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Calcium-dependent protein kinases (CDPKs) are encoded by a large gene family and play important roles against biotic and abiotic stresses and in plant growth and development. To date, little is known about the CDPK genes in strawberry ( Fragaria x ananassa ). In this study, analysis of Fragaria x ananassa CDPK gene family was performed, including gene structures, phylogeny, interactome and expression profiles. Nine new CDPK genes in Fragaria x ananassa were identified based on RNA-seq data. These identified strawberry FaCDPK genes were classified into four main groups, based on the phylogenetic analysis and structural features. FaCDPK genes were differentially expressed during fruit development and ripening, as well as in response to abiotic stress (salt and drought), and hormone (abscisic acid) treatment. In addition, the interaction network analysis pointed out proteins involved in the ABA-dependent response to plant stress via Ca 2+ signaling, especially RBOHs. To our knowledge, this is the first report on CDPK families in Fragaria x ananassa , and it will provide valuable information for development of biofortified fruits and stress tolerant plants.

The largest monkeypox virus (MPXV) outbreak described so far in non-endemic countries was identified in May 2022 (refs. 1 – 6 ). In this study, shotgun metagenomics allowed the rapid reconstruction and phylogenomic characterization of the first MPXV outbreak genome sequences, showing that this MPXV belongs to clade 3 and that the outbreak most likely has a single origin. Although 2022 MPXV (lineage B.1) clustered with 2018–2019 cases linked to an endemic country, it segregates in a divergent phylogenetic branch, likely reflecting continuous accelerated evolution. An in-depth mutational analysis suggests the action of host APOBEC3 in viral evolution as well as signs of potential MPXV human adaptation in ongoing microevolution. Our findings also indicate that genome sequencing may provide resolution to track the spread and transmission of this presumably slow-evolving double-stranded DNA virus. Analysis of the first sequences from the 2022 multi-country outbreak of monkeypox virus shows relatedness and substantial divergence from a 2018–2019 outbreak, suggesting rapid virus evolution with possible implications for human-to-human transmission.

A small number of individuals infected within a community can lead to the rapid spread of the disease throughout that community, leading to an epidemic outbreak. This is even more true for highly contagious diseases such as COVID-19, known to be caused by the new coronavirus SARS-CoV-2. Mathematical models of epidemics allow estimating several impacts on the population and, therefore, are of great use for the definition of public health policies. Some of these measures include the isolation of the infected (also known as quarantine), and the vaccination of the susceptible. In a possible scenario in which a vaccine is available, but with limited access, it is necessary to quantify the levels of vaccination to be applied, taking into account the continued application of preventive measures. This work concerns the simulation of the spread of the COVID-19 disease in a community by applying the Monte Carlo method to a Susceptible-Exposed-Infective-Recovered (SEIR) stochastic epidemic model. To handle the computational effort involved, a simple parallelization approach was adopted and deployed in a small HPC cluster. The developed computational method allows to realistically simulate the spread of COVID-19 in a medium-sized community and to study the effect of preventive measures such as quarantine and vaccination. The results show that an effective combination of vaccination with quarantine can prevent the appearance of major epidemic outbreaks, even if the critical vaccination coverage is not reached.

PurposeThis paper aims to propose a methodology to assist manufacturing companies in the implementation of condition-based maintenance (CBM) to their equipment. The developed methodology intends to consider the use of sensors already installed on the equipment and, when required, to support the selection of sensors available on the market. Since CBM using sensors is not always feasible, the information gathered for the feasibility study of CBM implementation is also used to assign other maintenance strategies.Design/methodology/approachBased on the literature review, requirements and specifications were established for endowing the methodology with relevant and distinctive characteristics. The structure of the methodology and the associated steps were defined based on this information. Then, the methodology was validated and refined using a case study.FindingsIn the case study company, following the methodology and the respective steps, appropriate maintenance strategies were assigned to a selected manufacturing machine, considering information related to the failure modes with the most significant impact, and CBM was applied to a selected component for which the benefit outweighs the costs involved, using data acquired by sensors subsequently installed on the analyzed machine.Practical implicationsDue to its comprehensiveness, this methodology can contribute to make CBM implementation accessible to a high number of companies and encourage the application of a wide variety of monitoring techniques.Originality/valueThis new methodology can be easily integrated into a computerized maintenance management system and has the advantage of facilitating the collection, organization and standardization of technical knowledge required to support CBM implementation and define the most appropriate maintenance strategy systematically and automatically. It guides the prioritization of equipment and failure modes, and the decision-making regarding the selection of sensors and the allocation of maintenance strategies with the aim of reducing costs.

Pollution of the environment with plastic is an important concern of the modern world. It is estimated that annually over 350 million tonnes of this material are produced, wherein, despite the recycling methods, a significant part is deposited in the environment. The plastic has been detected in the industrial areas, as well as farmlands and gardens in many world regions. Larger plastic pieces degraded in time into smaller pieces including microplastic (MP) and nanoplastic particles (NP). Nanoplastic is suggested to pose the most serious danger as due to the small size, it is effectively taken up from the environment by the biota and transported within the organisms. An increasing number of reports show that NP exert toxic effects also on plants. One of the most common plant response to abiotic stress factors is the accumulation of reactive oxygen species (ROS). On the one hand, these molecules are engaged in cellular signalling and regulation of genes expression. On the other hand, ROS in excess lead to oxidation and damage of various cellular compounds. This article reviews the impact of NP on plants, with special emphasis on the oxidative response.

Amphibians constitute the class of vertebrates with the highest proportion of threatened species, with infectious diseases being considered among the greatest causes for their worldwide decline. Aquatic oomycetes, known as “water molds”, are fungus-like microorganisms that are ubiquitous in freshwater ecosystems and are capable of causing disease in a broad range of amphibian hosts. Various species of Achlya sp., Leptolegnia sp., Aphanomyces sp., and mainly, Saprolegnia sp., are responsible for mass die-offs in the early developmental stages of a wide range of amphibian populations through a disease known as saprolegniosis, aka, molding or a “Saprolegnia-like infection”. In this context, the main objective of the present review was to bring together updated information about saprolegniosis in amphibians to integrate existing knowledge, identify current knowledge gaps, and suggest future directions within the saprolegniosis–amphibian research field. Based on the available literature and data, an integrated and critical interpretation of the results is discussed. Furthermore, the occurrence of saprolegniosis in natural and laboratory contexts and the factors that influence both pathogen incidence and host susceptibility are also addressed. The focus of this work was the species Saprolegnia sp., due to its ecological importance on amphibian population dynamics and due to the fact that this is the most reported genera to be associated with saprolegniosis in amphibians. In addition, integrated emerging therapies, and their potential application to treat saprolegniosis in amphibians, were evaluated, and future actions are suggested.

The young reader is not associated with the modern world in which s/he lives, but with an image of life 'from another time,' that is patriarchal and has no machinery, which reinforces the myth of happy past times, of a golden age.\" [...]most of the texts chosen for compulsory reading in schools present to the contemporary reader not the society in which s/he lives, but the idyllic society \"of once upon a time,\" of distant times, much closer to the purity of a world not yet influenced by industrial revolutions, in which the family ruled by the figure of the father becomes the model of life in society. [...]the boy describes his mother's dress, after which the book is titled. The author chose the dress precisely to displace consolidated concepts about reality. [...]wearing the dress does not imply a change in gender or sexual role, but rather, provokes a reflection about valuing special moments. In a light-hearted way, we enter into the private universe of Alexandra, who some days \"wants to wear dresses and let her hair down\" and other days \"wants to wear shorts and a ponytail to play freely.\"

The design of orthopedic implants is a complex challenge, requiring the careful balance of mechanical performance and biological integration to ensure long-term success. This study focuses on the development of a porous femoral stem implant aimed at reducing stiffness and mitigating stress shielding effects. To accelerate the design process, neural networks were trained to predict the optimal density distribution of the implant, enabling rapid optimization. Two initial design spaces were evaluated, revealing the necessity of incorporating the femur’s anatomical features into the design process. The trained models achieved a median error near 0 for both conventional and extended design spaces, producing optimized designs in a fraction of the computational time typically required. Finite element analysis (FEA) was employed to assess the mechanical performance of the neural network-generated implants. The results demonstrated that the neural network predictions effectively reduced stress shielding compared to a solid model in 50% of the test cases. While the graded porosity implant design did not show significant differences in stress shielding prevention compared to a uniform porosity design, it was found to be significantly stronger, highlighting its potential for enhanced durability. This work underscores the efficacy of neural network-accelerated design in improving implant development efficiency and performance.

Marine litter is a global problem which has been negatively affecting the environment. Plastic materials are the most commonly found marine debris, with potential biological (not only for aquatic organisms but also for humans) as well as socio-economic impacts. Considering that it is an anthropogenic problem, society could play an important role to minimize it. Although a considerable amount of research has addressed the biological effects of plastics (micro(nano)plastics) on biota, few studies have addressed how scientific information is being transmitted to the public and the potential role of citizen environmental education. The current paper discusses known effects, researched topics and how scientific knowledge is currently being transmitted to the public.