scholarly journals Where’s the best supermarket deal? Female Southern Rockhopper Penguins (Eudyptes chrysocome) show variable foraging areas during the guard stage at Isla de los Estados, Argentina

2021 ◽  
pp. 46-55
Author(s):  
Natalia G. Rosciano ◽  
Klemens Pütz ◽  
Michael J. Polito ◽  
Andrea Raya Rey

Understanding the spatial distribution of seabirds contributes to comprehending their ecological requirements and dispersion patterns. We studied the at-sea distribution of female Southern Rockhopper Penguins (Eudyptes chrysocome (J.R. Forster, 1781)) at Isla de los Estados colony during the early chick-rearing period. We used a clustering analysis approach to identify different groups according to the foraging trip (tracking and diving data from GPS and temperature and depth data loggers) and diet (δ15N composition on blood samples) characteristics. Foraging trips differed in duration, location, and dive depths explored. Females in clusters 1 and 3 traveled longer distances and in opposite directions (36.3 ± 21.3 and 40.3 ± 14.0 km, respectively). Females in cluster 2 fed closer to the colony (16.8 ± 7.8 km). Dives occurred in pelagic habitats. Higher δ15N values suggested a greater proportion of fish (e.g., the Fuegian sprat, Sprattus fuegensis (Jenyns, 1842)) consumption in the northern foraging areas (cluster 1). The variability observed in the spatial distribution suggests flexibility in the foraging behavior of Southern Rockhopper Penguins and availability of adequate foraging areas within the colony range during the early chick-rearing period, both important features for Southern Rockhopper Penguin population. These results contribute to understanding the use of the Southern Ocean by marine mesopredators and top predators and to the marine spatial planning in the area.

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 20.2-20
Author(s):  
A. M. Patiño-Trives ◽  
C. Perez-Sanchez ◽  
A. Ibañez-Costa ◽  
P. S. Laura ◽  
M. Luque-Tévar ◽  
...  

Background:To date, although multiple molecular approaches have illustrated the various aspects of Primary Antiphospholipid Syndrome (APS), systemic lupus erythematosus (SLE) and antiphospholipid syndrome plus lupus (APS plus SLE), no study has so far fully characterized the potential role of posttranscriptional regulatory mechanisms such as the alternative splicing.Objectives:To identify shared and differential changes in the splicing machinery of immune cells from APS, SLE and APS plus SLE patients, and their involvement in the activity and clinical profile of these autoimmune disorders.Methods:Monocytes, lymphocytes and neutrophils from 80 patients (22 APS, 35 SLE and 23 APS plus SLE) and 50 healthy donors (HD) were purified by immunomagnetic selection. Then, selected elements of the splicing machinery were evaluated using a microfluidic qPCR array (Fluidigm). In parallel, extensive clinical/serological evaluation was performed, comprising disease activity, thrombosis and renal involvement, along with autoantibodies, acute phase reactants, complement and inflammatory molecules. Molecular clustering analyses and correlation/association studies were developed.Results:Patients with primary APS, SLE and APS plus SLE displayed significant and specific alterations in the splicing machinery components in comparison with HD, that were further specific for each leukocyte subset. Besides, these alterations were associated with distinctive clinical features.Hence, in APS, clustering analysis allowed to identify two sets of patients representing different molecular profile groups with respect to the expression levels of splicing machinery components. Principal component analyses confirmed a clear separation between patients. Clinically, cluster 1 characterized patients with higher thrombotic episodes and recurrences than cluster 2 and displayed a higher adjusted global APS score (aGAPSS). Accordingly, these patients showed higher levels of inflammatory mediators than cluster 2.Similarly, in patients with APS plus SLE, clustering analysis allowed to identify two sets of patients showing differential expression of splicing machinery components. Clinical and laboratory profiles showed that cluster 2 characterized patients that had suffered more thrombotic recurrences, most of them displaying an aGAPSS over 12 points and expressing higher levels of inflammatory mediators than cluster 1. The incidence of lupus nephropathy was similarly represented in both clusters.Lastly, in SLE patients, molecular clustering analysis identified two sets of patients showing distinctive clinical features. One cluster characterized most of the patients positive for anti-dsDNA antibodies, further suffering lupus nephropathy, and a high proportion of them also presenting atheroma plaques and high levels of inflammatory mediators.Correlation studies further demonstrated that several deranged splicing machinery components in immune cells (i.e. SF3B1tv1, PTBP1, PRP8 and RBM17) were linked to the autoimmune profile of the three autoimmune diseases, albeit in a specific way on each disorder. Accordingly, in vitro treatment of HD lymphocytes with aPL-IgG or anti-dsDNA-IgG changed the expression of spliceosome components also found altered in vivo in the three autoimmune diseases. Finally, the induced over/downregulated expression of selected spliceosome components in leukocytes modulated the expression of inflammatory cytokines, changed the procoagulant/adhesion activities of monocytes and regulated NETosis in neutrophils.Conclusion:1) The splicing machinery, profoundly altered in leukocytes from APS, APS plus SLE and SLE patients, is closely related to the activity of these diseases, their autoimmune and inflammatory profiles. 2) The analysis of the splicing machinery allows the segregation of APS, APS plus SLE and SLE, with specific components explaining the CV risk and renal involvement in these highly related autoimmune disorders.Acknowledgements:Funded by ISCIII, PI18/00837 and RIER RD16/0012/0015 co-funded with FEDERDisclosure of Interests:None declared


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Eunyoung Emily Lee ◽  
Kyoung-Ho Song ◽  
Woochang Hwang ◽  
Sin Young Ham ◽  
Hyeonju Jeong ◽  
...  

AbstractThe objective of the study was to identify distinct patterns in inflammatory immune responses of COVID-19 patients and to investigate their association with clinical course and outcome. Data from hospitalized COVID-19 patients were retrieved from electronic medical record. Supervised k-means clustering of serial C-reactive protein levels (CRP), absolute neutrophil counts (ANC), and absolute lymphocyte counts (ALC) was used to assign immune responses to one of three groups. Then, relationships between patterns of inflammatory responses and clinical course and outcome of COVID-19 were assessed in a discovery and validation cohort. Unbiased clustering analysis grouped 105 patients of a discovery cohort into three distinct clusters. Cluster 1 (hyper-inflammatory immune response) was characterized by high CRP levels, high ANC, and low ALC, whereas Cluster 3 (hypo-inflammatory immune response) was associated with low CRP levels and normal ANC and ALC. Cluster 2 showed an intermediate pattern. All patients in Cluster 1 required oxygen support whilst 61% patients in Cluster 2 and no patient in Cluster 3 required supplementary oxygen. Two (13.3%) patients in Cluster 1 died, whereas no patient in Clusters 2 and 3 died. The results were confirmed in an independent validation cohort of 116 patients. We identified three different patterns of inflammatory immune response to COVID-19. Hyper-inflammatory immune responses with elevated CRP, neutrophilia, and lymphopenia are associated with a severe disease and a worse outcome. Therefore, targeting the hyper-inflammatory response might improve the clinical outcome of COVID-19.


Author(s):  
José Irving Monjarás-barrera ◽  
Mario Rocandio-rodríguez ◽  
Cristina Domínguez-castro ◽  
Francisco Reyes-zepeda ◽  
Sandra Grisell Mora-ravelo ◽  
...  

Ecological interactions between mites (predatory and phytophagous) and wild plants growing in undisturbed environments play a crucial role to understand their natural settlement, development and dispersion patterns. Pequin chili pepper, Capsicum annuum L. var. glabriusculum, is a low-cost natural resource for local communities living inside Natural Protected Areas (ANP) of Tamaulipas State in Mexico. The aims of this research work were: 1) determine the spatial distribution pattern of predatory and phytophagous mites, 2) determine the spatiotemporal association between predatory and phytophagous mites, and 3) determine the association among different mite species and some phenological stages of Pequin chili pepper. The most abundant phytophagous mites were Tetranychus merganser and Aculops lycpoersici, and the predatory species were Amblyseius similoides, Euseius mesembrinus and Metaseiulus (Metaseiulus) negundinis. Most mite species showed an aggregated distribution pattern according to the plant phenological stages. However, the distribution of mite species throughout time showed different types of aggregation. On the other hand, we found positive associations among A. lycopersici and T. merganser phytophagous mites with A. similoides, E. mesembrinus and M. (M.) negundinis predators mites. The association between plants and mite species were influenced by the phenological stages of Pequin chili pepper. This is an indication of the complexity among trophic-chain interactions that depend largely on the available resources and competition. These two factors serve as foundations for settlement, development and dispersion patterns of certain species.


2020 ◽  
Vol 7 (4) ◽  
pp. 861
Author(s):  
Ayu Hardianti ◽  
Dewi Agushinta. R

<p class="Abstrak"><span lang="IN">Penelitian ini bertujuan menganalisis pola lama studi mahasiswa fakultas teknik universitas Darma Persada dari</span><span lang="IN">data akademik. Metode yang digunakan adalah <em>clustering</em> algoritma K-Means. Variabel yang dianalisis adalah </span><span lang="IN">jurusan, daerah asal, umur, jenis kelamin, Indeks Prestasi Komulatif (IPK), Satuan Kredit Semester (SKS), tahun masuk, lama studi. Analisis dilakukan menggunakan perangkat lunak WEKA. Penelitian dilakukan melalui pengumpulan data dari arsip atau  <em>database</em> biro Administrasi Akademik yaitu berupa data akademik mahasiswa fakultas teknik Universitas Darma Persada angkatan 2009 sampai 2014. Tahapan selanjutnya adalah <em>preprocessing</em> data yang dilakukan melalui analisis metode <em>clustering</em> menggunakan algoritma K-Means dengan terlebih dahulu menentukan jumlah <em>cluster </em>menggunakan metode Elbow dan interpretasi hasil. Berdasarkan hasil metode Elbow, jumlah <em>cluster</em> sebanyak 4 <em>cluster</em>. Berdasarkan hasil proses K-Means <em>clustering, </em>pembagian data pada masing-masing <em>cluster </em>adalah <em>cluster </em>1 berjumlah 556 data (26%), <em>cluster </em>2 berjumlah 414 data (19%), <em>cluster </em>3 berjumlah 189 data (9%) dan <em>cluster </em>4 berjumlah 1010 data (46%). Selanjutnya, yang memiliki lama studi lebih dari 4 tahun (lebih dari 8 semester) berada pada <em>cluster </em>2, <em>cluster </em>3, <em>cluster </em>4 sedangkan mahasiswa yang memiliki masa studi 4 tahun (8 semester) berada pada <em>cluster </em>1.</span></p><p class="Abstrak"><span lang="IN"><br /></span></p><p class="Abstrak"><em><strong><span lang="IN">Abstract</span></strong></em></p><p class="Judul2"><em>The duration of student study is one of the factors that influence the completing students' timeliness. Based on the policy of the National Accreditation Board of Higher Education (BAN-PT) in Regulation No. 4 of 2017 concerning the Policy for Preparing Accreditation Instruments, the duration of study is one of the benchmarks and evaluation elements in accreditation of study programs. From the Faculty of Engineering academic data, Darma Persada University, many students take more than four years of study. The duration of study is one of the problems of the study program manager in terms of academic performance. This study aims to analyze the old patterns of study by students of the Faculty of Engineering, Darma Persada University from academic data. K-Means algorithm clustering technique is used with the variables are majors, the area of origin, age, gender, Grade Point Average (GPA), Semester Credit Unit (SKS), year of entry and study duration. The Waikato Environment for Knowledge Analysis (WEKA) software is used as an analytic tool. The initial stage of research is through collecting data from archives or Academic sections, namely academic data from students of the Faculty of Engineering, Darma Persada University, 2009 to 2014. The next stage is preprocessing data through K-Means algorithm clustering analysis by first calculating many clusters using the Elbow method and result interpretation. From the Elbow method result, the number of clusters used is 4 (four) clusters. Based on the results of the K-Means clustering process, the data sharing in each cluster is cluster 1 (one) totaling 556 data (26%), cluster 2 (two) totaling 414 data (19%), cluster 3 (three) totaling 189 data (9%) and cluster 4 (four) totaling 1010 data (46%). Furthermore, those who have more than 4 years of study are in cluster 2, cluster 3, cluster 4 and students who have a 4-year study period are in cluster 1.</em></p><p class="Judul2"> </p><p class="Abstrak"><em><strong><span lang="IN"><br /></span></strong></em></p>


1991 ◽  
Vol 3 (4) ◽  
pp. 363-369 ◽  
Author(s):  
Julian Gutt ◽  
M. Gorny ◽  
W. Arntz

Three species of shrimps (Notocrangon antarcticus, Chorismus antarcticus, Nematocarcinus lanceopes) were investigated in the south-eastern Weddell Sea using of underwater photography. Maximum densities of c. 100 specimens per 100 m2 were found for N. antarcticus on the continental shelf (200–600 m) and for N. lanceopes on the slope (800–1200 m). Small-scale dispersion patterns and size-frequency distributions were analyzed within dense concentrations. These direct observations indicate that the behaviour of the three species is adapted to different habitats with Chorismus distribution correlated with that of sponges and Notocrangon with base sediment.


2012 ◽  
Vol 78 (8) ◽  
pp. 2522-2532 ◽  
Author(s):  
G. A. Perkins ◽  
H. C. den Bakker ◽  
A. J. Burton ◽  
H. N. Erb ◽  
S. P. McDonough ◽  
...  

ABSTRACTLittle is known about the gastric mucosal microbiota in healthy horses, and its role in gastric disease has not been critically examined. The present study used a combination of 16S rRNA bacterial tag-encoded pyrosequencing (bTEFAP) and fluorescencein situhybridization (FISH) to characterize the composition and spatial distribution of selected gastric mucosal microbiota of healthy horses. Biopsy specimens of the squamous, glandular, antral, and any ulcerated mucosa were obtained from 6 healthy horses by gastroscopy and from 3 horses immediately postmortem. Pyrosequencing was performed on biopsy specimens from 6 of the horses and yielded 53,920 reads in total, with 631 to 4,345 reads in each region per horse. The microbiome segregated into two distinct clusters comprised of horses that were stabled, fed hay, and sampled at postmortem (cluster 1) and horses that were pastured on grass, fed hay, and biopsied gastroscopically after a 12-h fast (cluster 2). The types of bacteria obtained from different anatomic regions clustered by horse rather than region. The dominant bacteria in cluster 1 wereFirmicutes(>83% reads/sample), mainlyStreptococcusspp.,Lactobacillusspp. and,Sarcinaspp. Cluster 2 was more diverse, with predominantlyProteobacteria,Bacteroidetes, andFirmicutes, consisting ofActinobacillusspp.Moraxellaspp.,Prevotellaspp., andPorphyromonasspp.Helicobactersp. sequences were not identified in any of 53,920 reads. FISH (n= 9) revealed bacteria throughout the stomach in close apposition to the mucosa, with significantly moreStreptococcusspp. present in the glandular region of the stomach. The equine stomach harbors an abundant and diverse mucosal microbiota that varies by individual.


Nematology ◽  
2014 ◽  
Vol 16 (7) ◽  
pp. 797-805 ◽  
Author(s):  
Cécile Gracianne ◽  
Eric J. Petit ◽  
Jean-François Arnaud ◽  
Catherine Porte ◽  
Lionel Renault ◽  
...  

Most populations of crop pathogens have wild relative populations from which they can originate but for which basic knowledge of their ecological requirementsin naturais scarce. However, the study of spatial distribution and ecology of wild pathogen populations may help control them in crops through a better understanding of the environmental factors driving population dynamics. Here, we focused onHeterodera schachtiiandH. betae, two cyst nematodes that cause severe damage to sugar beet (Beta vulgarisssp.vulgaris) crops and can develop on a wild beet relative, the sea beet (B. vulgarisssp.maritima). We investigated the occurrence of both nematode species in the wild and explored some environmental factors that may influence their geographical distribution. To do so, we sampled the wild hostB. v.ssp.maritimaalong the European Atlantic and North Sea coastlines. Results showed thatH. schachtiimainly occurred in the colder environments of northern Europe, whereasH. betaewas preferentially distributed in the warm environments of southern Europe. It was previously established thatH. betaeonly recently appeared in The Netherlands, which are in the north of Europe. Thus, our results do not support this hypothesis. Overall, this study accurately documents the geographical occurrence of two nematode crop pest species in the wild and helps identify the main environmental factors affecting their distribution range.


2019 ◽  
Vol 24 (1) ◽  
pp. 43-52
Author(s):  
He-Ping Wei ◽  
Feng Wang ◽  
Rui-Ting Ju

Taylor’s power law and Iwao’s patchiness regression were used to describe the dispersion patterns for overwintering and wandering stages of Corythucha ciliata on the London plane trees, Platanus x acerifolia (Ait.) Willd. Both Taylor’s and Iwao’s tests fit the distribution data for the overwintering stage. The overwintering adults were spatially aggregated. In the wandering stage, Taylor’s power law consistently fit the data, whereas the fit of Iwao’s patchiness regression was erratic. Both Iwao’s and Taylor’s indices indicated a clumped distribution pattern for eggs, nymphs, and wandering adults. Trunk was identified as the best sampling target for the overwintering stage whereas twig was the best for the wandering stage. In order to determine the sample size for evaluating whether the population has reached the control threshold, the sampling of 35 and 7 trunks for the overwintering stage and 32 and 8 twigs per tree for the wandering stage would provide 0.5- and 0.25-precision levels, respectively.


2021 ◽  
Vol 22 (1) ◽  
pp. 1
Author(s):  
Febiyanti Alfiah ◽  
Almadayani Almadayani ◽  
Danial Al Farizi ◽  
Edy Widodo

 Keberadaan pandemi COVID-19 di Indonesia, mengakibatkan kemiskinan di Indonesia semakin tinggi terutama di Jawa Timur yang menjadi satu diantara provinsi lain dengan kasus COVID-19 tinggi di Indonesia. Tujuan penelitian ini yaitu mengetahui pengelompokan kabupaten/kota di Jawa Timur yang mempunyai kesamaan karakteristik berdasarkan indikator kemiskinan tahun 2020. Penelitian ini menggunakan data yang didapatkan dari Badan Pusat Statistik. Metode yang digunakan ialah metode k-medoids clustering yang merupakan metode partisi clustering guna pengelompokan n objek ke dalam k cluster. Berdasarkan hasil penelitian, diperoleh pengelompokan karakteristik masing-masing cluster yang dibentuk berdasarkan nilai indikator kemiskinan di Jawa Timur tahun 2020 sebanyak 2 cluster. Dimana 30 kabupaten/kota pada cluster 1 dan dan 8 kabupaten/kota pada cluster 2. Cluster 1 memiliki karakteristik Persentase Rumah Tangga yang Mempunyai Sanitasi Layak, Angka Harapan Hidup, dan Persentase Angka Melek Huruf Umur 15-55 Th tinggi. Sedangkan cluster 2 memiliki karakteristik Persentase Rumah Tangga Miskin Penerima Raskin, Persentase Penduduk Miskin, dan Persentase Pengeluaran Perkapita untuk Makanan dengan Status Miskin tinggi. Kata kunci: Clustering; Jawa Timur; K-medoids; kemiskinan  K-Medoids Clustering Analysis Based on Poverty Indicators in East Java in 2020 ABSTRACT The existence of the pandemic COVID-19 in Indonesia has resulted in higher poverty in Indonesia, especially in East Java, which is one of the other provinces with high cases in Indonesia. The purpose of this study is to find out the grouping of regencies/cities in East Java that have similar characteristics based on the poverty indicators in 2020. This study uses data obtained from the Badan Pusat Statistik. The method used is k-medoids clustering method which is a clustering partition method for grouping n objects into k clusters. Based on the results of the study, it was found that the grouping of the characteristics of each cluster formed based on the value of the poverty indicator in East Java in 2020 was 2 clusters. Where 30 regencies/cities in cluster 1 and and 8 regencies/cities in cluster 2. Cluster 1 has the characteristics of the percentage of households that have proper sanitation, life expectancy, and a high percentage of literacy rates aged 15-55 years. While cluster 2 has the characteristics of the percentage of poor households receiving Raskin, the percentage of poor people, and the percentage of per capita expenditure on food with high poor status. Keywords: Clustering; East Java; K-Medoids; poverty


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