A global perspective on the status of clinical metabolomics in laboratory medicine - a survey by the IFCC metabolomics working group.

OBJECTIVES: Metabolomics aims for comprehensive characterization and measurement of small molecule metabolites (<1700 Da) in complex biological matrices. This study sought to assess the current understanding and usage of metabolomics in laboratory medicine globally and evaluate the perception of its promise and future implementation. METHODS: A survey was conducted by the IFCC metabolomics working group that queried 400 professionals from 79 countries. Participants provided insights into their experience levels, knowledge, and usage of metabolomics approaches, along with detailing the applications and methodologies employed. RESULTS: Findings revealed a varying level of experience among respondents, with varying degrees of familiarity and utilization of metabolomics techniques. Targeted approaches dominated the field, particularly liquid chromatography coupled to a triple quadrupole mass spectrometer, with untargeted methods also receiving significant usage. Applications spanned clinical research, epidemiological studies, clinical diagnostics, patient monitoring, and prognostics across various medical domains, including metabolic diseases, endocrinology, oncology, cardiometabolic risk, neurodegeneration and clinical toxicology. CONCLUSIONS: Despite optimism for the future of clinical metabolomics, challenges such as technical complexity, standardization issues, and financial constraints remain significant hurdles. The study underscores the promising yet intricate landscape of metabolomics in clinical practice, emphasizing the need for continued efforts to overcome barriers and realize its full potential in patient care and precision medicine.

Advancing Renal Amyloidosis Care: The Role of Modern Diagnostic Techniques with the Potential of Enhancing Patient Outcomes.

Renal amyloidosis is a set of complex disorders characterized by the deposition of amyloid proteins in the kidneys, which causes gradual organ damage and potential kidney failure. Recent developments in diagnostic methods, particularly mass spectrometry and proteome profiling, have greatly improved the accuracy of amyloid typing, which is critical for disease management. These technologies provide extensive insights into the specific proteins involved, allowing for more targeted treatment approaches and better patient results. Despite these advances, problems remain, owing to the heterogeneous composition of amyloid proteins and the varying efficacy of treatments based on amyloid type. Access to sophisticated diagnostics and therapy varies greatly, highlighting the global difference in renal amyloidosis management. Future research is needed to investigate next-generation sequencing and gene-editing technologies, like clustered regularly interspaced short palindromic repeats (CRISPR), which promise more profound insights into the genetic basis of amyloidosis.

Infrared Spectroscopy in Gynecological Oncology: A Comprehensive Review of Diagnostic Potentials and Challenges.

The early detection of gynecological cancers, which is critical for improving patient survival rates, is challenging because of the vague early symptoms and the diagnostic limitations of current approaches. This comprehensive review delves into the game-changing potential of infrared (IR) spectroscopy, a noninvasive technology used to transform the landscape of cancer diagnosis in gynecology. By collecting the distinctive vibrational frequencies of chemical bonds inside tissue samples, Fourier-transform infrared (FTIR) spectroscopy provides a 'molecular fingerprint' that outperforms existing diagnostic approaches. We highlight significant advances in this field, particularly the identification of discrete biomarker bands in the mid- and near-IR spectra. Proteins, lipids, carbohydrates, and nucleic acids exhibited different absorption patterns. These spectral signatures not only serve to distinguish between malignant and benign diseases, but also provide additional information regarding the cellular changes associated with cancer. To underscore the practical consequences of these findings, we examined studies in which IR spectroscopy demonstrated exceptional diagnostic accuracy. This review supports the use of IR spectroscopy in normal clinical practice, emphasizing its capacity to detect and comprehend the intricate molecular underpinnings of gynecological cancers.

Applications of Artificial Intelligence in Urinalysis: Is the Future Already Here?

BACKGROUND: Artificial intelligence (AI) has emerged as a promising and transformative tool in the field of urinalysis, offering substantial potential for advancements in disease diagnosis and the development of predictive models for monitoring medical treatment responses. CONTENT: Through an extensive examination of relevant literature, this narrative review illustrates the significance and applicability of AI models across the diverse application area of urinalysis. It encompasses automated urine test strip and sediment analysis, urinary tract infection screening, and the interpretation of complex biochemical signatures in urine, including the utilization of cutting-edge techniques such as mass spectrometry and molecular-based profiles. SUMMARY: Retrospective studies consistently demonstrate good performance of AI models in urinalysis, showcasing their potential to revolutionize clinical practice. However, to comprehensively evaluate the real clinical value and efficacy of AI models, large-scale prospective studies are essential. Such studies hold the potential to enhance diagnostic accuracy, improve patient outcomes, and optimize medical treatment strategies. By bridging the gap between research and clinical implementation, AI can reshape the landscape of urinalysis, paving the way for more personalized and effective patient care.

Potentials and pitfalls of ChatGPT and natural-language artificial intelligence models for the understanding of laboratory medicine test results. An assessment by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Working Group on Artificial Intelligence (WG-AI).

OBJECTIVES: ChatGPT, a tool based on natural language processing (NLP), is on everyone's mind, and several potential applications in healthcare have been already proposed. However, since the ability of this tool to interpret laboratory test results has not yet been tested, the EFLM Working group on Artificial Intelligence (WG-AI) has set itself the task of closing this gap with a systematic approach. METHODS: WG-AI members generated 10 simulated laboratory reports of common parameters, which were then passed to ChatGPT for interpretation, according to reference intervals (RI) and units, using an optimized prompt. The results were subsequently evaluated independently by all WG-AI members with respect to relevance, correctness, helpfulness and safety. RESULTS: ChatGPT recognized all laboratory tests, it could detect if they deviated from the RI and gave a test-by-test as well as an overall interpretation. The interpretations were rather superficial, not always correct, and, only in some cases, judged coherently. The magnitude of the deviation from the RI seldom plays a role in the interpretation of laboratory tests, and artificial intelligence (AI) did not make any meaningful suggestion regarding follow-up diagnostics or further procedures in general. CONCLUSIONS: ChatGPT in its current form, being not specifically trained on medical data or laboratory data in particular, may only be considered a tool capable of interpreting a laboratory report on a test-by-test basis at best, but not on the interpretation of an overall diagnostic picture. Future generations of similar AIs with medical ground truth training data might surely revolutionize current processes in healthcare, despite this implementation is not ready yet.

The Potential Use of Near- and Mid-Infrared Spectroscopy in Kidney Diseases.

Traditional renal biomarkers such as serum creatinine and albuminuria/proteinuria are rather insensitive since they change later in the course of the disease. In order to determine the extent and type of kidney injury, as well as to administer the proper therapy and enhance patient management, new techniques for the detection of deterioration of the kidney function are urgently needed. Infrared spectroscopy is a label-free and non-destructive technique having the potential to be a vital tool for quick and inexpensive routine clinical diagnosis of kidney disorders. The aim of this review is to provide an overview of near- and mid-infrared spectroscopy applications in patients with acute kidney injury and chronic kidney disease (e.g., diabetic nephropathy and glomerulonephritis).

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.

Recent evolutions of machine learning applications in clinical laboratory medicine.

Machine learning (ML) is gaining increased interest in clinical laboratory medicine, mainly triggered by the decreased cost of generating and storing data using laboratory automation and computational power, and the widespread accessibility of open source tools. Nevertheless, only a handful of ML-based products are currently commercially available for routine clinical laboratory practice. In this review, we start with an introduction to ML by providing an overview of the ML landscape, its general workflow, and the most commonly used algorithms for clinical laboratory applications. Furthermore, we aim to illustrate recent evolutions (2018 to mid-2020) of the techniques used in the clinical laboratory setting and discuss the associated challenges and opportunities. In the field of clinical chemistry, the reviewed applications of ML algorithms include quality review of lab results, automated urine sediment analysis, disease or outcome prediction from routine laboratory parameters, and interpretation of complex biochemical data. In the hematology subdiscipline, we discuss the concepts of automated blood film reporting and malaria diagnosis. At last, we handle a broad range of clinical microbiology applications, such as the reduction of diagnostic workload by laboratory automation, the detection and identification of clinically relevant microorganisms, and the detection of antimicrobial resistance.

The role of soluble receptor for advanced glycation end-products (sRAGE) in the general population and patients with diabetes mellitus with a focus on renal function and overall outcome.

Isoforms of the receptor for advanced glycation end-product (RAGE) protein, which lack the transmembrane and the signaling (soluble RAGE or sRAGE) domains are hypothesized to counteract the detrimental action of the full-length receptor by acting as a decoy, and they provide a potential tool to treat RAGE-associated diseases. Multiple studies have explored the relationship between sRAGE and endogenous secretory RAGE and its polymorphism and obesity, metabolic syndrome, atherosclerosis, kidney function, and increased mortality in the general population. In addition, sRAGE may be a key player in the pathogenesis of diabetes mellitus and its microvascular (e.g. kidney disease) as well as macrovascular (e.g. cardiovascular disease) complications. In this review, we focus on the role of sRAGE as a biomarker in these specific areas. As there is a lack of an underlying unifying hypothesis about how sRAGE changes according to the disease condition or risk factor, there is a call to incorporate all three players of the AGE-RAGE axis into a new universal biomarker/risk marker: (AGE + RAGE)/sRAGE. However, the measurement of RAGE in humans is not practical as it is a cell-bound receptor for which tissue is required for analysis. A high AGE/sRAGE ratio may be a valuable alternative and practical universal biomarker/risk marker for diseases associated with the AGE-RAGE axis, irrespective of low or high serum sRAGE concentrations.

A Potential Role for Fructosamine-3-Kinase in Cataract Treatment.

Cataracts are the major cause of blindness worldwide, largely resulting from aging and diabetes mellitus. Advanced glycation end products (AGEs) have been identified as major contributors in cataract formation because they alter lens protein structure and stability and induce covalent cross-linking, aggregation, and insolubilization of lens crystallins. We investigated the potential of the deglycating enzyme fructosamine-3-kinase (FN3K) in the disruption of AGEs in cataractous lenses. Macroscopic changes of equine lenses were evaluated after ex vivo intravitreal FN3K injection. The mechanical properties of an equine lens pair were evaluated after treatment with saline and FN3K. AGE-type autofluorescence (AF) was measured to assess the time-dependent effects of FN3K on glycolaldehyde-induced AGE-modified porcine lens fragments and to evaluate its actions on intact lenses after in vivo intravitreal FN3K injection of murine eyes. A potential immune response after injection was evaluated by analysis of IL-2, TNFα, and IFNγ using an ELISA kit. Dose- and time-dependent AF kinetics were analyzed on pooled human lens fragments. Furthermore, AF measurements and a time-lapse of macroscopic changes were performed on intact cataractous human eye lenses after incubation with an FN3K solution. At last, AF measurements were performed on cataractous human eyes after crossover topical treatment with either saline- or FN3K-containing drops. While the lenses of the equine FN3K-treated eyes appeared to be clear, the saline-treated lenses had a yellowish-brown color. Following FN3K treatment, color restoration could be observed within 30 min. The extension rate of the equine FN3K-treated lens was more than twice the extension rate of the saline-treated lens. FN3K treatment induced significant time-dependent decreases in AGE-related AF values in the AGE-modified porcine lens fragments. Furthermore, in vivo intravitreal FN3K injection of murine eyes significantly reduced AF values of the lenses. Treatment did not provoke a systemic immune response in mice. AF kinetics of FN3K-treated cataractous human lens suspensions revealed dose- and time-dependent decreases. Incubation of cataractous human eye lenses with FN3K resulted in a macroscopic lighter color of the cortex and a decrease in AF values. At last, crossover topical treatment of intact human eyes revealed a decrease in AF values during FN3K treatment, while showing no notable changes with saline. Our study suggests, for the first time, a potential additional role of FN3K as an alternative treatment for AGE-related cataracts.

Near-infrared spectroscopy as a potential non-invasive tool in the assessment of disease activity in vitiligo patients.

Vitiligo is a common chronic depigmenting skin disease. We explored the utility of near-infrared (NIR) spectroscopy in the identification of spectral changes associated with disease activity in vitiligo patients. In vivo spectral measurements were performed directly on the perilesional skin of 70 vitiligo patients. Relative intensities (second derivative) at 1139, 1344, 1646 and 1839 nm appeared to be significantly lower in the perilesional region of patients with active vitiligo compared with stable disease, while the intensity at 1884 nm seemed to be significantly higher. A classification model based on the spectral ranges around those peaks generated a correct prediction in 82.9% of the cases. In conclusion, we can state that NIR spectroscopy could have potential in the assessment of disease activity. However, large-scale prospective studies are necessary to confirm our preliminary results.

Exploring the possibilities of infrared spectroscopy for urine sediment examination and detection of pathogenic bacteria in urinary tract infections.

Objectives In this study, the possibilities of Fourier-transformed infrared spectroscopy (FTIR) for analysis of urine sediments and for detection of bacteria causing urinary tract infections (UTIs) were investigated. Methods Dried urine specimens of control subjects and patients presenting with various nephrological and urological conditions were analysed using mid-infrared spectroscopy (4,000-400 cm-1). Urine samples from patients with a UTI were inoculated on a blood agar plate. After drying of the pure bacterial colonies, FTIR was applied and compared with the results obtained by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Chemometric data analysis was used to classify the different species. Results Due to the typical molecular assignments of lipids, proteins, nucleic acids and carbohydrates, FTIR was able to identify bacteria and showed promising results in the detection of proteins, lipids, white and red blood cells, as well as in the identification of crystals. Principal component analysis (PCA) allowed to differentiate between Gram-negative and Gram-positive species and soft independent modelling of class analogy (SIMCA) revealed promising classification ratios between the different pathogens. Conclusions FTIR can be considered as a supplementary method for urine sediment examination and for detection of pathogenic bacteria in UTI.

N-Linked Glycosylation and Near-Infrared Spectroscopy in the Diagnosis of Prostate Cancer.

BACKGROUND: Performing a prostate biopsy is the most robust and reliable way to diagnose prostate cancer (PCa), and to determine the disease grading. As little to no biochemical markers for prostate tissue exist, we explored the possibilities of tissue N-glycosylation and near-infrared spectroscopy (NIR) in PCa diagnosis. METHODS: Tissue specimens from 100 patients (benign prostate hyperplasia (BPH), n = 50; and PCa, n = 50) were obtained. The fresh-frozen tissue was dispersed and a tissue N-glycosylation profile was determined. Consequently, the formalin-fixed paraffin-embedded slides were analyzed using NIR spectroscopy. A comparison was made between the benign and malignant tissue, and between the various Gleason scores. RESULTS: A difference was observed for the tissue of N-glycosylation between the benign and malignant tissue. These differences were located in the fycosylation ratios and the total amount of bi- and tetra-antennary structures (all p < 0.0001). These differences were also present between various Gleason scores. In addition, the NIR spectra revealed changes between the benign and malignant tissue in several regions. Moreover, spectral ranges of 1055⁻1065 nm and 1450⁻1460 nm were significantly different between the Gleason scores (p = 0.0042 and p = 0.0195). CONCLUSIONS: We have demonstrated biochemical changes in the N-glycan profile of prostate tissue, which allows for the distinction between malignant and benign tissue, as well as between various Gleason scores. These changes can be correlated to the changes observed in the NIR spectra. This could possibly further improve the histological assessment of PCa diagnosis, although further method validation is needed.

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.

Infrared analysis of lipoproteins in the detection of alcohol biomarkers.

BACKGROUND: Alcoholism is a major public health problem. Alcohol causes modifications in the composition and concentration of lipoproteins and influences the enzymes and transfer proteins that transform lipoproteins in plasma. Alcohol is associated with the presence of alcohol biomarkers (fatty acid ethyl esters [FAEEs] and phosphatidylethanol [PEth]) in lipoproteins. We explore the possibilities of detecting alcohol biomarkers in non-high-density-lipoproteins (non-HDLs) precipitated from serum using attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR). METHODS: Analyzes were carried out on stored serum samples, with known % carbohydrate-deficient transferrin (CDT) values, included in a driver's license regranting program under the control of the Belgian Institute of Road Safety. The study consisted of 127 control samples (CDT≤1.3%) and 114 alcoholic samples (CDT>1.3%). Liver enzymes, CRP, triglycerides, total, HDL- and LDL-cholesterol values were determined. Non-HDLs were precipitated with sodium phosphotungstate and MgCl2 and analyzed using ATR-FTIR in the range from 4500 cm-1 to 450 cm-1 using a Perkin Elmer ATR-FTIR Spectrometer Two. RESULTS: The area under the curve of the 1130-990 cm-1 region (AUC1130-990 cm-1) was able to discriminate controls from alcoholics (p<0.0001) due to the presence of FAEEs in lipoproteins. Multiple regression analysis significantly predicted the AUC1130-990 cm-1 (adj. r2=0.13, p<0.0001). Significant correlations were found between AUC1130-990 cm-1 and CDT values (r=0.32, p<0.0001), AST/ALT ratio (r=0.21, p=0.001). GGT showed no significant correlation. CONCLUSIONS: Infrared analysis of lipoproteins is a potential tool in the detection of alcohol biomarkers.