Micromotors of MnO2 for the Recovery of Microplastics

Plastics, primarily microplastics, are among the greatest pollutants in aquatic environments. Their removal and/or degradation in these environments are crucial to ensure an optimal future of these ecosystems. In this work, MnO2 particles were synthesized and characterized for the removal of polystyrene microplastics as a model. MnO2 catalyzes the peroxide reaction, resulting in the formation of oxygen bubbles that propel the pollutants to the surface, achieving removal efficiencies of up to 80%. To achieve this, hydrothermal synthesis was employed using various methods. Parameters such as MnO2, pH, microplastics, and H2O2 concentrations were varied to determine the optimal conditions for microplastics recovering. The ideal conditions for a low microplastic concentrations (10 mg L-1) are 0.2 g L-1 MnO2, 1.6% of H2O2 and 0.01 triton as a surfactant. In these conditions, the micromotors can recover approximately 80% of 300 nm sized polystyrene microplastic within 40 min.

A Novel Approach to Obtain Vaccine Effectiveness Continuous Profiles. Example Case: COVID-19 in Elderly Mexicans

Population-wide vaccination is the most promising long-term COVID-19 disease management strategy. However, the protection offered by the currently available COVID-19 vaccines wanes over time, requiring boosters to be periodically given, which represents an unattainable challenge, especially if it is necessary to apply several doses per year. Therefore, it is essential to design strategies that contribute to maximizing the control of the pandemic with the available vaccines. Achieving this objective requires knowing, as precisely and accurately as possible, the changes in vaccine effectiveness over time in each population group, considering the eventual dependence on age, sex, etc. Thus, the present work proposes a novel approach to calculating realistic effectiveness profiles against symptomatic disease. In addition, this strategy can be adapted to estimate realistic effectiveness profiles against hospitalizations or deaths. All such time-dependent profiles allow the design of improved vaccination schedules, where each dose can be administrated to the population groups so that the fulfillment of the containment objectives is maximized. As a practical example for this analysis, vaccination against COVID-19 in Mexico was considered. However, this methodology can be applied to other countries' data or to characterize future vaccines with time-dependent effectiveness values. Since this strategy uses aggregated observational data collected from massive databases, assumptions about the data validity and the course of the studied epidemic could eventually be necessary.

Mortality predictors in patients with COVID-19 pneumonia: a machine learning approach using eXtreme Gradient Boosting model

Recently, global health has seen an increase in demand for assistance as a result of the COVID-19 pandemic. This has prompted many researchers to conduct different studies looking for variables that are associated with increased clinical risk, and find effective and safe treatments. Many of these studies have been limited by presenting small samples and a large data set. Using machine learning (ML) techniques we can detect parameters that help us to improve clinical diagnosis, since they are a system for the detection, prediction and treatment of complex data. ML techniques can be valuable for the study of COVID-19, especially because they can uncover complex patterns in large data sets. This retrospective study of 150 hospitalized adult COVID-19 patients, of which we established two groups, those who died were called Case group (n = 53) while the survivors were Control group (n = 98). For analysis, a supervised learning algorithm eXtreme Gradient Boosting (XGBoost) has been used due to its good response compared to other methods because it is highly efficient, flexible and portable. In this study, the response to different treatments has been evaluated and has made it possible to accurately predict which patients have higher mortality using artificial intelligence, obtaining better results compared to other ML methods.

A Ferrofluid with Surface Modified Nanoparticles for Magnetic Hyperthermia and High ROS Production

A ferrofluid with 1,2-Benzenediol-coated iron oxide nanoparticles was synthesized and physicochemically analyzed. This colloidal system was prepared following the typical co-precipitation method, and superparamagnetic nanoparticles of 13.5 nm average diameter, 34 emu/g of magnetic saturation, and 285 K of blocking temperature were obtained. Additionally, the zeta potential showed a suitable colloidal stability for cancer therapy assays and the magneto-calorimetric trails determined a high power absorption density. In addition, the oxidative capability of the ferrofluid was corroborated by performing the Fenton reaction with methylene blue (MB) dissolved in water, where the ferrofluid was suitable for producing reactive oxygen species (ROS), and surprisingly a strong degradation of MB was also observed when it was combined with H2O2. The intracellular ROS production was qualitatively corroborated using the HT-29 human cell line, by detecting the fluorescent rise induced in 2,7-dichlorofluorescein diacetate. In other experiments, cell metabolic activity was measured, and no toxicity was observed, even with concentrations of up to 4 mg/mL of magnetic nanoparticles (MNPs). When the cells were treated with magnetic hyperthermia, 80% of cells were dead at 43 °C using 3 mg/mL of MNPs and applying a magnetic field of 530 kHz with 20 kA/m amplitude.

Self-referencing mW-scale detection of sub-ns optical phase modulation in acetylene at 1530 nm

Application of the phase memory of acetylene (C₂H₂) vibrational-rotational transitions in the 1520-1540 nm wavelength range for a self-referencing homodyne detection of a sub-nanosecond optical phase modulation is reported. In the proposed configuration the collinearly propagating coherent dipole radiation of the excited molecule acts like a phase-locked reference wave (local oscillator) that enables transformation of the initial phase modulation into the intensity one. This technique does not need high light intensity and can operate in a linear range of the medium optical absorption. The linear optical phase demodulation (i.e., transformation of the phase-to-amplitude light modulation) is interpreted as an introduction of an additional phase shift to the carrier frequency component of the modulated signal in the maximum of the dispersion curve of a narrow optical absorption peak. It has been experimentally demonstrated with the bulk 10 cm long cuvette filled with low pressure (∼2  Torr) acetylene at room temperature. Effective demodulation of the milliwatt-scale incident laser wave of a single- and multi-mode structure is shown. As expected, the response to the fast (<1  ns) phase modulation was quadratic when the acetylene inhomogeneous Doppler-broadened (∼500  MHz) absorption line is excited in its center and was linearized by tuning at one of the absorption line sides. It is of a differentiating (high-pass) type with the cutoff frequency determined by the total spectral width of the utilized absorption line. Expected detection resolution is determined by the photon noise of the incident light intensity.

Structure of reverse microemulsion-templated metal hexacyanoferrate nanoparticles

The droplet phase of a reverse microemulsion formed by the surfactant cetyltrimethylammonium ferrocyanide was used as a matrix to synthesize nanoparticles of nickel hexacyanoferrate by adding just a solution of NiCl2 to the microemulsion media. Dynamic light scattering and small-angle neutron scattering measurements show that the reverse microemulsion droplets employed have a globular structure, with sizes that depend on water content. Transmission electron microscopy and electron diffraction are used to obtain information about the structure of the synthesized nanoparticles. The results show that the size and shape of the coordination compound nanoparticles correspond with the size and shape of the droplets, suggesting that the presented system constitutes an alternative method of the synthesis of metal hexacyanoferrate nanoparticles.

Surface characterization of electrodeposited silver on activated carbon for bactericidal purposes

The use of an electrochemical reactor operated under different flow conditions to deposit silver from aqueous AgNO(3) solutions and tartaric acid as an organic additive on a commercial activated carbon with ultimate bactericidal applications in water purification processes is presented. The characterization of carbon/silver samples was studied by BET, FTIR, X-ray diffraction, XPS, and SEM techniques. The bactericidal activity of the carbon/silver samples was tested on drinking water samples inoculated with E. coli. A reduction of carbon surface area was detected and was caused by increased amounts of silver deposited on carbon samples. Adherent silver deposits were obtained on the carbon/silver samples. X-ray diffraction studies of carbon with electrodeposited silver showed two different preferential deposition planes, [111] and [220]. The FTIR results confirm the presence of carboxyl, phenolic, quinone, and ether surface groups. The XPS results suggest the formation of Ag(2)O and AgO surface species and confirm the reduction of silver to the metallic form. Antimicrobial activity toward E. coli indicated reductions by up to 7 orders of magnitude in the log CFU/mL in just 10 min contact time and for silver contents of 2.47 wt%.