Terpenoids are involved in the expression of systemic-induced resistance in Austrian pine.

Terpenoids are defense metabolites that are induced upon infection or wounding. However, their role in systemic-induced resistance (SIR) is not known. Here, we explored the role of terpenoids in this phenomenon at a very early stage in the interaction between Austrian pine and the tip blight and canker pathogen Diplodia pinea. We induced Austrian pine saplings by either wounding or inoculating the lower stems with D. pinea. The seedlings were then challenged after 12 h, 72 h, or 10 days with D. pinea on the stem 15 cm above the induction. Lesion lengths and terpenoids were quantified at both induction and challenge locations. Key terpenoids were assayed for antifungal activity in in vitro bioassays. SIR increased with time and was correlated with the inducibility of several compounds. α-Pinene and a cluster of ß-pinene, limonene, benzaldehyde, dodecanol, and n-dodecyl acrylate were positively correlated with SIR and were fungistatic in vitro, while other compounds were negatively correlated with SIR and appeared to serve as a carbon source for D. pinea. This study shows that, overall, terpenoids are involved in SIR in this system, but their role is nuanced, depending on the type of induction and time of incubation. We hypothesize that some, such as α-pinene, could serve in SIR signaling.

A glimmer of hope - ash genotypes with increased resistance to ash dieback pathogen show cross-resistance to emerald ash borer.

Plants rely on cross-resistance traits to defend against multiple, phylogenetically distinct enemies. These traits are often the result of long co-evolutionary histories. Biological invasions can force naïve plants to cope with novel, coincident pests, and pathogens. For example, European ash (Fraxinus excelsior) is substantially threatened by the emerald ash borer (EAB), Agrilus planipennis, a wood-boring beetle, and the ash dieback (ADB) pathogen, Hymenoscyphus fraxineus. Yet, plant cross-resistance traits against novel enemies are poorly explored and it is unknown whether naïve ash trees can defend against novel enemy complexes via cross-resistance mechanisms. To gain mechanistic insights, we quantified EAB performance on grafted replicates of ash genotypes varying in ADB resistance and characterized ash phloem chemistry with targeted and untargeted metabolomics. Emerald ash borer performed better on ADB-susceptible than on ADB-resistant genotypes. Moreover, changes in EAB performance aligned with differences in phloem chemical profiles between ADB-susceptible and ADB-resistant genotypes. We show that intraspecific variation in phloem chemistry in European ash can confer increased cross-resistance to invasive antagonists from different taxonomic kingdoms. Our study suggests that promotion of ADB-resistant ash genotypes may simultaneously help to control the ADB disease and reduce EAB-caused ash losses, which may be critical for the long-term stability of this keystone tree species.

Does Climate Variability Impact COVID-19 Outbreak? An Enhanced Semantics-Driven Theory-Guided Model.

COVID-19, a life-threatening infection by novel coronavirus, has broken out as a pandemic since December 2019. Eventually, with the aim of helping the World Health Organization and other health regulators to combat COVID-19, significant research effort has been exerted during last several months to analyze how the various factors, especially the climatic aspects, impact on the spread of this infection. However, due to insufficient test and lack of data transparency, these research findings, at times, are found to be inconsistent as well as conflicting. In our work, we aim to employ a semantics-driven probabilistic framework for analyzing the causal influence as well as the impact of climate variability on the COVID-19 outbreak. The idea here is to tackle the data inadequacy and uncertainty issues using probabilistic graphical analysis along with embedded technology of incorporating semantics from climatological domain. Furthermore, the theoretical guidance from epidemiological model additionally helps the framework to better capture the pandemic characteristics. More significantly, we further enhance the impact analysis framework with an auxiliary module of measuring semantic relatedness on regional basis, so as to realistically account for the existence of multiple climate types within a single spatial region. This added notion of regional semantic relatedness further helps us to attain improved probabilistic analysis for modeling the climatological impact on this disease outbreak. Experimentation with COVID-19 datasets over 15 states (or provinces) belonging to varying climate regions in India, demonstrates the effectiveness of our semantically-enhanced theory-guided data-driven approach. It is worth noting that our proposed framework and the relevant semantic analyses are generic enough for intelligent as well as explainable impact analysis in many other application domains, by introducing minimal augmentation.

CONFRONT: Cloud-fog-dew based monitoring framework for COVID-19 management.

In the recent times, the IoT (Internet of Things) enabled devices and applications have seen a rapid growth in various sectors including healthcare. The ability of low-cost connected sensors to cover large areas makes it a potential tool in the fight against pandemics, like COVID-19. The COVID-19 has posed a formidable challenge for the developing countries, like India, which need to cater to large population base with limited health infrastructure. In this paper, we proposed a  Cloud-fog-dew based mOnitoriNg Framework foR cOvid-19 maNagemenT, called CONFRONT. This cloud-fog-dew based healthcare model may help in preliminary diagnosis and also in monitoring patients while they are in quarantine facilities or home based treatments. The fog architecture ensures that the model is suited for real-time scenarios while keeping the bandwidth requirements low. To analyse large scale COVID-19 statistics data for extracting aggregate information of the disease spread, the cloud servers are leveraged due to its scalable computational and storage capabilities. The dew architecture ensures that the application is available at a limited scale even when cloud connectivity is lost, leading to a faster uptime for the application. A low cost wearable device consisting of heterogeneous sensors has also been designed and fabricated to realize the proposed framework.

Telemedicine Supported Chronic Wound Tissue Prediction Using Classification Approaches.

Telemedicine helps to deliver health services electronically to patients with the advancement of communication systems and health informatics. Chronic wound (CW) detection and its healing rate assessment at remote distance is very much difficult due to unavailability of expert doctors. This problem generally affects older ageing people. So there is a need of better assessment facility to the remote people in telemedicine framework. Here we have proposed a CW tissue prediction and diagnosis under telemedicine framework to classify the tissue types using linear discriminant analysis (LDA). The proposed telemedicine based wound tissue prediction (TWTP) model is able to identify wound tissue and correctly predict the wound status with a good degree of accuracy. The overall performance of the proposed wound tissue prediction methodology has been measured based on ground truth images. The proposed methodology will assist the clinicians to take better decision towards diagnosis of CW in terms of quantitative information of three types of tissue composition at low-resource set-up.

A review on telemedicine-based WBAN framework for patient monitoring.

OBJECTIVE: In this article, we describe the important aspects like major characteristics, research issues, and challenges with body area sensor networks in telemedicine systems for patient monitoring in different scenarios. Present and emerging developments in communications integrated with the developments in microelectronics and embedded system technologies will have a dramatic impact on future patient monitoring and health information delivery systems. The important challenges are bandwidth limitations, power consumption, and skin or tissue protection. MATERIALS AND METHODS: This article presents a detailed survey on wireless body area networks (WBANs). RESULTS AND CONCLUSIONS: We have designed the framework for integrating body area networks on telemedicine systems. Recent trends, overall WBAN-telemedicine framework, and future research scope have also been addressed in this article.