An Ultrasensitive Molecularly Imprinted Point-Of-Care Electrochemical Sensor for Detection of Glial Fibrillary Acidic Protein.

Accurate assessment of neurological disease through monitoring of biomarkers has been made possible using the antibody-based assays. But these assays suffer from expensive development of antibody probes, reliance on complicated equipments, and high maintenance costs. Here, using the novel reduced graphene oxide/polydopamine-molecularly imprinted polymer (rGO/PDA-MIP) as the probe layer, a robust electrochemical sensing platform is demonstrated for the ultrasensitive detection of glial fibrillary acidic protein (GFAP), a biomarker for a range of neurological diseases. A miniaturized integrated circuit readout system is developed to interface with the electrochemical sensor, which empowers it with the potential to be used as a point-of-care (POC) diagnostic tool in primary clinical settings. This innovative platform demonstrated good sensitivity, selectivity, and stability, with imprinting factor evaluated as 2.8. A record low limit-of-detection (LoD) is down to 754.5 ag mL-1, with a wide dynamic range from 1 to 106 fg mL-1. The sensing platform is validated through the analysis of GFAP in clinical plasma samples, yielding a recovery rate range of 81.6-108.8% compared to Single Molecule Array (Simoa). This cost-effective and user-friendly sensing platform holds the potential to be deployed in primary and resource-limited clinical settings for the assessment of neurological diseases.

Annotated image dataset of fire blight symptoms for object detection in orchards.

The monitoring of plant diseases in nurseries, breeding farms and orchards is essential for maintaining plant health. Fire blight (Erwinia amylovora) is still one of the most dangerous diseases in fruit production, as it can spread epidemically and cause enormous economic damage. All measures are therefore aimed at preventing the spread of the pathogen in the orchard and containing an infection at an early stage [1-6]. Efficiency in plant disease control benefits from the development of a digital monitoring system if the spatial and temporal resolution of disease monitoring in orchards can be increased [7]. In this context, a digital disease monitoring system for fire blight based on RGB images was developed for orchards. Between 2021 and 2024, data was collected on nine dates under different weather conditions and with different cameras. The data source locations in Germany were the experimental orchard of the Julius Kühn Institute (JKI), Institute of Plant Protection in Fruit Crops and Viticulture in Dossenheim, the experimental greenhouse of the Julius Kühn Institute for Resistance Research and Stress Tolerance in Quedlinburg and the experimental orchard of the JKI for Breeding Research on Fruit Crops located in Dresden-Pillnitz. The RGB images were taken on different apple genotypes after artificial inoculation with Erwinia amylovora, including cultivars, wild species and progeny from breeding. The presented ERWIAM dataset contains manually labelled RGB images with a size of 1280  × 1280 pixels of fire blight infected shoots, flowers and leaves in different stages of development as well as background images without symptoms. In addition, symptoms of other plant diseases were acquired and integrated into the ERWIAM dataset as a separate class. Each fire blight symptom was annotated with the Computer Vision Annotation Tool (CVAT [8]) using 2-point annotations (bounding boxes) and presented in YOLO 1.1 format (.txt files). The dataset contains a total of 1611 annotated images and 87 background images. This dataset can be used as a resource for researchers and developers working on digital systems for plant disease monitoring.

Measuring air metagenomic diversity in an agricultural ecosystem.

All species shed DNA during life or in death, providing an opportunity to monitor biodiversity via environmental DNA (eDNA). In recent years, combining eDNA, high-throughput sequencing technologies, bioinformatics, and increasingly complete sequence databases has promised a non-invasive and non-destructive environmental monitoring tool. Modern agricultural systems are often large monocultures and so are highly vulnerable to disease outbreaks. Pest and pathogen monitoring in agricultural ecosystems is key for efficient and early disease prevention, lower pesticide use, and better food security. Although the air is rich in biodiversity, it has the lowest DNA concentration of all environmental media and yet is the route for windborne spread of many damaging crop pathogens. Our work suggests that ecosystems can be monitored efficiently using airborne nucleic acid information. Here, we show that the airborne DNA of microbes can be recovered, shotgun sequenced, and taxonomically classified, including down to the species level. We show that by monitoring a field growing key crops we can identify the presence of agriculturally significant pathogens and quantify their changing abundance over a period of 1.5 months, often correlating with weather variables. We add to the evidence that aerial eDNA can be used as a source for biomonitoring in terrestrial ecosystems, specifically highlighting agriculturally relevant species and how pathogen levels correlate with weather conditions. Our ability to detect dynamically changing levels of species and strains highlights the value of airborne eDNA in agriculture, monitoring biodiversity changes, and tracking taxa of interest.

Postmortem Sampling in Piglet Populations: Unveiling Specimens Accuracy for Porcine Reproductive and Respiratory Syndrome Detection.

Specimens collected from dead pigs are a welfare-friendly and cost-effective active surveillance. This study aimed to evaluate the accuracy of different postmortem specimens from dead piglets for disease detection, using PRRSV as an example. Three farrow-to-wean farms undergoing PRRSV elimination were conveniently selected. Samples were collected at approximately 8- and 20-weeks post-outbreak. Postmortem specimens included nasal (NS), oral (OS), and rectal (RS) swabs, tongue-tip fluids (TTF), superficial inguinal lymph nodes (SIL), and intracardiac blood. These were tested individually for PRRSV by RT-PCR. Sensitivity, specificity, negative and positive predictive values, and agreement of postmortem specimens were calculated using intracardiac sera as the gold standard. OS and SIL had the best overall performance, with sensitivities of 94.6-100%, specificities of 83.9-85.1%, and negative predictive values of 97.3-100%. TTF had high sensitivity (92.2%) but low specificity (53.9%) and positive predictive value (48.3%). While challenges in meeting sampling targets due to variable pre-weaning mortality were noted, PRRS was detected in all postmortem specimens. OS and NS showed promising results for disease monitoring, though TTF, despite their sensitivity, had lower specificity, making them less suitable for individual infection assessment but useful for assessing environmental contamination.

Artificial Intelligence- and Physician-Interpreted Stool Image Characteristics Correlate With C-Reactive Protein Among Inpatients With Acute Severe Ulcerative Colitis: A Pilot Study.

Background: Stool characteristics are used as a measure of ulcerative colitis (UC) disease activity, but they have not been validated against objective inflammation. We aimed to determine whether stool characteristics measured by trained artificial intelligence (AI) and physicians correlate with inflammation in UC. Methods: Patients hospitalized with acute severe UC (ASUC) were asked to capture images of all bowel movements using a smartphone application (Dieta®). Validated AI was used to measure five stool characteristics including the Bristol stool scale. Additionally, four physicians scored each image for blood amount, mucus amount, and whether stool was in a toilet or commode. AI measurements and mean physician scores were rank-normalized and correlated with rank-normalized CRP values using mixed linear regression models. Mann-Whitney tests were used to compare median CRP values of images with and without mucus and with and without blood. Results: We analyzed 151 stool images collected from 5 patients admitted with ASUC (mean age 42 years, 40% male). Overall, Bristol stool scale and fragmentation positively correlated with CRP, while stool consistency negatively correlated with CRP. The median CRP of images with mucus was higher than that of images without mucus. Conclusions: Smartphone application AI measurements of Bristol stool scale, stool consistency, and stool fragmentation significantly correlate with CRP values in hospitalized patients with ASUC. Additionally, median CRPs are higher when mucus is seen. Further training of smartphone-based AI algorithms to validate the association of stool characteristics with objective inflammation may yield a novel, noninvasive tool for UC disease monitoring.

Minimal residual disease detection in lymphoma: methods, procedures and clinical significance.

Lymphoma is a highly heterogeneous lymphohematopoietic tumor. As our understanding of the biological and pathological characteristics of lymphoma improves, we are identifying an increasing number of lymphoma subtypes. Genotyping has enhanced our ability to diagnose, treat, and monitor the prognosis of lymphoma. Despite significant improvements in treatment effectiveness, traditional methods for assessing disease response and monitoring prognosis are imperfect, and there is no significant improvement in overall remission rates for lymphoma patients. Minimal Residual Disease (MRD) is often indicative of refractory disease or early relapse. For lymphoma patients, personalized MRD monitoring techniques offer an efficient means to estimate disease remission levels, predict early relapse risk, and assess the effectiveness of new drug regimens. In this review, we delve into the MRD procedures in lymphoma, including sample selection and requirements, detection methods and their limitations and advantages, result interpretation. Besides, we also introduce the clinical applications of MRD detection in lymphoma.

Identifying highly connected sites for risk-based surveillance and control of cucurbit downy mildew in the eastern United States.

Objective: Surveillance is critical for the rapid implementation of control measures for diseases caused by aerially dispersed plant pathogens, but such programs can be resource-intensive, especially for epidemics caused by long-distance dispersed pathogens. The current cucurbit downy mildew platform for monitoring, predicting and communicating the risk of disease spread in the United States is expensive to maintain. In this study, we focused on identifying sites critical for surveillance and treatment in an attempt to reduce disease monitoring costs and determine where control may be applied to mitigate the risk of disease spread. Methods: Static networks were constructed based on the distance between fields, while dynamic networks were constructed based on the distance between fields and wind speed and direction, using disease data collected from 2008 to 2016. Three strategies were used to identify highly connected field sites. First, the probability of pathogen transmission between nodes and the probability of node infection were modeled over a discrete weekly time step within an epidemic year. Second, nodes identified as important were selectively removed from networks and the probability of node infection was recalculated in each epidemic year. Third, the recurring patterns of node infection were analyzed across epidemic years. Results: Static networks exhibited scale-free properties where the node degree followed a power-law distribution. Betweenness centrality was the most useful metric for identifying important nodes within the networks that were associated with disease transmission and prediction. Based on betweenness centrality, field sites in Maryland, North Carolina, Ohio, South Carolina and Virginia were the most central in the disease network across epidemic years. Removing field sites identified as important limited the predicted risk of disease spread based on the dynamic network model. Conclusions: Combining the dynamic network model and centrality metrics facilitated the identification of highly connected fields in the southeastern United States and the mid-Atlantic region. These highly connected sites may be used to inform surveillance and strategies for controlling cucurbit downy mildew in the eastern United States.

Molecular Disease Monitoring in Patients With Relapsed/refractory B-Cell Lymphoma Receiving Anti-CD19 CAR T-Cell Therapy.

BACKGROUND: Chimeric antigen receptor (CAR) T-cell therapy has improved the historically poor outcomes for relapsed and refractory (R/R) large B-cell non-Hodgkin's lymphoma (LBCL). However, nearly 60% of patients will either fail to respond or relapse after CAR T-cell therapy. Currently, PET/CT scans are used to assess response. Cell-free circulating tumor DNA (ctDNA) is released by tumor cells into the peripheral blood and can be measured for minimal residual disease (MRD) assessment. METHODS: In this retrospective, IRB approved pilot study, archived lymphoma tissue and ctDNA from peripheral blood samples on day 0, 14, 28, 56, 90, 180, and 365 after CAR T-cell infusion from 10 patients with R/R NHL were collected for next-generation sequencing (NGS) of clonal variable-diversity-joining (VDJ) rearrangements (Adaptive biotechnologies [Seattle, WA]). Response was assessed by PET/CT on days 90 and 365 and graded according to the Lugano 2014 criteria. The primary endpoint was to determine the feasibility of detecting ctDNA to monitor disease response after anti-CD19 CAR T-cell therapy. The secondary endpoint was to compare the sensitivity/specificity of MRD assessment from ctDNA to PET/CT imaging. RESULTS: Nine out of 10 patients with a trackable sequence [median age 69 (range: 56-76); 55.6% male; median LDH 224], were included in this study. Each received tisagenlecleucel (tisa-cel) CAR T-cell therapy after median 2 prior treatments (range: 2-4). 7/9 patients had R/R diffuse large B-cell lymphoma (DLBCL), and 2/9 had transformed follicular lymphoma. At a median follow up of 12.7 months (range: 1.5-30 months), 4 patients were alive. By day 90, 3 patients (33.3%) achieved a radiographic complete response (CR) whilst 6 patients (66.6%) had progressive disease (PD). Detectable MRD on day 14 or day 28 had 83% sensitivity and 100% specificity for radiographic progression at any time before 1 year. For patients with PD, the median (interquartile range) MRD at day 0, 14, and 28 were 17.31 (1.01, 96.84), 9.12 (0.30, 18.8), and 23.77 (8.01, 137.53) copies per milliliter (mL), respectively. For patients with detectable MRD at day 28, mOS and mPFS were 6.7 and 1.3 months, respectively. CONCLUSION: Monitoring MRD was a sensitive and specific method to detect poor response to tisa-cel. Additional studies evaluating MRD more frequently and with different products are warranted.

Laboratory validation and clinical utility of next-generation sequencing-based IGH/TCR clonality testing for the monitoring of measurable residual disease in acute lymphoblastic leukaemia: real-world experience at Austin Pathology.

Measurable residual disease (MRD) testing is an essential aspect of disease prognostication in acute lymphoblastic leukaemia (ALL) and informs clinical decisions. The depth of MRD clearance is highly relevant and requires assays with sufficient sensitivity. Austin Pathology is one of the few laboratories in Australia currently utilising a fully validated and National Association of Testing Authorities (NATA)-accredited ultrasensitive next-generation sequencing (NGS) platform for MRD monitoring in ALL. This technology is based on the detection of clonal rearrangement of immunoglobulin and T cell receptor genes in leukaemic cells, and is capable of achieving a limit of detection at least one to two logs below that of multiparametric flow cytometry (MFC). In this retrospective analysis, we report a clonotype detection rate of up to 85.7% at diagnosis, and a concordance rate of 78.7% in MRD results between NGS and MFC. Of the discordant samples, nearly all were NGS+/MFC-, highlighting the superior sensitivity of NGS. The enhanced sensitivity is clinically relevant, as discordant MRD results often heralded fulminant relapse, and therefore offer clinicians additional lead time and a window of opportunity to initiate pre-emptive therapy. Notwithstanding a small and heterogeneous cohort, our real-world survival data indicate an intermediate relapse risk for NGS+/MFC- patients. In light of recent approval of Medicare rebatable ALL MRD testing, we discuss how NGS can complement other techniques such as MFC in personalising management strategies. We recommend routine clonality testing by NGS at diagnosis and use a multi-modality approach for subsequent MRD monitoring.

Modern Management of Pregnancy in Systemic Lupus Erythematosus: From Prenatal Counseling to Postpartum Support.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that predominantly affects women of childbearing age. Pregnancy in SLE patients poses unique challenges due to the potential impact on maternal and fetal outcomes. We provide an overview of the management of SLE during pregnancy, including preconception risk stratification and counseling, treatment, and disease activity monitoring. These assessments are critical to minimize maternal and fetal adverse events in pregnant patients with SLE. Disease flares, preeclampsia, antiphospholipid syndrome complications, and maternal mortality are the major risks for a woman with SLE during gestation. Timely treatment of SLE relapse, differentiation of preeclampsia from lupus nephritis, and tailored management for antiphospholipid syndrome are essential for a successful pregnancy. Fetal outcomes include neonatal lupus (NL), preterm birth, cesarean delivery, fetal growth restriction (FGR), and small-for-gestational-age (SGA) infants. We focused on NL, linked to maternal anti-Ro/SS-A and anti-La/SS-B antibodies, which can lead to various manifestations, particularly cardiac abnormalities, in newborns. While there is a common consensus regarding the preventive effect of hydroxychloroquine, the role of echocardiographic monitoring and fluorinated steroid treatment is still debated. Finally, close postpartum monitoring and counseling for subsequent pregnancies are crucial aspects of care.

Wearable biosensors in cardiovascular disease.

This review provides a comprehensive overview of the latest advancements in wearable biosensors, emphasizing their applications in cardiovascular disease monitoring. Initially, the key sensing signals and biomarkers crucial for cardiovascular health, such as electrocardiogram, phonocardiography, pulse wave velocity, blood pressure, and specific biomarkers, are highlighted. Following this, advanced sensing techniques for cardiovascular disease monitoring are examined, including wearable electrophysiology devices, optical fibers, electrochemical sensors, and implantable cardiac devices. The review also delves into hydrogel-based wearable electrochemical biosensors, which detect biomarkers in sweat, interstitial fluids, saliva, and tears. Further attention is given to flexible electronics-based biosensors, including resistive, capacitive, and piezoelectric force sensors, as well as resistive and pyroelectric temperature sensors, flexible biochemical sensors, and sensor arrays. Moreover, the discussion extends to polymer-based wearable sensors, focusing on innovations in contact lens, textile-type, patch-type, and tattoo-type sensors. Finally, the review addresses the challenges associated with recent wearable biosensing technologies and explores future perspectives, highlighting potential groundbreaking avenues for transforming wearable sensing devices into advanced diagnostic tools with multifunctional capabilities for cardiovascular disease monitoring and other healthcare applications.

Factors Affecting Usage of a Digital Asthma Monitoring Application by Old-Age Asthmatics Living in Inner Central Portugal.

Purpose: To analyse factors affecting the ability to use the digital asthma monitoring application Mask-Air® in old-age individuals living in inland Portugal. Patients and Methods: In this observational study, patients with medically confirmed asthma who agreed to participate were interviewed and subdivided into Non-users Group: those who could not use the application and Users Group: those who could. Sociodemographic and psychological data, comorbidities, and asthma status were compared between groups. Assessment of reasons for refusal was based on a 6-item questionnaire. Results: Among the 72 sequentially recruited patients (mean age±SD 73.26±5.43 yrs; 61 women; 11 men), 44 (61.1%; mean age±SD 74.64±5.68 yrs; 38 women; 6 men)) were included in Non-users Group and 28 (38.9%; mean age±SD 71.11±4.26 yrs; 23 women; 5 men) in Users Group. Non-users Group patients were significantly older, had lower socioeconomic level, and more frequently had severe asthma (25% vs 3.6%; Odds ratio=0.08 (95% CI=0.01-0.81; p=0.033)) and diabetes (32.6% vs 7.4%; Odds ratio=0.17 (95% CI=0.03-0.80; p=0.025)) than Users Group. The main reasons for not using the App were "Lack of required hardware" (n=35) and "Digital illiteracy" (n=26), but lack of interest to use the App among those who had conditions to use it was uncommon. Conclusion: Most old-age asthmatics living in Beira Interior either lack a smartphone or digital skills, which are significant obstacles to implementing app-based monitoring studies.

This study was done to see whether it was possible to use a mobile phone application (App) to help old-age asthmatics living in inner Central Portugal better monitor and self-manage their disease. The researchers interviewed a group of 72 patients with proven asthma who agreed to participate in the study. This group was subdivided into two subgroups: Non-users Group (44 patients) included those who could not use the App because they did not have a smartphone; Users Group (28 patients) included those who had all the conditions to use the App. Patients were helped to download the App (called MASK-Air), were given a thorough explanation about it, and about how it should be used on a daily basis to monitor their asthma symptoms. The researchers found that patients in Non-users Group were significantly older, had worse socioeconomic conditions, and more often had severe asthma and diabetes. They also discovered that the main reasons for not using the App were lack of a smartphone and not knowing how to use a smartphone. These results show that lacking a smartphone and not knowing how to use digital tools are frequent situations in old-age asthmatics living in inner Central Portugal, and these may be obstacles for patients in monitoring their own asthma symptoms.

Biomarkers in inflammatory bowel disease: a practical guide.

Inflammatory bowel disease (IBD), comprising ulcerative colitis (UC) and Crohn's disease (CD), is a costly condition in terms of morbidity and healthcare utilization, with an increasing prevalence now approaching 1% in the Western world. Endoscopic assessment of IBD remains the gold standard for diagnosis, evaluation of treatment response and determination of post-operative recurrence, but is expensive and invasive. Biomarkers can facilitate non-invasive disease assessment, with C-reactive protein and faecal calprotectin as the most widely available biomarkers in current clinical practice. This narrative review summarizes the evidence for their use in both UC and CD and offers practical guidance for healthcare providers taking into account the limitations of biomarker interpretation. We present evidence for the future use of novel biomarkers in IBD and discuss how biomarker discovery could deliver the goal of precision medicine in IBD.

Biomarkers in inflammatory bowel disease: a practical guide Inflammatory bowel disease (IBD) is a term used to describe two conditions, ulcerative colitis (UC) and Crohn's disease (CD). These two diseases cause inflammation of the bowel, which can lead to diarrhoea, abdominal pain and bleeding from the back passage. The best way of assessing how active a patient's IBD is, is by performing a camera test called a colonoscopy. However, having a colonoscopy is inconvenient, comes with some risks to the patient, and uses a lot of healthcare resources. 'Biomarkers' are proteins detectable in body fluids (such as blood, poo and urine) which can give information to medical staff about how active a patient's disease is, without the need for colonoscopy. In this article, we give guidance about how best to use these tests, and when they might not be so useful. We also discuss new biomarkers and ways in which they could be used in the future to predict which treatments patients might respond to best.

Investigation of the pathogen-specific antibody response in periprosthetic joint infection.

PURPOSE: Periprosthetic joint infections (PJIs) are a very demanding complication of arthroplasty. Diagnosis of PJI and pathogen identification pose considerable challenges in clinical practice. We hypothesized that the pathogen-specific immune response to PJI reflects the infection process, provides clinically relevant information on disease course, and has the potential to further optimize antimicrobial therapy. METHODS: We conducted a prospective matched cohort pilot study with 13 patients undergoing two-stage septic revision arthroplasty (PJI patients) between 06/2020 and 06/2021, as well as 11 control patients undergoing one-stage aseptic revision arthroplasty (Non-PJI patients). Pre-, intra- and postoperative serum samples were collected at standardized time points. We developed a custom Luminex®-based quantitative bead-based suspension array (Infection Array; IA), and used it for simultaneous measurement of antibody specificities against 32 pathogens commonly associated with PJI in 267 serum samples. RESULTS: The IA was able to trace the dynamics of the pathogen-specific humoral immune response in all patients against PJI-related pathogens, prominently coagulase-negative staphylococci and streptococci. Pathogen-specific serum antibody titers declined in 62% of PJI patients over the course of treatment, while no changes in antibody titers were observed in 82% of Non-PJI patients during this study. Our serological data strongly suggested that antibody signatures reflect an immune response to microbial invasion. CONCLUSION: Our results provide insights into the pathophysiology of PJI and information on the individual disease courses. The IA is therefore a promising and novel serological tool of high resolution for monitoring the immunoproteomic footprints of infectious pathogens in the course of PJI.

Echocardiographic monitoring of myocardial function in a female patient with right heart Loeffler endocarditis at thrombotic stage after Epstein-Barr-virus infection.

BACKGROUND: Transthoracic echocardiography is usually the first non-invasive imaging modality for the detection of Loeffler endocarditis at thrombotic stage. In the recent decade 3D echocardiography and deformation imaging already proved as a helpful tool for the monitoring of left and right ventricular heart disease. CASE PRESENTATION: The present case illustrates the diagnostic role of 3D echocardiography and deformation imaging in the acute stage of right sided Loeffler endocarditis in a 70-year-old Western European (German) woman. This case proves that myocardial involvement due to inflammation can be detected at subclinical stages by speckle tracking echocardiography. Acute deterioration of left and right ventricular function and the early response to prednisolone therapy can objectively be monitored. In addition, alterations of effective stroke volume can quantitatively be assessed by 3D right ventricular volumetry with exclusion of thrombus formation in the volume measurements. CONCLUSION: This case underlines the importance of 3D echocardiography and deformation imaging as a helpful diagnostic tool in disease management in the acute phase of Loeffler endocarditis at thrombotic stage.

Transnasal Endoscopy Acquires Esophageal Biopsies Adequate for Comprehensive Pathology Evaluation in Patients With Eosinophilic Esophagitis.

BACKGROUND: Transnasal endoscopy (TNE) does not require general anesthesia, an attractive characteristic for monitoring eosinophilic esophagitis (EoE). We evaluated the adequacy of TNE-obtained esophageal biopsies using the EoE Histology Scoring System (EoEHSS). METHODS: The Cincinnati Center for Eosinophilic Disorders database was searched for esophageal biopsies obtained by the same endoscopist, using either TNE or conventional endoscopy (CE). Whole-slide biopsy images were evaluated. The Mann-Whitney test was used for median (interquartile range) values and Fisher exact test for categorical variables. P ≤ .05 was considered significant. RESULTS: Median age (P = .82) or height (P = .83) did not differ between TNE (n = 17) and CE (n = 17) groups. Although median largest piece size (mm2) differed between the groups (TNE: 0.59 (0.45, 0.86), CE: 2.24 (1.09, 2.82), P < .001), all 8 EoEHSS features were evaluated in each group; only 1 feature (lamina propria fibrosis) was missing in both groups (TNE: 19/34, CE: 11/34, P = .09). The median peak eosinophil count/high-power field differed (TNE: 3 (0, 29), CE: 16 (1, 66), P = .03), but overall grade (TNE: 0.17 (0.10, 0.29), CE: 0.22 (0.14, 0.46), P = .12), stage (TNE: 0.14 (0.10, 0.24), CE: 0.20 (0.10, 0.43), P = .15), and non-eosinophil-related individual EoEHSS scores did not differ. CONCLUSIONS: TNE- and CE-obtained esophageal biopsies are similarly sufficient for evaluation of key pathological features in EoE.

Utility of the Endoscopic Healing Index in Identifying Active Inflammation in Patients with Crohn's Disease: Real World Data from a Tertiary Center.

BACKGROUND: The Endoscopic Healing Index (EHI) analyzes biomarkers in a patient's peripheral blood to assess mucosal healing. We aimed to characterize the effectiveness of the EHI as a predictor of disease activity in a real world clinical setting. METHODS: This retrospective study looked at patients treated and followed up at the University of Chicago Medicine IBD center who had EHI tests done as part of routine clinical care. The results of the EHI were compared with radiological imaging or endoscopy performed within 3 months of the EHI in order to determine accuracy at diagnosing active inflammation. RESULTS: Fifty-five patients with CD and with an available EHI were included in this study. Four (50%) patients with an EHI of < 20 (n = 8) had evidence of objective inflammation. A cutoff of ≤ 20 had a sensitivity of 89% and specificity of 23.5% for predicting no evidence of any objective inflammation with an AUROC of 0.69. This score had a negative predictive value (NPV) of 50% and positive predictive value (PPV) of 72.3%. A cutoff EHI of 30 tended to classify patients as either having objective evidence of inflammation or not more often than FCAL (Correctly classifying inflammation: 89% vs 64%, respectively; p = 0.32). CONCLUSION: In this real world analysis, the EHI showed poor predictive value for the absence of active inflammation as assessed by imaging or endoscopy, has limited utility in confirming deep remission and should be used with another objective modality.

Turning the tide in aggressive lymphoma: liquid biopsy for risk-adapted treatment strategies.

Diffuse large B cell lymphoma (DLBCL) exhibits significant biological and clinical heterogeneity that presents challenges for risk stratification and disease surveillance. Existing tools for risk stratification, including the international prognostic index (IPI), tissue molecular analyses, and imaging, have limited accuracy in predicting outcomes. The therapeutic landscape for aggressive lymphoma is rapidly evolving, and there is a pressing need to identify patients at risk of refractory or relapsed (R/R) disease in the context of personalized therapy. Liquid biopsy, a minimally invasive method for cancer signal detection, has been explored to address these challenges. We review advances in liquid biopsy strategies focusing on circulating nucleic acids in DLBCL patients and highlight their clinical potential. We also provide recommendations for biomarker-guided trials to support risk-adapted treatment modalities.

New Biomarkers for Systemic Necrotizing Vasculitides.

Systemic necrotising vasculitides (SNVs) pose significant challenges due to their diverse clinical manifestations and variable outcomes. Therefore, identifying reliable biomarkers holds promise for improving precision medicine in SNVs. This review explores emerging biomarkers aiming to enhance diagnostic accuracy, prognostic assessment, and disease monitoring. We discuss recent advances in immunological biomarkers, inflammatory indicators, and other parameters that exhibit potential diagnostic and prognostic utility. A comprehensive understanding of these biomarkers may facilitate earlier and more accurate SNV detection, aiding in timely intervention and personalized treatment strategies. Furthermore, we highlight the evolving landscape of disease monitoring through innovative biomarkers, shedding light on their dynamic roles in reflecting disease activity and treatment response. Integrating these novel biomarkers into clinical practice can revolutionize the management of SNVs, ultimately improving patient outcomes and quality of life.