Exploring antioxidative, cytotoxic and neuropharmacological insights into Bixa orellana leaves: Experimental and in silico approaches.

Background Study: The aim of this research was to examine possible antioxidant, cytotoxic and neurological activity of methanol and n-hexane extracts of Bixa orellana leaves. Additionally, we aimed to identify potential lead compounds through in-silico analysis. Methods: In-vitro antioxidative properties were investigated through different assays, including: total phenolic content assay (TPC), total flavonoid content assay (TFC), DPPH free radical scavenging assay and reducing power assay. Also, the cytotoxic effect of the samples was assessed using the brine shrimp lethality test. In addition, anxiolytic, locomotor, and CNS depressant activities were assessed utilizing various established methods. Moreover, reported compounds were used in the in silico study to explore the best-fit phytoconstituents against gamma-aminobutyric acid (GABAA) receptor. Results: MBOL displayed substantial antioxidative activities in various established assays compared to NBOL. In brine shrimp lethality bioassay, both MBOL and NBOL revealed cytotoxic activity in a concentration-dependent approach. Again, in Elevated Plus Maze test, 200 and 400 mg/kg of NBOL and MBOL demonstrated significant anxiolytic activities evident from time spent in open arms. In addition, maximum number of head dipping was demonstrated by MBOL at 400 mg/kg (53.90 ± 1.16) in Hole Board test. NBOL and MBOL at both doses significantly diminished the magnitude of movements from the 2nd to 5th observation periods in Open Field test. Furthermore, in Hole Cross test, MBOL remarkably dwindled the locomotor activity at 120 min and 180 min (3.60 ± 0.40 and 2.40 ± 0.51) at 400 mg/kg. Finally, in silico analysis revealed 13 compounds as promising leads with strong binding affinity to GABAA receptor along with good pharmacokinetics and toxicity profiles. Conclusion: Therefore, the present study's findings advocate the traditional usage of this plant and recommend both MBOL and NBOL as as a potential source of therapeutic candidate for the management of neurological disorders.

Bioinformatics and Systems Biology Approaches to Identify the Synergistic Effects of Alcohol Use Disorder on the Progression of Neurological Diseases.

Clinical investigations showed that individuals with Alcohol Use Disorder (AUD) have worse Neurological Disease (ND) development, pointing to possible pathogenic relationships between AUD and NDs. It remains difficult to identify risk factors that are predisposing between AUD and NDs. In order to fix these issues, we created the bioinformatics pipeline and network-based approaches for employing unbiased methods to discover genes abnormally stated in both AUD and NDs and to pinpoint some of the common molecular pathways that might underlie AUD and ND interaction. We found 100 differentially expressed genes (DEGs) in both the AUD and ND patient's tissue samples. The most important Gene Ontology (GO) terms and metabolic pathways, including positive control of cytotoxicity caused by T cells, proinflammatory responses, antigen processing and presentation, and platelet-triggered interactions with vascular and circulating cell pathways were then extracted using the overlapped DEGs. Protein-protein interaction analysis was used to identify hub proteins, including CCL2, IL1B, TH, MYCN, HLA-DRB1, SLC17A7, and HNF4A, in the pathways that have been reported as playing a function in these disorders. We determined several TFs (HNF4A, C4A, HLA-B, SNCA, HLA-DMB, SLC17A7, HLA-DRB1, HLA-C, HLA-A, and HLA-DPB1) and potential miRNAs (hsa-mir-34a-5p, hsa-mir-34c-5p, hsa-mir-449a, hsa-mir-155-5p, and hsa-mir-1-3p) were crucial for regulating the expression of AUD and ND which could serve as prospective targets for treatment. Our methodologies discovered unique putative biomarkers that point to the interaction between AUD and various neurological disorders, as well as pathways that could one day be the focus of therapeutic intervention.

Neuropharmacological assessment and identification of possible lead compound (apomorphine) from Hygrophila spinosa through in-vivo and in-silico approaches.

The aim of this research is to examine possible neurological activity of methanol, ethyl acetate, and aqueous extracts of Hygrophila spinosa and identify possible lead compounds through in silico analysis. In vivo, neuropharmacological activity was evaluated by using four distinct neuropharmacological assessment assays. Previously reported GC-MS data and earlier literature were utilized to identify the phytochemicals present in Hygrophila spinosa. Computational studies notably molecular docking and molecular dynamic simulations were conducted with responsible receptors to assess the stability of the best interacting compound. Pharmacokinetics properties like absorption, distribution, metabolism, excretion, and toxicity were considered to evaluate the drug likeliness properties of the identified compounds. All the in vivo results support the notion that different extracts (methanol, ethyl acetate, and aqueous) of Hygrophila spinosa have significant (*p = 0.05) sedative-hypnotic, anxiolytic, and anti-depressant activity. Among all the extracts, specifically methanol extracts of Hygrophila spinosa (MHS 400 mg/kg.b.w.) showed better sedative, anxiolytic and antidepressant activity than aqueous and ethyl acetate extracts. In silico molecular docking analysis revealed that among 53 compounds 7 compounds showed good binding affinities and one compound, namely apomorphine (CID: 6005), surprisingly showed promising binding affinity to all the receptors . An analysis of molecular dynamics simulations confirmed that apomorphine (CID: 6005) had a high level of stability at the protein binding site. Evidence suggests that Hygrophila spinosa has significant sedative, anxiolytic, and antidepressant activity. In silico analysis revealed that a particular compound (apomorphine) is responsible for this action. Further research is required in order to establish apomorphine as a drug for anxiety, depression, and sleep disorders.Communicated by Ramaswamy H. Sarma.

Sensitivity of Clarireedia spp. to benzimidazoles and dimethyl inhibitors fungicides and efficacy of biofungicides on dollar spot of warm season turfgrass.

Dollar spot caused by Clarireedia spp. (formerly Sclerotinia homoeocarpa) is an economically destructive fungal disease of turfgrass that can significantly compromise turf quality, playability, and aesthetic value. Fungicides are frequently used to manage the disease but are costly and potentially unfavorable to the environment. Repeated use of some active ingredients has resulted in reduced efficacy on C. jacksonii causing dollar spot in cool-season turfgrasses in the US. Experiments were conducted to study fungicide sensitivity of Clarireedia spp. as well as to develop alternatives to fungicides against dollar spot on warm-season turfgrass in Georgia. First, 79 isolates of Clarireedia spp. collected across the state were tested on fungicide-amended agar plates for their sensitivity to thiophanate-methyl (benzimidazole) and propiconazole (dimethyl inhibitor). Seventy-seven isolates (97.5%) were sensitive (0.001 to 0.654 µg/mL) and two isolates (2.5%) were found resistant (>1000 µg/mL) to thiophanate-methyl. However, in the case of propiconazole, 27 isolates (34.2%) were sensitive (0.005 to 0.098 µg/mL) while 52 isolates (65.8%) were resistant (0.101 to 3.820 µg/mL). Next, the efficacy of three bio- and six synthetic fungicides and ten different combinations were tested in vitro against C. monteithiana. Seven bio- and synthetic fungicide spray programs comprising Bacillus subtilis QST713 and propiconazole were further tested, either alone or in a tank mix in a reduced rate, on dollar spot infected bermudagrass 'TifTuf' in growth chamber and field environments. These fungicides were selected as they were found to significantly reduce pathogen growth up to 100% on in vitro assays. The most effective spray program in growth chamber assays was 100% B. subtilis QST713 in rotation with 75% B. subtilis QST713 + 25% propiconazole tank mix applied every 14 days. However, the stand-alone application of the biofungicide B. subtilis QST713 every seven days was an effective alternative and equally efficacious as propiconazole, suppressing dollar spot severity and AUDPC up to 75%, while resulting in acceptable turf quality (>7.0) in field experiments. Our study suggests that increased resistance of Clarireedia spp. to benzimidazoles and dimethyl inhibitors warrants continuous surveillance and that biofungicides hold promise to complement synthetic fungicides in an efficacious and environmentally friendly disease management program.

The pathogenetic influence of smoking on SARS-CoV-2 infection: Integrative transcriptome and regulomics analysis of lung epithelial cells.

Corona virus disease (COVID-19) has been emerged as pandemic infectious disease. The recent epidemiological data suggest that the smokers are more vulnerable to infection with COVID-19; however, the influence of smoking (SMK) on the COVID-19 infected patients and the mortality is not known yet. In this study, we aimed to discern the influence of SMK on COVID-19 infected patients utilizing the transcriptomics data of COVID-19 infected lung epithelial cells and transcriptomics data smoking matched with controls from lung epithelial cells. The bioinformatics based analysis revealed the molecular insights into the level of transcriptional changes and pathways which are important to identify the impact of smoking on COVID-19 infection and prevalence. We compared differentially expressed genes (DEGs) between COVID-19 and SMK and 59 DEGs were identified as consistently dysregulated at transcriptomics levels. The correlation network analyses were constructed for these common genes using WGCNA R package to see the relationship among these genes. Integration of DEGs with network analysis (protein-protein interaction) showed the presence of 9 hub proteins as key so called "candidate hub proteins" overlapped between COVID-19 patients and SMK. The Gene Ontology and pathways analysis demonstrated the enrichment of inflammatory pathway such as IL-17 signaling pathway, Interleukin-6 signaling, TNF signaling pathway and MAPK1/MAPK3 signaling pathways that might be the therapeutic targets in COVID-19 for smoking persons. The identified genes, pathways, hubs genes, and their regulators might be considered for establishment of key genes and drug targets for SMK and COVID-19.

Real-time face mask position recognition system based on MobileNet model.

COVID-19 is a highly contagious disease that was first identified in 2019, and has since taken more than six million lives world wide till date, while also causing considerable economic, social, cultural and political turmoil. As a way to limit its spread, the World Health Organization and medical experts have advised properly wearing face masks, social distancing and hand sanitization, besides vaccination. However, people wear masks sometimes uncovering their mouths and/or noses consciously or unconsciously, thereby lessening the effectiveness of the protection they provide. A system capable of automatic recognition of face mask position could alert and ensure that an individual is wearing a mask properly before entering a crowded public area and putting themselves and others at risk. We first develop and publicly release a dataset of face mask images, which are collected from 391 individuals of different age groups and gender. Then, we study six different architectures of pre-trained deep learning models, and finally propose a model developed by fine tuning the pre-trained state of the art MobileNet model. We evaluate the performance (accuracy, F1-score, and Cohen's Kappa) of this model on the proposed dataset and MaskedFace-Net, a publicly available synthetic dataset created by image editing. Its performance is also compared to other existing methods. The proposed MobileNet is found as the best model providing an accuracy, F1-score, and Cohen's Kappa of 99.23%, 99.22%, and 99.19%, respectively for face mask position recognition. It outperforms the accuracy of the best existing model by about 2%. Finally, an automatic face mask position recognition system has been developed, which can recognize if an individual is wearing a mask correctly or incorrectly. The proposed model performs very well with no drop in recognition accuracy from real images captured by a camera.

Effects of spirulina as a functional ingredient in arsenic-induced broiler diet on growth performance and hematobiochemical parameters.

Objectives: The purpose of this research was to look into the impacts after the implication of feeding broiler chickens with spirulina in arsenic-incited toxicities. Materials and Methods: Birds (n = 125) were distributed equally (n = 25) into four groups treated (T 1, T 2, T 3, T 4) and a group controlled, T 0 (normal feed and water without supplement), the group taking in arsenic trioxide (100 mg/l)-induced diet (T 1), and the groups T 2, T 3, and T 4 (feed supplemented with 50, 100, and 200 mg/l of spirulina along with Arsenic Trioxide, respectively). The body weight and hematobiochemical parameters were recorded every 7 days. Results: Different growth development indicators, e.g., body weight, feed intake ratio, feed conversion ratio, depression, and skin lesions, were weak in arsenic trioxide groups and upstanding in the arsenic plus spirulina group. Over and above, the lack of body weight gain in chicken (2.7%-13.00%) in the arsenic-introduced groups given spirulina (T 2, T 3, and T 4) overtook the mere groups exposed to arsenic, where the lack of weight gain was optimum (54.90%). Thereafter, in arsenic-instituted groups given spirulina (T 2, T 3, and T 4), the drop in total erythrocyte count, total leukocyte count, hemoglobin, and packed cell volume values became less notable than in arsenic pollutant groups (T 1, p < 0.01). Two measurable factors (serum glutamate pyruvate transaminase and serum glutamic oxaloacetic transaminase) were substantially (p < 0.01) raised in the group (T 1) treated with arsenic, but in the arsenic-induced groups (T 2, T 3, and T 4) treated with spirulina, they were elevated less. Conclusion: This study demonstrates that arsenic is a threat to poultry. However, spirulina may be advantageous for alleviating the effects of arsenic in poultry.

Dataset describing the growth pattern, amino acid and fatty acid profile of five indigenous marine microalgae species of Bangladesh.

This paper presents the data on the growth pattern, amino acid, and fatty acid profile of five (5) selected indigenous marine microalgae (Chaetoceros sp.; Isochrysis sp.; Skeletonema sp.; Nannochloropsis sp.; and Tetraselmis sp.) of Bay of Bengal, Bangladesh. The microalgae species were cultured in f/2 Guillard's medium with maintaining standard physico-chemical parameters. The growth pattern was determined for all the microalgae as a prerequisite for further necessary experimental works. All the species were mass cultured using the same culture medium and harvested (centrifuging method), and dried (60 â„ƒ for 12 h) at their stationary phase. Finally, the amino acid and fatty acid analyses were performed. In many contexts, the amino acid and fatty acid data showed significant differences (p < 0.05) among these experimental species. However, by understanding these experimental species' nutritional profiles, one can easily choose the desired one that is most appropriate for their intended application.

In Vivo Bioactivities of Hoya parasitica (Wall.) and In Silico Study against Cyclooxygenase Enzymes.

Hoya parasitica (Wall.) is extensively used in traditional medicine for the treatment of various diseases including rheumatism, kidney problems, jaundice, urinary tract disorders, fever, and pain. The present study was designed to explore new lead compound(s) to alleviate pain, pyresis, and diarrhea from methanol, ethyl acetate, and n-hexane extracts of H. parasitica (Wall.) leaves (MHP, EAHP, and NHP, respectively). Analgesic activity of the extracts was assessed through acetic acid induced writhing, tail immersion, and hot plate tests while brewer's yeast-induced pyrexia test was employed for the assessment of antipyretic activity. Besides, castor oil and magnesium sulfate induced diarrheal tests were utilized for the evaluation of antidiarrheal properties. Moreover, in silico study of the isolated compounds was undertaken to seek out best-fit phytoconstituent(s) against cyclooxygenase enzymes. MHP revealed substantial antioxidant activities in different in vitro assays compared to EAHP and NHP. In the acetic acid-induced writhing test, among the extracts, MHP (400 mg/kg) revealed maximum 74.15 ± 1% inhibition of writhing comparable to that of standard (85.77 ± 1.39%). Again, in tail immersion and hot plate tests, higher doses of all the test samples exhibited a significant increase of latent period in a time-dependent manner. In brewer yeast-induced pyrexia test, at 3rd and 4th hour of treatment, significant (P < 0.05) antipyretic action was found in the test samples. In both castor oil and magnesium induced diarrheal tests, MHP at 400 mg/kg showed the highest percent inhibition of diarrhea (68.62 ± 4.74 and 64.99 ± 2.90, respectively). Moreover, molecular docking analysis corroborated the results of the present study. The findings of the present study supported the traditional uses of this plant for the alleviation of pain and fever. Furthermore, hoyasterone was found to be the most effective lead compound as cyclooxygenase enzyme inhibitor.

First Report of Ramularia coleosporii causing Leaf Spot on Perilla frutescens in Korea.

Perilla (Perilla frutescens var. japonica), a member of the family Labiatae, is an annual herbaceous plant native to Asia. Its fresh leaves are directly consumed and its seeds are used for cooking oil. In July 2018, leaf spots symptoms were observed in an experimental field at Gangneung-Wonju National University, Gangneung, Gangwon province, Korea. Approximately 30% of the perilla plants growing in an area of about 0.1 ha were affected. Small, circular to oval, necrotic spots with yellow borders were scattered across upper leaves. Masses of white spores were observed on the leaf underside. Ten small pieces of tissue were removed from the lesion margins of the lesions, surface disinfected with NaOCl (1% v/v) for 30 s, and then rinsed three times with distilled water for 60 s. The tissue pieces were then placed on potato dextrose agar (PDA) and incubated at 25°C for 7 days. Five single spore isolates were obtained and cultured on PDA. The fungus was slow-growing and produced 30-50 mm diameter, whitish colonies on PDA when incubated at 25ºC for 15 days. Conidia (n= 50) ranged from 5.5 to 21.3 × 3.5 to 5.8 µm, were catenate, in simple or branched chains, ellipsoid-ovoid, fusiform, and old conidia sometimes had 1 to 3 conspicuous hila. Conidiophores (n= 10) were 21.3 to 125.8 × 1.3 to 3.6 µm in size, unbranched, straight or flexuous, and hyaline. The morphological characteristics of five isolates were similar. Morphological characteristics were consistent with those described for Ramularia coleosporii (Braun, 1998). Two representative isolates (PLS 001 & PLS003) were deposited in the Korean Agricultural Culture Collection (KACC48670 & KACC 48671). For molecular identification, a multi-locus sequence analysis was conducted. The internal transcribed spacer (ITS) regions of the rDNA, partial actin (ACT) gene and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) gene were amplified using primer sets ITS1/4, ACT-512F/ACT-783R and gpd1/gpd2, respectively (Videira et al. 2016). Sequences obtained from each of the three loci for isolate PLS001 and PLS003 were deposited in GenBank with accession numbers MH974744, MW470869 (ITS); MW470867, MW470870 (ACT); and MW470868, MW470871 (GAPDH), respectively. Sequences for all three genes exhibited 100% identity with R. coleosporii, GenBank accession nos. GU214692 (ITS), KX287643 (ACT), and 288200 (GAPDH) for both isolates. A multi-locus phylogenetic tree, constructed by the neighbor-joining method with closely related reference sequences downloaded from the GenBank database and these two isolates demonstrated alignment with R. coleosporii. To confirm pathogenicity, 150 mL of a conidial suspension (2 × 105 spores per mL) was sprayed on five, 45 days old perilla plants. An additional five plants, to serve as controls, were sprayed with sterile water. All plants were placed in a humidity chamber (>90% relative humidity) at 25°C for 48 h after inoculation and then placed in a greenhouse at 22/28°C (night/day). After 15 days leaf spot symptoms, similar to the original symptoms, developed on the leaves of the inoculated plants, whereas the control plants remained symptomless. The pathogenicity test was repeated twice with similar results. A fungus was re-isolated from the leaf lesions on the inoculated plants which exhibited the same morphological characteristics as the original isolates, fulfilling Koch's postulates. R. coleosporii has been reported as a hyperparasite on the rust fungus Coleosporium plumeriae in India & Thailand and also as a pathogen infecting leaves of Campanula rapunculoides in Armenia, Clematis gouriana in Taiwan, Ipomoea batatas in Puerto Rico, and Perilla frutescens var. acuta in China (Baiswar et al. 2015; Farr and Rossman 2021). To the best of our knowledge, this is the first report of R. coleosporii causing leaf spot on P. frutescens var. japonica in Korea. This disease poses a threat to production and management strategies to minimize leaf spot should be developed.

First Report of Fusarium Wilt Caused by Fusarium equiseti on Cabbage (Brassica oleracea var. capitate L.) in Korea.

Cabbage (Brassica oleracea var. capitate L.) is an important vegetable crop that is widely cultivated throughout the world. In August 2019, wilting symptoms on cabbage (stunted growth, withered leaves, and wilted plants) were observed in a cabbage field of Pyeongchang, Gangwon Province, with an incidence of 5 to 10%. To identify the cause, symptomatic root tissue was excised, surface-sterilized with 70% ethanol, and rinsed thrice with sterile distilled water. The samples were dried on blotter paper, placed onto potato dextrose agar (PDA), and incubated at 25°C for 1 week. Five morphologically similar fungal isolates were sub-cultured and purified using the single spore isolation method (Choi et al. 1999). The fungus produced colonies with abundant, loosely floccose, whitish-brown aerial mycelia and pale-orange pigmentation on PDA. Macroconidia had four 4 to six 6 septa, a foot-shaped basal cell, an elongated apical cell, and a size of 20.2 to 31.8 × 2.2 to 4.1 µm (n = 30). No microconidia were observed. Chlamydospores were produced from hyphae and were most often intercalary, in pairs or solitary, globose, and frequently formed chains (6.2? to 11.7 µm, n = 10). Based on these morphological characteristics, the fungus was identified as Fusarium equiseti (Leslie and Summerell 2006). A representative isolate was deposited in the Korean Agricultural Culture Collection (KACC48935). For molecular characterization, portions of the translation elongation factor 1-alpha (TEF-1α) and second largest subunit of RNA polymerase II (RPB2) genes were amplified from the representative isolate using the primers pair of TEF-1α (O'Donnell et al. 2000) and GQ505815 (Fusarium MLST database), and sequenced. Searched BLASTn of the RPB2 sequence (MT576587) to the Fusarium MLST database showed 99.94% similarity to the F. incarnatum-equiseti species complex (GQ505850) and 98.85 % identity to both F. equiseti (GQ505599) and F. equiseti (GQ505772). Further, the TEF-1α sequence (MT084815) showed 100% identity to F. equiseti (KT224215) and 99.85% identity to F. equiseti (GQ505599), respectively. Therefore, the fungus was identified as F. equiseti based on morphological and molecular identification. For pathogenicity testing, a conidial suspension (1 × 106 conidia/ml) was prepared by harvesting macroconidia from 2-week-old cultures on PDA. Fifteen 4-week-old cabbage seedlings (cv. 12-Aadrika) were inoculated by dipping roots into the conidial suspension for 30 min. The inoculated plants were transplanted into a 50-hole plastic tray containing sterilized soil and maintained in a growth chamber at 25°C, with a relative humidity of >80%, and a 12-h/12-h light/dark cycle. After 4 days, the first wilt symptoms were observed on inoculated seedlings, and the infected plants eventually died within 1 to 2 weeks after inoculation. No symptoms were observed in plants inoculated with sterilized distilled water. The fungus was re-isolated from symptomatic tissues of inoculated plants and its colony and spore morphology were identical to those of the original isolate, thus confirming Koch's postulates. Fusarium wilt caused by F. equiseti has been reported in various crops, such as cauliflower in China, cumin in India, and Vitis vinifera in Spain (Farr and Rossman 2020). To our knowledge, this is the first report of F. equiseti causing Fusarium wilt on cabbage in Korea. It This disease poses a threat to cabbage production in Korea, and effective disease management strategies need to be developed.

Talaromyces halophytorum sp. nov. Isolated from Roots of Limonium tetragonum in Korea.

Talaromyces halophytorum sp. nov. was isolated from the roots of halophyte Limonium tetragonum collected from Seocheon-gun, Korea in November 2015. It showed a slow growth on yeast extract sucrose agar at 25 °C, no growth at 4 °C or 37 °C and produced smooth-walled and globose to sub-globose conidia. T. halophytorum is phylogenetically distinct from the other reported Talaromyces species of section Trachyspermi based on multi-locus sequence typing results using partial fragments of ß-tubulin, calmodulin, ITS, and RNA polymerase II genes.

Evaluation of the Tinetti score and fall risk assessment via accelerometry-based movement analysis.

Gait and balance disorders are among the main predisposing factors of falls in elderly. Clinical scales are widely employed to assess the risk of falling, but they require trained personnel. We investigate the use of objective measures obtained from a wearable accelerometer to evaluate the fall risk, determined by the Tinetti clinical scale. Seventy-nine patients and eleven volunteers were enrolled in two rehabilitation centers and underwent a full Tinetti test, while wearing a triaxial accelerometer at the chest. Tinetti scores were assessed by expert physicians and those subjects with a score ≤18 were considered at high risk. First, we analyzed 21 accelerometer features by means of statistical tests and correlation analysis. Second, one regression and one classification problem were designed and solved using a linear model (LM) and an artificial neural network (ANN) to predict the Tinetti outcome. Pearson's correlation between the Tinetti score and a subset of 9 features (mainly related with standing and walking) was 0.71. The misclassification error of high risk patient was 0.21 and 0.11, for LM and ANN, respectively. The work might foster the development of a new generation of applications meant to monitor the time evolution of the fall risk using low cost devices at home.

Low Computational Cost for Sample Entropy.

Sample Entropy is the most popular definition of entropy and is widely used as a measure of the regularity/complexity of a time series. On the other hand, it is a computationally expensive method which may require a large amount of time when used in long series or with a large number of signals. The computationally intensive part is the similarity check between points in m dimensional space. In this paper, we propose new algorithms or extend already proposed ones, aiming to compute Sample Entropy quickly. All algorithms return exactly the same value for Sample Entropy, and no approximation techniques are used. We compare and evaluate them using cardiac inter-beat (RR) time series. We investigate three algorithms. The first one is an extension of the k d -trees algorithm, customized for Sample Entropy. The second one is an extension of an algorithm initially proposed for Approximate Entropy, again customized for Sample Entropy, but also improved to present even faster results. The last one is a completely new algorithm, presenting the fastest execution times for specific values of m, r, time series length, and signal characteristics. These algorithms are compared with the straightforward implementation, directly resulting from the definition of Sample Entropy, in order to give a clear image of the speedups achieved. All algorithms assume the classical approach to the metric, in which the maximum norm is used. The key idea of the two last suggested algorithms is to avoid unnecessary comparisons by detecting them early. We use the term unnecessary to refer to those comparisons for which we know a priori that they will fail at the similarity check. The number of avoided comparisons is proved to be very large, resulting in an analogous large reduction of execution time, making them the fastest algorithms available today for the computation of Sample Entropy.

Performance comparison between wrist and chest actigraphy in combination with heart rate variability for sleep classification.

The concurrent usage of actigraphy and heart rate variability (HRV) for sleep efficiency quantification is still matter of investigation. This study compared chest (CACT) and wrist (WACT) actigraphy (actigraphs positioned on chest and wrist, respectively) in combination with HRV for automatic sleep vs wake classification. Accelerometer and ECG signals were collected during polysomnographic studies (PSGs) including 18 individuals (25-53 years old) with no previous history of sleep disorders. Then, an experienced neurologist performed sleep staging on PSG data. Eleven features from HRV and accelerometry were extracted from series of different lengths. A support vector machine (SVM) was used to automatically distinguish sleep and wake. We found 7 min as the optimal signal length for classification, while maximizing specificity (wake detection). CACT and WACT provided similar accuracies (78% chest vs 77% wrist), larger than what yielded by HRV alone (66%). The addition of HRV to CACT reduced slightly the accuracy, while improving specificity (from 33% to 51%, p < 0.05). On the contrary, the concurrent usage of HRV and WACT did not provide statistically significant improvements over WACT. Then, a subset of features (3 from HRV + 1 from actigraphy) was selected by reducing redundancy using a strategy based on Spearman's correlation and area under the ROC curve. The usage of the reduced set of features and SVM classifier gave only slightly reduced classification performances, which did not differ from the full sets of features. The study opens interesting possibilities in the design of wearable devices for long-term monitoring of sleep at home.

Bubble Entropy: An Entropy Almost Free of Parameters.

Objective: A critical point in any definition of entropy is the selection of the parameters employed to obtain an estimate in practice. We propose a new definition of entropy aiming to reduce the significance of this selection. Methods: We call the new definition Bubble Entropy. Bubble Entropy is based on permutation entropy, where the vectors in the embedding space are ranked. We use the bubble sort algorithm for the ordering procedure and count instead the number of swaps performed for each vector. Doing so, we create a more coarse-grained distribution and then compute the entropy of this distribution. Results: Experimental results with both real and synthetic HRV signals showed that bubble entropy presents remarkable stability and exhibits increased descriptive and discriminating power compared to all other definitions, including the most popular ones. Conclusion: The definition proposed is almost free of parameters. The most common ones are the scale factor r and the embedding dimension m . In our definition, the scale factor is totally eliminated and the importance of m is significantly reduced. The proposed method presents increased stability and discriminating power. Significance: After the extensive use of some entropy measures in physiological signals, typical values for their parameters have been suggested, or at least, widely used. However, the parameters are still there, application and dataset dependent, influencing the computed value and affecting the descriptive power. Reducing their significance or eliminating them alleviates the problem, decoupling the method from the data and the application, and eliminating subjective factors.Objective: A critical point in any definition of entropy is the selection of the parameters employed to obtain an estimate in practice. We propose a new definition of entropy aiming to reduce the significance of this selection. Methods: We call the new definition Bubble Entropy. Bubble Entropy is based on permutation entropy, where the vectors in the embedding space are ranked. We use the bubble sort algorithm for the ordering procedure and count instead the number of swaps performed for each vector. Doing so, we create a more coarse-grained distribution and then compute the entropy of this distribution. Results: Experimental results with both real and synthetic HRV signals showed that bubble entropy presents remarkable stability and exhibits increased descriptive and discriminating power compared to all other definitions, including the most popular ones. Conclusion: The definition proposed is almost free of parameters. The most common ones are the scale factor r and the embedding dimension m . In our definition, the scale factor is totally eliminated and the importance of m is significantly reduced. The proposed method presents increased stability and discriminating power. Significance: After the extensive use of some entropy measures in physiological signals, typical values for their parameters have been suggested, or at least, widely used. However, the parameters are still there, application and dataset dependent, influencing the computed value and affecting the descriptive power. Reducing their significance or eliminating them alleviates the problem, decoupling the method from the data and the application, and eliminating subjective factors.

First Report of Web Blight of Rosemary (Rosmarinus officinalis) Caused by Rhizoctonia solani AG-1-IB in Korea.

Herein, we report the first occurrence of web blight of rosemary caused by Rhizoctonia solani AG-1-IB in Gangneung, Gangwon Province, Korea, in August 2014. The leaf tissues of infected rosemary plants were blighted and white mycelial growth was seen on the stems. The fungus was isolated from diseased leaf tissue and cultured on potato dextrose agar for identification. The young hyphae had acute angular branching near the distal septum of the multinucleate cells and mature hyphal branches formed at an approximately 90° angle. This is morphologically identical to R. solani AG-1-IB, as per previous reports. rDNA-ITS sequences of the fungus were homologous to those of R. solani AG-1-IB isolates in the GenBank database with a similarity percentage of 99%, thereby confirming the identity of the causative agent of the disease. Pathogenicity of the fungus in rosemary plants was also confirmed by Koch's postulates.

Parametric estimation of sample entropy for physical activity recognition.

Insufficient amount of physical activity, and hence storage of calories may lead depression, obesity, cardiovascular diseases, and diabetes. The amount of consumed calorie depends on the type of activity. The recognition of physical activity is very important to estimate the amount of calories spent by a subject every day. There are some research works already published in the literature for activity recognition through accelerometers (body worn sensors). The accuracy of any recognition system depends on the robustness of selected features and classifiers. The typical features reported for most physical activities recognitions are autoregressive coefficients (ARcoeffs), signal magnitude area (SMA), tilt angle (TA), and standard deviation (STD). In this study, we have studied the feasibility of using single value of sample entropy estimated parametrically (SETH) of an AR model instead of ARcoeffs. After feasibility study, we also compared the recognition accuracies between two popular classifiers i.e. artificial neural network (ANN) and support vector machines (SVM). The recognition accuracies using linear structure (where all types of activities are classified using a single classifier) and hierarchical structure (where activities are first divided into static and dynamic events, and then activities of each event are classified in the second stage). The study showed that the use of SETH provides similar recognition accuracy (69.82%) as provided by ARcoeffs (67.67%) using ANN. The linear structure of SVM performs better (average accuracy of SVM: 98.22%) than linear ANN (average accuracy with ANN: 94.78%). The use of hierarchical structure of ANN increases the average recognition accuracy of static activities to about 100%. However, no significant changes are observed using hierarchical SVM than the linear one.

Automatic vs. clinical assessment of fall risk in older individuals: A proof of concept.

Falling in elderly is a worldwide major problem because it can lead to severe injuries, and even sudden death. Fall risk prediction would provide rapid intervention, as well as reducing the over burden of healthcare systems. Such prediction is currently performed by means of clinical scales. Among them, the Tinetti Scale is one of the better established and mostly used in clinical practice. In this work, we proposed an automatic method to assess the Tinetti scores using a wearable accelerometer. The balance and gait characteristics of 13 elderly subjects have been scored by an expert clinician while performing 8 different motor tasks according to the Tinetti Scale protocol. Two statistical analysis were selected. First, a linear regression study was performed between the Tinetti scores and 8 features (one feature for each task). Second, the generalization quality of the regression model was assessed using a Leave-One SubjectOut approach. The multiple linear regression provided a high correlation between the Tinetti scores and the features proposed (adj. R(2) = 0.948; p = 0.003). Moreover, six of the eight features added statistically significantly to the prediction of the scores (p <; 0.05). When testing the generalization capability of the model, a moderate linear correlation was obtained (R(2) = 0.67; p <; 0.05). The results suggested that the automatic method might be a promising tool to assess the falling risk of older individuals.

Non-linear regularity of arterial blood pressure variability in patient with atrial fibrillation in tilt-test procedure.

AIMS: Dynamics of cardiovascular series may be explored with non-linear techniques. It is unknown if the arterial pressure irregularity commonly observed in patients with atrial fibrillation (AF) might be further increased by a sympathetic stimulus such as orthostatic tilt. METHODS AND RESULTS: Twenty patients (62 ± 14 years, 15 men) were recruited for the study. Continuous beat-to-beat non-invasive arterial pressure was acquired at rest and during a passive orthostatic stimulus ('tilt test'). Systolic (SAP) and diastolic (DAP) arterial pressure series of 300 samples were analysed in both conditions. Approximate (ApEn) and sample entropy (SampEn) were computed, as irregularity measures. Equivalent metrics (ApEnAR and SampEnAR) derived from an autoregressive model of the series were also obtained through numerical simulations, to further elucidate the non-linear mechanisms present in the series. In 11 patients (Group A), SAP significantly increased during tilt (from 103 ± 13 to 114 ± 17 mmHg, P < 0.001 rest vs. tilt), whereas in 9 patients (Group B) SAP remained almost unchanged (SAP: 110 ± 18 vs. 106 ± 19 mmHg, rest vs. tilt). No clinical differences were found between Groups A and B. When analysing Group A, all irregularity measures significantly increased in SAP (ApEn: 1.75 ± 0.20 vs. 1.88 ± 0.16, P < 0.05; SampEn: 1.71 ± 0.30 vs. 1.88 ± 0.27, P < 0.05; ApEnAR: 1.87 ± 0.20 vs. 1.96 ± 0.18, P < 0.05; SampEnAR: 1.94 ± 0.27 vs. 2.06 ± 0.18, P < 0.05; rest vs. tilt), whereas no differences were found in DAP series. No significant differences were found in Group B for either SAP or DAP. CONCLUSION: The alterations of SAP during tilt in AF patients are not uniform and seem associated with different regularity patterns. The pressor response to sympathetic stimulation was also associated with an increase of SAP series irregularity.