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Objective To investigate the application value of umbilical cord blood inflammatory markers in neonatal pulmonary infectious diseases. Methods Samples of umbilical cord blood from the women with gestational age between 34 weeks and 42 weeks during delivery in our hospital were enrolled from Jane 2018 to September 2019. Thirty-nine samples were assigned into case group, with the neonates with high risk signs of maternal infection, respiratory distress and respiratory support within 24 h after birth, and another 40 samples from normal neonates without any signs of maternal infection and being healthy after birth were assigned into control group (40 cases). All blood samples were tested for the levels of neutrophils CD64 and inflammatory factors, including IL-2R, IL-8, IL-10, TNF-α and IL-6. The case group was further divided into pulmonary edema subgroup and non-pulmonary edema subgroup, and acute respiratory distress syndrome (ARDS) subgroup and non-ARDS subgroup. The levels of inflammatory markers were analyzed and compared between the groups and subgroups. Receiver operating characteristic (ROC) curve analysis and the area under the curve (AUC) were used to assess their values. Results The levels of IL-2R, IL-8, IL-10, TNF-α and IL-6 were significantly higher in the case group than the control group (P < 0.05), but no obvious difference was seen in the level of CD64 between them (P > 0.05). The levels of TNF-α and IL-6 in the pulmonary edema subgroup were notably higher than those in the non-pulmonary edema subgroup (P < 0.05). The ARDS subgroup had statistically higher TNF-α and IL-2R levels when compared with the non-ARDS subgroup (P < 0.05). Conclusion For the near-term and full-term neonates with high risk of intrauterine infection, inflammatory markers in the umbilical cord blood are expected to be early warning markers of neonatal pulmonary infectious diseases. TNF-α and IL-6 have clinical value in the early estimation of pulmonary edema, and TNF-α and IL-2R have the potential for ARDS.

Considering at the robotic management for tomato plants in the greenhouse, it is necessary to identify the stem, leaf and fruit with the similar color from the broad-band visible image. In order to highlight the difference between the target and background, and improve the identification efficiency, the multiple narrow-band image fusion method for identifying the tomato’s three similar-colored organs, including stem, leaf, and green fruit, was proposed, based on the spectral features of these organs. According to the 300-1000 nm spectral data of three organs, the regularized logistic regression model with Lasso for distinguishing their spectral characteristic was built. Based on the sparse solution of the model’s weight coefficients, the wavelengths 450, 600 and 900 nm with the maximum coefficients were determined as the optimal imaging band. The multi-spectral image capturing system was designed, which could output three images of optimal bands from the same view-field. The relationship between the organs’ image gray and their spectral feature was analyzed, and the optimal images could accurately show the organs’ reflection character at the various band. In order to obtain more significant distinctions, the weighted-fusion method based NSGA-II was proposed, which was supposed to combine the organ’s difference in the optimal band image. The algorithm’s objective function was defined to maximize the target-background difference and minimize the background-background difference. The coefficients obtained were adopted as the linear fusion factors for the optimal band images.Finally, the fusion method was evaluated based on intuitional and quantitative indexes, respectively considering the one among stem, leaf and green fruit as target, and the other two as the backgrounds. As the result showed, compared with the single optimal band image, the fused image greatly intensified the difference between the similar-colored target and background, and restrained the difference among the background. Specifically, the sum of absolute difference (SAD) was used to describe the grey value difference between the various organs, and the fusion result images’ SAD between the target and the background raised to 2.02, 8.63 and 7.89 times than the single band images. The Otsu automatic segmentation algorithm could respectively obtain the recognition accuracy of 71.14%, 60.32% and 98.32% for identifying the stem, leaf and fruit on the fusion result image. The research was supposed as a reference for the identification on similar-colored plant organs under agricultural condition.

This paper is devoted to suppressing the lumped disturbance, which is mainly composed of static and dynamic unbalanced disturbance, to ensure the imaging quality of the rotating payload satellite system with a five-degree-of-freedom active magnetic bearing. The dynamic model of lumped disturbance in imaging phase is established to design the balancing error index of payload unbalance, and the effect of bearing mechanical characteristics is analyzed. A novel fixed-time extended state observer is proposed to estimate unknown lumped disturbance and uncertainty. On this basis, a novel quaternion-based fixed-time nonsingular terminal sliding mode controller is presented to achieve high precision, high stability, and chattering-free attitude control. The complete proof on the faster convergence performance of the presented sliding mode surface compared to the existing sliding mode surfaces and the fixed-time convergence of the presented controller is provided. Numerical simulation results are carried out to verify the lumped disturbance modeling accuracy and the effectiveness of the proposed controller.

Background and Aim. Obesity has been linked to incomplete colonoscopy. In the present study, we aimed to determine whether an abdominal compression bandage could improve the complete colonoscopy rate (CCR) of obese patients. Methods. Eligible patients were randomly allocated into the abdominal bandage and conventional groups during a routine colonoscopy. The primary outcome was CCR. Results. A total of 250 eligible patients were randomly assigned to the abdominal bandage and conventional groups from January 2021 to April 2021. Eleven patients (five in the abdominal bandage group and six in the conventional group) were excluded due to schedule cancellation after randomization, and 239 patients were eventually included in the final analysis. There were no significant differences between the two groups regarding baseline characteristics (P > 0.05). Furthermore, no significant differences were observed in terms of advanced adenoma detection rate (AADR), polyp detection rate (PDR), bowel preparation scale (BBPS), bubble scale (BS), and withdrawal time between the two groups (P > 0.05). However, compared with the conventional group, the cecal insertion time (CIT) of the abdominal bandage group was significantly shortened (279.00 (234.50–305.75) vs. 421.00 (327.00–485.00), P

Objective: The study aimed to evaluate the role of the neutrophil percentage (N%) at admission in predicting in-hospital major adverse cardiovascular events (MACE) in patients ≥75 years of age with acute coronary syndrome (ACS). Methods: A total of 1189 patients above 75 years of age with ACS hospitalized at the Second Xiangya Hospital between January 2013 and December 2017 were enrolled in this retrospective study. Receiver operator characteristic curve analysis was performed to calculate the optimal N% cut-off value for patient grouping. The in-hospital MACE consisted of acute left heart failure, stroke and any cause of death. Multivariable logistic analyses were used to assess the role of N% in predicting MACE in older patients with ACS. Results: The patients were divided into a high N% group (N% ≥74.17%, n=396) and low N% group (N%

The end-operation accuracy of the satellite-borne robotic arm is closely related to the satellite attitude control accuracy, and the influence of the vibration of the satellite’s flexural structure on the satellite attitude control is not negligible. Therefore, a stable and reliable vibration frequency identification method of the satellite flexural structure is needed. Different from the traditional non-contact measurement and identification methods of large flexible space structures based on marker points or edge corner points, the condition of non-marker points relying on texture features can identify more feature points, but there are problems such as low recognition and poor matching of features. Given this, the concept of ‘the comprehensive matching parameter’ of scenes is proposed to describe the scene characteristics of non-contact optical measurement from the two dimensions of recognition and matching. The basic connotation and evaluation index of the concept are also given in the paper. Guided by this theory, the recognition accuracy and matching uniqueness of features can be improved by means of equivalent spatial transformation and novel relative position relationship descriptor. The above problems in non-contact measurement technology can be solved only through algorithm improvement without adding hardware devices. On this basis, the Eigensystem Realization Algorithm (ERA) method is used to obtain the modal parameters of the large flexible space structure. Finally, the effectiveness and superiority of the proposed method are verified by mathematical simulation and ground testing.

The cooperative positioning problem of hypersonic vehicles regarding LEO constellations is the focus of this research study on space-based early warning systems. A hypersonic vehicle is highly maneuverable, and its trajectory is uncertain. New challenges are posed for the cooperative positioning capability of the constellation. In recent years, breakthroughs in artificial intelligence technology have provided new avenues for collaborative multi-satellite intelligent autonomous decision-making technology. This paper addresses the problem of multi-satellite cooperative geometric positioning for hypersonic glide vehicles (HGVs) by the LEO-constellation-tracking system. To exploit the inherent advantages of hierarchical reinforcement learning in intelligent decision making while satisfying the constraints of cooperative observations, an autonomous intelligent decision-making algorithm for satellites that incorporates a hierarchical proximal policy optimization with random hill climbing (MAPPO-RHC) is designed. On the one hand, hierarchical decision making is used to reduce the solution space; on the other hand, it is used to maximize the global reward and to uniformly distribute satellite resources. The single-satellite local search method improves the capability of the decision-making algorithm to search the solution space based on the decision-making results of the hierarchical proximal policy-optimization algorithm, combining both random hill climbing and heuristic methods. Finally, the MAPPO-RHC algorithm’s coverage and positioning accuracy performance is simulated and analyzed in two different scenarios and compared with four intelligent satellite decision-making algorithms that have been studied in recent years. From the simulation results, the decision-making results of the MAPPO-RHC algorithm can obtain more balanced resource allocations and higher geometric positioning accuracy. Thus, it is concluded that the MAPPO-RHC algorithm provides a feasible solution for the real-time decision-making problem of the LEO constellation early warning system.

To study the regeneration of CF-100 type microcrystalline material after adsorbing carbon fluorides in SF6, an experimental device was built that can achieve both vacuum desorption of carbon fluorides and auxiliary heating to promote vacuum desorption of carbon fluorides. Thermogravimetric analyzer and Fourier transform infrared spectrometer were used to analyze the optimal treatment temperature and time of regeneration technology for promoting vacuum desorption of fluorocarbon by auxiliary heating. A comparative study was conducted on the two regeneration techniques mentioned above by analyzing the relationship between adsorption performance and the number of regenerations. The regeneration effects were also validated by using a specific surface area tester to examine the test data. The results demonstrate that desorption of fluorocarbons from CF-100 microcrystalline material is more efficient using a vacuum desorption method aided by auxiliary heating, as opposed to pure vacuum desorption. The CF-100 type of microcrystalline material achieves the best desorption effect when heated to 300°C with an auxiliary heating duration of 2 h, with an activation energy of 293.933 KJ/mol. After activation, CF-100 microcrystalline materials exhibit stable adsorption and desorption performance for decarbonization and possess excellent recyclability.

Over the last few years, a number of studies have quantified the role of radiomics, dynamic contrast enhancement and standard MRI (T2WI + DWI) in detecting prostate cancer; however, the aim of this paper was to assess the advantage of combining radiomics with other multiparametric magnetic resonance imaging (mpMRI) (T2-DWI-DCE) in improving the detection of prostate cancer. This study used 10 prostate-cancer-tissue-mimicking phantoms to obtain preclinical data. We then focused on 46 patients who underwent mpMRI and Transrectal Ultrasound (TRUS) guided biopsy between September 2016 and December 2017. The texture analysis parameters combined with the mpMRI and compared with the histopathology of TRUS biopsy have been assessed statistically by principal component analysis (PCA) and discriminant component analysis (DCA). The prediction model and goodness-of-fit were examined with the Akaike information criterion (AIC) and McFadden pseudo-R-squared. In the PCA, there was a higher separation between cancerous and noncancerous tissue in the preclinical compared with the clinical data. Both AIC and R2 showed an improvement in the model in cancer prediction by adding the radiomics to mpMRI. The discriminant analysis showed an accuracy of cancer prediction of 81% compared with 100% in the pre-clinical phantom data. Combining radiomics with mpMRI showed an improvement in prostate cancer prediction. The ex vivo experiments validated the findings of this study.

ObjectivesTo investigate the impact of ultrasound shear wave elastography (USWE) and multiparametric magnetic resonance imaging (mpMRI) in predicting a change in biopsy-assigned Gleason Score (GS) after radical surgery for localised prostate cancer (PCa).MethodA total of 212 men opting for laparoscopic radical prostatectomy (LRP) between September 2013 and June 2017 were recruited into this study. All the participants had 12-core transrectal ultrasound (TRUS) biopsies and imaging using USWE and mpMRI before radical surgery. The predictive accuracy for imaging modalities was assessed in relation to upgrading and downgrading of PCa GS between the biopsies and radical prostatectomy using Student’s t-test and multivariable logistic regression analyses. A decision analysis curve was constructed assessing the impact of nomogram on clinical situations using different thresholds of upgrading probabilities.ResultsMost GS 6 diseases on biopsies were upgraded on radical surgery (37/42, 88.1%). Major downgrading was seen in GS 8 category of disease (14/35; 37.1%), whereas no alteration was observed in GS 7 on biopsies in most men (55/75; 73.3%). In univariate analysis, higher preoperative prostate-specific antigen (PSA) (p = 0.001), higher prostate-specific antigen density (PSAD) (p = 0.002), stiffer USWE lesions (p = 0.009), and higher prostate imaging–reporting and data system (PIRADS) (p = 0.002) on mpMRI were significant predictors of upgrading. In multivariate logistic regression analyses, only PSA (p = 0.016) and USWE-measured tissue stiffness (p = 0.029) showed statistical significance in predicting upgrading.ConclusionsMeasurement of tissue stiffness using USWE in clinically localised PCa can predict upgrading of GS and has the potential to improve patient management options.

Tracking of hypersonic glide vehicles (HGVs) by a constellation tracking and observation system is an important part of the space-based early warning system. The uncertainty in the maneuver intentions of HGVs has a non-negligible impact on the tracking and observation process. The cooperative scheduling of multiple satellites in an environment of uncertainty in the maneuver intentions of HGVs is the main problem researched in this paper. For this problem, a satellite constellation tracking decision method that considers the HGVs’ maneuver intentions is proposed. This method is based on building an HGV maneuver intention model, developing a maneuver intention recognition and prediction algorithm, and designing a sensor-switching strategy to improve the local consensus-based bundle algorithm (LCBBA). Firstly, a recognizable maneuver intention model that can describe the maneuver types and directions of the HGVs in both the longitudinal and lateral directions was designed. Secondly, a maneuver intention recognition and prediction algorithm based on parallel, stacked long short-term memory neural networks (PSLSTM) was developed to obtain maneuver directions of the HGV. On the basis of that, a satellite constellation tracking decision method (referred to as SS-LCBBA in the following) considering the HGVs’ maneuver intentions was designed. Finally, the maneuver intention prediction capability of the PSLSTM network and two currently popular network structures: the multilayer LSTM (M-LSTM) and the dual-channel and bidirectional neural network (DCBNN) were tested for comparison. The simulation results show that the PSLSTM can recognize and predict the maneuver directions of HGVs with high accuracy. In the simulation of a satellite constellation tracking HGVs, the SS-LCBBA improved the cumulative tracking score compared to the LCBBA, the blackboard algorithm (BM), and the variable-center contract network algorithm (ICNP). Thus, it is concluded that SS-LCBBA has better adaptability to environments with uncertain intentions in solving multi-satellite collaborative scheduling problems.

Theabrownins are macromolecular compounds with many hydroxyl, carboxyl, and phenolic functional groups. They are usually extracted from dark tea, in which they are present at low concentrations. In this paper, a low-cost microbial liquid fermentation method was established by inoculating Aspergillus niger with minced tea extract as the raw material. After applying the Box–Behnken and response surface approach design, the optimum fermentation conditions in the fermentor were determined to be an 8% (80 g/L) sucrose concentration, 1:31 (0.03226 g/mL) solid–liquid ratio, 4.141 × 106 CFU/mL bacterial liquid concentration, 5 d fermentation time, 28 °C fermentation temperature, 187 r/min (rpm) rotation speed, and an oxygenation of 0.5 V/V·min (V). After fermenting about 168 h, the theabrownins content reached the maximum of 28.34%. The total phenolic content of the liquid-fermented theabrownins was 25.74% higher than that of solid fermentation. Acidic functional groups were determined, indicating that the phenolic hydroxyl groups were the main acidic groups of the theabrownins. The antioxidant activity of theabrownins was verified by measuring the potassium ferricyanide reducing power, hydroxyl radical scavenging rate, superoxide anion radical scavenging rate, and 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging rate of solid- and liquid-fermented chabein. The results of this study show that the production of theabrownins by the liquid fermentation of Aspergillus niger is fast, high in yield, and has antioxidant activity, which provides a basis for industrial production of theabrownins.

Abstract Background There is growing evidence suggesting that multiparametric magnetic resonance imaging (mpMRI) is a marker for prostate cancer (PCa) aggressiveness and could be used to plan treatment. Improving early detection of clinically significant PCa with pre-biopsy mpMRI would very likely have advantages including optimising the diagnosis and treatment of diseases and diminishing patient anxiety. Methods and materials This is a prospective multicentre study of pre-biopsy mpMRI diagnostic test accuracy with subgroup randomisation at a 1:1 ratio with respect to transrectal ultrasound (TRUS) and MRI/US fusion-guided biopsy or TRUS-only biopsy. It is designed as a single-gate study with a single set of inclusion criteria. The total duration of the recruitment phase was 48 months; however, this has now been extended to 66 months. A sample size of 600 participants is required. Discussion The primary objective is to determine whether mpMRI can improve PCa detection and characterisation. The key secondary objective is to determine whether MRI/US fusion-guided biopsy can reduce the number of false-negative biopsies. Ethical approval was obtained from the East of Scotland Research Ethics Committee 1 (14/ES/1070) on 20 November 2014. The results of this study will be used for publication and presentation in national and international journals and at scientific conferences. Trial registration ClinicalTrials.gov, NCT02745496. Retrospectively registered on 20 April 2016.

Based on the "octahedral structure model" of three-dimensional reticulated porous materials, the mathematical deductions are introduced one by one for the mathematical relations of their basic physical and mechanical properties in this paper. The present review on these deductions covers the unidirectional tension and the multidirectional tension/compression of porous materials, as well as the conductivity and the fatigue property. Emphasis is placed on describing the equivalent circuit of the inner structure of porous materials, and the force action model both of quasi-rigid body and deformed body structure of porous materials under unidirectional tension. On this basis, the compressive strength is discussed, and the biaxial tension and triaxial tension/compression are mathematically deducted and analyzed. According to this octahedron model, the mathematical relations of mechanical properties can be also obtained from the deduction of unidirectional tension and compression, for porous materials under loading of non-direct tension and compression.

The "octahedral structure model" is introduced for three-dimensional reticulated porous materials, as well as the mathematical relations of their basic physical and mechanical properties. On this basis, the verification works about some performance relations, including the conductivity and tension, etc, are reviewed in this paper. A number of issues were discussed with the emphases on the practicality of these mathematical and physical relations, the rationality of the correction coefficients, the significant influence on the calculation results, and the allowable stress and the plastic index value of the corresponding dense body were also analyzed in details. According to this mathematical and physical relationship, the performance indexes such as the electrical resistivity of porous products can be calculated by the easily measurable basic parameters like the porosity. The experimental results prove this way feasible. Therefore, this method can be superior to the finite element and other complex computational methods.

Three-dimensional reticulated porous materials are excellent engineering materials, and their application cover energy engineering, bioengineering, aerospace, environmental protection, transportation, etc. Author of this paper put forward a simplified structure model of octahedron based on the structural characteristics of these materials. On this basis, serial mathematical relations were obtained for their performance. This model and the related mathematical characterization of the basic physical and mechanical properties of this kind of materials,from unidirectional tension to multidirectional tension and compression,as well as conductivity and specific surface area were comprehensively introduced. The origin and characteristics of the simplified structural model were described comprehensively, and compared with other similar models; different property models and their relationships were explained one by one. Among them, the representative problems including the thin beams assumption of pore struts, the bending of pore struts and the restraint force of bearing units for the loaded porous body, and the correction coefficient and the plastic index value involved in the tension or/and compression relationship. The theoretical results were verified by the experiment of samples prepared in production line, which were well practicable.

Honeycomb sandwich plates are used widely in the aerospace industry. Building accurate finite element models of honeycomb sandwich plates is necessary for analyzing and optimizing the microvibration that occurs in spacecraft. A finite element dynamic model of a honeycomb plate was built, and then by using orthogonal design of experimental computation, the most important material parameters of honeycomb core equivalent model were identified. Through the global optimization based on adaptive sampling guided by response surface model, the parameters of honeycomb core were updated efficiently. The average error of first six modal frequencies of the updated finite element model against experimental result is reduced to less than 1%.

With the increasing demand for gold and the decreasing of easily treated gold resources, refractory gold ores, which are characterized by low gold recovery and high cyanide consumptions when subjected to direct cyanide leaching, have gradually become the main sources of gold. Thus, reasonable exploitation and utilization of refractory gold ores are of great significance to the sustainable development of the gold industry in China. To ensure a reasonable and efficient utilization of refractory gold ores, refractory gold ores were reviewed and classified in this paper, and the difficulties of handling were briefly reviewed. For over one hundred years, cyanidation has been the predominant process of extracting gold from mineral sources. The major reason for adopting cyanide rather than other lixiviants is its higher chemical stability and lower cost. But in recent years, the utilization of the traditional cyanide method to leach gold have been undesirable; this is mainly because the acute toxicity of cyanide can result in environmental pollution and human health hazard. Moreover, leaching of refractory gold ores by traditional cyanidation techniques also results in poor gold recovery. On this basis, non-cyanide lixiviants have attracted considerable attention in the metallurgical industry, and several non-cyanide leaching methods have been proposed for gold extraction because of their non-toxic nature, acceptable gold leaching rates, and high gold recovery. In this paper, the leaching mechanisms and the latest research progress of non-cyanide gold leaching techniques for refractory gold ores, such as leaching processes with thiosulfate, thiocyanate, thiourea, polysulfide, lime-sulfur-synthetic solution (LSSS) and chlorination, were discussed in detail. Then considering features of non-cyanide gold leaching such as a complex leaching system, unstable leaching agents, and large consumption of leaching agents, and development directions of non-cyanide gold leaching technology for refractory gold ores were proposed.

There is a recent trend of using lactic acid bacteria for the production of gamma-aminobutyric acid (GABA). This study described a method that combines fermentation and self-buffered whole-cell catalysis for the efficient production of GABA using Levilactobacillus brevis CD0817. Upon the completion of GABA fermentation, cells were recovered to conduct whole-cell catalysis by which the substrate L-glutamic acid was catalytically decarboxylated to GABA. L-glutamic acid itself maintained the acidity essential for decarboxylation. To maximize the whole-cell catalysis ability, the effects of the cell culture method, catalysis temperature, catalysis time, cell concentration, and L-glutamic acid dosage were investigated. The results illustrate that the cells that were cultivated for 16 h in a fermentation medium supplemented with 20.0 g/L of glucose were the most suitable for the whole-cell catalytic production of GABA. At 16 h, the fermentative GABA content reached 204.2 g/L. Under optimized whole-cell catalytic conditions (temperature 45.0 °C, time 12.0 h, wet cells 25.0 g/L, and L-glutamic acid 120.0 g/L), 85.1 g/L of GABA was obtained, with 3.7 ± 0.9 g/L of substrate residue. GABA was recovered from the system by sequentially performing rotary vacuum evaporation, precipitation with ethanol, filtration with filter paper, and drying. The purity of the GABA product reached 97.1%, with a recovery rate of 87.0%. These data suggest that the proposed method has potential applications in the production of GABA.

The associations between airway eosinophilia, measured in sputum or peripheral blood, and acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are inconsistent. We therefore aimed to determine the association between eosinophilia in bronchoalveolar lavage (BAL) fluid and AECOPD in a clinical cohort. We analyzed differential cell counts from baseline BAL fluid in participants in the DISARM clinical trial (Clinicaltrials.gov #NCT02833480) and classified participants by the presence or absence of BAL eosinophilia (>1% of total leukocytes). We determined the association between BAL eosinophilia and AECOPD over 1 year of follow-up using negative binomial regression and Cox proportional hazards test. N = 63 participants were randomized, and N = 57 had BAL differential cell counts available. Participants with BAL eosinophilia (N = 21) had a significantly increased rate of acute exacerbations (unadjusted incidence rate ratio (IRR) 2.0, p = 0.048; adjusted IRR 2.24, p = 0.04) and a trend toward greater probability of acute exacerbation (unadjusted hazard ratio (HR) 1.74, p = 0.13; adjusted HR 2.3, p = 0.1) in the year of follow-up compared to participants without BAL eosinophilia (N = 36). These associations were not observed for BAL neutrophilia (N = 41 participants), BAL lymphocytosis (N = 27 participants) or peripheral blood eosinophilia at various threshold definitions (2%, N = 37; 3%, N = 27; 4%, N = 16). BAL may therefore be a sensitive marker of eosinophilic inflammation in the distal lung and may be of benefit for risk stratification or biomarker-guided therapy in COPD.

Gut microbiota can influence host gene expression and physiology through metabolites. Besides, the presence or absence of gut microbiome can reprogram host transcriptome and epitranscriptome as represented by N6-methyladenosine (m6A), the most abundant mammalian mRNA modification. However, which and how gut microbiota-derived metabolites reprogram host transcriptome and m6A epitranscriptome remain poorly understood. Here, investigation is conducted into how gut microbiota-derived metabolites impact host transcriptome and m6A epitranscriptome using multiple mouse models and multi-omics approaches. Various antibiotics-induced dysbiotic mice are established, followed by fecal microbiota transplantation (FMT) into germ-free mice, and the results show that bile acid metabolism is significantly altered along with the abundance change in bile acid-producing microbiota. Unbalanced gut microbiota and bile acids drastically change the host transcriptome and the m6A epitranscriptome in multiple tissues. Mechanistically, the expression of m6A writer proteins is regulated in animals treated with antibiotics and in cultured cells treated with bile acids, indicating a direct link between bile acid metabolism and m6A biology. Collectively, these results demonstrate that antibiotic-induced gut dysbiosis regulates the landscape of host transcriptome and m6A epitranscriptome via bile acid metabolism pathway. This work provides novel insights into the interplay between microbial metabolites and host gene expression.

Chimeric antigen receptor (CAR) technology has revolutionized cancer treatment, particularly in malignant hematological tumors. Currently, the BCMA-targeted second-generation CAR-T cells have showed impressive efficacy in the treatment of refractory/relapsed multiple myeloma (R/R MM), but up to 50% relapse remains to be addressed urgently. Here we constructed the BCMA-targeted fourth-generation CAR-T cells expressing IL-7 and CCL19 (i.e., BCMA-7 × 19 CAR-T cells), and demonstrated that BCMA-7 × 19 CAR-T cells exhibited superior expansion, differentiation, migration and cytotoxicity. Furthermore, we have been carrying out the first-in-human clinical trial for therapy of R/R MM by use of BCMA-7 × 19 CAR-T cells (ClinicalTrials.gov Identifier: NCT03778346), which preliminarily showed promising safety and efficacy in first two enrolled patients. The two patients achieved a CR and VGPR with Grade 1 cytokine release syndrome only 1 month after one dose of CAR-T cell infusion, and the responses lasted more than 12-month. Taken together, BCMA-7 × 19 CAR-T cells were safe and effective against refractory/relapsed multiple myeloma and thus warranted further clinical study.

Polo-like kinases (Plks) are critical regulatory molecules during the cell cycle process. This family has five members: Plk1, 2, 3, 4, and 5. Plk4 has been identified as a master regulator of centriole replication, and its aberrant expression is closely associated with cancer development. In this review, we depict the DNA, mRNA, and protein structure of Plk4, and the regulation of Plk4 at a molecular level. Then we list the downstream targets of Plk4 and the hallmarks of cancer associated with these targets. The role of Plk4 in different cancers is also summarized. Finally, we review the inhibitors that target Plk4 in the hope of discovering effective anticancer drugs. From authors’ perspective, Plk4 might represent a valuable tumor biomarker and critical target for cancer diagnosis and therapy.

Background: Patients with chronic obstructive pulmonary disease (COPD) are highly susceptible from respiratory exacerbations from viral respiratory tract infections. However, it is unclear whether they are at increased risk of COVID-19 pneumonia or COVID-19-related mortality. We aimed to determine whether COPD is a risk factor for adverse COVID-19 outcomes including hospitalization, severe COVID-19, or death. Methods: Following the PRISMA guidelines, we performed a systematic review of COVID-19 clinical studies published between November 1st, 2019 and January 28th, 2021 (PROSPERO ID: CRD42020191491). We included studies that quantified the number of COPD patients, and reported at least one of the following outcomes stratified by COPD status: hospitalization; severe COVID-19; ICU admission; mechanical ventilation; acute respiratory distress syndrome; or mortality. We meta-analyzed the results of individual studies to determine the odds ratio (OR) of these outcomes in patients with COPD compared to those without COPD. Findings: Fifty-nine studies met the inclusion criteria, and underwent data extraction. Most studies were retrospective cohort studies/case series of hospitalized patients. Only four studies examined the effects of COPD on COVID-19 outcomes as their primary endpoint. In aggregate, COPD was associated with increased odds of hospitalization (OR 4.23, 95% confidence interval [CI] 3.65–4.90), ICU admission (OR 1.35, 95% CI 1.02–1.78), and mortality (OR 2.47, 95% CI 2.18–2.79). Interpretation: Having a clinical diagnosis of COPD significantly increases the odds of poor clinical outcomes in patients with COVID-19. COPD patients should thus be considered a high-risk group, and targeted for preventative measures and aggressive treatment for COVID-19 including vaccination.

A correct lane-changing plays a crucial role in traffic safety. Predicting the lane-changing behavior of a driver can improve the driving safety significantly. In this paper, a hybrid neural network prediction model based on recurrent neural network (RNN) and fully connected neural network (FC) is proposed to predict lane-changing behavior accurately and improve the prospective time of prediction. The dynamic time window is proposed to extract the lane-changing features which include driver physiological data, vehicle kinematics data, and driver kinematics data. The effectiveness of the proposed model is validated through the experiments in real traffic scenarios. Besides, the proposed model is compared with five prediction models, and the results show that the proposed prediction model can effectively predict the lane-changing behavior more accurate and earlier than the other models. The proposed model achieves the prediction accuracy of 93.5% and improves the prospective time of prediction by about 2.1 s on average.

Background and Aims. Simethicone (SIM), as an antifoaming agent, has been shown to improve bowel preparation during colonoscopy. However, the optimal timing of SIM addition remained undetermined. We aimed to investigate the optimal timing of SIM addition to polyethylene glycol (PEG) to improve bowel preparation. Methods. Eligible patients were randomly assigned to two groups: the SIM evening group (SIM addition to PEG in the evening of the day prior to colonoscopy) and the SIM morning group (SIM addition to PEG in the morning of colonoscopy). The primary outcome was Bubble Scale (BS). The secondary outcomes were Boston Bowel Preparation Scale (BBPS) and adenoma detection rate (ADR). Results. A total of 419 patients were enrolled in this study. The baseline characteristics of the patients were similar in both groups. No significant differences were observed in terms of BS (8.76 ± 0.90 vs. 8.65 ± 1.16, P = 0.81), ADR (34.1% vs. 30.8%, P = 0.47), Boston Bowel Preparation Scale (BBPS) (8.59 ± 0.94 vs. 8.45 ± 1.00, P = 0.15), and withdrawal time (8.22 ± 2.04 vs. 8.01 ± 2.51, P = 0.094) between the two groups. Moreover, safety and compliance were similar in both groups. However, the SIM evening group was associated with shorter cecal intubation time (3.80 ± 1.81 vs. 4.42 ± 2.03, P

Lane changing is an important scenario in traffic environments, and accurate prediction of lane-changing behavior is essential to ensure traffic and driver safety. To achieve this goal, a vehicle lane-changing prediction model based on game theory and deep learning is developed. In the game theory component, the interaction between vehicles during lane changing is analyzed according to the running state of the vehicle, with the probability of lane changing as its output. For the deep-learning component, long short-term memory and a convolutional neural network are used to extract and learn data features during the lane-changing process as well as combine the output of the game theory component to obtain the prediction result of whether the vehicle will change lanes. By using an open-source traffic dataset to train and verify the proposed model, the verification results show that the prediction accuracy can reach 94.56% within 0.4 s of lane-changing operation and that the model can achieve timely and accurate prediction of the lane-changing behavior of vehicles.

A flexible brush mechanism is designed and mounted at the end of a seven-degree-of-freedom robotic arm to despin a tumbling target. The dynamics model of the flexible brush is established using the absolute nodal coordinate method (ANCF), and its contact collision with the solar wing of the tumbling target is analysed. The H∞ optimal control is proposed for a seven-degree-of-freedom robotic arm during despinning of a tumbling target while ensuring the global robustness and stability. Simulations verify that the despinning strategy can successfully eliminate the rotation speed and is feasible and effective.