Genomic Mutations Within the Host Microbiome: Adaptive Evolution or Purifying Selection

Next-generation sequencing technology has transformed our ability to assess the taxonomic composition functions of host-associated microbiota and microbiomes. More human microbiome research projects—particularly those that explore genomic mutations within the microbiome—will be launched in the next decade. This review focuses on the coevolution of microbes within a microbiome, which shapes strain-level diversity both within and between host species. We also explore the correlation between microbial genomic mutations and common metabolic diseases, and the adaptive evolution of pathogens and probiotics during invasion and colonization. Finally, we discuss advances in methods and algorithms for annotating and analyzing microbial genomic mutations.

An Improved Bald Eagle Search Algorithm with Cauchy Mutation and Adaptive Weight Factor for Engineering Optimization

The Bald Eagle Search algorithm(BES)is an emerging meta-heuristic algorithm.The algorithm simulates the hunting behavior of eagles,and obtains an optimal solution through three stages,namely selection stage,search stage and swooping stage.However,BES tends to drop-in local optimization and the maximum value of search space needs to be improved.To fill this research gap,we propose an improved bald eagle algorithm(CABES)that integrates Cauchy mutation and adaptive optimization to improve the performance of BES from local optima.Firstly,CABES introduces the Cauchy mutation strategy to adjust the step size of the selection stage,to select a better search range.Secondly,in the search stage,CABES updates the search position update formula by an adaptive weight factor to further promote the local optimization capability of BES.To verify the performance of CABES,the benchmark function of CEC2017 is used to simulate the algorithm.The findings of the tests are compared to those of the Particle Swarm Optimization algorithm(PSO),Whale Optimization Algorithm(WOA)and Archimedes Algorithm(AOA).The experimental results show that CABES can provide good exploration and development capabilities,and it has strong competitiveness in testing algorithms.Finally,CABES is applied to four constrained engineering problems and a groundwater engineeringmodel,which further verifies the effectiveness and efficiency of CABES in practical engineering problems.

A new era of mutation rate analyses: Concepts and methods

The mutation rate is a pivotal biological characteristic,intricately governed by natural selection and historically garnering considerable attention.Recent advances in high-throughput sequencing and analytical methodologies have profoundly transformed our understanding in this domain,ushering in an unprecedented era of mutation rate research.This paper aims to provide a comprehensive overview of the key concepts and methodologies frequently employed in the study of mutation rates.It examines various types of mutations,explores the evolutionary dynamics and associated theories,and synthesizes both classical and contemporary hypotheses.Furthermore,this review comprehensively explores recent advances in understanding germline and somatic mutations in animals and offers an overview of experimental methodologies,mutational patterns,molecular mechanisms,and driving forces influencing variations in mutation rates across species and tissues.Finally,it proposes several potential research directions and pressing questions for future investigations.

A rare missense PAX6 mutation causes atypical aniridia in a three-generation Chinese family

●AIM:To investigate the molecular diagnosis of a threegeneration Chinese family affected with aniridia,and further to identify clinically a PAX6 missense mutation in members with atypical aniridia.●METHODS:Eleven family members with and without atypical aniridia were recruited.All family members underwent comprehensive ophthalmic examinations.A combination of whole exome sequencing(WES)and direct Sanger sequencing were performed to uncover the causative mutation.●RESULTS:Among the 11 family members,8 were clinically diagnosed with congenital aniridia(atypical aniridia phenotype).A rare heterozygous mutation c.622C>T(p.Arg208Trp)in exon 8 of PAX6 was identified in all affected family members but not in the unaffected members or in healthy control subjects.●CONCLUSION:A rare missense mutation in the PAX6 gene is found in members of a three-generation Chinese family with congenital atypical aniridia.This result contributes to an increase in the phenotypic spectrum caused by PAX6 missense heterozygous variants and provides useful information for the clinical diagnosis of atypical aniridia,which may also contribute to genetic counselling and family planning.

Mutation in the Agrobacterium his I gene enhances transient expression in pepper

Agrobacterium-mediated plant transformation is widely used in plant genetic engineering.However,its efficiency is limited by plant immunity against Agrobacterium.Chili pepper(Capsicum annuum L.)is an important vegetable that is recalcitrant to Agrobacterium-mediated transformation.In this work,Agrobacterium was found to induce a strong immune response in pepper,which might be the reason for T-DNA being difficult to express in pepper.An Agrobacterium mutant screen was conducted and a point mutation in the hisI gene was identified due to a weak immune response and enhanced transient expression mediated by this Agrobacterium mutant in pepper leaves.Further genetic analysis revealed that histidine biosynthesis deficiency caused by mutations in many genes of this pathway led to reduced pepper cell death,presumably due to reduced bacterial growth.However,mutation analysis of threonine and tryptophan biosynthesis genes showed that the biosynthesis of different amino acids may play different roles in Agrobacterium growth and stimulating the pepper immune response.The possible application of Agrobacterium amino acid biosynthesis mutations in plant biology was discussed.

An adaptive physics-informed deep learning method for pore pressure prediction using seismic data

Accurate prediction of formation pore pressure is essential to predict fluid flow and manage hydrocarbon production in petroleum engineering.Recent deep learning technique has been receiving more interest due to the great potential to deal with pore pressure prediction.However,most of the traditional deep learning models are less efficient to address generalization problems.To fill this technical gap,in this work,we developed a new adaptive physics-informed deep learning model with high generalization capability to predict pore pressure values directly from seismic data.Specifically,the new model,named CGP-NN,consists of a novel parametric features extraction approach(1DCPP),a stacked multilayer gated recurrent model(multilayer GRU),and an adaptive physics-informed loss function.Through machine training,the developed model can automatically select the optimal physical model to constrain the results for each pore pressure prediction.The CGP-NN model has the best generalization when the physicsrelated metricλ=0.5.A hybrid approach combining Eaton and Bowers methods is also proposed to build machine-learnable labels for solving the problem of few labels.To validate the developed model and methodology,a case study on a complex reservoir in Tarim Basin was further performed to demonstrate the high accuracy on the pore pressure prediction of new wells along with the strong generalization ability.The adaptive physics-informed deep learning approach presented here has potential application in the prediction of pore pressures coupled with multiple genesis mechanisms using seismic data.

C634Y mutation in RET-induced multiple endocrine neoplasia type 2A:A case report

BACKGROUND Multiple endocrine neoplasia type 2(MEN2)is a rare,autosomal dominant endocrine disease.Currently,the RET proto-oncogene is the only gene implicated in MEN2A pathogenesis.Once an RET carrier is detected,family members should be screened to enable early detection of medullary thyroid carcinoma,pheochromocytoma,and hyperparatitity.Among these,medullary thyroid carcinoma is the main factor responsible for patient mortality.Accordingly,delineating strategies to inform clinical follow-up and treatment plans based on genes is paramount for clinical practitioners.CASE SUMMARY Herein,we present RET proto-oncogene mutations,clinical characteristics,and treatment strategies in a family with MEN2A.A family study was conducted on patients diagnosed with MEN2A.DNA was extracted from the peripheral blood of family members,and first-generation exon sequencing of the RET protooncogene was conducted.The C634Y mutation was identified in three family members spanning three generations.Two patients were sequentially diagnosed with pheochromocytomas and bilateral medullary thyroid carcinomas.A 9-yearold child harboring the gene mutation was diagnosed with medullary thyroid carcinoma.Surgical resection of the tumors was performed.All family members were advised to undergo complete genetic testing related to the C634Y mutation,and the corresponding treatments administered based on test results and associated clinical guidelines.CONCLUSION Advancements in MEN2A research are important for familial management,assessment of medullary thyroid cancer invasive risk,and deciding surgical timing.

Adaptive Trajectory Tracking Control for Nonholonomic Wheeled Mobile Robots:A Barrier Function Sliding Mode Approach

The trajectory tracking control performance of nonholonomic wheeled mobile robots(NWMRs)is subject to nonholonomic constraints,system uncertainties,and external disturbances.This paper proposes a barrier function-based adaptive sliding mode control(BFASMC)method to provide high-precision,fast-response performance and robustness for NWMRs.Compared with the conventional adaptive sliding mode control,the proposed control strategy can guarantee that the sliding mode variables converge to a predefined neighborhood of origin with a predefined reaching time independent of the prior knowledge of the uncertainties and disturbances bounds.Another advantage of the proposed algorithm is that the control gains can be adaptively adjusted to follow the disturbances amplitudes thanks to the barrier function.The benefit is that the overestimation of control gain can be eliminated,resulting in chattering reduction.Moreover,a modified barrier function-like control gain is employed to prevent the input saturation problem due to the physical limit of the actuator.The stability analysis and comparative experiments demonstrate that the proposed BFASMC can ensure the prespecified convergence performance of the NWMR system output variables and strong robustness against uncertainties/disturbances.

Prevalence, risk factors, and BRAF mutation of colorectal sessile serrated lesions among Vietnamese patients

BACKGROUND Sessile serrated lesions(SSLs)are considered precancerous colorectal lesions that should be detected and removed to prevent colorectal cancer.Previous studies in Vietnam mainly investigated the adenoma pathway,with limited data on the serrated pathway.AIM To evaluate the prevalence,risk factors,and BRAF mutations of SSLs in the Vietnamese population.METHODS This is a cross-sectional study conducted on patients with lower gastrointestinal symptoms who underwent colonoscopy at a tertiary hospital in Vietnam.SSLs were diagnosed on histopathology according to the 2019 World Health Organi-zation classification.BRAF mutation analysis was performed using the Sanger DNA sequencing method.The multivariate logistic regression model was used to determine SSL-associated factors.RESULTS There were 2489 patients,with a mean age of 52.1±13.1 and a female-to-male ratio of 1:1.1.The prevalence of SSLs was 4.2%[95%confidence interval(CI):3.5-5.1].In the multivariate analysis,factors significantly associated with SSLs were age≥40[odds ratio(OR):3.303;95%CI:1.607-6.790],male sex(OR:2.032;95%CI:1.204-3.429),diabetes mellitus(OR:2.721;95%CI:1.551-4.772),and hypertension(OR:1.650,95%CI:1.045-2.605).The rate of BRAF mutations in SSLs was 35.5%.CONCLUSION The prevalence of SSLs was 4.2%.BRAF mutations were present in one-third of SSLs.Significant risk factors for SSLs included age≥40,male sex,diabetes mellitus,and hypertension.

Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

Underwater four-quadrant dual-beam circumferential scanning laser fuze using nonlinear adaptive backscatter filter based on pauseable SAF-LMS algorithm

The phenomenon of a target echo peak overlapping with the backscattered echo peak significantly undermines the detection range and precision of underwater laser fuzes.To overcome this issue,we propose a four-quadrant dual-beam circumferential scanning laser fuze to distinguish various interference signals and provide more real-time data for the backscatter filtering algorithm.This enhances the algorithm loading capability of the fuze.In order to address the problem of insufficient filtering capacity in existing linear backscatter filtering algorithms,we develop a nonlinear backscattering adaptive filter based on the spline adaptive filter least mean square(SAF-LMS)algorithm.We also designed an algorithm pause module to retain the original trend of the target echo peak,improving the time discrimination accuracy and anti-interference capability of the fuze.Finally,experiments are conducted with varying signal-to-noise ratios of the original underwater target echo signals.The experimental results show that the average signal-to-noise ratio before and after filtering can be improved by more than31 d B,with an increase of up to 76%in extreme detection distance.

Ferroptosis biomarkers predict tumor mutation burden's impact on prognosis in HER2-positive breast cancer

BACKGROUND Ferroptosis has recently been associated with multiple degenerative diseases.Ferroptosis induction in cancer cells is a feasible method for treating neoplastic diseases.However,the association of iron proliferation-related genes with prognosis in HER2+breast cancer(BC)patients is unclear.AIM To identify and evaluate fresh ferroptosis-related biomarkers for HER2+BC.METHODS First,we obtained the mRNA expression profiles and clinical information of HER2+BC patients from the TCGA and METABRIC public databases.A four gene prediction model comprising PROM2,SLC7A11,FANCD2,and FH was subsequently developed in the TCGA cohort and confirmed in the METABRIC cohort.Patients were stratified into high-risk and low-risk groups based on their median risk score,an independent predictor of overall survival(OS).Based on these findings,immune infiltration,mutations,and medication sensitivity were analyzed in various risk groupings.Additionally,we assessed patient prognosis by combining the tumor mutation burden(TMB)with risk score.Finally,we evaluated the expression of critical genes by analyzing single-cell RNA sequencing(scRNA-seq)data from malignant vs normal epithelial cells.RESULTS We found that the higher the risk score was,the worse the prognosis was(P<0.05).We also found that the immune cell infiltration,mutation,and drug sensitivity were different between the different risk groups.The highrisk subgroup was associated with lower immune scores and high TMB.Moreover,we found that the combination of the TMB and risk score could stratify patients into three groups with distinct prognoses.HRisk-HTMB patients had the worst prognosis,whereas LRisk-LTMB patients had the best prognosis(P<0.0001).Analysis of the scRNAseq data showed that PROM2,SLC7A11,and FANCD2 were significantly differentially expressed,whereas FH was not,suggesting that these genes are expressed mainly in cancer epithelial cells(P<0.01).CONCLUSION Our model helps guide the prognosis of HER2+breast cancer patients,and its combination with the TMB can aid in more accurate assessment of patient prognosis and provide new ideas for further diagnosis and treatment.

Automatic modulation recognition of radio fuzes using a DR2D-based adaptive denoising method and textural feature extraction

The identification of intercepted radio fuze modulation types is a prerequisite for decision-making in interference systems.However,the electromagnetic environment of modern battlefields is complex,and the signal-to-noise ratio(SNR)of such environments is usually low,which makes it difficult to implement accurate recognition of radio fuzes.To solve the above problem,a radio fuze automatic modulation recognition(AMR)method for low-SNR environments is proposed.First,an adaptive denoising algorithm based on data rearrangement and the two-dimensional(2D)fast Fourier transform(FFT)(DR2D)is used to reduce the noise of the intercepted radio fuze intermediate frequency(IF)signal.Then,the textural features of the denoised IF signal rearranged data matrix are extracted from the statistical indicator vectors of gray-level cooccurrence matrices(GLCMs),and support vector machines(SVMs)are used for classification.The DR2D-based adaptive denoising algorithm achieves an average correlation coefficient of more than 0.76 for ten fuze types under SNRs of-10 d B and above,which is higher than that of other typical algorithms.The trained SVM classification model achieves an average recognition accuracy of more than 96%on seven modulation types and recognition accuracies of more than 94%on each modulation type under SNRs of-12 d B and above,which represents a good AMR performance of radio fuzes under low SNRs.

Adaptive Optimal Discrete-Time Output-Feedback Using an Internal Model Principle and Adaptive Dynamic Programming

In order to address the output feedback issue for linear discrete-time systems, this work suggests a brand-new adaptive dynamic programming(ADP) technique based on the internal model principle(IMP). The proposed method, termed as IMP-ADP, does not require complete state feedback-merely the measurement of input and output data. More specifically, based on the IMP, the output control problem can first be converted into a stabilization problem. We then design an observer to reproduce the full state of the system by measuring the inputs and outputs. Moreover, this technique includes both a policy iteration algorithm and a value iteration algorithm to determine the optimal feedback gain without using a dynamic system model. It is important that with this concept one does not need to solve the regulator equation. Finally, this control method was tested on an inverter system of grid-connected LCLs to demonstrate that the proposed method provides the desired performance in terms of both tracking and disturbance rejection.

Ovarian Tumors in Senegalese Women: Impact of D-Loop Mutations between Healthy and Cancerous Tissues

In Senegal in particular, ovarian cancer, which is one of the most common gynecological cancers, accounts for 2.8% of deaths. The most important risk factor is genetic, with 10% of cases occurring in a context of genetic predisposition. The sequencing of the human genome, which has led to the discovery of millions of sequence variations, makes it possible to study variations within sequences. These variations are limited to Single Nucleotide Polymorphisms (SNPs) and this common form of polymorphism occurs approximately every 1000 bases in the human genome and 1.8 million SNPs are currently listed according to [1]. The aim of this study is to gain a better understanding of the impact of mutations in the D-loop region of mtDNA on ovarian cancer in Senegalese women. This study involved searching for mutations in our study population after DNA extraction and sequencing. Mutations were found after a comparison of our sequences with the Cambridge reference sequence (NC_012920). The mutations found in the DNA studied extend from position 7 to position 16568 and most of these mutations are located in the hypervariate zones (HV1 and HV2). Heteroplasmy with three mutant alleles was also found in certain variants. Common mutations were found in both healthy and cancerous tissues, with almost identical frequencies in both types of tissue. This enabled us to understand the spread of tumor cells throughout the ovary.

Appropriate Combination of Crossover Operator and Mutation Operator in Genetic Algorithms for the Travelling Salesman Problem

Genetic algorithms(GAs)are very good metaheuristic algorithms that are suitable for solving NP-hard combinatorial optimization problems.AsimpleGAbeginswith a set of solutions represented by a population of chromosomes and then uses the idea of survival of the fittest in the selection process to select some fitter chromosomes.It uses a crossover operator to create better offspring chromosomes and thus,converges the population.Also,it uses a mutation operator to explore the unexplored areas by the crossover operator,and thus,diversifies the GA search space.A combination of crossover and mutation operators makes the GA search strong enough to reach the optimal solution.However,appropriate selection and combination of crossover operator and mutation operator can lead to a very good GA for solving an optimization problem.In this present paper,we aim to study the benchmark traveling salesman problem(TSP).We developed several genetic algorithms using seven crossover operators and six mutation operators for the TSP and then compared them to some benchmark TSPLIB instances.The experimental studies show the effectiveness of the combination of a comprehensive sequential constructive crossover operator and insertion mutation operator for the problem.The GA using the comprehensive sequential constructive crossover with insertion mutation could find average solutions whose average percentage of excesses from the best-known solutions are between 0.22 and 14.94 for our experimented problem instances.

An Adaptive Program Recommendation System for Multi-User Sharing Environment

More and more accounts or devices are shared by multiple users in video applications,which makes it difficult to provide recommendation service.Existing recommendation schemes overlook multiuser sharing scenarios,and they cannot make effective use of the mixed information generated by multi-user when exploring users’potential interests.To solve these problems,this paper proposes an adaptive program recommendation system for multi-user sharing environment.Specifically,we first design an offline periodic identification module by building multi-user features and periodically predicting target user in future sessions,which can separate the profile of target user from mixed log records.Subsequently,an online recommendation module with adaptive timevarying exploration strategy is constructed by jointly using personal information and multi-user social information provided by identification module.On one hand,to learn the dynamic changes in user-interest,a time-varying linear upper confidence bound(LinUCB)based on personal information is designed.On the other hand,to reduce the risk of exploration,a timeinvariant LinUCB based on separated multi-user social information from one account/device is proposed to compute the quality scores of programs for each user,which is integrated into the time-varying LinUCB by cross-weighting strategy.Finally,experimental results validate the efficiency of the proposed scheme.

Prevention of thromboembolic events after radical prostatectomy in patients with hereditary thrombophilia due to a factor V Leiden mutation by multidisciplinary coagulation management

Objective:To examine the perioperative impact of factor V Leiden mutation on thromboembolic events'risk in radical prostatectomy(RP)patients.With an incidence of about 5%,factor V Leiden mutation is the most common hereditary hypercoagulability among Caucasians and rarer in Asia.The increased risk of thromboembolic events is three-to seven-fold in heterozygous and to 80-fold in homozygous patients.Methods:Within our prospectively collected database,we analysed 33006 prostate cancer patients treated with RP between December 2001 and December 2020.Of those,patients with factor V Leiden mutation were identified.All patients received individualised recommendation of haemostaseologists for perioperative anticoagulation.Thromboembolic complications(deep vein thrombosis and pulmonary embolism)were assessed during hospital stay,as well as according to patient reported outcomes within the first 3 months after RP.Results:Overall,85(0.3%)patients with known factor V Leiden mutation were identified.Median age was 65(interquartile range:61-68)years.There was at least one thrombosis in 53(62.4%)patients and 31(36.5%)patients had at least one embolic event in their medical history before RP.Within all 85 patients with factor V Leiden mutation,we experienced no thromboembolic complications within the first 3 months after surgery.Conclusion:In our cohort of patients with factor V Leiden mutation,no thromboembolic events were observed after RP with an individualised perioperative coagulation management concept.This may reassure patients with this hereditary condition who are counselled for RP.

Solar adaptive optics systems for the New Vacuum Solar Telescope at the Fuxian Lake Solar Observatory

Adaptive optics(AO)is essential for high-quality ground-based observations with large telescopes because it counters the impact of wavefront aberrations caused by atmospheric turbulence.The new vacuum solar telescope(NVST)is one of the most important high-resolution solar observation instruments in the world.Three sets of solar adaptive optics systems have been developed and installed on this telescope:conventional adaptive optics,ground layer adaptive optics,and multi-conjugate adaptive optics.These have been in operation from 2018 to 2023.This paper details the development and application of solar adaptive optics on the NVST and discusses the newest instrumentation.

Genetically modified pigs with CD163 point mutation are resistant to HP-PRRSV infection

Porcine reproductive and respiratory syndrome(PRRS)is a globally prevalent contagious disease caused by the positive-strand RNA PRRS virus(PRRSV),resulting in substantial economic losses in the swine industry.Modifying the CD163 SRCR5 domain,either through deletion or substitution,can eff1ectively confer resistance to PRRSV infection in pigs.However,large fragment modifications in pigs inevitably raise concerns about potential adverse effects on growth performance.Reducing the impact of genetic modifications on normal physiological functions is a promising direction for developing PRRSV-resistant pigs.In the current study,we identified a specific functional amino acid in CD163 that influences PRRSV proliferation.Viral infection experiments conducted on Marc145 and PK-15CD163 cells illustrated that the mE535G or corresponding pE529G mutations markedly inhibited highly pathogenic PRRSV(HP-PRRSV)proliferation by preventing viral binding and entry.Furthermore,individual viral challenge tests revealed that pigs with the E529G mutation had viral loads two orders of magnitude lower than wild-type(WT)pigs,confirming effective resistance to HP-PRRSV.Examination of the physiological indicators and scavenger function of CD163 verified no significant differences between the WT and E529G pigs.These findings suggest that E529G pigs can be used for breeding PRRSV-resistant pigs,providing novel insights into controlling future PRRSV outbreaks.