Статті в журналах з теми "NMR Methodologies Development"

While atomic scale structural and dynamic information are hallmarks of nuclear magnetic resonance (NMR) methodologies, sensitivity is a fundamental limitation in NMR studies. Fully exploiting NMR capabilities to study membrane proteins is further hampered by their dilution within biological membranes. Recent developments in dynamic nuclear polarization (DNP), which can transfer the relatively high polarization of unpaired electrons to nuclear spins, show promise for overcoming the sensitivity bottleneck and enabling NMR characterization of membrane proteins under native-like conditions. Here we discuss fundamental aspects of DNP-enhanced solid-state NMR spectroscopy, experimental details relevant to the study of lipid assemblies and incorporated proteins, and sensitivity gains which can be realized in biomembrane-based samples. We also present unique insights which can be gained from DNP measurements and prospects for further development of the technique for elucidating structures and orientations of membrane proteins in native lipid environments.

It is now well established that uncontrolled proliferation of tumour cells together with the chaotic and poorly regulated blood supply of solid tumours result in tissue hypoxia, and that hypoxic regions of tumours are resistant to radiotherapy and chemotherapy. The development and application of non–invasive methods to rapidly determine the degree and extent of tumour hypoxia in an individual tumour would clearly enhance cancer treatment strategies. This review describes the current status of two 19 F nuclear magnetic resonance (NMR) methodologies that have been exploited to investigate tumour hypoxia, namely: (i) 19 F NMR oximetry following administration of perfluorocarbons, from which tumour p O 2 measurements can be made; and (ii) 19 F NMR measurements of the tumour retention of fluorinated 2–nitroimidazoles.

Abstract NMR serves as an important technique for probing rock pore space, such as pore structure characterization, fluid identification, and petrophysical property testing, due to the reusability of cores, convenience in sample processing, and time efficiency in laboratory tests. In practice, NMR signal collection is normally achieved through polarized nuclei relaxation which releases crucial relaxation messages for result interpretation. The impetus of this work is to help engineers and researchers with petroleum background obtain new insights into NMR principals and extend existing methodologies for characterization of unconventional formations. This article first gives a brief description of the development history of relaxation theories and models for porous media. Then, the widely used NMR techniques for characterizing petrophysical properties and pore structures are presented. Meanwhile, limitations and deficiencies of them are summarized. Finally, future work on improving these insufficiencies and approaches of enhancement applicability for NMR technologies are discussed.

Paintings are complex multi-layered systems made of organic and inorganic materials. Several factors can affect the degradation of paintings, such as environmental conditions, past restoration works and, finally, the type of painting technique and the art materials used over the centuries. The chemical–physical characterization of paintings is a constant challenge that requires research into and the development of novel analytical methodologies and processes. In recent years, solvents and water-related issues in paintings are attracting more attention, and several studies have been focused on analyzing the interaction between water molecules and the constitutive materials. In this study, recent applications applying different NMR methodologies were shown, highlighting the weakness and the strength of the techniques in analyzing paintings. In particular, the study of water and its diffusive interactions within wall and oil paintings was performed to prove how the portable NMR can be used directly in museums for planning restoration work and to monitor the degradation processes. Furthermore, some preliminary results on the analysis of varnishes and binders, such us linseed oil, shellac, sandarac and colophony resins, were obtained by 1H HR-MAS NMR spectroscopy, highlighting the weakness and strengths of this technique in the field of conservation science.

The employment of nuclear magnetic resonance (NMR) spectroscopy for studying crystalline porous materials formation is reviewed in the context of the development of in situ methodologies for the observation of the real synthesis medium, with the aim of unraveling the nucleation and growth processes mechanism. Both liquid and solid state NMR techniques are considered to probe the local environment at molecular level of the precursor species either soluble in the liquid phase or present in the reactive gel. Because the mass transport between the liquid and solid components of the heterogeneous system plays a key role in the synthesis course, the two methods provide unique insights and are complementary. Recent technological advances for hydrothermal conditions NMR are detailed and their applications to zeolite and related materials crystallization are illustrated. Achievements in the field are exemplified with some representative studies of relevance to zeolites, aluminophosphate zeotypes, and metal-organic frameworks.

As fragment-based drug discovery has become mainstream, there has been an increase in various screening methodologies. Protein-observed 19F (PrOF) NMR and 1H CPMG NMR are two fragment screening assays that have complementary advantages. Here, we sought to combine these two NMR-based assays into a new screening workflow. This combination of protein- and ligand-observed experiments allows for a time- and resource-efficient multiplexed screen of mixtures of fragments and proteins. PrOF NMR is first used to screen mixtures against two proteins. Hit mixtures for each protein are identified then deconvoluted using 1H CPMG NMR. We demonstrate the benefit of this fragment screening method by conducting the first reported fragment screens against the bromodomains of BPTF and Plasmodium falciparum (Pf) GCN5 using 467 3D-enriched fragments. The hit rates were 6%, 5% and 4% for fragments binding BPTF, PfGCN5, and fragments binding both proteins, respectively. Select hits were characterized, revealing a broad range of affinities from low µM to mM dissociation constants. Follow-up experiments supported a low-affinity second binding site on PfGCN5. This approach can be used to bias fragment screens towards more selective hits at the onset of inhibitor development in a resource- and time-efficient manner.

Nuclear Magnetic Resonance (NMR) is a well-suited methodology to study bone composition and structural properties. This is because the NMR parameters, such as the T2 relaxation time, are sensitive to the chemical and physical environment of the 1H nuclei. Although magnetic resonance imaging (MRI) allows bone structure assessment in vivo, its cost limits the suitability of conventional MRI for routine bone screening. With difficulty accessing clinically suitable exams, the diagnosis of bone diseases, such as osteoporosis, and the associated fracture risk estimation is based on the assessment of bone mineral density (BMD), obtained by the dual-energy X-ray absorptiometry (DXA). However, integrating the information about the structure of the bone with the bone mineral density has been shown to improve fracture risk estimation related to osteoporosis. Portable NMR, based on low-field single-sided NMR devices, is a promising and appealing approach to assess NMR properties of biological tissues with the aim of medical applications. Since these scanners detect the signal from a sensitive volume external to the magnet, they can be used to perform NMR measurement without the need to fit a sample inside a bore of a magnet, allowing, in principle, in vivo application. Techniques based on NMR single-sided devices have the potential to provide a high impact on the clinical routine because of low purchasing and running costs and low maintenance of such scanners. In this review, the development of new methodologies to investigate structural properties of trabecular bone exploiting single-sided NMR devices is reviewed, and current limitations and future perspectives are discussed.

Micelles composed of amphiphilic copolymers linked to a radioactive element are used in nuclear medicine predominantly as a diagnostic application. A relevant advantage of polymeric micelles in aqueous solution is their resulting particle size, which can vary from 10 to 100 nm in diameter. In this review, polymeric micelles labeled with radioisotopes including technetium (99mTc) and indium (111In), and their clinical applications for several diagnostic techniques, such as single photon emission computed tomography (SPECT), gamma-scintigraphy, and nuclear magnetic resonance (NMR), were discussed. Also, micelle use primarily for the diagnosis of lymphatic ducts and sentinel lymph nodes received special attention. Notably, the employment of these diagnostic techniques can be considered a significant tool for functionally exploring body systems as well as investigating molecular pathways involved in the disease process. The use of molecular modeling methodologies and computer-aided drug design strategies can also yield valuable information for the rational design and development of novel radiopharmaceuticals.

LC-SPE/cryo NMR and MS methodologies have been developed and employed for a rapid structure determination of 4″-tetrahydrofurfuryl macrozone reaction mixture components. Macrozones, novel conjugates of azithromycin, and thiosemicarbazones have shown very good in vitro antibacterial activities against susceptible and some resistant bacterial strains and are promising agents for further development. The post-column multiple trapping of the chromatographically separated reaction mixture components on the SPE cartridges increased the sensitivity and together with cryogenically cooled NMR probe made it possible to identify and structurally characterize main 4″-tetrahydrofurfuryl macrozone reaction mixture compounds including those present at very low concentration level. This approach has several advantages over a classical off-line procedure, efficiency and low solvent consumption being the two most important ones. All identified components were process-related. It has been demonstrated that two different kinds of compounds with respect to structure were identified, i.e., macrolide-related and thiosemicarbazone-related ones. This methodology can serve as a platform for reliable and effective macrolides reaction components structure profiling, serving as both isolation and identification tools.

Among phosphorylated derivatives, phosphinates occupy a prominent place due to their ability to be bioisosteres of phosphates and carboxylates. These properties imply the necessity to develop efficient methodologies leading to phosphinate scaffolds. In recent years, our team has explored the nucleophilic potential of silylated phosphonite towards various electrophiles. In this paper, we propose to extend our study to other electrophiles. We describe here the implementation of a cascade reaction between (trimethylsilyl)imidates and hypophosphorous acid mediated by a Lewis acid allowing the synthesis of aminomethylenebisphosphinate derivatives. The present study focuses on methodological development including a careful NMR monitoring of the cascade reaction. The optimized conditions were successfully applied to various aliphatic and aromatic substituted (trimethylsilyl)imidates, leading to the corresponding AMBPi in moderate to good yields.

A fast, economic, and eco-friendly methodology for the wine variety and geographical origin differentiation using 13C nuclear magnetic resonance (NMR) data in combination with machine learning was developed. Wine samples of different grape varieties cultivated in different regions in Greece were subjected to 13C NMR analysis. The relative integrals of the 13C spectral window were processed and extracted to build a chemical fingerprint for the characterization of each specific wine variety, and then subjected to factor analysis, multivariate analysis of variance, and k-nearest neighbors analysis. The statistical analysis results showed that the 13C NMR fingerprint could be used as a rapid and accurate indicator of the wine variety differentiation. An almost perfect classification rate based on training (99.8%) and holdout methods (99.9%) was obtained. Results were further tested on the basis of Cronbach’s alpha reliability analysis, where a very low random error (0.30) was estimated, indicating the accuracy and strength of the aforementioned methodology for the discrimination of the wine variety. The obtained data were grouped according to the geographical origin of wine samples and further subjected to principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). The PLS-DA and variable importance in projection (VIP) allowed the determination of a chemical fingerprint characteristic of each geographical group. The statistical analysis revealed the possibility of acquiring useful information on wines, by simply processing the 13C NMR raw data, without the need to determine any specific metabolomic profile. In total, the obtained fingerprint can be used for the development of rapid quality-control methodologies concerning wine.

The definition of metabolic syndrome (MetS) has undergone several changes over the years due to the difficulty in establishing universal criteria for it. Underlying the disorders related to MetS is almost invariably a pro-inflammatory state related to altered glucose metabolism, which could lead to elevated cardiovascular risk. Indeed, the complications closely related to MetS are cardiovascular diseases (CVDs) and type 2 diabetes (T2D). It has been observed that the predisposition to metabolic syndrome is modulated by complex interactions between human microbiota, genetic factors, and diet. This review provides a summary of the last decade of literature related to three principal aspects of MetS: (i) the syndrome’s definition and classification, pathophysiology, and treatment approaches; (ii) prediction and diagnosis underlying the biomarkers identified by means of advanced methodologies (NMR, LC/GC-MS, and LC, LC-MS); and (iii) the role of foods and food components in prevention and/or treatment of MetS, demonstrating a possible role of specific foods intake in the development of MetS.

The development of the modern society imposes a fast-growing demand for new advanced functional polymer materials. To this aim, one of the most plausible current methodologies is the end-group functionalization of existing conventional polymers. If the end functional group is able to polymerize, this method enables the synthesis of a molecularly complex, grafted architecture that opens the access to a wider range of material properties, as well as tailoring the special functions required for certain applications. In this context, the present paper reports on α-thienyl-ω-hydroxyl-end-groups functionalized oligo-(D,L)-lactide (Th-PDLLA), which was designed to combine the polymerizability and photophysical properties of thiophene with the biocompatibility and biodegradability of poly-(D,L)-lactide. Th-PDLLA was synthesized using the path of “functional initiator” in the ring-opening polymerization (ROP) of (D,L)-lactide, assisted by stannous 2-ethyl hexanoate (Sn(oct)2). The results of NMR and FT-IR spectroscopic methods confirmed the Th-PDLLA’s expected structure, while the oligomeric nature of Th-PDLLA, as resulting from the calculations based on 1H-NMR data, is supported by the findings from gel permeation chromatography (GPC) and by the results of the thermal analyses. The behavior of Th-PDLLA in different organic solvents, evaluated by UV–vis and fluorescence spectroscopy, but also by dynamic light scattering (DLS), suggested the presence of colloidal supramolecular structures, underlining the nature of the macromonomer Th-PDLLA as an “shape amphiphile”. To test its functionality, the ability of Th-PDLLA to work as a building block for the synthesis of molecular composites was demonstrated by photoinduced oxidative homopolymerization in the presence of diphenyliodonium salt (DPI). The occurrence of a polymerization process, with the formation of a thiophene-conjugated oligomeric main chain grafted with oligomeric PDLLA, was proven, in addition to the visual changes, by the results of GPC, 1H-NMR, FT-IR, UV–vis and fluorescence measurements.

AbstractOne of the most challenging aspects of understanding the flow of gas and water during testing in clay-rich low-permeability materials is the difficulty in visualizing localized flow. Whilst understanding has been increased using X-ray Computed-tomography (CT) scanning, synchrotron X-ray imaging and Nuclear Magnetic Resonance (NMR) imaging, real-time testing is problematic under realistic in situ conditions confining pressures, which require steel pressure vessels. These methods tend not to have the nano-metre scale resolution necessary for clay mineral visualization, and are generally not compatible with the long duration necessary to investigate flow in such materials. Therefore other methods are necessary to visualize flow paths during post-mortem analysis of test samples. Several methodologies have been established at the British Geological Survey (BGS), in order to visualize flow paths both directly and indirectly. These include: (1) the injection of fluorescein-stained water or deuterium oxide; (2) the introduction of nanoparticles that are transported by carrier gas; (3) the use of radiologically tagged gas; and (4) the development of apparatus for the direct visualization of clay. These methodologies have greatly increased our understanding of the transport of water and gas through intact and fractured clay-rich materials. The body of evidence for gas transport through the formation of dilatant pathways is now considerable. This study presents observations using a new apparatus to directly visualize the flow of gas in a kaolinite paste. The results presented provide an insight into the flow of gas in clay-rich rocks. The flow of gas through dilatant pathways has been shown in a number of argillaceous materials (Angeli et al., 2009; Autio et al., 2006; Cuss et al., 2014; Harrington et al., 2012). These pathways are pressure induced and an increase in gas pressure leads to the dilation of pathways. Once the gas breakthrough occurs, pressure decreases and pathways begin to close. This new approach is providing a unique insight into the complex processes involved during the onset, development and closure of these dilatant gas pathways.

The Interdepartmental Research Centre for the Development of Crystallography (CrisDi) aims to be an institution of reference for researchers at the University of Turin interested on the field of diffraction (X-rays, neutrons and electrons), to promote the knowledge and dissemination of crystallography, and to facilitate the access to available laboratory instrumentation (diffractometers and TEM) and to large scale facilities (synchrotron and neutron sources). CrisDi hosts scientists with interest in the fields of solid state chemistry and physics, organic, inorganic, organometallic and theoretical chemistry, mineralogy, biology, pharmaceutical and agricultural sciences. The Centre encourages the design and the development of new methodologies and applications, and supports the enhancement of the available instruments. The submission of proposals at large scale instruments is encouraged specially for young researchers and PhD students. The cultural and scientific interchange among crystallographers coming from different disciplines is strongly encouraged by CrisDi. A main task of the CrisDi is the annual organization of a post-grade level School with a series of courses dedicated to: (i) basic level crystallography (symmetry, theory of diffraction, crystal-chemistry), diffraction techniques (single crystal and powder X-ray diffraction, neutron and electron scattering); (ii) advanced level (high temperature and high pressure structural studies, macromolecular crystallography, time resolved crystallography and kinetic studies); (iii) spectroscopic approaches (XAFS, XANES, XES and NMR) in crystallography. The school, which is held every year in May for about 20 ECTS equivalent, has no tuition fees and is also open to non-academia people.

Over the past decade, drug resistance has become a growing problem in the treatment of infectious diseases caused by bacteria, fungi and viruses. In particular, resistance of bacterial pathogens to current antibiotics has emerged as a measure of health problems. This is especially true in the case of infectious diseases such as pneumonia, meningitis and tuberculosis, which would once have been easily treated with antibiotics, is no longer so readily treated. At present, all widely used antibiotic, including some of the agent such as streptogramins and new generation fluoroquinolones are subjected to bacterial resistance. The search for new antimicrobial agent is one of the most challenging tasks to the medicinal chemist. A search for new antimicrobial compounds with potent and minor toxicity continues to be a region of exploration in medicinal chemistry. It has been well recognized that nitrogen containing heterocyclic molecule is a seat of diverse medicinal activities. Heterocyclic nucleus Pyrazole constitutes an important class of compounds for new drug development. The synthesis of these derivatives and investigation of their chemical and biological behavior have gained more importance in recent decades. Owing to the pharmacological importance of Pyrazole, and its derivatives, in the present work, it has been contemplated to combine various biologically active moieties with these heterocycles through active functional systems to form new molecular framework. Prompted by the therapeutic importance of these heterocyclic derivatives, in the present research work we have synthesized Pyrazole with fluorinated aromatic rings, and its derivatives through multistep reaction. Appropriate synthetic methodologies have been developed for the synthesis of new molecules. Their purification techniques have been established. All the newly synthesized compounds have been characterized by 1H NMR, 13C NMR, mass spectral, IR and elemental analyses. Also structures of a few molecules have been confirmed by X-ray crystallographic analysis. Further, the target molecules have been evaluated for their in vitro antibacterial and antifungal activity. From the pharmacological evaluation, it has been observed that some of Pyrazole, derivatives showed good antimicrobial activity

The current paper studies the influencing factors of permeability in shales of the Longmaxi Formation, located in the southern Sichuan Basin, China. The methodologies used in the present study include overburden pore permeability experiments, whole rock analysis and geochemical tests, NMR measurements of fluid saturation, pore size distribution and specific surface area distribution, SEM and extraction of pore structure parameters, and core analysis. The results show the following: (1) high TOC and high maturity generate a large number of organic pores, which may improve the permeability of shale. (2) Mineral composition and rock relative permeability also have influence on permeability to a certain degree, since different minerals have different effects on shale permeability. Clay in the study area has an adverse effect on permeability. The results show that the organic-rich siliceous clay mixed shale facies in this area has the best permeability. (3) A large specific surface area and total pore volume are associated with good shale permeability, while average pore size does not correlate with permeability. A small fractal dimension of pore morphology and simple pore structure result in good permeability, and bedding is the key controlling factor for the anisotropy of shale permeability. (4) Water in shales can influence the permeability of microfractures by binding to clay minerals. Low permeability in shales with high bound water saturation suggests that water and clay mineral absorption may block flow channels, resulting in poor permeability. The purpose of this study is to clarify the influencing factors on shale permeability of the Longmaxi Formation in the study area and to provide a reference for the exploration and development of shale gas in this area of the Sichuan Basin.

The application of NIR near-infrared spectroscopy and multivariate analysis as a rapid analysis technique in the quantification of the content of methanol in commercially distributed liqueurs (Aguardiente), to identify if these liqueurs exceed the methanol limits established in the standard. AOAC 972.11 (100 mg / dm3) (AOAC 972.11, 1973). For this, in a first stage, the application of a design of ternary mixtures methanol-ethanol-water (MDOE) was carried out in order to reduce correlation effects between the variables, in addition to achieving multivariate models that include variability important by expanding the calibration range that act under process conditions and in commercialization sites. The second stage was associated with the recording of the NIR spectra of the prepared samples, to obtain a data matrix, from which the multivariate models are developed using different algorithms. The results obtained showed that it is possible to develop a rapid analysis method for the quantification of methanol in Aguardiente samples, using NIR spectroscopy and the multivariate models constructed, in which a Mean Square Prediction Error (RMSEP) of 0.7766 was obtained. % and correlation coefficient (R2) of 0.9553.

Abstract Protein N-glycosylation plays a crucial role in a considerable number of important biological processes. Research studies on glycoproteomes and glycomes have already characterized many glycoproteins and glycans associated with cell development, life cycle, and disease progression. Mass spectrometry (MS) is the most powerful tool for identifying biomolecules including glycoproteins and glycans, however, utilizing MS-based approaches to identify glycoproteomes and glycomes is challenging due to the technical difficulties associated with glycosylation analysis. In this review, we summarize the most recent developments in MS-based glycoproteomics and glycomics, including a discussion on the development of analytical methodologies and strategies used to explore the glycoproteome and glycome, as well as noteworthy biological discoveries made in glycoproteome and glycome research. This review places special emphasis on China, where scientists have made sizeable contributions to the literature, as advancements in glycoproteomics and glycomincs are occurring quite rapidly.

Milk is one of the most important nutritious foods, widely consumed worldwide, either in its natural form or via dairy products. Currently, several economic, health and ethical issues emphasize the need for a more frequent and rigorous quality control of dairy products and the importance of detecting adulterations in these products. For this reason, several conventional and advanced techniques have been proposed, aiming at detecting and quantifying eventual adulterations, preferentially in a rapid, cost-effective, easy to implement, sensitive and specific way. They have relied mostly on electrophoretic, chromatographic and immunoenzymatic techniques. More recently, mass spectrometry, spectroscopic methods (near infrared (NIR), mid infrared (MIR), nuclear magnetic resonance (NMR) and front face fluorescence coupled to chemometrics), DNA analysis (real-time PCR, high-resolution melting analysis, next generation sequencing and droplet digital PCR) and biosensors have been advanced as innovative tools for dairy product authentication. Milk substitution from high-valued species with lower-cost bovine milk is one of the most frequent adulteration practices. Therefore, this review intends to describe the most relevant developments regarding the current and advanced analytical methodologies applied to species authentication of milk and dairy products.

There is currently a crucial need for improved diagnostic techniques and targeted treatment methods for Alzheimer’s disease (AD), a disease which impacts millions of elderly individuals each year. Metabolomic analysis has been proposed as a potential methodology to better investigate and understand the progression of this disease. In this report, we present our AD metabolomics results measured with high resolution magic angle spinning (HRMAS) nuclear magnetic resonance (NMR) on human blood plasma samples obtained from AD and non-AD subjects. Our study centers on developments of AD and non-AD metabolomics differentiating models with procedures of quality assurance (QA) and quality control (QC) through pooled samples. Our findings suggest that analysis of blood plasma samples using HRMAS NMR has the potential to differentiate between diseased and healthy subjects, which has important clinical implications for future improvements in AD diagnosis methodologies.

The efficient use of grains for animal feed requires the use of analytical methods that can provide rapid indications of the suitability of the grain for animal nutrition. Ideally, these methods need to be applied at the site of grain receival within the tight time and cost confines of grain delivery. In addition, methods are needed in plant breeding to efficiently screen for target aspects of feed-grain quality to facilitate the development of genotypes with improved nutritional quality. This review describes a range of techniques that can fulfil these analytical requirements. These include visual examination of grain samples for species identification and for recognition of defects and contaminants. This long-standing approach is rapid, but it is subjective and dependent on the expertise of the operator. The newer technology of image analysis offers the prospect of providing similar information automatically and quantitatively, without the risk of operator bias. Near-infrared (NIR) analysis is already in general use for grain analysis at many receival depots in wheat-growing countries, mainly for the determination of moisture and protein content. There are promising indications that NIR can be extended to the determination of many other aspects of grain composition, both the positive aspects that contribute to feed quality, as well as components such as beta-glucan content that have negative contributions for non-ruminants. Furthermore, NIR is being developed to provide a direct indication of metabolisable energy for a range of grain types. Whereas NIR is primarily suited to the determination of quantitatively major components of the grain, without the requirement of significant sample preparation, immunological analyses are appropriate for the determination of specific and minor components, such as mycotoxins, lectins, alkaloids, and pesticide residues. These and other methods, suited for on-site analysis, need to be combined with effective sampling to ensure that the results of testing are representative of the whole of the grain consignment, and also integrated into a systematic strategy to ensure cost-effective testing.

Abstract The article tells the story of the evolution of communication for development within the United Nation’s (UN) Food and Agriculture Organisation (FAO), describing the good times in the past as well as the difficult times in the last decade as an example of how the discipline continues to be marginalised in development institutions. The author argues that new challenges and trends demand new thinking on the part of institutions and governments, as well as new practices and skills by communication practitioners, and stresses the need to avoid re-inventing the wheel. New approaches should be married up with the participatory principles and methodologies applied in the past that are still valid for meeting the new challenges. The article concludes with a discussion of the prerequisites for an enabling environment for mainstreaming communication for development.

An efficient and facile synthesis of 3-amino pyrazoles has been described. The reaction of b-keto nitriles with hydrazines using p-toluenesulfonic acid as an efficient catalyst under solvent and solvent-free conditions afford corresponding 3-amino pyrazoles in excellent yields Introduction Pyrazoles, in particular 3-amino pyrazoles are an important class of compounds in medicinal chemistry and it has been well documented to posses antihypertensive,1 antibacterial,2 anti-inflammatory muscle relaxant3,4 and inhibitors of cyclin dependent kinases (CDK) such as CDK2/cycling A-E.5 They are also potent and selective Aurora kinase inhibitors.6,7 In addition the 3-amino pyrazoles also have industrial appliance in inhibition of corrosion on metals such as Zn, Cu, Al and Brass.8 Despite their importance from a pharmacological, industrial and synthetic point of view, comparatively few methods for the preparation of 3-amino pyrazoles have been reported. These includes condensation of hydrazines with β-keto nitriles,9 β-formyl nitriles,4 β-methoxy vinyl nitriles,10 α-nitrilo ethyl acetate11 and solid phase synthesis of 5-substituted amino pyrazoles.12 Unfortunately many of these processes suffer from one or other limitations such as incompletion of starting materials, long reaction times, with unsatisfactory yields. Thus there is a need for the development of an alternate route to construct the 3-amino pyrazoles. In recent years, p-toluenesulfonic acid is used as an efficient catalyst in various organic transformations,13 also it should be noted that p-toluenesulfonic acid is cheap, commercially available and comparatively non-toxic. The organic reactions assisted by microwaves,14 in particular have been gained special attention. One reason is that the use of microwave activation in organic synthesis can increase the purity of the resulting products, enhance the chemical yield and shorten the reaction times. And also organic reactions carried out in the absence of solvent, has been attracting attention of chemists due to ease of processing to the further step and eco-friendly in nature. In the case of synthesis of 3-amino pyrazoles, we thought that there is a scope for further innovation towards short reaction times and better yields. Here, we report an efficient and facile method for the synthesis of 3-amino pyrazoles catalyzed by p-toluenesulfonic acid under solvent and solvent-free conditions. Scheme 1 Results & discussion Reaction of benzoyl acetonitrile i. e. b-keto nitrile15 with 4-hydrazinobenzoic acid under reflux conditions in absolute ethanol for 8-10hr resulted in the formation of the corresponding 3-amino pyrazoles in <90% yield. However, we carried out the reaction in presence of catalytic amounts of p-toluenesulfonic acid (0.01 equiv.) and found reaction is completed in 45 min with nearly 100% conversion (Table 1, entry 7). This success has encouraged us to extend the generality of the reaction; various hydrazines with various b-keto nitriles in presence p-toluenesulfonic acid proceeded efficiently and smoothly at refluxing temperature and the products are obtained in excellent yields. And the reaction conditions are very favorable, no by-products are observed (Table 1, Method A). We further investigated the reaction conditions to improve the reaction conditions. It has been found that, b-keto nitrile 1 (1 mmol) and hydrazine 2 (1 mmol) reacts very rapidly (<5min) to give 3-amino pyrazoles in the presence of p-toluenesulfonic acid under microwave irradiation in solvent-free conditions (Table 1, Method B). The experimental procedure for this reaction is remarkably simple and no solvents or inert atmosphere is required. Under above conditions, in many cases it is noticed that in the absence of p-toluenesulfonic acid, the reaction is incomplete and uncyclized product was isolated along with pyrazole. Table 2: Synthesis of 3-Amino pyrazole catalyzed by p-toluenesulfonic acid under solvent and solvent free conditions. a Isolated yields after crystallization/column chromatography and all products gave satisfactory spectral (IR, 1HNMR and MASS) and analytical data In summary, the present procedures for the synthesis of 3-amino pyrazole have been developed by condensation reaction of hydrazines with b-keto nitriles catalyzed by p-toluenesulfonic acid under solvent and solvent free conditions. The advantage of present method is high efficient, reduced reaction time and inexpensive catalyst with high yields of products and simple experimental work-up procedure, which makes it, is a useful and important addition to the present existing methodologies. Acknowledgements: The authors are thankful to Director IICT for his constant encouragement and DOD New Delhi for providing fellowship. Typical Experimental procedure (Method A, Conventional): A mixture of b-keto nitile (10 mmol), hydrazine (10 mmol) and to this p-TSA (0.1mmol) was added and refluxed in absolute ethanol for appropriate time (Table 1, Method A). After completion of the reaction, as monitored by TLC, the solvent was evaporated under reduced pressure. The product was extracted into ethyl acetate (3 x 20 mL). The combined organic layer was washed with saturated sodium bicarbonate followed by brine solution, then dried over anhydrous sodium sulphate. The solvent was removed to afford crude product and purified by column chromatography. Typical Experimental procedure (Method B, Microwave): A mixture of b-keto nitile (10 mmol), hydrazine (10 mmol), p-TSA (0.1mmol) was suspended in water (1mL) in a reaction vessel, sealed without degassing and was subjected to microwave irradiation at 450Watt. at 1350C for appropriate time (Table 1, Method B). After completion of the reaction, as monitored by TLC, the reaction mass was cooled and product was extracted into ethyl acetate (3 x 20 mL). The combined organic layer was washed with saturated sodium bicarbonate followed by brine solution, then dried over anhydrous sodium sulphate. The solvent was removed under reduced pressure to afford crude product, it was purified by recrystallized from ethanol/column chromatography to give corresponding pure 3-amino pyrazoles. 3a: IR (KBr): 3418, 1618, 1509, 1009, 762, 707 cm-1; 1H NMR (200 MHz, DMSO+CDCl3): δ 1.25 (s, 9H), 5.85 (s, 1H); EIMS: m/z 139; Anal. Calcd. for C7H13N3: C, 60.431; H, 9.352; N, 30.215. Found: C, 60.399; H, 9.412, N, 30.186. 3b: IR (KBr): 3420, 1620, 1520, 750 cm-1; 1H NMR (200 MHz, DMSO+CDCl3): δ 2.26 (s, 3H), 4.75 (s, 2H br), 7.40 (s, 5H); EIMS: m/z 173; Anal. Calcd. for C10H11N3: C, 69.280; H, 6.350; N, 24.277. Found: C, 69.340; H, 6.401, N, 24.258. 3c: IR (KBr): 3415, 1618, 1124, 613 cm-1; 1H NMR (200 MHz, DMSO+CDCl3) δ 4.25 (s, 2H br.), 5.75 (s, 1H), 7.30 (m, 5H); EIMS: m/z 157; Anal. Calcd. for C9H9N3: C, 67.924; H, 5.660; N, 26.415. Found: C, 67.905; H, 5.698, N, 26.396. 3d: IR (neat): 3448, 1636 cm-1; 1H NMR (200 MHz, DMSO+CDCl3): δ 5.5 (s, 1H), 7.25 (d, 2H, J = 8.25Hz), 7.35 (d, 2H, J = 8.25Hz); EIMS: m/z 193, 195; Anal. Calcd. for C9H8ClN3: C, 55.958; H, 4.145; Cl, 18.393; N, 21.761. Found: C, 55.826; H, 4.164; Cl, 18.308; N, 21.700. 3e: IR (KBr): 3413, 1618, 1511, 1108, 613 cm-1; 1H NMR (200 MHz, DMSO+CDCl3): δ 2.50 (s, 3H), 5.95 (s, 1H), 7.45 (d, 2H, J = 8.20Hz), 7.75 (d, 2H, J = 8.20Hz); EIMS: m/z 173. Anal. Calcd. for C10H11N3: C, 69.364; H, 6.358; N, 24.277. Found: C, 69.340; H, 6.401; N, 24.258. 3f: IR (KBr): 3415, 1694, 1615, 1179, 616 cm-1; 1H NMR (200 MHz, DMSO+CDCl3): δ 5.68 (s, 1H), 6.41 (s, 1H), 6.59 (s, 1H), 7.4 (s, 1H); EIMS: m/z 149; Anal. Calcd. for C7H7N3O: C, 56.375; H, 4.697; N, 28.187; O, 10.738. Found: C, 56.369; H, 4.730; N, 28.173; O, 10.736. 3g: IR (KBr): 3414, 1616, 1091 cm-1; 1H NMR (200 MHz, DMSO+CDCl3): δ 6.60 (s, 1H), 7.40 (m, 5H), 7.8 (d, 2H, J = 8.50Hz), 8.40 (d, 2H, J = 8.50Hz); EIMS: m/z 279; Anal. Calcd. for C16H13N3O2: C, 68.817; H, 4.659; N, 15.053; O, 11,469. Found: C, 68.806; H, 4.691; N, 15.044; O, 11.456. 3h: IR (KBr): 3414, 1617, 1383, 618 cm-1; 1H NMR (200 MHz, DMSI+CDCl3): δ 5.9 (s, 1H), 7.15 (m, 5H), 7.35 (d, 1H, J = 8.15Hz), 7.60 (t, 1H, J = 3.15Hz), 7.85 (d, 1H, J = 8.25Hz), 7.9 (d, 1H, J = 8.15Hz), 8.30 (s, 1H); EIMS: m/z 279; Anal. Calcd. for C16H13N3O2: C, 68.817; H, 4.659; N, 15.053; O, 11.469. Found: C, 68.806; H, 4.691; N, 15.044; O, 11.456. 3i: IR (KBr): 3415, 1618, 1285, 761 cm-1; 1H NMR (200 MHz, DMSO+CDCl3): δ 1.25 (t, 3H), 3.90 (q, 2H), 6.25 (s, 1H), 7.40 (m, 5H), 7.7 (d, 2H, J = 8.25Hz), 8.05 (d, 2H, J = 8.25Hz); EIMS: m/z 313; 3j: IR (KBr): 3415, 1657, 1615, 1384, 1121, 758 cm-1; 1H NMR (200 MHz, DMSO+CDCl3): δ 1.25 (t, 3H), 4.25 (q, 2H), 4.925 (s, 2H), 5.85 (s, 1H), 7.5 (m, 5H); EIMS: m/z 245; Anal. Calcd. for C13H15N3O2: C, 63.673; H, 6.122; N, 17.142; O, 13.067. Found: C, 63.658; H, 6.164; N, 17.131; O, 13.045. 3k: IR (KBr): 3416, 1650, 1384, 1120, 758 cm-1; 1H NMR (200 MHz, DMSO+CDCl3) δ 6.02 (s, 1H), 7.15 (d, 2H, J = 8.15Hz), 7.35 (d, 2H, J = 8.23Hz), 7.60 (d, 2H, J = 8.15Hz), 8.10 (d, 2H, J = 8.23Hz); EIMS: m/z 303, 305; Anal. Calcd. for C16H12ClN3O2: C, 61.341; H, 3.833; Cl, 11.341; N, 13.415; O, 10.223. Found: C, 61.252; H, 3.855; Cl, 11.299; N, 13.393; O, 10.198. 3l: IR (KBr): 3415, 1650, 1090 cm-1; 1H NMR (200 MHz, DMSO+CDCl3) δ 6.8 (s, 1H), 7.4 (d, 2H, J = 8.15Hz), 7.6 (t, 1H, J = 3.00Hz), 7.8 (d, 3H, J = 8.25Hz), 8.1 (d, 1H, J = 8.25Hz), 8.3 (s, 1H, J = 8.15Hz), 9.93 (s, 1H); EIMS: m/z 303, 305; Anal. Calcd. for C16H12ClN3O2: C, 61.341; H, 3.833; Cl, 11.341; N, 13.415; O, 10.223. Found: C, 61.252; H, 3.855; Cl, 11.299; N, 13.393; O, 10.198. 3m: IR (KBr): 3415, 1617, 1384, 764, 619 cm-1; 1H NMR (200MHz, DMSO+CDCl3) δ 2.37 (s, 3H), 3.75 (s, 2H broad), 7.1 (d, 2H, J = 8.22Hz), 7.4 (d, 2H, J = 8.15Hz), 7.7 (d, 2H, J = 8.15Hz), 8.0 (d, 2H, J = 8.22Hz); EIMS: m/z 291; Anal. Calcd. for C17H15N3O2: C, 69.624; H, 5.119; N, 14.334; O, 10.921. Found: C, 69.611; H, 5.154; N, 14.325; O, 10.908. 3n: IR (KBr): 3415, 1618, 1384, 1216, 1047, 816, 619, 476 cm-1; 1H NMR (200 MHz, DMSO+CDCl3) δ 1.25 (t, 3H), 2.50 (s, 3H), 3.90 (q, 2H), 6.25 (s, 1H), 7.1 (d, 2H, J = 8.25Hz), 7.6 (d, 2H, J = 8.25Hz), 7.7 (d, 2H, J = 8.15Hz), 8.1 (d, 2H, J = 8.15Hz); EIMS: m/z 328; Anal. Calcd. for C17H17N3O2­­­­­­­­S: C, 62.385; H, 5.198; N, 12.84; O, 9.785; S, 9.785. Found: C, 62.365; H, 5.233; N, 12.834; O, 9.773; S, 9.793. 3o: 1H NMR (200 MHz, DMSO+CDCl3): δ 1.26 (s, 9H), 5.95 (s, 1H), 7.60 (d, 2H, J = 8.80Hz), 8.50 (d, 2H, J = 8.80Hz); EIMS: m/z 260. 3p: 1H NMR (200 MHz, DMSO+CDCl3): δ 2.26 (s, 3H), 7.40 (s, 5H), 7.62 (d, 2H, J = 8.60Hz), 8.56 (d, 2H, J = 8.60Hz); EIMS: m/z 294. 3q: 1H NMR (200 MHz, DMSO+CDCl3) δ 5.75 (s, 1H), 7.30 (m, 5H), 7.66 (d, 2H, J = 8.30Hz), 8.46 (d, 2H, J = 8.30Hz); EIMS: m/z 280. 3r: 1H NMR (200 MHz, DMSO+CDCl3): δ 5.5 (s, 1H), 7.26 (d, 2H, J = 8.25Hz), 7.36 (d, 2H, J = 8.25Hz), 7.68 (d, 2H, J = 8.20Hz), 8.49 (d, 2H, J = 8.20Hz); EIMS: m/z 314. 3s: 1H NMR (200 MHz, DMSO+CDCl3): δ 2.50 (s, 3H), 6.05 (s, 1H), 7.55 (d, 2H, J = 8.26Hz), 7.76 (d, 2H, J = 8.55Hz), 7.80 (d, 2H, J = 8.26Hz), 8.49 (d, 2H, J = 8.55Hz); EIMS: m/z 294. 3t: IR (KBr): 3425, 1694, 1615, 1500, 1485, 1425, 1179, 616 cm-1; 1H NMR (200 MHz, DMSO+CDCl3): δ 5.75 (s, 1H), 6.46 (s, 1H), 6.65 (s, 1H), 7.4 (s, 1H), 7.66 (d, 2H, J = 8.30Hz), 8.46 (d, 2H, J = 8.30Hz); EIMS: m/z 270; Anal. Calcd. for C13H10N4O3: C, 57.77; H, 5.119; N, 20.74; O, 17.77. Found: C, 57.78; H, 3.73; N, 20.73; O, 17.76. References: Almansa, L. A. Gomez, F. L Cavalcanti, A. F. de Arriba, J. Garcia-Rafanell, J. Form, J. Med. Chem., 1997, 40, 547. Daidone, B. Maggio, S. Plescia, D. Raffa, C. Musiu, C. Milia, G. Perra, M. E. Marongiu, Eur. J. Med. Chem., 1998, 33, 375; J. Finn, K. Mattia, M. Morytko, S. Ram, Y. Yang, X. Wu, E. Mak, P. Gallant, D. Keith, Bioorg. Med. Chem. Lett., 2003, 13, 2231. D. Penning, J. J. Talley, S. R. Bertenshaw, J. S. Carter, P. R. Collins, S. Docter, M. J. Graneto, L. F. Lee, J. W. Malecha, J. M. Miyashiro, R. S. Rogers, D. S. Rogier, S. S. Yu, G. G. Anderson, E. G. Burton, J. N. Cogburn, S. A. Gregory, C. M. Koboldt, W. E. Perkins, K. Seibert, A. W. Veenhuizen, Y. Y. Zhang, P. C. Isakson, J. Med. Chem., 1997, 40, 1347; S. Zhihua, J. Guan, F. P. Michael, M. Kathy, W. P. Michael, M. V. William, S. Monica, S. Michele, R. M. Dave, C. Dennis, Bioorg. Med. Chem. 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Abstract Introduction : Chronic kidney disease is common in patients with sickle cell disease (SCD) and is associated with increased mortality. As albuminuria and changes in estimated glomerular filtration rate (eGFR) occur well after substantial structural and functional tissue damage have ensued, biomarkers that predict the development of CKD are needed. Metabolite profiling and the bioinformatics tools to study them may aid in the discovery of novel associations and uncover pathophysiological pathways in SCD-related glomerulopathy. In this study, we have performed an exploratory study to identify urinary biomarkers, which may be predictive of kidney damage in children with SCD. Methods: Consecutive patients with SCD seen at a pediatric chronic care clinic at Kamuzu Central Hospital in Lilongwe, Malawi, between January and May 2015 were evaluated. Patient urine samples were analyzed for metabolites using NMR-based methodologies. Spot urine measurements for albumin/creatinine ratio (UACR) were required to ascertain the degree of albuminuria (normal albuminuria [UACR < 30 mg/ g creatinine] or albuminuria [UACR ≥ 30 mg/ g creatinine]). Descriptive statistics (mean and standard deviation for continuous variables, and count and percentage for discrete variables) were calculated for each of the baseline variables. T-test and Fisher's exact test were performed to compare the baseline measurements between those with and without albuminuria for continuous and discrete variables, respectively. Metabolite measurements were Pareto scaled and quantile normalized. To detect differential metabolites between the normal albuminuria and albuminuria groups, Wilcoxon rank sum test was performed. Results: Spot urine samples were obtained in 92 children, 32 (46.4%) of whom were female, average age of 40.6 (±0.98) months, and 23 (25%) patients with normal albuminuria. The patients in both categories were generally similar (age, sex, WBC count, hemoglobin, bilirubin and serum creatinine), except for higher baseline levels of lactate dehydrogenase (p < 0.05) in patients in the albuminuria category. From 1078 bins, we deleted those with low measurements across the majority (>95%) of samples and applied the differential metabolite analysis to 723 bins. Among these bins, 43 metabolites were different in both albuminuria categories (p ≤ 0.05). Although none of the metabolites were significantly different after adjustment for multiple comparisons, the top list is preliminarily identified as ethylmalonic acid, an acidogenic and a metabotoxic branched fatty acid, as an important urinary metabolite differentiating the two groups. High levels of ethylmalonic acid are also found in the urine of patients with short-chain acyl-coenzyme A dehydrogenase deficiency, a fatty acid metabolism disorder. The results remain largely unchanged after important covariates, age, sex, WBC count, hemoglobin, lactate dehydrogenase, bilirubin and creatinine were adjusted. In addition, principal component analysis (PCA) and partial least square discrimination analysis (PLS-DA) were performed (Figures 1A and 1B). Despite the lack of distinct clusters on the score plots, 15 metabolites were identified as "important features" in PLS-DA, based on their variance of importance projection (VIP) score (Figure 2). Conclusion: Our exploratory study shows that urinary ethylmalonic acid is a potentially important biomarker for the early detection of kidney damage in children with SCD. More studies of larger patient populations with SCD are required to identify urine metabolites which may predict the development of albuminuria. Disclosures Key: UniQure BV: Research Funding. Ataga:Global Blood Therapeutics: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Research Funding; Novartis: Consultancy, Honoraria; Modus Therapeutics: Honoraria; Bioverativ: Honoraria, Membership on an entity's Board of Directors or advisory committees.

Red wine grapes have an important impact on the economy of many regions, both for wine quality and for their richness in phenolic compounds, which have many health benefits. Climate has been changing substantially in the last years, which affects greatly grape polyphenolic composition and wine quality. In this review, we will unveil the importance of climate in grape development, both physically and chemically, the different methodologies used to evaluate grape quality, the interesting new approaches using NIR spectroscopy, and the functional properties of grapes and red wine, due to their high phenolic content. Climate has an impact in the development of phenolic compounds in grapes, namely in the anthocyanins biosynthesis. The phenolic chemical composition changes during maturation, therefore, it is essential to keep on track the accumulation of these key compounds. This information is crucial to help producers choose the best harvest date since specific compounds like polyphenols are responsible for the color, taste, and mouthfeel of wines, which directly affects wine quality. The usage of different methodologies to assess quality parameters in grapes and wine, can be used to provide essential information to create the chemical profile of each variety to develop calibration methods. NIR spectroscopy seems to be a reliable method to be used in vineyards during grape maturation to provide real time information on quality parameters to producers since many reliable calibration models have been developed over time.

Abstract Guanine-rich nucleic acids can fold into the non-B DNA or RNA structures called G-quadruplexes (G4). Recent methodological developments have allowed the characterization of specific G-quadruplex structures in vitro as well as in vivo, and at a much higher throughput, in silico, which has greatly expanded our understanding of G4-associated functions. Typically, the consensus motif G3+N1–7G3+N1–7G3+N1–7G3+ has been used to identify potential G-quadruplexes from primary sequence. Since, various algorithms have been developed to predict the potential formation of quadruplexes directly from DNA or RNA sequences and the number of studies reporting genome-wide G4 exploration across species has rapidly increased. More recently, new methodologies have also appeared, proposing other estimates which consider non-canonical sequences and/or structure propensity and stability. The present review aims at providing an updated overview of the current open-source G-quadruplex prediction algorithms and straightforward examples of their implementation.

Cryo-electron microscopy (cryoEM) has become a well established technique with the potential to produce structures of large and dynamic supramolecular complexes that are not amenable to traditional approaches for studying structure and dynamics. The size and low resolution of such molecular systems often make structural modelling and molecular dynamics simulations challenging and computationally expensive. This, together with the growing wealth of structural data arising from cryoEM and other structural biology methods, has driven a trend in the computational biophysics community towards the development of new pipelines for analysing global dynamics using coarse-grained models and methods. At the centre of this trend has been a return to elastic network models, normal mode analysis (NMA) and ensemble analyses such as principal component analysis, and the growth of hybrid simulation methodologies that make use of them. Here, this field is reviewed with a focus on ProDy, the Python application programming interface for protein dynamics, which has been developed over the last decade. Two key developments in this area are highlighted: (i) ensemble NMA towards extracting and comparing the signature dynamics of homologous structures, aided by the recent SignDy pipeline, and (ii) pseudoatom fitting for more efficient global dynamics analyses of large and low-resolution supramolecular assemblies from cryoEM, revisited in the CryoDy pipeline. It is believed that such a renewal and extension of old models and methods in new pipelines will be critical for driving the field forward into the next cryoEM revolution.

Prostate Cancer (PCa) is one of the common cancers among men in the world. About 16.67% of men will be affected by PCa in their life. Due to the integration of magnetic resonance imaging in the current clinical procedure for detecting prostate cancer and the apparent success of imaging techniques in the estimation of PCa volume in the gland, we provide a more detailed review of methodologies that use specific parameters for prostate tissue representation. After collecting over 200 researches on image-based systems for diagnosing prostate cancer, in this paper, we provide a detailed review of existing computer-aided diagnosis (CAD) methods and approaches to identify prostate cancer from images generated using Near-Infrared (NIR), Mid-Infrared (MIR), and Magnetic Resonance Imaging (MRI) techniques. Furthermore, we introduce two research methodologies to build intelligent CAD systems. The first methodology applies a fuzzy integral method to maintain the diversity and capacity of different classifiers aggregation to detect PCa tumor from NIR and MIR images. The second methodology investigates a typical workflow for developing an automated prostate cancer diagnosis using MRI images. Essentially, CAD development remains a helpful tool of radiology for diagnosing prostate cancer disease. Nonetheless, a complete implementation of effective and intelligent methods is still required for the PCa-diagnostic system. While some CAD applications work well, some limitations need to be solved for automated clinical PCa diagnostic. It is anticipated that more advances should be made in computational image analysis and computer-assisted approaches to satisfy clinical needs shortly in the coming years.

Abstract In this paper, we emphasize the importance of accurate initial conditions in predicting high-impact ocean-atmospheric environmental events, such as El Niño-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), tropical cyclone (TC), and Kuroshio large meander (KLM), by reviewing recent progresses toward target observations for improving the initialization of these events forecasting. Since field observations are costly and will never be dense enough to fully cover the vast space of these events, it is necessary to develop methodologies that guide the design of efficient and effective observation strategy. Of particular interest is a method called conditional non-linear optimal perturbation (CNOP), which has been shown to be very useful in determining the sensitive areas for target observations applicable to the predictions of ENSO, IOD, TC, and KLM. Further studies are needed to understand the predictability of these events under the influence of climate change, and to explore the possibility of implementing field programs of target observations. These studies are challenging but are crucially important for improving our forecast skill of the high-impact ocean-atmospheric environmental events, and thus for disaster prevention, climate change mitigation, and sustainable socio-economic development.

Abstract: Purpose: This paper presents a longitudinal evaluation of the research about Directive 2014/95/EU regarding Non-Financial Reporting (NFR), identifying the t theoretical approaches, methodological adopteds, and research topics. Research methodology: Data was collected from the Web of Science (WoS) database, between 2016 and 2021. The search criteria resulted in a total of 59 valid articles, after which we performed a quantitative bibliometric analysis using VOSviewer software. Results: Publications on this Directive 2014/95/EU has increased from 2015 to 2021. Findings show that most articles resorted to quantitative and qualitative methodologies, emphasizing content analysis, combined with other research methods. The frameworks based on stakeholders and institutional theories are very popular in the field. Research is focused on (1) Directive 2014/95/EU regulation, implementation, compliance, and investigation, (2) determinants and impacts of NFR, (3) NFR level/evolution and (4) reasons and skills for NFR. Papers published on EU non-financial information are very heterogeneous and lack consensus as to its impact on NFR. Limitations: This study only included the WoS database as a source of data collection, and it would be valuable in future studies to add other quality databases. Contribution: This research contributes to illuminating institutional pressures implication for NFR development. Therefore, this analysis is essential for institutions operating in accounting information standardization, as well as for information preparers given the necessity to acquire skills to ensure this new challenge related to the reporting of corporate social responsibility. Keywords: 1. Non-Financial Reporting 2. Directive 2014/95/EU 3. Institutional Pressures 4. Bibliometric literature review

Abstract Synthetic genome recoding is a new means of generating designed organisms with altered phenotypes. Synonymous mutations introduced into the protein coding region tolerate modifications in DNA or mRNA without modifying the encoded proteins. Synonymous genome-wide recoding has allowed the synthetic generation of different small-genome viruses with modified phenotypes and biological properties. Recently, a decreased cost of chemically synthesizing DNA and improved methods for assembling DNA fragments (e.g. lambda red recombination and CRISPR-based editing) have enabled the construction of an Escherichia coli variant with a 4-Mb synthetic synonymously recoded genome with a reduced number of sense codons (n = 59) encoding the 20 canonical amino acids. Synonymous genome recoding is increasing our knowledge of microbial interactions with innate immune responses, identifying functional genome structures, and strategically ameliorating cis-inhibitory signaling sequences related to splicing, replication (in eukaryotes), and complex microbe functions, unraveling the relevance of codon usage for the temporal regulation of gene expression and the microbe mutant spectrum and adaptability. New biotechnological and therapeutic applications of this methodology can easily be envisaged. In this review, we discuss how synonymous genome recoding may impact our knowledge of microbial biology and the development of new and better therapeutic methodologies.

<p>Post-fire management should be based on a proper evaluation of fire damage (burn severity), mainly for Large Fires (&gt;500 ha). Several methodologies have been developed based on remote sensing information validated with fieldwork. The most widespread techniques was the assessment of fire severity indices obtained from remote sensing. It allow a quick assessment of large areas at affordable costs, although the analysis of soil burn severity and the degree of agreement with the ground truth is not fully reliable. Our study case was the Donceles fire (summer 2012, Hellín, Albacete). The post-fire restoration planning, emergency actions, was based on cartographic information of burn severity. To optimize results in a short time and low budget, we applied methodologies in a similar way other similar fires in the Mediterranean peninsular area. We assessed burn severity by using spectral indices (NDVI, dNBR, RdNBR and RBR) and images from Landsat-7 (including banded) and Deimos-1. For each index, we developed both supervised and unsupervised classifications, using field data as training areas. The highest overall reliability values were found for dNBR (79%) and NBR (71%), obtaining low values with RdNBR. In all cases, the reliability was higher using the supervised classification, so using real-ground data to identify the categories of severity to be discriminated. We conclude the need to extend fire studies in our area to improve the reliability of the fire severity assessment obtained from spectral indexes, thus establishing a protocol of data collection and standard methodology of calculation adapted to the characteristics of the region.</p>

The application of calibration and prediction (CAP) to joint measurements of near-infrared (NIR) and Raman spectra for the same reference data requires the development of joint inversion methodologies for the implementation of the calibration step. Joint inversion has been successfully utilized in geophysical prospecting and in medical diagnosis, where the need to perform CAP is not involved. However, the obvious ways in which joint inversion might be implemented in spectroscopy, where some form of CAP must be performed, do not appear to work. Here, a new methodology, leap-frog calibration and prediction (LF-CAP), is proposed. It allows naturally for the information in the joint NIR and Raman spectra to yield a quite robust predictor of the property of interest. This new procedure is examined in some detail. The major limitation of CAP, as a strategy for recovering information from indirect measurements, is that it is a one-step process, in that the calibration step can only be applied once. If multiple independent spectral data are available for the same reference data, then the leap-frog implementation of CAP turns the recovery of information into an iterative process that converges under a wide range of circumstances.

The development of digital tools based on artificial intelligence can produce affordable and accurate methodologies to assess quality traits and sensory analysis of beers. These new and emerging technologies can also assess new products in a near real-time fashion through virtual simulations before the brewing process. This research was based on the development of specific digital tools (four models) to assess quality traits and sensory profiles of beers produced using sonication and traditional brewing techniques. Results showed that models developed using supervised machine learning (ML) regression algorithms based on near-infrared spectroscopy (NIR) were highly accurate in the estimation of physicochemical parameters (Model 1; R = 0.94; b = 0.91). Outputs from Model 1 were then used as inputs to obtain estimations of the intensity of sensory descriptors (Model 2; R = 0.99; b = 0.98), liking of sensory attributes (Model 3; R = 0.97; b = 0.99), and the classification of fermentation treatments using supervised classification ML algorithms (Model 4; 96% accuracy). These new digital tools can aid craft brewing companies for product development at lower costs and maintain specific quality traits and sensory profiles, creating original styles of beers to get positioned in the market.

Reliable predictions of the energy consumption and production is important information for the management and integration of renewable energy sources. Several different Machine Learning (ML) methodologies have been tested for predicting the energy consumption/production based on the information of hydro-meteorological data. The methods analysed include Multivariate Adaptive Regression Splines (MARS) and various Quantile Regression (QR) models like Quantile Random Forest (QRF) and Gradient Boosting Machines (GBM). Additionally, a Nonhomogeneous Gaussian Regression (NGR) approach has been tested for combining and calibrating monthly ML based forecasts driven by ensemble weather forecasts. The novelty and main focus of this study is the comparison of the capability of ML methods for producing reliable predictive uncertainties and the application of monthly weather forecasts. Different skill scores have been used to verify the predictions and their uncertainties and first results for combining the ML methods applying the NGR approach and coupling the predictions with monthly ensemble weather forecasts are shown for the southern Switzerland (Canton of Ticino). These results highlight the possibilities of improvements using ML methods and the importance of optimally combining different ML methods for achieving more accurate estimates of future energy consumptions and productions with sharper prediction uncertainty estimates (i.e., narrower prediction intervals).

Industrial wastewater contains excessive micro insoluble solids (MIS) that probably cause environmental pollutions. Near-infrared (NIR) spectroscopy is an advanced technology for rapid detection of the complex targets in wastewater. An Internet of Things (IoT) platform would support intelligent application of the NIR technologies. The studies of intelligent chemometric methods mainly contribute to improve the NIR calibration model based on the IoT platform. With the development of artificial intelligence, the backward interval and synergy interval techniques were proposed in combination use with the least square support vector machine (LSSVM) method, for adaptive selection of the informative spectral wavelength variables. The radial basis function (RBF) kernel is applied for nonlinear mapping. The regulation parameter and the kernel width are fused together for smart optimization. In the design for waveband autofittings, the total of digital wavelengths in the full scanning range was split into 43 equivalent subintervals, and then, the back interval LSSVM (biLSSVM) and the synergy interval LSSVM (siLSSVM) models were both established for the improvement of prediction results based on the adaptive selection of quasidiscrete variable combination. In comparison with some common linear and nonlinear models, the best training model was acquired with the siLSSVM method while the best testing model was obtained with biLSSVM. The intelligent optimization of model parameters indicated that the proposed biLSSVM and siLSSVM deep learning methodologies are feasible to improve the model prediction results in rapid determination of the wastewater MIS content by the IoT-based NIR technology. The machine learning framework is prospectively applied to the fast assessment of the environmental risk of industrial pollutions and water safety.

<abstract> <p>This study identifies the main results and research opportunities based on 52 hedge accounting-related studies, published in Scopus indexing journals from 2007-2019. The study was classified in five investigation groups based on their main topic, with Risk Management and Hedge Accounting being the topic most studied (18) and Regulatory Environment the least studied (six). The results show that during the period analysed, the journal with the largest number of publications on hedge accounting is in the United States of American and the most common origin of the journals is the United Kingdom (21). We have identified different research opportunities for each of the five groups and some general opportunities. The main opportunities relate to comparatives researches, considering samples from different countries, the development of methodologies for teaching hedge accounting and models for effectiveness measurement, the study of enterprise risk and disclosure analysis, and research on the impact of Covid-19 on hedge accounting through risk management. The study differs by identifying five classification groups for papers on hedge accounting, since prior studies didn't carry out such classification. The groups are: i) Regulatory Environment, ii) Academic Research, iii) Evolution of Hedge Accounting and Disclosure, iv) Hedge Effectiveness and v) Risk Management and Hedge Accounting. Furthermore, this study is, to our knowledge, the first bibliometric review done about hedge accounting. The paper is relevant to researchers because it points out opportunities for future studies, enabling the production of new research for a topic considered to be complex.</p> </abstract>

<abstract> <p>This study identifies the main results and research opportunities based on 52 hedge accounting-related studies, published in Scopus indexing journals from 2007-2019. The study was classified in five investigation groups based on their main topic, with Risk Management and Hedge Accounting being the topic most studied (18) and Regulatory Environment the least studied (six). The results show that during the period analysed, the journal with the largest number of publications on hedge accounting is in the United States of American and the most common origin of the journals is the United Kingdom (21). We have identified different research opportunities for each of the five groups and some general opportunities. The main opportunities relate to comparatives researches, considering samples from different countries, the development of methodologies for teaching hedge accounting and models for effectiveness measurement, the study of enterprise risk and disclosure analysis, and research on the impact of Covid-19 on hedge accounting through risk management. The study differs by identifying five classification groups for papers on hedge accounting, since prior studies didn't carry out such classification. The groups are: i) Regulatory Environment, ii) Academic Research, iii) Evolution of Hedge Accounting and Disclosure, iv) Hedge Effectiveness and v) Risk Management and Hedge Accounting. Furthermore, this study is, to our knowledge, the first bibliometric review done about hedge accounting. The paper is relevant to researchers because it points out opportunities for future studies, enabling the production of new research for a topic considered to be complex.</p> </abstract>

IntroductionPoor adolescent mental health is a barrier to achieving several sustainable development goals in Tanzania, where adolescent mental health infrastructure is weak. This is compounded by a lack of community and policy maker awareness or understanding of its burden, causes and solutions. Research addressing these knowledge gaps is urgently needed. However, capacity for adolescent mental health research in Tanzania remains limited. The existence of a National Institute for Medical Research (NIMR), with a nationwide mandate for research conduct and oversight, presents an opportunity to catalyse activity in this neglected area. Rigorous research priority setting, which includes key stakeholders, can promote efficient use of limited resources and improve both quality and uptake of research by ensuring that it meets the needs of target populations and policy makers. We present a protocol for such a research priority setting study and how it informs the design of an interinstitutional adolescent mental health research capacity strengthening strategy in Tanzania.Methods and analysisFrom May 2021, this 6 month mixed-methods study will adapt and merge the James Lind Alliance approach and validated capacity strengthening methodologies to identify priorities for research and research capacity strengthening in adolescent mental health in Tanzania. Specifically, it will use online questionnaires, face-to-face interviews, focus groups, scoping reviews and a consensus meeting to consult expert and adolescent stakeholders. Key evidence-informed priorities will be collaboratively ranked and documented and an integrated strategy to address capacity gaps will be designed to align with the nationwide infrastructure and overall strategy of NIMR.Ethics and disseminationNational and institutional review board approvals were sought and granted from the National Health Research Ethics Committee of the NIMR Medical Research Coordinating Committee (Tanzania) and the Liverpool School of Tropical Medicine (United Kingdom). Results will be disseminated through a national workshop involving all stakeholders, through ongoing collaborations and published commentaries, reviews, policy briefs, webinars and social media.

Introduction. In today’s knowledge society, the amount of scientificapplied information, which university graduates have to acquire, continues to increase continuously. There is a concurrent reduction in the number of study hours to undertake educational programmes in order to increase the hours for students’ independent work. Against this background, higher school is required to increase future experts’ competencies. Therefore, the content of fundamental and special disciplines of entire period of training and independent work of students should be thoroughly coordinated by increasing students’ motivation to self-education and self-development. Classroom-based and independent learning of disciplines and sections of fundamental academic courses, especially chemistry, is impossible without formation of students’ scientific thinking. Today, it is difficult to consider the activity of most professionals without the ability to think scientifically: active expansion of science into professional sphere has a strong tendency to be increased.The aim of the present research is to show the possibilities of formation and development of scientific thinking in the students of natural-scientific and technical directions of education using the example of studying of one of the elements of programmes in chemistry (the method of nuclear magnetic resonance (NMR) analysis).Methodology and research methods. The research was carried out on the basis of competency-based, systematic and interdisciplinary approaches. The methods of analysis, synthesis, integration, differentiation and compactification of fundamental knowledge and training material were used.Results and scientific novelty. The high potential of chemical education for formation of scientific thinking, subject content (chemical), natural-scientific and holistic scientific thinking is emphasised. However, chemistry education in higher education institution is complicated by the absence of the unified structure of fundamental preparation, the preservation of extensive approach to the content of chemical disciplines, the irrational organisation of students’ independent work, which now is accounted for a half of instructional time. Overcoming these problems lies in the dialectic unity of fundamental and practice-oriented knowledge, which is provided by the compliance with the principles of continuity and interdisciplinarity. It is necessary to provide deductive structurisation of training material in order to give integrity and systemacity to the content of education, without which it is impossible to create a comprehensive natural-scientific picture of the world in students. The key initial element of vocational training stimulating the formation of reflexive skills and scientific thinking of future experts is mastering by students of a categoricalconceptual framework of science, which is consistently and comprehensively revealed throughout a high school stage of education. The authors designated phases of development of scientific thinking (formal-logical, reflexive-theoretical, hypotheticodeductive thinking), which are not clearly differentiated due to interpenetration and entanglement of their components and identity of thought processes in terms of their speed and quality. However, the allocation of these stages allows to structure and to correct the content of educational material taking into account the characteristics and the level of students’ readiness. From these standpoints, the expediency of more detailed examination of the NMR method is proved within the disciplines such as “Chemistry”, “General Chemistry”, “Inorganic Chemistry” and “Analytical Chemistry” (a part of material about the NMR method can be worked out by students independently). This method, based on one phenomenon, includes hundreds of various types of the experiments, which are intended for receiving particular information. The NMR method is widely used both in scientific research, including master’s thesis, and in the most various manufacturing spheres. Today, the spectroscopy of NMR is recognised as the most powerful informative and perspective method of structural analysis of substance. The fundamental nature, interdisciplinarity and universality of the method provide students with basic professional knowledge on physics, chemistry, medicine, biology, technology and ecology. The authors of the present research propose the option of configuration of educational information on NMR. According to the suggested version, the principle of work is the following: firstly, bachelors study the system of key concepts and terms, moving gradually from formal-logical to substantial generalisations; then, students learn to explain the phenomena scientifically and to make forecasts, and, as a result, they become the “owners” of hypothetico-deductive thinking. The acquired competencies are the key to professional literacy, which is improved in master’s degree programme, when the previously compactified scientific knowledge in a contracted form is developed in the form suitable for an optimal solution of a particular research or practical aim. The similar scheme of vocational training makes it possible to overcome traditional orientation of high school programmes of the natural-science block (i.e. retention of permanently growing amount of factual material).Practical significance. The research materials can be useful for methodologists of the higher school, for experts engaged in methodological development and the organisation of educational process, for high school teachers of chemistry and related disciplines, for post-graduate students and master’s students of chemical and chemico-technological specialties as well.

Introduction. In today’s knowledge society, the amount of scientific-applied information, which university graduates have to acquire, continues to increase continuously. There is a concurrent reduction in the number of study hours to undertake educational programmes in order to increase the hours for students’ independent work. Against this background, higher school is required to increase future experts’ competencies. Therefore, the content of fundamental and special disciplines of entire period of training and independent work of students should be thoroughly coordinated by increasing students’ motivation to self-education and self-development. Classroom-based and independent learning of disciplines and sections of fundamental academic courses, especially chemistry, is impossible without formation of students’ scientific thinking. Today, it is difficult to consider the activity of most professionals without the ability to think scientifically: active expansion of science into professional sphere has a strong tendency to be increased.The aim of the present research is to show the possibilities of formation and development of scientific thinking in the students of natural-scientific and technical directions of education using the example of studying of one of the elements of programmes in chemistry (the method of nuclear magnetic resonance (NMR) analysis).Methodology and research methods. The research was carried out on the basis of competency-based, systematic and interdisciplinary approaches. The methods of analysis, synthesis, integration, differentiation and compactification of fundamental knowledge and training material were used.Results and scientific novelty. The high potential of chemical education for formation of scientific thinking, subject content (chemical), natural-scientific and holistic scientific thinking is emphasised. However, chemistry education in higher education institution is complicated by the absence of the unified structure of fundamental preparation, the preservation of extensive approach to the content of chemical disciplines, the irrational organisation of students’ independent work, which now is accounted for a half of instructional time. Overcoming these problems lies in the dialectic unity of fundamental and practice-oriented knowledge, which is provided by the compliance with the principles of continuity and interdisciplinarity. It is necessary to provide deductive structurisation of training material in order to give integrity and systemacity to the content of education, without which it is impossible to create a comprehensive natural-scientific picture of the world in students. The key initial element of vocational training stimulating the formation of reflexive skills and scientific thinking of future experts is mastering by students of a categorical-conceptual framework of science, which is consistently and comprehensively revealed throughout a high school stage of education. The authors designated phases of development of scientific thinking (formal-logical, reflexive-theoretical, hypothetico-deductive thinking), which are not clearly differentiated due to interpenetration and entanglement of their components and identity of thought processes in terms of their speed and quality. However, the allocation of these stages allows to structure and to correct the content of educational material taking into account the characteristics and the level of students’ readiness.From these standpoints, the expediency of more detailed examination of the NMR method is proved within the disciplines such as “Chemistry”, “General Chemistry”, “Inorganic Chemistry” and “Analytical Chemistry” (a part of material about the NMR method can be worked out by students independently). This method, based on one phenomenon, includes hundreds of various types of the experiments, which are intended for receiving particular information. The NMR method is widely used both in scientific research, including master’s thesis, and in the most various manufacturing spheres. Today, the spectroscopy of NMR is recognised as the most powerful informative and perspective method of structural analysis of substance. The fundamental nature, interdisciplinarity and universality of the method provide students with basic professional knowledge on physics, chemistry, medicine, biology, technology and ecology. The authors of the present research propose the option of configuration of educational information on NMR. According to the suggested version, the principle of work is the following: firstly, bachelors study the system of key concepts and terms, moving gradually from formal-logical to substantial generalisations; then, students learn to explain the phenomena scientifically and to make forecasts, and, as a result, they become the “owners” of hypothetico-deductive thinking. The acquired competencies are the key to professional literacy, which is improved in master’s degree programme, when the previously compactified scientific knowledge in a contracted form is developed in the form suitable for an optimal solution of a particular research or practical aim. The similar scheme of vocational training makes it possible to overcome traditional orientation of high school programmes of the natural-science block (i.e. retention of permanently growing amount of factual material).Practical significance. The research materials can be useful for methodologists of the higher school, for experts engaged in methodological development and the organisation of educational process, for high school teachers of chemistry and related disciplines, for post-graduate students and master’s students of chemical and chemico-technological specialties as well.

ABSTRACTTraditional pairwise meta-analysis (PMA) is a very useful method that pools evidence from one study design type if appropriate; its widespread use in nutrition research is an important phenomenon. Recently, a promising method for more advanced evidence-synthesis, called network meta-analysis (NMA), was introduced. NMA is an extension of PMA that enables simultaneous comparison of multiple interventions. NMA combines direct evidence (i.e., trials comparing 2 interventions directly) and indirect evidence (i.e., from a connected route via ≥1 comparators, e.g. placebo) in a network of studies. NMAs have the potential to advance knowledge in the field of nutrition as they provide insights that cannot be obtained by individual 2-arm randomized controlled trials or PMA. Thus, in this perspective paper, we aim to summarize the current (methodologic) status of published NMAs in nutrition research and emphasize advances and strengths in comparison with traditional PMA through specific examples, and highlight potential pitfalls and limitations. NMA is an emerging methodology in the field of nutrition research. A PubMed search identified only 23 nutrition research-related NMAs published since the inception of journals up to January 8, 2019 (61% of them published since 2017), compared with >5000 published PMAs. Moreover, we aim to highlight the scientific concepts and standards through the use of the following NMA example: “Which type of oils/solid fats offers the greatest impact on blood lipids?” In this regard, we discuss intervention definitions, transitivity/similarity, statistical methods, description and visualization of results, inconsistency, ranking, dissemination bias, assessing the certainty of evidence by Grading of Recommendations Assessment, Development and Evaluation, and reporting guidelines. We expect that rigorously conducted NMAs based on high-quality systematic reviews will become the new evidence synthesis benchmark in nutrition research. However, caution is warranted because abuse and misinterpretations of PMA and NMA findings could hamper the scientific field and possibly decision-making regarding public policy.

The process of teaching and learning through online or virtual mode has been gradually becoming an important part of the Indian education sector. Teachers and students in higher education have already been effectively using online education mode to optimize the learning process. Schools, too, have been using educational technologies in many ways at all levels and across all grades. But with the unexpected worldwide spread of the COVID-19 pandemic in the year 2020, a sudden exponential boom has come in the online teaching set up. Until now, online teaching was assumed to be an aid to the teaching-learning transactions and was immediately adopted as the only way out, to continue with the pedagogical process in schools and colleges. This research attempts to make a comparative analysis of the changes in various aspects of online teaching before and during the COVID-19 era, including content development and delivery and type of information shared with students in private schools of NCR of India. Data collected by the investigator from school teachers about their usage of online methodologies from 2017 will be compared with school teachers’ data in August 2020, and its educational implications will be discussed.

The increased complexity of modern systems is calling for an integrated and comprehensive approach to system design and development and, in particular, a shift toward Model-Based Systems Engineering (MBSE) approaches for system design. The requirements that serve as the foundation for these intricate systems are still primarily expressed in Natural Language (NL), which can contain ambiguities and inconsistencies and suffer from a lack of structure that hinders their direct translation into models. The colossal developments in the field of Natural Language Processing (NLP), in general, and Large Language Models (LLMs), in particular, can serve as an enabler for the conversion of NL requirements into machine-readable requirements. Doing so is expected to facilitate their standardization and use in a model-based environment. This paper discusses a two-fold strategy for converting NL requirements into machine-readable requirements using language models. The first approach involves creating a requirements table by extracting information from free-form NL requirements. The second approach consists of an agile methodology that facilitates the identification of boilerplate templates for different types of requirements based on observed linguistic patterns. For this study, three different LLMs are utilized. Two of these models are fine-tuned versions of Bidirectional Encoder Representations from Transformers (BERTs), specifically, aeroBERT-NER and aeroBERT-Classifier, which are trained on annotated aerospace corpora. Another LLM, called flair/chunk-english, is utilized to identify sentence chunks present in NL requirements. All three language models are utilized together to achieve the standardization of requirements. The effectiveness of the methodologies is demonstrated through the semi-automated creation of boilerplates for requirements from Parts 23 and 25 of Title 14 Code of Federal Regulations (CFRs).

Content uniformity is a critical attribute for potent and low-dosage formulations of active pharmaceutical ingredient (API) that, in addition to the formulation parameters, plays pivotal role during pharmaceutical development and production. However, when API content is low, implementing a vibrational spectroscopic analytical tool to monitor the content and blend uniformity remains a challenging task. The aim of this study was to showcase the potentials of mid-infrared (MIR), near-infrared (NIR), and Raman spectroscopy for quantitative analysis of alprazolam (ALZ) in a low-content powder blends with lactose, which is used as a common diluent for tablets produced by direct compression. The offered approach might be further scaled up and exploited for potential application in the process analytical technology (PAT). Partial least square and orthogonal PLS (OPLS) methodologies were employed to build the calibration models from raw and processed spectral data (standard normal variate, first and second derivatives). The models were further compared regarding their main statistical indicators: correlation coefficients, predictivity, root mean square error of estimation (RMSEE), and root mean square error of cross-validation (RMSEEcv). All statistical models presented high regression and predictivity coefficients. The RMSEEcv for the optimal models was 1.118, 0.08, and 0.059% for MIR, NIR, and Raman spectroscopy, respectively. The scarce information content extracted from the ALZ NIR spectra and the major band overlapping with those from lactose monohydrate was the main culprit of poor accuracy in the NIR model, whereas the subsampling instrumental setup (resulting in a non-representative spectral acquisition of the sample) was regarded as a main limitation for the MIR-based calibration model. The OPLS models of the Raman spectra of the powder blends manifested favorable statistical indicators for the accuracy of the calibration model, probably due to the distinctive ALZ Raman pattern resulting in the largest number of predictive spectral points that were used for the mathematical modeling. Furthermore, the Raman scattering calibration model was optimized in narrower scanning range (1700–700 cm−1) and its prediction power was evaluated (root mean square error of prediction, RMSEP = 0.03%). Thus, the Raman spectroscopy presented the most favorable statistical indicators in this comparative study and therefore should be further considered as a PAT for the quantitative determination of ALZ in low-content powder blends.