Elasticity as a measure for online determination of remission points in ongoing epidemics.

The correct identification of change-points during ongoing outbreak investigations of infectious diseases is a matter of paramount importance in epidemiology, with major implications for the management of health care resources, public health and, as the COVID-19 pandemic has shown, social live. Onsets, peaks, and inflexion points are some of them. An onset is the moment when the epidemic starts. A "peak" indicates a moment at which the incorporated values, both before and after, are lower: a maximum. The inflexion points identify moments in which the rate of growth of the incorporation of new cases changes intensity. In this study, after interpreting the concept of elasticity of a random variable in an innovative way, we propose using it as a new simpler tool for anticipating epidemic remission change-points. In particular, we propose that the "remission point of change" will occur just at the instant when the speed in the accumulation of new cases is lower than the average speed of accumulation of cases up to that moment. This gives stability and robustness to the estimation in the event of possible remission variations. This descriptive measure, which is very easy to calculate and interpret, is revealed as informative and adequate, has the advantage of being distribution-free and can be estimated in real time, while the data is being collected. We use the 2014-2016 Western Africa Ebola virus epidemic to demonstrate this new approach. A couple of examples analyzing COVID-19 data are also included.

Decreased soluble IFN-ß receptor (sIFNAR2) in multiple sclerosis patients: A potential serum diagnostic biomarker.

BACKGROUND: The soluble isoform of the interferon-ß (IFN-ß) receptor (sIFNAR2) could modulate the activity of both endogenous and systemically administered IFN-ß. Previously, we described lower serum sIFNAR2 levels in untreated multiple sclerosis (MS) than in healthy controls (HCs). OBJECTIVE: To assess sIFNAR2 levels in a new cohort of MS patients and HCs, as well as in patients with clinically isolated syndrome (CIS) and with other inflammatory neurological disorders (OIND) and to assess its ability as a diagnostic biomarker. METHODS: The cross-sectional study included 148 MS (84 treatment naive and 64 treated), 87 CIS, 42 OIND, and 96 HCs. Longitudinal study included 94 MS pretreatment and after 1 year of therapy with IFN-ß, glatiramer acetate (GA), or natalizumab. sIFNAR2 serum levels were measured by a quantitative ELISA developed and validated in our laboratory. RESULTS: Naive MS and CIS patients showed significantly lower sIFNAR2 levels than HCs and OIND patients. The sensitivity and specificity to discriminate between MS and OIND, for a sIFNAR2 cutoff value of 122.02 ng/mL, were 70.1%, and 79.4%, respectively. sIFNAR2 increased significantly in IFN-ß-treated patients during the first year of therapy in contrast to GA- and natalizumab-treated patients who showed non-significant changes. CONCLUSION: The results suggest that sIFNAR2 could be a potential diagnostic biomarker for MS.

Involvement of IGF-II receptors in the antioxidant and neuroprotective effects of IGF-II on adult cortical neuronal cultures.

Insulin-like growth factor-II (IGF-II) is a naturally occurring peptide that exerts known pleiotropic effects ranging from metabolic modulation to cellular development, growth and survival. IGF-II triggers its actions by binding to and activating IGF (IGF-I and IGF-II) receptors. In this study, we assessed the neuroprotective effect of IGF-II on corticosterone-induced oxidative damage in adult cortical neuronal cultures and the role of IGF-II receptors in this effect. We provide evidence that treatment with IGF-II alleviates the glucocorticoid-induced toxicity to neuronal cultures, and this neuroprotective effect occurred due to a decrease in reactive oxygen species (ROS) production and a return of the antioxidant status to normal levels. IGF-II acts via not only the regulation of synthesis and/or activity of antioxidant enzymes, especially manganese superoxide dismutase, but also the restoration of mitochondrial cytochrome c oxidase activity and mitochondrial membrane potential. Although the antioxidant effect of IGF-I receptor activation has been widely reported, the involvement of the IGF-II receptor in these processes has not been clearly defined. The present report is the first evidence describing the involvement of IGF-II receptors in redox homeostasis. IGF-II may therefore contribute to the mechanisms of neuroprotection by acting as an antioxidant, reducing the neurodegeneration induced by oxidative insults. These results open the field to new pharmacological approaches to the treatment of diseases involving imbalanced redox homeostasis. In this study, we demonstrated that the antioxidant effect of IGF-II is at least partially mediated by IGF-II receptors.

A detailed database of sub-annual Spanish demographic statistics: 2005-2021.

The big data revolution has made it possible to collect, transmit and exploit huge amounts of data. The potential this offer for data analysis, however, clashes with the limitations imposed by laws on protection of personal data. This paper details a new database (DEMOSPA0521) made after processing and summarising more than 868 million demographic records from Spain, corresponding to a period of seventeen years (2005-2021). DEMOSPA0521 is composed of fifteen files: a group of (monthly and daily moving averages) datasets derived from population stocks and a collection of (daily, monthly and quarterly) datasets obtained from population, death, migration and birth statistics. The intra-annual distributions were calculated by exploiting both the temporal dimensions of age and calendar. DEMOSPA0521 also includes eleven R-Code files that enables the summary datasets to be derived from the raw microdata. DEMOSPA0521 can be used to confirm established results and employed to answer new research questions.

New molecular mechanisms to explain the neuroprotective effects of insulin-like growth factor II in a cellular model of Parkinson's disease.

INTRODUCTION: One of the hallmarks of Parkinsons Disease (PD) is oxidative distress, leading to mitochondrial dysfunction and neurodegeneration. Insulin-like growth factor II (IGF-II) has been proven to have antioxidant and neuroprotective effects in some neurodegenerative diseases, including PD. Consequently, there isgrowing interest in understanding the different mechanisms involved in the neuroprotective effect of this hormone. OBJECTIVES: To clarify the mechanism of action of IGF-II involved in the protective effect of this hormone. METHODS: The present study was carried out on a cellular model PD based on the incubation of dopaminergic cells (SN4741) in a culture with the toxic 1-methyl-4-phenylpyridinium (MPP+), in the presence of IGF-II. This model undertakes proteomic analyses in order to understand which molecular cell pathways might be involved in the neuroprotective effect of IGF-II. The most important proteins found in the proteomic study were tested by Western blot, colorimetric enzymatic activity assay and immunocytochemistry. Along with the proteomic study, mitochondrial morphology and function were also studied by transmission electron microscopy and oxygen consumption rate. The cell cycle was also analysed using 7AAd/BrdU staining, and flow cytometry. RESULTS: The results obtained indicate that MPP+, MPP++IGF-II treatment and IGF-II, when compared to control, modified the expression of 197, 246 proteins and 207 respectively. Some of these proteins were found to be involved in mitochondrial structure and function, and cell cycle regulation. Including IGF-II in the incubation medium prevents the cell damage induced by MPP+, recovering mitochondrial function and cell cycle dysregulation, and thereby decreasing apoptosis. CONCLUSION: IGF-II improves mitochondrial dynamics by promoting the association of Mitofilin with mitochondria, regaining function and redox homeostasis. It also rebalances the cell cycle, reducing the amount of apoptosis and cell death by the regulation of transcription factors, such as Checkpoint kinase 1.

Dataset of an actual life-risk insurance portfolio.

The foundation of the insurance business is built on data, the latter being one of the most valuable assets of any insurer. In fact, the risk structure to which an insurance company is exposed can actually be deduced by reviewing its customer database. It is not surprising, therefore, that access to real insurance datasets is very limited. This paper introduces and describes a dataset corresponding to a cross-section extraction of a real life-risk insurance portfolio. The dataset contains information on 76,102 policies and a total of 15 variables, including the capital at risk, the genders and dates of birth of the insured, and the effective and renewal dates of their policies. This dataset can be used both in teaching and in research. Combined with external life tables, the data available in the dataset can be used to build and compare pricing systems, to evaluate marketing strategies, in portfolio analysis, for calculations required by Solvency II regulations or for market benchmarking analysis. For example, the data from this dataset have been used in Pavía and Lledó [1] to compare the classic pricing methodology based on annual life tables with a new pricing methodology based on life tables with less than annual periodicity Pavía and Lledó [2], specifically quarterly, and in Lledó et al. to demonstrate the impact that using a new methodology to manage catastrophic risks in life insurance would have in terms of solvency capital requirements.

Dataset of the COVID-19 post-lockdown survey conducted by GIPEyOP in Spain.

2020 was a year marked by COVID-19, an infectious disease caused by the SARS-CoV-2 virus. Since the official beginning of the pandemic (March 2020), the authorities in Spain have been imposing significant restrictions (mainly on mobility) to stop the spread of the disease. In October 2020, the research group GIPEyOP (Elections and Public Opinion Research Group from the University of Valencia) conducted a survey to analyse whether the Spanish population has maintained or modified their habits and customs once the strict measures imposed in Spain during the onset of the pandemic were relaxed. This article describes the dataset collected, which is provided as an attachment. The dataset is made up of 196 variables, following elimination of those variables that could potentially identify the respondents to ensure their anonymity. Over 22 days, from September 23 to October 14, 2020, GIPEyOP collected 1755 valid responses. Respondents were contacted by chain or snowball sampling via email and social media and answered a self-administered web questionnaire consisting of 40 questions. amongst other uses, the resulting dataset can be (re)used to analyse whether the period of home confinement that Spaniards experienced between March and June 2020 has caused them to change their habits and customs, such as how often they do sport or go to bars or restaurants. The data also permit the study of whether there have been changes in the distribution of household chores by comparing three clearly differentiated moments (before confinement, during confinement and after confinement), what type of work (telework or face-to-face) the respondents would prefer or to know how the management of the crisis by govern authorities impacted on their votes preferences.

Dataset of the COVID-19 lockdown survey conducted by GIPEyOP in Spain.

This article introduces a dataset that captures relevant information about the living conditions, feelings, and habits of residents in Spain during ninety nine days of home confinement. This and other measures, imposed by the Government of Spain to mitigate the impact of the pandemic on the population, have brought with them important economic, labor, and social changes, which have been accompanied by various modifications (some only temporary) in Spaniards habits and behaviours. Data collection was carried out through the implementation of a questionnaire with 33 questions, which was sent by email to the collaborators of GIPEyOP (Elections and Public Opinion Research Group from the University of Valencia). These collaborators, in turn, forwarded the questionnaire to their acquaintances using email and social networks, mainly WhatsApp, Facebook, and Twitter. This non-probabilistic methodology has generated a total of 8387 valid responses. The resulting dataset may be (re)used by sociologists, political scientists, economists, or psychologists, among others, to identify how household chores were distributed among family members during the lockdown, what impact the confinement had on the labor performance of workers, the extent of teleworking and on some (physical and psychological) health issues linked to the confinement, including relationships with the place of residence during confinement. The data also provides information on how social networks spread geographically or what Spaniards thought of the management of the crisis by local, national, and international authorities.

Spanish electoral archive. SEA database.

This paper introduces the SEA database (acronym for Spanish Electoral Archive). SEA brings together the most complete public repository available to date on Spanish election outcomes. SEA holds all the results recorded from the electoral processes of General (1979-2019), Regional (1989-2021), Local (1979-2019) and European Parliamentary (1987-2019) elections held in Spain since the restoration of democracy in the late 70 s, in addition to other data sets with electoral content. The data are offered for free and is presented in a homogeneous and friendly format. Most of the databases are available for download with data from various electoral levels, including from the ballot box level. This paper details how the information is organized, what the main variables are on offer for each election, which processes were applied to the data for their homogenization, and discusses future areas of work. This data has many applications, for example, as inputs in election prediction models and in ecological inference algorithms, to study determinants of turnout or voting, or for defining marketing strategies.

Impact of Glucocorticoid on a Cellular Model of Parkinson's Disease: Oxidative Stress and Mitochondrial Function.

Stress seems to contribute to the neuropathology of Parkinson's disease (PD), possibly by dysregulation of the hypothalamic-pituitary-adrenal axis. Oxidative distress and mitochondrial dysfunction are key factors involved in the pathophysiology of PD and neuronal glucocorticoid-induced toxicity. Animal PD models have been generated to study the effects of hormonal stress, but no in vitro model has yet been developed. Our aim was to examine the impact of corticosterone (CORT) administration on a dopaminergic neuronal cell model of PD induced by the neurotoxin MPP+, as a new combined PD model based on the marker of endocrine response to stress, CORT, and oxidative-mitochondrial damage. We determined the impact of CORT, MPP+ and their co-incubation on reactive oxygen species production (O2-•), oxidative stress cellular markers (advanced-oxidation protein products and total antioxidant status), mitochondrial function (mitochondrial membrane potential and mitochondrial oxygen consumption rate) and neurodegeneration (Fluoro-Jade staining). Accordingly, the administration of MPP+ or CORT individually led to cell damage compared to controls (p < 0.05), as determined by several methods, whereas their co-incubation produced strong cell damage (p < 0.05). The combined model described here could be appropriate for investigating neuropathological hallmarks and for evaluating potential new therapeutic tools for PD patients suffering mild to moderate emotional stress.

Insulin-like Growth Factor II Prevents MPP+ and Glucocorticoid Mitochondrial-Oxidative and Neuronal Damage in Dopaminergic Neurons.

Stress seems to contribute to Parkinson's disease (PD) neuropathology, probably by dysregulation of the hypothalamic-pituitary-adrenal axis. Key factors in this pathophysiology are oxidative stress and mitochondrial dysfunction and neuronal glucocorticoid-induced toxicity. The insulin-like growth factor II (IGF-II), a pleiotropic hormone, has shown antioxidant and neuroprotective effects in some neurodegenerative disorders. Our aim was to examine the protective effect of IGF-II on a dopaminergic cellular combined model of PD and mild to moderate stress measuring oxidative stress parameters, mitochondrial and neuronal markers, and signalling pathways. IGF-II counteracts the mitochondrial-oxidative damage produced by the toxic synergistic effect of corticosterone and 1-methyl-4-phenylpyridinium, protecting dopaminergic neurons from death and neurodegeneration. IGF-II promotes PKC activation and nuclear factor (erythroid-derived 2)-like 2 antioxidant response in a glucocorticoid receptor-dependent pathway, preventing oxidative cell damage and maintaining mitochondrial function. Thus, IGF-II is a potential therapeutic tool for treatment and prevention of disease progression in PD patients suffering mild to moderate emotional stress.

Insulin-like growth factor II prevents oxidative and neuronal damage in cellular and mice models of Parkinson's disease.

Oxidative distress and mitochondrial dysfunction, are key factors involved in the pathophysiology of Parkinson's disease (PD). The pleiotropic hormone insulin-like growth factor II (IGF-II) has shown neuroprotective and antioxidant effects in some neurodegenerative diseases. In this work, we demonstrate the protective effect of IGF-II against the damage induced by 1-methyl-4-phenylpyridinium (MPP+) in neuronal dopaminergic cell cultures and a mouse model of progressive PD. In the neuronal model, IGF-II counteracts the oxidative distress produced by MPP + protecting dopaminergic neurons. Improved mitochondrial function, increased nuclear factor (erythroid-derived 2)-like2 (NRF2) nuclear translocation along with NRF2-dependent upregulation of antioxidative enzymes, and modulation of mammalian target of rapamycin (mTOR) signalling pathway were identified as mechanisms leading to neuroprotection and the survival of dopaminergic cells. The neuroprotective effect of IGF-II against MPP + -neurotoxicity on dopaminergic neurons depends on the specific IGF-II receptor (IGF-IIr). In the mouse model, IGF-II prevents behavioural dysfunction and dopaminergic nigrostriatal pathway degeneration and mitigates neuroinflammation induced by MPP+. Our work demonstrates that hampering oxidative stress and normalising mitochondrial function through the interaction of IGF-II with its specific IGF-IIr are neuroprotective in both neuronal and mouse models. Thus, the modulation of the IGF-II/IGF-IIr signalling pathway may be a useful therapeutic approach for the prevention and treatment of PD.

Assessing uncertainty of voter transitions estimated from aggregated data. Application to the 2017 French presidential election.

Inferring electoral individual behaviour from aggregated data is a very active research area, with ramifications in sociology and political science. A new approach based on linear programming is proposed to estimate voter transitions among parties (or candidates) between two elections. Compared to other linear and quadratic programming models previously published, our approach presents two important innovations. Firstly, it explicitly deals with new entries and exits in the election census without assuming unrealistic hypotheses, enabling a reasonable estimation of vote behaviour of young electors voting for the first time. Secondly, by exploiting the information contained in the model residuals, we develop a procedure to assess the uncertainty in the estimates. This significantly distinguishes our model from other published mathematical programming methods. The method is illustrated estimating the vote transfer matrix between the first and second rounds of the 2017 French presidential election and measuring its level of uncertainty. Likewise, compared to the most current alternatives based on ecological regression, our approach is considerably simpler and faster, and has provided reasonable results in all the actual elections to which it has been applied. Interested scholars can easily use our procedure with the aid of the R-function provided in the Supplemental Material.

Lent impact on the seasonality of conceptions during the twentieth century in Spain.

In European past populations, religious canons shaped the seasonal distribution of marriages and births by means of banning weddings and sexual intercourse during important holidays within the religious calendar. In contemporary secularized societies, this seasonal modeling has disappeared. A few pieces of evidence have been gathered to explain how they have disappeared. This paper analyzes the impact of Lent on the seasonality of conceptions during the last century in Spain. Data births of the entire Spanish population born in Spain and alive on the first of January 2003 (more than 39 million) containing the date, size of the municipality (six groups) are used. To analyze this seasonality, we have used time-series techniques. We have built an ad hoc temporal regressor starting from the number of days of Lent that corresponds to each month. We have also used regression models with autoregressive and moving average errors (regARIMA models) to estimate, by maximum likelihood, the set of model parameters. The paper gathers new evidences about the importance of religion on the preproduction of Spanish population until very recently. They show that during the twentieth century, in Spain, there were a significant decrease in conceptions during Lent and a significant rebound after this period. We note that this previous effect disappeared in 1975-1980, when both democracy and the contraception revolution began in Spain. After this period, the seasonality of birth in general disappears.

Data from the GIPEyOP online election poll for the 2015 Spanish General election.

The general elections of 2015 in Spain took place in the middle of the Great Recession after several years of austerity economic policies. This election caused a political earthquake that shook the Spanish party system. During the campaign of that election, GIPEyOP (Elections and Public Opinion Research Group from University of Valencia) conducted a survey to collect relevant data about the electorate beliefs, intentions and motivations. This article describes the data set attained, which comprises 71 variables after removing, to ensure full anonymity, those variables that would potentially allow respondents to be identified. Respondents answered a self-administered online questionnaire and were recruited using chain sampling. A total of 14,261 valid observations were collected between 27th November and 18th December 2015. GIPEyOP employed the data collected up to 14th December to deliver a prediction of the election outcomes during that election campaign. Among other issues, this data set may be reused to assess theories of expectations' formation, to spot how social networks spread geographically and to measure gender, age and education technological gap of the Spanish population.

Neuronal Metabolism and Neuroprotection: Neuroprotective Effect of Fingolimod on Menadione-Induced Mitochondrial Damage.

Imbalance in the oxidative status in neurons, along with mitochondrial damage, are common characteristics in some neurodegenerative diseases. The maintenance in energy production is crucial to face and recover from oxidative damage, and the preservation of different sources of energy production is essential to preserve neuronal function. Fingolimod phosphate is a drug with neuroprotective and antioxidant actions, used in the treatment of multiple sclerosis. This work was performed in a model of oxidative damage on neuronal cell cultures exposed to menadione in the presence or absence of fingolimod phosphate. We studied the mitochondrial function, antioxidant enzymes, protein nitrosylation, and several pathways related with glucose metabolism and glycolytic and pentose phosphate in neuronal cells cultures. Our results showed that menadione produces a decrease in mitochondrial function, an imbalance in antioxidant enzymes, and an increase in nitrosylated proteins with a decrease in glycolysis and glucose-6-phosphate dehydrogenase. All these effects were counteracted when fingolimod phosphate was present in the incubation media. These effects were mediated, at least in part, by the interaction of this drug with its specific S1P receptors. These actions would make this drug a potential tool in the treatment of neurodegenerative processes, either to slow progression or alleviate symptoms.

Antiviral, Immunomodulatory and Antiproliferative Activities of Recombinant Soluble IFNAR2 without IFN-ß Mediation.

Soluble receptors of cytokines are able to modify cytokine activities and therefore the immune system, and some have intrinsic biological activities without mediation from their cytokines. The soluble interferon beta (IFN-ß) receptor is generated through alternative splicing of IFNAR2 and has both agonist and antagonist properties for IFN-ß, but its role is unknown. We previously demonstrated that a recombinant human soluble IFN-ß receptor showed intrinsic therapeutic efficacy in a mouse model of multiple sclerosis. Here we evaluate the potential biological activities of recombinant sIFNAR2 without the mediation of IFN-ß in human cells. Recombinant sIFNAR2 down-regulated the production of IL-17 and IFN-É£ and reduced the cell proliferation rate. Moreover, it showed a strong antiviral activity, fully protecting the cell monolayer after being infected by the virus. Specific inhibitors completely abrogated the antiviral activity of IFN-ß, but not that of the recombinant sIFNAR2, and there was no activation of the JAK-STAT signaling pathway. Consequently, r-sIFNAR2 exerts immunomodulatory, antiproliferative and antiviral activities without IFN-ß mediation, and could be a promising treatment against viral infections and immune-mediated diseases.

Combining Benford's Law and machine learning to detect money laundering. An actual Spanish court case.

OBJECTIVES: This paper is based on the analysis of the database of operations from a macro-case on money laundering orchestrated between a core company and a group of its suppliers, 26 of which had already been identified by the police as fraudulent companies. In the face of a well-founded suspicion that more companies have perpetrated criminal acts and in order to make better use of what are very limited police resources, we aim to construct a tool to detect money laundering criminals. METHODS: We combine Benford's Law and machine learning algorithms (logistic regression, decision trees, neural networks, and random forests) to find patterns of money laundering criminals in the context of a real Spanish court case. RESULTS: After mapping each supplier's set of accounting data into a 21-dimensional space using Benford's Law and applying machine learning algorithms, additional companies that could merit further scrutiny are flagged up. CONCLUSIONS: A new tool to detect money laundering criminals is proposed in this paper. The tool is tested in the context of a real case.

A fast-track anaemia clinic in the Emergency Department: cost-analysis of intravenous iron administration for treating iron-deficiency anaemia.

BACKGROUND: A fast-track anaemia clinic (FTAC) for the management of moderate-to-severe iron-deficiency anaemia (IDA) was established in our Emergency Department in 2010. In this FTAC, the replacement of packed red cell transfusion by ferric carboxymaltose administration was proven to be safe and effective. The aim of this study was a cost-analysis of IDA management in the FTAC, comparing this management with the previous standard care pathway consisting of packed red cell transfusion, if needed, and referral to outpatient specialised care. MATERIALS AND METHODS: A cost study was performed for patients with IDA who were at risk of requiring transfusion (haemoglobin <9 g/dL) but did not require hospitalisation. Total IDA treatment costs in the FTAC were compared to those theoretically incurred if these patients had been managed using the standard care pathway. In addition, a sensitivity analysis considering variations of up to ±30% in ferric carboxymaltose and packed red cell acquisition costs was performed (49 possible scenarios). RESULTS: Between 2012 and 2015, 238 IDA patients were treated in the FTAC. The average treatment cost was € 594±337/patient in the FTAC group and € 672±301/patient in the standard care pathway group, with a saving of € 78±28/patient (95% CI, 22-133; p<0.001). The sensitivity analysis showed that IDA treatment costs in the FTAC (€ 480-722/patient), compared with those of the standard care pathway (€ 550-794/patient), resulted in significant cost-savings for all studied scenarios (€ 51-104/patient; p<0.005). DISCUSSION: The administration of ferric carboxymaltose for IDA management in a FTAC may be cost-saving compared with the standard care pathway.