COVID-19 pandemic on coronary artery and cerebrovascular diseases in Southern Spain: interrupted time series analysis

Objective: Healthcare systems have been put under intense pressure by the COVID-19 pandemic, although some studies have shown a decline in hospital admissions for cardiovascular and cerebrovascular diseases during the first and second wave of the pandemic. In addition, studies analyzing gender and procedural differences are scarce. The present study aimed to determine the impact of the pandemic on hospital admissions for acute myocardial infarction (AMI) and cerebrovascular disease (CVD) in Andalusia (Spain) and analyzed differences by gender and by percutaneous coronary interventions performed. Patients and methods: An interrupted time series analysis of AMI and CVD hospital admissions in Andalusia (Spain) was carried out to measure the impact of the COVID-19 outbreak. AMI and CVD cases admitted daily in public hospitals of Andalusia between January 2018 and December 2020 were included. Results: During the pandemic, significant reductions in AMI [-19%; 95% confidence interval (CI): (-29%, -9%), p<0.001] and CVD [-17%; 95% CI: (-26%, -9%); p<0.01] in daily hospital admissions were observed. Differences were also produced according to the diagnosis (ST-Elevation Myocardial Infarction, Non-ST-Elevation Myocardial Infarction, other AMI and stroke), with a greater reduction in females for AMI and in males for CVD. Although there were more percutaneous coronary interventions during the pandemic, no significant reductions were observed. Conclusions: A decline in AMI and CVD daily hospital admissions during the first and second wave of COVID-19 pandemic was noted. Gender differences were observed, but no clear impact was observed in percutaneous interventions

Estimating confidence intervals in predicted responses for oscillatory biological models

BACKGROUND: The dynamics of gene regulation play a crucial role in a cellular control: allowing the cell to express the right proteins to meet changing needs. Some needs, such as correctly anticipating the day-night cycle, require complicated oscillatory features. In the analysis of gene regulatory networks, mathematical models are frequently used to understand how a network’s structure enables it to respond appropriately to external inputs. These models typically consist of a set of ordinary differential equations, describing a network of biochemical reactions, and unknown kinetic parameters, chosen such that the model best captures experimental data. However, since a model’s parameter values are uncertain, and since dynamic responses to inputs are highly parameter-dependent, it is difficult to assess the confidence associated with these in silico predictions. In particular, models with complex dynamics - such as oscillations - must be fit with computationally expensive global optimization routines, and cannot take advantage of existing measures of identifiability. Despite their difficulty to model mathematically, limit cycle oscillations play a key role in many biological processes, including cell cycling, metabolism, neuron firing, and circadian rhythms. RESULTS: In this study, we employ an efficient parameter estimation technique to enable a bootstrap uncertainty analysis for limit cycle models. Since the primary role of systems biology models is the insight they provide on responses to rate perturbations, we extend our uncertainty analysis to include first order sensitivity coefficients. Using a literature model of circadian rhythms, we show how predictive precision is degraded with decreasing sample points and increasing relative error. Additionally, we show how this method can be used for model discrimination by comparing the output identifiability of two candidate model structures to published literature data. CONCLUSIONS: Our method permits modellers of oscillatory systems to confidently show that a model’s dynamic characteristics follow directly from experimental data and model structure, relaxing assumptions on the particular parameters chosen. Ultimately, this work highlights the importance of continued collection of high-resolution data on gene and protein activity levels, as they allow the development of predictive mathematical models

Daylight Saving Time transitions and Cardiovascular Disease in Andalusia: Time Series Modeling and Analysis Using Visibility Graphs

The present study aimed to determine whether transitions both to and from daylight saving time (DST) led to an increase in the incidence of hospital admissions for major acute cardiovascular events (MACE). To support the analysis, natural visibility graphs (NVGs) were used with data from Andalusian public hospitals between 2009 and 2019. We calculated the incidence rates of hospital admissions for MACE, and specifically acute myocardial infarction and ischemic stroke during the 2 weeks leading up to, and 2 weeks after, the DST transition. NVG were applied to identify dynamic patterns. The study included 157 221 patients diagnosed with MACE, 71 992 with AMI (42 975 ST-elevation myocardial infarction (STEMI) and 26 752 non-ST-elevation myocardial infarction (NSTEMI)), and 51 420 with ischemic stroke. Observed/expected ratios shown an increased risk of AMI (1.06; 95% CI (1.00-1.11); P = .044), NSTEMI (1.12; 95% CI (1.02-1.22); P = .013), and acute coronary syndrome (1.05; 95% CI (1.00-1.10); P = .04) around the autumn DST. The NVG showed slight variations in the daily pattern of pre-DST and post-DST hospitalization admissions for all pathologies, but indicated that the increase in the incidence of hospital admissions after the DST is not sufficient to change the normal pattern significantly

Oleoresins from Capsicum spp.: Extraction Methods and Bioactivity

Capsicum spp. fruit is one of the most produced vegetables around the world, and it is consumed both as fresh vegetable and as a spice like a food additive for their characteristic red color and, in many cases, its pungency. In addition to its economic importance, the bioactivity of some important compounds such as capsaicinoids and carotenoids has promoted its research. The use of Capsicum oleoresins has been increased due to its advantages comparing with the traditional dry spice. These include obtaining higher quality products with the desired content of bioactive and flavored substances. The wide diversity of extraction methods including water extraction, organic solvent extraction, microwave-assisted extraction, and ultrasound assisted extraction as well as supercritical fluid extraction among others are discussed in the present review. Moreover, pretreatments such as chemical treatments, osmotic dehydration, sun and oven drying, and freeze-drying commonly used before the extraction are also presented. Due to its importance, Capsicum oleoresins produced with “green” solvents and the improvement of fractional extraction techniques that allow to obtain separately the various bioactive fractions will continue under research for further development