Many model organisms have obtained a prominent status due to an advantageous combination of their life-history characteristics, genetic properties and also practical considerations. In non-crop plants, Arabidopsis thaliana is the most renowned model and has been used as study system to elucidate numerous biological processes at the molecular level. Once a complete genome sequence was available, research has markedly accelerated and further established A. thaliana as the reference to stimulate studies in other species with different biology. Within the Brassicaceae family, the arctic-alpine perennial Arabis alpina has become a model complementary to A. thaliana to study life-history evolution and ecological genomics in harsh environments. In this review, we provide an overview of the properties that facilitated the rapid emergence of A. alpina as a plant model. We summarize the evolutionary history of A. alpina, including the diversification of its mating system, and discuss recent progress in the molecular dissection of developmental traits that are related to its perennial life history and environmental adaptation. We indicate open questions from which future research might be developed in other Brassicaceae species or more distantly related plant families.

Article type: letter to the editor

A document by Mehul Mahrishi. Click on the document to view its contents.

Although pneumothorax is a well-known complication of COVID-19 pneumonia especially in patients requiring mechanical ventilation, bronchopleural fistula causing persistent pneumothorax in sole COVID-19 pneumonia is extremely rare. In this case, we illustrate that bronchopleural fistula can be found in COVID-19 pneumonia, even with no risk factors nor mechanical ventilation administration.

Sentiment analysis of social media posts and texts can provide information and knowledge that is applicable in social settings, business intelligence, evaluation of citizens’ opinions in governance and mood triggered devices in Internet of Things. Feature extraction and selection is a key determinant of accuracy and computational cost of machine learning models for such analysis. Most feature extraction and selection techniques utilize bag of words such as N-grams and frequency-based algorithms especially Term Frequency-Inverse document frequency (TF-IDF). However, these approaches suffer shortcomings such as; they do not consider relationships between words, they ignore words’ characteristics and they suffer high feature dimensionality. In this paper we propose and evaluate an approach that utilizes a fixed hybrid N-gram window for feature extraction and Minimum Redundancy Maximum Relevance feature selection for sentence level sentiment analysis. The approach improves the existing feature extraction techniques specifically the N-gram by generating a tri-gram vector from words, Part of speech tags and word semantic orientation. The N-gram vector is extracted by employing a static 3-gram window identified by a lexicon where a sentiment word appears in a sentence. A blend of the words, POS tags and the sentiment orientations of the 3N-gram are used to build the feature vector. The optimal features from the vector are then selected using Minimum Redundancy Maximum Relevance (MR2) algorithm. Experiments were carried out with a publicly available yelp tweets dataset to evaluate the performance of four supervised machine learning classifiers (Naïve Bayes, K-Nearest Neighbor, Decision Tree and Support Vector Machines) when augmented with the proposed model. The results showed that the proposed model had the highest accuracy (86.85%), recall (86.85%) and precision (86.96%).

A document by Sara Zaidi. Click on the document to view its contents.

Ellis--van Creveld syndrome is a rare autosomal recessive disorder. We describe the case of a 7-year-old girl with Ellis--van Creveld Syndrome with the diagnosis of common atrium and partial atrioventricular septal defect. She underwent a successful surgical repair, and intraoperatively, a double orifice mitral valve was diagnosed as well.

The leopard coral grouper, Plectropomus leopardus, belonging to genus Plectropomus, family Epinephelinae, is a carnivorous coral reef fish widely distributing in the tropical and subtropical water of Indo-Pacific Oceans. Due to its appealing body appearance and delicious taste, P. leopardus has become a popular commercial fish for aquaculture in many countries. However, the lack of genomic and molecular resources for P. leopardus hinders its biological studies and genomic breeding programs. Here we report the de novo sequencing and assembly of P. leopardus genome using 10× Genomics and high-throughput chromosome conformation capture (Hi-C) technologies. Using 127.36 Gb 10× Genomics we generated a 902.90 Mb genome assembly with a contig and scaffold N50 of 31.8 Kb and 33.47 Mb, respectively. The scaffolds were clustered and oriented into 24 pseudo-chromosomes with 13.39 Gb valid Hi-C data. BUSCO analysis showed that 95.3% of the conserved single-copy genes were retrieved, indicating a good entirety of the assembly. We predicted 23,234 protein-coding genes, among which 96.5% were functional annotated. The P. leopardus genome provides a valuable genomic resource for genetics, evolutionary and biological studies of this species. Particularly, it is expected to benefit the development of genomic breeding programs in the farming industry.

Takotsubo Cardiomyopathy (TC), an acute cardiac event accounting for about 1-2% of all acute coronary syndromes is often associated with acute emotional stress usually in the setting of the other cardiovascular risk factors.This case report reviews a trigger of TC (severe hyponatremia) and the link between them.

Aim: To develop clinical algorithms for the assessment and management of slow progress of labour. Population: Low-risk singleton, term, pregnant women in labour. Setting: Institutional births in low- and middle-income countries. Search Strategy: We systematically reviewed the literature on normal labour progression, and guidance on clinical management of abnormally slow progression from 1 December 2015 to 1 December 2020. Case scenarios: We developed two clinical algorithms: one for abnormally slow labour progression and arrest during first and one for second stage. Conclusions: Identifying abnormal progress of labour is often challenging. These algorithms may help to reduce misdiagnosis.

Several biomarkers have been evaluated as predictors of severity or in directing the treatment of COVID-19, however there are no conclusive results with prediction of the pathobiology of the infection. In this study, we evaluated serum levels of cytokines, chemokines, and cell growth factors in association with the pathobiology of mild to moderate SARS-CoV-2 infection. Those markers may act as immuno-inflammatory biomarkers in adults with mild to moderate flu syndrome who sought care at health units. Serum levels of SARS-CoV-2 infected patients (n=113) and flu symptoms individuals negative for SARS-CoV-2 (n=58), tested by the RT-qPCR test - nasal swab were compared to healthy controls (n=53). Participants who were symptomatic but negative for SARS-CoV-2 were tested for Influenza A/B and Respiratory Syncytial Virus (RSV). Results showed that the pro-inflammatory cytokines IL-1β, MCP-3, TNF-α and G-CSF were increased in symptomatic patients and the cytokines IL-6 and IL-10 were associated with patients positive for SARS-CoV-2 when compared to healthy controls. Symptoms associated with COVID-19 were fever, anosmia, ageusia and myalgia. For patients without SARS-CoV-2 infection their major symptom was sore throat. Five percent (4/83) of SARS-CoV-2 negative patients were positive for RSV. The pathobiology of mild to moderate SARS-CoV-2 infection was associated with increasing pro-inflammatory cytokines and also a pleiotropic IL-6 and anti-inflammatory IL-10 cytokines compared to healthy controls.

Evidence-Based Medicine proposes a prescriptive model of physician decision-making in which “best evidence” is used to guide best practice. And yet, proponents of EBM acknowledge that EBM fails to offer a systematic theory of physician decision-making. In this paper, we explore how physicians from the neurology and emergency medicine communities have responded to an evolving body of evidence surrounding the acute treatment of patients with ischemic stroke. Through analysis of this case study, we argue that EBM’s vision of evidence-based medical decision-making fails to appreciate a process that we have termed epistemic evaluation. Namely, physicians are required to interpret and apply any knowledge — even what EBM would term “best evidence” — in light of their own knowledge, background and experience. This is consequential for EBM as understanding what physicians do and why they do it would appear to be essential to achieving optimal practice in accordance with best evidence.

A document by Marcin Moniuszko. Click on the document to view its contents.

This paper presents a novel real-time facial feature extraction algorithm, producing a small feature set, suitable for implementing emotion recognition with online game and metaverse avatars. The algorithm aims to reduce data transmission and storage requirements, hurdles in the adoption of emotion recognition in these mediums. The early results presented show a facial emotion recognition accuracy of up to 92% on one benchmark dataset, with an overall accuracy of 77.2% across a wide range of datasets, demonstrating the early promise of the research.

An exhaustive assessment of biodiversity is a major challenge of ecological research, and molecular approaches such as the metabarcoding of environmental DNA are boosting our ability to perform biodiversity inventories. Are we actually able to assess the whole community, to unravel the intricate interactions between organisms and the impacts of global changes on the different trophic levels? The majority of metabarcoding papers published in the last years used just one or two markers and analyzed a limited number of taxonomic groups. Nevertheless, approaches are emerging that might allow “all-taxa biological inventories”. Exhaustive biodiversity assessments can be attempted by combining a large number of specific primers, by exploiting the power of universal primers, or by combining specific and universal primers to obtain good information on key taxa while limiting the overlooked biodiversity. Multiplexes of primers and shotgun sequencing may provide a better coverage of biodiversity compared to standard metabarcoding, but still require major methodological advances. We identify the strengths and limitations of different approaches, and suggest new development lines that might improve broad scale biodiversity analyses in the near future.

Although sporadic Creutzfeldt Jakob disease is always fatal and no accepted treatment is currently available. Moreover, prevalence of COVID-19 in the same patient makes management protocol difficult and prognosis worse.

Harlequin Ichthyosis is a rare autosomal recessive disorder occurring in 1: 3,000,000 birth characterized by thick keratin skin with scaly appearance. Preterm deliveries, early marriage and consanguinity of marriage are some risk factors. Antenatal checkup of DNA for ABCA12 mutation helps in diagnosis but USG in places where not available.

Non-A non-B aortic dissections are an infrequent occurrence and represent a small proportion of aortic dissections. Treating this life-threatening medical emergency often requires surgeons to undertake some one of the most challenging surgical or endovascular cases in medicine. This literature review aims to define and classify non-A non-B dissections, describe their epidemiology as well as their pathology. This review also aims to discuss the range of surgical techniques employed in their treatment and management and to investigate the patient outcomes associated with each technique.