Background and Objectives: Psychological strain is one of the prevalent problems in nursing profession, which can lead to unpleasant consequences; also, psychological empowerment is of great ...importance due to its effects on nursing professional practice. The present study was conducted with the aim of determining the correlation between psychological empowerment and its components with psychological strain in nurses. Methods: This descriptive - correlational study was performed on 308 nurses working in 6 educational hospitals of Qom city in 2017. Samples were selected through census method and according to the inclusion criteria. Data collection tools included a 12-question questionnaire (5 degrees scale) of Spreitzer's Psychological Empowerment, and a 10-question questionnaire (5 degrees scale) of Psychological Strain (Osipow). Results: The mean psychological empowerment was determined 3.90±0.61 and the mean amount of psychological strain was 2.48±0.85 .According to the results of regression analysis, among predictor variables (psychological empowerment components), autonomy and impact, were significant at the error level less than 0.05. Among them, the greatest influence of empowerment was related to the autonomy component, which inversely predicts psychological strain. Conclusion: The results of this study showed that empowering nurses as much as possible in clinical settings and in "autonomy" component of psychological empowerment components, can reduce their psychological strain. This issue reveals the need to pay attention to the planning in the field of empowerment of nurses in clinical settings.
Geotechnical data are one of the most prevalent data types in civil engineering projects. The majority of the civil engineering projects that are in use today are designed using site-specific ...geotechnical data. The usage of geotechnical data is not limited to construction projects. This data is used in a wide range of applications, including seismic hazard analysis, planning and zoning studies, risk analysis and other infrastructure development projects. Demand for geotechnical data in these types of applications has increased in the past few decades, due to proliferation of geographic information systems (GIS) and a variety of applications that take advantage of GIS and spatial data. Considering the widespread collection and usage of geotechnical data in various disciplines, one might expect that data are readily available for most developed areas. However, unlike other types of spatial data that are available in spatial data infrastructures (SDI), geotechnical data is often managed using traditional and ineffective methods. Consequently, for a lot of projects it is difficult to find and acquire these data. This issue is frequently encountered in civil engineering projects, and more importantly, in large-scale multi-disciplinary studies that need large volumes of geotechnical data. In order to address this problem, the current methods used for management, archiving and distribution of geotechnical data need to be improved upon. The most viable solution is to leverage the existing information technology infrastructure and adopt methods that are already in use for other types of spatial data. These technologies include geography markup language (GML), spatial databases and Web services developed for spatial data exchange. Following this concept, in the subject dissertation development of a spatial data model for geotechnical data is discussed. The discussion includes an overview of the geotechnical data collection, processing and current methods used to archive and exchange data. The proprietary software and data formats that are used for geotechnical data exchange, including the association of geotechnical and geoenvironmental specialists (AGS) data format, are covered in this review. In addition, the current state of information technology for other types of spatial data is evaluated. This background study includes spatial databases, spatial data infrastructures and various standards that are adopted by the industry and regulating agencies for management and dissemination of spatial data. Based on this framework, a data model is proposed for integration of geotechnical data in SDIs. This data model uses the terminology of the AGS geotechnical data exchange format and combines it with a GML-conformant schema. GML is the industry-standard markup language for modeling spatial data for use in SDIs. The developed data model is compared with similar proposals from other research groups. The functionality of the data group is verified using several examples involving visualizing the geotechnical data and using it for analyses such as site response analysis and liquefaction hazard assessment. A case study is presented that demonstrates the potential benefits of these analysis scenarios in real-world studies. Finally, the achievements of the dissertation are summarized and suggestions are made in order to improve the results of the current study. Also, some related research topics are suggested to continue and further expand the concepts presented in this dissertation. The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.
COVID‐19: Neuroimaging Features of a Pandemic Ladopoulos, Theodoros; Zand, Ramin; Shahjouei, Shima ...
Journal of neuroimaging,
March/April 2021, Volume:
31, Issue:
2
Journal Article
Peer reviewed
Open access
ABSTRACT
BACKGROUND AND PURPOSE
The ongoing Coronavirus Disease 2019 (COVID‐19) pandemic is caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2). COVID‐19 is occasionally ...associated with manifold diseases of the central nervous system (CNS). We sought to present the neuroimaging features of such CNS involvement. In addition, we sought to identify typical neuroimaging patterns that could indicate possible COVID‐19‐associated neurological manifestations.
METHODS
In this systematic literature review, typical neuroimaging features of cerebrovascular diseases and inflammatory processes associated with COVID‐19 were analyzed. Reports presenting individual patient data were included in further quantitative analysis with descriptive statistics.
RESULTS
We identified 115 studies reporting a total of 954 COVID‐19 patients with associated neurological manifestations and neuroimaging alterations. A total of 95 (82.6%) of the identified studies were single case reports or case series, whereas 660 (69.2%) of the reported cases included individual information and were thus included in descriptive statistical analysis. Ischemia with neuroimaging patterns of large vessel occlusion event was revealed in 59.9% of ischemic stroke patients, whereas 69.2% of patients with intracerebral hemorrhage exhibited bleeding in a location that was not associated with hypertension. Callosal and/or juxtacortical location was identified in 58.7% of cerebral microbleed positive images. Features of hemorrhagic necrotizing encephalitis were detected in 28.8% of patients with meningo‐/encephalitis.
CONCLUSIONS
Manifold CNS involvement is increasingly reported in COVID‐19 patients. Typical and atypical neuroimaging features have been observed in some disease entities, so that familiarity with these imaging patterns appears reasonable and may assist clinicians in the differential diagnosis of COVID‐19 CNS manifestations.
, a subspecies of
, is a well-known eukaryotic probiotic with many benefits for human health. In the present study, a recombinant strain of
was prepared to use as a potential oral vaccine delivery ...vehicle. In this sense, a ura3 auxotroph strain of
CNCM I-745 (known as
HANSEN CBS 5926, Yomogi
) was generated using CRISPR/Cas9 methodology. Then a gene construct encoding a highly immunogenic protein, ovalbumin (OVA), was prepared and transformed into the
. To facilitate the transport of the recombinant immunogen across the intestinal barrier, a claudin-targeting sequence from
enterotoxin (CPE) was added to the C-terminus of the expression cassette. The recombinant
strain expressing the OVA-CPE fusion protein was then administered orally to a group of mice, and serum IgG and fecal IgA levels were evaluated by ELISA. Our results demonstrated that anti-OVA IgG in serum significantly increased in test group (
< 0.001) compared to control groups (receiving wild type
or PBS), and the fecal IgA titer was significantly higher in test group (
< 0.05) than control groups. In parallel, a recombinant
strain expressing the similar construct lacking C-terminal CPE was also administered orally. The result showed an increased level of serum IgG in group receiving yeasts expressing the CPE negative construct compared to control groups; however, the fecal IgA levels did not increase significantly. In conclusion, our findings indicated that the yeast
, as a delivery vehicle with possible immunomodulatory effects, and c-CPE, as a targeting tag, synergistically assist to stimulate systemic and local immunity. This proposed recombinant
system might be useful in the expression of other antigenic peptides, making it as a promising tool for oral delivery of vaccines or therapeutic proteins.
SARS-CoV-2 induced coagulopathy can lead to thrombotic complications such as stroke. Cerebral venous sinus thrombosis (CVST) is a less common type of stroke which might be triggered by COVID-19. We ...present a series of CVST cases with SARS-CoV-2 infection.
In a multinational retrospective study, we collected all cases of CVST in SARS-CoV-2 infected patients admitted to nine tertiary stroke centers from the beginning of the pandemic to June 30th, 2020. We compared the demographics, clinical and radiological characteristics, risk factors, and outcome of these patients with a control group of non-SARS-CoV-2 infected CVST patients in the same seasonal period of the years 2012–2016 from the country where the majority of cases were recruited.
A total of 13 patients fulfilled the inclusion criteria (62% women, mean age 50.9 ± 11.2 years). Six patients were discharged with good outcomes (mRS ≤ 2) and three patients died in hospital. Compared to the control group, the SARS-CoV-2 infected patients were significantly older (50.9 versus 36.7 years, p < 0.001), had a lower rate of identified CVST risk factors (23.1% versus 84.2%, p < 0.001), had more frequent cortical vein involvement (38.5% versus 10.5%, p: 0.025), and a non-significant higher rate of in-hospital mortality (23.1% versus 5.3%, p: 0.073).
CVST should be considered as potential comorbidity in SARS-CoV-2 infected patients presenting with neurological symptoms. Our data suggest that compared to non-SARS-CoV-2 infected patients, CVST occurs in older patients, with lower rates of known CVST risk factors and might lead to a poorer outcome in the SARS-CoV-2 infected group.
•Coagulopathy is a known feature of SARS-CoV-2 infection.•Only few cases of CVST associated with SARS-CoV-2 infection have been reported.•A series of 13 cases of CVST associated with SARS-CoV-2 has been described.•CVST patients with SARS-CoV-2 infection, were older and had a lower rate of identified CVST risk factors.•Cortical veins involvement and in-hospital mortality were more frequent in SARS-CoV-2 infected CVST patients.
SARS-CoV-2 infected patients are suggested to have a higher incidence of thrombotic events such as acute ischemic strokes (AIS). This study aimed at exploring vascular comorbidity patterns among ...SARS-CoV-2 infected patients with subsequent stroke. We also investigated whether the comorbidities and their frequencies under each subclass of TOAST criteria were similar to the AIS population studies prior to the pandemic.
This is a report from the Multinational COVID-19 Stroke Study Group. We present an original dataset of SASR-CoV-2 infected patients who had a subsequent stroke recorded through our multicenter prospective study. In addition, we built a dataset of previously reported patients by conducting a systematic literature review. We demonstrated distinct subgroups by clinical risk scoring models and unsupervised machine learning algorithms, including hierarchical K-Means (ML-K) and Spectral clustering (ML-S).
This study included 323 AIS patients from 71 centers in 17 countries from the original dataset and 145 patients reported in the literature. The unsupervised clustering methods suggest a distinct cohort of patients (ML-K: 36% and ML-S: 42%) with no or few comorbidities. These patients were more than 6 years younger than other subgroups and more likely were men (ML-K: 59% and ML-S: 60%). The majority of patients in this subgroup suffered from an embolic-appearing stroke on imaging (ML-K: 83% and ML-S: 85%) and had about 50% risk of large vessel occlusions (ML-K: 50% and ML-S: 53%). In addition, there were two cohorts of patients with large-artery atherosclerosis (ML-K: 30% and ML-S: 43% of patients) and cardioembolic strokes (ML-K: 34% and ML-S: 15%) with consistent comorbidity and imaging patterns. Binominal logistic regression demonstrated that ischemic heart disease (odds ratio (OR), 4.9; 95% confidence interval (CI), 1.6-14.7), atrial fibrillation (OR, 14.0; 95% CI, 4.8-40.8), and active neoplasm (OR, 7.1; 95% CI, 1.4-36.2) were associated with cardioembolic stroke.
Although a cohort of young and healthy men with cardioembolic and large vessel occlusions can be distinguished using both clinical sub-grouping and unsupervised clustering, stroke in other patients may be explained based on the existing comorbidities.
Acute kidney injury (AKI) is a common problem in critically ill patients and is independently associated with increased morbidity and mortality. Recently, serum cystatin C has been shown to be ...superior to creatinine in early detection of renal function impairment. We compared estimated GFR based on serum cystatin C with estimated GFR based on serum creatinine for early detection of renal dysfunction according to the RIFLE criteria.
During 9 months, three hundred post trauma patients that were referred to the intensive care unit of a referral trauma hospital were recruited. Serum creatinine and serum cystatin C were measured and the estimated GFR within 24 hours of ICU admission was calculated. The primary outcome was the incidence of AKI according to the RIFLE criteria within 2(nd) to 7(th) day of admission.
During the first week of ICU admission, 21% of patients experienced AKI. After adjusting for major confounders, only the patients with first day's serum cystatin level higher than 0.78 mg/l were at higher risk of first week AKI (OR=6.14, 95% CI: 2.5-14.7, P<0.001). First day's serum cystatin C and injury severity score were the major risk factors for ICU mortality (OR=3.54, 95% CI: 1.7-7.4, P=0.001) and (OR=4.6, 95% CI: 1.5-14, P=0.007), respectively.
Within 24 hours after admission in ICU due to multiple trauma, high serum cystatin C level may have prognostic value in predicting early AKI and mortality during ICU admission. However, such correlation was not seen neither with creatinine nor cystatin C based GFR.
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