Echinoderms from the Museum of Zoology from the Universidad de Costa Rica

El Museo de Zoología de la Universidad de Costa Rica (MZUCR) se funda en 1966 y alberga la colección de organismos vertebrados e invertebrados más completa de Costa Rica. El MZUCR cuenta actualmente con 24 colec-ciones que contienen más de cinco millones de especíme-nes, y más de 13 000 especies identificadas. Las primeras colecciones datan 1960 e incluyen peces, reptiles, anfibios, poliquetos, crustáceos y equinodermos. Para este último grupo, el MZUCR posee un total de 157 especies, en 1 173 lotes y 4 316 ejemplares. Estas 157 especies representan el 54% del total de especies de equinodermos que posee Costa Rica (293 especies). El resto de especies están repar-tidas en las siguientes instituciones: Academia de la Cien-cias de California (CAS) (4.8%), Instituto Oceanográfico Scripps (SIO) (5.2%), en la Colección Nacional de equino-dermos “Dra. Ma. Elena Caso” de la Universidad Nacional Autónoma de México (ICML-UNAM) (12.7%), Museo de Zoología Comparada de Harvard (MZC) (19.2%), y en el Museo Nacional de Historia Natural del Instituto Smithso-niano (USNM) (35.1%). Es posible que haya material de Costa Rica en el Museo de Historia Natural de Dinamarca (NCD) y en el Museo de Historia Natural de los Ángeles (LACM), sin embargo, no hubo acceso a dichas coleccio-nes. A su vez hay 9.6% de especies que no aparecen en ningún museo, pero están reportadas en la literatura. Con base en esta revisión de colecciones se actualizó el listado taxonómico de equinodermos para Costa Rica que consta de 293 especies, 152 géneros, 75 familias, 30 órdenes y cinco clases. La costa Pacífica de Costa Rica posee 153 especies, seguida por la isla del Coco con 134 y la costa Caribe con 65. Holothuria resultó ser el género más rico con 25 especies.The Museum of Zoology, Universidad de Costa Rica (MZUCR) was founded in 1966 and houses the most complete collection of vertebrates and invertebrates in Costa Rica. The MZUCR currently has 24 collections containing more than five million specimens, and more than 13 000 species. The earliest collections date back to 1960 and include fishes, reptiles, amphibians, polychaetes, crustaceans and echinoderms. For the latter group, the MZUCR has a total of 157 species, in 1 173 lots and 4 316 specimens. These 157 species represent 54% of the total species of echino-derms from Costa Rica. The remaining species are distributed in the following institutions: California Academy of Sciences (CAS) (4.8%), Scripps Oceanographic Institute (SIO) (5.2%), National Echinoderm Collection “Dr. Ma. Elena Caso” from the National Autonomous University of Mexico (ICML-UNAM) (12.7%), the National Museum of Natural History, Smithsonian Institute (USNM) (35.1%), and the Harvard Museum of Comparative Zoology (19.2%). There may be material from Costa Rica in the Natural History Museum of Denmark (NCD) and the Natural History Museum of Los Angeles (LACM), however, there was no access to such collections. There are 9.6% that do not appear in museums, but are reported in the literature. Based on this revision, the taxonomic list of echinoderms for Costa Rica is updated to 293 species, 152 genera, 75 families, 30 orders and 5 classes. The Pacific coast of Costa Rica has 153 species, followed by the Isla del Coco with 134 and the Caribbean coast with 65. Holothuria is the most diverse genus with 25 species.UCR::Vicerrectoría de Docencia::Ciencias Básicas::Facultad de Ciencias::Escuela de BiologíaUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigación en Ciencias del Mar y Limnología (CIMAR)UCR::Vicerrectoría de Investigación::Unidades de Investigación::Artes y Letras::Museo de la Universidad de Costa Ric

Affective pictures processing is reflected by an increased long-distance EEG connectivity

WOS: 000405704300004PubMed ID: 28761555Analysis of affective picture processing by means of EEG has invaded the literature. The methodology of event-related EEG coherence is one of the essential methods used to analyze functional connectivity. The aims of the present study are to find out the long range EEG connectivity changes in perception of different affective pictures and analyze gender differences in these long range connected networks. EEGs of 28 healthy subjects (14 female) were recorded at 32 locations. The participants passively viewed emotional pictures (IAPS, unpleasant, pleasant, neutral). The long-distance intra-hemispheric event-related coherence was analyzed for delta (1-3.5 Hz), theta (4-7.5 Hz), and alpha (8-13 Hz) frequency ranges for F-3-T-7, F-4-T-8, F-3-TP7, F-4-TP8, F-3-P-3, F-4-P-4, F-3-O-1, F-4-O-2, C-3-O-1, C-4-O-2 electrode pairs. Unpleasant pictures elicited significantly higher delta coherence values than neutral pictures (p < 0.05), over fronto-parietal, fronto-occipital, and centro-occipital electrode pairs. Furthermore, unpleasant pictures elicited higher theta coherence values than pleasant (p < 0.05) and neutral pictures (p < 0.05). The present study showed that female subjects had higher delta (p < 0.05) and theta (p < 0.05) coherence values than male subjects. This difference was observed more for emotional pictures than for neutral pictures. This study showed that the brain connectivity was higher during emotional pictures than neutral pictures. Females had higher connectivity between different parts of the brain than males during emotional processes. According to these results, we may comment that increased valence and arousal caused increased brain activity. It seems that not just single sources but functional networks were also activated during perception of emotional pictures

Improving cross-subject classification performance of motor imagery signals: a data augmentation-focused deep learning framework

Motor imagery brain-computer interfaces (MI-BCIs) have gained a lot of attention in recent years thanks to their potential to enhance rehabilitation and control of prosthetic devices for individuals with motor disabilities. However, accurate classification of motor imagery signals remains a challenging task due to the high inter-subject variability and non-stationarity in the electroencephalogram (EEG) data. In the context of MI-BCIs, with limited data availability, the acquisition of EEG data can be difficult. In this study, several data augmentation techniques have been compared with the proposed data augmentation technique adaptive cross-subject segment replacement (ACSSR). This technique, in conjunction with the proposed deep learning framework, allows for a combination of similar subject pairs to take advantage of one another and boost the classification performance of MI-BCIs. The proposed framework features a multi-domain feature extractor based on common spatial patterns with a sliding window and a parallel two-branch convolutional neural network. The performance of the proposed methodology has been evaluated on the multi-class BCI Competition IV Dataset 2a through repeated 10-fold cross-validation. Experimental results indicated that the implementation of the ACSSR method (80.47%) in the proposed framework has led to a considerable improvement in the classification performance compared to the classification without data augmentation (77.63%), and other fundamental data augmentation techniques used in the literature. The study contributes to the advancements for the development of effective MI-BCIs by showcasing the ability of the ACSSR method to address the challenges in motor imagery signal classification tasks

Neurological complications and effects of COVID-19: Symptoms and conceivable mechanisms

A novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first identified in December 2019 in Wuhan, China. The new coronavirus disease (COVID-19) was declared a global pandemic by the World Health Organization (WHO) in March 2020. SARS-CoV-2 can invade the nervous system aside from infecting the respiratory system as its primary target. The most common nervous system symptoms of COVID-19 are stated as headache, myalgia, fatigue, nausea, vomiting, sudden and unexplained anosmia, and ageusia. More severe conditions such as encephalomyelitis, acute myelitis, thromboembolic events, ischemic stroke, intracerebral hemorrhage, Guillain-Barré-syndrome, Bell's palsy, rhabdomyolysis, and even coma have also been reported. Cohort studies revealed that neurological findings are associated with higher morbidity and mortality. The neurological symptoms and manifestations caused by SARS-CoV-2 and COVID-19 are examined and summarized in this article

A rare clinical association: Barth syndrome and cystic fibrosis

Barth syndrome (BS) is a rare X-linked recessive metabolic disorder characterized by cardiomyopathy, hypotonia, neutropenia, growth retardation and 3-methylglutaconic aciduria type II. Cystic fibrosis is a common autosomal recessive genetic disorder in Caucasians. Herein, we reported a rare clinical association in an infant diagnosed based on clinical and genetic analysis. A six-month old boy admitted with chronic steatorrhea. The diagnosis of cystic fibrosis was made after clinical and laboratory examinations. Fifteen days later, the patient was presented with restlessness and moaning. He had hypoglycemia and lactic acidosis. The patient died three hours after the admission. Pedigree analysis revealed similar sudden infant deaths in close relatives. Postmortem genetic analysis revealed the diagnosis of Barth syndrome. This is the first case of the association of Barth syndrome with cystic fibrosis. Our case reinforces the importance of pedigree analysis and postmortem examinations