A preliminary evaluation of attenuated total reflection Fourier transform infrared spectroscopy for the hematological analysis of thalassemias

Serum-based ATR-FTIR spectroscopy combined with multivariate analysis for the diagnosis of pre-diabetes and diabetes

Diabetes mellitus (DM) is a metabolic disease with an increasing prevalence that is causing worldwide concern. The pre-diabetes stage is the only reversible stage in the patho-physiological process towards DM. Due to the limitations of traditional methods, the diagnosis and detection of DM and pre-diabetes are complicated, expensive, and time-consuming. Therefore, it would be of great benefit to develop a simple, rapid and inexpensive diagnostic test. Herein, the infrared (IR) spectra of serum samples from 111 DM patients, 111 pre-diabetes patients and 333 healthy volunteers were collected using attenuated total reflection Fourier-transform IR (ATR-FTIR) spectroscopy and this was combined with the multivariate analysis of principal component analysis linear discriminant analysis (PCA-LDA) to develop a discriminant model to verify the diagnostic potential of this approach. The study found that the accuracy of the test model established by ATR-FTIR spectroscopy combined with PCA-LDA was 97%, and the sensitivity and specificity were 100% and 100% in the control group, 94% and 98% in the pre-diabetes group, and 91% and 98% in the DM group, respectively. This indicates that this method can effectively diagnose DM and pre-diabetes, which has far-reaching clinical significance.

Infrared Spectroscopy: A New Frontier in Hematological Disease Diagnosis

Hematological diseases, due to their complex nature and diverse manifestations, pose significant diagnostic challenges in healthcare. The pressing need for early and accurate diagnosis has driven the exploration of novel diagnostic techniques. Infrared (IR) spectroscopy, renowned for its noninvasive, rapid, and cost-effective characteristics, has emerged as a promising adjunct in hematological diagnostics. This review delves into the transformative role of IR spectroscopy and highlights its applications in detecting and diagnosing various blood-related ailments. We discuss groundbreaking research findings and real-world applications while providing a balanced view of the potential and limitations of the technique. By integrating advanced technology with clinical needs, we offer insights into how IR spectroscopy may herald a new era of hematological disease diagnosis.

Applications of mid-infrared spectroscopy in the clinical laboratory setting

Fourier transform mid-infrared (MIR-FTIR) spectroscopy is a nondestructive, label-free, highly sensitive and specific technique that provides complete information on the chemical composition of biological samples. The technique both can offer fundamental structural information and serve as a quantitative analysis tool. Therefore, it has many potential applications in different fields of clinical laboratory science. Although considerable technological progress has been made to promote biomedical applications of this powerful analytical technique, most clinical laboratory analyses are based on spectroscopic measurements in the visible or ultraviolet (UV) spectrum and the potential role of FTIR spectroscopy still remains unexplored. In this review, we present some general principles of FTIR spectroscopy as a useful method to study molecules in specimens by MIR radiation together with a short overview of methods to interpret spectral data. We aim at illustrating the wide range of potential applications of the proposed technique in the clinical laboratory setting with a focus on its advantages and limitations and discussing the future directions. The reviewed applications of MIR spectroscopy include (1) quantification of clinical parameters in body fluids, (2) diagnosis and monitoring of cancer and other diseases by analysis of body fluids, cells, and tissues, (3) classification of clinically relevant microorganisms, and (4) analysis of kidney stones, nails, and faecal fat.

Waveband selection of reagent-free determination for thalassemia screening indicators using Fourier transform infrared spectroscopy with attenuated total reflection

A reagent-free determination method for the thalassemia screening indicators hemoglobin (Hb), mean corpuscular Hb (MCH), and mean corpuscular volume (MCV) was developed based on Fourier transform infrared spectrometers equipped with an attenuated total reflection accessory. A random and stability-dependent rigorous process of calibration, prediction, and validation was conducted. Appropriate wavebands were selected using the improved moving window partial least squares method with stability and equivalence. The obtained optimal wavebands were 1722 to 1504 cm⁻¹ for Hb, 1653 to 901 cm⁻¹ for MCH, and 1562 to 964 cm⁻¹ for MCV. A model set equivalent to the optimal model was proposed for each indicator; the public waveband of Hb equivalent wavebands was 1717 to 1510 cm⁻¹, and the public equivalent waveband for MCH and MCV was 1562 to 901 cm⁻¹. All selected wavebands were within the MIR fingerprint region and achieved high validation effects. The sensitivity and specificity were 100.0% and 96.9% for the optimal wavebands and 100.0% and 95.3% for the equivalent wavebands, respectively. Thus, the spectral prediction was highly accurate for determining negative and positive for thalassemia screening. This technique is rapid and simple in comparison with conventional methods and is a promising tool for thalassemia screening in large populations.

Rapid Analysis of Zinc in Soil with Long-NIR Spectroscopy

Near-infrared (NIR) spectroscopy combined with the partial least squares (PLS) regression was successfully applied for the rapid quantitative analysis of Zn2+ in soil. The models were established using an approach based on randomness and similarity to obtain objective and practical models. Sixty-three samples were randomly selected from a total of 148 samples as the validation set. The remaining 85 samples were used as the modeling set, and it was divided into similar calibration (50 samples) and prediction (35 samples) sets. The results show that the long-NIR region at 1100 nm to 2498 nm could be considered as the information waveband of Zn2+ in soil. The optimal number of PLS factors was 10, and the validation root mean square error (V-SEP) and validation correlation coefficients of prediction (V-RP) were 21.817 mg kg-1 and 0.849, respectively. The Zn2+ prediction values of the validation samples are close to the measured values. The results provided valuable reference for designing the dedicated spectrometers.