Random Green's Function Method for Large-Scale Electronic Structure Calculation

We report a linear-scaling random Green's function(rGF) method for large-scale electronic structure calculation. In this method, the rGF is defined on a set of random states and is efficiently calculated by projecting onto Krylov subspace. With the rGF method, the Fermi–Dirac operator can be obtained directly, avoiding the polynomial expansion to Fermi–Dirac function. To demonstrate the applicability, we implement the rGF method with the density-functional tight-binding method. It is shown that the Krylov subspace can maintain at small size for materials with different gaps at zero temperature, including H_(2)O and Si clusters. We find with a simple deflation technique that the rGF self-consistent calculation of H_(2)O clusters at T = 0 K can reach an error of~ 1 me V per H_(2)O molecule in total energy, compared to deterministic calculations. The rGF method provides an effective stochastic method for large-scale electronic structure simulation.

Push forward LC-MS-based therapeutic drug monitoring and pharmacometabolomics for anti-tuberculosis precision dosing and comprehensive clinical management

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.

Stability Analysis and Performance Evaluation of Additive Mixed-Precision Runge-Kutta Methods

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.

Developing risk models and subtypes of autophagy-associated LncRNAs for enhanced prognostic prediction and precision in therapeutic approaches for liver cancer patients

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.

Emerging perovskite materials for supercapacitors:Structure,synthesis,modification,advanced characterization,theoretical calculation and electrochemical performance

As a new generation electrode materials for energy storage,perovskites have attracted wide attention because of their unique crystal structure,reversible active sites,rich oxygen vacancies,and good stability.In this review,the design and engineering progress of perovskite materials for supercapacitors(SCs)in recent years is summarized.Specifically,the review will focus on four types of perovskites,perovskite oxides,halide perovskites,fluoride perovskites,and multi-perovskites,within the context of their intrinsic structure and corresponding electrochemical performance.A series of experimental variables,such as synthesis,crystal structure,and electrochemical reaction mechanism,will be carefully analyzed by combining various advanced characterization techniques and theoretical calculations.The applications of these materials as electrodes are then featured for various SCs.Finally,we look forward to the prospects and challenges of perovskite-type SCs electrodes,as well as the future research direction.

Bronchoalveolar lavage fluid assessment facilitates precision medicine for lung cancer

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.

Precision tuning of highly efficient Pt-based ternary alloys on nitrogen-doped multi-wall carbon nanotubes for methanol oxidation reaction

The electrochemical methanol oxidation is a crucial reaction in the conversion of renewable energy.To enable the widespread adoption of direct methanol fuel cells(DMFCs),it is essential to create and engineer catalysts that are both highly effective and robust for conducting the methanol oxidation reaction(MOR).In this work,trimetallic PtCoRu electrocatalysts on nitrogen-doped carbon and multi-wall carbon nanotubes(PtCoRu@NC/MWCNTs)were prepared through a two-pot synthetic strategy.The acceleration of CO oxidation to CO_(2) and the blocking of CO reduction on adjacent Pt active sites were attributed to the crucial role played by cobalt atoms in the as-prepared electrocatalysts.The precise control of Co atoms loading was achieved through precursor stoichiometry.Various physicochemical techniques were employed to analyze the morphology,element composition,and electronic state of the catalyst.Electrochemical investigations and theoretical calculations confirmed that the Pt_(1)Co_(3)Ru_(1)@NC/MWCNTs exhibit excellent electrocatalytic performance and durability for the process of MOR.The enhanced MOR activity can be attributed to the synergistic effect between the multiple elements resulting from precisely controlled Co loading content on surface of the electrocatalyst,which facilitates efficient charge transfer.This interaction between the multiple components also modifies the electronic structures of active sites,thereby promoting the conversion of intermediates and accelerating the MOR process.Thus,achieving precise control over Co loading in PtCoRu@NC/MWCNTs would enable the development of high-performance catalysts for DMFCs.

Hepatitis B virus genotypes in precision medicine of hepatitis Brelated hepatocellular carcinoma:Where we are now

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.

A new method for evaluating the firing precision of multiple launch rocket system based on Bayesian theory

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%.

Improving the spaceborne GNSS-R altimetric precision based on the novel multilayer feedforward neural network weighted joint prediction model

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.

Utility and Application of a Versatile Analytical Method for MMF Calculation in AC Machines

A versatile analytical method(VAM) for calculating the harmonic components of the magnetomotive force(MMF) generated by diverse armature windings in AC machines has been proposed, and the versatility of this method has been established in early literature. However, its practical applications and significance in advancing the analysis of AC machines need further elaboration. This paper aims to complement VAM by augmenting its theory, offering additional insights into its conclusions, as well as demonstrating its utility in assessing armature windings and its application of calculating torque for permanent magnet synchronous machines(PMSM). This work contributes to advancing the analysis of AC machines and underscores the potential for improved design and performance optimization.

High-throughput calculation-based rational design of Fe-doped MoS_(2) nanosheets for electrocatalytic p H-universal overall water splitting

Electrocatalytic water splitting is crucial for H2generation via hydrogen evolution reaction(HER)but subject to the sluggish dynamics of oxygen evolution reaction(OER).In this work,single Fe atomdoped MoS_(2)nanosheets(SFe-DMNs)were prepared based on the high-throughput density functional theory(DFT)calculation screening.Due to the synergistic effect between Fe atom and MoS_(2)and optimized intermediate binding energy,the SFe-DMNs could deliver outstanding activity for both HER and OER.When assembled into a two-electrode electrolytic cell,the SFe-DMNs could achieve the current density of 50 mA cm^(-2)at a low cell voltage of 1.55 V under neutral condition.These results not only confirmed the effectiveness of high-throughput screening,but also revealed the excellent activity and thus the potential applications in fuel cells of SFe-DMNs.

Genotype-based precision nutrition strategies for the prediction and clinical management of type 2 diabetes mellitus

Globally,type 2 diabetes mellitus(T2DM)is one of the most common metabolic disorders.T2DM physiopathology is influenced by complex interrelationships between genetic,metabolic and lifestyle factors(including diet),which differ between populations and geographic regions.In fact,excessive consumptions of high fat/high sugar foods generally increase the risk of developing T2DM,whereas habitual intakes of plant-based healthy diets usually exert a protective effect.Moreover,genomic studies have allowed the characterization of sequence DNA variants across the human genome,some of which may affect gene expression and protein functions relevant for glucose homeostasis.This comprehensive literature review covers the impact of gene-diet interactions on T2DM susceptibility and disease progression,some of which have demonstrated a value as biomarkers of personal responses to certain nutritional interventions.Also,novel genotype-based dietary strategies have been developed for improving T2DM control in comparison to general lifestyle recommendations.Furthermore,progresses in other omics areas(epigenomics,metagenomics,proteomics,and metabolomics)are improving current understanding of genetic insights in T2DM clinical outcomes.Although more investigation is still needed,the analysis of the genetic make-up may help to decipher new paradigms in the pathophysiology of T2DM as well as offer further opportunities to personalize the screening,prevention,diagnosis,management,and prognosis of T2DM through precision nutrition.

Integrating disulfidptosis-related long noncoding RNAs in colorectal cancer prognosis:A path to precision medicine

This commentary explores the burgeoning field of disulfidptosis-related long noncoding RNAs(lncRNAs)in the prognosis and therapeutic targeting of colorectal cancer(CRC).By evaluating recent research,including the pivotal study"Predicting colorectal cancer prognosis based on long noncoding RNAs of disulfidptosis genes"by Wang et al,this analysis underscores the critical role of lncRNAs in deciphering the molecular complexities of CRC.Highlighting the innovative methodologies and significant findings,I discuss the implications for patient survival,therapeutic response,and the potential of lncRNAs as biomarkers for precision medicine.The integration of bioinformatics,clinical databases,and molecular biology in these studies offers a promising avenue for advancing CRC treatment strategies and improving patient outcomes.

Re-evaluating the role of pelvic radiation in the age of modern precision medicine and systemic therapy

The efficacy of pelvic radiation in the management of locally advanced stage rectal cancer has come under scrutiny in the context of modern precision medicine and systemic therapy as evidenced by recent clinical trials such as FOWARC(J Clin Oncol 2019;37:3223-3233),NCT04165772(N Engl J Med 2022;386:2363-2376),and PROSPECT(N Engl J Med 2023;389:322-334).In this review,we comprehensively assess these pivotal trials and offer additional insights into the evolving role of pelvic radiation in contemporary oncology.

Design methodology of a mini-missile considering flight performance and guidance precision

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.

Envita’s Precision Cancer Care: 35-Fold Improvement in Response Rates

New clinical approaches are imperative beyond the widely adopted National Comprehensive Cancer Network (NCCN) guidelines, utilized by prominent cancer institutions. Cancer is the leading cause of death among individuals younger than 85 years within the United States. Despite significant technological advances, including the expenditure of hundreds of billions, treatment outcomes and overall survival have not notably improved for most types of advanced cancer over the last several decades. Over the past 24 years, Envita Medical Centers has pioneered a unique form of personalized treatment approach for late-stage and refractory cancer patients, introducing groundbreaking innovations in the field. Our integrated algorithm utilizes advanced genomics, transcriptomics, and highly tailored immunotherapy, resulting in remarkable outcome improvements. This study presents Envita’s innovative personalized treatment algorithms and examines the response outcomes of 199 late-stage cancer patients treated at Envita Medical Centers over a two-year period. Compared to standard of care and palliative chemotherapy, Envita’s treatment demonstrated a remarkable 35-fold improvement in overall response rates (Figure 1). Moreover, 88% of the patients, the majority presenting with Stage 3 or 4 cancer, experienced a 43-fold improvement in quality of life with minimal side effects, as compared to standard of care chemotherapy and palliative care. This revolutionary success is attributed to Envita’s personalized therapeutic algorithms, which incorporate customized immunotherapy. Envita’s precision care approach has also achieved a 100% better response rate compared to over 65 global chemotherapy clinical trials with more than 2700 patients. The results from this study suggest that a wider utilization of Envita’s personalized approach can significantly benefit patients with late-stage and refractory cancer.

The Chinese Consumers’Service Quality Satisfaction Differences of Cruise Tourism and Precision Marketing Strategy

The paper selected Chinese Cruise Line as the case study. Having based on the survey data of Chinese cruise tourism consumers, the factor analysis method, one-way analysis of variances method, cluster analysis method, and other quantitative and qualitative methods were taken to analyze Chinese consumers’ satisfaction differences of cruise tourism service quality with different segmentation markets and clusters markets, and the reasons of satisfaction differences were also explored. Then precision marketing strategy of Chinese cruise tourism with different segmentation markets and clusters markets from the supply-side reform perspective was discussed. The purpose of current research was to provide suggestions of precision management and precision marketing of Chinese cruise tourism for relevant enterprises and government departments.

Coping with the Impact of Climate Change: A Dive into Precision Agriculture in the United States

With the continued increase in the number of people that are food insecure globally, which could be increasing because of the ongoing Ukraine-Russia war, leading to reduction in international agribusinesses, coupled with drastic climate change exacerbating the problem of food insecurity, there is a constant need to come up with innovative approaches to solve this global issue. In this article, we articulated how precision agriculture can be a tool for ensuring food security in the United States. This study aims to reiterate the significance of precision agriculture in solving global food insecurity.

Precision Nutrition:早期肠内营养支持治疗可显著改善接受机械通气患者的临床结局

近期,四川省医学科学院·四川省人民医院的江华教授团队在Precision Nutrition杂志上发表题为“Dig-ital twin enabled personalized nutrition”的文章,该文章综述了当前临床营养诊断和治疗面临的挑战,并概述了经典临床试验和人工智能研究的局限性,并提出了数字孪生(digital twin,DT)个体化营养诊疗的概念和应用。