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Abstract Background PSEUDO RESPONSE REGULATOR (PRR) genes are essential components of circadian clock, playing vital roles in multiple processes including plant growth, flowering and stress response. Nonetheless, little is known about the evolution and function of PRR family in Rosaceae species. Results In this study, a total of 43 PRR genes in seven Rosaceae species were identified through comprehensive analysis. The evolutionary relationships were analyzed with phylogenetic tree, duplication events and synteny. PRR genes were classified into three groups (PRR1, PRR5/9, PRR3/7). The expansion of PRR family was mainly derived from dispersed and whole-genome duplication events. Purifying selection was the major force for PRR family evolution. Synteny analysis indicated the existence of multiple orthologous PRR gene pairs between pear and other Rosaceae species. Moreover, the conserved motifs of eight PbPRR proteins supported the phylogenetic relationship. PRR genes showed diverse expression pattern in various tissues of pear (Pyrus bretschneideri). Transcript analysis under 12-h light/ dark cycle and constant light conditions revealed that PRR genes exhibited distinct rhythmic oscillations in pear. PbPRR59a and PbPRR59b highly homologous to AtPRR5 and AtPRR9 were cloned for further functional verification. PbPRR59a and PbPRR59b proteins were localized in the nucleus. The ectopic overexpression of PbPRR59a and PbPRR59b significantly delayed flowering in Arabidopsis transgenic plants by repress the expression of AtGI, AtCO and AtFT under long-day conditions. Conclusions These results provide information for exploring the evolution of PRR genes in plants, and contribute to the subsequent functional studies of PRR genes in pear and other Rosaceae species.

Abstract The SARS-CoV-2 Omicron variant sparked the largest wave of infections worldwide. Mainland China eased its strict COVID-19 measures in late 2022 and experienced two nationwide Omicron waves in 2023. Here, we investigated lineage distribution and virus evolution in Guangdong, China, 2022-2023 by comparing 5813 local viral genomes with the datasets from other regions of China and worldwide. Additionally, we conducted three large-scale serological surveys involving 1696 participants to measure their immune response to the BA.5 and XBB.1.9 before and after the corresponding waves. Our findings revealed the Omicron variants, mainly the BA.5.2.48 lineage, causing infections in over 90% of individuals across different age groups within a month. This rapid spread led to the establishment of widespread immunity, limiting the virus’s ability to further adaptive mutation and dissemination. While similar immune responses to BA.5 were observed across all age groups after the initial wave, children aged 3 to 11 developed a stronger cross immune response to the XBB.1.9 strain, possibly explaining their lower infection rates in the following XBB.1 wave. Reinfection with Omicron XBB.1 variant triggered a more potent neutralizing immune response among older adults. These findings highlight the impact of age-specific immune responses on viral spread in potential future waves.

Bile acids (BAs) are natural metabolites in mammals and have the potential to function as drugs against viral infection. However, the limited understanding of chenodeoxycholic acid (CDCA) receptors and downstream signaling, along with its lower suppression efficiency in inhibiting virus infection limits its clinical application. In this study, we demonstrate that farnesoid X receptor (FXR), the receptor of CDCA, negatively regulates interferon signaling, thereby contributing to the reduced effectiveness of CDCA against virus replication. FXR deficiency or pharmacological inhibition enhances interferon signaling activation to suppress virus infection. Mechanistically, FXR impairs the DNA binding and transcriptional abilities of activated interferon regulatory factor 3 (IRF3) through interaction. Reduced IRF3 transcriptional activity by FXR–IRF3 interaction significantly undermines the expression of Interferon Beta 1 (IFNB1) and the antiviral response of cells, especially upon the CDCA treatment. In FXR-deficient cells, or when combined with Z-guggulsterone (GUGG) treatment, CDCA exhibits a more potent ability to restrict virus infection. Thus, these findings suggest that FXR serves as a limiting factor for CDCA in inhibiting virus replication, which can be attributed to the “signaling-brake” roles of FXR in interferon signaling. Targeting FXR inhibition represents a promising pharmaceutical strategy for the clinical application of BAs metabolites as antiviral drugs.

Abstract The coalbed methane (CBM) productivity is directly determined by the fracture permeability during hydraulic fracturing, which is regulated by the distribution of proppants. The proppant may be unevenly distributed in the fracture because of variables like the architecture of the fracture and the characteristics of the sand‐carrying fluid. This study used two types of random functions to produce different ununiform distributions of proppant clusters in large‐scale fractures, with the aim of investigating the effect of these distributions on the overall permeability of the fracture. A model of fluid‐structure coupling is proposed. The closure of large‐scale fractures under in‐situ stress is analyzed using solid mechanics and the penalty function; the CBM flowing in proppant clusters and the high‐speed channel between them is simulated using Darcy's law and the Navier–Stokes equation, respectively; and the overall permeability of fractures is computed using the fluid pressure drop throughout the fracture and the fluid flowing velocity in the fracture's outlet. Since most CBM flows along high‐speed channels between the proppant clusters, the simulated findings show that the overall permeability of fractures with an uneven distribution of proppant clusters is significantly higher than that of the proppant cluster itself. As CBM becomes more discretely distributed, the proportion of CBM flowing within the proppant cluster continuously drops. As the permeability of the proppant cluster increases, the volume ratio of proppant clusters decreases, and the distribution of proppant clusters becomes more discrete, the overall permeability of the fracture continuously increases.

ABSTRACTChina has a large population and is also a big agricultural country. Food security is an important strategic issue related to China’s national economy and people’s livelihood. Corn is one of the main food crops in China, its yield and quality are closely related to China’s growing grain demand. Improper field harvest, failure to dry out in time, and qualitative changes during the storage process will lead to yield loss. In this study, the issue of timely corn harvest, the growth curve, and the antioxidant enzyme activity of corn kernels were measured throughout the harvest process. The mathematical models of the change of moisture content, dry weight, and antioxidant enzyme activity were established, and the optimal harvest period was determined. The results showed that the moisture content of corn kernels decreased with the increase in harvest time. With the increase in harvest period, the dry weight of corn kernels accumulated in the early stage, when the dry weight of corn kernels entered the ripening period on October 3rd, the accumulation of dry weight tended to be a maximum and no longer increased. After that, there was even a decrease in dry weight which was called hidden loss, the trend of four varieties dry weight was different. The antioxidant enzyme activities of POD (peroxidase), CAT (catalase), and SOD (superoxide) of corn kernels were tended to rise first and then decline, there were significant differences between different varieties. The optimal harvest period for each corn variety was determined according to the change of moisture content, dry matter weight, and antioxidant enzyme activity.

In the Vehicle-to-Grid (V2G) scenario, a multitude of coordinated electric vehicles (EVs) equipped with high-capacity batteries actively participate in power grid dispatching as energy carriers, aiming to achieve a tripartite objective encompassing peak load reduction and valley filling, enhanced utilization of renewable energy sources, and added benefits for electric vehicle owners. To address the existing limitations in the charging–discharging decision-making process for electric vehicles based on V2G, such as the lack of consideration for charging pile constraints, EV profitability, EV transportation timeliness, and high costs associated with central servers, we proposed a reinforcement learning-based Multi-vehicle Joint Routing and Charging–Discharging Decision algorithm (MJRCDD). Firstly, the Markov decision process (MDP) was established to describe the problem, and the route selection and charging–discharging behavior of the vehicle were innovatively integrated in the vehicle action space. Secondly, the multi-vehicle joint route planning and charging–discharging decision problem was solved by multi-agent reinforcement learning. Finally, the effectiveness of MJRCDD was verified by simulation and comparison experiments based on PeMS.

Introduction To investigate the toxicity of combretastatin A4 phosphate (CA4P) hyaluronic acid (HA) gel nanoparticles (HA-CA4P-NPs) in OSCC (oral squamous cell carcinoma). Methods Toxicity was investigated using fluorescence microscopy, MTT as-say, flow cytometry, and OSCC xenograft mouse models. Results Compared with CA4P, HA-CA4P-NPs generated nearly 10 times more fluorescence in OSCC cells. Cytotoxicity assays showed that HACA4P-NPs were more toxic to SCC-4 cells but not to HNECs. Remarkable necrosis was induced in SCC-4 cells after exposure to HA-CA4P-NPs, and related proteins were upregulated. Furthermore, HA-CA4P-NPs significantly reduced the tu-mour size. Conclusions HA-CA4P-NPs improved drug release and delivery, and in-creased cytotoxicity to cancer cells.

Abstract To assess the concentration characteristics and ecological risks of potential toxic elements (PTEs) in water and sediment, 17 water samples and 17 sediment samples were collected in the Xiyu River to analyze the content of Cr, Ni, As, Cu, Zn, Pb, Cd and Hg, and the environmental risks of PTEs was evaluated by single-factor pollution index, Nemerow comprehensive pollution index, potential ecological risk, and human health risk assessment. The results indicated that Hg in water and Pb, Cu, Cd in sediments exceeded the corresponding environmental quality standards. In the gold mining factories distribution river section (X8-X10), there was a significant increase in PTEs in water and sediments, indicating that the arbitrary discharge of tailings during gold mining flotation is the main cause of PTEs pollution. The increase in PTEs concentration at the end of the Xiyu River may be related to the increased sedimentation rate, caused by the slowing of the riverbed, and the active chemical reactions at the estuary. The single-factor pollution index and Nemerow pollution index indicated that the river water was severely polluted by Hg. Potential ecological risk index indicated that the risk of Hg in sediments was extremely high, the risk of Cd was high, and the risk of Pb and Cu was moderate. The human health risk assessment indicated that As in water at point X10 and Hg in water at point X9 may pose non-carcinogenic risk to children through ingestion, and As at X8–X10 and Cd at X14 may pose carcinogenic risk to adults through ingestion. The average HQingestion value of Pb in sediments was 1.96, indicating that the ingestion of the sediments may poses a non-carcinogenic risk to children, As in the sediments at X8–X10 and X15–X17 may pose non-carcinogenic risk to children through ingestion.

The applications of clustering in biomedical is pervasive and ubiquitous. A typical example is gene expression data analysis, where clustering is emerging as a powerful solution for uncovering cancer-related insights. Neutrosophic c-means (NCM) clustering has advantages over other conventional clustering methods in characterizing the uncertainty and imprecision caused by cluster overlap and identifying outliers. Nonetheless, NCM and its derivatives equally treat the contribution of each attribute to the cluster. In biomedical applications, genes (i.e. attributes) should take different importance in identifying different clusters. In this paper, we first propose a self-adaptive attribute-weighted neutrosophic c-means (AWNCM) clustering method to overcome the above defects. Moreover, a new objective function is designed to obtain optimal neutrosophic partition, cluster centers and attribute weights. Since AWNCM tends to be more effective against spherical data, we further develop a kernelized version of AWNCM, called KAWNCM, in order to better satisfy the clustering of some complex data (i.e. non-spherical data). We employ the iterative optimization strategy to obtain the optimal solutions for AWNCM and KAWNCM. The advantage of AWNCM and KAWNCM is to improve performance by learning the importance of each attribute to the cluster while maintaining an efficient solution to cluster overlap and outliers. Extensive experimental results using synthetic data and gene expression data demonstrate the feasibility and effectiveness of the proposed methods.

The high-temperature mechanical properties and tribological behavior of the Al0.5CoCrFeNb0.5Ni high-entropy alloy (HEA) were investigated. The results show that Al0.5CoCrFeNb0.5Ni HEA consists of FCC, BCC and (Cr–Co–Fe)2Nb-type Laves phases. The hardness is about 572 HV at room temperature and decreases slightly at high temperatures, still maintaining a high value (>350 HV) at 900 °C. The yield strength is nearly 2000 MPa at room temperature and tends to decrease with rising temperature (800–1200 °C). The observation of the microstructure after the hot compression tests and the evaluation of the true stress-strain curves illustrate that the softening mechanism is primarily dynamic recrystallization, which occurs mainly in the FCC and BCC phases. The degree of wear increases and then decreases from 200 °C to 800 °C. The best wear resistance was observed at 800 °C, showing the maximum friction coefficient and the minimum wear rate, which was attributed to the increased oxidation that formed oxide layers mainly consisting of Cr2O3 to protect the wear surfaces. The wear mechanism of alloys is affected by temperature. Below 400 °C the wear is mainly abrasive and adhesive wear, at temperatures above 600 °C, the wear transitions from abrasive to oxidative wear, and at 800 °C the wear changes to oxidative wear.

Abstract In the nucleus, biological processes are driven by proteins that diffuse through and bind to a meshwork of nucleic acid polymers. To better understand this interplay, we present an imaging platform to simultaneously visualize single protein dynamics together with the local chromatin environment in live cells. Together with super-resolution imaging, new fluorescent probes, and biophysical modeling, we demonstrate that nucleosomes display differential diffusion and packing arrangements as chromatin density increases whereas the viscoelastic properties and accessibility of the interchromatin space remain constant. Perturbing nuclear functions impacts nucleosome diffusive properties in a manner that is dependent both on local chromatin density and on relative location within the nucleus. Our results support a model wherein transcription locally stabilizes nucleosomes while simultaneously allowing for the free exchange of nuclear proteins. Additionally, they reveal that nuclear heterogeneity arises from both active and passive processes and highlight the need to account for different organizational principles when modeling different chromatin environments.

Abstract Background To analyze the curvature characteristics of the talus trochlea in people from northern China in different sex and age groups. Methods Computed tomography scanning data of talus from 61 specimens were collected and constructed as a three-dimensional model by Materialise’s Interactive Medical Image Control System(MIMICS) software, anteromedial(AM), posteromedial(PM), anterolateral(AL), and posterolateral(PL) edge, anterior edge of medial trochlea, posterior edge of medial trochlea and anterior edge of lateral trochlea were defined according to the anatomical landmarks on trochlear surface. The curvature radii for different areas were measured using the fitting radius and measure module. Results There were significant differences among the talus curvatures in the six areas (F = 54.905, P = 0.000), and more trends in the analytical results were as follows: PM > PL > MP > AL > MA > AM. The average PL radius from specimens aged > 38 years old was larger than that from specimens aged

Abstract In this study, fast-growing poplar reclaimed from abandoned homestead in Xixian New District, Xi’an City, Shaanxi Province, was used as the research object to explore the multi-fractal characteristics of soil particle size distribution under different management modes of abandoned land (control), irrigation, fertilizer irrigation and mixed fertilizer irrigation. The results showed that the mean values of soil clay, silt and sand in abandoned land were 14.58%, 81.21% and 4.22% respectively, 14.08%, 79.92% and 5.99% under irrigation, 15.17%, 81.19% and 3.64% under fertilizer irrigation, and 16.75%, 80.20% and 3.05% in mixed fertilizer treatment. From 40 cm, with increasing soil depth, soil clay particles increase under irrigation, fertilizer irrigation, and mixed fertilizer irrigation modes. The single fractal dimension of soil particle size distribution (D) in each treatment ranges from 2.721 to 2.808. At 60–100 cm, D shows fertilizer irrigation > mixed fertilizer irrigation > irrigation > abandoned land, indicating that fertilization and irrigation can increase the fine-grained matter of deep soil particles and reduce soil roughness. Compared with abandoned land, under irrigation, fertilizer irrigation and mixed fertilizer modes the capacity dimension (D 0 ), entropy dimension (D 1 ), correlation dimension(D 2 ), shape characteristics of the multifractal spectrum (Δf) and overall inhomogeneity of the soil particle size distribution (D 0 –D 10 ) indicate an uneven distribution of soil particle size; fractal structure characteristics of soil (D −10 –D 0 ) indicate a simplified soil structure, and degree of dispersion of soil particle size distribution (D 1 /D 0 ) indicates that soil particle size is distributed in dense areas. Pearson correlation analysis showed that D was significantly correlated with clay, sand, D 0 –D 10 , soil organic matter (SOM) and soil available phosphorus (SAP) (P

AMPA-type receptors (AMPARs) are rapidly inserted into synapses undergoing plasticity to increase synaptic transmission, but it is not fully understood if and how AMPAR-containing vesicles are selectively trafficked to these synapses. Here, we developed a strategy to label AMPAR GluA1 subunits expressed from their endogenous loci in cultured rat hippocampal neurons and characterized the motion of GluA1-containing vesicles using single-particle tracking and mathematical modeling. We find that GluA1-containing vesicles are confined and concentrated near sites of stimulation-induced structural plasticity. We show that confinement is mediated by actin polymerization, which hinders the active transport of GluA1-containing vesicles along the length of the dendritic shaft by modulating the rheological properties of the cytoplasm. Actin polymerization also facilitates myosin-mediated transport of GluA1-containing vesicles to exocytic sites. We conclude that neurons utilize F-actin to increase vesicular GluA1 reservoirs and promote exocytosis proximal to the sites of synaptic activity.

Background Gestational diabetes mellitus (GDM) can increase the risk of adverse outcomes for both mothers and infants. Preventive interventions can effectively assist pregnant women suffering from GDM. At present, pregnant women are unaware of the importance of preventing GDM, and they possess a low level of self-management ability. Recently, mHealth technology has been used worldwide. Therefore, developing a mobile health app for GDM prevention could potentially help pregnant women reduce the risk of GDM. Objective To design and develop a mobile application, evaluate its acceptance, and understand the users’using experience and suggestions, thus providing a valid tool to assist pregnant women at risk of GDM in enhancing their self-management ability and preventing GDM. Methods An evidence-based GDM prevent app ( Better pregnancy ) was developed using user-centered design methods, following the health belief model, and incorporating GDM risk prediction. A convenient sampling method was employed from June to August 2022 to select 102 pregnant women at risk of GDM for the pilot study. After a week, the app's acceptability was evaluated using an application acceptance questionnaire, and we updated the app based on the feedback from the women. We used SPSS 26.0 for data analysis. Results The application offers various functionalities, including GDM risk prediction, health management plan, behavior management, health information, personalized guidance and consultation, peer support, family support, and other functions. In total, 102 pregnant women consented to participate in the study, achieving a retention rate of 98%; however, 2% ( n = 2) withdrew. The Better pregnancy app's average acceptability score is 4.07 out of 5. Additionally, participants offered several suggestions aimed at enhancing the application. Conclusions The Better pregnancy app developed in this study can serve as an auxiliary management tool for the prevention of GDM, providing a foundation for subsequent randomized controlled trials.

Summary: This study proposes a directed acyclic graph (DAG)-based framework for generalized variance decomposition for investigating the heterogeneous return spillovers in financial system and measuring the systemic importance of financial institutions among 34 listed Chinese financial institutions from 2011 to 2023. Findings indicate pronounced information spillovers among institutions within the same sector due to contemporaneous causal relationships. Both static and dynamic financial network analyses highlight the significance of the securities sector. Dynamic structural characteristics align with macroeconomic development and are sensitive to internal and external shocks. Systemic importance assessment reveals that market size alone doesn’t determine importance, with notable disparities between banking and non-banking sectors. State-owned and joint-stock commercial banks play a vital role in banking, while local government and private capital-controlled institutions are crucial in the securities sector. This research aids regulatory efforts in maintaining a balanced regulatory environment, ensuring market efficiency, and reducing operational costs.

It has been proven that the white-box ciphers with small encodings will be vulnerable to algebraic and computation attacks. By leveraging the large encodings, the self-equivalence and implicit implementations are proposed for ARXbased white-box ciphers. Unfortunately, these two types of white-box implementations are proven to be insecure under the algebraic attack. Different from algebraic attacks, computation analysis can extract the secret key from the memory access traces without software reverse engineering. It is still an open problem whether the self-equivalence and implicit implementations can resist the computation analysis. In this paper, we analyze the encoded structure of the self-equivalence/implicit whitebox ARX ciphers and discuss its resistance to the computation analysis, such as differential computation analysis (DCA) and algebraic degree computation analysis (ADCA). The results reveal that the large input, encoding, and round key can practically mitigate DCA and ADCA. To deal with the large space, we introduce a new method which is named chosen-plaintext computation analysis (CP-CA). Based on a partial key guess and deliberately chosen intermediate value, CP-CA constructs a reverse function to calculate a set of plaintexts. With the obtained plaintexts, the large affine and non-linear encodings will be reduced to a small space. Subsequently, CP-CA mounts the computation analysis on the traces to recover the secret key. Following CP-CA, we propose a CP-DCA attack and reformulate ADCA as chosen-plaintext linear encoding analysis (CP-LEA). The experimental results indicate that the selfequivalence white-box SPECK32/48/64/96/128 and implicit white-box SPECK32/64 implementations are vulnerable to CP-DCA and CP-LEA attacks.

With the rapid development of immunotherapy in recent years, cytokine storm has been recognized as a common adverse effect of immunotherapy. The emergence of COVID-19 has renewed global attention to it. The cytokine storm's inflammatory response results in infiltration of large amounts of monocytes/macrophages in the lungs, heart, spleen, lymph nodes, and kidneys. This infiltration leads to secondary tissue damage, acute respiratory distress syndrome (ARDS), organismal damage, and even death. However, there is currently no designated treatment for cytokine storm and the resulting ARDS. Consequently, there is a pressing need to identify a pharmaceutical agent that can effectively mitigate cytokine storms. Ebosin is a new exopolysaccharide generated by Streptomyces sp.139 and pharmacological activity for cytokine storm is investigated in vivo. The results show that Ebosin significantly augments the survival rates of mice, and its effectiveness increases with higher doses. It significantly inhibited the expression of cytokines IL-5, IL-6, IL-9 and chemokine Eotaxin in serum and lung tissues. Ebosin can alleviate the pathological damage in the lungs, liver, and spleen caused by LPS. Additionally, it can inhibit the phosphorylation of IKKα/β, Stat3 and NF-κB p65 upon LPS stimulation in vitro. We hypothesized that Ebosin may decrease cytokine release by inhibiting the phosphorylation of IKKα/β, Stat3, and NF-κB p65, neutrophil infiltration in animals. The article preliminarily elucidated the activity and mechanism of Ebosin against cytokine storm, which provides a reference for the study of anti-cytokine storm activity of microbial natural products.

Evaluating the computational complexity is critical for assessing the time-domain anti-jamming performance of GNSS receivers. The multiplier is the core component that contributes to the computational complexity in time-domain anti-jamming. However, current algorithms aimed at reducing the complexity of time-domain anti-jamming typically concentrate on shortening the filter length, which fails to address the high computational complexity introduced by the use of multipliers. This paper introduces a cascaded multiplier-free approach for implementing time-domain anti-jamming in navigation receivers. We propose a numerical power decomposition technique based on optimal Canonical Signed Digit coding and coefficient decomposition. By substituting the multiplier with minimal adder and shift operations, the computational complexity of the anti-jamming filter with a high quantization bit-width can be considerably decreased. An optimization strategy is presented, and the low-complexity multiplier-free technique is applied to the time-domain anti-jamming filter. Compared to the traditional Canonical Signed Digit multiplier-free technique, our method can reduce the components required for a 12-bit quantization anti-interference filter by one adder, 20 shift operations, and five coded word lengths, while maintaining a pseudo-range measurement deviation below 0.27 ns.

In response to environmental regulatory pressure from the government, enterprises – as the main employers of labor – adjust their production-related choices and may alter their demand for labor. Numerous researches have probed into how environmental regulations affect the labor demand, which has emerged as a significant concern in the discourse around the adoption of environmental regulation policies. Nonetheless, many researches predominantly concentrates on the evaluation on the effects of environmental regulations on economic and environmental levels. Moreover, rare attention has been paid to how environmental regulations affect social activities, especially in terms of labor demands. As a result, the Air Pollution Prevention and Control Action Plan (APPCAP) is adopted as a “quasi-natural experiment” and a difference-in-differences model is employed to analyze the effects of the APPCAP on labor demands of companies. Hence, the 2008–2020 panel data are considered for the 3,949 Chinese A-share listed enterprises. Furthermore, this paper probes deeply into the underlying mechanisms based on mediation models. The following findings are thus concluded: (1) The labor demands of enterprises can be remarkably increased by APPCAP; and the result is still persuasive even though the endogeneity issues are taken into account. (2) APPCAP improves enterprise labor demand through the output and factor substitution effects. (3) As evidently revealed by heterogeneity analysis, the APPCAP could significant positive affect the labor demand size in state-owned companies, large-scale companies, new companies, and companies in polluting industries. (4) The APPCAP strikingly boosts the demand for labor force with high skills. Nevertheless, it exerts little influence on the demand for labor force with low skills and company salary levels. Therefore, the government must continue to steadfastly implement environmental regulatory policies but adopt different policies based on enterprise characteristics. Overall, this study provides micro-level experimental evidence for more in-depth understanding of how environmental policies affect labor market, which is particularly important for actively resolving social employment problems and exploring new growth points in enterprise employment.

Upgrading of vacuum residue is of prime industrial significance due to the increasing demand for light oils. Elucidating the effect of catalyst morphology on vacuum residue hydrotreating performance by kinetic modeling is therefore of great importance. Herein, kinetic analysis of hydrodemetallization (HDM) and hydrodeconradson-carbon-residue (HDCCR) performances on industrial Ni–Mo/Al2O3 catalysts with spherical and cylindrical morphologies in ebullated-bed were evaluated for more than 1600 h. It was found that the percentage of light impurities easier to be removed on spherical catalysts were 78.20% and 39.43% in HDM and HDCCR reactions, respectively, higher than 65.20% and 17.50% on cylindrical catalysts. This suggests that catalyst morphology affects the impurity removal ability and the impurity properties, resulting in better hydrotreating performance of spherical catalysts. This work not only combines catalyst morphology with impurity removal capability through kinetic modeling, but also provides new insights into the design of efficient hydrotreating catalysts.

Abstract Liver kinase B1 (LKB1), an evolutionarily conserved serine/threonine kinase, is a master regulator of the AMPK subfamily and controls cellular events such as polarity, proliferation, and energy homeostasis. Functions and mechanisms of the LKB1-AMPK axis at specific subcellular compartments, such as lysosome and mitochondria, have been established. AMPK is known to be activated at the Golgi; however, functions and regulatory mechanisms of the LKB1-AMPK axis at the Golgi apparatus remain elusive. Here, we show that TBC1D23, a Golgi-localized protein that is frequently mutated in the neurodevelopment disorder pontocerebellar hypoplasia (PCH), is specifically required for the LKB1 signaling at the Golgi. TBC1D23 directly interacts with LKB1 and recruits LKB1 to Golgi, promoting Golgi-specific activation of AMPK upon energy stress. Notably, Golgi-targeted expression of LKB1 rescues TBC1D23 deficiency in zebrafish models. Furthermore, the loss of LKB1 causes neurodevelopmental abnormalities in zebrafish, which partially recapitulates defects in TBC1D23-deficient zebrafish, and LKB1 sustains normal neuronal development via TBC1D23 interaction. Our study uncovers a regulatory mechanism of the LKB1 signaling, and reveals that a disrupted Golgi-LKB1 signaling underlies the pathogenesis of PCH.

The accurate and fast recognition of women's clothing styles is conducive to the classification and recommendation of merchants, and it is also convenient for customers to choose from. This paper optimized the Canny algorithm used to extract the contour edge of the female clothing image and used a convolutional neural network (CNN) classifier to identify clothing styles based on the edges extracted by the Canny algorithm. Finally, the Canny algorithm and the CNN classifier were tested in the simulation experiment. The performance of the CNN classifier was compared with that of the template matching and SVM classifiers, the Resnet34-based recognition method, as well as the target detection network and genetic algorithm-back-propagation neural network combined recognition method. The results demonstrated that the optimized Canny algorithm extracted more distinct contour edges. The CNN classifier exhibited the best performance and the fastest recognition for female clothing styles.

Abstract Immune checkpoint inhibitor (ICI) rechallenge in non‐small cell lung cancer (NSCLC) is a promising therapeutic strategy. The situation for ICI rechallenge can be divided into three categories: adverse events (AEs); resistance to ICIs, and rechallenge becomes compulsive because of tumor relapse while the patients had completed a 2 year course of immunotherapy. However, these categories are still controversial and should be explored further. Through voting at the 6th Straits Summit Forum on Lung Cancer, in this study we summarize the consensus of 147 experts in ICI rechallenges. A total of 97.74% experts agreed to rechallenge; 48.87% experts rechallenge with the original drug, and the others rechallenge with a different drug; 40.3% agreed to rechallenge directly after progression; 88.06% experts agreed to ICI rechallenge with a combination regimen; and factors such as previous performance status score, PD‐1 expression, and age should also be considered. Understanding the the clinical studies in ICI rechallenge could bring us one step closer to understanding the consensus. In patients with advanced NSCLC who have suffered recurrent or distant metastasis after immunotherapy, the option of rechallenge with ICIs is a promising treatment option.

Abstract By automatically learning the priors embedded in images with powerful modelling capabilities, deep learning‐based algorithms have recently made considerable progress in reconstructing the high‐resolution hyperspectral (HR‐HS) image. With previously collected large‐amount of external data, these methods are intuitively realised under the full supervision of the ground‐truth data. Thus, the database construction in merging the low‐resolution (LR) HS (LR‐HS) and HR multispectral (MS) or RGB image research paradigm, commonly named as HSI SR, requires collecting corresponding training triplets: HR‐MS (RGB), LR‐HS and HR‐HS image simultaneously, and often faces difficulties in reality. The learned models with the training datasets collected simultaneously under controlled conditions may significantly degrade the HSI super‐resolved performance to the real images captured under diverse environments. To handle the above‐mentioned limitations, the authors propose to leverage the deep internal and self‐supervised learning to solve the HSI SR problem. The authors advocate that it is possible to train a specific CNN model at test time, called as deep internal learning (DIL), by on‐line preparing the training triplet samples from the observed LR‐HS/HR‐MS (or RGB) images and the down‐sampled LR‐HS version. However, the number of the training triplets extracted solely from the transformed data of the observation itself is extremely few particularly for the HSI SR tasks with large spatial upscale factors, which would result in limited reconstruction performance. To solve this problem, the authors further exploit deep self‐supervised learning (DSL) by considering the observations as the unlabelled training samples. Specifically, the degradation modules inside the network were elaborated to realise the spatial and spectral down‐sampling procedures for transforming the generated HR‐HS estimation to the high‐resolution RGB/LR‐HS approximation, and then the reconstruction errors of the observations were formulated for measuring the network modelling performance. By consolidating the DIL and DSL into a unified deep framework, the authors construct a more robust HSI SR method without any prior training and have great potential of flexible adaptation to different settings per observation. To verify the effectiveness of the proposed approach, extensive experiments have been conducted on two benchmark HS datasets, including the CAVE and Harvard datasets, and demonstrate the great performance gain of the proposed method over the state‐of‐the‐art methods.

Dempster-Shafer evidence theory (DSET) stands out as a mathematical model for handling imperfect data, garnering significant interest across various domains. However, a notable limitation of DSET is Dempster’s rule, which can lead to counterintuitive outcomes in cases of highly conflicting evidence. To mitigate this issue, this paper introduces a novel reinforced belief logarithmic similarity measure ( $\mathcal {RBLSM}$ ), which assesses discrepancies between the evidences by incorporating both belief and plausibility functions. $\mathcal {RBLSM}$ exhibits several intriguing properties including boundedness, symmetry, and non-degeneracy, making it a robust tool for analysis. Furthermore, we develop a new multisensor information fusion method based on $\mathcal {RBLSM}$ . The proposed method uniquely integrates credibility weight and information volume weight, offering a more comprehensive reflection the reliability of each evidence. The effectiveness and practicality of the proposed $\mathcal {RBLSM}$ -based fusion method are demonstrated through its applications in target recognition and pattern classification scenarios.

Abstract This study aimed to investigate the molecular mechanism of sporotrichosis and identify possible novel therapeutic targets. Total RNA was extracted from skin lesion samples from sporotrichosis patients and used to construct a long-chain RNA transcriptome library and miRNA transcriptome library for whole transcriptome sequencing. The differentially expressed genes (DEGs) between the groups were identified, and then Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis enrichment analyses were performed based on the DEGs. An lncRNA-miRNA-mRNA ceRNA network was constructed. The expressions of JAK/STAT pathway-related proteins were detected in the patient and control tissues using RT-qPCR and Western blot analysis. Enrichment analysis showed that the DEGs were mainly enriched in various infectious diseases and immune response-related signaling pathways. Competing endogenous RNA network analysis was performed and identified the hub lncRNAs, miRNAs, and mRNAs. Compared with the control group, the mRNA expressions of SOCS3, IL-6, and JAK3 were significantly upregulated, while the expression of STAT3 did not change significantly. Also, the protein expressions of SOCS3, IL-6, JAK3, and STAT3, as well as phosphorylated JAK3 and STAT3, were significantly upregulated. We identified 671 lncRNA DEGs, 3281 mRNA DEGs, and 214 miRNA DEGs to be involved in Sporothrix globosa infection. The study findings suggest that the JAK/STAT pathway may be a therapeutic target for sporotrichosis.

Digitization has permeated every aspect of industry, and the integration of immersive digital technology into traditional tourism dance performances has become a core concern in both theoretical and practical fields. However, existing literature lacks sufficient exploration on how the integration of immersive digital technology and tourism dance performances can improve tourist loyalty. Therefore, our research established a theoretical model based on the Stimulus-Organism-Response (SOR) framework and tested our proposed hypothesis through the structural equation model. The research results indicate that authenticity, esthetics, and entertainment have a significant promoting effect on immersive experience and meaningful experience, which have a positive impact on tourists’ revisit intention. In addition, authenticity, esthetics and entertainment promote the improvement of revisiting intention through the mediating effect of flow experience and meaningful experience. This research expands the research context of authenticity theory and experience economy framework, and provides a new research perspective for tourism destination loyalty research. Our conclusion provides theoretical guidance for the sustainable development of tourist destinations.

In order to increase the scalability and reduce the complexity of photonic multipath SIC systems, a photonic multipath self-interference cancellation (SIC) method based on optical frequency comb (OFC) is proposed. The OFC is generated by continuously frequency-shifting the seed laser in the re-circulating frequency shifter (RFS) loop. The reference signal is modulated to the multiple combs of the OFC via a Mach-Zehnder modulator (MZM), and the received signal is loaded into another MZM. These two MZMs work at opposite quadrature bias points to reverse the phase of the received signal and the reference signal. After splitting and filtering with a dense wavelength division multiplexer, the reference modulation signals are injected into a multipath amplitude-delay matched link, where the amplitude and delay time are accurately controlled by several sets of optical variable attenuators and tunable delay lines. Both the inversion and amplitude-delay matching of the reference signals are realised in the optical domain, contributing to a broad bandwidth and high operational frequency. Experimental results show that the cancellation depth is greater than 45.9 dB for single-frequency signals, and 23.9 dB for signals with a bandwidth of 100 MHz in a setup with three self-interference paths. The proposed method is characterized by easy scalability, good flexibility, and low cost, making it suitable for complex multipath SIC in in-band full-duplex wireless systems.

Abstract The study specifically focused on the Hongliulin mining area, where a total of 40 soil samples were meticulously collected and analyzed from within a 1000 m radius extending from the tailings dam. The findings revealed that soil pH within the 0–1000 m range generally leaned towards the alkaline side. In terms of soil nutrient content, encompassing factors such as soil organic matter (SOM), total nitrogen (TN), total phosphorus (TP), total potassium (TK), alkali nitrogen (AK), available phosphorus (AP), and quick-acting potassium (AK), the variations fell within the following ranges: 2.23–13.58 g/kg, 0.12–0.73 g/kg, 0.18–1.15 g/kg, 9.54–35.82 g/kg, 2.89–6.76 mg/kg, 3.45–11.25 mg/kg, and 5.86–130.9 mg/kg. Collectively, these values indicate relatively low levels of soil nutrients. Within the 0–500 m range of soil samples, the average concentrations of Cd, Hg, Pb, and As were 0.778, 0.198, 24.87, and 17.92 mg/kg, respectively. These concentrations exceeded the established soil background values of Shaanxi Province and emerged as the primary pollutants in the study area. Within this same range, the mean values of eight toxic metals (Pi) were ranked in the following descending order: 1.726 (Hg), 1.400 (As), 1.129 (Cr), 1.109 (Pb), 0.623 (Zn), 0.536 (Cd), 0.309 (Cu), and 0.289 (Ni). With the exception of Hg, As, Cr, and Pb, which exhibited slight pollution, the other toxic metals were found to be within acceptable pollution limits for this sampling range, in line with the results obtained using the geo-accumulation index method. The average potential ecological risk index for the eight toxic metals in the study area stood at 185.0, indicating a moderate overall pollution level. When assessing individual elements, the proportions of ecological risk attributed to Hg, As, Pb, and Cd were 34.57%, 27.44%, 25.11%, and 23.11%, respectively. This suggests that the primary potential ecological risk elements in the study area are Hg and As, followed by Cd and Pb. Notably, toxic metals Hg and Pb, as well as As and Pb, exhibited significant positive correlations within the sampling area, suggesting a common source. An analysis of the relationship between soil physicochemical properties and toxic metals indicated that soil pH, SOM, TN, and TP were closely linked to toxic metal concentrations. The toxic metal elements in the research area's soil exhibit moderate variability (0.16 0.36). Within the range of 0–200 m, the CV values for Cd and Hg exceed 1, indicating a high level of variability. The coefficient of variation for SOM, TP, AP, AK and TK is relatively high with the of 2.93, 2.36, 2.36, 21.01, 7.54. The soil in the sampling area has undergone significant disturbances due to human activities, resulting in toxic metal pollution and nutrient deficiencies.

The hot deformation behavior and microstructure of Fe-12.5Cr–4Al–2Mo-0.03Nb-0.08Y alloy were studied under conditions of 800 °C–1200 °C/0.01 s−1∼10 s−1 using a combination of hot compression experiments, EBSD and TEM characterization. The results indicate that the deformation temperature and strain rate have a significant impact on the flow stress and microstructure of the alloy, especially the deformation temperature. The constitutive equation constructed in this paper can reflect the hot deformation process and accurately calculate flow stress value of the FeCrAl alloy in corresponding states. The FeCrAl alloy undergoes DRV and DRX during hot deformation. DDRX grains distributed along the original grain boundaries mainly formed at low deformation temperatures and high strain rates, while CDRX grains mainly formed at high deformation temperatures and low strain rates and characterized by the internal distribution of the original grains. Moreover, the orientation of DDRX grains is mostly different from that of adjacent original grains, while the orientation of CDRX grains is relatively close to that of the original grains.

Abstract Rain gardens play a key role in urban non-point source pollution control. The drainage type affects the infiltration processes of runoff pollutants. The soil properties and microbial community structures were studied to reveal the stability of the ecosystem in rain gardens with different drainage types under long-term operation. The results showed that the soil water content and total organic carbon in the drained rain gardens were always higher than that of the infiltrated ones. With the increase in running time, the contents of heavy metals in rain gardens showed significant accumulation phenomena, especially the contents of Zn and Pb in drained rain gardens were higher than that in infiltrated ones. The accumulation of pollutants resulted in lower microbial diversity in drained rain gardens than in infiltrated rain gardens, but the microbial community structures were the same in all rain gardens. The effects of drainage type on microbial community evolution were not significant, only the accumulation of heavy metals led to changes in the abundance of dominant microorganisms. There were differences in the soil environment of rain gardens with different drainage types. The long-term operation of rain gardens led to fluctuations in the soil ecosystem, while the internal micro-ecosystems of the drained rain gardens were in unstable states.

Reliable classification results are crucial for guiding agricultural production, forecasting crop yield, and ensuring food security. Generating reliable classification results is relatively simple in regions with sufficient labeled samples, but regions with limited labeled samples remain a significant challenge. In this study, we propose two new solutions that leverage the feature representation capabilities of deep learning and the sample reuse potential of transfer learning to solve the limited label problem. Specifically, we develop a Variable-dimensional Symmetric Network with Position Encoding (VPSNet) to improve the efficiency of labeled sample utilization. Additionally, we introduce a transfer strategy based on the Inter-Regional Discrepancies in Crop Time Series (IRDCTS) to expand the labeled sample reuse region. We evaluated the proposed model in three regions with limited labels between 2017 and 2018. Experimental results show that our model has superior discriminative feature extraction capabilities compared to other existing models. The feasibility of the proposed transfer strategy is tested in three pair regions, showing that IRDCTS can enhance the model adaptability by reducing inter-domain discrepancies. This study provides a comprehensive solution to the classification problem of the limited labeled samples, involving both the development of classification models and the implementation of transfer strategies.

Personalized recommendation can recommend items of interest to different users and is widely used in the real world. Among them, graph collaborative filtering is a method of personalized recommendation. It can enrich the connection between users and items on the basis of collaborative filtering, to learn the embedded representation of nodes more accurately. Since graph collaborative filtering is based on bipartite graphs, few exciting graph collaborative methods consider the relationships between users (or items), the message between homogeneous nodes are diluted or ignored. Predicting and constructing the relationship between users (or items) has become a challenging. To solve this problem, we propose an enhanced sub-graph reconstruction graph neural network for recommendation (SRCF), using a heterogeneous graph neural network based encoder-decoder learn potential relationships between users (or items), and reconstruct sub-graphs based on those relationships. In the proposed model, the information of user and item sub-graphs is merged with the network of graph collaborative filtering, which enhances effective information transfer between homogeneous nodes, thereby improving the model performance. We have selected a number of data sets of different scenarios and different scales to comprehensively evaluate the performance of the model, and the experimental results confirmed the superiority of our model.

ABSTRACTThis cross-sectional epidemiological study aimed to investigate awareness regarding human papillomavirus (HPV) and willingness for vaccination among college students with or without medical background in Guizhou Province, China. A logistic regression model was used for univariate and multivariate analyses of cognition to determine factors influencing willingness for vaccination. In total, 2,540 questionnaires were collected, of which 2,360 were valid. The medical and nonmedical groups included 737 (31.2%) and 1,623 (68.8%) individuals, respectively. The medical group had heard of HPV and its vaccines more frequently than the nonmedical group, with the former also having greater awareness than the latter (P

Introduction: As an advanced agricultural technology equipment, the functional integration design and appearance aerodynamic characteristics of hexacopter agricultural UAV are significant for improving the efficiency of agricultural production.Methods: Firstly, the study carried out the functional integration design of the hexacopter agricultural UAV, and completed the matching analysis and selection of the relevant components of the power system. Then, the numerical simulation method of computational fluid dynamics was used to analyze the aerodynamic characteristics of the UAV. Finally, the role of different propeller pitch on important parameters such as lift and range time of the UAV was verified.Results and discussion: The results showed that in the XY section of the UAV, namely, the surface parallel to the flight direction, the areas with high streamline velocity were mainly concentrated at the intersection of the airflow with the landing gear and the motor. The streamlines in the front of the UAV were tightly and neatly distributed, while those in the rear were sparser. The motor force efficiencies of the UAVs with different propeller pitches ranged from 7.05 to 7.25 g/w. At a flight speed of 5 m/s, the motor force effect of the UAV with a pitch of 260 mm reached 7.25 g/w, which was the highest value among all models. Meanwhile, it had the longest endurance time of 19.14 min, indicating the best performance. The results suggested that it not only promoted the modernization of agricultural UAVs but also effectively enhanced the efficiency of agricultural production.

BackgroundChronic insomnia disorder (CID) is usually associated with Generalized Anxiety Disorder (GAD), which may change brain structure and function. However, the possible brain markers, imaging characteristics, and pathophysiology are unknown.ObjectiveTo look at the probable brain markers, imaging characteristics, and pathogenesis of CID in combination with GAD.MethodsA total of 57 patients with CID concomitant GAD and 57 healthy controls (HC) were enrolled. Voxel-based morphometry (VBM) and functional connectivity (FC) were utilized to measure gray matter volume (GMV) and functional changes. Correlation analysis was utilized to identify relationships between brain changes and clinical characteristics.ResultsPatients had decreased GMV in the left cerebellum, right cerebellar peduncle, and left insula; increased FC between the left cerebellum and right angular gyrus, as well as between the left insula and anterior left cingulate gyrus; and decreased FC in several areas, including the left cerebellum with the middle left cingulate gyrus and the left insula with the left superior postcentral gyrus. These brain changes related to CID and GAD. These data could be used to identify relevant brain markers, imaging features, and to better understand the etiology.ConclusionThe intensity of insomnia in patients was strongly related to the severity of anxiety. The lower GMV in the cerebellum could be interpreted as an imaging characteristic of CID. Reduced GMV in the insula, as well as aberrant function in the cingulate gyrus and prefrontal lobe, may contribute to the pathophysiology of CID and GAD. Abnormal function in the postcentral gyrus and angular gyrus may be associated with patients’ clinical complaints.

Summary: YAP/TEAD signaling is essential for organismal development, cell proliferation, and cancer progression. As a transcriptional coactivator, how YAP activates its downstream target genes is incompletely understood. YAP forms biomolecular condensates in response to hyperosmotic stress, concentrating transcription-related factors to activate downstream target genes. However, whether YAP forms condensates under other signals, how YAP condensates organize and function, and how YAP condensates activate transcription in general are unknown. Here, we report that endogenous YAP forms sub-micron scale condensates in response to Hippo pathway regulation and actin cytoskeletal tension. YAP condensates are stabilized by the transcription factor TEAD1, and recruit BRD4, a coactivator that is enriched at active enhancers. Using single-particle tracking, we found that YAP condensates slowed YAP diffusion within condensate boundaries, a possible mechanism for promoting YAP target search. These results reveal that YAP condensate formation is a highly regulated process that is critical for YAP/TEAD target gene expression.

This study aimed to investigate the dose–response relationship of rocuronium administered based on skeletal muscle weight and to assess the feasibility of calculating rocuronium dosage by skeletal muscle weight in short surgeries for patients with obesity. This single-center, randomized controlled clinical trial included 71 patients with obesity aged 28–70 years, with body fat percentages (PBF) >20% in men and > 28% in women, ASA status I-III, scheduled for tracheoscopy. Patients were randomly allocated into two groups: skeletal muscle group (SM group) received rocuronium based on the skeletal muscle content (1.0 mg/kg, n = 31), and the conventional administration group (conventional group) received rocuronium based on total body weight (0.45 mg/kg, n = 30). General anesthesia was administered using the same protocol. Parameters recorded included patients’ general condition, muscle relaxant usage, onset time of muscle relaxants, non-response time, clinical effect time, 75% recovery time, and recovery index. Additionally, occurrences of body movement, choking, and incomplete muscle relaxation during surgery were recorded. Compared to the conventional group, the SM group required significantly less rocuronium dosage, resulting in significantly lower non-response time, clinical effect time, 75% recovery time, and recovery index (p 0.05). Utilizing skeletal muscle weight to calculate rocuronium dosage in short surgeries for patients with obesity can reduce dosage, shorten recovery time, and prevent residual muscle relaxation while achieving satisfactory muscle relaxation to meet surgical requirements.

Objective To evaluate the effectiveness of oral probiotic supplements in patients undergoing immune checkpoint inhibitors (ICIs) for the treatment of advanced lung cancer. Methods This prospective real-world study enrolled patients with advanced lung cancer who were receiving ICIs as part of their treatment. The patients were divided into 2 groups: Group OPS received oral probiotic supplements along with ICIs, while Group C did not. The primary endpoint was progression-free survival (PFS). The secondary outcome measure was the objective response rate (ORR). Results A total of 253 patients were included in the study, with 71 patients in Group OPS and 182 patients in the control group (Group C). No significant differences were observed in the median PFS between the 2 groups for all patients. However, for small cell lung cancer (SCLC) patients, the median PFS was significantly better in the Group OPS compared to the Group C (11.1 months vs 7.0 months, P = .049). No significant differences were observed in median PFS for the non-small cell lung cancer (NSCLC) cohort between the 2 groups, but a trend towards better median PFS in Group OPS was noticed (16.5 months vs 12.3 months, P = .56). The ORR for the entire cohort was 58.0%. Conclusion Oral probiotics supplements in combination with ICIs included regimen may improve the outcome in patients with advanced SCLC. The above points should be proved by further study.

The COVID-19 pandemic has necessitated the development of robust tools for tracking and modeling the spread of the virus. We present ‘K-Track-Covid,’ an interactive web-based dashboard developed using the R Shiny framework, to offer users an intuitive dashboard for analyzing the geographical and temporal spread of COVID-19 in South Korea. Our dashboard employs dynamic user interface elements, employs validated epidemiological models, and integrates regional data to offer tailored visual displays. The dashboard allows users to customize their data views by selecting specific time frames, geographic regions, and demographic groups. This customization enables the generation of charts and statistical summaries pertinent to both daily fluctuations and cumulative counts of COVID-19 cases, as well as mortality statistics. Additionally, the dashboard offers a simulation model based on mathematical models, enabling users to make predictions under various parameter settings. The dashboard is designed to assist researchers, policymakers, and the public in understanding the spread and impact of COVID-19, thereby facilitating informed decision-making. All data and resources related to this study are publicly available to ensure transparency and facilitate further research.

Rainbow trout is a widely farmed economical cold-water fish worldwide, but the prevalence of infectious hematopoietic necrosis virus (IHNV) presents a severe risk to the aquaculture industry, resulting in high mortality and huge economic losses. In this study, the impacts of different concentrations (0, 10, 20, and 30 g/kg) of Chinese herbal medicine mixture (CHMM) on the immune response and resistance of rainbow trout to IHNV infection were evaluated. The results show that CHMM noticeably increased (P < 0.05) T-SOD, CAT, AST, ALT, ACP, and AKP activities and decreased MDA content. NF-κB, TNF-α, IFN-β, IL-1β, JAK1, HSP70, and HSP90 expressions were significantly upregulated (P < 0.05) in all CHMMs, while SOCS2 expression was downregulated (P < 0.05). Following infection with IHNV, feeding rainbow trout with varying amounts of CHMM resulted in noticeably increased (P < 0.05) T-SOD, ACP, and AKP activities and significantly decreased (P < 0.05) MDA content and AST and ALT activities. TNF-α, IFN-β, IL-1β, HSP70, and HSP90 expressions were significantly upregulated (P < 0.05) in all CHMMs, while the expressions of JAK1 and SOCS2 were downregulated. The expression level of the IHNV G protein gene at a dosage of 20 g/kg was notably lower than that of the other CHMM feeding groups. This study provides a solid scientific basis for promoting CHMM as an immunostimulant for boosting antiviral immunity in rainbow trout.

PurposeWhether the diagnosis of non-alcoholic fatty liver disease or metabolic dysfunction-associated fatty disease has a different impact on liver transplant recipients with hepatocellular carcinoma is not yet clear.MethodsData from a two-center retrospective cohort study were collected to compare and investigate the differences between non-alcoholic fatty liver disease and metabolic dysfunction-associated fatty liver disease in clinicopathologic parameters and prognosis among liver transplant recipients with hepatocellular carcinoma.ResultsA total of 268 liver transplant recipients with hepatocellular carcinoma were included. The prevalence among pre- and post-transplant metabolic dysfunction-associated fatty liver disease was 10.82% and 30.22%, while for non-alcoholic fatty liver disease, it was 7.09% and 26.87%, respectively. The clinicopathological parameters were similar between the two pre-transplant groups. In contrast, the post-transplant group with metabolic dysfunction-associated fatty liver disease exhibited a higher prevalence of diabetes mellitus and a greater body mass index. However, the other parameters were similar between the two post-transplant groups (p > 0.05). Factors such as the largest tumor size > 4 cm, microvascular invasion, lack of tumor capsule, post-transplant metabolic dysfunction-associated fatty liver disease, and decreased post-transplant lymphocyte percentage were related to an increased risk of recurrence.ConclusionIn patients undergone liver transplantation for hepatocellular carcinoma, the diagnosis of metabolic dysfunction-associated fatty disease is more strongly associated with metabolic abnormalities than the diagnosis of non-alcoholic fatty liver disease and is an independent predictor of hepatocellular carcinoma recurrence.

Background: Virtual simulation systems are being increasingly used in the field of nursing education. However, these systems are mostly designed based on the perspective of developers, and the needs of the end users are often neglected. The purpose of this study was to explore the perceptions and needs of Chinese undergraduate nursing students for the development of a community nursing virtual simulation system. Methods: This was a descriptive qualitative study enrolling 12 undergraduate nursing students at a University in China. Data were collected through semi-structured interviews. The content analysis method was used for data analysis. Result: Three themes and 15 sub-themes were extracted from this study: (1) Positive perceptions regarding virtual systems: a) Provides space for trials and errors, b) Not limited by time and space, c) Provides auxiliary tools; (2) Design and use requirements: a) Performance needs, b) Contents design needs, c) Appearance design needs, d) Support Needs; (3) Competency enhancement needs: a) Community nursing practice ability, b) Critical thinking ability, c) Independent thinking ability, d) Ability to deal with emergencies, e)Teamwork skills, f) Self-efficacy, g) Resilience, h)Interpersonal communication skills. Conclusion: Designers and engineers should consider students' needs, aim to improve students' abilities, improve the diversity, the scientific and rigor of content, and enhance user immersion and interest. The system should be programmed to provide real-time feedback, timely technical and professional support, in order to optimize use experience of nursing students.

Abstract Immune checkpoint inhibitors (PD‐1/PD‐L1 and CTLA‐4 blockade) have revolutionized the treatment landscape in non‐small cell lung cancer (NSCLC). Secondary resistance to immunotherapy (IO), which poses a substantial challenge in clinical settings, occurs in several initial responders. Currently, new treatment approaches have been extensively evaluated in investigational studies for these patients to tackle this difficult problem; however, the lack of consistency in clinical definition, uniform criteria for enrollment in clinical trials, and interpretation of results remain significant hurdles to progress. Thus, our expert panel comprehensively synthesized data from current studies to propose a practical clinical definition of secondary resistance to immunotherapy in NSCLC in metastatic and neoadjuvant settings. In addition to patients who received IO alone (including IO‐IO combinations), we also generated a definition for patients treated with chemotherapy plus IO. This consensus aimed to provide guidance for clinical trial design and facilitate future discussions with investigators. It should be noted that additional updates in this consensus are required when new data is available.

Abstract Telomere length (TL) shortening is a pivotal indicator of biological aging and is associated with many human diseases. The genetic determinates of human TL have been widely investigated, however, most existing studies were conducted based on adult tissues which are heavily influenced by lifetime exposure. Based on the analyses of terminal restriction fragment (TRF) length of telomere, individual genotypes, and gene expressions on 166 healthy placental tissues, we systematically interrogate TL-modulated genes and their potential functions. We discover that the TL in the placenta is comparatively longer than in other adult tissues, but exhibiting an intra-tissue homogeneity. Trans-ancestral TL genome-wide association studies (GWASs) on 644,553 individuals identify 20 newly discovered genetic associations and provide increased polygenic determination of human TL. Next, we integrate the powerful TL GWAS with placental expression quantitative trait locus (eQTL) mapping to prioritize 23 likely causal genes, among which 4 are functionally validated, including MMUT, RRM1, KIAA1429, and YWHAZ. Finally, modeling transcriptomic signatures and TRF-based TL improve the prediction performance of human TL. This study deepens our understanding of causal genes and transcriptomic determinants of human TL, promoting the mechanistic research on fine-grained TL regulation.

ABSTRACTControlling grain temperatures is the main approach employed in large commercial warehouses to maintain quality and prevent infestation by insects and fungi. Large commercial warehouses in northeast China have been utilizing inner cyclic cooling aeration (ICCA), a newly developed method for managing summertime temperatures, haphazardly and without tight standards. We utilized a homemade detector to track the temperature, humidity, and CO2 concentrations of maize that was held for four years under ICCA treatment. The monitoring occurred every week, specifically from July 1st to September 30th. In addition, we conducted weekly tests to determine the moisture content (MC) and free fatty acids (FFA) of the stored maize samples. Without the use of ICCA, the average temperature of the stored maize above a depth of 3.5 m ranged from 20°C to 28°C, and the relative humidity (RH) in the headspace was typically higher than 75%. However, when ICCA was applied, the average temperature could be maintained at 22°C, and the RH was below 65% for most of the time. In the first year, the MC of the stored maize at a depth of 1.0 m experienced a loss of approximately 0.5%. However, for one year, there was no significant loss in the MC of the maize stored at the same depth. Furthermore, the FFA in the stored maize at a depth of 1 m increased by 1–5 mg KOH/100 g. The use of ICCA effectively controls the temperature and RH in the stored maize, reducing the risk of insect and fungal reproduction.

The developing countries rely heavily on imports of capital goods to spur economic growth. When the economy grows, energy consumption rises, adversely impacting climate change. The low levels of renewable energy share in total energy consumption, developing nations confront a difficult task in achieving the SDGs targets related to an increase in renewable energy share and access to affordable, reliable, and modern energy. Finding solutions to increase renewable energy usage is critical. International trade is an unavoidable part of development, prompting us to consider the impact of imports on renewable energy usage. This study explores the effects of imports of capital goods from China, EU and USA on renewable energy consumption in developing countries by using panel data from 20 countries spanning 2000–2018. It is found that capital goods imported from China in developing countries negatively impact renewable energy consumption while imports from EU have a positive impact on renewable energy consumption. However, in the case of US it is found negative but insignificant. The role of economic, social, and political globalization is explored, and it is found that three types of globalization are positively and significantly linked with renewable energy consumption. Thus, this study recommends that trade policies complement domestic efforts toward increasing renewable energy production and consumption in developing countries.

AbstractContext Aryl hydrocarbon receptor (AhR) agonists are potential therapeutic agents for ulcerative colitis (UC). Indirubin (IDR), which is a natural AhR ligand approved for leukemia treatment, ameliorates dextran sulfate sodium (DSS)-induced colitis in mice. However, the therapeutic mechanisms of IDR are unknown, limiting its application.Objective This study explores the therapeutic mechanisms of IDR in DSS-induced colitis using transcriptomic analysis.Materials and methods Male BALB/c mice were categorized to six groups: normal, DSS model (2% DSS), IDR treatment (10, 20 and 40 mg/kg), and sulfasalazine (520 mg/kg) groups. The drugs were intragastrically administered for 7 consecutive days. The disease activity index (DAI) was recorded. After euthanasia, the colon length was measured, and histopathological examination, immunohistochemistry staining using F4/80, and colonic transcriptomic analysis were conducted. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and western blotting (WB) were conducted to verify our findings.Results Compared with DSS, IDR treatment decreased the DAI score by 64.9% and increased colon length by 26.2%. Moreover, it alleviated mucosal injury and reduced macrophage infiltration. Transcriptomic analysis identified several downregulated genes (Igkvs and Nlrp3), as well as Nlrp3/Il1β and hemoglobin gene networks, after IDR treatment. The abundances of NF-κB p65, NLRP3, IL-1β, and HBA decreased by 69.1, 59.4, 81.1, and 83.0% respectively, after IDR treatment.Discussion and conclusion Apart from the well-documented NF-κB signalling pathway, IL-17A, and NLRP3-IL-1β, the suppression of haemoglobin-induced lipid peroxidation could be a previously unknown mechanism of IDR. Our study can help improve its application for UC treatment.

AbstractContext Lappaol F (LAF), a natural lignan from Arctium lappa Linné (Asteraceae), inhibits tumor cell growth in vitro and in vivo. The underlying mechanism involves the suppression of the Yes-associated protein. However, the specific role of LAF in cell cycle regulation remains unknown.Objective This study determined the molecular mechanism by which LAF regulates cell cycle progression.Materials and methods Various colon cancer cell lines (SW480, HCT15, and HCT116) were treated with LAF (25, 50, and 75 μmol/L) for 48 h. The effects of LAF on cell proliferation and cell cycle were determined using sulforhodamine B and flow cytometry assays. Differentially expressed proteins (DEPs) were identified using quantitative proteomics. Bioinformatic analysis of DEPs was conducted via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Expression levels of DEPs in the cell cycle pathway were analyzed using RT-qPCR and western blotting.Results LAF suppressed the proliferation of SW480, HCT15, and HCT116 cells (IC50 47.1, 51.4, and 32.8 μmol/L, respectively) and induced cell cycle arrest at the S phase. A total of 6331 proteins were identified and quantified, of which 127 were differentially expressed between the LAF-treated and untreated groups. GO and KEGG enrichment analyses revealed that DEPs mainly participated in the cell cycle. CDKN1C/p57 showed the most significant differential expression, with the highest fold-change (3.155-fold). Knockdown of CDKN1C/p57 attenuated the S phase cell cycle arrest and proliferation inhibition induced by LAF.Conclusion LAF exerts antitumor effects via S phase arrest by activating CDKN1C/p57 in colorectal cancer cells.