Population Diversity Research Articles

Evaluation of Aedes aegypti control intervention with pyriproxyfen by lcWGS in Manacapuru, Amazonas, Brazil.

Ae. aegypti mosquitoes are considered a global threat to public health due to its ability to transmit arboviruses such as yellow fever, dengue, Zika and Chikungunya to humans. The lack of effective arboviral vaccines and etiological treatments make vector control strategies fundamental in interrupting the transmission cycle of these pathogens. This study evaluated Ae. aegypti mosquito populations pre- and post-intervention period with disseminating stations of the larvicide pyriproxyfen to understand its potential influence on the genetic structure and population diversity of these vectors. This study was conducted in Manacapuru city, Amazonas, Brazil, where 1,000 pyriproxyfen dissemination stations were deployed and monitored from FEB/2014 to FEB/2015 (pre-intervention) and AUG/2015 to JAN/2016 (post-intervention). Low-coverage whole genome sequencing of 36 individuals was performed, revealing significant stratification between pre- and post-intervention groups (pairwise FST estimate of 0.1126; p-value < 0.033). Tajima's D estimates were -3.25 and -3.07 (both p-value < 0.01) for pre- and post-intervention groups, respectively. Molecular diversity estimates (Theta(S) and Theta(Pi)) also showed divergences between pre- and post-intervention groups. PCA and K-means analysis showed clustering for SNP frequency matrix and SNP genotype matrix, respectively, being both mainly represented by the first principal component. PCA and K-means clustering also showed significant results that corroborate the impact of pyriproxyfen intervention on genetic structure populations of Ae. aegypti mosquitoes. The results revealed a bottleneck effect and reduced mosquito populations during intervention, followed by reintroduction from adjacent and unaffected populations by this vector. We highlighted that low-coverage whole genome sequencing can contribute to genetic and structure population data, and also generate important information to aid in genomic and epidemiological surveillance.

Improving the Kepler optimization algorithm with chaotic maps: comprehensive performance evaluation and engineering applications

The Kepler Optimisation Algorithm (KOA) is a recently proposed algorithm that is inspired by Kepler’s laws to predict the positions and velocities of planets at a given time. However, although promising, KOA can encounter challenges such as convergence to sub-optimal solutions or slow convergence speed. This paper proposes an improvement to KOA by integrating chaotic maps to solve complex engineering problems. The improved algorithm, named Chaotic Kepler Optimization Algorithm (CKOA), is characterized by a better ability to avoid local minima and to reach globally optimal solutions thanks to a dynamic diversification strategy based on chaotic maps. To confirm the effectiveness of the suggested approach, in-depth statistical analyses were carried out using the CEC2020 and CEC2022 benchmarks. These analyses included mean and standard deviation of fitness, convergence curves, Wilcoxon tests, as well as population diversity assessments. The experimental results, which compare CKOA not only to the original KOA but also to eight other recent optimizers, show that the proposed algorithm performs better in terms of convergence speed and solution quality. In addition, CKOA has been successfully tested on three complex engineering problems, confirming its robustness and practical effectiveness. These results make CKOA a powerful optimisation tool in a variety of complex real-world contexts. After final acceptance, the source code will be uploaded to the Github account: nawal.elghouate@usmba.ac.ma.

Genetic Diversity of Local Chili (Capsicum annum L.) from West Sumatra Indonesia Based on Inter Simple Sequences Repeat (ISSR) Markers

Capsicum annum L. is the most widely cultivated species due to its economic importance and health benefits. West Sumatra is one of the largest chili pepper producers in Indonesia, so it has a lot of local chili genetic resources. There is inadequate information on the genetic diversity of local chilies in West Sumatra. The purpose of this research was to analyze the genetic diversity of 23 genotypes of chili pepper from West Sumatra amplified with 10 markers of ISSR. The material used was leaves from 23 genotypes of West Sumatra’s local chili which are collections of the Agriculture Faculty, Andalas University, Padang, West Sumatra. The results showed that ISSR markers (ISSR primer 12, ISSR UBC, and ISSR 3M) had produced 84 polymorphic DNA bands with a total polymorphic percentage of 61.45%. The dendrogram based on 10 ISSR markers showed that the 23 chili genotypes were retrieved into three main groups (I, II, III, IV) with genetic similarity coefficient values ranging from 0.67 to 0.97 or a diversity of features of 0.03–0.33 (30%). Group I consisted of 1 genotype, group II consisted of 3 genotypes, and group III consisted of 14 genotypes. Kopay chili (G20) has a large genetic distance compared to the other genotypes, while Lolai and Gero chilies have a very high similarity. This genetic diversity information can be used as a basis for generating crosses between genotypes in a breeding program. The farther the genetic distance will produce a high population diversity, the greater the chance of getting superior hybrids. Keywords: Capsicum annum, ISSR, local chili, West Sumatra

Cross-ancestry analysis of brain QTLs enhances interpretation of schizophrenia genome-wide association studies

Research on brain expression quantitative trait loci (eQTLs) has illuminated the genetic underpinnings of schizophrenia (SCZ). Yet most of these studies have been centered on European populations, leading to a constrained understanding of population diversities and disease risks. To address this gap, we examined genotype and RNA-seq data from African Americans (AA, n= 158), Europeans (EUR, n= 408), and East Asians (EAS, n= 217). When comparing eQTLs between EUR and non-EUR populations, we observed concordant patterns of genetic regulatory effect, particularly in terms of the effect sizes of the eQTLs. However, 343,737 cis-eQTLs linked to 1,276 genes and 198,769 SNPs were found to be specific to non-EUR populations. Over 90% of observed population differences in eQTLs could be traced back to differences in allele frequency. Furthermore, 35% of these eQTLs were notably rare in the EUR population. Integrating brain eQTLs with SCZ signals from diverse populations, we observed a higher disease heritability enrichment of brain eQTLs in matched populations compared to mismatched ones. Prioritization analysis identified five risk genes (SFXN2, VPS37B, DENR, FTCDNL1, and NT5DC2) and three potential regulatory variants in known risk genes (CNNM2, MTRFR, and MPHOSPH9) that were missed in the EUR dataset. Our findings underscore that increasing genetic ancestral diversity is more efficient for power improvement than merely increasing the sample size within single-ancestry eQTLs datasets. Such a strategy will not only improve our understanding of the biological underpinnings of population structures but also pave the way for the identification of risk genes in SCZ.

Genetic Programming With Lexicase Selection for Large-Scale Dynamic Flexible Job Shop Scheduling

Dynamic flexible job shop scheduling is a prominent combinatorial optimisation problem with many real-world applications. Genetic programming has been widely used to automatically evolve effective scheduling heuristics for dynamic flexible job shop scheduling. A limitation of genetic programming is the premature convergence due to the loss of population diversity. To overcome this limitation, this work considers using lexicase selection to improve population diversity, which has achieved success on regression and program synthesis problems. However, it is not trivial to apply lexicase selection to genetic programming for dynamic flexible job shop scheduling, since a fitness case (training scheduling simulation) is often large-scale, making the fitness evaluation very time-consuming. To address this issue, we propose a new multi-case fitness scheme, which creates multiple cases from a single scheduling simulation. Based on the multi-case fitness, we develop a new genetic programming algorithm with lexicase selection, which uses a single simulation for fitness evaluation, thus achieving a better balance between the number of cases for lexicase selection and evaluation efficiency. The experiments on a wide range of dynamic scheduling scenarios show that the proposed algorithm can achieve better population diversity and final performance than the current genetic programming parent selection methods and a state-of-the-art deep reinforcement learning method.

Connectivity and high genetic diversity in populations of the dog snapper Lutjanus jocu (Lutjanidae: Perciformes) from the South Western Atlantic, recovered with multilocus analysis

Connectivity and high genetic diversity in populations of the dog snapper Lutjanus jocu (Lutjanidae: Perciformes) from the South Western Atlantic, recovered with multilocus analysis

Solving Multi-Objective Optimal Control Problems Using a Multiresolution Approach

This paper presents an adaptive multiresolution strategy for multi-objective optimal control problems. The optimal control problem is solved using a direct approach, with individualistic grid adaptation facilitated by a local error analysis at element boundaries. Multiple objectives are considered using a dominance-based approach applying both local and global search methods to a collaborative population of unique solutions. These aspects are simultaneously incorporated via a novel application of evolutionary algorithms for adaptive optimal control problems. Together, this avoids the need for a priori specification of the quantity and temporal location of element boundaries and the set of scalarization weights defining the multi-objective descent directions. Solution fidelity can thus increase concurrently with the exploration of the design space, which leads to increased numerical efficiency while propagating and maintaining population diversity. The benefits of the proposed approach over traditional uniform-grid implementations are demonstrated. Results show that the multiresolution approach is capable of striking an effective balance between solution fidelity, population diversity, and computational cost unachievable using uniform grids.

HLA Genetic Variants in COVID-19 Susceptibility: Assessing Diversity in Indian and Global Populations

Background: The rapid spread of the SARS-CoV-2 virus has had a global impact on various ethnic groups. In order to assess the genetic predisposition of the Indian population towards COVID-19, a comparative analysis was conducted using the Human Leukocyte Antigen (HLA) to investigate the frequencies of polymorphisms directly or potentially associated with COVID-19 susceptibility, severity, immune response, and fatal outcomes in comparison to other major populations. Objectives: The objective of this study is to evaluate the genetic predisposition of the Indian population to COVID-19 by analyzing the frequencies and associations of Human Leukocyte Antigen (HLA) polymorphisms. In addition, by delineating the role of specific HLA variants in the Indian context, the study seeks to enhance our understanding of genetic factors influencing COVID-19 impact and contribute to personalized approaches for disease management and prevention across diverse ethnic groups. Methods: We collected allelic information for DRB1 gene from 653 populations globally, as documented in The Allele Frequency Net Database (AFND). Data on COVID-19 susceptibility, severity, mortality, and protective factors were obtained from a previous global study. This study aimed to compare the specific frequencies of HLA-DRB1* in different ethnic groups, including other Indian populations with COVID-19-associated alleles and protective factors. Results: HLA-DRB1*01 was identified as a significant determinant of COVID-19 susceptibility among patients in 28 states of Mexico, whereas DRB1*08 in Saudi Arabian populations, DRB1*09:01 in Japanese populations, and DRB1*15:01 in Italian populations also showed this association. Likewise, DRB1*04 in the Iranian population played a role in disease severity, and DRB1*08 in the Italian population was associated with mortality in COVID-19 patients. In addition, alleles DRB1*01:01 and DRB1*04:01 were found to exhibit a protective role in Northeast England, whereas DRB1*04 demonstrated protective effects in Saudi Arabian populations. Conclusion: The involvement of HLA in COVID-19 requires further investigation, and epidemiological studies should focus on HLA profiles as determinants of the host immune system. Prolonged homozygosity in particular genomic regions could potentially increase susceptibility to COVID-19 infection. Therefore, prudent management strategies are recommended for this pandemic in isolated communities in India and worldwide.

Characterising healthy Australian oral microbiomes for ‘super donor’ selection

ObjectivesAmong healthy people, we understand very little about the sociodemographic, lifestyle, and dental hygiene behaviours that shape their oral microbiota. This study investigates how sociodemographic, lifestyle and dental hygiene behaviours shape oral microbiota diversity and composition in an Australian population to better inform healthy oral microbiota donors for Oral Microbiota Transplantation (OMT). MethodsThe study comprised 93 healthy people who underwent comprehensive oral examinations and questionnaires to assess their health status. Participants were excluded if they had any active systemic or oral disease. All completed a questionnaire containing information on socio-economic, lifestyle, behavioural, and oral health factors. Supragingival plaque was collected, and 16S ribosomal RNA (rRNA) amplicon sequencing was used to analyse microbial composition. Associations between the core microbiome, alpha- (within-sample), beta-diversity (between-sample) and an individual's co-variates were tested for statistical significance. A redundancy analysis (RDA), multivariate adonis, differential abundance and correlation analysis were performed to characterise which factors drive the variation in the healthy oral microbiome. ResultsStreptococcus and Corynebacterium were the most prevalent and abundant genera among healthy Australians. The alpha and beta diversity were higher among unemployed non-Australian-born students who consumed low carbohydrates, fat, and sugar and had not visited the dentist for over 12 months. Additionally, beta diversity was significantly higher among daily flossers who abstained from fluoride treatment and had high salivary pH, although no single factor explained more than 4% of the total variation (R2= 0.042). Alloprevotella, Lachnosporacea, and Parvimonas were significantly abundant among non-Australians who did not visit the dentist within a year. The RDA analysis revealed associations between microbiome composition and factors such as high carbohydrate, sugar, and fat consumption, low fibre intake, and regular dental checks among Australian-born individuals. ConclusionThese findings indicate that alpha and beta diversity of the oral microbiome varied significantly with sociodemographic, lifestyle, and dietary factors, including non-Australian birthplaces, unemployment, diet, and infrequent dental visits. Clinical SignificanceThese findings underscore the importance of considering diverse sociodemographic, lifestyle, and dietary factors in oral health management. Before microbiome transplantations, clinicians should account for individual characteristics that may be beneficial for shaping and maintaining optimal oral microbiome diversity and health.

New simple sequence repeat markers reveal undetected diversity in Spanish and Californian Diplodia sapinea populations

Diplodia sapinea is the causal agent of Diplodia shoot blight, an emerging disease affecting pine forests worldwide. The range expansion of this pathogen in northern Europe has been suggested to be partially facilitated by recent warmer conditions. Although D. sapinea has been studied extensively, critical aspects of its infection biology and population structure remain unexplored. In this study, we developed nine simple sequence repeat (SSR) markers mined from D. sapinea genomes to assess the genetic diversity at higher resolution. Isolates from northern Spain, an area formerly regarded as having low genetic diversity and samples from a Californian population that was formerly regarded as clonal, were analysed in the study. In Spain, the nine SSR markers identified 56 genotypes in 285 samples. Isolates from symptomatic shoots, cones and asymptomatic tissues collected from different stands, suggested admixture between local populations. The same genotype tended to dominate within a single cone, and the same genotypes were usually found in both symptomatic and asymptomatic shoot tissues. The nine new SSR markers developed in this study revealed a high level of genetic diversity in both the northern Spanish and northern Californian populations than previous anticipated. Analyses using these nine SSR markers should contribute to a better understanding of the epidemiology, evolution and origin of D. sapinea, a pathogen that is gaining prominence in many parts of the world.

Wolbachia infection in natural mosquito populations from Argentina.

The increasing spread of mosquito vectors has made mosquito-borne arboviral diseases a global threat to public health, leading to the urgent need for effective population control methods. Strategies based in the intracellular bacterium Wolbachia Hertig, 1936 are considered environmentally friendly, safe for humans, and potentially cost-effective for controlling arboviral diseases. To minimize undesirable side effects, it is relevant to assess whether Wolbachia is present in the area and understand the diversity associated with native infections before implementing these strategies. With this purpose, we investigated Wolbachia infection status, diversity, and prevalence in populations of Aedes albifasciatus (Macquart, 1838), Aedes fluviatilis (Lutz, 1904), and hybrids of the Culex pipiens (Linnaeus, 1758) complex from Argentina. Aedes albifasciatus and C. pipiens complex samples were collected in the province of Buenos Aires, and A. fluviatilis in the province of Misiones. Aedes albifasciatus was found to be uninfected, while infections with strains wFlu and wPip were detected in A. fluviatilis and hybrids of the C. pipiens complex, respectively. All strains were fixed or close to fixation and clustered within supergroup B. These finding provides valuable information on Wolbachia strains found in natural mosquito populations in Argentina that might be used in heterologous infections in the future or be considered when designing control strategies based on Wolbachia infection.

An Improved Grey Wolf Optimizer(IGWO) algorithm for optimization of centrifugal pump with guide vane

Abstract To improve the hydraulic performance of a centrifugal pump with guide vane, an improved grey wolf optimizer (IGWO) algorithm is proposed. First, the IGWO algorithm enhances the diversity and global exploration of the initial population with optimal Latin hypercube sampling. Then, the convergence factor is improved by combining the Tanh function to meet the needs of complex non-linear optimization problems. Finally, a search mechanism that enhances population communication is constructed and combined with a mutation-driven search scheme to improve the ability to avoids the local optima traps. The results show that IGWO algorithm has obvious advantages in convergence speed and robustness when dealing with complex non-linear optimization problems. Additionally, satisfactory results are achieved in the application of centrifugal pump optimization. The efficiency of optimized pump reaches 87.8%, which is 1.2% higher than that of the original pump. The anti-cavitation performance of the centrifugal pump is enhanced by improving the distribution of blade inlet attack angles. The vortex area inside the optimized pump impeller is reduced over a large area, and the operating stability of the pump, the matching between the impeller and the guide vane, and the flow characteristics in the guide vane domain are all improved.

Identifying and mitigating racial/ethnic disparities in clinical trials with screening data.

63 Background: ASCO and Association of Community Cancer Centers (ACCC) released a statement on increasing racial/ethnic equity, diversity, and inclusion (EDI) in cancer trials (1). It included recommendations for clinical practices and research sites to 1) screen every patient for trial eligibility; and 2) routinely collect and analyze screening and enrollment data by patient demographic characteristics, including race/ethnicity. Most of the 62 sites that completed a 2021 pilot study reported that screening data were not readily available by patient race/ethnicity (2). ASCO conducted a follow-up study about challenges, resource needs, and effective strategies for collecting and analyzing these data. Methods: Semi-structured interviews were conducted with research team members from sites that completed the 2021 pilot study. Sites were purposefully selected based on pilot study data quality and insights, diversity of patient population, and site type, size, and region. Sites completed a pre-interview questionnaire on site characteristics and screening and enrollment processes before participating in a 1-hour interview focused on challenges and effective strategies for collecting and analyzing screening and enrollment data, by race/ethnicity. Anticipated themes and relationships, stemming from the pilot study findings, informed a conceptual framework. Up to 20 interviews were planned and halted sooner when there was theme saturation. Results: Thirteen research sites participated in the study, representing academic centers (62%) and community-based practices/health systems (38%) with racially/ethnically diverse patient populations (median 31% non-white; range 11% to 63%). 53 research team members participated in the interviews (typically 4 per site), including investigators (23%), directors/managers (56%), and coordinators (21%). Aggregated responses were interpreted through content analysis and concepts were quantified for both frequency and extensiveness. Several barriers to patient screening, data collection, and analysis were cited, including lack of standardized procedures and documentation, dedicated staff and time, quality and/or accessible data on race/ethnicity and/or screening, and integrated technology that facilitates screening and documentation. Conclusions: Collecting and analyzing screening and enrollment data are critical to identifying and mitigating racial/ethnic disparities in trial access and EDI. Many sites do not systematically screen every patient for a trial and/or document outcomes. Lack of resources, including dedicated staff and time and integrated technology, make it difficult for them to do so in systematic and reliable ways. Greater investment in resources will help to facilitate routine screening of every patient and ensure underrepresented populations are not being overlooked for trials. 1. Oyer et al, JCO, 2022 . 2. Pressman et al, JCO, 2022 .

Ukrainian women's maternity care strategies in Poland after the outbreak of the full-scale war: Understanding unequal access to quality care

The outbreak of the full-scale war launched by Russia against Ukraine and, following it, significant migrations have not only increased the diversity of the Ukrainian migrant population in Poland, but also added to the complexity of their health needs and strategies. This study seeks to explore Ukrainian migrant women's experiences and practices related to the use of maternity care services. The article is based on fieldwork conducted between February and October 2023 and included 23 semi-structured interviews with Ukrainian migrant women who gave birth in Poland after February 24, 2022. To understand Ukrainian women's pathways to maternity care in Poland and unpack the differences in experiences within this group of migrants, we explore participants' healthcare strategies against the background of existing inequalities in access to quality care in Poland and Ukraine, in particularly the division between private and public services. We consider the role of financial, social and cultural resources and distinguish for this purpose between three groups of permanent, circular and wartime migrants. We show the decisive role of economic resources, nonetheless in articulation with the creation and mobilisation of social networks and time spent in Poland, which play a role in shaping migrant women's capacity to access better maternity care.

An enhanced seagull algorithm for multi-threshold image segmentation based on Kapur entropy

Abstract To address the shortcomings of the Seagull Optimization Algorithm (SOA), such as poor distribution of individuals’ positions and low population diversity leading to susceptibility to local optima after the collision avoidance phase, an Enhanced Seagull Algorithm (ESOA) is proposed. Firstly, a chaos-guided mechanism is utilized to replace the original individual positions after collision avoidance with the mean of individual optima and current positions, effectively improving the distribution of the population. Secondly, a circular-topology neighborhood structure with random weights is introduced, allowing interaction between the current individual’s position and the information from its two adjacent optimal positions, thereby improving population clustering and enhancing diversity. Thirdly, a dynamic lens mapping strategy is employed to direct the optimal seagull individuals toward their newly generated mapped points, enhancing their ability to avoid local optima. ESOA is applied to the problem of multi-threshold image segmentation based on Kapur entropy, and experimental results demonstrate its effectiveness in improving segmentation performance.

Ship Lock Chamber Arrangement in Xiangjiang River Based on Artificial Bee Colony and Adaptive Genetic Algorithm

Abstract To plan the ship lock chamber arrangement in Xiangjiang river, an artificial bee colony-adaptive genetic algorithm was proposed for the scheduling of the lock chamber, considering that the performance of the basic genetic algorithm relies on the quality of the initial population, the selection of genetic operators, crossover, and mutation operations. Firstly, the artificial bee colony algorithm was used to initialize the population to enhance population diversity. The utilization rate of the lock chamber and the waiting time for the lock were used as evaluation indicators for the fitness function. Then, adaptive strategies were designed to adjust the crossover and mutation operators to improve the convergence speed of the algorithm. Experimental results showed that, in a Xiangjiang river ship lock chamber with a size of 280 m×34 m, the average number of ships selected by the proposed artificial bee colony-adaptive genetic algorithm was 2 more than that of manual scheduling and 1.5 more than that of the genetic algorithm. The utilization rate of the lock chamber scheduling was increased by 13.01% compared to manual scheduling and by 5.4% compared to the genetic algorithm. The average waiting time for the lock was reduced by 1.3 hours compared to manual scheduling and by 0.8 hours compared to the genetic algorithm. It effectively improves the efficiency of ship traffic and optimizes the utilization of the lock chamber, making it practical for real-world applications.

Calibrating and Standardizing the Tip of the Red Giant Branch in the Small Magellanic Cloud Using Small-amplitude Red Giants

We investigate the absolute calibration of the tip of the red giant branch (TRGB) in the Small Magellanic Cloud (SMC) using small amplitude red giant stars (SARGs) classified by the Optical Gravitational Lensing Experiment (OGLE). We show that all stars near the SMC’s TRGB are SARGs. Distinguishing older and younger RGs near the tip according to two period–luminosity sequences labeled A and B, we show many similarities among SARG populations of the Large Magellanic Cloud (LMC) and the SMC, along with notable differences. In particular, SMC SARGs have shorter periods due to lower metallicity and smaller amplitudes due to younger ages than LMC SARGs. We discover two period–color relations near the TRGB that span all A-sequence and B-sequence stars in the OGLE-III footprints of the SMC and LMC, and we investigate using periods instead of color for TRGB standardization. Using variability-derived information only, we trace the SMC’s age and metallicity gradients and show the core to be populated by younger, more metal-rich RGs. The B-sequence yields the brightest and most accurate calibration (M F814W,syn = −4.057 ± 0.019(stat.) ± 0.029(syst.) mag), which we use to measure the distance modulus difference between the Clouds and investigate metallicity effects. Distance measurements not informed by variability should employ the SARG-based calibration based on all stars near the tip (M F814W,syn = −4.024 ± 0.041(stat.) ± 0.029(syst.) mag). Our work highlights the impact of RG population diversity on TRGB distance measurements. Further study is needed to unravel these effects and improve TRGB standardization.

Modified Genetic Algorithm for Efficient High-Utility Itemset Mining

In pattern mining, high-utility itemset mining (HUIM) is useful for discovering high-utility patterns. The study of HUIM using heuristic techniques reflects issues in producing better offspring. It is ineffective in terms of search space organization, population diversity, and utility calculation, which impact runtime and accuracy. It is observed that very few researchers have experimented with genetic algorithm (GA) and are still facing the same issues as mentioned before. To overcome these problems, a novel approach is proposed for HUIM using modified GA and optimized local search (HUIM-MGALS) with six potential contributions. First is linking the utility with the Bitmap dataset to reduce utility access time, leading to effective search space organization. Second, HUIM-MGALS employs a fitness scaling strategy to avoid redundancy. Third, a high-utility itemset (HUI) revision strategy is employed to explore significant HUIs. Modified population diversity maintenance strategy and iterative crossover help to preserve significant HUIs and improve search capability as fourth and fifth contributions. Sixth, the use of multiple mutations refines the wasted individuals to boost accuracy. Extensive experimentation showed that HUIM-MGALS significantly outperforms the presented algorithms, up to 8.6 times faster. It also demonstrates superior HUI discovery capabilities for both sparse and dense datasets. This is supported by the modified population diversity maintenance strategy, which is proved to be the most impactful modification for HUI discovery in HUIM-MGALS.

Genetic polymorphism of Duffy binding protein in Pakistan Plasmodium vivax isolates

Plasmodium vivax Duffy binding protein (PvDBP) is crucial for erythrocyte invasion, interacting with the Duffy Antigen Receptor for Chemokines (DARC) on the erythrocyte surface. The amino-terminal cysteine-rich region II of PvDBP (PvDBPII) is a promising blood stage vaccine candidate, yet the genetic polymorphisms of this protein in global P. vivax isolates complicate the design of effective vaccines against vivax malaria. This study analyzed the genetic polymorphism of PvDBPII in Pakistan P. vivax isolates. A total of 29 single nucleotide polymorphisms (SNPs), including 22 nonsynonymous SNPs, were identified in 118 Pakistan PvDBPII. Most amino acid substitutions occurred in subdomains II and III, with six commonly observed in the global PvDBPII population. The amino acid change patterns in Pakistan PvDBPII generally mirrored those in global PvDBPII, although the frequencies of amino acid changes varied by country. Nucleotide diversity in Pakistan PvDBPII was comparable to that found in global PvDBPII. Evidence of natural selection and recombination in Pakistan PvDBPII aligned with observations in global PvDBPII. Analysis of the haplotype network of global PvDBPII revealed a complexed network of 167 haplotypes, but no geographical clustering was observed. The findings are crucial for understanding the genetic characteristics of Pakistan PvDBPII. A comprehensive analysis of nucleotide diversity and evolutionary trends in the global PvDBPII population offers valuable insights for the development of vivax malaria vaccines based on this antigen.

New Chloroplast Microsatellites in Helichrysum italicum (Roth) G. Don: Their Characterization and Application for the Evaluation of Genetic Resources

Helichrysum italicum (Roth) G. Don is a Mediterranean medicinal plant with great potential in the cosmetics, culinary and pharmaceutical fields due to its unique bioactive compounds. Its recent introduction into agroecosystems has enhanced the exploitation of genetic diversity in natural populations, although limited molecular markers have made this challenging. In the present study, primers were designed for all 43 SSRs (72.1% mononucleotide, 21% dinucleotide and 6.9% trinucleotide repeats) identified in the chloroplast genome. Populations from Cape Kamenjak (Croatia) and Corsica (France) were analyzed with ten carefully selected cpSSR markers. From the initial set of 16 cpSSRs amplified in all samples, 6 cpSSR markers were removed due to low-length polymorphisms, size homoplasy and nucleotide polymorphisms that could not be detected with allele length. Of the 38 haplotypes detected, 32 were unique to their geographic origin. The highest number of private haplotypes was observed in the Cape Kamenjak population (seven out of nine detected). Based on clustering analyses, the Kamenjak population was the most similar to the Capo Pertusato (south Corsica) population, although only one sub-haplotype was shared. Other Corsican populations were more similar to each other. A cross-species transferability test with Helichrysum litoreum Guss. and Helichrysum arenarium (L.) Moench was successfully conducted and private alleles were identified.