scholarly journals Habitat Characteristics as Potential Drivers of the Angiostrongylus daskalovi Infection in European Badger (Meles meles) Populations

Pathogens ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 715
Author(s):  
Eszter Nagy ◽  
Ildikó Benedek ◽  
Attila Zsolnai ◽  
Tibor Halász ◽  
Ágnes Csivincsik ◽  
...  
Keyword(s):  
Pcr Amplification ◽  
Binary Logistic Regression ◽  
Meles Meles ◽  
Habitat Characteristics ◽  
Binary Logistic Regression Analysis ◽  
Sequencing Analysis ◽  
Agglomerative Clustering ◽  
Intermediate Hosts ◽  
Rdna Sequencing ◽  
Hierarchical Agglomerative Clustering

From 2016 to 2020, an investigation was carried out to identify the rate of Angiostrongylus spp. infections in European badgers in Hungary. During the study, the hearts and lungs of 50 animals were dissected in order to collect adult worms, the morphometrical characteristics of which were used for species identification. PCR amplification and an 18S rDNA-sequencing analysis were also carried out. Global and local spatial autocorrelation methods were used to detect high-rated and low-rated infected animal clusters. We conducted a binary logistic regression analysis along with hierarchical agglomerative clustering to determine the relation between selected biotic and abiotic variables, and the prevalence of an A. daskalovi infection. We found a high prevalence (72%) and moderate mean intensity (14.1) of Angiostrongylus sp. infection. Morphology and sequencing revealed that all animals were infected by A. daskalovi. The results of both spatial autocorrelations suggested that the spatial distribution of infected badgers was more spatially clustered than random. The results of an analysis of the correlation between habitat characteristics and infection showed that the infected animals could be associated with dry and open landscape habitats without extended and connected canopy. It is suggested that the territorial behaviour of badgers and the landscape-directed aggregation of potential intermediate hosts might be the drivers of an A. daskalovi infection.

Differentiation and Characterization by Molecular Techniques of Bacillus cereus Group Isolates from Poto Poto and Dégué, Two Traditional Cereal-Based Fermented Foods of Burkina Faso and Republic of Congo

2007 ◽  
Vol 70 (5) ◽  
pp. 1165-1173 ◽  
Author(s):  
HIKMATE ABRIOUEL ◽  
NABIL BEN OMAR ◽  
ROSARIO LUCAS LÓPEZ ◽  
MAGDALENA MARTÍNEZ CAÑAMERO ◽  
ELENA ORTEGA ◽  
...  
Keyword(s):  
Melting Curve ◽  
Pcr Amplification ◽  
Curve Analysis ◽  
Melting Curve Analysis ◽  
Toxin Gene ◽  
Fermented Foods ◽  
Sequencing Analysis ◽  
16S Rdna Sequencing ◽  
Bacillus Cereus Group ◽  
Rdna Sequencing

Poto poto (a maize sourdough) and dégué (a pearl millet–based food) are two traditional African fermented foods. The molecular biology of toxigenic and pathogenic bacteria found in those foods is largely unknown. The purpose of this study was to study the phylogenetic relatedness and toxigenic potential of 26 Bacillus cereus group isolates from these traditional fermented foods. The relatedness of the isolates was evaluated with repetitive element sequence-based PCR (REP-PCR) and 16S rDNA sequencing analysis. A multiplex real-time PCR assay targeting the lef and capC genes of B. anthracis pXO1 and pXO2 plasmids and the sspE chromosomal gene of B. cereus and B. anthracis also was carried out. Melting curve analysis of the sspE amplification product was used to differentiate B. cereus from B. anthracis, and the presence of the B. cereus enterotoxin genes was determined with PCR amplification. Isolates had 15 different REP-PCR profiles, according to which they could be clustered into four groups. 16S rDNA sequencing analysis identified 23 isolates as B. cereus or B. anthracis and three isolates as B. cereus or Bacillus sp. Multiplex real-time PCR amplification indicated the absence of the lef and capC genes of B. anthracis pXO1 and pXO2 plasmids, and melting curve analysis revealed amplification of the 71-bp sspE product typical of B. cereus in all isolates instead of the 188-bp amplicon of B. anthracis, confirming the identity of these isolates as B. cereus. Four isolates had amylolytic activity. All isolates had lecithinase activity and beta-hemolytic activity. Enterotoxin production was detected in two isolates. The emetic toxin gene was not detected in any isolate. The nheB toxin gene was detected in 19 isolates by PCR amplification; one of these isolates also contained the hblD (L1) gene. The cytotoxin K cytK-1 gene was not detected, but the cytK-2 gene was clearly detected in six isolates.

Front-line thrombectomy for acute large-vessel occlusion with underlying severe intracranial stenosis: stent retriever versus contact aspiration

2020 ◽  
Vol 132 (4) ◽  
pp. 1202-1208 ◽  
Author(s):  
Dong-Hun Kang ◽  
Woong Yoon ◽  
Byung Hyun Baek ◽  
Seul Kee Kim ◽  
Yun Young Lee ◽  
...  
Keyword(s):  
Binary Logistic Regression ◽  
Stent Retriever ◽  
Large Vessel ◽  
Binary Logistic Regression Analysis ◽  
Large Vessel Occlusion ◽  
Front Line ◽  
Vessel Occlusion ◽  
Aspiration Thrombectomy ◽  
Atherosclerotic Stenosis ◽  
Antegrade Flow

OBJECTIVEThe optimal front-line thrombectomy choice for primary recanalization of a target artery remains unknown for patients with acute large-vessel occlusion (LVO) and an underlying intracranial atherosclerotic stenosis (ICAS). The authors aimed to compare procedural characteristics and outcomes between patients who received a stent-retriever thrombectomy (SRT) and patients who received a contact aspiration thrombectomy (CAT), as the front-line approach for treating LVO due to severe underlying ICAS.METHODSOne hundred thirty patients who presented with acute LVO and underlying severe ICAS at the occlusion site were included. Procedural characteristics and treatment outcomes were compared between patients treated with front-line SRT (n = 70) and those treated with front-line CAT (n = 60). The primary outcomes were the rate of switching to an alternative thrombectomy technique, time from groin puncture to initial reperfusion, and duration of the procedure. Initial reperfusion was defined as revealing the underlying culprit stenosis with an antegrade flow after thrombectomy.RESULTSThe rate of switching to an alternative thrombectomy after failure of the front-line technique was significantly higher in the CAT group than in the SRT group (40% vs 4.3%; OR 2.543, 95% CI 1.893–3.417, p < 0.001). The median time from puncture to initial reperfusion (17 vs 31 minutes, p < 0.001) and procedure duration (39 vs 75.5 minutes, p < 0.001) were significantly shorter in the SRT group than in the CAT group. In the binary logistic regression analysis, a longer time from puncture to initial reperfusion was an independent predictor of a 90-day poor (modified Rankin Scale score 3–6) functional outcome (per 1-minute increase; OR 1.029, 95% CI 1.008–1.050, p = 0.006).CONCLUSIONSThe authors’ results suggest that SRT may be more effective than CAT for identifying underlying culprit stenosis and therefore considered the optimal front-line thrombectomy technique in acute stroke patients with LVO and severe underlying ICAS.

scholarly journals How well do neurosurgeons predict survival in patients with high-grade glioma?

2021 ◽  
Author(s):  
Lisa Millgård Sagberg ◽  
Asgeir S. Jakola ◽  
Ingerid Reinertsen ◽  
Ole Solheim
Keyword(s):  
Median Survival ◽  
Survival Curve ◽  
Binary Logistic Regression ◽  
High Grade Glioma ◽  
Accurate Estimation ◽  
Binary Logistic Regression Analysis ◽  
High Grade ◽  
Clinical Prediction ◽  
Individual Level ◽  
Actual Survival

AbstractDue to the lack of reliable prognostic tools, prognostication and surgical decisions largely rely on the neurosurgeons’ clinical prediction skills. The aim of this study was to assess the accuracy of neurosurgeons’ prediction of survival in patients with high-grade glioma and explore factors possibly associated with accurate predictions. In a prospective single-center study, 199 patients who underwent surgery for high-grade glioma were included. After surgery, the operating surgeon predicted the patient’s survival using an ordinal prediction scale. A survival curve was used to visualize actual survival in groups based on this scale, and the accuracy of clinical prediction was assessed by comparing predicted and actual survival. To investigate factors possibly associated with accurate estimation, a binary logistic regression analysis was performed. The surgeons were able to differentiate between patients with different lengths of survival, and median survival fell within the predicted range in all groups with predicted survival < 24 months. In the group with predicted survival > 24 months, median survival was shorter than predicted. The overall accuracy of surgeons’ survival estimates was 41%, and over- and underestimations were done in 34% and 26%, respectively. Consultants were 3.4 times more likely to accurately predict survival compared to residents (p = 0.006). Our findings demonstrate that although especially experienced neurosurgeons have rather good predictive abilities when estimating survival in patients with high-grade glioma on the group level, they often miss on the individual level. Future prognostic tools should aim to beat the presented clinical prediction skills.

scholarly journals Clustering Techniques for Secondary Substations Siting

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1028
Author(s):  
Silvia Corigliano ◽  
Federico Rosato ◽  
Carla Ortiz Dominguez ◽  
Marco Merlo
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Universal Access ◽  
Distribution Networks ◽  
Industrialized Countries ◽  
Agglomerative Clustering ◽  
Clustering Techniques ◽  
Hierarchical Agglomerative Clustering ◽  
Efficient Planning ◽  
Target Set

The scientific community is active in developing new models and methods to help reach the ambitious target set by UN SDGs7: universal access to electricity by 2030. Efficient planning of distribution networks is a complex and multivariate task, which is usually split into multiple subproblems to reduce the number of variables. The present work addresses the problem of optimal secondary substation siting, by means of different clustering techniques. In contrast with the majority of approaches found in the literature, which are devoted to the planning of MV grids in already electrified urban areas, this work focuses on greenfield planning in rural areas. K-means algorithm, hierarchical agglomerative clustering, and a method based on optimal weighted tree partitioning are adapted to the problem and run on two real case studies, with different population densities. The algorithms are compared in terms of different indicators useful to assess the feasibility of the solutions found. The algorithms have proven to be effective in addressing some of the crucial aspects of substations siting and to constitute relevant improvements to the classic K-means approach found in the literature. However, it is found that it is very challenging to conjugate an acceptable geographical span of the area served by a single substation with a substation power high enough to justify the installation when the load density is very low. In other words, well known standards adopted in industrialized countries do not fit with developing countries’ requirements.

scholarly journals Identifying organ dysfunction trajectory-based subphenotypes in critically ill patients with COVID-19

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chang Su ◽  
Zhenxing Xu ◽  
Katherine Hoffman ◽  
Parag Goyal ◽  
Monika M. Safford ◽  
...  
Keyword(s):  
New York ◽  
Respiratory Failure ◽  
Sofa Score ◽  
Severity Of Illness ◽  
Agglomerative Clustering ◽  
Baseline Severity ◽  
Organ Systems ◽  
Hierarchical Agglomerative Clustering ◽  
Dynamic Time ◽  
Post Intubation

AbstractCOVID-19-associated respiratory failure offers the unprecedented opportunity to evaluate the differential host response to a uniform pathogenic insult. Understanding whether there are distinct subphenotypes of severe COVID-19 may offer insight into its pathophysiology. Sequential Organ Failure Assessment (SOFA) score is an objective and comprehensive measurement that measures dysfunction severity of six organ systems, i.e., cardiovascular, central nervous system, coagulation, liver, renal, and respiration. Our aim was to identify and characterize distinct subphenotypes of COVID-19 critical illness defined by the post-intubation trajectory of SOFA score. Intubated COVID-19 patients at two hospitals in New York city were leveraged as development and validation cohorts. Patients were grouped into mild, intermediate, and severe strata by their baseline post-intubation SOFA. Hierarchical agglomerative clustering was performed within each stratum to detect subphenotypes based on similarities amongst SOFA score trajectories evaluated by Dynamic Time Warping. Distinct worsening and recovering subphenotypes were identified within each stratum, which had distinct 7-day post-intubation SOFA progression trends. Patients in the worsening suphenotypes had a higher mortality than those in the recovering subphenotypes within each stratum (mild stratum, 29.7% vs. 10.3%, p = 0.033; intermediate stratum, 29.3% vs. 8.0%, p = 0.002; severe stratum, 53.7% vs. 22.2%, p < 0.001). Pathophysiologic biomarkers associated with progression were distinct at each stratum, including findings suggestive of inflammation in low baseline severity of illness versus hemophagocytic lymphohistiocytosis in higher baseline severity of illness. The findings suggest that there are clear worsening and recovering subphenotypes of COVID-19 respiratory failure after intubation, which are more predictive of outcomes than baseline severity of illness. Distinct progression biomarkers at differential baseline severity of illness suggests a heterogeneous pathobiology in the progression of COVID-19 respiratory failure.

scholarly journals Rwanda’s Land Policy Reform: Self-Employment Perspectives from a Case Study of Kimonyi Sector

Land ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 117
Author(s):  
Mireille Mizero ◽  
Aristide Maniriho ◽  
Bosco Bashangwa Mpozi ◽  
Antoine Karangwa ◽  
Philippe Burny ◽  
...  
Keyword(s):  
Rural Areas ◽  
Policy Reform ◽  
Binary Logistic Regression ◽  
Literacy Skills ◽  
Land Policy ◽  
Binary Logistic Regression Analysis ◽  
Self Employment ◽  
Expropriation Risk ◽  
Main Activity

Rwanda’s Land Policy Reform promotes agri-business and encourages self-employment. This paper aims to analyze the situation from a self-employment perspective when dealing with expropriation risk in rural areas. In this study, we conducted a structured survey addressed to 63 domestic units, complemented by focus groups of 47 participants from Kimonyi Sector. The binary logistic regression analysis revealed that having job alternatives, men heading domestic units, literacy skills in English, and owning land lease certificates (p < 0.05) are positively and significantly related to awareness of land expropriation risk. The decision of the head of the domestic unit to practice the main activity under self-employment status is positively influenced by owning a land lease certificate, number of plots, and French skills, while skills in English and a domestic unit’s size have a positive and significant influence on involvement in a second activity as self-employed. Information on expropriation risk has no significant effect on self-employment. The domestic unit survey revealed that 34.9% of the heads of domestic units only have one job, 47.6% have at least two jobs in their everyday life, 12.7% have a minimum of three jobs, and 4.8% are inactive. The focus group synthesis exposed the limits to self-employment ability and facilities.

scholarly journals Raised TSH is associated with endothelial dysfunction in Metabolic Syndrome: A case control study

2017 ◽  
Vol 55 (4) ◽  
pp. 212-221 ◽  
Author(s):  
Ashok Kumar Ahirwar ◽  
Archana Singh ◽  
Anju Jain ◽  
Surajeet Kumar Patra ◽  
Binita Goswami ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Endothelial Dysfunction ◽  
Subclinical Hypothyroidism ◽  
Serum Insulin ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Analysis ◽  
Healthy Controls ◽  
Healthy Control ◽  
Study Population ◽  
Serum Tsh

AbstractIntroduction. Endothelial dysfunction has been considered as one of the important factors in pathogenesis of Metabolic Syndrome (Met S). Subclinical hypothyroidism (SCH) has also been reported to be associated with Met S. The aim of our study is to evaluate the association of raised TSH with mediators of endothelial dysfunction in Met S with Subclinical hypothyroidism as compared to healthy controls.Methods. Study population consisted of 100 subjects, out of which 50 were cases of Met S and 50 were healthy controls. Met S group were further divided into two, based on the presence & absence of SCH. Serum insulin, T3, T4, TSH were measured by chemiluminescence based immunoassay (CLIA). Serum nitric oxide (NO) levels were measured by Modified Griess’s method and serum endothelin-1 (ET-1) levels were measured by ELISA.Results. Out of 50 cases of Met S, SCH was diagnosed in 22. The mean serum TSH levels were significantly higher in Met S cases as compared to healthy controls (5.7 ± 1.2 μIU/mL vs. 2.3 ± 1.6 μIU/mL, P <0.0001). Mean serum NO levels were significantly lower in Met S cases as compared to healthy control (15.4 ± 10 μM vs. 21 ± 10 μM, p = 0.009). Mean serum ET-1 levels were significantly higher in Met S cases as compared to healthy controls (2.68 ± 1.7 fmol/mL vs. 2.1 ± 0.84 fmol/mL, p = 0.011). On Pearson’s correlation analysis, TSH showed positive correlation with ET-1 (r = 0.341, p = 0.001) and negative correlation with NO (r = −0.331, p = 0.001). Binary logistic regression analysis showed that TSH, NO and ET-1 has significant odd’s ratio for predicting Met S.Conclusion. Met S cases were screened for thyroid abnormalities and found to have 44% of SCH along with co-existing endothelial dysfunction. Raised TSH in SCH could cause endothelial dysfunction which may lead to Met S and associated co-morbidities. Present study gives new insight in linking endothelial dysfunction and raised TSH in Met S. Therefore, Met S cases should be screened for SCH and treated appropriately to attenuate endothelial dysfunction and associated comorbidities in Met S.

scholarly journals Predicting Burn Mortality Using a Simple Novel Prediction Model

2021 ◽  
Author(s):  
Sneha Sharma ◽  
Raman Tandon
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Prediction Model ◽  
Receiver Operating Characteristic ◽  
Logistic Regression Analysis ◽  
Operating Characteristic ◽  
Binary Logistic Regression ◽  
Apache Ii ◽  
Apache Ii Score ◽  
Binary Logistic Regression Analysis

Abstract Background Prediction of outcome for burn patients allows appropriate allocation of resources and prognostication. There is a paucity of simple to use burn-specific mortality prediction models which consider both endogenous and exogenous factors. Our objective was to create such a model. Methods A prospective observational study was performed on consecutive eligible consenting burns patients. Demographic data, total burn surface area (TBSA), results of complete blood count, kidney function test, and arterial blood gas analysis were collected. The quantitative variables were compared using the unpaired student t-test/nonparametric Mann Whitney U-test. Qualitative variables were compared using the ⊠2-test/Fischer exact test. Binary logistic regression analysis was done and a logit score was derived and simplified. The discrimination of these models was tested using the receiver operating characteristic curve; calibration was checked using the Hosmer—Lemeshow goodness of fit statistic, and the probability of death calculated. Validation was done using the bootstrapping technique in 5,000 samples. A p-value of <0.05 was considered significant. Results On univariate analysis TBSA (p <0.001) and Acute Physiology and Chronic Health Evaluation II (APACHE II) score (p = 0.004) were found to be independent predictors of mortality. TBSA (odds ratio [OR] 1.094, 95% confidence interval [CI] 1.037–1.155, p = 0.001) and APACHE II (OR 1.166, 95% CI 1.034–1.313, p = 0.012) retained significance on binary logistic regression analysis. The prediction model devised performed well (area under the receiver operating characteristic 0.778, 95% CI 0.681–0.875). Conclusion The prediction of mortality can be done accurately at the bedside using TBSA and APACHE II score.

scholarly journals Clinical Markers May Identify Patients at Risk for Early Parkinson’s Disease Dementia: A Prospective Study

2021 ◽  
Vol 36 ◽  
pp. 153331752110213
Author(s):  
Anamaria Jurcau ◽  
Vharoon Sharma Nunkoo
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Analysis ◽  
Clinical Markers ◽  
Pearson Coefficient ◽  
Autonomic Dysfunctions ◽  
Patients At Risk ◽  
A Prospective Study ◽  
State Examination

Background: The study aims at identifying features predictive of early onset of dementia in Parkinson’s disease (PD). Methods: 103 non-demented PD patients were evaluated on various scales at baseline and 89 patients at 3-year follow-up. Results: By the end of the study 43.8% of patients developed dementia. The development of dementia was linked to the baseline Mini Mental State Examination score (Pearson coefficient r = .404, p = 0.013), the presence of autonomic dysfunctions (r = −.621, p < 0.001) and insomnia (r = −.526, p = 0.001). A binary logistic regression analysis showed that the development of dementia was correlated strongly with the presence of autonomic dysfunctions (95% CI 2.60 to 52.83, p < 0.001), and insomnia (95% CI 0.60 to 0.95, p = 0.017). Conclusion: Patients with signs of autonomic dysfunction and insomnia are at higher risk for developing dementia and deserve closer monitoring of cognitive symptoms.

Determinants of housing demand in the Erzurum province, Turkey

2014 ◽  
Vol 7 (4) ◽  
pp. 586-602 ◽  
Author(s):  
Erkan Oktay ◽  
Abdulkerim Karaaslan ◽  
Ömer Alkan ◽  
Ali Kemal Çelik
Keyword(s):  
Housing Prices ◽  
Binary Logistic Regression ◽  
Housing Demand ◽  
Outcome Variable ◽  
Binary Logistic Regression Analysis ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Content Type ◽  
Comprehensive Survey ◽  
Income Expectations

Purpose – The main aim of this study is to determine the factors that influence the housing demand of households in Erzurum, northeastern Turkey. Housing demand is generally affected by several factors including housing prices, individuals’ income, expectations and choices and so on, as a means of its demographic and socio-psychological contexts. Design/methodology/approach – A questionnaire-based cross-sectional survey was carried out, in which the outcome variable had binary responses such as whether to invest in housing or not. A binary logistic regression analysis was performed to estimate the underlying data. Findings – The questionnaire was conducted in 2,927 households living in Erzurum city center, and 47 per cent of the respondents claimed that they would consider investing in housing in the future. The estimation results reveal that demographic or socio-economic factors that may possibly influence housing demand of the respondents are as follows: household head’s and spouse’s occupation, monthly income, the number of individuals in the family and car ownership. Originality/value – This paper involves the most comprehensive survey addressing the housing demand in the East Anatolian Region, Turkey. Additionally, this paper aims to contribute to the existing housing literature through establishing the statistical analysis of housing demand in an unstudied territory of the world.

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