scholarly journals Molecular recognition using tetralactam macrocycles with parallel aromatic sidewalls

2019 ◽  
Vol 15 ◽  
pp. 1086-1095 ◽  
Author(s):  
Dong-Hao Li ◽  
Bradley D Smith
Keyword(s):  
Organic Solvents ◽  
Near Infrared ◽  
Ion Pairs ◽  
Hydrophobic Effect ◽  
Guest Molecules ◽  
High Affinity ◽  
Secondary Interactions ◽  
Wide Range ◽  
Polar Functional Groups ◽  
Macrocyclic Cavity

This review summarizes the supramolecular properties of tetralactam macrocycles that have parallel aromatic sidewalls and four NH residues directed into the macrocyclic cavity. These macrocycles are versatile hosts for a large number of different guest structures in water and organic solvents, and they are well-suited for a range of supramolecular applications. The macrocyclic cavity contains a mixture of polar functional groups and non-polar surfaces which is reminiscent of the amphiphilic binding pockets within many proteins. In water, the aromatic surfaces in the tetralactam cavity drive high affinity due the hydrophobic effect and the NH groups provide secondary interactions that induce binding selectivity. In organic solvents, the supramolecular factors are reversed; the polar NH groups drive high affinity and the aromatic surfaces provide the secondary interactions. In addition to an amphiphilic cavity, macrocyclic tetralactams exhibit conformational flexibility, and the combination of properties enables them to be effective hosts for a wide range of guest molecules including organic biscarbonyl derivatives, near-infrared dyes, acenes, precious metal halide complexes, trimethylammonium ion-pairs, and saccharides.

scholarly journals Portable near Infrared Spectroscopy as a Tool for Fresh Tomato Quality Control Analysis in the Field

2021 ◽  
Vol 11 (7) ◽  
pp. 3209
Author(s):  
Karla R. Borba ◽  
Didem P. Aykas ◽  
Maria I. Milani ◽  
Luiz A. Colnago ◽  
Marcos D. Ferreira ◽  
...  
Keyword(s):  
Citric Acid ◽  
Near Infrared ◽  
Prediction Models ◽  
Quality Attributes ◽  
Internal Quality ◽  
Control Analysis ◽  
Tomato Quality ◽  
Wide Range ◽  
Different Types ◽  
Fresh Tomato

Portable spectrometers are promising tools that can be an alternative way, for various purposes, of analyzing food quality, such as monitoring in a few seconds the internal quality during fruit ripening in the field. A portable/handheld (palm-sized) near-infrared (NIR) spectrometer (Neospectra, Si-ware) with spectral range of 1295–2611 nm, equipped with a micro-electro-mechanical system (MEMs), was used to develop prediction models to evaluate tomato quality attributes non-destructively. Soluble solid content (SSC), fructose, glucose, titratable acidity (TA), ascorbic, and citric acid contents of different types of fresh tomatoes were analyzed with standard methods, and those values were correlated to spectral data by partial least squares regression (PLSR). Fresh tomato samples were obtained in 2018 and 2019 crops in commercial production, and four fruit types were evaluated: Roma, round, grape, and cherry tomatoes. The large variation in tomato types and having the fruits from distinct years resulted in a wide range in quality parameters enabling robust PLSR models. Results showed accurate prediction and good correlation (Rpred) for SSC = 0.87, glucose = 0.83, fructose = 0.87, ascorbic acid = 0.81, and citric acid = 0.86. Our results support the assertion that a handheld NIR spectrometer has a high potential to simultaneously determine several quality attributes of different types of tomatoes in a practical and fast way.

scholarly journals Tripodal, Squaramide-Based Ion Pair Receptor for Effective Extraction of Sulfate Salt

Molecules ◽  
2021 ◽  
Vol 26 (9) ◽  
pp. 2751
Author(s):  
Damian Jagleniec ◽  
Marcin Wilczek ◽  
Jan Romański
Keyword(s):  
Ion Pairs ◽  
Binding Mode ◽  
Selective Extraction ◽  
Ion Pair ◽  
Hofmeister Series ◽  
Sulfate Salt ◽  
Lower Affinity ◽  
High Affinity ◽  
Binding Domains ◽  
Hydrated Sulfate

Combining three features—the high affinity of squaramides toward anions, cooperation in ion pair binding and preorganization of the binding domains in the tripodal platform—led to the effective receptor 2. The lack of at least one of these key elements in the structures of reference receptors 3 and 4 caused a lower affinity towards ion pairs. Receptor 2 was found to form an intramolecular network in wet chloroform, which changed into inorganic–organic associates after contact with ions and allowed salts to be extracted from an aqueous to an organic phase. The disparity in the binding mode of 2 with sulfates and with other monovalent anions led to the selective extraction of extremely hydrated sulfate anions in the presence of more lipophilic salts, thus overcoming the Hofmeister series.

scholarly journals Nano-Crystallization of Ln-Fluoride Crystals in Glass-Ceramics via Inducing of Yb3+ for Efficient Near-Infrared Upconversion Luminescence of Tm3+

Nanomaterials ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 1033
Author(s):  
Jianfeng Li ◽  
Yi Long ◽  
Qichao Zhao ◽  
Shupei Zheng ◽  
Zaijin Fang ◽  
...  
Keyword(s):  
Crystal Structures ◽  
Near Infrared ◽  
Upconversion Luminescence ◽  
Glass Ceramics ◽  
Upconversion Emission ◽  
Ceramic Composites ◽  
Wide Range ◽  
Transmission Window ◽  
Optical Applications ◽  
Upconversion Emissions

Transparent glass-ceramic composites embedded with Ln-fluoride nanocrystals are prepared in this work to enhance the upconversion luminescence of Tm3+. The crystalline phases, microstructures, and photoluminescence properties of samples are carefully investigated. KYb3F10 nanocrystals are proved to controllably precipitate in the glass-ceramics via the inducing of Yb3+ when the doping concentration varies from 0.5 to 1.5 mol%. Pure near-infrared upconversion emissions are observed and the emission intensities are enhanced in the glass-ceramics as compared to in the precursor glass due to the incorporation of Tm3+ into the KYb3F10 crystal structures via substitutions for Yb3+. Furthermore, KYb2F7 crystals are also nano-crystallized in the glass-ceramics when the Yb3+ concentration exceeds 2.0 mol%. The upconversion emission intensity of Tm3+ is further enhanced by seven times as Tm3+ enters the lattice sites of pure KYb2F7 nanocrystals. The designed glass ceramics provide efficient gain materials for optical applications in the biological transmission window. Moreover, the controllable nano-crystallization strategy induced by Yb3+ opens a new way for engineering a wide range of functional nanomaterials with effective incorporation of Ln3+ ions into fluoride crystal structures.

scholarly journals The Use of a Micro Near Infrared Portable Instrument to Predict Bioactive Compounds in a Wild Harvested Fruit—Kakadu Plum (Terminalia ferdinandiana)

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1413
Author(s):  
Eshetu Bobasa ◽  
Anh Dao T. Phan ◽  
Michael Netzel ◽  
Heather E. Smyth ◽  
Yasmina Sultanbawa ◽  
...  
Keyword(s):  
Vitamin C ◽  
Bioactive Compounds ◽  
Ellagic Acid ◽  
Near Infrared ◽  
Wide Range ◽  
Fruit Samples ◽  
Nutritional Characteristics ◽  
Analytical Quantification ◽  
Kakadu Plum ◽  
Terminalia Ferdinandiana

Kakadu plum (KP; Terminalia ferdinandiana Exell, Combretaceae) is an emergent indigenous fruit originating from Northern Australia, with valuable health and nutritional characteristics and properties (e.g., high levels of vitamin C and ellagic acid). In recent years, the utilization of handheld NIR instruments has allowed for the in situ quantification of a wide range of bioactive compounds in fruit and vegetables. The objective of this study was to evaluate the ability of a handheld NIR spectrophotometer to measure vitamin C and ellagic acid in wild harvested KP fruit samples. Whole and pureed fruit samples were collected from two locations in the Kimberley region (Western Australia, Australia) and were analysed using both reference and NIR methods. The standard error in cross validation (SECV) and the residual predictive deviation (RPD) values were 1.81% dry matter (DM) with an RPD of 2.1, and 3.8 mg g−1 DM with an RPD of 1.9 for the prediction of vitamin C and ellagic acid, respectively, in whole KP fruit. The SECV and RPD values were 1.73% DM with an RPD of 2.2, and 5.6 mg g−1 DM with an RPD of 1.3 for the prediction of vitamin C and ellagic acid, respectively, in powdered KP samples. The results of this study demonstrated the ability of a handheld NIR instrument to predict vitamin C and ellagic acid in whole and pureed KP fruit samples. Although the RPD values obtained were not considered adequate to quantify these bioactive compounds (e.g., analytical quantification), this technique can be used as a rapid tool to screen vitamin C in KP fruit samples for high and low quality vitamin C.

scholarly journals Near-Infrared Spectroscopy for Monitoring Sternocleidomastoid Muscular Oxygenation during Isometric Flexion for Patients with Mild Nonspecific Neck Pain: A Pilot Study

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2197
Author(s):  
Chia-Chi Yang ◽  
Po-Ching Yang ◽  
Jia-Jin J. Chen ◽  
Yi-Horng Lai ◽  
Chia-Han Hu ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Neck Pain ◽  
Near Infrared Spectroscopy ◽  
Isometric Contraction ◽  
Oxidative Metabolism ◽  
Near Infrared ◽  
Maximum Voluntary Isometric Contraction ◽  
Clinical Scenarios ◽  
Wide Range ◽  
Asymptomatic Individuals

Since there is merit in noninvasive monitoring of muscular oxidative metabolism for near-infrared spectroscopy in a wide range of clinical scenarios, the present study attempted to evaluate the clinical usability for featuring the modulatory strategies of sternocleidomastoid muscular oxygenation using near-infrared spectroscopy in mild nonspecific neck pain patients. The muscular oxygenation variables of the dominant or affected sternocleidomastoid muscles of interest were extracted at 25% of the maximum voluntary isometric contraction from ten patients (5 males and 5 females, 23.6 ± 4.2 years) and asymptomatic individuals (6 males and 4 females, 24.0 ± 5.1 years) using near-infrared spectroscopy. Only a shorter half-deoxygenation time of oxygen saturation during a sternocleidomastoid isometric contraction was noted in patients compared to asymptomatic individuals (10.43 ± 1.79 s vs. 13.82 ± 1.42 s, p < 0.001). Even though the lack of statically significant differences in most of the muscular oxygenation variables failed to refine the definite pathogenic mechanisms underlying nonspecific neck pain, the findings of modulatory strategies of faster deoxygenation implied that near-infrared spectroscopy appears to have practical potential to provide relevant physiological information regarding muscular oxidative metabolism and constituted convincing preliminary evidences of the adaptive manipulations rather than pathological responses of oxidative metabolism capacity of sternocleidomastoid muscles in nonspecific neck patients with mild disability.

scholarly journals Autonomic nervous system dysfunction in schizophrenia: impact on cognitive and metabolic health

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Nicolette Stogios ◽  
Alexander Gdanski ◽  
Philip Gerretsen ◽  
Araba F. Chintoh ◽  
Ariel Graff-Guerrero ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Autonomic Dysfunction ◽  
Symptom Severity ◽  
Sympathetic Activity ◽  
Antipsychotic Treatment ◽  
Autonomic Activity ◽  
Autonomic Nervous System Dysfunction ◽  
High Affinity ◽  
Increased Risk ◽  
Wide Range

AbstractSchizophrenia (SCZ) is a psychiatric disorder characterized by a wide range of positive, negative and cognitive symptoms, along with an increased risk of metabolic syndrome and cardiovascular disease that contribute to a 15–20-year reduced life expectancy. Autonomic dysfunction, in the form of increased sympathetic activity and decreased parasympathetic activity, is postulated to be implicated in SCZ and its treatment. The aim of this narrative review is to view SCZ through an autonomic lens and synthesize the evidence relating autonomic dysfunction to different domains of SCZ. Using various methods of assessing autonomic activity, autonomic dysfunction was found to be associated with multiple aspects of SCZ pathophysiology, including symptom severity, cognitive impairment, and the development of cardiometabolic comorbidities, such as metabolic syndrome and high BMI. The strongest association of low heart rate variability was noted among patients on antipsychotic treatment with high-affinity muscarinic antagonism (i.e., clozapine, olanzapine and quetiapine). The review will also suggest ways in which studying autonomic dysfunction can help reduce morbidity and mortality associated with SCZ and its treatment.

Ether Synthesis through Reductive Cross-Coupling of Ketones with Alcohols Using Me2SiHCl as both Reductant and Lewis Acid

Synlett ◽  
2017 ◽  
Vol 28 (18) ◽  
pp. 2425-2428 ◽  
Author(s):  
Bill Morandi ◽  
Yong Lee
Keyword(s):  
Functional Groups ◽  
Lewis Acid ◽  
Carbonyl Compounds ◽  
Cross Coupling ◽  
Wide Range ◽  
Direct Cross ◽  
Sterically Hindered ◽  
Polar Functional Groups ◽  
Ether Synthesis ◽  
Dialkyl Ethers

We report that a Lewis acidic silane, Me2SiHCl, can mediate the direct cross-coupling of a wide range of carbonyl compounds with alcohols to form dialkyl ethers. The reaction is operationally simple, tolerates a range of polar functional groups, can be utilized to make sterically hindered ethers, and is extendable to sulfur and nitrogen nucleo­philes.

scholarly journals Prototype of the Near-Infrared Spectroscopy Expert System for Particleboard Identification

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Anna Sandak ◽  
Jakub Sandak ◽  
Dominika Janiszewska ◽  
Salim Hiziroglu ◽  
Marta Petrillo ◽  
...  
Keyword(s):  
Quality Control ◽  
Expert System ◽  
Near Infrared ◽  
System Development ◽  
Nir Spectroscopy ◽  
Original System ◽  
Adhesive System ◽  
Type Composition ◽  
Wide Range ◽  
Panel Type

The overall goal of this work was to develop a prototype expert system assisting quality control and traceability of particleboard panels on the production floor. Four different types of particleboards manufactured at the laboratory scale and in industrial plants were evaluated. The material differed in terms of panel type, composition, and adhesive system. NIR spectroscopy was employed as a pioneer tool for the development of a two-level expert system suitable for classification and traceability of investigated samples. A portable, commercially available NIR spectrometer was used for nondestructive measurements of particleboard panels. Twenty-five batches of particleboards, each containing at least three independent replicas, was used for the original system development and assessment of its performance. Four alternative chemometric methods (PLS-DA, kNN, SIMCA, and SVM) were used for spectroscopic data classification. The models were developed for panel recognition at two levels differing in terms of their generality. In the first stage, four among twenty-four tested combinations resulted in 100% correct classification. Discrimination precision with PLS-DA and SVMC was high (>99%), even without any spectra preprocessing. SNV preprocessed spectra and SVMC algorithm were used at the second stage for panel batch classification. Panels manufactured by two producers were 100% correctly classified, industrial panels produced by different manufacturing plants were classified with 98.9% success, and the experimental panels manufactured in the laboratory were classified with 63.7% success. Implementation of NIR spectroscopy for wood-based product traceability and quality control may have a great impact due to the high versatility of the production and wide range of particleboards utilization.

scholarly journals Deep learning classifiers for near infrared spectral imaging: a tutorial

2020 ◽  
Author(s):  
Jun-Li Xu ◽  
Cecilia Riccioli ◽  
Ana Herrero-Langreo ◽  
Aoife Gowen
Keyword(s):  
Deep Learning ◽  
Visual Recognition ◽  
Near Infrared ◽  
Three Dimensional ◽  
Spectral Imaging ◽  
Learning Approaches ◽  
Imaging Data ◽  
Spectral Image ◽  
Background Removal ◽  
Wide Range

Deep learning (DL) has recently achieved considerable successes in a wide range of applications, such as speech recognition, machine translation and visual recognition. This tutorial provides guidelines and useful strategies to apply DL techniques to address pixel-wise classification of spectral images. A one-dimensional convolutional neural network (1-D CNN) is used to extract features from the spectral domain, which are subsequently used for classification. In contrast to conventional classification methods for spectral images that examine primarily the spectral context, a three-dimensional (3-D) CNN is applied to simultaneously extract spatial and spectral features to enhance classificationaccuracy. This tutorial paper explains, in a stepwise manner, how to develop 1-D CNN and 3-D CNN models to discriminate spectral imaging data in a food authenticity context. The example image data provided consists of three varieties of puffed cereals imaged in the NIR range (943–1643 nm). The tutorial is presented in the MATLAB environment and scripts and dataset used are provided. Starting from spectral image pre-processing (background removal and spectral pre-treatment), the typical steps encountered in development of CNN models are presented. The example dataset provided demonstrates that deep learning approaches can increase classification accuracy compared to conventional approaches, increasing the accuracy of the model tested on an independent image from 92.33 % using partial least squares-discriminant analysis to 99.4 % using 3-CNN model at pixel level. The paper concludes with a discussion on the challenges and suggestions in the application of DL techniques for spectral image classification.

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