Search

Abstract Background Both interpregnancy intervals (IPI) and environmental factors might contribute to low birth weight (LBW). However, the extent to which air pollution influences the effect of IPIs on LBW remains unclear. We aimed to investigate whether IPI and air pollution jointly affect LBW. Methods A retrospective cohort study was designed in this study. The data of birth records was collected from the Jiangsu Maternal Child Information System, covering January 2020 to June 2021 in Nantong city, China. IPI was defined as the duration between the delivery date for last live birth and date of LMP for the subsequent birth. The maternal exposure to ambient air pollutants during pregnancy—including particulate matter (PM) with an aerodynamic diameter of ≤ 2.5 μm (PM2.5), PM10, ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2) and carbon monoxide (CO)—was estimated using a hybrid kriging-LUR-RF model. A novel air pollution score was proposed, assessing combined exposure to five pollutants (excluding CO) by summing their concentrations, weighted by LBW regression coefficients. Multivariate logistic regression models were used to estimate the effects of IPI, air pollution and their interactions on LBW. Relative excess risk due to interaction (RERI), attributable proportion of interaction (AP) and synergy index (S) were utilized to assess the additive interaction. Results Among 10, 512 singleton live births, the LBW rate was 3.7%. The IPI-LBW risk curve exhibited an L-shaped pattern. The odds ratios (ORs) for LBW for each interquartile range increase in PM2.5, PM10, O3 and the air pollution score were 1.16 (95% CI: 1.01–1.32), 1.30 (1.06–1.59), 1.22 (1.06–1.41), and 1.32 (1.10–1.60) during the entire pregnancy, respectively. An additive interaction between IPI and PM2.5 was noted during the first trimester. Compared to records with normal IPI and low PM2.5 exposure, those with short IPI and high PM2.5 exposure had the highest risk of LBW (relative risk = 3.53, 95% CI: 1.85–6.49, first trimester). Conclusion The study demonstrates a synergistic effect of interpregnancy interval and air pollution on LBW, indicating that rational birth spacing and air pollution control can jointly improve LBW outcomes.

With the advancement of computer vision technology, vision-based target perception has emerged as a predominant approach for harvesting robots to identify and locate fruits. However, little attention has been paid to the fact that fruits may be obscured by stems or other objects. In order to improve the vision detection ability of fruit harvesting robot, a fruit target selection and location approach considering obstacle perception was proposed. To enrich the dataset for tomato harvesting, synthetic data were generated by rendering a 3D simulated model of the tomato greenhouse environment, and automatically producing corresponding pixel-level semantic segmentation labels. An attention-based spatial-relationship feature extraction module (SFM) with lower computational complexity was designed to enhance the ability of semantic segmentation network DeepLab v3+ in accurately segmenting linear-structured obstructions such as stems and wires. An adaptive K-means clustering method was developed to distinguish individual instances of fruits. Furthermore, a barrier-free fruit selection algorithm that integrates information of obstacles and fruit instances was proposed to identify the closest and largest non-occluded fruit as the optimal picking target. The improved semantic segmentation network exhibited enhanced performance, achieving an accuracy of 96.75%. Notably, the Intersection-over-Union (IoU) of wire and stem classes was improved by 5.0% and 2.3%, respectively. Our target selection method demonstrated accurate identification of obstacle types (96.15%) and effectively excluding fruits obstructed by strongly resistant objects (86.67%). Compared to the fruit detection method without visual obstacle avoidance (Yolo v5), our approach exhibited an 18.9% increase in selection precision and a 1.3% reduction in location error. The improved semantic segmentation algorithm significantly increased the segmentation accuracy of linear-structured obstacles, and the obstacle perception algorithm effectively avoided occluded fruits. The proposed method demonstrated an appreciable ability in precisely selecting and locating barrier-free fruits within non-structural environments, especially avoiding fruits obscured by stems or wires. This approach provides a more reliable and practical solution for fruit selection and localization for harvesting robots, while also being applicable to other fruits and vegetables such as sweet peppers and kiwis.

Abstract A bi‐level planning strategy of a hydrogen‐supercapacitor hybrid energy storage system (H‐S HESS) has been proposed in this study for wind power fluctuation suppression. The proposed system consists of a supercapacitor array and a hydrogen energy storage unit, and the bi‐level planning strategy consists of an Energy Management Level and a Capacity Configuration Level. In the upper level, with Hilbert–Huang transform frequency analysis, a novel energy management strategy based on adaptive power allocation (APA) is designed. The lower level applies multi‐objective Harris hawks optimizer to solve the optimal parameters of each device in the system. Based on the data measured from a 2‐MW wind system in a hydrogen‐electric coupled DC microgrid demonstration project, the optimal system capacity configuration scheme is obtained. The annualized cost of the system is $150,212, which is 41.1% lower than the scheme without optimization. The fluctuation unsuppressed rate of H‐S HESS is 0.64% under the APA strategy, which is only 0.14% higher than the conventional HESS (supercapacitor + lithium‐ion batteries) with the same annualized cost of system. The proposed strategy reduces the frequency of HESS operational power fluctuations, improves capacity configuration accuracy, and significantly decreases the cost gap between the proposed H‐S HESS and conventional structures.

Abstract Strategies to improve T cell therapy efficacy in solid tumors such as hepatocellular carcinoma (HCC) are urgently needed. The common cytokine receptor γ chain (γc) family cytokines such as IL-2, IL-7, IL-15 and IL-21 play fundamental roles in T cell development, differentiation and effector phases. This study aims to determine the combination effects of IL-21 in T cell therapy against HCC and investigate optimized strategies to utilize the effect of IL-21 signal in T cell therapy. The antitumor function of AFP-specific T cell receptor-engineered T cells (TCR-T) was augmented by exogenous IL-21 in vitro and in vivo. IL-21 enhanced proliferation capacity, promoted memory differentiation, downregulated PD-1 expression and alleviated apoptosis in TCR-T after activation. A novel engineered IL-21 receptor was established, and TCR-T armed with the novel engineered IL-21 receptors (IL-21R-TCR-T) showed upregulated phosphorylated STAT3 expression without exogenous IL-21 ligand. IL-21R-TCR-T showed better proliferation upon activation and superior antitumor function in vitro and in vivo. IL-21R-TCR-T exhibited a less differentiated, exhausted and apoptotic phenotype than conventional TCR-T upon repetitive tumor antigen stimulation. The novel IL-21 receptor in our study programs powerful TCR-T and can avoid side effects induced by IL-21 systemic utilization. The novel IL-21 receptor creates new opportunities for next-generation TCR-T against HCC.

Abstract Background Autophagy is a lysosome-dependent degradation pathway that regulates macrophage activation, differentiation, and polarization. Autophagy related 5 (Atg5) is a key protein involved in phagocytic membrane elongation in autophagic vesicles that forms a complex with Atg12 and Atg16L1. Alterations in Atg5 are related to both acute and chronic kidney diseases in experimental models. However, the role of macrophage-expressed Atg5 in acute kidney injury remains unclear. Methods Using a myeloid cell-specific Atg5 knockout (MΦ atg5 −/−) mouse, we established renal ischemia/reperfusion and unilateral ureteral obstruction models to evaluate the role of macrophage Atg5 in renal macrophage migration and fibrosis. Results Based on changes in the serum urea nitrogen and creatinine levels, Atg5 deletion had a minimal effect on renal function in the early stages after mild injury; however, MΦ atg5 −/− mice had reduced renal fibrosis and reduced macrophage recruitment after 4 weeks of ischemia/reperfusion injury and 2 weeks of unilateral ureteral obstruction injury. Atg5 deficiency impaired the CCL20-CCR6 axis after severe ischemic kidneys. Chemotactic responses of bone marrow-derived monocytes (BMDMs) from MΦ atg5 −/− mice to CCL20 were significantly attenuated compared with those of wild-type BMDMs, and this might be caused by the inhibition of PI3K, AKT, and ERK1/2 activation. Conclusions Our data indicate that Atg5 deficiency decreased macrophage migration by impairing the CCL20-CCR6 axis and inhibited M2 polarization, thereby improving kidney fibrosis.

Abstract Background Sufentanil-induced cough is common during the induction of anesthesia. The objective of this study was to determine whether pretreatment with a small dose of esketamine is effective in treating sufentanil-induced cough. Methods 220 patients were screened, and 200 patients who had scheduled elective surgery and were between 18 and 70 years old were randomly divided into two groups. Before sufentanil was administered, esketamine group (group K) was injected with 0.15 mg/kg esketamine at 5 s, and control group (group C) was administered with the same volume. Within 1 min after sufentanil(0.4ug/kg) injection during induction, cough incidence and severity were evaluated. After sufentanil was injected, we recorded its hemodynamic changes and side effects. Results In the esketamine group (group K) and control group (group C), there was an incidence of cough of 5 and 34%, respectively. The esketamine group (group K) had a significantly lower incidence and severity of cough compared to the control group (group C) immediately after sufentanil injection (P 0.05). Conclusion In our study, we found that sufentanil-induced cough was significantly reduced by pretreatment with 0.15 mg/kg esketamine, but with no significant changes in the hemodynamic status. Trial registration Chinese Clinical Trial Registry (ChiCTR2200063821, registered date: 17/09/2022), http://www.chictr.org.cn

The application of machine learning (ML) techniques to climate science has received significant attention, particularly in the field of climate predictions, ranging from sub-seasonal to decadal time scales. This paper reviews recent progress of ML techniques employed in climate phenomena prediction and the enhancement of dynamic forecast models, which provide valuable insights into the great potentials of ML techniques to improve climate prediction capabilities with reduced computational time and resource consumption. This paper also discusses several major challenges in the application of ML to climate prediction, including the scarcity of datasets, physical inconsistency, and lack of model transparency and interpretability. Additionally, this paper sheds light on how climate change impacts ML model training and prediction, and explores three key areas with potential breakthroughs: large-scale climate models, knowledge discovery driven by ML, and hybrid dynamical-statistical models, underscoring the important role of the integration of “ML and dynamical models” in building a bridge between the artificial intelligence and climate science.

Rosa persica is considered a clonal plant because it is mainly propagated by clonal growth. Due to environmental degradation and habitat devastation, R. persica has been listed as a national second-class protected plant in China. However, the absence of research on wild populations of R. persica has impeded progress in formulating efficient conservation strategies. In this study, we investigated the clonal dispersal distance of R. persica to accurately determine the genetic diversity and population structure of the wild population in Xinjiang. We suggested that 20 m was the threshold distance with which to distinguish between different genets of plants. Based on this, we collated sequencing data from a total of 70 different genets of plants from 117 test samples. Eight populations of R. persica were primarily categorized into three subgroups: BL (Bole), TC (Tacheng) and CG (Changji). Of these, the CG subgroup exhibited the most genetic diversity. This research is the first to illustrates the clonal dispersal distance of R. persica, thus providing valuable reference guidelines for understanding the reproductive characteristics of clonal plants. In addition, the genetic diversity of R. persica provides a theoretical foundation for the formulation of conservation policies.

Abstract In July and August 2022, the Yangtze River basin (YRB) experienced its hottest summer since 1961. The SINTEX‐F2 seasonal prediction system initialized in early May predicted the hotter‐than‐normal summer due to its successful prediction of central Pacific La Niña, negative Indian Ocean Dipole and the resultant warming in the tropical West Pacific‐East Indian Ocean (TWP_EIO). The common SST forcing explains only about 26% to the heatwave strength, while the internal variations in the anomalous warming in the TWP_EIO and Europe, surplus precipitation in Pakistan, and local land‐air interaction account for approximately 65%, based on the analysis of 108 ensemble members. These factors have collectively increased the maximum temperature over the YRB through the enhancement and westward expansion of western North Pacific subtropical high. Our findings quantify the relative contributions of external forcing and internal variations to the unprecedented hot event, offering insights into its forming mechanism and potential predictability.

Brain diseases, encompassing neurodegenerative disorders, strokes, and brain tumors, represent significant medical conditions with profound implications for human health. The blood-brain barrier (BBB) and the blood-cerebral-spinal cord barrier (BCSFB) limited drug penetration, poor drug targeting, and limited proliferation and easy death of mature neuronal cells greatly impair regeneration of the central nervous system after the injury, and thus call for more advanced therapeutic strategies in the clinic. Biomedical hydrogel research presents a potentially novel therapeutic approach for the management of brain disorders. Hydrogels are extremely biocompatible scaffolding materials that can be loaded with a variety of drugs for achieving effective treatments for brain disorders and can be customized with different mechanical properties to match the target organ or modulate its environment. This article offers an overview of recent research progress, challenges, and prospective developments in the utilization of hydrogels for treating brain disorders, with the objective of accentuating their potential as an early intervention in the preclinical phase. The unique mechanisms of drug release in hydrogels are examined in detail: extended-release medications, environmental release of drugs, and the material's own activity. An understanding of these mechanisms helps to make more effective drug delivery systems to the brain possible.

Oomycete pathogens secrete numerous crinkling and necrosis proteins (CRNs) to manipulate plant immunity and promote infection. However, the functional mechanism of CRN effectors is still poorly understood. Previous research has shown that the Phytophthora sojae effector PsCRN108 binds to the promoter of HSP90s and inhibits their expression, resulting in impaired plant immunity. In this study, we found that in addition to HSP90, PsCRN108 also suppressed other Heat Shock Protein (HSP) family genes, including HSP40. Interestingly, PsCRN108 inhibited the expression of NbHSP40 through its promoter, but did not directly bind to its promoter. Instead, PsCRN108 interacted with NbCAMTA2, a negative regulator of plant immunity. NbCAMTA2 was a negative regulator of NbHSP40 expression, and PsCRN108 could promote such inhibition activity of NbCAMTA2. Our results elucidated the multiple roles of PsCRN108 in the suppression of plant immunity and revealed a new mechanism by which the CRN effector hijacked transcription factors to affect immunity. [Graphic: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

This study investigates the pile foundation of a nuclear power plant situated on medium-soft soil. It employs an improved viscoelastic artificial boundary unit to accurately simulate the boundary conditions of the calculation area. The research utilizes a constitutive model of concrete damage plasticity for the pile foundation and an equivalent linearized model for the soil layer. Through large-scale shaking table experiments and numerical simulations, we explore the internal force distribution within the nuclear power structure’s pile foundation and assess the extent of the damage. The results indicate that damage primarily occurs in the medium-soft ground, concentrating in the upper part of the pile and affecting the entire cross-section. Subsequent numerical analyses were conducted after reinforcing the soil layer around the top of the pile. The findings demonstrate that this reinforcement leads to a more uniform and rational distribution of internal forces along the pile, significantly reducing damage. Notably, there is no severe damage extending across the entire cross-section after reinforcement. This outcome highlights the potential for improving the force distribution in the pile foundations of nuclear power structures through appropriate soil layer reinforcement. The insights gained from this study provide valuable guidance for the seismic design of nuclear power structures.

Raindrop size distribution (DSD) has an essential effect on rainfall kinetic energy estimation (RKEE) and dual-polarization radar quantitative precipitation estimation (QPE); DSD is a key factor for establishing a dual-polarization radar QPE scheme and RKEE scheme, particularly in mountainous areas. To improve the understanding of seasonal DSD-based RKEE, dual-polarization radar QPE, and the impact of rainfall types and classification methods, we investigated RKEE schemes and dual-polarimetric radar QPE algorithms across seasons and rainfall types based on two classic classification methods (BR09 and BR03) and DSD data from a disdrometer in the Tianshan Mountains during 2020–2022. Two RKEE schemes were established: the rainfall kinetic energy flux–rain rate (KEtime–R) and the rainfall kinetic energy content–mass-weighted mean diameter (KEmm–Dm). Both showed seasonal variation, whether it was stratiform rainfall or convective rainfall, under BR03 and BR09. Both schemes had excellent performance, especially the KEmm–Dm relationship across seasons and rainfall types. In addition, four QPE schemes for dual-polarimetric radar—R(Kdp), R(Zh), R(Kdp,Zdr), and R(Zh,Zdr)—were established, and exhibited characteristics that varied with season and rainfall type. Overall, the performance of the single-parameter algorithms was inferior to that of the double-parameter algorithms, and the performance of the R(Zh) algorithm was inferior to that of the R(Kdp) algorithm. The results of this study show that it is necessary to consider different rainfall types and seasons, as well as classification methods of rainfall types, when applying RKEE and dual-polarization radar QPE. In this process, choosing a suitable estimator—KEtime(R), KEmm(Dm), R(Kdp), R(Zh), R(Kdp,Zdr), or R(Zh,Zdr)—is key to improving the accuracy of estimating the rainfall KE and R.

Background: Family involvement and comfort are equally important in palliative care. Dignity undertook a new meaning and novel challenges as a result of restrictions on visits and companionship during the pandemic. Family-centered family dignity interventions have been shown to be effective in increasing patients’ sense of dignity, increasing levels of hope, and reducing psychological distress; however, the effectiveness in enhancing family adaptability and intimacy in the survivor-caregiver binary and reducing expected grief have been inconclusive. Objectives: The primary objective of this study was to assess the efficacy of family dignity interventions on family adaptability and cohesion. The secondary objective was to explore the effects of the interventions on anticipatory grief and psychological distress, and the lasting effect 1 month after the intervention. Design: A single-blinded, two-arm parallel group, randomized controlled trial was conducted in China. Settings: and methods: Ninety-eight dyads who met the inclusion criteria were randomly assigned to the family dignity intervention (n = 51) or standard palliative care group (n = 47) between June and August 2022. Study outcomes were measured at baseline, immediately post-intervention, and at the 1-month follow-up post-intervention evaluation. Data were analyzed using the Kolmogorov-Smirnov test, chi-square test, Fisher's exact test, independent sample t-test, Wilcoxon rank-sum test, and generalized estimation equations. The Intention-To-Treat analysis was performed for all available data. Results: In comparison to the control group, significant improvements in family adaptability and cohesion and anticipatory grief over post-intervention and 1-month follow-up were demonstrated among the patients in the intervention group. The intervention group of caregivers had significant improvement in anticipatory grief at post-intervention and 1-month follow-up. The level of psychological distress was significantly lower in the intervention group than the control group (p

This study aimed to dynamically track the priorities and potential research hotspots in the field of heart failure with sarcopenia. Using CiteSpace, we analyzed the literature on heart failure with sarcopenia from the Web of Science database from 1995 to 2022. The analysis encompassed 507 records, revealing an overall upward trend in annual publication volume. Europe and the United States emerged as the primary regions for publishing, particularly driven by contributions from developed countries such as the United States, Germany, and Italy. Productive institutions included the Charite Universitatsmedizin Berlin, University Medical Center Gottingen, the German Center for Cardiovascular Research (DZHK), Universita Cattolica del Sacro Cuore, and the National Institute on Aging (NIA). Noteworthy academic groups have formed around these institutions; von Haehling S, Anker Stefan D, Springer J, and Doehner W frequently collaborated. The core journals that frequently published articles in this area included Circulation, European Heart Journal, and The Journals of Gerontology Series A-Biological Sciences and Medical Sciences.Based on the keyword analysis, we identified three key research areas. First, the diagnosis and definition of sarcopenia emerged as significant themes. Second, researchers have focused on exploring the mechanisms underlying heart failure with sarcopenia, including inflammation, insulin resistance, and oxidative stress. Finally, treatment strategies, such as physical activity and nutritional support, constitute another critical research theme. Furthermore, potential research hotspots within this field include clinical randomized controlled trials, investigations into inflammatory mechanisms, cardiac rehabilitation, studies on physical activity, androgen receptor modulators, and investigations into clinical outcomes such as cognitive impairment.

Summary: Background: Diabetic kidney disease (DKD) is a leading cause of end-stage kidney disease and is associated with high mortality rates. The influence of routine clinical parameters on DKD onset in patients with type 2 diabetes mellitus (T2DM) remains uncertain. Methods: In this systematic review and meta-analysis, we searched multiple databases, including PubMed, Embase, Scopus, Web of Science, and Cochrane Library, for studies published from each database inception until January 11, 2024. We included cohort studies examining the association between DKD onset and various clinical parameters, including body mass index (BMI), hemoglobin A1c (HbA1c), systolic blood pressure (SBP), diastolic blood pressure (DBP), total cholesterol (TC), triglycerides (TG), low-density lipoprotein (LDL), high-density lipoprotein (HDL), and serum uric acid (UA). Random-effect dose–response meta-analyses utilizing one-stage and/or cubic spline models, were used to estimate correlation strength. This study is registered in PROSPERO (CRD42022326148). Findings: This analysis of 46 studies involving 317,502 patients found that in patients with T2DM, the risk of DKD onset increased by 3% per 1 kg/m2 increase in BMI (relative risk (RR) = 1.03, confidence interval (CI) [1.01–1.04], I2 = 70.07%; GRADE, moderate); a 12% increased risk of DKD onset for every 1% increase in HbA1c (RR = 1.12, CI [1.07–1.17], I2 = 94.94%; GRADE, moderate); a 6% increased risk of DKD onset for every 5 mmHg increase in SBP (RR = 1.06. CI [1.03–1.09], I2 = 85.41%; GRADE, moderate); a 2% increased risk of DKD onset per 10 mg/dL increase in TG (RR = 1.02, CI [1.01–1.03], I2 = 78.45%; GRADE, low); an 6% decreased risk of DKD onset per 10 mg/dL increase in HDL (RR = 0.94, CI [0.92–0.96], I2 = 0.33%; GRADE, high), and a 11% increased risk for each 1 mg/dL increase in UA (RR = 1.11, CI [1.05–1.17], I2 = 79.46%; GRADE, moderate). Subgroup analysis revealed a likely higher risk association of clinical parameters (BMI, HbA1c, LDL, and UA) in patients with T2DM for less than 10 years. Interpretation: BMI, HbA1c, SBP, TG, HDL and UA are potential predictors of DKD onset in patients with T2DM. Given high heterogeneity between included studies, our findings should be interpreted with caution, but they suggest monitoring of these clinical parameters to identify individuals who may be at risk of developing DKD. Funding: Shenzhen Science and Innovation Fund, the Hong Kong Research Grants Council, and the HKU Seed Funds, and Scientific and technological innovation project of China Academy of Chinese Medical Sciences.

In order to deepen the knowledge of the seasonal variation in total cloud cover (TCC) in Xinjiang, China (XJ), a typical arid region, and to broaden the understanding of the seasonal variation in cloud type (CLT) in the region, we used TCC and CLT datasets from the latest generation of the geostationary satellite Fengyun 4A (FY-4A) from 2018 to 2022 to investigate the seasonal variation characteristics of TCC and CLT in XJ. Meanwhile, to verify the accuracy of TCC from FY-4A, ground observation (GROB) TCC datasets from 105 national meteorological stations (NMSs) in XJ and TCC datasets from ERA5 during the same period were used. In addition, the correlation between TCC from FY-4A and meteorological factors from ERA5 was also analyzed in this study. The TCC from FY-4A, GROB, and ERA5 can all well reflect the significant seasonal variation in TCC in XJ, with the highest (lowest) mean TCC and a distribution pattern of high in the southwest (northwest) and low in the northeast (southeast) in spring (fall) in XJ. Although the mean TCC from FY-4A in all four seasons was lower than that from GROB, the two were comparable in spring (44.09% and 47.32%) and summer (42.88% and 43.17%), while there was a significant difference between the two in fall (27.86% and 40.19%) and winter (30.58% and 46.93%) for 105 NMSs in XJ. The TCC from FY-4A was lower (higher) than that from GROB in spring and summer at most NMSs in northern (southern) XJ, while the TCC from FY-4A was lower than that from GROB for the vast majority of NMSs in fall and winter, especially in northern XJ. The seasonal variation in the spatial distribution of different CLTs (clear, water-type, supercooled-type, mixed-type, ice-type, cirrus-type, and overlap-type) from FY-4A exhibited diverse variation characteristics. Water-type (supercooled-water-type) had a high-frequency center of over 30% in the Tarim Basin (Kunlun Mountains) during summer. Mixed-type (ice-type and cirrus-type) had the highest frequency in winter (spring), while overlap-type had the highest frequency in summer. The correlation between TCC and water vapor conditions (total column vertically integrated water vapor, specific humidity at 250 hPa, 500 hPa, and 700 hPa) was positive in XJ.

Knowledge graphs (KGs) often suffer from incompleteness. Knowledge graph completion (KGC) is proposed to complete missing components in a KG. Most KGC methods focus on direct relations and fail to leverage rich semantic information in multi-hop paths. In contrast, path-based embedding methods can capture path information and utilize extra semantics to improve KGC. However, most path-based methods cannot take advantage of full multi-hop information and neglect to capture multiple semantic associations between single and multi-hop triples. To bridge the gap, we propose a novel path-enhanced joint learning approach called PEJL for KGC. Rather than learning multi-hop representations, PEJL can recover multi-hop embeddings by encoding full multi-hop components. Meanwhile, PEJL extends the definition of translation energy functions and generates new semantic representations for each multi-hop component, which is rarely considered in path-based methods. Specifically, we first use the path constraint resource allocation (PCRA) algorithm to extract multi-hop triples. Then we use an embedding recovering module consisting of a bidirectional gated recurrent unit (GRU) layer and a fully connected layer to obtain multi-hop embeddings. Next, we employ a KG modeling module to leverage various semantic information and model the whole knowledge graph based on translation methods. Finally, we define a joint learning approach to train our proposed PEJL. We evaluate our model on two KGC datasets: FB15K-237 and NELL-995. Experiments show the effectiveness and superiority of PEJL.

The recovery of valuable metals from waste battery materials and the thermal decomposition of PVC both require significant energy and material consumption. In this study, we propose an innovative strategy that integrates the lithium extraction process from spent LiNi0.85Co0.15Al0.05O2 (S-NCA) with PVC pyrolysis, resulting in a substantial reduction in energy consumption and chemical additive. Various characterization techniques, including SEM, TEM, XRD, and XPS, are employed to investigate the mechanism of gas-solid lithium extraction and provide valuable insights into the migration pathway of lithium from S-NCA to soluble LiCl. The optimal conditions for the process were determined as follows: a temperature of 600 °C, S-NCA/PVC mass ratio of 1:4, and a baking time of 2 h, achieving a lithium extraction efficiency of 94.37 %. The research provides valuable insights for the valorization of PVC thermal decomposition and lithium extraction from NCA, presenting a novel approach for future applications.

Abstract Background Rosai–Dorfman disease (RDD) is a rare form of non-Langerhans cell histiocytic disease. The aim of this study was to review the characteristics of RDD using 18F-FDG PET/CT and determine its efficacy in the disease management. Results A total of 28 RDD patients underwent 33 18F-FDG PET/CT scans for systematic assessment and follow-up. The common involved sites included the lymph nodes (17, 60.7%), upper respiratory tract (11, 39.3%), and skin (9, 32.1%). Five patients had more lesions detected in PET/CT images than in CT and/or MRI, including inapparent nodules (n = 5) and bone destruction (n = 3). After thorough treatment evaluation using PET/CT, the treatment strategies of 14 patients (14/16, 87.5%) were changed. Five patients underwent PET/CT twice during follow-up and the SUVs were significantly decreased (15.3 ± 3.4 vs. 4.4 ± 1.0, p = 0.02), which demonstrated disease improvement. Conclusions 18F-FDG PET/CT contributed to displaying the holistic characteristics of RDD, in particular during initial assessment, treatment strategy adjustment, or efficacy evaluation, and could compensate for some disadvantages of CT and MRI images.

The quality of sintered ore, which serves as the primary raw material for blast furnace ironmaking, is directly influenced by the moisture in the sintering mixture. In order to improve the precision of water addition in the sintering process, this paper proposes an intelligent model for predicting water-filling volume based on Temporal Fusion Transformer (TFT), whose symmetry enables it to effectively capture long-term dependencies in time series data. Utilizing historical sintering data to develop a prediction model for the amount of mixing and water addition, the results indicate that the TFT model can achieve the R squared of 0.9881, and the root mean square error (RMSE) of 3.5951. When compared to the transformer, long short-term memory (LSTM), and particle swarm optimization–long short-term memory (PSO-LSTM), it is evident that the TFT model outperforms the other models, improving the RMSE by 8.5403, 6.9852, and 0.453, respectively. As an application, the TFT model provides an effective interval reference for moisture control in normal sintering processes, which ensures that the error is within 1 t.

Pulsed laser deposition (PLD) is a simple and extremely versatile technique to grow thin films and nanomaterials from a wide variety of materials. Compared to traditional fabrication methods, PLD is a clean physical vapour deposition approach that avoids complicated chemical reactions and by-products, achieving a precise stochiometric transfer of the target material onto the substrate and providing control over the film thickness. Halide perovskite materials have attracted extensive attention due to their excellent photoelectric and photovoltaic properties. In this paper, we present an overview of the fundamental and practical aspects of PLD. The properties and preparation methods of the halide perovskite materials are briefly discussed. Finally, we will elaborate on recent research on the preparation of perovskite solar cells by PLD, summarize the advantages and disadvantages of the PLD preparation, and prospect the all-vacuum PLD-grown solar cells in a full solar cell structure.

Knowledge graph completion (KGC) has attracted significant research interest in applying knowledge graphs (KGs). Previously, many works have been proposed to solve the KGC problem, such as a series of translational and semantic matching models. However, most previous methods suffer from two limitations. First, current models only consider the single form of relations, thus failing to simultaneously capture the semantics of multiple relations (direct, multi-hop and rule-based). Second, the data-sparse problem of knowledge graphs would make part of relations challenging to embed. This paper proposes a novel translational knowledge graph completion model named multiple relation embedding (MRE) to address the above limitations. We attempt to embed multiple relations to provide more semantic information for representing KGs. To be more specific, we first leverage PTransE and AMIE+ to extract multi-hop and rule-based relations. Then, we propose two specific encoders to encode extracted relations and capture semantic information of multiple relations. We note that our proposed encoders can achieve interactions between relations and connected entities in relation encoding, which is rarely considered in existing methods. Next, we define three energy functions to model KGs based on the translational assumption. At last, a joint training method is adopted to perform KGC. Experimental results illustrate that MRE outperforms other baselines on KGC, demonstrating the effectiveness of embedding multiple relations for advancing knowledge graph completion.

Abstract Lignin is a promising alternative to traditional fossil resources for producing biofuels due to its aromaticity and renewability. Pyrolysis is an efficient technology to convert lignin to valuable chemicals, which is beneficial for improving lignin valorization. In this review, pyrolytic behaviors of various lignin were included, as well as the pyrolytic mechanism consisting of initial, primary, and charring stages were also introduced. Several parallel reactions, such as demethoxylation, demethylation, decarboxylation, and decarbonylation of lignin side chains to form light gases, major lignin structure decomposition to generate phenolic compounds, and polymerization of active lignin intermediates to yield char, can be observed through the whole pyrolysis process. Several parameters, such as pyrolytic temperature, time, lignin type, and functional groups (hydroxyl, methoxy), were also investigated to figure out their effects on lignin pyrolysis. On the other hand, zeolite-driven lignin catalytic pyrolysis and lignin co-pyrolysis with other hydrogen-rich co-feedings were also introduced for improving process efficiency to produce more aromatic hydrocarbons (AHs). During the pyrolysis process, phenolic compounds and/or AHs can be produced, showing promising applications in biochemical intermediates and biofuel additives. Finally, some challenges and future perspectives for lignin pyrolysis have been discussed.

Microbial production of cannabinoids promises a cheaper and more sustainable route to these important therapeutic molecules, but strain improvement and screening is challenging. Here, the authors develop a yeast-based Δ9-tetrahydrocannabinol (THC) biosensor for screening microbial mutant libraries.

Profound research on the characteristics of the long-term persistence of wind is greatly significant for understanding the characteristics of wind speed mechanisms as well as for avoiding disasters caused by wind. In the current study, we selected the hourly 10 min wind speed series between 2017 and 2021 from 105 nation-level meteorological stations in Xinjiang and investigated the spatiotemporal variations in the long-term persistence of wind speed in different regions of Xinjiang and in different seasons using detrended fluctuation analysis. The main findings are as follows: (1) The wind speed in Xinjiang shows noticeable annual and seasonal variations, exhibiting satisfactory long-term sustainability. Winter has the best long-term sustainability, followed sequentially by spring, autumn, and summer because of wind speed stability. (2) The long-term persistence of hourly wind speed in Xinjiang exhibits remarkable regionality, with regions with strong wind superior to the remaining regions. (3) The long-term persistence of wind speed within the same season is primarily associated with wind speed magnitude and the dispersion degree between 90% and 100% of the wind speed numerical values. A higher wind speed indicates better long-term persistence. At the same speed, the more discrete the numerical values in the 90–100% distribution range, the better the persistence.

Ulcerative colitis (UC), a type of inflammatory bowel disease characterized by recurring and incurable symptoms, causes immense suffering and economic burden for patients due to the limited treatment options available. Therefore, it is imperative to develop novel and promising strategies, as well as safe and effective drugs, for the clinical management of UC. Macrophages play a critical role as the initial line of defense in maintaining intestinal immune homeostasis, and their phenotypic transformation significantly influences the progression of UC. Scientific studies have demonstrated that directing macrophage polarization toward the M2 phenotype is an effective strategy for the prevention and treatment of UC. Phytochemicals derived from botanical sources have garnered the interest of the scientific community owing to their distinct bioactivity and nutritional value, which have been shown to confer beneficial protective effects against colonic inflammation. In this review, we explicated the influence of macrophage polarization on the development of UC and collated data on the significant potential of natural substances that can target the macrophage phenotype and elucidate the possible mechanism of action for its treatment. These findings may provide novel directions and references for the clinical management of UC.

Lithium-ion batteries (LIBs) account for the majority of energy storage devices due to their long service life, high energy density, environmentally friendly, and other characteristics. Although the cathode materials of LIB led by LiFePO4 (LFP), LiCoO2 (LCO), and LiNixCoyMn1-x-yO2 (NCM) occupy the majority of the market share at present, the demand of LiMn2O4 (LMO) cathode battery is also increasing year by year in recent years. With the rising price of various raw materials of LIBs and the need of environmental protection, the efficient recycling of spent LIBs has become a hot research topic. At present, the recycling of spent LIBs mainly focuses on LFP, LCO, and NCM batteries. However, with the continuous improvement of people’s safety of LIBs, LiMnxFe1-xPO4 (LMFP) batteries show better potential, which also improves the recycling value of LMO batteries. Therefore, this paper reviews current methods of spent LMO recovery, focusing on the characteristics of the recovery and separation process, which can serve as a reference for subsequent research on LMO recovery, increasing environmentally friendly recovery routes. Finally, the future development direction of LIBs recycling is prospected. Overall, this review is helpful to understand the current progress of LMO battery recycling.

Human papillomavirus (HPV) vaccine uptake remains low in China, especially among girls. Recently, China has initiated a pilot program on HPV immunization for girls aged 9–14 years. We conducted a cross-sectional online survey in Minhang district of Shanghai, a pilot region for the program, to investigate HPV vaccination status among mothers and their daughters 9–14. A total of 1031 parents and 1122 daughters 9–14 were included. Of them, 18.6% of mothers and 4.5% of daughters had been vaccinated with HPV vaccines or made an appointment; additionally, 62.7% and 78.4% intended to receive vaccination but did not make an appointment. Notably, 6.2% of parents did not intend to receive vaccination for themselves (or their wives) but intended to vaccinate their daughters. Moreover, we calculated parental knowledge and awareness scores toward HPV infection and vaccination. Both scores were significantly higher among the parents who had received HPV vaccination than those who intended to across mothers’ vaccination status (P

Precipitation in the Tianshan Mountains is abundant, and the quantitative estimation of precipitation in mountainous areas is important to the application and evaluation of regional water resources. With remote sensing technology, satellite inversion of precipitation can estimate precipitation in mountainous areas. However, the Tianshan Mountain terrain is complex, and the spatiotemporal variation in precipitation is large, so the accuracy of satellite precipitation inversion is not high. Here, precipitation data from around 1000 automatic weather stations in the Tianshan Mountains are used to study the correction technology of the Integrated Multisatellite Retrievals for the Global Precipitation Measurement (GPM) mission’s (IMERG) monthly precipitation products using stepwise regression (STEP), geographically weighted regression (GWR), and random forest (RF). First, geographic information system technology was used to extract topographic variables from a digital elevation model, and vegetation indexes, which are important precipitation indicators, were introduced as explanatory factors to correct satellite precipitation data. Second, GPM IMERG precipitation was corrected by establishing the stepwise regression, the geographically weighted regression model, and the random forest model. The three correction methods can improve the GPM IMERG in terms of relative bias, root mean square error, correlation coefficient, and Nash–Sutcliffe efficiency, while the random forest method shows better corrections than the two traditional methods. For dense rainfall stations, the geographically weighted regression method is as effective as random forest. For different altitudes, the results show that RF has the best correction effect in the first three zones, but the correction effect in the last zone (over 3000 m) is worse than STEP. This study provides a practical reference method for estimating precipitation data in the non-rainfall observation area, which helps to deepen the scientific understanding of the water resource distribution in the Tianshan Mountains and provide scientific data support for regional hydrological and meteorological research.

Abstract Phytophthora cactorum is a devastating pathogen that infects a wide range of plants and causes Phytophthora rot disease, which has resulted in great economic losses in crop production. Therefore, the rapid and practicable detection of P. cactorum is important for disease monitoring and forecasting. In this study, we developed a lateral flow recombinase polymerase amplification (LF-RPA) assay for the sensitive visual detection of P. cactorum. Specific primers for P. cactorum were designed based on the ras-related protein gene Ypt1; all 10 P. cactorum isolates yielded positive detection results, whereas no cross-reaction occurred in related oomycete or fungal species. The detection limit for the LF-RPA assay was 100 fg of genomic DNA under optimized conditions. Combined with a simplified alkaline lysis method for plant DNA extraction, the LF-RPA assay successfully detected P. cactorum in naturally diseased strawberry samples without specialized equipment within 40 min. Thus, the LF-RPA assay developed in this study is a rapid, simple, and accurate method for the detection of P. cactorum, with the potential for further application in resource-limited laboratories.

Introduction and spread of the halophyte Spartina alterniflora is one of the largest continental-scale biological invasion events in Asia and the Americas. Rapid globalization and broad environmental tolerance of the species increase the chance of novel invasions. Thus, we aimed to identify susceptible regions to inform prevention and control activities.A comprehensive global occurrence dataset and corresponding bioclimatic variables were used to characterize the species' climatic niche and predict current and future potential distributions. Conservatism of climatic niche between native and non-native ranges was tested, and climatic niche dynamics were analysed at spatial and temporal scales. The ensemble of eight species distribution models and eight climate change models was used to map the potential distribution of S. alterniflora under current and future climate conditions. We investigated the susceptibility of threatened ecosystems like mangroves and protected areas to S. alterniflora invasion to better inform management decisions.Our study revealed wide climatic tolerance and significant niche expansion of the species from humid regions of its native range to dry and arid environments of its non-native range with a very short lag period. With a marginal increase in temperature and precipitation in the future, range expansion was predicted towards higher latitude and more inland areas. The mangroves area, salt marshes, and protected areas that are at risk of ongoing and future invasions were identified. Given the invasion potential of S. alterniflora, the areas identified as climatically susceptible for the species’ establishment, both in current and future climates, should be prioritized for management actions.

Myeloid differentiation factor 88 (MyD88) is a key adapter molecule in Toll-like receptor signal transduction that triggers downstream immune cascades involved in the host defense response to exogenous pathogens. However, the function of MyD88s in mollusks, especially in freshwater shellfish, remains poorly understood. In this study, a novel freshwater shellfish MyD88 (denoted AwMyD88) was characterized from Anodonta woodiana. The present AwMyD88 protein consists of 474 amino acids and contains a conserved a typical death domain (DD) and a conservative Toll/IL-1R (TIR) domain with three typical boxes. Quantitative real-time PCR (qRT-PCR) analysis showed that AwMyD88 was broadly expressed in all the examined tissues, and the highest expression level was observed in hemocytes of A. woodiana. When challenged with Aeromonas hydrophila and lipopolysaccharide (LPS), the mRNA expression levels of AwMyD88 were significantly induced in hemocytes of A. woodiana in vivo and in vitro. In addition, in vivo injection experiments revealed that MyD88 signaling pathway genes showed strong responsiveness to A. hydrophila challenge, and their expression levels were significantly upregulated in hemocytes. Knockdown of AwMyD88 reduced the transcript levels of immune related transcription factors (AwNF-κB and AwAP-1) and effectors (AwTNF, AwLYZ, AwDefense and AwAIF) during A. hydrophila infection. Moreover, subcellular localization analysis indicated that AwMyD88 was mainly localized to the cytoplasm in HEK293T cells. Finally, luciferase reporter assays revealed that AwMyD88 associates with AwTLR to activate the NF-κB and AP-1 signaling pathways in HEK293T cells. These results suggested that AwMyD88 might be involved in the host defense response to bacterial challenge, providing new insight into the immune function of the MyD88 signaling pathway in freshwater shellfish.

Abstract Background MicroRNAs (miRNAs) play an important role in tumor occurrence. The role of miR-378a-5p and CDK1 in colorectal cancer (CRC) was investigated in this study. Methods Investigation of TCGA database and the detection of miR-378a-5p expression in colorectal cancer pathological tissues and colorectal cancer cell lines were undertaken by using qRT-PCR. We performed cell function experiments (CCK-8 assay, EdU assay, colony formation assay, wound healing assay, transwell assay, cell apoptosis assessment, and cell cycle assessment) and nude mouse tumor formation experiments to evaluate the effects of miR-378a-5p on proliferation, metastasis, and invasion to explore the role of miR-378a-5p in vivo and in vitro. Next, through TCGA database, immunohistochemical staining of pathological tissues, and cell function experiments, the role of the target gene CDK1 of miR-378a-5p was verified by database prediction, and dual luciferase reporter gene experiments in colorectal cancer cells were performed. Finally, whether upregulation of CDK1 restores the inhibitory effect of overexpression of miR-378a-5p on the proliferation of CRC cells was studied by overexpression of CDK1. Results Bioinformatic analysis showed significant downregulation of miR-378a-5p levels in colorectal cancer (CRC). Cell function experiments and tumor xenograft mouse models confirmed the low expression of miR-378a-5p within CRC tissues, which indicated the tumor suppressive role of miR-378a-5p in CRC. To better explore the regulation of miR-378a-5p in CRC, we predicted and validated cell cycle-dependent protein kinase 1 (CDK1) as the miR-378a-5p target gene and observed that miR-378a-5p suppressed CRC cell proliferation by targeting CDK1. Conclusion The results of this study help to elucidate the mechanism by which miR-378a-5p can be used as a tumor marker to inhibit the growth of colorectal cancer and CDK1, which is related to the prognosis of colorectal cancer patients. MiR-378a-5p inhibits CRC cell proliferation by suppressing CDK1 expression, which may become a possible therapeutic target for treatment of CRC.

Anthracnose caused by plant pathogenic Colletotrichum fungi results in large economic losses in field crop production worldwide. To aid the establishment of plant host infection, Colletotrichum pathogens secrete numerous effector proteins either in apoplastic space or inside of host cells for effective colonization. Understanding these effector repertoires is critical for developing new strategies for resistance breeding and disease management. With the advance of genomics and bioinformatics tools, a large repertoire of putative effectors has been identified in Colletotrichum genomes, and the biological functions and molecular mechanisms of some studied effectors have been summarized. Here, we review recent advances in genomic identification, understanding of evolutional characteristics, transcriptional profiling, and functional characterization of Colletotrichum effectors. We also offer a perspective on future research.

BackgroundThe global burden of serious health-related suffering requiring palliative care has been projected to grow significantly by 2060, which indicates the imminent need for integrating palliative care into health systems globally. Moreover, research evidence has been accumulating in support of the earlier adoption of palliative care into the treatment course of serious life-threatening illnesses. However, barriers to earlier access to palliative care still remain, which might be attributable to the global lack of awareness of palliative care and the prevalence of negative perceptions and attitudes. To address this, further investigation of the influencing factors of public perceptions of palliative care is imperative to help inform and develop effective targeted public health campaigns and education messages aimed at improving views of palliative care and thereby early access.MethodsWe used data from the Health Information National Trends Survey (HINTS), a nationally representative cross-sectional survey routinely administrated by the National Cancer Institute from the United States. Specifically, we analyzed the latest palliative care data from HINTS 5 Cycle 2 data set. Sociodemographic characteristics, individual factors such as self-perceived health status, and interpersonal factors such as relationship quality were examined as predictors of public awareness of and attitudes toward palliative care. Survey data were analyzed using SPSS 26 with multiple hierarchical regression tests.ResultsResults showed that people's quality of interpersonal relationships was a significant influencing factor of their awareness of and attitudes toward palliative care. Moreover, cancer diagnosis history and perceived healthcare quality were found to jointly affect their awareness of palliative care; perceived health status and patient centeredness interacted to influence their awareness of and attitudes toward palliative care. Finally, female, non-white, and poorer people were more aware of palliative care, while female and more educated people had more favorable attitudes.ConclusionsThe quality of social relationships emerges as a significant predictor of people's awareness of and attitude toward palliative care, as treatment options and decisions of serious life-threatening illnesses often involve the patients' family. The results hold strong implications for public health campaigns and education messages aiming at changing people's views of palliative care, which ultimately improve end-of-life outcomes.

Modeling sea surface height (SSH) and tides is important but challenging in shelf seas. The Eastern China Seas (ECSs) is such a shelf sea with large inter-model deviations in prior studies. In order to assess and compare the possible uncertainty sources, numerical scenarios of varying the open boundary forcing, bottom roughness length scale, atmospheric forcing, grid resolution, and regional bathymetry were conducted in a hydrodynamic model of the ECSs. Results indicate that bathymetry data and open boundary forcing with inadequate accuracy generate uncertainties in SSH and tides locally and throughout the basin. An increase in bottom roughness enhances tidal dissipation and shifts amphidromes to the left relative to the incoming Kelvin waves, causing SSH variations in the ECSs. Refining the model resolution from 4 to 2 km mainly affects nearshore SSH and tides due to minor changes in depicted coastlines. Using different reanalysis meteorological data appears more important on the episodic than annual scale. It is highlighted that some uncertainty sources have opposing effects on SSH or tides and counteract their individual biases, making it difficult to achieve a realistic simulation. For example, increasing bottom roughness can not only compensate effects of overestimated tidal amplitude at open boundaries, but also balance out the overestimated M2 phase along the West Coast of Korea in a coarser-resolution model. Based on findings in this study, suggestions are provided for further reducing uncertainties in SSH and tide modeling in the ECSs and other shelf seas.

BackgroundHepatocellular carcinoma (HCC) is the third cause of cancer-related deaths worldwide. L antigen family member 3 (LAGE3) is a prognostic biomarker and associated with progression in a variety of tumors. However, little has been reported about the role and potential mechanism of LAGE3 in HCC.MethodsThe clinical value and function of LAGE3 in HCC were obtained from multiple online databases. The potential functions and pathways of LAGE3 in HCC were analysed by R package of “clusterProfiler”. LAGE3 knockdown cells were constructed in HepG2, HuH7 and MHCC97H cell lines, respectively. The biological roles of LAGE3 were examined by in vitro and in vivo experiments.ResultsLAGE3 was upregulated in HCC tissues compared with normal tissues, and high expression of LAGE3 was significantly associated with several clinical characteristics and indicated a worse prognosis of HCC. The co-expressed genes of LAGE3 could be enriched in the mTOR signaling pathway in HCC. LAGE3 was upregulated in HCC cell lines. Functionally, knocking down LAGE3 expression not only increased apoptosis and inhibited growth rate, cell death mediated by T cells, colony formation, migration and invasion ability of HCC cell lines in vitro, but also reduced the progression of HCC in the subcutaneous xenotransplanted tumor model.ConclusionOur results suggested that LAGE3 served as an oncogenic factor of HCC and could be a potential biomarker and therapeutic target for HCC.

Abstract Background Mandible osteomyelitis can occur in synovitis, acne, pustulosis, hyperostosis, and osteitis (SAPHO) syndrome, a rare chronic inflammatory disease; however, few studies have explored its characteristics and management. Methods We reviewed the medical records of consecutive SAPHO patients with mandible involvement diagnosed in Peking Union Medical College Hospital from September 2014 to July 2019. Demographic, clinical, laboratory, and imaging data were collected at baseline. Prescription data and follow-up magnetic resonance imaging (MRI) and cone beam computed tomography (CBCT) images were collected from the hospital information system. An electronic questionnaire was distributed to all patients to obtain their latest symptoms. Results A total of 26 SAPHO patients with mandibular involvement were involved, all of whom responded to the questionnaire (38.5% male; median age, 28 years; median follow-up duration, 2.1 years). Ten patients (38.5%) had undergone an oral procedure 1 month before the onset of mandibular symptoms. All 14 of the patients who underwent a surgical intervention relapsed within a median duration of 2 months (range 0.25–4.0 months), and 24 patients (92.3%) achieved improvement with conservative treatment. Following bisphosphonate treatment, remission of bone marrow oedema and osteolysis was observed on MRI and CBCT, and 5 patients receiving bisphosphonates with follow-up CBCT after remission did not relapse in 5.4 months (mean 6.0, range 3.2–9.9 months). Conclusion Mandibular involvement of SAPHO syndrome predominantly occurs in young women. Dental procedures are a possible risk factor. Conservative treatment, especially intravenous bisphosphonates, can lead to oral improvement.

Abstract Background The anterior chest wall (ACW) involvement is characteristic of synovitis, acne, pustulosis, hyperostosis, and osteitis (SAPHO) syndrome, yet little research has focused on its magnetic resonance imaging (MRI) findings. Purpose To characterize the MRI features of the ACW in patients with SAPHO syndrome. Methods Seventy-one patients with SAPHO syndrome and ACW involvement evidenced by bone scintigraphy were recruited in this cross-sectional study. The ACW region was scanned using sagittal, axial, and oblique coronal Dixon T2-weighted sequences and axial Dixon T1-weighted sequences. The characteristics of both active inflammatory and chronic structural lesions were evaluated. Results The ACW lesions exhibited an asymmetrical distribution and a predilection for the sternocostoclavicular region (93.0%). Notably, 91.5% of the patients had lesions in the area of the anterior first ribs. Bone marrow edema (BME) was observed in 63 (88.7%) patients, which mainly affected the sternocostal joints (87.3%) and the manubrium sterni (84.5%). All of the BMEs were distributed under the articular surface or the bone cortex, consistent with the distribution of the ligaments and joint capsules. Synovitis was detected in 64 (90.1%) patients, with a predilection for the sternoclavicular joints (76.1%). A soft tissue mass or infiltration was found in all the patients who had bone marrow edema. Thirteen (18.3%) patients showed venous stenosis. Structural changes included bone bridge formation (80.3%), hyperostosis (43.7%), and fat infiltration (39.4%). Four common patterns of involvement were observed: the first rib area, the sternoclavicular area, the sternal angle area, and the areas of the second to sixth sternocostal joints. Conclusion The ACW lesions of SAPHO syndrome demonstrated a triad of enthesitis, synovitis, and osteitis, suggesting complex interactions among the ligaments, synovium, and bones in the region. The inflammatory changes in the first rib area were highlighted in SAPHO syndrome.

During the end-of-life (EOL) product recovery process, there are a series of combinatorial optimization problems (COPs) that should be efficiently solved. These COPs generally result from reverse logistics (RL) and remanufacturing, such as facility location and vehicle routing in RL, and scheduling, planning, and line balancing in remanufacturing. Each of the COPs in RL and remanufacturing has been reviewed; however, no review comprehensively discusses and summarizes the COPs in both. To fill the gap, a comprehensive review of the COPs in both RL and remanufacturing is given in this paper, in which typical COPs arising at the end of the product life cycle are discussed and analyzed for the first time. To better summarize these COPs, 160 papers published since 1992 are selected and categorized into three modules: facility location and vehicle routing in RL, scheduling in remanufacturing, and disassembly in remanufacturing. Finally, the existing research gaps are identified and some possible directions are described.

The non-canonical nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) signaling pathway is an important component of NF-κB transcription complex. Activation of this pathway mediates the development and function of host immune system involved in inflammation and viral infection. During hepatitis B virus (HBV) infection, there is a complex interaction between infected hepatocytes and the immune cells, which can hinder antiviral immune responses and is associated with pathological changes in liver tissue. Consistently, the host immune system is closely related to the severity of liver damage and the level of viral replication. Previous studies indicated that the non-canonical NF-κB signaling pathway was affected by HBV and might play an important regulatory role in the antiviral immunity. Therefore, systematically elucidating the interplay between HBV and non-canonical NF-κB signaling will contribute the discovery of more potential therapeutic targets and novel drugs to treat HBV infection.

BackgroundHepatocellular carcinoma (HCC) is the fourth leading cause of cancer-related deaths worldwide. PAFAH1B3 plays an important role on occurrence and development in a variety tumor. However, the function of PAFAH1B3 in HCC remains unclear.MethodsThe TIMER, ONCOMINE, Human Protein Atlas (HPA), GEPIA, The Cancer Genome Atlas (TCGA), HCCDB, UALCAN and LinkedOmics database were used to analyze the prognostic value, co-expression genes and regulator networks of PAFAH1B3 in HCC. siRNA transfections and inhibitor of PAFAH1B3 P11 were used to verify the anti-tumor effect on HCC cell lines. Gene expression was detected by qRT-PCR. The functions of PAFAH1B3 downregulation in HCC cell lines were investigated using cell cycle analysis, apoptosis detection, CCK8 assay and transwell assay. Western blot was used to evaluate the role of PAFAH1B3 on metabolic pathways in HCC cells.ResultsBased on the data from databases, the expression of PAFAH1B3 was remarkably increased in HCC patients. High expression of PAFAH1B3 was associated with poorer overall survival (OS) and disease-free survival (DFS). And PAFAH1B3 was notably linked to age, sex, grade, stage, race, and TP53 mutational status. Then, the functional network analysis showed PAFAH1B3 may be involved in HCC through cell cycle, cell metabolism, spliceosome, and RNA transport. Furthermore, the mRNA expression of PAFAH1B3 was also increased in HCC cell lines. Flow cytometry analysis showed that PAFAH1B3 manipulated apoptosis and cell cycle regulation. CCK8 assay showed that PAFAH1B3 silencing or pharmacologic inhibitor of PAFAH1B3 inhibited the proliferation of HepG2, Huh7 and MHCC-97H cells. Transwell assay results showed that PAFAH1B3 silencing also significantly impaired the invasion and migratory ability of HCC cells. In addition, PAFAH1B3 silencing significantly downregulated the expression of glycolysis and lipid synthesis signaling pathways.ConclusionOur findings suggested that PAFAH1B3 plays a critical role in progression of HCC. PAFAH1B3 as a prognosis marker and potential target for HCC has prospective clinical significance.

Entity prediction is the task of predicting a missing entity that has a specific relation-ship with another given entity. Researchers usually use knowledge graphs embedding(KGE) methods to embed triples into continuous vectors for computation and perform the tasks of entity prediction. However, KGE models tend to use simple operations to refactor entities and relationships, resulting in insufficient interaction of components of knowledge graphs (KGs), thus limiting the performance of the entity prediction model. In this paper, we propose a new entity prediction model called FRS(Feature Refactoring Scoring) to alleviate the problem of insufficient interaction and solve information incom-pleteness problems in the KGs. Different from the traditional KGE methods of directly using simple operations, the FRS model innovatively provides the procedure of feature processing in the entity prediction tasks, realizing the alignment of entities and relationships in the same feature space and improving the performance of entity prediction model. Although FRS is a simple three-layer network, we find that our own model outperforms state-of-the-art KGC methods in FB15K and WN18. Through extensive experiments on FRS, we discover several insights. For example, the effect of embedding size and negative candidate sampling probability on experimental results is in reverse.