Search

Abstract Endothelins and their receptors, ETA and ETB, play vital roles in maintaining vascular homeostasis. Therapeutically targeting endothelin receptors, particularly through ETA antagonists, has shown efficacy in treating pulmonary arterial hypertension (PAH) and other cardiovascular- and renal-related diseases. Here we present cryo-electron microscopy structures of ETA in complex with two PAH drugs, macitentan and ambrisentan, along with zibotentan, a selective ETA antagonist, respectively. Notably, a specialized anti-ETA antibody facilitated the structural elucidation. These structures, together with the active-state structures of ET-1-bound ETA and ETB, and the agonist BQ3020-bound ETB, in complex with Gq, unveil the molecular basis of agonist/antagonist binding modes in endothelin receptors. Key residues that confer antagonist selectivity to endothelin receptors were identified along with the activation mechanism of ETA. Furthermore, our results suggest that ECL2 in ETA can serve as an epitope for antibody-mediated receptor antagonism. Collectively, these insights establish a robust theoretical framework for the rational design of small-molecule drugs and antibodies with selective activity against endothelin receptors.

Abstract Commutation failure (CF) is one of the most common issues in line‐commuted converter‐based high voltage direct current systems (LCC‐HVDC), leading to critical power system security and stability problems. Accurate and rapid identification of CF is crucial to prevent subsequent CF in HVDC systems. However, the existing CF identification methods are lack of the required accuracy and speed. The relationship between bridge arm current, commutation voltage, and trigger pulse based on the commutation progress mechanism after the AC fault is analysed in this paper. A novel CF identification method is presented, which utilises the CF identification factor, enabling fast and high‐accurate identification without relying on the value of the extinction angle. The proposed method offers a simpler and more efficient implementation in engineering practice. Finally, the effectiveness of the proposed method is verified in both the standard International Council on Large Electric systems HVDC model and the Hardware in Loop test using practical project parameters. The results demonstrate that the proposed method can accurately and fast identify CF.

In order to identify and effectively control the impact of NO3− pollution on human health, on the basis of investigation, sampling, analysis and testing, statistical analysis software (SPSS19), groundwater pollution analysis software, Nemera comprehensive index method, correlation analysis method and human health risk assessment model are applied for analysis and research. The results indicate that the groundwater in the study area is mainly Class II water, with overall good water quality. The main influencing factors for producing Class IV are NO3−, Fe, F− and SO42−. The use of agricultural fertilizers is the main source of NO3− exceeding standards in groundwater in this area. There are significant differences in the health hazards caused by NO3− pollution in groundwater among different populations, and infants and young children are more susceptible to nitrate pollution. The division of pollution areas and high-risk groups plays an important guiding role in preventing health risks. The new achievements will help people improve their awareness of risk prevention, caring for the environment, respecting nature and implementing precise policies, promoting society to step onto the track of scientific and healthy development. HIGHLIGHTS Scientific evaluation of groundwater quality was conducted and the main factors affecting water quality were analyzed.; Scientific evaluation was conducted on NO3− pollution in the research area and the main sources of NO3− were identified.; The significant differences in the health hazards of NO3− pollution were identified.; The research results have an important guiding role in preventing health risks.;

To investigate the influence of wind, waves and tides on the floating state, stability and strength of stranded ships, based on the previous literature, this paper summarizes three kinds of stranded modes of stranded ships and establishes a mechanical model of the action of wind, waves and tides on stranded ships. The stability, ground force, wind moment, shear force, bending moment, and torque were obtained by simulating the floating state change course of the stranded ship in different wind, wave, and tidal environments. The mechanical analysis and calculation of the stranded ship under different working cases show that wind and waves will cause the ship to capsize under the 4-level sea condition. Under 3-level sea conditions, the balanced arrangement of multiple stranded points limits the floating state of the ship and ensures its stability. In a wave period, the maximum stability of each working case exceeded the stability of the other environments in each working case by at least 0.156 m, 0.169 m, 0.044 m and 0.502 m, respectively. When the sea condition is level 4, only under the action of waves is the displacement of the stranded ship less than that of the other working cases, and the total amount of ground force is greater than that of the other working cases, which indicates that the wave height has a significant effect on the mechanical distribution of the stranded ship. The bending moment distribution of the ship is mainly affected by the load; however, the ground force and displacement can weaken the effect of the load to a certain extent. The differences in the negative maximum bending moment between the trough environment and the peak environment in each working case are 24.158 MN.m, 24.459 MN.m, −4.173 MN.m, and 70.616 MN.m, respectively. Under only wave cases, the maximum positive torque value at the longitudinal coordinate of −50 is more than twice the maximum positive torque value under the wind and wave cases.

Summary: Monoacylglycerol acyltransferase-2 (MOGAT2), encodes MOGAT enzyme in the re-synthesis of triacylglycerol and protects from metabolism disorders. While, its precise involvement in colorectal cancer (CRC) progression remains inadequately understood. Our study demonstrated that knockout of Mogat2 in Apcmin/+ mice expedited intestinal tumor growth and progression, indicating that Mogat2 plays a tumor-suppressing role in CRC. Mechanically, Mogat2 deletion resulted in a significant alter the gut microbiota, while Fecal Microbiota Transplantation (FMT) experiments demonstrated that the gut microbiota in Mogat2 deleted mice promoted tumor growth. Furthermore, we identified Mogat2 as a functional regulator suppressing CRC cell proliferation and tumor growth by inhibiting the NF-κB signaling pathway in vivo. Collectively, these results provide novel insights into the protective double roles of Mogat2, inhibiting of NF-κB pathway and keeping gut microbiota homeostasis in colorectal cancer, which may help the development of novel cancer treatments for CRC.

In this study, an electrochemical sensor for the real-time monitoring of propofol (PPF) in anesthesia was developed using molecularly imprinted polymers and reduced graphene oxide-modified glassy carbon electrodes (MIPs/rGO/GCE). To make the electrode, GO was thermally reduced into rGO, which was then electrodeposited on GCE (rGO/GCE), followed by the electropolymerization of MIPs using LiClO4, pyrrole, and PPF (template) solution on rGO/GCE (MIPs/rGO/GCE). The PPF was then taken out of the pyrrole polymer. X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), and X-ray Photoelectron Spectroscopy (XPS) examinations of surface composition and morphology revealed that electropolymerization MIP on rGO/GCE and reduction and deposition of rGO on GCE were both successful processes. MIPs/rGO/GCE revealed significant sensitivity and selectivity towards PPF in electrochemical tests utilizing cyclic voltammetry (CV) and amperometry. Results demonstrated a linear range from 0.5 to 250 μM that was steady and wide, with a sensitivity of 1.0776 μA/μM and a detection limit value of 0.08 μM. MIPs/rGO/GCE demonstrated outstanding electrocatalytic activity over a broad linear range and a reasonable detection limit value for PPF concentrations. To assess the method's applicability for the analysis of PPF, it was applied to real biological samples of human plasma and urine.

Abstract While macrophage phagocytosis is an immune defense mechanism against invading cellular organisms, cancer cells expressing the CD47 ligand send forward signals to repel this engulfment. Here we report that the reverse signaling using CD47 as a receptor additionally enhances a pro-survival function of prostate cancer cells under phagocytic attack. Although low CD47-expressing cancer cells still allow phagocytosis, the reverse signaling delays the process, leading to incomplete digestion of the entrapped cells and subsequent tumor hybrid cell (THC) formation. Viable THCs acquire c-Myc from parental cancer cells to upregulate both M1- and M2-like macrophage polarization genes. Consequently, THCs imitating dual macrophage features can confound immunosurveillance, gaining survival advantage in the host. Furthermore, these cells intrinsically express low levels of androgen receptor and its targets, resembling an adenocarcinoma-immune subtype of metastatic castration-resistant prostate cancer. Therefore, phagocytosis-generated THCs may represent a potential target for treating the disease.

The strong airflow beneath a rotary drone generates a wind vortex within the rice canopy; precise control of the wind vortex distance and wind vortex area can improve pesticide utilization efficiency. This paper calculates the flight parameter curve based on the wind vortex target from the wind vortex target parameter control model of the four-rotor plant protection drone, designs a flight control system using a Cube Orange flight controller and a Jetson AGX Xavier onboard computer, and implements flight parameter control using both PID control and fuzzy control algorithms. Experimental results indicate that when using PID control and fuzzy control, the average deviation values of UAV flight altitude and speed are 0.08 m, 0.08 m/s, 0.06 m, and 0.08 m/s, respectively. When using PID control, the average distance and area errors of the target downwind and upwind are 0.17 m and 0.37 m2 and 0.20 m and 0.46 m2, respectively. The corresponding values for fuzzy control are 0.12 m, 0.38 m2, 0.09 m, and 0.31 m2. In the twelve voyage experiments, the target parameter variance using fuzzy control was relatively smaller for eight voyages compared to PID control, which had a smaller variance for four voyages. On the whole, the effect of fuzzy control is superior. The wind vortex control method proposed in this paper can effectively enable precise pesticide spraying by drones. This has significant implications for reducing agricultural production costs and safeguarding the natural environment.

Cervical cancer (CC) remains one of the most common and deadly malignancies among women worldwide, with exceptionally high morbidity and mortality rates. The aberrant activation of the hedgehog pathway is intimately associated with tumor development and progression. Nevertheless, the potential therapeutic targets within the hedgehog pathway in CC have yet to be clearly identified. In this study, we conducted an in-depth investigation of hedgehog pathway-related genes in CC, integrating single-cell sequencing data and spatial transcriptomics. Utilizing a comprehensive scoring algorithm, we identified that myofibroblasts within CC tissue exhibit a highly enriched hedgehog pathway. Our analysis of the myofibroblast development process revealed that MYH9 plays a crucial role. Further exploration using spatial transcriptome data allowed us to delve into the role of MYH9 in myofibroblasts. We discovered that MYH9-negative and MYH9-positive myofibroblasts display distinct profiles. Validation using extensive transcriptome data demonstrated that a high infiltration of MYH9-positive myofibroblasts is a risk factor for CC patients, significantly impacting prognosis and immunotherapeutic efficacy. Our study provides unique insights into the relationship between CC and the hedgehog pathway, offering new directions for cancer treatment strategies.

Abdominal fat deposition (AFD) in chickens is closely related to the gut microecological balance. In this study, the gut microbiota from high-AFD chickens was transplanted into the same strain of 0-day-old chicks via fecal microbiota transplantation (FMT). The FTM from chickens with high AFD had no obvious effects on growth traits, adult body weight, carcass weight, abdominal fat weight, and abdominal fat percentage, but did reduce the coefficient of variation of AFD traits. FMT significantly decreased cecal microbiome richness, changed the microbiota structure, and regulated the biological functions associated with energy metabolism and fat synthesis. Additionally, the cecal metabolite composition and metabolic function of FMT recipient chickens were also significantly altered from those of the controls. Transplantation of high-AFD chicken gut microbiota promoted fatty acid elongation and biosynthesis and reduced the metabolism of vitamins, steroids, and carbohydrates in the cecum. These findings provide insights into the mechanisms by which chicken gut microbiota affect host metabolic profiles and fat deposition.

At present, all the flight controllers of agricultural UAVs cannot accurately and quickly control the influencing factors of the UAV coupled rotor airflow backward tilt angle during the application process. To solve the above problem, a Rotor Airflow Backward Tilt Angle (RABTA) controller is established in this paper. The RABTA controller integrates advanced sensor technology with a novel algorithmic approach, utilizing real-time data acquisition and state–space analysis to dynamically adjust the UAV’s rotor airflow, ensuring precise control of the backward tilt angle. The control effect of the traditional flight controller and RABTA controller in the process of pesticide application and the corresponding operation effect are compared and analyzed. The comparison results show that the RABTA controller reduces the control error to less than 1 degree, achieving a 48.3% improvement in the uniformity of the distribution of pesticides droplets across the crop canopy, which means that the UAV field application effect is implemented and the innovation of the UAV field application control mode is realized.

The Revolving Floating Crane (RFC) is a specialized engineering vessel crucial for offshore lifting operations, such as offshore platform construction and deep-water salvaging. It boasts impressive lifting capacity, good adaptability to various environmental conditions, and high operational efficiency. Conventionally, the safety and stability of RFC operations heavily depend on manual ballast water allocation, which is directly influenced by factors such as personnel status and sea conditions. These manual operations often result in reduced lifting efficiency, higher energy consumption, and compromised operational safety. In response, this paper introduces a ballast water-allocation approach based on the Point-to-Point (PTP) theory for the intelligent operation process of the RFC. The fundamental principles of the PTP theory are analyzed, and a method tailored to optimize ballast water allocation for RFC is proposed. Considering the unique characteristics of the ballast system and the specific requirements of lifting operations, an optimization model for PTP-based ballast water allocation is established. Numerical experiments are conducted to verify the efficacy and reliability of the proposed method. Comparing it to the conventional approaches, the results demonstrate a notable 17.75% reduction in energy consumption and an impressive 73.49% decrease in decision-making time, showcasing the superiority of the proposed approach. Finally, the engineering feasibility of the PTP-based optimization method for ballast water allocation is validated through actual lifting experiments, underscoring its potential to enhance RFC operations.

Background & Aims: Acinar-to-ductal metaplasia (ADM) serves as a precursor event in the development of pancreatic ductal adenocarcinoma (PDAC) upon constitutive environmental and genetical stress. While the role of ADM in PDAC progression has been established, the molecular mechanisms underlying human ADM remain elusive. We previously demonstrated the induction of ADM in human acinar cells through the transforming growth factor beta (TGFβ) signaling pathway. We aim to investigate the interaction between TGFβ and Hippo pathways in mediating ADM. Methods: RNA-sequencing was conducted on sorted normal primary human acinar, ductal, and AD (acinar cells that have undergone ADM) cells. ATAC-seq analysis was utilized to reveal the chromatin accessibility in these three cell types. ChIP-Seq of YAP1, SMAD4, and H3K27ac was performed to identify the gene targets of YAP1 and SMAD4. The role of YAP1/TAZ in ADM-driven cell proliferation, as well as in oncogenic KRAS driven proliferation, was assessed using sphere formation assay. Results: AD cells have a unique transcription profile, with upregulated genes in open chromatin states in acinar cells. YAP1 and SMAD4 co-occupy the loci of ADM-related genes, including PROM1, HES1, and MMP7, co-regulating biological functions such as cell adhesion, cell migration, and inflammation. Overexpression of YAP1/TAZ promoted acinar cell proliferation but still required the TGFβ pathway. YAP1/TAZ were also crucial for TGFβ-induced sphere formation and were necessary for KRAS-induced proliferation. Conclusions: Our study reveals the intricate transition between acinar and AD states in human pancreatic tissues. It unveils the complex interaction between the Hippo and TGF-β pathways during ADM, highlighting the pivotal role of YAP1/TAZ and SMAD4 in PDAC initiation.

Astaxanthin is a high value carotenoid with a broad range of commercial applications due to its superior antioxidant properties. In this study, β-carotene-producing Yarrowia lipolytica XK17 constructed in the lab was employed for astaxanthin biosynthesis. The catalytic effects of β-carotene ketolase CrtW and β-carotene hydroxylase CrtZ from various species were investigated. The PspCrtW from Paracoccus sp. and HpCrtZ# from Haematococcus pluvialis were confirmed to be the best combination in converting β-carotene. Several key bottlenecks in biomass and astaxanthin biosynthesis were effectively eliminated by optimizing the expression of the above enzymes and restoring uracil/leucine biosynthesis. In addition, the effects of astaxanthin biosynthesis on cell metabolism were investigated by integrated analysis of pathway modification and transcriptome information. After further optimization, strain DN30 was able to synthesize up to 730.3 mg/L astaxanthin in laboratory 5-L fermenter. This study provides a good metabolic strategy and a sustainable development platform for high-value carotenoid production.

Abstract Background The outbreak of SARS-CoV-2 continues to pose a serious threat to human health and social. The ongoing pandemic of COVID-19 caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has made a serious threat to public health and economic stability worldwide. Given the urgency of the situation, researchers are attempting to repurpose existing drugs for treating COVID-19. Methods We first established an anti-coronavirus drug screening platform based on the Homogeneous Time Resolved Fluorescence (HTRF) technology and the interaction between the coronavirus spike protein and its host receptor ACE2. Two compound libraries of 2,864 molecules were screened with this platform. Selected candidate compounds were validated by SARS-CoV-2_S pseudotyped lentivirus and ACE2-overexpressing cell system. Molecular docking was used to analyze the interaction between S protein and compounds. Results We identified three potential anti-coronavirus compounds: tannic acid (TA), TS-1276 (anthraquinone), and TS-984 (9-Methoxycanthin-6-one). Our in vitro validation experiments indicated that TS-984 strongly inhibits the interaction of the coronavirus S protein and the human cell ACE2 receptor. Additionally, tannic acid showed moderate inhibitory effect on the interaction of S protein and ACE2. Conclusion This platform is a rapid, sensitive, specific, and high throughput system, and available for screening large compound libraries. TS-984 is a potent blocker of the interaction between the S-protein and ACE2, which might have the potential to be developed into an effective anti-coronavirus drug.

Diagnosis of gastric cancer currently requires gastroscopic biopsy, which requires time and expertize to perform. Here, the authors demonstrate a femto-SRS imaging method which showed high accuracy in diagnosing gastric cancer without the need for pathologistbased diagnosis.

AimsPermanent pacemaker implantation (PPI) combined with hypertension leads to a higher risk of new-onset atrial fibrillation (NOAF) for patients. Hence, it is essential to study how to reduce this risk. Currently, the effects of the two common anti-hypertensive drugs, angiotensin-converting enzyme inhibitors (ACEI)/angiotensin receptor blockers (ARB) and calcium channel blockers (CCB), on the risk of NOAF for such patients remain unknown. This study aimed to investigate this association.MethodsThis single-center retrospective study included hypertensive patients with PPI and without prior history of AF/atrial flutter, heart valve disease, hyperthyroidism, etc. Patients were classified into ACEI/ARB group and CCB group based on their exposure drug information. The primary outcome was NOAF events that occurred within 12 months after PPI. The secondary efficacy assessments were the changes from baseline to follow-up in blood pressure and transthoracic echocardiography (TTE) parameters. A multivariate logistic regression model was used to verify our aim.ResultsA total of 69 patients were finally included (51 on ACEI/ARB and 18 on CCB). Both univariate analysis [odds ratio (OR) 0.241, 95% confidence interval (CI) 0.078–0.745] and multivariate analysis (OR: 0.246, 95% CI: 0.077–0.792) demonstrated that ACEI/ARB were associated with a lower risk of NOAF compared to CCB. The mean reduction in left atrial diameter (LAD) from baseline was greater in ACEI/ARB group than in CCB group (P = 0.034). There was no statistical difference between groups in blood pressure and other TTE parameters after treatment.ConclusionFor patients with PPI combined with hypertension, ACEI/ARB may be superior to CCB in selecting anti-hypertensive drugs, as ACEI/ARB further reduces the risk of NOAF. One reason for this may be that ACEI/ARB improves left atrial remodelling such as LAD better.

As the key route detection device, the performance of marine LiDAR in harsh environments is of great importance. In this paper, a metric reliability analysis method for marine LiDAR systems under extreme wind loads is proposed. First, a static measurement accuracy evaluation model for the LiDAR system is proposed, targeting the problem that the LiDAR measurement tail reduces the measurement accuracy. Second, the distribution of extreme wind speeds in the Pacific Northwest is investigated, and a wind load probability model is developed. Finally, the impact of hull fluctuations on LiDAR measurement accuracy is analyzed by performing hull fluctuation simulations based on the wind load probability model, and the relationship curve between the metric reliability and measurement accuracy of marine LiDAR systems under extreme wind loads is addressed using the Monte-Carlo method. Experimental results show that the proposed LiDAR static measurement accuracy evaluation model can improve the measurement accuracy by more than 30%. Meanwhile, the solved curve of the LiDAR metric reliability versus the measurement allowable error indicates that the metric reliability can reach above 0.89 when the allowable error is 60 mm, which is instructive for the reliable measurement of marine LiDAR systems during ship navigation.

Automated evaluation of all glomeruli throughout the whole kidney is essential for the comprehensive study of kidney function as well as understanding the mechanisms of kidney disease and development. The emerging large-volume microscopic optical imaging techniques allow for the acquisition of mouse whole-kidney 3D datasets at a high resolution. However, fast and accurate analysis of massive imaging data remains a challenge. Here, we propose a deep learning-based segmentation method called FastCellpose to efficiently segment all glomeruli in whole mouse kidneys. Our framework is based on Cellpose, with comprehensive optimization in network architecture and the mask reconstruction process. By means of visual and quantitative analysis, we demonstrate that FastCellpose can achieve superior segmentation performance compared to other state-of-the-art cellular segmentation methods, and the processing speed was 12-fold higher than before. Based on this high-performance framework, we quantitatively analyzed the development changes of mouse glomeruli from birth to maturity, which is promising in terms of providing new insights for research on kidney development and function.

Abstract In modular multilevel converters (MMCs), the huge capacitor almost takes over half of the cost and weight of a submodule; as a result, the capacitance requirement reduction has attracted wide attention for using smaller capacitors. However, the existing methods have side effects, such as increasing the arm current and adding additional semiconductors, which restrict their practical applications. Thus, a side‐effect‐free capacitance requirement reduction (CRR) method is proposed in this paper. In the method, the capacitor voltage can be decreased by injecting a specific dc signal into the original control system; and the specific dc signal is outputted from the proposed CRR controller according to the transmitted power of the MMC. For ensuring the safe operation, the extent to which the capacitor voltage can be reduced is also studied; and an optimisation model is presented to obtain the minimum allowed capacitor voltage and the safety domain of CRR. The effectiveness of the proposed method is proved by both simulation and experiment. The results show that the capacitance requirement can be reduced by 32.4% without neither increasing the arm current nor adding additional semiconductors.

Abstract Immune checkpoint inhibitors (ICIs) have become a new hope for many patients with advanced cancer by blocking tumour immune evasion. However, with the widespread use of ICIs, immune‐related adverse events (irAEs) have also been discovered and reported increasingly. Immune‐related myocarditis, the most dangerous one of irAEs, still has high mortality in the context of the current treatment. We report the case of a 60‐year‐old female with fulminant myocarditis induced by ICIs, which caused her to experience frequent ventricular arrhythmias such as ventricular fibrillation and heart failure. She was successfully treated with current mainstream therapies for immune‐related myocarditis and additional treatment of sacubitril–valsartan and dapagliflozin. The intriguing observation that the patient condition recovered relatively rapidly in this case shows a possible treatment inspiration, which may be helpful for treating ICIs‐associated myocarditis and improving cancer patients' clinical prognosis.

African swine fever virus (ASFV) is a large and very complex DNA virus. The major capsid protein p72 is the most predominant structural protein and constitutes the outmost icosahedral capsid of the virion. In the present study, the nanobodies against ASFV p72 protein were screened from a camelid immune VHH library by phage display technique. Nine distinct nanobodies were identified according to the amino acid sequences of the complementary determining regions (CDRs), and contain typical amino acid substitutions in the framework region 2 (FR2). Six nanobodies were successfully expressed in E. coli, and their specificity and affinity to p72 protein were further evaluated. The results showed that nanobodies Nb25 had the best affinity to both recombinant and native p72 protein of ASFV. The Nb25 possesses an extremely long CDR3 with 23 amino acids compared with other nanobodies, which may allow this nanobody to access the hidden epitopes of target antigen. Furthermore, the Nb25 can specifically recognize the virus particles captured by polyclonal antibody against ASFV in a sandwich immunoassay, and its application as a biosensor to target virus in PAM cells was verified by an immunofluorescence assay. Nanobodies have been proven to possess many favorable properties with small size, high affinity and specificity, easier to produce, low costs and deep tissue penetration that make them suitable for various biotechnological applications. These findings suggest that nanobody Nb25 identified herein could be a valuable alternative tool and has potential applications in diagnostic and basic research on ASFV.

AimsAt present, the effects of Glucagon-Like Peptide 1 Receptor agonists (GLP-1RAs) on arrhythmia in patients with type 2 diabetes mellitus (T2DM) and myocardial infarction (MI) are still unclear. Hence, this systematic review and meta-analysis aimed to investigate this association.Methods and resultsPubMed, Embase, Cochrane Library, and Web of Science were searched from inception to 30 April 2022. Randomized controlled trials (RCTs) that compared GLP-1RAs with placebo and met the critical criterion of a proportion of patients with T2DM and MI > 30% were included to verify our purpose indirectly. The outcomes of interest included atrial arrhythmias, ventricular arrhythmias, atrioventricular block (AVB), sinus arrhythmia, and cardiac arrest. Relative risk (RR) and 95% confidence intervals (CI) were pooled using a random-effects model. We included five RCTs with altogether 31,314 patients. In these trials, the highest proportion of patients with T2DM and MI was 82.6%, while the lowest was 30.7%. Compared to placebo, GLP-1RAs were associated with a lower risk of atrial arrhythmias (RR 0.81, 95% CI 0.70–0.95). There was no significant difference in the risk of ventricular arrhythmias (RR 1.26, 95% CI 0.87–1.80), AVB (RR 0.95, 95% CI 0.63–1.42), sinus arrhythmia (RR 0.62, 95% CI 0.26–1.49), and cardiac arrest (RR 0.97, 95% CI 0.52–1.83) between groups.ConclusionGLP-1RAs may be associated with reduced risk for atrial arrhythmias, which seems more significant for patients with T2DM combined with MI. More studies are needed to clarify the definitive anti-arrhythmic role of this drug.

Abstract Background Overcrowding, abuse of antibiotics and increasing antimicrobial resistance negatively affect neonatal survival rates in developing countries. We aimed to define pathogens and their antimicrobial resistance (AMR) of early-onset sepsis (EOS), hospital-acquired late-onset sepsis (HALOS) and community-acquired late-onset sepsis (CALOS) in 25 neonatal intensive care units (NICUs) in China. Study design This retrospective descriptive study included pathogens and their AMR from all neonates with bloodstream infections (BSIs) admitted to 25 tertiary hospitals in China from January 1, 2017, and December 31, 2019. We defined EOS as the occurrence of BSI at or before 72 h of life and late-onset sepsis (LOS) if BSI occurred after 72 h of life. LOS were classified as CALOS if occurrence of BSI was ≤ 48 h after admission, and HALOS, if occurrence was > 48 h after admission. Results We identified 1092 pathogens of BSIs in 1088 infants from 25 NICUs. Thirty-two percent of all pathogens were responsible for EOS, 64.3% HALOS, and 3.7% CALOS. Gram-negative (GN) bacteria accounted for a majority of pathogens in EOS (56.7%) and HALOS (62.2%). The most frequent pathogens causing EOS were Escherichia coli (27.2%) and group B streptococcus (GBS; 14.6%) whereas in CALOS they were GBS (46.3%) and Staphylococcus aureus (41.5%). Klebsiella pneumoniae (27.9%), Escherichia coli (15.7%) and Fungi (12.8%) were the top three isolates in HALOS. Third-generation cephalosporin resistance rates in GN bacteria ranged from 9.7 to 55.6% in EOS and 26% to 63.3% in HALOS. Carbapenem resistance rates in GN bacteria ranged from 2.7 to 31.3% in HALOS and only six isolates in EOS were carbapenem resistant. High rates of multidrug resistance were observed in Klebsiella pneumoniae (60.7%) in HALOS and in Escherichia coli (44.4%) in EOS. All gram-positive bacteria were susceptible to vancomycin except for three Enterococcus faecalis in HALOS. All-cause mortality was higher among neonates with EOS than HALOS (7.4% VS 4.4%, [OR] 0.577, 95% CI 0.337–0.989; P = 0.045). Conclusions Escherichia coli, Klebsiella pneumoniae and GBS were the leading pathogens in EOS, HALOS and CALOS, respectively. The high proportion of pathogens and high degree of antimicrobial resistance in HALOS underscore understanding of the pathogenesis and emphasise the need to devise effective interventions in developing countries.

The formation of adventitious roots (ARs) is vital for the vegetative propagation of poplars. However, the relevant mechanisms remain unclear. To reveal the underlying molecular mechanism, we used RNA-seq to investigate the transcriptional alterations of poplar cuttings soaked in water for 0, 2, 4, 6, 8, and 10 d; 3,798 genes were differentially expressed at all the time points, including 2,448 upregulated and 1,350 downregulated genes. Biological processes including “cell cycle,” “photosynthesis,” “regulation of hormone levels,” and “auxin transport” were enriched in the differentially expressed genes (DEGs). KEGG results showed that the common DEGs were most enriched in the pathway of “Carbon fixation in photosynthetic organisms” and “Starch and sucrose metabolism.” We further dissected 38 DEGs related to root and auxin, including two lateral root primordium 1 (LRP1), one root meristem growth factor (RGF9), one auxin-induced in the root (AIR12), three rooting-associated genes (AUR1 and AUR3), eight auxin transcription factors (ARFs and LBDs), 10 auxin respective genes (SAURs and GH3s), nine auxin transporters (PINs, ABCs, LAX2, and AUXs), and four auxin signal genes (IAAs and TIR1). We found that the rooting abilities of poplar cuttings with and without leaves are different. By applying different concentrations of IBA and sucrose to the top of cuttings without leaves, we found that 0.2 mg/ml IBA and 2 mg/ml sucrose had the best effect on promoting AR formation. The transcriptome results indicated photosynthesis may influence AR formation in poplar cuttings with leaves and revealed a potential regulatory mechanism of leafy cuttage from poplar cuttings. In addition, we provided a new perspective to resolve rooting difficulties in recalcitrant species.

ABSTRACT African swine fever (ASF), an acute, severe, highly contagious disease caused by African swine fever virus (ASFV) infection in domestic pigs and boars, has a mortality rate of up to 100%. Because effective vaccines and treatments for ASF are lacking, effective control of the spread of ASF remains a great challenge for the pig industry. Host epigenetic regulation is essential for the viral gene transcription. Bromodomain and extraterminal (BET) family proteins, including BRD2, BRD3, BRD4, and BRDT, are epigenetic “readers” critical for gene transcription regulation. Among these proteins, BRD4 recognizes acetylated histones via its two bromodomains (BD1 and BD2) and recruits transcription factors, thereby playing a pivotal role in transcriptional regulation and chromatin remodeling during viral infection. However, how BET/BRD4 regulates ASFV replication and gene transcription is unknown. Here, we randomly selected 12 representative BET family inhibitors and compared their effects on ASFV infection in pig primary alveolar macrophages (PAMs). These were found to inhibit viral infection by interfering viral replication. The four most effective inhibitors (ARV-825, ZL0580, I-BET-762, and PLX51107) were selected for further antiviral activity analysis. These BET/BRD4 inhibitors dose dependently decreased the ASFV titer, viral RNA transcription, and protein production in PAMs. Collectively, we report novel function of BET/BRD4 inhibitors in inducing suppression of ASFV infection, providing insights into the role of BET/BRD4 in the epigenetic regulation of ASFV and potential new strategies for ASF prevention and control. IMPORTANCE Due to the continuing spread of the ASFV in the world and the lack of commercial vaccines, the development of improved control strategies, including antiviral drugs, is urgently needed. BRD4 is an important epigenetic factor and has been commonly used for drug development for tumor treatment. Furthermore, the latest research showed that BET/BRD4 inhibition could suppress replication of virus. In this study, we first showed the inhibitory effect of agents targeting BET/BRD4 on ASFV infection with no significant host cytotoxicity. Then, we found four BET/BRD4 inhibitors that can inhibit ASFV replication, RNA transcription, and protein synthesis. Our findings support the hypothesis that BET/BRD4 can be considered as attractive host targets in antiviral drug discovery against ASFV.

It is a complicated task to right a capsized ship on the sea bottom because of wave load. Based on the influence of waves on stability and mechanical action, this paper constructs a wave force calculation model by the airy wave theory, and the stability and righting force models of righting a grounded and capsized ship are obtained. The uprighting process of a grounded and capsized ship is simulated by GHS software. In the process, stability and righting force are solved, and the effect of wave parameters on stability and mechanical action is studied. The result shows that when the wave phase is at its origin, the stability and the righting force can be effectively reduced. The wavelength has a significant effect on the hull stability, righting force and ground force in the range of 25 m–35 m. The change of wave height has significant influence on the stability and ground force, but the maximum ground force does not always change regularly with the wave height. Variation of the angle between the hull and the direction of the wave could significantly affect the stability, righting force, and ground force. When the encounter angle is 90°, the righting force is smaller than in other cases, and the maximum negative-going stability, the maximum righting force, and the maximum ground force values are 7.1%, 7.57%, and 3.83%, respectively, 11.7% smaller than those of still water. It is found by comparing several groups of wave parameters that a transverse wave could significantly reduce the difficulty of righting a grounded and capsized ship.

The downwash airflow generated by the rotors can enhance the penetration of pesticide droplets, allowing them to penetrate deeper into the canopy and more comprehensively control pests. Downwash air will produce a “wind vortex” in plant canopy, and the parameters of a “wind vortex” represent the effect of pesticide deposition to a certain extent. To obtain the corresponding relationship between wind vortices and flight parameters and control the effect of pesticide spraying, this paper carried out unmanned aerial vehicle (UAV) flight experiments in the field. Wind vortices were generated in rice canopy by downwash airflow, and the parameters of wind vortices were obtained by identifying wind-vortex images using the inter-frame difference method. The wind-vortex parameter control model was established, which can calculate the altitude and speed of the UAV when applying pesticide according to the target wind-vortex parameter. The deviations in the altitude were determined to be 0.67 and 0.43 m, and the deviations in the speed were 0.29 and 0.35 m/s during downwind and headwind UAV operations, respectively. The model relation functions were established, and their accuracies were found to be 97.1%, 92.3%, 69%, and 58% (downwind), and 97%, 78.4%, 62%, and 57% (upwind), respectively, indicating that downwind UAV operation leads to a clear relation between the wind-vortex parameters and the UAV-flight parameters. The model establishes the corresponding relationship between the wind-vortex parameters and flight parameters, which provides a theoretical basis for studying the precise application control method of UAV.

Plant protection drones are commonly encountered in agricultural fields. Their downwash airflow can agitate flexible crops (e.g., rice and wheat) or even cause wind-induced losses. To predict the wind-induced responses of rice under wind fields, herein, a wind-induced rice response model (RWRM) was proposed using the finite element method. With the RWRM, the rice displacement and critical wind speed (CWS) were calculated at different wind speeds, considering the morphological and mechanical properties of rice, and the accuracy was experimentally verified and compared to that of an existing model. The results indicated that the mean paired difference and mean error in rice displacement amplitude prediction under 2~5 m/s wind speeds were 13.48 mm and 42.46 mm, respectively, and the predicted and measured values were highly correlated at the 1% significance level. Moreover, the CWS values for four rice species could be calculated with the model with an average of 3.57 m/s, and the difference between the simulated and theoretical values was 0.368. The strength of the wind-induced rice responses was primarily correlated with the mechanical properties, and to a lesser extent the morphology. The rice yield has a negative correlation with rice responses. Within a certain range, a bigger displacement and lower CWS could result in a higher rice yield. The RWRM achieved favorable modeling accuracy for the wind-induced responses of rice and could provide a simulation reference for balancing the wind-induced loss and rice yield.

The properties of crushing and absorbing energy are important for the security of automobiles. In this work, the crushing curves and section features of Al–Zn–Mg alloy twin-cell thin-walled profiles were studied in detail. The crushing process comprises four typical stages: near-elastic deformation, hinge forming, hinge tightening, and folding stages. It was found that, in the near-elastic stage, the relationship between crushing force and displacement is approximately linear. The crushing moment in the hinge-forming stage conforms to the principle of conservation. The crush curve in the hinge-tightening stage conforms to the cosine hypothesis. The folding stage involves a repetition of the hinge-forming and hinge-tightening stages. Moreover, numerical models of these stages are built and compared with measured data to demonstrate the accuracy and validity of these models.

This study presents a strategy to reduce the capacitance of the submodule (SM) capacitor of a modular multilevel converter-based medium-voltage wind power converter. The design of the SM capacitor of the modular multilevel converter (MMC) should consider the actual operating conditions, especially the influence of wind speed, because wind speed will affect the voltage ripple and voltage amplitude of the SM capacitor. In the traditional method, the capacitance design of the SM capacitor will be based on relatively high wind speed and leave a certain safety margin. However, in most cases, the system operates at the highest-frequency wind speed (HFWS). For the MMC-based wind energy conversion system, a constant capacitor voltage ripple (CCVR) control method is proposed. Using this method, the SM capacitor voltage ripple can be significantly reduced by injecting the second harmonic component of circulating current. In this way, the SM capacitor with smaller capacitance can be used. Finally, the effectiveness of the proposed method is validated in RT-Lab Platform.

Abstract Background It has been known for years that the same genetic defects drive breast cancer formation, yet, the onset of breast cancer in different individuals among the same population differs greatly in their life spans with unknown mechanisms. Methods We used a MMTV-PyMT mouse model with different genetic backgrounds (FVB/NJ vs. C57BL/6J) to generate different cancer onset phenotypes, then profiled and analyzed the gene expression of three tumor stages in both Fvb.B6 and Fvb mice to explore the underlying mechanisms. Results We found that in contrast with the FVB/N-Tg (MMTV-PyMT) 634Mul mice (Fvb mice), mammary tumor initiation was significantly delayed and tumor progression was significantly suppressed in the Fvb.B6 mice (generated by crossing FVB/NJ with C57BL/6J mice). Transcriptome sequencing and analysis revealed that the differentially expressed genes were enriched in immune-related pathways. Flow cytometry analysis showed a higher proportion of matured dendritic cells in the Fvb.B6 mice. The plasma levels of interleukin-6 (IL-6) and vascular endothelial growth factor (VEGF) were significantly reduced in the Fvb.B6 mice. IL-6 also impaired the maturation of bone marrow dendritic cells (BMDCs) of the Fvb mice in vitro. Conclusion All these findings suggest that immunity levels (characterized by a reduced IL-6 level and intact DC maturation in Fvb.B6 mice) are the key factors affecting tumor onset in a murine mammary cancer model.

The solving of quadratic matrix equations is a fundamental issue which essentially exists in the optimal control domain. However, noises exerted on the coefficients of quadratic matrix equations may affect the accuracy of the solutions. In order to solve the time-varying quadratic matrix equation problem under linear noise, a new error-processing design formula is proposed, and a resultant novel zeroing neural network model is developed. The new design formula incorporates a second-order error-processing manner, and the double-integration-enhanced zeroing neural network (DIEZNN) model is further proposed for solving time-varying quadratic matrix equations subject to linear noises. Compared with the original zeroing neural network (OZNN) model, finite-time zeroing neural network (FTZNN) model and integration-enhanced zeroing neural network (IEZNN) model, the DIEZNN model shows the superiority of its solution under linear noise; that is, when solving the problem of a time-varying quadratic matrix equation in the environment of linear noise, the residual error of the existing model will maintain a large level due to the influence of linear noise, which will eventually lead to the solution’s failure. The newly proposed DIEZNN model can guarantee a normal solution to the time-varying quadratic matrix equation task no matter how much linear noise there is. In addition, the theoretical analysis proves that the neural state of the DIEZNN model can converge to the theoretical solution even under linear noise. The computer simulation results further substantiate the superiority of the DIEZNN model in solving time-varying quadratic matrix equations under linear noise.

Small RNAs (sRNAs), particularly microRNAs (miRNAs), are functional molecules that modulate mRNA transcripts and have been implicated in the etiology of various types of cancer. Cold atmospheric plasma (CAP) is a physical technology widely used in the field of cancer treatment after exhibiting extensive lethality on cancer cells. However, few studies have reported the exact role of miRNAs in CAP-induced anti-cancer effects. The aim of the present study was to determine whether miRNAs are involved in CAP-induced cytotoxicity by using high-throughput sequencing. Our research demonstrated that 28 miRNAs were significantly changed (17 upregulated and 11downregulated) following 24 h of treatment with a room-temperature argon plasma jet for 90 s compared with that of the untreated group in human chronic myeloid leukemia K562 cells. GO enrichment analysis revealed that these target genes were related to cell organelles, protein binding, and single-organism processes. Furthermore, KEGG pathway analysis demonstrated that the target genes of differentially expressed miRNAs were primarily involved in the cAMP signaling pathway, AMPK signaling pathway, and phosphatidylinositol signaling system. Taken together, our study demonstrated that CAP treatment could significantly alter the small RNA expression profile of chronic myeloid leukemia cells and provide a novel theoretical insight for elucidating the molecular mechanisms in CAP biomedicine application.

Aquaporins (AQPs) are important functional proteins and are widely present in the cell membrane of almost all organisms, mediating transmembrane transport of liquid and other solutes. Much is known about the molecular characterization of AQPs in other tick species; however, nothing is known about them in Haemaphysalis qinghaiensis. In this study, we first sequenced the transcript variants of AQPs in H. qinghaiensis (HqAQPs), analyzed the biological structure features of AQPs, and investigated the pattern of gene expression of the AQP gene of H. qinghaiensis in different tick tissues and stages to predict their biological functions. In conclusion, four AQP transcript variants (i.e., HqAQP1-1, HqAQP1-2, HqAQP1-3, and HqAQP1-4) of H. qinghaiensis were found, and the sequences were comparable with its orthologs from the reported tick species. Gene expression of AQPs in different tick tissues and stages showed the higher expression level in salivary glands and gut of adult female, as well as in the female and nymph than in Malpighian tubules, ovary, male, larvae, and egg. Further studies will be performed to evaluate the function of HqAQPs against H. qinghaiensis infestation on animals.

With the high proportional renewable energy integration and rapid increase in the DC loads, such as the electric vehicle and distributed energy storage, the DC distribution system becomes a prospective solution for the urban power grid enhancement for its high-efficiency and eco-friendly nature. In most DC distribution systems, power interfaces are applied to connect low-voltage DC (LVDC) distribution systems with multiple medium-voltage (MV) systems in order to improve the operating reliability and economy. Compared to other types of multiports power interfaces, the three-port-isolated modular multilevel converter (I-M2C) has shown many advantages, including low cost, high power density, and low control complexity. However, the I-M2C cannot handle the power imbalance at the bipolar LVDC port like the other MMC-based three-port power interfaces, which limits the operating range and decreases the stability of the I-M2C in bipolar LVDC application. In order to solve the bipolar imbalance problems, a novel balance control method is proposed in this article. The proposed balance control method is based on symmetrical decomposition. By decoupling the MV power control and the LV bipolar power compensation control, the proposed method can eliminate the bipolar voltage deviation under different working conditions. The simulation results prove the validity and good control performance of the proposed method.

To address the problems of difficult leveling and poor stability of hill crawler tractors, an attitude adjustment device based on a parallel four-bar mechanism was designed, and the mechanical reasons for the sideslip instability of hill crawler tractors were analyzed. On this basis, a posture adjustment mechanism based on a parallel four-bar mechanism was proposed, and the structure of the complete attitude adjustment device was designed. To ensure that this device meets the strength requirements during operation, a mechanical analysis of the key components (active rocker and slave rocker) was carried out to accommodate the load during leveling. Based on ANSYS software, a finite element simulation analysis was used to determine the maximum stress position of the active and slave rockers. Finally, to verify the accuracy of the above simulation analysis results and determine the influence rules of the lateral slope angle, longitudinal slope angle and loading quality on the abovementioned maximum stress, a physical model test bench of the attitude adjustment device was built. An orthogonal regression experiment was carried out with the maximum stresses of the active and slave rockers as the test indices. The experimental data were analyzed by Design-Expert 10 software, and the results show that the order of the primary and secondary factors influencing the maximum stress of the active rocker was the loading mass, lateral slope angle and longitudinal slope angle. The order of the factors influencing the maximum stress of the slave rocker was the longitudinal slope angle, lateral slope angle and loading mass. The active and slave rockers meet the strength requirements. This work provides technical support for the production of hill crawler tractor physical prototypes.

With the rapid development of technologies such as big data and cloud computing, data communication and data computing in the form of exponential growth have led to a large amount of energy consumption in data centers. Globally, data centers will become the world’s largest users of energy consumption, with the ratio rising from 3% in 2017 to 4.5% in 2025. Due to its unique climate and energy-saving advantages, the high-latitude area in the Pan-Arctic region has gradually become a hotspot for data center site selection in recent years. In order to predict and analyze the future energy consumption and carbon emissions of global data centers, this paper presents a new method based on global data center traffic and power usage effectiveness (PUE) for energy consumption prediction. Firstly, global data center traffic growth is predicted based on the Cisco’s research. Secondly, the dynamic global average PUE and the high latitude PUE based on Romonet simulation model are obtained, and then global data center energy consumption with two different scenarios, the decentralized scenario and the centralized scenario, is analyzed quantitatively via the polynomial fitting method. The simulation results show that, in 2030, the global data center energy consumption and carbon emissions are reduced by about 301 billion kWh and 720 million tons CO2 in the centralized scenario compared with that of the decentralized scenario, which confirms that the establishment of data centers in the Pan-Arctic region in the future can effectively relief the climate change and energy problems. This study provides support for global energy consumption prediction, and guidance for the layout of future global data centers from the perspective of energy consumption. Moreover, it provides support of the feasibility of the integration of energy and information networks under the Global Energy Interconnection conception.

Abstract Background Discovering a highly accurate and robust gene signature for the prediction of breast cancer metastasis from gene expression profiling of primary tumors is one of the most challenging tasks to reduce the number of deaths in women. Due to the limited success of gene-based features in achieving satisfactory prediction accuracy, many methodologies have been proposed in recent years to develop network-based features by integrating network information with gene expression. However, evaluation results are inconsistent to confirm the effectiveness of network-based features, because of many confounding factors involved in classification model learning process, such as data normalization, dimension reduction, and feature selection. An unbiased comparative evaluation is essential for uncovering the strength of network-based features. Methods In this study, we compared several types of network-based features obtained using different mathematical operators (Mean, Maximum, Minimum, Median, Variance) on geneset (i.e., a gene and its’ neighbors in the network) in protein-protein interaction network and gene co-expression network for their ability in predicting breast cancer metastasis using gene expression data from more than 10 patient cohorts. Results While network-based features are usually statistically more significant than gene-based feature, a consistent improvement of prediction performance using network-based features requires a substantial number of patients in the dataset. In contrary to many previous reports, no evidence was found to support the robustness of network-based features and we argue some of the robustness may be due to the inherent bias associated with node degree in the network. In addition, different types of network features seem to cover different pathways and are complementary to each other. Consequently, an ensemble classifier combining different network features was proposed and was found to significantly outperform classifiers based on gene-based feature or any single type of network-based features. Conclusions Network-based features and their combination show promise for improving the prediction of breast cancer metastasis but may require a large amount of training data. Robustness claim of network-based features needs to be re-examined with network node degree and other confounding factors in consideration.

Abstract Background Anaplasma ovis is a gram-negative, tick-borne obligate intraerythrocytic pathogen, which causes ovine anaplasmosis in small ruminants worldwide. VirB10 of A. ovis is an integral component of the Type IV Secretion System (T4SS). The T4SS is used by bacteria to transfer DNA and/or proteins undeviatingly into the host cell to increase their virulence. To more thoroughly understand the interaction between A. ovis and Dermacentor silvarum, a vector containing the virb10 gene of A. ovis was used as a bait plasmid to screen interacting proteins from the cDNA library of the D. silvarum salivary gland using the yeast two-hybrid system. Methods The cDNA of the D. silvarum salivary gland was cloned into the pGADT7-SmaI vector (prey plasmid) to construct the yeast two-hybrid cDNA library. The virb10 gene was cloned into the pGBKT7 vector to generate a bait plasmid. Any gene auto-activation or toxicity effects in the yeast strain Y2HGold were excluded. The screening was performed by combining the bait and prey plasmids in yeast strains to identify positive preys. The positive preys were then sequenced, and the obtained sequences were subjected to further analyses using Gene Ontology, UniProt, SMART, and STRING. Additionally, the interaction between the bait and the prey was evaluated using the glutathione S-transferase (GST) pull-down assay. Results A total of two clones were obtained from the cDNA library using the yeast two-hybrid system, and the sequence analysis showed that both clones encoded the same large tegument protein, UL36. Furthermore, the proteins GST-UL36 and His-VirB10 were successfully expressed in vitro and the interaction between the two proteins was successfully demonstrated by the GST pull-down assay. Conclusions To our knowledge, this study is the first to screen for D. silvarum salivary gland proteins that interact with A. ovis VirB10. The resulting candidate, UL36, is a multi-functional protein. Further investigations into the functionality of UL36 should be carried out, which might help in identifying novel prevention and treatment strategies for A. ovis infection. The present study provides a base for exploring and further understanding the interactions between A. ovis and D. silvarum.

Design optimization of structure and control combined systems are coupled problems. The conventional sequential design strategy (structure design sequentially followed by control design) usually neglects the coupling effects between structure and control and can only produce sub-optimal designs of the complex systems. Nevertheless, simultaneous design strategy with a reasonable and explicit optimization iteration management can ensure global optimization designs of the coupled system. In this study, a surrogate based co-design is explored to achieve the simultaneous optimization, which transforms continuous optimal control problems into discrete nonlinear programming problems. The discrete control parameters combining with the structure parameters can be simultaneously optimized and the co-design strategy can be achieved by introducing necessary and reasonable dynamic constraints. Here, the proposed surrogate based co-design is tested using a practical engineering case study, a heavy-load face-shovel excavator (FSE). The case study is built upon existing FSE design problems by incorporating detailed structure and control design variables while satisfying the system dynamic equations. The proposed surrogate based co-design is implemented and compared with the conventional sequential design strategy and an existing co-design strategy. Results indicate that the surrogate based co-design is accurate and efficient enough to achieve better performances than the conventional sequential design strategy by making FSE's structure more compact with relatively small vibrations.

Abstract Background Bovine babesiosis is caused by protozoan parasites of the genus Babesia and presents a wide spectrum of clinical manifestations. Disease severity depends on the type of Babesia species infection. Generally, B. bovis and B. bigemina are considered as the causative agents of bovine babesiosis; in addition, Babesia ovata and B. major are a group of benign bovine piroplasms. Therefore, species identification is important for diagnosis, epidemiological investigations and follow-up management. Methods Real-time PCR combined with high resolution melting (RT-PCR-HRM) analysis was used to detect and discriminate four Babesia species infective to cattle, including Babesia bovis, B. bigemina, B. major and B. ovata. The melting profiles and melting temperatures (Tm) of the amplicon targeting 18S rRNA revealed differences that can discriminate the four Babesia spp. Sensitivity and specificity of the analytical method were evaluated using 50 blood samples collected from experimentally infected cattle and 240 blood samples from areas where bovine babesiosis is an issue. Results RT-PCR-HRM analysis allowed to detect and discriminate four Babesia spp. (B. bovis, B. bigemina, B. major and B. ovata), which were responsible for bovine babesiosis in China. The protocol was validated with DNA samples from experimentally infected cattle and field infection in cattle. Conclusions Our results indicate that RT-PCR-HRM is a fast and robust tool for the simultaneous detection and discrimination of four Babesia species that are responsible for bovine babesiosis in China. This approach is applicable for both field and experimental samples, thus it could be useful in epidemiological investigations and diagnoses of bovine babesiosis.

Abstract Background MicroRNA-mediated gene regulatory networks play a significant role in plant growth and development and environmental stress responses. Results We identified 79 microRNAs (miRNAs) and multiple miRNA variants (isomiRs) belonging to 26 miRNA families in the primary root growth zone of maize seedlings grown at one of three water potentials: well-watered (− 0.02 MPa), mild water deficit stress (− 0.3 MPa), and severe water deficit stress (− 1.6 MPa). The abundances of 3 miRNAs (mild stress) and 34 miRNAs representing 17 families (severe stress) were significantly different in water-deficit stressed relative to well-watered controls (FDR

African swine fever virus (ASFV) infection can result in lethal disease in pigs. ASFV encodes 150-167 proteins, of which only approximately 50 encoded viral structure proteins are functionally known. ASFV also encodes some nonstructural proteins that are involved in the regulation of viral transcription, viral replication and evasion from host defense. However, the understanding of the molecular correlates of the severity of these infections is still limited. The purpose of this study was to compare host and viral gene expression differences and perform functional analysis in acutely infected, dead and cohabiting asymptomatic pigs infected with ASFV by using RNA-Seq technique; healthy pigs were used as controls. A total of 3,760 and 2,874 upregulated genes and 4,176 and 2,899 downregulated genes were found in healthy pigs vs. acutely infected, dead pigs or asymptomatic pigs, respectively. Additionally, 941 upregulated genes and 956 downregulated genes were identified in asymptomatic vs. acutely infected, dead pigs. Different alternative splicing (AS) events were also analyzed, as were gene chromosome locations, and protein-protein interaction (PPI) network prediction analysis was performed for significantly differentially expressed genes (DEGs). In addition, 30 DEGs were validated by RT-qPCR, and the results were consistent with the RNA-Seq results. We further analyzed the interaction between ASFV and its host at the molecular level and predicted the mechanisms responsible for asymptomatic pigs based on the selected DEGs. Interestingly, we found that some viral genes in cohabiting asymptomatic pigs might integrate into host genes (DP96R, I73R and L83L) or remain in the tissues of cohabiting asymptomatic pigs. In conclusion, the data obtained in the present study provide new evidence for further elucidating ASFV-host interactions and the ASFV infection mechanism and will facilitate the implementation of integrated strategies for controlling ASF spread.

As a bimetal oxide, partial zinc stannate (ZnSnO3) is one of the most promising next-generation lithium anode materials, which has the advantages of low operating voltage, large theoretical capacity (1,317 mA h g−1), and low cost. However, the shortcomings of large volume expansion and poor electrical conductivity hinder its practical application. The core-shell ZnSnO3@ nitrogen-doped carbon (ZSO@NC) nanocomposite was successfully obtained by coating ZnSnO3 with polypyrrole (PPy) through in situ polymerization under ice-bath conditions. Benefiting from this unique compact structure, the shell formed by PPy cannot only effectively alleviate the volume expansion effect of ZnSnO3 but also enhance the electrical conductivity, thus, greatly improving the lithium storage performance. ZSO@NC can deliver a reversible capacity of 967 mA h g−1 at 0.1 A g−1 after 300 cycles and 365 mA h g−1 at 2 A g−1 after 1,000 cycles. This work may provide a new avenue for the synthesis of bimetal oxide with a core–shell structure for high-performance energy storage materials.

Glaucoma is the second-most-blinding eye disease in the world and accurate segmentation of the optic disc (OD) and optic cup (OC) is essential for the diagnosis of glaucoma. To solve the problems of poor real-time performance, high algorithm complexity, and large memory consumption of fundus segmentation algorithms, a lightweight segmentation algorithm, GlauNet, based on convolutional neural networks, is proposed. The algorithm designs an efficient feature-extraction network and proposes a multiscale boundary fusion (MBF) module, which greatly improves the segmentation efficiency of the algorithm while ensuring segmentation accuracy. Experiments show that the algorithm achieves Dice scores of 0.9701/0.8959, 0.9650/0.8621, and 0.9594/0.8795 on three publicly available datasets—Drishti-GS, RIM-ONE-r3, and REFUGE-train—for both the optic disc and the optic cup. The number of model parameters is only 0.8 M, and it only takes 13 ms to infer an 800 × 800 fundus image on a GTX 3070 GPU.

The precise path-tracking control of tractors and trailers is the key to realizing agricultural automation. In order to improve the path-tracking control accuracy and driving stability of orchard traction spraying robots, this study proposed a navigation path-tracking control algorithm based on Double Deep Q-Network (Double DQN). Drawing on the driver’s driving experience and referring to the principle of radar scanning and the principle of image recognition, a virtual radar model was constructed to generate a virtual radar map. The virtual radar map was used to describe the position relationship between the traction spraying robot and the planned path. Combined with the deep reinforcement learning method, all possible robot driving actions under the current virtual radar map were scored, and the best driving action was selected as the output of the network. In this study, a path-tracking algorithm was self-developed with a deep Q-network trained by driving the traction spraying robot in a simulated virtual environment. The algorithm was tested in both simulations and in a field to follow a typical ‘U’-shaped path. The simulation results showed that the proposed algorithm was able to achieve accurate path-tracking control of the spraying trailer. The field tests showed that when the vehicle speed was 0.36 m/s and 0.75 m/s, the maximum lateral deviation of the algorithm was 0.233 m and 0.266 m, the average lateral deviation was 0.071 m and 0.076 m, and the standard deviation was 0.051 m and 0.057 m, respectively. Compared with the algorithm based on the virtual radar model, the maximum lateral deviation was reduced by 56.37% and 51.54%, the average lateral deviation was reduced by 7.8% and 5.0%, and the standard deviation was reduced by 20.31% and 8.1%, respectively. The results showed that the Double-DQN-based navigation path-tracking control algorithm for the traction spraying robot in the orchard had higher path-tracking accuracy and driving stability, which could meet the actual operational requirements of traditional orchards.

Ballast systems and ballast water dynamic allocation between ballast tanks are very important for ensuring the offshore operation efficiency and safety of the revolving floating crane (RFC). Its modeling and solving have multiple difficulties such as modeling complexity, solving complexity and engineering practicability. Early studies showed that domain knowledge is of great significance for the optimization of the design quality and innovation of such complex engineering issues. By analyzing the coupled operation process characteristics among the floating crane, ship hull and ballast system, a ballast water allocation optimization model based on dynamic programming strategy is established. The domain knowledge of ship ballasting is extracted, and a domain knowledge base of expert experience rules for the ballast water allocation is established. A Fuzzy-Particle Swarm Optimization (FPSO) algorithm is given to obtain the optimal allocation scheme, which uses fuzzy logic inference to process domain knowledge and improve the solving quality. Three different cases are given to illustrate the validity of the proposed model and algorithm by comparing it with other algorithms. The analysis results show that the established optimization method can effectively improve the operation efficiency and reduce the calculation time and the number of ballast tanks involved in allocation, which makes the optimal scheme more suitable for engineering applications.

While improved tumor treatment has significantly reduced the overall mortality rates, invasive progression including recurrence, therapy resistance and metastasis contributes to the majority of deaths caused by cancer. Enhancers are essential distal DNA regulatory elements that control temporal- or spatial-specific gene expression patterns during development and other biological processes. Genome-wide sequencing has revealed frequent alterations of enhancers in cancers and reprogramming of distal enhancers has emerged as one of the important features for tumors. In this review, we will discuss tumor progression-associated enhancer dynamics, its transcription factor (TF) drivers and how enhancer reprogramming modulates gene expression during cancer invasive progression. Additionally, we will explore recent advancements in contemporary technology including single-cell sequencing, spatial transcriptomics and CUT&RUN, which have permitted integrated studies of enhancer reprogramming in vivo. Given the essential roles of enhancer dynamics and its drivers in controlling cancer progression and treatment outcome, understanding these changes will be paramount in mitigating invasive events and discovering novel therapeutic targets.