Infrared-spectroscopy: a non-invasive tool for medical diagnostics and drug analysis

Methods of Evaluating the Potential Success or Failure of Transition Dairy Cows

Early monitoring of the failure of metabolic adaptation to calving, represents the most effective measure for allowing a prompt intervention on transition dairy cows. This prevents deleterious effects on animal performance, health, and welfare, which are driven by multiple disorders during the following lactation. Applying metabolic profiling could (1) provide a deeper view on the cause of any pathologic condition affecting transition cows, aimed at increasing the effectiveness and timely application of any treatment and (2) provide detailed feedback on the management practices adopted in a farm during this challenging phase based on animal responses.

Examination of cervical swabs of patients with endometriosis using Fourier transform infrared spectroscopy

PURPOSE

There is no established non-invasive method to diagnose patients with endometriosis. As a nondestructive type of radiation, infrared light might be used for discrimination by causing vibration of the covalent bonds of the molecules when absorbed by the tissues. The aim of the study was to test whether cervical swab can be used to diagnose women with endometriosis using Fourier transform infrared spectroscopy (FTIR).

METHODS

In this prospective case-control study, women between 18-45 years old and undergoing laparoscopy due to various reasons were recruited (n = 20). According to the findings during laparoscopy, patients were stratified as stage I-II or stage III-IV endometriosis groups. Women lacking any visible lesions of endometriosis were recruited as controls. A cervical swab was taken from all patients just before the surgical procedure and pulled into a tube containing saline solution. FTIR spectra were obtained and the fingerprint region (1750-850 cm^-1) was used for analyses.

RESULTS

Finally, three samples in stage I-II, five samples in stage III-IV and five samples in the control group were analyzed. Hierarchical cluster analysis and principal component analysis were performed as the chemometric method. A total of ten observable peaks were detected in the absorbance spectra of samples. The peaks at 1450 and 1405 cm^-1 originating from lipids and proteins significantly increased in the stage III-IV endometriosis group when compared with controls. In addition, nucleic acid/carbohydrate ratio was significantly lower in the stage I-II group indicating that the alteration of the carbohydrate level might be important.

CONCLUSIONS

Examination of cervical swab with FTIR spectroscopy might be a proper candidate for a non-invasive diagnostic approach of endometriosis.

Assessment of the main plasma parameters included in a metabolic profile of dairy cow based on Fourier Transform mid-infrared spectroscopy: preliminary results

BACKGROUND

Although a metabolic profile represents a valid tool utilized in dairy herds to determine abnormalities in blood chemistry related to an increased risk of production diseases, there are no studies on application of Fourier Transform mid-infrared (FT-MIR) spectroscopy. This study assesses the potential application of FT-MIR to analyze the main blood biochemical parameters included in the metabolic profile of dairy cows. Infrared transmission spectra were acquired for 35 plasma samples (two replicates on each sample) of Italian Friesian dairy cows (14 primiparous and 21 pluriparous), all without clinical events, and at different stages of lactation, although mainly in the transition phase. Each sample was also analyzed independently using accepted reference clinical chemical methods and these results were used as calibrating values to perform predictive models by PLS method using cross validation.

RESULTS

Measured blood parameters concentrations were all within the reference ranges reported for healthy dairy cows. The number of extracted factors with the PLS procedure for each prediction model ranged between 3 and 7. The coefficient of determination (R(2)) of the prediction models ranged between 0.1 to values close to 1. R(2) values greater than 0.9 were observed for the prediction models of total cholesterol, total protein, globulin, and albumin; values between 0.75 and 0.9 were observed for urea, NEFA, and total bilirubin, while values of R(2) lower than 0.6 were observed for all minerals and for enzyme activity. The range error ratio (RER) and prediction to deviation (RPD) ranged from 5.1 to 43.8 and from 1 to 13.8 for RER and RPD, respectively. Values of RPD greater than 5 were observed for total cholesterol, total protein, albumin, and globulin. RPD ranged between 2 and 5 for the prediction models of urea, NEFA, and total bilirubin, while RPD and RER were low for minerals and enzyme activities.

CONCLUSIONS

Although the results of this study require further validation, the use of FT-MIR spectroscopy was possible and provides fairly accurate measurement of various parameters of great importance in the evaluation of the metabolic and inflammatory status in dairy cows.

High definition infrared spectroscopic imaging for lymph node histopathology

Chemical imaging is a rapidly emerging field in which molecular information within samples can be used to predict biological function and recognize disease without the use of stains or manual identification. In Fourier transform infrared (FT-IR) spectroscopic imaging, molecular absorption contrast provides a large signal relative to noise. Due to the long mid-IR wavelengths and sub-optimal instrument design, however, pixel sizes have historically been much larger than cells. This limits both the accuracy of the technique in identifying small regions, as well as the ability to visualize single cells. Here we obtain data with micron-sized sampling using a tabletop FT-IR instrument, and demonstrate that the high-definition (HD) data lead to accurate identification of multiple cells in lymph nodes that was not previously possible. Highly accurate recognition of eight distinct classes - naïve and memory B cells, T cells, erythrocytes, connective tissue, fibrovascular network, smooth muscle, and light and dark zone activated B cells was achieved in healthy, reactive, and malignant lymph node biopsies using a random forest classifier. The results demonstrate that cells currently identifiable only through immunohistochemical stains and cumbersome manual recognition of optical microscopy images can now be distinguished to a similar level through a single IR spectroscopic image from a lymph node biopsy.

A highly sensitive electrochemical genosensor based on Co-porphyrin-labelled DNA

Cobalt-porphyrin-modified DNA was used to design an electrochemical genosensor which is able to detect a minimum of 1000 DNA molecules.