Global Self-Regulation of the Cellular Metabolic Structure

Different studies have shown that cellular enzymatic activities are able to self-organize spontaneously, forming a metabolic core of reactive processes that remain active under different growth conditions while the rest of the molecular catalytic reactions exhibit structural plasticity. This global cellular metabolic structure appears to be an intrinsic characteristic common to all cellular organisms. Recent work performed with dissipative metabolic networks has shown that the fundamental element for the spontaneous emergence of this global self-organized enzymatic structure could be the number of catalytic elements in the metabolic networks.This work was supported by the Spanish Ministry of Science and Education Grants with the projects MTM2007-62186 and MTM2005-01504 and by the Basque Government grants GIC07/151-IT-254-07 and IT-305-07. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewe

Cost-effectiveness analysis of vaccines for COVID-19 according to sex, comorbidity and socioeconomics status: a population study

Background and Objective Coronavirus disease 2019 (COVID-19) vaccines are extremely effective in preventing severe disease, but their real-world cost-effectiveness is still an open question. We present an analysis of the cost-effectiveness and economic impact of the initial phase of the COVID-19 vaccination rollout in the Basque Country, Spain. Methods To calculate costs and quality-adjusted life years for the entire population of the Basque Country, dynamic modelling and a real-world data analysis were combined. Data on COVID-19 infection outcomes (cases, hospitalisations, intensive care unit admissions and deaths) and population characteristics (age, sex, socioeconomic status and comorbidity) during the initial phase of the vaccination rollout, from January to June of 2021, were retrieved from the Basque Health Service database. The outcomes in the alternative scenario (without vaccination) were estimated with the dynamic model used to guide public health authority policies, from February to December 2020. Individual comorbidity-adjusted life expectancy and costs were estimated. Results By averting severe disease-related outcomes, COVID-19 vaccination resulted in monetary savings of €26.44 million for the first semester of 2021. The incremental cost-effectiveness ratio was €707/quality-adjusted life year considering official vaccine prices and dominant real prices. While the analysis by comorbidity showed that vaccines were considerably more cost effective in individuals with pre-existing health conditions, this benefit was lower in the low socioeconomic status group. Conclusions The incremental cost-effectiveness ratio of the vaccination programme justified the policy of prioritising high-comorbidity patients. The initial phase of COVID-19 vaccination was dominant from the perspective of the healthcare payer

NewsMeSH: a new classifier designed to annotate health news with MeSH headings

Motivation In the age of big data, the amount of scientific information available online dwarfs the ability of current tools to support researchers in locating and securing access to the necessary materials. Well-structured open data and the smart systems that make the appropriate use of it are invaluable and can help health researchers and professionals to find the appropriate information by, e.g., configuring the monitoring of information or refining a specific query on a disease. Methods We present an automated text classifier approach based on the MEDLINE/MeSH thesaurus, trained on the manual annotation of more than 26 million expert-annotated scientific abstracts. The classifier was developed tailor-fit to the public health and health research domain experts, in the light of their specific challenges and needs. We have applied the proposed methodology on three specific health domains: the Coronavirus, Mental Health and Diabetes, considering the pertinence of the first, and the known relations with the other two health topics. Results A classifier is trained on the MEDLINE dataset that can automatically annotate text, such as scientific articles, news articles or medical reports with relevant concepts from the MeSH thesaurus. Conclusions The proposed text classifier shows promising results in the evaluation of health-related news. The application of the developed classifier enables the exploration of news and extraction of health-related insights, based on the MeSH thesaurus, through a similar workflow as in the usage of PubMed, with which most health researchers are familiar

Effect of resveratrol on alcohol-induced mortality and liver lesions in mice

Es reproducción del documenteo publicado en http://dx.doi.org/10.1186/1471-230X-6-35Background Resveratrol is a polyphenol with important antiinflammatory and antioxidant properties. We investigated the effect of resveratrol on alcohol-induced mortality and liver lesions in mice. Methods Mice were randomly distributed into four groups (control, resveratrol-treated control, alcohol and resveratrol-treated alcohol). Chronic alcohol intoxication was induced by progressively administering alcohol in drinking water up to 40% v/v. The mice administered resveratrol received 10 mg/ml in drinking water. The animals had free access to standard diet. Blood levels were determined for transaminases, IL-1 and TNF-α. A histological evaluation was made of liver damage, and survival among the animals was recorded. Results Transaminase concentration was significantly higher in the alcohol group than in the rest of the groups (p < 0.05). IL-1 levels were significantly reduced in the alcohol plus resveratrol group compared with the alcohol group (p < 0.05). TNF-α was not detected in any group. Histologically, the liver lesions were more severe in the alcohol group, though no significant differences between groups were observed. Mortality in the alcohol group was 78% in the seventh week, versus 22% in the alcohol plus resveratrol group (p < 0.001). All mice in the alcohol group died before the ninth week. Conclusion The results obtained suggest that resveratrol reduces mortality and liver damage in mice

Is hospital discharge administrative data an appropriate source of information for cancer registries purposes? Some insights from four Spanish registries

<p>Abstract</p> <p>Background</p> <p>The use of hospital discharge administrative data (HDAD) has been recommended for automating, improving, even substituting, population-based cancer registries. The frequency of false positive and false negative cases recommends local validation.</p> <p>Methods</p> <p>The aim of this study was to detect newly diagnosed, false positive and false negative cases of cancer from hospital discharge claims, using four Spanish population-based cancer registries as the gold standard. Prostate cancer was used as a case study.</p> <p>Results</p> <p>A total of 2286 incident cases of prostate cancer registered in 2000 were used for validation. In the most sensitive algorithm (that using five diagnostic codes), estimates for Sensitivity ranged from 14.5% (CI95% 10.3-19.6) to 45.7% (CI95% 41.4-50.1). In the most predictive algorithm (that using five diagnostic and five surgical codes) Positive Predictive Value estimates ranged from 55.9% (CI95% 42.4-68.8) to 74.3% (CI95% 67.0-80.6). The most frequent reason for false positive cases was the number of prevalent cases inadequately considered as newly diagnosed cancers, ranging from 61.1% to 82.3% of false positive cases. The most frequent reason for false negative cases was related to the number of cases not attended in hospital settings. In this case, figures ranged from 34.4% to 69.7% of false negative cases, in the most predictive algorithm.</p> <p>Conclusions</p> <p>HDAD might be a helpful tool for cancer registries to reach their goals. The findings suggest that, for automating cancer registries, algorithms combining diagnoses and procedures are the best option. However, for cancer surveillance purposes, in those cancers like prostate cancer in which care is not only hospital-based, combining inpatient and outpatient information will be required.</p

Effect of resveratrol on alcohol-induced mortality and liver lesions in mice

BACKGROUND: Resveratrol is a polyphenol with important antiinflammatory and antioxidant properties. We investigated the effect of resveratrol on alcohol-induced mortality and liver lesions in mice. METHODS: Mice were randomly distributed into four groups (control, resveratrol-treated control, alcohol and resveratrol-treated alcohol). Chronic alcohol intoxication was induced by progressively administering alcohol in drinking water up to 40% v/v. The mice administered resveratrol received 10 mg/ml in drinking water. The animals had free access to standard diet. Blood levels were determined for transaminases, IL-1 and TNF-α. A histological evaluation was made of liver damage, and survival among the animals was recorded. RESULTS: Transaminase concentration was significantly higher in the alcohol group than in the rest of the groups (p < 0.05). IL-1 levels were significantly reduced in the alcohol plus resveratrol group compared with the alcohol group (p < 0.05). TNF-α was not detected in any group. Histologically, the liver lesions were more severe in the alcohol group, though no significant differences between groups were observed. Mortality in the alcohol group was 78% in the seventh week, versus 22% in the alcohol plus resveratrol group (p < 0.001). All mice in the alcohol group died before the ninth week. CONCLUSION: The results obtained suggest that resveratrol reduces mortality and liver damage in mice

Critical fluctuations in epidemic models explain COVID-19 post-lockdown dynamics

As the COVID-19 pandemic progressed, research on mathematical modeling became imperative and very influential to understand the epidemiological dynamics of disease spreading. The momentary reproduction ratio r(t) of an epidemic is used as a public health guiding tool to evaluate the course of the epidemic, with the evolution of r(t) being the reasoning behind tightening and relaxing control measures over time. Here we investigate critical fluctuations around the epidemiological threshold, resembling new waves, even when the community disease transmission rate β is not significantly changing. Without loss of generality, we use simple models that can be treated analytically and results are applied to more complex models describing COVID-19 epidemics. Our analysis shows that, rather than the supercritical regime (infectivity larger than a critical value, β> βc) leading to new exponential growth of infection, the subcritical regime (infectivity smaller than a critical value, β< βc) with small import is able to explain the dynamic behaviour of COVID-19 spreading after a lockdown lifting, with r(t) ≈ 1 hovering around its threshold value.Fil: Aguiar, Maíra. Basque Center for Applied Mathematics; España. Ikerbasque; España. Universita degli Studi di Trento; ItaliaFil: Van Dierdonck, Joseba Bidaurrazaga. Basque Health Department; EspañaFil: Mar, Javier. Debagoiena Integrated Healthcare Organisation; España. Biodonostia Health Research Institute; España. Kronikgune Institute for Health Services Research; EspañaFil: Cusimano, Nicole. Basque Center for Applied Mathematics; EspañaFil: Knopoff, Damián Alejandro. Basque Center for Applied Mathematics; España. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Anam, Vizda. Basque Center for Applied Mathematics; EspañaFil: Stollenwerk, Nico. Basque Center for Applied Mathematics; España. Universita degli Studi di Trento; Itali