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A fast, simple, and reliable method for determination of metformin was developed by coupling surface-enhanced Raman spectroscopy (SERS) with chemometric methods. This relayed on the utilization of a portable Raman spectrometer and of citrate stabilized gold nanoparticles (AuNPs) as substrate, to carry out the measurement of SERS scattering signals, thus assuring improved sensitivity. The obtained datasets were analysed using principal component analysis (PCA) and partial least squares (PLS) regression. Upon optimization of the PLS model, in terms of latent variables, spectral region and pre-processing techniques, RMSECV and R 2 CV values of 0.42 mg/L and 0.94, respectively, were obtained. The optimized PLS regression model was further validated with the projection of commercial pharmaceutical samples, providing good results in terms of R 2 P (0.97), RE (4.54 %) and analytical sensitivity (2.13 mg/L)., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

A sensing platform combining carbon dots (CDs, with blue emission) and thiomalic acid (TMA)-capped AgInS 2 quantum dots (QDs, with orange emission) was developed aiming the photoluminescence (PL) ratiometric determination of ibandronic acid (IBAN), a bisphosphonate pharmaceutical. The ternary AgInS 2 QDs were used for IBAN probing, undergoing a concentration-related PL quenching in its presence, whilst the PL of CDs remained practically unaffected due to its chemical inertness towards the antiresorptive drug, provided an intrinsic self-reference fluorophore. In addition, a visual sensing approach was also proposed, employing for the first time ternary QDs. This relied on RGB images acquired by means of a digital camera and seek the development of a rapid IBAN screening test. The developed sensing platforms were employed for IBAN determination in samples with pharmaceutical interest providing good results, in accordance to the reported IBAN levels, and obtaining recovery values between 98 and 103%., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

In this work a kinetic fluorometric methodology relying on the time-based monitoring of the photoluminescence quenching of AgInS 2 ternary quantum dots induced by oxytetracycline, was developed. The kinetic approach allowed not only to reduce the LOD and improve sensitivity and selectivity but also to collect second-order data that was explored for the quantification of the target analyte in the presence of uncalibrated interfering species. Upon processing the acquired second-order kinetic PL data by unfolded partial least-squares (U-PLS), oxytetracycline was quantified in commercially available pharmaceutical formulations. The obtained results, namely an R 2 P higher than 0.99 and RE lower than 8%, proved the suitability and accuracy of the developed approach., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Peanut oil is considered one of the best frying oils, and, consequently there is an increasing worldwide demand. This has led to adulteration practices with unhealthy, synthetic or less expensive oils which raises concerns related with public health safety. Therefore, there is a high need for rapid, versatile, low-cost and reliable analytical methods, such as vibrational spectroscopic techniques, capable of identifying and quantifying the respective adulteration. The objective of this work focused on the application of two different vibrational spectroscopic techniques (NIR and Raman spectroscopy) for the qualitative and quantitative analysis of two adulterants in pure peanut oil, namely corn oil and vegetable oil. For the quantitative analysis two chemometric methods, namely PLS and MCR-ALS, were compared while for the qualitative analysis only MCR-ALS was tested. The analysis of peanut oil adulteration was performed by adding each adulterant individually and also by blending the peanut oil with both adulterants simultaneously. A total of 69 samples were analyzed, which was comprised by two sets of 20 samples each containing just one adulterant and another set of 29 samples containing both adulterants. Several pre-processing techniques were tested. The qualitative analysis performed by MCR-ALS allowed the identification of all the adulterants using both NIR and Raman spectra, with correlation coefficients higher than 0.99. For the quantification, none of the chemometric methods as well as the vibrational spectroscopic techniques tested showed significant better results. Nonetheless, the determination coefficients and the relative percentage errors for the validation samples for most of the developed models were higher than 0.98 and lower than 15%, respectively. Concluding, MCR-ALS was capable of correctly extracting the spectral profiles of all the adulterants in very complex mixtures (as the pure spectra of the adulterants and peanut oil are very similar) and both MCR-ALS and PLS were able to quantify the adulteration with low RE. To the best of our knowledge, it was the first time that MCR-ALS was used for the qualitative analysis of peanut oil adulteration (with all adulterants added simultaneously) and MCR-ALS and PLS were compared for the quantification of peanut oil adulteration using both NIR and Raman spectroscopy., (Copyright © 2021 Elsevier B.V. All rights reserved.)

The present short communication reports a promising analytical method for authentication of milk based on first-order near-infrared (NIR) spectroscopic data coupled to data driven soft independent modeling of class analogy (DD-SIMCA). This one-class classifier was able to correctly classify all samples of genuine milk powder as members of the target class from samples of milk powder adulterated with melamine and sucrose in a concentration range of 0.8-2% (w/w) and 1-3% (w/w), respectively. Multivariate curve resolution - alternating least-squares (MCR-ALS) was applied as a complementary chemometric model to DD-SIMCA aimed at retrieving pure profiles, allowing to identify the chemical composition of samples properly attributed in the target class or not, providing further investigation from forensic point of view. In order to extend the prime focus of the present report, which was aimed at developing an appropriate chemometric model for authentication purposes, the quantification analysis was also performed. This was done by successful bilinear data decomposition of NIR spectra into pure profiles for the contributing components contained in the system studied (milk and adulterants), allowing to quantify analytes with strong overlapping profiles, even in the presence of an uncalibrated interferent, as demonstrated in this short communication using MCR-ALS under various constraints in order to decrease the rotational ambiguity., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

This work focused on the combination of CdTe and AgInS 2 quantum dots in a dual-emission nanoprobe for the simultaneous determination of folic acid and Fe(II) in pharmaceutical formulations. The surface chemistry of the used QDs was amended with suitable capping ligands to obtain appropriate reactivity in terms of selectivity and sensitivity towards the target analytes. The implementation of PL-based sensing schemes combining multiple QDs of different nature, excited at the same wavelength and emitting at different ones, allowed to obtain a specific analyte-response profile. The first-order fluorescence data obtained from the whole emission spectra of the CdTe/AgInS 2 combined nanoprobe upon interaction with folic acid and Fe(II) were processed by using chemometric tools, namely partial least-squares (PLS) and artificial neural network (ANN). This enabled to circumvent the selectivity issues commonly associated with the use of QDs prone to indiscriminate interaction with multiple species, which impair reliable and accurate quantification in complex matrices samples. ANN demonstrated to be the most efficient chemometric model for the simultaneous determination of both analytes in binary mixtures and pharmaceutical formulations due to the non-linear relationship between analyte concentration and fluorescence data that it could handle. The R 2 P and SEP% obtained for both analytes quantification in pharmaceutical formulations through ANN modelling ranged from 0.92 to 0.99 and 5.7-9.1%, respectively. The obtained results revealed that the developed approach is able to quantify, with high reliability and accuracy, more than one analyte in complex mixtures and real samples with pharmaceutical interest., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

This work focused the implementation of FRET processes between CdTe quantum dots (QDs), acting as donors, and gold nanoparticles (AuNPs), behaving as acceptors, for the determination of several bioactive thiols such as captopril, glutathione, l-cysteine, thiomalic acid and coenzyme M. The surface chemistry of the QDs and AuNPs was adjusted with adequate capping ligands, i.e. mercaptopropionic acid and cysteamine, respectively, to guarantee the establishment of strong electrostatic interaction between them and promoting the formation of stable FRET assemblies. Under these circumstances the fluorescence emission of the QDs was completely suppressed by the AuNPs. The assayed target analytes were capable of disrupting the donor-acceptor assemblies yielding a concentration-related reversion of the FRET process and restoring QDs fluorescence emission. Distinct mechanisms, involving enhancing of the QDs quantum yield (QY), AuNPs agglomeration, nanoparticles detachment, etc., could be proposed to explain the referred FRET reversion. The developed approach assured good analytical working ranges and demonstrate adequate sensitivity for the assayed compounds, anticipating great prospective for implementing rapid, simple and reliable sensing methodologies for the monitoring of pharmaceutical, food and environmental species. However, selectivity could be a hindrance in the detection of these bioactive thiols in more complex matrices such as environmental and food samples. This problem could be circumvented through the employment of multivariate chemometric methods for the analysis and processing of whole fluorometric response. Moreover, the proposed methodology shows a great analytical versatility since it is possible to easily adapt the surface chemistry, of both QDs and AuNPs, to the chemical nature of the target analyte., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Gillespie syndrome (GS) [MIM: 206700] is a very rare condition characterized by bilateral iris defect, congenital hypotonia, cerebellar ataxia and intellectual disability. The typical iris anomaly is considered necessary to the diagnosis of GS. Recently, variants in ITPR1 were described causing GS. Non-neurological features were reported in few patients. Here we describe two consanguineous siblings with GS and a novel homozygous ITPR1 pathogenic variant (p.N984fs). They also present a cardiac defect (pulmonary valve stenosis) and one sib had a genitourinary malformation (ureteropelvic junction obstruction). Our report reinforces ITPR1 as the cause of GS and suggests a possible role of ITPR1 in the development of other organs., (Copyright © 2017 Elsevier Masson SAS. All rights reserved.)

Semiconductor quantum dots (QDs) have demonstrated a great potential as fluorescent probes for heavy metals monitoring. However, their great reactivity, whose tunability could be difficult to attain, could impair selectivity yielding analytical results with poor accuracy. In this work, the combination in the same analysis of multiple QDs, each with a particular ability to interact with the analyte, assured a multi-point detection that was not only exploited for a more precise analyte discrimination but also for the simultaneous discrimination of multiple mutually interfering species, in the same sample. Three different MPA-CdTe QDs (2.5, 3.0 and 3.8nm) with a good size distribution, confirmed by the FWHM values of 48.6, 55.4 and 80.8nm, respectively, were used. Principal component analysis (PCA) and partial least squares regression (PLS) were used for fluorescence data analysis. Mixtures of two MPA-CdTe QDs, emitting at different wavelength namely 549/566, 549/634 and 566/634nm were assayed. The 549/634nm emitting QDs mixture provided the best results for the discrimination of distinct ions on binary and ternary mixtures. The obtained RMSECV and R 2 CV values for the binary mixture were good, namely, from 0.01 to 0.08mgL -1 and from 0.74 to 0.89, respectively. Regarding the ternary mixture the RMSECV and R 2 CV values were good for Hg(II) (0.06 and 0.73mgL -1 , respectively) and Pb(II) (0.08 and 0.87mg L -1 , respectively) and acceptable for Cu(II) (0.02 and 0.51mgL -1 , respectively). In conclusion, the obtained results showed that the developed approach is capable of resolve binary and ternary mixtures of Pb (II), Hg (II) and Cu (II), providing accurate information about lead (II) and mercury (II) concentration and signaling the occurrence of Cu (II)., (Copyright © 2017 Elsevier B.V. All rights reserved.)

In this work, a fluorometric approach for the selective determination of calcium by using CdTe nanocrystals as chemosensors, was developed. The quantum dots interacted not with the metal, but with a ligand that also bonded the metal. The fluorescence response was modulated by the extension of the competitive metal-ligand binding, and therefore the amount of free ligand. CdTe quantum dots (QDs) with different capping layers were evaluated, as the QDs surface chemistry and capping nature affected recognition, thus the magnitude of the ensuing fluorescence quenching. The developed procedure was automated by using a multipumping flow system. Upon optimization, thioglycolic acid (TGA) and EDTA were selected as capping and ligand, respectively, providing a linear working range for calcium concentrations between 0.80-3.20 mg L(-1), and a detection limit of 0.66 mg L(-1). A quenching mechanism relying on nanocrystal destabilization upon detachment of surface Cd by the ligand was proposed., (Copyright © 2014 Elsevier B.V. All rights reserved.)