Factors associated with exclusive breastfeeding at discharge during the COVID-19 pandemic in 17 WHO European Region countries

Both the consumption of breastmilk in infancy and a person’s season of birth influences his or her health, educational, professional, and behavioral outcomes. Further, season of birth effects differ by sex. However, current research, for the most part, neglects to examine if season of birth and breastfeeding are related. This paper examines the impact of sex-based variations in season of birth on breastfeeding likelihood and duration in the U.S. Using data from children born to female respondents of the National Longitudinal Survey of Youth 1979 (born between 1970 and 2012), this study examines with Probit, Negative Binomial, and Ordinary Least Squares (OLS) regressions if a child’s season of birth and sex are correlated with breastfeeding incidence and duration. The breastfeeding incidence and duration data are self-reported by the mother. Season of birth has a small but statistically significant impact on the incidence and duration of breastfeeding, which varies depending on the sex of the infant. Mothers giving birth to sons in the spring are 13.5% less likely to breastfeed than those giving birth to sons in the winter (with a p - value of 0.0269). Mothers with daughters born in the summer or fall (autumn) breastfeed slightly longer than mothers with daughters born in the spring. On average, mothers of summer-born daughters breastfeed 4.1% longer (with a 95% confidence interval of 0.3 - 7.8) and those with fall-born daughters 3.8% longer (with a 95% confidence interval of 0 - 7.5). Mothers giving birth to daughters in the spring are also significantly less likely to reach the breastfeeding six-week duration target (compared to fall and winter births) and the one-year duration target (compared to fall births). These findings suggest that the costs and benefits of breastfeeding an infant vary with the season of birth and the sex of the child. This finding could explain some of the season of birth effects previously identified in the literature. Further, policymakers seeking to increase breastfeeding rates should consider the reduced breastfeeding rates and durations for children born in the spring.     

An analytical study of the factors that influence COVID-19 spread

The outbreak of the coronavirus disease 2019 (COVID-19) continues to constitute an international public health emergency. Seasonality is a long-recognized attribute of many viral infections of humans. Nevertheless, the relationship between environmental factors and the spread of infection, particularly for person-to-person communicable diseases, remains poorly understood. This study explores the relationship between environmental factors and the incidence of COVID-19 in 188 countries with reported COVID-19 cases as of April 13, 2020. Here we show that COVID-19 growth rates peaked in temperate zones in the Northern Hemisphere during the outbreak period, while they were lower in tropical zones. The relationships between COVID-19 and environmental factors were resistant to the potentially confounding effects of air pollution, sea level, and population. To prove the effect of those factors, study, and analysis of the prevalence of COVID-19 in Italy, Spain, and China was undertaken. A fuzzy logic system was designed to predict the effects of that variables on the rate of viral spread of COVID-19.     

Spatially resolved IR microspectroscopy of single cells

Fourier transform IR (FTIR) microspectroscopy at a spatial resolution of 18 microm was used to study skin fibroblasts and giant sarcoma cells. Both cell lines were derived from the same patient; they were metabolically active and in the exponentially growing phase. The IR spectra were acquired for the nuclei and cytosol of untreated cells, cells washed with ethanol, and cells treated with RNase or DNase. A comparison of the spectra of the two cell lines yielded only insignificant spectral differences, indicating that IR spectroscopy monitors the overall cell activity rather than specific signs of cancer.     

Epidemiological determinants for the spread of COVID-19 in Riyadh Province of Saudi Arabia

Background and objectiveCoronavirus Disease 2019 (COVID-19) has affected millions of individuals all over the world. In addition to the patients' compelling indications, various sociodemographic characteristics were identified to influence infection complications. The purpose of this study was to assess the impact of the aforementioned parameters on the dissemination of COVID-19 among residents of Saudi Arabia's Riyadh region.Materials and methodsIn the Saudi Arabian province of Riyadh, a cross-sectional retrospective analysis of COVID-19 incidences, recoveries, and case-fatality ratio (CFR) was undertaken. The study was carried out by gathering daily COVID-19 records from the ministry of health's official websites between October 2020 and September 2021. The influencing factors were obtained from the statistical authority. Using the SPSS IBM 25 software, the data was examined. The association between demographic factors as well as the presence of comorbidity on the COVID-19 outcome was determined using Spearman's correlation and regression tests. P < 0.05 was considered to indicate the significance of the results.ResultsThe data from the study indicated that the highest number of COVID-19 cases were recorded in June 2021, and peak recovery was observed in July 2021. The CFR declined progressively from October 2020 to just over 1, even when the cases peaked. A significant (p < 0.05) correlation between diabetes and COVID-19 incidences was observed. The recovery rate had a significant (p < 0.05) association with the literacy rate and those aged 14–49 years old. Presences of co-morbidities such as Dyslipidemia, hypertension, diabetes, asthma, stroke and heart failure have negatively affected the recovery from COVID-19 in the population. The CFR is significantly (p < 0.05) associated with people over 60, hypertensive patients, and asthma patients. Regression analysis suggested that the risk of complications due to COVID-19 infection is more in males, people above 60 years age and those suffering from co-morbidities.ConclusionsThe findings of the study indicate an association between several of the characteristics studied, such as gender, age, and comorbidity, and the spread of infection, recovery, and mortality. To restrict the spread of COVID-19 and prevent its complications, effective measures are required to control the modifiable risk factors.     

Antimicrobial resistance among enterococci from pigs in three European countries

Enterococci from pigs in Denmark, Spain, and Sweden were examined for susceptibility to antimicrobial agents and copper and the presence of selected resistance genes. The greatest levels of resistance were found among isolates from Spain and Denmark compared to those from Sweden, which corresponds to the amounts of antimicrobial agents used in food animal production in those countries. Similar genes were found to encode resistance in the different countries, but the tet(L) and tet(S) genes were more frequently found among isolates from Spain. A recently identified transferable copper resistance gene was found in all copper-resistant isolates from the different countries.     

Spatially resolved epigenomic profiling of single cells in complex tissues

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Contribution to COVID-19 spread modelling: a physical phenomenological dissipative formalism

Biomechanics and Modeling in Mechanobiology - In this study, we propose an evolution law of COVID-19 transmission. An infinite ordered lattice represents population. Epidemic evolution is...     

Spatially resolved force spectroscopy of biological surfaces using the atomic force microscope

The spatial distribution of intermolecular forces governs macromolecular interactions. The atomic force microscope, a relatively new tool for investigating interaction forces between nanometer-scale objects, can be used to produce spatially resolved maps of the surface or material properties of a sample; these include charge density, adhesion and stiffness, as well as the force required to break specific ligand-receptor bonds. Maps such as these will provide fundamental insights into biological structure and will become an important tool for characterizing technologically important biological systems.     

Spatially resolved quantification of metal ion concentration in a biofilm-mediated ion exchanger

A bioremediation process to remove Co(2+) from aqueous solution is investigated in this study using a magnetic resonance imaging (MRI) protocol to rapidly obtain multiple 2D spatially resolved Co(2+) ion concentration maps. The MRI technique is described in detail and its ability to determine the evolution in both axial and radial concentration profiles demonstrated, from which total column capacity can be determined. The final ion exchange column design allows operation in the 'plug flow' regime, hence making use of its full capacity before breakthrough. Conventional techniques for such process optimization are either restricted to the analysis of the exchanger outlet, which provides no information on the spatial heterogeneity of the system, or are invasive and need a variety of sample points to obtain 1D concentration information. To the best of our knowledge, our results represent the first concentration maps describing the bioremediation of metal ion contaminated water.     

Spatially resolved microrheology of heterogeneous biopolymer hydrogels using covalently bound microspheres

Characterization of the rheological properties of heterogeneous biopolymers is important not only to understand the effect of substrate elasticity on cell behaviors, but also to provide insights into mechanical changes during cellular remodeling of the environment. Conventional particle-tracking microrheology (PTM) techniques are compromised by probe–network slippage and cage-hopping problems, and require a priori knowledge of network mesh size in order to determine a suitable probe size. We demonstrated here the usefulness of covalently bound probes for PTM of biopolymers to overcome the above limitations. We showed that, in a well-defined system like polyacrylamide gels, surface-modified probe particles using a zero-length crosslinker provided more reliable measurements of network mechanics as compared to standard carboxylated probes. We further demonstrated that appropriate surface modification of microspheres for PTM circumvented the requirement of using microspheres larger than the network mesh, an approach typically considered to be ideal. Using the method presented in this study, we found the local network at the leading edge of a typical C6 glioma cell to be stiffer as compared to the side. Our findings established that permanent interaction between the probe and network is crucial to reliably measure the local network mechanics in reconstituted, heterogeneous networks using PTM.     

Spatially resolved monitoring of cellular metabolic activity with a semiconductor-based biosensor

Metabolic activity of cultured cells can be monitored by measuring changes in the pH of the surrounding medium caused by metabolic products such as protons, carbon dioxide or lactic acid. Although many systems designed for this purpose have been reported, almost all of them are based on bulk measurements, where the average metabolic activity of all cells in contact with the device is recorded. Here, we report on a novel biosensor, based on a modified light-addressable potentiometric sensor (LAPS) device, which enables the metabolic activity of cultured cells to be measured with spatial resolution. This is demonstrated here by detecting the differential sensitivity to a cholinergic receptor agonist of two different co-cultured cellular populations. By making simultaneous measurements of the metabolic activity of different cell types seeded on different segments of one sensor, this device not only provides a rapid means of assessing cellular specificity of pharmaceutical compounds but also has the potential of being used to non-invasively monitor humoral as well as synaptic communication between different cell populations in co-culture. The temporal and spatial resolution of the device were investigated and are discussed.     

Optimizing global COVID-19 vaccine allocation: An agent-based computational model of 148 countries

BackgroundBased on the principles of equity and effectiveness, the World Health Organization and COVAX formulate vaccine allocation as a mathematical optimization problem. This study aims to solve the optimization problem using agent-based simulations.MethodsWe built open-sourced agent-based models to simulate virus transition among a demographically representative sample of 198 million people in 148 countries using advanced computational services. All countries continuing their current vaccine progress is defined as the baseline scenario. Comparison scenarios include achieving minimum vaccination rates and allocating vaccines based on pandemic levels.FindingsThe simulations are fitted using the pandemic data from 148 countries from January 2020 to June 2021. Under the baseline scenario, the world will add 24.36 million cases and 468,945 deaths during the projection period of three months. Inoculating at least 10%, 20%, and 26% of populations in all countries requires 1.12, 3.31, and 5.00 million additional vaccine doses every day, respectively. Achieving these benchmarks reduces new cases by 0.56, 2.74, and 3.32 million, respectively. If allocated by the current global distribution, 5.00 million additional vaccine doses will only avert 1.45 million new cases. If those 5.00 million vaccines are allocated based on projected cases in each country, the averted cases will increase more than six-fold to 9.20 million. Similar differences between allocation methods are observed in averted deaths.ConclusionThe global distribution of COVID-19 vaccines can be optimized to achieve better outcomes in terms of both equity and effectiveness. Alternative vaccine allocation methods may avert several times more cases and deaths than the current global distribution. With reasonable requirements on additional vaccines, COVAX could adopt alternative allocation strategies that reduce cross-country inequity and save more lives.     

Mass gathering events and the spread of infectious diseases: Evidence from the early growth phase of COVID-19

This paper studies the impact on reported coronavirus 2019 (COVID-19) cases and deaths in Spain resulting from large mass gatherings that occurred from March 6 to March 8, 2020. To study these outcomes, the geographic differences in the planned pre-pandemic major events that took place on these dates were exploited, which is a quasi-random source of variation for identification purposes. We collected daily and detailed information about the number of attendees at football (soccer) and basketball matches in addition to individuals participating in the Women’s Day marches across Spain, which we merged with daily data on reported COVID-19 cases and deaths at the provincial level. Our results reveal evidence of non-negligible COVID-19 cases related to the differences in the percentage of attendees at these major events from March 6 to March 8. In a typical province, approximately 31% of the average daily reported COVID-19 cases per 100,000 inhabitants between mid-March and early April 2020 can be explained by the participation rate in those major events. A back-of-the-envelope calculation suggests that this implies almost five million euros (169,000 euros/day) of additional economic cost in the health system of a typical province with one million inhabitants in the period under consideration. Several mechanisms behind the spread of COVID-19 are also examined.     

Spatially resolved characterization of biogenic manganese oxide production within a bacterial biofilm

Pseudomonas putida strain MnB1, a biofilm-forming bacterial culture, was used as a model for the study of bacterial Mn oxidation in freshwater and soil environments. The oxidation of aqueous Mn+2 [Mn+2(aq)] by P. putida was characterized by spatially and temporally resolving the oxidation state of Mn in the presence of a bacterial biofilm, using scanning transmission X-ray microscopy (STXM) combined with near-edge X-ray absorption fine structure (NEXAFS) spectroscopy at the Mn L2,3 absorption edges. Subsamples were collected from growth flasks containing 0.1 and 1 mM total Mn at 16, 24, 36, and 48 h after inoculation. Immediately after collection, the unprocessed hydrated subsamples were imaged at a 40-nm resolution. Manganese NEXAFS spectra were extracted from X-ray energy sequences of STXM images (stacks) and fit with linear combinations of well-characterized reference spectra to obtain quantitative relative abundances of Mn(II), Mn(III), and Mn(IV). Careful consideration was given to uncertainty in the normalization of the reference spectra, choice of reference compounds, and chemical changes due to radiation damage. The STXM results confirm that Mn+2(aq) was removed from solution by P. putida and was concentrated as Mn(III) and Mn(IV) immediately adjacent to the bacterial cells. The Mn precipitates were completely enveloped by bacterial biofilm material. The distribution of Mn oxidation states was spatially heterogeneous within and between the clusters of bacterial cells. Scanning transmission X-ray microscopy is a promising tool for advancing the study of hydrated interfaces between minerals and bacteria, particularly in cases where the structure of bacterial biofilms needs to be maintained.