Search Results (54)

Background and Objectives: Congenital thrombophilias are biologically plausible contributors to chronic thromboembolic pulmonary hypertension (CTEPH), yet their frequency and clinical impact remain uncertain. We undertook a systematic review to (i) estimate the pooled prevalence of specific hereditary defects among adults with CTEPH, (ii) characterise associated demographic and haemodynamic phenotypes, and (iii) summarise peri-operative and survival outcomes after pulmonary endarterectomy (PEA) or balloon pulmonary angioplasty (BPA) in genetically defined subgroups. Methods: A protocol compliant with PRISMA-2020 was registered prospectively on the Open Science Framework (OSF). PubMed/MEDLINE, Scopus, and Web of Science were searched from inception to 1 June 2025 using validated, PRESS-reviewed strings combining CTEPH and thrombophilia terms. Observational cohorts, case–control studies and trials reporting laboratory-confirmed congenital thrombophilias in adults with right-heart-catheter-defined CTEPH were eligible. Results: Eight studies encompassing 677 unique CTEPH patients met the inclusion criteria. Among the 400 individuals screened for deficiencies of the natural anticoagulant pathways, 56 possessed a defect: protein S deficiency 5.3% (21/400; 95% CI 3.3–8.0), protein C deficiency 4.3% (17/400; 2.5–6.8), and antithrombin deficiency 1.5% (6/400; 0.6–3.3). In 520 genotyped patients, factor V Leiden and prothrombin G20210A were infrequent (1.3% and 1.0%, respectively) and confined to European/North American cohorts. Baseline haemodynamics were uniformly severe (mean mPAP 46.7 mm Hg; pulmonary vascular resistance ≈ 9 WU). Definitive reperfusion therapy was common (PEA 63%; BPA 18%), reducing mPAP to 20.5 mm Hg and yielding a weighted one-year survival of 96.2%. No study demonstrated a thrombophilia-specific effect on surgical candidacy or early survival. Conclusions: Approximately one in seven patients with CTEPH harbours a congenital thrombophilia, most often protein S or protein C deficiency, whereas classic venous-thrombo-embolism mutations are rare and ethnically restricted. Current evidence indicates that genetic status does not materially influence haemodynamic severity, uptake of PEA/BPA, or short-term survival, supporting guideline recommendations for universal referral to specialist reperfusion centres. Future multicentre registries integrating systematic genotyping and long-term outcome capture are needed to clarify genotype-specific prognostic and therapeutic implications. Full article

Cold stress severely limits legume productivity, threatening global food security, particularly in climate-vulnerable regions. This review synthesizes advances in understanding and enhancing cold tolerance in key legumes (chickpea, soybean, lentil, and cowpea), addressing three core questions: (1) molecular/physiological foundations of cold tolerance; (2) how emerging technologies accelerate stress dissection and breeding; and (3) integration strategies and deployment challenges. Legume cold tolerance involves conserved pathways (e.g., ICE-CBF-COR, Inducer of CBF Expression, C-repeat Binding Factor, Cold-Responsive genes) and species-specific mechanisms like soybean’s GmTCF1a-mediated pathway. Multi-omics have identified critical genes (e.g., CaDREB1E in chickpea, NFR5 in pea) underlying adaptive traits (membrane stabilization, osmolyte accumulation) that reduce yield losses by 30–50% in tolerant genotypes. Technologically, AI and high-throughput phenotyping achieve >95% accuracy in early cold detection (3–7 days pre-symptoms) via hyperspectral/thermal imaging; deep learning (e.g., CNN-LSTM hybrids) improves trait prediction by 23% over linear models. Genomic selection cuts breeding cycles by 30–50% (to 3–5 years) using GEBVs (Genomic estimated breeding values) from hundreds of thousands of SNPs (Single-nucleotide polymorphisms). Advanced sensors (LIG-based, LoRaWAN) enable real-time monitoring (±0.1 °C precision, <30 s response), supporting precision irrigation that saves 15–40% water while maintaining yields. Key barriers include multi-omics data standardization and cost constraints in resource-limited regions. Integrating molecular insights with AI-driven phenomics and multi-omics is revolutionizing cold-tolerance breeding, accelerating climate-resilient variety development, and offering a blueprint for sustainable agricultural adaptation. Full article

Disparities in the functional classification of secretory genes among aphid taxa may be attributed to variations in coding sequences and gene expression profiles. However, the driving factors that regulate sequence evolution remain unclear. This study aimed to investigate the differences in coding sequences and expression patterns of secretory genes between the rose grain aphid (Metopolophium dirhodum) and the pea aphid (Acrythosiphon pisum), with a particular focus on their roles in evolutionary adaptations and functional diversity. The study involved the rearing of aphids, RNA extraction, de novo transcriptome assembly, functional annotation, secretory protein prediction, and comparative analysis of coding sequences and expression patterns across various functional categories using bioinformatics tools. The results revealed that metabolic genes exhibited greater coding sequence divergence, indicating the influence of positive selection. Moreover, significant expression divergence was noted among functional categories, particularly in metabolic and genetic information processing genes, which exhibited higher variability. This study enhances our understanding of the molecular mechanisms that contribute to phenotypic and genetic diversity among aphid species. This study elucidates the relationship between variations in coding sequences and differences in gene expression among functional categories, thereby establishing a foundation for future studies on gene evolution in response to environmental pressures. Full article

Common beans (Phaseolus vulgaris L.) are considered a socially and economically important crop, with the biggest growers in India, Myanmar, and Brazil. Traditionally, common beans are also grown in most parts of Europe, including Latvia, where cultivation areas have remained relatively constant since the middle of the last century. This is explained by the plant’s higher thermal requirements compared to peas and faba beans more widely grown here. Despite this, landraces adapted to local conditions have been developed, whose origin and potential relationship with another European common bean germplasm is very limited. Therefore, the study aimed to characterise the morphology of the common bean germplasm collected and grown in Latvia to identify the most valuable material for further crop development and evaluate the local landraces in the European common bean germplasm context. The 28 genotypes representing Latvian landraces and European reference genotypes were phenotyped using 26 traits of bean seeds, pods, leaves, flowers, and stems, which were evaluated according to an internationally applied methodology. Latvian varieties showed phenotypical variability and characteristics that were different from those found in other European regions, showing the significance of the germplasm under study and highlighting the need for conservation. Local varieties (landraces) are reservoirs of unique genetic traits. Their adaptability to local environmental conditions, resistance to pests and diseases, and their potential to enhance nutritional quality make them invaluable resources for in situ conservation efforts and targeted genetic improvement programmes. Emphasising the utilisation of these landraces can contribute to sustainable agriculture, climate resilience, and food security. Full article

In recent years there has been a resurgent interest in plant products as substitutes for animal-derived food products, in which legumes, including peas, feature highly. Here, we report on a set of Pisum sativum L. (pea) near-isolines, comprising 24 unique mutants at five loci, where the impact of the mutations on the corresponding enzymes of the starch pathway confers a wrinkled-seeded phenotype. Together with a set of round-seeded mutants impacted at a sixth locus, all 27 mutants show variation for starch composition and protein content. The mutations have been mapped onto three-dimensional protein models to examine potential effects on the corresponding enzyme structures and their activities, and to guide targeted mutagenesis. The mutant lines represent a unique suite of alleles for rapid introduction into elite pea varieties to create new materials for the food and feed markets and industrial applications. Full article

In pea (Pisum sativum L.), alleles of the Sym2 gene determine the specificity of the interaction with nodule bacteria (rhizobia). The Sym2^A allele present in landraces from Afghanistan provides higher selectiveness toward rhizobia than the Sym2^E allele present in European cultivars. Rhizobial strains possessing the nodX gene can interact with both Sym2^A and Sym2^E peas, while strains lacking nodX can interact only with Sym2^E peas. Here, we studied the previously obtained introgression line A33.18 bearing Sym2^A in a homozygous state in the genome of the European pea cultivar ‘Rondo’. A33.18 has proved its high selectiveness in pot experiments. Genome sequencing has shown that A33.18 possesses an 18.2 Mb region inherited from Afghanistan pea with 63 genes, including 5 receptor kinase genes, among which was the Sym2 candidate gene LykX. In a field experiment, under inoculation with the nodX⁺ strain TOM, over 95% of nodules of A33.18 contained TOM, as opposed to less than 8% of nodules containing TOM in the parental European cultivar ‘Rondo’. Thus, introgression of Sym2^A enabled peas to interact specifically with the nodX⁺ strain, favoring the formation of nodules by the strain from the inoculum and protecting peas from the indigenous soil microbiota. Full article

Evaluating genetically superior genotypes is essential for developing new hybrid varieties. This study aimed to assess the genetic diversity of 28 edible-podded pea genotypes by analyzing phenological traits, vigor, yield, and biochemical traits across two distinct agro-climatic zones in India. Significant variation was observed for most traits, with high genotypic and phenotypic coefficients of variation, heritability, and genetic advance, especially in vigor, yield, and biochemical traits. Phenological traits, except for the node at which the first flower appeared, exhibited minimal variability, indicating a high degree of uniformity. Yield per plant was negatively correlated with plant height but positively correlated with pod length, the number of seeds per pod, the number of pods per plant, and pod weight, indicating the potential for the simultaneous selection of these traits in breeding programs. Principal component analysis (PCA) identified six components explaining over 75% of the total variation, with yield and biochemical traits contributing the most to the observed diversity. These findings provide crucial insights for breeders aiming to improve quantitative traits, supporting the development of high-yielding and climate-resilient edible-podded pea varieties in India. Full article

Clinical differentiation of progressive supranuclear palsy (PSP) from Parkinson’s disease (PD) is challenging due to overlapping phenotypes and late onset of PSP specific symptoms, highlighting the need for easily assessable biomarkers. We used proximity elongation assay (PEA) to analyze 460 proteins in serum samples from 46 PD, 30 PSP patients, and 24 healthy controls. ANCOVA was used to identify the most promising proteins and machine learning (ML) XGBoost and random forest algorithms to assess their classification performance. Promising proteins were also quantified by ELISA. Moreover, correlations between serum biomarkers and biological and clinical features were investigated. We identified five proteins (TFF3, CPB1, OPG, CNTN1, TIMP4) showing different levels between PSP and PD, which achieved good performance (AUC: 0.892) when combined by ML. On the other hand, when the three most significant biomarkers (TFF3, CPB1 and OPG) were analyzed by ELISA, there was no difference between groups. Serum levels of TFF3 positively correlated with age in all subjects’ groups, while for OPG and CPB1 such a correlation occurred in PSP patients only. Moreover, CPB1 positively correlated with disease severity in PD, while no correlations were observed in the PSP group. Overall, we identified CPB1 correlating with PD severity, which may support clinical staging of PD. In addition, our results showing discrepancy between PEA and ELISA technology suggest that caution should be used when translating proteomic findings into clinical practice. Full article

This study assessed eleven elements in 24 edible-podded peas, including sugar snap pea and snow pea genotypes aiming to identify promising parents for nutraceutical breeding. Elemental concentrations of pods (dry weight basis) were estimated through inductively coupled plasma-optical emission spectroscopy (ICP-OES). The ranges for these elements varied significantly, highlighting the diverse elemental profiles within the edible-podded pea genotypes. All the elements exhibited a high genotypic and phenotypic coefficient of variation along with considerable heritability and hereditary progress. Positive and significant correlations were recorded among all elements, suggesting the potential for simultaneous selection for these traits. Principal component analysis (PCA) revealed that the first two components accounted for 80.56% of the variation. Further, cluster analysis, based on Euclidean distance, grouped the 24 cultivars into two major clusters. Cluster I exhibited higher means for all estimated concentrations compared to Cluster II. Notably, Dwarf Grey Sugar and Arka Sampoorna from the snap pea group and PED-21-5 and Sugar Snappy from the sugar snap pea in Cluster II demonstrated superior elemental concentration in whole pods. The selected edible-podded pea genotypes serve as valuable genetic resources for new cultivar development, particularly in biofortification efforts targeting whole pod nutrient composition. Full article

Little resistance to the pea weevil insect pest (Bruchus pisorum) is available in pea (Pisum sativum) cultivars, highlighting the need to search for sources of resistance in Pisum germplasm and to decipher the genetic basis of resistance. To address this need, we screened the response to pea weevil in a Pisum germplasm collection (324 accession, previously genotyped) under field conditions over four environments. Significant variation for weevil seed infestation (SI) was identified, with resistance being frequent in P. fulvum, followed by P. sativum ssp. elatius, P. abyssinicum, and P. sativum ssp. humile. SI tended to be higher in accessions with lighter seed color. SI was also affected by environmental factors, being favored by high humidity during flowering and hampered by warm winter temperatures and high evapotranspiration during and after flowering. Merging the phenotypic and genotypic data allowed genome-wide association studies (GWAS) yielding 73 markers significantly associated with SI. Through the GWAS models, 23 candidate genes were found associated with weevil resistance, highlighting the interest of five genes located on chromosome 6. These included gene 127136761 encoding squalene epoxidase; gene 127091639 encoding a transcription factor MYB SRM1; gene 127097033 encoding a 60S ribosomal protein L14; gene 127092211, encoding a BolA-like family protein, which, interestingly, was located within QTL BpLD.I, earlier described as conferring resistance to weevil in pea; and gene 127096593 encoding a methyltransferase. These associated genes offer valuable potential for developing pea varieties resistant to Bruchus spp. and efficient utilization of genomic resources through marker-assisted selection (MAS). Full article

In common with other plant species, the garden pea (Pisum sativum) produces the auxin indole-3-acetic acid (IAA) from tryptophan via a single intermediate, indole-3-pyruvic acid (IPyA). IPyA is converted to IAA by PsYUC1, also known as Crispoid (Crd). Here, we extend our understanding of the developmental processes affected by the Crd gene by examining the phenotypic effects of crd gene mutations on leaves, flowers, and roots. We show that in pea, Crd/PsYUC1 is important for the initiation and identity of leaflets and tendrils, stamens, and lateral roots. We also report on aspects of auxin deactivation in pea. Full article

The huge development of climatic change highly affects our crop production and soil fertility. Also, the rise in the uncontrolled, excessive use of chemical fertilizers diminishes the soil prosperity and generates pollutants, threatening all environmental life forms, including us. Replacement of these chemical fertilizers with natural ones is becoming an inevitable environmental strategy. In our study, we evaluated the responses of Pisum sativum L. to the action of single species and consortiums of plant growth-promoting bacteria (Azotobacter chroococcum, Bacillus megaterium, and Bacillus cerkularice) in clay and new reclaimed soil types in terms of phenotype, yield components, and physiological and biochemical responses. Data analysis showed single or consortium microbial inoculation significantly increased the measured traits under clay and calcareous sandy soils compared to the control. Shoot physiological and biochemical activities, and seed biochemical activities were significantly enhanced with the inoculation of pea seeds with three types of bacteria in both soil types. The bud numbers, fresh weight, and seeds’ dry weight increased in seeds treated with A. chroococcum and B. megaterium in the sandy soil. Taken together, these findings suggested that the inoculation of plants with PGP bacteria could be used to diminish the implementation of chemical fertilizer and improve the goodness of agricultural products. These findings expand the understanding of the responsive mechanism of microbial inoculation under different soil types, especially at physiological and biochemical levels. Full article

In agroecosystems, plants frequently confront multiple biotic stressors, including herbivores and pathogens. The nature of these interactions plays a crucial role in mediating the activation of plant defense mechanisms. However, induction of plant chemical defenses has been more well studied than the induction of physical defenses. Here, we assessed the physical and chemical defense responses of pea (Pisum sativum) plants after exposure to three stressors: a vector herbivore (pea aphid, Acrythosiphon pisum), a non-vector herbivore (pea leaf weevil, Sitona lineatus), and a virus (Pea enation mosaic virus, PEMV). We used various histochemical staining techniques show that viruliferous A. pisum (transmitting PEMV) strongly induced callose deposition (aniline blue staining) and antioxidant-mediated defenses (DAB and NBT staining) in peas, primarily through accumulating reactive oxygen species (ROS). High-throughput phenotyping showed that viruliferous aphids reduced plant photosynthetic efficiency, but plants infected with PEMV had increased cell death (trypan blue staining). However, herbivory by aphids and weevils did not strongly induce defenses in peas, even though weevil feeding significantly reduced pea leaf area. These results show that not all herbivores induce strong defensive responses, and plant responses to vector species depends on their virus infection status. More broadly, our results indicate that variable stressors differentially regulate various plant responses through intricate chemical and physical defense pathways. Full article

Maturity is an important trait in dry pea breeding programs, but the conventional process predominately used to measure this trait can be time-consuming, labor-intensive, and prone to errors. Therefore, a more efficient and accurate approach would be desirable to support dry pea breeding programs. This study presents a novel approach for measuring dry pea maturity using machine learning algorithms and unmanned aerial systems (UASs)-collected data. We evaluated the abilities of five machine learning algorithms (random forest, artificial neural network, support vector machine, K-nearest neighbor, and naïve Bayes) to accurately predict dry pea maturity on field plots. The machine learning algorithms considered a range of variables, including crop height metrics, narrow spectral bands, and 18 distinct color and spectral vegetation indices. Backward feature elimination was used to select the most important features by iteratively removing insignificant ones until the model’s predictive performance was optimized. The study’s findings reveal that the most effective approach for assessing dry pea maturity involved a combination of narrow spectral bands, red-edge, near-infrared (NIR), and RGB-based vegetation indices, along with image textural metrics and crop height metrics. The implementation of a random forest model further enhanced the accuracy of the results, exhibiting the highest level of accuracy with a 0.99 value for all three metrics precision, recall, and f1 scores. The sensitivity analysis revealed that spectral features outperformed structural features when predicting pea maturity. While multispectral cameras achieved the highest accuracy, the use of RGB cameras may still result in relatively high accuracy, making them a practical option for use in scenarios where cost is a limiting factor. In summary, this study demonstrated the effectiveness of coupling machine learning algorithms, UASs-borne LIDAR, and multispectral data to accurately assess maturity in peas. Full article

Selection pressures driven by natural causes or human interference are key factors causing genome variants and signatures of selection in specific regions of the genome. Gamecocks were bred for cockfighting, presenting pea-combs, larger body sizes, stronger limbs, and higher levels of aggression than other chickens. In this study, we aimed to explore the genomic differences between Chinese gamecocks and commercial, indigenous, foreign, and cultivated breeds by detecting the regions or sites under natural or artificial selection using genome-wide association studies (GWAS), genome-wide selective sweeps based on the genetic differentiation index (F_ST), and transcriptome analyses. Ten genes were identified using GWAS and F_ST: gga-mir-6608-1, SOX5, DGKB, ISPD, IGF2BP1, AGMO, MEOX2, GIP, DLG5, and KCNMA1. The ten candidate genes were mainly associated with muscle and skeletal development, glucose metabolism, and the pea-comb phenotype. Enrichment analysis results showed that the differentially expressed genes between the Luxi (LX) gamecock and Rhode Island Red (RIR) chicken were mainly related to muscle development and neuroactive-related pathways. This study will help to understand the genetic basis and evolution of Chinese gamecocks and support the further use of gamecocks as an excellent breeding material from a genetic perspective. Full article