Search

Microbial communities are known to play a principal role in petroleum degradation. This study tries to determine the composition of bacteria in selected crude oil-contaminated soil from Tabasco and Tamaulipas states, Mexico. We determined the microbial populations living under these conditions. We evaluated the structure and diversity of bacterial communities in the contaminated soil samples. The most abundant phylum is proteobacteria. Next Generation Sequencing (NGS) analysis of the sampled soils from both states revealed that this phylum has the most relative abundance among the identified bacteria phyla. The heatmap represented the relative percentage of each genus within each sample and clustered the four samples into two groups. Moreover, this allowed us to identify many genera in alkaline soil from Tamaulipas, such as Skermanella sp., Azospirillum sp. and Unclassified species from the Rhodospirillaceae family in higher abundance. Meanwhile, in acidic soil from Tabasco, we identified Thalassospira, Unclassified members of the Sphingomonadaceae family and Unclassified members of the Alphaproteobacteria class with higher abundance. Alpha diversity analysis showed a low diversity (Shannon and Simpson index); Chao observed species in both Regions. These results suggest that the bacteria identified in these genera may possess the ability to degrade petroleum, and further studies in the future should elucidate their role in petroleum degradation.

Rice is an important source of nutrition and energy consumed around the world. Thus, quality inspection is crucial for protecting consumers and increasing the rice’s value in the productive chain. Currently, methods for rice labeling depending on grain quality features are based on image and/or visual inspection. These methods have shown subjectivity and inefficiency for large-scale analyses. Laser-induced breakdown spectroscopy (LIBS) is an analytical technique showing attractive features due to how quick the analysis can be carried out and its capability of providing spectra that are true fingerprints of the sample’s elemental composition. In this work, LIBS performance was evaluated for labeling rice according to grain quality features. The LIBS spectra of samples with their grain quality numerically described as Type 1, 2, and 3 were measured. Several spectral processing methods were evaluated when modeling a k-nearest neighbors (k-NN) classifier. Variable selection was also carried out by principal component analysis (PCA), and then the optimal k-value was selected. The best result was obtained by applying spectrum smoothing followed by normalization by using the first fifteen principal components (PCs) as input variables and k = 9. Under these conditions, the method showed excellent performance, achieving sample classification with 94% overall prediction accuracy. The sensitivities ranged from 90 to 100%, and specificities were in the range of 92–100%. The proposed method has remarkable characteristics, e.g., analytical speed and analysis guided by chemical responses; therefore, the method is not susceptible to subjectivity errors.

In recent years, immunotherapy has become a powerful therapeutic option against multiple malignancies. The unique capacity of natural killer (NK) cells to attack cancer cells without antigen specificity makes them an optimal immunotherapeutic tool for targeting tumors. Several approaches are currently being pursued to maximize the anti-tumor properties of NK cells in the clinic, including the development of NK cell expansion protocols for adoptive transfer, the establishment of a favorable microenvironment for NK cell activity, the redirection of NK cell activity against tumor cells, and the blockage of inhibitory mechanisms that constrain NK cell function. We here summarize the recent strategies in NK cell-based immunotherapies and discuss the requirement to further optimize these approaches for enhancement of the clinical outcome of NK cell-based immunotherapy targeting tumors.

In this study, nanostructured ZnO arrays were synthesized by an accessible thermal oxidation (TO) methodology. The Zn films were chemically etched with nitric acid (HNO3) and then oxidized in a furnace at 500 °C for 5 h. Two different morphologies were achieved by modifying the HNO3 concentration in the etching process: (a) ZnO grass-like nanostructures and (b) rod-like nanostructures, with an etching process in HNO3 solution at 2 and 8 M concentration, respectively. The physical and chemical properties of the samples were analyzed by X-ray diffraction (XRD), scanning (SEM) and transmission electron microscopy (TEM), energy dispersive X-ray spectroscopy (EDS), and Raman spectroscopy. Both morphologies were functionalized with hemoglobin, and a difference was found in the efficiency of functionalization, which was monitored by UV–Vis spectroscopy. The sample with the highest efficiency was the ZnO grass-like nanostructures. Afterward, the capture of carbon dioxide was evaluated by monitoring a sodium carbonate solution interacting with the as-functionalized samples. The evaluation was analyzed by UV–Vis spectroscopy and the results showed a CO2 capture of 98.3% and 54% in 180 min for the ZnO grass-like and rod-like nanostructures, respectively.

Sphingobium yanoikuyae S72 was isolated from the rhizosphere of sorghum plant in Mexico and we evaluated its survival and role in the degradation of some selected monoaromatic hydrocarbons and polycyclic aromatic hydrocarbons (PAHs) using minimal medium (Bushnell Hass medium (BH)) in which each of the hydrocarbons (naphthalene, phenanthrene, xylene, toluene, and biphenyl) served as sole carbon source. Gas column chromatography–mass spectrometry analysis was used to evaluate the effect of S72’s growth in the medium with the hydrocarbons. The genome of the S72 was sequenced to determine the genetic basis for the degradation of the selected hydrocarbon in S72. The genome was assembled de novo with Spades assembler and Velvet assembler and the obtained contigs were reduced to 1 manually using Consed software. Genome annotation was carried out Prokka version 1.12, and gene calling and further annotation was carried out with NCBI PGAAP. Pangenome analysis and COG annotation were done with bacteria pangenome analysis tool (BPGA) and with PATRIC online server, respectively. S72 grew effectively in the culture medium with the hydrocarbon with concentration ranging from 20–100 mg/mL for each hydrocarbon tested. S72 degraded biphenyl by 85%, phenanthrene by 93%, naphthalene by 81%, xylene by 19%, and toluene by 30%. The sequenced S72 genome was reduced to 1 contig and genome analysis revealed the presence of genes essential for the degradation of hydrocarbons in S72. A total of 126 unique genes in S72 are associated with the degradation of hydrocarbons and xenobiotics. S72 grew effectively in the tested hydrocarbon and shows good degradation efficiency. S72 will therefore be a good candidate for bioremediation of hydrocarbon contaminated soil.

Xenobiotic contamination, a worldwide environmental concern, poses risks for humans, animals, microbe health, and agriculture. Hydrocarbons and heavy metals top the list of toxins that represent a risk to nature. This review deals with the study of Azospirillum sp., widely reported as plant growth-promoting bacteria in various cultures. However, its adaptation properties in adverse environments make it a good candidate for studying remediation processes in environments polluted with hydrocarbons and heavy metals. This review includes studies that address its properties as a plant growth promoter, its genomics, and that evaluate its potential use in the remediation of hydrocarbons and heavy metals.

In this work, carbon dots were created from activated and non-activated pyrolytic carbon black obtained from waste tires, which were then chemically oxidized with HNO3. The effects caused to the carbon dot properties were analyzed in detail through characterization techniques such as ion chromatography; UV–visible, Fourier-transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), and Raman spectroscopy; ζ potential; transmission electron microscopy (TEM); and spectrofluorometry. The presence of functional groups on the surface of all carbon dots was revealed by UV–visible, FTIR, XPS, and Raman spectra. The higher oxidation degrees of carbon dots from activated precursors compared to those from nonactivated precursors resulted in differences in photoluminescence (PL) properties such as bathochromic shift, lower intensity, and excitation-dependent behavior. The results demonstrate that the use of an activating agent in the recovery of pyrolytic carbon black resulted in carbon dots with different PL properties. In addition, a dialysis methodology is proposed to overcome purification obstacles, finding that 360 h were required to obtain pure carbon dots synthesized by a chemical oxidation method.

Cities have high demand and limited availability of water and energy, so it is necessary to have adequate technologies to make efficient use of these resources and to be able to generate them. This research focuses on developing and executing a methodology for an urban living lab vocation identification for a new water and energy self-sufficient university building. The methods employed were constructing a technological roadmap to identify global trends and select the technologies and practices to be implemented in the building. Among the chosen technologies were those for capturing and using rain and residual water, the generation of solar energy, and water and energy generation and consumption monitoring. This building works as a living laboratory since the operation and monitoring generate knowledge and innovation through students and research groups that develop projects. The insights gained from this study may help other efforts to avoid pitfalls and better design smart living labs and off-grid buildings.

The use of statistical models and machine-learning techniques along satellite-derived aerosol optical depth (AOD) is a promising method to estimate ground-level particulate matter with an aerodynamic diameter of ≤2.5 μm (PM2.5), mainly in urban areas with low air quality monitor density. Nevertheless, the relationship between AOD and ground-level PM2.5 varies spatiotemporally and differences related to spatial domains, temporal schemes, and seasonal variations must be assessed. Here, an ensemble multiple linear regression (EMLR) model and an ensemble neural network (ENN) model were developed to estimate PM2.5 levels in the Monterrey Metropolitan Area (MMA), the second largest urban center in Mexico. Four AOD-SDSs (Scientific Datasets) from MODIS Collection 6 were tested using three spatial domains and two temporal schemes. The best model performance was obtained using AOD at 0.55 µm from MODIS-Aqua at a spatial resolution of 3 km, along meteorological parameters and daily scheme. EMLR yielded a correlation coefficient (R) of ~0.57 and a root mean square error (RMSE) of ~7.00 μg m−3. ENN performed better than EMLR, with an R of ~0.78 and RMSE of ~5.43 μg m−3. Satellite-derived AOD in combination with meteorology data allowed for the estimation of PM2.5 distributions in an urban area with low air quality monitor density.

The problems related to the increase in the generation of discarded tires demonstrate the need for profitable, efficient, cost-effective, and sustainable processes for their waste management. In particular, the valorization of pyrolytic solids for energy storage applications is of interest. In this study, four processes were performed: (1) pyrolysis; (2) chemical activation and pyrolysis; (3) pyrolysis and physical activation; and (4) chemical activation, pyrolysis, and physical activation. The process consisting of chemical activation, pyrolysis, and physical activation yielded 52% solid material with the highest electrical conductivity (2.43 Ω–1 cm–1) and a surface area of 339 m2/g with an average pore size of 3.6 nm. In addition, it was found that pore size had a greater effect on the conductivity than surface area. Liquid and gas fraction compositions were modified by the presence of chemical activation: aromatization reactions were favored, and limonene was not observed in the liquid fraction, while an increase on the CH4 concentration caused an increment in the heating value of the gas fraction. It was demonstrated that chemical and physical activation enhance the properties of the pyrolytic solid product derived from waste tires that make it suitable for the partial substitution of materials for electric energy storage applications.

Source attribution of airborne particulate matter (PM) relies on a host of different chemical species. Organic molecular markers are a set of particularly useful marker compounds for estimating source contributions to the fine PM fraction (i.e., PM2.5). Although there are many source apportionment studies based on organic markers, these studies heavily rely on the few studies that report region-specific emission profiles. Source attribution efforts, particularly those conducted in countries with emerging economies, benefit from ad hoc information to conduct the corresponding analyses. In this study, we report organic molecular marker source profiles for PM2.5 emitted from 12 major sources types from five general source categories (meat cooking operations, vehicle exhausts, industries, biomass and trash burning, and urban background) for the Monterrey Metropolitan Area (Mexico). Source emission samples were obtained from a ground-based source-dominated sampling approach. Filter-based instruments were utilized, and the loaded filters were chemically characterized for organic markers by GC-MS. Levoglucosan and cholesterol dominate charbroiled-cooking operation sources while methoxyphenols, PAHs and hopanes dominate open-waste burning, vehicle exhaust and industrial emissions, respectively. A statistical analysis showed values of the Pearson distance < 0.4 and the similarity identity distance > 0.8 in all cases, indicating dissimilar source profiles. This was supported by the coefficient of divergence average values that ranged from 0.62 to 0.72. These profiles could further be utilized in receptor models to conduct source apportionment in regions with similar characteristics and can also be used to develop air pollution abatement strategies.

In this work, the particulate matter (PM) from three different monitoring stations in the Monterrey Metropolitan Area in Mexico were investigated for their compositional, morphological, and optical properties. The main aim of the research was to decipher the different sources of the particles. The methodology involved the ex situ sequential analysis of individual particles by three analytical techniques: scanning electron microscopy-energy dispersive X-ray spectroscopy (SEM-EDS), polarized light microscopy (PLM), and micro-Raman spectroscopy (MRS). The microanalysis was performed on samples of total suspended particles. Different morphologies were observed for particles rich in the same element, including prismatic, spherical, spheroidal, and irregular morphologies. The sequential microanalysis by SEM-EDS/PLM/MRS revealed that Fe-rich particles with spherical and irregular morphologies were derived from anthopogenic sources, such as emissions from the metallurgical industry and the wear of automobile parts, respectively. In contrast, Fe-rich particles with prismatic morphologies were associated with natural sources. In relation to carbon (C), the methodology was able to distinguish between the C-rich particles that came from different anthopogenic sources—such as the burning of fossil fuels, biomass, or charcoal—and the metallurgical industry. The optical properties of the Si-rich particles depended, to a greater extent, on their chemical composition than on their morphology, which made it possible to quickly and accurately differentiate aluminosilicates from quartz. The methodology demonstrated in this study was useful for performing the speciation of the particles rich in different elements. This differentiation helped to assign their possible emission sources.

Statistical time series forecasting is a useful tool for predicting air pollutant concentrations in urban areas, especially in emerging economies, where the capacity to implement comprehensive air quality models is limited. In this study, a general multiple regression with seasonal autoregressive moving average errors model was estimated and implemented to forecast maximum ozone concentrations with a short time resolution: overnight, morning, afternoon and evening. In contrast to a number of short-term air quality time series forecasting applications, the model was designed to explicitly include the effects of meteorological variables on the ozone level as exogenous variables. As the application location, the model was constructed with data from five monitoring stations in the Monterrey Metropolitan Area of Mexico. The results show that, together with structural stochastic components, meteorological parameters have a significant contribution for obtaining reliable forecasts. The resulting model is an interpretable, useful and easily implementable model for forecasting ozone maxima. Moreover, it proved to be consistent with the general dynamics of ozone formation and provides a suitable platform for forecasting, showing similar or better performance compared to models in other existing studies.

Pyrolysis is a feasible solution for environmental problems related to the inadequate disposal of waste tires, as it leads to the recovery of pyrolytic products such as carbon black, liquid fuels and gases. The characteristics of pyrolytic carbon black can be enhanced through chemical activation in order to produce the required properties for its application. In the search to make the waste tire pyrolysis process profitable, new applications of the pyrolytic solid products have been explored, such as for the fabrication of energy-storage devices and precursor in the synthesis of nanomaterials. In this study, waste tires powder was chemically activated using acid (H2SO4) and/or alkali (KOH) to recover pyrolytic carbon black with different characteristics. H2SO4 removed surface impurities more thoroughly, improving the carbon black’s surface area, while KOH increased its oxygen content, which improved the carbon black’s stability in water suspension. Pyrolytic carbon black was fully characterized by elemental analysis, inductively coupled plasma–optical emission spectrometry (ICP-OES), Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy, X-ray diffraction (XRD), N2 adsorption/desorption, scanning electron microscopy–energy-dispersive X-ray spectroscopy (SEM-EDS), dynamic light scattering (DLS), and ζ potential measurement. In addition, the pyrolytic carbon black was used to explore its feasibility as a precursor for the synthesis of carbon dots; synthesized carbon dots were analyzed preliminarily by SEM and with a fluorescence microplate reader, revealing differences in their morphology and fluorescence intensity. The results presented in this study demonstrate the effect of the activating agent on pyrolytic carbon black from waste tires and provide evidence of the feasibility of using waste tires for the synthesis of nanomaterials such as carbon dots.

Aerosol and meteorological remote sensing data could be used to assess the distribution of urban and regional fine particulate matter (PM2.5), especially in locations where there are few or no ground-based observations, such as Latin America. The objective of this study is to evaluate the ability of Modern-Era Retrospective Analysis for Research and Application, version 2 (MERRA-2) aerosol components to represent PM2.5 ground concentrations and to develop and validate an ensemble neural network (ENN) model that uses MERRA-2 aerosol and meteorology products to estimate the monthly average of PM2.5 ground concentrations in the Monterrey Metropolitan Area (MMA), which is the main urban area in Northeastern Mexico (NEM). The project involves the application of the ENN model to a regional domain that includes not only the MMA but also other municipalities in NEM in the period from January 2010 to December 2014. Aerosol optical depth (AOD), temperature, relative humidity, dust PM2.5, sea salt PM2.5, black carbon (BC), organic carbon (OC), and sulfate (SO42−) reanalysis data were identified as factors that significantly influenced PM2.5 concentrations. The ENN estimated a PM2.5 monthly mean of 25.62 μg m−3 during the entire period. The results of the comparison between the ENN and ground measurements were as follows: correlation coefficient R ~ 0.90; root mean square error = 1.81 μg m−3; mean absolute error = 1.31 μg m−3. Overall, the PM2.5 levels were higher in winter and spring. The highest PM2.5 levels were located in the MMA, which is the major source of air pollution throughout this area. The estimated data indicated that PM2.5 was not distributed uniformly throughout the region but varied both spatially and temporally. These results led to the conclusion that the magnitude of air pollution varies among seasons and regions, and it is correlated with meteorological factors. The methodology developed in this study could be used to identify new monitoring sites and address information gaps.

Tropospheric levels of O3 have historically exceeded the official annual Mexican standards within the Monterrey Metropolitan Area (MMA) in NE Mexico. High-frequency and high-precision measurements of tropospheric O3, NOy, NO2, NO, CO, SO2, PM10 and PM2.5 were made at the Obispado monitoring site near the downtown MMA from September 2012 to August 2013. The seasonal cycles of O3 and NOy are driven by changes in meteorology and to a lesser extent by variations in primary emissions. The NOy levels were positively correlated with O3 precursors and inversely correlated with O3 and wind speed. Recorded data were used to assess the O3-Volatile Organic Compounds (VOC)-NOx system’s sensitivity through an observational-based approach. The photochemical indicator O3/NOy was derived from measured data during the enhanced O3 production period (12:00–18:00 Central Daylight Time (CDT), GMT-0500). The O3/NOy ratios calculated for this time period showed that the O3 production within the MMA is VOC sensitive. A box model simulation of production rates of HNO3 (PHNO3) and total peroxides (Pperox) carried out for O3 episodes in fall and spring confirmed the VOC sensitivity within the MMA environment. No significant differences were observed in O3/NOy from weekdays to weekends or for PHNO3/Pperox ratios, confirming the limiting role of VOCs in O3 production within the MMA. The ratified photochemical regime observed may allow the environmental authorities to revise and verify the current policies for air quality control within the MMA.

Triosephosphate isomerase (TPI) is a glycolysis enzyme, which catalyzes the reversible isomerization between dihydroxyactetone-3-phosphate (DHAP) and glyceraldehyde-3-phosphate (GAP). In pathogenic organisms, TPI is essential to obtain the energy used to survive and infect. Fusarium oxisporum (Fox) is a fungus of biotechnological importance due to its pathogenicity in different organisms, that is why the relevance of also biochemically analyzing its TPI, being the first report of its kind in a Fusarium. Moreover, the kinetic characteristics or structural determinants related to its function remain unknown. Here, the Tpi gene from F. oxysporum was isolated, cloned, and overexpressed. The recombinant protein named FoxTPI was purified (97% purity) showing a molecular mass of 27 kDa, with optimal activity at pH 8.0 and and temperature of 37 °C. The values obtained for Km and Vmax using the substrate GAP were 0.47 ± 0.1 mM, and 5331 μmol min−1 mg−1, respectively. Furthemore, a protein structural modeling showed that FoxTPI has the classical topology of TPIs conserved in other organisms, including the catalytic residues conserved in the active site (Lys12, His94 and Glu164). Finally, when FoxTPI was analyzed with inhibitors, it was found that one of them inhibits its activity, which gives us the perspective of future studies and its potential use against this pathogen.

It is well known that gadolinium chloride (GD) attenuates drug-induced hepatotoxicity by selectively inactivating Kupffer cells. In the present study the effect of GD in reference to cell cycle and postnecrotic liver regeneration induced by thioacetamide (TA) in rats was studied. Two months male rats, intraveously pretreated with a single dose of GD (0.1 mmol/Kg), were intraperitoneally injected with TA (6.6 mmol/Kg). Samples of blood and liver were obtained from rats at 0, 12, 24, 48, 72 and 96 h following TA intoxication. Parameters related to liver damage were determined in blood. In order to evaluate the mechanisms involved in the post-necrotic regenerative state, the levels of cyclin D and cyclin E as well as protein p27 and Proliferating Cell Nuclear Antigen (PCNA) were determined in liver extracts because of their roles in the control of cell cycle check-points. The results showed that GD significantly reduced the extent of necrosis. Noticeable changes were detected in the levels of cyclin D1, cyclin E, p27 and PCNA when compared to those induced by thioacetamide. Thus GD pre-treatment reduced TA-induced liver injury and accelerated the postnecrotic liver regeneration. These results demonstrate that Kupffer cells are involved in TA-induced liver and also in the postnecrotic proliferative liver states.

After 6 months of operation a long-term biofilter was stopped for two weeks and then it was started up again for a second experimental period of almost 1.3 years, with high toluene loads and submitted to several physical and chemical treatments in order to remove excess biomass that could affect the reactor’s performance due to clogging, whose main effect is a high pressure drop. Elimination capacity and removal efficiency were determined after each treatment. The methods applied were: filling with water and draining, backwashing, and air sparging. Different flows and temperatures (20, 30, 45 and 60 °C) were applied, either with distilled water or with different chemicals in aqueous solutions. Treatments with chemicals caused a decrease of the biofilter performance, requiring periods of 1 to 2 weeks to recover previous values. The results indicate that air sparging with pure distilled water as well as with solutions of NaOH (0.01% w/v) and NaOCl (0.01% w/v) were the treatments that removed more biomass, working either at 20, 30 or 45 °C and at relatively low flow rates (below 320 L h−1), but with a high biodegradation inhibition after the treatments. Dry biomass (g VS) content was determined at three different heights of the biofilter in order to carry out each experiment under the same conditions. The same amount of dry biomass when applying a treatment was established so it could be considered that the biofilm conditions were identical. Wet biomass was used as a control of the biofilter’s water content during treatments. Several batch assays were performed to support and quantify the observed inhibitory effects of the different chemicals and temperatures applied.