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In recent years, electric buses have advanced rapidly due to their green and low-carbon attributes. To address range anxiety and optimize charging strategies, accurately predicting charging load has become essential. This paper introduces a synchronous spatial-temporal attention transformer (S2TAT) model that models temporal and spatial dependencies simultaneously, utilizing operational data from new energy electric buses in Shanghai. To improve charging event prediction, we propose two key improvements: an adaptive adjacency matrix for dynamic spatial dependencies learning and a periodicity extraction mechanism for capturing cyclical patterns. These enhancements significantly boost prediction accuracy over baseline models. An ablation study further verifies the contributions of the model’s components.

Abstract Background Anti‐N‐methyl‐D‐aspartate receptor encephalitis (anti‐NMDARE) is a prevalent type of autoimmune encephalitis caused by antibodies targeting the NMDAR's GluN1 subunit. While significant progress has been made in elucidating the pathophysiology of autoimmune diseases, the immunological mechanisms underlying anti‐NMDARE remain elusive. This study aimed to characterize immune cell interactions and dysregulation in anti‐NMDARE by leveraging single‐cell multi‐omics sequencing technologies. Methods Peripheral blood mononuclear cells (PBMCs) from patients in the acute phase of anti‐NMDARE and healthy controls were sequenced using single‐cell joint profiling of transcriptome and chromatin accessibility. Differential gene expression analysis, transcription factor activity profiling, and cell‐cell communication modeling were performed to elucidate the immune mechanisms underlying the disease. In parallel, single‐cell B cell receptor sequencing (scBCR‐seq) and repertoire analysis were conducted to assess antigen‐driven clonal expansion within the B cell population. ResultsThe study revealed a significant clonal expansion of B cells, particularly plasma cells, in anti‐NMDARE patients. The novel finding of type I interferon (IFN‐I) pathway activation suggests a regulatory mechanism that may drive this expansion and enhance antibody secretion. Additionally, activation of Toll‐like receptor 2 (TLR2) in myeloid cells was noted, which may connect to tumor necrosis factor‐alpha (TNF‐α) secretion. This cytokine may contribute to the activation of B and T cells, thereby perpetuating immune dysregulation. Conclusions This study presents a comprehensive single‐cell multi‐omics characterization of immune dysregulation in anti‐NMDARE, highlighting the expansion of B cell and the activation of the IFN‐I and TLR2 pathways. These findings provide deeper insights into the molecular mechanism driving the pathogenesis of anti‐NMDARE and offer promising targets for future therapeutic intervention. Key points Significant B cell clonal expansion, particularly in plasma cells, driven by antigen recognition. IFN‐I pathway activation in plasma cells boosts their antibody production and potentially exacerbates immune dysregulation. TLR2 pathway activation in myeloid cells contributes to TNF‐α secretion and could influence adaptive immune responses.

Abstract Multiple sclerosis (MS) is a debilitating demyelinating disease characterized by remyelination failure attributed to inadequate oligodendrocyte precursor cells (OPCs) differentiation and aberrant astrogliosis. A comprehensive cell atlas reanalysis of clinical specimens brings to light heightened clusterin (CLU) expression in a specific astrocyte subtype links to active lesions in MS patients. Our investigation reveals elevated astrocytic CLU levels in both active lesions of patient tissues and female murine MS models. CLU administration stimulates primary astrocyte proliferation while concurrently impeding astrocyte-mediated clearance of myelin debris. Intriguingly, CLU overload directly impedes OPC differentiation and induces OPCs and OLs apoptosis. Mechanistically, CLU suppresses PI3K-AKT signaling in primary OPCs via very low-density lipoprotein receptor. Pharmacological activation of AKT rescues the damage inflicted by excess CLU on OPCs and ameliorates demyelination in the corpus callosum. Furthermore, conditional knockout of CLU emerges as a promising intervention, showcasing improved remyelination processes and reduced severity in murine MS models.

Early neuroinflammatory injury plays a crucial role in initiating and progressing multiple sclerosis (MS). Neutrophils are forerunners to neural lesions in MS, yet the temporal alterations of their functions in MS remains unclear. This study demonstrated a positive correlation between circulatory neutrophil counts and disease activity and severity in treatment-naïve MS patients. In experimental autoimmune encephalomyelitis (EAE), we documented the recruitment of neutrophils to spinal cord during the preclinical phase, with these cells contributing to the disruption of the blood-spinal cord barrier (BSCB) during the onset of the disease. Furthermore, during the peak phase, infiltrated neutrophils promoted demyelination through formation of neutrophil extracellular traps (NETs), cytokine secretion and antigen presentation. Notably, the inhibition of neutrophil infiltration using a CXCR2 inhibitor effectively mitigated white matter damage and physical disability, underscoring their potential as therapeutic targets. In conclusion, neutrophils represent promising candidates for both disease treatment and prognosis evaluation in MS. By elucidating their temporal roles and mechanisms of action, we can potentially harness their modulation to improve patient outcomes and disease management.

Endocrine-disrupting chemicals (EDCs) exhibited the detriment in female reproductive health. Our objective was to investigate the individual and mixture effects of EDCs present in follicular fluid, the environment in which oocytes grow and develop, on early reproductive outcomes. We recruited 188 women seeking reproduction examination from the Study of Exposure and Reproductive Health (SEARCH) cohort between December 2020 and November 2021. We assessed the concentrations of 7 categories of 64 EDCs in follicular fluid, and measured early reproductive outcomes, including retrieved oocytes, mature oocytes, normal fertilized oocytes, and high-quality embryos. In this study Monomethyl phthalate (MMP) (2.17 ng/ml) were the compounds found in the highest median concentrations in follicular fluid. After adjusting for multiple testing, multivariate regression showed that multiple EDCs were significantly negatively associated with early assisted reproduction outcomes. For example, MMP showed a significant negative correlation with the number of high quality embryos (β: −0.1, 95 % CI: −0.15, −0.04). Specifically, eight types of EDCs were significantly negatively associated with four early assisted reproductive outcomes (β range: −0.2 ∼ -0.03). In the mixed exposure model, we found that mixtures of EDC were significantly negatively correlated with all four outcomes. In the quantile g-computation (QGCOMP) model, for each interquartile range increase in the concentration of EDC mixtures, the number of oocytes retrieved, mature oocytes, normally fertilized oocytes, and high-quality embryos decreased by 0.46, 0.52, 0.77, and 1.2, respectively. Moreover, we identified that phthalates (PAEs) predominantly contributed to the negative effects. Future research should validate our findings.

With the advancement of satellite and 5G communication technologies, vehicles can transmit and exchange data from anywhere in the world. It has resulted in the generation of massive spatial trajectories, particularly from the Automatic Identification System (AIS) for surface vehicles. The massive AIS data lead to high storage requirements and computing costs, as well as low data transmission efficiency. These challenges highlight the critical importance of vessel trajectory compression for surface vehicles. However, the complexity and diversity of vessel trajectories and behaviors make trajectory compression imperative and challenging in maritime applications. Therefore, trajectory compression has been one of the hot spots in research on trajectory data mining. The major purpose of this work is to provide a comprehensive reference source for beginners involved in vessel trajectory compression. The current trajectory compression methods could be broadly divided into two types, batch (offline) and online modes. The principles and pseudo-codes of these methods will be provided and discussed in detail. In addition, compressive experiments on several publicly available data sets have been implemented to evaluate the batch and online compression methods in terms of computation time, compression ratio, trajectory similarity, and trajectory length loss rate. Finally, we develop a flexible and open software, called AISCompress, for AIS-based batch and online vessel trajectory compression. The conclusions and associated future works are also given to inspire future applications in vessel trajectory compression.

Abstract Background Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is a severe autoimmune neuropsychiatric disease. Brain access of anti-NMDAR autoantibody through the blood–brain barrier (BBB) is essential for pathogenesis. Most previous animal models limit the investigation of etiologies of BBB damage in patients. Methods In this study, we established a novel humanized mouse model of anti-NMDAR encephalitis by intraperitoneal injection of patients’ peripheral blood mononuclear cells (PBMCs) into BALB/c Rag2 −/− Il2rg −/− Sirpα NOD Flk2 −/− mice. Results We found that engraftment of patients’ PBMCs not only produced potent anti-GluN1 autoantibodies, but also disrupted BBB integrity to allow brain access of autoantibodies, resulting in a hyperactive locomotor phenotype, anxiety- and depressive-like behaviors, cognitive deficits, as well as functional changes in corresponding brain regions. Transcriptome analysis suggested an exaggerated immune response and impaired neurotransmission in the mouse model and highlighted Il-1β as a hub gene implicated in pathological changes. We further demonstrated that Il-1β was produced by endothelial cells and disrupted BBB by repressing tight junction proteins. Treatment with Anakinra, an Il-1 receptor antagonist, ameliorated BBB damage and neuropsychiatric behaviors. Conclusions Our study provided a novel and clinically more relevant humanized mouse model of anti-NMDAR encephalitis and revealed an intrinsic pathogenic property of the patient’s lymphocytes.

With the growth of global trade, port shipping is becoming more and more important. In this paper, an analysis of a ship’s inbound and outbound track characteristics is conducted using the OD–Hausdorff distance. The accuracy and efficiency of trajectory data analysis have been enhanced through clustering analysis. Trajectories are arranged in a time sequence, and representative port segments are selected. An improved OD–Hausdorff distance method is employed to capture the dynamic characteristics of a ship’s movements, such as speed and heading. Additionally, the DBSCAN algorithm is utilized for clustering, allowing for the processing of multidimensional AIS data. Data cleaning and preprocessing have ensured the reliability of the AIS data, and the Douglas–Peucker algorithm is used for trajectory simplification. Significant improvements in the accuracy and efficiency of trajectory clustering have been observed. Therefore, the main channel of the Guan River and the right side of Yanwei Port are usually followed by ships greater than 60 m in length, with a lateral Relative Mean Deviation (RMD) of 7.06%. Vessels shorter than 60 m have been shown to have greater path variability, with a lateral RMD of 7.94%. Additionally, a crossing pattern at Xiangshui Port is exhibited by ships shorter than 60 m due to the extension of berths and their positions at turns. Enhanced clustering accuracy has provided more precise trajectory patterns, which aids in better channel management.

The navigational safety of ships on waterways plays a crucial role in ensuring the operational efficiency of ports. Ship anomalous behavior detection is an important method of water traffic surveillance that can effectively identify abnormal ship behavior, such as sudden acceleration or deceleration. In order to detect potential anomalous ship behavior in real time, a method for ship anomalous behavior detection in waterways is proposed based on text similarity and kernel density estimation. Under the assumption of known traffic patterns entering and leaving the port, this method can identify ship behaviors that violate traffic patterns in real time. Firstly, kernel density estimation is applied to construct a traffic pattern density model for ship trajectories entering and leaving the port, used to estimate the density values of ship motion states. Simultaneously, a semantic transformation method is used to convert traffic pattern trajectory into pattern trajectory text, which is used to identify the ship’s traffic pattern. Subsequently, the historical trajectory data of the target ship are transformed into textual trajectories, and text similarity is used to identify ship inbound and outbound traffic patterns. Furthermore, the constructed traffic pattern density model is used to estimate real-time density values of the state of ship motion, and the trajectory points that exceed the threshold of the anomaly factor are marked as anomalies. Finally, the effectiveness of the proposed method is validated using simulation data, and the results indicate an accuracy of more than 90% for the comprehensive detection of anomalous behavior. This study, approaching the detection of potential ship anomalous behavior from the perspective of port traffic patterns, enriches the methods of ship anomalous behavior detection in port waterways.

Abstract Background Recently, a novel humanized mouse model for systemic sclerosis (SSc) was established by transferring peripheral blood mononuclear cells (PBMC) from patients with SSc to Rag2 −/− Il2rg −/− immunodeficient mice. Here, we aimed to investigate the role of T and B cells in this humanized mouse model. Methods T and B cells were depleted in vitro from freshly isolated PBMC using anti-CD3 and anti-CD19 magnetic microbeads, respectively. Subsequently, PBMC and T or B cell-depleted PBMC were transferred into Rag2 −/− /Il2rg −/− mice via intraperitoneal injection. Twelve weeks after the transfer, mice were sacrificed and evaluated. Results Mice transferred with whole PBMC from SSc patients developed systemic inflammation in the lungs, kidneys, and liver, and 6 out of 11 mice died or had to be sacrificed during the experiment. By contrast, such inflammation and death were not observed in mice transferred with corresponding T or B cell-depleted PBMC. In line with this finding, transfer with whole PBMC restored the splenic white pulp composing of human T, B, and plasma cells and led to the production of a considerable amount of human autoantibodies in recipient mice, while those immunological features were rarely observed in mice that received T or B cell-depleted PBMC. In contrast to our previous findings demonstrating a transfer of the protective effect of a B cell therapy into the mouse, treatment of SSc patients with chemical immunosuppressive drugs did not affect the pathogenicity of PBMC. Conclusions This study demonstrates that both T and B cells are indispensable for the pathogenesis of the PBMC transfer-induced mouse model for SSc.

Little information is available on how the types, concentrations, and distribution of chemicals have evolved over the years. The objective of the present study is therefore to review the spatial and temporal distribution profile of emerging contaminants with limited toxicology data in the pearl river basin over the years to build up the emerging contaminants database in this region for risk assessment and regulatory purposes. The result revealed that seven groups of emerging contaminants were abundant in this region, and many emerging contaminants had been detected at much higher concentrations before 2011. Specifically, antibiotics, phenolic compounds, and acidic pharmaceuticals were the most abundant emerging contaminants detected in the aquatic compartment, while phenolic compounds were of the most profound concern in soil. Flame retardants and plastics were the most frequently studied chemicals in organisms. The abundance of the field concentrations and frequencies varied considerably over the years, and currently available data can hardly be used for regulation purposes. It is suggested that watershed management should establish a regular monitoring scheme and comprehensive database to monitor the distribution of emerging contaminants considering the highly condensed population in this region. The priority monitoring list should be formed in consideration of historical abundance, potential toxic effects of emerging contaminants as well as the distribution of heavily polluting industries in the region.

Abstract Paraneoplastic autoimmune encephalitis (PAE) represents a group of rare neurological syndromes associated with neoplastic diseases. Here, we report a case that multiple anti‐neuronal antibodies were present in a patient with PAE who developed both small cell lung cancer and colorectal adenocarcinoma. Furthermore, the immunopathological investigation of the colorectal adenocarcinoma revealed the formation of abnormal neuronal antigens and a massive infiltration of plasma cells in the tumor tissue. These findings support the hypothesis that expression of neuronal antigens in neoplasm initiates autoimmune responses in PAE.

Abstract Background Early stage neuromyelitis optica spectrum disorders (NMOSD) with non-opticospinal manifestations as initial symptoms are easily misdiagnosed; however, data on the full symptom profile are limited. Moreover, the clinical characteristics and long-term outcomes of these patients remain unknown. We sought to analyze the clinical characteristics, imaging features, and long-term outcomes of NMOSD with non-opticospinal manifestations as initial symptoms. Methods We retrospectively included relevant patients from our center. Clinical, demographic, magnetic resonance imaging, treatment, and outcome data were compared according to the non-opticospinal vs. opticospinal initial symptoms. Results We identified 43 (9.13 %) patients with non-opticospinal initial symptoms among 471 patients with NMOSD. Of these, 88.37 % developed optic neuritis/myelitis during an average follow-up period of 6.33 years. All the non-opticospinal symptoms were brain/brainstem symptoms. Most of the symptoms and associated brain lesions were reversible. These patients had a younger onset age (P

The international crude oil maritime transportation system has always been disturbed by the external environment and its own mechanism of supply and demand, which can sometimes last for a long time. BDTI (Baltic Exchange Dirty Tanker Index) is one of the most typical indexes in the crude oil maritime transportation market, which is affected by many uncertain events and often lasts for a long time. So it is very significant to study fluctuation characteristics of the crude oil maritime transportation system and assess the impact of critical events, which have been referred to in this paper by improving the R/S model and selecting three international transportation lines in marine shipping ranging from 2008 to 2019. Through model applications, numerical results validate the effectiveness of this method, showing all of the three transportation lines possess long-term memory. The impact of the four critical events has also been evaluated. The study will help crude oil enterprises make investment decision on potential transportation lines and give policymakers advice to maintain stability of the crude oil industry.

The shipping volume in inland waterways has been rapidly increasing in recent years. However, it is still challenging to trace oil spills caused by maritime accidents. In this study, the oil spill dispersion trajectory in inland rivers was obtained by simulating the trajectory of oil particles under different waterway conditions based on a simulated flow field. Firstly, the flow field was simulated using a volume of fluid (VOF) model and the solution of an open-channel equation. Then, an oil particle diffusion and drift model was established using Python to simulate the diffusion of the oil. Finally, eight oil spill simulation scenarios were conducted with different channel shapes and cross-sections. The results showed that oil spills spread more extensively in a curved channel with a trapezoidal cross-section compared to other channel shapes and cross-sections. The findings of this research could be used to guide inland river environmental protection and oil spill trajectory tracking.

Ship exhaust gas has become an essential source of air pollution in recent years. To assess the impact of ship exhaust gas on the atmospheric environment and human health, this paper studies the problem of ship exhaust gas diffusion in the port area. According to automatic identification system (AIS) data, ship exhaust gas is estimated based on the bottom-up method, and the result of emission calculation is entered into a Gaussian puff model to calculate the superposition of the diffusion of gaseous pollutants from multiple ships. In addition, the results of a case study of the diffusion of ship exhaust gas in the western area of Shenzhen Port in China show that the distribution of the NO2 concentration in the studied area is not stable, the diffusion of exhaust gas from multiple ships mainly affects some areas near large ship berths at night, and there is a small impact on the whole study area. This lays a foundation for monitoring and treating the atmospheric environment in the port area.

This work concerns the numerical generation of stable solitary waves by using a piston-type wave maker and the propagation characteristics of a solitary wave in a step-type flume. The numerical generation of solitary waves was performed by solving N-S (Navier–Stokes) equations on the open source CFD (computational fluid dynamics) platform OpenFOAM. To this end, a new module of dynamic boundary conditions was programmed and can be applied to prescribe the horizontal linear motion of a paddle. Two kinds of paddle motions, based on both the first-order and ninth-order solutions of solitary waves, were first determined. The time history of paddle motion was restored in a file, which was then used as an input for the virtual wave maker. The solitary wave in water with a constant depth was generated by both numerical simulation and experiment in the wave flume installed with a piston wave maker. The results show that the amplitudes of trailing waves based on the first-order solution are larger than those based on the ninth-order solution and that wave height based on the first-order solution decays more quickly. The numerical wave profiles are in good agreement with the experimental ones. The propagation characteristics of a solitary wave in a step-type flume was numerically investigated as well. It was found that a part of the solitary wave is reflected when the solitary wave passes the step due to blockage effects, and the forward main wave collapses quickly when it enters shallow water. This work presents a very successful numerical study of stable solitary wave generation and reveals the phenomena when a solitary wave propagates in a step-type flume.

Ship path planning is crucial for the shipping industry, especially for the development of autonomous ships. Many algorithms have been developed over the last few decades to solve the ship path planning problem. However, it is still challenging for ship path planning in an inland waterway. In this paper, an improved RRT algorithm for ship path planning in complex inland waterways is proposed. The improved algorithm has a path shearing and smoothing module, and the function of keeping a safe distance between a moving ship and obstacles. In addition, the algorithm has been tested in two inland waterway scenarios, and the results have confirmed its feasibility and reliability. The path planning algorithm proposed in this research seeks to reduce the risks faced by ship navigation in inland water. It has theoretical and practical significance in improving navigation safety in complex inland waters.

Background: Multiple sclerosis (MS) patients have a wide spectrum of severity and responses to therapy; the personalization of treatment relies on sensitive and specific biomarkers. Previous studies have suggested that susceptibility contrast in demyelinated plaques is associated with iron-related pathology in multiple sclerosis which may indicate clinical severity. The aims of this study were to characterize the spatial distribution of MS lesions with different iron patterns by using quantitative susceptibility mapping and to explore neuroradiological findings that correlate with poor clinical outcome.Methods: Twenty-six patients with relapsing–remitting MS [14 men, 12 women; mean age, 29 ± 8 (standard deviation) years; age range, 21–52 years] were included in this study. Differences in lesion number, T2 volume, and susceptibility were compared among lesions subcategorized by location and by the presence or absence of a hyperintense rim on quantitative susceptibility mapping. Associations between these imaging features and clinical outcomes including Expanded Disability Status Scale scores and annual relapse rates were investigated.Results: A total of 811 unifocal MS lesions were included, and their QSM patterns were nodular hyperintensity with no rim (rim–, 540, 67%) or with a hyperintense rim on the edge (rim+, 172, 21%) and nodular isointensity (99, 12%). Rim+ lesions had significantly larger volume (115 ± 142 vs. 166 ± 185 mm3, p < 0.001) and lower susceptibility (4 ± 15 vs. 8 ± 16 ppb, p < 0.05) than rim– lesions. More rim+ lesions were found in periventricular areas [median, 45%; interquartile range (IQR), 36%], whereas a larger proportion of rim– lesions were distributed in juxtacortical (median, 32%; IQR, 21%) and deep white matter (median, 38%; IQR, 22%) areas. The annual relapse rate was positively correlated with the proportion of periventricular rim+ lesions (p < 0.001, r = 0.65) and the proportion of subtentorial rim+ lesions (p < 0.05, r = 0.40). Additionally, a significant association was found between the burden of periventricular rim+ lesions (β = 0.64, p < 0.001) and the burden of subtentorial rim– lesions (β = 0.36, p < 0.05).Conclusions: A high number or lesion burden of periventricular rim+ lesions or subtentorial lesions is associated with frequent clinical relapses.

ObjectiveThe contribution of sustained autologous autoantibody production by B cells to the pathogenesis of systemic sclerosis (SSc) and granulomatosis with polyangiitis (GPA) is not fully understood. To investigate this, a humanized mouse model was generated by transferring patient-derived peripheral blood mononuclear cells (PBMC) into immunocompromised mice.MethodsPBMC derived from patients with SSc and GPA as well as healthy controls (HD) were isolated, characterized by flow cytometry, and infused into Rag2-/-/IL2rg-/- mice. In addition, PBMC from SSc patients treated with rituximab were transferred into mice. Twelve weeks later, human autoantibodies were determined in blood of the recipient mice and affected tissues were analyzed for pathological changes by histology and immunohistochemistry.ResultsMice engrafted with PBMC derived from SSc patients developed autoantibodies such as antinuclear antibodies (ANA) mimicking the pattern of the respective donors. Moreover, cellular infiltrates dominated by B cells were observed in lung, kidney and muscles of the recipient mice. By contrast, PBMC derived from HD or GPA patients survived in recipient mice after transfer, but neither human autoantibodies nor inflammatory infiltrates in tissues were detected. Furthermore, these pathological changes were absent in mice transferred with PBMC from rituximab-treated SSc patients.ConclusionThis humanized mouse model is indicative for cross-reactivity of human lymphocytes to murine autoantigens and argues for a pivotal role of B cells as well as of sustained autoimmunity in the pathogenesis of SSc. It provides a powerful tool to study interstitial lung disease and so far, under-recognized disease manifestations such as myositis and interstitial nephritis.

Abstract Introduction The aim was to characterize the optical coherence tomography (OCT) angiography measures in patients with multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) and to evaluate their disease discrimination capacity. Methods Patients with MS (n = 83) and AQP4‐IgG‐seropositive NMOSD (n = 91) with or without a history of optic neuritis, together with healthy controls (n = 34), were imaged. The main outcome measures were peripapillary retinal nerve fiber layer (pRNFL) thickness, macular ganglion cell‐inner plexiform layer (GC‐IPL) thickness, macular vessel density (VD), and perfusion density (PD) in the superficial capillary plexus. Diagnostic accuracy was assessed using the area under the receiver operating characteristics curve. Results Compared with patients with MS, those with NMOSD had a significantly smaller average thickness of the pRNFL and GC‐IPL (80.0 [59.0; 95.8] μm versus 92.0 [80.2; 101] μm, p

The flag state control (FSC) inspection is an important measure to ensure maritime safety. However, it is difficult to improve ship safety management efficiency using data mining due to the scattered and multi-source ship inspection knowledge. In this paper, the emerging knowledge graph technology is used to integrate multi-source knowledge for the FSC inspection. Firstly, an ontology model is built to systematically describe the knowledge and guide the construction of the data layer of the knowledge graph. Then, the BERT-BiGRU-CRF model is used to extract entities from the unstructured data of the FSC inspection. The extracted results are associated with structured and semi-structured data and stored in the graph database Neo4j to construct the knowledge graph. In addition, a case study of the FSC inspection knowledge graph of Dafeng Port in Yancheng, China, is conducted to verify the strength of the proposed method. The results show that the knowledge graph can correlate trivial knowledge and benefit the efficiency of the FSC inspection. Moreover, the knowledge graph can reflect the deficiency characteristics of ships and support the safety management of water transportation.

Port environmental problems have gradually become the primary concern of port authorities. The future trend of port carbon emissions is crucial to port authorities and managers in formulating regulations and optimizing operation schedules. Owing to the limitations of current prediction methods and the complex social–environmental impact, the estimation results of port carbon emissions have insufficient accuracy to support port development in the future. In this work, the stochastic impacts by regression on population, affluence, and technology (STIRPAT)–long short-term memory (LSTM)–autoregressive integrated moving average with explanatory variable (ARIMAX) integrated model is proposed for the estimation of the carbon emission of Port of Los Angeles to improve the reliability of emission prediction. Macroeconomic indicators that affect port throughput are selected using the principal component analysis—multiple linear regression model. The chosen indicators are then combined with long-term historical port throughput data as the input of the multivariate autoregressive integrated moving average (ARIMAX) model to predict port throughput. Indicators related to port carbon emissions are verified by the STIRPAT model. The LSTM–ARIMAX integrated model is then applied to estimate the emission tendency, which can be useful in developing corresponding carbon reduction strategies and further understanding port emissions. Results show that the proposed method can significantly improve the estimation accuracy for port emission by 11% compared with existing techniques. Energy conservation strategies are also put forward to assist port authorities in achieving the peak clipping of port carbon emission.

Background/Aims: Atherosclerosis, a multifactorial chronic disease, is the main cause of death and impairment in the world. Endothelial cells (ECs) apoptosis plays a crucial role in the onset and development of atherosclerosis, whereas the underlying molecular mechanisms are unclear. MicroRNA-142-3p (miR-142-3p) is a well-defined tumor suppressor in several types of cancer, while the role of miR-142-3p in ECs apoptosis and the development of atherosclerosis has yet to be elucidated. Therefore, the present study aimed to investigate the role of miR-142-3p in ECs apoptosis during atherosclerosis and the underlying mechanism. Methods: Human aortic endothelial cells (HAECs) were treated with oxidized low-density lipoprotein (ox-LDL). The expression level of miR-142-3p was detected using qRT-PCR. Apoptosis was determined via flow cytometry and Caspase-3 activity assay. Prediction of the binding between miR-142-3p and 3’-UTR of Rictor mRNA was performed by bioinformatics analyses and confirmed by a dual luciferase reporter assay. The effects of miR-142-3p on endothelial apoptosis and atherosclerosis were further analyzed in an in vivo model using ApoE-/- mice fed with high-fat diet (HFD). Results: MiR-142-3p expression was substantially up-regulated during the ox-LDL-elicited apoptosis in HAECs. Forced expression of miR-142-3p exacerbated apoptosis in ECs whereas inhibition of miR-142-3p could partly alleviate apoptotic cell death mediated by ox-LDL. Further analysis identified Rictor as a direct target of miR-142-3p, and Rictor knockdown abolished the anti-apoptotic effect of miR-142-3p inhibitor. Moreover, the Akt/endothelial nitric oxide synthase (eNOS) signaling pathway was found to mediate the beneficial effect of miR-142-3p inhibitor on endothelial apoptosis. Finally, systemic treatment with miR-142-3p antagomir attenuated endothelial apoptosis and retarded the progression of atherosclerosis in the aorta of ApoE-/- mice. Conclusions: Down-regulation of miR-142-3p inhibited ECs apoptosis and atherosclerotic development by up-regulating the expression of Rictor and activating the Akt/eNOS signaling pathway. This indicates that miR-142-3p may be a potential target for the prevention and treatment of atherosclerosis.

Background: Myelin oligodendrocyte glycoprotein (MOG) antibody associated encephalomyelitis is increasingly being considered a distinct disease entity, with seizures and encephalopathy commonly reported. We investigated the clinical features of MOG-IgG positive patients presenting with seizures and/or encephalopathy in a single cohort.Methods: Consecutive patients with suspected idiopathic inflammatory demyelinating diseases were recruited from a tertiary University hospital in Guangdong province, China. Subjects with MOG-IgG seropositivity were analyzed according to whether they presented with or without seizure and/or encephalopathy.Results: Overall, 58 subjects seropositive for MOG-IgG were analyzed, including 23 (40%) subjects presenting with seizures and/or encephalopathy. Meningeal irritation (P = 0.030), fever (P = 0.001), headache (P = 0.001), nausea, and vomiting (P = 0.004) were more commonly found in subjects who had seizures and/or encephalopathy, either at presentation or during the disease course. Nonetheless, there was less optic nerve (4/23, 17.4%, P = 0.003) and spinal cord (6/16, 37.5%, P = 0.037) involvement as compared to subjects without seizures or encephalopathy. Most MOG encephalomyelitis subjects had cortical/subcortical lesions: 65.2% (15/23) in the seizures and/or encephalopathy group and 50.0% (13/26) in the without seizures or encephalopathy group. Cerebrospinal fluid (CSF) leukocytes were elevated in both groups. Subgroup analysis showed that 30% (7/23) MOG-IgG positive subjects with seizures and/or encephalopathy had been misdiagnosed for central nervous system infection on the basis of meningoencephalitis symptoms and elevated CSF leukocytes (P = 0.002).Conclusions: Seizures and encephalopathy are not rare in MOG encephalomyelitis, and are commonly associated with cortical and subcortical brain lesions. MOG-encephalomyelitis often presents with clinical meningoencephalitis symptoms and abnormal CSF findings mimicking central nervous system infection in pediatric and young adult patients.

Recent clinical data have led to the consideration of sexual steroids as new potential therapeutic tools for multiple sclerosis. Selective estrogen receptor modulators can exhibit neuroprotective effects like estrogen, with fewer systemic estrogen side effects than estrogen, offering a more promising therapeutic modality for multiple sclerosis. The important role of astrocytes in a proinflammatory effect mediated by CCL20 signaling on inflammatory cells has been documented. Their potential contribution to selective estrogen receptor modulator-mediated protection is still unknown. Using a mouse model of chronic neuroinflammation, we report that raloxifene, a selective estrogen receptor modulator, alleviated experimental autoimmune encephalomyelitis-an animal model of multiple sclerosis-and decreased astrocytic production of CCL20. Enzyme-linked immunosorbent assay, immunohistochemistry imaging and transwell migration assays revealed that reactive astrocytes express CCL20, which promotes Th17 cell migration. In cultured rodent astrocytes, raloxifene inhibited IL-1β-induced CCL20 expression and chemotaxis ability for Th17 migration, whereas the estrogen receptor antagonist ICI 182,780 blocked this effect. Western blotting further indicated that raloxifene suppresses IL-1β-induced NF-κB activation (phosphorylation of p65) and translocation but does not affect phosphorylation of IκB. In conclusion, these data demonstrate that raloxifene provides robust neuroprotection against experimental autoimmune encephalomyelitis, partially via an inhibitory action on CCL20 expression and NF-κB pathways in reactive astrocytes. Our results contribute to a better understanding of the critical roles of raloxifene in treating experimental autoimmune encephalomyelitis and uncover reactive astrocytes as a new target for the inhibitory action of estrogen receptors on chemokine CCL20 expression.

The article presents a study which developed a suspect screening-based strategy to identify environmental chemicals with potential neurotoxic effects in human cerebrospinal fluid (CSF). Topics discussed include how the relationship between serum and CSF concentrations were determined, median concentrations exhibited by the environmental chemicals, and summary of environmental chemicals detected in human CSF pairs from 180 adults in Guangzhou, China.