This chapter explores the pivotal role of maize (Zea mays L.) in global nutrition, emphasizing its status as a staple food worldwide. It discusses maize's complex nutritional profile, including macronutrients, micronutrients, and dietary fiber. The chapter also covers biofortification efforts to enhance maize with essential nutrients, addresses nutritional concerns related to maize-centric diets, and explores genetic modification and agronomic strategies to boost nutrient-rich maize yields. Additionally, it delves into maize processing traditions, nutrient retention techniques, and the importance of promoting nutrient-rich maize varieties. The chapter outlines post-harvest strategies to combat nutrient loss and prevent contamination while emphasizing the significance of consumer education and diverse diets. Case studies illustrate the impact of improved maize nutrition and provide replicable strategies. The chapter concludes by considering emerging research and technology, identifying challenges, and proposing solutions to enhance maize's nutritional value in the future.

The mass production of mosquitoes at an industrial scale requires efficient sex separation, which can be achieved through mechanical, genetic or artificial intelligence means. Compared with others methods, the genetic sexing approach offers the advantage of limiting costs and space by removing females at larval stage. We recently developed a GSS in Aedes albopictus based on the sex linkage of the rdl gene to the M locus, conferring dieldrin resistance in males only. It has been previously reported that dieldrin ingested by larvae can be detected in adults and bioaccumulated in predators, raising the question of its use at a large-scale. In this context, we performed several experiments aiming at optimizing dieldrin selection by decreasing both dieldrin concentration and exposure time while maintaining a stable percentage of females averaging 1%. We showed that the previously used dieldrin exposure induced an important toxicity as it killed 60% of resistant males at larval stage. We could easily lower this toxicity by reducing the dose and/or the exposure time to recover nearly all resistant males. We then quantified the residues of dieldrin in resistant male adults and showed that dieldrin toxicity in larvae was positively correlated with dieldrin concentrations detected in adults. Interestingly, we showed that the use of reduced dieldrin exposure led to a dieldrin detection in adult males that was below the sensitivity threshold of the Gas Chromatography Mass Spectrometry detection method. Presented data show that dieldrin exposure can be adjusted to suppress toxicity in males while achieving efficient sexing and lowering the levels of dieldrin residues in adults to barely detectable levels.

In order to understand the genetic diversity of germplasm resources of kumquat in Guangxi, 14 kumquat germplasm resources in Guangxi and 12 accessions from other provinces were analyzed by using SRAP markers. In total, 19 primer pairs with high stability, good reproducibility, and high polymorphism were chosen for analysis of all the 26 kumquat genotypes. Among the 101 amplified bands, 87 (86.14%) were polymorphic. SRAP markers were analyzed by employing Principal Coordinate Analysis, Population Structure Analysis and Hierarchical Cluster Analysis (UPGMA). The classification results showed that 26 kumquat germplasm could be divided into 5 groups, including cultivated kumquat, intergeneric hybrid, wild kumquat from other provinces, wild kumquat from Guangxi and hybrid kumquat from Guangxi. Guangxi kumquat germplasm occurred high genetic diversity, which were clearly divided into 3 groups like cultivated kumquat, wild kumquat and kumquat hybrid. And the 8 cultivated kumquat varieties in Guangxi were further divided into two subgroups. Wild kumquat in Guangxi and wild kumquat in other provinces belong to different groups, meanwhile the hybrids of Guangxi kumquat form independent groups, thus indicated that Guangxi wild kumquat and kumquat hybrid possessed certain specificity, or they maybe belonged to different species. Among the tested 26 kumquat accessions, 23 unique genotype-specific SRAP markers were detected for 14 kumquat genotypes, which made it possible to surely identify them. For the remaining 12 accessions without genotype-specific markers, they were distinguished by various combinations of markers. These results may have certain importance for kumquat genetic research and cultivar selection.

: Urinary schistosomiasis caused by the parasite Schistosoma haematobium is the most common form of schistosomiasis. This parasite has a high potential for genetic exchange within parasite populations giving rise to the genetic diversity that is important for its survival. Genetic differ-ences may lead to some parasite strains being more immunogenic which may have a negative impact on management and control of schistosomiasis. Therefore, understanding these genetic differences in the parasite may lead to better management of the disease. A literature search was done on PubMed, African Journals online and Google scholar using predefined search terms such as urinary schistosomiasis, S. haematobium, genetic diversity in sub-Saharan Africa in com-bination with Boolean operators (AND, OR). The search included studies published from 2000-2020 that emphasised on genetic diversity of Schistosoma haematobium in sub-Saharan Africa. Sixteen studies from 18 sub-Saharan African countries that met the inclusion criteria were se-lected. Most studies conducted in these countries showed a high genetic diversity of Schistosoma haematobium studies with microsatellite markers being the most commonly used method for ge-netic diversity determination. Fisher’s exact test showed that the distribution of genetic diversity in sub-Saharan African regions was not statistically significant (p=0.768). The highest number of studies on genetic diversity of Schistosoma haematobium were conducted in West Africa with Ni-geria and Zimbabwe in Southern Africa conducting the most studies, 4/36 (11%) each. Results obtained show the need for continued monitoring of genetic variations in Schistosoma haemato-bium in sub- Saharan Africa. This will aid in understanding the epidemiology of disease, ad-vancing novel treatment and vaccine strategies.

The contexts where there is mining and agriculture activities are potential sources of risk to human health due to contamination by chemical mixtures. This study explored the association between the frequency of micronuclei and pesticides in regions with ferronickel (Montelibano, Córdoba) and gold (Nechí, Antioquia) mining, and a closed native mercury mine (Aranzazu, Caldas). A cross-sectional study was carried out with 247 residents in the mining regions. Sociodemographic, occupational, and toxicological variables were ascertained. Blood and urine samples were taken for pesticide analysis (12 organochlorines, organophosphates, and carbamates), 68 chemical elements were quantified in hair, and micronuclei (MN) were quantified in lymphocytes. The mixtures of chemical elements were grouped through exploratory factor analysis. Prevalence ratios (PR) were estimated with robust variance Poisson regressions to explore associations. The highest concentrations of chemical elements were in the active mines. The potentially most toxic chemical mixture was observed in the ferronickel mine. Pesticides were detected in a low proportion of participants. The frequency of MN was similar in the three mining contexts. There was great heterogeneity in the exposure to pesticides and chemical elements. The “hormetic effect” of selenium is described, in which at low doses it acts as a chelator and at high doses it can enhance the toxic effects of other elements. It is proposed that future studies in mining contexts include the measurement of chemical mixtures to better assess exposure and potential adverse health effects.

There are many theories of carcinogenesis arguing against the orthodox mutation theory, debating on such as “epigenetic alteration” that is inheritable and yet, theoretically, reversible. Our integrated theory describes that any extracellular, intracellular, or intranuclear stressors, mutagenic or not, can initiate a lengthy tumorigenesis to engender a benign or malignant tumor, but the aberrations directly establishing cellular immortality and autonomy may be epigenetic or genetic alterations in the genomic DNA. A neoplasm is considered a semi-new organism with autonomy; it therefore should have genetic mutations to be “new”. We may be able to direct cancer cells towards differentiation as a remedy, because the extracellular milieu may control the phenotype of a cell and the tissue or organ made of the cell’s progenies, and the cytoplasm of a cell may override the nucleus in the phenotypic control. However, the nucleus retains the capacity to manifest itself if allowed by the microenvironment, which then allows the already reversed cells to revert back to tumor cells again. Neoplasms are malignant if they bear epigenetic or genetic anomalies in mutator genes defined as those whose alterations allow or accelerate alterations to occur in other genes, whereas neoplasms are benign if they bear epigenetic or genetic aberrations only in non-mutator genes. It is imperative to identify the immediate tumor-causing cellular alterations defined as those directly responsible for immortality and autonomy, and for treatment purposes to identify the extracellular and intracellular factors that control the phenotype of cancer cells.

Dilated cardiomyopathy (DCM) is a common form of cardiomyopathy, characterized by ventricular chamber dilatation and systolic dysfunction, in the absence of coronary artery disease, arterial hypertension, valvular or congenital diseases. DCM is a heterogeneous group of disorders of the myocardium caused by genetic factors, environmental factors, or a combination of both. DCM affects mainly men aged between 20 and 50 years, being considered one of the main causes of heart failure (HF) and the main indication for heart transplantation. Guideline-based HF treatment is the mainstay of management for patients with DCM. In recent years, gene therapy and induced pluripotent stem cells have become promising strategies. In this review, we summarize the relevant clinical issues, and current treatment of DCM patients, including the role of genetic evaluation.

Recent studies indicated that Plasmodium vivax can infect Duffy-negative individuals, but the varied diagnostic and methodological approaches have limited our ability to characterize P. vivax across Africa. Here, we utilized a standardized approach to compare epidemiological and genetic attributes of P. vivax from Botswana, Ethiopia, and Sudan, where Duffy-positive and Duffy-negative individuals coexist. Among 1,215 febrile patients, the proportions of Duffy negativity range from 20-36% in East Africa to 84% in Southern Africa. Considerable differences were observed in P. vivax prevalence among Duffy-negative populations ranging from averaged 9.2% in Sudan to 86% in Botswana. P. vivax parasite density in Duffy-negative infections is significantly lower than in Duffy-positive infections. Phylogenetic analyses of 229 PvDBP sequences indicated that Duffy-negative P. vivax were not monophyletic but occurred in multiple well-supported clades, suggesting independent origins. Duffy-negative Africans are clearly not resistant to P. vivax and the public health significance should no longer be neglected.

Introduction: Parkinson’s disease (PD) patients harboring recessive gene variants exhibit a distinct clinical phenotype with an early disease onset and relatively mild symptoms. Data concerning individualized therapy for autosomal recessive PD forms are still scarce. Methods: Demographic and treatment data of a cohort of PD carriers of recessive genes (9 homozygous or compound heterozygous PRKN carriers, 4 Heterozygous PRKN carriers and 3 biallelic PINK1 carriers) were evaluated. Results: The average Levodopa Equivalent daily dose (LEDD) was 806.8±453.5 (range 152-1810) in PRKN carriers and 765±96.6 (range 660-850) in PINK1 carriers. The majority responded to low/moderate doses of Levodopa. The response to Dopamine Agonists (DA) was often favorable both as initial and longitudinal therapy. 8/13 PRKN and 1/3 PINK1 carriers were treated with amantadine successfully, and this also applied to patients who could not tolerate Levodopa or DA. Conclusions: In the era of personalized treatment, the therapeutic approach in recessive PD gene carriers might differ as compared to idiopathic PD. Lower LEDD doses were efficient even in patients with a very long disease duration, while a few patients were doing well without any Levodopa treatment decades after disease initiation. DA or amantadine could be used as a first and main line treatment regimen if well tolerated. Literature data on therapeutic strategies in carriers of pathogenic mutations in recessive PD genes, including device-aided treatments will be further discussed.

We present a very computationally light and fast approximation algorithm and then verify it with genetic algorithm and simulated annealing. We show that our algorithm is on par with GA and SA in terms of output produced while having a tightly bounded time complexity. Our algorithm works best when there is a strong positive correlation between the reliability of a component and its cost. We present two algorithms with the same essence. One of them is system cost bounded and the other is target reliability bounded. Our proposed algorithm works on a subsystem level redundancy instead of component level redundancy.

The construction industry has a notable negative impact on the environment; thus, the promotion of the use of timber structures is an alternative to mitigate its effects. The research develops an artificial intelligence-based decision approach in the calculation of timber structures focused on the enhancement of the sustainability of roof structures. Based on the optimization carried out through genetic algorithms and the framework established in Eurocode 5, a general set of equations has been proposed for a laminated timber roof structure. The tool, which determines the most suitable roof structure for each strength class of laminated timber, allows for the determination of the dimensions of beams and purlins and their respective separations in order to minimize wood consumption. The ultimate goal is to offer multiple solutions regarding strength classes and structural designs in order to foster informed sustainable choices that promote efficient use of resources in construction.

Genetic variability in rice breeding program plays the very crucial role. It provides outstanding pool of superior alleles governing better agronomic and quality characters through association mapping. For the understanding of population structure and genetic relationship among the different rice lines is indispensable prior to setting of correlation among dynamic alleles and traits. In the present investigation, genetic diversity and population structure of 116 rice accessions by using 64 polymorphic SSR markers was targeted for the evaluation of the genetic relatedness and diversity. Genotyping assessment based on SSR markers revealed a total of 225 alleles, with an average PIC value of 0.755. The germplasm lines were classified into three distinct subgroups through population structure analysis, utilizing both model and distance-based approaches. AMOVA analysis showed that 11% of the total variation could be attributed to differences between groups, while the remaining 89% of the variation was likely due to differences within groups. The study suggests that the population structure and genetic relatedness should be considered when working with the core collection of 116 rice germplasm lines for association mapping, aiming to establish marker-trait associations.

The use of multi-gene panels for germline testing in breast cancer enables the estimation of cancer risk and guides risk-reducing management options for tested individuals and their family members. We performed an analysis in our clinical database to identify breast cancer patients undergoing genetic testing with positive reports. We reviewed positive results with respect to the different levels of information provided in the reports; risk estimation and management, cascade family testing, information from secondary findings and actionable information for treatment decision-making. A total of 415 positive test reports were identified with 57.1%, 18.1%, 10.8% and 13.5% of individuals having pathogenic/likely pathogenic variants in high (BRCA1, BRCA2, PALB2, PTEN, TP53), moderate (ATM, CHEK2, NBN), low (BARD1, BRIP1, CHEK2, MLH1, MSH2, MSH6, NF1, RAD51C) and with insufficient evidence for breast cancer risk genes (FANCA, FANCM, NBN, MRE11, PMS2, RAD50, RAD51B, XRCC2, MUTYH), respectively. 6.7% of individuals were double heterozygotes with two pathogenic variants. Germline findings in 92% of individuals are linked to evidence-based treatment information and receive risk estimates for predisposition to breast and/or other cancer types. The use of germline findings for treatment decision making expands the indication of genetic testing to include individuals that could benefit from targeted treatments.

Peripheral arterial diseases (PAD) are complex cardiovascular conditions influenced by environmental factors and somatic mutations in multiple genes involved in hematopoiesis and inflammation. While traditional risk factors such as smoking, hypercholesterolemia, and hypertension have been extensively studied, the role of somatic mutations in PAD progression remains underexplored. This article aims to provide a comprehensive review of the molecular mechanisms, genetic landscape, prognostic significance, and clinical implications of somatic mutations in PAD. The expansion of clonal hematopoiesis of indeterminate potential (CHIP) clones in the circulating blood, named clonal hematopoiesis (CH), leads to the infiltration of these clones into atherosclerotic plaques and the production of inflammatory cytokines, increasing the risk of cardiovascular diseases including PAD. Furthermore, recent experimental evidence has demonstrated the involvement of somatically mutated TP53 genes with a high variant allele frequency (VAF) in PAD development and prognosis. The review delves into the relationship between CH and PAD, elucidating the prevalence, impact, and underlying mechanisms of this association. This understanding paves the way for novel therapeutic approaches targeting CHIP to promote tissue regeneration and improve outcomes in PAD patients. It emphasizes the need for further re-search to fully unravel the genetic footprint of the disease and highlights potential clinical implications. The findings presented in this article lay the foundation for personalized medicine approaches and open avenues for the development of targeted therapies based on somatic mutation profiling.

Accurate and efficient battery modeling is essential to maximize the performance of isolated energy systems and to extend battery lifetime. This paper proposes a battery model that represents the charging and discharging process of a lead-acid battery bank. This model is validated over real measures taken from a battery bank installed in a research center placed at “El Chocó”, Colombia. In order to fit the model, three optimization algorithms (Particle Swarm Optimization, Cuckoo Search, and Particle Swarm Optimization+Perturbation) are implemented and compared, being the last one a new proposal. This research shows that the model with the proposed algorithm is able to estimate and manage the real battery characteristics as SOC and charging/discharging voltage. The comparison between simulations and real measures shows that the model is able to absorb reading problems, signal delays, and scaling errors. The approach we present can be implemented in other types of batteries especially those used in stand-alone systems.

The problem of scheduling is an area that has attracted a lot of attention from researchers for many years. Its goal is to optimize resources in the system. The assigning task to the lecturer is an example of the timetabling problem, a class of scheduling. This study introduces a mathematical model to assign fixed tasks (the time and required skills to be fixed) to university lecturers. Our model is capable of generating a calendar that maximizes faculty expectations. The formulated problem is in the form of a multi-objective problem that optimal makes decisions require the trade-off presence of trade-offs between two or more conflicting objectives. To solve this, we use the Compromise Programming approach to multi-objective programming. We then proposed the new version of the Genetic Algorithm to solve the introduced model. Finally, the model and algorithm tested with real scheduling data collected at the Computing Fundamental Department, FPT University, Hanoi, Vietnam.

To achieve an acceptable level of security on the web, the Completely Automatic Public Turing test to tell Computer and Human Apart (CAPTCHA) was introduced as a tool to prevent bots from doing destructive actions such as downloading or signing up. Mobile devices have small screens, and therefore, using the common CAPTCHA methods (e.g. text CAPTCHAs) in these devices raises usability issues. To introduce a reliable, secure, and usable CAPTCHA that is suitable for mobile devices, this paper introduces a hand gesture recognition CAPTCHA based on applying Genetic Algorithm (GA) principles on Multi-Layer Perceptron (MLP). The proposed method improves the performance of MLP-based hand gesture recognition. It has been trained and evaluated on 2201 videos of the IPN Hand dataset, and MSE and RMSE benchmarks report the index values of 0.0018 and 0.0424, respectively. Comparison with the related works shows a minimum of 1.79% fewer errors, and experiments produced a sensitivity of 93.42% and accuracy of 92.27% – 10.25% and 6.65% improvement compared to the MLP implementation.

This document introduces a new cryptosystem mixing two improvement standards generally used for text encryption, in order to give birth a new color image encryption algorithm capable of dealing with known attacks. Firstly, two substitution matrixes attached to a strong replacement function will be generated for advanced Vigenere technique application. At the end of this first round, the output vector is subdivided into size blocks according to the used chaotic map, for acting a single enhanced Hill circuit insured by a large inversible matrix. A detailed description of such a large involutive matrix constructed using Kronecker products will be given. accompanied by a dynamic translation vector to eliminate any linearity. A solid chaining is established between the encrypted block and the next clear block to avoid any differential attack. Simulations carried out on a large volume of images of different sizes and formats ensure that our approach is not exposed to any known attacks.

In the rescue operations the full time of action plays important role. It is a sum of planning, travel, and manipulation (in the action place) phases times. The time minimization of first two phases by autonomous vehicle for remote action is considered in the paper. For known a priori map the path planning consists of local optimal decision collected next in the general algorithm of the optimal path. Such approach significantly reduces time of path planning. The robot features and known sparse obstacles reduce the allowable robot speeds. The time of travel is calculated from allowable velocity profile. So, it can be used to estimate the travel performance. Genetic algorithm and random search-based methods for path finding with travel time optimization are exploited and compared in the paper. All the proposed time optimisation solutions of rescue operation are checked during computer simulations and results of simulation are presented.

The emergence of multi-drug resistant E. coli is an important matter of increasing considerable concern to global public health. The aim of this study was to investigate the incidence, antibiotic resistance pattern, phylogroups and genetic variation of E. coli isolates from raw milk, vegetable salad and ground meat samples. Methods: Culture-based techniques, Kirby-Bauer disk diffusion susceptibility testing, PCR and RAPD assays were used to determine the incidence rate, antimicrobial resistance pattern, phylogenetic groups and genetic diversity of the E. coli isolates. Results: E. coli isolates were highly resistant to amoxicillin (79.16%), trime-thoprim-sulfamethoxazole (70.83%), amoxicillin-clavulanic acid (62.50%), tetracycline (54.16%), chloramphenicol (54.16%), nitrofurantoin (54.16%), ampicillin (45.83%), streptomycin (45.83%), and kanamycin (33.33%); and completely susceptible to norfloxacin and azithromycin. 70.83% of the isolates were multi-drug resistant. Most E. coli isolates (46%) belonged to phylogroup A. RAPD with UBC245 primer categorized the isolates into 11 clusters. A high level of genetic di-versity was found among the isolates; however, 33.3% of the isolates were grouped in a major cluster (R5). Conclusions: Antibiotic resistance patterns are randomly distributed among the ge-netic clusters. Novel, practical, efficient food safety control and surveillance systems of multi-drug resistant foodborne pathogens are required to control the foodborne pathogen contamina-tion.

During the 1970s, Tunisian durum wheat landraces were replaced progressively by modern cultivars. These landraces are nowadays maintained by smallholder farmers in some ecological niches and are threatened gradually by extinction resulting on the narrowing of the genetic diversity. This study aims to investigate patterns of phenotypic variability using twelve quantitative traits in a panel of 189 durum wheat landraces and seven checks, based on farmer’s population name attribution and genetic structure. Our results showed high phenotypic variability among and within landraces and checks for the majority of the studied traits. The principal components analysis showed similar grouping using farmers name attribution and genetic structure using K = 6, which confirmed the identification of a new gene pool in the oases of Tunisia, represented by the sub-population Jenah Zarzoura and the robustness and high relationships between phenotypic and genome-wide genetic structure using DArTseq method. These findings will enhance the conservation efforts of these landraces and their use in breeding efforts at national and international levels to adapt to dry conditions.

Material Extrusion is a popular additive manufacturing technology due to its low cost, wide market availability, ability to construct complex parts, safety, and cleanliness. However, optimizing the process parameters to obtain the best possible mechanical properties has not been extensively studied. This paper aims to develop ensemble learning-based models to predict the ultimate tensile strength, Young's modulus, and strain at break of PLA and PLA-CF 3D-printed parts, using printing temperature, printing speed, and layer thickness as process parameters. Additionally, the study investigates the impact of process parameters and material selection on the mechanical properties of the printed parts and uses Genetic Algorithms for multi-objective optimization according to user specifications. The results indicate that process parameters and material selection significantly influence the mechanical properties of the printed parts. The Genetic Algorithm successfully identifies optimal parameter values for the desired mechanical properties. Moreover, this work is the first to model Process-Structure-Properties relationships for an additive manufacturing process and to use a multi-objective optimization approach for multiple mechanical properties, utilizing ensemble learning-based algorithms and Genetic Algorithms.

Service pricing is a bottleneck in the development of innovation services, as it is the issue of most concern between the suppliers and demanders. In this paper, a negotiation pricing model that is based on the multiobjective genetic algorithm is developed for innovation service pricing. Regarding the service pricing process as a multiobjective problem, the objective functions, which include the service price, service efficiency, and service quality, for suppliers and demanders are constructed. As the solution of a multiobjective problem is typically a series of alternatives, another negotiation process is necessary for determining the final decision. A learning strategy is adopted during the negotiation process to simulate reality. Finally, the model is implemented for an innovation service transaction, the objective of which is to identify the optimal price plan. The results demonstrate that the model can provide quantitative decision support for the pricing of an innovation service and ultimately yield a win-win result for both the supplier and demander of the innovation service. Furthermore, the influence of the parameters during the negotiation process is analyzed in detail. The effects of the learning strategy on accelerating the negotiation process, as well as the chosen of reasonable parameters are given.

The corrugated board is a versatile and durable material that is widely used in the packaging industry. Its unique structure provides strength and cushioning, while its recyclability and bio-degradability make it an environmentally friendly option. The strength of corrugated board depends on many factors, including the type of individual papers on flat and corrugated layers, the geometry of the flute, temperature, humidity, etc. This paper presents a new approach to analysis geometric features of corrugated boards based on the images. It allows for precise determination of the geometry of the corrugated layer, as well as the thickness of individual papers in all cardboard layers. The experimental set used in the work and the created software are characterized by high reliability and precision of measurement thanks to the use of an identification procedure based on image analysis and evolutionary algorithms. This allows to quickly find the main geometric characteristics of the corrugated board, which in turn leads to the possibility of performing numerical analyzes taking into account the real model of the corrugated board. Calculations made on a real (correctly mapped geometrically) model allow, for example, a more reliable analysis of the composition of the cardboard, and thus also to obtain greater savings in the optimization process.

Biological systems often need to operate in complex environments where conditions can rapidly change. This is possible due to their inherent ability to sense changes and adapt their behavior in response. Here, we detail recent advances in the creation of synthetic genetic parts and circuits whose behaviors can be dynamically tuned through a variety of intra- and extra-cellular signals. We show how this capability lays the foundation for implementing control engineering schemes in living cells and allows for the creation of biological systems that are able to self-adapt, ensuring their functionality is maintained in the face of varying environmental and physiological conditions. We end by discussing some of the broader implications of this technology for the safe deployment of synthetic biology.

Dental implants provide a predictable treatment option for partial and complete edentulism via the placement of fixed permanent artificial root to support prosthetic dental crowns. Despite the high survival rates, long-term implant failures are still reported leading to implant removal and additional financial and health burdens. While extrinsic factors that improve survival rate of implants have been well explored, the impact of genetic factors on this matter is poorly understood. A systematic review and meta-analysis study was conducted to determine whether genetic factors contribute to increase the risk of dental implant failure. A comprehensive search for peer-reviewed articles on dental implants and genetics was performed using various literature database libraries. The study design was conducted according to PRISMA guidelines, and the obtained records were registered in PROSPERO database. According to the exclusion/inclusion criteria, 11 studies were eligible for this study out of 808 articles. The meta-analysis of the combined association studies of DNA variations and dental implants did not indicate an increase risk for implant failure due to DNA variations in IL-1B, IL-10 and TNF-α. This study emphasizes the need for larger randomized controlled clinical trails to inform clinicians and patients about the role of genetic factors on dental implant survival and success rate in healthy and compromised patients.

The aim of this study has been to develop a novel two-level multi-objective genetic algorithm (GA) to optimize time series forecasting data for fans used in road tunnels by the Swedish Transport Administration (Trafikverket). Level 1 is for the process of forecasting time series cost data, while level 2 evaluates the forecasting. Level 1 implements either a multi-objective GA based on the ARIMA model or a multi-objective GA based on the dynamic regression model. Level 2 utilises a multi-objective GA based on different forecasting error rates to identify a proper forecasting. Our method is compared with using the ARIMA model only. The results show the drawbacks of time series forecasting using only the ARIMA model. In addition, the results of the two-level model show the drawbacks of forecasting using a multi-objective GA based on the dynamic regression model. A multi-objective GA based on the ARIMA model produces better forecasting results. In level 2, five forecasting accuracy functions help in selecting the best forecasting. Selecting a proper methodology for forecasting is based on the averages of the forecasted data, the historical data, the actual data and the polynomial trends. The forecasted data can be used for life cycle cost (LCC) analysis.

Genetic switches can be utilized for many purposes in synthetic biology including the assembly of complex genetic circuits to achieve sophisticated cellular systems and the construction of biosensors for real-time monitoring of intracellular metabolite concentrations. Although genetic switches have mainly been developed in prokaryotes to date, eukaryotic genetic switches are increasingly being reported as both rational and irrational engineering technologies mature. In this review, we describe genetic switches in yeast based on synthetic transcription factors and/or synthetic promoters. We also discuss directed evolution technologies for the rapid and robust construction of yeast genetic switches.

Between October 2021 and April 2022, 317 outbreaks caused by highly pathogenic avian influen-za (HPAI) H5N1 viruses were notified in poultry farms in the northeastern Italian Regions. The complete genomes of 214 strains were used to estimate the genetic network based on the virus similarity. An exponential random graph model (ERGM) was used to assess the effect of at-risk contacts, same owners, in-bound/out-bound risk windows overlap, genetic differences, geograph-ic distances, same species and poultry company, on the probability of observing a link within the genetic network, which can be interpreted as the potential propagation of the epidemic via lateral spread or a common source of infection. The variables same poultry company (Est.=0.548, C.I.=[0.179;0.918]) and risk windows overlap (Est.=0.339, C.I.=[0.309;0.368]) were associated with a higher probability of link formation, while the genetic differences (Est.=-0.563, C.I.=[-0.640;-0.486]) and geographic distances (Est.=-0.058, C.I.=[-0.078;-0.038]) indicated a re-duced probability. The integration of epidemiological data with genomic analyses allows moni-toring the epidemic evolution and helps explain the dynamics of lateral spreads suggesting the potential diffusion routes. The 2021-2022 epidemic stresses the need to further strengthen the bi-osecurity measures, and to encourage the reorganisation of the poultry production sector to mini-mize the impact of future epidemics.

Ningxiang pig is renowned breed for its exceptional meat quality, but it possesses suboptimal carcass traits. To elucidate the genetic architecture of meat quality and carcass traits in Ningxiang pigs, we assessed heritability and executed a genome-wide association study (GWAS) concerning carcass length, backfat thickness, meat color parameters (L.LD, a.LD, b.LD), and pH at two postmortem intervals (45 minutes and 24 hours) within a Ningxiang pig population. Heritability estimates ranged from moderate to high (0.30 ~ 0.80) for carcass traits and from low to high (0.11 ~ 0.48) for meat quality traits. We identified 21 significant SNPs, the majority of which were situated within previously documented QTL regions. Furthermore, the HMGA1 gene emerged as a pleiotropic gene correlated with carcass length and backfat thickness. The ADGRF1, FKBP5, and PRIM2 genes were associated with carcass length, while the NIPBL gene was linked to backfat thickness. These genes hold potential for use in selective breeding programs targeting carcass traits in Ningxiang pigs.

Improper design of friction pendulum bearings can lead to poor seismic reduction performance and may result in the failure of local vulnerable components. And the parameter design of friction pendulum bearings mainly relies on experience and verification calculations at present. This paper proposes an adaptive genetic algorithm considering the overall evolution state of the population, adjusting crossover and mutation probabilities adaptively based on individual fitness and population diversity. Compared to traditional algorithms, it exhibits better global search capabilities and convergence efficiency. Combining the improved genetic algorithm with finite element models, a parameter optimization method is proposed. The parameters of friction pendulum bearings are optimized, providing reference for the design of seismic isolation devices.

The cause and prevention of recurrent aphthous stomatitis (also called aphthous ulcers or canker sores) are still unknown. This may be due in part to ignorance of the risk factors present in susceptible people. In this systematic review (PROSPERO record #CRD42019122214), we show that most of the risk factors for the disease are single nucleotide genetic polymorphisms in genes related to the functioning of immune system (TLR4, MMP9, E-selectin, IL-1 beta and TNF-alpha). Single nucleotide genetic polymorphisms do not constitute a modifiable risk. This indicates that, at least in part, susceptibility to recurrent aphthous stomatitis is hereditary, and that these factors cannot be modified.

The last two decades have witnessed a surge in investigations proposing stem cells as a promising strategy to treat stroke. Since growth factor release is considered as one of the most important aspects of cell-based therapy, stem cells over-expressing growth factors are hypothesized to yield higher levels of therapeutic efficiency. In pre-clinical studies of the last 15 years that were investigating the efficiency of stem cell therapy for stroke, a variety of stem cell types were genetically modified to over-express various factors. In this review we summarize the current knowledge on the therapeutic efficiency of stem cell-derived growth factors, encompassing techniques employed and time points to evaluate. In addition, we discuss several types of stem cells, including the recently developed model of epidermal neural crest stem cells, and genetically modified stem cells over-expressing specific factors, which could elevate the restorative potential of naive stem cells. The restorative potential is based on enhanced survival/differentiation potential of transplanted cells, apoptosis inhibition, infarct volume reduction, neovascularization or functional improvement. Since the majority of studies have focused on the short-term curative effects of genetically engineered stem cells, we emphasize the need to address their long-term impact.

Tidal swamp rice has long been cultivated by the local people of the South Kalimantan, Indonesia. This germplasm possess some important traits for adapted to a wide range of abiotic and biotic stresses. In this study, a total of sixteen cultivars of this germplasm, consisting of fifteen of the South Kalimantan Province and one of Sumatera Island, Indonesia (an outgroup) were analyzed, phylogenetically based on the chloroplast trnL-F and nuclear intergenic spacer region (IGS). The results showed that this germplasm has a relatively more extraordinary genetic diversity than other local rice germplasm. In a nucleotide level, this germplasm showed a genetic diversity of 0.61 for nuclear IGS and 0.58 for trnL-F. The phylogenetic reconstruction also exhibited that this germplasm has the unique illustration of phylogenetic trees, particularly for the combined sequence datasets. Thus, the results of our study would provide useful information for further understanding of evolutionary relationships of this germplasm and facilitate the efficient utilization of valuable genes for genetic improvement, particularly in the tidal swamp areas.

The mitochondrial marker, cytochrome oxidase subunits II gene (mtDNA-COII) was employed to assess the genetic structure and diversity of Anopheles funestus, a very important malaria vector in Africa, that adapt and colonize different ecological niches in western Kenya. Mosquitoes were collected using mechanical aspirators in four sites (Bungoma, Port Victoria, Kombewa and Migori) in western Kenya. Following morphological identification, PCR was used to confirm species. The mtDNA-COII gene was amplified, sequenced and analyzed to determine genetic diversity and population structure. A total of 126 (Port Victoria-38, Migori-38, Bungoma-22 and Kombewa-28) sequences of mtDNA-COII were used for population genetic analysis. Anopheles funestus had high haplotype diversity (Hd= 0.97 to 0.98) but low nucleotide diversity (π =0.004 to 0.005). The neutrality test revealed significant (p<0.05) negative Tajima’s D and Fs values indicating population expansion with an excess of low-frequency variation due to evolutionary forces across all sites. No genetic differentiation or structure was observed across the sites (Fst = -0.01) and a high level of gene flow (Gamma St, Nm = 17.99 to 35.22) was observed among the populations. Population expansion suggests the high adaptability of this species to various ecological requirements hence sustaining its vectorial capacity and malaria transmission.

leaf beetle (BLB) (Ootheca mutabilis) has emerged as an important bean pest in Uganda, leading to devastating crop losses. There is limited information on the population genetic structure of BLB despite their importance. In this study, novel microsatellite markers and the partial mitochondrial cytochrome oxidase subunit I (mtCOI) gene sequences were used to analyze the spatial population genetic structure, genetic differentiation, gene flow and haplotype diversity of 87 O. mutabilis samples from five populations. We identified 19,356 simple sequence repeats (SSRs) (mono, di, tri, tetra, penta, and hexa-nucleotides) of which 81 di, tri and tetra-nucleotides were selected for primer synthesis. Five highly polymorphic SSR markers (4-21 alleles, heterozygosi-ty 0.59-0.84, polymorphic information content (PIC) 50.13-83.14%) were used for this study. Analyses of the five O. mutabilis populations with these five novel SSRs found 89% of genetic variation occurring within individuals, 9% among individuals and 2% among populations. Genetic differentiation was low but significant for SSR and insignificant for mtCOI partial sequence data while gene flow was high across the populations. There was no evidence of isolation by distance between geographical and genetic distances. Bayesian clustering identified signature of admixture that suggests genetic contributions from two ancestral genetic lineages, and the median-joining haplotype network showed low differentiation of many different haplotypes from the most common haplotype. Low genetic differentiation and high gene flow indicates unrestricted migrations between populations. This information will contribute to the design of BLB control strategies.

Nowadays industrial dryers are used instead of traditional methods for drying. In designing dryers suitable for controlling the process of drying and reaching a high quality product, it is necessary to predict the instantaneous moisture loss during drying. For this purpose, ten mathematical-experimental models with a neural network model based on the kinetic data of pistachio drying are studied. The data obtained from the cabinet dryer will be evaluated at four temperatures of inlet air and different air velocities. The pistachio seeds will be placed in a thin layer on an aluminum sheet on a drying tray and weighed by a scale attached to the computer at different times. In the neural network, data are divided into three parts: educational (60%), validation (20%) and test (20%). Finally, the best mathematical-experimental model using genetic algorithm and the best neural network structure for predicting instantaneous moisture are selected based on the least squared error and the highest correlation coefficient.

Long read sequencers, known for their effectiveness in detecting genomic structural variations (SV), are becoming a standard in comprehensive genetic analysis. In preimplantation genetic testing (PGT) for SV carriers, information on breakpoint junctions is required for the determination of carrier status in embryo selection. These sequencers are employed for challenging cases involving SVs that are difficult to analyze with conventional cytogenetical methods or detailed junctions of chromosomal translocations, providing valuable insights. They also play a crucial role in acquiring simultaneous information on surrounding single-nucleotide polymorphisms (SNPs) around causative variants in PGT. Despite their advantages, challenges related to sequencing accuracy and testing costs exist. Thus, understanding long read sequencers’ characteristics is essential for their effective utilization. This review summarizes the advanced applications of long read sequencers in preclinical workups and their integration into PGT. It also highlights in-house clinical cases, showing the implementation of long-read sequencing and discussing prospects in the field.

Hyperacusis, i.e., an increased sensitivity to sounds, is described in several neurodevelopmental disorders (NDDs), including Fragile X Syndrome (FXS). The mechanisms underlying hyperacusis in FXS are still largely unknown and effective therapies are lacking. Big conductance calci-um-activated potassium (BKCa) channels have been proposed as a therapeutic target to treat several behavioral disturbances in FXS preclinical models, but their role in mediating their au-ditory alterations has not been specifically addressed. Furthermore, studies on the acoustic phe-notypes of FXS animal models have mostly focused on central rather than peripheral auditory pathways. Here we provided an extensive characterization of the peripheral auditory phenotype of the Fmr1-knockout (KO) mouse model of FXS at adulthood. We also assessed whether the acute administration of Chlorzoxazone, a BKCa agonist, could rescue the auditory abnormalities of mutant mice. Fmr1-KO mice both at 3 and 6 months showed a hyperacusis-like startle pheno-type with paradoxically reduced auditory brainstem responses associated with a loss of ribbon synapses in the inner hair cells (IHCs). BKCa expression was markedly reduced in the IHCs of KO mice, but only at 6 months, when Chlorzoxazone rescued mutant auditory dysfunction. Our findings highlight the age-dependent and progressive contribution of peripheral mechanisms and BKCa channels to hyperacusis in FXS, suggesting a novel therapeutic target to treat auditory dysfunction in NDDs.

Evaporation from surface water plays a key role in water accounting of basins, water resources management, and irrigation systems management, so simulating evaporation with high accuracy is very important. In this study, two methods for simulating pan evaporation under different climatic conditions in Iran were developed. In the first method, six experimental relationships (linear, quadratic, and cubic, with two input combinations) were determined for Iran’s six climate types, inspired by a multilayer perceptron neural network (MLP-NN) neuron and optimized with the genetic algorithm. The best relationship of the six was selected for each climate type, and the results were presented in a three-dimensional graph. In the second method, the best overall relationship obtained in the first method was used as the basic relationship, and climatic correction coefficients were determined for other climate types using the genetic algorithm optimization model. Finally, the accuracy of the two methods was validated using data from 32 synoptic weather stations throughout Iran. For the first method, error tolerance diagrams and statistical coefficients showed that a quadratic experimental relationship performed best under all climatic conditions. To simplify the method, two graphs were created based on the quadratic relationship for the different climate types, with the axes of the graphs showing relative humidity and temperature, and with pan evaporation was drawn as contours. For the second method, the quadratic relationship for semi-dry conditions was selected as the basic relationship. The estimated climatic correction coefficients for other climate types lay between 0.8 and 1 for dry, semi-dry, semi-humid, Mediterranean climates, and between 0.4 and 0.6 for humid and very humid climates, indicating that one single relationship cannot be used to simulate pan evaporation for all climatic conditions in Iran. The validation results confirmed the accuracy of the two methods in simulating pan evaporation under different climatic conditions in Iran.

A novel coronavirus COVID-19 was first emerged in Wuhan city of Hubei Province in China in December 2019. The COVID-19, since then spreads to 213 countries and territories, and has become a pandemic. Genomic analyses have indicated that the virus, popularly named as corona, originated through a natural process and is probably not a purposefully manipulated laboratory construct. However, currently available data are not sufficient to precisely conclude the origin of this fearsome virus. Genome-wide annotation of thousands of genomes revealed that more than 1,407 nucleotide mutations and 722 amino acids replacements occurred at different positions of the SARS-CoV-2. The spike (S) glycoprotein of SARS-CoV-2 possesses a functional polybasic (furin) cleavage site at the S1-S2 boundary through the insertion of 12 nucleotides. It leads to the predicted acquisition of 3-O-linked glycan around the cleavage site. Although real-time RT-PCR methods targeting specific gene(s) have widely been used to diagnose the COVID-19 patients, however, recently developed more convenient, rapid, and specific diagnostic tools targeting IgM/IgG or newly developed plug and play methods should be available for resource-poor developing countries. Some drugs, vaccines and therapies have shown great promise in early trials, however, these candidates of preventive or therapeutic agents have to pass a long path of trials before being released for the practical application against COVID-19. This review updates current knowledge on origin, genomic evolution, development of the diagnostic tools and the preventive or therapeutic remedies of the COVID-19, and discusses on scopes for further research and effective management and surveillance of COVID-19.

The Complete Coverage Path Planning (CCPP) is a key technology in the field of agricultural robot, and has great significance for improving the efficiency and quality of tillage, fertilization, harvesting and other agricultural robot operations, as well as reducing the operation energy consumption. The traditional boustrophedon or heuristic search algorithm based CCPP methods, when coping with the field with irregular boundaries, obstacles and other complex environments, still face many problems and challenges, such as large repeated work areas, multiple turns or U-turns, low operation efficiency and prone to local optimum. In order to solve the above problems, an improved-genetic-algorithm-based CCPP method was proposed in this paper, which introduces the idea of chromosome pairs and multi-points mutation to improve its global optimization ability in complex environments, reduce the repeated work areas and the number of turns and U-turns, and thereby improve the operation efficiency. The simulation and experimental results on simple regular fields showed that the proposed improved genetic algorithm-based CCPP method achieved the comparable performance with the traditional boustrophedon-based CCPP method. However, on the complex irregular fields, although the proposed CCPP method increased the number of turns by 13.76%, the area of repeated operation and the number of U-turns were decreased by 38.54% and 35.00% respectively, and saves the battery voltage by 7.82% on average compared to the boustrophedon-based CCPP method. This proved that the proposed CCPP method has strong adaptive capacity to the environment, and has practical application value in improving the efficiency and quality of agricultural machinery operations, and reducing the energy consumption.

Introduction: Mucopolysaccharidosis type I (MPSI) is an autosomal recessive lysosomal storage disorder characterized by deficient or absent α-L-iduronidase (IDUA) enzyme activity due to pathogenic variants in IDUA gene. Early treatment with hematopoietic stem cell transplantation and/or enzyme replacement therapy is associated with improved outcomes in this progressive multisystem disease. The diagnosis is usually delayed due to late presentation and nonspecific symptoms resulting in high morbidity and mortality. The incidence of MPSI in US is estimated to be 0.26:100,000, however, it is unknown in Kuwait. This pilot study was undertaken to screen MPSI in all Kuwaiti neonates born at Farwaniya Hospital over a period of 12-months. This study examined the incidence of MPSI in a major center in Kuwait for inclusion in the national newborn screening program to enable its early detection and adequate treatment. Methods: All Kuwaiti neonates born at Farwaniya Hospital, Kuwait from December 2021 to December 2022, were screened for MPSI. The screening consisted of determining IDUA enzyme activity in dried blood spots (DBS)-derived samples by Tandem Mass Spectrometry. A follow-up genetic analysis of IDUA gene is planned to screen the cases with diminished IDUA enzyme activity as second-tier testing. Results: A total of 618 newborns, including 331 (54%) males and 287 (46%) females, were screened. Twenty of them had deficient IDUA enzyme activity but showed negative genetic testing for IDUA. However, we have diagnosed one additional female baby with MPSI, who belonged to Farwaniya Hospital, but the parents chose to deliver in a private hospital. She presented at age three months with recurrent upper airway infections, snoring and extensive Mongolian spots. The molecular study revealed previously reported pathogenic nonsense variant in IDUA c.1882C>T; p.(Arg628Ter), associated with severe phenotype. That being included, MPSI is estimated to be about 0.3% among tested females and 0.2% of all screened cases in Kuwait. Conclusion: Our study is the first to evaluate the incidence of MPSI in Kuwait. Given the single center, small number of screened babies and the short study duration thus far, it is premature to calculate the incidence of MPSI. It is anticipated that as the study continues and more infants are examined, we would be able to estimate the incidence of this disease in our population correctly. Further studies including screening newborns in all maternity hospitals in Kuwait are needed to calculate the actual incidence of MPSI. Our data supports including MPSI in national newborn screening program to allow early initiation of treatment and thus improve disease outcome.

Mercury (Hg) pollution not only poses a threat to the environment but also adversely affects the growth and development of plants, with potential repercussions for animals and humans through bioaccumulation in the food chain. Maize, a crucial source of food, industrial materials, and livestock feed, requires special attention in understanding the genetic factors influencing mercury accumulation. Developing maize varieties with low mercury accumulation is vital for both maize production and human health. In this study, a comprehensive genome-wide association study (GWAS) was conducted using an enlarged SNP panel comprising 1.25 million single nucleotide polymorphisms (SNPs) in 230 maize inbred lines across three environments. The analysis identified 111 significant SNPs within 78 quantitative trait loci (QTL), involving 169 candidate genes under the Q model. Compared to the previous study, the increased marker density and optimized statistical model led to the discovery of 74 additional QTL, demonstrating improved statistical power. Gene Ontology (GO) enrichment analysis revealed that most genes participate in arsenate reduction and stress responses. Notably, GRMZM2G440968, associated with the significant SNP chr6.S_155668107 of axis tissue, encodes a cysteine proteinase inhibitor, suggesting its potential role in alleviating Hg toxicity by inhibiting cysteine. Haplotype analyses provided further insights, indicating that lines carrying hap3 exhibited the lowest mercury content compared to other haplotypes. In summary, our study significantly enhances the statistical power of GWAS, identifying additional genes related to mercury accumulation and metabolism. These findings offer valuable insights into unraveling the genetic basis of mercury content in maize and contribute to the development of maize varieties with low mercury accumulation.

Throughout history, the pursuit of diagnosing and predicting crop yields has evidenced genetics, environment, and management practices' intertwined roles in achieving food security. However, the sensitivity of crop phenotypes and genetic responses to weather and climate remains unclear, hampering the identification of the underlying abilities of plants to adapt to climate change. We hypothesize that the PAWN global sensitivity analysis (GSA) coupled with a genetic by environment (GxE) model -built of environmental covariance and genetic markers structures- can evidence the contributions of climate on the predictability of maize yields in the U.S. and Ontario, Canada (US-CA). The GSA-GxE modeling framework estimates the relative contribution of climate variables such as solar radiation, temperature, rainfall, and relative humidity on improving maize yield predictions in US-CA. We use an improved version of the Genomes to Fields (G2F) initiative multi-dimensional database to build the environmental covariance matrices for the proposed GSA-GxE framework. The PAWN indices show that the aggregated GxE model’s highest sensitivity levels over US-CA were attributed to solar radiation, temperature, rainfall, and relative humidity. In one-third of the locations, rainfall was the primary climate variable responsible for maize yield predictability. Also, a consistent pattern of top sensitivity indices by location indicates that Relative Humidity, Solar Radiation, and Temperature were distributed as the main or the second most relevant drivers of maize yield predictability.

Blueberries (Vaccinium section Cyanococcus) are perennial shrubs widely cultivated for their edible fruits. In this study, we used admixture and genetic relatedness analysis of northern highbush (NHB, V. corymbosum) and southern highbush (SHB, V. darrowii) blueberry genotypes and F2 progenies of the V. corymbosum × V. darrowii cross. Using genotyping-by-sequencing (GBS), we generated ~3.34 billion reads (75 bp). The GBS reads were aligned to the Vaccinium corymbosum cv. Draper v1.0 reference genome sequence, and ~2.8 million reads were successfully mapped. From the alignments, we identified 2,244,039 single nucleotide polymorphisms (SNPs), which were used for principal component, haplotype, and admixture analysis. PCA formed three main groups: 1) NHB cultivars, 2) SHB cultivars, and 3) BNJ16-5 progenies. The overall fixation index (FST) and nucleotide diversity for NHB and SHB, indicated wide genetic differentiation, and haplotype analysis revealed that SHB cultivars are more genetically diverse than NHB cultivars. The admixture analysis identified a mix of various lineages of parental genomic introgression. This study demonstrated the effectiveness of GBS-derived SNP markers in genetic and admixture analyses to reveal genetic relatedness and to examine parental lineages in blueberry, which may be useful for future breeding plans.

Many dioecious plants have sex chromosomes that are cytologically heteromorphic, but about half of species lack cytological differences between males and females and are thus homomorphic. Very little is known about the size and content of the non-recombining sex-determining region (SDR) in these species. Here, we assess the size and content of the SDR of the diploid dioecious herb Mercurialis annua, which has homomorphic sex chromosomes and shows signatures of mild Y-chromosome degeneration. We used RNAseq to identify new Y-linked markers for M. annua. Twelve of 24 transcripts with male-specific and male-biased expression could only be PCR-amplified from males and are thus Y-linked. We found a further six Y-linked sequences that were present in males but not females using genome capture data from multiple populations. We used the Y-linked sequences to identify and sequence 17 sex-linked bacterial artificial chromosomes (BACs), which form 11 groups of non-overlapping sequence, covering a total sequence length of about 1.5 Mb. Content analysis of this region suggests it is enriched for repeats, has a low gene density and contains few candidate sex-determining genes. The BACs map to a subset of the sex-linked region of the genetic map, which is estimated to be at least 14.5 Mb. This is substantially larger than estimates for other dioecious plants with homomorphic sex chromosomes, especially given the small genome size of M. annua. Our data provide a rare, high-resolution view of the homomorphic Y chromosome of a dioecious plant.

This study introduces an innovative optimization method to identify the optimal configuration of a sparse symmetric 2D array for applications in security, particularly multistatic imaging. Utilizing Genetic Algorithms (GA) in a sophisticated optimization process, the research focuses on achieving the most favorable antenna distribution while mitigating the common issue of secondary lobes in sparse arrays. The main objective is to determine the ideal configuration from specific design parameters, including hardware specifications such as number of radiating elements, minimum spacing, operating frequency range, and image separation distance. The study employs a cost function based on the the point spread function (PSF), the system response to a point source, with the goal of minimizing the secondary lobe levels and maximizing their separation from the main lobe. Advanced simulation algorithms based on Physical Optics (PO) are used to validate the presented methodology and results.

In order to explore the genetic diversity of the extremely small population wild plant Habenaria dentata and protect and optimize its wild resources. The genetic diversity of 133 samples from 6 wild populations of H.dentata was analyzed by ISSR molecular marker technique to provide a scientific basis for the screening of improved germplasm resources. The results show that the average number of alleles (Na) was 1.765, the average number of effective alleles (Ne) was 1.424, the average Nei 's gene diversity index (He) was 0.252, the average Shannon information diversity index (I) was 0.381, and the average percentage of polymorphic loci (PPL) was 76.499%. The variation within populations was 77.34%, and the variation between populations was 22.66%. Gene flow (Nm) was 1.705 8, greater than 1. The results of cluster analysis showed that the six populations were mainly divided into four branches and not classified according to geographical location. There was no significant correlation between geographical location and genetic distance between populations (r=0.557, P>0.05). The genetic diversity of H.dentata is high. Among the six wild populations, the genetic diversity of Mulun population is the highest and this population can be used as a key protection unit.

There is a growing number of evidence-based indications for pharmacogenetic (PGx) testing. We aimed to evaluate clinical relevance of a 16-gene panel test for PGx-guided pharmacotherapy. In an observational cohort study we included subjects tested with a PGx panel for variants of ABCB1, COMT, CYP1A2, CYP2B6, CYP3A4, CYP3A5, CYP2C9, CYP2C19, CYP2D6, CYP4F2, DPYD, OPRM1, POR, SLCO1B1, TPMT and VKORC1. PGx-guided pharmacotherapy management was supported by the PGx expert system SONOGEN XP. The primary study outcome was PGx-based changes and recommendations regarding current and potential future medication. PGx-testing was triggered by specific drug-gene pairs in 102 subjects, and by screening in 33. Based on PharmGKB expert guidelines we identified at least one “actionable” variant in all 135 (100%) tested patients. Drugs that triggered PGx-testing were clopidogrel in 60, tamoxifen in 15, polypsychopharmacotherapy in 9, opioids in 7, and other in 11 patients. Among those, PGx variants resulted in clinical recommendations to change PGx-triggering drugs in 33 (32.4 %), and other current pharmacotherapy in 23 (22.5%). Additional costs of panel vs. single gene tests are moderate, and the efficiency of PGx panel testing challenges traditional cost-benefit calculations for single drug-gene pairs. However, PGx-guided pharmacotherapy requires specialized expert consultations with interdisciplinary collaborations.

Keyhole neurosurgery implies reaching a target area inside the brain through an entry point specified by the neurosurgeon. In order to avoid complications, a risk assessment procedure must be done to establish the minimum risk trajectory from the entry point to the target area. The neurosurgeon establishes the risk values for the brain structure according to the type of intervention. The preset brain structure risk value is used to assess the risk value for each voxel of the brain. This paper proposes an improved risk assessment methodology based on the sum of N maximum risk values for each voxel. Then, risk assessment for a trajectory is done by adding the risk of all voxels that are part of the path. The safest trajectory is defined as the trajectory with the lower risk. Our proposed search trajectory methodology includes a Genetic Algorithm (GA) for finding the safest trajectories. The use of a GA drastically reduces the number of trajectories to analyze, speeding up the planning procedure. The achieved results were qualified by expert neurosurgeons as satisfactory. Our proposed method allows neurosurgeons to calibrate the surgical planning system by allowing them to establish the risk brain structure and the risk value for each structure.

As a result of the spread of SARS-CoV-2, a global pandemic was declared. Indiscriminate COVID-19 vaccination has been extended to include age groups and naturally immune people with minimal danger of suffering serious complications due to COVID-19. Solid immuno-histopathological evidence demonstrates that the COVID-19 genetic vaccines can display an off-target distribution in tissues that are terminally differentiated, triggering autoimmune reactions. These include the heart and brain, which may incur in situ production of spike protein eliciting a strong autoimmunological inflammatory response. Due to the fact that every human cell which synthesizes non-self antigens becomes inevitably the target of the immune system, and since the human body is not a strictly compartmentalized system, accurate pharmacokinetic and pharmacodynamic studies are needed in order to determine precisely which tissues can be harmed. Therefore, our article aims to draw the attention of the scientific and regulatory communities on the critical need of bio-distribution studies for the genetic vaccines against COVID-19, as well as of rational harm-benefit assessments by age group.

The optimal structural design is imperative to minimize material consumption and reduce the environmental impact of construction. Given the complexity in the formulation of structural design problems, the process of optimization is commonly performed using artificial intelligence (AI) global optimization, such as Genetic Algorithm (GA). However, the integration of AI-based optimization together with visual programming (VP) in building information modeling (BIM) projects warrants further investigation. This study proposes a workflow by combining structure analysis, VP, BIM, and GA to optimize trusses. The methodology encompasses several steps including: (i) generation of parametric trusses in Dynamo VP; (ii) performing the finite element modeling (FEM) using Robot Structural Analysis (RSA); (iii) retrieving and evaluating the FEM results interchangeably between Dynamo and RSA; (iv) finding the best solution using GA; and (v) importing the optimized model into Revit, enabling the user to perform simulations and engineering analysis, such as life cycle assessment (LCA) and quantity surveying. The feasibility of the proposed workflow was tested on benchmark problems and compared with open literature. The outcomes of this study offer insight into the opportunities and limitations of combining VP, GA, FEA, and BIM for structural optimization applications, particularly to enhance structural efficiency and sustainability in construction.

Tick borne encephalitis virus (TBEV) is the causative agent of Tick borne encephalitis in humans, a severe zoonosis occurring in the Paleartic region mainly transmitted through ticks belonging to the genus Ixodes. In Italy, TBEV is restricted to few foci in the north-eastern part of the country. This report describes for the first time a case of clinical TBE in a roe deer, occurred in the Belluno province, Veneto region, an area highly endemic for the presence of the virus. The affected roe deer showed ataxia, staggering movements, muscle tremors and persistent teeth grinding causing hypersalivation. At necropsy, the macroscopic picture was inconclusive. RNA of TBEV was detected by real-time RT-PCR. Phylogenetic analysis revealed a close relationship to TBEV of the European subtype, and 100% similarity with a virus from the bordering Trento Province. The histological examination of the midbrain confirmed the viral etiology and specific immunofluorescence indicated the presence of a Flavivirus infection and characterized the pattern of infection in the neurons. This report underlines for the first time the occurrence of clinical encephalitic manifestations due to TBEV in a roe deer, thussuggesting to include this pathogen in the frame of differential diagnosis in this species.

Enteroviruses (EVs) are viruses of the family Picornaviridae that cause mild to severe infections in humans and in several animal species, including nonhuman primates (NHPs). We conducted a survey and characterization of enteroviruses circulating between humans and great apes in the Congo. Fecal samples (N=24) of gorillas and chimpanzees living close to or distant from humans in three Congolese parks were collected, as well as from healthy humans (N=38) living around and within these parks. Enterovirus were detected in 29.4% gorilla and 13.15% human feces, including wild and human-habituated gorillas, local humans and eco-guards. Two identical strains were isolated from two humans come from two remote regions. Their genomes were similar and all genes showed their close similarity to Coxsackieviruses except for 3C, 3D and 5’UTR region where they were most similar to poliovirus 1 and 2, suggesting recombination. Recombination events were found between these strains, poliovirus 1 and 2 and EV-C99. The same EV- C species detected in both humans and apes in different regions suggest a clonal distribution of the virus in Congo.

Background: Colorectal cancer is considered the third most fetal among all type of cancer. Spleen tyrosine kinase (SYK) is a non-receptor type tyrosine-protein that plays crucial role in signaling mediated via immune receptor. We adopted an onco-informatics analysis to evaluate the SYK expression and prognostic value of SYK in colorectal cancer, and identification of potential phytochemicals which may inhibit overexpression of SYK protein as well as minimized colorectal cancer. Materials & Methods: Differential expression of SYK gene was analyzed using the several transcriptomic databases including Oncomine, UALCAN, GENT2 and GEPIA2. The server, cBioPortal was used to analyze mutation and copy number alterations whereas GENT2, GEPIA, OncoLnc and PrognoScan were employed to examine the survival rate. A protein-protein interaction network of SYK and co-expressed genes of SYK was conducted via GeneMANIA. Considering SYK gene encoding protein as drug target, selected phytochemicals were assessed by molecular docking using PyRx 0.8 packages. YASARA molecular dynamics simulators were applied for the post validation of the molecular docking data. Results: We have observed significant overexpression of mRNA expression levels of SYK gene colorectal adenocarcinoma (COAD) samples compared with normal tissues. Significant methylation level and various genetic alterations are assembled in SYK gene which can lead to the development of colorectal cancer. As a result, lower level of SYK expression was related to the more chances of patients’ survival by which all the outcomes from the multiple bioinformatics platforms and web resources have demonstrated the significant evidences that the SYK kinsase can possess as a potential biomarker for the treatment of colorectal cancer. Here, aromatic phytochemicals namely, Kaempferol and Glabridin targeting SYK showed more stability compared to controls and may be useful for the treatment of colorectal cancer. Conclusion: Our study showed dysregulated expression of SYK in colorectal cancer and potentiality to act as a biomarker for the prognosis of CRC. Moreover, we have shown phytochemicals (Kaempferol and Glabridin) target SYK as potential treatment strategies and drug repositioning potentiality in colorectal cancer.

Members of the genus Armillaria are widespread forest pathogens against which effective protection has not yet been developed. Due to their longevity and the creation of large-scale cloning of Armillaria individuals, the use of mycoviruses as biocontrol agents (BCAs) against these pathogens could be an effective alternative. This work describes the screening of double-stranded RNA banding patterns as a first approach for potential virus discovery and the use of stranded total RNA-seq for viral detection and characterization in Armillaria spp. collected in the Czech Republic. A total of five single-stranded RNA viruses were detected in Armillaria ostoyae and A. cepistipes, including the first virus of the family Tymoviridae found infecting a member the genus Armillaria and four viruses belonging to the recently described virus group "ambiviruses" with circular ambisense genome organization. Both hammerhead (HHRz) and hairpin (HpRz) ribozymes were detected in all the ambiviricot sequences. Armillaria viruses were compared by phylogenetic analysis and confirmed their specific host by direct RT-PCR, which showed the occurrence of interspecies transmission.

Genetic parameters of overreach, term and acuteness in Peruvian Paso horses (PPH) have not been determined to date. It is important to estimate these parameters for application in PPH breeding, therefore, the aim of this study was to estimate the heritability, repeatability, and genetic correlations under field conditions of overreach, term, and acuteness of PPHs. The study included records of up to 137 stallions and mares. All measurements were recorded in MP4 video format with a resolution of 1920 x 1080 megapixels and at 60 frames per second. All traits were measured three times (once per stride), and each trait was analyzed. KINOVEA software version 0.9.5 was used to analyze the measurements. A multivariate repeated measures animal model with sex effect was used to estimate the variance components for each trait using WOMBAT software. The results showed heritability of 0.411, 0.476 and 0.405, for the traits of overreach, term, and acuteness, respectively. Repeatability was high in all traits (&gt; 0.78). Genetic additive correlations ranged from -0.30 to 0.49. It can be concluded that overreach and term have high heritability values, which allows these traits to respond better in a selection process, unlike acuteness which has a moderate heritability value.

Cerebellar ataxia, neuronopathy, and vestibular areflexia syndrome (CANVAS) is caused by biallelic pathogenic expansions, or compound heterozygosity with other pathogenic variants in the RFC1 gene. CANVAS is estimated to be underdiagnosed, both because of the lack of formal diagnostic criteria and molecular challenges that translate to lesser access and high cost of routine testing. Our aim was to address the need for making CANVAS genetic testing routine, by designing a streamlined two-step PCR consisting of a short-allele screening PCR and a confirmatory PCR with fragment capillary electrophoresis detection. Exome sequencing of RFC1 was additionally foreseen to resolve potential compound heterozygosity cases. Specificity of our approach was evaluated using ataxia patients with known non-CANVAS diagnoses, and optimized using Southern blot confirmed CANVAS patients. We evaluated our approach by testing patients consecutively referred for clinically suspected CANVAS using first the two-step PCR, followed by exome sequencing. Our approach was able to accurately identify negative and confirm positive cases in prospectively collected suspected CANVAS patients presenting with at least three typical clinical signs. The proposed testing approach provides an alternative method able to clearly distinguish between CANVAS negative and positive cases and can be easily incorporated into the genetic diagnostic laboratory workflow.

Abstract Safflower (Carthamus tinctorius L.) is a multipurpose minor crop consumed by developed and developing nations around the world with a limited research fund and genetic resources. Genomic selection (GS) is an effective modern breeding tool which could help to fast track the genetic diversity preserved in genebank collections to facilitate rapid and efficient germplasm improvement and variety development. In the present study, we simulated four GS strategies to compare genetic gains and inbreeding rates during breeding cycles in a safflower recurrent selection breeding program targeting grain yield (GY) and seed oil content (OL). We observed positive genetic gains over cycles in all four GS strategies, where the first cycle delivered the largest genetic gain. Single traits GS strategies had the greatest gain for the target trait but with very limited genetic improvement for the other trait. Simultaneous selection for GY and OL via index indicated higher gains for both traits than crossing between the two single trait independent culling strategies. The the multi-trati GS strategy with inbreeding control (GS_GY+OL+Rel) showed lower inbreeding rate but similar gain compared to GS_GY+OL (without inbreeding control) after few cycles. Our finding lay the foundation for the future safflower GS breeding.

Crop yield enhancement is crucial for ensuring food security and meeting the growing global demand for agricultural products. The development of innovative technologies, such as CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats), has provided new avenues for precise genetic modifications in crops. In this research article, we explore the application of CRISPR technology for crop yield improvement. We discuss the methodology, present recent results, and engage in a comprehensive discussion of the potential benefits, challenges, and future prospects of CRISPR-mediated crop yield enhancement.

Diseases pose a significant and pressing concern for the sustainable development of the aquaculture sector, particularly as their impact continues to grow due to climatic shifts such as rising water temperatures. While various approaches, ranging from biosecurity measures to vaccines, have been devised to combat infectious diseases, their efficacy is disease- and species-specific and contingent upon a multitude of factors. The field of genetics and genomics offer effective tools to control and prevent disease outbreaks in aquatic animal species. In this study, we present the key findings from our recent research, focusing on the genetic resistance to three specific diseases: White Spot Syndrome Virus WSSV) in white shrimp, Bacterial Necrotic Pancreatitis (BNP) in striped catfish and skin fluke (a parasitic ailment) in yellowtail kingfish. Our investigations reveal that all three species possess substantial heritable genetic components for disease resistant traits, indicating their potential responsiveness to artificial selection in genetic improvement programs tailored to combat these diseases. Also, we observed a high genetic association between disease traits and survival rates. Through selective breeding aimed at enhancing resistance to these pathogens, we achieved substantial genetic gains, averaging 10% per generation. These selection programs also contributed positively to the overall production performance and productivity of these species. Although the effects of selection on immunological traits or immune responses were not significant in white shrimp, they yielded favourable results in striped catfish. Furthermore, our genomic analyses, including shallow genome sequencing of pedigreed populations, enriched our understanding of the genomic architecture underlying disease resistance traits. These traits are primarily governed by a polygenic nature, with numerous genes or genetic variants, each with small effects. Leveraging a range of advanced statistical methods, from mixed models to machine and deep learning, we developed prediction models that demonstrated moderate to high levels of accuracy in forecasting these disease-related traits. In addition to genomics, our RNA-seq experiments identified several genes that undergo upregulation in response to infection or viral loads within the populations. Preliminary microbiome data, while offering limited predictive accuracy for disease traits in one of our studied species, underscore the potential for combining such data with genome sequence information to enhance predictive power for disease traits in our populations. Lastly, this paper briefly discusses the roles of precision agriculture systems, AI algorithms, and outlines the path for future research to expedite the development of disease-resistant genetic lines tailored to our target species. In conclusion, our study underscores the critical role of genetics and genomics in fortifying the aquaculture sector against the threats posed by diseases, paving the way for more sustainable and resilient aquaculture development.

Computer network attacks are evolving in parallel with the evolution of hardware and neural network architecture. Despite major advancements in Network Intrusion Detection System (NIDS) technology, most implementations still depend on signature-based intrusion detection systems, which can’t identify unknown attacks. Deep learning can help NIDS to detect novel threats since it has a strong generalization ability. The deep neural network’s architecture has a significant impact on the model’s results. We propose a genetic algorithm based model to find the optimal number of hidden layers and the number of neurons in each layer of the deep neural network (DNN) architecture for the network intrusion detection binary classification problem. Experimental results demonstrate that the proposed DNN architecture shows better performance than classical machine learning algorithms at a lower computational cost.

Shewanella spp. are gram-negative bacteria that thrive in aquatic niches and also cause infectious diseases as opportunistic pathogens. Chromosomal integrons (CI) and mobile integrons (MI) were previously described in some Shewanella isolates. Here, we evaluated the occurrence of integrase genes, the integron systems and their genetic surroundings in the genus. We identified 22 integrase gene types, 17 of which were newly described, in different Shewanella species, evidencing multiple gain and loss events. Phylogenetic analysis showed that most of them were strain-specific, except for Shewanella algae, which seem to have co-evolve within the host as typical CIs. Noteworthy, co-existence of up to 5 different integrase genes, as well as their wide dissemination to Alteromonadales, Vibronales, Chromatiales, Oceanospirillales and Enterobacterales was observed. Identification of novel MIs suggests that lateral genetic transfer may have occurred resembling the behavior of class 1 integrons. The constant emergence of determinants associated to antimicrobial resistance worldwide, concomitantly with novel MIs in strains capable to harbor several types of integrons may be an alarming threat for the recruitment of novel antimicrobial resistance gene cassettes in the genus Shewanella, and its evolution towards the multidrug resistance.

We have used Daphnia cucullata as a model organism for the first time in the four deepest Latvian lakes from the Boreal biogeographical region lakes in order to find the genetic diversity of Daphnia cucullata populations. During the research, the most appropriate microsatellite markers for future genetic studies of Daphnia cucullata populations in Boreal biogeographical region lakes. It was the loci Dgm105 and Dgm101, in which the maximum number of alleles and the maximum number of private alleles were found. The Dgm105 locus had five private alleles (62% of all detected alleles), while the Dgm101 locus had four private alleles (57% of all detected alleles) in these loci. We was determined the observed heterozygosity (Hobs) and the expected heterozygosity (Hexp) level (by Hardy-Weinberg), the number of polymorphic loci, the number of detected alleles in each analyzed microsatellite locus, the average number of alleles at the locus (Na), the average effective number of alleles at the locus (Ne), FST of the population genetic differentiation, the genetic distance (D) (by Nei) and significance (χ2- test) of differences between the levels of observed and expected heterozygosity. It was shown that Daphnia cucullata populations from lakes with a low number of zooplankton taxa (Riča and Geraņimovas-Ilzas) have a higher genetic diversity compared to lakes with a high number of zooplankton taxa (Dridzis and Svente) in lakes. It was found, that Daphnia cucullata populations from lakes Dridzis and Svente have the least genetic distance and these populations form a single genetic group, as confirmed by clustering

Clustered regularly interspaced short palindromic repeats or CRISPR, one of the major technological tools from nature's toolbox, has revolutionized the scientific world with its potential use in humans and plants. CRISPR Cas9 was first known as an adaptive immune system of bacteria. It is a system that cleaves foreign DNA. It has been exploited to be used as a genome editing tool for correcting genetic diseases in humans, for plants to create stress-resistant plants, and for a variety of different purposes. This review provides a basic overview of its applications in different areas of biological research. It has immense potential for a variety of researches, but it's still a mystery for science. It feels like scientists just know a tip of an iceberg.

Bitter gourd is an important vegetable of the family Cucurbitaceae, cultivated mainly in humid and subtropical Asia. Bitter gourd is vegetable with immense health benefits due to the presence of medicinal compounds such as charatin, vicine, and polypeptide-p, which play an essential role in lessening the blood glucose levels. Moreover, bitter gourd fruits are particularly rich in vitamin C, minerals, and carotenes. Here, an effort has been made to critically evaluate the extent of achievements during the enhancement and enactment of bitter gourd breeding programs with the use of latest technologies. Broadening of the genetic base of cultivated bitter groud varieties as a result of enrichment of the existing resources by using the wild species in the breeding programs. Practical seed production technological know-how along with the use of the MS system (male sterility)/chemical-induced sterility procedure is nonetheless vital to cope up with the market demands. Superior yielding bitter gourd hybrids combining early maturity and resistance to biotic and abiotic stresses are regularly needed to cope up with the challenge of bitter gourd production.

Oats represents a promising alternative to small-grain cereals from Triticeae group (wheat, barley, rye) for persons suffering from any form of gluten intolerance, especially celiac disease (CD), since oat-specific prolamins avenins reveal generally lower gluten content and immunoreactivity. Recent studies on avenin molecular structure revealed large genetic variability in avenin sequences affecting the spectrum of gluten peptides produced by hydrolases in human digestive tract. The aim of the present review is to summarise recent knowledge obtained in laboratory in vitro studies focused on the effect of avenin-derived peptides on reactivity of crucial components of human immune system such as dendritic cells (DC) and T-cells. The other part of the review summarises the results of clinical studies with CD patients including oat products in their diet. Since different clinical studies revealed contradictory results regarding potential safety of oats for CD patients, the focus has to be directed at genetic variability in oat avenins. Identification of avenin isoforms with minimum CD immunoreactivity will open up ways leading to designing novel oat cultivars suitable for CD patients. Knowledge on immunoreactivity of gluten peptides together with breeding new oat cultivars revealing minimum avenin immunoreactivity with respect to CD as well as application of food processing technologies leading to gluten content reduction should result in development of gluten-free oats safe for celiacs.

In the past, Unmanned Aerial Vehicles (UAVs) were mostly used in the military operations to prevent pilot losses. Nowadays, the fast technological evolution enables the production of a class of cost-effective UAVs which can service a plethora of public and civilian applications, specially when configured to work cooperatively to accomplish a task. However, designing a communication network among the UAVs is challenging task. In this article, we propose a centralized UAV placement strategy, where UAVs are used as flying access points forming a mesh network, providing connectivity to ground nodes deployed in a target area. The geographical placement of UAVs is optimized based on a Multi-Objective Evolutionary Algorithm (MOEA). The goal of the proposed scheme is to cover all ground nodes using a minimum number of UAVs, while maximizing the fulfillment of their data rate requirements. The UAVs can employ different data rates depending on the channel conditions, which are expressed by the Signal-to-Noise-Ratio (SNR). In this work, elitist Non-Dominated Sorting Genetic Algorithm II (NSGA-II) is used to find a set of optimal positions to place UAVs, given the positions of the ground nodes. We evaluate the trade-off between the number of UAVs used to cover the target area and the data rate requirement of the ground nodes. Simulation results show that the proposed algorithm can optimize the UAV placement given the requirement and the positions of the ground nodes in the geographical area.

Nowadays, we live in a world in which people are facing with a lot of data that should be stored or displayed. One of the key methods to control and manage this data refers to grouping and classifying them in clusters. Today, clustering has a critical role in information retrieval methods for organizing large collections inside a few significant clusters. One of the main motivations for the use of clustering is to determine and reveal the hidden and inherent structure of a set of data. Ensemble clustering algorithms combine multiple clustering algorithms to finally reach an overall clustering system. Ensemble clustering methods by lack of information fusing utilize several primary partitions of data to find better ways. Since various clustering algorithms look at the different data points, they can produce various partitions from such data. It is possible to create a partition with high performance by combining the partitions obtained from different algorithms, even if the clusters to be very dense from each other. Most studies in this area have examined all the initial clusters. In this study, a new method is used in which the most sustainable clusters are utilized instead of all primary produced clusters. Consensus function based on co-association matrixes used to select more stable clusters. The most stable clusters selection method is done by cluster stability criterion based on F-measure. Optimization functions are used to optimize the obtained final clusters. The genetic algorithm is the optimizer used in this article to find the ultimate clusters participated in a consensus. Experimental results on several datasets show that the output of proposed method is various clusters with high stability.

Alum sludge is a byproduct of water treatment plants and its use as a soil stabilizer has gained increasing attention due to its economic and environmental benefits. Its application has been shown to improve the strength and stability of soil, making it suitable for various engineering applications. However, to go beyond just measuring the effects of alum sludge as a soil stabilizer, this paper explores the use of artificial intelligence (AI) methods to predict the California bearing ratio (CBR) of soils stabilized with alum sludge. Three AI methods, including two black box methods (artificial neural network and support vector machines) and one grey box method (genetic programming), were used to predict CBR based on a database with nine input parameters. The results showed that all three AI models were able to predict CBR with good accuracy, with coefficient of determination (R2) values ranging from 0.94 to 0.99 and mean absolute error (MAE) values ranging from 0.30 to 0.51. In a novel approach, the genetic programming method was used to produce an equation to estimate CBR, which included seven inputs and accurately predicted CBR. The analysis of sensitivity and importance of parameters showed that the number of hammer blows for compaction was the most important parameter, while the parameters for maximum dry density of soil and mixture were the least important. This study suggests that AI methods can effectively predict the performance of alum sludge as a soil stabilizer, and the proposed equation using genetic programming can be a useful tool for predicting CBR.

Since its advent in the mid-twentieth century, the field of artificial intelligence (AI) has been heavily influenced by biology. From the structure of the brain to evolution by natural selection, core biological concepts underpin many of the fundamental breakthroughs in modern AI. Here, focusing specifically on artificial neural networks (ANNs) that have become commonplace in machine learning, we show the numerous connections between theories based on coevolution, multi-level selection, modularity and competition and related developments in ANNs. Our aim is to illuminate the valuable but often overlooked inspiration biologists have provided AI research and to spark future contributions at this intersection of biology and computer science. Although recent advances in AI have been swift, many significant challenges remain requiring innovative solutions. Thankfully, biology in all its forms still has a lot to teach us, especially when trying to create truly intelligent machines.

Among the various complex systems that we experience each day, there is the physical phenomenon of infiltration. Infiltration is considered as the dynamics of water flow in the subsurface soil that in this work is framed for the context of civil construction. This issue is approached with the use of mathematical models and stochastic techniques, however, there are hardships in collecting the samples in the field, the adoption of a scale type, the influence in soil layers interfaces, the effects of soil anisotropic characteristics and so on. In this study, methodology is proposed to deal with the soil sampling input such as the retro model, constitutive model and optimization algorithms. Additionally, an automatic calibration is set forth to fix parameters from the mathematical model submitted. Especially among the existing Optimization Algorithms there are Genetic Algorithms and the Generalized Simulated Annealing Algorithm (GSA). This work presents an overview of these optimization methods and a proposal for a more efficient and faster algorithm called GSA-HYBRID based on convergence gradient technique. The applied strategy depends on the type of case study considering its physical properties and constraints. In this sense, it is found that while Genetic Algorithms are able to replicate the optimization surface, Generalized Simulated Annealing is much more adequate in characterizing the system at an extremely low computational cost. Nevertheless, the hybrid technique GSA-HYBRID performed the fastest. Further research is necessary to implement the novel GSA-HYBRID algorithm due to its flexibility and higher speed, also, studying its application at different case studies.

: Using line × tester analysis, the current research analyses parental genotypes and their combinations in normal conditions and identifies the genes influencing yield characteristics. In the present study, 15 diverse genotypes, including 10 lines, 5 testers, and 50 F1s hybrids, were evaluated for 13 morphological and 2 biochemical traits. A suitable location was taken to study the effect of 15 characters. The results exposed that ability mean squares were significant for all studied additive and non-additive components. In this direction, the general combining ability of PBW-343, DBW-39, K-402, K-1317, KRL-210, and K-68 were higher than the remaining parents. For morphological traits like yield, the top five crosses were described based on SCA effects, namely, HD-3086 × HD-3171, K-402 × K-9107, K-1317 × K-9107, HD-2967 × K-0307 and K-402 × K-68 in F1 generation. In addition, the high value of heritability was estimated for plant height (77.32%), spike length (32.26%), biological yield/plant (59.52%), and grain yield/plant (68.76%). However, the moderate values of heritability were estimated for days to maturity (22.78%) and phenol color reaction (18.00%). The higher genetic advance was not found for recorded characters; however, a moderate genetic advance was recorded for grain yield per plant (13.15%) and harvest index (11.72%). High heritability coupled with moderate genetic advance was recorded for two characters grain yield per plant and harvest index in F1 and F2 generations.

Multiple sclerosis is an autoinflammatory condition that results in damage of myelinated neurons in affected patients. While disease-modifying treatments have been successful in slowing the progression of relapsing remittent disease, most patients still progress to secondary progressive disease that is largely unresponsive to disease-modifying treatments. Similarly, there is currently no effective treatment for patients with primary progressive MS. Innate and adaptive immune cells in the CNS play a critical role in initiating an autoimmune attack and in maintaining the chronic inflammation that drives disease progression. In this review, we will focus on recent insights into the role of T cells with regulatory function in suppressing the progression of MS, and, more importantly, in promoting the remyelination and repair of MS lesions in the CNS. We will discuss the exciting opportunity to genetically reprogram regulatory T cells to achieve immune suppression and enhance repair locally at sites of tissue damage, while retaining a fully competent immune system outside the CNS. In the future, reprogramed regulatory T cells with defined specificity and function may provide life medicines that can persist in patients and achieve lasting disease suppression after one cycle of treatment.

Missing observation is a common problem in scientific and industrial experiments, particularly in a small-scale experiment. They often present significant challenges when experiment repetition is infeasible. In this research, we propose a multi-objective genetic algorithm as a practical alternative for generating optimal mixture designs that remain robust in the face of missing observation. Our algorithm prioritizes designs that exhibit superior D-efficiency while maintaining a high minimum D-efficiency due to missing observation. The focus on D-efficiency stems from its ability to minimize the impact of missing observations on parameter estimates, ensure reliability across the experimental space, and maximize the utility of available data. We study problems with three mixture components where the experimental region is an irregularly shaped polyhedral within the simplex. Our designs have proven to be D-optimal designs, demonstrating exceptional performance in terms of D-efficiency and robustness against missing observations. We provide a well-distributed set of optimal designs derived from the Pareto front, enabling experimenters to select the most suitable design based on their priorities using the desirability function.

The ASCE-EWRI reference evapotranspiration (ETo) equation is recommended as a standardized method for reference crop ETo estimation. However, various climate data as input variables to the standardized ETo method are considered limiting factors in most cases and restrict the ETo estimation. This paper assessed the potential of different machine learning (ML) models for ETo estimation using limited meteorological data. The ML models used to estimate daily ETo included Gene Expression Programming (GEP), Support Vector Machine (SVM), Multiple Linear Regression (LR), and Random Forest (RF). Three input combinations of daily maximum and minimum temperature (Tmax and Tmin), wind speed (W) with Tmax and Tmin, and solar radiation (Rs) with Tmax and Tmin were considered using meteorological data during 2003–2016 from six weather stations in the Red River Valley. To understand the performance of the applied models with the various combinations, station, and yearly based tests were assessed with local and spatial approaches. Considering the local and spatial approaches analysis, the LR and RF models illustrated the lowest rate of improvement compared to GEP and SVM. The spatial RF and SVM approaches showed the lowest and highest values of the scatter index as 0.333 and 0.457, respectively. As a result, the radiation-based combination and the RF model showed the best performance with higher accuracy for all stations either locally or spatially, and the spatial SVM and GEP illustrated the lowest performance among models and approaches.

Corrugated board, widely used in the packing industry, is a recyclable and durable material. Its strength and cushioning, influenced by geometry, environmental conditions like humidity and temperature, and paper quality, make it versatile. Double-walled (or five-ply) corrugated board, comprising two flutes and three liners, enhances these properties. This study introduces a novel approach to analyze 5-layered corrugated board, extending a previously published algorithm for single-walled boards. Our method focuses on measuring layer and overall board thickness, flute height, and center lines of each layer. Integrating image processing and genetic algorithms, the research successfully developed an algorithm for precise geometric feature identification of double-walled boards. Images were recorded using a special device with a sophisticated camera and image sensor for detailed corrugated board cross-sections. Demonstrating high accuracy, the method faced limitations only with very deformed or damaged samples. This research contributes significantly to quality control in the packaging industry and paves the way for further automated material analysis using advanced machine learning and image sensors. It emphasizes the importance of sample quality and suggests areas for algorithm refinement to enhance robustness and accuracy.

Fluctuating stock prices make it difficult for investors to see investment opportunities. One tool that can help investors overcome this is forecasting techniques. Long Short-Term Memory (LSTM) is one of deep learning methods used in forecasting time series. The training and success of deep learning is strongly influenced by the selection of hyperparameters. This research uses a hybrid method between the Genetic Algorithm (GA) and LSTM to find a suitable model for predicting stock prices. GA is used in optimizing the architecture such as the number of epochs, window size, and the number of LSTM units in the hidden layer. Tuning optimizer is also carried out using several optimizers to achieve the best value. From method that has been applied, it shows that the method has a good level of accuracy with MAPE values below 10% in every optimizer used. The error rate generated is quite low, in case-1 with a minimum RMSE value of 93.03 and 94.40, & in case-2 with an RMSE value of 104.99 and 150.06 during training and testing. A fairly stable and small value is generated by setting it using the Adam Optimizer.

Plasmodium vivax causes the second highest number of malaria morbidity and mortality cases in humans. Several biological traits of this parasite species, including the formation of dormant stages (hypnozoites) that persist inside the liver for prolonged periods of time, present an obstacle for intervention measures and create a barrier for the elimination of malaria. Research into the biology of hypnozoites requires efficient systems for parasite transmission, liver stage cultivation and genetic modification. However, P. vivax research is hampered by the lack of an in vitro blood stage culture system, rendering it reliant on in vivo derived, mainly patient material, for transmission and liver stage culture. This has also resulted in a limited capability for genetic modification, creating a bottleneck in investigations into the mechanisms underlying the persistence of the parasite inside the liver. This bottleneck can be overcome through optimal use of the closely related and experimentally more amenable nonhuman primate (NHP) parasite Plasmodium cynomolgi as model system. In this review we discuss the genetic modification tools and liver stage cultivation platforms available for studying P. vivax persistent stages and highlight how their combined use may advance our understanding of hypnozoite biology.

In this review, we discuss the insulin resistance (IR) and its development in the insulin target tissues that leads to diabetes. Also, we highlight the use of induced pluripotent stem cells (iPSCs) to understand the mechanisms underlying the development of IR. IR is associated with several metabolic disorders, including type 2 diabetes (T2D). The development of IR in insulin target tissues involves genetic and acquired factors. Persons at genetic risk for T2D tend to develop IR several years before glucose intolerance. Although there are currently several mouse models for both IR and T2D that had provided a lot of information about the disease, these models cannot recapitulate all the aspects of this complex disease as seen in each individual. Patient-specific iPSCs can overcome the hurdles faced with the classical mouse models for studying IR. iPSC technology can generate cells genetically identical to IR individuals, which can help in distinguishing between genetic and acquired defects in insulin sensitivity. Combining the technologies of the genome editing and iPSCs may provide important information about the inherited factors underlying the development of different forms of IR. Further studies are required to fill the gaps in understanding the pathogenesis of IR and diabetes.

This paper presents an alternative constraint handling approach within a specialized genetic algorithm (SGA) for the optimal reactive power dispatch (ORPD) problem. The ORPD is formulated as a nonlinear single-objective optimization problem aiming to minimize power losses while keeping network constraints. The proposed constraint handling approach is based on a product of sub-functions that represents permissible limits on system variables and that includes a specific goal on power loss reduction. The main advantage of this approach is the fact that it allows a straightforward verification of both feasibility and optimality. The SGA is examined and tested with the proposed constraint handling approach and the traditional penalization of deviations from feasible solutions. Several tests are run in the IEEE 30, 57, 118 and 300 bus test power systems. The results obtained with the proposed approach are compared to those offered by other metaheuristic techniques reported in the specialized literature. Simulation results indicate that the proposed genetic algorithm with the alternative constraint handling approach yields superior solutions when compared to other recently reported techniques.

Drought poses a significant constraint on rice production, and in this study, we have discovered a novel drought-sensitive mutant, designated as dsm3, arising from the progenies of indica rice variety Zhonghui8015 treated with EMS. Under drought stress conditions, dsm3 exhibited characteristic withered leaf tips, accompanied by increased levels of MDA and H2O2, reduced Pn, and decreased activity of POD and SOD. Genetic analysis revealed that the withered leaf tip phenotype was governed by a single recessive gene, designated as Osdsm3.To begin with, Osdsm3 was initially mapped to the short arm of chromosome 1 through a cross involving dsm3 and 02428. Subsequently, utilizing a population of 2591 F2 individuals, we narrowed down the location of Osdsm3 to a 78Kb interval, encompassing 13 open reading frames (ORFs). Sequencing analysis unveiled a mutation (1275G→A) in the exon of the candidate gene (LOC_Os01g10680), leading to premature translation termination. Moreover, a quantitative RT-PCR assay demonstrated high expression of OsDSM3 in the panicle and sheath, with a significant upregulation of drought stress-related genes under drought conditions. Phylogenetic analyses indicated that Osdsm3 shares evolutionary homology with UNE1, an intracellular transport protein found in Arabidopsis thaliana. Subcellular studies further confirmed that OsDSM3 resides in the cytoplasm. In conclusion, the forthcoming cloning of Osdsm3 holds promise for delving deeper into the molecular mechanisms governing rice drought resistance.

The production of plants and crops is influenced by environmental stress, which is a serious scientific issue. Cotton is an essential crop for producing natural fibers that are used to make biofuel and edible oils. Salinity is the main element that influences cotton growth during the beginning of germination. The type of salt and the growth stage affects how sensitive a plant is to salt stress. Developing ways to enhance cotton performance in salty circumstances can be aided by an understanding of the response of cotton to salt, its mechanism of resistance, and its management methods. Osmotic and ionic imbalances originate due to the deposition of soluble salts under salinity stress in the plant's root zone. Soil salinity significantly reduces plant growth due to several factors, such as nutritional ion imbalance, which reduces K+, PO4-, and NO- absorption, excessive salt chloride concentrations, and osmotic stress, which hinders water availability. Research has revealed that compared to subsequent stages, the germination, emergence, and seedling phases are more vulnerable to salinity stress, which ultimately affects the seed cotton yield by delaying blooming, reducing fruiting positions, shedding fewer fruits, and reducing boll weight. The morphology, growth of cotton roots, shoots, yield, and fiber quality are all strongly impacted by salinity stress. It slows down plant feeding, cellular metabolism, and photosynthesis. The soil, water, and climate all affect how the plant responds to salinity stress. During salt stress, excessive exclusion of sodium or its compartmentalization is the key adaptation process in cotton. A major adaptive potential to create cotton types that can withstand salt is provided by the up-regulation of both physicochemical and non-enzymatic antioxidant genes. A successful strategy to increase cotton germination in saline soils is seed priming. Moreover, the transgenic strategy might be a viable choice for improving cotton yield in saline environments. Our review focuses on the impacts of salinity on cotton productivity as well as how plants react to salt stress. It also clarifies recent genetic advancements and molecular breeding for cotton's resistance to soil salt. To create salt-tolerant cultivars, a combination of traditional breeding and novel molecular approaches will be useful.

Marek’s disease (MD) is an important neoplastic disease caused by serotype 1 Marek's disease virus (MDV-1), which results in severe economic losses worldwide. Despite vaccination practices that have controlled the MD epidemic, current increasing MD-suspected cases indicate the persistent viral infections circulating among vaccinated chicken farms in many countries. However, the lack of available information about phylogeny and molecular characterization of circulating MDV-1 field strains in Taiwan reveals a potential risk in MD outbreaks. This study investigated the genetic characteristics of 18 MDV-1 isolates obtained from 17 vaccinated chicken flocks in Taiwan between 2018 and 2020. Based on the sequences of the meq oncogene, phylogenetic analysis demonstrated that the circulating Taiwanese MDV-1 field strains were predominantly in a single cluster that showed high similarity with strains/isolates from countries of East Asian region. Because the isolated strains were obtained from CVI988/Rispens vaccinated chicken flocks and the molecular characteristics of the Meq oncoprotein showed the features like vvMDV and vv+MDV strains, the circulating Taiwanese MDV-1 field strains may have higher virulence compared with vvMDV pathotype. In conclusion, the presented data demonstrate the circulation of hypervirulent MDV-1 strains in Taiwan and highlight the importance of routine surveillance and precaution strategies in response to the emergence of enhanced virulent MDV-1.

This paper provides a comprehensive review of the current understanding of non-alcoholic fatty liver disease (NAFLD) and its progression to non-alcoholic steatohepatitis (NASH), focusing on key factors influencing its pathogenesis and emerging therapeutic strategies. The background highlights the growing prevalence of NAFLD and NASH, emphasizing their multifactorial nature. The methods section outlines the various contributors to NAFLD development, including genetic, dietary, and environmental factors. The results highlight the intricate interplay between these factors and their impact on hepatic lipid metabolism, inflammation, and insulin resistance. Genetic predisposition, dietary fat intake, and excessive fructose consumption are discussed as significant contributors to NAFLD progression. The conclusions emphasize the lack of a single therapeutic approach and underscore the need for combination strategies. Lifestyle interventions, particularly weight loss through diet and exercise, remain crucial, while pharmacological options like GLP-1 receptor agonists, obeticholic acid, lanifibranor, and resmetirom show promise but require further validation. Bariatric surgery and emerging endoscopic procedures offer potential in eligible patients. In sum, this review underscores the complexity of NAFLD and NASH, advocating for a multifaceted approach to address this increasingly prevalent and clinically relevant condition.

Nonsense mutations cause several genetic diseases such as Cystic fibrosis, Duchenne muscular dystrophy, β-thalassemia, and Shwachman-Diamond syndrome. These mutations induce the formation of a premature termination codon (PTC) inside the mRNA sequence that leads to the aberrant translation, resulting in the synthesis of truncated polypeptides. Nonsense suppression therapy mediated by translational readthrough-inducing drugs (TRIDs) is a promising approach to correct these genetic defects. TRIDs generate a ribosome miscoding of the PTC named “translational readthrough” and restore the synthesis of full-length and potentially functional protein. The new oxadiazole-core TRIDs NV848, NV914, and NV930 showed translational readthrough activity in nonsense-related in vitro systems. In this work, the possible off-target effect of NV molecules on natural termination codons (NTCs) was investigated. Two different in vitro approaches were used to assess if the NV molecules treatment induce NTCs readthrough: 1) A study of translational induced p53 molecular weight and functionality; 2) the evaluation of two housekeeping proteins (Cys-C and β2M) molecular weights. Our results showed that the treatment with NV848, NV914, or NV930 do not induce any translation alterations in both experimental systems. Data suggested that NV molecules have a specific action for the PTCs and an undetectable effect on the NTCs.

CRISPR-Cas9 technology allows the modification of DNA sequences in vivo at the location of interest. Although CRISPR-Cas9 can produce genomic changes that do not require DNA vector carriers, the use of transgenesis for stable integration of DNA coding for gene-editing tools into plant genomes is still the most used approach and it can generate unintended transgenic integrations, while Cas9 prolonged expression can increase cleavage at off-target sites. In addition, the selection of genetically modified cells from millions of treated cells, especially plant cells, is still challenging. These downfalls can be avoided with the delivery of preassembled ribonucleoprotein complexes (RNPs) composed of purified recombinant enzyme Cas9 and in vitro- transcribed guide RNA (gRNA) molecules in a protoplast system. We therefore aimed to develop the first DNA-free protocol for gene-editing in maize and introduced RNPs into their protoplasts with PEG 4000. We performed effective transformation of maize protoplasts using different gRNAs sequences targeting the inositol phosphate kinase gene and applying two different exposure times to RNPs. Using low-cost Sanger sequencing protocol, we observed an efficiency rate of 0.85 up to 5.85%, which is equivalent to DNA-free protocols used in other plant species. A positive correlation was displayed between exposure time and mutation frequency. Mutation frequency was gRNA sequence- and exposure time-dependent. In summary, we demonstrated the suitability of RNP transfection as an effective screening platform for gene-editing in maize. This efficient and relatively easy assay method for selection of gRNA suitable for editing of gene of interest will be highly useful for genome editing in maize, since genome size and GC-content are large and high in maize genome, respectively. Nevertheless, the large amplitude of mutations at target site requires scrutiny when checking mutations at off-target sites and potential safety concerns.

The identification of an emerging pathogen in humans can remain difficult by conventional methods such as enrichment culture assays that remain highly selective, require appropriate medium and cannot avoid misidentifications, or serological tests that use surrogate antigens and are often hampered by the level of detectable antibodies. Although not originally designed for this purpose, the implementation of polymerase-chain-reaction (PCR) has resulted in an increasing number of diagnostic tests for many diseases. However, the design of specific molecular assays relies on the availability and reliability of published genetic sequences for the target pathogen as well as enough knowledge on the genetic diversity of species and/or variants giving rise to the same disease symptoms. Usually designed for clinical isolates, molecular tests are often not suitable for environmental samples in which the target DNA is mixed with a mixture of environmental DNA. A key challenge of such molecular assays is thus to ensure high specificity of the target genetic markers when focusing on clinical and environmental samples in order to follow the dynamics of disease transmission and emergence in humans. Here we focus on Buruli ulcer (BU), a human necrotizing skin disease mainly affecting tropical and subtropical areas, commonly admitted to be caused by Mycobacterium ulcerans worldwide although other mycolactone-producing mycobacteria and even mycobacterium species were found associated with BU or BU-like cases. By revisiting the literature, we show that many studies have used non-specific molecular markers (IS2404, IS2606, KR) to identify M. ulcerans from clinical and environmental samples and propose that all mycolactone-producing mycobacteria should be definitively considered as variants from the same group rather than different species. Importantly, we provide evidence that the diversity of mycolactone-producing mycobacteria variants as well as mycobacterium species potentially involved in BU or BU-like skin ulcerations might have been underestimated. We also suggest that the specific variants/species involved in each BU or BU-like case should be carefully identified during the diagnosis phase, either via the key of genetic identification proposed here or by broader metabarcoding approaches, in order to guide the medical community in the choice for the most appropriate antibiotic therapy.

Waste management is an unavoidable technological operation in the process of raw material extraction. The main characteristic of this technological operation is the handling of large quantities of waste material, which can amount to several hundred million cubic metres. Working with this amount of material usually requires high-capacity systems for excavation and loading, a large fleet of trucks for haulage, construction, and maintenance of a complex roads network, use of a significant area of land in order to achieve the required capacities, etc. At the same time, this operation must comply with all administrative and environmental standards. Therefore, optimising waste rock management (particularly haulage and dumping) has the potential to significantly improve the overall value of the project. This paper presents a hybrid model for the optimisation of waste dump design and site selection. The model is based on different mathematical methods (genetic algorithm, analytic hierarchy process and heuristic methods) adapted to different aspects of the problem. The main objective of the model is to provide a solution (in analytical and graphical form) for the draft waste dump design, on the basis of which the final waste dump design can be defined.

Photogrammetry involves aerial photography of the earth’s surface and subsequently processing the images to provide a more accurate depiction of the area (Orthophotography). It’s used by the Spanish Instituto Geográfico Nacional to update road cartography but requires a significant amount of manual labor due to the need to perform visual inspection of all tiled images. Deep Learning techniques (artificial neural networks with more than one hidden layer) can perform road detection but it is still unclear how to find the optimal network architecture. Our system applies grammar guided genetic programming to the search of deep neural network architectures. In this kind of evolutive algorithm all the population individuals (here candidate network architectures) are constrained to rules specified by a grammar that defines valid and useful structural patterns to guide the search process. Grammar used includes well-known complex structures (e.g. Inception-like modules) combined with a custom designed mutation operator (dynamically links the mutation probability to structural diversity). Pilot results show that the system is able to design models for road detection that obtain test accuracies similar to that reached by state of the art models when evaluated over a dataset from the Spanish National Aerial Orthophotography Plan.

The populations of clearwing moth borers in Korea have recently exploited and severe damage on pin oaks (Quercus palustris Munchh.). We conducted the field monitoring and the molecular analyses to identify them in an integrated manner. Morphological examination and molecular analyses on COI-gene based intra-and inter-specific genetic divergences (GD) were revealed that the borers were recognized as two invasive species, Sphecodoptera sheni and Paranthrenella pinoakula sp. nov.. The maximum intraspecific GD was found to be 1.9%, whereas the minimum interspecific GD was confirmed as 8.1%, with a distinct barcoding gap. Both MJ network and NJ tree were also showed that 18 haplotypes (HAPs) were detected from the 52 COI sequences. The borers were revealed total 17 HAPs: i) H1-H7 were detected from all seven regions with S. sheni; ii) Wonju and Goyang populations of S. sheni were revealed as more than three HAPs; iii) H7 was closely connected with H8 of Chinese population of S. sheni; iv) H9-H10 were detected as the other samples from Wonju population with P. pinoakula sp. n., and closely located with congeneric species. Maximum likelihood tree also revealed that P. pinoacula sp. n. nested within the congeneric species by genetically separating from the S. sheni.

This mini-review provides an overview of traditional, emerging, and future applications of lactic acid bacteria (LAB) and discusses how genome editing tools can be used to overcome current challenges in all these applications. It also describes currently available tools and how these can be further developed, and takes current legislation into account. Genome editing tools are necessary for the construction of strains for new applications and products, but can also play a crucial role in traditional ones, such as food and probiotics, as a research tool for understanding mechanistic insights and discovering new properties. Traditionally, recombinant DNA techniques for LAB have strongly focused on being food-grade, but they lack throughput and the number of genetically tractable strains is still rather limited. Further tool development in this direction will enable rapid construction of multiple mutants or mutant libraries on a genomic level in a wide variety of LAB strains. We also propose an iterative Design-Build-Test-Learn workflow cycle for LAB cell factory development based on systems biology, with “cell factory” expanding beyond its traditional meaning of production strains and making use of high-throughput genome editing tools to advance LAB understanding, applications and strain development.

On-going intensification of rice production systems in Southeast Asia is causing devastating yield losses each year due to rice hoppers. Continuing development of immunity to resistant rice varieties and pesticide application further complicate this problem. Hence, there is a high demand for biological control agents. Egg parasitoid wasps are among the most important natural enemies of rice hoppers such as Nilaparvata lugens and Nephotettix spp. However, our knowledge on their diversity is still very limited due to their small size and the lack of available morphological information. Classifying these parasitoids is the first step to properly understand their role in the rice agroecosystem. We used traditional morphological identification as well as DNA sequencing of COI and 28S genes to investigate the diversity of four important hopper egg parasitoid genera in the Philippines. Parasitoids of the genera Anagrus spp., Oligosita spp., Gonatocerus spp. and Paracentrobia spp. were collected in eight study landscapes located in Luzon. We found discrepancies between the morphological and the molecular analysis. Morphological and molecular results were only valid for Paracentrobia spp. Anagrus spp. and Gonatocerus spp. showed more genetic diversity, than expected after the morphological analysis, indicating cryptic species. The sequences for Oligosita spp. revealed less variation than expected. This is the first study on molecular diversity of rice parasitoids in the Philippines. More research combining morphological, behavioural and genetic methods as well as the establishment of a comprehensive DNA database is urgently needed to assess the performance and suitability of these organisms as biocontrol agents.

The genetic diversity of local coffee populations is crucial to breed new varieties better adapted to the increasingly stressful environment due to climate change and the evolving consumer preferences. Unfortunately, local coffee germplasm conservation and genetic assessment have not received much attention. Molecular tools offer substantial benefits in identifying and selecting new cultivars or clones suitable for sustainable commercial utilization. New annotation methods, such as chloroplast barcoding, are necessary to produce accurate and high-quality phylogenetic analyses. This study used DNA barcoding techniques to examine the genetic relationships among fifty-six accessions collected from the southern part of Saudi Arabia. PCR amplification and sequence characterization were used to investigate the effectiveness of four barcoding loci, namely atpB-rbcl, TrnL-TrnF, TrnT-TrnL, and TrnL. The maximum nucleotide sites, nucleotide diversity, and an average number of nucleotide differences were recorded for atpB-rbcl, while TrnT-TrnL had the highest variable polymorphic sites, segregating sites, and haploid diversity. Among the four barcode loci, TrnT-TrnL recorded the highest singleton variable sites, while TrnL recorded the highest parsimony information sites. Furthermore, the phylogenetic analysis clustered the Coffea arabica genotypes into four different groups, with three genotypes (KSA31, KSA38, and KSA46) found to be the most divergent genotypes standing alone in the cluster and remained apart during the analysis. The study demonstrates the presence of considerable diversity among coffee populations in Saudi Arabia. Furthermore, it also shows that DNA barcoding is an effective technique for identifying local coffee genotypes, with potential applications in coffee conservation and breeding efforts.

Production of lumpfish (Cyclopterus lumpus) has become crucial in controlling sea lice levels in salmonid aquaculture. To improve their breeding, there is a need for early sex identification. The genomic region containing anti-Müllerian hormone (amh) gene was suggested as the candidate sex-determining gene in lumpfish. However, the genome of lumpfish contains three copies of amh with ambiguous sex specificity, designated amh1, amh2, and amh3. The study aims to analyse the male-specific region between these amh paralogues, for its application as a sex marker. In this study, we utilised polymerase chain reaction (PCR)-based assays to identify the male-specific amh markers in lumpfish and estimate the length of the male-specific region in the lumpfish genome. Our results suggest that a region of approximately 26 kilobase (kb) region containing amh1 and amh2 is male-specific, while both sexes share amh3. The developed PCR-based genetic sex identification assays targeting amh1 and amh2 exhibited more than 97% accuracy. Further experiments in other members of the Cyclopteridae: Aptocyclus ventricosus, Eumicrotremus taranetzi, and E. asperrimus revealed male-specific amh fragments only in A. ventricosus. Phylogenetic analyses using the available Cyclopteridae amh sequences suggest that male-specific amh arose early in the Cyclopteridae lineage. These findings and development of the PCR test will be of service to lumpfish aquaculture as well as to future studies attempting to further elucidate the sex-determination system and sex chromosome evolution in lumpfish.

Tobacco smoke is an environmental mixture including polycyclic aromatic hydrocarbons and may interfere in endocrine system as an EDC in aging. Thus, we performed a molecular epidemiological approach with in-depth biological monitoring of combustible cigarette smoking among adolescents and adults in South Korea (N=620) with exposure biomarkers, i.e., exhaled CO, urinary cotinine, t,t-muconic acid (TTMA), malondialdehyde (MDA), and obtained information of their lifestyle and tobacco addiction status. We also diagnosed the genetic polymorphisms on the 96 SNPs for tobacco-metabolism, -addiction, and expression differences and compared mtDNA abnormalities in buccal and blood cells. As results, there were positive associations among the above tobacco exposure biomarkers. Man or youth smokers showed high frequency in some of mtDNA alteration, such as ‘SNPs for inconsistent bases between buccal and blood cells’. Among the SNPs, the polymorphisms on SULT1A1, DRD2, and ADH1B were related to multi-exposure biomarkers. Interestingly, youth showed similar levels of urinary TTMA and MDA to adults, although their pack-year was approx. 1/6 volume of that of adults. We also observed the negative association between urinary MDA levels and the growth rate in the adolescents (p<0.05). In conclusion, the present biological monitoring provides high susceptible population, i.e., adolescents rather than adults, and reliable genetic factors affecting tobacco exposure. The inferred environment-gene-gene interaction suggests tobacco smoking accelerats aging in adolescents as an EDC.

Current oncological developments are based on improved understanding of genetics, and especially the discovery of genes whose alterations affect cell functions with consequences for the whole body. Our work is focused on the one of these genes, the BARD1 and its oncogenic role in breast cancer. Most importantly, the study points to new avenues in the treatment and prevention of the most frequent female cancer based on BARD1 research. The BARD1 and BRCA1 proteins have similar structures and functions, and they combine to form the new molecule BARD1-BRCA1 heterodimer. The BARD1-BRCA1 complex is involved in genetic stabilization at the cellular level. It allows to mark abnormal DNA fragments by attaching ubiquitin to them. In addition, it blocks (by ubiquitination of RNA polymerase II) the transcription of damaged DNA. Ubiquitination, as well as stabilizing chromatin, or regulating the number of centrosomes, confirms the protective cooperation of BARD1 and BRCA1 in the stabilization of the genome. The overexpression of the oncogenic isoforms BARD1β and BARD1δ permit cancer development. The introduction of routine tests, for instance, to identify the presence of the BARD1β isoform, would make it possible to detect patients at high risk of developing cancer. On the other hand, introducing BARD1δ isoform blocking therapy, which would reduce estrogen sensitivity, may be a new line of cancer therapy with potential to modulate responses to existing treatments. It is possible that the BARD 1 gene offers new hope for improving breast cancer therapy.

Current oncological developments are based on improved understanding of genetics, and especially the discovery of genes whose alterations affect cell functions with consequences for the whole body. Our work is focused on the most important of these genes, the BARD1 and its oncogenic role in breast cancer. Most importantly, the study points to new avenues in the treatment and prevention of the most frequent female cancer based on BARD1 research. The BARD1 and BRCA1 proteins have similar structures and functions, and they combine to form the new molecule BARD1-BRCA1 heterodimer. Through ubiquitination, this heterodimer has significant effects on individual proteins, enabling, among others, the destruction of damaged DNA fragments. Ubiquitination, as well as stabilizing chromatin, or regulating the number of centrosomes, confirms the protective cooperation of BARD1 and BRCA1 in the stabilization of the genome. The overexpression of the oncogenic isoforms BARD1β and BARD1δ permit cancer development. The introduction of routine tests, for instance, to identify the presence of the BARD1β isoform, would make it possible to detect patients at high risk of developing cancer. On the other hand, introducing BARD1δ isoform blocking therapy, which would reduce estrogen sensitivity, may be a new line of cancer therapy with potential to modulate responses to existing treatments. It is possible that the BARD 1 gene offers new hope for improving breast cancer therapy.

Artemia franciscana, native to America, has recently colonized non-indigenous populations in Eurasia, Mediterranean regions and Australia. In present we sought to evaluate the potential effects of colonization of A. franciscana on genetic differentiation in the new environments in UAE. We used the COI marker to determine population genetic structure and identify the origins of exotic populations in UAE. Our findings have confirmed the colonization of both localities by A. franciscana. Genetic variation of invasive A. franciscana were exclusively lower than native population in Great Salt Lake and San Francisco Bay. Results have showed the studied population could not possibly have colonized directly from natural American localities, perhaps resulting from secondary introduction events from other non-indigenous populations. Genetic analysis have yielded different demographic patterns for invasive studied populations. Al Wathba Wetland Reserve (AWWR) population have represented demographic expansion. In contrast, Godolphin Lakes (GL) population was at demographic equilibrium. Neutrality tests have documented the excess of both recent and historical mutations in the COI gene pool of invasive AWWR Artemia throughout establishment in the new environment.