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Abstract Background Percutaneous endoscopic lumbar discectomy (PELD) has demonstrated variable efficacy in alleviating low back pain (LBP) associated with lumbar disc herniation (LDH). Sinuvertebral nerve ablation (SNA), which targets the nociceptive pathway implicated in discogenic LBP pathogenesis, has emerged as a potential adjunctive therapy. The efficacy of endoscopic radiofrequency ablation in enhancing PELD for the treatment of LBP in patients with LDH remains unclear. Methods A retrospective cohort study was conducted on LDH patients with concomitant LBP treated at the Spinal Surgery Department, China-Japan Friendship Hospital, from June 2020 to June 2023. Participants were categorized into two groups: PELD combined with SNA (n = 51) and PELD alone (n = 46). Primary outcome measures included the Visual Analog Scale (VAS) for pain, the Japanese Orthopaedic Association (JOA) score, and the Oswestry Disability Index (ODI) at baseline and 1-, 3-, and 6-month follow-ups. Results Both groups exhibited significant improvements in VAS, JOA, and ODI scores for LBP and leg pain postoperatively compared to preoperative assessments. Notably, the PELD combined with SNA group demonstrated statistically significant superior outcomes in VAS, JOA, and ODI scores specifically for LBP compared to the PELD group. Conclusion The combination of PELD with SNA significantly improves LBP outcomes compared to PELD alone in LDH patients. While the observed improvements did not reach the minimal clinically important differences (MICD), these findings suggest that SNA may enhance the efficacy of PELD in LBP management.

Abstract Background Osteoarthritis (OA) is marked by the progressive degradation of joint cartilage and subchondral bone. The precise molecular mechanisms driving meniscus deterioration in OA, especially at the single-cell level, remain poorly understood. Method We analyzed two datasets from the GEO database, GSE220243 and GSE98918, focusing on meniscus tissue sequencing data from OA and non-OA patients. The standard Seurat procedure was employed to process single-cell data and identify differentially expressed genes (DEGs). Immune cell infiltration was assessed using the Microenvironment Cell Populations (MCP) counter and CIBERSORT algorithms. For the microarray data, DEGs were identified with the limma package, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using ClusterProfiler. The overlapping DEGs from both datasets were imported into Cytoscape to generate protein-protein interaction (PPI) networks and identify hub genes. Transcription factor (TF) and miRNA interaction networks were analyzed using NetworkAnalyst, and gene-related predictive drugs were enriched through the DSigDB platform. Result After quality control, 34,763 cells from the OA patients and 34,145 cells from the healthy controls were analyzed. UMAP identified and SingleR annotated 14 cell clusters. The 10 largest cell clusters were selected for further analysis. The OA group exhibited a notable increase in macrophages and a reduction in cytotoxic lymphocytes and endothelial cells in the meniscus. In GSE98918, 220 DEGs were identified, and the MCODE plug-in in Cytoscape pinpointed a key module containing 12 candidate genes. The MCC methodfiltered the top 20 DEGs in each GSE220243 cluster. Overlapping DEGs from GSE220243 and GSE98918 identified COL1A1, COL3A1, COL5A2, COL6A3, LOX, and VEGFA as significantly decreased in OA, with COL3A1, COL5A2, LOX, and VEGFA upregulated in meniscal chondrocytes. The interaction network highlighted 3 key miRNAs and 13 shared TFs. Ten gene-related predictive drug molecules were identified. Conclusion This research highlights crucial genes in the OA meniscus and uncovers their differing regulatory patterns between chondrocytes and non-chondrocytes. These findings enhance our understanding of the molecular mechanisms driving OA pathogenesis and aid in identifying potential drug targets.

Abstract Objective This study aims to investigate how the impact of preoperative sarcopenia and inflammatory markers for laryngeal cancer patients and develop a new scoring system to predict their prognosis. Materials and methods Patients who underwent laryngectomy for laryngeal cancer (LC) from December 2015 to December 2020 at the Second Affiliated Hospital of Fujian Medical University were included. Independent prognostic factors were determined using univariate and multivariate analyses. A new scoring system (SFAR) was established based on FAR and preoperative sarcopenia, and statistically analyzed. Results 198 cases included in this study that met the admission criteria. Multivariate analysis shown that preoperative sarcopenia, pTNM stage, and FAR were independent prognostic factors for laryngeal cancer. Based on these three indicators, we developed the SFAR scoring system. Multivariate analysis showed that SFAR was an independent predictor of laryngeal cancer (p

Abstract Artificial intelligence empowers the rapid development of autonomous intelligent systems (AISs), but it still struggles to cope with open, complex, dynamic, and uncertain environments, limiting its large-scale industrial application. Reliable human feedback provides a mechanism for aligning machine behavior with human values and holds promise as a new paradigm for the evolution and enhancement of machine intelligence. This paper analyzes the engineering insights from ChatGPT and elaborates on the evolution from traditional feedback to human feedback. Then, a unified framework for self-evolving intelligent driving (ID) based on human feedback is proposed. Finally, an application in the congested ramp scenario illustrates the effectiveness of the proposed framework.

Abstract Background Percutaneous endoscopic lumbar discectomy (PELD) has demonstrated efficacy in alleviating leg pain among patients with lumbar disc herniation. Nonetheless, residual back pain persists as a troubling issue for surgeons following the procedure. In the treatment of discogenic back pain, sinuvertebral nerve radiofrequency ablation has shown promising results. Nevertheless, the potential benefit of simultaneously implementing sinuvertebral nerve radiofrequency ablation during PELD surgery to address residual back pain has not been thoroughly investigated in current literature. Methods This retrospective study reviewed Lumbar disc herniation (LDH) patients with low back pain who underwent combined PELD and sinuvertebral nerve ablation in our department between January 2021 and September 2023. Residual low back pain post-surgery was assessed and compared with existing literature. Results A total of 80 patients, including 53 males and 27 females, were included in the study. Following surgical intervention, patients demonstrated remarkable improvements in pain and functional parameters. One month post-operatively, the VAS score for low back pain exhibited a 75% reduction (6.45 ± 1.3 to 1.61 ± 1.67), while the VAS score for leg pain decreased by 85% (7.89 ± 1.15 to 1.18 ± 1.26). Notably, the JOA score increased from 12.89 ± 5.48 to 25.35 ± 4.96, and the ODI score decreased form 59.48 ± 9.58 to 20.3 ± 5.37. These improvements were sustained at three months post-operatively. According to the modified Mac Nab criteria, the excellent and good rate was 88.75%. Residual low back pain is observed to be comparatively reduced compared to the findings documented in earlier literature. Conclusion The combination of percutaneous endoscopic lumbar discectomy and sinuvertebral nerve ablation demonstrates effective improvement in low back pain for LDH patients.

Semantic segmentation of high-resolution multispectral remote sensing image has been intensely studied. However, the shadow occlusions, or the similar color and textures, between the categories influence the segmentation accuracy. Concomitantly, the size of targets in the remote sensing images is diverse and the network cannot balance their segmentation. This paper introduces a network, Transformer-based Multi-modal Fusion Network (TMFNet), which fuses the multi-modal features and incorporates height features from the digital surface model (DSM) to supplement the extra different features between each category. Particularly, we introduce two parallel encoders to extract the features from different modalities, a Multi-Modal fusion model based on the Transformer (MMformer) to complete the multi-modal fusion, and a Border Region Attention based multi-level Fusion Module (BRAFM) to integrate the cross-level features and enhance the small target segmentation by utilizing the details around the border. The experiment results on the ISPRS Vaihingen and Potsdam benchmark datasets indicate that the proposed TMFNet outperforms the SOTA methods on the segmentation performance.

Abstract Existing monocular depth estimation driving datasets are limited in the number of images and the diversity of driving conditions. The images of datasets are commonly in a low resolution and the depth maps are sparse. To overcome these limitations, we produce a Synthetic Digital City Dataset (SDCD) which was collected under 6 different weather driving conditions, and 6 common adverse perturbations caused by the data transmission. SDCD provides a total of 930 K high-resolution RGB images and corresponding perfect observed depth maps. The evaluation shows that depth estimation models which are trained on SDCD provide a clearer, smoother, and more precise long-range depth estimation compared to those trained on one of the best-known driving datasets KITTI. Moreover, we provide a benchmark to investigate the performance of depth estimation models in different adverse driving conditions. Instead of collecting data from the real world, we generate the SDCD under severe driving conditions with perfect observed data in the digital world, enhancing depth estimation for autonomous driving.

Decision-making and motion planning are extremely important in autonomous driving to ensure safe driving in a real-world environment. This study proposes an online evolutionary decision-making and motion planning framework for autonomous driving based on a hybrid data- and model-driven method. First, a data-driven decision-making module based on deep reinforcement learning (DRL) is developed to pursue a rational driving performance as much as possible. Then, model predictive control (MPC) is employed to execute both longitudinal and lateral motion planning tasks. Multiple constraints are defined according to the vehicle’s physical limit to meet the driving task requirements. Finally, two principles of safety and rationality for the self-evolution of autonomous driving are proposed. A motion envelope is established and embedded into a rational exploration and exploitation scheme, which filters out unreasonable experiences by masking unsafe actions so as to collect high-quality training data for the DRL agent. Experiments with a high-fidelity vehicle model and MATLAB/Simulink co-simulation environment are conducted, and the results show that the proposed online-evolution framework is able to generate safer, more rational, and more efficient driving action in a real-world environment.

Abstract With the tremendous success of machine learning (ML), concerns about their black-box nature have grown. The issue of interpretability affects trust in ML systems and raises ethical concerns such as algorithmic bias. In recent years, the feature attribution explanation method based on Shapley value has become the mainstream explainable artificial intelligence approach for explaining ML models. This paper provides a comprehensive overview of Shapley value-based attribution methods. We begin by outlining the foundational theory of Shapley value rooted in cooperative game theory and discussing its desirable properties. To enhance comprehension and aid in identifying relevant algorithms, we propose a comprehensive classification framework for existing Shapley value-based feature attribution methods from three dimensions: Shapley value type, feature replacement method, and approximation method. Furthermore, we emphasize the practical application of the Shapley value at different stages of ML model development, encompassing pre-modeling, modeling, and post-modeling phases. Finally, this work summarizes the limitations associated with the Shapley value and discusses potential directions for future research.

Abstract Background Markers that can be used to evaluate the prognosis of patients with head and neck squamous cell carcinoma (HNSCC) remain undefined. Objective This study aimed to investigate the prognostic impact of preoperative neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR) in patients with HNSCC who underwent surgery-based treatment for the first time. Methods This retrospective study included patients HNSCC who underwent surgery-based treatment at our institution between January 2018 and December 2020. Specificity and sensitivity were analyzed using receiver operating characteristic (ROC) curves and the critical value was determined. Patients were divided into low and high groups according to NLR, PLR, and LMR the critical value. Log-rank and Cox proportional hazards models were used to evaluate the associations between preoperative NLR, PLR, LMR, and overall survival (OS). Results A total of 304 patients with HNSCC were included, of whom 190 (62.5%) and 114 (37.5%), 203 (66.8%) and 101 (33.2%), 98 (32.2%), and 206 (67.8%) cases were classified as low NLR and high NLR groups, low PLR and high PLR groups, and low LMR and high LMR groups, respectively. Univariate analysis showed that white blood cell count (WBC), neutrophil count (NEU), platelet count (PLT), NLR, pathologic N stage (pN stage), TNM stage and postoperative complications were significantly associated with OS (p

Summary: Cooperative vehicle-infrastructure system (CVIS) is an important part of the intelligent transport system (ITS). Autonomous vehicles have the potential to improve safety, efficiency, and energy saving through CVIS. Although a few CVIS studies have been conducted in the transportation field recently, a comprehensive analysis of CVIS is necessary, especially about how CVIS is applied in autonomous vehicles. In this paper, we overview the relevant architectures and components of CVIS. After that, state-of-the-art research and applications of CVIS in autonomous vehicles are reviewed from the perspective of improving vehicle safety, efficiency, and energy saving, including scenarios such as straight road segments, intersections, ramps, etc. In addition, the datasets and simulators used in CVIS-related studies are summarized. Finally, challenges and future directions are discussed to promote the development of CVIS and provide inspiration and reference for researchers in the field of ITS.

Abstract Currently licensed influenza vaccines focus immune responses on viral hemagglutinin (HA), while the other major surface glycoprotein neuraminidase (NA) is not tightly controlled in inactivated vaccine formulations despite evidence that anti-NA antibodies reduce clinical disease. We utilized a bicistronic self-amplifying mRNA (sa-mRNA) platform encoding both HA and NA from four seasonal influenza strains, creating a quadrivalent influenza vaccine. sa-mRNA vaccines encoding an NA component induced the production of NA-inhibiting antibodies and CD4+ T-cell responses in both monovalent and quadrivalent formulations. Including NA in the vaccine enabled cross-neutralization against antigenically drifted strains and provided greater protection than HA alone upon A(H3N2) challenge in ferrets. These results demonstrate that next-generation bicistronic sa-mRNA vaccines expressing HA and NA induce potent antibodies against both viral coat proteins, as well as vaccine-specific cell-mediated immunity. When formulated as a quadrivalent seasonal influenza vaccine, the sa-mRNA platform provides an opportunity to increase the breadth of protection through cross-neutralizing anti-NA antibodies.

Abstract Background The application of coagulation-related markers in laryngeal squamous cell carcinoma(LSCC) remains unclear. This study explored the prognostic role of coagulation markers in the progression and metastasis of LSCC. Methods Coagulation markers of patients with LSCC receiving surgery in the Second Affiliated Hospital of Fujian Medical University in China, from January 2013 to May 2022 were retrospectively analyzed and compared with those of contemporary patients with benign laryngeal diseases. The relationship between clinicopathological features of LSCC and coagulation markers was analyzed with the chi-square and rank sum tests. The ROC curve analysis was utilized to evaluate the diagnostic efficacy of seven coagulation markers for LSCC and its different clinicopathological features, and to find the optimal cutoff value of each coagulation marker. Results 303 patients with LSCC and 533 patients with benign laryngeal diseases were included in the present analysis. Compared to the control group, prothrombin time (PT) (p

Chitosan was used as the raw material. A quaternization reaction was carried out between 2,3-epoxypropyltrimethylammonium chloride and water-soluble chitosan to prepare quaternary ammonium salt water-soluble chitosan (QWSC), and its corrosion inhibition performance against the corrosion of carbon steel in stone processing wastewater was evaluated. The corrosion inhibition efficiencies of QWSC on carbon steel in stone processing wastewater were investigated through weight loss, as well as electrochemical and surface morphology characterization techniques. The results show that QWSC has superior corrosion inhibition performance for A3 carbon steel. When an amount of 60 mL·L−1 is added, the corrosion inhibition efficiency can reach 59.51%. Electrochemical research has shown that a QWSC inhibitor is a mixed-type corrosion inhibitor. The inhibition mechanisms of the QWSC inhibitor revealed that the positive charge on the surface of carbon steel in stone wastewater was conducive to the adsorption of Cl− in the medium, which produced an excessive negative charge on the metal’s surface. At the same time, the quaternary ammonium cation and amino cation formed in QWSC in stone processing wastewater can be physically absorbed on the surface of A3 carbon steel, forming a thin-film inhibitor to prevent metal corrosion.

Abstract Model predictive control is widely used in the design of autonomous driving algorithms. However, its parameters are sensitive to dynamically varying driving conditions, making it difficult to be implemented into practice. As a result, this study presents a self-learning algorithm based on reinforcement learning to tune a model predictive controller. Specifically, the proposed algorithm is used to extract features of dynamic traffic scenes and adjust the weight coefficients of the model predictive controller. In this method, a risk threshold model is proposed to classify the risk level of the scenes based on the scene features, and aid in the design of the reinforcement learning reward function and ultimately improve the adaptability of the model predictive controller to real-world scenarios. The proposed algorithm is compared to a pure model predictive controller in car-following case. According to the results, the proposed method enables autonomous vehicles to adjust the priority of performance indices reasonably in different scenarios according to risk variations, showing a good scenario adaptability with safety guaranteed.

Abstract This study aimed to investigate the prognostic impact of lymphovascular and perineural invasions in patients with squamous cell carcinoma of the tongue who received surgery-based treatment at our institution between January 2013 and December 2020. Patients were divided into four groups based on the presence of perineural (P−/P +) and lymphovascular invasions (V−/V +): P–V−, P–V + , P + V−, and P + V + . Log-rank and Cox proportional hazard models were used to evaluate the association between perineural /lymphovascular invasion and overall survival (OS). Altogether, 127 patients were included, and 95 (74.8%), 8 (6.3%), 18 (14.2%), and 6 (4.7%) cases were classified as P–V−, P–V + , P + V−, and P + V + , respectively. Pathologic N stage (pN stage), tumor stage, histological grade, lymphovascular invasion, perineural invasion, and postoperative radiotherapy were significantly associated with OS (p

The effect of a high-fat diet (HFD) on mood is a widely debated topic, with the underlying mechanisms being poorly understood. This study explores the anxiolytic effects of a four-week HFD in C57BL/6 mice. Five-week-old mice were exposed to either an HFD (60% calories from fat) or standard chow diet (CD) for four weeks, followed by cannula implantation, virus infusion, behavioral tests, and biochemical assays. Results revealed that four weeks of an HFD induced anxiolytic-like behaviors and increased the protein levels of mature brain-derived neurotrophic factor (mBDNF) and phosphorylated tyrosine kinase receptor B (p-TrkB) in the medial prefrontal cortex (mPFC). Administration of a BDNF-neutralizing antibody to the mPFC reversed HFD-induced anxiolytic-like behaviors. Elevated BDNF levels were observed in both neurons and astrocytes in the mPFC of HFD mice. Additionally, these mice exhibited a higher number of dendritic spines in the mPFC, as well as upregulation of postsynaptic density protein 95 (PSD95). Furthermore, mRNA levels of the N6-methyladenosine (m6A) demethylase, fat mass and obesity-associated protein (FTO), and the hydrolase matrix metalloproteinase-9 (MMP9), also increased in the mPFC. These findings suggest that an HFD may induce FTO and MMP9, which could potentially regulate BDNF processing, contributing to anxiolytic-like behaviors. This study proposes potential molecular mechanisms that may underlie HFD-induced anxiolytic behaviors.

Summary: Severe weather conditions pose a significant challenge for computer vision algorithms in autonomous driving applications, particularly regarding robustness. Image rain-removal algorithms have emerged as a potential solution by leveraging the power of neural networks to restore rain-free backgrounds in images. However, existing research overlooks the vulnerability concerns in neural networks, which exposes a potential threat to the intelligent perception of autonomous vehicles in rainy conditions. This paper proposes a universal rain-removal attack (URA) that exploits the vulnerability of image rain-removal algorithms. By generating a non-additive spatial perturbation, URA significantly diminishes scene restoration similarity and image quality. The imperceptible and generic perturbation employed by URA makes it a crucial tool for vulnerability detection in image rain-removal algorithms and a potential real-world AI attack method. Experimental results demonstrate that URA can reduce scene repair capability by 39.5% and image generation quality by 26.4%, effectively targeting state-of-the-art rain-removal algorithms.

Abstract The disposal of waste oil, paint and coating barrels (WOPCBs) after use is an ongoing social and environmental problem. In this paper, a novel technological scheme using steel converter co-processing is proposed for the safe disposal and resource utilization of WOPCBs. The scheme is mainly composed of WOPCBs pretreatment and converter disposal, focusing on the impact of converter co-processing WOPCBs on the environment and production process. Compared to the traditional technology, the scheme presented takes full advantages of the production process and environmental protection facilities of steel converter, and has many advantages, such as a large disposal capacity, low cost, highly efficient and environmentally friendly. The industrial trials results show that after adding 180–540 kg WOPCBs to each furnace load (nominal capacity 250 t), the converter operation is safe and controllable, and all the pollutant emission indicators generated in the process meet the Chinese national standards. In addition, WOPCBs are suitable to be used as a supplementary material for scrap steel. Therefore, this study provides important insights for sustainable resource utilization from WOPCBs.

Abstract Biomolecule-functionalized fluorescent gold nanocluster (AuNCs) have attracted a lot of attention due to good biocompatibility, stable physicochemical properties and considerable cost advantages. Inappropriate concentration of Cu2+ may cause a variety of diseases. In this study, AuNCs were synthesized in alkaline aqueous solution using bovine serum albumin (BSA) as a template. And then, the peptide CCYWDAHRDY was coupled to AuNCs. Furthermore, the fluorescence of synthesized CCYWDAHRDY-AuNCs response to Cu2+ was evaluated. As the results shown that the CCYWDAHRDY-AuNCs can sensitively detect Cu2+. After adding Cu2+ to the probe system, the fluorescence of the CCYWDAHRDY-AuNCs was quenched. The detection conditions were at pH 6 and 30 °C for 10 min, the linear relationship between Cu2+ concentration and fluorescence intensity were good in the range of 0.1 ~ 4.2 μmol/L. The regression equation was y = − 105.9x + 693.68, the linear correlation coefficient is 0.997, and the minimum detection limit was 52 nmol/L.

Abstract An autonomous vehicle (AV) is a cyber‐physical system (CPS) incorporating dynamics, perception sensors (e.g. camera and radar), embedded electronic control units (ECUs) and in‐vehicle networking (e.g. CAN, LIN and FlexRay).Achieving path‐following control of an AV to track a desired path is therefore a highly non‐linear task that is naturally vulnerable to denial‐of‐service (DoS) attacks. Considering that DoS attacks can inhibit the services of a control system by overwhelming the performance capabilities of the ECUs or the bus, this paper investigates the cyber‐physical system problem of path‐following control for AVs under intermittent DoS attacks. To solve this problem, we propose resilient observer‐based non‐linear control based on the triple‐step approach. The core ideas behind this method are the integrated design of the observer and feedback gains incorporating the DoS duration and the convex design of controller parameters by solving a set of linear matrix inequalities. The proposed control scheme guarantees that the closed‐loop system maintains input‐to‐stable stability, while the error signals theoretically converge to a small neighbourhood of the origin. The effectiveness of the proposed approach is confirmed by the simulation results obtained for a high‐fidelity veDYNA full‐vehicle model with different driving tests and DoS attacks.

Abstract A comparative study of model predictive control (MPC) schemes and robust $$H_{\infty }$$ H ∞ state feedback control (RSC) method for trajectory tracking is proposed in this paper. The main objective of this paper is to compare MPC and RSC controllers’ performance in tracking predefined trajectory under different scenarios. MPC controller is designed based on the simple longitudinal-yaw-lateral motions of a single-track vehicle with a linear tire, which is an approximation of the more realistic model of a vehicle with double-track motion with a non-linear tire mode. RSC is designed on the basis of the same method as adopted for the MPC controller to achieve a fair comparison. Then, three test cases are built in CarSim-Simulink joint platform. Specifically, the verification test is used to test the tracking accuracy of MPC and RSC controller under well road conditions. Besides, the double lane change test with low road adhesion is designed to find the maximum velocity that both controllers can carry out while guaranteeing stability. Furthermore, an extreme curve test is built where the road adhesion changes suddenly, in order to test the performance of both controllers under extreme conditions. Finally, the advantages and disadvantages of MPC and RSC under different scenarios are also discussed.

Abstract Vertical tire forces are essential for vehicle modelling and dynamic control. However, an evaluation of the vertical tire forces on a multi-axle truck is difficult to accomplish. The current methods require a large amount of experimental data and many sensors owing to the wide variation of the parameters and the over-constraint. To simplify the design process and reduce the demand of the sensors, this paper presents a practical approach to estimating the vertical tire forces of a multi-axle truck for dynamic control. The estimation system is based on a novel vertical force model and a proposed adaptive treble extend Kalman filter (ATEKF). To adapt to the widely varying parameters, a sliding mode update is designed to make the ATEKF adaptive, and together with the use of an initial setting update and a vertical tire force adjustment, the overall system becomes more robust. In particular, the model aims to eliminate the effects of the over-constraint and the uneven weight distribution. The results show that the ATEKF method achieves an excellent performance in a vertical force evaluation, and its performance is better than that of the treble extend Kalman filter.

Summary: Carbon quantum dots (CQDs) are highly promising to be applied in light-emitting, chemosensing, and other cutting-edge domains. Herein, we successfully fabricate high-quality full-color CQDs under unprecedentedly low temperature and pressure (85°C, 1.88 bar). Stable and narrow fluorescent emissions ranging from blue to green and red light were realized by simple amine engineering, which were further mixed into white-light CQDs with the absolute photoluminescent quantum yield reaching 19.2%. The average mass yield of the CQDs reached 69.0%. The optical performances demonstrated that the CQDs possessed uniform luminescent centers and dominant radiative decay channels. Component analysis further suggested that dehydrated condensation between carboxyl and amine groups directed the growth of the CQDs. By utilizing the CQDs, full-color light-emitting diodes and logic gate sensors were developed. This study paves an important step for promoting the application of CQDs by providing an energy-efficient, safe, and productive synthetic strategy.

Brain iron is precisely regulated, and disrupted brain iron homeostasis is implicated in neuropsychological disease. Mounting evidence connects the iron status of the substantia nigra (SN) with locomotion-related neural symptomatology. Researchers in this field have long speculated that iron deficiency in the SN directly causes the high-locomotion symptoms observed in neuropsychiatric disorders. However, no direct experimental evidence of a causal relationship has been presented. To explore the relationship between iron deficiency in the SN and locomotion-related phenotypes, we stereotaxically injected the well-documented iron chelator, deferiprone (DFP) into the SN of mice to induce regional brain iron deprivation and subsequently performed behavioral tests. Altered expression of iron metabolism-related molecules was detected in the brain regions with interventions, and behavioral changes were observed. Targeted iron chelation effectively decreased the local iron content of the SN. Among the brain regions examined, only DFP injected into the SN resulted in the hyperlocomotion phenotype. Upon SN iron chelation, transferrin receptor (Tfr) expression was found to be upregulated. Conversely, viral vector-mediated SN-Tfr knockdown was sufficient to induce SN iron deficiency and mimic the hyperlocomotion phenotype. All locomotion changes had a significant negative correlation with iron alteration in the SN. Furthermore, SN iron disturbance also contributed to poor sleep efficiency. Thus, SN iron deficiency directly contributed to triggering both hyperlocomotion and sleep disturbances. This study offers a promising research and therapeutic direction for iron-linked neuropsychiatric diseases.

A novel pyridine-modified chitosan (PYCS) adsorbent was prepared in a multistep procedure including the successive grafting of 2-(chloromethyl) pyridine hydrochloride and crosslinking with glutaraldehyde. Then, the as-prepared materials were used as adsorbents for the removal of metal ions from acidic wastewater. Batch adsorption experiments were carried out to study the impact of various factors such as solution pH value, contact time, temperature, and Fe (III) concentration. The results showed that the absorbent exhibited a high capacity of Fe (III) and the maximum adsorption capacity was up to 66.20 mg/g under optimal experimental conditions (the adsorption time = 12 h, pH = 2.5, and T = 303 K). Adsorption kinetics and isotherm data were accurately described by the pseudo-second-order kinetic model and Sips model, respectively. Thermodynamic studies confirmed that the adsorption was a spontaneous endothermic process. Moreover, the adsorption mechanism was investigated using Fourier transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS). The results revealed the pyridine group forms a stable chelate with iron (III) ions. Therefore, this acid-resistant adsorbent exhibited excellent adsorption performance for heavy metal ions from acidic wastewater compared to the conventional adsorbents, helping realize direct decontamination and secondary utilization.

In this study, high-performance modified biochar/alginate composite bead (MCB/ALG) adsorbents were prepared from recycled agricultural waste corncobs by a high-temperature pyrolysis and KOH/FeCl3 activation process. The prepared MCB/ALG beads were tested for the adsorption of methylene blue (MB) dye from wastewater. A variety of analytical methods, such as SEM, BET, FTIR and XRD, were used to investigate the structure and properties of the as-prepared adsorbents. The effects of solution pH, time, initial MB concentration and adsorption temperature on the adsorption performance of MCB/ALG beads were discussed in detail. The results showed that the adsorption equilibrium of MB dye was consistent with the Langmuir isothermal model and the pseudo-second-order kinetic model. The maximum adsorption capacity of MCB/ALG−1 could reach 1373.49 mg/g at 303 K. The thermodynamic studies implied endothermic and spontaneous properties of the adsorption system. This high adsorption performance of MCB/ALG was mainly attributed to pore filling, hydrogen bonding and electrostatic interactions. The regeneration experiments showed that the removal rate of MB could still reach 85% even after five cycles of experiments, indicating that MCB/ALG had good reusability and stability. These results suggested that a win-win strategy of applying agricultural waste to water remediation was feasible.

Abstract To evaluate the correlation between “hot cross bun” sign (HCBs) and disease severity in multiple system atrophy (MSA). We recruited patients with probable and possible MSA with parkinsonism (MSA-P) or the cerebellar ataxia (MSA-C) subtypes. Clinical and imaging characteristics were collected and comparison was performed between MSA-C and MSA-P cases. Spearman test was used to evaluate the correlation between HCBs and other variables. Curve estimate and general linear regression was performed to evaluate the relationship between HCBs and the Scale for Assessment and Rating of Ataxia (SARA). Unified Multiple System Atrophy Rating Scale (UMSARS) IV was used to assess the severity of disease. Multinomial ordered logistic regression was used to confirm the increased likelihood of disability for the disease. Eighty-one MSA with HCBs comprising of 50 MSA-C and 31 MSA-P were recruited. We demonstrated that the severity of HCBs showed a positive linear correlation with SARA scores in MSA-C. Multinomial ordered logistic regression test revealed that the increase in the HCBs grade may be associated with an increased likelihood of disability for the disease severity in MSA, especially in those with cerebellar ataxia subtype. We demonstrated that HCBs is a potential imaging marker for the severity of cerebellar ataxia. The increase in the HCBs grade may be associated with an increased likelihood of disability in MSA-C, but not MSA-P cases, suggesting that it may be a useful imaging indicator for disease progression in Chinese patients with MSA-C.

Summary: In the intelligent transportation system (ITS), speed prediction plays a significant role in supporting vehicle routing and traffic guidance. Recently, a considerable amount of research has been devoted to a single-level (e.g., traffic or vehicle) prediction. However, a systematic review of speed prediction in and between different levels is still missing. In this article, existing research is comprehensively analyzed and divided into three levels, i.e. macro traffic, micro vehicles, and meso lane. In addition, this article summarizes the influencing factors and reviews the prediction methods based on how those methods utilize the available information to meet the challenges of the prediction at different levels. This is followed by a summary of evaluation metrics, public datasets, and open-source codes. Finally, future directions in this field are discussed to inspire and guide readers. This article aims to draw a complete picture of speed prediction and promote the development of ITS.

Antimicrobial Photodynamic Treatment (aPDT) is a non-thermal sterilization technology, which can inactivate common foodborne pathogens. In the present study, photodynamic inactivation on Staphylococcus aureus (S. aureus) with different concentrations of curcumin and light dose was evaluated and the mechanisms were also investigated. The results showed that curcumin-based aPDT could inactivate S. aureus cells by 6.9 log CFU/mL in phosphate buffered saline (PBS). Moreover, the modified Gompertz model presented a good fit at the inactivation data of S. aureus. Photodynamic treatment caused cell membrane damage as revealed by analyzing scanning electron microscopy (SEM) images. Leakage of intracellular constituents further indicated that cell membrane permeability was changed. Flow cytometry with double staining demonstrated that cell membrane integrity and the activity of nonspecific esterase were destroyed. Compared with the control group, intracellular reactive oxygen species (ROS) levels caused by photodynamic treatment significantly increased. Furthermore, curcumin-based aPDT reduced S. aureus by 5 log CFU/mL in juices. The color of the juices was also tested using a Chromatic meter, and it was found that b* values were the most markedly influenced by photodynamic treatment. Overall, curcumin-based aPDT had strong antibacterial activity against S. aureus. This approach has the potential to remove foodborne pathogens from liquid food.

Abstract Vehicle rollover, and its resulting fatalities, is an actively researched topic especially for multi-axle vehicles in the field of vehicle dynamics and control. This paper first presents a new rollover index for a triaxle bus to accurately evaluate its rollover possibility and then discusses the influence laws of the vehicle rollover dynamics to explore the mechanism of its stability. First, a six degree of freedom rollover model of the triaxle bus is developed, including lateral, yaw, roll motion of the sprung mass of the front/rear axle, and roll motion of the unsprung mass of the front/rear axle. Next, some key parameters of the vehicle rollover model are identified. A new rollover index is deduced according to the basics of vehicle dynamics, to predict vehicle rollover risk for the triaxle bus, which is verified by TruckSim. Furthermore, the influence laws of vehicle rollover dynamics by vehicle parameters and road parameters are discussed based on the simulation results. More importantly, the results show that the new method of modeling can precisely describe the rollover dynamics of the studied bus, and the proposed new index can effectively evaluate the rollover possibility. Therefore, this study provides a theoretical basis to improve anti-rollover ability for triaxle buses.

Abstract Differential braking and active steering have already been integrated to overcome their shortcomings. However, existing research mainly focuses on two-axle vehicles and controllers are mostly designed to use one control method to improve the other. Moreover, many experiments are needed to improve the robustness; therefore, these control methods are underutilized. This paper proposes an integrated control system specially designed for multi-axle vehicles, in which the desired lateral force and yaw moment of vehicles are determined by the sliding mode control algorithm. The output of the sliding mode control is distributed to the suitable wheels based on the abilities and potentials of the two control methods. Moreover, in this method, fewer experiments are needed, and the robustness and simultaneity are both guaranteed. To simplify the optimization system and to improve the computation speed, seven simple optimization subsystems are designed for the determination of control outputs on each wheel. The simulation results show that the proposed controller obviously enhances the stability of multi-axle trucks. The system improves 68% of the safe velocity, and its performance is much better than both differential braking and active steering. This research proposes an integrated control system that can simultaneously invoke differential braking and active steering of multi-axle vehicles to fully utilize the abilities and potentials of the two control methods.

Globally, methamphetamine (MA) is the second most abused drug, with psychotic symptoms being one of the most common adverse effects. Emotional disorders induced by MA abuse have been widely reported both in human and animal models; however, the mechanisms underlying such disorders have not yet been fully elucidated. In this study, a chronic MA administration mouse model was utilized to elucidate the serotonergic pathway involved in MA-induced emotional disorders. After 4 weeks of MA administration, the animals exhibited significantly increased depressive and anxious symptoms. Molecular and morphological evidence showed that chronic MA administration reduced the expression of the 5-hydroxytryptamine (5-HT) rate-limiting enzyme, tryptophan hydroxylase 2, in the dorsal raphe and the concentrations of 5-HT and its metabolite 5-hydroxyindoleacetic acid in the basolateral amygdala (BLA) nuclei. Alterations in both 5-HT and 5-HT receptor levels occurred simultaneously in BLA; quantitative polymerase chain reaction, western blotting, and fluorescence analysis revealed that the expression of the 5-HT2C receptor (5-HT2CR) increased. Neuropharmacology and virus-mediated silencing strategies confirmed that targeting 5-HT2CR reversed the depressive and anxious behaviors induced by chronic MA administration. In the BLA, 5-HT2CR-positive cells co-localized with GABAergic interneurons. The inactivation of 5-HT2CR ameliorated impaired GABAergic inhibition and decreased BLA activation. Thus, herein, for the first time, we report that the abnormal regulation of 5-HT2CR is involved in the manifestation of emotional disorder-like symptoms induced by chronic MA use. Our study suggests that 5-HT2CR in the BLA is a promising clinical target for the treatment of MA-induced emotional disorders.

Often associated with sexual dysfunction (SD), chronic stress is the main contributing risk factor for the pathogenesis of depression. Radix bupleuri had been widely used in traditional Chinese medicine formulation for the regulation of emotion and sexual activity. As the main active component of Radix bupleuri, saikosaponin D (SSD) has a demonstrated antidepressant effect in preclinical studies. Herein, we sought to investigate the effect of SSD to restore sexual functions in chronically stressed mice and elucidate the potential brain mechanisms that might underly these effects. SSD was gavage administered for three weeks during the induction of chronic mild stress (CMS), and its effects on emotional and sexual behaviors in CMS mice were observed. The medial posterodorsal amygdala (MePD) was speculated to be involved in the manifestation of sexual dysfunctions in CMS mice. Our results revealed that SSD not only alleviated CMS-induced depressive-like behaviors but also rescued CMS-induced low sexual motivation and poor sexual performance. CMS destroyed astrocytes and activated microglia in the MePD. SSD treatment reversed the changes in glial pathology and inhibited neuroinflammatory and oxidative stress in the MePD of CMS mice. The neuronal morphological and functional deficits in the MePD were also alleviated by SSD administration. Our results provide insights into the central mechanisms involving the brain associated with sexual dysfunction. These findings deepen our understanding of SSD in light of the psychopharmacology of stress and sexual disorders, providing a theoretical basis for its potential clinical application.

Objective: To characterize the clinical phenotypes associated with the “hot cross bun” sign (HCBs) on MRI and identify correlations between neuroimaging and clinical characteristics.Methods: Firstly, we screened a cohort of patients with HCBs from our radiologic information system (RIS) in our center. Secondly, we systematically reviewed published cases on HCBs and classified all these cases according to their etiologies. Finally, we characterized all HCBs cases in detail and classified the disease spectra and their clinical heterogeneity.Results: Out of a total of 3,546 patients who were screened, we identified 40 patients with HCBs imaging sign in our cohort; systemic literature review identified 39 cases, which were associated with 14 diseases. In our cohort, inflammation [neuromyelitis optica spectrum disorders (NMOSD), multiple sclerosis (MS), and acute disseminated encephalomyelitis (ADEM)] and toxicants [toxic encephalopathy caused by phenytoin sodium (TEPS)] were some of the underlying etiologies. Published cases by systemic literature review were linked to metabolic abnormality, degeneration, neoplasm, infection, and stroke. We demonstrated that the clinical phenotype, neuroimaging characteristics, and HCBs response to therapy varied greatly depending on underlying etiologies.Conclusion: This is the first to report HCBs spectra in inflammatory and toxication diseases. Our study and systemic literature review demonstrated that the underpinning disease spectrum may be broader than previously recognized.

Parkinson’s disease (PD) is one of the most prevalent and life-threatening neurodegenerative disease and mainly characterized by lack of sufficient dopaminergic neurons in the substantia nigra pars compacta (SNc). Although current treatments help to alleviate clinical symptoms, effective therapies preventing neuronal loss remain scarce. Tovophyllin A (TA), one of the xanthones extracted from Garcinia mangostana L. (GM), has recently been reported to play a beneficial role in the therapy of neurodegenerative diseases. In our research, we explored whether TA has protective effects on dopaminergic neurons in PD models. We found that TA significantly reduced apoptotic cell death in primary cortical neurons treated with 1-methyl-4-phenyl pyridinium (MPP+) or paraquat (PQ) in the in vitro PD model. In an in vivo acute PD model induced by 1-methyl4-phenyl-1,2,3,5-tetrahydropyridine (MPTP) treatment, TA also attenuated the resulting behavioral dysfunctions and dopaminergic neuron loss. In the collected brain tissues, TA increased the phosphorylation of Akt and GSK-3β, which may be related to TA-mediated dopaminergic neuronal protective effects. In summary, our results illustrated that TA is a powerful cytoprotective agent for dopaminergic neurons in the MPTP-induced PD model, suggesting TA as a possible therapeutic candidate for PD.

Objective: The objective of this study was to investigate the roles and mechanisms of inflammatory mediators NLRP3 and IL-1β in refractory temporal epilepsy brain injury.Method: First, the brain tissue and the peripheral blood of children undergoing intractable temporal lobe epilepsy surgery were analyzed as research objects. The expression levels of NLRP3 in brain tissue and IL-1β in blood were measured. A model of temporal lobe epilepsy was established using wild-type and NLRP3 knockout 129 mice. Pilocarpine was injected intraperitoneally into the experimental group, and isovolumetric saline was injected intraperitoneally into the control group (n = 8 in each group). The expression of IL-1β in the peripheral blood, cerebral cortex, and hippocampus of mice was measured by ELISA at 3 h, 24 h, 3 days, and 7 days after modeling. Fluoro-Jade B (FJB) and TUNEL methods were used to determine necrosis and apoptosis in hippocampal neurons, respectively, and the expression of NLRP3 in the cortex was measured by immunofluorescence methods.Result: (1) The IL-1β levels in the peripheral blood of children with intractable temporal lobe epilepsy were higher than those in the control group (t = 2.813, P = 0.01). There was also a positive correlation between IL-1β expression levels and the onset time of a single convulsion in patients with refractory epilepsy (r = 0.9735, P < 0.05). The expression level of NLRP3 in the cerebral cortex of patients with refractory temporal lobe epilepsy was higher than that in the control group. (2) The expression level of NLRP3 in the hippocampus of wild-type mice increased 3 days after modeling and decreased slightly at 7 days but remained higher than that of the control group. IL-1β levels in peripheral blood were significantly higher than those in the control group at 3 days (t = 8.259, P < 0.0001). The IL-1β levels in the peripheral blood of NLRP3 knockout mice were lower than those in the wild-type group at 3 days (t = 3.481, P = 0.004). At day 7, the neuronal necrosis and apoptosis levels in the CA3 region of the hippocampus decreased.Conclusion: NLRP3 may be involved in the development of refractory temporal lobe epilepsy. Inhibiting NLRP3 may alleviate local brain injury by downregulating the IL-1β expression. The IL-1β levels in the peripheral blood of patients with refractory temporal lobe epilepsy may reflect the severity of convulsions.

Connected and automated vehicle (CAV) technologies have great potential to improve road safety. However, an emerging type of mixed traffic flow with human-driven vehicles (HDVs) and CAVs has also arisen in recent years. To improve the overall safety of this mixed traffic flow, a novel car-following model is proposed to control the driving behaviors of the above two types of vehicles in a platoon from the perspective of a mechanical system, mass-spring-damper (MSD) system. Furthermore, a quantitative index is proposed by incorporating the psychological field theory into the MSD model. The errors of spacing and speed in the car-following processes can be expressed as the accumulation of the virtual total energy, and the magnitude of the energy is used to reflect the danger level of vehicles in the mixed platoon. At the same time, the optimization model of minimum total energy is solved under the constraints of vehicle dynamics and the mechanical characteristics of the MSD system, and the optimal solutions are used as the parameters of the MSD car-following model. Finally, a mixed platoon composed of 3 CAVs and 2 HDVs without performing lane changing is tested using the driver-in-the-loop test platform. The test results show that, in the mixed platoon, CAVs can optimally adjust the intervehicle spacing by making full use of the braking distance, which also provides sufficient reaction time for the driver of HDV to avoid rear-end collisions. Furthermore, in the early stage of the emergency braking, the spacing error is the dominant factor influencing the car-following behaviors, but in the later stage of emergency braking, the speed error becomes the decisive factor of the car-following behaviors. These results indicate that the proposed car-following model and quantitative index are of great significance for improving the overall safety of the mixed traffic flow with CAVs and HDVs.

Autonomous vehicle (AV) is regarded as the ultimate solution to future automotive engineering; however, safety still remains the key challenge for the development and commercialization of the AVs. Therefore, a comprehensive understanding of the development status of AVs and reported accidents is becoming urgent. In this article, the levels of automation are reviewed according to the role of the automated system in the autonomous driving process, which will affect the frequency of the disengagements and accidents when driving in autonomous modes. Additionally, the public on-road AV accident reports are statistically analyzed. The results show that over 3.7 million miles have been tested for AVs by various manufacturers from 2014 to 2018. The AVs are frequently taken over by drivers if they deem necessary, and the disengagement frequency varies significantly from 2 × 10−4 to 3 disengagements per mile for different manufacturers. In addition, 128 accidents in 2014–2018 are studied, and about 63% of the total accidents are caused in autonomous mode. A small fraction of the total accidents (∼6%) is directly related to the AVs, while 94% of the accidents are passively initiated by the other parties, including pedestrians, cyclists, motorcycles, and conventional vehicles. These safety risks identified during on-road testing, represented by disengagements and actual accidents, indicate that the passive accidents which are caused by other road users are the majority. The capability of AVs to alert and avoid safety risks caused by the other parties and to make safe decisions to prevent possible fatal accidents would significantly improve the safety of AVs. Practical applications. This literature review summarizes the safety-related issues for AVs by theoretical analysis of the AV systems and statistical investigation of the disengagement and accident reports for on-road testing, and the findings will help inform future research efforts for AV developments.

Abstract Background In previous studies, we have shown that the combination of metformin and gefitinib inhibits the growth of bladder cancer cells. Here we examined whether the metformin analogue phenformin, either used alone or in combination with gefitinib, could inhibit growth of bladder cancer cells. Methods The growth-inhibitory effects of phenformin and gefitinib were tested in one murine and two human bladder cancer cell lines using MTT and clonogenic assays. Effects on cell migration were assessed in a wound healing assay. Synergistic action between the two drugs was assessed using CompuSyn software. The potential involvement of AMPK and EGFR pathways in the effects of phenformin and gefitinib was explored using Western blotting. Results In MTT and clonogenic assays, phenformin was > 10-fold more potent than metformin in inhibiting bladder cancer cell growth. Phenformin also potently inhibited cell migration in wound healing assays, and promoted apoptosis. AMPK signaling was activated; EGFR signaling was inhibited. Phenformin was synergistic with gefitinib, with the combination of drugs showing much stronger anticancer activity and apoptotic activation than phenformin alone. Conclusions Phenformin shows potential as an effective drug against bladder cancer, either alone or in combination with gefitinib.

Starch is one of the most popular nutritional sources for both human and animals. Due to the variation of its nutritional traits and biochemical specificities, starch has been classified into rapidly digestible, slowly digestible and resistant starch. Resistant starch has its own unique chemical structure, and various forms of resistant starch are commercially available. It has been found being a multiple-functional regulator for treating metabolic dysfunction. Different functions of resistant starch such as modulation of the gut microbiota, gut peptides, circulating growth factors, circulating inflammatory mediators have been characterized by animal studies and clinical trials. In this mini-review, recent remarkable progress in resistant starch on gut microbiota, particularly the effect of structure, biochemistry and cell signaling on nutrition has been summarized, with highlights on its regulatory effect on gut microbiota.

In recent years, increasing concerns regarding environmental pollution and requirements for lower fossil fuel consumption have increased interest in alternative hybrid powertrains. As a result, this paper presents a novel hydraulic/electric synergy powertrain with multiple working modes. The three energy sources (i.e., engine, battery, and hydraulic accumulator) in this configuration are regulated by a dual planetary gear set to achieve optimal performances. This paper selects the component sizes of a hybrid electric vehicle (HEV), a hydraulic hybrid vehicle (HHV), and a hydraulic/electric synergy vehicle (HESV), based on the dynamic performance of a target vehicle (TV). In addition, this paper develops the forward simulation models of the four aforementioned vehicles in the MATLAB/Simulink/Driveline platform, in which the fuel economy simulations are carried out in relation to the Chinese urban bus cycle. The simulation results show that the fuel consumption of the three hybrid vehicles is similar, but much better than, that of the TV. Finally, based on the operating cost calculations over a five-year working period, the lowest cost ranges of the three hybrid vehicles are determined, which provides a method for choosing the optimal hybrid scheme.