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Abstract Background The high recurrence rate after liver resection emphasizes the urgent need for neoadjuvant therapy in hepatocellular carcinoma (HCC) to enhance the overall prognosis for patients. Immune checkpoint inhibitors, camrelizumab combined with an anti-angiogenic tyrosine kinase inhibitor (TKI) apatinib, have emerged as a first-line treatment option for patients with unresectable HCC, yet its neoadjuvant application in combination with transarterial chemoembolization (TACE) in HCC remains unexplored. Therefore, this study aims to investigate the efficacy and safety of sequential TACE, camrelizumab, and apatinib as a neoadjuvant therapy for single, huge HCC. Methods This multi-center, open-label randomized phase 3 trial will be conducted at 7 tertiary hospitals. Patients with single huge (≥ 10 cm in diameter), resectable HCC will be randomly assigned in a 1:1 ratio to arm of surgery alone or arm of neoadjuvant therapy followed by surgery. In the neoadjuvant therapy group, patients will receive TACE within 1 week after randomization, followed by camrelizumab (200 mg q2w, 4 cycles), along with apatinib (250 mg qd, 2 months). Patients will receive liver resection after neoadjuvant therapy unless the disease is assessed as progressive. The primary outcome is recurrence-free survival (RFS) at 1 year. The planned sample size of 60 patients will be calculated to permit the accumulation of sufficient RFS events in 1 year to achieve 80% power for the RFS primary endpoint. Discussion Synergistic effects provided by multimodality therapy of locoregional treatment, TKI, and anti-programmed cell death 1 inhibitor significantly improved overall survival for patients with unresectable HCC. Our trial will investigate the efficacy and safety of the triple combination of TACE, camrelizumab, and apatinib as a neoadjuvant strategy for huge, resectable HCC. Trial registration www.chitr.org.cn ChiCTR2300078086. Registered on November 28, 2023. Start recruitment: 1st January 2024. Expected completion of recruitment: 15th June 2025.

Abstract Purpose Ventilator care bundles are effective in the prevention of ventilator-associated pneumonia (VAP). However, the compliance of these bundles in intensive care units (ICUs) remains poorly studied. This study investigates the Medical Information Mart for Intensive Care (MIMIC)-IV cohort’s compliance with the Institute for Healthcare Improvement (IHI) bundle and its resulting association with VAP incidence. Methods This is a retrospective cohort study of the MIMIC-IV database. Patients with > 48 h of invasive mechanical ventilation (IMV) were included. Diagnosis of VAP was identified with the International Classification of Diseases (ICD)-9 and ICD-10 codes. Compliance rates to the IHI bundle were extracted. The association of the IHI bundle and its individual interventions with VAP incidence was analyzed with univariate and multivariate analysis. Results 8270 patients were included, of which 1328 (16.1%) had VAP. 25 patients (0.3%) had full compliance to the IHI bundle. 137 patients (1.7%) received no interventions from the bundle. Gastroprophylaxis had the lowest (2.1%) while head elevation had the highest (89.3%) compliance rates. In patients receiving the IHI bundle, each additional intervention was associated with lower VAP incidence (OR [odds ratio] = 0.906, 95% CI [confidence interval] 0.847–0.969). Appropriate sedation levels (OR = 0.765, 95% CI 0.661–0.885) and the use of heat and moisture exchanger (HME) filters (OR = 0.862, 95% CI 0.745–0.998) were individually associated with reduced VAP incidence, while active humidification was individually associated with increased VAP incidence (OR = 1.139, 95% CI 1.001–1.296). Conclusion The use of the IHI bundle was associated with a lower incidence of VAP, but compliance with the bundle was poor. Appropriate sedation and HME filters were individually associated with reduced VAP incidence. Better compliance with the IHI bundle may reduce VAP rates in mechanically ventilated patients. Graphical Abstract

BackgroundAs global populations age and become susceptible to neurodegenerative illnesses, new therapies for Alzheimer disease (AD) are urgently needed. Existing data resources for drug discovery and repurposing fail to capture relationships central to the disease’s etiology and response to drugs. ObjectiveWe designed the Alzheimer’s Knowledge Base (AlzKB) to alleviate this need by providing a comprehensive knowledge representation of AD etiology and candidate therapeutics. MethodsWe designed the AlzKB as a large, heterogeneous graph knowledge base assembled using 22 diverse external data sources describing biological and pharmaceutical entities at different levels of organization (eg, chemicals, genes, anatomy, and diseases). AlzKB uses a Web Ontology Language 2 ontology to enforce semantic consistency and allow for ontological inference. We provide a public version of AlzKB and allow users to run and modify local versions of the knowledge base. ResultsAlzKB is freely available on the web and currently contains 118,902 entities with 1,309,527 relationships between those entities. To demonstrate its value, we used graph data science and machine learning to (1) propose new therapeutic targets based on similarities of AD to Parkinson disease and (2) repurpose existing drugs that may treat AD. For each use case, AlzKB recovers known therapeutic associations while proposing biologically plausible new ones. ConclusionsAlzKB is a new, publicly available knowledge resource that enables researchers to discover complex translational associations for AD drug discovery. Through 2 use cases, we show that it is a valuable tool for proposing novel therapeutic hypotheses based on public biomedical knowledge.

The Shanghai Cooperation Organisation (SCO) is the most extensive and populous comprehensive regional cooperation organization in the world, covering about half of the world's population, with not only a huge consumer market, but also rich natural resources and strong productivity. As one of the important platforms for the implementation of the Green Belt and Road Initiative, it is an important opportunity for the SCO to actively participate in global governance and contribute to building a community of global life. To investigate the status of biodiversity conservation in the SCO countries, we used literature analysis approach. We surveyed the performance and international cooperation status of the SCO countries in the implementation of the Convention on Biological Diversity (CBD), listed facing problems and threats to biodiversity conservation, including not optimistic biodiversity conservation project implementation status, contradiction between ecological protection and economic development, impacts of human activities, lack of funds and talents, etc., and analyzed the biodiversity protection needs of the SCO countries from the perspectives of project and policy implementation status and international cooperation. According to the cooperation between China and the other SCO countries on biodiversity conservation and the post-2020 global biodiversity framework goals, we gave some recommendations: (1) promoting access to genetic resources and benefit-sharing; (2) integrating multiple funds and innovating the implementation of funding mechanism; (3) developing talent training and exchange programs and deepening multilateral cooperation; (4) strengthening cross-border cooperation and improving cooperation network; and (5) establishing a coordination mechanism for biodiversity conservation within the framework of the SCO.

In order to scientifically evaluate the target damage effect of uncertain intersection between projectile and target confrontation game, this paper establishes a basic model of target damage in the intersection between projectile and target game, which is through the spatial relationship between the explosive position of the projectile and the target position and gives a calculation method of target damage evaluation. The study applies Nash equilibrium theory to analyze income-loss functions in an adversarial game model. According to the definition of the possibility degree of interval number in uncertain multi-attribute decision-making, we proposed a method of solving the Nash equilibrium value of the income matrix of both sides of the game, which is using the interval possibility degree. We used quantitative calculations to analyze game strategies and changes in target damage under different states, such as fragment numbers, velocities, and angles of hit in the confrontation game between projectile and target. Based on the Nash equilibrium value solution method of the particle swarm optimization algorithm, we quantitatively calculated the fitness change relationship between the projectile and the target under different strategy sets. Based on the actual projectile confrontation game test, we analyze the damage probability effects of two projectiles at different explosion positions and different rendezvous angle angles on the three cabins. The results show that in the same area, the intersection angle is smaller, the probability of target damage is greater, and the intersection distance is farther, the damage probability is smaller.

Abstract In computational toxicology, prediction of complex endpoints has always been challenging, as they often involve multiple distinct mechanisms. State‐of‐the‐art models are either limited by low accuracy, or lack of interpretability due to their black‐box nature. Here, we introduce AIDTox, an interpretable deep learning model which incorporates curated knowledge of chemical‐gene connections, gene‐pathway annotations, and pathway hierarchy. AIDTox accurately predicts cytotoxicity outcomes in HepG2 and HEK293 cells. It also provides comprehensive explanations of cytotoxicity covering multiple aspects of drug activity, including target interaction, metabolism, and elimination. In summary, AIDTox provides a computational framework for unveiling cellular mechanisms for complex toxicity endpoints.

BackgroundIn sepsis patients, kidney damage is among the most dangerous complications, with a high mortality rate. In addition, major adverse kidney events within 30 days (MAKE30) served as a comprehensive and unbiased clinical outcome measure for sepsis patients due to the recent shift toward targeting patient-centered renal outcomes in clinical research. However, the underlying predictive model for the prediction of MAKE30 in sepsis patients has not been reported in any study.MethodsA cohort of 2,849 sepsis patients from the Medical Information Mart for Intensive Care (MIMIC)-IV database was selected and subsequently allocated into a training set (n = 2,137, 75%) and a validation set (n = 712, 25%) through randomization. In addition, 142 sepsis patients from the Xi’An No. 3 Hospital as an external validation group. Univariate and multivariate logistic regression analyses were conducted to ascertain the independent predictors of MAKE30. Subsequently, a nomogram was developed utilizing these predictors, with an area under curve (AUC) above 0.6. The performance of nomogram was assessed through calibration curve, receiver operating characteristics (ROC) curve, and decision curve analysis (DCA). The secondary outcome was 30-day mortality, persistent renal dysfunction (PRD), and new renal replacement therapy (RRT). MAKE30 were a composite of death, PRD, new RRT.ResultsThe construction of the nomogram was based on several independent predictors (AUC above 0.6), including age, respiratory rate (RR), PaO2, lactate, and blood urea nitrogen (BUN). The predictive model demonstrated satisfactory discrimination for MAKE30, with an AUC of 0.740, 0.753, and 0.821 in the training, internal validation, and external validation cohorts, respectively. Furthermore, the simple prediction model exhibited superior predictive value compared to the SOFA model in both the training (AUC = 0.710) and validation (AUC = 0.692) cohorts. The nomogram demonstrated satisfactory calibration and clinical utility as evidenced by the calibration curve and DCA. Additionally, the predictive model exhibited excellent accuracy in forecasting 30-day mortality (AUC = 0.737), PRD (AUC = 0.639), and new RRT (AUC = 0.846) within the training dataset. Additionally, the model displayed predictive power for 30-day mortality (AUC = 0.765), PRD (AUC = 0.667), and new RRT (AUC = 0.783) in the validation set.ConclusionThe proposed nomogram holds the potential to estimate the risk of MAKE30 promptly and efficiently in sepsis patients within the initial 24 h of admission, thereby equipping healthcare professionals with valuable insights to facilitate personalized interventions.

IntroductionPrehabilitation, which involves improving a patient’s physical and psychological condition before surgery, has shown potential benefits but has yet to be extensively studied from an economic perspective. To address this gap, a systematic review was conducted to summarize existing economic evaluations of prehabilitation interventions.MethodsThe PRISMA Protocols 2015 checklist was followed. Over 16,000 manuscripts were reviewed, and 99 reports on preoperative interventions and screening tests were identified, of which 12 studies were included in this analysis. The costs are expressed in Pounds (GBP, £) and adjusted for inflation to December 2022.ResultsThe studies were conducted in Western countries, focusing on specific surgical subspecialties. While the interventions and study designs varied, most studies demonstrated cost savings in the intervention group compared to the control group. Additionally, all cost-effectiveness analysis studies favored the intervention group. However, the review also identified several limitations. Many studies had a moderate or high risk of bias, and critical information such as time horizons and discount rates were often missing. Important components like heterogeneity, distributional effects, and uncertainty were frequently lacking as well. The misclassification of economic evaluation types highlighted a lack of knowledge among physicians in prehabilitation research.ConclusionThis review reveals a lack of robust evidence regarding the economics of prehabilitation programs for surgical patients. This suggests a need for further research with rigorous methods and accurate definitions.

Aiming at the problem of damage calculation under the confront game mechanism formed by the projectile and target intersection in the weapon range damage test, this paper proposes a target damage calculation model and method of gain-loss game distribution mechanism on projectile and target intersection confront based on the characteristics of the projectile and target intersection confront game. In this method, the damage of the confront game between the projectile and the target is regarded as the participants of the two-person zero-sum non-cooperative game. According to the gain-loss relationship between the participants of the projectile and the target, we establish a damage assessment calculation model with the confront game between the projectile and the target, and derive the payoff function of the attack-defense game between the projectile and the target. We also establish a target damage calculation model with value / cost index function, determine the value / cost index function of projectile attack target, and give the calculation algorithm of projectile attack target damage based on game theory, and also research the allocation method of projectile attack target based on value / cost index function, at last, give the optimized target damage evaluation system. Through quantitative calculation and analysis, it is found that the effect of target damage is different under different conditions of game strategies, especially the value of value / cost index function is different. The obtained game damage probability presents a random number of Gaussian distribution. When the optimal distribution value is satisfied, the target damage effect is the best, which verifies the scientific type and rationality of the damage calculation model proposed in this paper.

The use of epidermal growth factor for wound healing is limited by transdermal permeability, reduction, and receptor desensitization. Here the authors develop a microneedle-based self-powered transcutaneous electrical stimulation system to overcome these challenges.

IntroductionVacuolar protein sorting 29 (VPS29) is a core component of the retromer-retriever complex and is essential for recycling numerous cell-surface cargoes from endosomes. However, there are no reports yet on VPS29 of Eimeria spp.MethodsHere, we cloned and prokaryotically expressed a partial sequence of Eimeria tenella VPS29 (EtVPS29) with RT-PCR and engineered strain of Escherichia coli respectively. The localization of the VPS29 protein in E. tenella sporozoites was investigated with immunofluorescence (IFA) and overexpression assays. And its protective efficacy against E. tenella infection was investigated in chickens with the animal protection test.ResultsAn EtVPS29 gene fragment with an ORF reading frame of 549 bp was cloned. The band size of the expressed recombinant protein, rEtVPS29, was approximately 39 kDa and was recognized by the chicken anti-E. tenella positive serum. EtVPS29 protein was observed widely distributing in the cytoplasm of E. tenella sporozoites in the IFA and overexpression assays. rEtVPS29 significantly increased average body weight gain and decreased mean lesion score and oocyst output in chickens. The relative weight gain rate in the rEtVPS29-immunized group was 62.9%, which was significantly higher than that in the unimmunized and challenged group (P < 0.05). The percentage of reduced oocyst output in the rEtVPS29 immunized group was 32.2%. The anticoccidial index of the rEtVPS29-immunized group was 144.2. Serum ELISA also showed that rEtVPS29 immunization induced high levels of specific antibodies in chickens.DiscussionThese results suggest that rEtVPS29 can induce a specific immune response and is a potential candidate for the development of novel vaccines against E. tenella infections in chickens.

Abstract Background Allergic rhinitis (AR) is an upper respiratory tract inflammation disease caused by IgE-mediated reactions against inhaled allergens. The incidence of AR is significantly increasing throughout the world. Hence, more specific, and sensitive gene biomarkers and understanding the underlying pathways are necessary to further explore the AR pathogenesis. Objective To identify gene biomarkers in nasal mucosa and in blood from AR patients which could be used in AR diagnosis. Methods The gene expression profiles of GSE43523 from nasal epithelial cells and GSE75011 from Th2-enriched CD4+ T cells in blood were downloaded from the Gene Expression Omnibus database. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses and protein–protein interaction (PPI) network analysis were conducted to investigate the functional changes of genes. The receiver operating characteristic (ROC) curves were used to assess the diagnostic values of the hub genes. Real-time quantitative PCR (RT-qPCR) was performed to validate the hub genes. Results Significant differentially enriched gene signatures in AR patients were identified in nasal epithelial cells (n-DEGs) and in blood (t-DEGs). Signatures associated with axoneme, extracellular matrix, collagen fibril organization, cell motility, calcium ion binding, and so on were more enriched in n-DEGs, whereas signatures associated with TNF signaling pathway, detoxification of inorganic compound, and cellular response to corticotropin-releasing hormone stimulus were enriched in t-DEGs. In addition, we identified 8 hub genes and 14 hub genes from n-DEGs and t-DEGs, respectively. The combination of POSTN in nasal mucosa and PENK and CDC25A in blood was constructed with a good AR predicting performance. The area under the curve (AUC) of the ROC curve of 3 hub genes’ combination was 0.98 for AR diagnosis. Conclusion This study utilized gene expression profiles and RT-qPCR validation on nasal mucosa and blood from AR patients to investigate the potential biomarkers for AR diagnosis.

To effectively evaluate the damage efficiency of the terminal-sensitive projectile to the ground target under the power of multiple projectiles, this paper proposes a new method to calculate the damaging effect of the ground target by dividing the falling multiple sensitive projectiles into a multi-layer plane, uses the superposition principle to set up the multiple projectile power situation and analyzes the distribution of projectiles falling near the ground. The paper researches the detection method of the terminal-sensitive projectile with laser and infrared composite detection and establishes the calculation model of laser reflection echo power and thermal radiated power of the target. From the aspects of detection, attack and electronic jamming abilities, this paper set up the calculation model for multiple projectile power situation. Based on the distribution of the terminal-sensitive projectile group established, the fuzzy relationship between each evaluation index of the ground target and the distribution state of the terminal-sensitive missile group is used to establish the power evaluation function of the terminal-sensitive projectile. The analysis results demonstrate that the power of terminal-sensitive projectiles is related to the distance of the intersection of projectile and target, and when the intersection distance is small, the damaging effect of terminal-sensitive projectiles on the ground targets is better.

The roots of Astragalus membranaceus var. mongholicus (AMM) and A. membranaceus (AM) are widely used in traditional Chinese medicine. Although AMM has higher yields and accounts for a larger market share, its cultivation is fraught with challenges, including mixed germplasm resources and widespread adulteration of commercial seeds. Current methods for distinguishing Astragalus seeds from similar (SM) seeds are time-consuming, laborious, and destructive. To establish a non-destructive method, AMM, AM, and SM seeds were collected from various production areas. Machine vision and hyperspectral imaging (HSI) were used to collect morphological data and spectral data of each seed batch, which was used to establish discriminant models through various algorithms. Several preprocessing methods based on hyperspectral data were compared, including multiplicative scatter correction (MSC), standard normal variable (SNV), and first derivative (FD). Then selection methods for identifying informative features in the above data were compared, including successive projections algorithm (SPA), uninformative variable elimination (UVE), and competitive adaptive reweighted sampling (CARS). The results showed that support vector machine (SVM) modeling of machine vision data could distinguish Astragalus seeds from SM with >99% accuracy, but could not satisfactorily distinguish AMM seeds from AM. The FD-UVE-SVM model based on hyperspectral data reached 100.0% accuracy in the validation set. Another 90 seeds were tested, and the recognition accuracy was 100.0%, supporting the stability of the model. In summary, HSI data can be applied to discriminate among the seeds of AMM, AM, and SM non-destructively and with high accuracy, which can drive standardization in the Astragalus production industry.

ObjectiveWe aimed to use the cancer genome atlas and gene expression omnibus databases to explore the characterization of tumor microenvironment (TME) infiltration and construct a predictive index of prognosis and treatment effect based on cuproptosis-related genes (CRGs) in primary lung adenocarcinoma (LUAD).MethodsWe described the alterations of CRGs in 954 LUAD samples from genetic and transcriptional fields and evaluated their expression patterns from three independent datasets. We identified two distinct molecular subtypes and found that multi-layer CRG alterations were correlated with patient clinicopathological features, prognosis, and TME cell infiltrating characteristics. Then, a cuproptosis scoring system (CSS) for predicting the prognosis was constructed, and its predictive capability in LUAD patients was validated.ResultsTwo molecular subtypes of cuproptosis (Copper Genes cluster A and cluster B) in LUAD were identified. Copper Genes cluster B had better survival than those with Copper Genes cluster A (p

In Global Navigation Satellite System (GNSS)-denied environments, image registration has emerged as a prominent approach to utilize visual information for estimating the position of Unmanned Aerial Vehicles (UAVs). However, traditional image-registration-based localization methods encounter limitations, such as strong dependence on the prior initial position information. In this paper, we propose a systematic method for UAV geo-localization. In particular, an efficient range–visual–inertial odometry (RVIO) is proposed to provide local tracking, which utilizes measurements from a 1D Laser Range Finder (LRF) to suppress scale drift in the odometry. To overcome the differences in seasons, lighting conditions, and other factors between satellite and UAV images, we propose an image-registration-based geo-localization method in a coarse-to-fine manner that utilizes the powerful representation ability of Convolutional Neural Networks (CNNs). Furthermore, to ensure the accuracy of global optimization, we propose an adaptive weight assignment method based on the evaluation of the quality of image-registration-based localization. The proposed method is extensively evaluated in both synthetic and real-world environments. The results demonstrate that the proposed method achieves global drift-free estimation, enabling UAVs to accurately localize themselves in GNSS-denied environments.

The effective defense of sparsely populated border islands, surrounded by a multifaceted sea, against enemy infiltration poses a crucial problem in national defense. One possible solution is to deploy multiple unmanned surface vessels (USVs) to form an intelligent patrol and defense system. With the designated or daily patrols of USVs, we need to allocate target positions in real time to ensure their continuous operation. Currently, the state-of-art methods contain two major problems of target deadlock and local optimization, which limit the efficiency of reaching the target. To this end, we proposed a novel Region-Construction (RECO) method aimed at high-efficiency target allocation. Firstly, a dynamic calculation approach in K value for unsupervised clustering and time factor’s lead-in for Market-Based Mechanism (MBM) method was created to resolve potential target deadlock among USVs. Secondly, we proposed a novel construction strategy in a non-complete graph (NCG) consisting of neighborhood connection and pheromone extension to provide enough feasible nodes for solution searching. Finally, we introduced adjustment of search range and edge weights, and activated node interaction in traditional Ant Colony Optimization (ACO) algorithm in NCG to obtain the optimal combination of each USV’s target allocations. We established a simulation platform with an airborne managing base station and several USVs. The experimental results demonstrated that when the number of USVs was four, the average time for all USVs to reach the target in the RECO method reduced by 10.9% and 7.7% compared to the MBM and ACO methods, respectively. This reduction was 25% and 11.6% for 6 USVs, 25.7% and 21.8% for 8 USVs, 20% and 19% for 10 USVs. It reflects that the proposed RECO allocation method has shown improvements in terms of successfully-assigned USVs’ quantity and operational efficiency, compared to the state-of-art MBM and ACO algorithms.

Natural extracellular vesicles (EVs) play important roles in many life processes such as in the intermolecular transfer of substances and genetic information exchanges. Investigating the origins and working mechanisms of natural EVs may provide an understanding of life activities, especially regarding the occurrence and development of diseases. Additionally, due to their vesicular structure, EVs (in small molecules, nucleic acids, proteins, etc.) could act as efficient drug-delivery carriers. Herein, we describe the sources and biological functions of various EVs, summarize the roles of EVs in disease diagnosis and treatment, and review the application of EVs as drug-delivery carriers. We also assess the challenges and perspectives of EVs in biomedical applications.

ObjectiveTo assess the effects of Hong Huang Decoction (HHD), a Chinese herbal medicine, on myocardial injury in breast cancer patients who underwent anthracycline (ANT)-based chemotherapy.MethodsA total of 51 patients with breast cancer who underwent an ANT-based chemotherapy program and met the inclusion/exclusion criteria were allocated to the treatment or placebo groups using a random number generation process. Patients in the treatment group received liquid HHD twice a day. Treatment was given from 1 day prior to chemotherapy up to the end of chemotherapy (after 6 months). Participants in the placebo group received a placebo over the same schedule. Left ventricular ejection fraction (LVEF), global longitudinal strain (GLS), diagnostic markers of acute myocardial infarction [e.g., lactate dehydrogenase (LDH), creatine kinase-MB (CK-MB), and B-type natriuretic peptide (BNP)], nitric oxide (NO), superoxide dismutase (SOD), as well as pro-inflammatory cytokines [e.g., tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and human C-reactive protein (CRP)], and anti-inflammatory cytokine interleukin-10 (IL-10), were outcome measures assessed before chemotherapy, 3 and 6 months after chemotherapy.ResultsCompared to the placebo group, the GLS value was significantly higher in the treatment group (19.95 ± 1.16 vs. 19.06 ± 1.64, P ≤ 0.001). Significant differences were also noted for levels of SOD (689.71 ± 203.60 vs. 807.88 ± 182.10, P < 0.05), IL-6 (58.04 ± 22.06 vs. 194.20 ± 40.14, P ≤ 0.001), IL-10 (237.90 ± 94.98 vs. 68.81 ± 32.92, P ≤ 0.001), NO (75.05 ± 26.39 vs. 55.83 ± 19.37, P ≤ 0.005), and TNF-α (301.80 ± 134.20 vs. 680.30 ± 199.60, P ≤ 0.001) in the patients before chemotherapy compared to 6 months after initiating chemotherapy.ConclusionHHD regulated the levels of IL-6, IL-10, SOD, NO, and TNF-α. The results demonstrated that GLS is a better indicator of early myocardial injury compared to LVEF, and HHD could modulate oxidative stress to protect against ANT cardio toxicity.Clinical trial registrationChinese Clinical Trial Registry, identifier ChiCTR1900022394. Date of registration: 2019-04-09.

Abstract Designing inter-regional and inter-provincial responsibility-sharing mechanisms for climate change mitigation requires the knowledge of carbon distributions. This study is the first to use a two-sector (i.e., productive and household sectors) inequality decomposition approach to examine the regional, provincial, and national inequalities of per capita CO2 emissions (CPC) in China, as well as their determinants. We show that the CPC inequality index in China increased from 1.1364 in 2000 to 2.3688 in 2017, with the productive sector accounting for 91.42% of this expansion and households responsible for the rest. The production-side per capita output level, energy efficiency, energy structure, and industrial structure explain 69.01%, 12.81%, 5.57%, and 4.03% of these inequalities, respectively. Further, the household per capita energy consumption and energy structure explain only 8.12% and 0.46%, respectively. Therefore, future responsibility-sharing mechanisms for climate mitigation need to be formulated taking mainly the productive sector into account.

Accurate, robust and drift-free global pose estimation is a fundamental problem for autonomous vehicles. In this work, we propose a global drift-free map-based localization method for estimating the global poses of autonomous vehicles that integrates visual–inertial odometry and global localization with respect to a pre-built map. In contrast to previous work on visual–inertial localization, the global pre-built map provides global information to eliminate drift and assists in obtaining the global pose. Additionally, in order to ensure the local odometry frame and the global map frame can be aligned accurately, we augment the transformation between these two frames into the state vector and use a global pose-graph optimization for online estimation. Extensive evaluations on public datasets and real-world experiments demonstrate the effectiveness of the proposed method. The proposed method can provide accurate global pose-estimation results in different scenarios. The experimental results are compared against the mainstream map-based localization method, revealing that the proposed approach is more accurate and consistent than other methods.

A mixed Co and Ni boride precursor was synthesized via chemical reduction and subsequently annealed at 400 or 500 °C with or without prior addition of the monomer benzoxazine (BO). The resulting mixed CoNiB materials were investigated as electrocatalysts for three alcohol oxidation reactions (AOR) in alkaline electrolyte: the oxidation of glycerol (GOR), ethylene glycol (EGOR) and ethanol (EOR). Comparison of the rotating disk electrode (RDE) cyclic voltammograms for the different catalysts revealed that CoNiB annealed at 500 °C without the addition of BO exhibited the lowest overpotentials in AORs at 10 mA cm ^−2 , promoting GOR at 224 ± 6 mV lower potential compared to OER. When pyrolysis was conducted at 400 °C, the BO-containing catalyst showed a significant increase in the electrocatalytic activity for the AORs compared to the CoNiB catalyst only. The product selectivity on the different catalysts was investigated in a batch-type reactor with flow recirculation revealing formate as the main oxidation product during GOR and EGOR with faradaic efficiencies (FE) in a range of 60%–80%, while acetate was obtained during EOR (FE ∼ 85%–90%). The electrode potential, electrolyte composition and the type of ionomer were explored with respect to their influence on the GOR selectivity. The use of different ionomers resulted in significant differences in the activity trends between RDE and the batch-type reactor with flow recirculation measurements, indicating a strong influence of the two different substrates used, namely glassy carbon and carbon paper on the catalyst formation and thus on the recorded electrochemical activity.

The target damage assessment when a projectile is attacking a ground target under uncertain information is a difficult problem to solve, because the intersection-relative position of the projectile and target is a random distribution and the target damage is also uncertain in the intersection confrontation between projectile and target. This paper regards the projectile and target as two participants of the zero-sum non-cooperative confrontation game and studies an offensive/defensive game damage strategy modeling method when the projectile meets the target under uncertain information. According to the information of both the projectile and the target, from the perspective of the gain of the projectile attacking the ground target and the gain of the ground target defense, this paper establishes the indicator function of offensive/defensive game of projectile and target intersection under uncertain information and constructs the payoff matrix of the confrontation game between the projectile and the target. The Nash equilibrium of the game is obtained by combining the particle swarm optimization algorithm and the interval number multiple attribute ranking method in the case of uncertain information, and then, a new optimal damage assessment strategy method of Offensive/Defensive Game of projectile and target is gained, the method to solve the Nash equilibrium value of the payment matrix is given. Simulations are performed to validate the feasibility and effectiveness of the proposed game damage strategy model and the solution method.

BackgroundVarious factors are discovered in the development of clinodactyly. The purpose of this retrospective study was to present a group of children with a rare clinodactyly deformity caused by phalangeal intra-articular osteochondroma and evaluate the efficacy of various treatment methods.MethodsAll child patients that were treated for finger problems in our center between Jan 2017 and Dec 2020 were reviewed. A detailed analysis was made of the diagnosis and treatment methods in eight rare cases. X-rays and histopathology were applied.ResultsA preliminary analysis of 405 patients in total was performed, and we included eight cases in our final analysis. This cohort consisted of 2 girls and 6 boys, with a mean age of 5.74 ± 3.22 years (range: 2y5m to 11y). Overall, four patients had their right hand affected and four patients had their left hand affected. One patient was diagnosed as having hereditary multiple osteochondroma (HMO) while the other seven patients were all grouped into solitary osteochondroma. Osteochondroma was proven in all of them by histopathology examination. Preoperative X-rays were used to allow identification and surgery planning in all cases. All osteochondromas were intra-articular and in the distal end of the phalanges, which is located opposite the epiphyseal growth area. All of the osteochondromas developed in half side of the phalanges. The angulation in the finger long axis was measured, and resulted in a mean angulation of 34.63 ± 24.93 degree (range: 10.16-88.91 degree). All of them received surgery, resulting in good appearance and fingers straightening. No recurrence was recorded.ConclusionsThis retrospective analysis indicates that 10 degrees can be selected as the angulation level for diagnosis of clinodactyly deformities. What’s more important, the abnormal mass proven by X-rays should be included as the classical direct sign for diagnosis. The first choice of treatment is surgery in symptomatic osteochondromas.

Background: Diaphyseal and metaphyseal modeling defects lead to severe changes in bone mass and shape, which are common features in osteoporosis that linked to non-vertebral fractures. Original mechanism of diaphyseal and metaphyseal modeling defects has proved elusive. Studying rare syndromes can elucidate mechanisms of common disorders and identify potential therapeutic targets.Methods: We evaluated a family pedigree with craniometadiaphyseal dysplasia (CRMDD, OMIM 269300), a genetic disorder that is characterized by cortical-bone thinning, limb deformity, and absent of normal metaphyseal flaring and diaphyseal constriction. Systemic radiographic examination and serum hormone test were made for this rare disease. One patient and her two normal parents were examined by means of whole-exome sequencing (WES) to identify the candidate pathogenic gene and rule out mucopolysaccharidosis and Prader–Willi Syndrome by means of Sanger sequencing.Results: There are several conspicuous radiographic characteristics: (1) bullet-shaped phalanges, (2) long and narrow pelvic inlet, absent of supra-acetabular constriction, (3) round rod-shaped long tubular bones, (4) prominent aiploic mastoid, (5) bending-shaped limb, genua varus and genu varum, and (6) congenital dislocation of elbow. Here, we did not find any wormian bones, and there are several typical clinical characteristics: (1) macrocephaly and wide jaw, (2) Avatar elf-shaped ears, pointed and protruding ears, (3) hypertrophy of limbs, (4) flat feet and giant hand phenomenon, (5) nail dystrophy, (6) limb deformity, (7) high-arched palate, (8) superficial hemangiomas, (9) tall stature, and intellectual disability. In this patient, we found biallelic frameshift deletion mutations in WRAP53, and those two mutations were transmitted from her parents respectively.Conclusions: We describe her clinical and radiological findings and presented a new subtype without wormian bones and with a tall stature. Our study showed that craniometadiaphyseal dysplasia was caused by a deficiency of WRAP53 with autosomal recessive inheritance.

Glucocorticoids are a class of steroid hormones secreted from the adrenal glands. The strong anti-inflammatory effects make it be one of the most popular and versatile drugs available to treat chronic inflammatory diseases. Additionally, supramolecular materials have been widely exploited in drug delivery, due to their biocompatibility, tunability, and predictability. Thus, steroid-based supramolecular materials and the release of steroids have been applied in the treatment of inflammatory diseases. This mini-review summarized recent advances in supramolecular materials loaded with glucocorticoid drugs in terms of hydrophobic interactions, electrostatic interactions, hydrogen bonding, and π-π stackings. We also discussed and prospected the application of the glucocorticoid drugs-based supramolecular system on chronic rhinosinusitis, multifactorial inflammatory disease of the nasal and paranasal sinuses mucosal membranes. Overall, supramolecular materials can provide an alternative to traditional materials as a novel delivery platform in clinical practice.

Chronic rhinosinusitis with nasal polyps (CRSwNP) is a chronic sinonasal inflammatory disease with limited treatment options of corticosteroids, sinus surgery, or both. CRSwNP is frequently associated with allergic rhinitis and asthma, but the molecular mechanisms underlying CRSwNP inflammation are not completely understood. We obtained four gene expression profiles (GSE136825, GSE36830, GSE23552, and GSE72713) from four Gene Expression Omnibus (GEO), which collectively included 65 nasal polyp samples from CRSwNP patients and 54 nasal mucosal samples from healthy controls. Using an integrated analysis approach, we identified 76 co-differentially expressed genes (co-DEGs, including 45 upregulated and 31 downregulated) in CRSwNP patients compared with the healthy controls. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses identified the terms including immune effector process, leukocyte migration, regulation of the inflammatory response, Staphylococcus aureus infection, and cytokine-cytokine receptor interaction. protein-protein interaction (PPI) network analysis and real-time quantitative PCR (RT-qPCR) showed that 7 genes might be crucial in CRSwNP pathogenesis. Repurposing drug candidates (Alfadolone, Hydralazine, SC-560, Iopamidol, Iloprost, etc) for CRSwNP treatment were identified from the Connectivity Map (CMap) database. Our results suggest multiple molecular mechanisms, diagnostic biomarkers, potential therapeutic targets, and new repurposing drug candidates for CRSwNP treatment.

Abstract As a pivotal vesicular trafficking protein, Myoferlin (MYOF) has become an attractive target for cancer therapy. However, the roles of MYOF in colorectal cancer invasion remain enigmatic, and MYOF‐targeted therapy in this malignancy has not been explored. In the present study, we provided the first functional evidence that MYOF promoted the cell invasion of colorectal cancer. Furthermore, we identified a novel small molecule inhibitor of MYOF (named YQ456) that showed high binding affinity to MYOF (KD = 37 nM) and excellent anti‐invasion capability (IC50 = 110 nM). YQ456 was reported for the first time to interfere with the interactions between MYOF and Ras‐associated binding (Rab) proteins at low nanomolar levels. This interference disrupted several vesicle trafficking processes, including lysosomal degradation, exosome secretion, and mitochondrial dynamics. Further, YQ456 exhibited excellent inhibitory effects on the growth and invasiveness of colorectal cancer. As the first attempt, the anticancer efficacy of YQ456 in the patient‐derived xenograft (PDX) mouse model indicated that targeting MYOF may serve as a novel and practical therapeutic approach for colorectal cancer.

In order to scientifically evaluate the target damage effectiveness when warhead fragments formed by projectile explosion attack targets, this paper proposes a new method by using the multi-layer warhead fragments distribution division mechanism to study an evaluation and calculation model of target damage effectiveness under uncertain information of warhead fragments. On the basis of the spatial relationship between projectile explosion position and target, we first analyze the target damage rules based on the target’s own vulnerability characteristics. Then we use the fuzzy prior probability theory to establish the membership function of the target damage factor and an evaluation model of the target damage grade, and use the stochastic multi-criteria acceptability analysis method to obtain the evaluation index value of the target damage level. Finally, considering the ratio between the effective area of the warhead fragment group attacking target and the area of target itself and the effective number and area ratio of warhead fragments penetrating target, we give a numerical calculation method of target damage effectiveness. Through simulation and calculation, the results show that when the distance between the projectile explosion position and the target is less than 7 m and the coordinate interval of the projectile flight direction is −2.5 m to 2.5 m, the damage probability of warhead fragments to the target is greater than 75%. When the weight of the damage factor of the target changes, the damage effectiveness of the target also changes, and this result is in accordance with the actual experiment, which verifies the rationality of the proposed mathematical model.

Herein, we have verified the interaction between the functional peptides from the SARS-CoV-2 and cell membrane, and we further proved that peptides exhibit little membrane disruption. The specific amino acids (Lys, Ile, Glu, Asn, Gln, etc.) with charge or hydrophobic residues play a significant role during the functional-peptide binding to membrane. The findings could provide the hints related to viral infection and also might pave the way for development of new materials based on peptides with membrane-binding activity, which would enable functional peptides further as peptide adjuvants, in order to help deliver the cancer drug into tumor cells for the efficient tumor therapy.

Improved therapeutics are needed for treating breast cancer. Here they show the druggability of myoferlin with a small molecule inhibitor in breast cancer and demonstrate its anti-breast cancer effects in vitro and in vivo.

Understanding the downstream consequences of pharmacologically targeted proteins is essential to drug design. Current approaches investigate molecular effects under tissue‐naïve assumptions. Many target proteins, however, have tissue‐specific expression. A systematic study connecting drugs to target pathways in in vivo human tissues is needed. We introduced a data‐driven method that integrates drug‐target relationships with gene expression, protein‐protein interaction, and pathway annotation data. We applied our method to four independent genomewide expression datasets and built 467,396 connections between 1,034 drugs and 954 pathways in 259 human tissues or cell lines. We validated our results using data from L1000 and Pharmacogenomics Knowledgebase (PharmGKB), and observed high precision and recall. We predicted and tested anticoagulant effects of 22 compounds experimentally that were previously unknown, and used clinical data to validate these effects retrospectively. Our systematic study provides a better understanding of the cellular response to drugs and can be applied to many research topics in systems pharmacology.

In this study, a series of new indole derivatives of ursolic acid bearing different N-(aminoalkyl)carboxamide side chains were designed, synthesized, and evaluated for their in vitro cytotoxic activities against two human hepatocarcinoma cell lines (SMMC-7721 and HepG2) and normal hepatocyte cell line (LO2) via MTT assay. Among them, compound 5f exhibited the most potent activity against SMMC-7721 and HepG2 cells with IC50 values of 0.56 ± 0.08 μM and 0.91 ± 0.13 μM, respectively, and substantially lower cytotoxicity to LO2 cells. A follow-up enzyme inhibition assay and molecular docking study indicated that compound 5f can significantly inhibit the activity of Topoisomerase IIα. Further mechanistic studies performed in SMMC-7721 cells revealed that compound 5f can elevate the intracellular ROS levels, decrease mitochondrial membrane potential, and finally lead to the apoptosis of SMMC-7721 cells. Collectively, compound 5f is a promising Topoisomerase II (Topo II) inhibitor, which exhibited the potential as a lead compound for the discovery of novel anticancer agents.

This study compared the sensing characteristics of ZnO (ZO) treated with ammonia (NH3) plasma for 1 min, 3 min, and 6 min, under the EIS structure. The measurement results revealed that, after 3 min of NH3 plasma treatment, the Mg-doped ZnO (MZO) sensing film had a high hydrogen ion sensitivity, linearity, hysteresis, and drift rate of 53.82 mV/pH, 99.04%, 2.52 mV, and 1.75 mV/h, respectively. The sensing film was used with sodium and potassium ion solutions, and it performed satisfactorily in sensing hydrogen ions. Additionally, we investigated the biomedical sensing properties of Mg-doped ZnO (MZO) sensing film with regard to urea, creatinine, and glucose solutions and found that the Mg-doped ZnO (MZO) sensing film treated with NH3 plasma for 3 min had the best properties for sensing urea, creatinine, and glucose. Specifically, with glucose, the sensing film achieved the best linearity and sensitivity and of 97.87% and 10.73 mV/mM, respectively. The results revealed that the sensing characteristics varied with the processing environment and are useful in the developing biomedical sensing applications with different sensing elements.

Monocyte/macrophage recruitment is closely associated with the degree of hypertensive renal injury. We investigated the direct role of macrophages using liposome-encapsulated clodronate (LEC) to deplete monocytes/macrophages in hypertensive renal injury. C57BL/6 mice were treated with a pressor dose of angiotensin (Ang, 1.4 mg/kg/day) II plus LEC or the PBS-liposome for 2 weeks. Ang II mice developed hypertension, albuminuria, glomerulosclerosis, and renal fibrosis. LEC treatment reduced systolic blood pressure (SBP), albuminuria, and protected against renal structural injury in Ang II mice. Ang II significantly increased renal macrophage infiltration (MOMA2+ cells) and the expression of renal tumor necrosis factor α and interleukin β1, which were significantly reduced in Ang II/LEC mice. Ang II increased renal oxidative stress and the expression of profibrotic factors transforming growth factor (TGF) β1 and fibronectin. Ang II also inhibited the phosphorylation of endothelial nitric oxide synthase [phospho-endothelial nitric oxide synthesis (eNOS), ser1177]. LEC treatment reduced renal oxidative stress and TGFβ1 and fibronectin expressions, and increased phospho-eNOS expression in the Ang II mice. In Dahl rats of salt-sensitive hypertension, LEC treatment for 4 weeks significantly attenuated the elevation of SBP induced by high salt intake and protected against renal injury and fibrosis. Our results demonstrate that renal macrophages play a critical role in the development of hypertension and hypertensive renal injury and fibrosis; the underlying mechanisms may be involved in the reduction in macrophage-driven renal inflammation and restoration of the balance between renal oxidative stress and eNOS. Therefore, macrophages should be considered as a potential therapeutic target to reduce the adverse consequences of hypertensive renal diseases.