Mutational Processes Research Articles

Aberrant Expression of Sprouty2 In Human Colon Cancer

Purpose: The study investigates the role of Sprouty2 (SPRY2) in colorectal cancer (CRC) cell function. It found that SPRY2 inhibits the RAS/MAPK/ERK pathway and promotes cancer invasion in KRAS-WT CRC. However, it did not significantly alter p-ERK levels, cell proliferation, or invasion in KRAS-mutant CRCs. High SPRY2 expression was associated with shorter cancer-specific survival in both KRAS-WT and KRAS-mutant CRC patients. The study suggests that SPRY2 may promote invasion and progression in both types of CRC. Methods: The gene expression data were retrieved from Gene Expression Omnibus (GEO). Fold change, p.value t-test and David Functional analysis, hierarchical clustering was performed. Results: In this study, we identified altered genes involved in SPRY2 mutation in the colon and the relevant pathways to understand whether the SPRY2 mutation changes cancer progression. 4 genes of 5 genes were downregulated following the mutation in colon cancer cells. We identified a network between these genes and pathways they belong to. Pathway analysis showed that these genes are mostly associated with cancer cell proliferation. Conclusion: MAL2, ESRP1, CDH3, CXCL14 and CDH1 genes were found to be associated with in SPRY2 mutation in colon cancer pathogenesis. Almost all these genes are effective in the proliferation of cancer cells, especially during the SPRY2 mutation process. Therefore, it is hypothesized that downregulation or upregulation of these genes may affect colon cancer pathogenesis by reducing cell proliferation. And it is predicted that SPRY2 mutation may be an important factor for colon cancer.

Multiple evolutionary pressures shape identical consonant avoidance in the world’s languages

Languages disfavor word forms containing sequences of similar or identical consonants, due to the biomechanical and cognitive difficulties posed by patterns of this sort. However, the specific evolutionary processes responsible for this phenomenon are not fully understood. Words containing sequences of identical consonants may be more likely to arise than those without; processes of word form mutation may be more likely to remove than create sequences of identical consonants in word forms; finally, words containing identical consonants may die out more frequently than those without. Phylogenetic analyses of the evolution of homologous word forms indicate that words with identical consonants arise less frequently than those without. However, words with identical consonants do not die out more frequently than those without. Further analyses reveal that forms with identical consonants are replaced in basic meaning functions more frequently than words without. Taken together, results suggest that the underrepresentation of sequences of identical consonants is overwhelmingly a by-product of constraints on word form coinage, though processes related to word usage also serve to ensure that such patterns are infrequent in more salient vocabulary items. These findings clarify aspects of processes of lexical evolution and competition that take place during language change, optimizing communicative systems.

Topography of mutational signatures in non-small cell lung cancer: emerging concepts, clinical applications, and limitations.

The genome of a cell is continuously battered by a plethora of exogenous and endogenous processes that can lead to damaged DNA. Repair mechanisms correct this damage most of the time, but failure to do so leaves mutations. Mutations do not occur in random manner, but rather typically follow a more or less specific pattern due to known or imputed mutational processes. Mutational signature analysis is the process by which the predominant mutational process can be inferred for a cancer and can be used in several contexts to study both the genesis of cancer and its response to therapy. Recent pan-cancer genomic efforts such as "The Cancer Genome Atlas" have identified numerous mutational signatures that can be categorized into single base substitutions, doublet base substitutions, or small insertions/deletions. Understanding these mutational signatures as they occur in non-small lung cancer could improve efforts at prevention, predict treatment response to personalized treatments, and guide the development of therapies targeting tumor evolution. For non-small cell lung cancer, several mutational signatures have been identified that correlate with exposures such as tobacco smoking and radon and can also reflect endogenous processes such as aging, APOBEC activity, and loss of mismatch repair. Herein, we provide an overview of the current knowledge of mutational signatures in non-small lung cancer.

The clock-like accumulation of germline and somatic mutations can arise from the interplay of DNA damage and repair.

The rates at which mutations accumulate across human cell types vary. To identify causes of this variation, mutations are often decomposed into a combination of the single-base substitution (SBS) "signatures" observed in germline, soma, and tumors, with the idea that each signature corresponds to one or a small number of underlying mutagenic processes. Two such signatures turn out to be ubiquitous across cell types: SBS signature 1, which consists primarily of transitions at methylated CpG sites thought to be caused by spontaneous deamination, and the more diffuse SBS signature 5, which is of unknown etiology. In cancers, the number of mutations attributed to these 2 signatures accumulates linearly with age of diagnosis, and thus the signatures have been termed "clock-like." To better understand this clock-like behavior, we develop a mathematical model that includes DNA replication errors, unrepaired damage, and damage repaired incorrectly. We show that mutational signatures can exhibit clock-like behavior because cell divisions occur at a constant rate and/or because damage rates remain constant over time, and that these distinct sources can be teased apart by comparing cell lineages that divide at different rates. With this goal in mind, we analyze the rate of accumulation of mutations in multiple cell types, including soma as well as male and female germline. We find no detectable increase in SBS signature 1 mutations in neurons and only a very weak increase in mutations assigned to the female germline, but a significant increase with time in rapidly dividing cells, suggesting that SBS signature 1 is driven by rounds of DNA replication occurring at a relatively fixed rate. In contrast, SBS signature 5 increases with time in all cell types, including postmitotic ones, indicating that it accumulates independently of cell divisions; this observation points to errors in DNA repair as the key underlying mechanism. Thus, the two "clock-like" signatures observed across cell types likely have distinct origins, one set by rates of cell division, the other by damage rates.

A multimodal multi-objective differential evolution with series-parallel combination and dynamic neighbor strategy

Multimodal multi-objective optimization problems (MMOPs), which aim to identify as many optimal solutions as possible and exhibit multiple equivalent Pareto optimal solution sets (PSs) that correspond to the same Pareto optimal front (PF), commonly arise in a wide range of optimization problems in the real world. However, some dominated solutions that exhibit greater diversity in the decision space may be substituted by non-dominated solutions with a higher level of decision space crowding. To tackle this issue, this paper proposes a multimodal multi-objective differential evolution with series-parallel combination and dynamic neighbor strategy (MMODE_SPDN), which can balance convergence, objective space diversity and decision space diversity. Specifically, two archives are initially updated serially followed by the overall update of the parallel structure, in which the serial-first approach can enhance population diversity and the parallel structure can greatly reduce the amount of calculation. In addition, a dynamic neighbor strategy which utilizes adaptive selection among neighbors to generate difference vectors in the decision space and objective space and then adopts the main and auxiliary parent method during the mutation process is proposed. Furthermore, the utilization of an auxiliary archive and the clustering-based special crowding distance (CSCD) method are employed to facilitate the updating of the archive, thereby enhancing diversity. MMODE_SPDN is compared with other multimodal multi-objective optimization evolutionary algorithms (MMOEAs) on numerous test problems and the experimental results demonstrate that MMODE_SPDN exhibits superior performance.

An Underwater Passive Electric Field Positioning Method Based on Scalar Potential

In order to fulfill the practical application demands of precisely localizing underwater vehicles using passive electric field localization technology, we propose a scalar-potential-based method for the passive electric field localization of underwater vehicles. This method is grounded on an intelligent differential evolution algorithm and is particularly suited for use in three-layer and stratified oceanic environments. Firstly, based on the potential distribution law of constant current elements in a three-layer parallel stratified ocean environment, the mathematical positioning model is established using the mirror method. Secondly, the differential evolution (DE) algorithm is enhanced with a parameter-adaptive strategy and a boundary mutation processing mechanism to optimize the key objective function in the positioning problem. Additionally, the simulation experiments of the current element in the layered model prove the effectiveness of the proposed positioning method and show that it has no special requirements for the sensor measurement array, but the large range and moderate number of sensors are beneficial to improve the positioning effect. Finally, the laboratory experiments on the positioning method proposed in this paper, involving underwater simulated current elements and underwater vehicle tracks, were carried out successfully. The results indicate that the positioning method proposed in this paper can achieve the performance requirements of independent initial value, strong anti-noise capabilities, rapid positioning speed, easy implementation, and suitability in shallow sea environments. These findings suggest a promising practical application potential for the proposed method.

DNA mismatch and damage patterns revealed by single-molecule sequencing.

Mutations accumulate in the genome of every cell of the body throughout life, causing cancer and other diseases1,2. Most mutations begin as nucleotide mismatches or damage in one of the two strands of the DNA before becoming double-strand mutations if unrepaired or misrepaired3,4. However, current DNA-sequencing technologies cannot accurately resolve these initial single-strand events. Here we develop a single-molecule, long-read sequencing method (Hairpin Duplex Enhanced Fidelity sequencing (HiDEF-seq)) that achieves single-molecule fidelity for base substitutions when present in either one or both DNA strands. HiDEF-seq also detects cytosine deamination-a common type of DNA damage-with single-molecule fidelity. We profiled 134 samples from diverse tissues, including from individuals with cancerpredisposition syndromes, and derive from them single-strand mismatch and damage signatures. We find correspondences between these single-strand signatures and known double-strand mutational signatures, which resolves the identity of the initiating lesions. Tumours deficient in both mismatch repair and replicative polymerase proofreading show distinct single-strand mismatch patterns compared to samples that are deficient in only polymerase proofreading. We also define a single-strand damage signature for APOBEC3A. In the mitochondrial genome, our findings support a mutagenic mechanism occurring primarily during replication. As double-strand DNA mutations are only the end point of the mutation process, our approach to detect the initiating single-strand events at single-molecule resolution will enable studies of how mutations arise in a variety of contexts, especially in cancer and ageing.

Abstract IA020: Functional studies of genetic variation using precision genome editing

Abstract Tumor genomes often harbor a complex spectrum of single nucleotide mutations, small indels, and large chromosome rearrangements that can perturb coding and non-coding regions of the genome in ways that remain poorly understood. The mutational processes responsible for the genesis of these events are also not static; instead, they continue to operate throughout disease evolution and further diversify the genetic and phenotypic landscape of cancer cells. Mounting evidence suggests that tumor genotype can be an important determinant of disease progression and therapy response, such as by modulating the sensitivity or resistance of cancer cells to mutant-specific drugs. These types of observations have motivated efforts to treat cancers with genome-informed therapies, highlighting the need to understand how different genetic variants precisely affect gene function and overall tumor phenotypes. Variant-function maps that provide a mechanistic understanding of the biology driven by cancer-associated mutations are needed to design these types of treatment strategies. Precision genome editing technologies like base and prime editing are uniquely suited to tackle this problem. Nevertheless, deploying these methods for systematic variant-function studies and disease modeling in vivo has not been straightforward due to lack of robust and scalable platforms capable of assessing editing efficiency and precision, particularly at endogenous loci. With this goal in mind, we previously developed and applied high-throughput base editing ‘sensor’ approaches that link endogenous genome editing outcomes with synthetic DNA-based readouts and cellular fitness measurements. Using these approaches, we showed that several uncharacterized mutant p53 alleles drive cancer cell proliferation and in vivo tumor development. Building upon this work, we recently developed new prime editing guide RNA design tools and sensor-based approaches that similarly couple quantitative editing outcomes to cellular fitness, allowing us to significantly expand the breadth of cancer-associated mutations that can be interrogated using these precision genome editing technologies. In this talk, I will describe ongoing work using base and prime editing sensor libraries to probe the biological impact of thousands of functionally-distinct genetic variants in diverse types of protein-coding genes and families to learn how these influence various cancer phenotypes. I will also discuss how the implementation of these modular technologies will allow researchers to functionally disentangle the impact of endogenous and exogenous mutational processes on functional selection and tumor evolution with close to single base pair resolution. This generalizable precision genome editing framework will facilitate the functional interrogation of genetic variants across diverse biological contexts, providing much needed insight into cancer variant-function relationships that could be leveraged to develop more precise cancer treatment paradigms, including synthetic lethal therapies that exploit tumor genotype. Citation Format: Francisco J. Sánchez-Rivera, Samuel I. Gould, Alexandra N. Wuest, Kexin Dong, Grace A. Johnson, Alvin Hsu, Varun K. Narendra, Ondine Atwa, Stuart S. Levine, David R. Liu. Functional studies of genetic variation using precision genome editing [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr IA020.

Fuzzing JavaScript engines with a syntax-aware neural program model

Neural network language modeling has become a remarkable approach in the generation of test cases for fuzzing JavaScript engines. Fuzzers built upon neural language models offer several advantages. They obviate the need for manually developing code generation rules, enable the extraction of patterns from high-quality seed sets, and exhibit commendable portability. Nevertheless, existing works confront challenges in three key aspects: diminished language modeling performance attributable to extensive vocabularies, potential semantic errors within generated test cases, and the limitation of black-box fuzzing, which fails to leverage the internal feedback from the target engine.This paper proposes an innovative neural model-based grey-box fuzzing approach for JavaScript engines. We incorporate the context-free grammar of JavaScript into the neural language model to mitigate the challenges associated with extensive vocabularies, thereby enhancing the model’s performance. Furthermore, to enhance the semantic validity of the generated test cases, we introduce semantic constraints into the mutation process. Notably, this work pioneers the integration of grey-box testing into a fuzzer built upon a neural language model, thereby enhancing the exploration of deep paths. Our prototype, PMFuzz, surpasses NNLM-based counterparts in both language modeling performance and test case generation capabilities. PMFuzz demonstrates a high level of competitiveness in exploring the software state space when compared to traditional coverage-guided grey-box fuzzers. In our evaluation, PMFuzz successfully identified 20 new defects within mainstream JS engines. Eight of them have been confirmed and fixed. Moreover, upon applying our method to C compilers, PMFuzz has revealed 11 new defects.

Uncovering of NRAGE/JNK and PI3K/AKT pathways through serial WGS of patients with breast cancer.

e12577 Background: Cancer genomic sequencing has fundamentally advanced our understanding of the basic biology of this disease, and more recently, has offered method to guide and evaluate treatment in clinic. We performed whole-genome sequencing (WGS) on three consecutive tissue and blood samples from breast cancer patients: diagnosis, post-neoadjuvant chemotherapy, recurrence after curative resection. Methods: We performed WGS to compare the genetic profiles of the primary, surgical and recurrent samples (tissue and blood) to determine: (1) how closely related the genetics are among the primary, post-neoadjuvant chemotherapy, and the recurrent tumors, (2) whether there are variations in mutational processes among the primary, post- neoadjuvant chemotherapy, and recurrent tumor. WGS was performed on three patients for whom both tissue and blood were available at diagnosis, at surgery after neoadjuvant chemotherapy and at a recurrence. Results: As a result of somatic protein coding variant analysis, PIK3CA mutation was confirmed at the time of diagnosis tissue in all cases. Mutations were found at p.E545K in patient 14, p.R916C in patient 18, and p.R916C in patient 3. Among these, patients 14 and 18 had PIK3CA mutations even at the time of recurrence. In patient 14, the same PIK3CA mutation was found in 3 consecutive samples, but in patient 18, it changed from p.R916C at diagnosis to p.G480E at relapse. Furthermore, functional enrichment analysis identified a common NRAGE signaling system in the cfDNA. The NRAG pathway was found in the blood at diagnosis, surgery, and recurrence in all three patients. Conclusions: This study was a proof-of-concept study, in which we hypothesized that NRAGE/JNK and PI3K/AKT signaling pathways are involved in breast cancer recurrence and treatment response through WGS of consecutive samples. Further research is ongoing with larger numbers of patients.

Increased risk for thyroid carcinoma in patients with Li-Fraumeni syndrome.

10612 Background: Patients with Li-Fraumeni syndrome (LFS) are predisposed to a 90% lifetime risk of cancer, thus undergoing extensive cancer surveillance. While thyroid cancer is not a core LFS-associated malignancy, increased incidence of thyroid carcinoma has been reported within the LFS tumor spectrum. In the general population, thyroid cancer incidence has soared mainly via incidental detection. We investigated the rate of thyroid carcinoma in relation to p53 mutational process and increased screening. Methods: A retrospective chart review was conducted for clinico-pathological features for adult carriers of confirmed germline TP53 variants at three tertiary cancer centers. Standardized incidence ratio (SIR) was calculated using age, sex, and year-specific expected incidence rates of thyroid cancer from Surveillance, Epidemiology, and End Results (SEER) 1975 – 2020 data. Results: Among 600 patients from 400 families with LFS, 39 (6.5%) patients from 36 (9%) families developed thyroid carcinoma at an average age of 42 years (median = 40, ranged from 23 to 70 years of age). The majority of LFS patients with thyroid carcinoma were female (N=30, 77%). Thyroid carcinoma was the presenting cancer diagnosis in 17 (44%) patients. Over 70% of thyroid carcinoma diagnoses (N=31) were detected incidentally either via LFS cancer screening (N=12, 39%) or via an imaging study unrelated to LFS screening (N=10, 32%). All 39 thyroid carcinomas were of follicular cell origin (non-medullary), most were multifocal (67% of N=32), and 30% had nodal metastasis (N=10 of 33). Of 35 tumors with histologic data, papillary carcinoma (papillary, follicular, and tall cell subtypes) was most common (N=29, 83%), followed by follicular carcinoma (N=4, 11%) and oncocytic carcinoma (N=2, 6%). LFS patients most often underwent a total thyroidectomy (N=27, 69%) compared to a hemithyroidectomy (N=10, 26%) or hemithyroidectomy with completion surgery within three months (N=2, 5%). Intermediate to high risk of recurrence based on tumor characteristics was noted in 17 patients (44%), warranting consideration of radioactive iodine (RAI) therapy, including tall cell subtype (N=3), oncocytic or follicular histology, incomplete resection (N=2), extrathyroidal extension (N = 6), and greater than five positive lymph nodes (N=6). Five (29%) of these 17 patients received RAI. The SIR for thyroid carcinoma in LFS compared to SEER was 13 (95% CI 9.2-17.8, p<0.0001). The SIR was elevated for LFS patients diagnosed with thyroid carcinoma both prior to and after genetic testing (SIR 9.0, CI 5.3-14.2, p<0.0001 and SIR 20, CI 12.2- 30.9, p<0.0001, respectively). Conclusions: In this multi-institutional cohort, a 6-9% prevalence rate of thyroid carcinoma was observed in LFS patients and families, with >70% of the tumors identified incidentally. The rate of thyroid carcinoma in LFS is significantly elevated over the general population.

Mutations, substitutions, and selection: Linking mutagenic processes to cancer using evolutionary theory

Cancers are the product of evolutionary events, where molecular variation occurs and accumulates in tissues and tumors. Sequencing of this molecular variation informs not only which variants are driving tumorigenesis, but also the mechanisms behind what is fueling mutagenesis. Both of these details are crucial for preventing premature deaths due to cancer, whether it is by targeting the variants driving the cancer phenotype or by measures to prevent exogenous mutations from contributing to somatic evolution. Here, we review tools to determine both molecular signatures and cancer drivers, and avenues by which these metrics may be linked.

Pseudogenes in plasmid genomes reveal past transitions in plasmid mobility.

Evidence for gene non-functionalization due to mutational processes is found in genomes in the form of pseudogenes. Pseudogenes are known to be rare in prokaryote chromosomes, with the exception of lineages that underwent an extreme genome reduction (e.g. obligatory symbionts). Much less is known about the frequency of pseudogenes in prokaryotic plasmids; those are genetic elements that can transfer between cells and may encode beneficial traits for their host. Non-functionalization of plasmid-encoded genes may alter the plasmid characteristics, e.g. mobility, or their effect on the host. Analyzing 10832 prokaryotic genomes, we find that plasmid genomes are characterized by threefold-higher pseudogene density compared to chromosomes. The majority of plasmid pseudogenes correspond to deteriorated transposable elements. A detailed analysis of enterobacterial plasmids furthermore reveals frequent gene non-functionalization events associated with the loss of plasmid self-transmissibility. Reconstructing the evolution of closely related plasmids reveals that non-functionalization of the conjugation machinery led to the emergence of non-mobilizable plasmid types. Examples are virulence plasmids in Escherichia and Salmonella. Our study highlights non-functionalization of core plasmid mobility functions as one route for the evolution of domesticated plasmids. Pseudogenes in plasmids supply insights into past transitions in plasmid mobility that are akin to transitions in bacterial lifestyle.

Indel variation in the mitochondrial ND5 region supports monophyly of the tribe Hippoglossoidini (sensu Vinnikov et al. 2018) within the family Pleuronectidae

AbstractIndel (insertion–deletion) events observed in the genome represent irreversible mutational processes, making indel regions crucial characteristics for discussing phylogenetic relationships. The tribe Hippoglossoidini is a recently proposed taxonomic group based on the molecular phylogenetic analyses of both mitochondrial (mt) and nuclear DNA sequences. However, no synapomorphic characteristics have been identified within this tribe, either morphologically or molecularly. In the present study, we sequenced the ND5 region of mtDNA in the righteye flounder species and conducted interspecific comparisons. We found a 12 bp indel immediately upstream of the stop codon in the ND5 region. A comparative analysis of this region with outgroup species from the Paralichthyidae revealed that the indel was a unique insertion shared by the common ancestor of the Hippoglossoidini species, providing irreversible evidence to support the monophyly of this taxonomic group (synapomorphic characters).

#1193 Tracking kidney cancer initiation via somatic mutation analysis of pre-cancer cells from Von Hippel Lindau cancer predisposition syndrome

Abstract Background and Aims Somatic mutations promote the transition from a normal cell to a cancer clone. Little is known about the factors that promote mutation in normal tissues, but whole genome sequencing of pre-cancer cells, followed by mutational pattern analyses, is a revolutionary tool to understand somatic mutation mechanisms active during an individual's lifetime. In the kidney, we have shown that normal kidney tubule epithelial cells (TEC) derived from damaged PT display an excess of somatic mutations and a peculiar enrichment of mutations in exons and highly transcribed DNA compared to other cell types [1]. However, the direct contribution of this PT-specific mutational process to carcinogenesis needs further demonstration. Here, we have analyzed normal TEC that are genetically predisposed to evolve into clear cell renal cell carcinoma (ccRCC), as they harbor a germline heterozygous mutation in the tumor suppressor Von Hippel Lindau, VHL. Using this genetic model of tumor predisposition, we have tracked the PT-specific mutational process from normal cells to overt ccRCC. This study sheds light on the etiology of this mutational process, as well as its causative role in ccRCC. Method We detected somatic mutations in single genomes from normal kidney TEC from 8 control individuals and 7 VHL-disease patients in the age range 24-70. Different from our previous study [1], we isolated kidney tubule cells from the urine. Multiple TECs per individual were subjected to in vitro clonal expansion, followed by whole genome sequencing (WGS), a golden-standard method to obtain high confidence somatic mutation data. We analyzed concomitant somatic mutation- and gene expression-data from 58 clones, and expression data from 154 TEC clones. Results First, we compared our newly generated dataset (TECs obtained from urines) with our previous dataset (TECs obtained from kidney biopsies). QPCR measurements of marker gene expression and somatic mutational pattern analyses showed that the same two populations could be clonally expanded from both urines and kidney biopsies. One population expressed markers of proximal tubule (AQP1, SLC17A3) and tubule damage (VCAM1, KIM1), and showed an excess of somatic single base substitutions (SBSs). This TEC population was defined: VCAM1-PT cells. We characterized the types of SBSs that are more frequently found in VCAM1-PT genomes. The mutation spectrum was different from that induced by exposure to common mutagens, e.g. aristolochic acid, reactive oxygen species and tobacco. Normal cells, including TEC, fat and blood progenitors, showed mutation depletion in highly transcribed genes, in agreement with more efficient repair. Instead, VCAM1-PT cells showed an enrichment of specific SBS types, distinct from those induced by another transcription-coupled mutational process described in the liver. In vitro exposure of TECs to the alkylating agent ENU recapitulates some features of the spectrum of mutations observed in vivo, suggesting that VCAM1-PT cells might fail to repair damage induced by endogenous alkylating agents. The VCAM1-PT-specific mutational signature was observed in ccRCC, but not found in a variety of non-kidney cell-types and cancers. Importantly, the impact of the mutational signature was more evident in VCAM1-PT genomes from VHL-disease patients compared to similar samples from control individuals. Moreover, VCAM1-PT cells were more common (8-fold increase, chi squared test P = .026) in the urines of VHL-disease patients than in the urines of controls. Conclusion Our data show that TECs derived from damaged PTs are subjected to a specific somatic mutation process during adult life. The process is a distinctive feature of kidney cancer (ccRCC) genomes, and is more evident in patients affected by VHL-cancer predisposition syndrome. These data suggest that heterozygous loss of VHL facilitates a PT-specific, somatic mutation process involved in cancer initiation.

Probabilistic Chain-Enhanced Parallel Genetic Algorithm for UAV Reconnaissance Task Assignment

With the increasing diversity and complexity of tasks assigned to unmanned aerial vehicles (UAVs), the demands on task assignment and sequencing technologies have grown significantly, particularly for large UAV tasks such as multi-target reconnaissance area surveillance. While the current exhaustive methods offer thorough solutions, they encounter substantial challenges in addressing large-scale task assignments due to their extensive computational demands. Conversely, while heuristic algorithms are capable of delivering satisfactory solutions with limited computational resources, they frequently struggle with converging on locally optimal solutions and are characterized by low iteration rates. In response to these limitations, this paper presents a novel approach: the probabilistic chain-enhanced parallel genetic algorithm (PC-EPGA). The PC-EPGA combines probabilistic chains with genetic algorithms to significantly enhance the quality of solutions. In our approach, each UAV flight is considered a Dubins vehicle, incorporating kinematic constraints. In addition, it integrates parallel genetic algorithms to improve hardware performance and processing speed. In our study, we represent task points as chromosome nodes and construct probabilistic connection chains between these nodes. This structure is specifically designed to influence the genetic algorithm’s crossover and mutation processes by taking into account both the quantity of tasks assigned to UAVs and the associated costs of inter-task flights. In addition, we propose a fitness-based adaptive crossover operator to circumvent local optima more effectively. To optimize the parameters of the PC-EPGA, Bayesian networks are utilized, which improves the efficiency of the whole parameter search process. The experimental results show that compared to the traditional heuristic algorithms, the probabilistic chain algorithm significantly improves the quality of solutions and computational efficiency.

Genomic Context of SARS-CoV-2 Outbreaks in Farmed Mink in Spain during Pandemic: Unveiling Host Adaptation Mechanisms.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infects various mammalian species, with farmed minks experiencing the highest number of outbreaks. In Spain, we analyzed 67 whole genome sequences and eight spike sequences from 18 outbreaks, identifying four distinct lineages: B.1, B.1.177, B.1.1.7, and AY.98.1. The potential risk of transmission to humans raises crucial questions about mutation accumulation and its impact on viral fitness. Sequencing revealed numerous not-lineage-defining mutations, suggesting a cumulative mutation process during the outbreaks. We observed that the outbreaks were predominantly associated with different groups of mutations rather than specific lineages. This clustering pattern by the outbreaks could be attributed to the rapid accumulation of mutations, particularly in the ORF1a polyprotein and in the spike protein. Notably, the mutations G37E in NSP9, a potential host marker, and S486L in NSP13 were detected. Spike protein mutations may enhance SARS-CoV-2 adaptability by influencing trimer stability and binding to mink receptors. These findings provide valuable insights into mink coronavirus genetics, highlighting both host markers and viral transmission dynamics within communities.

Monitoring and Assessment of the Quality of Chlorinated Water in Schools

All water destined for human consumption must be subjected to disinfection processes via chlorination with the aim of eliminating the risk of the transmission of waterborne diseases. However, the treatment of water using this method leads to the formation of trihalomethanes (THMs), which are toxic compounds that may be ingested, inhaled, or absorbed by the skin, increasing the risk of carcinogenic and mutagenic processes. High trihalomethane concentrations in water may be directly related to physicochemical properties, such as temperature, pH, hardness, and potentially toxic metal concentrations. In this work, physicochemical characterization was performed and water quality was assessed with regard to the presence of trihalomethanes in 17 samples collected from points before and after storage in reservoirs. Atomic absorption spectroscopy to determine potentially toxic metals and the measurement of physicochemical properties demonstrated that all results were in accordance with the standards established by Brazilian legislation. Gas chromatography–mass spectrometry was used to determine levels of trihalomethanes in the water samples (trichloromethane, bromodichloromethane, chlorodibromomethane, and bromoform), which were also in accordance with the limits established by Brazilian legislation. Hierarchical clustering on principal components confirmed changes in the water quality depending on location. This work constitutes a paradigm for future studies on the monitoring of toxic organic compounds in water to avoid health problems in humans and animals.

A Hybrid Strategy Improved SPEA2 Algorithm for Multi-Objective Web Service Composition

A Hybrid Strategy Improved SPEA2 Algorithm for Multi-Objective Web Service Composition

Molecular mechanisms of Tetrastigma hemsleyanum Diels&Gilg against lung squamous cell carcinoma: From computational biology and experimental validation

Ethnopharmacological relevanceTetrastigma hemsleyanum （T. hemsleyanum）, valued in traditional medicine for its potential to boost immunity and combat tumors, contains uncharacterized active compounds and mechanisms. This represents a significant gap in our understanding of its ethnopharmacological relevance. Aim of the studyTo involve the mechanism of anti-lung cancer effect of T. hemsleyanum by means of experiment and bioinformatics analysis. Materials and methodsThe anticancer mechanism of T. hemsleyanum against lung squamous carcinoma (LUSC) in zebrafish was investigated. The LUSC model was established by injecting NCI–H2170 cells in the zebrafish and evaluating its anti-tumor efficacy. Next, component targets and key genes were obtained by molecular complex detection (MCODE) analysis and protein-protein interaction (PPI) network analysis. Component analysis of T. hemsleyanum was performed by UPLC-Q-TOF-MS. Molecular docking was used to simulate the binding activities of key potential active components to core targets were simulated using. Prognostic and pan-cancer analyses were then performed to validate the signaling pathways involved in the prognostic genes using gene set enrichment analysis (GSEA). Subsequently, Molecular dynamics simulations were then performed for key active components and core targets. Finally, cellular experiments were used to verify the expression of glutamate metabotropic receptor 3 (GRM3) and glutamate metabotropic receptor 7 (GRM7) in the anticancer effect exerted of T. hemsleyanum. ResultsWe experimentally confirmed the inhibitory effect of T. hemsleyanum on LUSC by transplantation of NCI–H2170 cells into zebrafish. There are 20 main compounds in T. hemsleyanum, such as procyanidin B1, catechin, quercetin, and kaempferol, etc. A total of 186 component targets of T. hemsleyanum and sixteen hub genes were screened by PPI network and MCODE analyses. Molecular docking and molecular dynamics simulation results showed that Gingerglycolipid B and Rutin had higher affinity with GRM3 and GRM7, respectively. Prognostic analysis, Pan-cancer analysis and verification experiment also confirmed that GRM3 and GRM7 were targets for T. hemsleyanum to exert anti-tumor effects and to participate in immune and mutation processes. In vitro experiments suggested that the inhibitory effect of T. hemsleyanum on cancer cells was correlated with GRM3 and GRM7. ConclusionIn vivo, in vitro and in silico results confirmed the potential anticancer effects against LUSC of T. hemsleyanum, which further consolidated the claim of its traditional uses.