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Abstract It remains a great challenge to achieve strong and reversible hydrogel adhesion. Hydrogel adhesives also suffer from poor environmental stability due to dehydration. To overcome these problems, here reversible adhesive gels are designed using a new switching mechanism and new solvent. For the first time, the study observes UCST (upper critical solution temperature)‐type thermosensitive behaviors of poly(benzyl acrylate) (PBnA) polymer and gel in menthol:thymol deep eutectic solvents (DESs). The temperature‐induced phase transition allows adjusting cohesive force, and hence adhesion strength of PBnA gels by temperature. To further improve the mechanical and adhesion properties, a peptide crosslinker is used to allow energy dissipation when deforming. The resulting eutectogel exhibits thermal reversible adhesion with a high switching ratio of 14.0. The adhesion strength at attachment state reaches 0.627 MPa, which is much higher than most reversible adhesive hydrogels reported before. The low vapor pressure of DES endows the gel excellent environmental stability. More importantly, the gel can be repeatedly switched between attachment and detachment states. The strong and reversible gel adhesive is successfully used to design soft gripper for the transport of heavy cargos and climbing robot capable of moving on vertical and inverted surface in a manner similar to gecko.

In the past two decades, extensive and in-depth research has been conducted on Time Series InSAR technology with the advancement of high-performance SAR satellites and the accumulation of big SAR data. The introduction of distributed scatterers in Distributed Scatterers InSAR (DS-InSAR) has significantly expanded the application scenarios of InSAR geodetic measurement by increasing the number of measurement points. This study traces the history of DS-InSAR, presents the definition and characteristics of distributed scatterers, and focuses on exploring the relationships and distinctions among proposed algorithms in two crucial steps: statistically homogeneous pixel selection and phase optimization. Additionally, the latest research progress in this field is tracked and the possible development direction in the future is discussed. Through simulation experiments and two real InSAR case studies, the proposed algorithms are compared and verified, and the advantages of DS-InSAR in deformation measurement practice are demonstrated. This work not only offers insights into current trends and focal points for theoretical research on DS-InSAR but also provides practical cases and guidance for applied research.

Abstract The commercialization of Li−S batteries is seriously hindered by polysulfides with severe shuttle effect, and the inherent insulating properties and slow reaction kinetics of insoluble Li2S products. Transition metal sulfides (TMSs) have a high adsorption capacity for polysulfides and have been shown to have a strong catalytic effect on polysulfide conversion reactions. This paper reviews the research on the application of Unary TMSs, heterostructures, etc. in Li−S batteries, and gives some research methods for TMD catalysts in Li−S batteries. Finally, it points out the main focuses and direction of future Li−S battery research and development. It aims to provide some insights into the design and manufacture of advanced Li−S batteries for commercial use.

Abstract Background Cerebrovascular autoregulation (CVAR) is the mechanism that maintains constant cerebral blood flow by adjusting the caliber of the cerebral vessels. It is important to have an effective, contactless way to monitor and assess CVAR in patients with ischemia. Methods The adjustment of cerebral blood flow leads to changes in the conductivity of the whole brain. Here, whole-brain conductivity measured by the magnetic induction phase shift method is a valuable alternative to cerebral blood volume for non-contact assessment of CVAR. Therefore, we proposed the correlation coefficient between spontaneous slow oscillations in arterial blood pressure and the corresponding magnetic induction phase shift as a novel index called the conductivity reactivity index (CRx). In comparison with the intracranial pressure reactivity index (PRx), the feasibility of the conductivity reactivity index to assess CVAR in the early phase of cerebral ischemia has been preliminarily confirmed in animal experiments. Results There was a significant difference in the CRx between the cerebral ischemia group and the control group (p = 0.002). At the same time, there was a significant negative correlation between the CRx and the PRx (r = − 0.642, p = 0.002) after 40 min after ischemia. The Bland–Altman consistency analysis showed that the two indices were linearly related, with a minimal difference and high consistency in the early ischemic period. The sensitivity and specificity of CRx for cerebral ischemia identification were 75% and 20%, respectively, and the area under the ROC curve of CRx was 0.835 (SE = 0.084). Conclusion The animal experimental results preliminarily demonstrated that the CRx can be used to monitor CVAR and identify CVAR injury in early ischemic conditions. The CRx has the potential to be used for contactless, global, bedside, and real-time assessment of CVAR of patients with ischemic stroke.

The accurate prediction of the future trajectories of traffic participants is crucial for enhancing the safety and decision-making capabilities of autonomous vehicles. Modeling social interactions among agents and revealing the inherent relationships is crucial for accurate trajectory prediction. In this context, we propose a goal-guided and interaction-aware state refinement graph attention network (SRGAT) for multi-agent trajectory prediction. This model effectively integrates high-precision map data and dynamic traffic states and captures long-term temporal dependencies through the Transformer network. Based on these dependencies, it generates multiple potential goals and Points of Interest (POIs). Through its dual-branch, multimodal prediction approach, the model not only proposes various plausible future trajectories associated with these POIs, but also rigorously assesses the confidence levels of each trajectory. This goal-oriented strategy enables SRGAT to accurately predict the future movement trajectories of other vehicles in complex traffic scenarios. Tested on the Argoverse and nuScenes datasets, SRGAT surpasses existing algorithms in key performance metrics by adeptly integrating past trajectories and current context. This goal-guided approach not only enhances long-term prediction accuracy, but also ensures its reliability, demonstrating a significant advancement in trajectory forecasting.

Modifying nanocrystals with functional materials have been common strategy to enlarge the enhancing ability on oral absorption via nanocrystals; however, whether the functional materials have played their full enhancing ability in oral absorption is still unknown. In this study, we synthetized a novel chitosan-based copolymer (the copolymer of sodium dodecyl sulfate (SDS), chitosan (CS) and D-α-Tocopherol polyethylene glycol 1000 succinate, SDS-CS-TPGS), and modified nanocrystals with this copolymer, aiming to enhance the oral absorption of polymer andrographolide (ADR). In real-time distribution study, we found the distribution of ADR, SDS, CS and TPGS varies in gastrointestinal tract, while the distribution of ADR and SDS-CS-TPGS was similar, revealing the SDS-CS-TPGS could able to participate in the absorption process of andrographolide timely. To explore the oral absorption enhancing ability of SDS-CS-TPGS, we prepared a series of nanocrystals modified with different materials and explored their pharmacokinetic performances on SD rats. The results showed the nanocrystals modified with SDS-CS-TPGS (S-C-TANs) exhibited the highest bioavailability, which could enhance the AUC0-∞ of ADR from 1.291 mg/L*h to 5.275 mg/L*h (enhanced for about 4.09-folds). The enhanced anti- inflammatory efficacy was also found on ICR mice by employing ear swelling rate, TNF-α, IL-1β and IL-6 and pharmacodynamic index. These results indicated that modified with synthesized copolymer containing different functional stabilizers is an efficient strategy to enlarge the enhancing ability on oral absorption of nanocrystals.

Introduction: Mechanical properties of biological tissue are important for numerical simulations. Preservative treatments are necessary for disinfection and long-term storage when conducting biomechanical experimentation on materials. However, few studies have been focused on the effect of preservation on the mechanical properties of bone in a wide strain rate. The purpose of this study was to evaluate the influence of formalin and dehydration on the intrinsic mechanical properties of cortical bone from quasi-static to dynamic compression.Methods: Cube specimens were prepared from pig femur and divided into three groups (fresh, formalin, and dehydration). All samples underwent static and dynamic compression at a strain rate from 10−3 s−1 to 103 s−1. The ultimate stress, ultimate strain, elastic modulus, and strain-rate sensitivity exponent were calculated. A one-way ANOVA test was performed to determine if the preservation method showed significant differences in mechanical properties under at different strain rates. The morphology of the macroscopic and microscopic structure of bones was observed.Results: The results show that ultimate stress and ultimate strain increased as the strain rate increased, while the elastic modulus decreased. Formalin fixation and dehydration did not affect elastic modulus significantly whereas significantly increased the ultimate strain and ultimate stress. The strain-rate sensitivity exponent was the highest in the fresh group, followed by the formalin group and dehydration group. Different fracture mechanisms were observed on the fractured surface, with fresh and preserved bone tending to fracture along the oblique direction, and dried bone tending to fracture along the axial direction.Discussion: In conclusion, preservation with both formalin and dehydration showed an influence on mechanical properties. The influence of the preservation method on material properties should be fully considered in developing a numerical simulation model, especially for high strain rate simulation.

Abstract Phosphoglycerate kinase 1 (PGK1) has complicated and multiple functions in cancer occurrence, tumor progression and drug resistance. Sorafenib is the first-line treatment targeted drug for patients with kidney renal clear cell carcinoma (KIRC) as a tyrosine kinase inhibitor, but sorafenib resistance is extremely common to retard therapy efficiency. So far, it is unclear whether and how PGK1 is involved in the pathogenesis and sorafenib resistance of KIRC. Herein, the molecular mechanisms of PGK1-mediated KIRC progression and sorafenib resistance have been explored by comprehensively integrative studies using biochemical approaches, mass spectrometry (MS) identification, microarray assay, nude mouse xenograft model and bioinformatics analysis. We have confirmed PGK1 is specifically upregulated in KIRC based on the transcriptome data generated by our own gene chip experiment, proteomics identification and the bioinformatics analysis for five online transcriptome datasets, and PGK1 upregulation in tumor tissues and serum is indicative with poor prognosis of KIRC patients. In the KIRC tissues, a high expression of PGK1 is often accompanied with an increase of glycolysis-related enzymes and CXCR4. PGK1 exhibits pro-tumorigenic properties in vitro and in a xenograft tumor model by accelerating glycolysis and inducing CXCR4-mediated phosphorylation of AKT and ERK. Moreover, PGK1 promotes sorafenib resistance via increasing CXCR4-mediated ERK phosphorylation. In conclusion, PGK1-invovled metabolic reprogramming and activation of CXCR4/ERK signaling pathway contributes to tumor growth and sorafenib resistance of KIRC.

Abstract Atherosclerosis (AS) is a leading cause of vascular diseases that severely threats the human health due to the lack of efficient therapeutic methods. During the development and progress of AS, macrophages play critical roles, which are polarized into pro-inflammatory M1 phenotype to excrete abundant cytokines and overproduce reactive oxygen species (ROS), and take up excess amount of lipid to form foam cells. In this work, we developed a MnO2-based nanomedicine to re-educate macrophages for targeting AS therapy. The MnO2 was one-pot synthesized under mild condition, showing intrinsic catalase-mimic activity for self-oxygenation by using endogenous H2O2 as substrate. Moreover, the mesoporous structure as well as the abundant metal coordination sites in MnO2 structure facilitated the loading of an anti-AS drug of curcumin (Cur), achieving extraordinarily high drug loading capacity of 54%. Cur displayed a broad spectrum of anti-oxidant and anti-inflammatory capabilities to repolarize M1 macrophages into M2 phenotype, and the catalytic MnO2 recovered the function of lipid efflux transporter to remove lipid from cells by suppressing HIF-1α. Collectively, the nanocarrier and the payload drug functioned as an all-active nanoplatform to synergistically alleviate the syndromes of AS. In ApoE−/− mice model, the nanosystem could significantly prolong the circulation half-life of Cur by sixfold, and enhance drug accumulation in atherosclerotic lesion by 3.5-fold after intravenous injection by virtue of surface hyaluronic acid (HA) modification. As a result, a robust anti-AS efficacy was achieved as evidenced by the decrease of atherosclerotic lesion, plaque area, lipid level. Graphical Abstract

Purpose: To investigate the immune biomarker in Leiomyosarcoma (LMS), which is rare and recognized as an immune cold cancer showing a poor response rate (Patients and methods: We used comprehensive transcriptomic profiling and a deconvolution method extracted from RNA-sequencing gene expression data in two independent LMS cohorts, the International Cancer Genome Consortium (ICGC, N = 146) and The Cancer Genome Atlas (TCGA, N = 75), to explore tumor immune microenvironment (TIME) in LMS. Results: Unsupervised clustering analysis using the previously validated two methods, 90-gene signature and Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT), identified immune hot (I-H) and immune high (I-Hi) LMS, respectively, in the ICGC cohort. Similarly, immune active groups (T-H, T-Hi) were identified in the TCGA cohort using these two methods. These immune active (“hot”) clusters were significantly associated, but not completely overlapping, with several validated immune signatures such as sarcoma immune class (SIC) classification and TLS score, T cell inflamed signature (TIS) score, immune infiltration score (IIS), and macrophage score (M1/M2), with more patients identified by our clustering as potentially immune hot. Conclusions: Comprehensive immune profiling revealed a subset of LMS with a distinct active (“hot”) TIME, consistently associated with several validated immune signatures in other cancers. This suggests that the methodologies that we used in this study warrant further validation and development, which can potentially help refine our current immune biomarkers to select the right LMS patients for ICIs in clinical trials.

Improving the stability of drugs in the gastrointestinal tract and their penetration ability in the mucosal layer by implementing a nanoparticle delivery strategy is currently a research focus in the pharmaceutical field. However, for most drugs, nanoparticles failed in enhancing their oral absorption on a large scale (4 folds or above), which hinders their clinical application. Recently, several researchers have proved that the intestinal epithelial cell membrane crossing behaviors of nanoparticles deeply influenced their oral absorption, and relevant reviews were rare. In this paper, we systematically review the behaviors of nanoparticles in the intestinal epithelial cell membrane and mainly focus on their intracellular mechanism. The three key complex intracellular processes of nanoparticles are described: uptake by intestinal epithelial cells on the apical side, intracellular transport and basal side exocytosis. We believe that this review will help scientists understand the in vivo performance of nanoparticles in the intestinal epithelial cell membrane and assist in the design of novel strategies for further improving the bioavailability of nanoparticles.

The pine wood nematode (PWN; Bursaphelenchus xylophilus) is a major invasive species in China, causing huge economic and ecological damage to the country due to the absence of natural enemies and the extremely rapid rate of infection and spread. Accurate monitoring of pine wilt disease (PWD) is a prerequisite for timely and effective disaster prevention and control. UAVs can carry hyperspectral sensors for near-ground remote sensing observations, which can obtain rich spatial and spectral information and have the potential for infected tree identification. Deep learning techniques can use rich multidimensional data to mine deep features in order to achieve tasks such as classification and target identification. Therefore, we propose an improved Mask R-CNN instance segmentation method and an integrated approach combining a prototypical network classification model with an individual tree segmentation algorithm to verify the possibility of deep learning models and UAV hyperspectral imagery for identifying infected individual trees at different stages of PWD. The results showed that both methods achieved good performance for PWD identification: the overall accuracy of the improved Mask R-CNN with the screened bands as input data was 71%, and the integrated method combining prototypical network classification model with individual tree segmentation obtained an overall accuracy of 83.51% based on the screened bands data, in which the early infected pine trees were identified with an accuracy of 74.89%. This study indicates that the improved Mask R-CNN and integrated prototypical network method are effective and practical for PWD-infected individual trees identification using UAV hyperspectral data, and the proposed integrated prototypical network enables early identification of PWD, providing a new technical guidance for early monitoring and control of PWD.

Abstract In fully mechanized top‐coal caving (FMTC), the effects of coal caving are closely related to the degree of damage to the top‐coal which is determined by the stress state therein. Therefore, research into the evolution of mining‐induced stress field is key to understanding failure mechanisms of top‐coal. By taking the 12 309 FMTC face in Wangjialing Coal Mine (China) as the engineering background and using field measurement and numerical simulation, we studied the evolution of the principal stress field in FMTC under high horizontal stress. The research results demonstrated that in situ stress in Wangjialing Coal Mine was a high horizontal stress and lateral pressure coefficients in the north‐south and east‐west directions were 1.52 and 0.45, respectively. Under the influence of mining, principal stresses were concentrated in front of the coal wall, with concentration factors of 2.26, 2.24, and 2.85, respectively. The minimum principal stress in unconstrained sides of the top‐coal in the roof‐control zone was tensile. The directions of intermediate and minimum principal stresses in the top‐coal were more sensitive to the influence of mining compared to the maximum principal stress. During rotation of the principal stress direction in top‐coal, the location (19 m in front of the coal wall) where the maximum and intermediate principal stresses were equal and the location of the coal wall are key positions.

Abstract Stress concentration in partially caved goaf is the main cause of dynamic pressure accident in the lower seam mining. Aimed at the characteristics of caving in shallow partially caved goaf (PCG) and the specificity of interior load‐bearing structures, a classification criterion of goaf caving was proposed. The characteristics of cooperative load‐bearing in pillar group and gob pile were revealed by numerical calculation, physical simulation, and theoretical analysis. Taking intermittent mining as an example, combined with the deformation behaviors of the main roof and the loading characteristics of waster rock mass, the characteristics of the load‐bearing of gob piles were described in the form of a piecewise function. A FLAC3D model of intermittent mining is modeled to evaluate the stability of pillars, the long‐term stability and distribution laws of overlying loads were revealed through a refined model. The results show that the width of the caved zone bearing the load in the intermittent goaf is about 20 m, and the maximum load‐bearing capacity is 1.055 MPa. The maximum depth of the plastic region in one side of the pillar is 1.48 m, and the load on elastic zone is about 11.33 MPa. This study provides a method for the study of the caving characteristics and load uncertainty in PCG, and the results provide important theoretical values for the safe mining of lower coal seams.

Abstract Background Cognitive impairment is commonly reported in patients receiving chemotherapy, but the acuity of onset is not known. This study utilized the psychomotor vigilance test (PVT) and trail-making test B (TMT-B) to assess cognitive impairment immediately post-chemotherapy. Methods Patients aged 18–80 years receiving first-line intravenous chemotherapy for any stage of breast or colorectal cancer were eligible. Patient symptoms, peripheral neuropathy and Stanford Sleepiness Scale were assessed. A five-minute PVT and TMT-B were completed on a tablet computer pre-chemotherapy and immediately post-chemotherapy. Using a mixed linear regression model, changes in reciprocal transformed PVT reaction time (mean 1/RT) were assessed. A priori, an increase in median PVT reaction times by > 20 ms (approximating PVT changes with blood alcohol concentrations of 0.04–0.05 g%) was considered clinically relevant. Results One hundred forty-two cancer patients (73 breast, 69 colorectal, median age 55.5 years) were tested. Post-chemotherapy, mean 1/RT values were significantly slowed compared to pre-chemotherapy baseline (p = 0.01). This corresponded to a median PVT reaction time slowed by an average of 12.4 ms. Changes in PVT reaction times were not correlated with age, sex, cancer type, treatment setting, or use of supportive medications. Median post-chemotherapy PVT reaction time slowed by an average of 22.5 ms in breast cancer patients and by 1.6 ms in colorectal cancer patients. Post-chemotherapy median PVT times slowed by > 20 ms in 57 patients (40.1%). Exploratory analyses found no statistically significant association between the primary outcome and self-reported anxiety, fatigue or depression. TMT-B completion speed improved significantly post-chemotherapy (p = 0.03), likely due to test-retest phenomenon. Conclusions PVT reaction time slowed significantly immediately post-chemotherapy compared to a pre-chemotherapy baseline, and levels of impairment similar to effects of alcohol consumption in other studies was seen in 40% of patients. Further studies assessing functional impact of cognitive impairment on patients immediately after chemotherapy are warranted.

Introduction: The role of surgery and non-surgical locoregional treatments (LRT) such as radiation therapy (RT) and local ablation techniques in patients with metastatic gastrointestinal stromal tumor (GIST) is unclear. This study examines LRT practice patterns in metastatic GIST and their clinical outcomes in British Columbia (BC). Methods: Patients diagnosed with either recurrent or de novo metastatic GIST from January 2008 to December 2017 were identified. Clinical characteristics and outcomes were analyzed in patients who underwent LRT, including surgical resection of the primary tumor or metastectomy, RT, or other local ablative procedures. Results: 127 patients were identified: 52 (41%) had de novo metastasis and 75 (59%) had recurrent metastasis. Median age was 67 (23–90 years), 58.2% were male, primary site was 33.1% stomach, 40.2% small intestine, 11% rectum/pelvis, and 15.7% others. 37 (29.1%) of patients received palliative surgery, the majority of which had either primary tumor removal only (43.3%) or both primary tumor removal and metastectomy (35.1%). A minority of patients underwent metastectomy only (21.6%). A total of 12 (9.5%) patients received palliative RT to metastatic sites only (58.3%) or primary tumors only (41.7%), mostly for symptomatic control (n = 9). A few patients (n = 3) received local ablation for liver metastatic deposits with 1 patient receiving microwave ablation (MWA) and 2 receiving radiofrequency ablation (RFA). Most patients (n = 120, 94.5%) received some type of systemic treatment. It is notable that prolonged progression free survival (PFS) was observed for the majority of patients who underwent surgery in the metastatic setting with a median PFS of 20.5 (95% confidence interval (CI): 14.29–40.74) months. In addition, significantly higher median overall survival (mOS) was observed in patients who underwent surgery (97.15 months; 95% CI: 77.7-not reached) and LRT (78.98 months; 95% CI: 65.58-not reached) versus no surgery (45.37 months; 95% CI: 38.7–64.69) and no LRT (45.27 months; 95% CI: 33.25–58.66). Almost all patients (8 out of 9) achieved symptomatic improvement after palliative RT. All 3 patients achieved partial response and 2 out of 3 patients had relatively durable responses of 1 year or more after local ablation. Discussion: This study is among the first to systematically examine the use of various LRT in metastatic GIST management. Integration of LRT with systemic treatments may potentially provide promising durable response and prolonged survival for highly selected metastatic GIST patients with low volume disease, limited progression and otherwise well controlled on systemic treatments. These observations, consistent with others, add to the growing evidence that supports the judicious use of LRT in combination with systemic treatments to further optimize the care of metastatic GIST patients.

Small water bodies ranging in size from 1 to 50,000 m2, are numerous, widely distributed, and have various functions in water storage, agriculture, and fisheries. Small water bodies used for agriculture and fisheries are economically significant in China, hence it is important to properly identify and analyze them. In remote sensing technology, water body identification based on band analysis, image classification, and water indices are often designed for large, homogenous water bodies. Traditional water indices are often less accurate for small water bodies, which often contain submerged or floating plants or easily confused with hill shade. Water quality inversion commonly depends on establishing the relationship between the concentration of water constituents and the observed spectral reflectance. However, individual variation in water quality in small water bodies is enormous and often far beyond the range of existing water quality inversion models. In this study, we propose a method for small water body identification and water quality estimation and test its applicability in Wuhan. The kappa coefficient of small water body identification is over 0.95, and the coefficient of determination of the water quality inversion model is over 0.9. Our results show that the method proposed in this study can be employed to accurately monitor the dynamics of small water bodies. Due to the outbreak of the COVID-19 pandemic, the intensity of human activities decreased. As a response, significant changes in the water quality of small water bodies were observed. The results also suggest that the water quality of small water bodies under different production modes (intensive/casual) respond differently in spatial and temporal dimensions to the decrease in human activities. These results illustrate that effective remote sensing monitoring of small water bodies can provide valuable information on water quality.

As a rising emerging field, synthetic biology intends to realize precise regulations of cellular network by constructing artificial synthetic circuits, and it brings great opportunities to treat diseases and discover novel drug targets. Depending on the combination mode of different logic gates, various synthetic circuits are created to carry out multilevel regulations. In given synthetic circuits, drugs often act as inputs to drive circuits operation. It is becoming available to construct drug-responsive gene circuits for experimentally treating various disease models, including metabolic disease, immunity disease, cancer and bacterial infection. Synthetic biology works well in association with the CRISPR system for drug target functional screening. Remarkably, more and more well-designed circuits are developed to discover novel drug targets and precisely regulate drug therapy for diseases.

Ki67 is a commonly used marker of cancer cell proliferation, and has significant prognostic value in breast cancer. In spite of its clinical importance, assessment of Ki67 remains a challenge, as current manual scoring methods have high inter- and intra-user variability. A major reason for this variability is selection bias, in that different observers will score different regions of the same tumor. Here, we developed an automated Ki67 scoring method that eliminates selection bias, by using whole-slide analysis to identify and score the tumor regions with the highest proliferative rates. The Ki67 indices calculated using this method were highly concordant with manual scoring by a pathologist (Pearson's r = 0.909) and between users (Pearson's r = 0.984). We assessed the clinical validity of this method by scoring Ki67 from 328 whole-slide sections of resected early-stage, hormone receptor-positive, human epidermal growth factor receptor 2-negative breast cancer. All patients had Oncotype DX testing performed (Genomic Health) and available Recurrence Scores. High Ki67 indices correlated significantly with several clinico-pathological correlates, including higher tumor grade (1 versus 3, P