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Current Topics in Medicinal Chemistry

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ISSN (Print): 1568-0266
ISSN (Online): 1873-4294

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Current Frontiers

Review on the Discovery of Water Absorbance Spectral Pattern in Aquaphotomics based on Chemometrics Analytical Tools

Author(s): Xiaobo Ma, Boran Lin, Bing Zhao, Xiaoying Wei, Qin Dong, Hui Zhang, Lian Li and Hengchang Zang*

Volume 23, Issue 17, 2023

Published on: 05 May, 2023

Page: [1606 - 1623] Pages: 18

DOI: 10.2174/1568026623666230329090341

Price: $65

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Abstract

Aquaphotomics, as a new discipline is a powerful tool for exploring the relationship between the structure of water and the function of matter by analyzing the interaction between water and light of various frequencies. However, chemometric tools, especially the Water Absorbance Spectral Pattern (WASP) determinations, are essential in this kind of data mining. In this review, different state-of-the-art chemometrics methods were introduced to determine the WASP of aqueous systems. We elucidate the methods used for identifying activated water bands in three aspects, namely: 1) improving spectral resolution; the complexity of water species in aqueous systems leads to a serious overlap of NIR spectral signals, therefore, we need to obtain reliable information hidden in spectra, 2) extracting spectral features; sometimes, certain spectral information cannot be revealed by simple data processing, it is necessary to extract deep data information, 3) overlapping peak separation; since the spectral signal is produced by multiple factors, overlapping peak separation can be used to facilitate the extraction of spectral components. The combined use of various methods can characterize the changes of different water species in the system with disturbance and can determine the WASP. WASPs of research systems vary from each other, and it is visually displayed in the form of the aquagram. As a new omics family member, aquaphotomics could be applied as a holistic marker in multidisciplinary fields.

Keywords: Aquaphotomics, Water, Water absorbance spectral pattern (WASP), Near-infrared spectroscopy (NIR), Chemometrics, Water species.

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[1]
Segtnan, V.H.; Šašić, Š.; Isaksson, T.; Ozaki, Y. Studies on the structure of water using two-dimensional near-infrared correlation spectroscopy and principal component analysis. Anal. Chem., 2001, 73(13), 3153-3161.
[http://dx.doi.org/10.1021/ac010102n] [PMID: 11467567]
[2]
Muncan, J.; Tsenkova, R. Aquaphotomics—from innovative knowledge to integrative platform in science and technology. Molecules, 2019, 24(15), 2742.
[http://dx.doi.org/10.3390/molecules24152742] [PMID: 31357745]
[3]
Huse, N.; Wen, H.; Nordlund, D.; Szilagyi, E.; Daranciang, D.; Miller, T.A.; Nilsson, A.; Schoenlein, R.W.; Lindenberg, A.M. Probing the hydrogen-bond network of water via time-resolved soft X-ray spectroscopy. Phys. Chem. Chem. Phys., 2009, 11(20), 3951-3957.
[http://dx.doi.org/10.1039/b822210j] [PMID: 19440624]
[4]
Robertson, W.H.; Diken, E.G.; Price, E.A.; Shin, J.W.; Johnson, M.A. Spectroscopic determination of the OH- solvation shell in the OH-.(H2O)n clusters. Science, 2003, 299(5611), 1367-1372.
[http://dx.doi.org/10.1126/science.1080695] [PMID: 12543981]
[5]
Rezus, Y.L.A.; Bakker, H.J. Observation of immobilized water molecules around hydrophobic groups. Phys. Rev. Lett., 2007, 99(14), 148301.
[http://dx.doi.org/10.1103/PhysRevLett.99.148301] [PMID: 17930728]
[6]
Tsenkova, R. Aquaphotomics: Dynamic spectroscopy of aqueous and biological systems describes peculiarities of water. J. Near Infrared Spectrosc., 2009, 17(6), 303-313.
[http://dx.doi.org/10.1255/jnirs.869]
[7]
Tsenkova, R.; Kovacs, Z.; Kubota, Y. Aquaphotomics: Near infrared spectroscopy and water states in biological systems. Subcell. Biochem., 2015, 71, 189-211.
[http://dx.doi.org/10.1007/978-3-319-19060-0_8] [PMID: 26438266]
[8]
Tsenkova, R.; Munćan, J.; Pollner, B.; Kovacs, Z. Essentials of aquaphotomics and its chemometrics approaches. Front Chem., 2018, 6, 363.
[http://dx.doi.org/10.3389/fchem.2018.00363] [PMID: 30211151]
[9]
Sun, Y.; Cai, W.; Shao, X. Water as a spectroscopic probe for detection of structural analysis. Fenxi Ceshi Xuebao, 2020, 39(10), 1204-1208.
[10]
Steen, G.W.; Fuchs, E.C.; Wexler, A.D.; Offerhaus, H.L. Identification and quantification of 16 inorganic ions in water by Gaussian curve fitting of near-infrared difference absorbance spectra. Appl. Opt., 2015, 54(19), 5937-5942.
[http://dx.doi.org/10.1364/AO.54.005937] [PMID: 26193135]
[11]
Muncan, J.; Tei, K.; Tsenkova, R. Real-time monitoring of yogurt fermentation process by aquaphotomics near-infrared spectroscopy. Sensors, 2020, 21(1), 177.
[http://dx.doi.org/10.3390/s21010177] [PMID: 33383861]
[12]
Mura, S.; Cappai, C.; Greppi, G.F.; Barzaghi, S.; Stellari, A.; Cattaneo, T.M.P. Vibrational spectroscopy and Aquaphotomics holistic approach to determine chemical compounds related to sustainability in soil profiles. Comput. Electron. Agric., 2019, 159, 92-96.
[http://dx.doi.org/10.1016/j.compag.2019.03.002]
[13]
Cui, X.; Zhang, J.; Cai, W.; Shao, X. Selecting temperature-dependent variables in near-infrared spectra for aquaphotomics. Chemom. Intell. Lab. Syst., 2018, 183, 23-28.
[http://dx.doi.org/10.1016/j.chemolab.2018.10.006]
[14]
Vanoli, M.; Lovati, F.; Grassi, M.; Buccheri, M.; Zanella, A.; Cattaneo, T.M.P. Water spectral pattern as a marker for studying apple sensory texture. Adv. Hortic. Sci., 2018, 32(3), 343-351.
[http://dx.doi.org/10.13128/ahs-22380]
[15]
Vanoli, M.; Grassi, M.; Lovati, F.; Barzaghi, S.; Cattaneo, T.M.P.; Rizzolo, A. Influence of innovative coatings on salami ripening assessed by near infrared spectroscopy and aquaphotomics. J. Near Infrared Spectrosc., 2019, 27(1), 54-64.
[http://dx.doi.org/10.1177/0967033518811796]
[16]
Santos-Rivera, M.; Woolums, A.R.; Thoresen, M.; Meyer, F.; Vance, C.K. Bovine Respiratory Syncytial Virus (BRSV) infection detected in exhaled breath condensate of dairy calves by near-infrared aquaphotomics. Molecules, 2022, 27(2), 549.
[http://dx.doi.org/10.3390/molecules27020549] [PMID: 35056864]
[17]
Baishya, N.; Mamouei, M.; Budidha, K.; Qassem, M.; Vadgama, P.; Kyriacou, P.A. Near Infrared and Aquaphotomic analysis of water absorption in lactate containing media. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc., 2020, 2020, 4381-4384.
[http://dx.doi.org/10.1109/EMBC44109.2020.9176675] [PMID: 33018966]
[18]
Ozaki, Y.; Šašić, S.; Jiang, J.H. How can we unravel complicated near infrared spectra? Recent progress in spectral analysis methods for resolution enhancement and band assignments in the near infrared region. J. Near Infrared Spectrosc., 2001, 9(2), 63-95.
[http://dx.doi.org/10.1255/jnirs.295]
[19]
Czarnecki, M.A.; Morisawa, Y.; Futami, Y.; Ozaki, Y. Advances in molecular structure and interaction studies using near-infrared spectroscopy. Chem. Rev., 2015, 115(18), 9707-9744.
[http://dx.doi.org/10.1021/cr500013u] [PMID: 26370249]
[20]
Kojić, D.; Tsenkova, R.; Tomobe, K.; Yasuoka, K.; Yasui, M. Water confined in the local field of ions. Chem. Phys. Chem., 2014, 15(18), 4077-4086.
[http://dx.doi.org/10.1002/cphc.201402381] [PMID: 25284338]
[21]
Uema, T.; Ohata, T.; Washizuka, Y.; Nakanishi, R.; Kawashima, D.; Kakuta, N. Near-infrared imaging in a microfluidic channel of aqueous acid-base reactions. Chem. Eng. J., 2021, 403, 126338.
[http://dx.doi.org/10.1016/j.cej.2020.126338]
[22]
Kojić, D.; Tsenkova, R.; Yasui, M. Improving accuracy and reproducibility of vibrational spectra for diluted solutions. Anal. Chim. Acta, 2017, 955, 86-97.
[http://dx.doi.org/10.1016/j.aca.2016.12.019] [PMID: 28088284]
[23]
Li, D.; Li, L.; Quan, S.; Dong, Q.; Liu, R.; Sun, Z.; Zang, H. A feasibility study on quantitative analysis of low concentration methanol by FT-NIR spectroscopy and aquaphotomics. J. Mol. Struct., 2019, 1182, 197-203.
[http://dx.doi.org/10.1016/j.molstruc.2019.01.056]
[24]
Li, Y.; Guo, L.; Li, L.; Yang, C.; Guang, P.; Huang, F.; Chen, Z.; Wang, L.; Hu, J. Early diagnosis of Type 2 diabetes based on near-infrared spectroscopy combined with machine learning and aquaphotomics. Front Chem., 2020, 8, 580489.
[http://dx.doi.org/10.3389/fchem.2020.580489] [PMID: 33425846]
[25]
Bázár, G.; Romvári, R.; Szabó, A.; Somogyi, T.; Éles, V.; Tsenkova, R. NIR detection of honey adulteration reveals differences in water spectral pattern. Food Chem., 2016, 194, 873-880.
[http://dx.doi.org/10.1016/j.foodchem.2015.08.092] [PMID: 26471630]
[26]
Sannia, M.; Serva, L.; Balzan, S.; Segato, S.; Novelli, E.; Fasolato, L. Application of near-infrared spectroscopy for frozen-thawed characterization of cuttlefish (Sepia officinalis). J. Food Sci. Technol., 2019, 56(10), 4437-4447.
[http://dx.doi.org/10.1007/s13197-019-03957-6] [PMID: 31686675]
[27]
Czarnecki, M.A. Resolution enhancement in second-derivative spectra. Appl. Spectrosc., 2015, 69(1), 67-74.
[http://dx.doi.org/10.1366/14-07568] [PMID: 25499557]
[28]
Rinnan, Å.; Berg, F.; Engelsen, S.B. Review of the most common pre-processing techniques for near-infrared spectra. Trends Analyt. Chem., 2009, 28(10), 1201-1222.
[http://dx.doi.org/10.1016/j.trac.2009.07.007]
[29]
Dong, Q.; Guo, X.; Li, L.; Yu, C.; Nie, L.; Tian, W.; Zhang, H.; Huang, S.; Zang, H. Understanding hyaluronic acid induced variation of water structure by near-infrared spectroscopy. Sci. Rep., 2020, 10(1), 1387.
[http://dx.doi.org/10.1038/s41598-020-58417-5] [PMID: 31992833]
[30]
Kuroki, S.; Tsenkova, R.; Moyankova, D.; Muncan, J.; Morita, H.; Atanassova, S.; Djilianov, D. Water molecular structure underpins extreme desiccation tolerance of the resurrection plant Haberlea rhodopensis. Sci. Rep., 2019, 9(1), 3049.
[http://dx.doi.org/10.1038/s41598-019-39443-4] [PMID: 30816196]
[31]
Ozaki, Y. A new trend in spectral analysis in the NIR region. SAGE J., 2001, 12(6), 3-5.
[http://dx.doi.org/10.1255/nirn.636]
[32]
Jinendra, B.; Tamaki, K.; Kuroki, S.; Vassileva, M.; Yoshida, S.; Tsenkova, R. Near infrared spectroscopy and aquaphotomics: Novel approach for rapid in vivo diagnosis of virus infected soybean. Biochem. Biophys. Res. Commun., 2010, 397(4), 685-690.
[http://dx.doi.org/10.1016/j.bbrc.2010.06.007] [PMID: 20570650]
[33]
Liu, L.; Zhang, K.; Sun, Z.; Dong, Q.; Li, L.; Zang, H. A new perspective in understanding the dissolution behavior of nifedipine controlled release tablets by NIR spectroscopy with aquaphotomics. J. Mol. Struct., 2021, 1230, 129872.
[http://dx.doi.org/10.1016/j.molstruc.2021.129872]
[34]
Shao, X.; Ma, C. A general approach to derivative calculation using wavelet transform. Chemom. Intell. Lab. Syst., 2003, 69(1-2), 157-165.
[http://dx.doi.org/10.1016/j.chemolab.2003.08.001]
[35]
Shao, X.; Cui, X.; Wang, M.; Cai, W. High order derivative to investigate the complexity of the near infrared spectra of aqueous solutions. Spectrochim. Acta A Mol. Biomol. Spectrosc., 2019, 213, 83-89.
[http://dx.doi.org/10.1016/j.saa.2019.01.059] [PMID: 30684883]
[36]
Fan, M.; Cai, W.; Shao, X. Investigating the structural change in protein aqueous solution using temperature-dependent near-infrared spectroscopy and continuous wavelet transform. Appl. Spectrosc., 2017, 71(3), 472-479.
[http://dx.doi.org/10.1177/0003702816664103] [PMID: 27650983]
[37]
Cui, X.; Sun, Y.; Cai, W.; Shao, X. Chemometric methods for extracting information from temperature-dependent near-infrared spectra. Sci. China Chem., 2019, 62(5), 583-591.
[http://dx.doi.org/10.1007/s11426-018-9398-2]
[38]
Yuan, B.; Murayama, K.; Wu, Y.; Tsenkova, R.; Dou, X.; Era, S.; Ozaki, Y. Temperature-dependent near-infrared spectra of bovine serum albumin in aqueous solutions: Spectral analysis by principal component analysis and evolving factor analysis. Appl. Spectrosc., 2003, 57(10), 1223-1229.
[http://dx.doi.org/10.1366/000370203769699072] [PMID: 14639749]
[39]
Gowen, A.A.; Marini, F.; Tsuchisaka, Y.; De Luca, S.; Bevilacqua, M.; O’Donnell, C.; Downey, G.; Tsenkova, R. On the feasibility of near infrared spectroscopy to detect contaminants in water using single salt solutions as model systems. Talanta, 2015, 131, 609-618.
[http://dx.doi.org/10.1016/j.talanta.2014.08.049] [PMID: 25281148]
[40]
Gao, LL.; Zhong, L.; Zhang, J.; Zhang, MQ.; Zeng, YZ.; Li, L Water as a probe to understand the traditional Chinese medicine extraction process with near infrared spectroscopy: A case of Danshen (Salvia miltiorrhiza Bge) extraction process Spectrochimica Acta Part a-Molecular and Biomolecular Spectroscopy, 2021, 244, 118854.
[http://dx.doi.org/10.1016/j.saa.2020.118854]
[41]
Kaur, H.; Künnemeyer, R.; McGlone, A. Correction of temperature variation with independent water samples to predict soluble solids content of kiwifruit juice using NIR spectroscopy. Molecules, 2022, 27(2), 504.
[http://dx.doi.org/10.3390/molecules27020504] [PMID: 35056819]
[42]
Kaur, H. Investigating aquaphotomics for fruit quality assessment; The University of Waikato: PhD Thesis, Hamilton, New Zealand, 2020.
[43]
Kovacs, Z.; Bázár, G.; Oshima, M.; Shigeoka, S.; Tanaka, M.; Furukawa, A.; Nagai, A.; Osawa, M.; Itakura, Y.; Tsenkova, R. Water spectral pattern as holistic marker for water quality monitoring. Talanta, 2016, 147, 598-608.
[http://dx.doi.org/10.1016/j.talanta.2015.10.024] [PMID: 26592651]
[44]
Wang, L.; Zhu, X.; Cai, W.; Shao, X. Understanding the role of water in the aggregation of poly(N, N -dimethylaminoethyl methacrylate) in aqueous solution using temperature-dependent near-infrared spectroscopy. Phys. Chem. Chem. Phys., 2019, 21(10), 5780-5789.
[http://dx.doi.org/10.1039/C8CP07153E] [PMID: 30801574]
[45]
Sun, Y.; Cai, W.; Shao, X. Chemometrics: An Excavator in temperature-dependent near-infrared spectroscopy. Molecules, 2022, 27(2), 452.
[http://dx.doi.org/10.3390/molecules27020452] [PMID: 35056768]
[46]
Cui, X.; Zhang, J.; Cai, W.; Shao, X. Chemometric algorithms for analyzing high dimensional temperature dependent near infrared spectra. Chemom. Intell. Lab. Syst., 2017, 170, 109-117.
[http://dx.doi.org/10.1016/j.chemolab.2017.08.010]
[47]
Gowen, A.A.; Amigo, J.M.; Tsenkova, R. Characterisation of hydrogen bond perturbations in aqueous systems using aquaphotomics and multivariate curve resolution-alternating least squares. Anal. Chim. Acta, 2013, 759, 8-20.
[http://dx.doi.org/10.1016/j.aca.2012.10.007] [PMID: 23260672]
[48]
Cheng, D.; Cai, W.; Shao, X. Understanding the interaction between oligopeptide and water in aqueous solution using temperature-dependent near-infrared spectroscopy. Appl. Spectrosc., 2018, 72(9), 1354-1361.
[http://dx.doi.org/10.1177/0003702818769410] [PMID: 29664323]
[49]
Thissen, U.; Pepers, M.; Üstün, B.; Melssen, W.J.; Buydens, L.M.C. Comparing support vector machines to PLS for spectral regression applications. Chemom. Intell. Lab. Syst., 2004, 73(2), 169-179.
[http://dx.doi.org/10.1016/j.chemolab.2004.01.002]
[50]
Putra, A.; Vassileva, M.; Santo, R.; Tsenkova, R. An efficient near infrared spectroscopy based on aquaphotomics technique for rapid determining the level of Cadmium in aqueous solution. IOP Conf. Series Mater. Sci. Eng., 2017, 210, 012014.
[http://dx.doi.org/10.1088/1757-899X/210/1/012014]
[51]
Bázár, G.; Kovacs, Z.; Tanaka, M.; Furukawa, A.; Nagai, A.; Osawa, M.; Itakura, Y.; Sugiyama, H.; Tsenkova, R. Water revealed as molecular mirror when measuring low concentrations of sugar with near infrared light. Anal. Chim. Acta, 2015, 896, 52-62.
[http://dx.doi.org/10.1016/j.aca.2015.09.014] [PMID: 26481987]
[52]
Malegori, C.; Muncan, J.; Mustorgi, E.; Tsenkova, R.; Oliveri, P. Analysing the water spectral pattern by near-infrared spectroscopy and chemometrics as a dynamic multidimensional biomarker in preservation: Rice germ storage monitoring. Spectrochim. Acta A Mol. Biomol. Spectrosc., 2022, 265, 120396.
[http://dx.doi.org/10.1016/j.saa.2021.120396] [PMID: 34592685]
[53]
Goto, N.; Bazar, G.; Kovacs, Z.; Kunisada, M.; Morita, H.; Kizaki, S.; Sugiyama, H.; Tsenkova, R.; Nishigori, C. Detection of UV-induced cyclobutane pyrimidine dimers by near-infrared spectroscopy and aquaphotomics. Sci. Rep., 2015, 5(1), 11808.
[http://dx.doi.org/10.1038/srep11808] [PMID: 26133899]
[54]
Marium, M.; Rahman, M.M.; Mollah, M.Y.A.; Susan, M.A.B.H. Molecular level interactions in binary mixtures of 1-ethyl 3-methylimidazolium tetrafluoroborate and water. RSC Advances, 2015, 5(26), 19907-19913.
[http://dx.doi.org/10.1039/C5RA00083A]
[55]
Cao, W.; Mao, C.; Chen, W.; Lin, H.; Krishnan, S.; Cauchon, N. Differentiation and quantitative determination of surface and hydrate water in lyophilized mannitol using NIR spectroscopy. J. Pharm. Sci., 2006, 95(9), 2077-2086.
[http://dx.doi.org/10.1002/jps.20706] [PMID: 16850397]
[56]
Takeuchi, M.; Martra, G.; Coluccia, S.; Anpo, M. Investigations of the structure of H2O clusters adsorbed on TiO2 surfaces by near-infrared absorption spectroscopy. J. Phys. Chem. B, 2005, 109(15), 7387-7391.
[57]
Mai, R.; He, F.; Pan, D.; Huang, Z. Application of wavelet and neural network in dealing with dynamic testing signals of piles. Hydrogeology & Engineering Geology, 2004, 31(5), 91-96.
[58]
Zhang, H.; Zhang, J.; Zhong, H.; Pan, Z.; Zhang, M. Investigation on application of wavelet transform in resolving overlapped peaks in oscillographic chronopotentiom etry. J Northwest Univ., 1999, 29(4), 313-316.
[59]
Durickovic, I. Using Raman Spectroscopy for Characterization of Aqueous Media and Quantification of Species in Aqueous Solution. In: Applications of Molecular Spectroscopy to Current Research in the Chemical and Biological Sciences; Stauffer, M.T., Ed.; , 2016; pp. 405-427.
[http://dx.doi.org/10.5772/64550]
[60]
Xu, J.L.; Dorrepaal, R.M.; Martinez-Gonzalez, J.; Tsenkova, R.; Gowen, A.A. Near‐infrared multivariate model transfer for quantification of different hydrogen bonding species in aqueous systems. J. Chemometr., 2020, 34(9), 3274.
[http://dx.doi.org/10.1002/cem.3274]
[61]
Takeuchi, M.; Martra, G.; Coluccia, S.; Anpo, M. Evaluation of the adsorption states of H2O on oxide surfaces by vibrational absorption: Near- and mid-infrared spectroscopy. J. Near Infrared Spectrosc., 2009, 17(6), 373-384.
[http://dx.doi.org/10.1255/jnirs.843]
[62]
Dong, Q.; Yu, C.; Li, L.; Nie, L.; Li, D.; Zang, H. Near-infrared spectroscopic study of molecular interaction in ethanol-water mixtures. Spectrochim. Acta A Mol. Biomol. Spectrosc., 2019, 222, 117183.
[http://dx.doi.org/10.1016/j.saa.2019.117183] [PMID: 31185441]
[63]
Ma, L.; Cui, X.; Cai, W.; Shao, X. Understanding the function of water during the gelation of globular proteins by temperature-dependent near infrared spectroscopy. Phys. Chem. Chem. Phys., 2018, 20(30), 20132-20140.
[http://dx.doi.org/10.1039/C8CP01431K] [PMID: 30027956]
[64]
Dong, Q.; Yu, C.; Li, L.; Nie, L.; Zhang, H.; Zang, H. Analysis of hydration water around human serum albumin using near-infrared spectroscopy. Int. J. Biol. Macromol., 2019, 138, 927-932.
[http://dx.doi.org/10.1016/j.ijbiomac.2019.07.183] [PMID: 31362025]
[65]
Cui, X.; Cai, W.; Shao, X. Glucose induced variation of water structure from temperature dependent near infrared spectra. RSC Advances, 2016, 6(107), 105729-105736.
[http://dx.doi.org/10.1039/C6RA18912A]
[66]
Sun, Q. The effects of dissolved hydrophobic and hydrophilic groups on water structure. J. Solution Chem., 2020, 49(12), 1473-1484.
[http://dx.doi.org/10.1007/s10953-020-01035-6]
[67]
Czarnik-Matusewicz, B.; Murayama, K.; Tsenkova, R.; Ozaki, Y. Analysis of near-infrared spectra of complicated biological fluids by two-dimensional correlation spectroscopy: Protein and fat concentration-dependent spectral changes of milk. Appl. Spectrosc., 1999, 53(12), 1582-1594.
[http://dx.doi.org/10.1366/0003702991946046]
[68]
Muncan, J.; Matovic, V.; Nikolic, S.; Askovic, J.; Tsenkova, R. Aquaphotomics approach for monitoring different steps of purification process in water treatment systems. Talanta, 2020, 206, 120253.
[http://dx.doi.org/10.1016/j.talanta.2019.120253] [PMID: 31514899]
[69]
Slavchev, A.; Kovacs, Z.; Koshiba, H.; Nagai, A.; Bázár, G.; Krastanov, A.; Kubota, Y.; Tsenkova, R. Monitoring of water spectral pattern reveals differences in probiotics growth when used for rapid bacteria selection. PLoS One, 2015, 10(7), e0130698.
[http://dx.doi.org/10.1371/journal.pone.0130698] [PMID: 26133176]
[70]
Li, H.; Liang, Y.; Xu, Q.; Cao, D. Key wavelengths screening using competitive adaptive reweighted sampling method for multivariate calibration. Anal. Chim. Acta, 2009, 648(1), 77-84.
[http://dx.doi.org/10.1016/j.aca.2009.06.046] [PMID: 19616692]
[71]
Szliszka, E.; Czuba, Z.; Domino, M.; Mazur, B.; Zydowicz, G.; Krol, W. Ethanolic extract of propolis (EEP) enhances the apoptosis- inducing potential of TRAIL in cancer cells. Molecules, 2009, 14(2), 738-754.
[http://dx.doi.org/10.3390/molecules14020738] [PMID: 19223822]
[72]
Bozhynov, V.; Kovacs, Z.; Cisar, P.; Urban, J. Application of visible aquaphotomics for the evaluation of dissolved chemical concentrations in aqueous solutions. Photonics, 2021, 8(9), 391.
[http://dx.doi.org/10.3390/photonics8090391]
[73]
Wang, S.; Wang, M.; Han, L.; Sun, Y.; Cai, W.; Shao, X. Insight into the stability of protein in confined environment through analyzing the structure of water by temperature-dependent near-infrared spectroscopy. Spectrochim. Acta A Mol. Biomol. Spectrosc., 2022, 267(Pt 2), 120581.
[http://dx.doi.org/10.1016/j.saa.2021.120581] [PMID: 34776375]
[74]
Seasholtz, M.B.; Kowalski, B.R. Qualitative information from multivariate calibration models. Appl. Spectrosc., 1990, 44(8), 1337-1348.
[http://dx.doi.org/10.1366/000370290789619478]
[75]
Fan, M.L.; Zhao, Y.; Liu, Y.; Cai, W.S.; Shao, X.G. Aquaphotomics of Near Infrared Spectroscopy. Huaxue Jinzhan, 2015, 27(2-3), 242-250.
[http://dx.doi.org/10.7536/pc140803]
[76]
Zhang, M.; Liu, L.; Yang, C.; Sun, Z.; Xu, X.; Li, L.; Zang, H. Research on the structure of peanut allergen protein Ara h1 Based on Aquaphotomics. Front. Nutr., 2021, 8, 696355.
[http://dx.doi.org/10.3389/fnut.2021.696355] [PMID: 34222311]
[77]
Muncan, J.; Kovacs, Z.; Pollner, B.; Ikuta, K.; Ohtani, Y.; Terada, F.; Tsenkova, R. Near infrared aquaphotomics study on common dietary fatty acids in cow’s liquid, thawed milk. Food Control, 2021, 122, 107805.
[http://dx.doi.org/10.1016/j.foodcont.2020.107805]
[78]
Kaur, H.; Künnemeyer, R.; McGlone, A. Investigating aquaphotomics for temperature-independent prediction of soluble solids content of pure apple juice. J. Near Infrared Spectrosc., 2020, 28(2), 103-112.
[http://dx.doi.org/10.1177/0967033519898891]
[79]
Tjandra Nugraha, D.; Zinia Zaukuu, J.L.; Aguinaga Bósquez, J.P.; Bodor, Z.; Vitalis, F.; Kovacs, Z. Near-Infrared Spectroscopy and Aquaphotomics for Monitoring Mung Bean (Vigna radiata) Sprout Growth and Validation of Ascorbic Acid Content. Sensors, 2021, 21(2), 611.
[http://dx.doi.org/10.3390/s21020611] [PMID: 33477304]
[80]
Yang, X.; Guang, P.; Xu, G.; Zhu, S.; Chen, Z.; Huang, F. Manuka honey adulteration detection based on near-infrared spectroscopy combined with aquaphotomics. Lebensm. Wiss. Technol., 2020, 132, 109837.
[http://dx.doi.org/10.1016/j.lwt.2020.109837]
[81]
Chatani, E.; Tsuchisaka, Y.; Masuda, Y.; Tsenkova, R. Water molecular system dynamics associated with amyloidogenic nucleation as revealed by real time near infrared spectroscopy and aquaphotomics. PLoS One, 2014, 9(7), e101997.
[http://dx.doi.org/10.1371/journal.pone.0101997] [PMID: 25013915]
[82]
Šakota Rosić, J.; Munćan, J.; Mileusnić, I.; Kosić, B.; Matija, L. Detection of protein deposits using NIR spectroscopy. Soft Mater., 2016, 14(4), 264-271.
[http://dx.doi.org/10.1080/1539445X.2016.1198377]
[83]
Muncan, J.; Matija, L.; Simic-Krstic, J.; Nijemcevic, S.; Koruga, D. Discrimination of mineral waters using near infrared spectroscopy and aquaphotomics. Hem. Ind., 2014, 68(2), 257-264.
[http://dx.doi.org/10.2298/HEMIND130412049M]
[84]
Cattaneo, T.M.P.; Cutini, M.; Cammerata, A.; Stellari, A.; Marinoni, L.; Bisaglia, C.; Brambilla, M. Near infrared spectroscopic and aquaphotomic evaluation of the efficiency of solar dehydration processes in pineapple slices. J. Near Infrared Spectrosc., 2021, 29(6), 352-358.
[http://dx.doi.org/10.1177/09670335211054303]

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