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Abstract TNF inhibitors have been used to treat autoimmune and autoinflammatory diseases. Here we report an unexpected mechanism underlying the therapeutic effects of TNF inhibitors in Behçet’s disease (BD), an autoimmune inflammatory disorder. Using serum metabolomics and peripheral immunocyte transcriptomics, we find that polymorphonuclear neutrophil (PMN) from patients with BD (BD-PMN) has dysregulated mevalonate pathway and subsequently increased farnesyl pyrophosphate (FPP) levels. Mechanistically, FPP induces TRPM2-calcium signaling for neutrophil extracellular trap (NET) and proinflammatory cytokine productions, leading to vascular endothelial inflammation and damage. TNF, but not IL-1β, IL-6, IL-18, or IFN-γ, upregulates TRPM2 expression on BD-PMN, while TNF inhibitors have opposite effects. Results from mice with PMN-specific FPP synthetase or TRPM2 deficiency show reduced experimental vasculitis. Meanwhile, analyses of public datasets correlate increased TRPM2 expressions with the clinical benefits of TNF inhibitors. Our results thus implicate FPP-TRPM2-TNF/NETs feedback loops for inflammation aggravation, and novel insights for TNF inhibitor therapies on BD.

Abstract Background This study aimed to explore the potential associations between trans fatty acid (TFA) and α-klotho levels. Methods Datasets from the 2009–2010 National Health and Nutrition Examination Survey (NHANES) were analysed for this study. Multivariable linear regression and restricted cubic spline (RCS) analyses were performed to examine the relationships between plasma TFA and serum α-klotho levels. Results A total of 1,205 participants were included, with a geometric mean (GM) of 803.60 (95% CI: 787.45, 820.00) pg/mL for serum α-klotho levels. RCS analysis revealed L-shaped relationships between TFA and α-klotho levels. The inflection points for palmitelaidic acid (PA), vaccinic acid (VA), elaidic acid (EA), and total TFA levels were 4.55, 20.50, 18.70, and 46.40 µmol/L, respectively. Before reaching the inflection point, serum α-klotho levels were negatively correlated with plasma PA, VA, EA and total TFA levels, with β values (95% CI) of -0.15 (-0.24, -0.06), -0.16 (-0.23, -0.09), -0.14 (-0.22, -0.05) and − 0.19 (-0.27, -0.11), respectively. Linolelaidic acid (LA) levels exhibited an inverse and linear association with α-klotho levels ( P nonlinearity=0.167, P overall

Abstract Developing superporous hemostatic sponges with simultaneously enhanced permeability and mechanical properties remains challenging but highly desirable to achieve rapid hemostasis for non-compressible hemorrhage. Typical approaches to improve the permeability of hemostatic sponges by increasing porosity sacrifice mechanical properties and yield limited pore interconnectivity, thereby undermining the hemostatic efficacy and subsequent tissue regeneration. Herein, we propose a temperature-assisted secondary network compaction strategy following the phase separation-induced primary compaction to fabricate the superporous chitosan sponge with highly-interconnected porous structure, enhanced blood absorption rate and capacity, and fatigue resistance. The superporous chitosan sponge exhibits rapid shape recovery after absorbing blood and maintains sufficient pressure on wounds to build a robust physical barrier to greatly improve hemostatic efficiency. Furthermore, the superporous chitosan sponge outperforms commercial gauze, gelatin sponges, and chitosan powder by enhancing hemostatic efficiency, cell infiltration, vascular regeneration, and in-situ tissue regeneration in non-compressible organ injury models, respectively. We believe the proposed secondary network compaction strategy provides a simple yet effective method to fabricate superporous hemostatic sponges for diverse clinical applications.

ObjectiveTo analyze the changing trends of the disease burden of viral hepatitis B (HB) and its risk factors among Chinese residents from 1990 to 2019, to provide a reference for HB prevention and control. MethodsData on the disease burden of HB and its risk factors among Chinese residents from 1990 to 2019 were collected from the Global Burden of Disease Study 2019 (GBD 2019). Descriptive statistics were performed using standardized incidence, prevalence, mortality, and disability-adjusted life years (DALYs) rate of HB. Joinpoint regression model was used to analyze the trends of disease burden of HB attributable to smoking, alcohol consumption, drug abuse, and high body mass index (BMI) among Chinese residents from 1990 to 2019. ResultsDuring the 30-year period among Chinese residents there were significant decreasing trends in the HB standardized rate (1/100 000) of incidence (2 725.98 to 1 397.31), prevalence (12 239. 53 to 6 566.12), mortality (24.67 to 8.07), and DALYs (793.38 to 247.71), with average annual percentage changes (AAPC) of – 2.29%, – 2.13%, – 3.82%, and – 3.98%, respectively (P < 0.001 for all), and although declining more rapidly in a global comparison, these standardized rates were still higher than those in the total world population. The values of APPC were significantly higher negatively in the female population than in the male population for HB standardized of incidence (– 2.49% vs. – 2.14%), prevalence (– 2.26% vs. – 2.04%), mortality (– 4.82% vs. – 3.48%), and DALYs (– 5.15% vs. – 3.63%) rates (all P < 0.001), indicating that there was still a higher disease burden of HB in the male Chinese population. During this period, the standardized mortality rate and DALYs rate of HB attributable to smoking, drinking alcohol, drug use, and high BMI showed a significant decreasing trend (both P < 0.01), with the AAPC of – 62.20%, – 62.01%, – 44.44%, and – 18.18% for the mortality rate and – 63.90%, – 63.54%, – 47.71%, and – 18.76% for the DALYs rate. ConclusionAlthough the disease burden of viral hepatitis B among Chinese residents has decreased from 1990 to 2019, it is still higher than that of the world population, and male residents who smoke, consume alcohol, take drugs and have high body mass index still need to pay more attention.

BackgroundResearch on the correlation between exposure to per- and polyfluoroalkylated substances (PFASs)/heavy metals and bone health during childhood and adolescence is limited. Considering their role as endocrine disruptors, we examined relationships of six PFASs and three heavy metals with bone mineral density (BMD) in children and adolescents using representative samples from the National Health and Nutrition Examination Survey (NHANES).MethodsThe study included 622 participants aged 12–19. The relationship between single pollutant and lumbar spine and total BMD was studied using linear regression analyses. Additionally, Bayesian Kernel Machine Regression (BKMR) models were applied to assess the joint effects of multiple PFASs and heavy metals exposure on the lumbar spine and total BMD.ResultsStatistically significant differences were noted in the serum concentrations of perfluorooctanoic acid (PFOA), perfluorooctane sulfonic acid (PFOS), perfluorohexane sulfonic acid (PFHxS), blood lead (Pb), and blood manganese (Mn) between male and female participants (all p

Hypertrophic scarring (HS) is a complication of wound healing that causes physiological and psychological distress in patients. However, the possible mechanism underlying HS is not fully understood, and there is no gold standard for its treatment. Natural products are more effective, economical, convenient, and safe than existing drugs, and they have a wide application prospect. However, there is a lack of literature on this topic, so we reviewed in vivo, in vitro, and clinical studies and screened natural products showing beneficial effects on HS that can become potential therapeutic agents for HS to fill in the gaps in the field. In addition, we discussed the drug delivery systems related to these natural products and their mechanisms in the treatment of HS. Generally speaking, natural products inhibit inflammation, myofibroblast activation, angiogenesis, and collagen accumulation by targeting interleukins, tumor necrosis factor-α, vascular endothelial growth factors, platelet-derived growth factors, and matrix metalloproteinases, so as to play an anti-HS effects of natural products are attributed to their anti-inflammatory, anti-proliferative, anti-angiogenesis, and pro-apoptotic (enhancing apoptosis and autophagy) roles, thus treating HS. We also screened the potential therapeutic targets of these natural compounds for HS through network pharmacology and constructed a protein-protein interaction (PPI) network, which may provide clues for the pharmacological mechanism of natural products in treating this disease and the development and application of drugs.

Abstract Background There have been studies on the relationship between hepatitis B virus (HBV) infection and diet. We hypothesized HBV infection is related to dietary calcium intake, but the evidence is limited. This study aimed to examine whether dietary calcium intake is independently related to HBV infection in the United States population. Methods A total of 20,488 participants aged over 20 years from the National Health and Nutrition Examination Survey (NHANES), conducted from 2007 to 2020, were included in this study. Pearson correlation was used to test the association between dietary calcium and serum calcium. The relationships of HBV infection with dietary calcium and serum calcium were assessed by logistic regression models. Results There was a weak correlation between dietary calcium and serum calcium (r = 0.048). Logistic regression models indicated that HBV infection had a linear negative correlation with dietary calcium (OR 0.37; 95%CI 0.19, 0.76). For each additional 10 mg dietary calcium, the possibility of HBV infection was reduced by 63%. Hepatitis B positive participants had lower serum calcium content than negative participants. Stratified analysis shown the linear relationship between calcium and HBV infection varied among sex, race/ethnicity, and body mass index. Conclusion Our findings demonstrated HBV infection was linearly and inversely correlated with dietary calcium. The current study is expected to offer a fresh perspective on reducing HBV infection.

It is imperative to develop and implement newer, more effective strategies to address refractory diabetic wounds. As of now, there is currently no optimal solution for these wounds. Hypoxic human umbilical vein endothelial cells (HUVECs)-derived exosomes have been postulated to promote diabetic wound healing, however, its effect and molecular mechanism need further study. In this study, we aimed to investigate whether hypoxic exosomes enhance wound healing in diabetics. Based on our high-throughput sequencing, differentially expressed lncRNAs (including 64 upregulated lncRNAs and 94 downregulated lncRNAs) were found in hypoxic exosomes compared to normoxic exosomes. Interestingly, lncHAR1B was one of the prominently upregulated lncRNAs in hypoxic exosomes, showing a notable correlation with diabetic wound healing. More specifically, hypoxic exosomes were transmitted to surrounding cells, which resulted in a significant increase in lncHAR1B level, thereby relieving the dysfunction of endothelial cells and promoting the switch from M1 to M2 macrophages under high glucose conditions. Mechanistically, lncHAR1B directly interacted with the transcription factor basic helix-loop-helix family member e23 (BHLHE23), which subsequently led to its binding to the KLF transcription factor 4 (KLF4) and promoted KLF4 expression. In our in vivo experiments, the use of hypoxic exosomes-loaded HGM-QCS hydrogels (Gel-H-Exos) resulted in rapid wound healing compared to that of normoxic exosomes-loaded HGM-QCS hydrogels (Gel-N-Exos) and diabetic groups. Consequently, our study provides potentially novel therapeutic approaches aimed at accelerating wound healing and developing a practical exosomes delivery platform.

The accurate prediction of vehicle behavior is crucial for autonomous driving systems, impacting their safety and efficiency in complex urban environments. To address the challenge of multi-agent trajectory prediction, we propose a novel model integrating multiple input modalities, including historical trajectories, map data, vehicle features, and interaction information. Our approach employs a Conditional Variational Autoencoder (CVAE) framework with a decoder that predicts control actions using the Gaussian Mixture Model (GMM) and then converts these actions into dynamically feasible trajectories through a bicycle model. Evaluated on the nuScenes dataset, the model achieves great performance across key metrics, including minADE5 of 1.26 and minFDE5 of 2.85, demonstrating robust performance across various vehicle types and prediction horizons. These results indicate that integrating multiple data sources, physical models, and probabilistic methods significantly improves trajectory prediction accuracy and reliability for autonomous driving. Our approach generates diverse yet realistic predictions, capturing the multimodal nature of future outcomes while adhering to Physical Constraints and vehicle dynamics.

Abstract This study proposes a method of constructing and transforming three-dimensional (3D) models that can convert a 3D model into a chain-type modular configuration and realize the mutual transformation between different configurations with a straight chain as the intermediate state through standard folding steps. A method for detailed representation of voxels is proposed. Based on detailed voxels, an accelerated generation algorithm for the connection forest, which can describe the possible chain configurations, is developed. The foldability verification of the configurations and the generation of the folding operations are realized according to the folding rules. A collision detection algorithm based on encoding and projection is also introduced to detect collisions in the process of folding sequence generation. In this work, an interactive platform is established for users to calculate the input model transformation through simple operations and obtain a simulation animation of the folding operations. The experimental cases prove the effectiveness of the method in constructing and transforming the chain-type modular configurations of the input 3D models.

Abstract A 3D transformable model can be transformed into different shapes through folding operations to suit different needs, such as a table or a chair in daily life. Furthermore, the features of foldable structure and flat components allow it to be folded into a smaller stack for compact storage when not in use. To this end, this study applies a new foldable modular chain structure and proposes a novel method of constructing 3D models into 3D shapes based on this structure and guiding the transformation between shapes. For the construction of the model, that is, to find a module chain path that constructs the model shape, the divide-and-conquer method is adopted. The model is first divided into multiple units, and then the search for the linearly connected module sub-path is executed for each unit. This involves three major steps: unit-based segmentation of the model, search for the unit tree structure that can form the target 3D shape, and search for the modular chain path based on the unit tree. The experimental cases demonstrate the application of the square modular chain in the fields of furniture and toys and prove the effectiveness of the method in constructing and transforming the foldable chain-type modular configurations of the input 3D models.

Highlights The flower-like δ-MnO2 nanostructures with controlled oxygen vacancies as an extraordinary ZIBs cathode are innovatively developed. The cathode can present large capacity and high-rate zinc-ion storage. DFT analysis substantially unveils the effects of various vacancy concentrations on their electrochemical performances.

Background: The determination of serum anti-pertussis toxin (PT) IgG antibodies is recommended for the diagnosis and surveillance of pertussis. However, the diagnostic power of anti-PT IgG can be hampered by possible interference from previous vaccinations. We aim to assess if anti-PT IgA antibodies can be well induced by Bordetella pertussis (B. pertussis) infections in children, and their capacity to improve pertussis serodiagnosis. Methods: Serum samples from 172 hospitalized children younger than 10 years old with confirmed pertussis were tested. Pertussis was confirmed by culture, PCR and/or serology. Anti-PT IgA antibodies were determined with commercial ELISA kits. Results: Sixty-four (37.2 %) subjects had anti-PT IgA antibodies greater than or equal to 15 IU/ml, and 52 (30.2 %) of them had anti-PT IgA antibodies greater than or equal to 20 IU/ml. No children with negative anti-PT IgG (less than 40 IU/ml) were observed to have anti-PT IgA antibodies greater than or equal to 15 IU/ml. Of patients younger than one year of age, about 50 % had an IgA antibody response. Moreover, the proportion of subjects with anti-PT IgA antibodies greater than or equal to 15 IU/ml among PCR negative subjects was significantly higher than that among PCR positive subjects (76.9 % vs 35.5 %). Conclusions: The determination of anti-PT IgA antibodies does not seem to have added value for the serodiagnosis of pertussis in children older than one year of age. However, for infants, determination of serum anti-PT IgA antibodies appears to be useful for the diagnosis of pertussis especially when PCR and culture are negative. The results should be interpreted with caution as the number of subjects included in this study was limited.

Objectives: This study aimed to estimate the life expectancy (LE) and health-adjusted life expectancy (HALE) of type 2 diabetes mellitus (T2DM) among the rural elderly population.Methods: A total of 10,318 participants aged 65 to 79 were derived from the Henan Rural Cohort. The LE and HALE were calculated via the Sullivan method and multistate life table.Results: Among 10,318 subjects, 1,325 suffered from T2DM at the baseline, and 394 participants had newly-developed T2DM. The results from the Sullivan method showed that the LE, HALE, and HALE/LE were 17.98, 16.18 years, and 89.95% for men aged 65 to 69, and the corresponding estimates for women were 21.81, 18.73 years, and 85.86%, respectively. The LE, HALE and HALE/LE calculated via multistate life table were 19.86, 17.53 years, and 88.29% for men at aged 65, and the corresponding values for women were 25.01, 20.87 years, and 83.44%, respectively.Conclusion: Rural elderly women have a longer LE and HALE of T2DM, but they have lower quality of life than men. More attention should be paid to T2DM among rural elderly people, especially in women.Clinical Trial Registration: The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). Date of registration: 06 July 2015. http://www.chictr.org.cn/showproj.aspx?proj=11375.

The perception systems of autonomous vehicles face significant challenges under adverse conditions, with issues such as obscured objects and false detections due to environmental noise. Traditional approaches, which typically focus on noise removal, often fall short in such scenarios. Addressing the lack of diverse adverse weather data in existing automotive datasets, we propose a novel data augmentation method that integrates realistically simulated adverse weather effects into clear condition datasets. This method not only addresses the scarcity of data but also effectively bridges domain gaps between different driving environments. Our approach centers on a conditional generative model that uses segmentation maps as a guiding mechanism to ensure the authentic generation of adverse effects, which greatly enhances the robustness of perception and object detection systems in autonomous vehicles, operating under varied and challenging conditions. Besides the capability of accurately and naturally recreating over 90% of the adverse effects, we demonstrate that this model significantly improves the performance and accuracy of deep learning algorithms for autonomous driving, particularly in adverse weather scenarios. In the experiments employing our augmented approach, we achieved a 2.46% raise in the 3D average precision, a marked enhancement in detection accuracy and system reliability, substantiating the model’s efficacy with quantifiable improvements in 3D object detection compared to models without augmentation. This work not only serves as an enhancement of autonomous vehicle perception systems under adverse conditions but also marked an advancement in deep learning models in adverse condition research.

Abstract Senescence of vascular smooth muscle cells (VSMCs) contributes to the formation of abdominal aortic aneurysm (AAA). Although mesenchymal stem cell exosomes (MSC-EXO) have been confirmed to restrict the development of AAA, their biological activity depends largely on the physiological state of the MSCs. This study aimed to compare the effects of adipose-derived MSC-EXO from healthy donors (HMEXO) and AAA patients (AMEXO) on senescence of VSMCs in AAA and explore the underlying mechanisms. An ApoE-/- mouse model of AAA was used to investigate the therapeutic effects of HMEXO, AMEXO or miR-19b-3p-AMEXO on AAA development. This in vitro model of AAA was established by treating VSMCs with Ang II (Angiotensin II). The senescence of VSMCs was determined by senescence-associated β-galactosidase (SA-β-gal) staining. The morphology of mitochondria in VSMCs was examined by MitoTracker staining. HMEXO exhibited superior capacity compared with AMEXO to inhibit VSMC senescence and attenuate AAA formation in Ang II–treated ApoE-/- mice. In vitro, both AMEXO and HMEXO inhibited Ang II-induced VSMC senescence via downregulation of mitochondrial fission. Notably, compared with HMEXO, the ability of AMEXO to inhibit VSMC senescence was significantly decreased. miRNA sequencing and the expression of miR-19b-3p was significantly decreased in AMEXO compared with HMEXO. Luciferase assay suggested that MST4 (Mammalian sterile-20-like kinase 4) is a potential target of miR-19b-3p. Mechanistically, miR-19b-3p in HMEXO ameliorated VSMC senescence by inhibiting mitochondrial fission via regulation of the MST4/ERK/Drp1 signaling pathway. Overexpression of miR-19b-3p in AMEXO improved their beneficial effect on AAA formation. Our study reveals that MSC-exosomal miR-19b-3p exerts protective effects against Ang II-induced AAA and VSMC senescence via regulation of the MST4/ERK/Drp1 pathway. The pathological state of AAA patients alters the miRNA components of AMEXO and impairs their therapeutic benefits.

Transformer-based models have gained popularity in the field of natural language processing (NLP) and are extensively utilized in computer vision tasks and multi-modal models such as GPT4. This paper presents a novel method to enhance the explainability of transformer-based image classification models. Our method aims to improve trust in classification results and empower users to gain a deeper understanding of the model for downstream tasks by providing visualizations of class-specific maps. We introduce two modules: the “Relationship Weighted Out” and the “Cut” modules. The “Relationship Weighted Out” module focuses on extracting class-specific information from intermediate layers, enabling us to highlight relevant features. Additionally, the “Cut” module performs fine-grained feature decomposition, taking into account factors such as position, texture, and color. By integrating these modules, we generate dense class-specific visual explainability maps. We validate our method with extensive qualitative and quantitative experiments on the ImageNet dataset. Furthermore, we conduct a large number of experiments on the LRN dataset, which is specifically designed for automatic driving danger alerts, to evaluate the explainability of our method in scenarios with complex backgrounds. The results demonstrate a significant improvement over previous methods. Moreover, we conduct ablation experiments to validate the effectiveness of each module. Through these experiments, we are able to confirm the respective contributions of each module, thus solidifying the overall effectiveness of our proposed approach.

To verify the effect of nutritional compensation on the preservation of broccoli, the filtered squeeze juice of broccoli stalks was used as stem extract, and by dipping at the base of the stem to simulated the nutrient supply of broccoli growth state. In the experiment, broccoli heads were respectively drenched by stem-extract-solution and distilled-water for 12 h as treatments, and natural placement was designed as control. During storage at 10 ℃ ethylene release, respiration rate, water content, weight loss rate, relative conductivity, and malondialdehyde, chlorophyll, vitamin C content, total soluble solids, titratable acid were studied. The results showed that, compared with the control treatment, the extract treatment could postpone the release of ethylene and the arrival of the respiratory peak, and reduce the respiratory intensity, the maximum values of ethylene release and respiratory intensity were respectively 60.29% and 77.22% of the control treatment, and maintain the water content of broccoli and delay weight loss. The water content of broccoli treated with the extract solution reached 83.64%, and the weight loss was only 7.01% at the end of storage, and the increasing of MDA content and electrical conductivity were delayed at 70.19% and 49.93% respectively. The extract treatment could maintain a high chlorophyll content, reached 7.01 mg/kg. VC content and TSS content maintained a high level, 60.99%, 20.82% higher than the control treatment, and the final TA content was 0.30%. In summary, the broccoli stem extract could have a good fresh-keeping effect on broccoli heads.

Since the introduction of electroporation a decade ago, the chick embryo has evolved into a powerful system for studying gene regulation and function during development. Although this is a straightforward method for embryos, skin (especially lamellar tissue) present special challenges. Here we describe a protocol for electroporation of expression vectors into the chick skin explant, with precise spatial and temporal control. We have improved the design of the electroporation chamber, which can achieve precise regulation of the electroporation area by changing the parameters of the laser cutting of the acrylic plate. We give the electroporation parameters of chicken embryo skin, which can effectively improve the electroporation efficiency. This technique can be used for time-lapse imaging and to study gene regulation in chick embryo skin.

Machine learning has shown great potential in bridging materials structures and properties. However, efficient and general descriptors for materials structures are still missing. This work dedicates to establishing an efficient and self-adaptable materials structure descriptor based on the graph attention network (GAT). In the GAT descriptor generation, the concrete structure is represented by graphic atomic clusters (atoms as nodes, edges as bonds) consisting of one central atom and the surroundings. A multi-head-GAT is applied to gather the short- and long-distance topological information from the graphical atomic clusters to generate dimension-flexible descriptors regardless of atom number; the GAT descriptors are contracted and help avoiding overfitting during the training process theoretically. Further verification of the GAT descriptors is carried out by performing the phase classification, energy prediction, and potential energy surface (PES) prediction task for Al-Cu alloys with complex precipitates and defects. The GAT descriptors adapt themselves for cross tasks without manual intervention and produce accurate predictions that agree with the density functional theory (DFT) results. The GAT descriptors are also testified as differentiable, universal, and precise on structural characterization containing point-, line-, and planar- defects. Further applications will be found for the materials design field demanding accurate structure descriptions.

LiDAR point clouds are significantly impacted by snow in driving scenarios, introducing scattered noise points and phantom objects, thereby compromising the perception capabilities of autonomous driving systems. Current effective methods for removing snow from point clouds largely rely on outlier filters, which mechanically eliminate isolated points. This research proposes a novel translation model for LiDAR point clouds, the ‘L-DIG’ (LiDAR depth images GAN), built upon refined generative adversarial networks (GANs). This model not only has the capacity to reduce snow noise from point clouds, but it also can artificially synthesize snow points onto clear data. The model is trained using depth image representations of point clouds derived from unpaired datasets, complemented by customized loss functions for depth images to ensure scale and structure consistencies. To amplify the efficacy of snow capture, particularly in the region surrounding the ego vehicle, we have developed a pixel-attention discriminator that operates without downsampling convolutional layers. Concurrently, the other discriminator equipped with two-step downsampling convolutional layers has been engineered to effectively handle snow clusters. This dual-discriminator approach ensures robust and comprehensive performance in tackling diverse snow conditions. The proposed model displays a superior ability to capture snow and object features within LiDAR point clouds. A 3D clustering algorithm is employed to adaptively evaluate different levels of snow conditions, including scattered snowfall and snow swirls. Experimental findings demonstrate an evident de-snowing effect, and the ability to synthesize snow effects.

In the field of intelligent vehicle technology, there is a high dependence on images captured under challenging conditions to develop robust perception algorithms. However, acquiring these images can be both time-consuming and dangerous. To address this issue, unpaired image-to-image translation models offer a solution by synthesizing samples of the desired domain, thus eliminating the reliance on ground truth supervision. However, the current methods predominantly focus on single projections rather than multiple solutions, not to mention controlling the direction of generation, which creates a scope for enhancement. In this study, we propose a generative adversarial network (GAN)–based model, which incorporates both a style encoder and a content encoder, specifically designed to extract relevant information from an image. Further, we employ a decoder to reconstruct an image using these encoded features, while ensuring that the generated output remains within a permissible range by applying a self-regression module to constrain the style latent space. By modifying the hyperparameters, we can generate controllable outputs with specific style codes. We evaluate the performance of our model by generating snow scenes on the Cityscapes and the EuroCity Persons datasets. The results reveal the effectiveness of our proposed methodology, thereby reinforcing the benefits of our approach in the ongoing evolution of intelligent vehicle technology.

Abstract Background Application of mesenchymal stem cell-derived exosomes (MSC-EXO) has emerged as a novel therapeutic strategy for myocardial infarction (MI). Our previous study showed that pretreatment with hemin, a potent heme oxygenase-1 (HO-1) inducer, enhanced the cardioprotective effects of MSCs in a mouse model of MI. This study aimed to investigate the therapeutic effects of EXO derived from hemin-pretreated MSCs (Hemin-MSC-EXO) in MI and explore the potential mechanisms. Methods MSC-EXO and Hemin-MSC-EXO were collected and characterized. MSC-EXO and Hemin-MSC-EXO were intramuscularly injected into the peri-infarct region in a mouse model of MI. Heart function of mice was assessed by echocardiography. The mitochondrial morphology of neonatal mice cardiomyocytes (NMCMs) under serum deprivation and hypoxic (SD/H) conditions was examined by Mitotracker staining. The cellular senescence of NMCMs was determined by senescence-associated-β-galactosidase assay. A loss-of-function approach was adopted to determine the role of Hemin-MSC-exosomal-miR-183-5p in the regulation of cardiomyocyte senescence Results EXO were successfully isolated from the supernatant of MSCs and Hemin-pretreated MSCs. Compared with MSC-EXO, injection of Hemin-MSC-EXO significantly improved cardiac function and reduced fibrosis. Both MSC-EXO and Hemin-MSC-EXO ameliorated cardiomyocyte senescence and mitochondrial fission in vitro and in vivo, and the latter exhibited better protective effects. MicroRNA sequencing revealed a higher level of miR-183-5p in Hemin-MSC-EXO than in MSC-EXO. MiR-183-5p knockdown partially abrogated the protective effects of Hemin-MSC-EXO in attenuating mitochondrial fission and cellular senescence of cardiomyocytes induced by SD/H. High mobility group box-1 (HMGB1) abundance was lower in Hemin-MSC-EXO-treated than MSC-EXO-treated mouse hearts, and HMGB1 was identified as one of the potential target genes of miR-183-5p. Mechanistically, Hemin-MSC-EXO inhibited SD/H-induced cardiomyocyte senescence partially by delivering miR-183-5p into recipient cardiomyocytes via regulation of the HMGB1/ERK pathway. Furthermore, knockdown of miR-183-5p reduced the Hemin-MSC-EXO-mediated cardioprotective effects in a mouse model of MI. Conclusion Our results reveal that Hemin-MSC-EXO are superior to MSC-EXO in treating MI. Exosomal miR-183-5p mediates, at least partially, the cardioprotective effects of Hemin-MSC-EXO by inhibiting cardiomyocyte senescence via regulation of the HMGB1/ERK pathway. This study highlights that MSC-EXO have high translational value in repairing cardiac dysfunction following infarction. Graphic abstract

To extend the application of the swashplate engine from special engines to the field of general power machinery， it is necessary to considerate speed stability， dynamic balance performance and manufacturing， etc. A new swashplate engine is designed， it used the nutation movement of a pair of spiral bevel gears to drive the body of the swashplate engine to rotate， so that there is a relative angular displacement between the cylinder cover and the cylinder， and then the differential speed distribution is realized. This scheme not only eliminates the planetary gear system and reduces the kinetic energy loss， but also uses arc bevel gear instead of traditional straight bevel gear to reduce vibration and noise， and the distribution system layout is optimized. A three-dimensional model built with SolidWorks is simulated and comparative analyzed by the Adams platform. The results show that the presented structure scheme has a better stable performance of rotating speed and can effectively control vibration than the conventional straight bevel gear mechanism.

Mixed Enterobacter sp. Z1 and Klebsiella sp. Z2 displayed an outstanding ammonia removal capacity than using a single strain. Metabolomics, proteomics, and RNA interference analysis demonstrated that the HNAD process was closely related to indole-acetic acid (IAA). Under the cocultured conditions, the excess IAA produced by Z2 could be absorbed by Z1 to compensate for the deficiency of IAA in the cells. IAA directly induced the expression of denitrifying enzymes and further activated the IAA metabolism level, thus greatly improving the nitrogen removal ability of Z1. In turn, nitrate and nitrite induced the expression of key enzymes in the IAA pathways. Moreover, Z1 and Z2 enhanced two IAA metabolic pathways in the process of mixed removal process. The activated hydrolysis-redox pathway in Z1 reduced the oxidative stress level, and the activated decarboxylation pathway in Z2 promoted intracellular energy metabolism, which indirectly promoted the process of HNAD in the system.

7-dehydrocholesterol (7-DHC) and cholesterol (CHOL) are biomarkers of Smith-Lemli-Opitz Syndrome (SLOS), a congenital autosomal recessive disorder characterized by elevated 7-DHC level in patients. Hair samples have been shown to have great diagnostic and research value, which has long been neglected in the SLOS field. In this study, we sought to investigate the feasibility of using hair for SLOS diagnosis. In the presence of antioxidants (2,6-ditert-butyl-4-methylphenol and triphenylphosphine), hair samples were completely pulverized and extracted by micro-pulverized extraction in alkaline solution or in n-hexane. After microwave-assisted derivatization with N,O-Bis(trimethylsilyl)trifluoroacetamide, the analytes were measured by GC-MS. We found that the limits of determination for 7-DHC and CHOL were 10 ng/mg and 8 ng/mg, respectively. In addition, good linearity was obtained in the range of 50–4000 ng/mg and 30–6000 ng/mg for 7-DHC and CHOL, respectively, which fully meets the requirement for SLOS diagnosis and related research. Finally, by applying the proposed method to real hair samples collected from 14 healthy infants and two suspected SLOS patients, we confirmed the feasibility of hair analysis as a diagnostic tool for SLOS. In conclusion, we present an optimized and validated analytical method for the simultaneous determination of two SLOS biomarkers using human hair.

Contextualized in the prolonged period of COVID-19-related school suspension in Hong Kong, the present study unravels relationships among socioeconomic status (SES), parental involvement, and learning outcomes for a matched sample of 186 primary and 932 secondary school students and their parents who participated in the eCitizen Education 360 survey. Three-step latent profile analysis (LPA) revealed different types of parental involvement at home and in school. For the primary school sample, students’ SES did not predict membership in the parental involvement typology, but students whose parents provided more home monitoring and support had the highest level of online self-efficacy. As for the secondary student sample, students whose parents provided more home monitoring and support tended to have access to more home learning resources. Students whose parents provided home monitoring and support had the highest levels of online self-efficacy, acquisition of digital skills, and cognitive-emotional regulation, and were the least worried about school resumption. The study underscores complex patterns of parental involvement and identifies effective parental involvement practices that contribute to students’ home online learning during the school suspension.

Abstract Background Decreased heart rate variability (HRV) is a predictor of autonomic system dysfunction, and is considered as a potential mechanism of increased risk of cardiovascular disease (CVD) induced by exposure to particulate matter less than 2.5 μm in diameter (PM2.5). Previous studies have suggested that exposure to PM2.5 may lead to decreased HRV levels, but the results remain inconsistent. Methods An updated systematic review and meta-analysis of panel studies till November 1, 2019 was conducted to evaluate the acute effect of exposure to ambient PM2.5 on HRV. We searched electronic databases (PubMed, Web of Science, and Embase) to identify panel studies reporting the associations between exposure to PM2.5 and the four indicators of HRV (standard deviation of all normal-to-normal intervals (SDNN), root mean square of successive differences in adjacent normal-to-normal intervals (rMSSD), high frequency power (HF), and low frequency power (LF)). Random-effects model was used to calculate the pooled effect estimates. Results A total of 33 panel studies were included in our meta-analysis, with 16 studies conducted in North America, 12 studies in Asia, and 5 studies in Europe. The pooled results showed a 10 μg/m3 increase in PM2.5 exposure which was significantly associated with a − 0.92% change in SDNN (95% confidence intervals (95%CI) − 1.26%, − 0.59%), − 1.47% change in rMSSD (95%CI − 2.17%, − 0.77%), − 2.17% change in HF (95%CI − 3.24%, − 1.10%), and − 1.52% change in LF (95%CI − 2.50%, − 0.54%), respectively. Overall, subgroup analysis suggested that short-term exposure to PM2.5 was associated with lower HRV levels in Asians, healthy population, and those aged ≥ 40 years. Conclusion Short-term exposure to PM2.5 was associated with decreased HRV levels. Future studies are warranted to clarity the exact mechanism of exposure to PM2.5 on the cardiovascular system through disturbance of autonomic nervous function.

Bladder Urothelial Carcinoma (BLCA) is the major subtype of bladder cancer, and the prognosis prediction of BLCA is difficult. Ferroptosis is a newly discovered iron-dependent cell death pathway. However, the clinical value of ferroptosis-related genes (FRGs) on the prediction of BLCA prognosis is still uncertain. In this study, we aimed to construct a novel prognostic signature to improve the prognosis prediction of advanced BLCA based on FRGs. In the TCGA cohort, we identified 23 differentially expressed genes (DEGs) associated with overall survival (OS) via univariate Cox analysis (all P < 0.05). 8 optimal DEGs were finally screened to generate the prognostic risk signature through LASSO regression analysis. Patients were divided into two risk groups based on the median risk score. Survival analyses revealed that the OS rate in the high-risk group was significantly lower than that in the low-risk group. Moreover, the risk score was determined as an independent predictor of OS by the multivariate Cox regression analysis (Hazard ratio > 1, 95% CI = 1.724-2.943, P < 0.05). Many potential ferroptosis-related pathways were identified in the enrichment analysis in BLCA. With the aid of an external FAHWMU cohort (n = 180), the clinical predication value of the signature was further verified. In conclusion, the prognosis of advanced BLCA could be accurately predicted by this novel FRG-signature.

Purpose: Coronary artery disease (CAD) and atrial fibrillation (AF) often coexist and lead to a much higher risk of mortality in the elderly population. The aim of this study was to investigate whether the CHA2DS2-VASc score could predict the risk of death in elderly patients with CAD and AF.Methods: Hospitalized patients aged ≥65 years with a diagnosis of CAD and AF were recruited consecutively. Patients were divided into 5 groups according to the CHA2DS2-VASc score (≤2, =3, =4, =5, and ≥6). At least a 1-year follow-up was carried out for the assessment of all-cause death.Results: A total of 1,579 eligible patients were recruited, with 582 all-cause deaths (6.86 per 100 patient-years) occurring during a follow-up of at least 1 year. With the increase in the CHA2DS2-VASc score, the 1-year and 5-year survival rate decreased (96.4% vs. 95.7% vs. 94.0% vs. 86.5% vs. 85.7%, respectively, P < 0.001; 78.4% vs. 68.9% vs. 64.6% vs. 55.5% vs. 50.0%, respectively, P < 0.001). Compared with the patients with CHA2DS2-VASc score

Weather variation in the distribution of image data can cause a decline in the performance of existing visual algorithms during evaluation. Adding additional samples of target domain to training data or using pre-trained image restoration methods such as de-hazing, de-raining, and de-snowing, to improve the quality of input images are two promising solutions. In this work, we propose Multiple Weather Translation GAN (MWTG), a CycleGAN-based, dual-purpose framework that simultaneously learns weather generation and its removal from image data. MWTG consists of four GANs constrained using cycle consistency that carry out domain translation tasks between hazy, rainy, snowy, and clear weather, using an asymmetric approach. To increase network capacity, we employ a spatial feature transform (SFT) layer to fuse the features extracted from the weather layer, which contains high-level domain information from the previous generators. Further, we collect an unpaired, real-world driving dataset recorded under various weather conditions called Realistic Driving Scenes under Bad Weather (RDSBW). We qualitatively and quantitatively evaluate MWTG using the RDSBW and the variation of Cityscapes that synthesize weather effects, eg., FoggyCityscape. Our experimental results suggest that MWTG can generate realistic weather in clear images and also accurately remove noise from weather images. Furthermore, the SOTA pedestrian detector ASCP is shown to achieve an impressive gain in detection precision after image restoration using the proposed MWTG method.

This study aimed to explore the effects of nucleate agent sizes on lysozyme crystallization. Silica nanoparticles (SNP) with four different particle sizes of 5 nm, 15 nm, 50 nm, and 100 nm were chosen for investigation. Studies were carried out both microscopically and macroscopically. After adding SNP, the morphological defects of lysozyme crystals decreased, and the number of crystals increases with the size of the SNP. The interaction between SNP and lysozyme was further explored using UV spectroscopy, fluorescence spectroscopy, and Zeta potential. It was found that the interaction between SNP and lysozyme was mainly electrostatic interaction, which increased with the size of SNP. As a result, lysozyme could be attracted to the surface of SNP and aggregated to form the nucleus. Finally, the activity test and circular dichroism showed that SNP had little effect on protein secondary structure.

Abstract Background The mitochondrial genotype 5178 cytosine/adenine (5178 C > A) within the NADH dehydrogenase subunit-2 gene (ND2) was proved to associate with longevity and predispose resistance to adult-onset diseases. This study aimed to confirm the interactive effects between ND 25178 C > A and clinical risk factors on the susceptibility of essential hypertension in Chinese general population. Materials and Methods The relationship between the ND2 5178 C > A variation and the risk of hypertension was investigated in 817 hypertensives and 821 matched normotensives. The interactive effects between ND2 5178 C > A and clinical risk factors were evaluated. Results The ND2 5178 A allele was more frequent in normotensives than in hypertensives (32.64% vs. 24.24%; adjusted OR: 0.62, 95% CI: 0.49–0.79, P = 1.3 × 10− 4). After stratification, the significant association between ND2 5178 C > A and hypertension was found only in current smokers (OR: 0.44, 95% CI: 0.31–0.62), but not in non-current smokers (p

Background: Graf’s method is currently the most commonly used ultrasound-based technique for the diagnosis of developmental dysplasia of the hip (DDH). However, the efficiency and accuracy of diagnosis are highly affected by the sonographers’ qualification and the time and effort expended, which has a significant intra- and inter-observer variability. Methods: Aiming to minimize the manual intervention in the diagnosis process, we developed a deep learning-based computer-aided framework for the DDH diagnosis, which can perform fully automated standard plane detection and angle measurement for Graf type I and type II hips. The proposed framework is composed of three modules: an anatomical structure detection module, a standard plane scoring module, and an angle measurement module. This framework can be applied to two common clinical scenarios. The first is the static mode, measurement and classification are performed directly based on the given standard plane. The second is the dynamic mode, where a standard plane from ultrasound video is first determined, and measurement and classification are then completed. To the best of our knowledge, our proposed framework is the first CAD method that can automatically perform the entire measurement process of Graf’s method. Results: In our experiments, 1051 US images and 289 US videos of Graf type I and type II hips were used to evaluate the performance of the proposed framework. In static mode, the mean absolute error of α, β angles are 1.71° and 2.40°, and the classification accuracy is 94.71%. In dynamic mode, the mean absolute error of α, β angles are 1.97° and 2.53°, the classification accuracy is 89.51%, and the running speed is 31 fps. Conclusions: Experimental results demonstrate that our fully automated framework can accurately perform standard plane detection and angle measurement of an infant’s hip at a fast speed, showing great potential for clinical application.

The number of reported pertussis cases has significantly decreased during the coronavirus disease 2019 (COVID-19) pandemic under the influence of strict public health measures in many countries including China. This study evaluated the prevalence of serum anti-pertussis toxin (anti-PT) IgG antibodies in adults at childbearing age pre- and post- COVID-19 in Beijing, China. Altogether, 2021 serum samples collected from individuals aged 20 to 39 years who attended an annual health examination at the Sixth Medical Center of PLA General Hospital, Beijing, in 2018~2020 were measured by ELISA. The median concentration of anti-PT IgG antibodies among participants in 2020 (2.96 IU/mL) was significantly lower than that in 2018 (3.27 IU/mL) (p = 0.011) and in 2019 (3.24 IU/mL) (p = 0.014). The percentage of participants with anti-PT IgG antibodies higher than 40 IU/mL (indicating a pertussis infection within the past few years) was 1.79% (9/503) in 2018, 2.04% (15/735) in 2019 and 1.66% (13/783) in 2020, respectively. The corresponding numbers of the non-detectable (

Genome-wide association studies have identified many susceptibility genes for adolescent idiopathic scoliosis (AIS). However, most of the results are hard to be replicated in multi-ethnic populations. LBX1 is the most promising candidate gene in the etiology of AIS. We aimed to appraise the literature for the association of LBX1 gene polymorphisms with susceptibility and curve progression in AIS. We also reviewed the function of the LBX1 gene in muscle progenitor cell migration and neuronal determination processes. Three susceptibility loci (rs11190870, rs625039, and rs11598564) near the LBX1 gene, as well as another susceptibility locus (rs678741), related to LBX1 regulation, have been successfully verified to have robust associations with AIS in multi-ethnic populations. The LBX1 gene plays an essential role in regulating the migration and proliferation of muscle precursor cells, and it is known to play a role in neuronal determination processes, especially for the fate of somatosensory relay neurons. The LBX1 gene is the most promising candidate gene in AIS susceptibility due to its position and possible functions in muscle progenitor cell migration and neuronal determination processes. The causality between susceptibility loci related to the LBX1 gene and the pathogenesis of AIS deserves to be explored with further integrated genome-wide and epigenome-wide association studies.

Antimony (Sb)-resistant bacteria have potential applications in the remediation of Sb-contaminated sites. However, the effect of Sb(III) exposure on whole-cell metabolic change has not been studied. Herein, we combined untargeted metabolomics with a previous proteomics dataset and confirmatory gene transcription analysis to identify metabolic responses to Sb(III) exposure in Agrobacterium tumefaciens GW4. Dynamic changes in metabolism between control and Sb(III)-exposed groups were clearly shown. KEGG pathway analysis suggested that with Sb(III) exposure: (1) the branching pathway of gluconeogenesis is down-regulated, resulting in the up-regulation of pentose phosphate pathway to provide precursors of anabolism and NADPH; (2) glycerophospholipid and arachidonic acid metabolisms are down-regulated, resulting in more acetyl-CoA entry into the TCA cycle and increased capacity to produce energy and macromolecular synthesis; (3) nucleotide and fatty acid synthesis pathways are all increased perhaps to protect cells from DNA and lipid peroxidation; (4) nicotinate metabolism increases which likely leads to increased production of co-enzymes (e.g., NAD+ and NADP+) for the maintenance of cellular redox and Sb(III) oxidation. Expectedly, the total NADP+/NADPH content, total glutathione, and reduced glutathione contents were all increased after Sb(III) exposure in strain GW4, which contribute to maintaining the reduced state of the cytoplasm. Our results provide novel information regarding global bacterial responses to Sb(III) exposure from a single gene level to the entire metabolome and provide specific hypotheses regarding the metabolic change to be addressed in future research.

Background. This study aimed to analyse the role of the HAS-BLED score with the addition of genotype bins for bleeding risk prediction in warfarin-treated patients with atrial fibrillation (AF). Methods and Results. Consecutive patients with AF on initial warfarin treatment were recruited. For each patient, CYP2C9∗3 and VKORC1-1639 A/G genotyping was performed to create 3 genotype functional bins. The predictive values of the HAS-BLED score with or without the addition of genotype bins were compared. According to the carrier status of the genotype bins, the numbers of normal, sensitive, and highly sensitive responders among 526 patients were 64 (12.17%), 422 (80.23%), and 40 (7.60%), respectively. A highly sensitive response was independently associated with clinically relevant bleeding (HR: 3.85, 95% CI: 1.88–7.91, P=0.001) and major bleeding (HR:3.75, 95% CI: 1.17–11.97, P=0.03). With the addition of genotype bins, the performance of the HAS-BLED score for bleeding risk prediction was significantly improved (c-statistic from 0.60 to 0.64 for clinically relevant bleeding and from 0.64 to 0.70 for major bleeding, P

Leukemia is one of the most common cancers. We conducted this study to comprehensively analyze the temporal trends of leukemia mortality during 2003–2017 and project the trends until 2030. We extracted national-level data on annual leukemia mortality from China Health Statistics Yearbooks (2003–2017). We applied the Joinpoint regression model to assess leukemia mortality trends in urban and rural China by sex during 2003–2017. We also produced sex-specific leukemia mortality using the adjusted Global Burden Disease (GBD) 2016 projection model. In urban areas, age-standardized leukemia mortality decreased significantly among females during 2003–2017 (APC = −0.9%; 95% CI: −1.7, −0.1%). In rural areas, significant decreases of age-standardized leukemia mortality were both found among males (APC = −1.7%; 95% CI: −2.9, −0.5%) and females (APC = −1.6%; 95% CI: −2.6, −0.7%) from 2008 to 2017. Rural-urban and sex disparities of leukemia mortality will continue to exist until the year 2030. According to projection, the leukemia mortality rates of males and rural populations are higher than that of females and urban populations. In 2030, leukemia mortality is projected to decrease to 3.03/100,000 and 3.33/100,000 among the males in urban and rural areas, respectively. In females, leukemia mortality will decrease to 1.87/100,000 and 2.26/100,000 among urban and rural areas, respectively. Our study suggests that more precautionary measures to reduce leukemia mortality are need, and more attention should be paid to rural residents and males in primary prevention of leukemia in China.

By adding Buck-type AC/AC converter to conventional power capacitor, dynamic capacitor (D-CAP) can be formed to compensate variable rather than fixed reactive power. However, some nonlinear distortion factors, namely grid harmonic voltage, voltage drop of switches and dead-time, would cause harmonics in its compensation current, meanwhile, its capacitance may interact with the grid inductance to cause series resonance. Both nonlinear distortion factors and series resonance would distort the waveform of its compensation current and make the grid current failed to meet the power quality standard IEEE Std.519. This paper focuses on the output current distortion of Buck-type D-CAP in reactive power compensation. For harmonic distortion, through establishing the equivalent circuit of Buck-type D-CAP, the generation of low-order harmonic current is investigated under three nonlinear factors. A current reshaping method to simultaneously diminish the harmonics caused by the three nonlinear distortion factors is thus adopted, which is a feedback control of output current harmonics. Then for series resonance, based on the block diagram of Buck-type D-CAP within the grid, transfer function from grid voltage to the output current is deduced and the corresponding Bode diagram is depicted. An active damping method is therefore suggested to shrink the low-order series resonance peak, by detecting power capacitor's voltage for feedback control. Finally, a combined control, reactive current reshaping with series resonance damping is proposed in this paper for three-phase Buck-type D-CAP. A wide variety of experimental results from a 33kVar/220V laboratory prototype are provided to demonstrate the validity of the combined control.

Identification of the priority area is of great significance for the rational layout of river protected areas (RPAs), and it also poses new challenges for protected areas’ (PAs) construction. This study started with the characteristics of RPAs and chose China’s Sichuan Province as the case for the present study, based on its characteristics of biodiversity conservation value and other characteristic elements. The study selected the river dendritic connectivity index and the other four indicators adding them according to different weights to calculate the comprehensive protected value (CPV) area. Finally, the existing PA distributions within the CPV were compared, and the priority conservation area was identified. The main conclusions are as follows: the total area of high-value areas is about 175,068 km2, accounting for 36.02% of the province and concentrated in the high mountain plateaus of the northwest and the southwest mountain region; the existing PAs are 131,687 km2 in sized, covering only 25.08% of the high-value areas of CPV. In other words, 74.92% of the high-value areas still have not been effectively protected, and the construction of RPAs is relatively lagging in these areas; the total area of priority conservation areas (PCAs) is 131,162 km2, accounting for about 26.99% of the province. The total length of the reach in the PCAs is about 9190.72 km, which is approximately 26.84% of the length of the province’s alternative reaches. The research can provide a scientific basis for the optimization and integration of nature protected areas and land space planning.

Abstract Enterovirus A71 (EV-A71) is a major etiological agent of human hand, foot and mouth disease, and it can cause severe neurological complications. Although several genotypes of EV-A71 strains are prevalent in different regions of the world, the genotype C4 has circulated in mainland China for more than 20 years. The pathogenicity of different EV-A71 clinical isolates varies and needs to be explored. In this study, hSCARB2 knock-in mice (N = 181) with a wide range of ages were tested for their susceptibility to two EV-A71 strains with the subgenotypes C4 and C2, and two infection routes (intracranial and venous) were compared. The clinical manifestations and pathology and their relationship to the measured viral loads in different tissues were monitored. We observed that 3 weeks is a crucial age, as mice younger than 3-week-old that were infected became extremely ill. However, mice older than 3 weeks displayed diverse clinical symptoms. Significant differences were observed in the pathogenicity of the two strains with respect to clinical signs, disease incidence, survival rate, and body weight change. We concluded that hSCARB2 knock-in mice are a sensitive model for investigating the clinical outcomes resulting from infection by different EV-A71 strains. The intracranial infection model appears to be suitable for evaluating EV-A71 neurovirulence, whereas the venous infection model is appropriate for studying the pathogenicity of EV-A71.

Aiming at few-shot classification in the field of hyperspectral remote sensing images, this paper proposes a classification method based on cross-scene adaptive learning. First, based on the unsupervised domain adaptive technology, cross-scene knowledge transfer learning is carried out to reduce the differences between source scene and target scene. At the same time, depthwise over-parameterized convolution is used in the deep embedding model to improve the convergence speed and feature extraction ability. Second, two symmetrical subnetworks are designed in the model to further reduce the differences between source scene and target scene. Then, Manhattan distance is learned in the Manhattan metric space in order to reduce the computational cost of the model. Finally, the weighted K-nearest neighbor is introduced for classification, in which the weighted Manhattan metric distance is assigned to the clustered samples to improve the processing ability to the imbalanced hyperspectral image data. The effectiveness of the proposed algorithm is verified on the Pavia and Indiana hyperspectral dataset. The overall classification accuracy is 90.90% and 65.01%. Compared with six other kinds of hyperspectral image classification methods, the proposed cross-scene method has better classification accuracy.

Although hyperspectral data provide rich feature information and are widely used in other fields, the data are still scarce. Training small sample data classification is still a major challenge for HSI classification based on deep learning. Recently, the method of mining sample relationships has been proved to be an effective method for training small samples. However, this strategy requires high computational power, which will increase the difficulty of network model training. This paper proposes a modified depthwise separable relational network to deeply capture the similarity between samples. In addition, in order to effectively mine the similarity between samples, the feature vectors of support samples and query samples are symmetrically spliced. According to the metric distance between symmetrical structures, the dependence of the model on samples can be effectively reduced. Firstly, in order to improve the training efficiency of the model, depthwise separable convolution is introduced to reduce the computational cost of the model. Secondly, the Leaky-ReLU function effectively activates all neurons in each layer of neural network to improve the training efficiency of the model. Finally, the cosine annealing learning rate adjustment strategy is introduced to avoid the model falling into the local optimal solution and enhance the robustness of the model. The experimental results on two widely used hyperspectral remote sensing image data sets (Pavia University and Kennedy Space Center) show that compared with seven other advanced classification methods, the proposed method achieves better classification accuracy under the condition of limited training samples.

To understand the anomalous electronic transport properties of ZrTe5 remains an elusive puzzle. Here, Zhang et al. report direct electronic evidence to the origin of the resistivity anomaly and temperature induced Lifshitz transition in ZrTe5, indicating it being a weak topological insulator.

Gut microbiome plays an essential role in modulating host immune responses. However, little is known about the interaction of microbiota, their metabolites and relevant inflammatory responses in the gut. By treating the mice with three different antibiotics (enrofloxacin, vancomycin, and polymixin B sulfate), we aimed to investigate the effects of different antibiotics exposure on gut microbiota, microbial metabolism, inflammation responses in the gut, and most importantly, pinpoint the underlying interactions between them. Although the administration of different antibiotics can lead to different effects on mouse models, the treatment did not affect the average body weight of the mice. A heavier caecum was observed in vancomycin treated mice. Treatment by these three antibiotics significantly up-regulated gene expression of various cytokines in the colon. Enrofloxacin treated mice seemed to have an increased Th1 response in the colon. However, such a difference was not found in mice treated by vancomycin or polymixin B sulfate. Vancomycin treatment induced significant changes in bacterial composition at phylum and family level and decreased richness and diversity at species level. Enrofloxacin treatment only induced changes in composition at family presenting as an increase in Prevotellaceae and Rikenellaceae and a decrease in Bacteroidaceae. However, no significant difference was observed after polymixin B sulfate treatment. When compared with the control group, significant metabolic shift was found in the enrofloxacin and vancomycin treated group. The metabolic changes mainly occurred in Valine, leucine, and isoleucine biosynthesis pathway and beta-Alanine metabolism in enrofloxacin treated group. For vancomycin treatment metabolic changes were mainly found in beta-Alanine metabolism and Alanine, aspartate and glutamate metabolism pathway. Moreover, modifications observed in the microbiota compositions were correlated with the metabolite concentrations. For example, concentration of pentadecanoic acid was positively correlated with richness of Rikenellaceae and Prevotellaceae and negatively correlated with Enterobacteriaceae. This study suggests that the antibiotic-induced changes in gut microbiota might contribute to the inflammation responses through the alternation of metabolic status, providing a novel insight regarding a complex network that integrates the different interactions between gut microbiota, metabolic functions, and immune responses in host.

Antimony (Sb) pollution is a worldwide problem. In some anoxic sites, such as Sb mine drainage and groundwater sediment, the Sb concentration is extremely elevated. Therefore, effective Sb remediation strategies are urgently needed. In contrast to microbial aerobic antimonite [Sb(III)] oxidation, the mechanism of microbial anaerobic Sb(III) oxidation and the effects of nitrate and Fe(II) on the fate of Sb remain unknown. In this study, we discovered the mechanism of anaerobic Sb(III) oxidation coupled with Fe(II) oxidation and denitrification in the facultative anaerobic Sb(III) oxidizer Sinorhizobium sp. GW3. We observed the following: (1) under anoxic conditions with nitrate as the electron acceptor, strain GW3 was able to oxidize both Fe(II) and Sb(III) during cultivation; (2) in the presence of Fe(II), nitrate and Sb(III), the anaerobic Sb(III) oxidation rate was remarkably enhanced, and Fe(III)-containing minerals were produced during Fe(II) and Sb(III) oxidation; (3) qRT-PCR, gene knock-out and complementation analyses indicated that the arsenite oxidase gene product AioA plays an important role in anaerobic Sb(III) oxidation, in contrast to aerobic Sb(III) oxidation; and (4) energy-dispersive X-ray spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS) and powder X-ray diffraction (XRD) analyses revealed that the microbially produced Fe(III) minerals were an effective chemical oxidant responsible for abiotic anaerobic Sb(III) oxidation, and the generated Sb(V) was adsorbed or coprecipitated on the Fe(III) minerals. This process included biotic and abiotic factors, which efficiently immobilize and remove soluble Sb(III) under anoxic conditions. The findings revealed a significantly novel development for understanding the biogeochemical Sb cycle. Microbial Sb(III) and Fe(II) oxidation coupled with denitrification has great potential for bioremediation in anoxic Sb-contaminated environments.

Single nanowires (NWs) are of great importance for optoelectronic applications, especially solar cells serving as powering nanoscale devices. However, weak off-resonant absorption can limit its light-harvesting capability. Here, we propose a single NW coated with the graded-index dual shells (DSNW). We demonstrate that, with appropriate thickness and refractive index of the inner shell, the DSNW exhibits significantly enhanced light trapping compared with the bare NW (BNW) and the NW only coated with the outer shell (OSNW) and the inner shell (ISNW), which can be attributed to the optimal off-resonant absorption mode profiles due to the improved coupling between the reemitted light of the transition modes of the leak mode resonances of the Si core and the nanofocusing light from the dual shells with the graded refractive index. We found that the light absorption can be engineered via tuning the thickness and the refractive index of the inner shell, the photocurrent density is significantly enhanced by 134% (56%, 12%) in comparison with that of the BNW (OSNW, ISNW). This work advances our understanding of how to improve off-resonant absorption by applying graded dual-shell design and provides a new choice for designing high-efficiency single NW photovoltaic devices.