Constructing a nomogram to predict overall survival of colon cancer based on computed tomography characteristics and clinicopathological factors

BACKGROUND The colon cancer prognosis is influenced by multiple factors,including clinical,pathological,and non-biological factors.However,only a few studies have focused on computed tomography(CT)imaging features.Therefore,this study aims to predict the prognosis of patients with colon cancer by combining CT imaging features with clinical and pathological characteristics,and establishes a nomogram to provide critical guidance for the individualized treatment.AIM To establish and validate a nomogram to predict the overall survival(OS)of patients with colon cancer.METHODS A retrospective analysis was conducted on the survival data of 249 patients with colon cancer confirmed by surgical pathology between January 2017 and December 2021.The patients were randomly divided into training and testing groups at a 1:1 ratio.Univariate and multivariate logistic regression analyses were performed to identify the independent risk factors associated with OS,and a nomogram model was constructed for the training group.Survival curves were calculated using the Kaplan–Meier method.The concordance index(C-index)and calibration curve were used to evaluate the nomogram model in the training and testing groups.RESULTS Multivariate logistic regression analysis revealed that lymph node metastasis on CT,perineural invasion,and tumor classification were independent prognostic factors.A nomogram incorporating these variables was constructed,and the C-index of the training and testing groups was 0.804 and 0.692,respectively.The calibration curves demonstrated good consistency between the actual values and predicted probabilities of OS.CONCLUSION A nomogram combining CT imaging characteristics and clinicopathological factors exhibited good discrimination and reliability.It can aid clinicians in risk stratification and postoperative monitoring and provide important guidance for the individualized treatment of patients with colon cancer.

Chromosome-level assembly of triploid genome of Sichuan pepper(Zanthoxylum armatum)

As an important spice species in Rutaceae, the Sichuan pepper (Zanthoxylum armatum) can provide pungent and numbing taste, as well as aroma in its mature fruit. Here we assembled a chromosome-level genome of green prickly ash which was widely cultivated in a major production area including Chongqing and Sichuan province, China. We generated 712 Gb (~112×) PacBio long reads and 511 Gb (~82×) Hi-C data, and yielded an assembly of 99 pseudochromosomes with total size of 5.32 Gb and contig N50 of 796 kb. The genomic analyses and cytogenetic experiments both indicated that the cultivarZhuye Huajiao’ was a triploid. We identified a Zanthoxylum-specific whole genome duplication event emerging about 24.8 million years ago (Mya). We also detected a transposition burst event (0.3-0.4 Mya) responsible for the large genome size of Z. armatum. Metabolomic analysis of the Zanthoxylum fruits during development stages revealed profiles of39 volatile aroma compounds and 528 secondary metabolites, from which six types of sanshools were identified. Based on metabolomic and transcriptomic network analysis, we screened candidate genes encoding long chain acyl-CoA synthetase, fatty acid desaturase,branched-chain amino acid aminotransferase involved in sanshool biosynthesis and three genes encoding terpene synthase during fruit development. The multi-omics data provide insights into the evolution of Zanthoxylum and molecular basis of numbing and aroma flavor of Sichuan pepper.

Association mapping of lignin response to Verticillium wilt through an eight-way MAGIC population in Upland cotton

Lignin metabolism plays a pivotal role in plant defense against pathogens and is always positively correlated as a response to pathogen infection. Thus, understanding resistance genes against plant pathogens depends on a genetic analysis of the lignin response. This study used eight Upland cotton lines to construct a multi-parent advanced generation intercross(MAGIC) population(n=280), which exhibited peculiar characteristics from the convergence of various alleles coding for advantageous traits. In order to measure the lignin response to Verticillium wilt(LRVW), the artificial disease nursery(ADN) and rotation nursery(RN) were prepared for MAGIC population planting in four environments. The stem lignin contents were collected, and the LRVW was measured with the lignin value of ADN/RN in each environment, which showed significant variations. We employed 9 323 high-quality single-nucleotide polymorphism(SNP) markers obtained from the Cotton-SNP63K array for genotyping the MAGIC population. The SNPs were distributed through the whole genome with 4.78 SNP/Mb density, ranging from 1.14(ChrA06) to 10.08(ChrD08). In addition, a genome-wide association study was performed using a Mixed Linear Model(MLM) for LRVW. Three stable quantitative trait loci(QTLs), qLRVW-A04, qLRVW-A10, and qLRVW-D05, were identified in more than two environments. Two key candidate genes, Ghi_D05G01046 and Ghi_D05G01221, were selected within the QTLs through the combination of variations in the coding sequence, induced expression patterns, and function annotations. Both genes presented nonsynonymous mutations in coding regions and were strongly induced by Verticillium dahliae. Ghi_D05G01046 encodes a leucine-rich extensin(LRx) protein involved in Arabidopsis cell wall biosynthesis and organization. Ghi_D05G01221 encodes a transcriptional co-repressor novel interactor of novel interactor of jasmonic acid ZIM-domain(JAZ–NINJA), which functions in the jasmonic acid(JA) signaling pathway. In summary, the study creates valuable genetic resources for breeding and QTL mapping and opens up a new perspective to uncover the genetic basis of VW resistance in Upland cotton.

PGSLM:Edge-Enabled Probabilistic Graph Structure Learning Model for Traffic Forecasting in Internet of Vehicles

With the rapid development of the 5G communications,the edge intelligence enables Internet of Vehicles(IoV)to provide traffic forecasting to alleviate traffic congestion and improve quality of experience of users simultaneously.To enhance the forecasting performance,a novel edge-enabled probabilistic graph structure learning model(PGSLM)is proposed,which learns the graph structure and parameters by the edge sensing information and discrete probability distribution on the edges of the traffic road network.To obtain the spatio-temporal dependencies of traffic data,the learned dynamic graphs are combined with a predefined static graph to generate the graph convolution part of the recurrent graph convolution module.During the training process,a new graph training loss is introduced,which is composed of the K nearest neighbor(KNN)graph constructed by the traffic feature tensors and the graph structure.Detailed experimental results show that,compared with existing models,the proposed PGSLM improves the traffic prediction performance in terms of average absolute error and root mean square error in IoV.

Altered gene expression in human brain microvascular endothelial cells in response to the infection of influenza H1N1 virus

Influenza viruses not only cause respiratory illness,but also have been reported to elicit neurological manifestations following acute viral infection.The central nervous system(CNS)has a specific defense mechanism against pathogens structured by cerebral microvasculature lined with brain endothelial cells to form the blood–brain barrier(BBB).To investigate the response of human brain microvascular endothelial cells(hBMECs)to the Influenza A virus(IAV),we inoculated the cells with the A/WSN/33(H1N1)virus.We then conducted an RNAseq experiment to determine the changes in gene expression levels and the activated disease pathways following infection.The analysis revealed an effective activation of the innate immune defense by inducing the pattern recognition receptors(PRRs).Along with the production of proinflammatory cytokines,we detected an upregulation of interferons and interferon-stimulated genes,such as IFN-β/λ,ISG15,CXCL11,CXCL3 and IL-6,etc.Moreover,infected hBMECs exhibited a disruption in the cytoskeletal structure both on the transcriptomic and cytological levels.The RNAseq analysis showed different pathways and candidate genes associated with the neuroactive ligand-receptor interaction,neuroinflammation,and neurodegenerative diseases,together with a predicted activation of the neuroglia.Likewise,some genes linked with the mitochondrial structure and function displayed a significantly altered expression.En masse,this data supports that hBMECs could be infected by the IAV,which induces the innate and inflammatory immune response.The results suggest that the influenza virus infection could potentially induce a subsequent aggravation of neurological disorders.

Wild Gibbon Optimization Algorithm

Complex optimization problems hold broad significance across numerous fields and applications.However,as the dimensionality of such problems increases,issues like the curse of dimensionality and local optima trapping also arise.To address these challenges,this paper proposes a novel Wild Gibbon Optimization Algorithm(WGOA)based on an analysis of wild gibbon population behavior.WGOAcomprises two strategies:community search and community competition.The community search strategy facilitates information exchange between two gibbon families,generating multiple candidate solutions to enhance algorithm diversity.Meanwhile,the community competition strategy reselects leaders for the population after each iteration,thus enhancing algorithm precision.To assess the algorithm’s performance,CEC2017 and CEC2022 are chosen as test functions.In the CEC2017 test suite,WGOA secures first place in 10 functions.In the CEC2022 benchmark functions,WGOA obtained the first rank in 5 functions.The ultimate experimental findings demonstrate that theWildGibbonOptimization Algorithm outperforms others in tested functions.This underscores the strong robustness and stability of the gibbonalgorithm in tackling complex single-objective optimization problems.

Fuzzy Multi-Criteria Decision Support System for the Best Anti-Aging Treatment Selection Process through Normal Wiggly Hesitant Fuzzy Sets

This socialized environment among educated and developed people causes themto focusmore on their appearance and health,which turns them towards medical-related treatments,leading us to discuss anti-aging treatment methods for each age group,particularly for urban people who are interested in this.Some anti-aging therapies are used to address the alterations brought on by aging in human life without the need for surgery or negative effects.Five anti-aging therapies such as microdermabrasion or dermabrasion,laser resurfacing anti-aging skin treatments,chemical peels,dermal fillers for aged skin,and botox injections are considered in this study.Based on the criteria of safety risk,investment cost,customer happiness,and side effects,the optimal alternative is picked.As a result,a NormalWiggly Hesitant Pythagorean Fuzzy Set(NWHPFS)is constructed and used in Multi-Criteria Decision-Making(MCDM)using traditional wavy mathematical approaches.The entropy approach is utilized to determine weight values,and the Normal Wiggly Hesitant Pythagorean-VlseKriterijumska Optimizacija I Kompromisno Resenje(NWHPF-VIKOR)method is utilized to rank alternatives using MCDM methodologies.Sensitivity analysis and comparative analysis were performed to ensure the robustness and reliability of the proposed method.The smart final choice will undoubtedly assist Decision Makers(DM)in making the right judgments,and the MCDM approach will undoubtedly assist individuals in understanding the medicine.

An Integrated Bipolar Picture Fuzzy Decision Driven System to Scrutinize Food Waste Treatment Technology through Assorted Factor Analysis

Food Waste(FW)is a pressing environmental concern that affects every country globally.About one-third of the food that is produced ends up as waste,contributing to the carbon footprint.Hence,the FW must be properly treated to reduce environmental pollution.This study evaluates a few available Food Waste Treatment(FWT)technologies,such as anaerobic digestion,composting,landfill,and incineration,which are widely used.A Bipolar Picture Fuzzy Set(BPFS)is proposed to deal with the ambiguity and uncertainty that arise when converting a real-world problem to a mathematical model.A novel Criteria Importance Through Intercriteria Correlation-Stable Preference Ordering Towards Ideal Solution(CRITIC-SPOTIS)approach is developed to objectively analyze FWT selection based on thirteen criteria covering the industry’s technical,environmental,and entrepreneurial aspects.The CRITIC method is used for the objective analysis of the importance of each criterion in FWT selection.The SPOTIS method is adopted to rank the alternative hassle-free,following the criteria.The proposed model offers a rank reversal-free model,i.e.,the rank of the alternatives remains unaffected even after the addition or removal of an alternative.In addition,comparative and sensitivity analyses are performed to ensure the reliability and robustness of the proposed model and to validate the proposed result.

Structural basis of SARS-CoV-2 3CL^pro and anti-COVID-19 drug discovery from medicinal plants

The recent pandemic of coronavirus disease 2019(COVID-19)caused by SARS-CoV-2 has raised global health concerns.The viral 3-chymotrypsin-like cysteine protease(3CL^pro)enzyme controls coronavirus replication and is essential for its life cycle.3CL^pro is a proven drug discovery target in the case of severe acute respiratory syndrome coronavirus(SARS-CoV)and Middle East respiratory syndrome coronavirus(MERS-CoV).Recent studies revealed that the genome sequence of SARS-CoV-2 is very similar to that of SARS-CoV.Therefore,herein,we analysed the 3CL^pro sequence,constructed its 3D homology model,and screened it against a medicinal plant library containing 32,297 potential anti-viral phytochemicals/traditional Chinese medicinal compounds.Our analyses revealed that the top nine hits might serve as potential anti-SARS-CoV-2 lead molecules for further optimisation and drug development process to combat COVID-19.

Feasibility of MRI Radiomics for Predicting KRAS Mutation in Rectal Cancer

The mutation status of KRAS is a significant biomarker in the prognosis of rectal cancer.This study investigated the feasibility of MRI-based radiomics in predicting the mutation status of KRAS with a composite index which could be an important criterion for KRAS mutation in clinical practice.In this retrospective study,a total of 127 patients with rectal cancer were enrolled.The 3D Slicer was used to extract the radiomics features from the MRI images,and sparse support vector machine(SVM)with linear kernel was applied for feature reduction.The radiomics classifier for predicting the KRAS status was then constructed by Linear Discriminant Analysis(LDA)and its performance was evaluated.The composite index was determined with LDA model.Out of 127 rectal cancer subjects,there were 44 KRAS mutation cases and 83 wild cases.A total of 104 radiomics features were extracted,54 features were filtered by linear SVM with L1-norm regularization and 6 features that had no significant correlations within them were finally selected.The radiomics classifier constructed using the 6 features featured an AUC value of 0.669(specificity:0.506;sensitivity:0.773)with LDA.Furthermore,the composite index(Radscore)had statistically significant difference between the KRAS mutation and wild groups.It is suggested that the MRI-based radiomics has the potential in predicting the KRAS status in patients with rectal cancer,which may enhance the diagnostic value of MRI in rectal cancer.

Co-location of QTL for Sclerotinia stem rot resistance and flowering time in Brassica napus

Sclerotinia stem rot(SSR) caused by Sclerotinia sclerotiorum(Lib.) de Bary is one of the most devastating diseases of Brassica napus worldwide. Both SSR resistance and flowering time(FT) adaptation are major breeding goals in B. napus. However, early maturing rapeseed varieties, which are important for rice-rapeseed rotation in China, are often highly susceptible to SSR. Here, we found that SSR resistance was significantly negatively correlated with FT in a natural population containing 521 rapeseed inbred lines and a double haploid(DH) population with 150 individual lines, both of which had great variation in FT. Four chromosomal regions on A2, A6, C2, and C8 affecting both SSR resistance and FT were identified using quantitative trait loci(QTL) mapping after constructing a high-density genetic map based on single nucleotide polymorphism markers in the DH population.Furthermore, we aligned QTL for the two traits identified in the present and previous studies to the B. napus reference genome, and identified four colocalized QTL hotspots of SSR resistance and FT on A2(0–7.7 Mb), A3(0.8–7.5 Mb), C2(0–15.2 Mb), and C6(20.2–36.6 Mb). Our results revealed a genetic link between SSR resistance and FT in B.napus, which should facilitate the development of effective strategies in both early maturing and SSR resistance breeding and in map-based cloning of SSR resistance QTL.

Study of the Preparation Technology and Mechanics of the Compound Temperature-Humidity Sensor

The development and character of compound temperature-humidity sensor were discussed in this study.The design of sampling,control and output unit of temperature-humidity sensor as well as their manufacture method and character were studied in detail.The relationship between components of humidity resistance materials and negative temperature coefficient ( NTC) thermistor materials in sampling unit of compound sensor and character of electrical resistance and temperature was obtained.Couples of character curves of compound temperature-humidity sensor and data of materials of sampling unit were shown in this paper too.

Energy-Efficient Optimal Guaranteed Cost Intermittent-Switch Control of a Direct Expansion Air Conditioning System

To improve the energy efficiency of a direct expansion air conditioning(DX A/C) system while guaranteeing occupancy comfort, a hierarchical controller for a DX A/C system with uncertain parameters is proposed. The control strategy consists of an open loop optimization controller and a closed-loop guaranteed cost periodically intermittent-switch controller(GCPISC). The error dynamics system of the closed-loop control is modelled based on the GCPISC principle. The difference,compared to the previous DX A/C system control methods, is that the controller designed in this paper performs control at discrete times. For the ease of designing the controller, a series of matrix inequalities are derived to be the sufficient conditions of the lower-layer closed-loop GCPISC controller. In this way, the DX A/C system output is derived to follow the optimal references obtained through the upper-layer open loop controller in exponential time, and the energy efficiency of the system is improved. Moreover, a static optimization problem is addressed for obtaining an optimal GCPISC law to ensure a minimum upper bound on the DX A/C system performance considering energy efficiency and output tracking error. The advantages of the designed hierarchical controller for a DX A/C system with uncertain parameters are demonstrated through some simulation results.

Association mapping and domestication analysis to dissect genetic improvement process of upland cotton yield-related traits in China

Background: Cotton fiber yield is a complex trait,which can be influenced by multiple agronomic traits.Unravelling the genetic basis of cotton fiber yield-related traits contributes to genetic improvement of cotton.Results: In this study,503 upland cotton varieties covering the four breeding stages(BS1–BS4,1911–2011)in China were used for association mapping and domestication analysis.One hundred and forty SSR markers significantly associated with ten fiber yield-related traits were identified,among which,29 markers showed an increasing trend contribution to cotton yield-related traits from BS1 to BS4,and 26 markers showed decreased trend effect.Four favorable alleles of 9 major loci(R^(2)≥3)were strongly selected during the breeding stages,and the candidate genes of the four strongly selected alleles were predicated according to the gene function annotation and tissue expression data.Conclusions :The study not only uncovers the genetic basis of 10 cotton yield-related traits but also provides genetic evidence for cotton improvement during the cotton breeding process in China.

Identification of candidate genes controlling fiber quality traits in upland cotton through integration of meta-QTL,significant SNP and transcriptomic data

Background:Meta-analysis of quantitative trait locus(QTL)is a computational technique to identify consensus QTL and refine QTL positions on the consensus map from multiple mapping studies.The combination of meta-QTL intervals,significant SNPs and transcriptome analysis has been widely used to identify candidate genes in various plants.Results:In our study,884 QTLs associated with cotton fiber quality traits from 12 studies were used for meta-QTL analysis based on reference genome TM-1,as a result,74 meta-QTLs were identified,including 19 meta-QTLs for fiber length;18 meta-QTLs for fiber strength;11 meta-QTLs for fiber uniformity;11 meta-QTLs for fiber elongation;and 15 meta-QTLs for micronaire.Combined with 8589 significant single nucleotide polymorphisms associated with fiber quality traits collected from 15 studies,297 candidate genes were identified in the meta-QTL intervals,20 of which showed high expression levels specifically in the developing fibers.According to the function annotations,some of the 20 key candidate genes are associated with the fiber development.Conclusions:This study provides not only stable QTLs used for marker-assisted selection,but also candidate genes to uncover the molecular mechanisms for cotton fiber development.

Molecular and in vitro biochemical assessment of chemosensory protein 10 from brown planthopper Nilaparvata lugens at acidic pH

Chemosensory proteins(CSPs)are important molecular components of the insect olfactory system,which are involved in capturing,binding,and transporting hydrophobic odour molecules across the sensillum in sensillar lymph in regulating insect behavior.This protein family(CSPs)is also involved in many other systems that are not linked to olfactory receptors in olfactory sensilla.The brown planthopper(BPH)is a monophagous pest of rice that causes damage by sucking phloem sap and transmitting a number of diseases caused by viruses.In this study,fluorescence competitive binding assay and fluorescence quenching assay at acidic p H were performed as well as homology modelling to describe the binding affinity of Nlug CSP10.Fluorescence competitive binding assay(FCBA)demonstrated that Nlug CSP10 bound strongly to nonadecane,farnesene,and 2-tridecanone at acidic p H.The results of FCBA indicated that Nlug CSP10 bound different ligands at the physiological p H(5.0)of the bulk sensillum lymph.Fluorescence quenching assay demonstrated that Nlug CSP10 generated a stable complex with 2-tridecanone,while two ligands nonadecane and farnesene collided due to molecular collisions.The interaction of selected ligands with the modelled structure of Nlug CSP10 was also analyzed,which found the key amino acids(Gln23,Gln24,Gln25,Asn27,Met33,Ser34,Ile35,Tyr36,Asn42,Met43,Val45,Asn46,Asn93,Arg96,Ala97,Lys99,and Ala100)in Nlug CSP10 that were involved in binding of volatile compounds.The present study contributes to the binding profile of Nlug CSP10 that promotes the development of behaviorally active ligands based on BPH olfactory system.

Discovery of human coronaviruses pan-papain-like protease inhibitors using computational approaches

The papain-like protease(PLpro)is vital for the replication of coronaviruses(Co Vs),as well as for escaping innate-immune responses of the host.Hence,it has emerged as an attractive antiviral drug-target.In this study,computational approaches were employed,mainly the structure-based virtual screening coupled with all-atom molecular dynamics(MD)simulations to computationally identify specific inhibitors of severe acute respiratory syndrome coronavirus 2(SARS-Co V-2)PLpro,which can be further developed as potential pan-PLprobased broad-spectrum antiviral drugs.The sequence,structure,and functional conserveness of most deadly human Co Vs PLprowere explored,and it was revealed that functionally important catalytic triad residues are well conserved among SARS-Co V,SARS-Co V-2,and middle east respiratory syndrome coronavirus(MERS-Co V).The subsequent screening of a focused protease inhibitors database composed of^7,000 compounds resulted in the identification of three candidate compounds,ADM13083841,LMG15521745,and SYN15517940.These three compounds established conserved interactions which were further explored through MD simulations,free energy calculations,and residual energy contribution estimated by MM-PB(GB)SA method.All these compounds showed stable conformation and interacted well with the active residues of SARS-Co V-2 PLpro,and showed consistent interaction profile with SARS-Co V PLproand MERS-Co V PLproas well.Conclusively,the reported SARS-Co V-2 PLprospecific compounds could serve as seeds for developing potent pan-PLprobased broad-spectrum antiviral drugs against deadly human coronaviruses.Moreover,the presented information related to binding site residual energy contribution could lead to further optimization of these compounds.

Genetic parameter estimation and genome-wide association study(GWAS) of red blood cell count at three stages in a Duroc×Erhualian pig population

Red blood cells play an essential role in the immune system.Moreover,red blood cell count(RBC) is an important clinical indicator of various diseases,including anemia,type 2 diabetes and the metabolic syndrome.Thus,it is necessary to reveal the genetic mechanism of RBC for animal disease resistance breeding.However,quite a few studies had focused on porcine RBC,especially at different stages.Thus,studies on porcine RBC at different stages are needed for disease resistant breeding.In this study,the porcine RBC of 20-,33-,and 80-day old were measured,and genetic parameter estimation and genome-wide association study(GWAS) were both performed.As a result,the heritability was about 0.6 at the early stages,much higher than that at 80 days.Nine novel genome wide significant single nucleotide polymorphisms(SNPs),located at Sus scrofa chromosome(SSC)3,4,8,9,10 and 15,respectively,were identified.Further,TGFβ2,TMCC2 and PPP1 R15 B genes were identified as important candidate genes of porcine red blood cell count.So different SNPs and candidate genes were found significantly associated with porcine RBC at different stages,suggesting that different genes might play key roles on porcine RBC at different stages.Overall,new evidences were offered in this study for the genetic bases of animal RBC,and that the SNPs and candidate genes would be useful for disease resistant breeding of pig.

Guidance for use of weights: an analysis of different types of weights and their implications when using SAS PROCs

SAS and other popular statistical packages provide support for survey data with sampling weights. For example, PROC MEANS and PROC LOGISTIC in SAS have their counterparts PROC SURVEYMEANS and PROC SURVEYLOGISTIC to facilitate analysis of data from complex survey studies. On the other hand, PROC MEANS and many other classic SAS procedures also provide an option for including weights and yield identical point estimates, but different standard errors (SEs), as their corresponding survey procedures. This paper takes an in-depth look at different types of weights and provides guidance on use of different SAS procedures.

Progress of Research on Origins of Life in China

The development of Chinese space science and technology plays a great role in promoting the researches in the field of the origin of life.With the multidisciplinary cooperation,there are fruitful achievements in this research field obtained over the past two years.This report summarizes the major progress of the basic researches about the origin of life in China during 2018–2020.