Estimation of cut-off points under complex-sampling design data

In the context of logistic regression models, a cut-off point is usually selected to dichotomize the estimated predicted probabilities based on the model. The techniques proposed to estimate optimal cut-off points in the literature, are commonly developed to be applied in simple random samples and their applicability to complex sampling designs could be limited. Therefore, in this work we propose a methodology to incorporate sampling weights in the estimation process of the optimal cut-off points, and we evaluate its performance using a real data-based simulation study. The results suggest the convenience of considering sampling weights for estimating optimal cut-off points.IT1294-19 BERC 2018-2021 KK-2020/00049 PIF18/21

Variable selection with LASSO regression for complex survey data

Variable selection is an important step to end up with good prediction models. LASSO regression models are one of the most commonly used methods for this purpose, for which cross-validation is the most widely applied validation technique to choose the tuning parameter (λ). Validation techniques in a complex survey framework are closely related to “replicate weights”. However, to our knowledge, they have never been used in a LASSO regression context. Applying LASSO regression models to complex survey data could be challenging. The goal of this paper is two-fold. On the one hand, we analyze the performance of replicate weights methods to select the tuning parameter for fitting LASSO regression models to complex survey data. On the other hand, we propose new replicate weights methods for the same purpose. In particular, we propose a new design-based cross-validation method as a combination of the traditional cross-validation and replicate weights. The performance of all these methods has been analyzed and compared by means of an extensive simulation study to the traditional cross-validation technique to select the tuning parameter for LASSO regression models. The results suggest a considerable improvement when the new proposal design-based cross-validation is used instead of the traditional crossvalidation.IT1456-22 PIF18/21

Acute toxicity, bioaccumulation and effects of dietary 1 transfer of silver from brine 2 shrimps exposed to PVP/PEI-coated silver nanoparticles to zebrafish

The extensive use and release to the aquatic environment of silver nanoparticles (NPs) could lead to their incorporation into the food web. Brine shrimp larvae of 24 h showed low sensitivity to the exposure to PVP/PEI-coated Ag NPs (5 nm), with EC50 values at 24 h of 19.63 mg Ag L-1, but they significantly accumulated silver after 24 h of exposure to 100 μg L-1 of Ag NPs. Thus, to assess bioaccumulation and effects of silver transferred by the diet in zebrafish, brine shrimp larvae were exposed to 100 ng L-1 of Ag NPs as an environmentally relevant concentration or to 100 μg L-1 as a potentially effective concentration and used to feed zebrafish for 21 days. Autometallography revealed a dose- and time-dependent metal accumulation in the intestine and in the liver of zebrafish. Three-day feeding with brine shrimps exposed to 100 ng L-1 of Ag NPs was enough to impair fish health as reflected by the significant reduction of lysosomal membrane stability and the presence of vacuolization and necrosis in the liver. However, dietary exposure to 100 μg L-1 of Ag NPs for 3 days did not significantly alter gene transcription levels, neither in the liver nor in the intestine. After 21 days, biological processes such as lipid transport and localization, cellular response to chemical stimulus and response to xenobiotic stimulus were significantly altered in the liver. Overall, these results indicate an effective dietary transfer of silver and point out to liver as the main target organ for Ag NP toxicity in zebrafish after dietary exposure.MINECO (NanoSilverOmicsproject- MAT2012-39372) Basque Government (consolidated research groups IT810-13 and IT620-13; Saiotek S-PE13UN142) University of the Basque Country (UFIs 11/37 and 11/52)

The diagnosis of the culture’s crisis in Spain: from public cuts to the systemic crisis

Since its invention in the fifties, cultural policy has been subject of analysis and reflection by Social Sciences. However, Spain, due to Franco period, has a number of distinguishing features as compared to Western European democracies. With the restoration of democracy, Spain acquires the dominant paradigm of a democratic cultural policy based on freedom, pluralism and the right to culture. However, after decades of democratic governments, diagnosis of cultural policy in Spain shows signs of systemic crisis, added to the impact of the global financial crisis at the beginning of the XXI century. In this context, scholars, using the Delphi method along with secondary sources, identify a set of social discourses and narratives that seem to function as solving cognitive resources in the artistic and cultural sphere and which, because of their empirical contrast, are not free of contradictions and aporiae.</p

COPD classification models and mortality prediction capacity

Our aim was to assess the impact of comorbidities on existing COPD prognosis scores. Patients and methods: A total of 543 patients with COPD (FEV1 < 80% and FEV1/ FVC <70%) were included between January 2003 and January 2004. Patients were stable for at least 6 weeks before inclusion and were followed for 5 years without any intervention by the research team. Comorbidities and causes of death were established from medical reports or information from primary care medical records. The GOLD system and the body mass index, obstruction, dyspnea and exercise (BODE) index were used for COPD classification. Patients were also classified into four clusters depending on the respiratory disease and comorbidities. Cluster analysis was performed by combining multiple correspondence analyses and automatic classification. Receiver operating characteristic curves and the area under the curve (AUC) were calculated for each model, and the DeLong test was used to evaluate differences between AUCs. Improvement in prediction ability was analyzed by the DeLong test, category-free net reclassification improvement and the integrated discrimination index. Results: Among the 543 patients enrolled, 521 (96%) were male, with a mean age of 68 years, mean body mass index 28.3 and mean FEV1% 55%. A total of 167 patients died during the study follow-up. Comorbidities were prevalent in our cohort, with a mean Charlson index of 2.4. The most prevalent comorbidities were hypertension, diabetes mellitus and cardiovascular diseases. On comparing the BODE index, GOLDABCD, GOLD2017 and cluster analysis for pre-dicting mortality, cluster system was found to be superior compared with GOLD2017 (0.654 vs 0.722, P=0.006), without significant differences between other classification models. When cardiovascular comorbidities and chronic renal failure were added to the existing scores, their prognostic capacity was statistically superior (P<0.001). Conclusion: Comorbidities should be taken into account in COPD management scores due to their prevalence and impact on mortalit

Chronic obstructive pulmonary disease subtypes. transitions over time

Background Although subtypes of chronic obstructive pulmonary disease are recognized, it is unknown what happens to these subtypes over time. Our objectives were to assess the stability of cluster-based subtypes in patients with stable disease and explore changes in clusters over 1 year. Methods Multiple correspondence and cluster analysis were used to evaluate data collected from 543 stable patients included consecutively from 5 respiratory outpatient clinics. Results Four subtypes were identified. Three of them, A, B, and C, had marked respiratory profiles with a continuum in severity of several variables, while the fourth, subtype D, had a more systemic profile with intermediate respiratory disease severity. Subtype A was associated with less dyspnea, better health-related quality of life and lower Charlson comorbidity scores, and subtype C with the most severe dyspnea, and poorer pulmonary function and quality of life, while subtype B was between subtypes A and C. Subtype D had higher rates of hospitalization the previous year, and comorbidities. After 1 year, all clusters remained stable. Generally, patients continued in the same subtype but 28% migrated to another cluster. Together with movement across clusters, patients showed changes in certain characteristics (especially exercise capacity, some variables of pulmonary function and physical activity) and changes in outcomes (quality of life, hospitalization and mortality) depending on the new cluster they belonged to Conclusions Chronic obstructive pulmonary disease clusters remained stable over 1 year. Most patients stayed in their initial subtype cluster, but some moved to another subtype and accordingly had different outcomes

Changes in Biomarkers of Redox Status in Saliva of Pigs after an Experimental Sepsis Induction

Saliva from pigs is gaining attention as an easy sample to obtain, being a source of biomarkers that can provide information on animal health and welfare. This study aimed to evaluate the changes that can occur in salivary biomarkers of the redox status of pigs with an experimentally induced sepsis. For that, the cupric reducing antioxidant capacity (CUPRAC), ferric reducing ability of saliva (FRAS), Trolox equivalent antioxidant capacity (TEAC), advanced oxidation protein products (AOPP), ferrous oxidation-xylenol orange (FOX), peroxide activity (POX-Act), and reactive oxygen-derived compounds (d-ROMs) were measured in the saliva of pigs with experimentally induced sepsis by endotoxin lipopolysaccharide (LPS), non-septic inflammation induced by turpentine, and in healthy individuals before and after 3 h, 6 h, 24 h, and 48 h. AOPP, POX-Act, and d-ROMs in the sepsis group were higher than in the control from 3 h to 24 h after the inoculation. CUPRAC, FRAS, and TEAC were higher in sepsis than the control group at 24 h. These changes were of higher magnitude than those that occurred in the turpentine group. In conclusion, our findings reveal that sepsis produces changes in salivary biomarkers of redox status, which opens the possibility of using them as potential biomarkers in this species

Extracting relevant predictive variables for COVID-19 severity prognosis: An exhaustive comparison of feature selection techniques

With the COVID-19 pandemic having caused unprecedented numbers of infections and deaths, large research efforts have been undertaken to increase our understanding of the disease and the factors which determine diverse clinical evolutions. Here we focused on a fully data-driven exploration regarding which factors (clinical or otherwise) were most informative for SARS-CoV-2 pneumonia severity prediction via machine learning (ML). In particular, feature selection techniques (FS), designed to reduce the dimensionality of data, allowed us to characterize which of our variables were the most useful for ML prognosis. We conducted a multi-centre clinical study, enrolling n=1548 patients hospitalized due to SARS-CoV-2 pneumonia: where 792, 238, and 598 patients experienced low, medium and high-severity evolutions, respectively. Up to 106 patient-specific clinical variables were collected at admission, although 14 of them had to be discarded for containing ⩾60% missing values. Alongside 7 socioeconomic attributes and 32 exposures to air pollution (chronic and acute), these became d=148 features after variable encoding. We addressed this ordinal classification problem both as a ML classification and regression task. Two imputation techniques for missing data were explored, along with a total of 166 unique FS algorithm configurations: 46 filters, 100 wrappers and 20 embeddeds. Of these, 21 setups achieved satisfactory bootstrap stability (⩾0.70) with reasonable computation times: 16 filters, 2 wrappers, and 3 embeddeds. The subsets of features selected by each technique showed modest Jaccard similarities across them. However, they consistently pointed out the importance of certain explanatory variables. Namely: patient’s C-reactive protein (CRP), pneumonia severity index (PSI), respiratory rate (RR) and oxygen levels –saturation SpO2, quotients SpO2/RR and arterial SatO2/FiO2 –, the neutrophil-to-lymphocyte ratio (NLR) –to certain extent, also neutrophil and lymphocyte counts separately–, lactate dehydrogenase (LDH), and procalcitonin (PCT) levels in blood. A remarkable agreement has been found a posteriori between our strategy and independent clinical research works investigating risk factors for COVID-19 severity. Hence, these findings stress the suitability of this type of fully data-driven approaches for knowledge extraction, as a complementary to clinical perspectives

Pathogenic Potential of Hic1-Expressing Cardiac Stromal Progenitors

The cardiac stroma contains multipotent mesenchymal progenitors. However, lineage relationships within cardiac stromal cells are poorly defined. Here, we identified heart-resident PDGFRa(+) SCA-1(+) cells as cardiac fibro/adipogenic progenitors (cFAPs) and show that they respond to ischemic damage by generating fibrogenic cells. Pharmacological blockade of this differentiation step with an anti-fibrotic tyrosine kinase inhibitor decreases post-myocardial infarction (post-MI) remodeling and leads to improvement in cardiac function. In the undamaged heart, activation of cFAPs through lineage-specific deletion of the gene encoding the quiescence-associated factor HIC1 reveals additional pathogenic potential, causing fibrofatty infiltration within the myocardium and driving major pathological features pathognomonic in arrhythmogenic cardiomyopathy (AC). In this regard, cFAPs contribute to multiple pathogenic cell types within cardiac tissue and therapeutic strategies aimed at modifying their activity are expected to have tremendous benefit for the treatment of diverse cardiac diseases