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Abstract Approximately 15–30% of patients with lung cancer harbor mutations in the EGFR gene. Major EGFR mutations (>90% of EGFR-mutated lung cancer) are highly sensitive to EGFR tyrosine kinase inhibitors (TKIs). Many uncommon EGFR mutations have been identified, but little is known regarding their characteristics, activation, and sensitivity to various EGFR-TKIs, including allosteric inhibitors. We encountered a case harboring an EGFR-L747P mutation, originally misdiagnosed with EGFR-del19 mutation using a routine diagnostic EGFR mutation test, which was resistant to EGFR-TKI gefitinib. Using this minor mutation and common EGFR-activating mutations, we performed the binding free energy calculations and microsecond-timescale molecular dynamic (MD) simulations, revealing that the L747P mutation considerably stabilizes the active conformation through a salt-bridge formation between K745 and E762. We further revealed why several EGFR inhibitors, including the allosteric inhibitor, were ineffective. Our computational structural analysis strategy would be beneficial for future drug development targeting the EGFR minor mutations.

Resistance to ALK inhibitors such as lorlatinib often arise due to on-target mutations. Here, the authors show the multi-kinase inhibitor gilteritinib is effective against different mutations that arise during lorlatinib in ALK fusion positive lung cancer to cause resistance.

Drug abuse is becoming increasingly dangerous nowadays. Morphine (MOP), methamphetamine (MET) and ketamine (KET) are the most commonly abused drugs. The abuse of these drugs without supervision can cause serious harm to the human body and also endanger public safety. Developing a rapid and accurate method to screen drug suspects and thus control these drugs is essential to public safety. This paper presents a method for the simultaneous quantitative detection of these three drugs in hair by a europium nanoparticles-based fluorescence immunochromatographic assay (EuNPs−FIA). In our study, the test area of the nitrocellulose membrane was composed of three equally spaced detection lines and a quality control line. The test strip realized the quantitative analysis of the samples by detecting the fluorescence brightness of the europium nanoparticles captured on the test line within 15 min. For the triple test strip, the limits of detection of MOP, KET and MET were 0.219, 0.079 and 0.329 ng/mL, respectively. At the same time, it also showed strong specificity. The strip was stable and could be stored at room temperature for up to one year, and the average recovery rate was 85.98–115.92%. In addition, the EuNPs−FIA was validated by high-performance liquid chromatography (HPLC) analysis, and a satisfactory consistency was obtained. Compared to the current immunochromatographic methods used for detecting abused drugs in hair, this method not only increased the number of detection targets, but also ensured sensitivity, improving detection efficiency to a certain extent. The approach can also be used as an alternative to chromatography. It provides a rapid and accurate screening method for the detection of abused drugs in hair and has great application prospects in regard to public safety.

The compression molding performance of a substrate block has a significant effect on the quality and stability of mechanical transplanting. The physical experiment and DEM simulation were combined to evaluate the compression molding behavior of substrate block in this study. A calibration procedure of DEM parameters of peat particles was proposed at first. Then, the above parameters were brought into the contact model of the compression system–particles, and the effect of the loading speed on the compression behavior of the peat substrate block was investigated. The compressive force–displacement curves of the simulated and measured tests were all contained in the initial linear stage and non-linear stiffing stage. The particle number of central sections was higher than side section, and the variable coefficient was greater at higher loading speed. The substrate blocks all expanded after demolding. The higher the loading speed, the greater the expansion in the height’s direction, and the easier it was for cracks to be generated near the bottom. This study will provide a reference for the design of substrate block forming machines.

Conventional enzyme-based continuous glucose sensors in interstitial fluid usually rely on dissolved oxygen as the electron-transfer mediator to bring electrons from oxidase to electrode while generating hydrogen peroxide. This may lead to several problems. First, the sensor may provide biased detection results owing to fluctuation of oxygen in interstitial fluid. Second, the polymer coatings that regulate the glucose/oxygen ratio can affect the dynamic response of the sensor. Third, the glucose oxidation reaction continuously produces corrosive hydrogen peroxide, which may compromise the long-term stability of the sensor. Here, we introduce an oxygen-independent nonenzymatic glucose sensor based on water splitting-assisted electrocatalysis for continuous glucose monitoring. For the water splitting reaction (i.e., hydrogen evolution reaction), a negative pretreatment potential is applied to produce a localized alkaline condition at the surface of the working electrode for subsequent nonenzymatic electrocatalytic oxidation of glucose. The reaction process does not require the participation of oxygen; therefore, the problems caused by oxygen can be avoided. The nonenzymatic sensor exhibits acceptable sensitivity, reliability, and biocompatibility for continuous glucose monitoring in hypoxic environments, as shown by the in vitro and in vivo measurements. Therefore, we believe that it is a promising technique for continuous glucose monitoring, especially for clinically hypoxic patients.

Oncolytic viruses have the capacity to selectively kill infected tumor cells and trigger protective immunity. As such, oncolytic virotherapy has become a promising immunotherapy strategy against cancer. A variety of viruses from different families have been proven to have oncolytic potential. Senecavirus A (SVA) was the first picornavirus to be tested in humans for its oncolytic potential and was shown to penetrate solid tumors through the vascular system. SVA displays several properties that make it a suitable model, such as its inability to integrate into human genome DNA and the absence of any viral-encoded oncogenes. In addition, genetic engineering of SVA based on the manipulation of infectious clones facilitates the development of recombinant viruses with improved therapeutic indexes to satisfy the criteria of safety and efficacy regulations. This review summarizes the current knowledge and strategies of genetic engineering for SVA, and addresses the current challenges and future directions of SVA as an oncolytic agent.

Legionella, a waterborne pathogen, is the main cause of Legionnaires’ disease. Therefore, timely and accurate detection and differentiation of Legionella pneumophila and non-Legionella pneumophila species is crucial. In this study, we develop an easy and rapid recombinase polymerase amplification assay combined with EuNPs-based lateral flow immunochromatography (EuNPs-LFIC-RPA) to specifically distinguish Legionella pneumophila and non-Legionella pneumophila. We designed primers based on the mip gene of Legionella pneumophila and the 5S rRNA gene of non-Legionella pneumophila. The recombinase polymerase amplification reaction could go to completion in 10 min at 37°C, and the amplification products could be detected within 5 min with EuNPs-LFIC strips. Using a florescent test strip reader, the quantitative results were achieved by reading the colored signal intensities on the strips. The sensitivity was 1.6 × 101 CFU/ml, and a linear standard linear curve plotted from the test strip reader had a correlation coefficient for the determination of Legionella pneumophila (R2 = 0.9516). Completed concordance for the presence or absence of Legionella pneumophila by EuNPs-LFIC-RPA and qPCR was 97.32% (κ = 0.79, 95% CI), according to an analysis of practical water samples (n = 112). In short, this work shows the feasibility of EuNPs-LFIC-RPA for efficient and rapid monitoring of Legionella pneumophila and non-Legionella pneumophila in water samples.

Abstract Background The gut microbiota participates in the metabolism of substances and energy, promotes the development and maturation of the immune system, forms the mucosal barrier, and protects the host from pathogen attacks. Although the pathogenesis of cholesterol gallstones is still not clear, studies have suggested that gut microbiota dysbiosis plays an important role in their formation. Methods Microbial DNA from faeces of normal control patients and those of patients with calculi was subjected to 16S rRNA gene sequencing to detect gene expression changes in intestinal microbes. ELISA kits were used to measure free bile acids, secondary bile acids and coprostanol according to the manufacturer’s instructions. The relationship between flora and their metabolites was then analysed. Results In the gallstone group, the diversity of intestinal bacteria and the abundances of certain phylogroups were significantly decreased (p

The calcium-activated chloride channel, also known as TMEM16A, shows both calcium and membrane potential dependent activation. The channel is expressed broadly and contributes to a variety of physiological processes, and it is expected to be a target for the treatment of diseases such as hypertension, pain, cystic fibrosis and lung cancer. A thorough understanding of the structural characteristics of TMEM16A is important to reveal its physiological and pathological roles. Recent studies have released several Cryo-EM structures of the channel, revealed the structural basis and mechanism of the gating of the channel. This review focused on the understandings of the structural basis and molecular mechanism of the gating and permeation of TMEM16A channel, which will provide important basis for the development of drugs targeting TMEM16A.

The operational rotational speeds of hydroturbines change arbitrarily within a small range, and the friction power consumption caused by the asymmetric curl represents a technical difficulty in magnetofluid sealing. In this study, the pressure-withstanding value and equations for the asymmetric curl of a magnetofluid sealing device under different rotational speeds were deduced. By considering the magnetofluid sealing device characteristics with Halbach magnetic arrays, temperature fields under a static field and low rotational speed were calculated for determining the Halbach magnetofluid sealing device with the best sealing performance. Comparisons and analyses were performed with the friction power consumption and sealing pressure-withstanding value of the selected structure under high (3000 r/min), medium (1500 r/min), and low (300 r/min) rotational speeds and alternating work conditions of ±3, ±6, and ±9. The results indicated that changes in magnetic moment caused by changes in the external magnetic field are the primary cause of friction power consumption. Heat generation occurs concurrently with the friction power consumption. Consequently, the pressure-withstanding value of the magnetofluid sealing is reduced; the friction power consumption of the magnetofluid is directly proportional to the magnetic field strength, rotational speed, and alternating amplitude. Unstable states and asymmetry of the external magnetic field lead to nonlinear increments in the friction power consumption of the magnetofluid. A stable and symmetrical magnetic effect, with a smaller rotational speed and alternating amplitude leads to lower friction power consumption, resulting in a more ideal sealing effect.

Regular inspection of pavement conditions is important to guarantee the safety of transportation. However, current approaches are time-consuming and subjective, which requires the technician to annotate each training image exactly pixel by pixel. To ease the workload of the inspector and lower the cost of acquiring the high-quality training dataset, a semi-supervised method for the pavement crack detection is proposed. Firstly, unlabeled pavement images can be used for the model training in our proposed algorithm, our model can generate a supervisory signal for unlabeled pavement images, which makes up for the deficiency of image annotation. Secondly, an adversarial learning method and a full convolution discriminator are adopted, which can learn to distinguish the ground truth from segmentation predictions. To improve the accuracy of pavement crack detection, the adversarial loss is coupled with the cross-entropy loss in discriminator. Thus, the quality of the training model is no longer dependent on the quantity of the labeled dataset and the accuracy of the labeled. Compared with existing methods that can only employ labeled images, our method utilizes unlabeled images to improve the pavement crack detection accuracy. Moreover, our model is validated on the CFD dataset and AigleRN dataset, the experimental results show that the proposed algorithm is effective. Compared with existing methods, not only can our method detect different types of cracks, but also be particularly effective when only a few labeled are available: when using 118 crack images with a resolution of 480 × 320, using only 50% of the labeled data, the detection accuracy of our model can reach 95.91%.

Ethylene regulates adaptive root growth during waterlogging in rice. Here, the authors identify MHZ1 (aka OsHK1), a histidine kinase that positively regulates the root ethylene response by interacting with the ethylene receptor ERS2 and promoting phosphorylation of the response regulator, OsRR21.

Both the human body and its motion are three-dimensional information, while the traditional feature description method of two-person interaction based on RGB video has a low degree of discrimination due to the lack of depth information. According to the respective advantages and complementary characteristics of RGB video and depth video, a retrieval algorithm based on multisource motion feature fusion is proposed. Firstly, the algorithm uses the combination of spatiotemporal interest points and word bag model to represent the features of RGB video. Then, the directional gradient histogram is used to represent the feature of the depth video frame. The statistical features of key frames are introduced to represent the histogram features of depth video. Finally, the multifeature image fusion algorithm is used to fuse the two video features. The experimental results show that multisource feature fusion can greatly improve the retrieval accuracy of motion features.

The growth of field crops needs appropriate soil nutrients. As a basic fertilizer, liquid manure provides biological nutrients for crop growth and increases the content of organic matter in crops. However, improper spraying not only reduces soil fertility but also destroys soil structure. Therefore, the precise control of the amount of liquid manure is of great significance for agricultural production and weight loss. In this study, we first built the model of spraying control, then optimized the BP neural network algorithm through a genetic algorithm. The stability and efficiency of the optimized controller were compared with PID, fuzzy PID and BPNN-PID control. The simulation results show that the optimized algorithm has the shortest response time and lowest relative error. Finally, platform experiments were designed to verify the four control algorithms at four different vehicle speeds. The results show that, compared with other control algorithms, the control algorithm described here has good stability, short response time, small overshoot, and can achieve an accurate fertilizer application effect, providing an optimization scheme for research on the precise application of liquid manure.

Ferroptosis is a new form of iron-dependent cell death and plays an important role during the occurrence and development of various tumors. Increasingly, evidence shows a convincing interaction between ferroptosis and tumor immunity, which affects cancer patients’ prognoses. These two processes cooperatively regulate different developmental stages of tumors and could be considered important tumor therapeutic targets. However, reliable prognostic markers screened based on the combination of ferroptosis and tumor immune status have not been well characterized. Here, we chose the ssGSEA and ESTIMATE algorithms to evaluate the ferroptosis and immune status of a TCGA breast invasive ductal carcinoma (IDC) cohort, which revealed their correlation characteristics as well as patients’ prognoses. The WGCNA algorithm was used to identify genes related to both ferroptosis and immunity. Univariate COX, LASSO regression, and multivariate Cox regression models were used to screen prognostic-related genes and construct prognostic risk models. Based on the ferroptosis and immune scores, the cohort was divided into three groups: a high-ferroptosis/low-immune group, a low-ferroptosis/high-immune group, and a mixed group. These three groups exhibited distinctive survival characteristics, as well as unique clinical phenotypes, immune characteristics, and activated signaling pathways. Among them, low-ferroptosis and high-immune statuses were favorable factors for the survival rates of patients. A total of 34 differentially expressed genes related to ferroptosis-immunity were identified among the three groups. After univariate, Lasso regression, and multivariate stepwise screening, two key prognostic genes (GNAI2, PSME1) were identified. Meanwhile, a risk prognosis model was constructed, which can predict the overall survival rate in the validation set. Lastly, we verified the importance of model genes in three independent GEO cohorts. In short, we constructed a prognostic model that assists in patient risk stratification based on ferroptosis-immune-related genes in IDC. This model helps assess patients’ prognoses and guide individualized treatment, which also further eelucidatesthe molecular mechanisms of IDC.

To study the influence of the blade entropy production range on the efficiency of a tubular turbine under coassociated conditions, the renormalization group K–ε turbulence model was used to simulate the full flow passage of the tubular turbine based on the Navier–Stokes equation, and the blade interface was analyzed using the eddy analysis method and entropy production theory. The results reveal that there is a strong correlation between the size of the high-entropy production area and the level of association. If the level of association is high, the size of the high-entropy production is small, and the turbine efficiency is high. Furthermore, if the level of association is low, the size of the high-entropy production area is large, and the turbine efficiency is low. Under small opening and small flow conditions, the blade entropy generation is due to the sharp change in the velocity gradient caused by the vortex on the blade. Under large opening and large flow conditions, the blade entropy production is mainly due to the friction loss caused by the impact of high-speed water flow.

A fluorescent immunoassay based on europium nanoparticles (EuNPs-FIA) was developed for the simultaneous detection of antibiotic residues, solving the problems of single target detection and low sensitivity of traditional immunoassay methods. In the EuNPs-FIA, EuNPs were used as indictive probes by binding to anti-tetracyclines monoclonal antibodies (anti-TCs mAb), anti-sulphonamides monoclonal antibodies (anti-SAs mAb) and anti-fluoroquinolones monoclonal antibodies (anti-FQs mAb), respectively. Different artificial antigens were assigned to different regions of the nitrocellulose membrane as capture reagents. The EuNPs-FIA allowed for the simultaneous detection of three classes of antibiotics (tetracyclines, fluoroquinolones and sulphonamides) within 15 min. It enabled both the qualitative determination with the naked eye under UV light and the quantitative detection of target antibiotics by scanning the fluorescence intensity of the detection probes on the corresponding detection lines. For qualitative analysis, the cut-off values for tetracyclines (TCs), fluoroquinolones (FQs) and sulphonamides (SAs) were 3.2 ng/ml, 2.4 ng/ml and 4.0 ng/ml, respectively, which were much lower than the maximum residue limit in food. For quantitative analysis, these ranged from 0.06 to 6.85 ng/ml for TCs, 0.03–5.14 ng/ml for FQs, and 0.04–4.40 ng/ml for SAs. The linear correlation coefficients were higher than 0.97. The mean spiked recoveries ranged from 92.1 to 106.2% with relative standard deviations less than 8.75%. Among them, the three monoclonal antibodies could recognize four types of TCs, seven types of FQs and 13 types of SAs, respectively, and the detection range could cover 24 antibiotic residues with different structural formulations. The results of the detection of antibiotic residues in real samples using this method were highly correlated with those of high performance liquid chromatography (R2 > 0.98). The accuracy and precision of the EuNPs-FIA also met the requirements for quantitative analysis. These results suggested that this multiplex immunoassay method was a promising method for rapid screening of three families of antibiotic residues.

Colon adenocarcinoma (COAD) is one of the diseases with the highest morbidity and mortality in the world. At present, immunotherapy has become a valuable method for the treatment of COAD. Tumor mutational burden (TMB) is considered to be the most common biomarker for predicting immunotherapy. According to reports, the mutation rate of COAD ranks third. However, whether these gene mutations are related to TMB and immune response is still unknown. Here, COAD somatic mutation data were downloaded from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Bioinformatics methods were used to study the relationships among gene mutations, COAD survival prognosis, and tumor immune response. A total of 22 of the top 40 mutations in TCGA and ICGC databases were the same. Among them, the USH2A mutation was associated with high TMB and poor clinical prognosis. According to Gene Set Enrichment Analysis (GSEA) and the CIBERSORT algorithm, we determined that the USH2A mutation upregulates signaling pathways involved in the immune system and the antitumor immune response. In cases with a USH2A mutation, the immune score and MSI score of TCGA samples increased, the expression of immune checkpoint genes decreased significantly, and the TIDE score decreased significantly. Dependent on the presence or absence of a USH2A mutation, TCGA COAD samples were analyzed for differentially expressed genes, 522 of which were identified. Using a univariate Cox analysis and LASSO COX analysis of these differential genes, a prediction model was established, which established significant differences in the infiltration of immune cells, immune checkpoint gene expression, immune score, MSI score, TMB, and TIDE in patients in high- and low-risk groups. In conclusion, mutation of USH2A is frequent in COAD and is related to an increase in TMB and the antitumor immunity. The differential genes screened by USH2A mutation allowed the construction of a risk model for predicting the survival and prognosis of cancer patients, in addition to providing new ideas for COAD immunotherapy.

Safe and effective vaccines for Corona Virus Disease 2019 (COVID-19) can prevent the virus from infecting human populations and treat patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we discuss the inhibitory abilities of primary and booster vaccine-induced antibodies inhibitory ability toward the SARS-CoV-2 wild-type strain, as well as B.1.1.7, B.1.351, P.1, B.1.617.2, and B.1.1.529. We confirmed these antibodies had the strongest inhibitory effects on the wild-type strain and cross-inhibition activities against other mutant strains after two inactivated vaccine doses. However, the B.1.351, B.1.617.2 and B.1.1.529 mutants exhibit antibody resistance in the vaccine serum. Antibodies induced by homologous inactivated vaccines (n = 92) presented more effective inhibition against tested SARS-CoV-2 strains (p < 0.0001), especially B.1.351, B.1.617.2, and B.1.1.529 mutant strains, which had strong immune escape characteristics. In addition, a heterologous booster vaccination (n = 50) of a protein subunit vaccine ZifiVax (ZF2001) significantly restored humoral immune responses and even showed an increasing response against wild-type, B.1.351, B.1.617.2, and B.1.1.529 than homologous inactivated vaccines. Our analysis of the humoral immune response elicited by the different vaccine regimens, including inhibiting antibodies, indicated that a booster, whether homologous or heterologous, could be essential for achieving greater efficacy against SARS-CoV-2.

Conductive and stretchable fibers are the cornerstone of intelligent textiles and imperceptible electronics. Among existing fiber conductors, gallium-based liquid metals (LMs) featuring high conductivity, fluidity, and self-healing are excellent candidates for highly stretchable fibers with sensing, actuation, power generation, and interconnection functionalities. However, current LM fibers fabricated by direct injection or surface coating have a limitation in shape programmability. This hinders their applications in functional fibers with tunable electromechanical response and miniaturization. Here, we reported a simple and efficient method to create shape-programmable LM fibers using the phase transition of gallium. Gallium metal wires in the solid state can be easily shaped into a 3D helical structure, and the structure can be preserved after coating the wire with polyurethane and liquifying the metal. The 3D helical LM fiber offered enhanced stretchability with a high breaking strain of 1273% and showed invariable conductance over 283% strain. Moreover, we can reduce the fiber diameter by stretching the fiber during the solidification of polyurethane. We also demonstrated applications of the programmed fibers in self-powered strain sensing, heart rate monitoring, airflow, and humidity sensing. This work provided simple and facile ways toward functional LM fibers, which may facilitate the broad applications of LM fibers in e-skins, wearable computation, soft robots, and smart fabrics.

As the basic link of autonomous navigation in agriculture, crop row detection is vital to achieve accurate detection of crop rows for autonomous navigation. Machine vision algorithms are easily affected by factors such as changes in field lighting and weather conditions, and the majority of machine vision algorithms detect early periods of crops, but it is challenging to detect crop rows under high sheltering pressure in the middle and late periods. In this paper, a crop row detection algorithm based on LiDAR is proposed that is aimed at the middle and late crop periods, which has a good effect compared with the conventional machine vision algorithm. The algorithm proposed the following three steps: point cloud preprocessing, feature point extraction, and crop row centerline detection. Firstly, dividing the horizontal strips equally, the improved K-means algorithm and the prior information of the previous horizontal strip are utilized to obtain the candidate points of the current horizontal strip, then the candidate points information is used to filter and extract the feature points in accordance with the corresponding threshold, and finally, the least squares method is used to fit the crop row centerlines. The experimental results show that the algorithm can detect the centerlines of crop rows in the middle and late periods of maize under the high sheltering environment. In the middle period, the average correct extraction rate of maize row centerlines was 95.1%, and the average processing time was 0.181 s; in the late period, the average correct extraction rate of maize row centerlines was 87.3%, and the average processing time was 0.195 s. At the same time, it also demonstrates accuracy and superiority of the algorithm over the machine vision algorithm, which can provide a solid foundation for autonomous navigation in agriculture.

To intercept a maneuvering target in a two-dimensional plane, the inverse optimal guidance law based on zero effort miss (ZEM) and disturbance observer (DO) is studied in this paper. Firstly, the relative kinematics equation is simplified to obtain the missile-target ZEM and its dynamics. In order to enhance the robustness of the inverse optimal guidance law, the integral of the ZEM is introduced as a new state to form an augmented system with the original system based on the idea of proportional integral (PI) control. Then, the target maneuver acceleration is assumed as the unknown external disturbance of the guidance augmented system, which is estimated by the DO. Based on the estimated value of DO and the backstepping method, the inverse optimal guidance law is designed to reduce the adverse effect of the disturbance on the guidance system. Finally, simulations are designed to verify the effectiveness of the inverse optimal guidance method based on DO.

The plant-specific SHI-related sequence (SRS) family of transcription factors plays a vital role in growth regulation, plant development, phytohormone biosynthesis, and stress response. However, the genome-wide identification and role in the abiotic stress-related functions of the SRS gene family were not reported in white sweet clover (Melilotus albus). In this study, nine M. albus SRS genes (named MaSRS01-MaSRS09) were identified via a genome-wide search method. All nine genes were located on six out of eight chromosomes in the genome of M. albus and duplication analysis indicated eight segmentally duplicated genes in the MaSRS family. These MaSRS genes were classified into six groups based on their phylogenetic relationships. The gene structure and motif composition results indicated that MaSRS members in the same group contained analogous intron/exon and motif organizations. Further, promoter region analysis of MaSRS genes uncovered various growth, development, and stress-responsive cis-acting elements. Protein interaction networks showed that each gene has both functions of interacting with other genes and members within the family. Moreover, real-time quantitative PCR was also performed to verify the expression patterns of nine MaSRS genes in the leaves of M. albus. The results showed that nine MaSRSs were up- and down-regulated at different time points after various stress treatments, such as salinity, low-temperature, salicylic acid (SA), and methyl jasmonate (MeJA). This is the first systematic study of the M. albus SRS gene family, and it can serve as a strong foundation for further elucidation of the stress response and physiological improvement of the growth functions in M. albus.

Summary: Non-degradative ubiquitin chains and phosphorylation events govern signaling responses by innate immune receptors. The deubiquitinase CYLD in complex with SPATA2 is recruited to receptor signaling complexes by the ubiquitin ligase LUBAC and regulates Met1- and Lys63-linked polyubiquitin and receptor signaling outcomes. Here, we investigate the molecular determinants of CYLD activity. We reveal that two CAP-Gly domains in CYLD are ubiquitin-binding domains and demonstrate a requirement of CAP-Gly3 for CYLD activity and regulation of immune receptor signaling. Moreover, we identify a phosphorylation switch outside of the catalytic USP domain, which activates CYLD toward Lys63-linked polyubiquitin. The phosphorylated residue Ser568 is a novel tumor necrosis factor (TNF)-regulated phosphorylation site in CYLD and works in concert with Ser418 to enable CYLD-mediated deubiquitination and immune receptor signaling. We propose that phosphorylated CYLD, together with SPATA2 and LUBAC, functions as a ubiquitin-editing complex that balances Lys63- and Met1-linked polyubiquitin at receptor signaling complexes to promote LUBAC signaling.

There is increasing appreciation for the roles of the gut-liver axis in liver and gall diseases. Specific gut microbes are associated with susceptibility to gallstone diseases, while the relationship between intestinal flora and liver metabolism in the formation of gallstones remains unclear. In this study, an experimental group of model mice was given a lithogenic diet, and a control group was given a normal diet. Both groups were fed for 8 weeks. Integrating 16S rRNA gene sequencing and non-targeted metabolomics to explore the impact of the lithogenic diet on intestinal flora and liver metabolism, Spearman correlation analysis reveals the network of relationships between the intestine and liver. Our findings showed that the gut microbiome and liver metabolome compositions of the test group were significantly changed compared with those of the normal group. Through our research, biomarkers of gallstones were identified at the phylum (5), class (5), order (5), family (7), and genus levels. We predicted the function of the differential flora. We analyzed the liver metabolism of mice with gallstones paired with their flora, and the results showed that there were 138 different metabolites between the two groups. The metabolic pathways enriched by these differential metabolites are highly consistent with the functions of the disordered flora. We focused on an analysis of the relationship between deoxycholic acid, asymmetric dimethylarginine, glucosamine, tauroursodeoxycholic acid, and the disordered flora. This provides a basis for the establishment of the intestine-liver axis in gallstone disease. This research provides a theoretical basis for the research and development of probiotics and prebiotics.

When considering the transition probability matrix of ordinal patterns, transition permutation entropy (TPE) can effectively extract fault features by quantifying the irregularity and complexity of signals. However, TPE can only characterize the complexity of the vibration signals at a single scale. Therefore, a multiscale transition permutation entropy (MTPE) technique has been proposed. However, the original multiscale method still has some inherent defects in the coarse-grained process, such as considerably shortening the length of time series at large scale, which leads to a low entropy evaluation accuracy. In order to solve these problems, a composite multiscale transition permutation entropy (CMTPE) method was proposed in order to improve the incomplete coarse-grained analysis of MTPE by avoiding the loss of some key information in the original fault signals, and to improve the performance of feature extraction, robustness to noise, and accuracy of entropy estimation. A fault diagnosis strategy based on CMTPE and an extreme learning machine (ELM) was proposed. Both simulation and experimental signals verified the advantages of the proposed CMTPE method. The results show that, compared with other comparison strategies, this strategy has better robustness, and can carry out feature recognition and bearing fault diagnosis more accurately and with improved stability.

Aiming to solve the problems of easy clogging and high energy consumption of multi-way fertilization devices for liquid manure, a crushing and impurity removal device for liquid manure was designed by combining the physical characteristics of liquid manure and impurities, and building the corresponding test bench. The proposed device could crush flexible impurities such as straw and filoplume and intercept hard impurities with high density. The main structural parameters of the device were determined according to the survey analysis and the theoretical design. The influences of cutter head shape, cutter edge angle, cutter shaft speed, and cutting clearance on the disqualification rate and energy consumption of straw crushing were obtained by a single-factor experiment. Furthermore, the Box–Behnken central composite design method of the response surface was employed to investigate the effects of the cutter shaft speed, cutting clearance, and cutter edge angle on the disqualification rate and energy consumption of straw crushing. In addition, the working parameters of the device were optimized by employing the response surface method. On this basis, the mathematical relationship model among the disqualification rate, energy consumption, and all influencing factors was established. The results show that the optimal combination of working parameters includes a cutter shaft speed of 312 r/min, a cutting clearance of 1.4 mm, and a cutter edge angle of 45°. From the prediction model, the predicted failure rate was 4.15%, and the predicted energy consumption was 47.53 J. The verification experiment was then performed under the optimal combination of working parameters. The obtained disqualification rate was 4.08% and the energy consumption was 47.56 J, which met the design and work requirements.

Tumor cell-microenvironment interactions generate heterogeneity and promote progression. Here, Ma et al. show that the E3 ligase SIAH2 degrades NRF1 in response to hypoxia to enhance pro-tumor metabolic and environmental effects, whereas NRF1 stabilization sensitizes tumor cells to apoptosis.

Background: Alectinib has shown a greater efficacy to ALK-rearranged non-small-cell lung cancers in first-line setting; however, most patients relapse due to acquired resistance, such as secondary mutations in ALK including I1171N and G1202R. Although ceritinib or lorlatinib was shown to be effective to these resistant mutants, further resistance often emerges due to ALK-compound mutations in relapse patients following the use of ceritinib or lorlatinib. However, the drug for overcoming resistance has not been established yet. Methods: We established lorlatinib-resistant cells harboring ALK-I1171N or -G1202R compound mutations by performing ENU mutagenesis screening or using an in vivo mouse model. We performed drug screening to overcome the lorlatinib-resistant ALK-compound mutations. To evaluate these resistances in silico, we developed a modified computational molecular dynamic simulation (MP-CAFEE). Findings: We identified 14 lorlatinib-resistant ALK-compound mutants, including several mutants that were recently discovered in lorlatinib-resistant patients. Some of these compound mutants were found to be sensitive to early generation ALK-TKIs and several BCR-ABL inhibitors. Using our original computational simulation, we succeeded in demonstrating a clear linear correlation between binding free energy and in vitro experimental IC50 value of several ALK-TKIs to single- or compound-mutated EML4-ALK expressing Ba/F3 cells and in recapitulating the tendency of the binding affinity reduction by double mutations found in this study. Computational simulation revealed that ALK-L1256F single mutant conferred resistance to lorlatinib but increased the sensitivity to alectinib. Interpretation: We discovered lorlatinib-resistant multiple ALK-compound mutations and an L1256F single mutation as well as the potential therapeutic strategies for these ALK mutations. Our original computational simulation to calculate the binding affinity may be applicable for predicting resistant mutations and for overcoming drug resistance in silico. Fund: This work was mainly supported by MEXT/JSPS KAKENHI Grants and AMED Grants. Keywords: ALK-rearranged lung cancer, Resistant mutation, Computational simulation, MP-CAFEE, Compound mutation, Quantum chemistry

This paper proposes a new systematic method for assessing system material wear to build a system degradation model and estimate residual technical life. Selected metal wear debris from lubricating oil, which contains information about the lubricant conditions and system conditions, is analyzed. We focus on the iron (Fe) and copper (Cu) debris, which we (and other researchers) consider to be valuable, of the contact degradation and wear failure systems. By monitoring the changes in debris content in the lubricating oil, we build a system degradation model and further predict the moment when the system no longer fulfills its functions; the residual life might then be set as the time reference to implement preventive maintenance. The degradation model is founded on the specific characteristics of a stochastic diffusion process with bivariable, using the bivariate Wiener process with a time scale transformation. An inference function to describe the dependency among the selected wear debris was also applied because the oil field data exhibit some uncertainty and correlation. Based on the degradation modeling results, the system reliability curve and the failure probability density curve predict the MTBF value and the expected mean residual life can be obtained, and provide the foundations for the condition-based maintenance of the system. However, the potential applications of the results are much broader. For instance, the results can be used as inputs to mission plan optimization and further reduce system maintenance costs.

The regular replacement of lubricating oil plays a key role in improving machine reliability and reducing unexpected failures of an oil lubricated system. This paper proposes a condition-based maintenance problem with selected oil field data to determine the optimal time of the lubricating oil replacement. The selected oil field data contain health information about the lubricating oil, so the degradation state of the oil can be predicted and the future health condition can be evaluated. The proposed lubricating oil replacement problem is modeled with the evaluated oil health condition in a Markov decision process framework and then, a method for constructing a health index for the lubricating oil is proposed based on information theory to fuse the multiple oil field data and build a degradation progression prediction model. Finally, the proposed method for condition-based lubricating oil replacement is illustrated in a practical case study. The possible applications of an optimal policy for lubricating oil replacement are much wider. For instance, the method can be used as an input to optimize an operational plan and further reduce the maintenance costs.

The clutch temperature rise characteristics in successive shifting conditions are crucial to its thermal stability and thermal safety. In the present paper, a comprehensive numerical model is proposed to investigate the temperature change of separator discs during successive shifting with the consideration of convection heat transfer in disengaged friction pair gaps, which is validated by repeated shifting experiments on the SAE#2 test bench. Since the second separator disc near the piston has the widest disengaged gaps and double-sided heat input, its temperature rise and temperature drop are the highest. The temperature rise gradually equals the temperature drop with the increasing working cycle, then the maximum clutch temperature no longer increases. The longer the shifting interval, the better the heat dissipation is, thus the lower the accumulated temperature rise. Moreover, the increasing lubrication oil temperature reduces the convection heat transfer and increases the temperature rise in an engaging process, but the accumulated temperature rise does not increase due to the widened friction pair gaps. This paper can obtain the temperature rise characteristics of a wet multi-disc clutch concerning its disengaged gaps during successive shifting, which is a promising candidate for investigating its overall performance.

In recent years, foodborne disease outbreaks have caused huge losses to the economy and have had severe impacts on public health. The accuracy and variety of detection techniques is crucial to controlling the outbreak and spread of foodborne diseases. The need for instruments increases the difficulty of field detection, while manually-handled samples are subject to user error and subjective interpretation. Here, we use a mini automatic nucleic acid extractor combined with recombinant polymerase amplification (RPA) and lateral flow immunoassay (LFIA) for simultaneous quantitative detection of five major foodborne pathogens. The pre-treatment device using the magnetic bead method allows for nucleic acid extraction of the reagent tank without manual operation, which is highly efficient and stable for preventing aerosol contamination. The nuc gene of Staphylococcus aureus, the toxR gene of Vibrio parahaemolyticus, the rfbE gene of Escherichia coli O157:H7, the hlyA gene of Listeria monocytogenes, and the fimY gene of Salmonella enterica were used as target fragments. The labeled antibody concentration is optimized on the LFIA to find the equilibrium point for the binding capacity of the five chemical markers and to efficiently and accurately visualize the bands. The RPA assay shows an optimal performance at 37 °C for 15 min. The optimized RPA-LFIA detection limit can reach 101 CFU/mL. There was no cross-reactivity among forty-eight strains. Furthermore, the average recoveries in spiked food samples were 90.5–104.5%. In summary, the RPA-LFIA established in this study can detect five pathogenic bacteria simultaneously with little dependence on laboratory equipment, and it has promising prospects for screening in low-resource areas.

Background: The pathogenesis of chronic pancreatitis is still unclear. Trypsinogen activation is an active factor in acute pancreatitis that has not been studied in the occurrence of chronic pancreatitis. Methods: Immunofluorescence was used to detect the location and expression of trypsinogen in chronic pancreatitis and normal tissues. Microarray and single-cell RNA-seq (scRNA-seq) were used to screen core genes and pathways in pancreatic stellate cells (PSCs). Western blotting and immunofluorescence were used to verify trypsinogen expression in PSCs after silencing Rabep1. Immunofluorescence and flow cytometry were used to validate trypsinogen activation and PSC activation after intervening in the endocytosis pathway. Results: Endocytosed trypsinogen was found in PSCs in CP clinical samples. Bioinformatic analysis showed that Rabep1 is a core gene that regulates trypsinogen endocytosis through the endocytosis pathway, verified by Western blot and immunofluorescence. Immunofluorescence and flow cytometry analyses confirmed the activation of trypsinogen and PSCs through the endocytosis pathway in PSCs. Conclusion: This study discovered a new mechanism by which trypsinogen affects the activation of PSCs and the occurrence and development of CP. Through communication between pancreatic acinar cells and PSCs, trypsinogen can be endocytosed by PSCs and activated by the Rabep1 gene.

Friction and wear performance is one of the key mechanical properties of accident tolerant fuel cladding coatings. In this study, reciprocating sliding wear tests had performed on two types of CrAl and CrAlN coatings with two different Al content ratios and Zr-4. The coefficient of friction, wear depth, and abrasion loss were measured and compared. The results indicated that the CrAl-based coatings improve the wear behavior significantly and nitrogen has an obvious improvement on the wear resistance of the coating. The friction and wear performance was also studied in a water environment. The results show that the presence of water degrade the wear performance of Zr-4 and CrAl coatings but ameliorates the friction and wear performance of CrAlN coatings. The feasibility of depositing ATF coating on conventional Zr-4 substrates to mitigate the influence of grid-to-rod fretting was demonstrated.

Phage display technology in combination with next-generation sequencing (NGS) currently is a state-of-the-art method for the enrichment and isolation of monoclonal antibodies from diverse libraries. However, the current NGS methods employed for sequencing phage display libraries are limited by the short contiguous read lengths associated with second-generation sequencing platforms. Consequently, the identification of antibody sequences has conventionally been restricted to individual antibody domains or to the analysis of single domain binding moieties such as camelid VHH or cartilaginous fish IgNAR antibodies. In this study, we report the application of third-generation sequencing to address this limitation. We used single molecule real time (SMRT) sequencing coupled with hairpin adaptor loop ligation to facilitate the accurate interrogation of full-length single-chain Fv (scFv) libraries. Our method facilitated the rapid isolation and testing of scFv antibodies enriched from phage display libraries within days following panning. Two libraries against CD160 and CD123 were panned and monitored by NGS. Analysis of NGS antibody data sets led to the isolation of several functional scFv antibodies that were not identified by conventional panning and screening strategies. Our approach, which combines phage display selection of immune libraries with the full-length interrogation of scFv fragments, is an easy method to discover functional antibodies, with a range of affinities and biophysical characteristics.

This paper investigates the effects of disc deformation on the tilting-induced vibration of a splined spinning disc with axial-fixed boundaries.The purpose is to provide an intuitive interpretation of the vibration variance of the wet clutch system with different deformed discs. First, tilting models of flat and deformed discs are derived by introducing distinctive shape functions. Additionally, the inner spline interface is chosen as the friction boundary. Then, an impact model between friction pairs and the rigid boundary is established by adopting Hertz’s contact theory. Finally, the dynamic equations are solved via numerical methods, and the responses are analyzed in both time and frequency domains. The deformation can increase the nonlinearity of the dynamic response of the spinning disc. Moreover, the effects of increasing the impulse force and reducing the boundary distance are quite similar; they both increase the motion intensity.

To detect two types of β2-agonist residues at the same time, we coupled two haptens of clenbuterol (CLE) and ractopamine (RAC) to the same carrier protein through diazotization to prepare dimeric artificial antigen, and a fluorescent lateral flow immunoassay method based on europium nanoparticles (EuNP-FLFIA) was established by combining polyclonal antibodies with europium nanoparticles to form probes. Under optimized conditions, the EuNP-FLFIA could simultaneously detect eight aniline-type and one phenol-type β2-agonists, and the limits of detection (LOD) were 0.11–0.19 ng/mL and 0.12 ng/mL, respectively. The recovery rate of this method was 84.00–114.00%. This method was verified by liquid chromatography–tandem mass spectrometry (LC-MS/MS), and the test results were consistent (R2 > 0.98). Therefore, the method established in this study could be used as a high-throughput screening for the efficient and sensitive detection of β2-agonists in food.

An ultrahigh-sensitivity lateral flow immunochromatography (LFIC) assay based on up-converting nanoparticles (UCNPs) was developed to carry out a multi-residue detection of tetracycline in milk. The sensitivity of the immunoassay was greatly improved by the use of a broad-spectrum monoclonal antibody attached to UCNPs to form a signal probe. Under the optimal conditions, the UCNP-LFIC assay enabled sensitive detection of tetracycline (TC) as well as of oxytetracycline (OTC), chlortetracycline (CTC), and doxycycline (DOX) within 10 min, with IC50 values of 0.32, 0.32, 0.26, 0.22 ng/mL, respectively. There was no cross-reactivity with ten other antibiotics. Similarly, we evaluated the experimental results for matrix effects. Experiments involving spiking showed the four tetracycline antibiotics displaying mean recoveries ranging from 93.95 to 111.90% with relative standard deviations (RSDs) of < 9.95%. The detection results of actual samples using the developed method showed a good correlation (R2 ≥ 0.98) with the results using high-performance liquid chromatography (HPLC). Thus, the assay can achieve an ultrahighly sensitive detection of antibiotics in milk, and can hence promote human health and provides promising applications in the bio-detection field.

The concentration of wear debris in used lubricating oil is generally observed from spectral oil analysis. The element concentration data are one of the commonly used oil field data for degradation evaluation of power-shift steering transmission. However, in practical applications, the underlying degradation degree of the power-shift steering transmission is difficult to evaluate due to the complexity of element concentration data. To solve this problem, we propose a health index extraction methodology using a weighted average method to better characterize the underlying degradation, which leads to an accurate estimation of the residual life before the power-shift steering transmission needs to be maintained. The extracted health index not only maximizes the monotonic trend of underlying degradation but also minimizes the failure threshold variance between different power-shift steering transmissions. The method includes element concentration data modification, data selection, and data fusion steps that result in a reasonable power-shift steering transmission degradation model. Finally, a case study is provided to illustrate the proposed method. The results show that the extracted health index outperforms each selected element concentration data.

Abstract The deposition of Amyloid-beta peptides (Aβ) is detected at an earlier stage in Alzheimer’s disease (AD) pathology. Thus, the approach toward Aβ metabolism is considered to play a critical role in the onset and progression of AD. Mounting evidence suggests that lifestyle-related diseases are closely associated with AD, and exercise is especially linked to the prevention and the delayed progression of AD. We previously showed that exercise is more effective than diet control against Aβ pathology and cognitive deficit in AD mice fed a high-fat diet; however, the underlying molecular mechanisms remain poorly understood. On the other hand, a report suggested that exercise induced expression of fibronectin type III domain-containing protein 5 (FNDC5) in the hippocampus of mice through PGC1α pathway. Thus, in the current study, we investigated a possibility that FNDC5 interacts with amyloid precursor protein (APP) and affects Aβ metabolism. As a result, for the first time ever, we found the interaction between FNDC5 and APP, and forced expression of FNDC5 significantly decreased levels of both Aβ40 and Aβ42 secreted in the media. Taken together, our results indicate that FNDC5 significantly affects β-cleavage of APP via the interaction with APP, finally regulating Aβ levels. A deeper understanding of the mechanisms by which the interaction between APP and FNDC5 may affect Aβ production in an exercise-dependent manner would provide new preventive strategies against the development of AD.

Abstract Background There is a lack of large-scale epidemiological data on the clinical practice of enteral nutrition (EN) feeding in China. This study aimed to provide such data on Chinese hospitals and to investigate factors associated with EN delivery. Methods This cross-sectional study was launched in 118 intensive care units (ICUs) of 116 mainland hospitals and conducted on April 26, 2017. At 00:00 on April 26, all patients in these ICUs were included. Demographic and clinical variables of patients on April 25 were obtained. The dates of hospitalization, ICU admission and nutrition initiation were reviewed. The outcome status 28 days after the day of investigation was obtained. Results A total of 1953 patients were included for analysis, including 1483 survivors and 312 nonsurvivors. The median study day was day 7 (IQR 2–19 days) after ICU entry. The proportions of subjects starting EN within 24, 48 and 72 h after ICU entry was 24.8% (84/352), 32.7% (150/459) and 40.0% (200/541), respectively. The proportion of subjects receiving > 80% estimated energy target within 24, 48, 72 h and 7 days after ICU entry was 10.5% (37/352), 10.9% (50/459), 11.8% (64/541) and 17.8% (162/910), respectively. Using acute gastrointestinal injury (AGI) 1 as the reference in a Cox model, patients with AGI 2–3 were associated with reduced likelihood of EN initiation (HR 0.46, 95% CI 0.353–0.599; p

The multi-disc wet clutch is widely used in transmission systems as it transfers the torque and power between the gearbox and the driving engine. During service, the buckling of the friction components in the wet clutch is inevitable, which can shorten the lifetime of the wet clutch and decrease the vehicle performance. Therefore, fault diagnosis and online monitoring are required to identify the buckling state of the friction components. However, unlike in other rotating machinery, the time-domain features of the vibration signal lack efficiency in fault diagnosis for the wet clutch. This paper aims to present a new fault diagnosis method based on multi-speed Hilbert spectrum entropy to classify the buckling state of the wet clutch. Firstly, the wet clutch is classified depending on the buckling degree of the disks, and then a bench test is conducted to obtain vibration signals of each class at varying speeds. By comparing the accuracy of different classifiers with and without entropy, Hilbert spectrum entropy shows higher efficiency than time-domain features for the wet clutch diagnosis. Thus, the classification results based on multi-speed entropy achieve even better accuracy.

Clutch disengaging dynamic characteristics, including the disengaging duration and the variations of friction pair gaps and friction torque, are crucial to the shifting control of an automatic transmission. In the present paper, the influence of lubrication oil (ATF) temperature on disengaging dynamic characteristics is investigated through a comprehensive numerical model for the clutch disengaging process, which considers the hydrodynamic lubrication, the asperity contact, the heat transfer, the spline resistance, and the impact between the piston and clutch hub. Moreover, the non-uniformity coefficient (NUC) is proposed to characterize the disengaging uniformity of friction pairs. As the ATF temperature increases from 60 °C to 140 °C, the clutch disengaging duration shortens remarkably (shortened by 55.1%); besides, the NUC sees a decreasing trend before a slight increase. When the ATF temperature is 80 °C, the distribution of friction pair gaps is most uniform. During the disengaging process, the increase of ATF temperature not only accelerates the change of the lubrication status between friction pairs but also contributes to the decrease of contact torque and hydrodynamic torque. This research demonstrates for the first time, evidence for clutch disengaging dynamic characteristics with the consideration of ATF temperature.

The constitutive model is the crucial part for the finite element analyses. To study the elasto-plastic properties of unbound granular materials (UGMs) under repeated vehicular loads, an elasto-plastic constitutive model called revised spatially mobilized plane (SMP) was proposed and validated. In this study, the revised SMP model was used for the plastic strain analyses of a typical three-layer pavement structure. To make comparisons, the Mohr-Coulomb and Druck-Prager models were employed for the numerical computation. The results show that plastic tensile and compressive strains in the horizontal and vertical directions appear on the top surface of UGM using the revised SMP model, but no plastic strains are produced by the Mohr-Coulomb and Druck-Prager models. The distribution of plastic strains in the revised SMP model had a good relationship with the actual loading areas under the vehicular loading, which related to the rutting. With the Mohr-Coulomb and Druck-Prage models, a great plastic strain was produced during the first several loading cycles and hardly increased in the following loading cycles, while the plastic strain in the revised SMP model presented an obvious increasing tendency with increased loading cycles. The predicted permanent deformations of the revised SMP, Mohr-Coulomb and Druck-Prage models were 0.557 mm, 0.78 mm and 0.155 mm, respectively. Our work reveals that the Mohr-Coulomb model may over-predict and Druck-Prage model may under-predict the rutting of pavement in early loading stage and the results proved that the revised SMP model had advantages in the description of the plastic strain of UMG under repeated loads.