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Abstract Human society is facing increasingly serious problems of environmental pollution and energy shortage, and up to now, achieving high NH3-SCR activity at ultra-low temperatures (

In order to understand the current status of plankton and fish population structure and diversity after the construction of the ‘One Dam and Three Routes’ project in the Dazhangxi River, plankton and fish samples were collected in the Dazhangxi River watershed in June and October 2023.A total of 149 species of phytoplankton from 7 phyla were found. The biomass of phytoplankton ranged from 0.88 to 21.35 mg/L, the Shannon ∼ Wiener diversity index (H’) ranged from 2.04 to 3.99, the Margalef abundance index (D) ranged from 1.56 to 3.72, and the Pielou homogeneity index (J’) ranged from 0.41 to 3.72. The permanganate index (CODMn) and pH were the most important environmental factors affecting the distribution of phytoplankton, and the variation of Margalef’s richness index (D) ranged from 1.56 to 3.72, and Pielou’s uniformity index (J’) ranged from 0.41 to 0.76. Seventy species of zooplankton were found in the survey, the biomass of zooplankton ranged from 0.0042 to 3.20 mg/L, the Shannon ∼ Wiener diversity index (H’) ranged from 0.1972 to 3.22, the Margalef abundance index (D) ranged from 1.50 to 5.17, the Pielou index (J’) ranged from 0.41 to 0.76, and CODMn and pH were important environmental factors affecting the distribution of phytoplankton. The variation range of Pielou’s evenness index (J’) was 0.066 ∼ 0.824. ammonia nitrogen∼, Secchi depth, and electrical conductivity were important environmental factors affecting the distribution of zooplankton. A total of 38 species of fish were collected in the survey, belonging to 7 orders, 13 families, and 33 genera, with the predominance of Carpiformes accounting for 50%, Perchiformes accounting for 23.68%, the diversity index of the fish ranged from 1.703 to 2.386, the richness index from 1.763 to 3.882, the predominance index from 0.754 to 0.888, and the uniformity index from 1.504 to 2.144, and the diversity index from 1.504 to 2.14. The fish community was obviously miniaturized, but some rare and uncommon fish were found. The diversity index of zooplankton in the Dazhangxi River fluctuated greatly, and the fish resources showed a declining trend and obvious miniaturization.

The safety of the rice-fish co-culture system (RFCS) is threatened by severe soil cadmium (Cd) pollution. However, the characteristics of Cd accumulation in aquatic animals within this system remain poorly understood. To investigate the Cd accumulation characteristics and dietary risks in aquatic animals with varying habitat characteristics, three species — crayfish Procambarus clarkii, loach Paramisgumus dabryanus, and crucian carp Carassius auratus — were cultured in RFCS with soil Cd pollution ranging from 0.2 to 32.0 mg/kg. The results demonstrated that the survival of the three aquatic animals did not differ significantly at medium to low Cd concentrations (0.2–4 mg/kg) but decreased markedly at high concentrations (16–32 mg/kg). The WGR of crayfish decreased as the Cd treatment concentration increased. The Cd accumulation in various tissues showed an increasing trend with increasing Cd exposure. At the same concentration, the accumulation of Cd was in the order of liver (or hepatopancreas) ≈ intestine > gill > muscle. At the same Cd treatment concentration, the Cd accumulation in different animal species generally showed a trend of crayfish > loach > crucian carp, indicating that accumulation of Cd in the aquatic animals within the Cd-contaminated RFCS is closely related to their habitat characteristics. The soil pollution thresholds for crayfish, loach and crucian carp were determined to be 11.7, 38.8 and 90.5 mg/kg, respectively, which can serve as early warnings for safe production. Within the tested concentration range, the aquatic animals did not pose non-carcinogenic risks; however, they posed carcinogenic risks when these animals are exposed to high soil Cd concentrations.

BackgroundMethods for accurately predicting the prognosis of patients with recurrent hepatolithiasis (RH) after biliary surgery are lacking. This study aimed to develop a model that dynamically predicts the risk of hepatolithiasis recurrence using a machine-learning (ML) approach based on multiple clinical high-order correlation data.Materials and methodsData from patients with RH who underwent surgery at five centres between January 2015 and December 2020 were collected and divided into training and testing sets. Nine predictive models, which we named the Correlation Analysis and Recurrence Evaluation System (CARES), were developed and compared using machine learning (ML) methods to predict the patients’ dynamic recurrence risk within 5 post-operative years. We adopted a k-fold cross validation with k = 10 and tested model performance on a separate testing set. The area under the receiver operating characteristic curve was used to evaluate the performance of the models, and the significance and direction of each predictive variable were interpreted and justified based on Shapley Additive Explanations.ResultsModels based on ML methods outperformed those based on traditional regression analysis in predicting the recurrent risk of patients with RH, with Extreme Gradient Boosting (XGBoost) and Light Gradient Boosting Machine (LightGBM) showing the best performance, both yielding an AUC (Area Under the receiver operating characteristic Curve) of∼0.9 or higher at predictions. These models were proved to have even better performance on testing sets than in a 10-fold cross validation, indicating that the model was not overfitted. The SHAP method revealed that immediate stone clearance, final stone clearance, number of previous surgeries, and preoperative CA19-9 index were the most important predictors of recurrence after reoperation in RH patients. An online version of the CARES model was implemented.ConclusionThe CARES model was firstly developed based on ML methods and further encapsulated into an online version for predicting the recurrence of patients with RH after hepatectomy, which can guide clinical decision-making and personalised postoperative surveillance.

The escalating prevalence of non-alcoholic fatty liver disease (NAFLD), driven by inadequate dietary habits and metabolic imbalances, underscores the urgent need for effective dietary interventions. This study investigated the potential of 80 % peanut diacylglycerol (DAG) as a functional lipid component in preventing NAFLD and associated intestinal microenvironment based on a high-cholesterol diet (HCD)-induced zebrafish model. We first found that the zebrafish fatty liver model shared multiple similar pathways like lipid-induced atherosclerosis, insulin resistance with NAFLD patient in terms of lipid metabolism. Employing larvae and grown zebrafish, we aimed to elucidate the preventive and alleviating effect of a DAG diet on NAFLD respectively. Results showed that DAG post-intervention significantly decreased hepatic lipid accumulation and diminished intestinal inflammatory in fatty liver zebrafish model. Notably, transcriptomic sequencing illuminated upregulation in genes related to lipid metabolism (e.g., fasn, mogat2, cd36), suggesting that peanut DAG accelerated lipid transportation and fostered a metabolic environment less conducive to NAFLD symptoms. Besides, reduced liver lipid droplets and hepatic inflammatory suggested DAG feeding could also prevent the formation of NAFLD. The study provided compelling evidence supporting the incorporation of DAG into the diet as a strategy for the prevention and management of fatty liver disease, proposing a novel approach to functional food development aimed at combating metabolic diseases.

Hydrogel-based tissue-engineered skin has attracted increased attention due to its potential to restore the structural integrity and functionality of skin. However, the mechanical properties of hydrogel scaffolds and natural skin are substantially different. Here, we developed a polyvinyl alcohol (PVA)/acrylamide based interpenetrating network (IPN) hydrogel that was surface modified with polydopamine (PDA) and termed Dopa-gel. The Dopa-gel exhibited mechanical properties similar to native skin tissue and a superior ability to modulate paracrine functions. Furthermore, a tough scaffold with tensile resistance was fabricated using this hydrogel by three-dimensional printing. The results showed that the interpenetration of PVA, alginate, and polyacrylamide networks notably enhanced the mechanical properties of the hydrogel. Surface modification with PDA endowed the hydrogels with increased secretion of immunomodulatory and proangiogenic factors. In an in vivo model, Dopa-gel treatment accelerated wound closure, increased vascularization, and promoted a shift in macrophages from a proinflammatory M1 phenotype to a prohealing and anti-inflammatory M2 phenotype within the wound area. Mechanistically, the focal adhesion kinase (FAK)/extracellular signal-related kinase (ERK) signaling pathway may mediate the promotion of skin defect healing by increasing paracrine secretion via the Dopa-gel. Additionally, proangiogenic factors can be induced through Rho-associated kinase-2 (ROCK-2)/vascular endothelial growth factor (VEGF)-mediated paracrine secretion under tensile stress conditions. Taken together, these findings suggest that the multifunctional Dopa-gel, which has good mechanical properties similar to those of native skin tissue and enhanced immunomodulatory and angiogenic properties, is a promising scaffold for skin tissue regeneration.

Abstract Background Despite emerging evidence linking blood cell indices (BCIs) to sepsis mortality, the inconsistency of observational studies obscures the clarity of these associations. This study aims to clarify the causal influence of BCIs on 28-day mortality rates in sepsis patients. Methods Utilizing univariable and multivariable Mendelian randomization (MR) analyses, we examined the impact of BCIs on sepsis mortality by analyzing data from extensive genome-wide association studies. The inverse-variance weighted (IVW) method was our primary analytic tool, complemented by several robustness checks to mitigate pleiotropy, including weighted median, mode-based estimates, MR-Egger regression, and MR-PRESSO. Subsequently, we conducted a retrospective study to further explore the correlation between platelet indices and 28-day mortality of sepsis using real-world data. Results Our findings highlight a significant causal relationship between platelet distribution width (PDW) and 28-day mortality in sepsis, with the univariable Mendelian randomization approach yielding an odds ratio of 1.12 (95% CI, 1.06–1.26; P

ObjectiveResearch indicates that cognitive control is compromised in individuals with internet gaming disorder (IGD). However, the neural mechanisms behind it are still unclear. This study aims to investigate alterations in resting-state brain networks in adolescents with IGD and the potential neurobiological mechanisms underlying cognitive dysfunction.Materials and methodsA total of 44 adolescent IGD subjects (male/female: 38/6) and 50 healthy controls (male/female: 40/10) were enrolled. Participants underwent demographic assessments, Young’s Internet Addiction Scale, Barratt Impulsiveness Scale 11 Chinese Revised Version, the Chinese Adolescents’ Maladaptive Cognitions Scale, exploratory eye movement tests, and functional magnetic resonance imaging (fMRI). FMRI data were analyzed using the GIFT software for independent component analysis, focusing on functional connectivity within and between resting-state brain networks.ResultsIn comparison to the control group, impulsivity in adolescent IGD subjects showed a positive correlation with the severity of IGD (r=0.6350, p < 0.001), linked to impairments in the Executive Control Network (ECN) and a decrease in functional connectivity between the Salience Network (SN) and ECN (r=0.4307, p=0.0021; r=-0.5147, p=0.0034). Decreased resting state activity of the dorsal attention network (DAN) was associated with attentional dysregulation of IGD in adolescents (r=0.4071, p=0.0017), and ECN increased functional connectivity with DAN. The degree of IGD was positively correlated with enhanced functional connectivity between the ECN and DAN (r=0.4283, p=0.0037).ConclusionsThis research demonstrates that changes in the ECN and DAN correlate with heightened impulsivity and attentional deficits in adolescents with IGD. The interaction between cognitive control disorders and resting-state brain networks in adolescent IGD is related.

In order to improve the control capability of distributed photovoltaic support, a distributed photovoltaic support consumption method based on energy storage configuration mode and random events is proposed. A networked and constrained parameter analysis model for distributed photovoltaic power supply control was constructed. Based on the direct flexible mode of optical storage, an AC/DC voltage level control model for distributed solar power supply control was constructed. In the operation mode of DC hybrid distribution network, the demand response tracking identification method was used to analyze the uncertain characteristic parameters of distributed solar power supply load, and combined with the planned energy storage capacity parameters, the distributed solar power supply load and photovoltaic output were estimated. By configuring the optimal energy storage capacity, adjusting the power distribution of the microgrid, and integrating the analysis of uncertain factors and random events in the energy storage configuration mode, the design of distributed photovoltaic support consumption has been achieved. The experimental results show that the distributed photovoltaic absorption control using this method has lower load requirements, can effectively reduce the exchange power of the interconnection line, and improve the configuration scale, system reliability, and economy of the photovoltaic energy storage system.

BackgroundLactiplantibacillus plantarum (L. plantarum) is known for its probiotic properties, including antioxidant and anti-inflammatory effects. Recent studies have highlighted the role of extracellular vesicles (EVs) from prokaryotic cells in anti-inflammatory effects.ObjectiveThis study aims to investigate the anti-inflammatory effects of extracellular vesicles derived from a newly isolated strain of L. plantarum (LP25 strain) and their role in macrophage polarization.MethodsThe LP25 strain and its extracellular vesicles were isolated and identified through genomic sequencing, transmission electron microscopy (TEM), and nanoparticle tracking analysis (NTA). RAW 264.7 cells were treated with lipopolysaccharide (LPS) and/or LP25-derived extracellular vesicles (LEV). Morphological changes in the cells were observed, and the expression levels of pro-inflammatory cytokines (TNF-α, IL-6)、iNOS and anti-inflammatory cytokines (IL-10) 、Arg-1 were measured using quantitative real-time PCR (qPCR). Flow cytometry was used to detect the expression of Arg-1 in the treated cells.ResultsTreatment with LP25 EVs led to significant morphological changes in RAW 264.7 cells exposed to LPS. LP25 EVs treatment resulted in increased expression of Arg-1 and anti-inflammatory cytokines IL-10, and decreased expression of iNOS and surface markers protein CD86. Flow cytometry confirmed the increased expression of the M2 macrophage marker Arg-1 in the LP25 EVs-treated group.ConclusionExtracellular vesicles from Lactiplantibacillus plantarum LP25 can suppress inflammatory responses and promote the polarization of macrophages toward the anti-inflammatory M2 phenotype. These findings provide new evidence supporting the anti-inflammatory activity of L. plantarum-derived EVs.

Abstract Small cell lung cancer (SCLC) is a highly aggressive malignancy characterized by rapid growth and early metastasis and is susceptible to treatment resistance and recurrence. Understanding the intra‐tumoral spatial heterogeneity in SCLC is crucial for improving patient outcomes and clinically relevant subtyping. In this study, a spatial whole transcriptome‐wide analysis of 25 SCLC patients at sub‐histological resolution using GeoMx Digital Spatial Profiling technology is performed. This analysis deciphered intra‐tumoral multi‐regional heterogeneity, characterized by distinct molecular profiles, biological functions, immune features, and molecular subtypes within spatially localized histological regions. Connections between different transcript‐defined intra‐tumoral phenotypes and their impact on patient survival and therapeutic response are also established. Finally, a gene signature, termed ITHtyper, based on the prevalence of intra‐tumoral heterogeneity levels, which enables patient risk stratification from bulk RNA‐seq profiles is identified. The prognostic value of ITHtyper is rigorously validated in independent multicenter patient cohorts. This study introduces a preliminary tumor‐centric, regionally targeted spatial transcriptome resource that sheds light on previously unexplored intra‐tumoral spatial heterogeneity in SCLC. These findings hold promise to improve tumor reclassification and facilitate the development of personalized treatments for SCLC patients.

IntroductionSoil fungal communities play a crucial role in maintaining the ecological functions of alpine forest soil ecosystems. However, it is currently unclear how the distribution patterns of fungal communities in different soil layers of alpine forests will change along the elevational gradients.Material and methodsTherefore, Illumina MiSeq sequencing technology was employed to investigate fungal communities in three soil layers (0–10, 10–20, and 20–30 cm) along an elevational gradient (3500 m to 4300 m) at Sygera Mountains, located in Bayi District, Nyingchi City, Tibet.Results and discussionThe results indicated that: 1) Soil depth had a greater impact on fungal diversity than elevation, demonstrating a significant reduction in fungal diversity with increased soil depth but showing no significant difference with elevation changes in all soil layers. Within the 0–10 cm soil layer, both Basidiomycota and Ascomycota co-dominate the microbial community. However, as the soil depth increases to 10–20 and 20–30 cm soil layers, the Basidiomycota predominantly dominates. 2) Deterministic processes were dominant in the assembly mechanism of the 0–10 cm fungal community and remained unchanged with increasing elevation. By contrast, the assembly mechanisms of the 10–20 and 20–30 cm fungal communities shifted from deterministic to stochastic processes as elevation increased. 3) The network complexity of the 0–10 cm fungal community gradually increased with elevation, while that of the 10–20 and 20–30 cm fungal communities exhibited a decreasing trend. Compared to the 0–10 cm soil layer, more changes in the relative abundance of fungal biomarkers occurred in the 10–20 and 20–30 cm soil layers, indicating that the fungal communities at these depths are more sensitive to climate changes. Among the key factors driving these alterations, soil temperature and moisture soil water content stood out as pivotal in shaping the assembly mechanisms and network complexity of fungal communities. This study contributes to the understanding of soil fungal community patterns and drivers along elevational gradients in alpine ecosystems and provides important scientific evidence for predicting the functional responses of soil microbial ecosystems in alpine forests.

The immune system requires a high energy expenditure to resist pathogen invasion. Macrophages undergo metabolic reprogramming to meet these energy requirements and immunologic activity and polarize to M1-type macrophages. Understanding the metabolic pathway switching in large yellow croaker (Larimichthys crocea) macrophages in response to lipopolysaccharide (LPS) stimulation and whether this switching affects immunity is helpful in explaining the stronger immunity of hypoxia-tolerant L. crocea. In this study, transcript levels of glycolytic pathway genes (Glut1 and Pdk1), mRNA levels or enzyme activities of glycolytic enzymes [hexokinase (HK), phosphofructokinase (PFK), pyruvate kinase (PK), and lactate dehydrogenase A (LDHA)], aerobic respiratory enzymes [pyruvate dehydrogenase (PDH), isocitrate dehydrogenase (IDH), and succinate dehydrogenase (SDH)], metabolites [lactic acid (LA) and adenosine triphosphate (ATP)], levels of bactericidal products [reactive oxygen species (ROS) and nitric oxide (NO)], and transcripts and level changes of inflammatory factors [IL1β, TNFα, and interferon (IFN) γ] were detected in LPS-stimulated L. crocea head kidney macrophages. We showed that glycolysis was significantly induced, the tricarboxylic acid (TCA) cycle was inhibited, and metabolic reprogramming occurred, showing the Warburg effect when immune cells were activated. To determine the potential regulatory mechanism behind these changes, LcHIF-1α was detected and found to be significantly induced and transferred to the nucleus after LPS stimulation. LcHif-1α interference led to a significant reduction in glycolytic pathway gene transcript expression, enzyme activity, metabolites, bactericidal substances, and inflammatory factor levels; a significant increase in the aerobic respiration enzymes; and decreased migration, invasion, and phagocytosis. Further ultrastructural observation by electron microscopy showed that fewer microspheres contained phagocytes and that more cells were damaged after LcHif-1α interference. LcHif-1α overexpression L. crocea head kidney macrophages showed the opposite trend, and promoter activities of Ldha and Il1β were significantly enhanced after LcHif-1α overexpression in HEK293T cells. Our data showed that LcHIF-1α acted as a metabolic switch in L. crocea macrophages and was important in polarization. Hypoxia-tolerant L. crocea head kidney showed a stronger Warburg effect and inhibited the TCA cycle, higher metabolites, and bactericidal substance levels. These results collectively revealed that LcHif-1α may promote the functional activities of head kidney macrophages in protecting hypoxia-tolerant L. crocea from Aeromonas hydrophila infection.

Groundwater numerical modeling is a crucial scientific tool for understanding groundwater circulation and supporting regional water resource planning and management. The effectiveness of these models depends largely on the accuracy of hydrogeological parameters within aquifers, which are often spatially heterogeneous and randomly distributed due to complex geological and tectonic factors. Traditional modeling approaches frequently overlook this randomness, compromising the precision and resolution of groundwater simulations. This study focuses on a section of the Qingshui River in the Huaihe River Basin. Using field and laboratory data, probability distribution functions for key parameters like hydraulic conductivity, specific yield, and specific storage were developed. These functions were integrated into the groundwater model to reflect the inherent stochastic nature of aquifer properties. This integration significantly enhanced model accuracy, reducing the root mean square error of simulated water levels from 0.47–1.43 m to 0.13–0.16 m and improving the Nash-Sutcliffe efficiency coefficients (NSE) from −2.96–0.73 to 0.94–0.98. Additionally, the model facilitated analysis of the interactions between river and groundwater, particularly in the hyporheic zone, under various scenarios. It identified spatial and temporal variations in groundwater recharge dynamics and delay effects at different distances from the river channel. For instance, recharge rates at 50 m and 150 m from the river were 0.295 m/day and 0.015 m/day, respectively, indicating stronger recharge closer to the river. The study also assessed the impact of varying river flows, riverbed permeability, and irrigation practices on water exchanges between the river and groundwater. These factors were found to significantly influence the intensity of water exchange, seepage, and groundwater reserves. This research provides valuable insights for managing river-groundwater interactions and analyzing the ecological environment of surrounding groundwater systems, underscoring the importance of incorporating stochastic characteristics into groundwater modeling.

IntroductionBivalve aquaculture is an important pillar of China's fisheries, with over 1 million tonnes of scallop shells produced annually. However, most of these shells are directly discarded into the sea, leading to continuous pollution of the marine and coastal environments, especially the coast of Yantai in the Bohai Sea where a large number of discarded scallop shell have accumulated.MethodsTo trace the fate of scallop shells in the ocean, this study established a model for the transport of scallop shells, coupling a two-dimensional tidal current model using the adjoint method with a Lagrangian particle model. By simulating nested tidal models, the distribution of tidal residual current in the Yantai coastal region was obtained. Then, a Lagrangian particle model was used to track the transport pathways of pollutants in the sea.ResultsDriven by the residual current calculated from the tidal model with the actual situation, possible pollutant release areas were inferred. The results of Lagrangian particle tracking experiments indicate that pollutants were released from the upstream accumulation area, specifically the area near Penglai Hulushan, confirming previous speculation.DiscussionThe scallop shells transport model can accurately simulate the spatiotemporal profile of scallop shells, which is helpful for managing scallop shell resources and improving the level of shell reuse.

The coastal sea surface wind (SSW) field can be influenced by factors like land pollution and land terrain characteristics, resulting in lower accuracy than the open ocean. This article proposes an SSW field correction method that combines the light gradient boosting machine model with the cascade forest framework (CFLGBM) using Haiyang-2C (HY-2C) scatterometer to improve the quality of SSW field retrieval in global coastal regions. This method considers precipitation, sea surface temperature, and ocean currents, which influence the SSW, achieving significant correction performance in global coastal regions. Relative to the ERA5 wind field, the corrected SSW speed (SSWS) and SSW direction (SSWD) show root mean square errors (RMSE) of 0.89 m/s and 19.28°, with improvements of 40.67% and 36.93% over the HY-2C Level 2B (L2B) product. In comparison with the National Data Buoy Center buoy, the corrected SSWS and SSWD reduced the RMSE of the HY-2C L2B product by 40.69% and 29.77%, respectively. Moreover, the variation in RMSE of the corrected SSW field with distance from the coastline was analyzed. The corrected SSW field shows the most notable improvement within 0–50 km of the coastline, with up to 0.97 m/s reduction for SSWS and 15.69° reduction for SSWD. The CFLGBM SSW field correction method provides more accurate coastal wind field data for HY-2C and can be further extended to other scatterometers for coastal SSW field correction.

Handwritten mathematical expression recognition (HMER) poses a formidable challenge due to the intricate two-dimensional structures and diverse handwriting styles. This paper introduces a novel approach to improve HMER accuracy by employing an integrated, high-capacity architecture that combines Transformer and Convolutional Neural Network (CNN) models, along with a denoising diffusion probabilistic model (DDPM)-based data augmentation technique. We explore three combination strategies for an attention-based encoder-decoder (AED) HMER model: 1) The “Tandem” strategy, which harnesses CNN features within a Transformer encoder to capture global interdependencies; 2) The “Parallel” strategy, which integrates Transformer encoder outputs with CNN outputs to achieve comprehensive feature fusion; 3) The “Mixing” strategy, which introduces multi-head self-attention (MHSA) at the final stage of the CNN. We evaluate these methods using the CROHME benchmark dataset and conduct a detailed comparative analysis. All three approaches significantly enhance model performance. Notably, the “Tandem” approach achieves expression recognition rates (ExpRate) of 54.85% and 58.56% on the CROHME 2016 and 2019 test sets, respectively, while the “Parallel” method attains 55.63% and 57.39% on the same test sets. Furthermore, we introduce an innovative data augmentation approach that utilizes DDPM to generate synthetic training samples. The DDPM, conditioned on LaTeX-rendered images, bridges the gap between printed and handwritten expressions, enabling the creation of realistic, stylistically diverse handwriting samples. This augmentation boosts the ExpRates of all strategies on both CROHME 2016 and 2019 test sets, yielding improvements of 1.6-4.6% relative to the unaugmented dataset.

Abstract Global lake ecosystems are subjected to an increased occurrence of heat extremes, yet their impact on lake warming remains poorly understood. In this study, we employed a hybrid physically-based/statistical model to assess the contribution of heat extremes to variations in surface water temperature of 2260 lakes in China from 1985 to 2022. Our study indicates that heat extremes are increasing at a rate of about 2.08 days/decade and an intensity of about 0.03 °C/ day·decade in China. The warming rate of lake surface water temperature decreases from 0.16 °C/decade to 0.13 °C/decade after removing heat extremes. Heat extremes exert a considerable influence on long-term lake surface temperature changes, contributing 36.5% of the warming trends within the studied lakes. Given the important influence of heat extremes on the mean warming of lake surface waters, it is imperative that they are adequately accounted for in climate impact studies.

Abstract Small cell lung cancer (SCLC) is a highly aggressive subtype of lung cancer characterized by rapid tumor growth and early metastasis. Accurate prediction of prognosis and therapeutic response is crucial for optimizing treatment strategies and improving patient outcomes. In this study, we conducted a deep-learning analysis of Hematoxylin and Eosin (H&E) stained histopathological images using contrastive clustering and identified 50 intricate histomorphological phenotype clusters (HPCs) as pathomic features. We identified two of 50 HPCs with significant prognostic value and then integrated them into a pathomics signature (PathoSig) using the Cox regression model. PathoSig showed significant risk stratification for overall survival and disease-free survival and successfully identified patients who may benefit from postoperative or preoperative chemoradiotherapy. The predictive power of PathoSig was validated in independent multicenter cohorts. Furthermore, PathoSig can provide comprehensive prognostic information beyond the current TNM staging system and molecular subtyping. Overall, our study highlights the significant potential of utilizing histopathology images-based deep learning in improving prognostic predictions and evaluating therapeutic response in SCLC. PathoSig represents an effective tool that aids clinicians in making informed decisions and selecting personalized treatment strategies for SCLC patients.

Abstract Background Prunella vulgaris polysaccharide extracted by hot water and 30% ethanol precipitation (PVE30) was reported to possess potent antiviral effects against herpes simplex virus (HSV) infection. However, its anti-HSV mechanism has not yet been fully elucidated. Purpose This study aimed to investigate the potential mechanisms of PVE30 against HSV infection. Methods Antiviral activity was evaluated by a plaque reduction assay, and the EC50 value was calculated. Immunofluorescence staining and heparin bead pull-down assays confirmed the interactions between PVE30 and viral glycoproteins. Real-time PCR was conducted to determine the mRNA levels of viral genes, including UL54, UL29, UL27, UL44, and US6, and the proinflammatory cytokines IL-6 and TNF-α. The protein expression of viral proteins (ICP27, ICP8, gB, gC, and gD), the activity of the TLR-NF-κB signalling pathway, and necroptotic-associated proteins were evaluated by Western blotting. The proportion of necroptotic cells was determined by flow cytometric analysis. Results The P. vulgaris polysaccharide PVE30 was shown to compete with heparan sulfate for interaction with HSV surface glycoprotein B and gC, thus strongly inhibiting HSV attachment to cells. In addition, PVE30 downregulated the expression of IE genes, which subsequently downregulated the expression of E and L viral gene products, and thus effectively restricted the yield of progeny virus. Further investigation confirmed that PVE30 inhibited TLR2 and TLR3 signalling, leading to the effective suppression of NF-κB activation and IL-6 and TNF-α expression levels, and blocked HSV-1-induced necroptosis by reducing HSV-1-induced phosphorylation of MLKL. Conclusion Our results demonstrate that the P. vulgaris polysaccharide PVE30 is a potent anti-HSV agent that blocks TLR-mediated NF-κB activation. Graphical Abstract

Using the FY-3G/MWRI-RM observations, this paper proposes a precipitation retrieval method that combines the Synthetic Minority Over-sampling Technique with Light Gradient Boosting Machine (SMOTE-LGBM) and analyzes the impact of MWRI-RM channel settings on precipitation retrieval. The SMOTE-LGBM-based model consists of two LGBM models for precipitation identification and estimation, respectively. The SMOTE method is used to address the imbalance between precipitation and non-precipitation samples. Using the Integrated Multi-Satellite Retrievals for the Global Precipitation Measurement (IMERG) product as a reference, we validate the retrieved precipitation by the SMOTE-LGBM-based model with an independent testing dataset. The critical success indexes are 0.483 and 0.526, and the Pearson correlation coefficients are 0.611 and 0.645 for the ocean and land regions, respectively. The spatial distributions of the retrieved and IMERG accumulated precipitation in the testing dataset are similar. In addition, we visualize and analyze the cases of Meiyu and two typhoons. The results indicate that the SMOTE-LGBM-based model effectively represents the spatial distribution characteristics of precipitation and achieves high agreement with IMERG precipitation products. Overall, the SMOTE-LGBM-based model successfully retrieves precipitation from MWRI-RM and provides accurate precipitation products for FY-3G/MWRI-RM for the first time.

Our study investigates the use of machine learning models for daily precipitation prediction using data from 56 meteorological stations in Jilin Province, China. We evaluate Stacked Long Short-Term Memory (LSTM), Transformer, and Support Vector Regression (SVR) models, with Stacked-LSTM showing the best performance in terms of accuracy and stability, as measured by the Root Mean Square Error (RMSE). To improve robustness, Gaussian noise was introduced, particularly enhancing predictions for zero-precipitation days. Key predictors identified through variable attribution analysis include temperature, dew point, prior precipitation, and air pressure. Additionally, we demonstrate the practical benefits of precipitation forecasts in optimizing water resource allocation. A prediction-based strategy outperforms equal distribution in managing resources efficiently, as shown in a case study using 2022 Beidahu data. Overall, our research advances precipitation forecasting through deep learning and offers valuable insights for water resource management.

Clinical treatment of diabetic refractory ulcers is impeded by chronic inflammation and cell dysfunction associated with wound healing. The significant clinical application of bFGF in wound healing is limited by its instability in vivo. Sulfur has been applied for the treatment of skin diseases in the clinic for antibiosis. We previously found that sulfur incorporation improves the ability of selenium nanoparticles to accelerate wound healing, yet the toxicity of selenium still poses a risk for its clinical application. To obtain materials with high pro-regeneration activity and low toxicity, we explored the mechanism by which selenium-sulfur nanoparticles aid in wound healing via RNA-Seq and designed a nanoparticle called Nano-S@bFGF, which was constructed from sulfur and bFGF. As expected, Nano-S@bFGF not only regenerated zebrafish tail fins and promoted skin wound healing but also promoted skin repair in diabetic mice with a profitable safety profile. Mechanistically, Nano-S@bFGF successfully coactivated the FGFR and Hippo signalling pathways to regulate wound healing. Briefly, the Nano-S@bFGF reported here provides an efficient and feasible method for the synthesis of bioactive nanosulfur and bFGF. In the long term, our results reinvigorated efforts to discover more peculiar unique biofunctions of sulfur and bFGF in a great variety of human diseases.

Maize, a salt-sensitive crop, frequently suffers severe yield losses due to soil salinization. Enhancing salt tolerance in maize is crucial for maintaining yield stability. To address this, we developed an introgression line (IL76) through introgressive hybridization between maize wild relatives Zea perennis, Tripsacum dactyloides, and inbred Zheng58, utilizing the tri-species hybrid MTP as a genetic bridge. Previously, genetic variation analysis identified a polymorphic marker on Zm00001eb244520 (designated as ZmSC), which encodes a vesicle-sorting protein described as a salt-tolerant protein in the NCBI database. To characterize the identified polymorphic marker, we employed gene cloning and homologous cloning techniques. Gene cloning analysis revealed a non-synonymous mutation at the 1847th base of ZmSCIL76, where a guanine-to-cytosine substitution resulted in the mutation of serine to threonine at the 119th amino acid sequence (using ZmSCZ58 as the reference sequence). Moreover, homologous cloning demonstrated that the variation site derived from Z. perennis. Functional analyses showed that transgenic Arabidopsis lines overexpressing ZmSCZ58 exhibited significant reductions in leaf number, root length, and pod number, alongside suppression of the expression of genes in the SOS and CDPK pathways associated with Ca2+ signaling. Similarly, fission yeast strains expressing ZmSCZ58 displayed inhibited growth. In contrast, the ZmSCIL76 allele from Z. perennis alleviated these negative effects in both Arabidopsis and yeast, with the lines overexpressing ZmSCIL76 exhibiting significantly higher abscisic acid (ABA) content compared to those overexpressing ZmSCZ58. Our findings suggest that ZmSC negatively regulates salt tolerance in maize by suppressing downstream gene expression associated with Ca2+ signaling in the CDPK and SOS pathways. The ZmSCIL76 allele from Z. perennis, however, can mitigate this negative regulatory effect. These results provide valuable insights and genetic resources for future maize salt tolerance breeding programs.

The rapid expansion of urban drainage pipe networks, driven by economic development, poses significant challenges for efficient monitoring and management. The complexity and scale of these networks make it difficult to effectively monitor and manage the discharge of urban domestic sewage, rainwater, and industrial effluents, leading to illegal discharges, leakage, environmental pollution, and economic losses. Efficient management relies on a rational layout of drainage pipe network monitoring points. However, existing research on optimal monitoring point layout is limited, primarily relying on manual analysis and fuzzy clustering methods, which are prone to human bias and ineffective monitoring data. To address these limitations, this study proposes a coupled model approach for the automatic optimization of monitoring point placement in drainage pipe networks. The proposed model integrates the information entropy index, Bayesian reasoning, the Monte Carlo method, and the stormwater management model (SWMM) to optimize monitoring point placement objectively and measurably. The information entropy algorithm is utilized to quantify the uncertainty and complexity of the drainage pipe network, facilitating the identification of optimal monitoring point locations. Bayesian reasoning is employed to update probabilities based on observed data, while the Monte Carlo method generates probabilistic distributions for uncertain parameters. The SWMM is utilized to simulate stormwater runoff and pollutant transport within the drainage pipe network. Results indicate that (1) the relative mean error of the parameter inversion simulation results of the pollution source tracking model is linearly fitted with the information entropy. The calculation shows that there is a good positive linear correlation between them, which verifies the feasibility of the information entropy algorithm in the field of monitoring node optimization; (2) the information entropy algorithm can be well applied to the optimal layout of a single monitoring node and multiple monitoring nodes, and it can correspond well to the inversion results of the tracking model parameters; (3) the constructed monitoring point optimization model can well realize the optimal layout of monitoring points of a drainage pipe network. Finally, the pollution source tracking model is used to verify the effectiveness of the optimal layout of monitoring points, and the whole process has less human participation and a high degree of automation. The automated monitoring point optimization layout model proposed in this study has been successfully applied in practical cases, significantly improving the efficiency of urban drainage network monitoring and reducing the degree of manual participation, which has important practical significance for improving the level of urban water environment management.

Introduction: The bone ingrowth depth in the porous scaffolds is greatly affected by the structural design, notably the pore size, pore geometry, and the pore distribution. To enhance the bone regeneration capability of scaffolds, the bionic design can be regarded as a potential solution. Objectives: We proposed a Haversian system-like gradient structure based on the triply periodic minimal surface architectures with pore size varying from the edge to the center. And its effects in promoting bone regeneration were evaluated in the study. Methods: The gradient scaffold was designed using the triply periodic minimal surface architectures. The mechanical properties were analyzed by the finite element simulation and confirmed using the universal machine. The fluid characteristics were calculated by the computational fluid dynamics analysis. The bone regeneration process was simulated using a in silico computational model containing the main biological, physical, and chemical variation during the bone growth process. Finally, the in vitro and in vivo studies were carried out to verify the actual osteogenic effect. Results: Compared to the uniform scaffold, the biomimetic gradient scaffold demonstrated better performance in stress conduction and reduced stress shielding effects. The fluid features were appropriate for cell migration and flow diffusion, and the permeability was in the same order of magnitude with the natural bone. The bone ingrowth simulation exhibited improved angiogenesis and bone regeneration. Higher expression of the osteogenesis-related genes, higher alkaline phosphatase activity, and increased mineralization could be observed on the gradient scaffold in the in vitro study. The 12-week in vivo study proved that the gradient scaffold had deeper bone inserting depth and a more stable bone-scaffold interface. Conclusion: The Haversian system-like gradient structure can effectively promote the bone regeneration. This structural design can be used as a new solution for the clinical application of prosthesis design.

To supply more insights into the roles of putrescine (Put) in alleviating salt stress in wheat crops, we explored the effects of Put on ascorbate (ASC) and glutathione metabolism, photosynthetic performance, and ion homeostasis in leaves of salt-stressed wheat seedlings. Our results displayed that salt stress increased the activities of enzymes in ASC and glutathione metabolism, including ascorbate peroxidase, dehydroascorbate reductase, monodehydroascorbate reductase, glutathione reductase, gamma-glutamylcysteine synthetase, and l-galactono-1,4-lactone dehydrogenase, which increased reduced ascorbate (AsA), dehydroascorbate (DHA), reduced glutathione (GSH), oxidised glutathione (GSSG), total ASC and total glutathione contents. Whereas, salt stress induced higher increases in the contents of DHA and GSSG than those of AsA and GSH, which led to reduced AsA/DHA and GSH/GSSG. Meanwhile, salt stress reduced photosynthetic rate (Pn), maximum photochemical efficiency of PSII (Fv/Fm), and the contents of chlorophyll and carotenoids, and destroyed Na+/K+ homeostasis, which further inhibited plant growth. In comparison with salt stress alone, Put strengthened the activities of the above enzymes, which further increased the above metabolites contents, as well as AsA/DHA and GSH/GSSG in leaves of salt-treated seedlings. In this way, Put reduced malondialdehyde content and electrolyte leakage. Besides, Put also increased Pn, Fv/Fm, and above pigments contents, and maintained Na+/K+ homeostasis. Meanwhile, Put increased plant height and biomass of salt-treated seedlings. The present findings clearly implied that Put enhanced salt tolerance of wheat crops by strengthening ASC and glutathione metabolism, photosynthetic performance, and maintaining ion homeostasis in leaves. Therefore, Put can be applied to strengthen the salt tolerance of wheat crops in production and cultivation.

Abstract Atmospheric warming heats lakes, but the causes of variation among basins are poorly understood. Here, multi-decadal profiles of water temperatures, trophic state, and local climate from 345 temperate lakes are combined with data on lake geomorphology and watershed characteristics to identify controls of the relative rates of temperature change in water (WT) and air (AT) during summer. We show that differences in local climate (AT, wind speed, humidity, irradiance), land cover (forest, urban, agriculture), geomorphology (elevation, area/depth ratio), and water transparency explain >30% of the difference in rate of lake heating compared to that of the atmosphere. Importantly, the rate of lake heating slows as air warms (P

This paper proposes an improved multi-agent deep deterministic policy gradient algorithm called the equal-reward and action-enhanced multi-agent deep deterministic policy gradient (EA-MADDPG) algorithm to solve the guidance problem of multiple missiles cooperating to intercept a single intruding UAV in three-dimensional space. The key innovations of EA-MADDPG include the implementation of the action filter with additional reward functions, optimal replay buffer, and equal reward setting. The additional reward functions and the action filter are set to enhance the exploration performance of the missiles during training. The optimal replay buffer and the equal reward setting are implemented to improve the utilization efficiency of exploration experiences obtained through the action filter. In order to prevent over-learning from certain experiences, a special storage mechanism is established, where experiences obtained through the action filter are stored only in the optimal replay buffer, while normal experiences are stored in both the optimal replay buffer and normal replay buffer. Meanwhile, we gradually reduce the selection probability of the action filter and the sampling ratio of the optimal replay buffer. Finally, comparative experiments show that the algorithm enhances the agents’ exploration capabilities, allowing them to learn policies more quickly and stably, which enables multiple missiles to complete the interception task more rapidly and with a higher success rate.

Exploring the spatial distribution of sea surface height involves two primary methodologies: utilizing gridded reanalysis data post-secondary processing or conducting direct fitting along-track data. While processing gridded reanalysis data may entail information loss, existing direct fitting methods have limitations. Therefore, there is a pressing need for novel direct fitting approaches to enhance efficiency and accuracy in sea surface height fitting. This study demonstrates the viability of Legendre polynomial surface fitting, benchmarked against bicubic quasi-uniform B-spline surface fitting, which has been proven to be a well-established direct fitting method. Despite slightly superior accuracy exhibited by bicubic quasi-uniform B-spline surface fitting under identical order combinations, Legendre polynomial surface fitting offers a simpler structure and enhanced controllability. However, it is pertinent to note that significant expansion of the spatial scope of fitting often results in decreased fitting efficacy. To address this, the current research achieves the precise fitting of sea surface height across expansive spatial ranges through a regional stitching methodology.

Finger vein recognition methods, as emerging biometric technologies, have attracted increasing attention in identity verification due to their high accuracy and live detection capabilities. However, as privacy protection awareness increases, traditional centralized finger vein recognition algorithms face privacy and security issues. Federated learning, a distributed training method that protects data privacy without sharing data across endpoints, is gradually being promoted and applied. Nevertheless, its performance is severely limited by heterogeneity among datasets. To address these issues, this paper proposes a dual-decoupling personalized federated learning framework for finger vein recognition (DDP-FedFV). The DDP-FedFV method combines generalization and personalization. In the first stage, the DDP-FedFV method implements a dual-decoupling mechanism involving model and feature decoupling to optimize feature representations and enhance the generalizability of the global model. In the second stage, the DDP-FedFV method implements a personalized weight aggregation method, federated personalization weight ratio reduction (FedPWRR), to optimize the parameter aggregation process based on data distribution information, thereby enhancing the personalization of the client models. To evaluate the performance of the DDP-FedFV method, theoretical analyses and experiments were conducted based on six public finger vein datasets. The experimental results indicate that the proposed algorithm outperforms centralized training models without increasing communication costs or privacy leakage risks.

The tomato leafminer, Tuta absoluta (Lepidoptera: Gelechiidae), is a highly destructive invasive pest targeting Solanaceae crops. Its olfactory system plays a crucial role in host location, mate finding, and other behavioral activities. However, there is a notable gap in the literature regarding the characterization of its chemosensory genes. In this study, we conducted a genome-wide identification of 58 odorant receptors (ORs) of T. absoluta. The identified ORs exhibit coding sequence (CDS) lengths ranging from 1062 bp to 1419 bp, encoding proteins of 354 to 473 amino acids. Gene structure analysis showed that the majority of these ORs consist of five, seven, eight, or nine exons, collectively representing 67% of the total ORs identified. Through chromosomal mapping, we identified several tandemly duplicate genes, including TabsOR12a, TabsOR12b, TabsOR12c, TabsOR21a, TabsOR21b, TabsOR34a, TabsOR34b, TabsOR34c, TabsOR62a, and TabsOR62b. The phylogenetic analysis indicated that six TabsORs were clustered within the lepidopteran sex pheromone receptor clade, while an expansion clade containing ten TabsORs resulted from tandem duplication events. Additionally, five TabsORs were classified into a specific OR clade in T. absoluta. Furthermore, through RNA-Seq and RT-qPCR analyses, we identified five TabsORs (TabsOR21a, TabsOR26a, TabsOR34a, TabsOR34c, and TabsOR36) exhibiting female-antennae-biased expression. Our study provides a valuable foundation to further investigations into the molecular and ecological functions of TabsORs, particularly in relation to oviposition behavior. These findings provide foundational data for the future exploration of the functions of female-biased expression OR genes in T. absoluta, thereby facilitating the further development of eco-friendly attract-and-kill techniques for the prevention and control of T. absoluta.

Due to the existence of cotton weeds in a complex cotton field environment with many different species, dense distribution, partial occlusion, and small target phenomena, the use of the YOLO algorithm is prone to problems such as low detection accuracy, serious misdetection, etc. In this study, we propose a YOLOv8-DMAS model for the detection of cotton weeds in complex environments based on the YOLOv8 detection algorithm. To enhance the ability of the model to capture multi-scale features of different weeds, all the BottleNeck are replaced by the Dilation-wise Residual Module (DWR) in the C2f network, and the Multi-Scale module (MSBlock) is added in the last layer of the backbone. Additionally, a small-target detection layer is added to the head structure to avoid the omission of small-target weed detection, and the Adaptively Spatial Feature Fusion mechanism (ASFF) is used to improve the detection head to solve the spatial inconsistency problem of feature fusion. Finally, the original Non-maximum suppression (NMS) method is replaced with SoftNMS to improve the accuracy under dense weed detection. In comparison to YOLO v8s, the experimental results show that the improved YOLOv8-DMAS improves accuracy, recall, mAP0.5, and mAP0.5:0.95 by 1.7%, 3.8%, 2.1%, and 3.7%, respectively. Furthermore, compared to the mature target detection algorithms YOLOv5s, YOLOv7, and SSD, it improves 4.8%, 4.5%, and 5.9% on mAP0.5:0.95, respectively. The results show that the improved model could accurately detect cotton weeds in complex field environments in real time and provide technical support for intelligent weeding research.

Abstract In this study, Sb‐doped SnO2 nanosphere composite polypyrrole nanohybrid with different doping ratios (0–5 mol%, Sb:Sn) and composite ratios (0–30 mol%, Sb‐doped SnO2:polypyrrole) is synthesized by hydrothermal method and in situ chemical oxidation method. The flexible sensors are fabricated by drop‐casting the materials on polyamide substrate and gas sensing performances are investigated systematically at room temperature. The results show that the 3 at% Sb‐doped 20 mol% SnO2/polypyrrole nanohybrid exhibits excellent sensitivity (≈213% toward 100 ppm NH3) at room temperature, which are about 3 times as much as those of polypyrrole, as well as excellent selectivity and humidity resistance, reliable repeatability, and good robustness. The enhance sensing performance can be attributed to the formation of p‐n junction between conducting polymers and metal oxide semiconductor materials and the doping of Sb elements allows more electrons to transfer to polypyrrole, which further thickens the depletion layer and decreases hole concentrations in air. Therefore, Sb‐doped SnO2/polypyrrole nanohybrid may be a promising sensitive material for the design and manufacture of room temperature flexible ammonia gas sensors.

F– ions (fluoride ions) are crucial in various chemical waste and environmental safety contexts. However, excessive fluoride exposure can pose a threat to human well-being. In this study, a simple 4-substituted pyrene derivative known as 4-hydroxypyrene (4-PyOH) was designed as a colorimetric probe for detecting F– through the formation of hydrogen bonds between F– and a hydroxyl group. The probe 4-PyOH exhibited exceptional sensitivity and selectivity towards F– ions and was successfully utilized as test strips for detecting F– ions in organic solvents. The detection limit reached an impressively low level of 3.06 × 10−7 M in the organic solvent. The recognition mechanism was confirmed through 1H NMR titration.

Abstract Background Hepatocellular carcinoma (HCC) is one of the most common and lethal cancers worldwide, but current treatment options remain limited and cause serious life-threatening side effects. Aberrant FGFR4 signaling has been validated as an oncogenic driver of HCC, and EZH2, the catalytic subunit of the PRC2 complex, is a potential factor that contributes to acquired drug resistance in many tumors, including HCC. However, the functional relationship between these two carcinogenic factors, especially their significance for HCC treatment, remains unclear. In this study, we systematically evaluated the feasibility of a combination therapy targeting FGFR4 and EZH2 for HCC. Methods RNA sequencing data of patients with Liver hepatocellular carcinoma (LIHC) from The Cancer Genome Atlas (TCGA) were analyzed to determine FGFR4 and EZH2 expression and their interaction with prognosis. Moreover, the HCC cell lines, zebrafish/mouse HCC xenografts and zebrafish HCC primary tumors were treated with FGFR4 inhibitor (Roblitinib) and/or EZH2 inhibitor (CPI-169) and then subjected to cell proliferation, viability, apoptosis, and tumor growth analyses to evaluate the feasibility of combination therapy for HCC both in vitro and in vivo. Furthermore, RNA-Seq was performed in combination with ChIP-Seq data analysis to investigate the critical mechanism underlying the combination treatment with Roblitinib and CPI-169. Results EZH2 accumulated through the non-canonical NF-kB signaling in response to FGFR4 inhibitor treatment, and the elevated EZH2 levels led to the antagonism of HCC against Roblitinib (FGFR4 inhibitor). Notably, knockdown of EZH2 sensitized HCC cells to Roblitinib, while the combination treatment of Roblitinib and CPI-169 (EZH2 inhibitor) synergistically induced the HCC cell apoptosis in vitro and suppressed the zebrafish/mouse HCC xenografts and zebrafish HCC primary tumors development in vivo. Moreover, Roblitinib and CPI-169 synergistically inhibited HCC development via repressing YAP signaling. Conclusions Collectively, our study highlighted the potential of the therapeutic combination of FGFR4 and EZH2 inhibitors, which would provide new references for the further development of clinical treatment strategies for HCC.

Thumbnail-preserving encryption (TPE) can balance the usability and the privacy of images in the cloud. Most ideal TPE schemes obtain thumbnails by dividing the plaintext image into multiple blocks, and then perform substitution and permutation operations in each block. The size of partitioned blocks affect the usability and the privacy of the encrypted images. The size of the pixel groups in the blocks, i.e., the number of encrypted pixels per time, has experienced the development from 2-pixel to n-pixel in recent years. Existing solutions cannot promote the real implementation and commercial realization because of inefficiency and instability. In this paper, we propose an efficient and stable TPE scheme, which can select intelligently different sizes of pixel groups in each block. Theoretical analysis indicates that the encryption time is influenced by the sum and the number of pixels in a pixel group. The length of the pixel group and the sum of pixel values in a group influence each other. We try to determine the optimal combination of these two factors. Through the analysis of Markov model, the proposed scheme has the nonce-respecting security. The experimental results of comparison show that, for the images with size of 480 × 320, the average encryption time of the proposed scheme is 61.7% less than that of 3-pixel flexible TPE, which is the most effective scheme up to now. And the fluctuation value decreases by 34.8%.

African swine fever virus (ASFV) infection is a major public and socioeconomic concern that has a serious impact on the global swine industry. Unfortunately, there are currently no commercially available vaccines or antiviral agents that are both safe and effective against ASFV. In the study, we use primary porcine alveolar macrophages to screen a kinase inhibitor library for anti-ASFV compounds. Six candidate compounds that inhibited ASFV infection with inhibition of > 90% were identified, among which brincidofovir exhibited optimal inhibitory effects on ASFV. Brincidofovir reduces ASFV replication in a dose-dependent manner (IC50 = 2.76 nM) without cytotoxicity (CC50 = 58 μM). It possesses the ability to reduce viral titres and inhibit viral structural protein expression. Time-of-addition assays suggest that the compound interferes with the post-invasion stage of the viral infection cycle. In pig challenge experiments, brincidofovir was indicated to protect pigs against ASFV-induced lethality by decreasing the viral load in organs and peripheral blood, while it alleviated the histopathological changes associated with ASFV infection. Furthermore, brincidofovir also decreased viral shedding in pigs with ASFV infection. Our data together demonstrate that brincidofovir may serve as a potentially effective agent for the prevention and control of ASFV infection, whereas further investigations are still required.

Objective: Non-alcoholic fatty liver disease (NAFLD) is the leading chronic liver disease. We have developed a Korean Red Ginseng Formula (KRGF) containing extracts of Korean Red Ginseng (KRG), Crataegus Fructus, and Cassiae Semen. In this study, our aims were to investigate the therapeutic potential and underpinning mechanisms of KRGF in NAFLD complicated by hyperlipidemia. Methods: In the in vitro assays, HepG2 cells were treated with KRGF for 24 h in the presence or absence of oleic acid (OA). To assess the in vivo protective effect of KRGF against NAFLD, rats fed a high-fat diet (HFD) were given intragastric administration for 30 days. Results: KRGF exerted protective effects against NAFLD by reducing lipid accumulation and steatosis in OA-stimulated HepG2 cells and HFD-fed rats. In HFD-fed rats, KRGF effectively decreased triglyceride levels in both blood and liver tissue and modulated the expression of key regulators of lipogenesis and fatty acid oxidation. KRGF downregulated the expression of lipogenesis factors, namely C/EBPα, FAS, SREBP-1c, and PPARγ, while upregulating the expression of PPARα and CPT-1, thus promoting fatty acid oxidation. Additionally, KRGF intensified the phosphorylation of AMPK and ACC, which are two enzymes that suppress fatty acid synthesis and promote fatty acid oxidation. KRGF effectively decreased total cholesterol (TC) levels in both blood and liver tissue, and it modulated the expression of major enzymes related to TC metabolism, namely apoB, ACAT2, CYP7A1, and HMGCR. Conclusion: In conclusion, KRGF mitigated NAFLD complicated by hyperlipidemia by modulating triglyceride and cholesterol metabolism, suggesting its potential for future development in the treatment of NAFLD.

MXenes have great potential as fast‐charging anodes for sodium storage due to their excellent electrical conductivity, high pseudocapacitive charge storage, and large interlayer distance. The intercalation pseudocapacitance provided by the active sites within the laminate MXene nanosheets is generally the major contributor to their sodium‐storage capacity. Thus, it is highly preferred to construct porous materials with abundant laminate structures to overcome the ion‐diffusion limitation in MXene multilayer films and increase the accessible interlayer sites. Herein, the enhancement of laminate structures in a pre‐assembled Ti3C2Tx network is achieved, under the effects of interlayer slipping of MXene nanosheets during capillary densification, and finally obtained a dense monolith with both high density (2.37 g cm−3) and high porosity (87.3 m2 g−1). This MXene anode material delivers a high capacity of 185 mAh g−1 and a superior rate performance of 55 mAh g−1 (5 A g−1). With improvement of both density and gravimetric capacity, this monolith has a high volumetric capacity of up to 200 mAh cm−3 at 1 A g−1 even after 2000 cycles. Herein, new insights are provided into the design of high‐capacity MXene anodes for sodium‐ion batteries and control of different 2D materials in compact structures.

Viral infections are known as one of the major factors causing death. Ginseng is a medicinal plant that demonstrated a wide range of antiviral potential, and saponins are the major bioactive ingredients in the genus Panax with vast therapeutic potential. Studies focusing on the antiviral activity of the genus Panax plant-derived agents (extracts and saponins) and their mechanisms were identified and summarized, including contributions mainly from January 2016 until January 2022. P. ginseng, P. notoginseng, and P. quinquefolius were included in the review as valuable medicinal herbs against infections with 14 types of viruses. Reports from 9 extracts and 12 bioactive saponins were included, with 6 types of protopanaxadiol (PPD) ginsenosides and 6 types of protopanaxatriol (PPT) ginsenosides. The mechanisms mainly involved the inhibition of viral attachment and replication, the modulation of immune response by regulating signaling pathways, including the Janus kinase (JAK)/signal transducer and activator of transcription (STAT) pathway, cystathionine γ-lyase (CSE)/hydrogen sulfide (H2S) pathway, phosphoinositide-dependent kinase-1 (PDK1)/ protein kinase B (Akt) signaling pathway, c-Jun N-terminal kinase (JNK)/activator protein-1 (AP-1) pathway, and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) pathway. This review includes detailed information about the mentioned antiviral effects of the genus Panax extracts and saponins in vitro and in vivo, and in human clinical trials, which provides a scientific basis for ginseng as an adjunctive therapeutic drug or nutraceutical.

Abstract Background Globally, millions of patients suffer from regenerative deficiencies, such as refractory wound healing, which is characterized by excessive inflammation and abnormal angiogenesis. Growth factors and stem cells are currently employed to accelerate tissue repair and regeneration; however, they are complex and costly. Thus, the exploration of new regeneration accelerators is of considerable medical interest. This study developed a plain nanoparticle that accelerates tissue regeneration with the involvement of angiogenesis and inflammatory regulation. Methods Grey selenium and sublimed sulphur were thermalized in PEG-200 and isothermally recrystallised to composite nanoparticles (Nano-Se@S). The tissue regeneration accelerating activities of Nano-Se@S were evaluated in mice, zebrafish, chick embryos, and human cells. Transcriptomic analysis was performed to investigate the potential mechanisms involved during tissue regeneration. Results Through the cooperation of sulphur, which is inert to tissue regeneration, Nano-Se@S demonstrated improved tissue regeneration acceleration activity compared to Nano-Se. Transcriptome analysis revealed that Nano-Se@S improved biosynthesis and ROS scavenging but suppressed inflammation. The ROS scavenging and angiogenesis-promoting activities of Nano-Se@S were further confirmed in transgenic zebrafish and chick embryos. Interestingly, we found that Nano-Se@S recruits leukocytes to the wound surface at the early stage of regeneration, which contributes to sterilization during regeneration. Conclusion Our study highlights Nano-Se@S as a tissue regeneration accelerator, and Nano-Se@S may provide new inspiration for therapeutics for regenerative-deficient diseases. Graphical Abstract

Abstract Acne is a chronic skin condition that has serious consequences for mental and social well-being because it frequently occurs on the face. Several acne treatment approaches have commonly been used but have been hampered by side effects or weak activity. Thus, the investigation of the safety and efficacy of anti-acne compounds is of considerable medical importance. Herein, an endogenous peptide (P5) derived from fibroblast growth factors 2 (FGF2) was conjugated to the polysaccharide hyaluronic acid (HA) to generate the bioconjugate nanoparticle HA-P5, which suppresses fibroblast growth factor receptors (FGFRs) to significantly rehabilitate acne lesions and reduce sebum accumulation in vivo and in vitro. Moreover, our results show that HA-P5 inhibits both fibroblast growth factor receptor 2 (FGFR2) and androgen receptor (AR) signalling in SZ95 cells, reverses the acne-prone transcriptome, and decreases sebum secretion. Furthermore, the cosuppression mechanism revealed that HA-P5 blocks FGFR2 activation, as well as the YTH N6-methyladenosine RNA binding protein F3 (YTHDF3) downstream molecules, including an N6-methyladenosine (m6A) reader that facilitates AR translation. More importantly, a significant difference between HA-P5 and the commercial FGFR inhibitor AZD4547 is that HA-P5 does not trigger the overexpression of aldo-keto reductase family 1 member C3 (AKR1C3), which blocks acne treatment by catalyzing the synthesis of testosterone. Overall, we demonstrate that a polysaccharide-conjugated and naturally derived oligopeptide HA-P5 can alleviate acne and act as an optimal FGFR2 inhibitor and reveal that YTHDF3 plays a crucial role in signalling between FGFR2 and AR. Graphical Abstract

Bacterial cellulose (BC) possesses the desirable properties of biocompatibility, high porosity, high surface area and noticeable mechanical strength as a scaffold in bone tissue engineering. However, the lack of osteogenic activity restricts its application. In this study, gold nanoparticles (GNPs) with excellent osteogenic differentiation ability were incorporated into the network of BC hydrogel (Au/BC hydrogels) by the in-situ fermentation. The effects of GNPs on physicochemical properties of BC hydrogel and subsequently in vitro osteogenic differentiation and in vivo bone regeneration of Au/BC hydrogels were comprehensively investigated. The results showed that the increased feeding amounts of GNPs could remarkablly enhance the Au/BC hydrogels with better mechanical properties, higher porosity, larger surface area, and biocompatibility. The sustainable release of GNPs endowed the hydrogels with an outstanding biological activity in facilitating osteogenic differentiation of human bone marrow-derived mesenchymal stem cells (hBMSCs). Mechanism research showed that autophagy might be a potential pathway for Au/BC hydrogels-induced osteogenic differentiation of hBMSCs. In addition, Au/BC hydrogel exhibited an excellent in vivo bone repair performance in a rabbit model of femoral defect, which was evidenced by the significant newly bone formation. Overall, the multifunctional Au/BC hydrogels fabricated by in-situ fermentation could serve as a good scaffold for promoting bone tissue regeneration in clinic.

Abstract Background Tripsacum dactyloides (2n = 4x = 72) and Zea perennis (2n = 4x = 40) are tertiary gene pools of Zea mays L. and exhibit many abiotic adaptations absent in modern maize, especially salt tolerance. A previously reported allopolyploid (hereafter referred to as MTP, 2n = 74) synthesized using Zea mays, Tripsacum dactyloides, and Zea perennis has even stronger salt tolerance than Z. perennis and T. dactyloides. This allopolyploid will be a powerful genetic bridge for the genetic improvement of maize. However, the molecular mechanisms underlying its salt tolerance, as well as the key genes involved in regulating its salt tolerance, remain unclear. Results Single-molecule real-time sequencing and RNA sequencing were used to identify the genes involved in salt tolerance and reveal the underlying molecular mechanisms. Based on the SMRT-seq results, we obtained 227,375 reference unigenes with an average length of 2300 bp; most of the unigenes were annotated to Z. mays sequences (76.5%) in the NR database. Moreover, a total of 484 and 1053 differentially expressed genes (DEGs) were identified in the leaves and roots, respectively. Functional enrichment analysis of DEGs revealed that multiple pathways responded to salt stress, including “Flavonoid biosynthesis,” “Oxidoreductase activity,” and “Plant hormone signal transduction” in the leaves and roots, and “Iron ion binding,” “Acetyl-CoA carboxylase activity,” and “Serine-type carboxypeptidase activity” in the roots. Transcription factors, such as those in the WRKY, B3-ARF, and bHLH families, and cytokinin negatively regulators negatively regulated the salt stress response. According to the results of the short time series-expression miner analysis, proteins involved in “Spliceosome” and “MAPK signal pathway” dynamically responded to salt stress as salinity changed. Protein–protein interaction analysis revealed that heat shock proteins play a role in the large interaction network regulating salt tolerance. Conclusions Our results reveal the molecular mechanism underlying the regulation of MTP in the response to salt stress and abundant salt-tolerance-related unigenes. These findings will aid the retrieval of lost alleles in modern maize and provide a new approach for using T. dactyloides and Z. perennis to improve maize.

Abstract To compare the safety and effectiveness of surgical treatment of jugular paragangliomas (JPs) following the application of our modified surgical techniques. Fifty-six patients with JPs were analyzed for tumor classification, surgical outcomes, and intratumor blood vessels. The gross total resection in C1–2 (100%) was significantly greater than that in C3 and D (66.7%). Good postoperative facial nerve (FN) function (House–Brackmann I–II) was achieved in 89.5% C1–2 cases, which was not significantly different from C3 and D (93.3%) (P = 0.694). Preoperative and postoperative lower cranial nerve (LCN) deficits correlated with the Fisch’s classification of tumors (P

Abstract Background Stroke is a devastating disease and can be sufficiently traumatic to induce post-traumatic stress disorder (PTSD). Post-stroke PTSD is attracting increasing attention, but there was no study assessing the psychometric properties of the PCL-5 in stroke populations. Our study was conducted to examine the psychometric properties of the PTSD Checklist for DSM-5 (PCL-5) in Chinese stroke patients. Methods This was a cross-sectional observational study conducted at our hospital. Three hundred and forty-eight Chinese stroke patients came to our hospital for outpatient service were recruited. They were instructed to complete the PCL-5 scales and were interviewed for PTSD diagnosis with the Clinician Administered PTSD Scale for DSM-5 (CAPS-5). The cutoff scores, reliability and validity of the PCL-5 were analyzed. Results PCL-5 scores in our sample were positively skewed, suggesting low levels of PTSD symptoms. The reliability of PCL-5 was good. Exploratory and confirmatory factor analyses indicated acceptable construct validity, and confirmed the multi-dimensionality of the PCL-5. By CFA analysis, the seven-factor hybrid model demonstrated the best model fit. The PCL-5 also showed good convergent validity and discriminant validity. Receiver operating characteristic (ROC) analyses revealed a PCL-5 score of 37 achieved optimal sensitivity and specificity for detecting PTSD. Conclusions Our findings supported the use of PCL-5 as a psychometrically adequate measure of post-stroke PTSD in the Chinese patients.

Secchi disk depth (SDD) is a simple but particularly important indicator for characterizing the overall water quality status and assessing the long-term dynamics of water quality for diverse global waters. For this reason, countless efforts have been made to collect SDD data from the field and through remote sensing systems. Many empirical and semianalytical algorithms have been proposed to estimate SDD from different satellite images for a specific or regional water. However, the construction of a robust global SDD estimation model is still challenging due to the nonlinear response of SDD to optical properties and the complex physical and biogeochemical processes of different waters. Therefore, machine learning methods to better interpret nonlinear processes were used to improve remote sensing estimations of SDD for global lakes and reservoirs based on a global matchup dataset from Landsat TM (N = 4099), ETM+ (N = 2420), and OLI (N = 1249) covering in situ SDD from 0.01 m to over 18 m. Overall, extreme gradient boosting (XGBoost) and random forest (RF) had better SDD retrievals than back propagation neural network, support vector regression, empirical and quasi-analytical models showing high precision with mean relative error of approximately 30% and good agreements with the long-term in situ SDD in different waters with various optical properties. Our results can support long-term global-level water quality evaluation and thus making informed decisions about development policy.

Abstract Background Patients with type 2 diabetes mellitus (T2DM) usually have higher blood viscosity attributed to high blood glucose that can decrease blood supply to the pancreas. A mild increase in blood pressure (BP) has been reported as a potential compensatory response that can maintain blood perfusion in the islet. However, how BP influences beta-cell function in T2DM subjects remains inconsistent. This study aimed to examine the relationship between BP and beta-cell function in patients with T2DM under different HbA1c levels. Methods This is a cross-sectional study of 615 T2DM patients, whose clinical data were extracted from hospital medical records. Beta-cell function was assessed by insulin secretion-sensitivity index-2 (ISSI2). Multivariable linear regression analysis and restricted cubic splines (RCS) analysis were performed to identify the association between systolic BP (SBP) and ISSI2. Mediation analysis was performed to determine whether higher SBP could reduce blood glucose by enhancing beta-cell function. Results After adjustment of potential confounders, in participants with HbA1c ≥ 10%, the SBP between 140 to150 mmHg had the highest log ISSI2 (b = 0.227, 95% CI 0.053–0.402), an association specific to participants with

ABSTRACT: Porphyromonas gingivalis (P. gingivalis, P. g) is the main pathogen of periodontal disease, which is treated with egg yolk immunoglobulin Y (IgY) against P. gingivalis. In order to quickly obtain IgY, 30 hens were immunized with inactivated P. gingivalis. The purification of IgY was carried out by the oleic acid (OA) method and the classical method (AS), respectively. The IgY antibody characteristics and antibacterial effects in HPDLF cells were detected by SDS-PAGE, indirect ELISA, Western blot and viability/toxicity assays. SDS-PAGE and Western blot analysis showed that IgY molecules which were rapidly purified by OA method were complete and specific to P. gingivalis. In addition, the results of crystal violet staining and bacterial staining indicated that IgY could agglutinate with P. gingivalis, inhibiting bacterial invasion of host cells. This study is the first to rapidly and efficiently purify IgY by OA method, and the purified IgY is expected to be used in the detection and treatment of P. gingivalis.