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Abstract The global environmental issue of soil contamination with antibiotic-resistance genes has garnered increased attention in recent years due to its impact on ecosystems and human health. Despite this recognition, researchers face challenges in comprehensively understanding the mechanisms underlying the production and dissemination of soil resistance genes, particularly in relation to their implications for human health. This lack of understanding poses a barrier to the development of effective and precise control strategies. Biochar, a sustainable material, exhibits favorable adsorption properties characterized by its large pores and specific surface area. Therefore, we propose to explore the potential application of biochar addition in soil resistance gene management. In order to establish a solid research foundation in this area, in this paper we review the mechanisms underlying the generation and accumulation of soil resistance genes over the last decade, along with their transmission pathways and interfacial interactions. Biochar may help repair soil resistance genes by affecting factors like antibiotic levels, environmental conditions, enzymatic activity, and gene migration mechanisms, opening up new research possibilities. Graphical Abstract

Network performance evaluation is crucial in ensuring the effective operation of 5G wireless networks, offering valuable insights into evaluating network status and user experience. However, the complexity of network conditions, characterized by high dynamics and diverse user requirements across various vertical applications, presents a significant challenge for generating accurate and detailed evaluation results using existing algorithms. To provide a feasible solution for this issue, an artificial intelligence-enabled 5G network performance evaluation scheme for private 5G networks is proposed. First, the network performance evaluation at different granularities is modeled with the deployment of network performance evaluation introduced. Furthermore, an intelligent network performance evaluation architecture based on residual networks with the attention mechanism is introduced, which can generate evaluation scores based on key performance indicators of reliability, accessibility, utilization, integrity, mobility and retainability. Additionally, the corresponding training strategies for the intelligent model, catering to different evaluation granularity, are thoroughly designed. Finally, to validate the effectiveness of the proposed scheme, comprehensive experiments are conducted using practical 5G network operation system data. The experimental results demonstrate the scheme’s ability to achieve highly accurate evaluations with fine spatial granularity. These findings establish the feasibility and efficacy of the proposed artificial intelligence-enabled scheme in enhancing 5G network performance evaluation.

Abstract Rural areas are at the forefront of achieving sustainable development goals, and elite actors tend to be the most influential local decision-makers in rural development. Nevertheless, improving the effectiveness of governance by elites and avoiding or redressing “elite capture” remain key challenges for sustainable rural development globally. This research integrates a large-scale quantitative dataset consisting of 604 villages in seven counties of Jiangsu province in China with qualitative data from eight villages in three out of the seven counties to examine whether and how collective action mediates the correlation between rural elites and rural development. Our quantitative analysis using multiple regression and path analysis indicates that collective action is a mediator, but it is more influential in linking governing elites than in linking economic elites with rural development. Our case studies with interviews further illuminate that collective action fuels rural development by improving resource reallocation and resource-use efficiency with the participation of both elites and non-elites. Innovative collective action designs that leverage a reputation effect to foster reciprocity norms promote the participation of elites while discouraging elite capture. Additionally, this research contributes to longstanding debates in commons governance about the role of authority interventions: we find evidence justifying the benefits of authority in catalyzing and sustaining collective action while also corroborating the critical role of democratization in improving rural governance by elites.

ABSTRACTBackground Dental caries is a multifactorial disease, and the bacteria such as Streptococcus mutans (S. mutans) is one of the risk factors. The poor effect of existing anti-bacterial is mainly related to drug resistance, the short time of drug action, and biofilm formation.Methods To address this concern, we report here on the cinnamaldehyde (CA) loaded chitosan (CS) nanocapsules (CA@CS NC) sustained release CA for antibacterial treatment. The size, ζ-potential, and morphology were characterized. The antibacterial activities in vitro were studied by growth curve assay, pH drop assay, biofilm assay, and qRT-PCR In addition, cytotoxicity assay, organ index, body weight, and histopathology results were analyzed to evaluate the safety and biocompatibility in a rat model.Results CA@CS NC can adsorb the bacterial membrane due to electronic interaction, releasing CA slowly for a long time. At the same time, it has reliable antibacterial activity against S. mutans and downregulated the expression levels of QS, virulence, biofilm, and adhesion genes. In addition, it greatly reduced the cytotoxicity of CA and significantly inhibited dental caries in rats without obvious toxicity.Conclusion Our results showed that CA@CS NC had antibacterial and antibiofilm effects on S. mutans and inhibit dental caries. Besides, it showed stronger efficacy and less toxicity, and was able to adsorb bacteria releasing CA slowly, providing a new nanomaterial solution for the treatment of dental caries.

Atmospheric mercury plays a crucial role in the biogeochemical cycle of mercury. This study conducted an intensive measurement of atmospheric mercury from 2015 to 2018 at a regional site in eastern China. During this period, the concentration of particle-bound mercury (PBM) decreased by 13%, which was much lower than those of gaseous elemenral mercury (GEM, 30%) and reactive gaseous mercury (GOM, 62%). The gradual decrease in the correlation between PBM and CO, K, and Pb indicates that the influence of primary emissions on PBM concentration was weakening. Moreover, the value of the partitioning coefficient (Kp) increased gradually from 0.05 ± 0.076 m3/μg in 2015 to 0.16 ± 0.37 m3/μg in 2018, indicating that GOM was increasingly inclined to adsorb onto particulate matter. Excluding the influence of meteorological conditions and the primary emissions, the change in aerosol composition is designated as the main trigger factor for the increasing gas-particle partitioning of reactive mercury (RM). The increasing ratio of Cl−, NO3−, and organics (Org) in the chemical composition of particle matters (PM2.5), as well as the decrease in the proportion of SO42−, NH4+, and K+, are conducive to the adsorption of GOM onto particles, forming PBM, which led to an increase of Kp and a lag of PBM reduction compared to GEM and GOM under the continuous control measures of anthropogenic mercury emissions. The evolution of aerosol compositions in recent years affects the migration and transformation of atmospheric mercury, which in turn can affect the biogeochemical cycle of mercury.

Human glutaminyl cyclase (hQC) is drawing considerable attention and emerging as a potential druggable target for Alzheimer's disease (AD) due to its close involvement in the pathology of AD via the post-translational pyroglutamate modification of amyloid-β. A recent phase 2a study has shown promising early evidence of efficacy for AD with a competitive benzimidazole-based QC inhibitor, PQ912, which also demonstrated favorable safety profiles. This finding has sparked new hope for the treatment of AD. In this review, we briefly summarize the discovery and evolution of hQC inhibitors, with a particular interest in classic Zinc binding group (ZBG)-containing chemicals reported in recent years. Additionally, we highlight several high-potency inhibitors and discuss new trends and challenges in the development of QC inhibitors as an alternative and promising disease-modifying therapy for AD.

Abstract Background Protein–protein interactions are widespread in biological systems and play an important role in cell biology. Since traditional laboratory-based methods have some drawbacks, such as time-consuming, money-consuming, etc., a large number of methods based on deep learning have emerged. However, these methods do not take into account the long-distance dependency information between each two amino acids in sequence. In addition, most existing models based on graph neural networks only aggregate the first-order neighbors in protein–protein interaction (PPI) network. Although multi-order neighbor information can be aggregated by increasing the number of layers of neural network, it is easy to cause over-fitting. So, it is necessary to design a network that can capture long distance dependency information between amino acids in the sequence and can directly capture multi-order neighbor information in protein–protein interaction network. Results In this study, we propose a multi-hop neural network (LDMGNN) model combining long distance dependency information to predict the multi-label protein–protein interactions. In the LDMGNN model, we design the protein amino acid sequence encoding (PAASE) module with the multi-head self-attention Transformer block to extract the features of amino acid sequences by calculating the interdependence between every two amino acids. And expand the receptive field in space by constructing a two-hop protein–protein interaction (THPPI) network. We combine PPI network and THPPI network with amino acid sequence features respectively, then input them into two identical GIN blocks at the same time to obtain two embeddings. Next, the two embeddings are fused and input to the classifier for predict multi-label protein–protein interactions. Compared with other state-of-the-art methods, LDMGNN shows the best performance on both the SHS27K and SHS148k datasets. Ablation experiments show that the PAASE module and the construction of THPPI network are feasible and effective. Conclusions In general terms, our proposed LDMGNN model has achieved satisfactory results in the prediction of multi-label protein–protein interactions.

BackgroundCoronary artery calcification (CAC) is associated with high rates of restenosis and adverse clinical events after percutaneous coronary intervention (PCI) with drug-eluting stents (DES).ObjectivesThe aim of this study was to evaluate the long-term clinical outcomes of drug-coated balloon (DCB)-only treatment for de novo lesions with and without CAC.MethodsPatients with de novo coronary disease treated with the DCB-only strategy were retrospectively enrolled from three centers and categorized into a CAC group and a non-CAC group. The primary endpoint was the target lesion failure (TLF) rate during the 3-year follow-up. Secondary endpoints included the occurrence of major adverse cardiac events (MACEs), target lesion revascularization (TLR), cardiac death, myocardial infarction (MI) and any revascularization. Propensity score matching (PSM) was conducted to assemble a cohort of patients with similar baseline characteristics.ResultsA total of 1,263 patients with 1,392 lesions were included, and 243 patients were included in each group after PSM. Compared with the non-CAC group, the incidence rates of TLF (9.52% vs. 4.94%, odds ratio [OR]: 2.080; 95% confidence interval [CI]: 1.083–3.998, P = 0.034) and TLR (7.41% vs. 2.88%, OR: 2.642; 95% CI: 1.206–5.787, P = 0.020) in the CAC group were higher. The incidence rates of MACE (12.35% vs. 7.82%, OR: 1.665; 95% CI: 0.951–2.916, P = 0.079), cardiac death (2.06% vs. 2.06%, OR: 0.995; 95% CI: 0.288–3.436, P = 0.993), MI (1.23% vs. 0.82%, OR: 2.505; 95% CI: 0.261–8.689, P = 0.652) and any revascularization (12.76% vs. 9.67%, OR: 1.256; 95% CI: 0.747–2.111, P = 0.738) were similar between groups.ConclusionsCAC increased the incidence of TLF and TLR without a substantial increase in the risk of MACE, cardiac death, MI, or any revascularization in patients treated with DCB-only angioplasty during the 3-year follow-up.

One of the main reasons impeding wound healing is wound infection caused by bacterial colonization with a continuous stage of inflammation. Traditional wound treatments like gauze are being replaced by tissue adhesives with strong wet tissue adhesion and biocompatibility. Herein, a fast-crosslinking hydrogel is developed to achieve both strong antimicrobial properties and excellent biocompatibility. In this study, a simple and non-toxic composite hydrogel was prepared by the Schiff base reaction between the aldehyde group of 2,3,4-trihydroxybenzaldehyde (TBA) and the amino group of ε-Poly-L-lysine (EPL). Subsequently, a succession of experiments toward this new hydrogel including structure characterization, antimicrobial properties, cell experiment and wound healing were applied. The results of the experiments show that the EPL-TBA hydrogel not only exhibited excellent contact-active antimicrobial activities against Gram-negative bacteria Escherichia coli (E. coil) and Gram-positive Bacteria Staphylococcus aureus (S. aureus), but also inhibited the biofilm formation. More importantly, the EPL-TBA hydrogel promoted the wound healing with low cytotoxicity in vivo. These findings indicate that the EPL-TBA hydrogel has a promising use as a wound dressing in the bacterial infection prevention and wounds healing acceleration.

Promoting rural sustainable development requires improving rural systems’ self-organization to reduce dependence on external resources, which is inherently difficult in peasant economies due to low rural household income. Bottom-up collective action can help address these issues. However, few studies have examined how networks of elite and non-elite actors influence collective action and system transitions toward sustainability. This study scrutinizes the changing structures of collaborative networks in three Chinese villages through analysis of elite and non-elite actor groups and their relationships. We also examine the key elements that influence system transitions at every phase of rural sustainable development. The three case studies demonstrate that (1) elites play a vital role in the formation of collaborative networks and facilitate actor awareness; (2) spatial relationships are as essential as institutional design for successful collective action in response to sustainable development problems; (3) highly centralized collaborative networks help to improve the efficiency of the reorganization, renewal, and innovation of the village system, but the collective action outcome depends on the leadership and spatial relationships of the central actors; and (4) social memory and human capital are the most important system elements needed to exploit technology-driven windows of opportunity and achieve strong sustainability. These results provide important insights for enhancing rural systems’ capacity to self-organize and capturing windows of opportunity to achieve sustainable development.

This study focuses on the synthesis and evaluation of carbon−coated Ni−Fe alloy catalysts (NiFex@C, x = 0, 0.3, 0.7, 1.1) for the hydrogenation of cinnamaldehyde. The catalysts were characterized using Transmission Electron Microscopy (TEM), X-ray Diffraction (XRD), Raman spectroscopy, and X-ray Photoelectron Spectroscopy (XPS). The introduction of Fe was found to increase the average particle size of the bimetallic catalysts compared to the monometallic Ni@C. Ni existed in both metallic and oxide states, while Fe exhibited multiple oxidation states in the bimetallic catalysts. The carbon layer, approximately 2–3 nm thick, was confirmed to envelop the alloy particles. The catalytic performance of carbon−coated Ni−Fe alloy catalysts indicated that the addition of Fe to Ni@C enhanced the selectivity towards hydrocinnamaldehyde (HCAL), with NiFe0.7@C showing the highest selectivity (~88.6%) but at a reduced conversion rate. The carbon layer played a pivotal role in the stability and reusability of the catalysts. NiFe0.7@C maintained consistent performance over multiple reaction cycles, while NiFe0.7 NPs (without a carbon layer) exhibited significant deactivation. Both catalysts displayed strong magnetism, facilitating easy separation from the reaction mixture. This study sheds light on the significance of the carbon layer in bimetallic catalysts and provides valuable insights for designing efficient catalysts for hydrogenation processes.

Abstract Background Drug-Drug interactions (DDIs) are a challenging problem in drug research. Drug combination therapy is an effective solution to treat diseases, but it can also cause serious side effects. Therefore, DDIs prediction is critical in pharmacology. Recently, researchers have been using deep learning techniques to predict DDIs. However, these methods only consider single information of the drug and have shortcomings in robustness and scalability. Results In this paper, we propose a multi-type feature fusion based on graph neural network model (MFFGNN) for DDI prediction, which can effectively fuse the topological information in molecular graphs, the interaction information between drugs and the local chemical context in SMILES sequences. In MFFGNN, to fully learn the topological information of drugs, we propose a novel feature extraction module to capture the global features for the molecular graph and the local features for each atom of the molecular graph. In addition, in the multi-type feature fusion module, we use the gating mechanism in each graph convolution layer to solve the over-smoothing problem during information delivery. We perform extensive experiments on multiple real datasets. The results show that MFFGNN outperforms some state-of-the-art models for DDI prediction. Moreover, the cross-dataset experiment results further show that MFFGNN has good generalization performance. Conclusions Our proposed model can efficiently integrate the information from SMILES sequences, molecular graphs and drug-drug interaction networks. We find that a multi-type feature fusion model can accurately predict DDIs. It may contribute to discovering novel DDIs.

BackgroundData on drug-coated balloons (DCB) for de novo coronary chronic total occlusion (CTO) are limited. We aimed to investigate the long-term outcomes of substitution of drug-eluting stents (DES) by DCB.MethodsWe compared the outcomes of less DES strategy (DCB alone or combined with DES) and DES-only strategy in treating de novo coronary CTO in this prospective, observational, multicenter study. The primary endpoints were major adverse cardiovascular events (MACE), target vessel revascularization, myocardial infarction, and death during 3-year follow-up. The secondary endpoints were late lumen loss (LLL) and restenosis until 1-year after operation.ResultsOf the 591 eligible patients consecutively enrolled between January 2015 and December 2019, 281 (290 lesions) were treated with DCB (DCB-only or combined with DES) and 310 (319 lesions) with DES only. In the DCB group, 147 (50.7%) lesions were treated using DCB-only, and the bailout stenting rate was relatively low (3.1%). The average stent length per lesion in the DCB group was significantly shorter compared with the DES-only group (21.5 ± 25.5 mm vs. 54.5 ± 26.0 mm, p 0.999). The Kaplan–Meier estimates of MACE at 3-year (11.8% vs. 12.0%, log-rank p = 0.688) was similar between the groups.ConclusionPercutaneous coronary intervention with DCB is a potential “stent-less” therapy for de novo CTO lesions with satisfactory long-term clinical results compared to the DES-only approach.

Abstract There has been significant progress in skeleton-based action recognition. Human skeleton can be naturally structured into graph, so graph convolution networks have become the most popular method in this task. Most of these state-of-the-art methods optimized the structure of human skeleton graph to obtain better performance. Based on these advanced algorithms, a simple but strong network is proposed with three major contributions. Firstly, inspired by some adaptive graph convolution networks and non-local blocks, some kinds of self-attention modules are designed to exploit spatial and temporal dependencies and dynamically optimize the graph structure. Secondly, a light but efficient architecture of network is designed for skeleton-based action recognition. Moreover, a trick is proposed to enrich the skeleton data with bones connection information and make obvious improvement to the performance. The method achieves 90.5% accuracy on cross-subjects setting (NTU60), with 0.89M parameters and 0.32 GMACs of computation cost. This work is expected to inspire new ideas for the field.

AimsAn increasing body of evidence suggests that drug-coated balloon (DCB) angioplasty represents a valuable option for revascularization in selected patients with coronary bifurcation disease. However, there remains a paucity of real-world observational evidence on the efficacy of DCB in left main (LM) true bifurcation lesion. We compared clinical and angiographic outcomes of hybrid [DCB + drug-eluting stent (DES)] versus DES-only strategy (provisional stenting or two-stent strategies) in de novo LM true bifurcated lesions.MethodsThe primary endpoint was the 2-year composite rate of target lesion failure (TLF): cardiac death, target vessel myocardial infarction (TVMI), or clinically driven target lesion revascularization (CD-TLR). A routine 1-year angiographic follow-up was scheduled. Propensity-score matching was utilized to assemble a cohort of patients with similar baseline characteristics.ResultsAmong 1077 eligible patients, 199 who received DCB treatment and 398 who were assigned to DES therapy had similar propensity scores and were included in the analysis. TLF within 2 years occurred in 13 patients (7.56%) assigned to DCB group, and 52 patients (14.36%) assigned to DES group (odds ratio: 0.487; 95% confidence interval: 0.258–0.922; P = 0.025; Log-rank P = 0.024). Compared with the DES group, the DCB group resulted in a lower rate of CD-TLR (2.91% vs. 9.42%; P = 0.007). Cardiac death, TVMI, all-cause mortality, and stent thrombosis were comparable between both groups. Patients treated with DES-only were associated with a higher late lumen loss (0.42 ± 0.62 mm vs. 0.13 ± 0.42 mm, P < 0.001) compared with the DCB group at 1 year. In sensitivity analysis, the DCB group also presented a lower incidence of TLF, CD-TLR and stent thrombosis both compared to the two-stent strategy and compared to provisional stenting (Ps < 0.05).ConclusionThe 2-year results of PCI utilizing DCB for LM true bifurcation lesions are superior to employing DES alone in terms of safety and effectiveness.

Nucleus, as the machinery for genome transcription, play prominent roles to support the fundamental cellular functions, the destruction of any of these specific parts would significantly modulate the cell function. Therefore, troumendous drug delivery systems with enhanced nucleus targeting ability have been studied for nucleus-related disease regulation. The purpose of this review is to sort out the fundamental nuclear targeting strategy, especially the active mechanism of various nuclear targeting ligands and their extensive applications based on cancer targeting therapy. Various nuclear targeting ligands are first introduced to understand their nuclear entry mechanism. Next, to overcome biological barriers and avoid the serum protein absorption, diverse robust delivery strategies based on different nuclear targeting ligands are discussed. Moreover, other sophisticated carrier systems with enhanced nuclear entry, while without nuclear targeting ligands are also assembled. At the end the challenges and future opportunities in the field of nuclear targeting nanotherapeutics are tentatively proposed, to speed up their clinical translation.

BackgroundDrug-coated balloons (DCB), alone or in combination with drug-eluting stents (DES), may be used to treat diffuse coronary lesions. We aimed to explore the efficacy and safety of DCB in patients with diffuse coronary lesions.MethodsConsecutive patients with diffuse coronary lesions (lesion length > 25 mm) who underwent DCB and/or DES between January 2015 and December 2019 were included in this prospective, observational, multicenter study. The DCB group included 355 patients (360 lesions), of which 142 patients (143 lesions, 39.7%) received the DCB-only strategy and 213 patients (217 lesions, 60.3%) received the hybrid strategy (DCB combined with DES). The DES group included 672 patients (831 lesions) treated with DES alone. Target lesion revascularization (TLR) during 3-year follow-up was the primary outcome of interest. The secondary outcome was major adverse cardiac events (MACE), defined as a composite of all-cause death, non-fatal myocardial infarction, and target vessel revascularization.ResultsThe two groups had comparable baseline clinical and lesion characteristics. Lesion length was similar (43.52 ± 16.46 mm vs. 44.87 ± 15.80 mm, P = 0.181), but the stent length in the DCB group was significantly shorter (24.02 ± 23.62 mm vs. 51.89 ± 15.81 mm, P < 0.001). Ten lesions (2.8%) in the DCB group received bailout stents. Over 3 years of follow-up, no significant difference in TLR incidence between the groups (7.3 vs. 8.3%, log-rank P = 0.636) was observed. Incidence of MACE also did not differ significantly (11.3 vs. 13.7%, log-rank P = 0.324). No thrombosis events occurred in the DCB group, while four patients (0.6%) in the DES group experienced stent thrombosis (log-rank P = 0.193). Moreover, similar TLR and MACE rates were observed between DCB-only and hybrid strategies (TLR: 6.4 vs. 8.0%, log-rank P = 0.651; MACE: 11.4 vs. 11.2%, log-rank P = 0.884).ConclusionLong-term outcomes show that the efficacy and safety of the DCB strategy (DCB alone or combined with DES) are similar to those of DES alone in diffuse coronary lesions. These findings suggest that this strategy is a promising alternative for select patients with diffuse coronary lesions.

Abstract Background Although use of cellular bone allografts (CBA) in orthopedic surgery has become increasingly common, little information is available regarding their short-term clinical performance. In these two case reports of two-stage hip arthroplasties, ViviGen Formable CBA (V-CBA) was used in stage one to fill voids left by previous metal implants. Methods The two patients had distinctly different health profiles, but each of them had previous metal implants due to a hip fracture. In the otherwise healthy 49-year-old male patient, the total hip arthroplasty (THA) was performed 7 weeks after nail removal and V-CBA backfill. In the 64-year-old female patient with Type 1 diabetes and severe osteoporosis, stage 2 was performed after 12 weeks. At the time of THA for each patient, bone containing some V-CBA was removed to accommodate the hip implant. The explants were histologically analyzed for bone matrix, mineralization, and neovascularization. Results Histological staining showed substantial new bone formation and neovascularization in both explants albeit at different levels of maturity. Conclusions Although limited, these results suggest that V-CBA may facilitate new bone formation in healthy as well as in metabolically challenged patients. Level of evidence V, case report

Abstract Background Bone allografts are used in many orthopedic procedures to provide structural stability as well as an osteoconductive matrix for bone ingrowth and fusion. Traditionally, bone allografts have been preserved by either freezing or freeze-drying. Each of these preservation methods has some disadvantages: Frozen grafts require special shipping and storage conditions, and freeze-drying requires special lyophilization equipment and procedures that may impact biomechanical integrity. This report describes an alternate type of preservation using glycerol, which allows storage of fully-hydrated tissues at ambient temperature avoiding the potential complications from freeze-drying. Methods In the in vitro three-point bend test, cortical bone was processed and frozen, freeze-dried, or treated with glycerol-based preservation (GBP). Load was applied to each graft at a rate of 2.71 mm/min. The flexural strain, flexural strength, and flexural modulus were then calculated. In the in vitro axial compression test, iliac crest wedges, fibular segments, and Cloward dowels were processed and either freeze-dried or GBP treated. The compressive strength of the grafts were tested at time zero and after real time aging of 1, 4, and 5 years. In the in vivo rat calvarial defect assessment, freeze-dried, frozen, and GBP bone implants were compared after being implanted into a critical sized defect. Samples underwent histological and biomechanical evaluation. Results Bone grafts subjected to GBP were found to be at least biomechanically equivalent to frozen bone while also being significantly less brittle than freeze-dried bone. GBP-preserved bone demonstrated significantly greater compressive strength than freeze-dried at multiple time points. Preclinical research performed in calvaric defect models found that GBP-preserved bone had similar osteoconductivity and biocompatibility to frozen and freeze-dried samples. Conclusion Preclinical research demonstrated that glycerol–preservation of bone yields a material that maintains biomechanical strength while eliminating the need for extensive rehydration or thaw periods if used clinically. Additionally, in vivo evidence suggests no negative impact of glycerol-preservation on the ability of bone grafts to successfully participate in new bone formation and fusion.

Fully-convolutional Siamese networks for visual tracking have drawn great attention in balancing tracking accuracy and speed. However, there is still some inherent inaccuracy with advanced trackers, since they only learn a general matching model from large scale datasets by off-line training. This generates the target template without sufficient discriminant information and does not adapt well to the current tracking sequence. In this paper, we introduce the channel attention mechanism into the network to better learn the matching model and, during the online tracking phase, we design an initial matting guidance strategy in which: 1) the superpixel matting algorithm is applied to extract the target foreground in the initial frame, and 2) the matted image with foreground only is fed into the network and fused with the original image feature. Under matting guidance, the fused target template has more details for representation of target appearance and more structural information from superpixels for robust tracking. The experimental results on object tracking benchmark (OTB) show that our approach achieves excellent performance while it also provides real-time tracking speed.

Efficient cellular delivery of biologically active molecules is one of the key factors that affect the discovery and development of novel drugs. The plasma membrane is the first barrier that prevents direct translocation of chemic entities, and thus obstructs their efficient intracellular delivery. Generally, hydrophilic small molecule drugs are poor permeability that reduce bioavailability and thus limit the clinic application. The cellular uptake of macromolecules and drug carriers is very inefficient without external assistance. Therefore, it is desirable to develop potent delivery systems for achieving effective intracellular delivery of chemic entities. Apart from of the types of delivery strategies, the composition of the cell membrane is critical for delivery efficiency due to the fact that cellular uptake is affected by the interaction between the chemical entity and the plasma membrane. In this review, we aimed to develop a profound understanding of the interactions between delivery systems and components of the plasma membrane. For the purpose, we attempt to present a broad overview of what delivery systems can be used to enhance the intracellular delivery of poorly permeable chemic entities, and how various delivery strategies are applied according to the components of plasma membrane.

Background. Diabetes is an independent risk factor for coronary artery disease and portends adverse prognosis in diabetic patients undergoing percutaneous coronary intervention (PCI) compared to nondiabetic patients. Few studies are currently available regarding the relationship between diabetes duration and major adverse cardiac events (MACEs) post-PCI. This study is aimed at assessing the association between diabetes duration and major adverse cardiac events after PCI. Methods. A total of 302 cases of diabetic patients undergoing an elective PCI with drug-eluting stent (DES) deployment and or percutaneous transluminal coronary angioplasty (PTCA) using a drug-coated balloon (DCB) were prospectively studied. We divided patients into three groups based on diabetes duration: 10-year group than was it in groups with shorter duration of diabetes (23.1% vs. 19.4% and 9.10%, P=0.03). After adjustment for confounding risk factors, longer diabetes duration remained an independent predictor of MI (hazard ratio (HR): 5.525, confidence interval (CI): 1.273-23.978, P=0.022) and repeat revascularization (HR: 1.608, CI: 1.058-2.443, P=0.026). Repeat revascularization was significantly related to the progression of nontreated lesions (De novo lesions 20% vs. 18% and 7.3%, P=0.009) compared to previously treated lesions (target lesion revascularization (TLR) 3% vs. 1.3% and 2%, P=0.774). However, all-cause mortality was not significantly different among the groups (3.1% vs. 5.6% and 0.6%, P=0.06, HR: 2.403, CI: 0.464-12.436, P=0.293). Conclusion. Diabetes duration was associated with significant differences in major adverse cardiac events after the percutaneous coronary intervention; the longest diabetes duration portended higher rates of MACEs than shorter duration at the 12-month follow-up.

Background. The revascularization of small vessels using drug-eluting stents remains challenging. The use of the drug-coated balloon is an attractive therapeutic strategy in de novo lesions in small coronary vessels, particularly in the diabetic group. This study aimed to assess the outcomes of DCB-only angioplasty in small vessel disease. Methods. A total of 1198 patients with small vessel disease treated with DCB-only strategy were followed. Patients were divided into the diabetic and nondiabetic groups. Clinical and angiographical follow-up were organized at 12 months. The primary endpoints were target lesion failure and secondary major adverse cardiac events. Results. There was a significantly higher rate of target lesion failure among diabetic patients compared to nondiabetic [17 (3.9%) vs. 11 (1.4%), P=0.006], taken separately, the rate of target lesion revascularization significantly differed between groups with a higher rate observed in the diabetic group [9 (2%) vs. 4 (0.5%), P=0.014]. Diabetes mellitus remained an independent predictor for TLF (HR: 2.712, CI: 1.254–5.864, P=0.011) and target lesion revascularization (HR: 3.698, CI: 1.112–12.298, P=0.033) after adjustment. However, no significant differences were observed between groups regarding the target vessel myocardial infarction (0.6% vs. 0.1%, P=0.110) and MACE [19 (4.4%) vs. 21 (2.7%), P=0.120]. Conclusion. Drug-coated balloon-only treatment achieved lower incidence rates of TLF and MACE. Diabetes is an independent predictor for target lesion failure and target lesion revascularization at one year following DCB treatment in small coronary vessels. We observed no significant differences between groups regarding MACE in one year.

Background. Relative to nondiabetic patients, percutaneous coronary intervention (PCI) in patients with diabetes mellitus (DM) is associated with inferior clinical outcomes. We aimed to evaluate the outcomes of drug-coated balloon (DCB) in diabetic versus nondiabetic patients. Methods and Results. In this observational, prospective, multicenter study, we compared the outcomes of patients with and without DM after undergoing PCI with DCBs. Target lesion failure (TLF) was analyzed as primary endpoint. Secondary endpoints were the rates of target lesion revascularization (TLR), major adverse cardiovascular events (MACE), cardiac death, myocardial infarction (MI), and any revascularization. Propensity score matching was used to assemble a cohort of patients with similar baseline characteristics. Among 2,306 eligible patients, 578 with DM and 578 without DM had similar propensity scores and were included in the analyses. During follow-up (366±46 days), compared with DM patients, patients without DM were associated with a lower yearly incidence of TLF (2.77% vs. 5.36%; OR, 1.991; 95% CI, 1.077 to 3.681; P=0.025) and TLR (1.90% vs. 4.15%; OR, 2.233; 95% CI, 1.083 to 4.602; P=0.026). No significant differences were observed with regards to rates of MACE (OR: 1.580, 95% CI: 0.912-2.735; P=0.100), cardiac death (OR: 1.608, 95% CI: 0.523-4.946; P=0.403), MI (OR: 4.042, 95% CI: 0.855-19.117; P=0.057), and any revascularization (OR: 1.534, 95% CI: 0.983-2.393; P=0.058). Conclusions. Diabetic patients experience higher TLF and TLR rates following DCB angioplasty without substantial increase in the risk of MACE, cardiac death, MI, or revascularization.

The analytically time integrable time-space domain (ATI-TSD) is discovered based on which the minimum time-space domain is identified for treatment on singularities in the three-dimensional time-domain boundary element method (3D TD-BEM) formulation. A direct method to solve singular integrals in the 3D TD-BEM formulation for elastodynamic problems is proposed. The wavefront singularity can be analytically eliminated in ATI-TSD, while the dual singularity can be treated by the direct method using Kutt’s quadrature in the identified minimum time-space domain. Three benchmark examples are presented to verify the correctness and the applicability of the direct method for solving the singular integrals in 3D TD-BEM.

Abstract We firstly conducted a long-term in-situ field measurement at a marginal area (Hotan) of the southern Taklimakan Desert covering all four seasons. Detailed chemical characterization of dust aerosol over Hotan showed several unconventional features, including (1) ubiquity of high Na+ and Cl− abundances in the Taklimakan dust aerosol and its Cl−/Na+ ratio close to seawater; (2) high Ca content in the Taklimakan dust (7.4~8.0%) which was about two times of that in the natural crust; (3) high abundance of soluble sulfate concentrations and strong correlations between sulfate and Na+ and Cl− as well as typical mineral tracers such as Al and Ca. Our results collectively indicated that the dust aerosol from the Taklimakan Desert was characterized of evident paelo-oceanic signature as the Taklimakan Desert was found as an ocean in the ancient times from the perspective of paleogeology. It was estimated that primary sources dominated the total abundances of sulfate during the dust seasons while previous climate modeling works had seldom considered the cooling effects of sulfate from the Taklimakan Desert.

Rural human settlements are an integral part of a rural system. The evaluation of public feedback based on farmers’ satisfaction is a crucial way to understand the current situation of rural human settlements. This paper establishes a framework to evaluate local dwellers’ satisfaction towards the environment of rural human settlements in northwest China from six dimensions involving living conditions, the environment, physical infrastructure, public service, governance, and culture. The empirical study was conducted in Yanchi County, which demonstrates the applicability of this evaluating method. This study shows that the overall degree of satisfaction towards the environment of rural human settlements is relatively high, with a figure of 77.38. However, the satisfaction scores for the six dimensions are uneven, and there are significant differences between the villages. Further, these villages can be divided into three types according to the residents’ satisfaction, and viable strategies are suggested correspondingly. To sustain rural settlement development, the authors argue that more efforts should be put into technology advancement, public participation incentives, and the subsequent maintenance of projects in the long run.

Abstract Background This study examined the ability of lipopolysaccharide (LPS) to affect glioma and glioma stem-like cells (GSCs) in vitro and to induce antitumor immunity in vivo and the role of TLR4 in these processes. Methods Using RT-PCR and immunohistochemistry, we examined the expression of TLR4 in 34 glioblastoma clinical samples. Using real time-PCR, western blot and ELISA analyses, the effect of LPS stimulation on the expression of immune related molecules was evaluated in RG2 and U87 GSCs. Control or LPS-pretreated RG2 GSCs were intracranially or subcutaneously implanted into wild-type or nude Fisher 344 rats. Histopathological examinations were used to assess tumor progression and immune infiltration and Kaplan-Meier analyses to compare survival times of the animal models. Results TLR4 was highly expressed in glioblastoma clinical samples. In vitro LPS stimulation for 6 h significantly altered expression of immune related molecules in RG2 and U87 GSCs. However, prolonged LPS stimulation diminished this effect. Rats inoculated intracranially with LPS-pretreated RG2 GSCs survived significantly longer than rats inoculated with control RG2 GSCs. In vivo, LPS-pretreated RG2 GSCs expressed higher levels of MHC molecules, CXCL10 and TNF-α and recruited more CD8+ lymphocytes. However, intratumoral LPS treatment was not equally beneficial. Furthermore, the in vitro and in vivo effects of LPS stimulation appeared to be largely TLR4-dependent. Conclusion LPS pretreatment promotes the recognition and eradication of tumor GSCs in vivo when the immune function of the tumor-bearing host is intact. In addition, our data indicate a complex relationship between bacterial infection and glioma prognosis.

A library of 23 pure compounds of varying structural and chemical characteristics was screened for their quorum sensing (QS) inhibition activity using a synthetic fluorescent Escherichia coli biosensor that incorporates a modified version of lux regulon of Vibrio fischeri. Four such compounds exhibited QS inhibition activity without compromising bacterial growth, namely, phenazine carboxylic acid (PCA), 2-heptyl-3-hydroxy-4-quinolone (PQS), 1H-2-methyl-4-quinolone (MOQ) and genipin. When applied at 50 µM, these compounds reduced the QS response of the biosensor to 33.7% ± 2.6%, 43.1% ± 2.7%, 62.2% ± 6.3% and 43.3% ± 1.2%, respectively. A series of compounds only showed activity when tested at higher concentrations. This was the case of caffeine, which, when applied at 1 mM, reduced the QS to 47% ± 4.2%. In turn, capsaicin, caffeic acid phenethyl ester (CAPE), furanone and polygodial exhibited antibacterial activity when applied at 1mM, and reduced the bacterial growth by 12.8% ± 10.1%, 24.4% ± 7.0%, 91.4% ± 7.4% and 97.5% ± 3.8%, respectively. Similarly, we confirmed that trans-cinnamaldehyde and vanillin, when tested at 1 mM, reduced the QS response to 68.3% ± 4.9% and 27.1% ± 7.4%, respectively, though at the expense of concomitantly reducing cell growth by 18.6% ± 2.5% and 16% ± 2.2%, respectively. Two QS natural compounds of Pseudomonas aeruginosa, namely PQS and PCA, and the related, synthetic compounds MOQ, 1H-3-hydroxyl-4-quinolone (HOQ) and 1H-2-methyl-3-hydroxyl-4-quinolone (MHOQ) were used in molecular docking studies with the binding domain of the QS receptor TraR as a target. We offer here a general interpretation of structure-function relationships in this class of compounds that underpins their potential application as alternatives to antibiotics in controlling bacterial virulence.

Medical image segmentation is a fundamental task in medical image analysis. Dynamic receptive field is very helpful for accurate medical image segmentation, which needs to be further studied and utilized. In this paper, we propose Match Feature U-Net, a novel, symmetric encoder– decoder architecture with dynamic receptive field for medical image segmentation. We modify the Selective Kernel convolution (a module proposed in Selective Kernel Networks) by inserting a newly proposed Match operation, which makes similar features in different convolution branches have corresponding positions, and then we replace the U-Net’s convolution with the redesigned Selective Kernel convolution. This network is a combination of U-Net and improved Selective Kernel convolution. It inherits the advantages of simple structure and low parameter complexity of U-Net, and enhances the efficiency of dynamic receptive field in Selective Kernel convolution, making it an ideal model for medical image segmentation tasks which often have small training data and large changes in targets size. Compared with state-of-the-art segmentation methods, the number of parameters in Match Feature U-Net (2.65 M) is 34% of U-Net (7.76 M), 29% of UNet++ (9.04 M), and 9.1% of CE-Net (29 M). We evaluated the proposed architecture in four medical image segmentation tasks: nuclei segmentation in microscopy images, breast cancer cell segmentation, gland segmentation in colon histology images, and disc/cup segmentation. Our experimental results show that Match Feature U-Net achieves an average Mean Intersection over Union (MIoU) gain of 1.8, 1.45, and 2.82 points over U-Net, UNet++, and CE-Net, respectively.

A method was developed for simultaneous determination of 15 amino acids and 7 alkyl amines. The method was based on the employment of high performance liquid chromatography/fluorescence detection and online derivatization with o-phthaldiadehyde. The 22 derivatives were separated within 30 min including the equilibration time and detected by a fluorescence detector at an excitation wavelength of 230 nm and emission wavelength of 450 nm. The analysis procedure was satisfactorily validated by the reproducibility, recovery, linearity and detection limit of the analytes. The relative standard deviations (RSDs) of retention time and peak area for individual amino acids and alkyl amines were consistently less than 0.30% and 2.35%, respectively. Good recovery values ranging from 70% to 109% were obtained. The proposed method showed good linearity (R2≥0.99) in the range of 0.125-125 μM/L for amino acids and 2.5-5000 ng/L for alkyl amines. The detection limit ranged from 0.13 pM to 0.37 pM for individual amino acids and from 0.9 ng to 7.2 ng for individual alkyl amines. The developed and validated method was successfully applied to the quantitative analysis of amino acids and alkyl amines in continental and marine aerosols in China. Among the identified organic nitrogen compounds, 7 amino acids and 6 alkyl amines were detected in every aerosol sample. Glycine was the dominant amino acid, with the average of 130.93 pmol/m3 (accounting for 83% of the total amino acids) and 137.22 pmol/m3 (accounting for 66% of the total amino acids) in continental and marine aerosols in China, respectively. Methylamine and ethanolamine were the most abundant alkyl amines, contributing 87% and 64% to the total alkyl amines in continental and marine aerosols in China, respectively. This work provided an accurate, sensitive and simple method to determine simultaneously amino acids and alkyl amines, and applied the proposed method to the first investigation of amino acids in Shanghai and amino acids and alkyl amines in Huaniao Island in China. The finding of considerable amino acids and alkyl amines in continental and marine aerosols may exert significant implications on nitrogen cycling and atmospheric chemistry.

The blackmouth croaker, Atrobucca nibe (Jordan & Thompson, 1911), is one of the most important economic fish in China. The mitogenome of A. nibe was determined in this study. The full circle length of the complete mitochondrial DNA was 16,505 bp. It contained 13 protein-coding genes, 22 tRNA genes, 2 rRNA genes, and a control region (D-loop). All 21 tRNA genes can fold into a typical cloverleaf structure except for tRNASer (AGY). The phylogenetic analysis revealed that A. nibe clustered into the three species of Sciaenidae (Pennahia microcephalus, Chrysochi aureus and Protonibea diacanthus).

A label-free electrochemical aptasensor was fabricated to sensitively determine malachite green (MG) based on Au nanoparticles/graphene quantum dots-tungsten disulfide nanosheet composite film modified glassy carbon electrode (AuNPs/GQDs-WS2/GCE). A facial strategy for the self-assembly of graphene quantum dots (GQDs) on tungsten disulfide nanosheets (WS2) was developed to fabricate 0D/2D nanocomposites. As-prepared GQDs-WS2 hybrids exhibited significantly enhanced electrocatalytic properties, and were first used as electroactive materials to construct electrochemical aptasensor. The AuNPs/GQDs-WS2/GCE was prepared through depositing Au nanoparticles on the surface of the GQDs-WS2 film, which acted as the electrochemical sensing matrix to covalently immobilize the aptamers of MG via the Au⁻S bond. In this label-free proposal, the aptasensor was applied to detect MG by monitoring voltammetric signal resulted from electrochemical oxidation of the MG captured by the aptamer. Under the optimized conditions, the aptasensor showed a wide linear range from 0.01 to 10 μM for MG detection with a low detection limit of 3.38 nM (S/N = 3). The method was applied to determination of MG in spiked fish samples and gave satisfactory results.

In order to investigate the interplay between the cells and TiO2 nanotube array, and to explore the ability of cells to sense the size change in nano-environment, we reported on the behavior of glioma C6 cells on nanotube array coatings in terms of proliferation and apoptosis. The behavior of glioma C6 cells was obviously size-dependent on the coatings; the caliber with 15 nm diameter provided effective spacing to improve the cells proliferation and enhanced the cellular activities. C6 cells’ biological behaviors showed many similar tendencies to many phorocytes; the matching degree of geometry between nanotube and integrin defined that a spacing of 15 nm was optimal for inducing signals to nucleus, which results in achieving maximum activity of glioma cells. In addition, the immune behavior of cells was studied, a variety of inflammatory mediator’s gene expression levels were controlled by the nanoscale dimension, the expressions of IL-6 and IL-10 were higher on 30 nm than on 15 nm nanotube.

New approaches to deal with drug-resistant pathogenic bacteria are urgent. We studied the antibacterial effect of chitosans against an Escherichia coli quorum sensing biosensor reporter strain and selected a non-toxic chitosan to evaluate its quorum sensing (QS) inhibition activity and its effect on bacterial aggregation. To this end, chitosans of varying degree of acetylation (DA) (12 to 69%) and molecular weight (Mw) (29 to 288 kDa) were studied. Only chitosans of low DA (~12%) inhibited bacterial growth, regardless of their Mw. A chitosan with medium degree of polymerization (named MDP) DA30, with experimental DA 42% and Mw 115 kDa was selected for further QS inhibition and scanning electron microscopy (SEM) imaging studies. MDP DA30 chitosan exhibited QS inhibition activity in an inverse dose-dependent manner (≤12.5 µg/mL). SEM images revealed that this chitosan, when added at low concentration (≤30.6 µg/mL), induced substantial bacterial aggregation, whereas at high concentration (234.3 µg/mL), it did not. Aggregation explains the QS inhibition activity as the consequence of retardation of the diffusion of N-acylated homoserine lactones (AHLs).

The characteristics of biogenic aerosols in an urban area were explored by determining the composition and temporal distribution of saccharides in PM2.5 in Shanghai. The total saccharides showed a wide range of 9.4 ng/m3 to 1652.9 ng/m3, with the averaged concentrations of 133.1 ng/m3, 267.5 ng/m3, 265.1 ng/m3, and 674.4 ng/m3 in spring, summer, autumn, and winter, respectively. The saccharides include anhydrosaccharides (levoglucosan and mannosan), which were higher in cold seasons due to the increased biomass burning; saccharide alcohols (mannitol, arabitol, sorbitol); and monosaccharides (fructose, glucose), which were more abundant in warm seasons and attributed to the biological emissions. Through positive matrix factorization (PMF) analysis, four emission sources of saccharides were resolved, including biomass burning, fungal spores, plant decomposition, and pollen. Moreover, the process analysis of high concentrations of leveglucosan was conducted by backward trajectory and fire points. We found that concentrations of anhydrosaccharides were relatively stable under different pollution levels, while saccharide alcohols exhibited an obvious decrease with the concentration of PM2.5, indicating that biomass burning was not the core reason for heavy haze pollution. However, high level PM2.5 pollution might inhibit the effects of biological activities.