Monitoring the efficacy of antibiotic therapy in febrile pediatric oncology patients with bacteremia using infrared spectroscopy of white blood cells-based machine learning.

Bacteremia refers to the presence of bacteria in the bloodstream, which can lead to a serious and potentially life-threatening condition. In oncology patients, individuals undergoing cancer treatment have a higher risk of developing bacteremia due to a weakened immune system resulting from the disease itself or the treatments they receive. Prompt and accurate detection of bacterial infections and monitoring the effectiveness of antibiotic therapy are essential for enhancing patient outcomes and preventing the development and dissemination of multidrug-resistant bacteria. Traditional methods of infection monitoring, such as blood cultures and clinical observations, are time-consuming, labor-intensive, and often subject to limitations. This manuscript presents an innovative application of infrared spectroscopy of leucocytes of pediatric oncology patients with bacteremia combined with machine learning to diagnose the etiology of infection as bacterial and simultaneously monitor the efficacy of the antibiotic therapy in febrile pediatric oncology patients with bacteremia infections. Through the implementation of effective monitoring, it becomes possible to promptly identify any indications of treatment failure. This, in turn, indirectly serves to limit the progression of antibiotic resistance. The logistic regression (LR) classifier was able to differentiate the samples as bacterial or control within an hour, after receiving the blood samples with a success rate of over 95 %. Additionally, initial findings indicate that employing infrared spectroscopy of white blood cells (WBCs) along with machine learning is viable for monitoring the success of antibiotic therapy. Our follow up results demonstrate an accuracy of 87.5 % in assessing the effectiveness of the antibiotic treatment.

Correction: Diagnosis of inaccessible infections using infrared microscopy of white blood cells and machine learning algorithms.

Correction for 'Diagnosis of inaccessible infections using infrared microscopy of white blood cells and machine learning algorithms' by Adam H. Agbaria et al., Analyst, 2020, DOI: 10.1039/D0AN00752H.

Diagnosis of inaccessible infections using infrared microscopy of white blood cells and machine learning algorithms.

Physicians diagnose subjectively the etiology of inaccessible infections where sampling is not feasible (such as, pneumonia, sinusitis, cholecystitis, peritonitis), as bacterial or viral. The diagnosis is based on their experience with some medical markers like blood counts and medical symptoms since it is harder to obtain swabs and reliable laboratory results for most cases. In this study, infrared spectroscopy with machine learning algorithms was used for the rapid and objective diagnosis of the etiology of inaccessible infections and enables an assessment of the error for the subjective diagnosis of the etiology of these infections by physicians. Our approach allows for diagnoses of the etiology of both accessible and inaccessible infections as based on an analysis of the innate immune system response through infrared spectroscopy measurements of white blood cell (WBC) samples. In the present study, we examined 343 individuals involving 113 controls, 89 inaccessible bacterial infections, 54 accessible bacterial infections, 60 inaccessible viral infections, and 27 accessible viral infections. Using our approach, the results show that it is possible to differentiate between controls and infections (combined bacterial and viral) with 95% accuracy, and enabling the diagnosis of the etiology of accessible infections as bacterial or viral with >94% sensitivity and > 90% specificity within one hour after the collection of the blood sample with error rate <6%. Based on our approach, the error rate of the physicians' subjective diagnosis of the etiology of inaccessible infections was found to be >23%.

Potential of infrared microscopy to differentiate between dementia with Lewy bodies and Alzheimer's diseases using peripheral blood samples and machine learning algorithms.

SIGNIFICANCE: Accurate and objective identification of Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) is of major clinical importance due to the current lack of low-cost and noninvasive diagnostic tools to differentiate between the two. Developing an approach for such identification can have a great impact in the field of dementia diseases as it would offer physicians a routine objective test to support their diagnoses. The problem is especially acute because these two dementias have some common symptoms and characteristics, which can lead to misdiagnosis of DLB as AD and vice versa, mainly at their early stages. AIM: The aim is to evaluate the potential of mid-infrared (IR) spectroscopy in tandem with machine learning algorithms as a sensitive method to detect minor changes in the biochemical structures that accompany the development of AD and DLB based on a simple peripheral blood test, thus improving the diagnostic accuracy of differentiation between DLB and AD. APPROACH: IR microspectroscopy was used to examine white blood cells and plasma isolated from 56 individuals: 26 controls, 20 AD patients, and 10 DLB patients. The measured spectra were analyzed via machine learning. RESULTS: Our encouraging results show that it is possible to differentiate between dementia (AD and DLB) and controls with an ∼86 % success rate and between DLB and AD patients with a success rate of better than 93%. CONCLUSIONS: The success of this method makes it possible to suggest a new, simple, and powerful tool for the mental health professional, with the potential to improve the reliability and objectivity of diagnoses of both AD and DLB.

Differentiation of Pectobacterium and Dickeya spp. phytopathogens using infrared spectroscopy and machine learning analysis.

Pectobacterium and Dickeya spp. are soft rot Pectobacteriaceae that cause aggressive diseases on agricultural crops leading to substantial economic losses. The accurate, rapid and low-cost detection of these pathogenic bacteria are very important for controlling their spread, reducing the consequent financial loss and for producing uninfected potato seed tubers for future generations. Currently used methods for the identification of these bacterial pathogens at the strain level are based mainly on molecular techniques, which are expensive. We used an alternative method, infrared spectroscopy, to measure 24 strains of five species of Pectobacterium and Dickeya. Measurements were then analyzed using machine learning methods to differentiate among them at the genus, species and strain levels. Our results show that it is possible to differentiate among different bacterial pathogens with a success rate of ~99% at the genus and species levels and with a success rate of over 94% at the strain level.

Rapid diagnosis of infection etiology in febrile pediatric oncology patients using infrared spectroscopy of leukocytes.

Rapid diagnosis of the etiology of infection is highly important for an effective treatment of the infected patients. Bacterial and viral infections are serious diseases that can cause death in many cases. The human immune system deals with many viral and bacterial infections that cause no symptoms and pass quietly without treatment. However, oncology patients undergoing chemotherapy have a very weak immune system caused by leukopenia, and even minor pathogen infection threatens their lives. For this reason, physicians tend to prescribe immediately several types of antibiotics for febrile pediatric oncology patients (FPOPs). Uncontrolled use of antibiotics is one of the major contributors to the development of resistant bacteria. Therefore, for oncology patients, a rapid and objective diagnosis of the etiology of the infection is extremely critical. Current identification methods are time-consuming (>24 h). In this study, the potential of midinfrared spectroscopy in tandem with machine learning algorithms is evaluated for rapid and objective diagnosis of the etiology of infections in FPOPs using simple peripheral blood samples. Our results show that infrared spectroscopy enables the diagnosis of the etiology of infection as bacterial or viral within 70 minutes after the collection of the blood sample with 93% sensitivity and 88% specificity.

Differential Diagnosis of the Etiologies of Bacterial and Viral Infections Using Infrared Microscopy of Peripheral Human Blood Samples and Multivariate Analysis.

Human viral and bacterial infections are responsible for a variety of diseases that are still the main causes of death and economic burden for society across the globe. Despite the different responses of the immune system to these infections, some of them have similar symptoms, such as fever, sneezing, inflammation, vomiting, diarrhea, and fatigue. Thus, physicians usually encounter difficulties in distinguishing between viral and bacterial infections on the basis of these symptoms. Rapid identification of the etiology of infection is highly important for effective treatment and can save lives in some cases. The current methods used for the identification of the nature of the infection are mainly based on growing the infective agent in culture, which is a time-consuming (over 24 h) and usually expensive process. The main objective of this study was to evaluate the potential of the mid-infrared spectroscopic method for rapid and reliable identification of bacterial and viral infections based on simple peripheral blood samples. For this purpose, white blood cells (WBCs) and plasma were isolated from the peripheral blood samples of patients with confirmed viral or bacterial infections. The obtained spectra were analyzed by multivariate analysis: principle component analysis (PCA) followed by linear discriminant analysis (LDA), to identify the infectious agent type as bacterial or viral in a time span of about 1 h after the collection of the blood sample. Our preliminary results showed that it is possible to determine the infectious agent with high success rates of 82% for sensitivity and 80% for specificity, based on the WBC data.

Tracing overlapping biological signals in mid-infrared using colonic tissues as a model system.

AIM: To understand the interference of carbohydrates absorbance in nucleic acids signals during diagnosis of malignancy using Fourier transform infrared (FTIR) spectroscopy. METHODS: We used formalin fixed paraffin embedded colonic tissues to obtain infrared (IR) spectra in the mid IR region using a bruker II IR microscope with a facility for varying the measurement area by varying the aperture available. Following this procedure we could measure different regions of the crypt circles containing different biochemicals. Crypts from 18 patients were measured. Circular crypts with a maximum diameter of 120 µm and a lumen of about 30 µm were selected for uniformity. The spectral data was analyzed using conventional and advanced computational methods. RESULTS: Among the various components that are observed to contribute to the diagnostic capabilities of FTIR, the carbohydrates and nucleic acids are prominent. However there are intrinsic difficulties in the diagnostic capabilities due to the overlap of major absorbance bands of nucleic acids, carbohydrates and phospholipids in the mid-IR region. The result demonstrates colonic tissues as a biological system suitable for studying interference of carbohydrates and nucleic acids under ex vivo conditions. Among the diagnostic parameters that are affected by the absorbance from nucleic acids is the RNA/DNA ratio, dependent on absorbance at 1121 cm-1 and 1020 cm-1 that is used to classify the normal and cancerous tissues especially during FTIR based diagnosis of colonic malignancies. The signals of the nucleic acids and the ratio (RNA/DNA) are likely increased due to disappearance of interfering components like carbohydrates and phosphates along with an increase in amount of RNA. CONCLUSION: The present work, proposes one mechanism for the observed changes in the nucleic acid absorbance in mid-IR during disease progression (carcinogenesis).

A novel method for screening colorectal cancer by infrared spectroscopy of peripheral blood mononuclear cells and plasma.

BACKGROUND: Early detection of colorectal cancer (CRC) can reduce mortality and morbidity. Current screening methods include colonoscopy and stool tests, but a simple low-cost blood test would increase compliance. This preliminary study assessed the utility of analyzing the entire bio-molecular profile of peripheral blood mononuclear cells (PBMCs) and plasma using Fourier transform infrared (FTIR) spectroscopy for early detection of CRC. METHODS: Blood samples were prospectively collected from 62 candidates for CRC screening/diagnostic colonoscopy or surgery for colonic neoplasia. PBMCs and plasma were separated by Ficoll gradient, dried on zinc selenide slides, and placed under a FTIR microscope. FTIR spectra were analyzed for biomarkers and classified by principal component and discriminant analyses. Findings were compared among diagnostic groups. RESULTS: Significant changes in multiple bands that can serve as CRC biomarkers were observed in PBMCs (p = ~0.01) and plasma (p = ~0.0001) spectra. There were minor but statistically significant differences in both blood components between healthy individuals and patients with benign polyps. Following multivariate analysis, the healthy individuals could be well distinguished from patients with CRC, and the patients with benign polyps were mostly distributed as a distinct subgroup within the overlap region. Leave-one-out cross-validation for evaluating method performance yielded an area under the receiver operating characteristics curve of 0.77, with sensitivity 81.5% and specificity 71.4%. CONCLUSIONS: Joint analysis of the biochemical profile of two blood components rather than a single biomarker is a promising strategy for early detection of CRC. Additional studies are required to validate our preliminary clinical results.

Early detection of colorectal cancer relapse by infrared spectroscopy in "normal" anastomosis tissue.

Colorectal cancer is one of the most aggressive cancers usually occurring in people above the age of 50 years. In the United States, colorectal cancer is the third most diagnosed cancer. The American Cancer Society has estimated 96,830 new cases of colon cancer and 40,000 new cases of rectal cancer in 2014 in the United States. According to the literature, up to 55% of colorectal cancer patients experience a recurrence within five years from the time of surgery. Relapse of colorectal cancer has a deep influence on the quality of patient life. Infrared (IR) spectroscopy has been widely used in medicine. It is a noninvasive, nondestructive technique that can detect changes in cells and tissues that are caused by different disorders, such as cancer. Abnormalities in the colonic crypts, which are not detectable using standard histopathological methods, could be determined using IR spectroscopic methods. The IR measurements were performed on formalin-fixed, paraffin-embedded colorectal tissues from eight patients (one control, four local recurrences, three distant recurrences). A total of 128 crypts were measured. Our results showed the possibility of differentiating among control, local, and distant recurrence crypts with more than a 92% success rate using spectra measured from the crypts' middle sites.

Early detection of breast cancer using total biochemical analysis of peripheral blood components: a preliminary study.

BACKGROUND: Most of the blood tests aiming for breast cancer screening rely on quantification of a single or few biomarkers. The aim of this study was to evaluate the feasibility of detecting breast cancer by analyzing the total biochemical composition of plasma as well as peripheral blood mononuclear cells (PBMCs) using infrared spectroscopy. METHODS: Blood was collected from 29 patients with confirmed breast cancer and 30 controls with benign or no breast tumors, undergoing screening for breast cancer. PBMCs and plasma were isolated and dried on a zinc selenide slide and measured under a Fourier transform infrared (FTIR) microscope to obtain their infrared absorption spectra. Differences in the spectra of PBMCs and plasma between the groups were analyzed as well as the specific influence of the relevant pathological characteristics of the cancer patients. RESULTS: Several bands in the FTIR spectra of both blood components significantly distinguished patients with and without cancer. Employing feature extraction with quadratic discriminant analysis, a sensitivity of ~90 % and a specificity of ~80 % for breast cancer detection was achieved. These results were confirmed by Monte Carlo cross-validation. Further analysis of the cancer group revealed an influence of several clinical parameters, such as the involvement of lymph nodes, on the infrared spectra, with each blood component affected by different parameters. CONCLUSION: The present preliminary study suggests that FTIR spectroscopy of PBMCs and plasma is a potentially feasible and efficient tool for the early detection of breast neoplasms. An important application of our study is the distinction between benign lesions (considered as part of the non-cancer group) and malignant tumors thus reducing false positive results at screening. Furthermore, the correlation of specific spectral changes with clinical parameters of cancer patients indicates for possible contribution to diagnosis and prognosis.

Study of plasma-induced peripheral blood mononuclear cells survival using Fourier transform infrared microspectroscopy.

Components present in the acellular fraction of blood influence the blood cell survival and function and the response to biotic and abiotic factors. Human plasma and sera have been used as therapeutic agents and are known to increase cell survival. White blood cells in normal blood are exposed to plasma components in vivo, but the effect of such plasma components in vitro on adherent peripheral blood mononuclear cells (PBMCs) that includes monocytes has not been fully investigated. We cultured human PBMCs with autologous plasma and observed structural variation due to plasma addition in PBMCs along with increased cell survival. Light microscopy of the cells showed increased granularity in plasma-treated cells. Fourier transform infrared (FTIR) spectroscopy was used to elucidate the possible mechanism by studying the changes in the biochemical composition of the cells that explained the observations. FTIR spectroscopy of plasma-treated cells show altered spectral pattern in the mid-IR region, indicating increased phospholipid levels. Heat-stable components in the plasma possibly increase the differentiation of PBMCs, as evident by increased phospholipid metabolism. The data suggest that plasma-stimulated membrane biogenesis may contribute to PBMC survival by inducing them to differentiate into antigen presenting cells (APCs) like macrophages and dendritic cells.

Detection of cancer using advanced computerized analysis of infrared spectra of peripheral blood.

We have developed a novel approach for detection of cancer based on biochemical analysis of peripheral blood plasma using Fourier transform infrared spectroscopy. This approach has proven to be quick, safe, minimal invasive, and effective. Our approach recognizes any signs of solid tumor presence, regardless of location in the body or cancer type by measuring a spectrum that gives information regarding the total molecular composition and structure of the peripheral blood samples. The analysis includes clinically relevant preprocessing and feature extraction with principal component analysis, and uses Fisher's linear discriminant analysis to classify between cancer patients and healthy controls. We evaluated our method with leave-one-out cross validation and were able to establish sensitivity of 93.33%, specificity of 87.8%, and overall accuracy of 90.7%. Using our method for cancer detection should result in fewer unnecessary invasive procedures and yield fast detection of solid tumors.

Identification of fungal phytopathogens using Fourier transform infrared-attenuated total reflection spectroscopy and advanced statistical methods.

The early diagnosis of phytopathogens is of a great importance; it could save large economical losses due to crops damaged by fungal diseases, and prevent unnecessary soil fumigation or the use of fungicides and bactericides and thus prevent considerable environmental pollution. In this study, 18 isolates of three different fungi genera were investigated; six isolates of Colletotrichum coccodes, six isolates of Verticillium dahliae and six isolates of Fusarium oxysporum. Our main goal was to differentiate these fungi samples on the level of isolates, based on their infrared absorption spectra obtained using the Fourier transform infrared-attenuated total reflection (FTIR-ATR) sampling technique. Advanced statistical and mathematical methods: principal component analysis (PCA), linear discriminant analysis (LDA), and k-means were applied to the spectra after manipulation. Our results showed significant spectral differences between the various fungi genera examined. The use of k-means enabled classification between the genera with a 94.5% accuracy, whereas the use of PCA [3 principal components (PCs)] and LDA has achieved a 99.7% success rate. However, on the level of isolates, the best differentiation results were obtained using PCA (9 PCs) and LDA for the lower wavenumber region (800-1775 cm(-1)), with identification success rates of 87%, 85.5%, and 94.5% for Colletotrichum, Fusarium, and Verticillium strains, respectively.

Pre-screening and follow-up of childhood acute leukemia using biochemical infrared analysis of peripheral blood mononuclear cells.

BACKGROUND: Recent advances in chemotherapeutic treatment of childhood acute leukemia have improved remission rates to about 80%. With the development of novel drugs and treatment protocols adapted for specific individual patients, a simple diagnostic tool for following patients' responses on a daily basis is required. In the present clinical study, we have investigated the usefulness of Fourier transform infrared microscopy (FTIR-MSP) for pre-screening and follow-up of leukemia patients undergoing chemotherapy. METHODS: Blood samples were collected from leukemia patients before and during treatment as well as from patients with high fever and healthy subjects which served as control groups. Peripheral blood mononuclear cells (PBMCs) were isolated and their spectra obtained using FTIR-MSP. The presence of blasts in bone marrow and other diagnostic and prognostic clinical parameters were determined during follow-up up to 1000 days. RESULTS: Leukemia was efficiently indicated by a reduced lipids and elevated DNA absorption of PBMC together with additional characteristic spectral bands. These diagnostic markers were used for monitoring the biochemical changes in PBMCs during chemotherapy. The trends of several markers were found to be in agreement with blast percentage as determined by flow cytometry. CONCLUSIONS: Our findings reveal the utility of FTIR-MSP for leukemia pre-screening independently of symptoms common to leukemia. Furthermore, FTIR-MSP supplies precursor indication regarding patient response to treatment compared to current methods. GENERAL SIGNIFICANCE: This preliminary study shows a great potential of FTIR-MSP as a complementary tool for childhood leukemia pre-screening and follow-up which may allow faster response to critical problems arise during treatment.

Spectral signatures of colonic malignancies in the mid-infrared region: from basic research to clinical applicability.

The process of carcinogenesis in the colon progresses through several overlapping stages, making the evaluation process challenging, as well as subjective. Owing to the complexity of colonic tissues and the search for a technique that is rapid and foolproof for precise grading and evaluation of biopsies, many spectroscopic techniques have been evaluated in the past few decades for their efficiency and clinical compatibility. Fourier-transform infrared spectroscopy, being quantitative and objective, has the capacity for automation and relevance to cancer diagnosis. This article highlights investigations on the application of Fourier-transform infrared spectroscopy (particularly microscopy) in colon cancer diagnosis and parallel developments in data analysis techniques for the characterization of spectral signatures of malignant tissues in the colon.

Biochemical analysis and quantification of hematopoietic stem cells by infrared spectroscopy.

Identification of hematopoietic stem cells (HSCs) in different stages of maturation is one of the major issues in stem cell research and bone marrow (BM) transplantation. Each stage of maturation of HSCs is characterized by a series of distinct glycoproteins present on the cell plasma membrane surface, named a cluster of differentiation (CD). Currently, complicated and expensive procedures based on CD expression are needed for identification and isolation of HSCs. This method is under dispute, since the correct markers' composition is not strictly clear, thus there is need for a better method for stem cell characterization. In the present study, Fourier transform infrared (FTIR) spectroscopy is employed as a novel optical method for identification and characterization of HSCs based on their entire biochemical features. FTIR spectral analysis of isolated mice HSCs reveals several spectral markers related to lipids, nucleic acids, and carbohydrates, which distinguish HSCs from BM cells. The unique "open" conformation of HSC DNA as identified by FTIR is exploited for HSCs quantification in the BM. The proposed method of FTIR spectroscopy for HSC identification and quantification can contribute to stem cell research and BM transplantation.

Prediction potential of IR-micro spectroscopy for colon cancer relapse.

This study aimed to determine the potential of IR-spectroscopy to diagnose abnormality in histologically normal resection margins for predicting relapse in colon cancer patients. The present study evaluates potential abnormal crypt proliferation in histologically normal resection margins. Resection margins of 10 colon cancer patients (adenocarcinoma) (27 biopsies in all), found completely normal by standard histology were re-evaluated. Fourier transform infrared microscopy (FTIR-MSP) was performed on the longitudinal sections of the crypt, and spectral data collected from the base, middle and top portion of crypts. Absorbance in the region 900-1185 cm(-1) arising from carbohydrates and nucleic acids was found to be the most effective variate for such evaluation. In total 225 crypts were classified after assessing the levels of abnormality observed by the above technique. The abnormal biopsies detected using the above optical method was correlated with a relapse in the patient's history. Patients who had a relapse had at least one abnormal biopsy (crypt) based on the present methodology. Among the patients, the only case without a relapse was also the case where no abnormal crypts were found in any biopsies from the resection margins. The agreement between the biopsy status, as determined by the optical methodology, and the relapse of colonic malignancy based on the patients' medical files, establishes the translational nature of FTIR-MSP for medical purposes and hints at future clinical evaluation of the biopsies using this technique to determine more precisely the zone of excision during anastomosis.

Fluorescence spectroscopy of H-ras transfected murine fibroblasts: a comparison with Monte Carlo simulations.

Autofluorescence properties of tissues have been widely used to diagnose various types of malignancies. In this study, we measured the autofluorescence properties of H-ras transfected murine fibroblasts and the counterpart control cells. The pair of cells is genetically identical except for the transfected H-ras gene. We applied Monte Carlo simulations to evaluate the relative contributions of Rayleigh and Mie scattering effects towards fluorescence in an in vitro model system of normal and H-ras transfected fibroblasts. The experimental results showed that fluorescence emission intensity was higher for normal cells than the malignant counterpart cells by about 30%. In normal cells, linearity in emission intensity was observed for cell densities of up to 1.0 x 10(6) cells/ml whereas for transformed cells it was up to 1.4 x 10(6) cells/ml. Nuclear volume changes give good account for the differences in the intrinsic fluorescence between normal and malignant cells. The Monte Carlo (MC) code, newly developed for this study, explains both predominant experimental features: the large fluorescence intensity differences between the transfected and the corresponding control cells as well as the phenomena of the red shift in the excitation spectra as a function of cell density. The contribution of Rayleigh scattering was found to be predominant compared to Mie scattering.

Diagnosis of cell death by means of infrared spectroscopy.

Fourier transform infrared (FTIR) spectroscopy has been established as a fast spectroscopic method for biochemical analysis of cells and tissues. In this research we aimed to investigate FTIR's utility for identifying and characterizing different modes of cell death, using leukemic cell lines as a model system. CCRF-CEM and U937 leukemia cells were treated with arabinoside and doxorubicin apoptosis inducers, as well as with potassium cyanide, saponin, freezing-thawing, and H(2)O(2) necrosis inducers. Cell death mode was determined by various gold standard biochemical methods in parallel with FTIR-microscope measurements. Both cell death modes exhibit large spectral changes in lipid absorbance during apoptosis and necrosis; however, these changes are similar and thus cannot be used to distinguish apoptosis from necrosis. In contrast to the above confounding factor, our results reveal that apoptosis and necrosis can still be distinguished by the degree of DNA opaqueness to infrared light. Moreover, these two cell death modes also can be differentiated by their infrared absorbance, which relates to the secondary structure of total cellular protein. In light of these findings, we conclude that, because of its capacity to monitor multiple biomolecular parameters, FTIR spectroscopy enables unambiguous and easy analysis of cell death modes and may be useful for biochemical and medical applications.