针对现有基于测距的集群UAV协同导航方法普遍忽略了空间构型对定位定能的影响,难以获得精确的导航定位结果,提出一种基于空间构型优选的5G集群UAV协同导航方法。构建了复杂环境下基于5G信号的UAV相对测距误差模型,基于最小几何精度因子(...针对现有基于测距的集群UAV协同导航方法普遍忽略了空间构型对定位定能的影响,难以获得精确的导航定位结果,提出一种基于空间构型优选的5G集群UAV协同导航方法。构建了复杂环境下基于5G信号的UAV相对测距误差模型,基于最小几何精度因子(geometric dilution of precision,GDOP)准则建立了协同导航节点寻优策略,实现了协同导航空间构型的实时优选;设计了基于5G测距网络的协同导航滤波器,对UAV导航信息进行在线估计和实时补偿,提高集群UAV的协同定位精度。仿真结果表明:该方法从机定位精度平均提升了约42.05%,为集群UAV实现在卫星不可用条件下的自主导航提供了一种有效的新方法。展开更多
The spread of tuberculosis(TB),especially multidrug-resistant TB and extensively drug-resistant TB,has strongly motivated the research and development of new anti-TB drugs.New strategies to facilitate drug combination...The spread of tuberculosis(TB),especially multidrug-resistant TB and extensively drug-resistant TB,has strongly motivated the research and development of new anti-TB drugs.New strategies to facilitate drug combinations,including pharmacokinetics-guided dose optimization and toxicology studies of first-and second-line anti-TB drugs have also been introduced and recommended.Liquid chromatography-mass spectrometry(LC-MS)has arguably become the gold standard in the analysis of both endo-and exo-genous compounds.This technique has been applied successfully not only for therapeutic drug monitoring(TDM)but also for pharmacometabolomics analysis.TDM improves the effectiveness of treatment,reduces adverse drug reactions,and the likelihood of drug resistance development in TB patients by determining dosage regimens that produce concentrations within the therapeutic target window.Based on TDM,the dose would be optimized individually to achieve favorable outcomes.Pharmacometabolomics is essential in generating and validating hypotheses regarding the metabolism of anti-TB drugs,aiding in the discovery of potential biomarkers for TB diagnostics,treatment monitoring,and outcome evaluation.This article highlighted the current progresses in TDM of anti-TB drugs based on LC-MS bioassay in the last two decades.Besides,we discussed the advantages and disadvantages of this technique in practical use.The pressing need for non-invasive sampling approaches and stability studies of anti-TB drugs was highlighted.Lastly,we provided perspectives on the prospects of combining LC-MS-based TDM and pharmacometabolomics with other advanced strategies(pharmacometrics,drug and vaccine developments,machine learning/artificial intelligence,among others)to encapsulate in an all-inclusive approach to improve treatment outcomes of TB patients.展开更多
Background Optimal gut health is important to maximize growth performance and feed efficiency in broiler chickens.A total of 1,365 one-day-old male Ross 308 broiler chickens were randomly divided into 5 treatments gro...Background Optimal gut health is important to maximize growth performance and feed efficiency in broiler chickens.A total of 1,365 one-day-old male Ross 308 broiler chickens were randomly divided into 5 treatments groups with 21 replicates,13 birds per replicate.The present research investigated effects of microbial muramidase or a precision glycan alone or in combination on growth performance,apparent total tract digestibility,total blood carotenoid content,intestinal villus length,meat quality and gut microbiota in broiler chickens.Treatments included:NC:negative control(basal diet group);PC:positive control(basal diet+0.02%probiotics);MR:basal diet+0.035%microbial muramidase;PG:basal diet+0.1%precision glycan;and MRPG:basal diet+0.025%MR+0.1%PG,respectively.Results MRPG group increased the body weight gain and feed intake(P<0.05)compared with NC group.Moreover,it significantly increased total serum carotenoid(P<0.05)and MRPG altered the microbial diversity in ileum contents.The MRPG treatment group increased the abundance of the phylum Firmicutes,and family Lachnospiraceae,Ruminococcaceae,Oscillospiraceae,Lactobacillaceae,Peptostreptococcaceae and decreased the abundance of the phylum Campilobacterota,Bacteroidota and family Bacteroidaceae.Compared with the NC group,the chickens fed MRPG showed significantly increased in duodenum villus length at end the trial.Conclusion In this study,overall results showed that the synergetic effects of MR and PG showed enhancing growth performance,total serum carotenoid level and altering gut microbiota composition of broilers.The current research indicates that co-supplementation of MR and PG in broiler diets enhances intestinal health,consequently leading to an increased broiler production.展开更多
Landmines continue to pose an ongoing threat in various regions around the world,with countless buried landmines affecting numerous human lives.The detonation of these landmines results in thousands of casualties repo...Landmines continue to pose an ongoing threat in various regions around the world,with countless buried landmines affecting numerous human lives.The detonation of these landmines results in thousands of casualties reported worldwide annually.Therefore,there is a pressing need to employ diverse landmine detection techniques for their removal.One effective approach for landmine detection is UAV(Unmanned Aerial Vehicle)based AirborneMagnetometry,which identifies magnetic anomalies in the local terrestrial magnetic field.It can generate a contour plot or heat map that visually represents the magnetic field strength.Despite the effectiveness of this approach,landmine removal remains a challenging and resource-intensive task,fraughtwith risks.Edge computing,on the other hand,can play a crucial role in critical drone monitoring applications like landmine detection.By processing data locally on a nearby edge server,edge computing can reduce communication latency and bandwidth requirements,allowing real-time analysis of magnetic field data.It enables faster decision-making and more efficient landmine detection,potentially saving lives and minimizing the risks involved in the process.Furthermore,edge computing can provide enhanced security and privacy by keeping sensitive data close to the source,reducing the chances of data exposure during transmission.This paper introduces the MAGnetometry Imaging based Classification System(MAGICS),a fully automated UAV-based system designed for landmine and buried object detection and localization.We have developed an efficient deep learning-based strategy for automatic image classification using magnetometry dataset traces.By simulating the proposal in various network scenarios,we have successfully detected landmine signatures present in themagnetometry images.The trained models exhibit significant performance improvements,achieving a maximum mean average precision value of 97.8%.展开更多
Crop improvement is crucial for addressing the global challenges of food security and sustainable agriculture.Recent advancements in high-throughput phenotyping(HTP)technologies and artificial intelligence(AI)have rev...Crop improvement is crucial for addressing the global challenges of food security and sustainable agriculture.Recent advancements in high-throughput phenotyping(HTP)technologies and artificial intelligence(AI)have revolutionized the field,enabling rapid and accurate assessment of crop traits on a large scale.The integration of AI and machine learning algorithms with HTP data has unlocked new opportunities for crop improvement.AI algorithms can analyze and interpret large datasets,and extract meaningful patterns and correlations between phenotypic traits and genetic factors.These technologies have the potential to revolutionize plant breeding programs by providing breeders with efficient and accurate tools for trait selection,thereby reducing the time and cost required for variety development.However,further research and collaboration are needed to overcome the existing challenges and fully unlock the power of HTP and AI in crop improvement.By leveraging AI algorithms,researchers can efficiently analyze phenotypic data,uncover complex patterns,and establish predictive models that enable precise trait selection and crop breeding.The aim of this review is to explore the transformative potential of integrating HTP and AI in crop improvement.This review will encompass an in-depth analysis of recent advances and applications,highlighting the numerous benefits and challenges associated with HTP and AI.展开更多
Lung cancer is the most common and fatal malignant disease worldwide and has the highest mortality rate among tumor-related causes of death.Early diagnosis and precision medicine can significantly improve the survival...Lung cancer is the most common and fatal malignant disease worldwide and has the highest mortality rate among tumor-related causes of death.Early diagnosis and precision medicine can significantly improve the survival rate and prognosis of lung cancer patients.At present,the clinical diagnosis of lung cancer is challenging due to a lack of effective non-invasive detection methods and biomarkers,and treatment is primarily hindered by drug resistance and high tumor heterogeneity.Liquid biopsy is a method for detecting circulating biomarkers in the blood and other body fluids containing genetic information from primary tumor tissues.Bronchoalveolar lavage fluid(BALF)is a potential liquid biopsy medium that is rich in a variety of bioactive substances and cell components.BALF contains information on the key characteristics of tumors,including the tumor subtype,gene mutation type,and tumor environment,thus BALF may be used as a diagnostic supplement to lung biopsy.In this review,the current research on BALF in the diagnosis,treatment,and prognosis of lung cancer is summarized.The advantages and disadvantages of different components of BALF,including cells,cell-free DNA,extracellular vesicles,and micro RNA are introduced.In particular,the great potential of extracellular vesicles in precision diagnosis and detection of drug-resistant for lung cancer is highlighted.In addition,the performance of liquid biopsies with different body fluid sources in lung cancer detection are compared to facilitate more selective studies involving BALF,thereby promoting the application of BALF for precision medicine in lung cancer patients in the future.展开更多
We present a quantitative measurement of the horizontal component of the microwave magnetic field of a coplanar waveguide using a quantum diamond probe in fiber format.The measurement results are compared in detail wi...We present a quantitative measurement of the horizontal component of the microwave magnetic field of a coplanar waveguide using a quantum diamond probe in fiber format.The measurement results are compared in detail with simulation,showing a good consistence.Further simulation shows fiber diamond probe brings negligible disturbance to the field under measurement compared to bulk diamond.This method will find important applications ranging from electromagnetic compatibility test and failure analysis of high frequency and high complexity integrated circuits.展开更多
Recent trends suggest that Chinese herbal medicine formulas(CHM formulas)are promising treatments for complex diseases.To characterize the precise syndromes,precise diseases and precise targets of the precise targets ...Recent trends suggest that Chinese herbal medicine formulas(CHM formulas)are promising treatments for complex diseases.To characterize the precise syndromes,precise diseases and precise targets of the precise targets between complex diseases and CHM formulas,we developed an artificial intelligence-based quantitative predictive algorithm(DeepTCM).DeepTCM has gone through multilevel model calibration and validation against a comprehensive set of herb and disease data so that it accurately captures the complex cellular signaling,molecular and theoretical levels of traditional Chinese medicine(TCM).As an example,our model simulated the optimal CHM formulas for the treatment of coronary heart disease(CHD)with depression,and through model sensitivity analysis,we calculated the balanced scoring of the formulas.Furthermore,we constructed a biological knowledge graph representing interactions by associating herb-target and gene-disease interactions.Finally,we experimentally confirmed the therapeutic effect and pharmacological mechanism of a novel model-predicted intervention in humans and mice.This novel multiscale model opened up a new avenue to combine“disease syndrome”and“macro micro”system modeling to facilitate translational research in CHM formulas.展开更多
How to effectively evaluate the firing precision of weapon equipment at low cost is one of the core contents of improving the test level of weapon system.A new method to evaluate the firing precision of the MLRS consi...How to effectively evaluate the firing precision of weapon equipment at low cost is one of the core contents of improving the test level of weapon system.A new method to evaluate the firing precision of the MLRS considering the credibility of simulation system based on Bayesian theory is proposed in this paper.First of all,a comprehensive index system for the credibility of the simulation system of the firing precision of the MLRS is constructed combined with the group analytic hierarchy process.A modified method for determining the comprehensive weight of the index is established to improve the rationality of the index weight coefficients.The Bayesian posterior estimation formula of firing precision considering prior information is derived in the form of mixed prior distribution,and the rationality of prior information used in estimation model is discussed quantitatively.With the simulation tests,the different evaluation methods are compared to validate the effectiveness of the proposed method.Finally,the experimental results show that the effectiveness of estimation method for firing precision is improved by more than 25%.展开更多
Additive Runge-Kutta methods designed for preserving highly accurate solutions in mixed-precision computation were previously proposed and analyzed.These specially designed methods use reduced precision for the implic...Additive Runge-Kutta methods designed for preserving highly accurate solutions in mixed-precision computation were previously proposed and analyzed.These specially designed methods use reduced precision for the implicit computations and full precision for the explicit computations.In this work,we analyze the stability properties of these methods and their sensitivity to the low-precision rounding errors,and demonstrate their performance in terms of accuracy and efficiency.We develop codes in FORTRAN and Julia to solve nonlinear systems of ODEs and PDEs using the mixed-precision additive Runge-Kutta(MP-ARK)methods.The convergence,accuracy,and runtime of these methods are explored.We show that for a given level of accuracy,suitably chosen MP-ARK methods may provide significant reductions in runtime.展开更多
Background:Limited research has been conducted on the influence of autophagy-associated long non-coding RNAs(ARLncRNAs)on the prognosis of hepatocellular carcinoma(HCC).Methods:We analyzed 371 HCC samples from TCGA,id...Background:Limited research has been conducted on the influence of autophagy-associated long non-coding RNAs(ARLncRNAs)on the prognosis of hepatocellular carcinoma(HCC).Methods:We analyzed 371 HCC samples from TCGA,identifying expression networks of ARLncRNAs using autophagy-related genes.Screening for prognostically relevant ARLncRNAs involved univariate Cox regression,Lasso regression,and multivariate Cox regression.A Nomogram was further employed to assess the reliability of Riskscore,calculated from the signatures of screened ARLncRNAs,in predicting outcomes.Additionally,we compared drug sensitivities in patient groups with differing risk levels and investigated potential biological pathways through enrichment analysis,using consensus clustering to identify subgroups related to ARLncRNAs.Results:The screening process identified 27 ARLncRNAs,with 13 being associated with HCC prognosis.Consequently,a set of signatures comprising 8 ARLncRNAs was successfully constructed as independent prognostic factors for HCC.Patients in the high-risk group showed very poor prognoses in most clinical categories.The Riskscore was closely related to immune cell scores,such as macrophages,and the DEGs between different groups were implicated in metabolism,cell cycle,and mitotic processes.Notably,high-risk group patients demonstrated a significantly lower IC50 for Paclitaxel,suggesting that Paclitaxel could be an ideal treatment for those at elevated risk for HCC.We further identified C2 as the Paclitaxel subtype,where patients exhibited higher Riskscores,reduced survival rates,and more severe clinical progression.Conclusion:The 8 signatures based on ARLncRNAs present novel targets for prognostic prediction in HCC.The drug candidate Paclitaxel may effectively treat HCC by impacting ARLncRNAs expression.With the identification of ARLncRNAsrelated isoforms,these results provide valuable insights for clinical exploration of autophagy mechanisms in HCC pathogenesis and offer potential avenues for precision medicine.展开更多
Objective:Some patients exhibit septic symptoms following laparoscopic surgery,leading to a poor prognosis.Effective clinical subphenotyping is critical for guiding tailored therapeutic strategies in these cases.By id...Objective:Some patients exhibit septic symptoms following laparoscopic surgery,leading to a poor prognosis.Effective clinical subphenotyping is critical for guiding tailored therapeutic strategies in these cases.By identifying predisposing factors for postoperative sepsis,clinicians can implement targeted interventions,potentially improving outcomes.This study outlines a workflow for the subphenotype methodology in the context of laparoscopic surgery,along with its practical application.Methods:This study utilized data routinely available in clinical case systems,enhancing the applicability of our findings.The data included vital signs,such as respiratory rate,and laboratory measures,such as blood sodium levels.The process of categorizing clinical routine data involved technical complexities.A correlation heatmap was used to visually depict the relationships between variables.Ordering points were used to identify the clustering structure and combined with Consensus K clustering methods to determine the optimal categorization.Results:Our study highlighted the intricacies of identifying clinical subphenotypes following laparoscopic surgery,and could thus serve as a valuable resource for clinicians and researchers seeking to explore disease heterogeneity in clinical settings.By simplifying complex methodologies,we aimed to bridge the gap between technical expertise and clinical application,fostering an environment where professional medical knowledge is effectively utilized in subphenotyping research.Conclusion:This tutorial could primarily serve as a guide for beginners.A variety of clustering approaches were explored,and each step in the process contributed to a comprehensive understanding of clinical subphenotypes.展开更多
Gastric organoids are models created in the laboratory using stem cells and sophisticated three-dimensional cell culture techniques.These models have shown great promise in providing valuable insights into gastric phy...Gastric organoids are models created in the laboratory using stem cells and sophisticated three-dimensional cell culture techniques.These models have shown great promise in providing valuable insights into gastric physiology and advanced disease research.This review comprehensively summarizes and analyzes the research advances in culture methods and techniques for adult stem cells and induced pluripotent stem cell-derived organoids,and patient-derived organoids.The potential value of gastric organoids in studying the pathogenesis of stomach-related diseases and facilitating drug screening is initially discussed.The construction of gastric organoids involves several key steps,including cell extraction and culture,three-dimensional structure formation,and functional expression.Simulating the structure and function of the human stomach by disease modeling with gastric organoids provides a platform to study the mechanism of gastric cancer induction by Helicobacter pylori.In addition,in drug screening and development,gastric organoids can be used as a key tool to evaluate drug efficacy and toxicity in preclinical trials.They can also be used for precision medicine according to the specific conditions of patients with gastric cancer,to assess drug resistance,and to predict the possibility of adverse reactions.However,despite the impressive progress in the field of gastric organoids,there are still many unknowns that need to be addressed,especially in the field of regenerative medicine.Meanwhile,the reproducibility and consistency of organoid cultures are major challenges that must be overcome.These challenges have had a significant impact on the development of gastric organoids.Nonetheless,as technology continues to advance,we can foresee more comprehensive research in the construction of gastric organoids.Such research will provide better solutions for the treatment of stomach-related diseases and personalized medicine.展开更多
Global navigation satellite system-reflection(GNSS-R)sea surface altimetry based on satellite constellation platforms has become a new research direction and inevitable trend,which can meet the altimetric precision at...Global navigation satellite system-reflection(GNSS-R)sea surface altimetry based on satellite constellation platforms has become a new research direction and inevitable trend,which can meet the altimetric precision at the global scale required for underwater navigation.At present,there are still research gaps for GNSS-R altimetry under this mode,and its altimetric capability cannot be specifically assessed.Therefore,GNSS-R satellite constellations that meet the global altimetry needs to be designed.Meanwhile,the matching precision prediction model needs to be established to quantitatively predict the GNSS-R constellation altimetric capability.Firstly,the GNSS-R constellations altimetric precision under different configuration parameters is calculated,and the mechanism of the influence of orbital altitude,orbital inclination,number of satellites and simulation period on the precision is analyzed,and a new multilayer feedforward neural network weighted joint prediction model is established.Secondly,the fit of the prediction model is verified and the performance capability of the model is tested by calculating the R2 value of the model as 0.9972 and the root mean square error(RMSE)as 0.0022,which indicates that the prediction capability of the model is excellent.Finally,using the novel multilayer feedforward neural network weighted joint prediction model,and considering the research results and realistic costs,it is proposed that when the constellation is set to an orbital altitude of 500 km,orbital inclination of 75and the number of satellites is 6,the altimetry precision can reach 0.0732 m within one year simulation period,which can meet the requirements of underwater navigation precision,and thus can provide a reference basis for subsequent research on spaceborne GNSS-R sea surface altimetry.展开更多
In this editorial,we comment on the article by Zhang et al entitled Development of a machine learning-based model for predicting the risk of early postoperative recurrence of hepatocellular carcinoma.Hepatocellular ca...In this editorial,we comment on the article by Zhang et al entitled Development of a machine learning-based model for predicting the risk of early postoperative recurrence of hepatocellular carcinoma.Hepatocellular carcinoma(HCC),which is characterized by high incidence and mortality rates,remains a major global health challenge primarily due to the critical issue of postoperative recurrence.Early recurrence,defined as recurrence that occurs within 2 years posttreatment,is linked to the hidden spread of the primary tumor and significantly impacts patient survival.Traditional predictive factors,including both patient-and treatment-related factors,have limited predictive ability with respect to HCC recurrence.The integration of machine learning algorithms is fueled by the exponential growth of computational power and has revolutionized HCC research.The study by Zhang et al demonstrated the use of a groundbreaking preoperative prediction model for early postoperative HCC recurrence.Challenges persist,including sample size constraints,issues with handling data,and the need for further validation and interpretability.This study emphasizes the need for collaborative efforts,multicenter studies and comparative analyses to validate and refine the model.Overcoming these challenges and exploring innovative approaches,such as multi-omics integration,will enhance personalized oncology care.This study marks a significant stride toward precise,efficient,and personalized oncology practices,thus offering hope for improved patient outcomes in the field of HCC treatment.展开更多
Objective:Mammographic calcifications are a common feature of breast cancer,but their molecular characteristics and treatment implications in hormone receptor-positive(HR+)/human epidermal growth factor receptor 2-neg...Objective:Mammographic calcifications are a common feature of breast cancer,but their molecular characteristics and treatment implications in hormone receptor-positive(HR+)/human epidermal growth factor receptor 2-negative(HER2−)breast cancer remain unclear.Methods:We retrospectively collected mammography records of an HR+/HER2−breast cancer cohort(n=316)with matched clinicopathological,genomic,transcriptomic,and metabolomic data.On the basis of mammographic images,we grouped tumors by calcification status into calcification-negative tumors,tumors with probably benign calcifications,tumors with calcification of lowmoderate suspicion for maligancy and tumors with calcification of high suspicion for maligancy.We then explored the molecular characteristics associated with each calcification status across multiple dimensions.Results:Among the different statuses,tumors with probably benign calcifications exhibited elevated hormone receptor immunohistochemical staining scores,estrogen receptor(ER)pathway activation,lipid metabolism,and sensitivity to endocrine therapy.Tumors with calcifications of high suspicion for malignancy had relatively larger tumor sizes,elevated lymph node metastasis incidence,Ki-67 staining scores,genomic instability,cell cycle pathway activation,and may benefit from cyclin-dependent kinase 4 and 6(CDK4/6)inhibitors.Conclusions:Our research established links between tumor calcifications and molecular features,thus proposing potential precision treatment strategies for HR+/HER2−breast cancer.展开更多
Developing effective and long-term treatment strategies for rare and complex neurodegenerative diseases is challenging. One of the major roadblocks is the extensive heterogeneity among patients. This hinders understan...Developing effective and long-term treatment strategies for rare and complex neurodegenerative diseases is challenging. One of the major roadblocks is the extensive heterogeneity among patients. This hinders understanding the underlying disease-causing mechanisms and building solutions that have implications for a broad spectrum of patients. One potential solution is to develop personalized medicine approaches based on strategies that target the most prevalent cellular events that are perturbed in patients. Especially in patients with a known genetic mutation, it may be possible to understand how these mutations contribute to problems that lead to neurodegeneration. Protein–protein interaction analyses offer great advantages for revealing how proteins interact, which cellular events are primarily involved in these interactions, and how they become affected when key genes are mutated in patients. This line of investigation also suggests novel druggable targets for patients with different mutations. Here, we focus on alsin and spastin, two proteins that are identified as “causative” for amyotrophic lateral sclerosis and hereditary spastic paraplegia, respectively, when mutated. Our review analyzes the protein interactome for alsin and spastin, the canonical pathways that are primarily important for each protein domain, as well as compounds that are either Food and Drug Administration–approved or are in active clinical trials concerning the affected cellular pathways. This line of research begins to pave the way for personalized medicine approaches that are desperately needed for rare neurodegenerative diseases that are complex and heterogeneous.展开更多
Hepatitis B virus(HBV)infection is a major player in chronic hepatitis B that may lead to the development of hepatocellular carcinoma(HCC).HBV genetics are diverse where it is classified into at least 9 genotypes(A to...Hepatitis B virus(HBV)infection is a major player in chronic hepatitis B that may lead to the development of hepatocellular carcinoma(HCC).HBV genetics are diverse where it is classified into at least 9 genotypes(A to I)and 1 putative genotype(J),each with specific geographical distribution and possible different clinical outcomes in the patient.This diversity may be associated with the precision medicine for HBV-related HCC and the success of therapeutical approaches against HCC,related to different pathogenicity of the virus and host response.This Editorial discusses recent updates on whether the classification of HBV genetic diversity is still valid in terms of viral oncogenicity to the HCC and its precision medicine,in addition to the recent advances in cellular and molecular biology technologies.展开更多
The design of mini-missiles(MMs)presents several novel challenges.The stringent mission requirement to reach a target with a certain precision imposes a high guidance precision.The miniaturization of the size of MMs m...The design of mini-missiles(MMs)presents several novel challenges.The stringent mission requirement to reach a target with a certain precision imposes a high guidance precision.The miniaturization of the size of MMs makes the design of the guidance,navigation,and control(GNC)have a larger-thanbefore impact on the main-body design(shape,motor,and layout design)and its design objective,i.e.,flight performance.Pursuing a trade-off between flight performance and guidance precision,all the relevant interactions have to be accounted for in the design of the main body and the GNC system.Herein,a multi-objective and multidisciplinary design optimization(MDO)is proposed.Disciplines pertinent to motor,aerodynamics,layout,trajectory,flight dynamics,control,and guidance are included in the proposed MDO framework.The optimization problem seeks to maximize the range and minimize the guidance error.The problem is solved by using the nondominated sorting genetic algorithm II.An optimum design that balances a longer range with a smaller guidance error is obtained.Finally,lessons learned about the design of the MM and insights into the trade-off between flight performance and guidance precision are given by comparing the optimum design to a design provided by the traditional approach.展开更多
BACKGROUND Brain abscess is a serious and potentially fatal disease caused primarily by microbial infection.Although progress has been made in the diagnosis and treatment of brain abscesses,the diagnostic timeliness o...BACKGROUND Brain abscess is a serious and potentially fatal disease caused primarily by microbial infection.Although progress has been made in the diagnosis and treatment of brain abscesses,the diagnostic timeliness of pathogens needs to be improved.CASE SUMMARY We report the case of a 54-year-old male with a brain abscess caused by oral bacteria.The patient recovered well after receiving a combination of metagenomic next-generation sequencing(mNGS)-assisted guided medication and surgery.CONCLUSION Therefore,mNGS may be widely applied to identify the pathogenic microor-ganisms of brain abscesses and guide precision medicine.展开更多
文摘针对现有基于测距的集群UAV协同导航方法普遍忽略了空间构型对定位定能的影响,难以获得精确的导航定位结果,提出一种基于空间构型优选的5G集群UAV协同导航方法。构建了复杂环境下基于5G信号的UAV相对测距误差模型,基于最小几何精度因子(geometric dilution of precision,GDOP)准则建立了协同导航节点寻优策略,实现了协同导航空间构型的实时优选;设计了基于5G测距网络的协同导航滤波器,对UAV导航信息进行在线估计和实时补偿,提高集群UAV的协同定位精度。仿真结果表明:该方法从机定位精度平均提升了约42.05%,为集群UAV实现在卫星不可用条件下的自主导航提供了一种有效的新方法。
基金sponsored by the National Research Foundation of Korea(NRF)Grant funded by the Korean government(MSIT)(Grant No.:2018R1A5A2021242).
文摘The spread of tuberculosis(TB),especially multidrug-resistant TB and extensively drug-resistant TB,has strongly motivated the research and development of new anti-TB drugs.New strategies to facilitate drug combinations,including pharmacokinetics-guided dose optimization and toxicology studies of first-and second-line anti-TB drugs have also been introduced and recommended.Liquid chromatography-mass spectrometry(LC-MS)has arguably become the gold standard in the analysis of both endo-and exo-genous compounds.This technique has been applied successfully not only for therapeutic drug monitoring(TDM)but also for pharmacometabolomics analysis.TDM improves the effectiveness of treatment,reduces adverse drug reactions,and the likelihood of drug resistance development in TB patients by determining dosage regimens that produce concentrations within the therapeutic target window.Based on TDM,the dose would be optimized individually to achieve favorable outcomes.Pharmacometabolomics is essential in generating and validating hypotheses regarding the metabolism of anti-TB drugs,aiding in the discovery of potential biomarkers for TB diagnostics,treatment monitoring,and outcome evaluation.This article highlighted the current progresses in TDM of anti-TB drugs based on LC-MS bioassay in the last two decades.Besides,we discussed the advantages and disadvantages of this technique in practical use.The pressing need for non-invasive sampling approaches and stability studies of anti-TB drugs was highlighted.Lastly,we provided perspectives on the prospects of combining LC-MS-based TDM and pharmacometabolomics with other advanced strategies(pharmacometrics,drug and vaccine developments,machine learning/artificial intelligence,among others)to encapsulate in an all-inclusive approach to improve treatment outcomes of TB patients.
基金supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(NRF-RS-2023-00275307)。
文摘Background Optimal gut health is important to maximize growth performance and feed efficiency in broiler chickens.A total of 1,365 one-day-old male Ross 308 broiler chickens were randomly divided into 5 treatments groups with 21 replicates,13 birds per replicate.The present research investigated effects of microbial muramidase or a precision glycan alone or in combination on growth performance,apparent total tract digestibility,total blood carotenoid content,intestinal villus length,meat quality and gut microbiota in broiler chickens.Treatments included:NC:negative control(basal diet group);PC:positive control(basal diet+0.02%probiotics);MR:basal diet+0.035%microbial muramidase;PG:basal diet+0.1%precision glycan;and MRPG:basal diet+0.025%MR+0.1%PG,respectively.Results MRPG group increased the body weight gain and feed intake(P<0.05)compared with NC group.Moreover,it significantly increased total serum carotenoid(P<0.05)and MRPG altered the microbial diversity in ileum contents.The MRPG treatment group increased the abundance of the phylum Firmicutes,and family Lachnospiraceae,Ruminococcaceae,Oscillospiraceae,Lactobacillaceae,Peptostreptococcaceae and decreased the abundance of the phylum Campilobacterota,Bacteroidota and family Bacteroidaceae.Compared with the NC group,the chickens fed MRPG showed significantly increased in duodenum villus length at end the trial.Conclusion In this study,overall results showed that the synergetic effects of MR and PG showed enhancing growth performance,total serum carotenoid level and altering gut microbiota composition of broilers.The current research indicates that co-supplementation of MR and PG in broiler diets enhances intestinal health,consequently leading to an increased broiler production.
基金funded by Institutional Fund Projects under Grant No(IFPNC-001-611-2020).
文摘Landmines continue to pose an ongoing threat in various regions around the world,with countless buried landmines affecting numerous human lives.The detonation of these landmines results in thousands of casualties reported worldwide annually.Therefore,there is a pressing need to employ diverse landmine detection techniques for their removal.One effective approach for landmine detection is UAV(Unmanned Aerial Vehicle)based AirborneMagnetometry,which identifies magnetic anomalies in the local terrestrial magnetic field.It can generate a contour plot or heat map that visually represents the magnetic field strength.Despite the effectiveness of this approach,landmine removal remains a challenging and resource-intensive task,fraughtwith risks.Edge computing,on the other hand,can play a crucial role in critical drone monitoring applications like landmine detection.By processing data locally on a nearby edge server,edge computing can reduce communication latency and bandwidth requirements,allowing real-time analysis of magnetic field data.It enables faster decision-making and more efficient landmine detection,potentially saving lives and minimizing the risks involved in the process.Furthermore,edge computing can provide enhanced security and privacy by keeping sensitive data close to the source,reducing the chances of data exposure during transmission.This paper introduces the MAGnetometry Imaging based Classification System(MAGICS),a fully automated UAV-based system designed for landmine and buried object detection and localization.We have developed an efficient deep learning-based strategy for automatic image classification using magnetometry dataset traces.By simulating the proposal in various network scenarios,we have successfully detected landmine signatures present in themagnetometry images.The trained models exhibit significant performance improvements,achieving a maximum mean average precision value of 97.8%.
基金supported by a grant from the Standardization and Integration of Resources Information for Seed-cluster in Hub-Spoke Material Bank Program,Rural Development Administration,Republic of Korea(PJ01587004).
文摘Crop improvement is crucial for addressing the global challenges of food security and sustainable agriculture.Recent advancements in high-throughput phenotyping(HTP)technologies and artificial intelligence(AI)have revolutionized the field,enabling rapid and accurate assessment of crop traits on a large scale.The integration of AI and machine learning algorithms with HTP data has unlocked new opportunities for crop improvement.AI algorithms can analyze and interpret large datasets,and extract meaningful patterns and correlations between phenotypic traits and genetic factors.These technologies have the potential to revolutionize plant breeding programs by providing breeders with efficient and accurate tools for trait selection,thereby reducing the time and cost required for variety development.However,further research and collaboration are needed to overcome the existing challenges and fully unlock the power of HTP and AI in crop improvement.By leveraging AI algorithms,researchers can efficiently analyze phenotypic data,uncover complex patterns,and establish predictive models that enable precise trait selection and crop breeding.The aim of this review is to explore the transformative potential of integrating HTP and AI in crop improvement.This review will encompass an in-depth analysis of recent advances and applications,highlighting the numerous benefits and challenges associated with HTP and AI.
基金supported by grants from the National Natural Science Foundation of China(Grant No.82173182)the Sichuan Science and Technology Program(Grant No.2021YJ0117 to Weiya Wang+1 种基金Grant No.2023NSFSC1939 to Dan Liu)the 1·3·5 project for Disciplines of Excellence–Clinical Research Incubation Project,West China Hospital,Sichuan University(Grant Nos.2019HXFH034 and ZYJC21074)。
文摘Lung cancer is the most common and fatal malignant disease worldwide and has the highest mortality rate among tumor-related causes of death.Early diagnosis and precision medicine can significantly improve the survival rate and prognosis of lung cancer patients.At present,the clinical diagnosis of lung cancer is challenging due to a lack of effective non-invasive detection methods and biomarkers,and treatment is primarily hindered by drug resistance and high tumor heterogeneity.Liquid biopsy is a method for detecting circulating biomarkers in the blood and other body fluids containing genetic information from primary tumor tissues.Bronchoalveolar lavage fluid(BALF)is a potential liquid biopsy medium that is rich in a variety of bioactive substances and cell components.BALF contains information on the key characteristics of tumors,including the tumor subtype,gene mutation type,and tumor environment,thus BALF may be used as a diagnostic supplement to lung biopsy.In this review,the current research on BALF in the diagnosis,treatment,and prognosis of lung cancer is summarized.The advantages and disadvantages of different components of BALF,including cells,cell-free DNA,extracellular vesicles,and micro RNA are introduced.In particular,the great potential of extracellular vesicles in precision diagnosis and detection of drug-resistant for lung cancer is highlighted.In addition,the performance of liquid biopsies with different body fluid sources in lung cancer detection are compared to facilitate more selective studies involving BALF,thereby promoting the application of BALF for precision medicine in lung cancer patients in the future.
基金Project supported by the National Key Research and Development Program of China (Grant No.2021YFB2012600)。
文摘We present a quantitative measurement of the horizontal component of the microwave magnetic field of a coplanar waveguide using a quantum diamond probe in fiber format.The measurement results are compared in detail with simulation,showing a good consistence.Further simulation shows fiber diamond probe brings negligible disturbance to the field under measurement compared to bulk diamond.This method will find important applications ranging from electromagnetic compatibility test and failure analysis of high frequency and high complexity integrated circuits.
基金supported by the National Natural Science Foundation of China(Grant No.:82174246)the National Key R&D Program of China(Grant No.:2019YFC1708701)the Postdoctoral Innovation Talent Support Program(Grant No.:BX20220329).
文摘Recent trends suggest that Chinese herbal medicine formulas(CHM formulas)are promising treatments for complex diseases.To characterize the precise syndromes,precise diseases and precise targets of the precise targets between complex diseases and CHM formulas,we developed an artificial intelligence-based quantitative predictive algorithm(DeepTCM).DeepTCM has gone through multilevel model calibration and validation against a comprehensive set of herb and disease data so that it accurately captures the complex cellular signaling,molecular and theoretical levels of traditional Chinese medicine(TCM).As an example,our model simulated the optimal CHM formulas for the treatment of coronary heart disease(CHD)with depression,and through model sensitivity analysis,we calculated the balanced scoring of the formulas.Furthermore,we constructed a biological knowledge graph representing interactions by associating herb-target and gene-disease interactions.Finally,we experimentally confirmed the therapeutic effect and pharmacological mechanism of a novel model-predicted intervention in humans and mice.This novel multiscale model opened up a new avenue to combine“disease syndrome”and“macro micro”system modeling to facilitate translational research in CHM formulas.
基金National Natural Science Foundation of China(Grant Nos.11972193 and 92266201)。
文摘How to effectively evaluate the firing precision of weapon equipment at low cost is one of the core contents of improving the test level of weapon system.A new method to evaluate the firing precision of the MLRS considering the credibility of simulation system based on Bayesian theory is proposed in this paper.First of all,a comprehensive index system for the credibility of the simulation system of the firing precision of the MLRS is constructed combined with the group analytic hierarchy process.A modified method for determining the comprehensive weight of the index is established to improve the rationality of the index weight coefficients.The Bayesian posterior estimation formula of firing precision considering prior information is derived in the form of mixed prior distribution,and the rationality of prior information used in estimation model is discussed quantitatively.With the simulation tests,the different evaluation methods are compared to validate the effectiveness of the proposed method.Finally,the experimental results show that the effectiveness of estimation method for firing precision is improved by more than 25%.
基金supported by ONR UMass Dartmouth Marine and UnderSea Technology(MUST)grant N00014-20-1-2849 under the project S31320000049160by DOE grant DE-SC0023164 sub-award RC114586-UMD+2 种基金by AFOSR grants FA9550-18-1-0383 and FA9550-23-1-0037supported by Michigan State University,by AFOSR grants FA9550-19-1-0281 and FA9550-18-1-0383by DOE grant DE-SC0023164.
文摘Additive Runge-Kutta methods designed for preserving highly accurate solutions in mixed-precision computation were previously proposed and analyzed.These specially designed methods use reduced precision for the implicit computations and full precision for the explicit computations.In this work,we analyze the stability properties of these methods and their sensitivity to the low-precision rounding errors,and demonstrate their performance in terms of accuracy and efficiency.We develop codes in FORTRAN and Julia to solve nonlinear systems of ODEs and PDEs using the mixed-precision additive Runge-Kutta(MP-ARK)methods.The convergence,accuracy,and runtime of these methods are explored.We show that for a given level of accuracy,suitably chosen MP-ARK methods may provide significant reductions in runtime.
文摘Background:Limited research has been conducted on the influence of autophagy-associated long non-coding RNAs(ARLncRNAs)on the prognosis of hepatocellular carcinoma(HCC).Methods:We analyzed 371 HCC samples from TCGA,identifying expression networks of ARLncRNAs using autophagy-related genes.Screening for prognostically relevant ARLncRNAs involved univariate Cox regression,Lasso regression,and multivariate Cox regression.A Nomogram was further employed to assess the reliability of Riskscore,calculated from the signatures of screened ARLncRNAs,in predicting outcomes.Additionally,we compared drug sensitivities in patient groups with differing risk levels and investigated potential biological pathways through enrichment analysis,using consensus clustering to identify subgroups related to ARLncRNAs.Results:The screening process identified 27 ARLncRNAs,with 13 being associated with HCC prognosis.Consequently,a set of signatures comprising 8 ARLncRNAs was successfully constructed as independent prognostic factors for HCC.Patients in the high-risk group showed very poor prognoses in most clinical categories.The Riskscore was closely related to immune cell scores,such as macrophages,and the DEGs between different groups were implicated in metabolism,cell cycle,and mitotic processes.Notably,high-risk group patients demonstrated a significantly lower IC50 for Paclitaxel,suggesting that Paclitaxel could be an ideal treatment for those at elevated risk for HCC.We further identified C2 as the Paclitaxel subtype,where patients exhibited higher Riskscores,reduced survival rates,and more severe clinical progression.Conclusion:The 8 signatures based on ARLncRNAs present novel targets for prognostic prediction in HCC.The drug candidate Paclitaxel may effectively treat HCC by impacting ARLncRNAs expression.With the identification of ARLncRNAsrelated isoforms,these results provide valuable insights for clinical exploration of autophagy mechanisms in HCC pathogenesis and offer potential avenues for precision medicine.
基金The study was funded by the China National Key Research and Development Program(2022YFC2504503,2023YFC3603104)General Health Science and Technology Program of Zhejiang Province(2024KY1099)+2 种基金the Huadong Medicine Joint Funds of the Zhejiang Provincial Natural Science Foundation of China(LHDMD24H150001)National Natural Science Foundation of China(82272180)the Project of Drug Clinical Evaluate Research of Chinese Pharmaceutical Association(CPA-Z06-ZC-2021e004).
文摘Objective:Some patients exhibit septic symptoms following laparoscopic surgery,leading to a poor prognosis.Effective clinical subphenotyping is critical for guiding tailored therapeutic strategies in these cases.By identifying predisposing factors for postoperative sepsis,clinicians can implement targeted interventions,potentially improving outcomes.This study outlines a workflow for the subphenotype methodology in the context of laparoscopic surgery,along with its practical application.Methods:This study utilized data routinely available in clinical case systems,enhancing the applicability of our findings.The data included vital signs,such as respiratory rate,and laboratory measures,such as blood sodium levels.The process of categorizing clinical routine data involved technical complexities.A correlation heatmap was used to visually depict the relationships between variables.Ordering points were used to identify the clustering structure and combined with Consensus K clustering methods to determine the optimal categorization.Results:Our study highlighted the intricacies of identifying clinical subphenotypes following laparoscopic surgery,and could thus serve as a valuable resource for clinicians and researchers seeking to explore disease heterogeneity in clinical settings.By simplifying complex methodologies,we aimed to bridge the gap between technical expertise and clinical application,fostering an environment where professional medical knowledge is effectively utilized in subphenotyping research.Conclusion:This tutorial could primarily serve as a guide for beginners.A variety of clustering approaches were explored,and each step in the process contributed to a comprehensive understanding of clinical subphenotypes.
基金Supported by Chinese Medicine Service System and Capacity Building(Key Project with Chinese Medicine Characteristics and Advantages,Ruikang Hospital,2023)Guangxi Science and Technology Major Project during the 14th five-year Plan,No.Guike AA22096028.
文摘Gastric organoids are models created in the laboratory using stem cells and sophisticated three-dimensional cell culture techniques.These models have shown great promise in providing valuable insights into gastric physiology and advanced disease research.This review comprehensively summarizes and analyzes the research advances in culture methods and techniques for adult stem cells and induced pluripotent stem cell-derived organoids,and patient-derived organoids.The potential value of gastric organoids in studying the pathogenesis of stomach-related diseases and facilitating drug screening is initially discussed.The construction of gastric organoids involves several key steps,including cell extraction and culture,three-dimensional structure formation,and functional expression.Simulating the structure and function of the human stomach by disease modeling with gastric organoids provides a platform to study the mechanism of gastric cancer induction by Helicobacter pylori.In addition,in drug screening and development,gastric organoids can be used as a key tool to evaluate drug efficacy and toxicity in preclinical trials.They can also be used for precision medicine according to the specific conditions of patients with gastric cancer,to assess drug resistance,and to predict the possibility of adverse reactions.However,despite the impressive progress in the field of gastric organoids,there are still many unknowns that need to be addressed,especially in the field of regenerative medicine.Meanwhile,the reproducibility and consistency of organoid cultures are major challenges that must be overcome.These challenges have had a significant impact on the development of gastric organoids.Nonetheless,as technology continues to advance,we can foresee more comprehensive research in the construction of gastric organoids.Such research will provide better solutions for the treatment of stomach-related diseases and personalized medicine.
基金the National Natural Science Foundation of China under Grant(42274119)the Liaoning Revitalization Talents Program under Grant(XLYC2002082)+1 种基金National Key Research and Development Plan Key Special Projects of Science and Technology Military Civil Integration(2022YFF1400500)the Key Project of Science and Technology Commission of the Central Military Commission.
文摘Global navigation satellite system-reflection(GNSS-R)sea surface altimetry based on satellite constellation platforms has become a new research direction and inevitable trend,which can meet the altimetric precision at the global scale required for underwater navigation.At present,there are still research gaps for GNSS-R altimetry under this mode,and its altimetric capability cannot be specifically assessed.Therefore,GNSS-R satellite constellations that meet the global altimetry needs to be designed.Meanwhile,the matching precision prediction model needs to be established to quantitatively predict the GNSS-R constellation altimetric capability.Firstly,the GNSS-R constellations altimetric precision under different configuration parameters is calculated,and the mechanism of the influence of orbital altitude,orbital inclination,number of satellites and simulation period on the precision is analyzed,and a new multilayer feedforward neural network weighted joint prediction model is established.Secondly,the fit of the prediction model is verified and the performance capability of the model is tested by calculating the R2 value of the model as 0.9972 and the root mean square error(RMSE)as 0.0022,which indicates that the prediction capability of the model is excellent.Finally,using the novel multilayer feedforward neural network weighted joint prediction model,and considering the research results and realistic costs,it is proposed that when the constellation is set to an orbital altitude of 500 km,orbital inclination of 75and the number of satellites is 6,the altimetry precision can reach 0.0732 m within one year simulation period,which can meet the requirements of underwater navigation precision,and thus can provide a reference basis for subsequent research on spaceborne GNSS-R sea surface altimetry.
文摘In this editorial,we comment on the article by Zhang et al entitled Development of a machine learning-based model for predicting the risk of early postoperative recurrence of hepatocellular carcinoma.Hepatocellular carcinoma(HCC),which is characterized by high incidence and mortality rates,remains a major global health challenge primarily due to the critical issue of postoperative recurrence.Early recurrence,defined as recurrence that occurs within 2 years posttreatment,is linked to the hidden spread of the primary tumor and significantly impacts patient survival.Traditional predictive factors,including both patient-and treatment-related factors,have limited predictive ability with respect to HCC recurrence.The integration of machine learning algorithms is fueled by the exponential growth of computational power and has revolutionized HCC research.The study by Zhang et al demonstrated the use of a groundbreaking preoperative prediction model for early postoperative HCC recurrence.Challenges persist,including sample size constraints,issues with handling data,and the need for further validation and interpretability.This study emphasizes the need for collaborative efforts,multicenter studies and comparative analyses to validate and refine the model.Overcoming these challenges and exploring innovative approaches,such as multi-omics integration,will enhance personalized oncology care.This study marks a significant stride toward precise,efficient,and personalized oncology practices,thus offering hope for improved patient outcomes in the field of HCC treatment.
基金supported by grants from the National Key Research and Development Project of China(Grant No.2020YFA0112304)the National Natural Science Foundation of China(Grant Nos.81922048,82072922,91959207,and 92159301)+3 种基金the Program of Shanghai Academic/Technology Research Leader(Grant No.20XD1421100)the Shanghai Key Laboratory of Breast Cancer(Grant No.12DZ2260100)the Clinical Research Plan of SHDC(Grant Nos.SHDC2020CR4002 and SHDC2020CR5005)the SHDC Municipal Project for Developing Emerging and Frontier Technology in Shanghai Hospitals(Grant No.SHDC12021103).
文摘Objective:Mammographic calcifications are a common feature of breast cancer,but their molecular characteristics and treatment implications in hormone receptor-positive(HR+)/human epidermal growth factor receptor 2-negative(HER2−)breast cancer remain unclear.Methods:We retrospectively collected mammography records of an HR+/HER2−breast cancer cohort(n=316)with matched clinicopathological,genomic,transcriptomic,and metabolomic data.On the basis of mammographic images,we grouped tumors by calcification status into calcification-negative tumors,tumors with probably benign calcifications,tumors with calcification of lowmoderate suspicion for maligancy and tumors with calcification of high suspicion for maligancy.We then explored the molecular characteristics associated with each calcification status across multiple dimensions.Results:Among the different statuses,tumors with probably benign calcifications exhibited elevated hormone receptor immunohistochemical staining scores,estrogen receptor(ER)pathway activation,lipid metabolism,and sensitivity to endocrine therapy.Tumors with calcifications of high suspicion for malignancy had relatively larger tumor sizes,elevated lymph node metastasis incidence,Ki-67 staining scores,genomic instability,cell cycle pathway activation,and may benefit from cyclin-dependent kinase 4 and 6(CDK4/6)inhibitors.Conclusions:Our research established links between tumor calcifications and molecular features,thus proposing potential precision treatment strategies for HR+/HER2−breast cancer.
基金funded by NIH-NIA R01AG061708 (to PHO)Patrick Grange Memorial Foundation (to PHO)+1 种基金A Long Swim (to PHO)CureSPG4 Foundation (to PHO)。
文摘Developing effective and long-term treatment strategies for rare and complex neurodegenerative diseases is challenging. One of the major roadblocks is the extensive heterogeneity among patients. This hinders understanding the underlying disease-causing mechanisms and building solutions that have implications for a broad spectrum of patients. One potential solution is to develop personalized medicine approaches based on strategies that target the most prevalent cellular events that are perturbed in patients. Especially in patients with a known genetic mutation, it may be possible to understand how these mutations contribute to problems that lead to neurodegeneration. Protein–protein interaction analyses offer great advantages for revealing how proteins interact, which cellular events are primarily involved in these interactions, and how they become affected when key genes are mutated in patients. This line of investigation also suggests novel druggable targets for patients with different mutations. Here, we focus on alsin and spastin, two proteins that are identified as “causative” for amyotrophic lateral sclerosis and hereditary spastic paraplegia, respectively, when mutated. Our review analyzes the protein interactome for alsin and spastin, the canonical pathways that are primarily important for each protein domain, as well as compounds that are either Food and Drug Administration–approved or are in active clinical trials concerning the affected cellular pathways. This line of research begins to pave the way for personalized medicine approaches that are desperately needed for rare neurodegenerative diseases that are complex and heterogeneous.
基金Supported by Rumah Program 2024 of Research Organization for Health,National Research and Innovation Agency of Indonesia2023 Grant of The Fondazione Veronesi,Milan,Italy(Caecilia H C Sukowati)2023/2024 Postdoctoral Fellowship of The Manajemen Talenta,Badan Riset dan Inovasi Nasional,Indonesia(Sri Jayanti).
文摘Hepatitis B virus(HBV)infection is a major player in chronic hepatitis B that may lead to the development of hepatocellular carcinoma(HCC).HBV genetics are diverse where it is classified into at least 9 genotypes(A to I)and 1 putative genotype(J),each with specific geographical distribution and possible different clinical outcomes in the patient.This diversity may be associated with the precision medicine for HBV-related HCC and the success of therapeutical approaches against HCC,related to different pathogenicity of the virus and host response.This Editorial discusses recent updates on whether the classification of HBV genetic diversity is still valid in terms of viral oncogenicity to the HCC and its precision medicine,in addition to the recent advances in cellular and molecular biology technologies.
文摘The design of mini-missiles(MMs)presents several novel challenges.The stringent mission requirement to reach a target with a certain precision imposes a high guidance precision.The miniaturization of the size of MMs makes the design of the guidance,navigation,and control(GNC)have a larger-thanbefore impact on the main-body design(shape,motor,and layout design)and its design objective,i.e.,flight performance.Pursuing a trade-off between flight performance and guidance precision,all the relevant interactions have to be accounted for in the design of the main body and the GNC system.Herein,a multi-objective and multidisciplinary design optimization(MDO)is proposed.Disciplines pertinent to motor,aerodynamics,layout,trajectory,flight dynamics,control,and guidance are included in the proposed MDO framework.The optimization problem seeks to maximize the range and minimize the guidance error.The problem is solved by using the nondominated sorting genetic algorithm II.An optimum design that balances a longer range with a smaller guidance error is obtained.Finally,lessons learned about the design of the MM and insights into the trade-off between flight performance and guidance precision are given by comparing the optimum design to a design provided by the traditional approach.
文摘BACKGROUND Brain abscess is a serious and potentially fatal disease caused primarily by microbial infection.Although progress has been made in the diagnosis and treatment of brain abscesses,the diagnostic timeliness of pathogens needs to be improved.CASE SUMMARY We report the case of a 54-year-old male with a brain abscess caused by oral bacteria.The patient recovered well after receiving a combination of metagenomic next-generation sequencing(mNGS)-assisted guided medication and surgery.CONCLUSION Therefore,mNGS may be widely applied to identify the pathogenic microor-ganisms of brain abscesses and guide precision medicine.