Search Results (197)

Living systems can be understood as organized entities that capture, transform, and reproduce information. Classical gene-centered models explain adaptation through frequency changes driven by differential fitness, yet they often overlook the higher-order organization and causal closure that characterize living systems. Here we revisit several evolutionary frameworks, from the replicator equation to group selection and holobiont dynamics, and show that evolutionary change in population frequencies can be expressed as a Jeffreys divergence. Building on this foundation, we introduce a categorical model of Information Handlers (IHs), entities capable of self-maintenance, mutation, and combination. This abstract architecture illustrates the usefulness of category theory for framing evolutionary processes that range from very simple to highly complex. The same categorical scheme can represent basic allele-frequency change as well as more elaborate scenarios involving reproductive interactions, symbiosis, and other organizational layers. A key feature of the framework is that different levels of evolutionary change can be summarized through a measure that quantifies the information generated, thereby distinguishing diverse types of evolutionary transformation, such as individual and sexual selection, mate choice, or even holobiont selection. Finally, we show that the informational partition associated with host–microbiome pairings in holobionts generalizes the information-theoretic structure previously developed for non-random mating, revealing a common underlying architecture across biological scales. Full article

To cope with the highly stochastic nature of wind speed, we explored the development of a predictive methodology. Considering an absence of studies pertaining to wind speed prediction that utilise state-of-the-art fuzzy models, the proposed approach adopted a novel higher-order Takagi–Sugeno–Kang fuzzy model intermixed with variational mode decomposition. The novelty of the predictive fuzzy model arises from the enhancement of rule consequents to include generalised terms and the incorporation of model complexity into the training scheme. To optimise the model, two approaches are considered: an adaptive differential evolution and a surrogate-based optimisation algorithm. The evolutionary approach employed two populations and a dual mutation scheme. The surrogate-based optimisation employed a Bayesian framework by fitting a Gaussian process model to the objective function. The latter approach yielded accurate predictive results while rapidly reducing the training time of the fuzzy model. A sequential wrapper-based algorithm was developed to effectively determine the feature space. The variational mode decomposed wind speed data were predicted individually, using an associated optimised fuzzy model. The proposed method was applied to a real-world wind speed dataset with exceptional approximation results. Comparisons with several artificial intelligence models highlighted the effectiveness and statistical significance of the methodology. Full article

Phosphate-solubilizing microorganisms (PSMs) show promise for sustainable agriculture, yet inconsistent field performance limits their application. We investigated phosphate solubilization mechanisms in Enterobacter ludwigii strains GMG278, GMG291, GMG378 and Enterobacter soli GMG1156 through greenhouse wheat experiments, high-performance liquid chromatography (HPLC) organic acid analysis, and comparative genomics. Greenhouse trials demonstrated that bacterial inoculation compensated for phosphorus deficiency, with GMG291, GMG1156, and GMG278 showing superior performance. HPLC identified malic acid as the predominant secreted organic acid, with E. soli producing threefold higher concentrations than E. ludwigii strains. Phosphate solubilization efficiency followed the order FePO₄ > AlPO₄ > Ca₃(PO₄)₂, with maximal release (95.9–97.7 μg/mL) from iron phosphate despite lower malic acid secretion, suggesting siderophore involvement. An inverse correlation between malic acid levels and soluble phosphate concentrations likely reflects competitive bacterial phosphate uptake and secondary precipitation processes. Comparative genomics revealed missense mutations in the LuxR transcriptional regulator of strain GMG378 (Asp86Asn and Arg97Leu) near predicted DNA-binding domains, correlating with reduced solubilization capacity. Phosphate solubilization in Enterobacter proceeds primarily through metal–malic acid complex formation, with strain-specific efficiency linked to LuxR-regulated biofilm formation genes. These findings suggest PSM screening should incorporate biofilm-related genetic markers alongside acid production measurements. Full article

Yersinia pestis caused the three plague pandemics that claimed more than two hundred million human lives. There is still no vaccine that meets all WHO requirements, and many researchers continue to develop plague vaccines using various technological platforms. For example, researchers led by Roy Curtiss 3rd have developed a new approach to achieve controlled, delayed attenuation of bacterial pathogens. Mutants generated using this method were superior in protecting Y. pestis-infected mice immunized with strains generated using traditional gene knockout. However, further studies are needed to determine the safety and efficacy of these delayed-attenuated strains in other mammalian species in order to extrapolate on humans the data obtained in accordance with the FDA Animal Rule. Three Y. pestis strains, a Δcrp mutant, a mutant with arabinose-dependent regulated crp expression (araC P_BAD crp) or an araC P_BAD crp mutant cured of plasmid pPst were derived from virulent wild-type strain 231. To evaluate the safety, outbred mice or guinea pigs were immunized subcutaneously with serial tenfold dilutions of mutated strains. For vaccine studies, immunized animals were subcutaneously challenged with 200 LD₁₀₀ (lethal dose in all exposed subjects) of the wild-type Y. pestis strain. The challenge caused the death of 100% of naïve animals in controls. The Y. pestis strain 231Δcrp was nonlethal in mice at a dose of 10⁷ CFs. The LD₅₀ of the 231Δcrp strain in guinea pigs increased by at least 10⁷-fold compared to that of the wild-type strain. The LD₅₀s of the 231P_BAD-crp mutant in mice and guinea pigs were approximately 10⁴-fold and 10⁷-fold higher than those of Y. pestis 231, respectively. The 231P_BAD-crp(pPst¯) strain did not cause death in mice (LD₅₀ > 10⁷ CFU) and guinea pigs (LD₅₀ > 10⁹ CFU) when administered subcutaneously and was capable of inducing intense protective immunity in both species of laboratory animals. Our research has shown once again the necessity of balance between safety and effectiveness demonstrating the feasibility of further investigation of crp mutants as promising candidate plague vaccines. Full article

Hypertrophic cardiomyopathy (HCM) is a common and deadly cardiac disease characterized by enlarged myocytes, increased myocardial wall thickening, and fibrosis. A majority of HCM cases are associated with mutations in the β-myosin heavy chain (MYH7) converter domain locus, which leads to varied pathophysiological and clinical manifestations. Using base-editing technology, we generated mutant human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) harboring HCM-causing myosin converter domain mutations (MYH7 c.2167C>T [R723C]; MYH6 c.2173C>T [R725C]) to define HCM pathogenesis in vitro. In this study, we integrated transcriptomic analysis with phenotypic and molecular analyses to dissect the HCM disease mechanisms using MYH6/7 myosin mutants. Our KEGG analysis of bulk RNA-sequencing data revealed significant upregulation of transcripts associated with HCM in the mutant hiPSC-CMs. Further, in-depth transcriptomic analysis using Gene-Ontology (GO-term) analysis for biological process showed upregulation of several transcripts associated with heart development and disease. Notably, our analysis showed robust upregulation of cytoskeletal transcripts, including actin-cytoskeleton networks, sarcomere components, and other structural proteins in the mutant CMs. Furthermore, cellular and nuclear morphological analysis showed that the MYH6/7 mutation induced cellular hypertrophy and increased aspect ratio compared to the isogenic control. Immunostaining experiments showed marked sarcomere disorganization with lower sarcomeric order and higher dispersion in the mutant hiPSC-CMs, highlighting the remodeling of the myofibril arrangement. Notably, the MYH6/7 mutant showed reduced cortical F-actin expression and increased central F-actin expression compared to the isogenic control, confirming the cytoskeletal remodeling and sarcomeric organization during HCM pathogenesis. These pathological changes accumulated progressively over time, underscoring the chronic and evolving nature of HCM driven by the MYH6/7 mutations. Together, our findings provide critical insights into the cellular and molecular underpinnings of MYH6/7-mutation-associated disease. These findings offer valuable insights into HCM pathogenesis, aiding in future therapies. Full article

Because of the problem that the traditional unscented Kalman filter algorithm (UKF) may terminate the iteration due to the non-positive definite error covariance matrix during state of charge (SOC) estimation of lithium-ion battery, considering the unknown noise and current mutation during the actual operation of the battery, an SOC estimation method based on covariance adaptive singular value decomposition unscented Kalman filter (CA-SVDUKF) algorithm was proposed. Based on the singular value decomposition traceless Kalman filtering algorithm, the proposed CA-SVDUKF algorithm introduced an adaptive method of covariance matching to improve the algorithm’s anti-interference capability to unknown noise. Accordingly, an error covariance matrix adaptive method with adaptive scaling factor was proposed, which could reduce the influence of current mutation exerting on the estimated convergence rate. Taking the lithium-ion battery as the research object, the second-order RC equivalent circuit model of the lithium-ion battery was first built, and then the online parameters of the battery were identified. Finally, the CA-SVDUKF algorithm was used to complete the SOC estimation. The algorithm was simulated and verified under three working conditions: ordinary pulse condition, DST working condition, and US06 working condition. The experimental results showed that the algorithm had higher accuracy and stability compared with the traditional extended Kalman filter algorithm (EKF) and the UKF algorithm. The maximum absolute error was less than 0.6%, and the root mean square error was less than 0.3%, which could verify the effectiveness and superiority of the algorithm. Full article

The C1858T PTPN22 (R620W) variant has been implicated in the pathogenesis of several autoimmune disorders and represents a promising immunotherapeutic target for Type 1 diabetes. We have been implementing a novel immunotherapeutic approach based on the use of lipoplexes that deliver siRNA duplexes. The efficacy and safety of lipoplexes was previously demonstrated in vitro in halting variant expression in the peripheral blood of patients. Preclinical safety and efficacy must be ascertained in vivo in appropriate animal models before clinical investigations can be undertaken, according to regulatory authorities in Europe. In the light of the foregoing, this study aims to verify that lipoplexes against the murine Ptpn22-R619W, equivalent to the human PTPN22-R620W, could be used for animal experimentation. The murine fibroblast cell line L929 was transfected with the PF62-pLentiPtpn22-R619W plasmid. We designed specific siRNA duplexes for the Ptpn22-R619W allele and formulated them into cationic lipoplexes in order to halt variant expression in the transfected L929 cell line. Transfection of fibroblasts expressing R619W using lipoplexes resulted in efficient silencing at 100 pmol siRNA after 48 h post-transfection, reaching higher significant knockdown after 72 h. Lipoplexes efficiently suppress pathogenic Ptpn22 variant expression in vitro, supporting the feasibility of a pre-clinical platform for testing of in vivo lipoplexes in CRISPR-engineered NOD/ShiLtJ mice carrying the R619W mutation. Full article

Campylobacter spp. remain among the most common pathogens causing acute diarrhea worldwide. Campylobacter jejuni and Campylobacter coli are the main species that cause gastroenteritis. Campylobacteriosis is a food-borne disease, although this Gram-negative bacterium may be transmitted via water-borne outbreaks as well as direct contact with animals, emphasizing its zoonotic potential. Campylobacterisosis does not usually require hospitalization. Antimicrobials are warranted only for patients with severe disease, as well as patients who are at risk for severe disease, such as the elderly, pregnant women or immunocompromised patients. Nonetheless, the irrational use of antibiotics in human and veterinary medicine enhances antimicrobial resistance (AMR). Resistance of Campylobacter spp. to fluoroquinolones, macrolides and tetracyclines is a significant concern to the scientific community. Point mutations, horizontal gene transfer and efflux pumps are the main mechanisms for the development and transmission of AMR in Campylobacter spp. Emerging evidence suggests that climate change may indirectly contribute to the spread of AMR in Campylobacter, particularly through its influence on bacterial ecology, transmission pathways and antibiotic use patterns. Higher temperatures and extreme weather events accelerate bacterial growth, amplify the transfer of AMR genes and magnify disease transmission, including drug-resistant infections. Horizontal gene transfer, especially in the context of biofilm formation, may further perplex the situation. Excessive farming and overuse of antibiotics as growth promoters in animals may also contribute to increased AMR rates. Climate change and AMR are interconnected and pose a significant threat to global public health. Multidisciplinary strategies mitigating both phenomena are crucial in order to contain the spread of Campylobacter-related AMR. The aim of this review is to describe the molecular mechanisms that result in AMR of Campylobacter spp. and underscore the association between climate change and Campylobacteriosis. Novel methods to mitigate Campylobacter-related AMR will also be discussed. Full article

The permutation flow shop scheduling problem (PFSP) is one of the hot issues in current research, and its production methods are widely used in steel, medicine, semiconductor, and other industries. Due to the characteristics of permutation flow (optimize the production process through the principle of symmetry to achieve efficient allocation and balance of resources), its task processes only need to be sorted on the first machine, and the subsequent machines are completely symmetrical with the first machine. This paper proposes an enhanced particle swarm optimization algorithm (EPSO) for the PFSP. Firstly, in order to enhance the diversity of the algorithm, a new dynamic inertia weight method was introduced to dynamically adjust the search range of particles. Secondly, a new speed update strategy was proposed, which makes full use of the information of high-quality solutions and further improves the convergence speed of the algorithm. Subsequently, an interference strategy based on individual mutations was designed, which improved the universality of the model’s global search. Finally, to verify the effectiveness of the EPSO algorithm, six benchmark functions were tested, and the results proved the superiority of the EPSO algorithm. In addition, the average relative error of the improved algorithm is at least 21.6% higher than that of the unimproved algorithm when solving large-scale PFSPs. Full article

CAR-T therapy has transformed the treatment of relapsed or refractory B-cell acute lymphoblastic leukemia (B-ALL), particularly in pediatric and young adult patients. Many studies report one-year overall survival rates of between 60% and 80% following therapy. Event-free survival rates at one year are around 50–70%, with 40–50% of patients in remission after two years. Despite these impressive results, disease relapse remains a problem. Future CAR-T cell platforms should target multiple antigens, and the optimal design of such constructs must be determined. Modern trials should explore the role of CAR-T cell therapy as a consolidation treatment for patients with high-risk ALL, including those with persistent minimal residual disease at the end of induction/consolidation therapy, an IKZF1-positive gene expression profile, or a TP53 mutation or Ph-like gene expression profile. Improving the efficiency of gene-editing methods could lead to higher success rates in creating CAR-T cells, as well as reducing manufacturing time and costs. Producing universal CAR-T cells from healthy donors could significantly reduce production time and costs. These issues underscore the dynamic and evolving nature of B-ALL research. Ongoing studies and clinical trials are addressing many of these challenges in order to improve outcomes for B-ALL patients and expand the applications of CAR-T cell therapy. Full article

The discovery of oncogenes and tumor suppressor genes provided important insights into the molecular pathogenesis of cancer but also revealed some contradictions in the prevailing somatic mutation theory. The evidence that noncoding RNAs (ncRNAs) form an elaborate network that regulates the flow of genetic information in eukaryotic cells offers an explanation for the inconsistencies. ncRNAs comprise a wide variety of molecules that interact with one another as well as with other RNAs, DNA, and proteins, over whose activities they exert a regulatory influence. The outcome of the dynamic interactions of the cell’s biomolecules is the emergence of higher-order states of equilibrium, called attractor states, which correspond to the gene-expression configurations of distinct cell types. Attractor states are relatively stable systems, but they are susceptible to perturbation by a disturbing force, such as mutation. Mutations that disrupt the ncRNA network can enable the cell to undergo a state transition towards a potentially neoplastic one. This is the crux of tumorigenesis. An inquiry into the architecture of the ncRNA network and its role in tumorigenesis is required to complement our knowledge of the well-known cancer genes as well as serve as a guide in the design of new anticancer therapeutics. Full article

Existing smart contract honeypot detection approaches exhibit high false negatives and positives due to (i) their inability to generate transaction sequences triggering order-dependent traps and (ii) their limited code coverage from traditional fuzzing’s random mutations. In this paper, we propose a hybrid fuzzing framework for smart contract honeypot detection based on taint analysis, SCH-Hunter. SCH-Hunter conducts source-code-level feature analysis of smart contracts and extracts data dependency relationships between variables from the generated Control Flow Graph to construct specific transaction sequences for fuzzing. A symbolic execution module is also introduced to resolve complex conditional branches that fuzzing alone fails to penetrate, enabling constraint solving. Furthermore, real-time dynamic taint propagation monitoring is implemented using taint analysis techniques, leveraging taint flow information to optimize seed mutation processes, thereby directing mutation resources toward high-value code regions. Finally, by integrating EVM (Ethereum Virtual Machine) code instrumentation with taint information flow analysis, the framework effectively identifies and detects security-sensitive operations, ultimately generating a comprehensive detection report. Empirical results are as follows. (i) For code coverage, SCH-Hunter performs better than the state-of-art tool, HoneyBadger, achieving higher average code coverage rates on both datasets, surpassing it by 4.79% and 17.41%, respectively. (ii) For detection capabilities, SCH-Hunter is not only roughly on par with HoneyBadger in terms of precision and recall rate but also capable of detecting a wider variety of smart contract honeypot techniques. (iii) For the evaluation of components, we conducted three ablation studies to demonstrate that the proposed modules in SCH-Hunter significantly improve the framework’s detection capability, code coverage, and detection efficiency, respectively. Full article

The Black-winged Kite Optimization Algorithm (BKA) is likely to experience a sluggish convergence rate when confronted with the optimization of complex multimodal functions. The fundamental algorithm has a tendency to get stuck in local optima, thus rendering it arduous to identify the global optimal solution. When dealing with large-scale data or high-dimensional optimization challenges, the BKA algorithm entails significant computational expenses, which might lead to excessive memory usage or prolonged running durations. In order to enhance the BKA and tackle these problems, a revised Black-winged Kite Optimization Algorithm (TGBKA) that incorporates the Tent chaos mapping and Gaussian mutation strategies is put forward. The algorithm is simulated and analyzed alongside other swarm intelligence algorithms by utilizing the CEC2017 test function set. The optimization outcomes of the test functions and the function convergence curves indicate that the TGBKA demonstrates superior optimization precision, a quicker convergence speed, as well as robust anti-interference and environmental adaptability. It is also contrasted with numerous similar algorithms via simulation experiments in various scene models for Unmanned Aerial Vehicle (UAV) path planning. In comparison to other algorithms, the TGBKA produces a shorter flight route, a higher convergence speed, and stronger adaptability to complex environments. It is capable of efficiently addressing UAV path planning issues and improving the UAV’s path planning abilities. Full article

Active space debris removal is now integral to modern space exploration. In order to address the problem of a heterogeneous satellite swarm with different payloads carrying out the emergency active removal of space debris, this paper proposes a Multi-type Chromosome Fast Elitist Non-Dominated Sorting Genetic Algorithm (MC-NSGA-II). The algorithm is designed to enable the satellite swarm to execute multiple coupled tasks in succession with improved optimization efficiency. An arbitrary execution order may result in deadlock, where one or more satellites become trapped in an infinite waiting loop. In order to address the heterogeneous problem of satellites and task coupling constraints, a multi-type chromosome coding strategy is developed. To evaluate different allocation strategies, three optimization objectives—time consumption, fuel consumption, and task balance—are introduced. To align with the multi-type chromosome coding strategy, two distinct sorting methods are developed for crossover and mutation operations, ensuring that all offspring individuals meet the constraints. Additionally, the algorithm incorporates a dynamic parameter-setting strategy to enhance solution efficiency. Finally, comparative simulations validate the effectiveness and superiority of the proposed method. The results show that the high-quality solution search ability of the MC-NSGA-II algorithm is 23.07% higher than that of the standard NSGA-II algorithm. Full article

Background/Objectives: The MAST kinases are ancient AGC kinases associated with many human diseases, such as cancer, diabetes, and neurodevelopmental disorders. We set out to describe the origins and diversification of MAST kinases from a structural and bioinformatic perspective to inform future research directions. Methods: We investigated MAST-lineage kinases using database and sequence analysis. We also estimate the functional consequences of disease point mutations on protein stability by integrating predictive algorithms and AlphaFold. Results: Higher-order organisms often have multiple MASTs and a single MASTL kinase. MAST proteins conserve an AGC kinase domain, a domain of unknown function 1908 (DUF), and a PDZ binding domain. D. discoideum contains MAST kinase-like proteins that exhibit a characteristic insertion within the T-loop but do not conserve DUF or PDZ domains. While the DUF domain is conserved in plants, the PDZ domain is not. The four mammalian MASTs demonstrate tissue expression heterogeneity by mRNA and protein. MAST1-4 are likely regulated by 14-3-3 proteins based on interactome data and in silico predictions. Comparative ΔΔG estimation identified that MAST1-L232P and G522E mutations are likely destabilizing. Conclusions: We conclude that MAST and MASTL kinases diverged from the primordial MAST, which likely operated in both biological niches. The number of MAST paralogs then expanded to the heterogeneous subfamily seen in mammals that are all likely regulated by 14-3-3 protein interaction. The reported pathogenic mutations in MASTs primarily represent alterations to post-translational modification topology in the DUF and kinase domains. Our report outlines a computational basis for future work in MAST kinase regulation and drug discovery. Full article