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Abstract With the development of laser scanners and machine learning, point cloud semantic segmentation plays a significant role in autonomous driving, scene reconstruction, human-computer interaction, and other fields. In recent years, point cloud semantic segmentation based on deep learning has become one of the key research directions in point cloud processing. Due to the limited ability to exploit geometric details and contextual information in point clouds, most methods that adopt encoder-decoder architecture lose local structural information easily, especially detailed features, and extract features insufficiently. To address this issue, the edge-preserving inception DenseGCN U-Net (entitled as EIDU-Net) is proposed. EIDU-Net makes full use of the complementation between geometric details in the original point cloud and high-level features. The edge-preserved graph pooling (EGP) layer, the key module of the EIDU-Net, is designed to retain additional edge feature information from the original point cloud during pooling operations. Accordingly, the edge-preserved graph unpooling (EGU) layer can restore the feature graph more efficiently based on the additionally retained edge features. Extensive experiments demonstrate that our proposed EIDU-Net has remarkable improvements on semantic segmentation tasks under whatever S3DIS or Terracotta Warrior fragments. Our code is publicly available at https://github.com/caoxin918/EIDU-Net .

Abstract Background Though several nomograms have been established to predict the survival probability of patients with small-cell lung cancer (SCLC), none involved enough variables. This study aimed to construct a novel prognostic nomogram and compare its performance with other models. Methods Seven hundred twenty-two patients were pathologically diagnosed with SCLC in Shanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences, Cancer Hospital Affiliated to Shanxi Medical University from January 2016 to December 2018. We input Forty-one factors by reviewing the medical records. The nomogram was constructed based on the variables identified by univariate and multivariate analyses in the training set and validated in the validation set. Then we compared the performance of the models in terms of discrimination, calibration, and clinical net benefit. Results There were eight variables involved in the nomogram: gender, monocyte (MON), neuron-specific enolase (NSE), cytokeratin 19 fragments (Cyfra211), M stage, radiotherapy (RT), chemotherapy cycles (CT cycles), and prophylactic cranial irradiation (PCI). The calibration curve showed a good correlation between the nomogram prediction and actual observation for overall survival (OS). The area under the curve (AUC) of the nomogram was higher, and the Integrated Brier score (IBS) was lower than other models, indicating a more accurate prediction. Decision curve analysis (DCA) showed a significant improvement in the clinical net benefit compared to the other models. Conclusions We constructed a novel nomogram to predict OS for patients with SCLC using more comprehensive and objective variables. It performed better than existing models and would assist clinicians in individually estimating risk and making a therapeutic regimen.

Abstract People’s livelihood serves as the primary impetus driving all social activities. Faced with intense regional competition and stringent assessment, regional governments often resort to manipulating GDP figures. This study investigates the repercussions of such economic distortion on residents’ welfare. Our findings reveal a significant negative relationship between regional GDP manipulation and investment in livelihood improvements. This correlation is particularly pronounced during the initial phase of officials’ tenure and diminishes when officials serve in their hometowns. Moreover, we observe that the reduction in livelihood investment is exacerbated during periods of economic downturn. These conclusions contribute to the existing literature on regional GDP manipulation and livelihood investment, shedding light on the potential implications for residents’ welfare.

Objective To establish the internal quality control standard of leukocyte-depleted suspended red blood cell volume in our center, so as to guide the preparation of components, strengthen the internal quality control and improve the quality of blood preparations. Methods A total of 1 523 bags of whole blood collected using two manufacturers′ leukocyte-depleted blood bags from March to August 2023 at our center were extracted. The blood before and after filtration were weighed, and the volume of whole blood collected, the volume of filtration loss and the product volume based on the formula and measured specific gravity were calculated. According to the data distribution characteristics, the reference range of leukocyte-depleted suspended red blood cell volume was determined, and the differences of whole blood collection volume, filtration loss capacity and product capacity between the two manufacturers were analyzed. The quality control data of leukocyte-depleted red blood cells over the past year with the difference between another 100 bags of these cells and the reference interval were compared, and the effectiveness of reference interval was validated. Results The median whole blood collection volume in the sample size was 402.0 mL, with a median filtration loss of 42.4 mL, and an average volume of leukocyte-depleted suspended red blood cells at 322.5 mL. The whole blood collection volume (A: median 404.4 mL; B: median 397.7 mL, P0.05). Conclusion According to the actual situation of our center, the volume standard of leukocyte-depleted suspended red blood cells in our center is determined to be 284.1-360.9 mL.

Abstract Background Chicken coccidiosis is a protozoan disease that leads to considerable economic losses in the poultry industry. Live oocyst vaccination is currently the most effective measure for the prevention of coccidiosis. However, it provides limited protection with several drawbacks, such as poor immunological protection and potential reversion to virulence. Therefore, the development of effective and safe vaccines against chicken coccidiosis is still urgently needed. Methods In this study, a novel oral vaccine against Eimeria tenella was developed by constructing a recombinant Lactobacillus plantarum (NC8) strain expressing the E. tenella RON2 protein. We administered recombinant L. plantarum orally at 3, 4 and 5 days of age and again at 17, 18 and 19 days of age. Meanwhile, each chick in the commercial vaccine group was immunized with 3 × 102 live oocysts of coccidia. A total of 5 × 104 sporulated oocysts of E. tenella were inoculated in each chicken at 30 days. Then, the immunoprotection effect was evaluated after E. tenella infection. Results The results showed that the proportion of CD4+ and CD8+ T cells, the proliferative ability of spleen lymphocytes, inflammatory cytokine levels and specific antibody titers of chicks immunized with recombinant L. plantarum were significantly increased (P

This is an article in the field of ceramics and composites. In order to effectively treat and resource utilize lateritic nickel slag, this study used lateritic nickel slags as raw materials and measured the pH value of leaching solution, metal leaching concentration, material unconfined compressive strength, dry shrinkage, elastic modulus, permeability coefficient and other indexes of the cementing material formed by cement solidification, and analyzed the feasibility of using it as backfill material for construction land or highway construction engineering materials. The results show that the cementitious material is made of waste slag (dry basis) 92%, PO42.5 cement 5%, bentonite 3%, PAC 0.5% and water, the pH value of leaching solution is about 8.45, the concentration of leaching metal ions is less than 0.1 mg/L, the unconfined compressive strength is 1.47 MPa, the modulus of elasticity is 1196 MPa, the permeability coefficient is 8.77×10-7 cm/s, and the dry shrinkage resistance is good. It can be used as backfill material for construction land or highway construction engineering. The raw soil cementitious material made of 92% raw soil (dry basis), 5% PO42.5 cement, 3% bentonite, 0.02% additional CHF and 5%～8% water has better dry shrinkage resistance. It can be used as the surface layer of large volume cementitious material to resist dry shrinkage cracks caused by long-term contact with dry air, protect the waste slag cementitious material in the lower layer and ensure the overall stability of cementitious materials. The above research provides a new way for the comprehensive utilization of laterite nickel slags, and lays a theoretical foundation for the research and engineering practice of waste slag as backfill materials or highway building materials.

Summary: Background: Current embolic agents in transcatheter arterial chemoembolization (TACE) of hepatocellular carcinoma (HCC) encounter instability and easy leakage, discounting TACE efficacy with residual HCC. Moreover, clinical TACE aggravates hypoxia and pro-metastatic microenvironments, rendering patients with HCC poor prognosis. Methods: Herein, we developed Zein-based embolic agents that harness water-insoluble but ethanol-soluble Zein to encompass doxorubicin (DOX)-loaded mesoporous hollow MnO2 (HMnO2). The conditions and capacity of HMnO2 to generate reactive oxygen species (ROS) were assayed. Mechanical examinations of Zein-HMnO2@DOX were performed to evaluate its potential as the embolic agent. In vitro experiments were carried out to evaluate the effect of Zein-HMnO2@DOX on HCC. The subcutaneous HCC mouse model and rabbit VX2 HCC model were established to investigate its anti-tumor and anti-metastasis efficacy and explore its potential anti-tumor mechanism. Findings: The high adhesion and crosslinking of Zein with HMnO2@DOX impart Zein-HMnO2@DOX with strong mechanical strength to resist deformation and wash-off. Zein gelation and HMnO2 decomposition in response to water and acidic tumor microenvironment, respectively, enable continuous DOX release and Fenton-like reaction for reactive oxygen species (ROS) production and O2 release to execute ROS-enhanced TACE. Consequently, Zein-based embolic agents outperform clinically-used lipiodol to significantly inhibit orthotopic HCC growth. More significantly, O2 release down-regulates hypoxia inducible factor (HIF-1α), vascular endothelial growth factor (VEGF) and glucose transporter protein 1 (GLUT1), which thereby re-programmes TACE-aggravated hypoxic and pro-metastatic microenvironments to repress HCC metastasis towards lung. Mechanistic explorations uncover that such Zein-based TACE agents disrupt oxidative stress, angiogenesis and glycometabolism pathways to inhibit HCC progression. Interpretation: This innovative work not only provides a new TACE agent for HCC, but also establishes a new strategy to ameliorate TACE-aggravated hypoxia and metastasis motivation against clinically-common HCC metastasis after TACE operation. Funding: Excellent Young Science Fund for National Natural Science Foundation of China (82022033); National Natural Science Foundation of China (Grant No. 82373086, 82102761); Major scientific and technological innovation project of Wenzhou Science and Technology Bureau (Grant No. ZY2021009); Shanghai Young Top-Notch Talent.

ABSTRACT The loss of freshwater fish habitats, exacerbated by climate change and dam constructions, poses a critical environmental concern. The upper Yangtze River basin, noted for its abundant fish fauna and concentrated dam development, serves as a crucial locale for investigating the impacts of climate shifts and dam construction. This study aims to disentangle the impacts of hydroelectric dams and climate change on fish habitat distribution by analyzing species presence data across different periods. Species distribution models were constructed using Maxent for Coreius guichenoti (a warm‐water endangered fish) and Schizopygopsis malacanthus (a cold‐water endangered fish). The model accuracy was assessed using the area under the curve of the receiver operating characteristic. Habitat distribution modeling and prediction for the pre‐dam period (1970–2000) and post‐dam period (2001–2020), as well as future climate change under two shared socioeconomic pathways scenarios, were conducted. The impacts of climate change and dam construction on the habitat suitability of two fish species were quantified. The results revealed dam construction predominantly diminished habitat suitability and range, with high‐suitability habitats in the post‐dam period decreasing by 56.3% (720.18 km) and 67.0% (1665.52 km) for the two fishes, respectively. Climate change would enhance the habitat suitability of Coreius guichenoti, while it would decrease the habitat suitability of Schizopygopsis malacanthus. The impact of dam construction is greater that of climate change for them. This study underscores the profound impacts of dam construction on fish habitats, particularly for cold‐water species, and highlights the critical need for habitat restoration in sustainable hydropower development. Our method of disentangling these factors also provides a new approach to evaluating environmental impacts in large river basins.

Streptococcus pneumoniae is a pathogenic bacterium that causes infections such as pneumonia, meningitis, otitis media, and bacteremia. The prevention of pneumococcal disease by vaccination has become more urgent due to increased antibiotic resistance. Pneumococcal capsular polysaccharides (CPS) are effective vaccine antigens that stimulate the host to produce protective antibodies. S. pneumoniae serotype 14 is one of most prevalent types in Latin America and across the world. However, the yield of S. pneumoniae serotype 14 CPS from existing fermentation processes remains low and requires improvement. In this study, various aspects of the fermentation process were optimized to improve pneumococcal growth and polysaccharide productivity, including feed medium, cultivation gas environment, fermentation pH, and temperature. A simplified purification method was also developed to obtain pure CPS, including ultrafiltration, acid and ethanol precipitation, diafiltration, and lyophilization. These fermentation optimizations significantly enhanced the optical density of pneumococcal bacterial cultures and increased fermentation yields to 2.4–2.6 g/L—significantly higher than previously achieved. Furthermore, the test results of pure CPS could meet the requirements in the European Pharmacopoeia (11th edition). These optimizations provide valuable insights into the nutritional requirements and impact of varying fermentation process parameters on pneumococcal growth and CPS productivity, thus contributing to the development of a more efficient and cost-effective method for the production of pneumococcal CPS—essential for manufacturing vaccines against pneumococcal infections.

ABSTRACT: Avian influenza virus (AIV) subtype H9N2 has significantly threatened the poultry business in recent years by having become the predominant subtype in flocks of chickens, ducks, and pigeons. In addition, the public health aspects of H9N2 AIV pose a significant threat to humans. Early and rapid diagnosis of H9N2 AIV is therefore of great importance. In this study, a new method for the detection of H9N2 AIV based on fluorescence intensity was successfully established using CRISPR/Cas13a technology. The Cas13a protein was first expressed in a prokaryotic system and purified using nickel ion affinity chromatography, resulting in a high-purity Cas13a protein. The best RPA (recombinase polymerase amplification) primer pairs and crRNA were designed and screened, successfully constructing the detection of H9N2 AIV based on CRISPR/Cas13a technology. Optimal concentration of Cas13a and crRNA was determined to optimize the constructed assay. The sensitivity of the optimized detection system is excellent, with a minimum detection limit of 10° copies/μL and didn't react with other avian susceptible viruses, with excellent specificity. The detection method provides the basis for the field detection of the H9N2 AIV.

Abstract Potassium‐ion batteries (PIBs) offer a cost‐effective and resource‐abundant solution for large‐scale energy storage. However, the progress of PIBs is impeded by the lack of high‐capacity, long‐life, and fast‐kinetics anode electrode materials. Here, we propose a dual synergic optimization strategy to enhance the K+ storage stability and reaction kinetics of Bi2S3 through two‐dimensional compositing and cation doping. Externally, Bi2S3 nanoparticles are loaded onto the surface of three‐dimensional interconnected Ti3C2Tx nanosheets to stabilize the electrode structure. Internally, Cu2+ doping acts as active sites to accelerate K+ storage kinetics. Various theoretical simulations and ex situ techniques are used to elucidate the external–internal dual synergism. During discharge, Ti3C2Tx and Cu2+ collaboratively facilitate K+ intercalation. Subsequently, Cu2+ doping primarily promotes the fracture of Bi2S3 bonds, facilitating a conversion reaction. Throughout cycling, the Ti3C2Tx composite structure and Cu2+ doping sustain functionality. The resulting Cu2+‐doped Bi2S3 anchored on Ti3C2Tx (C‐BT) shows excellent rate capability (600 mAh g–1 at 0.1 A g–1; 105 mAh g–1 at 5.0 A g–1) and cycling performance (91 mAh g–1 at 5.0 A g–1 after 1000 cycles) in half cells and a high energy density (179 Wh kg–1) in full cells.

ABSTRACT E3 ubiquitin ligase (E3) plays a vital role in regulating inflammatory responses by mediating ubiquitination. Previous studies have shown that ankyrin repeat and SOCS box-containing protein 3 (ASB3) is involved in immunomodulatory functions associated with cancer. However, the impact of ASB3 on the dynamic interplay of microbiota and inflammatory responses in inflammatory bowel disease (IBD) is unclear. Here, we systematically identify the E3 ligase ASB3 as a facilitative regulator in the development and progression of IBD. We observed that ASB3 exhibited significant upregulation in the lesions of patients with IBD. ASB3−/− mice are resistant to dextran sodium sulfate-induced colitis. IκBα phosphorylation levels and production of proinflammatory factors IL-1β, IL-6, and TNF-α were reduced in the colonic tissues of ASB3−/− mice compared to WT mice. This colitis-resistant phenotype was suppressed after coprophagic microbial transfer and reversed after combined antibiotics removed the gut commensal microbiome. Mechanistically, ASB3 specifically catalyzes K48-linked polyubiquitination of TRAF6 in intestinal epithelial cells. In contrast, in ASB3-deficient organoids, the integrity of the TRAF6 protein is shielded, consequently decelerating the onset of intestinal inflammation. ASB3 is associated with dysregulation of the colitis microbiota and promotes proinflammatory factors’ production by disrupting TRAF6 stability. Strategies to limit the protein level of ASB3 in intestinal epithelial cells may help in the treatment of colitis.IMPORTANCEUbiquitination is a key process that controls protein stability. We determined the ubiquitination of TRAF6 by ASB3 in intestinal epithelial cells during colonic inflammation. Inflammatory bowel disease patients exhibit upregulated ASB3 expression at focal sites, supporting the involvement of degradation of TRAF6, which promotes TLR-Myd88/TRIF-independent NF-κB aberrant activation and intestinal microbiota imbalance. Sustained inflammatory signaling in intestinal epithelial cells and dysregulated protective probiotic immune responses mediated by ASB3 collectively contribute to the exacerbation of inflammatory bowel disease. These findings provide insights into the pathogenesis of inflammatory bowel disease and suggest a novel mechanism by which ASB3 increases the risk of colitis. Our results suggest that future inhibition of ASB3 in intestinal epithelial cells may be a novel clinical strategy.

Abstract Due to the antiquity and difficulty of excavation, the Terracotta Warriors have suffered varying degrees of damage. To restore the cultural relics to their original appearance, utilizing point clouds to repair damaged Terracotta Warriors has always been a hot topic in cultural relic protection. The output results of existing methods in point cloud completion often lack diversity. Probability-based models represented by Denoising Diffusion Probabilistic Models have recently achieved great success in the field of images and point clouds and can output a variety of results. However, one drawback of diffusion models is that too many samples result in slow generation speed. Toward this issue, we propose a new neural network for Terracotta Warriors fragments completion. During the reverse diffusion stage, we initially decrease the number of sampling steps to generate a coarse result. This preliminary outcome undergoes further refinement through a multi-scale refine network. Additionally, we introduce a novel approach called Partition Attention Sampling to enhance the representation capabilities of features. The effectiveness of the proposed model is validated in the experiments on the real Terracotta Warriors dataset and public dataset. The experimental results conclusively demonstrate that our model exhibits competitive performance in comparison to other existing models.

Abstract Background Social anxiety has been shown to affect college students’ academic performance. However, the role of social media addiction and academic engagement in this association is unclear. Methods A total 2661 college students completed a self-report questionnaire including Liebowitz Social Anxiety Scale, the Bergen Social Media Addiction Scale, the Utrecht Student Work Engagement Scale for Students, and the grade point average. Hayes’ PROCESS macro for SPSS was employed to test the serial mediation effect. Results Results indicated that social anxiety was negatively related to academic performance, only academic engagement played a single mediating role in the relationship between social anxiety and academic performance, meanwhile social media addiction and academic engagement acted as serial mediators between social anxiety on academic performance. Conclusions Social media addiction and academic engagement can explain the potential mechanisms of the association between social anxiety and academic performance, which have implications for devising intervention strategies to enhance the mental health and academic outcomes of college students.

Pertussis has reemerged globally, with rising incidence in China. Controlling this disease remains a significant public health challenge worldwide. This study applies bibliometric methods to analyze global and Chinese research on pertussis, assessing current trends, identifying hot topics, predicting future research directions, and providing guidance for scientific research and clinical practice. Pertussis-related articles from 2000 to 2023 were retrieved from four major Chinese databases and three English databases. COOC and CiteSpace software were used to analyze publication trends, geographic distribution, institutions, disciplines, and keywords, to visualize through network maps. The study analyzed 2,580 Chinese and 5,311 foreign articles and reviews. Pertussis research publications have increased globally, with foreign research peaking earlier than in China. The United States leads in publication volume, while China showed the highest burst of activity from 2019 to 2023. Research mainly focuses on animal experiments, vaccine development and safety, clinical characteristics and treatment, and pertussis toxin. Pertussis research is thriving globally and in China. Future research should emphasize interdisciplinary collaboration across molecular biology, immunology, and epidemiology to innovate vaccines and control strategies. Additionally, continued development of treatment drugs remains crucial as current vaccines do not fully control pertussis.

Salmonella is a foodborne pathogen that causes disruption of intestinal mucosal immunity, leading to acute gastroenteritis in the host. In this study, we found that Salmonella Typhimurium (STM) infection of the intestinal tract of mice led to a significant increase in the proportion of Lacticaseibacillus, while the secretion of IL-22 from type 3 innate lymphoid cells (ILC3) increased significantly. Feeding Lacticaseibacillus rhamnosus GG (LGG) effectively alleviated the infection of STM in the mouse intestines. TLR2−/− mice experiments found that TLR2-expressing dendritic cells (DCs) are crucial for LGG‘s activation of ILC3. Subsequent in vitro experiments showed that heat-killed LGG (HK-LGG) could promote DCs to secrete IL-23, which in turn further promotes the activation of ILC3 and the secretion of IL-22. Finally, organoid experiments further verified that IL-22 secreted by ILC3 can enhance the intestinal mucosal immune barrier and inhibit STM infection. This study demonstrates that oral administration of LGG is a potential method for inhibiting STM infection.

ABSTRACTThe Central Business Districts (CBDs) are important hubs for urban economic activities. In the context of globalization, a unified CBD boundary would greatly facilitate the study of global CBD comparative analysis, urban socio-economic development, urban transport and commuting mode. However, previous studies have encountered challenges in developing a practical method for global CBD identification due to limitations in data sources and methodologies. In this study, we selected 32 global megacities as research objects and used the open-access Black Marble nighttime light (NTL) products to construct indicators with the intensity and angular effects of NTL. Clustering and decision tree were then employed to derive rules for CBD identification. Results show that combining Z-score indicators and the strategy of clustering 32 cities before decision tree classification could improve the accuracy of CBD identification, which achieved a producer accuracy of 85%. The 32 cities were clustered into three types, i.e. U.S.A.-like, the mixed type, and China-like. The rules for CBD identification became more complex in the above order, but the accuracy decreased in turn. This study provides a new CBD identification method for cities lacking reference data, allowing for the delineation of unified and comparable CBD boundaries on a large scale.

G protein-coupled receptor-associated sorting protein 2 (GPRASP2) deficiency has been implicated in immunological inflammation, cancers, and neurological disorders. Our previous work revealed that the pathogenic mutation in GPRASP2 was responsible for X-linked recessive syndromic hearing loss (SHL). Given the specific high expression of GPRASP2 in the spiral ganglion, GPRASP2 likely contributes to the maintenance and functionality of neurons, potentially playing a role in synaptic transmission. The impact of GPRASP2 deficiency on spiral ganglion cells (SGCs) and their underlying pathogenic mechanisms will be investigated in this study. The primary culture of SGCs obtained from mouse cochleae was treated with Gprasp2-targeting short hairpin RNA (Gprasp2-shRNA) via lentivirus infection. The results showed that GPRASP2 deficiency enhanced SGCs apoptosis and decreased cell viability. Meanwhile, a significant abnormality of mitochondrial morphology and decreased membrane potential were observed in GPRASP2-deficient SGCs. These effects could be mitigated by treatment with the mitochondrial division inhibitor 1 (Mdivi-1). In addition to enhancing SGCs apoptosis and decreasing cell viability, GPRASP2 deficiency also inhibited the development of SGCs in mouse cochlear explant culture. Our study further revealed that this deficiency resulted in increased phosphorylation of AMPK and activation of the AMPK/DRP1 pathway, promoting SGCs apoptosis. These findings provide insight into the pathogenic mechanisms by which GPRASP2 deficiency is implicated in auditory dysfunction.

Pneumococcal disease is caused by Streptococcus pneumoniae, including pneumonia, meningitis and sepsis. Capsular polysaccharides (CPSs) have been shown as effective antigens to stimulate protective immunity against pneumococcal disease. A major step in the production of pneumococcal vaccines is to prepare CPSs that meet strict quality standards in immunogenicity and safety. The major impurities come from bacterial proteins, nucleic acids and cell wall polysaccharides. Traditionally, the impurity level of refined CPSs is reduced by optimization of purification process. In this study, we investigated new aeration strategy and advanced sterilization methods by formaldehyde or β-propiolactone (BPL) to increase the amount of soluble polysaccharide in fermentation supernatant and to prevent bacterial lysis during inactivation. Furthermore, we developed a simplified process for the CPS purification, which involves ultrafiltration and diafiltration, followed by acid and alcohol precipitation, and finally diafiltration and lyophilization to obtain pure polysaccharide. The CPSs prepared from formaldehyde and BPL sterilization contained significantly lower level of residual impurities compared to the refined CPSs obtained from traditional deoxycholate sterilization. Finally, we showed that this novel approach of CPS preparation can be scaled up for polysaccharide vaccine production.

Several immune related adverse events (irAEs) were reported with the wide application of immune checkpoint inhibitors (ICIs) in tumors. ICI-related skin reactions are the most common, which are manifested as maculopapules, rash, pruritus, vitiligo, psoriasis, and lichenoid rash.Among them, the incidence of pruritus is second only to maculopapule/rash, but both often co-exist. The severity of pruritus is mostly mild to moderate and can be relieved after symptomatic treatment with antihistamines. Symptoms are slightly relieved after conventional treatment in patients with severe pruritus, but it easily recurs and eventually develops into refractory pruritus.The patient's quality of life may be affected and may also be life-threatening.We report a case of a patient with postoperative recurrence of gallbladder neuroendocrine carcinoma,who developed refractory pruritus after sintilimab use, which was relieved after naloxone infusion after unsuccessful conventional drug therapy. By analyzing the treatment plan of this typical case of immune-related refractory pruritus after using sintilimab, this report discusses how clinical pharmacists can provide individualized treatment of patients by using their expertise and clinicians' cooperation and complementation in treating clinically difficult cases. This case report may be used as a reference in treating patients with refractory pruritus after the clinical use of sintilimab.

Abstract Background The gut microbiota is a critical factor in the regulation of host health, but the relationship between the differential resistance of hosts to pathogens and the interaction of gut microbes is not yet clear. Herein, we investigated the potential correlation between the gut microbiota of piglets and their disease resistance using single-cell transcriptomics, 16S amplicon sequencing, metagenomics, and untargeted metabolomics. Results Porcine epidemic diarrhea virus (PEDV) infection leads to significant changes in the gut microbiota of piglets. Notably, Landrace pigs lose their resistance quickly after being infected with PEDV, but transplanting the fecal microbiota of Min pigs to Landrace pigs alleviated the infection status. Macrogenomic and animal protection models identified Lactobacillus reuteri and Lactobacillus amylovorus in the gut microbiota as playing an anti-infective role. Moreover, metabolomic screening of the secondary bile acids’ deoxycholic acid (DCA) and lithocholic acid (LCA) correlated significantly with Lactobacillus reuteri and Lactobacillus amylovorus, but only LCA exerted a protective function in the animal model. In addition, LCA supplementation altered the distribution of intestinal T-cell populations and resulted in significantly enriched CD8+ CTLs, and in vivo and in vitro experiments showed that LCA increased SLA-I expression in porcine intestinal epithelial cells via FXR receptors, thereby recruiting CD8+ CTLs to exert antiviral effects. Conclusions Overall, our findings indicate that the diversity of gut microbiota influences the development of the disease, and manipulating Lactobacillus reuteri and Lactobacillus amylovorus, as well as LCA, represents a promising strategy to improve PEDV infection in piglets. Video Abstract

Abstract Background As stroke has become the leading cause of death and disability in China, it has induced a heavy disease burden on society, families, and patients. Despite much attention within the literature, the effect of multiple risk factors on length of stay (LOS) and inpatient costs in China is still not fully understood. Aim To analyse the association between the number of risk factors combined and inpatient costs among adults with stroke and explore the mediating effect of LOS on inpatient costs. Methods A retrospective cross-sectional study was conducted among stroke patients in a tertiary hospital in Nantong City from January 2018 to December 2019. Lifestyle factors (smoking status, exercise), personal disease history (overweight, hypertension, dyslipidemia, diabetes mellitus, atrial fibrillation), family history of stroke, and demographic characteristics were interviewed by trained nurses. Inpatient costs and LOS were extracted from electronic medical records. Hierarchical multiple linear regression models and mediation analysis were used to examine the direct and indirect effects of the number of risk factors combined for stroke on inpatient costs. Results A total of 620 individuals were included, comprising 391 ischaemic stroke patients and 229 haemorrhagic stroke patients, and the mean age was 63.2 years, with 60.32% being male. The overall mean cost for stroke inpatients was 30730.78 CNY ($ 4444.91), and the average length of stay (LOS) was 12.50 days. Mediation analysis indicated that the greater number of risk factors was not only directly related to higher inpatient costs (direct effect = 0.16, 95%CI:[0.11,0.22]), but also indirectly associated with inpatient cost through longer LOS (indirect effect = 0.08, 95% CI: [0.04,0.11]). Furthermore, patients with high risk of stroke had longer LOS than those in low-risk patients, which in turn led to heavier hospitalization expenses. Conclusions Both the greater number of risk factors and high-risk rating among stroke patients increased the length of stay and inpatient costs. Preventing and controlling risk behaviors of stroke should be strengthened.

Abstract Continuously monitoring global population spatial dynamics is crucial for implementing effective policies related to sustainable development, including epidemiology, urban planning, and global inequality. However, existing global gridded population data products lack consistent population estimates, making them unsuitable for time-series analysis. To address this issue, this study designed a data fusion framework based on cluster analysis and statistical learning approaches, which led to the generation of a continuous global gridded population dataset (GlobPOP). The GlobPOP dataset was evaluated through two-tier spatial and temporal validation to demonstrate its accuracy and applicability. The spatial validation results show that the GlobPOP dataset is highly accurate. The temporal validation results also reveal that the GlobPOP dataset performs consistently well across eight representative countries and cities despite their unique population dynamics. With the availability of GlobPOP datasets in both population count and population density formats, researchers and policymakers can leverage the new dataset to conduct time-series analysis of the population and explore the spatial patterns of population development at global, national, and city levels.

As the proportion of renewable energy (RE) increases, the inertia and the primary frequency regulation (FR) capability of the power system decrease. Thus, ensuring frequency security in the scheduling model has become a new technical requirement in power systems with a high share of RE. Due to a shortage of conventional synchronous generators, the frequency support of multi-source converters has become an indispensable part of the system frequency resources, especially variable-speed wind turbine generation (WTG) and battery energy storage (BES). Quantitative expression of the FR capability of multi-source converters is necessary to construct frequen-cyconstrained scheduling model. However, the frequency support performance of these converter-interfaced devices is related to their working states, operation modes, and parameters, and the complex coupling of these factors has not been fully exploited in existing models. In this study, we propose an integrated frequency-constrained scheduling model considering the coordination of FR capabilities from multi-source converters. Switchable FR control strategies and variable FR parameters for WTG with or without reserved power are modeled, and multi-target allocation of BES capacity between tracking dispatch instruction and emergency FR is analyzed. Then, the variable FR capabilities of WTG and BES are embedded into the integrated frequency-constrained scheduling model. The nonlinear constraints for frequency security are precisely linearized through an improved iteration-based strategy. The effectiveness of the proposed model is verified in a modified IEEE 24-bus standard system. The results suggest that the coordinated participation of BES and WTG in FR can effectively reduce the cost of the scheduling model while meeting frequency security constraints.

Abstract Vaccination is still the most promising strategy for combating influenza virus pandemics. However, the highly variable characteristics of influenza virus make it difficult to develop antibody-based universal vaccines, until now. Lung tissue-resident memory T cells (TRM), which actively survey tissues for signs of infection and react rapidly to eliminate infected cells without the need for a systemic immune reaction, have recently drawn increasing attention towards the development of a universal influenza vaccine. We previously designed a sequential immunization strategy based on orally administered Salmonella vectored vaccine candidates. To further improve our vaccine design, in this study, we used two different dendritic cell (DC)-targeting strategies, including a single chain variable fragment (scFv) targeting the surface marker DC-CD11c and DC targeting peptide 3 (DCpep3). Oral immunization with Salmonella harboring plasmid pYL230 (S230), which displayed scFv-CD11c on the bacterial surface, induced dramatic production of spleen effector memory T cells (TEM). On the other hand, intranasal boost immunization using purified DCpep3-decorated 3M2e-ferritin nanoparticles in mice orally immunized twice with S230 (S230inDC) significantly stimulated the differentiation of lung CD11b+ DCs, increased intracellular IL-17 production in lung CD4+ T cells and elevated chemokine production in lung sections, such as CXCL13 and CXCL15, as determined by RNAseq and qRT‒PCR assays, resulting in significantly increased percentages of lung TRMs, which could provide efficient protection against influenza virus challenge. The dual DC targeting strategy, together with the sequential immunization approach described in this study, provides us with a novel “prime and pull” strategy for addressing the production of protective TRM cells in vaccine design.

Accurate prediction of short-term wind power plays an important role in the safe operation and economic dispatch of the power grid. In response to the current single algorithm that cannot further improve the prediction accuracy, this study proposes a combined wind power prediction model based on data processing, signal decomposition, and deep learning. First, outliers in the original data can affect prediction accuracy. This study detects the outliers by the Z-score method and fills them with cubic spline interpolation to ensure the integrity of the data. Second, for the volatility of wind power, the wind power time series is decomposed using the complete ensemble empirical modal decomposition with adaptive noise (CEEMDAN). The component complexity of the decomposition is calculated using the sample entropy (SE), and the components are reconstructed according to the SE size to improve the prediction accuracy. Finally, the traditional convolutional neural network (CNN) structure is improved and the bi-directional long short-term memory (BiLSTM) network is used to further extract the feature links between wind power data and superimpose the prediction results of each reconstructed component to obtain the final wind power prediction value. The experimental results demonstrate that the hybrid model proposed in this study has better performance in terms of prediction performance.

PHPs (pulsating heat pipes) are widely used as an efficient heat transfer element in equipment thermal management and waste heat recovery due to their flexibility. The purpose of this study was to design a heat transfer device that utilizes an asymmetric pulsating heat pipe structure by adjusting the lengths of selected pipes within the entire circulation pipeline. In the experiment, a constant temperature water bath was used as the heat source, with heat dissipated in the condensing section via natural convection. An infrared thermal imager was used to record the temperature of the condensing section, and the local wall temperature distribution was measured in different channels of the condensing section. Based on an in-depth analysis of the wavelet frequency, the following research conclusions are drawn: Firstly, as the heat source temperature increases, the start-up time of the pulsating heat pipe is shortened, the operating state changes from start–stop–start to stable and continuous oscillation, and the oscillation mode changes from high amplitude and low frequency to low amplitude and high frequency. These changes are especially pronounced when the heat source temperature is 80 °C, which is when the thermal resistance reaches its lowest value of 0.0074 K/W, and the equivalent thermal conductivity reaches its highest value of 666.29 W/(m·K). Secondly, the flow and oscillation of the working fluid can be effectively promoted by appropriately shortening the length of the condensing section of the pulsating heat pipes or the heat transfer distance between the evaporation and condensing sections. Third, under a low-temperature heat source, the oscillation frequency of each channel of a pulsating heat pipe is found to be low based on wavelet analysis. However, as the heat source temperature increases, the energy content of the temperature signal of the working fluid in each channel changes from a low- to a high-frequency value, gradually converging to the same characteristic frequency. At this point, the working fluid in the pipes no longer flows randomly in multiple directions but rather in a single direction. Finally, we determined that the maximum oscillation frequency of working fluid in a PHP is around 0.7 HZ when using the water bath heating method.

In this study, a leading–drawing–cutting–type profiled root–trimming device was designed to address the problems of high impurity and damage rates that occur with the operation of a pull–cut garlic harvester. The main components of the designed device include a pull–clamp mechanism, roll–pulling mechanism, root–trimming knife mechanism, lifter, gearbox, universal drive shaft, motor, and frame that, together, can complete the root–trimming operation for a pull–cut garlic harvester. An orthogonal regression test was carried out by taking the roller diameter, the roller inclination angle, the knife rotation speed, and the working speed as factors and by taking the impurity rate and the damage rate as indices. The results of the orthogonal regression test showed that the impurity rate was most strongly affected by the roller diameter, followed by the knife rotation speed, the working speed, and the roller inclination angle. Meanwhile, the damage rate was most strongly affected by the knife rotation speed, followed by the roller diameter, the working speed, and the roller inclination angle. The regression analysis showed that when the roller diameter was 100 mm, the roller inclination angle was 25°, the knife rotation speed was 200 r·min−1, and the working speed was 1.22 km·h−1, the comprehensive trimming quality reached its maximum value of 97.82%. The verification result of the parallel test gave a value of 97.52%, which was mainly affected by the irregular sizes of the bulbs, but it showed no significant difference from the regression analysis results. The tests verified that the profiled root–trimming device could be applied to develop the technology of garlic pull–cut harvesters.

Antioxidants are substances that have the ability to resist or delay oxidative damage. Antioxidants can be used not only for the diagnosis and prevention of vascular diseases, but also for food preservation and industrial production. However, due to the excessive use of antioxidants, it can cause environmental pollution and endanger human health. It can be seen that the development of antioxidant detection technology is important for environment/health maintenance. It is found that traditional detection methods, including high performance liquid chromatography, gas chromatography, etc., have shortcomings such as cumbersome operation and high cost. In contrast, the nanozyme-based detection method features advantages of low cost, simple operation, and rapidity, which has been widely used in the detection of various substances such as glucose and antioxidants. This article focuses on the latest research progress of nanozymes for antioxidant detection. Nanozymes for antioxidant detection are classified according to enzyme-like types. Different types of nanozyme-based sensing strategies and detection devices are summarized. Based on the summary and analysis, one can find that the development of commercial nanozyme-based devices for the practical detection of antioxidants is still challenging. Some emerging technologies (such as artificial intelligence) should be fully utilized to improve the detection sensitivity and accuracy. This article aims to emphasize the application prospects of nanozymes in antioxidant detection and to provide new ideas and inspiration for the development of detection methods.

In the last decade, organoid research has entered a golden era, signifying a pivotal shift in the biomedical landscape. The year 2023 marked a milestone with the publication of thousands of papers in this arena, reflecting exponential growth. However, amid this burgeoning expansion, a comprehensive and accurate overview of the field has been conspicuously absent. Our review is intended to bridge this gap, providing a panoramic view of the rapidly evolving organoid landscape. We meticulously analyze the organoid field from eight distinctive vantage points, harnessing our rich experience in academic research, industrial application, and clinical practice. We present a deep exploration of the advances in organoid technology, underpinned by our long-standing involvement in this arena. Our narrative traverses the historical genesis of organoids and their transformative impact across various biomedical sectors, including oncology, toxicology, and drug development. We delve into the synergy between organoids and avant-garde technologies such as synthetic biology and single-cell omics and discuss their pivotal role in tailoring personalized medicine, enhancing high-throughput drug screening, and constructing physiologically pertinent disease models. Our comprehensive analysis and reflective discourse provide a deep dive into the existing landscape and emerging trends in organoid technology. We spotlight technological innovations, methodological evolution, and the broadening spectrum of applications, emphasizing the revolutionary influence of organoids in personalized medicine, oncology, drug discovery, and other fields. Looking ahead, we cautiously anticipate future developments in the field of organoid research, especially its potential implications for personalized patient care, new avenues of drug discovery, and clinical research. We trust that our comprehensive review will be an asset for researchers, clinicians, and patients with keen interest in personalized medical strategies. We offer a broad view of the present and prospective capabilities of organoid technology, encompassing a wide range of current and future applications. In summary, in this review we attempt a comprehensive exploration of the organoid field. We offer reflections, summaries, and projections that might be useful for current researchers and clinicians, and we hope to contribute to shaping the evolving trajectory of this dynamic and rapidly advancing field.

In May 2023, the EU formally adopted the Carbon Border Adjustment Mechanism (CBAM) bill, which requires that from 2026 onwards, high-carbon imports must use the appropriate Carbon Border Adjustment Mechanism (CBAM) certificates. At the initial stage, the mechanism has gradually covered eight high-carbon industries, and is likely to be expanded to include more industries, including the already highly competitive home appliance industry. In order to cope with the challenges that the CBAM may bring, and in line with the general trend of international green trade and circular economy, the government and the international trade industry in multiple categories, including home appliance enterprises, should react quickly and take feasible countermeasures. This study adopts a case study analytical framework to understand the responses of Chinese home appliance enterprises to CBAM through cluster analysis of 240 samples, and to explore the impact of CBAM on individual enterprises, as well as their product development and design strategies in the transition to a carbon-reducing economy. The results show that, firstly, CBAM has both negative and positive impacts on Chinese home appliance firms. Second, four product development strategies were summarized in the cluster analysis, including technological advantage, customer orientation, cost advantage and imitation. Third, 20 strategies related to product cycle design were summarized in the case interviews. In addition, there is a correlation between the product design strategies adopted by the sample firms and the firm attributes (firm size, business form and product development type). The results of this study can provide product design strategy references for the sample companies to deal with CBAM and future competition, as well as practical experience for companies in other fields to deal with CBAM.

Optical molecular tomography (OMT) is a potential pre-clinical molecular imaging technique with applications in a variety of biomedical areas, which can provide non-invasive quantitative three-dimensional (3D) information regarding tumor distribution in living animals. The construction of optical transmission models and the application of reconstruction algorithms in traditional model-based reconstruction processes have affected the reconstruction results, resulting in problems such as low accuracy, poor robustness, and long-time consumption. Here, a gates joint locally connected network (GLCN) method is proposed by establishing the mapping relationship between the inside source distribution and the photon density on surface directly, thus avoiding the extra time consumption caused by iteration and the reconstruction errors caused by model inaccuracy. Moreover, gates module was composed of the concatenation and multiplication operators of three different gates. It was embedded into the network aiming at remembering input surface photon density over a period and allowing the network to capture neurons connected to the true source selectively by controlling three different gates. To evaluate the performance of the proposed method, numerical simulations were conducted, whose results demonstrated good performance in terms of reconstruction positioning accuracy and robustness.

ABSTRACTCanine distemper virus (CDV) poses a severe threat to both domesticated and wild animals, including multiple carnivores. With the continued expansion of its host range, there is an urgent need for the development of a safer and more effective vaccine. In this study, we developed subunit vaccines based on a bacterium-like particle (BLP) delivery platform containing BLPs-F and BLPs-H, which display the CDV F and H glycoprotein antigens, respectively, using the antigen-protein anchor fusions produced by a recombinant baculovirus insect cell expression system. The combination of BLPs-F and BLPs-H (CDV-BLPs), formulated with colloidal manganese salt [Mn jelly (MnJ)] adjuvant, triggered robust CDV-specific antibody responses and a substantial increase in the number of interferon gamma (IFN-γ)-secreting CD4+ and CD8+ T cells in mice. Dogs immunized intramuscularly with this vaccine not only produced CDV-specific IgG but also displayed elevated concentrations of IFN-γ and interleukin 6 in their serum, along with an increase of the CD3+CD4+ and CD3+CD8+ T cell subsets. Consequently, this heightened immune response provided effective protection against disease development and reduced viral shedding levels following challenge with a virulent strain. These findings suggest that this BLP-based subunit vaccine has the potential to become a novel canine distemper vaccine.IMPORTANCEMany sensitive species require a safe and effective distemper vaccine. Non-replicating vaccines are preferred. We constructed subunit particles displaying canine distemper virus (CDV) antigens based on a bacterium-like particle (BLP) delivery platform. The CDV-BLPs formulated with theMn jelly adjuvant induced robust humoral and cell-mediated immune responses to CDV in mice and dogs, thereby providing effective protection against a virulent virus challenge. This work is an important step in developing a CDV subunit vaccine.

The magnetospheric systems of ice giants, as the ideal and the unique template of a typical class of exoplanets, have not been sufficiently studied in the past decade. The complexity of these asymmetric and extremely dynamic magnetospheres provides us a great chance to systematically investigate the general mechanism of driving the magnetospheres of such common exoplanets in the Universe, and the key factors of influencing the global and local magnetospheric structures of this type of planets. In this paper, we discuss the science return of probing magnetospheric systems of ice giants for the future missions, throughout different magnetospheric regions, across from the interaction with upstream solar wind to the downstream region of the magnetotail. We emphasize the importance of detecting the magnetospheric systems of ice giants in the next decades, which enables us to deeply understand the space enviroNMent and habitability of not only the ice giants themselves but also the analogous exoplanets which are widely distributed in the Universe.

Composite lymphoma is an uncommon type of lymphoid malignancy, and those consisting of concurrent diffuse large B-cell lymphoma (DLBCL) and peripheral T-cell lymphoma, not otherwise specified (PTCL-NOS) in the same organ are rare. Here, we report a case of a 75-year-old male patient admitted to our emergency department with intestinal obstruction presenting with abdominal pain and vomiting. He underwent partial resection of the small intestine under general anesthesia, and subsequent histopathology confirmed the mass to be composite DLBCL and PTCL-NOS. The patient received chemotherapy with a rituximab-based regimen and achieved complete remission (CR). However, the recurrent disease presented with obstruction again ten months after treatment. He refused a second surgery, but salvage treatment was not effective. The patient survived for 20 months after diagnosis. In addition, we did a literature review to understand the clinical features, pathology, treatment, and prognosis of this type of composite lymphoma.

Highlights Heterostructure engineering is proposed to construct CoTe2/ZnTe heterostructures with built-in electric field. Conductive and elastic Ti3C2T x MXene is introduced to improve the conductivity and alleviate the volume change of CoTe2/ZnTe upon cycling. The resulting CoTe2/ZnTe/Ti3C2T x (CZT) demonstrates outstanding rate capability (137.0 mAh g−1 at 10 A g−1) and cycling stability (175.3 mAh g−1 after 4000 cycles at 3.0 A g−1). Moreover, the CZT-based full cells demonstrate excellent energy density (220.2 Wh kg−1) and power density (837.2 W kg−1).

Abstract Cingulin (CGN) is a cytoskeleton‐associated protein localized at the apical junctions of epithelial cells. CGN interacts with major cytoskeletal filaments and regulates RhoA activity. However, physiological roles of CGN in development and human diseases are currently unknown. Here, we report a multi‐generation family presenting with autosomal dominant non‐syndromic hearing loss (ADNSHL) that co‐segregates with a CGN heterozygous truncating variant, c.3330delG (p.Leu1110Leufs*17). CGN is normally expressed at the apical cell junctions of the organ of Corti, with enriched localization at hair cell cuticular plates and circumferential belts. In mice, the putative disease‐causing mutation results in reduced expression and abnormal subcellular localization of the CGN protein, abolishes its actin polymerization activity, and impairs the normal morphology of hair cell cuticular plates and hair bundles. Hair cell‐specific Cgn knockout leads to high‐frequency hearing loss. Importantly, Cgn mutation knockin mice display noise‐sensitive, progressive hearing loss and outer hair cell degeneration. In summary, we identify CGN c.3330delG as a pathogenic variant for ADNSHL and reveal essential roles of CGN in the maintenance of cochlear hair cell structures and auditory function.

Self-supervised learning has made significant progress in point cloud processing. Currently, the primary tasks of self-supervised learning, which include point cloud reconstruction and representation learning, are trained separately due to their structural differences. This separation inevitably leads to increased training costs and neglects the potential for mutual assistance between tasks. In this paper, a self-supervised method named PointUR-RL is introduced, which integrates point cloud reconstruction and representation learning. The method features two key components: a variable masked autoencoder (VMAE) and contrastive learning (CL). The VMAE is capable of processing input point cloud blocks with varying masking ratios, ensuring seamless adaptation to both tasks. Furthermore, CL is utilized to enhance the representation learning capabilities and improve the separability of the learned representations. Experimental results confirm the effectiveness of the method in training and its strong generalization ability for downstream tasks. Notably, high-accuracy classification and high-quality reconstruction have been achieved with the public datasets ModelNet and ShapeNet, with competitive results also obtained with the ScanObjectNN real-world dataset.

GaN Schottky diodes show great potential in high-power terahertz frequency multipliers. The thermal characteristics of GaN Schottky diodes with single and double-row anode arrangements are described in this paper. The temperature distribution inside the Schottky diode is discussed in detail under the coupling condition of Joule heat and solid heat transfer. The effects of different substrates and substrate geometric parameters on the thermal characteristics of the Schottky diode chips with single and double-row anode arrangements are systematically analyzed. Compared with that of the chip with single-row anode arrangement, the maximum temperature of the chip with double-row anode arrangement can be reduced by 40 K at the same conditions. For chips with different substrates, chips with diamond substrates can withstand greater power dissipation when reaching the same temperature. The simulation results are instructive for the design and optimization of Schottky diodes in the terahertz field.

Pulsating heat pipes (PHPs) are widely used in the heat dissipation of electronic components, waste heat recovery, solar energy utilization, etc., relying on the pulsating flow of the work material in the pipe and the heat transfer by phase change, and they have the advantages of high heat-transfer efficiency, simple structure, and low cost. In this paper, an experimental method is used to adjust the length of local pipes in the PHP structure, so that the PHP forms a high- and low-staggered asymmetric structure, and to study the effects of different liquid charging rates and heat-source temperatures on the vibration, startup, and operation of the PHP in the asymmetric structure. We found the following: it is difficult to start up and operate the workpiece at 10%, 68%, and 80% liquid charging rates; the effect of the oscillating impact is worse; the temperature difference between the evaporation section of the pulsating heat pipe and condensation section is larger; and the temperature difference between the evaporation section and condensation section is larger. The temperature difference between the evaporation section and condensation section of the pulsating heat pipe is large, the temperature difference is between 10~25 °C, and it is difficult to achieve a small temperature difference in heat transfer. When the liquid charging rate is 30% and 50%, the pulsating heat pipe oscillates better; the pulsation frequency is relatively high; and the temperature difference between the end of the cold and hot sections is small, the temperature difference is between 3 and 7 °C, and the performance of heat transfer is better. However, when the liquid charging rate is 30% and the heat source is 70 °C, the thermal resistance is increased to 0.016 K/W, and the equivalent thermal conductivity is reduced. When the performance of heat transfer is changed to 0.016 K/W and the equivalent thermal conductivity is reduced, the coefficient decreases, and the heat-transfer performance becomes weaker.

Potential inconsistencies between the goals of unsupervised representation learning and clustering within multi-stage deep clustering can diminish the effectiveness of these techniques. However, because the goal of unsupervised representation learning is inherently flexible and can be tailored to clustering, we introduce PointStaClu, a novel single-stage point cloud clustering method. This method employs stable cluster discrimination (StaClu) to tackle the inherent instability present in single-stage deep clustering training. It achieves this by constraining the gradient descent updates for negative instances within the cross-entropy loss function, and by updating the cluster centers using the same loss function. Furthermore, we integrate entropy constraints to regulate the distribution entropy of the dataset, thereby enhancing the cluster allocation. Our framework simplifies the process, employing a single loss function and an encoder for deep point cloud clustering. Extensive experiments on the ModelNet40 and ShapeNet dataset demonstrate that PointStaClu significantly narrows the performance gap between unsupervised point cloud clustering and supervised point cloud classification, presenting a novel approach to point cloud classification tasks.

Abstract Choroidal neovascularization (CNV) occurs in neovascular age-related macular degeneration (AMD) and often leads to permanent visual impairment. Intravitreal injection of anti-vascular endothelial growth factor (VEGF) agents is the gold standard for the treatment of CNV. However, anti-VEGF treatment did not always cause vision improvement and sometimes had detrimental effects on normal retinal tissues. Herein, we identified a novel retinoic acid drug, EYE-502, which had great therapeutic effects on CNV. Administration of EYE-502 could inhibit VEGF-induced dysfunction of endothelial cells (ECs) and reduce platelet-derived growth factor (PDGF)-induced recruitment of pericytes to ECs in vitro. Administration of EYE-502 could reduce the area of choroidal sprouting and laser-induced CNV, exhibiting similar anti-angiogenic effects as aflibercept. Moreover, administration of EYE-502 could reduce pericyte coverage in the sprouting vessels and choroidal neovascularization. Mechanistically, EYE-502 primarily bound to retinoic acid receptors (RARs) and exerted the anti-angiogenic effects by targeting ECs and pericytes via affecting the activation of Wnt/β-catenin and PDGF/PDGFR/PI3K/Akt signaling. Taken together, this study reports a novel retinoic acid drug, EYE-502, which can exert the anti-angiogenic effects by simultaneous targeting of ECs and pericytes.

The wind energy industry has expanded in recent years. Promotion of the Sustainable Development Goals (SDGs) is expected to further increase the scale of the wind energy industry. Determining the location and quantity of wind turbines is crucial for monitoring the development status of the wind energy industry and evaluating wind energy production. In this study, we propose a method for simultaneously detecting and positioning wind turbines in remote sensing images, namely, Wind Turbine YOLO (WT-YOLO), based on the You Only Look Once version 5 model (YOLOv5). The wind turbine hub, base, and shadow hub are treated as key points in the proposed method. Regression terms are incorporated into the head of the YOLOv5 basic framework to predict the location of these three key points. The base point is utilized to determine the exact position of the wind turbine. A multibackground and multiresolution wind-turbine image dataset is constructed by sampling high-resolution images from Google Earth. The WT-YOLO method outperforms existing methods in both wind turbine detection and positioning on different types of land cover backgrounds and multiresolution images of the constructed dataset. In the spatial resolution range of 0.6 m to 5.4 m, WT-YOLO exhibits enhanced wind-turbine detection, where the average precision (AP) is 5.92 % to 15.43 % higher than that of existing wind-turbine detection methods. Wind-turbine positioning by WT-YOLO has a mean distance error (MDE) that is 16.06 m to 21.59 m lower than that of existing wind-turbine positioning methods. A comparative analysis showed that the shadow and the three key points are effective features for wind-turbine detection. The proposed WT-YOLO model can support detection, positioning and counting for wind turbines worldwide.

The extent of human activity has expanded, and the intensity of human activity has increased, supported by a progressive economy and powerful technology. Compared with daytime remote sensing images or statistical data, nighttime light (NTL) remote sensing has the advantages of long time series, global coverage, objectivity, and quantifiability in observing the development of global human activities. Existing studies have focused more on the levels of human activity development at multiple points in time and less on overall patterns of human activity development during a period. We developed a non-parametric time-series curve morphology classification methodology combining trend analysis and change-point detection. We identified modes and phases of human activity development based on NTL datasets and analyzed the spatial and temporal patterns, modes, and phases of county-level human activity development globally over the past 30 years (1992–2021). We found that the level of human activity development is generally on the rise globally, with areas of significant growth mainly along the coast of China and in global ports. In more than half of the counties, the extent of human activity development is saturated. A significant increase mode was observed in most counties (71.5 %), while a few counties (1.1 %) saw a decrease mode. 10.1 % of global counties are in an anomalous phase, with low levels of human activity and slower or even stopped development. The new method has been validated in cases of different development modes and has the potential to generalize to the pixel level. Monitoring human activity development facilitates understanding development modes globally over a long time series, which can guide future policy formulation and socioeconomic progress. We recommend a greater focus on inequalities within and between countries.

Electroacupuncture (EA) at the Neiguan acupoint (PC6) has shown significant cardioprotective effects. Sympathetic nerves play an important role in maintaining cardiac function after myocardial infarction (MI). Previous studies have found that EA treatment may improve cardiac function by modulating sympathetic remodeling after MI. However, the mechanism in how EA affects sympathetic remodeling and improves cardiac function remains unclear. The aim of this study is to investigate the cardioprotective mechanism of EA after myocardial ischemic injury by improving sympathetic remodeling and promoting macrophage M2 polarization. We established a mouse model of MI by occluding coronary arteries in male C57/BL6 mice. EA treatment was performed at the PC6 with current intensity (1 mA) and frequency (2/15 Hz). Cardiac function was evaluated using echocardiography. Heart rate variability in mice was assessed via standard electrocardiography. Myocardial fibrosis was evaluated by Sirius red staining. Levels of inflammatory factors were assessed using RT-qPCR. Sympathetic nerve remodeling was assessed through ELISA, western blotting, immunohistochemistry, and immunofluorescence staining. Macrophage polarization was evaluated using flow cytometry. Our results indicated that cardiac systolic function improved significantly after EA treatment, with an increase in fractional shortening and ejection fraction. Myocardial fibrosis was significantly mitigated in the EA group. The sympathetic nerve marker tyrosine hydroxylase and the nerve sprouting marker growth-associated Protein 43 were significantly reduced in the EA group, indicating that sympathetic remodeling was significantly reduced. EA treatment also promoted macrophage M2 polarization, reduced levels of inflammatory factors TNF-α, IL-1β, and IL-6, and decreased macrophage-associated nerve growth factor in myocardial tissue. To sum up, our results suggest that EA at PC6 attenuates sympathetic remodeling after MI to promote macrophage M2 polarization and improve cardiac function.

In response to the challenge posed by the limited capacity of postmining paste and original waste filling mining technology for small-scale waste rock treatment, which is incompatible with the requirements of modern high-yield mines producing millions of tons, fluidized filling mining technology in goaf presents a sustainable and environmentally friendly solution. This innovative method effectively addresses the balance between mining and filling operations while enabling large-scale waste rock management in coal mines. This article presents a model for predicting the spatial morphology of goaf and employs theoretical calculations to determine the residual space left after goaf caving. It unveils the fluidization filling approach for goaf caving, utilizing a “high- and low-level collaborative filling” strategy and taking advantage of various types of residual spaces within cavities and voids. Experimental investigations into gangue slurry diffusion in the goaf reveal insights into its diffusion patterns along three directions: horizontal, inclined, and vertical. The analysis also establishes correlations between porosity, space utilization rate, and the Talbol index. Furthermore, the research identifies the flow characteristics of fluidized filling slurry as consistent with the Bingham fluid behavior. A calculation formula for determining the diffusion radius of the filling slurry within cracks is provided. The study highlights four distinct flow stages in the process: stable laminar diffusion, transition from advection to turbulence, turbulence, and stoppage. To validate these findings, COMSOL simulation software is employed to simulate and analyze the diffusion patterns of gangue slurry within the goaf. The research outcomes offer valuable theoretical insights into the postgangue fluidization goaf filling technology and serve as a technical reference for the design of coal-based solid waste fluidization filling processes.

Rapeseed mapping is important for national food security and government regulation of land use. Various methods, including empirical index-based and machine learning-based methods, have been developed to identify rapeseed using remote sensing. Empirical index-based methods commonly employed empirically designed indices to enhance rapeseed’s bright yellow spectral feature during the flowering period, which is straightforward to implement. Unfortunately, the heavy cloud cover in the flowering period of China would lead to serious omission errors; and the required flowering period varies spatially and yearly, which often cannot be acquired accurately. Machine learning-based methods mitigate the reliance on clear observations during the flowering period by inputting all-season imagery to adaptively learn features. However, it is difficult to collect sufficient samples across all of China considering the large intraclass variation in both land cover types of rapeseed and non-rapeseed. This study proposed an automated rapeseed mapping approach integrating rule-based sample generation and a one-class classifier (RSG-OC) to overcome the shortcomings of the two types of methods. First, a set of sample selection rules based on empirical indices of rapeseed were developed to automatically generate samples in cloud-free pixels during the predicted flowering period throughout China. Second, all available features composited based on the rapeseed phenological calendar were used for classification to eliminate the phenology differences in different regions. Third, a specific sample augmentation that removes the observation in the flowering period was employed to improve the generalization to the pixels without cloud-free observation in the flowering period. Finally, to avoid the need for diverse samples of nonrapeseed classes, a typical one-class classifier, positive unlabeled learning implemented by random forest (PUL-RF) trained by the generated samples, was applied to map rapeseed. With the proposed method, China rapeseed was mapped at 20 m resolution during 2017–2021 based on the Google Earth Engine (GEE). Validation on six typical rapeseed planting areas demonstrates that RSG-OC achieves an average accuracy of 94.90%. In comparison, the average accuracy of the other methods ranged from 83.33% to 88.25%, all of which were poorer than the proposed method. Additional experiments show that the performance of RSG-OC was not sensitive to cloud contamination, inaccurate predicted flowering time and the threshold of sample selection rule. These results indicate that the rapeseed maps produced in China are overall reliable and that the proposed method is an effective and robust method for annual rapeseed mapping across China.

Abstract Comprehensive and timely identification of vulnerable nodes is of great significance to ensure the security of the power system. With the development of power grids, traditional identification methods for vulnerable nodes with high operational risks can no longer meet the actual operation needs in terms of model accuracy, and it is prone to ignore some critical nodes. In view of this, a method based on graph deep learning is proposed for grid vulnerable nodes identification to realize fast and accurate identification of vulnerable nodes. Firstly, the GraphSAGE algorithm is used to aggregate the operation states of each node and its neighbours. The node attribute information and topology information are mapped to the output layer at the same time to form a comprehensive representation of the node state through non‐linear transformation. Then according to the similarity between the states, the improved K‐means algorithm is used to cluster the nodes so as to realize the identification of vulnerable nodes. The distances between the nodes and the vulnerability centre are calculated to rank the node vulnerabilities. Finally, the effectiveness and feasibility of the proposed method are verified by the simulation results of the IEEE 30‐bus system and a practical power system.

Negative Poisson's ratio (NPR) materials are a type of structural materials that show an atypical deformation response. In general, metal-based porous materials with NPR do not have good mechanical properties due to the substrate's limited yield strength and plasticity, as the NPR behavior is unlikely to play a continuous role in the deformation. AlCoCrFeNi2.1, a eutectic high-entropy alloy (EHEA) with high yield strength and high ductility was used to fabricate the NPR structures by laser powder bed fusion (LPBF) to enhance the structures mechanical properties and NPR behavior. Structures with four different sets of structural parameters were designed for this study. The microstructure and mechanical properties of AlCoCrFeNi2.1 EHEA, synthesized by LPBF were studied, and the strength and energy absorption effect of NPR porous structure materials were investigated by static and dynamic compression experiments. Research showed the large number of inter-phase interfaces provided by the nano-scale cellular eutectic microstructure effectively restrict dislocation movement, thereby enhancing the strength and toughness of this EHEA alloy, endowing it with superior impact resistance, fracture resistance, and mechanical energy absorption. The compressive performance and the mechanical energy absorption capacity of the 3D EHEA-based NPR porous structure strongly depend on the inclination angle Ф between the thick rod and the horizontal direction in the 2D single-body model design. The strength and energy absorption of the structure with a high inclination angle of 75° material are both higher than those of the structure with a low inclination angle of 45° by almost a factor of two.