Development of Fluorescent Sensors for Biorelevant Anions in Aqueous Media Using Positively Charged Quantum Dots.

Quantum dots (QDs) have captured the attention of the scientific community due to their unique optical and electronic properties, leading to extensive research for different applications. They have also been employed as sensors for ionic species owing to their sensing properties. Detecting anionic species in an aqueous medium is a challenge because the polar nature of water weakens the interactions between sensors and ions. The anions bicarbonate (HCO3-), carbonate (CO32-), sulfate (SO42-), and bisulfate (HSO4-) play a crucial role in various physiological, environmental, and industrial processes, influencing the regulation of biological fluids, ocean acidification, and corrosion processes. Therefore, it is necessary to develop approaches capable of detecting these anions with high sensitivity. This study utilized CdTe QDs stabilized with cysteamine (CdTe-CYA) as a fluorescent sensor for these anions. The QDs exhibited favorable optical properties and high photostability. The results revealed a gradual increase in the QDs' emission intensity with successive anion additions, indicating the sensitivity of CdTe-CYA to the anions. The sensor also exhibited selectivity toward the target ions, with good limits of detection (LODs) and quantification (LOQs). Thus, CdTe-CYA QDs show potential as fluorescent sensors for monitoring the target anions in water sources.

Understanding the Metastability of Theophylline FIII by Means of Low-Frequency Vibrational Spectroscopy.

While theophylline has been extensively studied with multiple polymorphs discovered, there is still currently no conclusive structure for the metastable theophylline form III. In this present work, by combining more widely used techniques such as X-ray diffraction and thermogravimetric analysis with more emerging techniques like low-frequency Raman and terahertz time-domain spectroscopy, to analyze the structure and dynamics of a crystalline system, it was possible to provide further evidence that the form III structure has a theophylline monohydrate structure with the water molecules removed. Solid-state density functional theory simulations were paramount in proving that this proposed structure is correct and explain how vibrational modes within the crystal structures feature and govern polymorphic transitions and the metastable form III. Through the insight provided by both simulated and experimental results, it was possible to decisively conclude the elusive crystal structure of theophylline form III. It was also shown that the correct space group for theophylline monohydrate is not P21/n but, in fact, Pc.

Evaluation of chemometric approaches for polymorphs quantification in tablets using near-infrared hyperspectral images.

Near-Infrared hyperspectral imaging (HSI-NIR) is a useful technique for pharmaceutical research and industry alike. It can provide important surface information such as the polymorphs quantification and its distribution over the tablet. Several chemometric tools are applied for this purpose, with MCR-ALS and PLS regression being the most common approaches. In this work, a detailed comparison between these two approaches is performed. Beyond a "simple" regression comparison, a comparison of the score images (local quantification) was also evaluated. The system under study is tablets with ternary mixtures of Mebendazol (MBZ) polymorphs, microcrystalline cellulose and magnesium stearate. PLS models, in general, gave lower RMSEP (below 1.7% w/w for the three MBZ polymorphs) than the corresponding MCR-ALS predictions. Analyzing the distributions of the scores in the images of each sample shows clear differences between the PLS and MCR-ALS models. The MCR-ALS gave more chemical meaningful distribution maps for all polymorphs, even though the PLS accurately predicts the average concentration across the image. The problem is that the PLS models used the main spectral regions to quantify each MBZ polymorph, but at the same time undermines the minor spectroscopic changes caused by the different polymorphs. Although this may seem as a minor deviation from the truth, the results clearly show that this deviation is detrimental for the analysis of the spatial distribution of the analytes. These results indicate that the optimal multivariate model for multivariate images depend on the goal of the analysis: global quantification or a distribution analysis.

Comparison of macro and micro Raman measurement for reliable quantitative analysis of pharmaceutical polymorphs.

This work reports on the use of micro- and macro-Raman measurements for quantification of mebendazole (MBZ) polymorphs A, B, and C in mixtures. Three Raman spectrophotometers were studied with a laser spot size of 3, 80 and 100 µm and spectral resolutions of 3.9, 9 and 4 cm-1, respectively. The samples studied were ternary mixtures varying the MBZ polymorphs A and C from 0 to 100% and polymorph B from 0 to 30%. Partial Least Squares (PLS) regression models were developed using the pre-processing spectra (2nd derivative) of the ternary mixtures. The best performance was obtained when the macro-Raman configuration was applied, obtaining RMSEP values of 1.68%, 1.24% and 2.03% w/w for polymorphs A, B, and C, respectively. In general, micro-Raman presented worst results for MBZ polymorphs prediction because the spectra obtained with this configuration does not represent the bulk proportion of mixtures, which have different particle morphologies and sizes. In addition, the influence of these particle features on micro-Raman measurements was also studied. Finally, the results demonstrated that reliable analytical quantifying of MBZ polymorphs can be reached using a laser with wider area illuminated, thus enabling acquisition of more reproductive and representative spectra of the mixtures.

High sucrolytic activity by invertase immobilized onto magnetic diatomaceous earth nanoparticles.

Invertase immobilized on magnetic diatomaceous earth nanoparticles (mDE-APTES-invertase) with high sucrolytic activity was obtained by an easy and low-cost method. An experimental design was carried out to investigate the best immobilization conditions and it allowed obtaining an immobilized derivative with a residual specific activity equal to 92.5%. Then, a second experimental design selected the mDE-APTES-invertase with higher specific activity in relation to other derivatives reported in the literature (2.42-fold). Thermal and storage stability for immobilized invertase were found to be 35 °C for 60 min (85% retained activity) and 120 days storage period (80% retained activity), respectively. Besides, a residual activity higher than 60% and 50% were observed for mDE-APTES-invertase after reuse in short and long term, respectively. Given the simple and efficient method to obtain an immobilized derivative with high activity, the mDE nanoparticles appear to be a promising matrix for invertase immobilization as well as for other biomolecules.

Multivariate quantification of mebendazole polymorphs by terahertz time domain spectroscopy (THZ-TDS).

This work presents an analytical method based on terahertz-time domain spectroscopy (THz-TDS) and partial least squares (PLS) regression models to quantify mebendazole (MBZ) polymorphs (forms A, B and C) in pharmaceutical raw material. Mebendazole polymorphs A, B and C were quantified with RMSEP values of 1.5% w/w, 1.2% w/w and 1.8% w/w, respectively. The limits of detection (LOD) ranges obtained with the best PLS regression models were 2.7-4.3% w/w, 2.9-4.0% w/w and 2.4-3.1% w/w, for polymorphs A, B and C, respectively. This analytical performance is better than those for the methods described in the literature using near (NIR) and middle (MIR) infrared spectroscopies. The main advantage of THz spectroscopy is its ability to access directly information related to crystal lattices. According to the results, the developed method is a powerful technique for the quantification of MBZ polymorphs in raw material. This methodology can be implemented as a Process Analytical Technology (PAT) tool for quality control of pharmaceutical feedstock.

Quantitative analysis of mebendazole polymorphs in pharmaceutical raw materials using near-infrared spectroscopy.

This work evaluates the feasibility of using NIR spectroscopy for quantification of three polymorphs of mebendazole (MBZ) in pharmaceutical raw materials. Thirty ternary mixtures of polymorphic forms of MBZ were prepared, varying the content of forms A and C from 0 to 100% (w/w), and for form B from 0 to 30% (w/w). Reflectance NIR spectra were used to develop partial least square (PLS) regression models using all spectral variables and the variables with significant regression coefficients selected by the Jack-Knife algorithm (PLS/JK). MBZ polymorphs were quantified with RMSEP values of 2.37% w/w, 1.23% w/w and 1.48% w/w for polymorphs A, B and C, respectively. This is an easy, fast and feasible method for monitoring the quality of raw pharmaceutical materials of MBZ according to polymorph purity.

Screening analysis of biodiesel feedstock using UV-vis, NIR and synchronous fluorescence spectrometries and the successive projections algorithm.

This paper investigates the use of UV-vis, near infrared (NIR) and synchronous fluorescence (SF) spectrometries coupled with multivariate classification methods to discriminate biodiesel samples with respect to the base oil employed in their production. More specifically, the present work extends previous studies by investigating the discrimination of corn-based biodiesel from two other biodiesel types (sunflower and soybean). Two classification methods are compared, namely full-spectrum SIMCA (soft independent modelling of class analogies) and SPA-LDA (linear discriminant analysis with variables selected by the successive projections algorithm). Regardless of the spectrometric technique employed, full-spectrum SIMCA did not provide an appropriate discrimination of the three biodiesel types. In contrast, all samples were correctly classified on the basis of a reduced number of wavelengths selected by SPA-LDA. It can be concluded that UV-vis, NIR and SF spectrometries can be successfully employed to discriminate corn-based biodiesel from the two other biodiesel types, but wavelength selection by SPA-LDA is key to the proper separation of the classes.