonator (HDSSWG-MRR) refractive index sensor operating in a water refractive index environment is proposed. By designing a new waveguide structure, a sensitivity of up to 1005 nm/RIU has been achieved, which is 182 nm/RIU higher than the currently highest sensitivity silicon photonic micro ring refractive index sensor. Meanwhile, utilizing a unique waveguide structure, a Q of 22,429 was achieved and a low limit of detection of 6.86 × 10 -5 RIU was calculated.

Using metal additive manufacturing processes can make up for traditional forging technologies when forming complex-shaped parts. At the same time, metal additive manufacturing has a fast forming speed and excellent manufacturing flexibility, so it is widely used in the aerospace industry and other fields. The fatigue strength of metal additive manufacturing is related to the microstructure of the epitaxially grown columnar grains and crystallographic texture. The crystal plasticity finite element method is widely used in the numerical simulation of the microstructure and macro-mechanical response of materials, which provides a strengthening and toughening treatment and can reveal the inner rules of material deformation. This paper briefly introduces common metal additive manufacturing processes. In terms of additive manufacturing fatigue, crystal plasticity simulations are summarized and discussed with regard to several important influencing factors, such as the microstructure, defects, surface quality, and residual stress.

Intensive shrimp farming may lead to adverse environmental consequences due to discharged water effluent. Inoculation of microalgae can moderate the adverse effect of shrimp-farming water. However, how bacterial communities with different lifestyles (free-living (FL) and particle-attached (PA)) respond to microalgal inoculation is unclear. In the present study, we investigated the effects of two microalgae ( Nannochloropsis oculata and Thalassiosira weissflogii ) alone or in combination in regulating microbial communities in shrimp-farmed water and their potential applications. PERMANOVA revealed significant differences among treatments in terms of time and lifestyle. Community diversity analysis showed that PA bacteria responded more sensitively to different microalgal treatments than FL bacteria. Redundancy analysis (RDA) indicated that the bacterial community was majorly influenced by environmental factors, compared to microalgal direct influence. Moreover, the neutral model analysis and the average variation degree (AVD) index indicated that the addition of microalgae affected the bacterial community structure and stability during the stochastic process, and the PA bacterial community was the most stable with the addition of T. weissflogii . Therefore, the present study revealed the effects of microalgae and nutrient salts on bacterial communities in shrimp aquaculture water by adding microalgae to control the process of community change. This study is important for understanding the microbial community assembly and interpreting complex interactions among zoo-, phyto-, and bacterioplankton in shrimp aquaculture ecosystems. Additionally, these findings may contribute to the sustainable development of shrimp aquaculture and ecosystem conservation.

The high electrons and holes recombination rate of ZnIn 2 S 4 significantly limits its photocatalytic performance. Herein, a simple in situ photodeposition strategy is adopted to introduce the cocatalyst cobalt phosphate (Co-Pi) on ZnIn 2 S 4 , aiming at facilitating the separation of electron-hole by promoting the transfer of photogenerated holes of ZnIn 2 S 4 . The study reveals that the composite catalyst has superior photocatalytic performance than blank ZnIn 2 S 4 . In particular, ZnIn 2 S 4 loaded with 5% Co-Pi (ZnIn 2 S 4 /5%Co-Pi) has the best photocatalytic activity, and the H 2 production rate reaches 3593 μmol·g -1 ·h -1 , approximately double that of ZnIn 2 S 4 alone. Subsequent characterization data demonstrate that the introduction of the cocatalyst Co-Pi facilitates the transfer of ZnIn 2 S 4 holes, thus improving the efficiency of photogenerated carrier separation. This investigation focuses on the rational utilization of high-content and rich cocatalysts on earth to design low-cost and efficient composite catalysts to achieve sustainable photocatalytic hydrogen evolution.

We propose an air gap fiber Bragg grating (g-FBG) sensor that can measure strain and temperature simultaneously. The sensor is made by aligning two fiber Bragg gratings (FBGs), and an air gap exists between these two sub-gratings. This sensor's architecture allows it to form a spectrum with phase-shifted fiber Bragg grating (PSFBG) spectroscopy and Fabry-Perot interference (FPI) spectroscopy. Since the sensitivity of PSFBG and FPI spectra is different for strain and temperature, it is possible to measure both strain and temperature by measuring one of the reflected dips of PSFBG and the interference dip of FPI. The experimental results show that the strain sensitivity is about 11.95 pm/με via the dip wavelength detection of FPI, and the temperature sensitivity is about 9.64 pm/°C via the dip wavelength detection of PSFBG. The g-FBG sensor demonstrates a resolution of approximately ±3.7 με within the strain range of 0 to 1000 με and about ±0.6 °C within the temperature range of 25 °C to 120 °C. The proposed g-FBG sensor, characterized by its simple structure, compact size, and cost-effectiveness, exhibits significant potential in the field of multi-parameter measurements.

Intelligent vehicles are constrained by road, resulting in a disparity between the assumed six degrees of freedom (DoF) motion within the Visual Simultaneous Localization and Mapping (SLAM) system and the approximate planar motion of vehicles in local areas, inevitably causing additional pose estimation errors. To address this problem, a stereo Visual SLAM system with road constraints based on graph optimization is proposed, called RC-SLAM. Addressing the challenge of representing roads parametrically, a novel method is proposed to approximate local roads as discrete planes and extract parameters of local road planes (LRPs) using homography. Unlike conventional methods, constraints between the vehicle and LRPs are established, effectively mitigating errors arising from assumed six DoF motion in the system. Furthermore, to avoid the impact of depth uncertainty in road features, epipolar constraints are employed to estimate rotation by minimizing the distance between road feature points and epipolar lines, robust rotation estimation is achieved despite depth uncertainties. Notably, a distinctive nonlinear optimization model based on graph optimization is presented, jointly optimizing the poses of vehicle trajectories, LPRs, and map points. The experiments on two datasets demonstrate that the proposed system achieved more accurate estimations of vehicle trajectories by introducing constraints between the vehicle and LRPs. The experiments on a real-world dataset further validate the effectiveness of the proposed system.

Grain size in rice ( Oryza sativa L.) shapes yield and quality, but the underlying molecular mechanism is not fully understood. We functionally characterized GRAIN NUMBER AND LARGE GRAIN SIZE 44 ( GNL44 ), encoding a RING-type protein that localizes to the cytoplasm. The gnl44 mutant has fewer but enlarged grains compared to the wild type. GNL44 is mainly expressed in panicles and developing grains. Grain chalkiness was higher in the gnl44 mutant than in the wild type, short-chain amylopectin content was lower, middle-chain amylopectin content was higher, and appearance quality was worse. The amylose content and gel consistency of gnl44 were lower, and protein content was higher compared to the wild type. Rapid Visco Analyzer results showed that the texture of cooked gnl44 rice changed, and that the taste value of gnl44 was lower, making the eating and cooking quality of gnl44 worse than that of the wild type. We used gnl44 , qgl3 , and gs3 monogenic and two-gene near-isogenic lines to study the effects of different combinations of genes affecting grain size on rice quality-related traits. Our results revealed additive effects for these three genes on grain quality. These findings enrich the genetic resources available for rice breeders.

Liver fibrosis (LF) is a chronic progressive disease with no definitive treatment. The aim of this study was to assess helminth-derived molecules as potential therapeutic targets to prevent or reverse LF. A mouse model of carbon tetrachloride (CCL 4 )-induced LF was established and sja-let-7 was overexpressed by treatment with a miRNA agomir once per week. After four weeks, serum biochemistry, hepatic hydroxyproline content measurements, liver histology, mRNA expression profiling of fibrotic markers, the dual-luciferase reporter assay, and fluorescence in situ hybridization (FISH) were performed. Administration of the sja-let-7 agomir markedly ameliorated hepatosplenomegaly and reduced the liver hydroxyproline content. Liver histological analysis showed significant reductions in collagen deposition in the sja-let-7 agomir-treated mice. Additionally, the mRNA levels of both pro-fibrotic markers and pro-inflammatory cytokines were diminished after treatment. Furthermore, the dual-luciferase reporter assay and FISH identified the α2 chain of collagen type 1 (Col1α2) as the direct target of sja-let-7. Accordingly, the progression of LF was attenuated by targeting Col1α2 and the TGF-β/Smad signaling pathway.

Embedded devices are pervasive nowadays with the rapid development of the Internet of Things (IoT). This brings significant security issues that make the security analysis of embedded devices important. This paper presents a survey on the security analysis research of embedded devices. First, we analyze the embedded device types and their operating systems. Then, we describe a major dynamic security analysis method for an embedded device, i.e., simulating the firmware of the embedded device and performing fuzzing on the web interface provided by the firmware. Third, we discuss some other issues in embedded security analysis, such as analyzing the attack surface, applying static analysis, and performing large-scale analysis. Based on these analyses, we finally conclude three challenges in the current research and present our insights for future research directions.

A valve-controlled hydraulic motor system operating in a complex environment is subject to complex load changes. In extreme cases, the load can be regarded as a disturbance signal with complex frequency and strong amplitude fluctuations, which greatly affects the speed stability of the hydraulic motor and reduces the operating efficiency. In this paper, the structure of valve-controlled hydraulic motor systems is analyzed, and a valve-controlled hydraulic motor system model with uncertain parameters is established after considering the actual target parameter error and model linearization error. Different from the common H-infinity control, which regards the load disturbance as external disturbance, this paper presents a robust H-infinity tracking control strategy, which considers uncertain parameters and the load torque of the valve-controlled hydraulic motor system as internal disturbances. The simulation results show that the proposed control scheme has better control characteristics and robustness than the traditional PID control.

Visual perception plays a crucial role in foraging, avoiding predators, mate selection, and communication. The regulation of color vision is largely dependent on opsin, which is the first step in the formation of the visual transduction cascade in photoreceptor cells. Short-wave-sensitive 1 ( sws1 ) is a visual pigment that mediates short-wavelength light transduction in vertebrates. The depletion of sws1 resulted in increased M-opsin in mice. However, there is still no report on the visual function of sws1 in teleost fish. Here, we constructed the sws1 knockout medaka using CRISPR/Cas9 technology. The 6 dph (days post-hatching) medaka sws1 -/- larvae exhibited significantly decreased food intake and total length at the first feeding stage, and the mRNA levels of orexigenic genes ( npy and agrp ) were significantly upregulated after feeding. The swimming speed was significantly reduced during the period of dark-light transition stimulation in the sws1 -mutant larvae. Histological analysis showed that the thickness of the lens was reduced, whereas the thickness of the ganglion cell layer (GCL) was significantly increased in sws1 -/- medaka larvae. Additionally, the deletion of sws1 decreased the mRNA levels of genes involved in phototransduction ( gnb3b , grk7a , grk7b, and pde6c ). We also observed increased retinal cell apoptosis and oxidative stress in sws1 knockout medaka larvae. Collectively, these results suggest that sws1 deficiency in medaka larvae may impair visual function and cause retinal cell apoptosis, which is associated with the downregulation of photoconduction expression and oxidative stress.

Neuropathic pain (NP) is a chronic and intractable disease that is widely present in the general population. It causes painful behavior and even mood changes such as anxiety and depression by altering the metabolism of substances. However, there have been limited metabolomics studies conducted in relation to neuropathic pain. Therefore, in this study, the effects of NP on metabolites in serum and the dorsal root ganglion (DRG) were investigated using a non-targeted metabolomics approach detected by gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) to uncover differential metabolites and affected metabolic pathways associated with NP. Sixty mice were divided into the following two groups: a chronic constriction injury (CCI) of the sciatic nerve group and a sham group ( n = 30, each). After 7 days of CCI modeling, the metabolite profiles of serum and the DRG were analyzed using GC/LC-MS for both the CCI and sham groups of mice. Multivariate analysis revealed differential metabolites and altered metabolic pathways between the CCI and sham groups. In the CCI group, our findings provided insights into the complex phospholipid, amino acid and acylcarnitine metabolic perturbations of DRG metabolism. In addition, phospholipid metabolic disorders and impaired glucose metabolism were observed in the serum. Moreover, the metabolic differences in the DRG and serum were correlated with each other. The results from this untargeted metabolomics study provide a perspective on the metabolic impact of NP on serum and the DRG.

Currently, real-time semantic segmentation networks are intensely demanded in resource-constrained practical applications, such as mobile devices, drones and autonomous driving systems. However, most of the current popular approaches have difficulty in obtaining sufficiently large receptive fields, and they sacrifice low-level details to improve inference speed, leading to decreased segmentation accuracy. In this paper, a lightweight and efficient multi-level feature adaptive fusion network (MFAFNet) is proposed to address this problem. Specifically, we design a separable asymmetric reinforcement non-bottleneck module, which designs a parallel structure to extract short- and long-range contextual information and use optimized convolution to increase the inference speed. In addition, we propose a feature adaptive fusion module that effectively balances feature maps with multiple resolutions to reduce the loss of spatial detail information. We evaluate our model with state-of-the-art real-time semantic segmentation methods on the Cityscapes and Camvid datasets. Without any pre-training and post-processing, our MFAFNet has only 1.27 M parameters, while achieving accuracies of 75.9% and 69.9% mean IoU with speeds of 60.1 and 82.6 FPS on the Cityscapes and Camvid test sets, respectively. The experimental results demonstrate that the proposed method achieves an excellent trade-off between inference speed, segmentation accuracy and model size.

Prostate-specific membrane antigen (PSMA) is a well-validated prostate cancer marker but reported PSMA-targeted tracers derived from the Lys-urea-Glu pharmacophore including the clinically validated [ 99m Tc]Tc-EDDA/HYNIC-iPSMA have high off-target uptake in kidneys, spleen, and salivary glands. In this study, we synthesized and evaluated three novel 99m Tc-labeled PSMA-targeted tracers and investigated if the tracers derived from the Lys-urea-Aad pharmacophore could have minimized uptake in off-target organs/tissues. In vitro competition binding assays showed that compared with HYNIC-iPSMA, the three novel ligands had slightly weaker PSMA binding affinity (average K i = 3.11 vs. 8.96-11.6 nM). Imaging and ex vivo biodistribution studies in LNCaP tumor-bearing mice showed that [ 99m Tc]Tc-EDDA/HYNIC-iPSMA and the three novel tracers successfully visualized LNCaP tumor xenografts in SPECT images and were excreted mainly via the renal pathway. The average tumor uptake at 1 h post-injection varied from 5.40 to 18.8%ID/g, and the tracers derived from the Lys-urea-Aad pharmacophore had much lower uptake in the spleen and salivary glands. Compared with the clinical tracer [ 99m Tc]Tc-EDDA/HYNIC-iPSMA, the Lys-urea-Aad-derived [ 99m Tc]Tc-EDDA-KL01127 had lower background uptake and superior tumor-to-background contrast ratios and is therefore promising for clinical translation to detect prostate cancer lesions with SPECT.

Afatinib, the world's first irreversible ErbB family (containing four different cancer cell epidermal growth factor receptors, including EGFR, HER2, ErbB3, and ErbB4) inhibitor, is a second-generation oral epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI). It can be used as a first-line treatment for locally advanced or metastatic non-small-cell lung cancer (NSCLC) with an EGFR-sensitive mutation or for patients with locally advanced or metastatic squamous lung cancer whose disease progresses during or after platinum-containing chemotherapy. Currently, with the use of third-generation EGFR-TKIs, afatinib is no longer clinically indicated as the first choice for patients with NSCLC who have EGFR-sensitive mutations. However, afatinib showed a considerable inhibitory effect in NSCLC patients with uncommon EGFR mutations (G719X, S768I, and L861Q) according to a combined post hoc analysis of the LUX-Lung2/3/6 trials. With the development of genetic testing technology, the detection rate of uncommon EGFR mutations is increasing. The aim of this paper is to describe in detail the sensitivity of rare EGFR mutations to afatinib and to provide information and a reference for those suffering from advanced NSCLC who have uncommon EGFR mutations.

Worldwide, breast cancer is the most common malignancy. LHX2, a member of the LIM homeobox gene family and a transcription factor, plays a crucial role in numerous tumors, but the function of LHX2 in breast cancer progression remains unknown. In this study, we show that LHX2 is upregulated in breast cancer tissues and positively correlated with breast cancer progression. Meanwhile, the clinical characteristics of breast cancer and LHX2 expression showed a strong correlation. GSEA showed that a high LHX2 expression may activate the T-cell activation pathway, PI3K/AKT/mTOR signaling pathway, and apoptosis pathway. Moreover, ssGSEA showed that Th1 cells and Th2 cells had a positive correlation with LHX2 expression in breast cancer. Experiments showed that LHX2 promotes the proliferation, colony formation, migration, and invasion of breast cancer cells. Immunohistochemistry and immunofluorescence assays helped to analyze LHX2-associated immune infiltration in breast cancer. A Western blot assay proved that LHX2 activated the PI3K/AKT/mTOR pathway and the apoptosis pathway. A TUNEL assay confirmed that LHX2 inhibited apoptosis. Taken together, LHX2 plays a vital role in breast cancer's progression and prognosis and could be an immune infiltration biomarker for breast cancer, and LHX2 activates the PI3K/AKT/mTOR pathway and apoptosis pathway in breast cancer.

The medaka ( Oryzias latipes ) is an excellent vertebrate model for studying the development of the retina. Its genome database is complete, and the number of opsin genes is relatively small compared to zebrafish. Short wavelength sensitive 2 ( sws2 ), a G-protein-coupled receptor expressed in the retina, has been lost in mammals, but its role in eye development in fish is still poorly understood. In this study, we established a sws2a and sws2b knockout medaka model by CRISPR/Cas9 technology. We discovered that medaka sws2a and sws2b are mainly expressed in the eyes and may be regulated by growth differentiation factor 6a ( gdf6a ). Compared with the WT, sws2a -/- and sws2b -/- mutant larvae displayed an increase in swimming speed during the changes from light to dark. We also observed that sws2a -/- and sws2b -/- larvae both swam faster than WT in the first 10 s of the 2 min light period. The enhanced vision-guided behavior in sws2a -/- and sws2b -/- medaka larvae may be related to the upregulation of phototransduction-related genes. Additionally, we also found that sws2b affects the expression of eye development genes, while sws2a is unaffected. Together, these findings indicate that sws2a and sws2b knockouts increase vision-guided behavior and phototransduction, but on the other hand, sws2b plays an important role in regulating eye development genes. This study provides data for further understanding of the role of sws2a and sws2b in medaka retina development.

In this paper, the copolymerization of poly (p-dioxanone) (PPDO) and polylactide (PLA) was carried out via a Diels-Alder reaction to obtain a new biodegradable copolymer with self-healing abilities. By altering the molecular weights of PPDO and PLA precursors, a series of copolymers (DA2300, DA3200, DA4700 and DA5500) with various chain segment lengths were created. After verifying the structure and molecular weight by 1H NMR, FT-IR and GPC, the crystallization behavior, self-healing properties and degradation properties of the copolymers were evaluated by DSC, POM, XRD, rheological measurements and enzymatic degradation. The results show that copolymerization based on the DA reaction effectively avoids the phase separation of PPDO and PLA. Among the products, DA4700 showed a better crystallization performance than PLA, and the half-crystallization time was 2.8 min. Compared to PPDO, the heat resistance of the DA copolymers was improved and the Tm increased from 93 °C to 103 °C. Significantly, the rheological data also confirmed that the copolymer was self-healing and showed obvious self-repairing properties after simple tempering. In addition, an enzyme degradation experiment showed that the DA copolymer can be degraded by a certain amount, with the degradation rate lying between those of PPDO and PLA.

Ethylene Insensitive 2 (EIN2) is an integral membrane protein that regulates ethylene signaling towards plant development and immunity by release of its carboxy-terminal functional portion (EIN2C) into the nucleus. The present study elucidates that the nuclear trafficking of EIN2C is induced by importin β1, which triggers the phloem-based defense (PBD) against aphid infestations in Arabidopsis. In plants, IMPβ1 interacts with EIN2C to facilitate EIN2C trafficking into the nucleus, either by ethylene treatment or by green peach aphid infestation, to confer EIN2-dependent PBD responses, which, in turn, impede the phloem-feeding activity and massive infestation by the aphid. In Arabidopsis, moreover, constitutively expressed EIN2C can complement the impβ1 mutant regarding EIN2C localization to the plant nucleus and the subsequent PBD development in the concomitant presence of IMPβ1 and ethylene. As a result, the phloem-feeding activity and massive infestation by green peach aphid were highly inhibited, indicating the potential value of EIN2C in protecting plants from insect attacks.

Conventional methods to prepare supported metal catalysts are chemical reduction and wet impregnation. This study developed and systematically investigated a novel reduction method based on simultaneous Ti 3 AlC 2 fluorine-free etching and metal deposition to prepare gold catalysts. The new series of Au pre /Ti 3 Al x C 2 Ty catalysts were characterized by XRD, XPS, TEM, and SEM and were tested in the selective oxidation of representative aromatic alcohols to aldehydes. The catalytic results demonstrate the effectiveness of the preparation method and better catalytic performances of Au pre /Ti 3 Al x C 2 T y , compared with those of catalysts prepared by traditional methods. Moreover, this work presents a comprehensive study on the influence of calcination in air, H 2 , and Ar, and we found that the catalyst of Au pre /Ti 3 Al x C 2 T y -Air600 obtained by calcination in air at 600 °C performed the best, owing to the synergistic effect between tiny surface TiO 2 species and Au NPs. The tests of reusability and hot filtration confirmed the catalyst stability.

OTUD5 (OTU Deubiquitinase 5) is a functional cysteine protease with deubiquitinase activity and is a member of the ovarian tumor protease (OTU) family. OTUD5 is involved in the deubiquitination of many key proteins in various cellular signaling pathways and plays an important role in maintaining normal human development and physiological functions. Its dysfunction can affect physiological processes, such as immunity and DNA damage repair, and it can even lead to tumors, inflammatory diseases and genetic disorders. Therefore, the regulation of OTUD5 activity and expression has become a hot topic of research. A comprehensive understanding of the regulatory mechanisms of OTUD5 and its use as a therapeutic target for diseases is of great value. Herein, we review the physiological processes and molecular mechanisms of OTUD5 regulation, outline the specific regulatory processes of OTUD5 activity and expression, and link OTUD5 to diseases from the perspective of studies on signaling pathways, molecular interactions, DNA damage repair and immune regulation, thus providing a theoretical basis for future studies.

Embodied PointGoal navigation is a fundamental task for embodied agents. Recent works have shown that the performance of the embodied navigation agent degrades significantly in the presence of visual corruption, including Spatter, Speckle Noise, and Defocus Blur, showing the weak robustness of the agent. To improve the robustness of embodied navigation agents to various visual corruptions, we propose a navigation framework called Regularized Denoising Masked AutoEncoders Navigation (RDMAE-Nav). In a nutshell, RDMAE-Nav mainly consists of two modules: a visual module and a policy module. In the visual module, a self-supervised pretraining method, dubbed Regularized Denoising Masked AutoEncoders (RDMAE), is designed to enable the Vision Transformers (ViT)-based visual encoder to learn robust representations. The bidirectional Kullback-Leibler divergence is introduced in RDMAE as the regularization term for a denoising masked modeling task. Specifically, RDMAE mitigates the gap between clean and noisy image representations by minimizing the bidirectional Kullback-Leibler divergence. Then, the visual encoder is pretrained by RDMAE. In contrast to existing works, RDMAE-Nav applies denoising masked visual pretraining for PointGoal navigation to improve robustness to various visual corruptions. Finally, the pretrained visual encoder with frozen weights is applied to extract robust visual representations for policy learning in the RDMAE-Nav. Extensive experiments show that RDMAE-Nav performs competitively compared with state of the arts (SOTAs) on various visual corruptions. In detail, RDMAE-Nav performs the absolute improvement: 28.2% in SR and 23.68% in SPL under Spatter; 2.28% in SR and 6.41% in SPL under Speckle Noise; and 9.46% in SR and 9.55% in SPL under Defocus Blur.

With the development of urban road traffic, road noise pollution is becoming a public concern. Controlling and reducing the harm caused by traffic noise pollution have been the hot spots of traffic noise management research. The subjective annoyance level of traffic noise has become one of the most important measurements for evaluating road traffic pollution. There are subjective experimental methods and objective prediction methods to assess the annoyance level of traffic noise: the subjective experimental method usually uses social surveys or listening experiments in laboratories to directly assess the subjective annoyance level, which is highly reliable, but often requires a lot of time and effort. The objective method extracts acoustic features and predicts the annoyance level through model mapping. Combining the above two methods, this paper proposes a deep learning model-based objective annoyance evaluation method, which directly constructs the mapping between the noise and annoyance level based on the listening experimental results and realizes the rapid evaluation of the noise annoyance level. The experimental results show that this method has reduced the mean absolute error by 30% more than the regression algorithm and neural network, while its performance is insufficient in the annoyance interval where samples are lacking. To solve this problem, the algorithm adopts transfer learning to further improve the robustness with a 30% mean absolute error reduction and a 5% improvement in the correlation coefficient between the true results and predicted results. Although the model trained on college students' data has some limitations, it is still a useful attempt to apply deep learning to noise assessment.

Several observational studies have indicated an association between high serum levels of branched-chain amino acids (BCAAs) and an increased risk of cardiovascular disease (CVD). To assess whether theses associations reflect causality, we carried out two-sample Mendelian randomization (MR). Single-nucleotide polymorphisms (SNPs) associated with BCAA were evaluated in 10 studies, including 24,925 participants. The association between SNPs and coronary artery disease (CAD) were assessed using summary estimates from the CARDIoGRAMplusC4D consortium. Further MR analysis of BCAAs and seven CVD outcomes was performed. The BCAA-raising gene functions were also analyzed. MR analyses revealed a risk-increasing causal relationship between serum BCAA concentrations and CAD (odds ratio 1.08; 95% confidence interval (CI) 1.02-1.14), which was partly mediated by blood pressure and type 2 diabetes. BCAA also demonstrated a causal relationship with ischemic CVD events induced by plaque rupture and thrombosis (false discovery rate <0.05). Two BCAA-raising genes ( MRL33 and CBLN1 ) were preferentially associated with myocardial infarction risk in the presence of atherosclerosis ( p < 0.003). Functional analysis of the BCAA-raising genes suggested the causal involvement of two pathophysiological pathways, including glucose metabolism ( PPM1K and TRMT61A ) related to plaque progression, and the newly discovered neuroendocrine disorders regulating blood pressure ( MRPL33 , CBLN1 , and C2orf16 ) related to plaque rupture and thrombosis. This comprehensive MR analysis provided insights into the potential causal mechanisms linking BCAA with CVD risk and suggested targeting neuroendocrine disorders as a potential strategy for the prevention of CVD. These results warrant further studies to elucidate the mechanisms underlying these reported causal associations.

The green and clean sunlight-driven catalytic conversion of CO 2 into high-value-added chemicals can simultaneously solve the greenhouse effect and energy problems. The controllable preparation of semiconductor catalyst materials and the study of refined structures are of great significance for the in-depth understanding of solar-energy-conversion technology. In this study, we prepared nitrogen-doped NiO semiconductors using a one-pot molten-salt method. The research shows that the molten-salt system made NiO change from p-type to n-type. In addition, nitrogen doping enhanced the adsorption of CO 2 on NiO and increased the separation of photogenerated carriers on the NiO. It synergistically optimized the CO 2 -reduction system and achieved highly active and selective CO 2 photoreduction. The CO yield on the optimal nitrogen-doped photocatalyst was 235 μmol·g -1 ·h -1 (selectivity 98%), which was 16.8 times that of the p-type NiO and 2.4 times that of the n-type NiO. This can be attributed to the fact that the nitrogen doping enhanced the oxygen vacancies of the NiOs and their ability to adsorb and activate CO 2 molecules. Photoelectrochemical characterization also confirmed that the nitrogen-doped NiO had excellent electron -transfer and separation properties. This study provides a reference for improving NiO-based semiconductors for photocatalytic CO 2 reduction.

Mutation rate is a crucial parameter in evolutionary genetics. However, the mutation rate of most species as well as the extent to which the environment can alter the genome of multicellular organisms remain poorly understood. Here, we used parents-progeny sequencing to investigate the mutation rate and spectrum of the domestic silkworm ( Bombyx mori ) among normal and two temperature stress conditions (32 °C and 0 °C). The rate of single-nucleotide mutations in the normal temperature rearing condition was 0.41 × 10 -8 (95% confidence interval, 0.33 × 10 -8 -0.49 × 10 -8 ) per site per generation, which was up to 1.5-fold higher than in four previously studied insects. Moreover, the mutation rates of the silkworm under the stresses are significantly higher than in normal conditions. Furthermore, the mutation rate varies less in gene regions under normal and temperature stresses. Together, these findings expand the known diversity of the mutation rate among eukaryotes but also have implications for evolutionary analysis that assumes a constant mutation rate among species and environments.

Regional lymph node metastasis (LNM) increases the risk of distant metastasis in papillary thyroid cancer (PTC) patients. However, it remains unclear how tumor cells in PTC patients with LNM evade immune system surveillance and proceed to colonize distant organs. Here, we comprehensively characterize the tumor-infiltrating immune cell landscape in PTC with LNM. LNM-related genes include multiple important soluble mediators such as CXCL6, IL37, MMP10, and COL11A1, along with genes involved in areas such as extracellular matrix organization and TLR regulation by endogenous ligands. In PTC without LNM, the tumor infiltration of activated dendritic cells and M0 macrophages showed increases from normal cells, but with yet greater increases and correspondingly worse prognosis in PTC with LNM. Conversely, the tumor infiltration of activated NK cells and eosinophils was decreased in PTC without LNM, as compared to normal cells, and yet further decreased in PTC with LNM, with such decreases associated with poor prognosis. We further demonstrate that mutations of driver genes in tumor cells influence the infiltration of surrounding immune cells in the tumor microenvironment (TME). Particularly, patients carrying TG mutations tend to show increased filtration of M2 macrophages and activated NK cells in the TME, whereas patients carrying HRAS mutations tend to show reduced filtration of M0 macrophages and show enhanced filtration of activated dendritic cells in the TME. These findings increase our understanding of the mechanisms of regional lymph node metastasis in PTC and its associated tumor microenvironment, potentially facilitating the development of personalized treatment regimens to combat immunotherapy failure.

Hepatic encephalopathy (HE) is a neuropsychiatric syndrome derived from metabolic disorders due to various liver failures. Clinically, HE is characterized by hyperammonemia, EEG abnormalities, and different degrees of disturbance in sensory, motor, and cognitive functions. The molecular mechanism of HE has not been fully elucidated, although it is generally accepted that HE occurs under the influence of miscellaneous factors, especially the synergistic effect of toxin accumulation and severe metabolism disturbance. This review summarizes the recently discovered cellular mechanisms involved in the pathogenesis of HE. Among the existing hypotheses, ammonia poisoning and the subsequent oxidative/nitrosative stress remain the mainstream theories, and reducing blood ammonia is thus the main strategy for the treatment of HE. Other pathological mechanisms mainly include manganese toxicity, autophagy inhibition, mitochondrial damage, inflammation, and senescence, proposing new avenues for future therapeutic interventions.

When a fire occurs in a street canyon, smoke recirculation is the most harmful factor to human beings inside the canyon, while the wind condition is an essential factor determining if the smoke is recirculated. This paper focuses on the wind direction's effect on buoyancy-driven fire smoke dispersion in a street canyon, which is innovative research since the effect of wind direction has not been reported before. In this study, an ideal street canyon model with a height-width ratio of 1 was established, and both the wind velocity and wind direction were changed to search for the critical point at which smoke recirculation occurs. The results show that with an increase in the wind direction angle (the angle of wind towards the direction of the street width), the smoke recirculation could be distinguished into three regimes, i.e., the "fully re-circulation stage", the "semi re-circulation stage", and the "non-recirculation stage". The critical recirculation velocity was increased with the increase in the wind direction angle, and new models regarding the critical wind velocity and the Froude number were proposed for different wind direction conditions.

Argonautes (AGOs) interact with microRNAs (miRNAs) to form the RNA-induced silencing complex (RISC), which can posttranscriptionally regulate the expression of targeted genes. To date, however, the AGOs and their miRNA triggers remain elusive in rapeseed ( Brassica napus ). Here, we systematically performed a phylogenetic analysis and examined the collinear relationships of the AGOs among four Brassicaceae species. Their physicochemical properties, gene structures, and expression patterns among 81 tissues from multiple materials and developmental stages were further analyzed. Additionally, their posttranscriptional regulation was analyzed using psRNATarget prediction, miRNA-/mRNA-Seq analyses, and a qRT-PCR verification. We finally identified 10 AtAGOs, 13 BolAGOs, 11 BraAGOs, and 24 BnaAGOs. An expression analysis of the BnaAGO s in the B. napus cultivar ZS11, as well as genotypes with extreme phenotypes in various yield-related traits, revealed the conservation and diversity of these genes. Furthermore, we speculated the posttranscriptional regulation of the B. napus miR168a-AGO1s and miR403-AGO2s modules. Combining miRNA-Seq and mRNA-Seq analyses, we found that the B. napus miR168a-AGO1s module may play an essential role in negatively regulating yield traits, whereas the miR403-AGO2s module positively impacts yield. This is the first attempt to comprehensively analyze the AGOs and their miRNA triggers in B. napus and provides a theoretical basis for breeding high-yielding varieties through the manipulation of the miRNA-AGOs modules.

Motor imagery brain-computer interface (MI-based BCIs) have demonstrated great potential in various applications. However, to well generalize classifiers to new subjects, a time-consuming calibration process is necessary due to high inter-subject variabilities of EEG signals. This process is costly and tedious, hindering the further expansion of MI-based BCIs outside of the laboratory. To reduce the calibration time of MI-based BCIs, we propose a novel domain adaptation framework that adapts multiple source subjects' labeled data to the unseen trials of target subjects. Firstly, we train one Subject Separation Network(SSN) for each of the source subjects in the dataset. Based on adversarial domain adaptation, a shared encoder is constructed to learn similar representations for both domains. Secondly, to model the factors that cause subject variabilities and eliminate the correlated noise existing in common feature space, private feature spaces orthogonal to the shared counterpart are learned for each subject. We use a shared decoder to validate that the model is actually learning from task-relevant neurophysiological information. At last, an ensemble classifier is built by the integration of the SSNs using the information extracted from each subject's task-relevant characteristics. To quantify the efficacy of the framework, we analyze the accuracy-calibration cost trade-off in MI-based BCIs, and theoretically guarantee a generalization bound on the target error. Visualizations of the transformed features illustrate the effectiveness of domain adaptation. The experimental results on the BCI Competition IV-IIa dataset prove the effectiveness of the proposed framework compared with multiple classification methods. We infer from our results that users could learn to control MI-based BCIs without a heavy calibration process. Our study further shows how to design and train Neural Networks to decode task-related information from different subjects and highlights the potential of deep learning methods for inter-subject EEG decoding.