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Furthermore, we demonstrate through a case study that already trained networks can be easily extended by the best fusion strategy, outperforming other approaches by large margin.Two winter rapeseed cultivars, "NS" (cold tolerant) and "NF" (cold sensitive), were used to reveal the morphological, physiological, and proteomic characteristics in leaves of plants after treatment at -4°C for 12 h(T1) and 24 h(T2), and at room temperature(T0), to understand the molecular mechanisms of cold tolerance. Antioxidant activity and osmotic adjustment ability were higher, and plasma membrane injury was less obvious, in NS than in NF under cold stress. We detected different abundant proteins (DAPs) related to cold tolerance in winter rapeseed through data-independent acquisition (DIA). Compared with NF, A total of 1,235 and 1,543 DAPs were identified in the NSs under T1 and T2, respectively. Compared with NF, 911 proteins were more abundant in NS only after cold treatment. Some of these proteins were related to ROS scavenging through four metabolic pathways lysine degradation; phenylalanine, tyrosine, and tryptophan; flavonoid biosynthesis; and ubiquinone and other terpenoid-quinone biosynthesis. Analysis of these proteins in the four candidate pathways revealed that they were rapidly accumulated to quickly enhance ROS scavenging and improve the cold tolerance of NS. These proteins were noticeably more abundant during the early stage of cold stress, which was critical for avoiding ROS damage.Plant mitochondrial genomes have distinctive features compared to those of animals; namely, they are large and divergent, with sizes ranging from hundreds of thousands of to a few million bases. Recombination among repetitive regions is thought to produce similar structures that differ slightly, known as "multipartite structures," which contribute to different phenotypes. Although many reference plant mitochondrial genomes represent almost all the genes in mitochondria, the full spectrum of their structures remains largely unknown. Sunitinib cell line The emergence of long-read sequencing technology is expected to yield this landscape; however, many studies aimed to assemble only one representative circular genome, because properly understanding multipartite structures using existing assemblers is not feasible. To elucidate multipartite structures, we leveraged the information in existing reference genomes and classified long reads according to their corresponding structures. We developed a method that exploits two classic algorithms, partial order alignment (POA) and the hidden Markov model (HMM) to construct a sensitive read classifier. This method enables us to represent a set of reads as a POA graph and analyze it using the HMM. We can then calculate the likelihood of a read occurring in a given cluster, resulting in an iterative clustering algorithm. For synthetic data, our proposed method reliably detected one variation site out of 9,000-bp synthetic long reads with a 15% sequencing-error rate and produced accurate clustering. It was also capable of clustering long reads from six very similar sequences containing only slight differences. For real data, we assembled putative multipartite structures of mitochondrial genomes of Arabidopsis thaliana from nine accessions sequenced using PacBio Sequel. The results indicated that there are recurrent and strain-specific structures in A. thaliana mitochondrial genomes.

Understanding contraceptive use dynamics is critical to addressing unmet need for contraception. Despite evidence that male partners may influence contraceptive decision-making, few studies have prospectively examined the supportive ways that men influence women's contraceptive use and continuation.

This study sought to understand the predictive effect of partner influence, defined as partner's fertility intentions and support for contraception, and discussions about avoiding pregnancy prior to contraceptive use, on contraceptive use dynamics (continuation, discontinuation, switching, adoption) over a one-year period.

This study uses nationally representative longitudinal data of Ugandan women aged 15-49 collected in 2018-2019 (n = 4,288 women baseline; n = 2,755 women one-year follow-up). Two analytic sub-samples of women in union and in need of contraception at baseline were used (n = 618 contraceptive users at baseline for discontinuation/switching analysis; n = 687 contraceptive non-users at baselineptive use was associated with nearly three-fold increased odds of contraceptive adoption.

These results highlight the potentially supportive role of male partners in contraceptive adoption. Future research is encouraged to elucidate the complex pathways between couple-based decision-making and contraceptive dynamics through further prospective studies.

These results highlight the potentially supportive role of male partners in contraceptive adoption. Future research is encouraged to elucidate the complex pathways between couple-based decision-making and contraceptive dynamics through further prospective studies.Several factors such as genotype, environment, and post-harvest processing can affect the responses of important traits in the coffee production chain. Determining the influence of these factors is of great relevance, as they can be indicators of the characteristics of the coffee produced. The most efficient models choice to be applied should take into account the variety of information and the particularities of each biological material. This study was developed to evaluate statistical and machine learning models that would better discriminate environments through multi-traits of coffee genotypes and identify the main agronomic and beverage quality traits responsible for the variation of the environments. For that, 31 morpho-agronomic and post-harvest traits were evaluated, from field experiments installed in three municipalities in the Matas de Minas region, in the State of Minas Gerais, Brazil. Two types of post-harvest processing were evaluated natural and pulped. The apparent error rate was estimated for each method. The Multilayer Perceptron and Radial Basis Function networks were able to discriminate the coffee samples in multi-environment more efficiently than the other methods, identifying differences in multi-traits responses according to the production sites and type of post-harvest processing. The local factors did not present specific traits that favored the severity of diseases and differentiated vegetative vigor. Sensory traits acidity and fragrance/aroma score also made little contribution to the discrimination process, indicating that acidity and fragrance/aroma are characteristic of coffee produced and all coffee samples evaluated are of the special type in the Mata of Minas region. The main traits responsible for the differentiation of production sites are plant height, fruit size, and bean production. The sensory trait "Body" is the main one to discriminate the form of post-harvest processing.

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