Physicochemical Data Research Articles

Physicochemical characteristics of lakes along the southern Baltic Sea coast

We present a unique data set of selected physicochemical parameters characterizing the environment of the Baltic coastal lakes within Polish borders. The peculiarity of the system derives principally from the interaction of the lakes with a sea of relatively low salinity. In contrast to our best understanding of the state of biological knowledge, the abiotic parameters of coastal lakes along the southern Baltic Sea have never previously been so comprehensively supplemented. The database consists of physicochemical properties of 13 coastal lakes based on the analytical assessment of 419 water samples collected seasonally between 2014 and 2019. Water properties were analyzed according to the connection of the lakes to the Baltic Sea using a total of 23 predictors. The lakes were classified as closed, intermittently connected, or open. Based on the physicochemical data, a relationship between the hydrological connection between the lakes and the sea was determined. The data collected could be used to monitor ongoing global climate change at the biosphere level.

Integration of electronic nose, electronic tongue, and colorimeter in combination with chemometrics for monitoring the fermentation process of Tremella fuciformis

This study proposes an efficient method for monitoring the submerged fermentation process of Tremella fuciformis (T. fuciformis) by integrating electronic nose (e-nose), electronic tongue (e-tongue), and colorimeter sensors using a data fusion strategy. Chemometrics was employed to establish qualitative identification and quantitative prediction models. The Pearson correlation analysis was applied to extract features from the e-nose and tongue sensor arrays. The optimal sensor arrays for monitoring the submerged fermentation process of T. fuciformis were obtained, and four different data fusion methods were developed by incorporating the colorimeter data features. To achieve qualitative identification, the physicochemical data and principal component analysis (PCA) results were utilized to determine three stages of the fermentation process. The fusion signal based on full features proved to be the optimal data fusion method, exhibiting the highest accuracy across different models. Notably, random forest (RF) was shown to be the most accurate pattern recognition method in this paper. For quantitative prediction, partial least squares regression (PLSR) and support vector regression (SVR) were employed to predict the sugar content and dry cell weight during fermentation. The best respective predictive R2 values for reducing sugar, tremella polysaccharide and dry cell weight were found to be 0.965, 0.988, and 0.970. Furthermore, due to its ability to capture nonlinear data relationships, SVR had superior performance in prediction modeling than PLSR. The results demonstrated that the combination of electronic sensor fusion signals and chemometrics provided a promising method for effectively monitoring T. fuciformis fermentation.

Precision medicine to personalize medicine in allergic airway disease.

The purpose of this study is to understand the approach to precision medicine and personalized medicine in the management of allergic airway disease. Identification of biomarkers as key tools used in precision medicine has led to the development of multiple biologic drugs being used as new treatments for allergic airway disease. In addition to these advances, there is still much needed effort to improve the feasibility and utility of integrating biologic omics data of precision medicine with physicochemical, behavioral, psychological, and social data to deliver optimized treatments that is personalized for each individual.

Source of arsenic pollution in southern Indus alluvial plain aquifers, Pakistan

Aquifers in Indus alluvial plain are naturally polluted by arsenic (As). Millions of population in Pakistan use groundwater for drinking is exposed to As ingested diseases. Present investigations were focused on the mobilization mechanism of As in the alluvial aquifers, in Matiari district of Pakistan, which is mainly covered by alluvial sediments of Holocene and Pleistocene age. These sediments are weathered from Himalayas and its neighboring regions and are primarily deposited by Indus River. About 94 samples of groundwater were collected from various localities of Matiari district. Physico-chemical data revealed that 60% of wells exceed 10 μg/L, WHO permissible standard for drinking water. Low nitrate and neutral to near neutral pH and negative Eh in most of the wells are indicative of reducing conditions in the aquifers. Ancient courses of Indus river and domestic and agricultural wastes could be an important source of organic matter. Microbiodegradation of organic matter has created reducing conditions in the aquifer, which trigger the reduction of sedimentary iron oxyhydroxides and the mobilize As in shallow aquifers of Matiari. A borehole was also drilled to decipher the lithological and geochemical characteristics of aquifer material. Elemental, petrographic and SEM-EDS data revealed that sediments are comprised of brown aquitard clay and well sorted grey fine sand. Arsenic in sand and clay samples ranged between 0.8 and 3.9 mg/kg and 0.3–3.2 mg/kg respectively. Dominant minerals in the aquifers sediments are phlogopite and biotite. Leaching of these minerals under reducing conditions is likely to provide higher concentration of As in the groundwater of the area.

Simulation approach to study kinetic heterogeneity of gadolinium catalytic system in the 1,4-cis-polyisoprene production

Abstract This article presents a novel simulation approach for solving the inverse problem of kinetic heterogeneity in polymerization processes, specifically focusing on the production of polyisoprene using a gadolinium chloride solvate-based catalytic system. The proposed method is based on the assumption that the distribution of active centers (ACs) can be described by model distributions. By utilizing primary physicochemical data, such as the polymerization rate and molecular weight distribution, the simulation approach automatically identifies the kinetic parameters, determining the Frenkel statistical parameter and solving the problem of kinetic heterogeneity. The experimental results revealed the presence of at least three distinct types of ACs, each contributing different proportions to the polymerization process. The simulation approach offers valuable insights into the complexities of catalytic systems and their role in polymerization, paving the way for optimizing reaction conditions and advancing industrial polymer synthesis processes. This study marks a significant step forward in understanding and controlling polymerization reactions, with potential implications for the development of innovative materials and industrial applications.

Synergistic Effect of Opuntia ficus-indica Cladode mucilage on Physicochemical and Rheological properties of HPAM polymer solutions for EOR Application

This study focuses on the synthesis of a series of mixtures of a partially hydrolyzed polyacrylamide (HPAM), noted (H), and a cladode Opuntia ficus-indica mucilage (M). The main objective is to minimize the exclusive dependence of HPAM in the field of tertiary oil recovery, specifically in the process known as EOR.This study showed that a combination of 20% mucilage and 80% HPAM, for a total concentration of 800 ppm in solution, gives rheological performance equivalent to a solution of HPAM alone at 6000 ppm. The resulting mixture which is characterized by viscoelastic liquid behavior, exhibits remarkable flow and elasticity properties.This characteristic is considered favorable for extracting trapped oils from pores under effect of the normal stress. Spectral analysis revealed the presence of silica groups in the mixture, elements widely used in researchers in association with HPAM. Thermogravimetric analysis (TGA) demonstrated that mucilage decomposition only occurs at temperatures above 200 °C. As the main conclusion, all the physicochemical and rheological data argue in favor of the integration of mucilage in HPAM in order to minimize its concentration in Enhanced Oil Recovery (EOR) applications.

Iron-carbohydrate complexes treating iron anaemia: Understanding the nano-structure and interactions with proteins through orthogonal characterisation

Intravenous (IV) iron-carbohydrate complexes are widely used nanoparticles (NPs) to treat iron deficiency anaemia, often associated with medical conditions such as chronic kidney disease, heart failure and various inflammatory conditions. Even though a plethora of physicochemical characterisation data and clinical studies are available for these products, evidence-based correlation between physicochemical properties of iron-carbohydrate complexes and clinical outcome has not fully been elucidated yet. Studies on other metal oxide NPs suggest that early interactions between NPs and blood upon IV injection are key to understanding how differences in physicochemical characteristics of iron-carbohydrate complexes cause variance in clinical outcomes. We therefore investigated the core-ligand structure of two clinically relevant iron-carbohydrate complexes, iron sucrose (IS) and ferric carboxymaltose (FCM), and their interactions with two structurally different human plasma proteins, human serum albumin (HSA) and fibrinogen, using a combination of cryo-scanning transmission electron microscopy (cryo-STEM), x-ray diffraction (XRD), small-angle x-ray scattering (SAXS) and small-angle neutron scattering (SANS). Using this orthogonal approach, we defined the nano-structure, individual building blocks and surface morphology for IS and FCM. Importantly, we revealed significant differences in the surface morphology of the iron-carbohydrate complexes. FCM shows a localised carbohydrate shell around its core, in contrast to IS, which is characterised by a diffuse and dynamic layer of carbohydrate ligand surrounding its core. We hypothesised that such differences in carbohydrate morphology determine the interaction between iron-carbohydrate complexes and proteins and therefore investigated the NPs in the presence of HSA and fibrinogen. Intriguingly, IS showed significant interaction with HSA and fibrinogen, forming NP-protein clusters, while FCM only showed significant interaction with fibrinogen. We postulate that these differences could influence bio-response of the two formulations and their clinical outcome. In conclusion, our study provides orthogonal characterisation of two clinically relevant iron-carbohydrate complexes and first hints at their interaction behaviour with proteins in the human bloodstream, setting a prerequisite towards complete understanding of the correlation between physicochemical properties and clinical outcome.

Ecological and environmental characteristics of a seagrass-dominated hypersaline coastal Mediterranean lagoon: a multidisciplinary approach

In the present paper, sedimentological, water physicochemical data and biological benthic assemblages are compiled to provide an integrated environmental assessment of a protected shallow Mediterranean lagoon with a long history of management interventions (Klisova Lagoon, Western Greece). Satellite remote sensing techniques were used for mapping the seagrass Cymodocea nodosa (Ucria) Asch, which presents an extensive expansion in the study area. The results showed that Klisova is a hypersaline, well-oxygenated lagoon presenting changes in temperature, salinity, pH and dissolved oxygen over the course of 1 year, but largely lacks any spatial differentiation other than an east–west gradient in salinity in spring and summer. Sediment was classified as silty sand to silt, rich in total organic carbon (TOC), total nitrogen (TN) and total phosphorus (TP). The benthic community was characterised by a high species richness and the presence of marine species, without a clear spatial pattern. The multivariate-AZTI’s marine biotic index (M-AMBI) showed that the ecological quality of the macrobenthos was good in most stations. C. nodosa covered over 70% of the lagoon area and formed meadows even in the eastern part of the lagoon where salinity during spring and summer was close to the reported upper tolerance limit of the species (> 50). The present multidisciplinary approach provides valuable baseline information on various components of the ecosystem which can be used as a basis for management bodies and future conservation plans for the lagoon.

Molecular docking, ADME-Tox, DFT and molecular dynamics simulation of butyroyl glucopyranoside derivatives against DNA gyrase inhibitors as antimicrobial agents

The emergence of antibiotic resistance highlights the critical need for novel antimicrobial agents. In this study, we investigated the synthesis of methyl α-D-glucopyranoside (1) analogs (2–6) which play vital roles in bacterial replication, in the context of DNA gyrase inhibitors. The unimolar one-step butyroylation of glucopyranoside furnished the 6-O-butyroyl derivative, which was further converted into five newer 6-O-butyroyl-2,3,4-tri-acyl-α-D-glucopyranoside analogs. The newly synthesized chemical structures were determined through physicochemical, elemental, and spectroscopic data. In vitro studies against bacteria and fungi with PASS (activity spectra for substances) prediction showed excellent antimicrobial activity of these glucopyranoside analogs. The cytotoxicity assessment indicated that the compounds exhibited less toxicity. In-depth molecular docking studies were carried out to elucidate the mechanism of action, binding energies, and interaction profiles of the synthesized compounds targeting gyrase. Additionally, a reference molecule, 4-methyl-5-[3-(methylsulfanyl)-1H-pyrazol-5-yl]-2-thiophen-2-yl-1,3-thiazole, was docked into the gyrase receptor to evaluate the inhibitory potential of the synthesized compounds. Moreover, a 100 ns molecular dynamics simulation process was performed to monitor the behavior of the complex structure, and a stable conformation and binding mode were found in the stimulating environment of the compounds. Pharmacokinetic predictions were investigated to evaluate the absorption, distribution, metabolism and toxicity of these compounds, and the combination of pharmacokinetic and drug-likeness predictions has shown promising results in silico. In summary, an integrated computational approach combining molecular docking, ADME-Tox assessment, DFT calculations, and molecular dynamics simulations highlights the promise of these derivatives as candidates for the development of new antimicrobial agents targeting DNA gyrase.

Environmental impact of PFAS: Filling data gaps using theoretical quantum chemistry and QSPR modeling

Per- and polyfluorinated alkyl substances (PFAS), known for their widespread environmental presence and slow degradation, pose significant concerns. Of the approximately 10,000 known PFAS, only a few have undergone comprehensive testing, resulting in limited experimental data. In this study, we employed a combination of physics-based methods and data-driven models to address gaps in PFAS bioaccumulation potential. Using the COnductor-like Screening MOdel for Realistic Solvents (COSMO-RS) method, we predicted n-octanol/water partition coefficients (logKOW), crucial for PFAS bioaccumulation. Our developed Quantitative Structure-Property Relationship (QSPR) model exhibited high accuracy (R2 = 0.95, RMSEC = 0.75) and strong predictive ability (Q2LOO = 0.93, RMSECV = 0.83). Leveraging the extensive NORMAN, we predicted logKOW for over 4,000 compounds, identifying 244 outliers out of 4519. Further categorizing the database into eight Organisation for Economic Co-operation and Development (OECD) categories, we confirmed fluorine atoms role in enhanced bioaccumulation. Utilizing predicted logKOW, water solubility logSW, and vapor pressure logVP values, we calculated additional physicochemical properties that are responsible for the transport and dispersion of PFAS in the environment. Parameters such as Henry’s Law (kH), air–water partition coefficient (KAW), octanol–air coefficient (KOA), and soil adsorption coefficient (KOC) exhibited favorable correlations with literature data (R2 > 0.66). Our study successfully filled data gaps, contributing to the understanding of ubiquitous PFAS in the environment and estimating missing physicochemical data for these compounds.

High temperature synthesis, surface characterization, and photoluminescence property of boron carbon nitride

The present study demonstrates the synthesis of boron carbon nitride (BCN) by molten salt method which utilizes melamine (source of carbon and nitrogen), boric acid (source of boron) and potassium chloride as the salt. The synthesis is performed at 915 °C for 4 h under N2-atmosphere. The synthesized material is further acid-treated. The physicochemical characterization data for as-synthesized and acid-treated materials confirm successful synthesis of BCN. SEM and AFM data display that synthesized BCN pre and post acid-treatment exhibit sheet-type morphology. Thermogravimetric analysis data confirm that the acid-treated material is thermally stable up to 800 °C, with only 2 % mass-loss is observed till 800 °C. Water contact angle measurement study demonstrates that acid-treatment significantly improves the surface hydrophilicity. Additionally, the low photoluminescence peak intensity of the acid-treated material indicates low electron-hole pair recombination rate. The synthesized material may be useful for the photocatalytic degradation of potentially toxic chemicals from water.

Honey produced by apini and meliponini in Brazil: multivariate analysis of physicochemical parameters, sugar and metabolite profiles

The objective of this study was to investigate honey samples from two bee tribes grouped in Meliponini (stingless bee) and Apini (Apis mellifera) honeys from Brazil, in order to compare their chemical composition. Thirty-four honey samples were collected and evaluated by proton NMR spectroscopy, HPLC and physicochemical parameters, using chemometric methods. Principal component analysis (PCA) was able to discriminate Apini and Meliponini goups. Additionally, the partial least squares discriminant analysis (PLS-DA) models were able to predict the Apini and Meliponini honey samples with sensitivity, specificity and accuracy values close to 100%. Frequency values between 4.00 − 3.00 ppm, corresponding to the sugar region, were important for the classification by the PLS-DA model using NMR data. For the PLS-DA model using physicochemical data, the main parameters for classification were water activity, reducing sugar, moisture, refractive index, total soluble solids, maltose and glucose. Since stingless honeys have no regulation, the data presented in this study can compose a database to assist in the establishment of regulatory criteria. Moreover, the chemometric models proposed can be used as a tool for the quality control of honey, especially for authentication purposes.

Use of water quality parameters to assess the ecological health of Atlantic coastal areas in the northwestern Morocco

Coastal waters are confronted with multiple stressors, including chemical contamination/pollution and climate change. Water quality along the Atlantic coast of Morocco was assessed, in this study, at six stations over four seasons, including three heavily industrialized stations (S2, S4, and S6) and three clean stations (S1, S3, and S5), spreading over a distance of ∼300 km from Azemmour to Essaouira cities. The physicochemical characteristics (temperature, salinity, pH, dissolved oxygen, suspended matter, and sulfate), and chlorophyll-a, as well as nutrients (nitrite, nitrate, ammonium, total phosphorus, orthophosphate, and silicate) were analyzed to investigate their spatial and seasonal trends in the study areas. The results revealed significant spatiotemporal variations in the distribution of the hydrological characteristics across the sampling sites. In addition, the observed sulfate and nutrient concentrations showed significant spatial and seasonal differences. The disturbed stations showed the highest concentrations of nutrients, while the clean stations exhibited the highest concentrations of chlorophyll-a, particularly in the spring season. As expected, the compressive pollution index (CPI) and water pollution index (WPi) results supported the pollution status of stations. Accordingly, the surface seawater quality was better in the clean stations compared to the polluted stations. According to the CPI and WPi values, the sampling stations were classified in the following descending order of pollution, from strongly and moderately polluted stations to slightly or unpolluted stations (S4 > S2 > S6 > S1> S3 > S5). The total phosphorus, orthophosphate, sulfate, and chlorophyll-a concentrations were substantially higher than the surface water quality standards of Morocco, especially at the most industrialized stations in the winter.The physicochemical, biological, and nutrient data obtained in this study provide a valuable reference for assessing the ecological quality status of the Atlantic coastal environments in the study areas.

A comparative analysis of soil physicochemical properties and microbial community structure among four shelterbelt species in the northeast China plain.

The focal point of this study lies in the implementation of a controlled experiment conducted under field conditions. In this experiment, we deliberately selected four shelterbelts within the same field, characterized by identical planting density, and planting year. This deliberate selection effectively mitigated the potential impact of extraneous factors on the three microbiomes, thereby enhancing the reliability and validity of our findings.

Refining the Occurrence of Viral Encephalopathy and Retinopathy, Photobacteriosis, and Vibriosis in Connection with Seawater Physicochemical Parameters: A Five-Year Case Study

The marine environment and its physicochemical parameters play a pivotal role in the context of fish farming. Fundamental physicochemical factors of water, including temperature (T°C), salinity (S psu), dissolved oxygen (D.O. mg/l), and pH, exert a profound influence on the physiology of farmed aquatic animals and the composition of microbial communities. This study aimed to establish correlations between documented disease occurrences in sea bass intensive rearing and the prevailing physicochemical parameters of water. The objective was to analyse the significance of these parameters in disease outbreaks and develop a predictive model for the outbreak risk of key diseases. To this end, real-time physicochemical data were collected daily over five years (2011-2015) from two fish farms (A and B) located in the Gulf of Argostoli, island of Cephalonia, Western Greece. The focus was on incidences of Viral Encephalopathy and Retinopathy (VER), Photobacteriosis caused by Photobacterium damselae subsp. piscicida (PHDP) and Vibriosis caused by Vibrio anguillarum serotype O1 (VAO1). Statistically significant correlations were found between increasing water temperature and salinity and the occurrence of VER, PHDP, and VAO1 diseases. The reduction of dissolved oxygen, when combined with other parameters, synergistically triggered the manifestation of these three diseases. The study’s findings were discussed within the context of their potential to predict disease outbreaks based on fluctuations in the physicochemical parameters of water and anticipated climate change scenarios.

A deep learning-based theoretical protocol to identify potentially isoform-selective PI3Kα inhibitors.

Phosphoinositide 3-kinase alpha (PI3Kα) is one of the most frequently dysregulated kinases known for their pivotal role in many oncogenic diseases. While the side effects linked to existing drugs against PI3Kα-induced cancers provide an avenue for further research, the significant structural conservation among PI3Ks makes it extremely difficult to develop new isoform-selective PI3Kα inhibitors. Embracing this challenge, we herein designed a hybrid protocol by integrating machine learning (ML) with in silico drug-designing strategies. A deep learning classification model was developed and trained on the physicochemical descriptors data of known PI3Kα inhibitors and used as a screening filter for a database of small molecules. This approach led us to the prediction of 662 compounds showcasing appropriate features to be considered as PI3Kα inhibitors. Subsequently, a multiphase molecular docking was applied to further characterize the predicted hits in terms of their binding affinities and binding modes in the targeted cavity of the PI3Kα. As a result, a total of 12 compounds were identified whereas the best poses highlighted the efficiency of these ligands in maintaining interactions with the crucial residues of the protein to be targeted for the inhibition of associated activity. Notably, potential activity of compound 12 in counteracting PI3Kα function was found in a previous in vitro study. Following the drug-likeness and pharmacokinetic characterizations, six compounds (compounds 1, 2, 3, 6, 7, and 11) with suitable ADME-T profiles and promising bioavailability were selected. The mechanistic studies in dynamic mode further endorsed the potential of identified hits in blocking the ATP-binding site of the receptor with higher binding affinities than the native inhibitor, alpelisib (BYL-719), particularly the compounds 1, 2, and 11. These outcomes support the reliability of the developed classification model and the devised computational strategy for identifying new isoform-selective drug candidates for PI3Kα inhibition.

Lake Water Quality Assessment Through GIS based Interpolation Method: A Case Study of Beris Dam, Kedah, Malaysia

Preliminary research on physicochemical and water quality in the Beris dam shows that the water catchment area has the best standards and quality during the observation of the wet season and dry season mainly in the northern states of peninsular Malaysia. The analysis of water quality assessment using the DOE-WQI and Carlson Trophic State Index (CTSI) resulted that during the dry season (February), the average DOE-WQI reading is 88 or Class II; while during the wet season, the average DOE-WQI reading recorded 87.1 (October). Although the CTSI score was 34.2 - 27.0 during wet season and dry season, both seasons were classified as oligotrophic conditions. Some physicochemical parameters also show a high correlation between them and indicates minor water quality issues. The use of more efficient interpolation techniques in water quality studies also reinforces the evaluation of water quality. As a reference point for future water research, GIS interpolation application methods can be more effectively and efficiently used with Inverse Distance Weighted (IDW), Ordinary Kriging and Spline techniques. HIGHLIGHTS Investigation of physicochemical and water quality in lake water in Beris Dam Assessment by using water quality index by DOE-WQI and Carlson Trophic State Index (CTSI) to acknowledge water quality and trophic condition. Analyzing physicochemical data into mathematical method to compare between physicochemical data and correlate between them. Application of GIS based interpolation methods to analyze and referencing physicochemical data into spatial interpolation maps. Comparing appropriate spatial interpolation techniques to analyze physicochemical observation data and index. GRAPHICAL ABSTRACT

EFFECT OF FERMENTATION TIME AND ROASTING TEMPERATURE ON THE CHARACTERISTICS OF WINE COFFEE ARABICA SEMERU

This study was conducted to identify the best fermentation period and roasting temperature for semeru arabica wine coffee. This study used the factorial RSBD research approach (three levels of roasting temperature and four levels of fermentation duration). Physicochemical and organoleptic data were analyzed using ANOVA 5%, LSD 5%, and HSD 5%. Then, the best treatment's ash alkalinity, coffee juice content, and caffeine level were assessed. According to the study, the fermentation period has impact on the moisture level of green beans, the moisture and ash content of roasted beans, acidity, body, and balance. The water and ash content of roasted beans, aroma, flavor, acidity, aftertaste, body, balance, and overall attribute, are influenced by the roasting temperature. Then the interaction between factors significantly affects the water content of roasted beans, flavor, acidity, and body. The best treatment achieved a total score of 81.83 (40 days, 200 °C).

Solid-liquid equilibrium solubility, modeling, Hansen solubility parameter and thermodynamic analysis of 2-Mercaptobenzimidazole in eleven mono-solvents and three binary solvents at different temperatures

The solubility of drugs is an important physicochemical data for its development and design. In this work, the solubility of 2-mercaptobenzimidazole (2-MBI) in eleven mono-solvent solvents (2-propoxyethanol, isopropyl acetate, butyl acetate, 2-methoxyethanol, 2-butanol, ethyl formate, 2-ethoxyethanol, isobutanol, 4-methyl-2-pentanone, 2-butoxyethanol and ethylene glycol) and three binary solvents (2-methoxyethanol + ethyl formate, 2-methoxyethanol + isopropyl acetate, 2-ethoxyethanol+ ethyl formate) was measured by a gravimetric analysis method at the temperatures from 283.15 to 323.15 K. The solubility of 2-MBI in the studied solvents increased with the increasing temperature. The measured solubility data of 2-MBI was described mathematically and back-calculated by CNIBS/R-K model, Margules model, UNIQUAC model, Jouyban-Acree-van't Hoff model and NRTL model. Hansen solubility parameters was calculated to assess the qualitative trend of 2-MBI in all selected mono and binary mixed solvents, analysis results indicating that the solubilization behavior of 2-MBI was intricate and can not only be assessed by one factor. In this study, the apparent thermodynamic parameters including ∆solHo, ∆solSo, ∆solGo, ξH and ξTS were investigated, positive values of ∆solHo indicating that the corresponding dissolution process of 2-MBI in all selected solvents was endothermic. In conclusion, these experimental and thermodynamic analysis can enrich the database and give support for design and optimize the crystallization process of 2-MBI.

Evaluación de la calidad del agua mediante el uso de macroinvertebrados como bioindicadores en el Río Toribio de Ciénaga – Magdalena

Water quality in various aquatic ecosystems has become very important nowadays due to the effects of anthropogenic impact, which is why developed countries have made managements plans for these ecosystems based mostly on the use of physicochemical indices that provide instantaneous data on the state of the resource and, according to these indices, establish regulations on the management of this resource. Therefore, at present the use of bioindicators has become very relevant when evaluating aquatic ecosystems, since they can evaluate not only the quality in physicochemical terms but also the ecological quality of the entire ecosystem. In this sense, the research aimed to evaluate the water quality of the Toribio River using macroinvertebrates as bioindicators, applying the BMWP -Biological Monitoring Working Party- biological index. The study was descriptive since physicochemical data and the different populations of macroinvertebrates present in three stations established in the lower area of the Toribio River were collected in two rainy seasons of the year: one rainy and the other dry. For this, specimen capture, identification and taxonomic classification were carried out to later apply the BMWP index, in order to establish the ecological quality of the ecosystem. Among the data obtained from the sampling, one of the most notable is the difference in macroinvertebrates present in the two seasons studied (dry season and rainy seasons) and how these conditions affect the presence or absence of these species.