Overview of Raman Spectroscopy: Fundamental to Applications
173
substrate for the screening of metabolic diseases such as diabetes in whole blood
by using Raman spectroscopy [266]. The excretion of urinary albumin remains the
key biomarker for the detection of renal complications in type 2 diabetes. As the
epidemic of diabetes grows, particularly in low-income countries, efficient and lowcost methods are needed to measure urinary albumin. Jose and his group performed a
pilot study in this regard and evaluated the ability of Raman spectroscopy in urinary
albumin assessment in patients with type 2 diabetes. This piece of the study revealed
that Raman spectroscopy is capable of detecting low amounts of urinary albumin,
indicating this method’s effectiveness for screening complications of type 2 diabetes
renal [267].
4.5.4 Virus Capture and Identification
In structural biology, Raman spectroscopy has been named as “sleeping giant”
because this technique offers a wealth of essential information for biomolecules,
diabetes, and cancer, etc. [268]. Infectious and inflammatory diseases also require
substantial attention because they encompass an enormous level of the worldwide
burden on the global health care system. In such a manner, Raman spectroscopy has
also been utilized for contemplating various infectious and inflammatory diseases
including dengue [238, 269, 270], tuberculosis [271–276], sepsis [277–279], ulcerative colitis [280, 281], inflammatory bowel disease [282–285] etc. Nascent and reemerging viruses are responsible for a variety of recent epidemic outbreaks. A crucial
step in the identification and prevention of outbreaks is the prompt and accurate characterization of emerging virus strains. Raman spectroscopy might be helpful in this
regard for the rapid diagnosis and characterization of emerging strains of viruses.
Among various virus infections, Dengue virus infection is caused by a mosquitoborne dengue virus (DENV) that belongs to the Flaviviridae family, claims several
lives particularly in developing countries. In India, dengue is endemic in almost all
states and its wrath can be understood by a Delhi example where this union territory
reported its worst outbreak in 2015 with more than 15,000 cases [286]. Likewise,
malaria influences more than 500 million individuals each year, and one child dies
every 30 s [287]. Patel et al. conducted the first serum-based Raman spectroscopic
analysis to stratify malaria and dengue, as the serum is found to be the first preference for dengue detection across different clinical samples [288, 289]. In the just
mentioned study, Raman spectra were recorded for 130 subjects to generate a predictive model [288]. Raman spectra for malaria vs healthy controls (HC) and dengue
vs HC recorded and represented in Fig. 9a, b, respectively, and major spectral peaks
(cell-free DNA (1340 and 1420 cm
−1 ), amide linkages (1280, 1302, and 1337 cm
−1 ),
β-carotene (1157 cm
−1 ), Tyr (830 and 850 cm
−1 ), CH 2 deformation (1337, 1398,
and 1445 cm
−1 ), Phe (1004 and 1204 cm
−1 ), Trp (1552 cm
−1 ), creatine (846 and
908 cm
−1 ), etc.) were identified as biomarkers for the identification of these diseases.
This research work provides a detailed comparative description of the Raman spectra
to distinguish between infectious disease (malaria and dengue) and the related clinical symptoms. Recently, the Terrones group presented a robust and high-throughput
173
substrate for the screening of metabolic diseases such as diabetes in whole blood
by using Raman spectroscopy [266]. The excretion of urinary albumin remains the
key biomarker for the detection of renal complications in type 2 diabetes. As the
epidemic of diabetes grows, particularly in low-income countries, efficient and lowcost methods are needed to measure urinary albumin. Jose and his group performed a
pilot study in this regard and evaluated the ability of Raman spectroscopy in urinary
albumin assessment in patients with type 2 diabetes. This piece of the study revealed
that Raman spectroscopy is capable of detecting low amounts of urinary albumin,
indicating this method’s effectiveness for screening complications of type 2 diabetes
renal [267].
4.5.4 Virus Capture and Identification
In structural biology, Raman spectroscopy has been named as “sleeping giant”
because this technique offers a wealth of essential information for biomolecules,
diabetes, and cancer, etc. [268]. Infectious and inflammatory diseases also require
substantial attention because they encompass an enormous level of the worldwide
burden on the global health care system. In such a manner, Raman spectroscopy has
also been utilized for contemplating various infectious and inflammatory diseases
including dengue [238, 269, 270], tuberculosis [271–276], sepsis [277–279], ulcerative colitis [280, 281], inflammatory bowel disease [282–285] etc. Nascent and reemerging viruses are responsible for a variety of recent epidemic outbreaks. A crucial
step in the identification and prevention of outbreaks is the prompt and accurate characterization of emerging virus strains. Raman spectroscopy might be helpful in this
regard for the rapid diagnosis and characterization of emerging strains of viruses.
Among various virus infections, Dengue virus infection is caused by a mosquitoborne dengue virus (DENV) that belongs to the Flaviviridae family, claims several
lives particularly in developing countries. In India, dengue is endemic in almost all
states and its wrath can be understood by a Delhi example where this union territory
reported its worst outbreak in 2015 with more than 15,000 cases [286]. Likewise,
malaria influences more than 500 million individuals each year, and one child dies
every 30 s [287]. Patel et al. conducted the first serum-based Raman spectroscopic
analysis to stratify malaria and dengue, as the serum is found to be the first preference for dengue detection across different clinical samples [288, 289]. In the just
mentioned study, Raman spectra were recorded for 130 subjects to generate a predictive model [288]. Raman spectra for malaria vs healthy controls (HC) and dengue
vs HC recorded and represented in Fig. 9a, b, respectively, and major spectral peaks
(cell-free DNA (1340 and 1420 cm
−1 ), amide linkages (1280, 1302, and 1337 cm
−1 ),
β-carotene (1157 cm
−1 ), Tyr (830 and 850 cm
−1 ), CH 2 deformation (1337, 1398,
and 1445 cm
−1 ), Phe (1004 and 1204 cm
−1 ), Trp (1552 cm
−1 ), creatine (846 and
908 cm
−1 ), etc.) were identified as biomarkers for the identification of these diseases.
This research work provides a detailed comparative description of the Raman spectra
to distinguish between infectious disease (malaria and dengue) and the related clinical symptoms. Recently, the Terrones group presented a robust and high-throughput