Structure and regulation of the Asr gene family in banana

Abscisic acid, stress, ripening proteins (ASR) are a family of plant-specific small hydrophilic proteins. Studies in various plant species have highlighted their role in increased resistance to abiotic stress, including drought, but their specific function remains unknown. As a first step toward their potential use in crop improvement, we investigated the structure and regulation of the Asr gene family in Musa species (bananas and plantains). We determined that the MusaAsr gene family contained at least four members, all of which exhibited the typical two exons, one intron structure of Asr genes and the “ABA/WDS” (abscisic acid/water deficit stress) domain characteristic of Asr genes. Phylogenetic analyses determined that the MusaAsr genes were closely related to each other, probably as the product of recent duplication events. For two of the four members, two versions corresponding to the two sub-genomes of Musa, acuminata and balbisiana were identified. Gene expression and protein analyses were performed and Asr expression could be detected in meristem cultures, root, pseudostem, leaf and cormus. In meristem cultures, mAsr1 and mAsr3 were induced by osmotic stress and wounding, while mAsr3 and mAsr4 were induced by exposure to ABA. mASR3 exhibited the most variation both in terms of amino acid sequence and expression pattern, making it the most promising candidate for further functional study and use in crop improvement

Biological variability dominates and influences analytical variance in HPLC-ECD studies of the human plasma metabolome

<p>Abstract</p> <p>Background</p> <p>Biomarker-based assessments of biological samples are widespread in clinical, pre-clinical, and epidemiological investigations. We previously developed serum metabolomic profiles assessed by HPLC-separations coupled with coulometric array detection that can accurately identify <it>ad libitum </it>fed and caloric-restricted rats. These profiles are being adapted for human epidemiology studies, given the importance of energy balance in human disease.</p> <p>Methods</p> <p>Human plasma samples were biochemically analyzed using HPLC separations coupled with coulometric electrode array detection.</p> <p>Results</p> <p>We identified these markers/metabolites in human plasma, and then used them to determine which human samples represent blinded duplicates with 100% accuracy (N = 30 of 30). At least 47 of 61 metabolites tested were sufficiently stable for use even after 48 hours of exposure to shipping conditions. Stability of some metabolites differed between individuals (N = 10 at 0, 24, and 48 hours), suggesting the influence of some biological factors on parameters normally considered as analytical.</p> <p>Conclusion</p> <p>Overall analytical precision (mean median CV, ~9%) and total between-person variation (median CV, ~50–70%) appear well suited to enable use of metabolomics markers in human clinical trials and epidemiological studies, including studies of the effect of caloric intake and balance on long-term cancer risk.</p

Diagnostic tools in Rhinology EAACI position paper

This EAACI Task Force document aims at providing the readers with a comprehensive and complete overview of the currently available tools for diagnosis of nasal and sino-nasal disease. We have tried to logically order the different important issues related to history taking, clinical examination and additional investigative tools for evaluation of the severity of sinonasal disease into a consensus document. A panel of European experts in the field of Rhinology has contributed to this consensus document on Diagnostic Tools in Rhinology

International Consensus Statement on Rhinology and Allergy: Rhinosinusitis

Background: The 5 years since the publication of the first International Consensus Statement on Allergy and Rhinology: Rhinosinusitis (ICAR‐RS) has witnessed foundational progress in our understanding and treatment of rhinologic disease. These advances are reflected within the more than 40 new topics covered within the ICAR‐RS‐2021 as well as updates to the original 140 topics. This executive summary consolidates the evidence‐based findings of the document. Methods: ICAR‐RS presents over 180 topics in the forms of evidence‐based reviews with recommendations (EBRRs), evidence‐based reviews, and literature reviews. The highest grade structured recommendations of the EBRR sections are summarized in this executive summary. Results: ICAR‐RS‐2021 covers 22 topics regarding the medical management of RS, which are grade A/B and are presented in the executive summary. Additionally, 4 topics regarding the surgical management of RS are grade A/B and are presented in the executive summary. Finally, a comprehensive evidence‐based management algorithm is provided. Conclusion: This ICAR‐RS‐2021 executive summary provides a compilation of the evidence‐based recommendations for medical and surgical treatment of the most common forms of RS

Text-dependent speaker recognition using wavelets and neural networks

An intelligent system for text-dependent speaker recognition is proposed in this paper. The system consists of a wavelet-based module as the feature extractor of speech signals and a neural-network-based module as the signal classifier. The Daubechies wavelet is employed to filter and compress the speech signals. The fuzzy ARTMAP (FAM) neural network is used to classify the processed signals. A series of experiments on text-dependent gender and speaker recognition are conducted to assess the effectiveness of the proposed system using a collection of vowel signals from 100 speakers. A variety of operating strategies for improving the FAM performance are examined and compared. The experimental results are analyzed and discussed.<br /