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Liver cancer poses a great threat to the life safety of patients, which is a common malignant tumor worldwide. This study aims to explore the effect of miR-144 negatively regulating CCNB1 on the biological behavior of liver cancer cells, including the proliferation, apoptosis and migration of liver cancer cells, so as to provide a sufficient biological basis for the treatment of liver cancer. A 3 armour hospital at the records of 100 patients with liver cancer in 2015-2019 as the research object, and resection of the liver cancer cells and tissue adjacent to carcinoma as the research samples, using polymerase chain reaction (PCR) for the organization of miR-144 gene and detect CCNB1 protein expression level, and by using a technique called RNA interference to silence the CCNB1 gene, and try to transfer by transfection CCNB1 protein, thus all kinds of biological behaviour of hepatocellular carcinoma cells. The liver tissue of miR-144 is low, the level of gene expression CCNB1 protein expression level is higher, the expression level in liver cancer cells directly influences the curative effect of hepatocellular carcinoma patients, the miR-144 gene can negative regulation CCNB1 protein, through this kind of negative adjustment to the biological behavior of liver cancer cells have a profound impact.

In recent years, Chinese Long March (LM) launchers have experienced several launch failures, most of which occurred in their propulsion systems, and this paper studies Autonomous Mission Reconstruction (AMRC) technology to alleviate losses due to these failures. The status of the techniques related to AMRC, including trajectory and mission planning, guidance methods, and fault tolerant technologies, are reviewed, and their features are compared, which reflect the challenges faced by AMRC technology. After a brief introduction about the failure modes of engines that can occur during flight, and the fundamentals of trajectory planning and joint optimization of the target orbit and flight path, an AMRC algorithm is proposed for geostationary transfer orbit launch missions. The algorithm evaluates the residual performance onboard, and plans new objectives and corresponding flight path by iterative guidance mode or segmented state triggered optimization methods in real-time. Three failure scenarios that have occurred during previous LM missions are simulated to check the robustness of the algorithm: imminent risk of the boosters’ engines, thrust drop during the first stage of flight, and being unable to start the engine during the second stage. The payloads would fall from space according to the current design under these conditions, but they were saved with the AMRC algorithm in the simulations, which allowed the rocket to get into the target orbit as intended or the payloads were deployed in other orbits without crashing. Although spaceflight can be very unforgiving, the AMRC algorithm has the potential to avoid the total loss of a launch mission when faced with these kinds of typical failures.

Following six decades of development, the technology of launch vehicle has progressed with respect to the dual action of demand traction and technical promotion, providing increasingly valuable high-tech services for society. Currently, the development of launch vehicle is progressing with respect to stronger capabilities, higher reliability, lowering costs, flexibility, and user convenience. Retrospectively, the global development history of the launch vehicle technology can be roughly categorized into four stages with distinct characteristics of the decades.

The purpose of the guidance control is to release a payload into a prescribed target orbit (PTO) accurately. The parameters that determine an orbit are called orbital elements (OEs), which include the semi-major axis a, the eccentricity e, the argument of perigee $$\omega $$ ω , the inclination angle i, and the longitude of ascending node (LAN) or the right ascension of ascending node (RAAN) $$\Omega $$ Ω , where a and e can be converted to the perigee height $$h_p$$ h p and the apogee height $$h_a$$ h a . Thus, the guidance mission of a launcher is a typical optimal control problem with multi-terminal constraints, which requires complex iterative calculations. Considering various constraints in practical applications, such as the accuracy of inertial navigation systems and the performances of embedded computing devices (speed and storage capacity), guidance methods need to balance the mission requirements, hardware resources, and algorithm complexity. A variety of guidance methods has been developed with distinct era characteristics.

This paper proposes a guidance method for the powered soft landing of a launcher with non-cluster configured engines, for which it is difficult to maintain a low thrust-to-weight ratio (TWR) preferable for rocket recovery. For rockets in service with one or two engines rather than a cluster of engines in the boosters, it is a challenge to deeply throttle the engines to a low level, especially lower than 30%, and if one of the two engines is shut down to reduce the thrust, the attitude control is also difficult due to thrust asymmetry. The theoretical analysis and simulations show that the higher the TWR is, the smaller the feasible region for a soft landing becomes. The analysis also reveals that the bang–bang solutions of fuel-optimal methods are vulnerable to uncertainties and disturbances. A thrust regulation rate constraint is proposed or convexified to reconstruct the landing problem under high TWRs. An initial guess based on mean thrust and relaxing the initial velocity constraint is proposed, making both the adaptive collocation method and the successive convex programming applicable for real-time landing planning. Simulations under TWRs larger than four show that the proposed methods ensure a safe landing and are more adaptive than fuel-optimal solutions when facing disturbances and uncertainties.

Background: Parkinson’s disease (PD) is a common neurodegenerative disease. With the aging of the Chinese population, it is important to understand the prevalence of PD in the elderly. Objective: Little data are available on the current prevalence of PD in China. The aim of this study was to determine the prevalence of PD in Chinese individuals aged 65 years and older and to analyze associated risk factors. Methods: We performed a population-based cross-sectional survey using a multistage cluster sampling design. Residents aged 65 years and older were drawn from 11 urban districts and 10 rural counties across China. Data were entered into spreadsheets and analyzed using SPSS 24. Results: We identified 151 patients with PD among 8,124 residents aged 65 years and over, including 75 men and 76 women. The overall prevalence of PD in the study population was 1.86%, and the standardized prevalence of PD was 1.60%. The crude prevalence in men (2.12%) was higher than that in women (1.66%) and the standardized prevalence in urban areas (1.98%) was higher than that in rural areas (1.48%). Logistic regression analysis showed that independent risk factors for PD were older age, heavy metal or pesticide exposure, urban residence, rapid eye movement sleep behavior disorder, and heart disease. Conclusions: The prevalence of PD among individuals aged 65 years and older in China has remained constant. The prevalence of PD is higher in men than in women and higher in urban areas than in rural areas.

Multi-access mobile edge computing (MEC) allows each user to offload partial task bits to multiple MEC servers via multi-access radio transmission, enabling the collaboration of edge computing. By leveraging the advantage of nonorthogonal multiple access (NOMA) in improving the transmission efficiency, it is expected to effectively reduce the energy consumption of users in multi-access MEC with the aid of NOMA. However, considering the co-channel interference of NOMA and computation collaboration among MEC servers, the joint task offloading and resource allocation is a challenging problem. In this article, with the objective to minimize the weighted sum energy of users, we first propose optimal task offloading and resource allocation algorithms for the special single-user (OTORA-SU) and general multi-user (OTORA-MU) cases, by exploiting the convex and layered structure of the formulated problem. Interestingly, it is found that the single user always preferentially offloads task bits to the MEC servers with better channel gains, regardless of the computation capacity of each MEC server. Then, a low-complexity algorithm (LTORA-MU) is proposed for the general multi-user case, which converges fast and achieves near-optimal performances. Considering the channel estimation error, the impacts of imperfect channel state information (CSI) and successive interference cancellation (SIC) are also investigated. Simulation results demonstrate that for both perfect and imperfect CSI and SIC, 1) the proposed OTORA-SU and LTORA-MU outperform the local computing, full offloading, FDMA-based offloading and non-collaborative MEC schemes; 2) as the number of MEC servers grows, the ratio of offloading task bits increases while the energy consumption is decreased.

This paper introduces the sea-launch technology of a cryogenic liquid-fueled medium-lift rocket. It first reviews the current state of sea launch technology, and then gives a brief introduction of China’s New Generation Medium-lift Launch Vehicle (NGMLV). The innovations in the NGMVL, such as responsive test and launch control, a H3 launch model, and unmanned operations, provide convenience for sea launches. Based on these innovations, this paper proposes a sea launch scheme, including the system configuration, test and launch processes, and an improved adaptive design for the rocket. Then, the launch platform is discussed in detail, which integrates the functions of sea transportation, assembly and test, as well as technical and launch areas. The layout and function divisions, fluid filling, gas supply and distribution systems, and lossless storage technology of LH2 are described in order. This breakthrough in sea launch technology will enable China to launch medium and large satellites and constellations ‘both on land and sea’, especially into low-inclination Low-Earth Orbits (LEOs), and it allows China to remain competitive in the fast-paced space industry.

As a critical technology in both civil and military fields, specific emitter identification (SEI) can identify signal sources according to their various features. Existing methods on SEI are mostly based on the prior knowledge of emitters, which are powerless in the non-cooperative scenario. In order to realize the unsupervised identification, the mobile SEI method based on fingerprint set construction and feedback classification algorithm is proposed in this paper. The proposed method first divides signal fingerprints into static features and dynamic features, where the former describe the inherent features of emitters, and the latter represent the moving state features of emitters. Then, the feedback classification algorithm composed of dynamic curve fitting and back propagation (BP) neural network is applied in the classification of signals. The dynamic curve accomplishes the first classification and the results with high credibility are used to train the BP neural network which accomplishes the final classification. Simulation results demonstrate that the proposed method can complete the identification of mobile specific emitter sources in the unsupervised state with more than 95% identification rate.

This paper describes the study of a powered-coast-powered guidance reconfiguration (PCPGR) method used to solve the autonomous rescue problem for the mission profile of a launch vehicle with a coasting phase when the thrust drop fault occurs in the first powered phase (FPP) of the final stage. We first described the constraints of the final stage and the construction of the PCP guidance problem. Then we evaluated the adaptability of the guidance reconfiguration (GR) offline with numerical optimization by adjusting the constraints of the FPP, the coast phase, and the second powered phase. To determine the fault state set where the rocket can enter the prescribed target orbit through the GR initiate, we proposed a Newton method-based rapid replanning method of the transfer orbit that transforms the complex multi-flight phase trajectory planning problem into a feasible transfer orbit search problem to produce a fast solution onboard. Combined with the adaptive adjustment of the coasting time and the iterative guidance mode, we realized the autonomous online rescue of the payload. The simulation results showed that the proposed method achieved a reliable and rapid solution and improved a launch vehicle’s adaptability to a thrust drop fault.

This paper solves the problem of the on-line joint optimization of the target orbit and flight trajectory of a launch vehicle experiencing a thrust drop failure, and proposes state-triggered indices to improve the solving efficiency. The ‘highest-height index’ is triggered first to find the maximum-height circular orbit (MCO) in the orbital plane formed at the time of failure. If the orbital altitude is less than the perigee height of the prescribed target orbit, the MCO will be regarded as the optimal circular orbit to ensure safety. If not, the ‘minimal orbital plane deviations index’ is triggered to subsequently find the optimal elliptical orbit (OEO), where the orbital inclination and longitude of the ascending node are preferentially adjusted on the basis of the MCO. Furthermore, if the OEO is coplanar with the target orbit, a ‘minimal orbital shape deviations index’ is triggered to find the optimal rescue orbit, which eliminates the deviations of the perigee altitude, semi-major axis and perigee argument on the basis of the OEO. Estimation of the geocentric angle of the injection point, construction of the approximated sub-problem, and convexification processing are adopted to provide initial guesses to boost the computing. Monte Carlo simulations show that the method not only converges to the optimal or sub-optimal solution for different failure states, which avoids suspended calculations, non-convergence, and constraint violations that are common when directly solving this type of rescue problem, but also meets the basic requirements of on-line applications.

This article mainly focus on addressing the non-orthogonal multiple access (NOMA) enhanced unmanned aerial vehicle (UAV)-to-Everything (U2X) networks. A novel three dimension (3D) network for providing wireless services to randomly roaming NOMA receivers (Rxs) in the sphere space is proposed by utilizing stochastic geometry tools. In an effort to evaluate the performance of the proposed network, we first derive the closed-form expressions for the outage probability and the ergodic rate of the paired NOMA Rxs. Both the diversity orders and the high-signal-to-noise (SNR) slopes of the paired NOMA Rxs are derived. The spectrum efficiency (SE) in both the NOMA and orthogonal multiple access (OMA) enhanced U2X networks are derived. Our analytical results demonstrate that the diversity order and the high-SNR slope of the proposed network are fading parameter $m$ and one, respectively. Numerical results are provided to confirm that: i) the proposed NOMA enhanced U2X networks have superior outage performance and SE compared with the OMA enhanced U2X networks; and ii) for the case of fixed LoS probability, the outage performance of the paired NOMA Rxs mainly depends on the poorer channel conditions.

Background: The clinical application of EGFR tyrosine kinase inhibitors is always accompanied by inevitable drug resistance. However, the mechanism remains elusive. In the present study, we investigate the involvement of MAPK/SREBP1 pathway in NSCLC gefitinib resistance and evaluate the synergistic effects of shenqi fuzheng injection (SFI) and gefitinib on NSCLC cells. Methods: To investigate the MAPK/SREBP1 pathway involved in gefitinib resistance, Western blotting was used to examine p-MEK, p-ERK and SREBP1 expression in PC-9 and PC-9/GR cells, MTT was used on cell proliferation, wound healing assay was used on cell migration. To detect the cooperative effects of SFI and gefitinib, clonogenic assay was used on cell proliferation. Apoptosis assay was analyzed by flow cytometry. Immunofluorescence was used to detect gefitinib binding to EGFR. Western blotting was used to detect whether SFI regulate the resistance to gefitinib via the suppression of MAPK/SREBP1 pathway. Results: Our results showed that MAPK/SREBP1 pathway mediated resistance to gefitinib in NSCLC cells. MAPK pathway was found to directly target SREBP1 and inhibition of SREBP1 increased gefitinib sensitivity. In addition, SFI showed cooperative anti-proliferation and pro-apoptosis impacts on gefitinib resistant cells via down-regulating MAPK/SREBP1 pathway. Moreover, the combination of SFI and gefitinib enhanced gefitinib binding to EGFR resulting in the restoration of sensitivity to gefitinib. Conclusions: Taken together, MAPK/SREBP1 pathway could be regarded as the potential treatment target for overcoming resistance to EGFR-TKIs in NSCLC and adjuvant therapy of SFI could be a potential therapeutic strategy for gefitinib resistant treatment.

An online autonomous rescue strategy and the algorithm for launch vehicle are studied in the case of a thrust drop during ascending flight. First, an iterative guidance method and numerical integration are used to evaluate the remaining carrying capacity. When the target orbit is unreachable, but the lowest safe orbit could be met, an optimal rescue orbit (ORO) needs to be solved. Using the geocentric angle estimation, orbit coordinate system transformation, and convexification, the maximum-height circular orbit in the orbit plane determined by states at failure time, is found under the constraint of geocentric angle. Then, an optimal circular orbit (OCO) relaxing the above constraint is solved by the adaptive collocation method (ACM) using the former solution as initial values. Finally, a decision whether to adjust other orbital elements by comparing the height between OCO and target orbit is made. The algorithm gives priority to the orbit height, optimizes the ORO based on the objective function weights, and makes full use of the advantages of geocentric angle estimation: simplifying the terminal constraints, making the convex optimization achieve good convergence, and improving the effectiveness of the ACM under reasonable initial guess. The simulation results show that the proposed strategy and algorithm are adaptable and, convergent for onboard application.

In addition to the launch phase optimization, the trajectory optimization of the Reusable Launch Vehicle (RLV) includes the optimization of the booster landing phase. Due to the coupling relationship between the launch trajectory and the landing trajectory, it is difficult to solve a multi-phase trajectory optimization problem of RLV. To overcome the above challenge, this paper proposes a Phase-rendezvous Approach (PRA) which reconstructs the original multi-phase optimization problem to obtain the optimal solution and takes the VTVL multi-phase trajectory optimization problem as an example to carry out optimization calculations. The calculation results show that PRA successfully solves multi-phase trajectory optimization problem of RLV.

Next-generation powered descent guidance (PDG) for planetary soft landing needs multi-point-guidance capabilities. Multi-point-guidance capabilities involve two parts: landing site selection and trajectory generation. A novel multi-point PDG algorithm is presented in this study. A modified K-means clustering method and optimal sensitivity based on Interior Point OPTimizer (IPOPT) are utilized to select the fuel-optimal landing site from a list of candidate landing sites. The cluster radius is determined by offline calculation. During the selection of the fuel-optimal landing site, estimated trajectories to each candidate landing site are generated by sensitivity analysis. The optimized trajectory to the best landing site can be efficiently obtained based on a good guess of initial value provided by the estimated trajectory. Theoretical error analysis is given for the proposed guidance algorithm. Numerical results indicate that the proposed guidance algorithm can effectively and efficiently address the multi-point powered descent problem.

A joint radio and computational resource allocation problem is investigated for non-orthogonal multiple access (NOMA)-based mobile edge computing (MEC) in heterogeneous networks (HetNets). The aim is to minimize the energy consumption of all users under the task execution latency constraint with partial task offloading. Due to the non-convexity of the formulated problem, we propose an iterative algorithm by decomposing the optimization problem into two subproblems, where the computational resource allocation is a convex optimization problem, and the uplink power allocation is solved by the sequential convex programming. Simulation results reveal that the partial offloading is superior to local computing-only and full offloading-only and NOMA-based MEC outperforms the orthogonal multiple access-based MEC in HetNets.

Cellular RNA is decorated with over 170 types of chemical modifications. Many modifications in mRNA, including m6A and m5C, have been associated with critical cellular functions under physiological and/or pathological conditions. To understand the biological functions of these modifications, it is vital to identify the regulators that modulate the modification rate. However, a high‐throughput method for unbiased screening of these regulators is so far lacking. Here, we report such a method combining pooled CRISPR screen and reporters with RNA modification readout, termed CRISPR integrated gRNA and reporter sequencing (CIGAR‐seq). Using CIGAR‐seq, we discovered NSUN6 as a novel mRNA m5C methyltransferase. Subsequent mRNA bisulfite sequencing in HAP1 cells without or with NSUN6 and/or NSUN2 knockout showed that NSUN6 and NSUN2 worked on non‐overlapping subsets of mRNA m5C sites and together contributed to almost all the m5C modification in mRNA. Finally, using m1A as an example, we demonstrated that CIGAR‐seq can be easily adapted for identifying regulators of other mRNA modification., CIGAR‐seq is a new method combining pooled CRISPR screen with an epitranscriptomic reporter for identifying mRNA modification regulators. NSUN6 is discovered as a novel mRNA m5C methyltransferase, which together with NSUN2, contributes to almost all the m5C modification in mRNA.

Cellular RNA is decorated with over 170 types of chemical modifications. Many modifications in mRNA, including m6A and m5C, have been associated with critical cellular functions under physiological and/or pathological conditions. To understand the biological functions of these modifications, it is vital to identify the regulators that modulate the modification rate. However, a high-throughput method for unbiased screening of these regulators is so far lacking. Here, we report such a method combining pooled CRISPR screen and reporters with RNA modification readout, termed CRISPR integrated gRNA and reporter sequencing (CIGAR-seq). Using CIGAR-seq, we discovered NSUN6 as a novel mRNA m5C methyltransferase. Subsequent mRNA bisulfite sequencing in HAP1 cells without or with NSUN6 and/or NSUN2 knockout showed that NSUN6 and NSUN2 worked on non-overlapping subsets of mRNA m5C sites, and together contributed to almost all the m5C modification in mRNA. Finally, using m1A as an example, we demonstrated that CIGAR-seq can be easily adapted for identifying regulators of other mRNA modification.

ObjectiveTo investigate the differences in amino acid metabolism in aqueous humor of patients with cataract, according to diabetes status, using a1H-nuclear magnetic resonance approach.MethodsAqueous humor samples from patients with age-related cataract, with or without diabetes, were collected during cataract surgery. All samples underwent nuclear magnetic resonance spectra analysis to characterize their metabolic function. Potential metabolic pathways were analyzed via MetaboAnalyst 3.0.ResultsThis study included eight aqueous humor samples from patients with cataract and diabetes and eight aqueous humor samples from age- and sex-matched patients with cataract alone. Four metabolites were found to significantly differ in the aqueous humor of patients with cataract and diabetes, relative to patients with cataract alone; these metabolites were glucose (higher in patients with diabetes), valine, lysine, and tyrosine (all lower in patients with diabetes). Aminoacyl-tRNA biosynthesis was presumed to be involved in the metabolic differences observed in patients with cataract, according to diabetes status.ConclusionsThe amino acid metabolic profile in the aqueous humor differed among patients with cataract, according to diabetes status. Disturbance of amino acid metabolism in the aqueous humor may be related to cataract formation in patients with diabetes.

This paper conceive a large intelligent surface (LIS)aided multiple-input multiple-output network for providing wireless services to randomly roaming users. The network performance is analyzed by utilizing stochastic geometry tools. We aim for serving multiple users by jointly designing the passive beamforming weight at LISs and detection weight vectors at users. As a benefit, the interference imposed by the LISs can be suppressed. In an effort to evaluate the performance of the proposed network, we first derive approximated channel statistics for characterizing the effective channel gains. Then, we derive closed-form expressions for the ergodic rate of users. For gleaning further insights, we investigate the high-signal-to-noise-ratio (SNR) of ergodic rate. Our analytical results demonstrate that the specific fading environments encountered between the LISs and users have almost no impact on the ergodic rate attained.

This paper investigates a massive non-orthogonal multiple access (NOMA) enhanced Internet of Things (IoT) network. In order to provide massive connectivity, a novel cluster strategy is proposed, where massive devices can be served simultaneously. New channel statistics are derived. The exact and the asymptotic expressions in terms of coverage probability are derived. In order to obtain further engineering insights, short-packet communication scenarios are investigated. From our analysis, we show that the performance of NOMA enhanced IoT networks is capable of outperforming orthogonal multiple access (OMA) enhanced IoT networks.

PurposeThe purpose of this paper is to analyze the mechanism and filter efficacy of accumulation generation operator (AGO)/inverse accumulation generation operator (IAGO) in the frequency domain.Design/methodology/approachThe AGO/IAGO in time domain will be transferred to the frequency domain by the Fourier transform. Based on the consistency of the mathematical expressions of the AGO/IAGO in the gray system and the digital filter in digital signal processing, the equivalent filter model of the AGO/IAGO is established. The unique methods in digital signal processing systems “spectrum analysis” of AGO/IAGO are carried out in the frequency domain.FindingsThrough the theoretical study and practical example, benefit of spectrum analysis is explained, and the mechanism and filter efficacy of AGO/IAGO are quantitatively analyzed. The study indicated that the AGO is particularly suitable to act on the system's behavior time series in which the long period parts is the main factor. The acted sequence has good effect of noise immunity.Practical implicationsThe AGO/IAGO has a wonderful effect on the processing of some statistical data, e.g. most of the statistical data related to economic growth, crop production, climate and atmospheric changes are mainly affected by long period factors (i.e. low-frequency data), and most of the disturbances are short-period factors (high-frequency data). After processing by the 1-AGO, its high frequency content is suppressed, and its low frequency content is amplified. In terms of information theory, this two-way effect improves the signal-to-noise ratio greatly and reduces the proportion of noise/interference in the new sequence. Based on 1-AGO acting, the information mining and extrapolation prediction will have a good effect.Originality/valueThe authors find that 1-AGO has a wonderful effect on the processing of data sequence. When the 1-AGO acts on a data sequence X, its low-pass filtering effect will benefit the information fluctuations removing and high-frequency noise/interference reduction, so the data shows a clear exponential change trends. However, it is not suitable for excessive use because its equivalent filter has poles at the non-periodic content. But, because of pol effect at zero frequency, the 1-AGO will greatly amplify the low-frequency information parts and suppress the high-frequency parts in the information at the same time.