This PDF file contains the front matter associated with SPIE Proceedings Volume 8939, including the Title Page, Copyright information, Table of Contents, Invited Panel Discussion, and Conference Committee listing.

Raman spectroscopy is a promising tool for detection of virus infection in live cells. In the present study, we demonstrate its feasibility to observe dynamic reaction of the live cell infected by virus. The Raman spectra of the adenovirus infected live cell (293 HEK) are analyzed by comparing with those of control cells. Principal component analysis (PCA) is employed also to analyze the spectra in detail. A band at 1650 cm-1 increases its intensity in the spectra measured at 24 hours after the virus infection. The infection of the virus is also examined by immune-staining and transmission electron microscope (TEM), and the virus infection is confirmed with these method also. It should be noted that the present technique does not require specifying the type of virus in advance.

In this paper we present a longitudinal study of bacteria metabolism performed with a novel Raman spectrometer system. Longitudinal study is possible with our Raman setup since the overall procedure to localize a single bacterium and collect a Raman spectrum lasts only 1 minute. Localization and detection of single bacteria are performed by means of lensfree imaging, whereas Raman signal (from 600 to 3200 cm^-1) is collected into a prototype spectrometer that allows high light throughput (HTVS technology, Tornado Spectral System). Accomplishing time-lapse Raman spectrometry during growth of bacteria, we observed variation in the net intensities for some band groups, e.g. amides and proteins. The obtained results on two different bacteria species, i.e. Escherichia coli and Bacillus subtilis clearly indicate that growth affects the Raman chemical signature. We performed a first analysis to check spectral differences and similarities. It allows distinguishing between lag, exponential and stationary growth phases. And the assignment of interest bands to vibration modes of covalent bonds enables the monitoring of metabolic changes in bacteria caused by growth and aging. Following the spectra analysis, a SVM (support vector machine) classification of the different growth phases is presented. In sum this longitudinal study by means of a compact and low-cost Raman setup is a proof of principle for routine analysis of bacteria, in a real-time and non-destructive way. Real-time Raman studies on metabolism and viability of bacteria pave the way for future antibiotic susceptibility testing.

Cell identification by Raman spectroscopy has evolved to be an attractive complement to established optical techniques. Raman activated cell sorting (RACS) offers prospects to complement the widely applied fluorescence activated cell sorting. RACS can be realized by combination with optical traps and microfluidic devices. The progress of RACS is reported for a cellular model system that can be found in peripheral blood of tumor patients. Lymphocytes and erythrocytes were extracted from blood samples. Breast carcinoma derived tumor cells (MCF-7, BT-20) and acute myeloid leukemia cells (OCI-AML3) were grown in cell cultures. First, Raman images were collected from dried cells on calcium fluoride slides. Support vector machines (SVM) classified 99.7% of the spectra to the correct cell type. Second, a 785 nm laser was used for optical trapping of single cells in aqueous buffer and for excitation of the Raman spectrum. SVM distinguished 1210 spectra of tumor and normal cells with a sensitivity of >99.7% and a specificity of >99.5%. Third, a microfluidic glass chip was designed to inject single cells, modify the flow speed, accommodate fibers of an optical trap and sort single cells after Raman based identification with 514 nm for excitation. Forth, the microfluidic chip was fabricated by quartz which improved cell identification results with 785 nm excitation. Here, partial least squares discriminant analysis gave classification rates of 98%. Finally, a Raman-on-chip approach was developed that integrates fibers for trapping, Raman excitation and signal detection in a single compact unit.

Leucocytes in the blood of mammals form a powerful protective system against a wide range of dangerous pathogens. There are several types of immune cells that has specific role in the whole immune system. The number and type of immune cells alter in the disease state and identifying the type of immune cell provides information about a person’s state of health. There are several immune cell subsets that are essentially morphologically identical and require external labeling to enable discrimination. Here we demonstrate the feasibility of using Wavelength Modulated Raman Spectroscopy (WMRS) with suitable machine learning algorithms as a label-free method to distinguish between different closely lying immune cell subset. Principal Component Analysis (PCA) was performed on WMRS data from single cells, obtained using confocal Raman microscopy for feature reduction, followed by Support Vector Machine (SVM) for binary discrimination of various cell subset, which yielded an accuracy >85%. The method was successful in discriminating between untouched and unfixed purified populations of CD4+CD3+ and CD8+CD3+ T lymphocyte subsets, and CD56+CD3- natural killer cells with a high degree of specificity. It was also proved sensitive enough to identify unique Raman signatures that allow clear discrimination between dendritic cell subsets, comprising CD303+CD45+ plasmacytoid and CD1c+CD141+ myeloid dendritic cells. The results of this study clearly show that WMRS is highly sensitive and can distinguish between cell types that are morphologically identical.

Raman spectroscopy is a powerful technique that can be used to obtain detailed chemical information about a system without the need for chemical markers. It has been widely used for a variety of applications such as cancer diagnosis and material characterization. However, Raman scattering is a highly inefficient process, where only one in 10¹¹ scattered photons carry the needed information. Several methods have been developed to enhance this inherently weak effect, including surface enhanced Raman scattering and coherent anti-Stokes Raman scattering. These techniques suffer from drawbacks limiting their commercial use, such as the need for spatial localization of target molecules to a ‘hot spot’, or the need for complex laser systems. Here, we present a simple instrument to enhance spontaneous Raman scattering using elastic light scattering. Elastic scattering is used to substantially increase the interaction volume. Provided that the scattering medium exhibits very low absorption in the spectral range of interest, a large enhancement factor can be attained in a simple and inexpensive setting. In our experiments, we demonstrate an enhancement of 10⁷ in Raman signal intensity. The proposed novel device is equally applicable for analyzing solids, liquids, and gases.

There is a growing need for new biodiagnostics that combine high throughput with enhanced spatial resolution and sensitivity. Gold nanoparticle (NP) assemblies with sub-10 nm particle spacing have the benefits of improving detection sensitivity via Surface enhanced Raman scattering (SERS) and being of potential use in biomedicine due to their colloidal stability. A promising and versatile approach to form solution-stable NP assemblies involves the use of multi-branched molecular linkers which allows tailoring of the assembly size, hot-spot density and interparticle distance. We have shown that linkers with multiple anchoring end-groups can be successfully employed as a linker to assemble gold NPs into dimers, linear NP chains and clustered NP assemblies. These NP assemblies with diameters of 30-120 nm are stable in solution and perform better as SERS substrates compared with single gold NPs, due to an increased hot-spot density. Thus, tailored gold NP assemblies are potential candidates for use as biomedical imaging agents. We observed that the hot-spot density and in-turn the SERS enhancement is a function of the linker polymer concentration and polymer architecture. New deep Raman techniques like Spatially Offset Raman Spectroscopy (SORS) have emerged that allow detection from beneath diffusely scattering opaque materials, including biological media such as animal tissue. We have been able to demonstrate that the gold NP assemblies could be detected from within both proteinaceous and high lipid containing animal tissue by employing a SORS technique with a backscattered geometry.

In this paper we present results on single bacteria rapid identification obtained with a low-cost and compact Raman spectrometer. At present, we demonstrate that a 1 minute procedure, including the localization of single bacterium, is sufficient to acquire comprehensive Raman spectrum in the range of 600 to 3300 cm^-1. Localization and detection of single bacteria is performed by means of lensfree imaging over a large field of view of 24 mm². An excitation source of 532 nm and 30 mW illuminates single bacteria to collect Raman signal into a Tornado Spectral Systems prototype spectrometer (HTVS technology). The acquisition time to record a single bacterium spectrum is as low as 10 s owing to the high light throughput of this spectrometer. The spectra processing features different steps for cosmic spikes removal, background subtraction, and gain normalization to correct the residual inducted fluorescence and substrate fluctuations. This allows obtaining a fine chemical fingerprint analysis. We have recorded a total of 1200 spectra over 7 bacterial species (E. coli, Bacillus species, S. epidermis, M. luteus, S. marcescens). The analysis of this database results in a high classification score of almost 90 %. Hence we can conclude that our setup enables automatic recognition of bacteria species among 7 different species. The speed and the sensitivity (<30 minutes for localization and spectra collection of 30 single bacteria) of our Raman spectrometer pave the way for high-throughput and non-destructive real-time bacteria identification assays. This compact and low-cost technology can benefit biomedical, clinical diagnostic and environmental applications.

Oral cancers are the sixth most common malignancy worldwide, with low 5-year disease free survival rates, attributable to late detection due to lack of reliable screening modalities. Our in vivo Raman spectroscopy studies have demonstrated classification of normal and tumor as well as cancer field effects (CFE), the earliest events in oral cancers. In view of limitations such as requirement of on-site instrumentation and stringent experimental conditions of this approach, feasibility of classification of normal and cancer using serum was explored using 532 nm excitation. In this study, strong resonance features of β-carotenes, present differentially in normal and pathological conditions, were observed. In the present study, Raman spectra of sera of 36 buccal mucosa, 33 tongue cancers and 17 healthy subjects were recorded using Raman microprobe coupled with 40X objective using 785 nm excitation, a known source of excitation for biomedical applications. To eliminate heterogeneity, average of 3 spectra recorded from each sample was subjected to PC-LDA followed by leave-one-out-cross-validation. Findings indicate average classification efficiency of ~70% for normal and cancer. Buccal mucosa and tongue cancer serum could also be classified with an efficiency of ~68%. Of the two cancers, buccal mucosa cancer and normal could be classified with a higher efficiency. Findings of the study are quite comparable to that of our earlier study, which suggest that there exist significant differences, other than β- carotenes, between normal and cancerous samples which can be exploited for the classification. Prospectively, extensive validation studies will be undertaken to confirm the findings.

Acute myeloid leukemia (AML) is a proliferative neoplasm, that if not properly treated can rapidly cause a fatal outcome. The diagnosis of AML is challenging and the first diagnostic step is the count of the percentage of blasts (immature cells) in bone marrow and blood sample, and their morphological characterization. This evaluation is still performed manually with a bright field light microscope. Here we report results of a study applying Raman spectroscopy for analysis of samples from two patients affected by two AML subtypes characterized by a different maturation stage in the neutrophilic lineage. Ten representative cells per sample were selected and analyzed with high-resolution confocal Raman microscopy by scanning 64x64 (4096) points in a confocal layer through the volume of the whole cell. The average spectrum of each cell was then used to obtain a highly reproducible mean fingerprint of the two different AML subtypes. We demonstrate that Raman spectroscopy efficiently distinguishes these different AML subtypes. The molecular interpretation of the substantial differences between the subtypes is related to granulocytic enzymes (e.g. myeloperoxidase and cytochrome b₅₅₈), in agreement with different stages of maturation of the two considered AML subtypes . These results are promising for the development of a new, objective, automated and label-free Raman based methods for the diagnosis and first assessment of AML.

Increasing interest in the role of lipids in cancer cell proliferation or resistance to drug therapies has motivated the need to develop better tools for cellular lipid analysis. Quantification of lipids in cells is typically done by destructive chromatography protocols that do not provide spatial information on lipid distribution and prevent dynamic live cell studies. Methods that allow the analysis of lipid content in live cells is therefore of great importance for research. Using Raman micro-spectroscopy we investigated whether the female hormone medroxyprogesterone acetate (MPA) and the synthetic androgen R1881 affect the lipid expression in breast (T47D) and prostate (LNCaP) cancer cells. Differences were noted in the spectral regions at 830-1800 cm^-1 and 2800-3000 cm^-1 when comparing different drug treatments. Significant changes were noticed for saturated (1063 - 1125 cm^-1, 1295 cm^-1 and 1439 cm^-1), unsaturated (1262 cm^-1 and 1656 cm^-1, and 1720 - 1748 cm^-1) chemical bonds, suggesting that the composition of the lipid droplets was changed by the hormone treatments. Also, significant differences were observed in the high frequency regions of lipids and proteins at 2851 cm^-1 and around 2890 cm^-1. Principal component analysis with Linear Discriminant Analysis (PCA-LDA) of the Raman spectra was able to differentiate between cancer cells that were treated with MPA, R1881 or vehicle (P < 0.05). Future work includes analysis to determine exact lipid composition and concentrations as well as development of clinical techniques to characterize differences in patient tumor lipid profiles to determine response to drug treatment and prognosis.

Hepatocellular carcinoma (HCC) is the most common form of primary hepatic carcinoma. HCC ranks the fourth most prevalent malignant tumor and the third leading cause of cancer related death in the world. Hepatocellular carcinoma develops in the context of chronic liver disease and its evolution is characterized by progression through intermediate stages to advanced disease and possibly even death. The primary sequence of hepatocarcinogenesis includes the development of cirrhosis, followed by dysplasia, and hepatocellular carcinoma.1 We addressed the utility of Fourier Transform Infrared (FT-IR) spectroscopic imaging, both as a diagnostic tool of the different stages of the disease and to gain insight into the biochemical process associated with disease progression. Tissue microarrays were obtained from the University of Illinois at Chicago tissue bank consisting of liver explants from 12 transplant patients. Tissue core biopsies were obtained from each explant targeting regions of normal, liver cell dysplasia including large cell change and small cell change, and hepatocellular carcinoma. We obtained FT-IR images of these tissues using a modified FT-IR system with high definition capabilities. Firstly, a supervised spectral classifier was built to discriminate between normal and cancerous hepatocytes. Secondly, an expanded classifier was built to discriminate small cell and large cell changes in liver disease. With the emerging advances in FT-IR instrumentation and computation there is a strong drive to develop this technology as a powerful adjunct to current histopathology approaches to improve disease diagnosis and prognosis.

Optical spectroscopy and imaging methods have proved to have potential to discriminate between normal and abnormal tissue types through minimally invasive procedures. Raman spectroscopy and Optical Coherence Tomography (OCT) provides chemical and morphological information of tissues respectively, which are complementary to each other. When used individually they might not be able to obtain high enough sensitivity and specificity that is clinically relevant. In this study we combined Raman spectroscopy information with information obtained from OCT to enhance the sensitivity and specificity in discriminating between Colonic Adenocarcinoma from Normal Colon. OCT being an imaging technique, the information from this technique is conventionally analyzed qualitatively. To combine with Raman spectroscopy information, it was essential to quantify the morphological information obtained from OCT. Texture analysis was used to extract information from OCT images, which in-turn was combined with the information obtained from Raman spectroscopy. The sensitivity and specificity of the classifier was estimated using leave one out cross validation (LOOCV) method where support vector machine (SVM) was used for binary classification of the tissues. The sensitivity obtained using Raman spectroscopy and OCT individually was 89% and 78% respectively and the specificity was 77% and 74% respectively. Combining the information derived using the two techniques increased both sensitivity and specificity to 94% demonstrating that combining complementary optical information enhances diagnostic accuracy. These results demonstrate that a multimodal approach using Raman-OCT would be able to enhance the diagnostic accuracy for identifying normal and cancerous tissue types.

Raman spectroscopy represents a unique optical vibrational technique based on the fundamental premise of inelastic light scattering. Raman spectroscopy enables histopathological assessment at the biomolecular level. We have developed a fiber-optic depth-resolved near-infrared (NIR) Raman endoscopy technique integrated with on-line diagnostic algorithms for in vivo real-time epithelial diagnostics under multimodal wide-field imaging (i.e., white light reflectance (WLR), narrow-band imaging (NBI), autofluorescence imaging (AFI)) modalities. A selection of 450 patients who previously underwent Raman endoscopy (n=1900 spectra) was used to render diagnostic models for identifying gastric precancer (i.e., dysplasia) based on probabilistic partial least squares (PLS) - discriminant analysis (DA). The on-line Raman endoscopy technique was tested prospectively on (n=5) patients for real-time in vivo gastric epithelium tissue diagnosis. The fiber-optic confocal Raman endoscopic technique developed could prospectively identify gastric dysplasia in real-time with a sensitivity: 81.3% (61/75) and specificity 88.3% (188/213) on spectrum basis. On lesion basis, all dysplastic lesions were identified. This study successfully demonstrates for the first time the prospective real-time in vivo diagnosis of gastric precancer using depth-resolved Raman endoscopy.

Sexual reproductive body can be produced from a fertilized ovum. Once the ovum is fertilized with sperm, it runs through the cell division, differentiates to all kinds of cells, and goes to make a complete body. However, not all of them are viable and some of them stop to ontogenesis showing the developmental abnormality. In order to discriminate the egg quality, we apply Raman spectroscopy for fish egg. After the measurement, these Raman data are checked up with the information about the eggs can survive or not, and we examine what factors are important in egg components to distinguish between “good quality” and “not good quality”. We present the results of assessment of egg quality, and investigate whether Raman spectroscopy can be used to a discriminate of egg quality.

Here we report on combination of the data obtained from MICs (minimum inhibitory concentrations) with infor- mation of microoragnisms fingerprint provided by Raman spectroscopy. In our feasibility study we could follow mechanisms of the bacteriostatic versus bactericidal action on biofilm-positive Staphylococcus epidermidis simply by monitoring Raman bands corresponding to DNA translating the changes introduced by selected antibiotics. The Raman spectra of Staphylococcus epidermidis treated with a bacteriostatic agent show little effect on DNA which is in contrast with the action of a bactericidal agent where decreased in dedicated Raman spectra signal strength suggests DNA fragmentation. Moreover, we demonstrate that Raman tweezers are indeed able to distinguish strains of biofilm-forming (biofilm-positive) and biofilm-negative Staphylococcus epidermidis strains using principal component analysis (PCA).

Inflammatory bowel disease (IBD), including ulcerative colitis (UC) and Crohn’s colitis (CC), affects nearly 2 million Americans, and the incidence is increasing worldwide. It has been established that UC and CC are distinct forms of IBD and require different medical care, however the distinction made between UC and CC is based upon inexact clinical, radiological, endoscopic, and pathologic features. A diagnosis of indeterminate colitis occurs in up to 15% of patients when UC and CC features overlap and cannot be differentiated; in these patients, diagnosis relies on long term followup, success or failure of existing treatment, and recurrence of the disease. Thus, there is need for a tool that can improve the sensitivity and specificity for fast, accurate and automated diagnosis of IBD. Here we present colonoscopy-coupled fiber probe-based Raman spectroscopy as a novel in vivo diagnostic tool for IBD. This in vivo study of both healthy control (NC, N=10) and diagnosed IBD patients with UC (N=15) and CC (N=26) aims to characterize spectral signatures of NC, UC, and CC. Samples are correlated with tissue pathology markers and endoscopic evaluation. Optimal collection parameters for detection have been identified based upon the new, application specific instrument design. The collected spectra are processed and analyzed using multivariate statistical techniques to identify spectral markers and discriminate NC, UC, and CC. Development of spectral markers to discriminate disease type is a necessary first step in the development of real-time, accurate and automated in vivo detection of IBD during colonoscopy procedures.

Fourier Transform Infrared (FT-IR) spectroscopic imaging can allow for the rapid imaging of tissue biochemistry in a label-free and non-perturbing fashion. With the rapid adoption of new minimally invasive surgery (MIS) technologies over the last 20 years, adequate skill to safely and effectively use these technologies may not be achieved and risk of undue physical pressure being placed on tissues is a concern. Previous work has demonstrated that a number of histological stains can detect tissue damage, however, this process requires the initiation and progression of a signaling cascade that results in the epitope of interest being expressed. We proposed to identify the early biochemical markers associated with physical tissue damage from applied forces, thus not requiring transcriptional and translational protein synthesis as traditional immunohistochemistry does. To demonstrate that FT-IR can measure biochemical changes in tissues that have undergone physical force, we took ex-vivo lamb’s liver that had been freshly excised and applied varying levels of physical pressure (0kPa to 30kPa). Tissues were then formalin-fixed, paraffin-embedded, and sectioned on to glass for H and E staining to identify damage and on to an IR slide for FT-IR imaging. Regions of interest containing hepatocytes were identified and average FT-IR spectra were extracted from the damaged and undamaged livers. FT-IR spectra showed clear biochemical changes associated with tissue damage. In addition, chemical changes could be observed proceeding histological changes observed when using conventional staining approaches.

Two different optical fiber probes for combined Raman and fluorescence spectroscopic measurements were designed, developed and used for tissue diagnostics. Two visible laser diodes were used for fluorescence spectroscopy, whereas a laser diode emitting in the NIR was used for Raman spectroscopy. The two probes were based on fiber bundles with a central multimode optical fiber, used for delivering light to the tissue, and 24 surrounding optical fibers for signal collection. Both fluorescence and Raman spectra were acquired using the same detection unit, based on a cooled CCD camera, connected to a spectrograph. The two probes were successfully employed for diagnosing melanocytic lesions in a good agreement with common routine histology. The obtained results demonstrated that the multimodal approach is crucial for improving diagnostic capabilities. Further investigations were performed on colon and brain tissue samples in order to have a benchmark for diagnosing a broader range of tissue lesions and malignancies. The system presented here can improve diagnostic capabilities on a broad range of tissues and has the potential of being used for endoscopic inspections in the near future.

Molecular profiling of tissue using near-infrared (NIR) Raman spectroscopy has shown great promise for in vivo detection and prognostication of cancer. The Raman spectra measured from the tissue generally contain fundamental information about the absolute biomolecular concentrations in tissue and its changes associated with disease transformation. However, producing analogues tissue Raman spectra present a great technical challenge. In this preliminary study, we propose a method to ensure the reproducible tissue Raman measurements and validated with the in vivo Raman spectra (n=150) of inner lip acquired using different laser powers (i.e., 30 and 60 mW). A rapid Raman spectroscopy system coupled with a ball-lens fiber-optic Raman probe was utilized for tissue Raman measurements. The investigational results showed that the variations between the spectra measured with different laser powers are almost negligible, facilitating the quantitative analysis of tissue Raman measurements in vivo.

Removal of intrinsic brain tumours is a delicate process, where a high degree of specificity is required to remove all of the tumour tissue without damaging healthy brain. The accuracy of this process can be greatly enhanced by intraoperative guidance. Optical biopsies using Raman spectroscopy are a minimally invasive and lower cost alternative to current guidance methods. A miniature Raman probe for performing optical biopsies of human brain tissue is presented. The probe allows sampling inside a conventional stereotactic brain biopsy system: a needle of length 200mm and inner diameter of 1.8mm. The probe achieves a very low fluorescent background whilst maintaining good collection of Raman signal by employing a miniature stand-off Raman design. To illustrate this, the probe is compared with a Raman probe that uses a pair of optical fibres for collection. The miniature stand-off Raman probe is shown to collect a comparable number of Raman scattered photons, but the fluorescence caused by silica fibres in a Raman needle probe is reduced by a factor of two for Raman shifts under 500 cm^-1, and by 30% at 600-700 cm^-1. In addition, this design contains only medically approved materials at the distal end. The probe’s suitability for use on tissue is demonstrated by discriminating between different types of porcine brain tissue.

Shifted Excitation Raman Difference Spectroscopy (SERDS) has proven an effective method for performing Raman analysis of fluorescent samples. This technique allows achieving excellent signal to noise performance with shorter excitation wavelengths, thus taking full advantage of the superior signal strength afforded by shorter excitation wavelengths and the superior performance, also combined with lower cost, delivered by silicon CCDs. The technique is enabled by use of two closely space fixed-wavelength laser diode sources stabilized with the Volume Bragg gratings (VBGs). A side by side comparison reveals that SERDS technique delivers superior signal to noise ratio and better detection limits in most situations, even when a longer excitation wavelength is employed for the purpose of elimination of the fluorescence. We have applied the SERDS technique to the quantitative analysis of the presence of trace amounts of methanol in red wines, which is an important task in quality control operations within wine industry and is currently difficult to perform in the field. So far conventional Raman spectroscopy analysis of red wines has been impractical due to the high degree of fluorescence.

Despite the successes of mid-infrared hyperspectral imaging in a research environment, progress in the migration of technology into the day-to-day clinical application is slow. Clinical acceptance may be improved if the spectroscopy would be faster and the infrared microscopes available at lower cost. Here we present first results of a fast, multi-scale mid-infrared microscopy setup which allows for the investigation of 10.6×11.7 mm² and 2.8×3.1mm² fields of view with a resolution of 23.0±3.5 μm and 9.4±1.8 μm, respectively. Tunable quantum cascade lasers in the wavenumber ranges of 1030-1090 cm^-1 and 1160-1320 cm^-1 serve as light sources. A vapor cell is used as a frequency reference during the rapid scanning. As far as the imaging is concerned, it is the high spectral power density of the quantum cascade laser which enables the use of a microbolometer array while still obtaining reasonable signal-to-noise ratios on each pixel. Hyperspectral images are taken in times which can be as low as 52s for the overall image acquisition including referencing.

A new approach for quantitative analysis of melamine in milk was proposed based on two-dimensional (2D) correlation near-infrared spectroscopy and multi-way partial least squares (N-PLS) in this paper. 40 pure milk samples and 40 milk samples adulterated with different contents of melamine were prepared. The near-infrared transmittance spectra of all samples were measured at room temperature. Then 2D NIR-NIR correlation spectroscopy under the perturbation of adulterant concentration was calculated and N-PLS model for the melamine concentration was established with 2D correlation spectra (28x51x51). For the prediction set, the root mean square errors of prediction (RMSEP) for melamine concentration was 0.067 g/L and the coefficient correlation between actual reference values and predicted values was 0.999, which means the model has good predictive ability. For comparison purpose, partial least squares (PLS) model was also built using the conventional one-dimensional near-infrared spectra (28x51), where the RMSEP and the coefficient correlation were 0.079 g/L and 0.998, respectively. The average relative prediction error was 22.9% for N-PLS model; whereas it was 122.4% for PLS model. The N-PLS models yielded relatively low RMSEP and average relative prediction error as compared to PLS model. Therefore, N-PLS method was more robust than PLS method for accurate quantification of the concentration of melamine in milk.

In this work the infrared absorption spectra of intercellular fluid of normal and tumor kidney tissue were recorded and analyzed. The samples were prepared by stamping freshly resected tissue onto a CaF₂ substrate. FT-IR spectra obtained from intracellular fluid of tumor tissue exhibit stronger absorption bands in the spectral region from 1000-1200 cm^-1 and around 1750 cm^-1 than those obtained from normal tissue. It is likely the spectra of extracellular matrix of kidney tumor tissue with large increases in the intensities of these bands represent a higher concentration of fatty acids and glycerol. Amide I and amide II bands are stronger in spectra of normal tissue indicating a higher level of proteins. The results demonstrate that FT-IR spectroscopy of intercellular fluids is a novel approach for a quick diagnosis during surgical resection, which can improve the therapy of kidney tumors.

The combination of confocal micro-Raman spectroscopy and multivariate analysis is carried out for analysis of maturation of neurons. This study suggests that Raman data reflects the stages of neural maturation which relates with the expression of new neural function such as spontaneous activity. Neurons obtained from a hippocampus of rat embryos are cultured in a dish with quartz bottom. According to the previous electrophysiological study, matured neural cell network showed regulated pulsation with interval of several seconds without any stimulation. It suggested that alterations in the molecular composition took place in the cell. The Raman measurements are carried out to observe this alteration along with the maturing process of neurons. The spectra of live neural cells measured after 2, 8, 15, 30, 45, 60, 75, 90, 105 and 120 days of culturing are analyzed by principal component analysis (PCA). The result shows several groups suggesting the maturation scheme which is observed by the electrophysiological studies. It demonstrates that the maturation process of neural cells can be monitored by Raman spectroscopy.