Prediction of pollutant emission characteristics in ISO50001 energy management in the Americas: Uni and multivariate machine learning approach.

The American continent is experiencing significant economic and industrial development driven by sustainability principles. In this context, discussions on improving energy consumption have become increasingly frequent and dynamic across various sectors of civil society, including the implementation of energy efficiency measures as advocated by the ISO50001 energy management standard. However, there is a pressing need to investigate which socioeconomic aspects are responsible for the issuance of this certification in the Americas and how these factors relate to characteristic industrial emissions, especially particulate matter. This study aims to evaluate the socioeconomic factors influencing ISO50001 standard issuance and how these adjusted factors correlate with particulate matter of 2.5 µm and 10 µm dimensions. To achieve this, machine learning techniques were employed, considering the complex nature and risk of data overfitting. Model fitting was performed through multiple lasso regression, and the relationship between the adjusted factors was examined through cross-correlation analysis. The analyses indicate a strong correlation of adjusted macroeconomic indicators, especially with PM2.5, suggesting an association with cardiorespiratory problems and methane-related origins. This work is of great relevance to academia as it proposes new concepts regarding the interaction between energy efficiency standards and particulate matter. For the industrial sector, the adjusted factors provide guidance for standard implementation while also helping to mitigate health issues. Additionally, for the government, these results can assist in formulating policies to address specific health problems related to this area.

Biomarkers in psychiatric disorders.

Psychiatric disorders represent a significant socioeconomic and healthcare burden worldwide. Of these, schizophrenia, bipolar disorder, major depressive disorder and anxiety are among the most prevalent. Unfortunately, diagnosis remains problematic and largely complicated by the lack of disease specific biomarkers. Accordingly, much research has focused on elucidating these conditions to more fully understand underlying pathophysiology and potentially identify biomarkers, especially those of early stage disease. In this chapter, we review current status of this endeavor as well as the potential development of novel biomarkers for clinical applications and future research study.

Evaluation of physicochemical properties as supporting information on quality control of raw materials and veterinary pharmaceutical formulations.

This study aimed to show that the physicochemical proprieties obtained by Fourier transform infrared spectroscopy (FTIR), thermogravimetry (TG), and scanning electronic microscopy (SEM) can be useful tools for evaluating the quality of active pharmaceutical ingredients (APIs) and pharmaceutical products. In addition, a simple, sensitive, and efficient method employing HPLC-DAD was developed for simultaneous determination of lidocaine (LID), ciprofloxacin (CFX) and enrofloxacin (EFX) in raw materials and in veterinary pharmaceutical formulations. Compounds were separated using a Gemini C18 (250 mm × 4.6 mm, 5 µm) Phenomenex® column, at a temperature of 25 °C, with a mobile phase containing 10 mM of phosphoric acid (pH 3.29): acetonitrile (85.7:14.3, v/v) and a flow rate of 1.5 mL/min. Physicochemical characterization by TG, FTIR, and SEM of raw materials of LID, CFX, and EFX provided information useful for the evaluation, differentiation, and qualification of raw materials. Finally, the HPLC method was proved to be useful for evaluation of raw material and finished products, besides satisfying the need for an analytical method that allows simultaneous determination of EFX, CFX, and LID, which can also be extended to other matrices and applications.

Efficient molecularly imprinted polymer as a pipette-tip solid-phase sorbent for determination of carvedilol enantiomers in human urine.

In this work, an efficient pipette tip based on molecularly imprinted polymers solid-phase extraction (PT-MIP-SPE) method was developed for carvedilol (CAR) analysis. This compound is available in clinical practice as a racemic mixture, in which (-)-(S)-CAR is a ß- and α1-adrenergic antagonist, while (+)-(R)-CAR only acts as an α1-adrenergic antagonist. Enantioseparation of CAR presented satisfactory retention times (5.85 and 14.84min), acceptable theoretical plates (N=2048 and 2018) and good resolution (Rs=9.27). The separation was performed using a Chiralpak® IA column (100mm×4.6mm, 3µm), a mixture of methanol:ethanol:water (64:15:21, v/v/v) plus 0.3% diethylamine as mobile phase, temperature of 35°C and flow rate of 1.5mLmin-1. After density functional theory calculations based on prepolymerization complexes, the best protocol for the MIP synthesis was chosen. Then, some parameters that affect the PT-MIP-SPE technique were investigated. After optimization, the best conditions were 300µL of water as washing solvent, 500µL of acetonitrile:acetic acid (7:3, v/v) as eluting solvent, 20mg of MIP, 500µL of urine sample (pH 12.5) and no addition of NaCl. Recoveries±relative standard deviation (RSD%) for (+)-(R)-CAR and (-)-(S)-CAR were 101.9±4.8% and 104.6±2.1%, respectively. The method was linear over the concentration range from 20 to 1280ngmL-1 for each enantiomer, with correlation coefficients larger than 0.99 for both enantiomers. The method was applied successfully in a preliminary study of urinary excretion after administration of CAR racemate to a healthy volunteer.

Molecularly imprinted microparticles in lipid-based formulations for sustained release of donepezil.

Donepezil is a drug administered for Alzheimer's disease treatment, and it is a potential template molecule for imprinted microparticles. The precipitation polymerization technique allows the synthesis of spherical imprinted microparticles, and the intermolecular interactions among drug and molecularly imprinted polymers (MIPs) play a promising role for delineating drug delivery systems. Once that donepezil is a poorly-water soluble compound, lipid based-formulations (LBFs) may enhance its oral administration. Based on this, LBFs are useful vehicles to incorporate imprinted microparticles synthesized by precipitation polymerization. In these formulations, the drug dissolved in lipids is accessible to adsorbate in the polymers, and the hydrophobic environment of lipids increases the molecular recognition of MIPs. The formulations based on MIPs using pure oleic acid as vehicle prolong the in vitro release of donepezil up to several hours by a Fickian diffusion mechanism, and it provides a multiphasic release pattern related to the heterogeneity of the binding sites. The modulation of donepezil release from MIPs-based formulations using oil vehicles may contribute to decrease its side effects, possibly regulating its absorption rate in the gastrointestinal tract. These systems represent a novel technological platform to prolong the delivery not only for donepezil, but also for a variety of therapeutics.

Analysis of fluoxetine and norfluoxetine in human plasma by liquid-phase microextraction and injection port derivatization GC-MS.

A two-phase liquid phase microextraction using a hollow fiber combined with injection port derivatization and gas chromatographic analysis was developed for extracting and detecting fluoxetine (FLU) and norfluoxetine (NOR) in human plasma. Simultaneous extraction in a multiple tube shaker was used and, afterward, the organic phase was simply injected together with the derivatizing agent n-methyl-bis(trifluoroacetamide) (MBTFA). Factors influencing injection port derivatization, and several extraction parameters were optimized. Under optimal conditions the proposed method provided linearity between 10 and 500ngmL(-1) (R(2)=0.9973) for FLU, and between 15 and 500ngmL(-1) (R(2)=0.9972) for NOR. Intra-assay precision (RSD) between 4.8 and 13.1% and inter-assay between 5.4 and 14.2% were obtained, with detection and quantification limits of 3 and 10ngmL(-1), and of 5 and 15ngmL(-1) for FLU and NOR, respectively, using selected ion monitoring mode. Selectivity, short term stability and extraction efficiency were also evaluated. This method was simple, cheap, and environmentally friendly, yielding significant reduction of solvents and derivatizing agent consumption. The method was successfully applied to the analysis of samples from 5 patients under fluoxetine treatment.

A homemade autosampler/injector commutator for flow injection analysis.

An autosampler/injector commutator for flow injection analysis (FIA) was constructed with electronic components of used equipments. The apparatus is controlled by commercially available multifunctional interface (PCL711B) connected to a personal computer, and the software was written in Visual Basic language. The system was applied to water analysis and it presented satisfactory results. The low cost and simplicity are the principal characteristics of the autosampler/injector commutator.