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Here, we present the first examination of the state of water under a soft confinement in eight aliphatic alcohols including cyclopentanol, 1-pentanol, 1-hexanol, 1-heptanol, 1-octanol, 1-decanol, 2-octanol and 3-octanol. Due to relatively large size of the aliphatic part, water has limited solubility in all studied alcohols. Water content in saturated solutions was determined by Karl Fischer titration and correlated with the spectroscopic data. This way, we determined the molar absorptivity of the ν 2 +ν 3 combination mode. The effect of addition of water and temperature variation was monitored by ATR-IR and NIR spectroscopy. Analysis of the experimental results was guided by DFT calculations, which provided the structures, harmonic MIR spectra and binding energies of selected alcohol-water complexes. Our studies demonstrated that the state of water in alcohols is related to its solubility, which depends on structure of solvent molecules. The solubility of water in 1-alcohols decreases on increasing of the chain length, but for long chain alcohols this effect is less evident. More apparent solubility reduction appears in going from the primary to secondary alcohols. The effective shielding of the OH group in the linear alcohols is achieved when on both sides of the OH group are ethyl or longer substituents, while the shielding by methyl groups is less efficient. Water is much better soluble in the cyclic alcohols as compared with the linear ones due to better accessibility of the OH group. The soft confinement of water in aliphatic alcohols allows for flexible structural arrangements and interactions. Even at low water content, we did not observe free molecules of water. At these conditions, the molecules of water are singly or doubly bonded to the OH groups from the alcohol. Increasing solubility of water reduces the number of the free OH groups and leads to formation of water clusters. Obtained results allow concluding that in alcohols with sizable aliphatic part the molecules of water are confined in the vicinity of the OH groups., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Contamination by microplastics, a global environmental concern, demands effective monitoring. While current methods focus on characterizing the smallest particles, their low throughput hinders practical assessment. Miniaturized near-infrared (NIR) spectroscopy offers high-throughput capabilities and rapid on-site analysis, potentially filling this gap. However, diverse sensor characteristics result in significant differences among handheld NIR spectrometers. This study characterizes the analytical performance of these instruments for identifying soil microplastics, comparing miniaturized devices MicroNIR 1700ES, NeoSpectra Scanner, microPHAZIR, nanoFTIR-NIR, NIR-S-G1, and SCiO sensor against a reference benchtop instrument, the NIRFlex N-500. Detection of common polymers, ABS, EVAC, HDPE, LDPE, PA6, PMMA, POM, PET, PS, PTFE, and SBR, at low concentrations (0.75 % w/w) was possible without sample preparation. Sensor selection proved crucial; FT instruments N-500 and NeoSpectra Scanner provided the most accurate analysis, while other handheld instruments faced various challenges. Covariance analysis, Principal Component Analysis (PCA), and mid-level data fusion revealed that miniaturized NIR spectrometers can successfully screen microplastics on-site. However, the ability of each sensor to discriminate certain groups of polymers strongly depends on its spectral characteristics. This study demonstrates the importance of sensor selection in the development of portable NIR spectroscopy for environmental monitoring of microplastics., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

The post-mortem interval estimation for human skeletal remains is critical in forensic medicine. This study used Raman spectroscopy, specifically comparing a handheld device to a Raman microscope for PMI estimations. Analyzing 99 autopsy bone samples and 5 archeological samples, the research categorized them into five PMI classes using conventional methods. Key parameters-like ν 1 PO 4 3- intensity and crystallinity-were measured and analyzed. A principal component analysis effectively distinguished between PMI classes, indicating high classification accuracy for both devices. While both methods proved reliable, the fluorescence interference presented challenges in accurately determining the age of archeological samples. Ultimately, the study highlighted how Raman spectroscopy could enhance PMI estimation accuracy, especially in non-specialized labs, suggesting the potential for improved device optimization in the field.

The aim of the presented study was to qualitatively and quantitatively determine the chemical composition of oak bark extracts in order to gain insights into the effectiveness as alternative medication for various diseases. The primary emphasis was on developing a near-infrared spectroscopy (NIRS) method for precise quantification of two key polyphenolic compounds, specifically gallic acid and catechin, in form of a fast and non-destructive quality control. A comprehensive dataset consisting of 48 samples from various production batches was analyzed throughout this research. Qualitative analysis was conducted using High Performance Liquid Chromatography coupled with a mass detector (LC-MS) to separate and identify individual components of the oak bark extract. Individual components were identified, confirmed and quantified using existing literature combined with appropriate standard references. Whereas the predominant nature of identified substances was of polyphenolic nature. Furthermore, a semi-quantitative assessment was additionally performed for eight identified constituents to identify their chemical stability or possible occurring transformations during storage, utilizing quantification via internal standard met in order to identify fluctuations and chemical variability within oakbark, five key components were precisely quantified using LC-MS and corresponding standard substances. For this purpose, HPLC measurements coupled to an Ultraviolet/Visible (UV/Vis) detector were utilized as reference method. NIRS measurements were performed on a FT-NIR benchtop device in transmission mode. Partial least squares regression (PLSR) was then applied for model building, after identifying the optimal spectral pretreatment. Model evaluation was performed using leave-one-out-cross validation followed by evaluation of an independent test set. The model proved promising results for the quantification of gallic acid on the benchtop device with a standard error of cross validation (SECV) of 13.41 mg/L and a standard error of prediction (SEP) of 19.33 mg/L, while the absolute concentrations of the different batches analyzed ranged from 126.49 to 332.54 mg/L. For the quantification of catechin the SECV was reported at 23.61 mg/L, the SEP at 32.35 mg/L with sample concentrations falling between 13.50 and 383.72 mg/L. In this study, we introduce various analytical methodologies for both qualitative and quantitative assessment of a complex phytochemical sample, specifically oak bark extract, aimed at identifying and confirming the presence of active compounds within the extract., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

We investigated the anharmonicity and intermolecular interactions of N-methylformamide (NMF) and di-N,N-methylformamide (DMF) in the neat liquid phase with particular interest in the amide bands. The vibrational spectra, complex refractive index, and complex electric permittivity were determined in in the mid- (MIR) and near-infrared (NIR) regions (11,500-560 cm -1 ; 870-17857 nm). Dispersion analysis was based on the Classical Damped Harmonic Oscillator (CDHO) and simultaneous modelling of the real and imaginary components of the spectra. This data delivered insights into the vibrational energy dissipation and self-association in liquid amides. Identification of the MIR and NIR bands was based on anharmonic GVPT2//B3LYP/6-311++G(d,p) calculations. DMF and NMF follow distinct self-association, evidenced in the MIR fingerprint by the two components of the νCO, the analog of the Amide I band. These conclusions are supported by the structural information derived from the NIR spectra. Furthermore, the contribution of overtones and combination bands in the MIR spectra of amides was examined. The conclusions on molecular interactions and structural dynamics of NMF and DMF contribute to a deeper understanding of the effects of changes in the local environment of the amide group., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Neocallimastigomycota are a phylum of anaerobic gut fungi (AGF) that inhabit the gastrointestinal tract of herbivores and play a pivotal role in plant matter degradation. Their identification and characterization with marker gene regions has long been hampered due to the high inter- and intraspecies length variability in the commonly used fungal marker gene region internal transcribed spacer (ITS). While recent research has improved methodology (i.e. switch to LSU D2 as marker region), molecular methods will always introduce bias through nucleic acid extraction or PCR amplification. Here, near-infrared spectroscopy (NIRS) and hyperspectral imaging (HSI) are introduced as two nucleic acid sequence-independent tools for the characterization and identification of AGF strains. We present a proof-of-concept for both, achieving an independent prediction accuracy of above 95% for models based on discriminant analysis trained with samples of three different genera. We further demonstrated the robustness of the NIRS model by testing it on cultures of different growth times. Overall, NIRS provides a simple, reliable, and nondestructive approach for AGF classification, independent of molecular approaches. The HSI method provides further advantages by requiring less biomass and adding spatial information, a valuable feature if this method is extended to mixed cultures or environmental samples in the future., Competing Interests: The authors have no conflicts of interest to declare that are relevant to the content of this article., (© The Author(s) 2024. Published by Oxford University Press on behalf of FEMS.)

The bioactive compounds Acetyl-11-keto-β-boswellic acid (AKBA) and 11-keto-β-boswellic acid (KBA), found in the resin of the Boswellia tree, exhibit anti-inflammatory properties, rendering Boswellia resin an intriguing natural medicinal products. However, the content of boswellic acids varies across different Boswellia species and proper knowledge of its species-dependent nature, as well as alternatives to the resource- and time-intensive HPLC analysis, are lacking. Here we present a comprehensive investigation into the boswellic acid content of seven Boswellia species from ten countries and introduce a novel and non-destructive Near-Infrared spectroscopy method for predicting boswellic acid concentrations in solid resin samples. The HPLC-UV reference analysis revealed AKBA concentrations of up to 7.27 % (w/w) with KBA concentrations reaching up to 1.28 % (w/w). Principal Component Analysis of the HPLC and NIR spectroscopy data unveiled species-specific variations, facilitating differentiation based on boswellic acid content, characteristic chromatograms and NIR spectra. Using the HPLC-UV quantification as reference, we developed a Partial Least Squares regression model based on NIR spectra of the resin samples. This model demonstrated highly satisfactory predictive capabilities for AKBA content, achieving a root mean square error of prediction of 0.74 % (w/w) and an R 2 val of 0.79 in independent test set validation. Although the model was less effective for predicting KBA content, it still offered valuable estimates. The spectroscopic method introduced in this study provides a cost-effective and solvent-free approach for predicting boswellic acid content, demonstrating the potential for application in non-laboratory settings through the use of miniaturized NIR spectrometers. Consequently, this method aligns well with the principles of green chemistry and addresses the growing demand for alternative analytical techniques., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Cystic echinococcosis (CE) is a global health concern caused by cestodes, posing diagnostic challenges due to nonspecific symptoms and inconclusive radiographic results. Diagnosis relies on histopathological evaluation of affected tissue, demanding comprehensive tools. In this retrospective case study, Fourier transform infrared microscopy was explored for detecting and identifying CE through biochemical changes in human tissue sections. Tissue samples from 11 confirmed CE patients were analyzed. Archived FFPE blocks were cut and stained, and then CE-positive unstained sections were examined using Fourier transform infrared microscopy post-deparaffinization. Results revealed the method's ability to distinguish echinococcus elements from human tissue, irrespective of organ type. This research showcases the potential of mid-infrared microscopy as a valuable diagnostic tool for CE, offering promise in enhancing diagnostic precision in the face of the disease's complexities., (© 2024 The Authors. Journal of Biophotonics published by Wiley‐VCH GmbH.)

This comprehensive review paper aims to captivate the applicability of in-sorbent detection, where near-infrared spectroscopy (NIRS) converges with enrichment technologies. For this purpose, we collected and summarized information regarding the combination of several sophisticated analytical enrichment techniques with NIRS to further explore and develop this synergistic approach. Peer-reviewed publications, matching the criteria of in situ NIR measurements prior analyte elution, have been collected, investigated, and concluded within this review. Investigations according to used materials, commercial or self-made, composition, organic or inorganic and applied analytical methodologies have been carried out. Applications extending over a multitude of chemical fields, from environmental to medicinal applications. As this review concludes, the combination of these techniques further expands the applicability of NIRS and moreover tries to solve the long-standing issue of the comparably low sensitivity regarding this vibrational technique., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

In forensic medicine, estimating human skeletal remains' post-mortem interval (PMI) can be challenging. Following death, bones undergo a series of chemical and physical transformations due to their interactions with the surrounding environment. Post-mortem changes have been assessed using various methods, but estimating the PMI of skeletal remains could still be improved. We propose a new methodology with handheld hyperspectral imaging (HSI) system based on the first results from 104 human skeletal remains with PMIs ranging between 1 day and 2000 years. To differentiate between forensic and archaeological bone material, the Convolutional Neural Network analyzed 65.000 distinct diagnostic spectra: the classification accuracy was 0.58, 0.62, 0.73, 0.81, and 0.98 for PMIs of 0 week-2 weeks, 2 weeks-6 months, 6 months-1 year, 1 year-10 years, and >100 years, respectively. In conclusion, HSI can be used in forensic medicine to distinguish bone materials >100 years old from those <10 years old with an accuracy of 98%. The model has adequate predictive performance, and handheld HSI could serve as a novel approach to objectively and accurately determine the PMI of human skeletal remains., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Background: Biliary complications (BCs) negatively impact the outcome after liver transplantation. We herein tested whether hyperspectral imaging (HSI) generated data from bile ducts (BD) on reperfusion and machine learning techniques for data readout may serve as a novel approach for predicting BC., Methods: Tissue-specific data from 136 HSI liver images were integrated into a convolutional neural network (CNN). Fourteen patients undergoing liver transplantation after normothermic machine preservation served as a validation cohort. Assessment of oxygen saturation, organ hemoglobin, and tissue water levels through HSI was performed after completing the biliary anastomosis. Resected BD segments were analyzed by immunohistochemistry and real-time confocal microscopy., Results: Immunohistochemistry and real-time confocal microscopy revealed mild (grade I: 1%-40%) BD damage in 8 patients and moderate (grade II: 40%-80%) injury in 1 patient. Donor and recipient data alone had no predictive capacity toward BC. Deep learning-based analysis of HSI data resulted in >90% accuracy of automated detection of BD. The CNN-based analysis yielded a correct classification in 72% and 69% for BC/no BC. The combination of HSI with donor and recipient factors showed 94% accuracy in predicting BC., Conclusions: Deep learning-based modeling using CNN of HSI-based tissue property data represents a noninvasive technique for predicting postoperative BC., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Iberian ham is a highly appreciated product and according to Spanish legislation different labels identify different products depending on the genetic purity. Consequently, "100% Iberian" ham from purebred Iberian animals is more expensive than "Iberian" ham from Iberian x Duroc crosses. The hypothesis of this study was that to avoid labelling fraud it is possible to distinguish the breed (Iberian or Iberian x Duroc) of acorn-fed pigs of Iberian ham without any prior preparation of the sample by using spectroscopy that is a rapid and reliable technology. Moreover, portable devices which can be used in situ could provide similar results to those of benchtop equipment. Therefore, the spectra of the 60 samples (24 samples of 100% Iberian ham and 36 samples of Iberian x Duroc crossbreed ham) were recorded only for the fat, only for the muscle, or for the whole slice with two benchtop near-infrared (NIR) spectrometers (Büchi NIRFlex N-500 and Foss NIRSystem 5000) and five portable spectrometers including four portable NIR devices (VIAVI MicroNIR 1700 ES, TellSpec Enterprise Sensor, Thermo Fischer Scientific microPHAZIR, and Consumer Physics SCiO Sensor), and one RAMAN device (BRAVO handheld). The results showed that, in general, the whole slice recording produced the best results for classification purposes. The SCiO device showed the highest percentages of correctly classified samples (97% in calibration and 92% in validation) followed by TellSpec (100% and 81%). The SCiO sensor also showed the highest percentages of success when the analyses were performed only on lean meat (97% in calibration and 83% in validation) followed by microPHAZIR (84% and 81%), while in the case of the fat tissue. Raman technology showed the best discrimination capacity (96% and 78%) followed by microPHAZIR (89% and 81%). Therefore, spectroscopy has proved to be a suitable technology for discriminating ham samples according to breed purity; portable devices have been shown to give even better results than benchtop spectrometers., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Osteomyelitis is a bone disease caused by bacteria that can damage bone. Raman handheld spectroscopy has emerged as a promising diagnostic tool for detecting bone infection and can be used intraoperatively during surgical procedures. This study involved 120 bone samples from 40 patients, with 80 samples infected with either Staphylococcus aureus or Staphylococcus epidermidis. Raman handheld spectroscopy demonstrated successful differentiation between healthy and infected bone samples and between the two types of bacterial pathogens. Raman handheld spectroscopy appears to be a promising diagnostic tool in bone infection and holds the potential to overcome many of the shortcomings of traditional diagnostic procedures. Further research, however, is required to confirm its diagnostic capabilities and consider other factors, such as the limit of pathogen detection and optimal calibration standards.

This work provides new insight into the state of water in a series of aliphatic ketones. For our studies, we selected nine aliphatic ketones of different size and structure to examine the effect of various structural motifs on behavior of water in the mixtures. Our results reveal that conformational flexibility of aliphatic chains in the linear ketones allows for effective shielding of the carbonyl group, and this flexibility is the main reason for poor solubility of water. Hence, in the linear ketones molecules of water are involved mostly in ketone-water interactions, while the water-water interactions are rare. Higher solubility of water in the cyclic ketones allows for creation of clusters of water, where the molecules are in water-like environment. The temperature rise in wet cyclic ketones increases population of ketone-water interactions at the expense of the water-water ones, while in the linear ketones and 2,6-dimethylcyclohexanone at an elevated temperature there is an increase in the population of singly bonded water at the expense of the doubly bonded one. DFT calculations reveal that the substitution of cyclohexanone by a single methyl group does not affect the strength of the ketone-water interactions, while it has a significant impact on the solubility of water in the ketone. The most important conclusion from this study is that the accessibility of the carbonyl group is the most important factor determining the intermolecular interactions and solubility of water in aliphatic ketones., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

The present study presents an alternative analytical workflow that combines mid-infrared (MIR) microscopic imaging and deep learning to diagnose human lymphoma and differentiate between small and large cell lymphoma. We could show that using a deep learning approach to analyze MIR hyperspectral data obtained from benign and malignant lymph node pathology results in high accuracy for correct classification, learning the distinct region of 3900 to 850 cm -1 . The accuracy is above 95% for every pair of malignant lymphoid tissue and still above 90% for the distinction between benign and malignant lymphoid tissue for binary classification. These results demonstrate that a preliminary diagnosis and subtyping of human lymphoma could be streamlined by applying a deep learning approach to analyze MIR spectroscopic data., (© 2023 The Authors. Journal of Biophotonics published by Wiley-VCH GmbH.)

Estimating postmortem intervals (PMI) is crucial in forensic investigations, providing insights into criminal cases and determining the time of death. PMI estimation relies on expert experience and a combination of thanatological data and environmental factors but is prone to errors. The lack of reliable methods for assessing PMI in bones and soft tissues necessitates a better understanding of bone decomposition. Several research groups have shown promise in PMI estimation in skeletal remains but lack valid data for forensic cases. Current methods are costly, time-consuming, and unreliable for PMIs over 5 years. Raman spectroscopy (RS) can potentially estimate PMI by studying chemical modifications in bones and teeth correlated with burial time. This review summarizes RS applications, highlighting its potential as an innovative, nondestructive, and fast technique for PMI estimation in forensic medicine., (© 2023 The Authors. Journal of Biophotonics published by Wiley-VCH GmbH.)

Bone analyses using mid-infrared spectroscopy are gaining popularity, especially with handheld spectrometers that enable on-site testing as long as the data quality meets standards. In order to diagnose Staphylococcus epidermidis in human bone grafts, this study was carried out to compare the effectiveness of the Agilent 4300 Handheld Fourier-transform infrared with the Perkin Elmer Spectrum 100 attenuated-total-reflectance infrared spectroscopy benchtop instrument. The study analyzed 40 non-infected and 10 infected human bone samples with Staphylococcus epidermidis , collecting reflectance data between 650 cm -1 and 4000 cm -1 , with a spectral resolution of 2 cm -1 (Agilent 4300 Handheld) and 0.5 cm -1 (Perkin Elmer Spectrum 100). The acquired spectral information was used for spectral and unsupervised classification, such as a principal component analysis. Both methods yielded significant results when using the recommended settings and data analysis strategies, detecting a loss in bone quality due to the infection. MIR spectroscopy provides a valuable diagnostic tool when there is a tissue shortage and time is of the essence. However, it is essential to conduct further research with larger sample sizes to verify its pros and cons thoroughly.

E-liquids have become increasingly popular in society in recent years. A wide variety of flavors and nicotine strengths make it possible for every user to get a product according to their wishes. Many of these e-liquids are marketed with countless different flavors, which are often characterized by a strong and sweet smell. Sweeteners, such as sucralose, are therefore commonly added as sugar substitutes. However, recent studies have shown the potential formation of highly toxic chlorinated compounds. This can be explained by the high temperatures (above 120 °C) within the heating coils and the used basic composition of these liquids. Nevertheless, the legal situation is composed of proposals without clear restrictions, only recommendations for tobacco products. For this reason, a high level of interest lies within the establishment of fast, reliable and cost-effective methods for the detection of sucralose in e-liquids. In this study, a number of 100 commercially available e-liquids was screened for sucralose in order to identify the suitability of ambient mass spectrometry and near-infrared spectroscopy for this application. A highly sensitive high-performance liquid chromatography coupled to a tandem mass spectrometer method was used as reference method. Furthermore, the advantages and limitations of the two mentioned methods are highlighted in order to provide a reliable quantification of sucralose. The results clearly revile the necessity for product quality due to the absence of declaration on many of the used products. Further on, it could be shown, that both methods are suitable for the quantification of sucralose in e-liquids, with beneficial economic and ecological aspects, over classical analytical tools including high-performance liquid chromatography. Clear correlations between the reference and novel developed methods are displayed. In summary, these methods enable an important contribution to ensure consumer protection and elimination of confuse package labelling.

Spectroscopic methods deliver a valuable non-destructive analytical tool that provides simultaneous qualitative and quantitative characterization of various samples. Apples belong to the world's most consumed crops and with the current challenges of climate change and human impacts on the environment, maintaining high-quality apple production has become critical. This review comprehensively analyzes the application of spectroscopy in near-infrared (NIR) and visible (Vis) regions, which not only show particular potential in evaluating the quality parameters of apples but also in optimizing their production and supply routines. This includes the assessment of the external and internal characteristics such as color, size, shape, surface defects, soluble solids content (SSC), total titratable acidity (TA), firmness, starch pattern index (SPI), total dry matter concentration (DM), and nutritional value. The review also summarizes various techniques and approaches used in Vis/NIR studies of apples, such as authenticity, origin, identification, adulteration, and quality control. Optical sensors and associated methods offer a wide suite of solutions readily addressing the main needs of the industry in practical routines as well, e.g., efficient sorting and grading of apples based on sweetness and other quality parameters, facilitating quality control throughout the production and supply chain. This review also evaluates ongoing development trends in the application of handheld and portable instruments operating in the Vis/NIR and NIR spectral regions for apple quality control. The use of these technologies can enhance apple crop quality, maintain competitiveness, and meet the demands of consumers, making them a crucial topic in the apple industry. The focal point of this review is placed on the literature published in the last five years, with the exceptions of seminal works that have played a critical role in shaping the field or representative studies that highlight the progress made in specific areas.

Introduction: We analyzed the expression of PD-L1 in human lymphomas using hyperspectral imaging (HSI) compared to visual assessment (VA) and conventional digital image analysis (DIA) to strengthen further the value of HSI as a tool for the evaluation of brightfield-based immunohistochemistry (IHC). In addition, fluorescent multiplex immunohistochemistry (mIHC) was used as a second detection method to analyze the impact of a different detection method., Material and Methods: 18 cases (6 follicular lymphomas and 12 diffuse large B-cell lymphomas) were stained for PD-L1 by IHC and for PD-L1, CD3, and CD8 by fluorescent mIHC. The percentage of positively stained cells was evaluated with VA, HSI, and DIA for IHC and VA and DIA for mIHC. Results were compared between the different methods of detection and analysis., Results: An overall high concordance was found between VA, HSI, and DIA in IHC (Cohens Kappa = 0.810 VA / HSI , 0.710 VA/DIA , and 0.516 HSI / DIA ) and for VA mIHC versus DIA mIHC (Cohens Kappa = 0.894). Comparing IHC and mIHC general agreement differed depending on the methods compared but reached at most a moderate agreement (Coheńs Kappa between 0.250 and 0.483). This is reflected by the significantly higher percentage of PD-L1+ cells found with mIHC (p Friedman  = 0.014)., Conclusion: Our study shows a good concordance for the different analysis methods. Compared to VA and DIA, HSI proved to be a reliable tool for assessing IHC. Understanding the regulation of PD-L1 expression will further enlighten the role of PD-L1 as a biomarker. Therefore it is necessary to develop an instrument, such as HSI, which can offer a reliable and objective evaluation of PD-L1 expression., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Introduction: Raman microscopic spectroscopyis a new approach for further characterization and detection of molecular features in many pathological processes. This technique has been successfully applied to scrutinize the spatial distribution of small molecules and proteins within biological systems by in situ analysis. This study uses Raman microscopic spectroscopyto identify any in-depth benefits and drawbacks in diagnosing Staphylococcus epidermidis in human bone grafts., Material and Methods: 40 non-infected human bone samples and 10 human bone samples infected with Staphylococcus epidermidis were analyzed using Raman microscopic spectroscopy. Reflectance data were collected between 200 cm -1 and 3600 cm -1 with a spectral resolution of 4 cm -1 using a Senterra II microscope (Bruker, Ettlingen, Germany). The acquired spectral information was used for spectral and unsupervised classification, such as principal component analysis., Results: Raman measurements produced distinct diagnostic spectra that were used to distinguish between non-infected human bone samples and Staphylococcus epidermidis infected human bone samples by spectral and principal component analyses. A substantial loss in bone quality and protein conformation was detected by human bone samples co-cultured with Staphylococcus epidermidis. The mineral-to-matrix ratio using the phosphate/Amide I ratio (p = 0.030) and carbonate/phosphate ratio (p = 0.001) indicates that the loss of relative mineral content in bones upon bacterial infection is higher than in non-infected human bones. Also, an increase of alterations in the collagen network (p = 0.048) and a decrease in the structural organization and relative collagen in infected human bone could be detected. Subsequent principal component analyses identified Staphylococcus epidermidis in different spectral regions, respectively, originating mainly from CH 2 deformation (wagging) of protein (at 1450 cm -1 ) and bending and stretching modes of C-H groups (∼2800-3000 cm -1 )., Conclusion: Raman microscopic spectroscopyis presented as a promising diagnostic tool to detect Staphylococcus epidermidis in human bone grafts. Further studies in human tissues are warranted., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Quantum mechanical calculations are routinely used as a major support in mid-infrared (MIR) and Raman spectroscopy. In contrast, practical limitations for long time formed a barrier to developing a similar synergy between near-infrared (NIR) spectroscopy and computational chemistry. Recent advances in theoretical methods suitable for calculation of NIR spectra opened the pathway to modeling NIR spectra of various molecules. Accurate theoretical reproduction of NIR spectra of molecules reaching the size of long-chain fatty acids was accomplished so far. In silico NIR spectroscopy, where the spectra are calculated ab initio, provides substantial improvement in our understanding of the overtones and combination bands that overlap in staggering numbers and create complex lineshape typical for NIR spectra. This improves the comprehension of the spectral information enabling access to rich and detail molecular footprint, essential for fundamental research and useful in routine analysis by NIR spectroscopy and chemometrics. This review article summarizes the most recent accomplishments in the emerging field with examples of simulated NIR spectra of molecules reaching long-chain fatty acids and polymers. In addition to detailed NIR band assignments and new physical insights, simulated spectra enable innovative support in applications. Understanding of the difference in the performance observed between miniaturized NIR spectrometers and chemical interpretation of the chemometric models are noteworthy here. These new elements integrated into NIR spectroscopy framework enable a knowledge-based design of the analysis with comprehension of the processed chemical information., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

The interaction of water with polymers is an intensively studied topic. Vibrational spectroscopy techniques, mid-infrared (MIR) and Raman, were often used to investigate the properties of water-polymer systems. On the other hand, relatively little attention has been given to the potential of using near-infrared (NIR) spectroscopy (12,500-4000 cm -1 ; 800-2500 nm) for exploring this problem. NIR spectroscopy delivers exclusive opportunities for the investigation of molecular structure and interactions. This technique derives information from overtones and combination bands, which provide unique insights into molecular interactions. It is also very well suited for the investigation of aqueous systems, as both the bands of water and the polymer can be reliably acquired in a range of concentrations in a more straightforward manner than it is possible with MIR spectroscopy. In this study, we applied NIR spectroscopy to investigate interactions of water with polymers of varying hydrophobicity: polytetrafluoroethylene (PTFE), polypropylene (PP), polystyrene (PS), polyvinylchloride (PVC), polyoxymethylene (POM), polyamide 6 (PA), lignin (Lig), chitin (Chi) and cellulose (Cell). Polymer-water mixtures in the concentration range of water between 1-10%( w / w ) were investigated. Spectra analysis and interpretation were performed with the use of difference spectroscopy, Principal Component Analysis (PCA), Median Linkage Clustering (MLC), Partial Least Squares Regression (PLSR), Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) and Two-Dimensional Correlation Spectroscopy (2D-COS). Additionally, from the obtained data, aquagrams were constructed and interpreted with aid of the conclusions drawn from the conventional approaches. We deepened insights into the problem of water bands obscuring compound-specific signals in the NIR spectrum, which is often a limiting factor in analytical applications. The study unveiled clearly visible trends in NIR spectra associated with the chemical nature of the polymer and its increasing hydrophilicity. We demonstrated that changes in the NIR spectrum of water are manifested even in the case of interaction with highly hydrophobic polymers (e.g., PTFE). Furthermore, the unveiled spectral patterns of water in the presence of different polymers were found to be dissimilar between the two major water bands in NIR spectrum ( ν s + ν as and ν as + δ ).

Estimating the post-mortem interval (PMI) of human skeletal remains is a critical issue of forensic analysis, with important limitations such as sample preparation and practicability. In this work, NIR spectroscopy (NIRONE® Sensor X; Spectral Engines, 61449, Germany) was applied to estimate the PMI of 104 human bone samples between 1 day and 2000 years. Reflectance data were repeatedly collected from eight independent spectrometers between 1950 and 1550 nm with a spectral resolution of 14 nm and a step size of 2 nm, each from the external and internal bone. An Artificial Neural Network was used to analyze the 66,560 distinct diagnostic spectra, and clearly distinguished between forensic and archaeological bone material: the classification accuracies for PMIs of 0−2 weeks, 2 weeks−6 months, 6 months−1 year, 1 year−10 years, and >100 years were 0.90, 0.94, 0.94, 0.93, and 1.00, respectively. PMI of archaeological bones could be determined with an accuracy of 100%, demonstrating the adequate predictive performance of the model. Applying a handheld NIR spectrometer to estimate the PMI of human skeletal remains is rapid and extends the repertoire of forensic analyses as a distinct, novel approach.

Introduction: To implement Hyperspectral Imaging (HSI) as a tool for quantifying inflammatory cells in tissue specimens by the example of myocarditis in a collective of forensic patients., Material and Methods: 44 consecutive patients with suspected myocardial inflammation at autopsy, diagnosed between 2013 and 2018 at the Institute of ForensicMedicine, Medical University of Innsbruck, were selected for this study. Using the IMEC SNAPSCAN camera, visible and near infrared hyperspectral images were collected from slides stained with CD3 and CD45 to assess quantity and spatial distribution of positive cells. Results were compared with visual assessment (VA) and conventional digital image analysis (DIA)., Results: Finally, specimens of 40 patients were evaluated, of whom 36 patients (90%) suffered from myocarditis, two patients (5%) had suspected healing/healed myocarditis, and two did no have myocarditis (5%). The amount of CD3 and CD45 positive cells did not differ significantly between VA, HSI, and DIA (p VA/HSI/DIA  = 0.46 for CD3 and 0.81 for CD45). Coheńs Kappa showed a very high correlation between VA versus HSI, VA versus DIA, and HSI versus DIA for CD3 (Coheńs Kappa = 0.91, 1.00, and 0.91, respectively). For CD45 an almost as high correlation was seen for VA versus HSI and HSI versus DIA (Coheńs Kappa = 0.75 and 0.70) and VA versus DIA (Coheńs Kappa = 0.89)., Conclusion: HSI is a reliable and objective method to count inflammatory cells in tissue slides of suspected myocarditis. Implementation of HSI in digital pathology might further expand the possibility of a sophisticated method., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier B.V.)

The ongoing miniaturization of spectrometers creates a perfect synergy with the common advantages of near-infrared (NIR) spectroscopy, which together provide particularly significant benefits in the field of food analysis. The combination of portability and direct onsite application with high throughput and a noninvasive way of analysis is a decisive advantage in the food industry, which features a diverse production and supply chain. A miniaturized NIR analytical framework is readily applicable to combat various food safety risks, where compromised quality may result from an accidental or intentional (i.e., food fraud) origin. In this review, the characteristics of miniaturized NIR sensors are discussed in comparison to benchtop laboratory spectrometers regarding their performance, applicability, and optimization of methodology. Miniaturized NIR spectrometers remarkably increase the flexibility of analysis; however, various factors affect the performance of these devices in different analytical scenarios. Currently, it is a focused research direction to perform systematic evaluation studies of the accuracy and reliability of various miniaturized spectrometers that are based on different technologies; e.g., Fourier transform (FT)-NIR, micro-optoelectro-mechanical system (MOEMS)-based Hadamard mask, or linear variable filter (LVF) coupled with an array detector, among others. Progressing technology has been accompanied by innovative data-analysis methods integrated into the package of a micro-NIR analytical framework to improve its accuracy, reliability, and applicability. Advanced calibration methods (e.g., artificial neural networks (ANN) and nonlinear regression) directly improve the performance of miniaturized instruments in challenging analyses, and balance the accuracy of these instruments toward laboratory spectrometers. The quantum-mechanical simulation of NIR spectra reveals the wavenumber regions where the best-correlated spectral information resides and unveils the interactions of the target analyte with the surrounding matrix, ultimately enhancing the information gathered from the NIR spectra. A data-fusion framework offers a combination of spectral information from sensors that operate in different wavelength regions and enables parallelization of spectral pretreatments. This set of methods enables the intelligent design of future NIR analyses using miniaturized instruments, which is critically important for samples with a complex matrix typical of food raw material and shelf products.

The decarboxylation of Δ9-tetrahydrocannabinolic acid (THCA) plays pivotal role in the potency of medical cannabis and its extracts. Our present work aims to draw attention to mid-infrared (MIR) spectroscopy to in-situ monitor and decipher the THCA decarboxylation reaction in the solid state. The initial TG/DTG curves of THCA, for a first time, outlined the solid-solid decarboxylation dynamics, defined the endpoint of the process and the temperature of the maximal conversion rate, which aided in the design of the further IR experiment. Temperature controlled IR spectroscopy experiments were performed on both THCA standard and cannabis flower by providing detailed band assignment and conducting spectra-structure correlations, based on the concept of functional groups vibrations. Moreover, a multivariate statistical analysis was employed to address the spectral regions of utmost importance for the THCA → THC interconversion process. The principal component analysis model was reduced to two PCs, where PC1 explained 94.76% and 98.21% of the total spectral variations in the THCA standard and in the plant sample, respectively. The PC1 plot score of the THCA standard, as a function of the temperature, neatly complemented to the TG/DTG curves and enabled determination of rate constants for the decarboxylation reaction undertaken on several selected temperatures. The predictive capability of MIR was further demonstrated with PLS (R2X = 0.99, R2Y = 0.994 and Q2 = 0.992) using thermally treated flower samples that covered broad range of THCA/THC content. Consequently, a progress in elucidation of kinetic models of THCA decarboxylation in terms of fitting the experimental data for both, solid state standard substance and a plant flower, was achieved. The results open the horizon to promote an appropriate process analytical technology (PAT) in the outgrowing medical cannabis industry., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Truffles represent the best known and most expensive edible mushroom. Known as Ascomycetes , they belong to the genus Tuber and live in symbiosis with plant host roots. Due to their extraordinary taste and smell, truffles are sold worldwide for high prices of up to 3000-5000 euros per kilogram ( Tuber magnatum &nbsp;PICO). Amongst black truffles, the species Tuber melanosporum &nbsp;VITTAD. is highly regarded for its organoleptic properties. Nonetheless, numerous different sorts of black truffle are offered at lower prices, including Tuber aestivum &nbsp;VITTAD., Tuber indicum and Tuber uncinatum , which represent the most frequently consumed types. Because truffles do not differ visually for inexperienced consumers, food fraud is likely to occur. In particular, for the highly prized Tuber melanosporum , which morphologically forms very similar fruiting bodies to those of Tuber indicum , there is a risk of fraud via imported truffles from Asia. In this study, 126 truffle samples belonging to the four mentioned species were investigated by four different NIR instruments, including three miniaturized devices-the Tellspec Enterprise Sensor, the VIAVI solutions MicroNIR 1700 and the Consumer Physics SCiO-working on different technical principles. Three different types of measurement techniques were applied for all instruments (outer shell, rotational device and fruiting body) in order to identify the best results for classification and quality assurance in a non-destructive manner. Results provided differentiation with an accuracy up to 100% for the expensive Tuber melanosporum from Tuber indicum . Classification between Tuber melanosporum , Tuber indicum , Tuber aestivum and Tuber uncinatum could also be achieved with success of 100%. In addition, quality monitoring including discrimination between fresh and frozen/thawed, and prediction of the approximate date of harvesting, was performed. Furthermore, feasibility studies according to the geographical origin of the truffle were attempted. The presented work compares the performance for prediction and quality monitoring of portable vs. benchtop NIR devices and applied measurement techniques in order to be able to present a suitable, accurate, fast, non-destructive and reliable method for consumers.

This study describes a newly developed method for the fast and straightforward differentiation of two turmeric species using Direct Analysis in Real Time mass spectrometry and miniaturized Near Infrared spectroscopy. Multivariate analyses (PCA and LDA) were performed on the mass spectrometric data, thus creating a powerful model for the discrimination of Curcumalonga and Curcumaxanthorrhiza. Cross-validation of the model revealed correctness-scores of 100% with 20-fold as well as leave-one-out validation techniques. To further estimate the models prediction power, seven retail samples of turmeric powder were analyzed and assorted to a species. Looking for a fast, non-invasive, cost-efficient and laboratory independent method, miniaturized NIR spectrometers offer an alternative for quality control of turmeric species. However, different technologies implemented to compensate for their small size, lead to different applicability of these spectrometers. Therefore, we investigated the three handheld spectrometers microPHAZIR, MicroNIR 2200 and MicroNIR 1700ES for their application in spice analysis in hyphenation to PCA, LDA and ANN methods used for the discriminant analysis. While microPHAZIR proved to be the most valuable device for differentiating C.longa and C.xanthorrhiza, MicroNIR 1700ES offered the worst results. These findings are interpreted on the basis of a quantum chemical simulation of the NIR spectrum of curcumin as the representative constituent. It was found that the information accessible to MicroNIR 1700ES that is relevant to the analyzed constituents is located in the spectral region prone to interferences with the matrix, likely limiting the performance of this spectrometer in this analytical scenario., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved.)

The content of the flavonolignan mixture silymarin and its individual components (silichristin, silidianin, silibinin A, silibinin B, isosilibinin A, and isosilibinin B) in whole and milled milk thistle seeds (Silybi mariani fructus) was analyzed with near-infrared spectroscopy. The analytical performance of one benchtop and two handheld near-infrared spectrometers was compared. Reference analysis was performed with HPLC following a Soxhlet extraction (European Pharmacopoeia) and a more resource-efficient ultrasonic extraction. The reliability of near-infrared spectral analysis determined through partial least squares regression models constructed independently for the spectral datasets obtained by the three spectrometers was as follows. The benchtop device NIRFlex N-500 performed the best both for milled and whole seeds with a root mean square error of CV between 0.01 and 0.17%. The handheld spectrometer MicroNIR 2200 as well as the microPHAZIR provided a similar performance (root mean square error of CV between 0.01 and 0.18% and between 0.01 and 0.23%, respectively). We carried out quantum chemical simulation of near-infrared spectra of silichristin, silidianin, silibinin, and isosilibinin for interpretation of the results of spectral analysis. This provided understanding of the absorption regions meaningful for the calibration. Further, it helped to better separate how the chemical and physical properties of the samples affect the analysis. While the study demonstrated that milling of samples slightly improves the performance, it was deemed to be critical only for the analysis carried out with the microPHAZIR. This study evidenced that rapid and nondestructive quantification of silymarin and individual flavonolignans is possible with miniaturized near-infrared spectroscopy in whole milk thistle seeds., Competing Interests: The authors declare that they have no conflict of interest., (Thieme. All rights reserved.)

Near-infrared (NIR) spectroscopy is a valued analytical tool in various applications involving polymers. However, complex nature of NIR spectra imposes difficulties in their direct interpretation. Here, anharmonic quantum chemical calculations are used to simulate NIR spectra of nine polymers; acrylonitrile butadiene styrene (ABS), ethylene-vinyl acetate (EVAC), polycarbonate (PC), polyethylene terephthalate (PET), polylactide or polylactic acid (PLA), polymethylmethacrylate (PMMA), polyoxymethylene (POM), polystyrene (PS) and polyvinylchloride (PVC). The generalized spectra-structure correlations are derived for these systems with focus given to the manifestation in NIR spectra of aromatic ring, C=O, C≡N and C-Cl functionalities. It is concluded that the nature of NIR polymer bands is only moderately sensitive to the remote chemical neighborhood. The majority of NIR absorption of polymers originates from binary combination bands, while the first overtones are meaningful only in ca. 6200-5500 cm -1 region. The contribution of the overtone bands is relatively higher for the polymers bearing aromatic rings because of higher intensity of C-H stretching overtones. Highly characteristic combination bands of the modes localized in aromatic ring (ring deformation and CH stretching) are relatively independent on the remaining structure of the polymer. The combination bands originating from C=O group are more sensitive to the chemical neighborhood in near proximity, forming a useful fingerprint for a specific polymer. In contrast, the vibrational bands of C≡N functionality are far less useful in NIR region than in infrared (IR) region. With aid of the calculated absorption bands, structural specificity of NIR spectroscopy of polymers can be markedly improved., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved.)

Mutations in HFE cause hereditary hemochromatosis type I hallmarked by increased iron absorption, iron accumulation in hepatocytes and iron deficiency in myeloid cells. HFE encodes an MHC-I like molecule, but its function in immune responses to infection remains incompletely understood. Here, we investigated putative roles of Hfe in myeloid cells and hepatocytes, separately, upon infection with Salmonella Typhimurium, an intracellular bacterium with iron-dependent virulence. We found that constitutive and macrophage-specific deletion of Hfe protected infected mice. The propagation of Salmonella in macrophages was reduced due to limited intramacrophage iron availability for bacterial growth and increased expression of the anti-microbial enzyme nitric oxide synthase-2. By contrast, mice with hepatocyte-specific deletion of Hfe succumbed earlier to Salmonella infection because of unrestricted extracellular bacterial replication associated with high iron availability in the serum and impaired expression of essential host defense molecules such as interleukin-6, interferon-γ and nitric oxide synthase-2. Wild-type mice subjected to dietary iron overload phenocopied hepatocyte-specific Hfe deficiency suggesting that increased iron availability in the serum is deleterious in Salmonella infection and underlies impaired host immune responses. Moreover, the macrophage-specific effect is dominant over hepatocyte-specific Hfe-depletion, as Hfe knock-out mice have increased survival despite the higher parenchymal iron load associated with systemic loss of Hfe. We conclude that cell-specific expression of Hfe in hepatocytes and macrophages differentially affects the course of infections with specific pathogens by determining bacterial iron access and the efficacy of anti-microbial immune effector pathways. This may explain the high frequency and evolutionary conservation of human HFE mutations.

Mid-infrared (MIR) and near-infrared (NIR) spectra of crystalline menadione (vitamin K 3 ) were measured and analyzed with aid of quantum chemical calculations. The calculations were carried out using the harmonic approach for the periodic model of crystal lattice and the anharmonic DVPT2 calculations applied for the single molecule model. The theoretical spectra accurately reconstructed the experimental ones permitting for reliable assignment of the MIR and NIR bands. For the first time, a detailed analysis of the NIR spectrum of a molecular system based on a naphthoquinone moiety was performed to elucidate the relationship between the chemical structure of menadione and the origin of the overtones and combination bands. In addition, the importance of these bands during interpretation of the MIR spectrum was demonstrated. The overtones and combination bands contribute to 46.4% of the total intensity of menadione in the range of 3600-2600 cm -1 . Evidently, these bands play a key role in shaping of the C-H stretching region of MIR spectrum. We have shown also that the spectral regions without fundamentals may provide valuable structural information. For example, the theoretical calculations reliably reconstructed numerous overtones and combination bands in the 4000-3600 and 2800-1800 cm -1 ranges. These results, provide a comprehensive origin of the fundamentals, overtones and combination bands in the NIR and MIR spectra of menadione, and the relationship of these spectral features with the molecular structure.

Future food supply will become increasingly dependent on edible material extracted from insects. The growing popularity of artisanal food products enhanced by insect proteins creates particular needs for establishing effective methods for quality control. This study focuses on developing rapid and efficient on-site quantitative analysis of protein content in handcrafted insect bars by miniaturized near-infrared (NIR) spectrometers. Benchtop (Büchi NIRFlex N-500) and three miniaturized (MicroNIR 1700 ES, Tellspec Enterprise Sensor and SCiO Sensor) in hyphenation to partial least squares regression (PLSR) and Gaussian process regression (GPR) calibration methods and data fusion concept were evaluated via test-set validation in performance of protein content analysis. These NIR spectrometers markedly differ by technical principles, operational characteristics and cost-effectiveness. In the non-destructive analysis of intact bars, the root mean square error of cross prediction (RMSEP) values were 0.611% (benchtop) and 0.545-0.659% (miniaturized) with PLSR, and 0.506% (benchtop) and 0.482-0.580% (miniaturized) with GPR calibration, while the analyzed total protein content was 19.3-23.0%. For milled samples, with PLSR the RMSEP values improved to 0.210% for benchtop spectrometer but remained in the inferior range of 0.525-0.571% for the miniaturized ones. GPR calibration improved the predictive performance of the miniaturized spectrometers, with RMSEP values of 0.230% (MicroNIR 1700 ES), 0.326% (Tellspec) and 0.338% (SCiO). Furthermore, Tellspec and SCiO sensors are consumer-oriented devices, and their combined use for enhanced performance remains a viable economical choice. With GPR calibration and test-set validation performed for fused (Tellspec + SCiO) data, the RMSEP values were improved to 0.517% (in the analysis of intact samples) and 0.295% (for milled samples).

The purpose of this review is to demonstrate advances, challenges and perspectives of quantum chemical approaches in molecular spectroscopy of the condensed phase. Molecular spectroscopy, particularly vibrational spectroscopy and electronic spectroscopy, has been used extensively for a wide range of areas of chemical sciences and materials science as well as nano- and biosciences because it provides valuable information about structure, functions, and reactions of molecules. In the meantime, quantum chemical approaches play crucial roles in the spectral analysis. They also yield important knowledge about molecular and electronic structures as well as electronic transitions. The combination of spectroscopic approaches and quantum chemical calculations is a powerful tool for science, in general. Thus, our article, which treats various spectroscopy and quantum chemical approaches, should have strong implications in the wider scientific community. This review covers a wide area of molecular spectroscopy from far-ultraviolet (FUV, 120-200 nm) to far-infrared (FIR, 400-10 cm -1 )/terahertz and Raman spectroscopy. As quantum chemical approaches, we introduce several anharmonic approaches such as vibrational self-consistent field (VSCF) and the combination of periodic harmonic calculations with anharmonic corrections based on finite models, grid-based techniques like the Numerov approach, the Cartesian coordinate tensor transfer (CCT) method, Symmetry-Adapted Cluster Configuration-Interaction (SAC-CI), and the ZINDO (Semi-empirical calculations at Zerner's Intermediate Neglect of Differential Overlap). One can use anharmonic approaches and grid-based approaches for both infrared (IR) and near-infrared (NIR) spectroscopy, while CCT methods are employed for Raman, Raman optical activity (ROA), FIR/terahertz and low-frequency Raman spectroscopy. Therefore, this review overviews cross relations between molecular spectroscopy and quantum chemical approaches, and provides various kinds of close-reality advanced spectral simulation for condensed phases.

Mid-infrared (MIR) microscopic imaging of indolent and aggressive lymphomas was performed including formalin-fixed and paraffin-embedded samples of six follicular lymphomas and 12 diffuse large B-cell-lymphomas as well as reactive lymph nodes to investigate benefits and challenges for lymphoma diagnosis. MIR images were compared to defined pathological characteristics such as indolent versus aggressive versus reactive, germinal centre versus activated cell-of-origin (COO) subtypes, or a low versus a high proliferative index and level of PD-L1 expression. We demonstrated that MIR microscopic imaging can differentiate between reactive lymph nodes, indolent and aggressive lymphoma samples. Also, it has potential to be used in the subtyping of lymphomas, as shown with the differentiation between COO subtypes, the level of proliferation and PD-L1 expression. MIR microscopic imaging is a promising tool for diagnosis and subtyping of lymphoma and further evaluation is needed to fully explore the advantages and disadvantages of this method for pathological diagnosis., (© 2021 The Authors. Journal of Biophotonics published by Wiley-VCH GmbH.)

Anharmonic quantum chemical calculations were employed to simulate and interpret a near-infrared (NIR) spectrum of caffeine. First and second overtones, as well as binary and ternary combination bands, were obtained, accurately reproducing the lineshape of the experimental spectrum in the region of 10,000-4000 cm -1 (1000-2500 nm). The calculations enabled performing a detailed analysis of NIR spectra of caffeine, including weak bands due to the second overtones and ternary combinations. A highly convoluted nature of NIR spectrum of caffeine was unveiled, with numerous overlapping bands found beneath the observed spectral lineshape. To properly reflect that intrinsic complexity, the band assignments were provided in the form of heat maps presenting the contributions to the NIR spectrum from various kinds of vibrational transitions. These contributions were also quantitatively assessed in terms of the integral intensities. It was found that the combination bands provide the decisively dominant contributions to the NIR spectrum of caffeine. The first overtones gain significant importance between 6500-5500 cm -1 , while the second overtones are meaningful in the higher wavenumber regions, particularly in the 10,000-7000 cm -1 region. The obtained detailed band assignments enabled deep interpretation of the absorption regions of caffeine identified in the literature as meaningful for analytical applications of NIR spectroscopy focused on quantitative analysis of caffeine content in drugs and natural products.

Recently polyphenols attracted great interest in the field of food and nutrition as well as in the pharmaceutical and cosmetics industries due to their health benefits through antioxidative behavior in the human body. However, because of the high number of compounds characterized as phenols and their structural diversity, quantification of polyphenols turns out to be a highly complex task. Although, a wide variety of analytical methods are used for the determination of total polyphenolic content, they are all found to be lacking in a variety of different tasks, such as their limits of detection and quantification, repeatability, accuracy and specificity. For this reason, a novel approach combining the advantages of solid phase purification, near infrared analysis and multivariate data analysis was investigated for the prediction of total polyphenolic content, suitable for a wide range of sample matrices. Dispersive solid phase extraction was performed and optimized using polyvinylpyrrolidone as sorbent, known to selectively bind polyphenols. Near-infrared detection of adsorbed polyphenols was carried out subsequently. Furthermore, the method was in-house validated, examining selectivity, repeatability and accuracy, working range, as well as multivariate limit of detection and limit of quantification, comparing it with two routinely used methods-namely, Folin-Ciocalteu photometric assay and Löwenthal titration. The novel established method was applied for the prediction of total polyphenolic content in tea and wine samples.

We investigated the near-infrared spectrum of piperine using quantum mechanical calculations. We evaluated two efficient approaches, DVPT2//PM6 and DVPT2//ONIOM [PM6:B3LYP/6-311++G(2df, 2pd)] that yielded a simulated spectrum with varying accuracy versus computing time factor. We performed vibrational assignments and unveiled complex nature of the near-infrared spectrum of piperine, resulting from a high level of band convolution. The most meaningful contribution to the near-infrared absorption of piperine results from binary combination bands. With the available detailed near-infrared assignment of piperine, we interpreted the properties of partial least square regression models constructed in our earlier study to describe the piperine content in black pepper samples. Two models were compared with spectral data sets obtained with a benchtop and a miniaturized spectrometer. The two spectrometers implement distinct technology which leads to a profound instrumental difference and discrepancy in the predictive performance when analyzing piperine content. We concluded that the sensitivity of the two instruments to certain types of piperine vibrations is different and that the benchtop spectrometer unveiled higher selectivity. Such difference in obtaining chemical information from a sample can be one of the reasons why the benchtop spectrometer performs better in analyzing the piperine content of black pepper. This evidenced direct correspondence between the features critical for applied near-infrared spectroscopic routine and the underlying vibrational properties of the analyzed constituent in a complex sample.