Noninvasive Diagnostic Strategies Research Articles

Dual SERS enhancement based on Ag@Au Nanopizza combined with superhydrophobic silicon substrate for the detection of early bladder cancer marker-APOA1

Currently, clinical detection of early bladder cancer (BC) biomarkers suffers from insufficient specificity and sensitivity. In this study, a novel triangular nanostructure with protrusions on the surface shaped like a pizza was prepared. It combined with a superhydrophobic Si substrate to achieve trace and ultra-sensitive Surface-enhanced Raman spectroscopy (SERS) detection of APOA1, a urinary biomarker for early BC. Firstly, we precisely controlled the number and spacing of gold protrusions on the surface of Ag@Au Nanopizza to achieve an enhancement factor (EF) of 3.86 × 107 for Ag@Au Nanopizza. In addition, we prepared substrates with superhydrophobic properties by functionalized modification using PS microsphere films as substrate. The enrichment of nanoparticles on the superhydrophobic Si substrate achieves a secondary enhancement of its SERS performance (EF = 5.73 × 107), while also attenuating the coffee-ring effect and improving the homogeneity of the substrate performance. The double SERS enhanced strategy was successfully applied to detect early BC biomarker APOA1. In a wide range (100 fg/mL-100 ng/mL), we achieved quantitative detection of APOA1 with a limit of detection (LOD) of 52 fg/mL. This provides an ultrasensitive, specific, and non-invasive diagnostic strategy for the early diagnosis of BC.

Innovative approaches to metabolic dysfunction-associated steatohepatitis diagnosis and stratification

The global rise in Metabolic dysfunction-associated steatotic liver disease (MASLD)/Metabolic dysfunction-associated steatohepatitis (MASH) highlights the urgent necessity for noninvasive biomarkers to detect these conditions early. To address this, we endeavored to construct a diagnostic model for MASLD/MASH using a combination of bioinformatics, molecular/biochemical data, and machine learning techniques. Initially, bioinformatics analysis was employed to identify RNA molecules associated with MASLD/MASH pathogenesis and enriched in ferroptosis and exophagy. This analysis unveiled specific networks related to ferroptosis (GPX4, LPCAT3, ACSL4, miR-4266, and LINC00442) and exophagy (TSG101, HGS, SNF8, miR-4498, miR-5189–5p, and CTBP1-AS2). Subsequently, serum samples from 400 participants (151 healthy, 150 MASH, and 99 MASLD) underwent biochemical and molecular analysis, revealing significant dyslipidemia, impaired liver function, and disrupted glycemic indicators in MASLD/MASH patients compared to healthy controls. Molecular analysis indicated increased expression of LPCAT3, ACSL4, TSG101, HGS, and SNF8, alongside decreased GPX4 levels in MASH and MASLD patients compared to controls. The expression of epigenetic regulators from both networks (miR-4498, miR-5189–5p, miR-4266, LINC00442, and CTBP1-AS2) significantly differed among the studied groups. Finally, supervised machine learning models, including Neural Networks and Random Forest, were applied to molecular signatures and clinical/biochemical data. The Random Forest model exhibited superior performance, and molecular features effectively distinguished between the three studied groups. Clinical features, particularly BMI, consistently served as discriminatory factors, while biochemical features exhibited varying discriminant behavior across MASH, MASLD, and control groups. Our study underscores the significant potential of integrating diverse data types to enable early detection of MASLD/MASH, offering a promising approach for non-invasive diagnostic strategies.

Silver Nanoclusters-Decorated Porous Microneedles Coupling Duplex-Specific Nuclease-Assisted Signal Amplification for Sampling and Detection of MicroRNA in Interstitial Fluid.

MicroRNAs (miRNAs) in dermal interstitial fluid (ISF) have recently been recognized as clinically promising biomarkers for the diagnosis and prognosis of cancer. However, the detection poses significant challenges, primarily due to the low abundance of miRNAs and the limitations of current sampling techniques. To address this issue, we develop novel porous microneedles (PMNs) array-based sensor composed of poly(vinyl alcohol) porous hydrogel and DNA-templated silver nanoclusters (AgNCs) to facilitate the enrichment and highly sensitive detection of ISF miRNA. Leveraging the capillary action facilitated by its unique porous structure and the swelling properties of the hydrogel, the PMNs array can efficiently extract 2.7 ± 0.3 mg of ISF within 5 min. Additionally, the interconnected pores within the PMNs array contribute to an increased specific surface area, thereby offering a convenient platform for the decoration of DNA-templated AgNCs. The immobilized large amount of AgNCs effectively capture the target miRNA from the extracted ISF, resulting in miRNA-induced fluorescence quenching of AgNCs. Subsequently, the introduction of the duplex-specific nuclease leads to the cleavage of DNA in DNA-RNA heteroduplexes, which release miRNA to interact with other AgNCs. This process of target recycling triggers a further reduction in fluorescence intensity, thereby enabling sensitive detection of the low-abundant miRNA down to 1.6 pM. Both in vitro and in vivo experiments validate the efficacy of the AgNCs immobilized PMNs array for the detection of miRNA biomarkers in ISF within minutes. These results indicate that the proposed PMNs array-based sensor holds great potential for the development of noninvasive personalized diagnostic strategies.

Unlocking the potential of exosomes: A new frontier in liver cancer liquid biopsy

Liquid biopsy has emerged as one of the non-invasive diagnostic strategies for cancer, offering significant advantages over traditional tissue biopsies. Exosomes the nanoscale extracellular vesicles, have significantly been in the spotlight of research and investigation as highly informative biomarkers in liquid biopsy. These vesicles, which are secreted by a variety of cells, including tumor cells, contain useful information on the molecular characteristics of the parent cell and could be used as a mirror into the processes underlying cancer biology. The analysis of the biomolecular exosomal cargo, including proteins, nucleic acids, and lipids, has shown great promise for the development of sensitive and specific liquid biopsy-based biomarkers for cancer detection, monitoring, and prognosis. This review discusses the role of exosomes in the liver cancer development and metastatic process, including their ability to transfer oncogenic material and facilitate tumor progression. It also explores the application of exosomes as a tool for early cancer detection, monitoring disease status, and predicting prognosis, with a specific focus on liver cancer. Exosomes hold great promise as a minimally invasive liquid biopsy approach that could revolutionize the way we diagnose and manage this deadly disease.

Machine-learning models for diagnosis of rotator cuff tears in osteoporosis patients based on anteroposterior X-rays of the shoulder joint

ObjectiveThis study aims to diagnose Rotator Cuff Tears (RCT) and classify the severity of RCT in patients with Osteoporosis (OP) through the analysis of shoulder joint anteroposterior (AP) X-ray-based localized proximal humeral bone mineral density (BMD) measurements and clinical information based on machine learning (ML) models. MethodsA retrospective cohort of 89 patients was analyzed, including 63 with both OP and RCT (OPRCT) and 26 with OP only. The study analyzed a series of shoulder radiographs from April 2021 to April 2023. Grayscale values were measured after plotting ROIs based on AP X-rays of shoulder joint. Five kinds of ML models were developed and compared based on their performance in predicting the occurrence and severity of RCT from ROIs' greyscale values and clinical information (age, gender, advantage side, lumbar BMD, and acromion morphology (AM)). Further analysis using SHAP values illustrated the significant impact of selected features on model predictions. ResultsR1-6 had a positive correlation with BMD respectively. The nine variables, including greyscale R1-6, age, BMD, and AM, were used in the prediction models. The RF model was determined to be superior in effectively diagnosing RCT in OP patients, with high AUC scores of 0.998, 0.889, and 0.95 in the training, validation, and testing sets, respectively. SHAP values revealed that the most influential factors on the diagnostic outcomes were the grayscale values of all cancellous bones in ROIs. A column-line graph prediction model based on nine variables was constructed, and DCA curves indicated that RCT prediction in OP patients was favored based on this model. Furthermore, the RF model was also the most superior in predicting the types of RCT within the OPRCT group, with an accuracy of 86.364% and 73.684% in the training and test sets, respectively. SHAP values indicated that the most significant factor affecting the predictive outcomes was the AM, followed by the grayscale values of the greater tubercle, among others. ConclusionsML models, particularly the RF algorithm, show significant promise in diagnosing RCT occurrence and severity in OP patients using conventional shoulder X-rays based on the nine variables. This method presents a cost-effective, accessible, and non-invasive diagnostic strategy that has the potential to substantially enhance the early detection and management of RCT in OP patient population.

Personalized Noninvasive Diagnostic Algorithms Based on Urinary Free Cortisol in ACTH-dependant Cushing's Syndrome.

Current guidelines for distinguishing Cushing's disease (CD) from ectopic ACTH secretion (EAS) are questionable, as they use pituitary magnetic resonance imaging (MRI) as first-line investigation for all patients. CRH testing is no longer available, and they suggest performing inferior petrosal sinus sampling (BIPPS), an invasive and rarely available investigation, in many patients. To establish noninvasive personalized diagnostic strategies based on the probability of EAS estimated from simple baseline parameters. Retrospective study. University hospitals. Two hundred forty-seven CD and 36 EAS patients evaluated between 2001 and 2023 in 2 French hospitals. A single-center cohort of 105 Belgian patients served as external validation. Twenty-four-hour urinary free cortisol (UFC) had the highest area under the receiver operating characteristic curve for discrimination of CD from EAS (.96 [95% confidence interval (CI), .92-.99] in the primary study and .99 [95% CI, .98-1.00] in the validation cohort). The addition of clinical, imaging, and biochemical parameters did not improve EAS prediction over UFC alone, with only BIPPS showing a modest improvement (C-statistic index .99 [95% CI, .97-1.00]). Three groups were defined based on baseline UFC: < 3 (group 1), 3-10 (group 2), and > 10 × the upper limit of normal (group 3), and they were associated with 0%, 6.1%, and 66.7% prevalence of EAS, respectively. Diagnostic approaches performed in our cohort support the use of pituitary MRI alone in group 1, MRI first followed by neck-to-pelvis computed tomography scan (npCT) when negative in group 2, and npCT first followed by pituitary MRI when negative in group 3. When not combined with the CRH test, the desmopressin test has limited diagnostic value. UFC accurately predicts EAS and can serve to define personalized and noninvasive diagnostic algorithms.

Exploring the Mechanistic Interplay between Gut Microbiota and Precocious Puberty: A Narrative Review.

The gut microbiota has been implicated in the context of sexual maturation during puberty, with discernible differences in its composition before and after this critical developmental stage. Notably, there has been a global rise in the prevalence of precocious puberty in recent years, particularly among girls, where approximately 90% of central precocious puberty cases lack a clearly identifiable cause. While a link between precocious puberty and the gut microbiota has been observed, the precise causality and underlying mechanisms remain elusive. This narrative review aims to systematically elucidate the potential mechanisms that underlie the intricate relationship between the gut microbiota and precocious puberty. Potential avenues of exploration include investigating the impact of the gut microbiota on endocrine function, particularly in the regulation of hormones, such as gonadotropin-releasing hormone (GnRH), luteinizing hormone (LH), and follicle-stimulating hormone (FSH). Additionally, this review will delve into the intricate interplay between the gut microbiome, metabolism, and obesity, considering the known association between obesity and precocious puberty. This review will also explore how the microbiome's involvement in nutrient metabolism could impact precocious puberty. Finally, attention is given to the microbiota's ability to produce neurotransmitters and neuroactive compounds, potentially influencing the central nervous system components involved in regulating puberty. By exploring these mechanisms, this narrative review seeks to identify unexplored targets and emerging directions in understanding the role of the gut microbiome in relation to precocious puberty. The ultimate goal is to provide valuable insights for the development of non-invasive diagnostic methods and innovative therapeutic strategies for precocious puberty in the future, such as specific probiotic therapy.

Abstract 13423: Magnetocardiography as a Noninvasive Diagnostic Strategy for Ischemia Evaluating Following Coronary Revascularization of Patients With Non-ST Segment Elevation Myocardial Infarction

Introduction: Magnetocardiography (MCG) constitutes a non-invasive and radiation-free procedure that quantifies the heart's magnetic fields and has exhibited sensitive diagnostic capabilities for ischemia. Typically, MCG presents a distinctive pattern in healthy subjects, characterized by a positive and a negative pole that forms an angle of approximately 45-60 degrees within the T peak segment. Hypothesis: Our study aims to monitor the significant alterations in MCG patterns among patients with Non-ST Segment Elevation Myocardial Infarction (NSTEMI) undergoing revascularization. Methods: Patients were prospectively enrolled and MCG scans were conducted thrice: three days pre-intervention, one week post-intervention, and at a three-month follow-up. Results: Four patients underwent anatomical complete revascularization, while one patient had incomplete revascularization. When comparing the MCG patterns of patients with NSTEMI (Figures B-F) to a normal MCG pattern (Figure A), pre-intervention scans showed angular deflection (80%, except for patient 3) and an anomalous distribution of poles (100%). One week post-intervention, patients who underwent complete revascularization (Figures B-D) had myocardial enzymes normalized, along with slight angle recovery and reshaping of the poles (100%). By the three-month follow-up, these patients experienced symptom resolution, and their MCG patterns showed normalized angles with recovered poles (100%). However, the patient who underwent incomplete revascularization (Figure F) exhibited sustained myocardial ischemia symptoms, with no further angle recovery and continued anomalous distribution of positive poles, both post-intervention and during follow-up. Conclusions: The distribution of poles and angular deflection could potentially serve as indicators of ischemia. MCG may represent a promising strategy for evaluating myocardial recovery in patients with NSTEMI.

Protocol for SNOTOB study: radical prostatectomy without prostate biopsy following 18F-PSMA-1007 PET/CT based on a diagnostic model: a single-centre, single-arm, open-label study

IntroductionNowadays, invasive prostate biopsy is the standard diagnostic test for patients with suspected prostate cancer (PCa). However, it has some shortcomings such as perioperative complications, economic and psychological burden on...

Hollow Core-Shell Metal Oxide Heterojunctions for the Urinary Metabolic Fingerprint-Based Noninvasive Diagnostic Strategy.

Urine is a preferred object for noninvasive diagnostic strategies. Urinary metabolic analysis is speculatively regarded as an ideal tool for screening diseases closely related to the genitourinary system in view of the intimate relationship between metabolomics and phenotype. Herein, we propose a urinary metabolic fingerprint-based noninvasive diagnostic strategy by designing hollow core-shell metal oxide heterojunctions (denoted as MOHs). With outstanding light absorption and electron-hole separation ability, MOHs aid in the extraction of high-performance urine metabolic fingerprints. Coupled with optimized machine learning algorithms, we establish a metabolic marker panel for accurate diagnosis of prostate cancer (PCa), which is the most common malignant tumor of the male genitourinary system, achieving accuracies of 84.72 and 83.33% in the discovery and validation sets, respectively. Furthermore, metabolite variations and related pathway analyses confirm the credibility and change correlation of key metabolic features in PCa. This work tends to advance the noninvasive diagnostic strategy toward clinical realities.

Ecological change of the gut microbiota during pregnancy and progression to dyslipidemia

The composition of the gut microbiome was previously found to be associated with clinical responses to dyslipidemia, but there is limited consensus on the dynamic change of the gut microbiota during pregnancy and the specific microbiome characteristics linked to dyslipidemia in pregnant women. We collected fecal samples from 513 pregnant women at multiple time points during pregnancy in a prospective cohort. Taxonomic composition and functional annotations were determined by 16S rRNA amplicon sequencing and shotgun metagenomic sequencing. The predictive potential of gut microbiota on the risk of dyslipidemia was determined. The gut microbiome underwent dynamic changes during pregnancy, with significantly lower alpha diversity observed in dyslipidemic patients compared to their healthy counterparts. Several genera, including Bacteroides, Paraprevotella, Alistipes, Christensenellaceae R7 group, Clostridia UCG-014, and UCG-002 were negatively associated with lipid profiles and dyslipidemia. Further metagenomic analysis recognized a common set of pathways involved in gastrointestinal inflammation, where disease-specific microbes played an important role. Machine learning analysis confirmed the link between the microbiome and its progression to dyslipidemia, with a micro-averaged AUC of 0.824 (95% CI: 0.782-0.855) combined with blood biochemical data. Overall, the human gut microbiome, including Alistipes and Bacteroides, was associated with the lipid profile and maternal dyslipidemia during pregnancy by perturbing inflammatory functional pathways. Gut microbiota combined with blood biochemical data at the mid-pregnancy stage could predict the risk of dyslipidemia in late pregnancy. Therefore, the gut microbiota may represent a potential noninvasive diagnostic and therapeutic strategy for preventing dyslipidemia in pregnancy.

Telomere Length Changes in Cancer: Insights on Carcinogenesis and Potential for Non-Invasive Diagnostic Strategies

Telomere dynamics play a crucial role in the maintenance of chromosome integrity; changes in telomere length may thus contribute to the development of various diseases including cancer. Understanding the role of telomeric DNA in carcinogenesis and detecting the presence of cell-free telomeric DNA (cf-telDNA) in body fluids offer a potential biomarker for novel cancer screening and diagnostic strategies. Liquid biopsy is becoming increasingly popular due to its undeniable benefits over conventional invasive methods. However, the organization and function of cf-telDNA in the extracellular milieu are understudied. This paper provides a review based on 3,398,017 cancer patients, patients with other conditions, and control individuals with the aim to shed more light on the inconsistent nature of telomere lengthening/shortening in oncological contexts. To gain a better understanding of biological factors (e.g., telomerase activation, alternative lengthening of telomeres) affecting telomere homeostasis across different types of cancer, we summarize mechanisms responsible for telomere length maintenance. In conclusion, we compare tissue- and liquid biopsy-based approaches in cancer assessment and provide a brief outlook on the methodology used for telomere length evaluation, highlighting the advances of state-of-the-art approaches in the field.

Detection of NRAS Mutation in Kaposiform Lymphangiomatosis Using Cell-free DNA from Plasma

Kaposiform lymphangiomatosis is a rare lymphatic anomaly that occurs in children and is associated with life-threatening complications. The somatic mutation NRAS Q61R (c.182A&gt;G) has been identified in lesional tissue samples of patients with kaposiform lymphangiomatosis, and can be used to differentiate this condition from other complex lymphatic anomalies and to guide treatment. Tissue sampling in this lymphatic anomaly is inherently risky due to its involvement of thoracic and abdominal organs and associated coagulopathy. Analysis of cell-free DNA isolated from blood plasma presents a promising noninvasive diagnostic strategy. Here, we describe the use of this approach using a commercial assay.

Exosomal miR-202 derived from leukorrhea as a potential biomarker for endometriosis

Endometriosis (EMS) is a chronic gynecological disorder with an urgent need of a reliable non-invasive diagnostic strategy. Recently, there has been increasing interest in using the contents of exosomes, especially exosomal microRNAs (miRNAs), as potential biomarkers for various types of diseases. In this study, we assessed the differentially expressed miRNAs in exosomes derived from primary normal and ectopic endometrial cells. We used miRNA microarray analysis to identify differentially expressed exosomal miRNAs. Among the selected exosomal miRNAs, we focused on hsa-miR-202-3p and hsa-miR-202-5p and validated their expression levels using quantitative reverse transcription polymerase chain reaction analysis. We then further examined their expression in exosomes derived from vaginal discharge (leukorrhea) from patients with EMS and the negative control group. The data show that hsa-miR-202-3p and hsa-miR-202-5p were expressed significantly higher in leukorrhea-derived exosomes from EMS patients compared with the negative controls. Taken together, our results suggest that leukorrhea-derived exosomal hsa-miR-202 could serve as a potential useful biomarker for diagnosing EMS.

Noninvasive diagnostic work-up for suspected acute pulmonary embolism during pregnancy: a systematic review and meta-analysis of individual patient data

BackgroundFew studies evaluated the performance of noninvasive diagnostic strategies for suspected acute pulmonary embolism (PE) in pregnant women. ObjectivesThe aim of this study was to establish the safety and efficiency of the Wells rule with fixed and adapted D-dimer threshold, and the YEARS algorithm, combined with compression ultrasonography (CUS), in pregnant women with suspected PE in an individual patient data meta-analysis. MethodsWe performed a systematic review to identify prospective diagnostic management studies in pregnant women with suspected PE. Primary outcomes were safety, defined as the failure rate, ie, the 3-month venous thromboembolism (VTE) incidence after excluding PE without chest imaging, and efficiency, defined as the proportion of patients in whom chest imaging could be avoided. ResultsWe identified 2 relevant studies, of which individual patient-level data were analyzed in a fixed-effect meta-analysis, totaling 893 pregnant women. The Wells rule with fixed and adapted D-dimer threshold as well as the YEARS algorithm could safely rule out acute PE (failure rate, 0·37%-1·4%), but efficiency improved considerably when applying pretest probability-adapted D-dimer thresholds. The efficiency of bilateral CUS was limited (2·3% overall; number needed to test 43), especially in patients without symptoms of deep-vein thrombosis (efficiency 0·79%; number needed to test 127). ConclusionThis study supports the latest guideline recommendations (European Society of Cardiology 2019) to apply pretest probability assessment and D-dimer tests to rule out PE in pregnant women. From an efficiency perspective, the use of a strategy with pretest probability-adapted D-dimer threshold is preferred. The yield of CUS was very limited in patients without concomitant symptoms of deep-vein thrombosis.

901 DIAGNOSTIC STRATEGIES FOR THE ASSESSMENT OF SUSPECTED STABLE CORONARY ARTERY DISEASE: A SYSTEMATIC REVIEW AND NETWORK META-ANALYSIS

Abstract Background It is unclear which diagnostic strategy for detecting coronary artery disease (CAD) yields better outcomes. We aimed to compare the clinical accuracy and efficacy of non-invasive and invasive diagnostic strategies for the initial assessment of patients with suspected stable CAD. Methods On March 16, 2022, we searched PubMed, Embase, and CENTRAL databases for randomised controlled trials comparing diagnostic strategies for CAD detection among patients with symptoms suggestive of stable CAD. Diagnostic modalities included coronary computed tomographic angiography (CCTA), cardiovascular magnetic resonance (CMR), exercise electrocardiography, invasive coronary angiography (ICA), single photon emission computed tomography-myocardial perfusion imaging (SPECT-MPI), and stress echocardiography. Functional tests were grouped into a single node for the primary analyses, while being analysed as separate nodes for the secondary analyses. Frequentist random-effect network meta-analyses were conducted to summarise the evidence. GRADE frameworks were applied to rate the certainty of findings. The primary efficacy outcome was trial-defined major adverse cardiovascular events (MACE) and the primary accuracy outcome was the rate of unnecessary angiography. The study was registered with PROSPERO (CRD42022329635). Results Twenty trials (n=27753 participants) were included. Compared with direct-ICA referral, CCTA and functional testing provided no significant difference in the risk of MACE (incidence rate ratios [IRRs] 0·87 [95% CI 0·65-1·17] and 1·19 [95% CI 0·87-1·62], respectively; moderate certainty) and a large reduction in the rate of unnecessary angiography (odds ratios 0·04 [95% CI 0·02-0·09] and 0·08 [95% CI 0·03-0·18], respectively; high certainty). Among non-invasive diagnostic strategies, CCTA significantly reduced the risk of MACE compared with functional testing (IRR 0·73, 95% CI 0·57-0·95; high certainty). The worse prognostic performance of functional testing was mainly driven by the poor efficacy of exercise electrocardiography (high certainty) and stress echocardiography (moderate to low certainty), whose risk of MACE was significantly reduced by CCTA (IRRs 0·56 [95% CI 0·42-0·75] and 0·59 [95% CI 0·42-0·81], respectively), SPECT-MPI (IRRs 0·56 [95% CI 0·41-0·77] and 0·59 [95% CI 0·43-0·81], respectively), and direct-ICA referral (IRRs 0·64 [95% CI 0·45-0·91] and 0·67 [95% CI 0·48-0·92], respectively), while non-significantly reduced by CMR (IRRs 0·71 [95% CI 0·47-1·06] and 0·74 [95% CI 0·53-1·04], respectively). Conclusion In patients with suspected stable CAD, an initial assessment with non-invasive diagnostic strategies is safe and addresses the low diagnostic yield of direct-ICA referral. CCTA is among the most effective strategies in terms of both clinical accuracy and efficacy. Among functional non-invasive tests, exercise electrocardiography and stress echocardiography may not be deemed effective diagnostic alternatives, while SPECT-MPI and CMR are valuable and feasible options, respectively.

Magnetocardiography as a noninvasive diagnostic strategy for suspected coronary microvascular dysfunction

Abstract Background Coronary microvascular dysfunction (CMD) is increasingly recognized as an independent predictor of mortality with a 4-fold higher risk. However current diagnostic modalities are limited by the need for an invasive procedure, access, cost, and exposure of ionizing radiation. Purpose To investigate the ability of magnetocardiography (MCG) to identify CMD in patients with suspected ischemia and no obstructive coronary artery disease (INOCA). Methods This is an observational, prospective pilot study of patients scheduled for coronary functional angiography (CFA), gold standard for evaluation for CMD (defined as coronary flow reserve (CFR) ≤2). 13 patients underwent both CFA and a noninvasive 36-channel MCG scan. A machine learning model was developed to characterize the presence of CMD in these patients against age matched controls (AMCs). The model consists of a logistic regression classifier which takes features representing the relative strengths of the “characteristic dipoles” of the MCG scan as input. The characteristic dipoles are parameterizations of the three strongest magnetic field map components resulting from a singular value decomposition of the MCG signal. A total of 37 patients were included in this analysis including 13 patients who completed CFA (7 had CMD and 6 had CFR &amp;gt;2 and included in the AMCs group). An additional 24 asymptomatic, healthy patients that did not undergo CFR were also included in the AMC group. Results The mean age for AMCs was 57 years (70% women) and mean age for CMD patients was 54 years (100% women). The performance of the model was evaluated using repeated stratified cross-validation with 5 folds and 3 repeats, resulting in 15 different 80%/20% train/test splits. Figure 1 shows the distribution of samples belonging to the CMD and AMC groups in a 2-dimensional representation of the feature space. The clear separation of the two groups and the clustering of the AMCs demonstrates the ability of the model to identify patients with CMD. We found that MCG had a mean accuracy of 94.8% (±6.4%), sensitivity of 100% (±0.0%) and specificity of 93.3% (±8.2%) for the detection of CMD using gold standard CFR ≤2 as reference. Conclusion(s) First study to show that MCG can be used with 94.8% accuracy to identify CMD among patients suspicious for INOCA with no exposure to ionization, 90 seconds of scan time and minimal cost. The use of this noninvasive modality to identify CMD warrants further investigation. Funding Acknowledgement Type of funding sources: Private company. Main funding source(s): Genetesis

Chronic recurrent multifocal osteomyelitis. A narrative and pictorial review.

Chronic recurrent and multifocal osteomyelitis (CRMO) is a nonsporadic autoinflammatory disorder. Currently, it is diagnosed based on clinical, radiologic, pathological, and longitudinal data. Numerous aspects should be highlighted due to increased knowledge in imaging and immunology. We emphasize the use of whole-body MRI, which is a non-invasive diagnostic strategy. A literature review was carried out on longitudinal studies. Commonly, the mean age at diagnosis is 11 years, ranging between 3 and 17. The most common sites are the long bone metaphysis, particularly femoral and tibial metaphysis. In addition, the pelvis, spine, clavicle, and mandible may be involved. In long bones, the radiologic appearance can show typical structure, mixed lytic and sclerotic, sclerotic or lytic. It is frequently metaphyseal or juxta-physeal, with hyperostosis or periosteal thickening. The involvement of the vertebral skeleton is often multifocal. Therefore, whole-body MRI is essential in identifying subclinical lesions. CRMO is a polymorphic disorder in which whole-body MRI is beneficial to demonstrate subclinical edema. Vertebral collapse requires long-term monitoring.

A non-invasive ultrasensitive diagnostic approach for COVID-19 infection using salivary label-free SERS fingerprinting and artificial intelligence.

Clinical diagnostics for SARS-CoV-2 infection usually comprises the sampling of throat or nasopharyngeal swabs that are invasive and create patient discomfort. Hence, saliva is attempted as a sample of choice for the management of COVID-19 outbreaks that cripples the global healthcare system. Although limited by the risk of eliciting false-negative and positive results, tedious test procedures, requirement of specialized laboratories, and expensive reagents, nucleic acid-based tests remain the gold standard for COVID-19 diagnostics. However, genetic diversity of the virus due to rapid mutations limits the efficiency of nucleic acid-based tests. Herein, we have demonstrated the simplest screening modality based on label-free surface enhanced Raman scattering (LF-SERS) for scrutinizing the SARS-CoV-2-mediated molecular-level changes of the saliva samples among healthy, COVID-19 infected and COVID-19 recovered subjects. Moreover, our LF-SERS technique enabled to differentiate the three classes of corona virus spike protein derived from SARS-CoV-2, SARS-CoV and MERS-CoV. Raman spectral data was further decoded, segregated and effectively managed with the aid of machine learning algorithms. The classification models built upon biochemical signature-based discrimination method of the COVID-19 condition from the patient saliva ensured high accuracy, specificity, and sensitivity. The trained support vector machine (SVM) classifier achieved a prediction accuracy of 95% and F1-score of 94.73%, and 95.28% for healthy and COVID-19 infected patients respectively. The current approach not only differentiate SARS-CoV-2 infection with healthy controls but also predicted a distinct fingerprint for different stages of patient recovery. Employing portable hand-held Raman spectrophotometer as the instrument and saliva as the sample of choice will guarantee a rapid and non-invasive diagnostic strategy to warrant or assure patient comfort and large-scale population screening for SARS-CoV-2 infection and monitoring the recovery process.

Beneficial effect of ursodeoxycholic acid in patients with acyl-CoA oxidase 2 (ACOX2) deficiency-associated hypertransaminasemia.

A variant (p.Arg225Trp) of peroxisomal acyl-CoA oxidase 2 (ACOX2), involved in bile acid (BA) side-chain shortening, has been associated with unexplained persistent hypertransaminasemia and accumulation of C27-BAs, mainly 3α,7α,12α-trihydroxy-5β-cholestanoic acid (THCA). We aimed to investigate the prevalence of ACOX2 deficiency-associated hypertransaminasemia (ADAH), its response to ursodeoxycholic acid (UDCA), elucidate its pathophysiological mechanism and identify other inborn errors that could cause this alteration. Among 33 patients with unexplained hypertransaminasemia from 11 hospitals and 13 of their relatives, seven individuals with abnormally high C27-BA levels (>50% of total BAs) were identified by high-performance liquid chromatography-mass spectrometry. The p.Arg225Trp variant was found in homozygosity (exon amplification/sequencing) in two patients and three family members. Two additional nonrelated patients were heterozygous carriers of different alleles: c.673C>T (p.Arg225Trp) and c.456_459del (p.Thr154fs). In patients with ADAH, impaired liver expression of ACOX2, but not ACOX3, was found (immunohistochemistry). Treatment with UDCA normalized aminotransferase levels. Incubation of HuH-7 hepatoma cells with THCA, which was efficiently taken up, but not through BA transporters, increased reactive oxygen species production (flow cytometry), endoplasmic reticulum stress biomarkers (GRP78, CHOP, and XBP1-S/XBP1-U ratio), and BAXα expression (reverse transcription followed by quantitative polymerase chain reaction and immunoblot), whereas cell viability was decreased (tetrazolium salt-based cell viability test). THCA-induced cell toxicity was higher than that of major C24-BAs and was not prevented by UDCA. Fourteen predicted ACOX2 variants were generated (site-directed mutagenesis) and expressed in HuH-7 cells. Functional tests to determine their ability to metabolize THCA identified six with the potential to cause ADAH. Dysfunctional ACOX2 has been found in several patients with unexplained hypertransaminasemia. This condition can be accurately identified by a noninvasive diagnostic strategy based on plasma BA profiling and ACOX2 sequencing. Moreover, UDCA treatment can efficiently attenuate liver damage in these patients.