77 research outputs found
Structural assumptions underlying Fishbein's expectancy-value model of attitudes / 207
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Previous issue date:Includes bibliographical references (p. 13-14)
On a subspace of dual Zariski topology
No full textLet R be a commutative ring with identity and S pee (M) (resp. Min(M)) denote the set of all second (resp minimal) submodules of a non-zero R-module M. In this paper, we investigate several properties of the subspace topology on Min(M) induced by the dual Zariski on S pee(M) and determine some cases in which Min(M) is a max-spectral space
Experimental Research on Rubble Stone Masonry Walls
No full textThis research was developed in the Structural Laboratory of DEC-FCT/UNL, and the first author was supported by a scholarship through the Program 2/5.3/PRODEP/2002. The authors are grateful to the following industrial companies, which sponsored the majority of the experimental work: Grupo Edifer; Secil Outão, SA; Secil Martingança, Lda; Lusical, SA; Tecnasol-FGE, SA; Betopal, SA; Tecnima-Enerpac; Betão LIZ, SA; SPGO Lda; Cimianto, SA; Lusoceram, SA; Construtora do Infantado, Lda; Ensul, SA; SIKA Portugal, SA; Degussa -Bettor MBT, SA; Codimetal, SA; Vimaplás, Lda; Fradical, Lda; Dywidag, SA; Parapedra, Lda; Somator, Lda; J. Piteira, Lda and F. F. Caçador, Lda.authorsversionpublishe
Behçet’s Disease: A Comprehensive Review on the Role of HLA-B*51, Antigen Presentation, and Inflammatory Cascade
No full textBehçet’s disease (BD) is a complex, recurring inflammatory disorder with autoinflammatory and autoimmune components. This comprehensive review aims to explore BD’s pathogenesis, focusing on established genetic factors. Studies reveal that HLA-B*51 is the primary genetic risk factor, but non-HLA genes (ERAP1, IL-10, IL23R/IL-12RB2), as well as innate immunity genes (FUT2, MICA, TLRs), also contribute. Genome-wide studies emphasize the significance of ERAP1 and HLA-I epistasis. These variants influence antigen presentation, enzymatic activity, and HLA-I peptidomes, potentially leading to distinct autoimmune responses. We conducted a systematic review of the literature to identify studies exploring the association between HLA-B*51 and BD and further highlighted the roles of innate and adaptive immunity in BD. Dysregulations in Th1/Th2 and Th17/Th1 ratios, heightened clonal cytotoxic (CD8+) T cells, and reduced T regulatory cells characterize BD’s complex immune responses. Various immune cell types (neutrophils, γδ T cells, natural killer cells) further contribute by releasing cytokines (IL-17, IL-8, GM-CSF) that enhance neutrophil activation and mediate interactions between innate and adaptive immunity. In summary, this review advances our understanding of BD pathogenesis while acknowledging the research limitations. Further exploration of genetic interactions, immune dysregulation, and immune cell roles is crucial. Future studies may unveil novel diagnostic and therapeutic strategies, offering improved management for this complex disease
Rheumatoid Arthritis and Coexisting Parkinson's Disease a Report of 5 Cases
No full textIt is a commonly seen condition that the hand deformities which are seen in Parkinson disease (PD) mistakenly diagnosed as Rheumatoid arthritis (RA) so PD and RA have been associated with each other in the literature. Looking for the another view, in autoimmune diseases, such as RA, there is a chronically high concentrations of inflammatory mediators product over long periods of time and it has been hypothesized that these patients may be at increased risk for neurodegenerative diseases such as PD. To contribute to a few recently published reports, we describe five patients, over 65 years old, with a primary diagnosis of RA and coexisting PD and we discuss possible pathogenetic link between RA and PD. The coexisting cases in this report are most probably incidental but the prevalence of coexisting of RA and PD may be higher than that of regularly thought. The present report is draw attention to the possibility of coexisting and to keep in mind the possibility of developing neurodegenerative disorders due to the chronic inflammation in the course of patients with RA
COVID-19 mortality correlation with cloudiness, sunlight, latitude in European countries
No full text"COVID-19 mortality correlation with cloudiness, sunlight, latitude in European countries"
Dataset for preprint titled
"COVID-19 mortality: positive correlation with cloudiness but no correlation with sunlight and latitude in Europe"
https://doi.org/10.1101/2021.01.27.21250658
by SECIL OMER, ADRIAN IFTIME, VICTOR BURCEA
Corresponding author: A. Iftime, University of Medicine and Pharmacy "Carol Davila", Biophysics Department, 8 Blvd. Eroii Sanitari, 050474 Bucharest, Romania. Email address: adrian.iftime [at] umfcd.ro.
===========
Dataset file:
2.0.0.COVID-19_Mortality_Cloudiness_Insolation_EUROPE_March_December_2020.csv
Dataset graphical preview:
2.0.0.INFOGRAPHIC_CloudFraction_vs_COVID-19_mortality_Europe_March-December_2020.png
DATASET:
444 rows (records), with the following fields:
"Country" :
Country name; 37 European countries included.
"Date":
Date stamp at the collection time.
Data collection was performed in the last day of every month.
Date format: YYYY-MM-DD
"Month_Key" :
Date stamp at the collection time, formatted for easier monthly time series analysis.
Date format: YYYY-MM
"Month_Fct2020"
Date stamp at the collection time,formatted for easier graphing, as a string with names of the months
(in English).
"Deaths_per_1Mpop" :
Monthly mortality from COVID-19 raported in the country,
reported as number of COVID-19 deaths per 1 million population of the country,
in that particular month / country.
NB: it is reported as million population, not patients.
"LogDeaths_per_1Mpop" :
Log10 transformation of "Deaths_per_1Mpop"
"Insolation_Average" :
Insolation average (solar irradiance at ground level),
in that particular month / country.
It is expressed in Watt / square meter of the ground surface.
Data derived from data avaialble at NASA Langley Research Center, NASA’s Earth Observatory,
CERES / FLASHFlux team, 2020,
https://neo.gsfc.nasa.gov/view.php?datasetId=CERES_INSOL_M
(old link: https://neo.sci.gsfc.nasa.gov/view.php?datasetId=CERES_INSOL_M )
"Cloud_Fraction" :
Cloudiness (also known as cloud fraction, cloud cover, cloud amount or sky cover),
as decimal fraction of the sky obscured by clouds,
in that particular month / country.
Data derived from NASA Goddard Space Flight Center, NASA’s Earth Observatory,
MODIS Atmosphere Science Team, 2020,
https://neo.gsfc.nasa.gov/view.php?datasetId=MODAL2_M_CLD_FR
(old link: https://neo.sci.gsfc.nasa.gov/view.php?datasetId=MODAL2_M_CLD_FR )
"CENTR_latitude" and
"CENTR_longitude" :
Latitude and Longitude of the country centroid, for each country.
Data derived from Google LLC, "Dataset publishing language: country centroids",
https://developers.google.com/public-data/docs/canonical/countries_csv
NOTE: This is identical in every month (obviuously);
it is redundantly included for easier monthly sectional analysis of the data.
===========
Versioning of the dataset:
MAJOR: changes yearly; 1 = 2020
MINOR: changes if new monthly data is added in that particular year.
PATCH: Changes only if errors or minor edits were performed.
===========
CHANGELOG:
Version 2.0.0.COVID-19_Mortality_Cloudiness_Insolation_EUROPE_March_December_2020.csv
- CERES/FLASHFLUX data for August-December 2020 became available at new links at nasa.gov
- These data were gathered, analyzed and introduced in this dataset (2.0.0).
- updated links for CERES/FLASHFLUX and MODIS dataset
- added DOI link for preprint
- minor edits on text.
-Dataset file source for this version (internal analysis source file):
db_covid_all-ANALYSIS.2020-all-year_versiunea18d.csv
Version 1.0.0.COVID-19_Mortality_Cloudiness_Insolation_EUROPE_March_August_2020.csv
First version
Dataset file source for this version (internal analysis source file):
db_covid_all-ANALYSIS.2020-09-22_r10.cs
The Role of Patient Awareness and Knowledge in Developing Secondary Lymphedema After Breast and Gynecologic Cancer Surgery
No full textAyhan, Fikriye Figen/0000-0001-6906-991XBackground:This study aimed to compare the effects of awareness and knowledge on demographic and clinical factors in patients with breast cancer-related lymphedema (BCRL) and gynecologic cancer-related lymphedema (GCRL) in the oncologic rehabilitation setting. Methods and Results:A total of 506 female patients with upper or lower extremity lymphedema, were evaluated for lymphedema education in their postoperative period. Only 74 survivors (25%) with BCRL and 34 survivors (16.83%) with GCRL reported that they had received information about lymphedema by physicians/primary health care providers. In breast cancer survivors, the time of diagnostic delay for lymphedema was shorter in the informed group (p < 0.001), and there was a higher rate of cellulite attacks in uninformed patients (p = 0.021). Duration between surgery and lymphedema was longer and duration of diagnostic delay for lymphedema was shorter in the informed group than uninformed group in gynecologic cancer survivors (p = 0.019,p < 0.001). There was a higher rate of cellulite history in the uninformed patients than informed patients in gynecologic cancer survivors (p < 0.001). In gynecologic cancer survivors who were educated about lymphedema were at an earlier stage than noneducated patients (p = 0.024). Conclusion:The rate of awareness about lymphedema among patients with a history of surgery for gynecologic malignancies is lower compared with those for breast cancer. In female cancer survivors, awareness and knowledge about lymphedema may lead to a later onset of lymphedema, lower lymphedema grades, and fewer infection
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