Label-Free and Ultrasensitive Detection of Cartilage Acidic Protein 1 in Osteoarthritis Using a Single-Walled Carbon Nanotube Field-Effect Transistor Biosensor.

Osteoarthritis (OA), a prevalent degenerative joint disease, significantly affects the well-being of afflicted individuals and compromises the standard functionality of human joints. The emerging biomarker, Cartilage acidic protein 1 (CRTAC1), intricately associates with OA initiation and serves as a prognostic indicator for the trajectory toward joint replacement. However, existing diagnostic methods for CRTAC1 are hampered by the limited abundance, thus restricting the precision and specificity. Herein, a novel approach utilizing a single-walled carbon nanotube field-effect transistor (SWCNTs FET) biosensor is reported for the direct label-free detection of CRTAC1. High-purity semiconducting carbon nanotube films, functionalized with antibodies of CRTAC1, provide excellent electrical and sensing properties. The SWCNTs FET biosensor exhibits high sensitivity, notable reproducibility, and a wide linear detection range (1 fg/mL to 100 ng/mL) for CRTAC1 with a theoretical limit of detection (LOD) of 0.2 fg/mL. Moreover, the SWCNTs FET biosensor is capable of directly detecting human serum samples, showing excellent sensing performance in differentiating clinical samples from OA patients and healthy populations. Comparative analysis with traditional enzyme-linked immunosorbent assay (ELISA) reveals that the proposed biosensor demonstrates faster detection speeds, higher sensitivity/accuracy, and lower errors, indicating high potential for the early OA diagnosis. Furthermore, the SWCNTs FET biosensor has good scalability for the combined diagnosis and measurement of multiple disease markers, thereby significantly expanding the application of SWCNTs FETs in biosensing and clinical diagnostics.

Variable and Large Losses of Diagnostic Biomarkers After Simulated Cosmic Radiation Exposure in Clay- and Carbonate-Rich Mars Analog Samples.

Mars has been exposed to ionizing radiation for several billion years, and as part of the search for life on the Red Planet, it is crucial to understand the impact of radiation on biosignature preservation. Several NASA and ESA missions are looking for evidence of ancient life in samples collected at depths shallow enough that they have been impacted by galactic cosmic rays (GCRs). In this study, we exposed a diverse set of Mars analog samples to 0.9 Megagray (MGy) of gamma radiation to mimic 15 million years of exposure on the Martian surface. We measured no significant impact of GCRs on the total organic carbon (TOC) and bulk stable C isotopes in samples with initial TOC concentration > 0.1 wt. %; however, diagnostic molecular biosignatures presented a wide range of degradation that didn't correlate to factors like mineralogy, TOC, water content, and surface area. Exposure dating suggests that the surface of Gale crater has been irradiated at more than five times our dose, yet using this relatively low dose and "best-case scenario" geologically recalcitrant biomarkers, large and variable losses were nevertheless evident. Our results empasize the importance of selecting sampling sites at depth or recently exposed at the Martian surface.

Serum and salivary interleukin-1ß level in oral precancer: An observational study.

BACKGROUND AND AIM: Precancer biomarkers help in early detection and management of oral potentially malignant disorders (OPMDs). Interleukin-1ß (IL-1ß), a biomarker, is known to be altered in oral submucous fibrosis (OSMF) and oral leukoplakia (OL). Therefore, we evaluated and compared the serum and salivary IL-1ß levels in patients with OSMF/oral leukoplakia and in gender- and age-matched healthy individuals. MATERIALS AND METHODS: An in vivo, prospective, observational study was conducted on 40 subjects. Subjects were divided into two groups with 20 individuals in each group, that is, Group I: OSMF/oral leukoplakia and Group II: control group. Salivary and serum IL-1ß levels were quantitatively estimated using enzyme-linked immunosorbent assay (ELISA). The statistical tests used were unpaired t-test and Chi-square test. RESULTS: The serum IL-1ß levels were significantly (P 0.001) lesser in Group I in comparison to Group II. The salivary IL-1ß levels remained insignificant between both the groups. However, in both the groups, the salivary IL-1ß levels were significantly higher compared to the serum IL-1ß levels. CONCLUSION: We found that the serum IL-1ß level can be considered as a prospective biomarker for dysplasia, whereas salivary IL-1ß alone needs more elaborated studies to account for its application as a potential biomarker in OPMD.

Integrated clustering of multiple immune marker trajectories reveals different immunotypes in severely injured patients.

BACKGROUND: The immune response of critically ill patients, such as those with sepsis, severe trauma, or major surgery, is heterogeneous and dynamic, but its characterization and impact on outcomes are poorly understood. Until now, the primary challenge in advancing our understanding of the disease has been to concurrently address both multiparametric and temporal aspects. METHODS: We used a clustering method to identify distinct groups of patients, based on various immune marker trajectories during the first week after admission to ICU. In 339 severely injured patients, we initially longitudinally clustered common biomarkers (both soluble and cellular parameters), whose variations are well-established during the immunosuppressive phase of sepsis. We then applied this multi-trajectory clustering using markers composed of whole blood immune-related mRNA. RESULTS: We found that both sets of markers revealed two immunotypes, one of which was associated with worse outcomes, such as increased risk of hospital-acquired infection and mortality, and prolonged hospital stays. This immunotype showed signs of both hyperinflammation and immunosuppression, which persisted over time. CONCLUSION: Our study suggest that the immune system of critically ill patients can be characterized by two distinct longitudinal immunotypes, one of which included patients with a persistently dysregulated and impaired immune response. This work confirms the relevance of such methodology to stratify patients and pave the way for further studies using markers indicative of potential immunomodulatory drug targets.

Surrogate measures of first-phase insulin secretion versus reference methods intravenous glucose tolerance test and hyperglycemic clamp: a systematic review and meta-analyses.

INTRODUCTION: In this systematic review, we investigated the diagnostic accuracy of surrogate measures of insulin secretion based on fasting samples and the oral glucose tolerance test (OGTT). The first phase of insulin secretion was calculated using two gold standard methods; the hyperglycemic clamp (HGC) test and intravenous glucose tolerance test (IVGTT). RESEARCH DESIGN AND METHODS: We conducted searches in the PubMed, Cochrane Central, and Web of Science databases, the last of which was conducted at the end of June 2021. Studies were included that measured first-phase insulin secretion in adults using both a gold-standard reference method (either HGC or IVGTT) and one or more surrogate measures from either fasting samples, OGTT or a meal-tolerance test. QUADAS-2, a revised tool for the quality assessment of diagnostic accuracy studies, was used for quality assessment. Random-effects meta-analyses were performed to examine the correlation between first-phase measured with gold standard and surrogate methods. RESULTS: A total of 33 articles, encompassing 5362 individuals with normal glucose tolerance, pre-diabetes or type 2 diabetes, were included in our systematic review. Homeostatic model assessment (HOMA)-beta and Insulinogenic Index 30 (IGI(30)) were the surrogate measures validated in the largest number of studies (17 and 13, respectively). HOMA-beta's pooled correlation to the reference methods was 0.48 (95% CI 0.40 to 0.56) The pooled correlation of IGI to the reference methods was 0.61 (95% CI 0.54 to 0.68). The surrogate measures with the highest correlation to the reference methods were Kadowaki (0.67 (95% CI 0.61 to 0.73)) and Stumvoll's first-phase secretion (0.65 (95% CI 0.58 to 0.71)), both calculated from an OGTT. CONCLUSIONS: Surrogate measures from the first 30 min of an OGTT capture the first phase of insulin secretion and are a good choice for epidemiological studies. HOMA-beta has a moderate correlation to the reference methods but is not a measure of the first phase specifically. PROSPERO REGISTRATION NUMBER: The meta-analysis was registered at PROSPERO (Id: CRD42020169064) before inclusion started.

Correlation of amniotic fluid inflammatory markers with preterm birth: a meta-analysis.

BACKGROUND: The relationship between amniotic fluid inflammatory biomarkers and preterm birth in second- or third-trimester pregnancy has been a focus, and understanding the correlation between these markers and preterm birth is important for early identification and intervention in preterm birth. The aim of this study was to explore potential inflammatory biomarkers in second- or third-trimester pregnancy amniotic fluid associated with preterm birth. METHODS: On November 30, 2023, we searched literature involved the influence of second- or third-trimester pregnancy amniotic fluid inflammatory biomarkers on preterm birth through PubMed, Web of Science, Embase, Scope, CNKI, WanFang, VIP and China Biomedical Databases. The search languages were Chinese and English. Included outcomes indexes were combined utility analysis via R software. RESULTS: A total of 11 articles were included in the combined utility analysis. This combined analysis revealed significant differences in several inflammatory biomarkers in amniotic fluid between the two groups (MD = 6.87, 95%CI: 0.26 - 13.47, P < 0.01); the difference in amniotic fluid IL-6 between the two groups (MD = 5.73, 95%CI: 3.13-8.32, P < 0.01); the difference in amniotic fluid IL-10 between the two groups (MD = 0.11, 95%CI: -3.26-3.48, P < 0.01); the difference in amniotic fluid CRP between the two groups (MD = 21.34, 95%CI: 11.69-30.89, P < 0.01); the difference in amniotic fluid MCP-1 between the two groups (MD = 312.14, 95%CI: 211.34-412.97, P < 0.01); the difference in the amniotic fluid MMP-9 between the two groups (MD = 0.86, 95%CI: -0.10-1.82, P < 0.01); and the difference in TNF-α in amniotic fluid between the two groups (MD = 22.78, 95%CI: -5.05-50.61, P < 0.01). CONCLUSIONS: The inflammatory biomarkers IL-1ß, IL-6, IL-10, CRP, TNFα, MCP-1 and MMP-9 in the amniotic fluid of patients in the second- or third-trimester pregnancy were all correlated with preterm birth.

The premature foetus has many serious complications in the near and long term because of the immature organs, which is related to the long-term incidence of cerebral palsy, developmental delay and retinopathy of prematurity, which is the main cause of perinatal foetal death. Preterm birth cases are accompanied by infection of pathogenic microorganisms in amniotic cavity, which then leads to inflammatory reaction in amniotic cavity. However, research on the correlation between inflammatory markers and preterm birth has shown certain complexity and differences. The results of this meta-analysis show that the inflammatory biomarkers interleukin-1 beta (IL-1ß), interleukin-6 (IL-6) and interleukin-10 (IL-10), C-reactive protein (CRP), tumour necrosis factor-alpha (TNF-α), monocyte chemoattractant protein-1 (MCP-1) and matrix metalloproteinase-9 (MMP-9) in amniotic fluid of patients in the second- or third-trimester pregnancy are significant between the preterm birth group and the control group, and the expression level of inflammatory factors in amniotic fluid of patients in the preterm birth group is elevated, thus suggesting that these inflammatory factors may be able to predict preterm birth.

Multi-omics analysis reveals drivers of loss of ß-cell function after newly diagnosed autoimmune type 1 diabetes: An INNODIA multicenter study.

AIMS: Heterogeneity in the rate of ß-cell loss in newly diagnosed type 1 diabetes patients is poorly understood and creates a barrier to designing and interpreting disease-modifying clinical trials. Integrative analyses of baseline multi-omics data obtained after the diagnosis of type 1 diabetes may provide mechanistic insight into the diverse rates of disease progression after type 1 diabetes diagnosis. METHODS: We collected samples in a pan-European consortium that enabled the concerted analysis of five different omics modalities in data from 97 newly diagnosed patients. In this study, we used Multi-Omics Factor Analysis to identify molecular signatures correlating with post-diagnosis decline in ß-cell mass measured as fasting C-peptide. RESULTS: Two molecular signatures were significantly correlated with fasting C-peptide levels. One signature showed a correlation to neutrophil degranulation, cytokine signalling, lymphoid and non-lymphoid cell interactions and G-protein coupled receptor signalling events that were inversely associated with a rapid decline in ß-cell function. The second signature was related to translation and viral infection was inversely associated with change in ß-cell function. In addition, the immunomics data revealed a Natural Killer cell signature associated with rapid ß-cell decline. CONCLUSIONS: Features that differ between individuals with slow and rapid decline in ß-cell mass could be valuable in staging and prediction of the rate of disease progression and thus enable smarter (shorter and smaller) trial designs for disease modifying therapies as well as offering biomarkers of therapeutic effect.

Exploration of Stress and Inflammatory Biomarkers Among Non-Hispanic Black and Hispanic Cancer Survivors.

OBJECTIVES: To evaluate associations among social determinants of health (SDOH), stress, interleukin-6 (IL-6), and quality of life among non-Hispanic Black and Hispanic cancer survivors. SAMPLE & SETTING: Individuals who had completed cancer treatment and did not identify as White (N = 46) were recruited through community partnerships in western Massachusetts and a state cancer registry. METHODS & VARIABLES: This descriptive cross-sectional study used questionnaires and morning salivary samples to collect data between June 2022 and September 2023. RESULTS: Most participants were breast cancer survivors, were female, identified as African American or Black, and reported moderate levels of stress and low physical activity. Cortisol levels were higher among African American or Black participants, those with lower body mass index, and those with less consumption of fruit and vegetables. Higher symptom experience was associated with higher IL-6 levels. No associations were identified between IL-6 and cortisol or perceived stress and cortisol levels. IMPLICATIONS FOR NURSING: Incorporating SDOH in self-reported outcomes, including health behaviors and associated biologic indicators, can facilitate early identification and interventions to improve symptom experience and health outcomes of cancer survivors.

Sedimentary biomarkers and bone specimens reveal a history of prehistoric occupation on Somerset Island (Arctic Canada).

Archaeological studies of pre-historic Arctic cultures are often limited to artefacts and architecture; such records may be incomplete and often do not provide a continuous record of past occupation. Here, we used lake sediment archives to supplement archaeological evidence to explore the history of Thule and Dorset populations on Somerset Island, Nunavut (Canada). We examined biomarkers in dated sediment cores from two ponds adjacent to abandoned Thule settlements (PaJs-3 and PaJs-13) and compared these to sediment cores from two ponds without past human occupation. Coprostanol and epicoprostanol, δ15N measurements, sedimentary chlorophyll a and the ratio of diatom valves to chrysophyte cysts were elevated in the dated sediment profiles at both sites during Thule and Dorset occupations. Periods of pronounced human impact during the Thule occupation of the site were corroborated by 14C-dated caribou bones found at both sites that identified intense caribou hunting between ca 1185 and 1510 CE. Notably, these sediment core data show evidence of the Dorset occupation from ca 200 to 500 CE at sites where archaeological evidence was heretofore lacking. We highlight the utility of lake sediments in assisting archaeological studies to better establish the timings, peak occupations and even lifestyle practices of the Dorset and Thule Arctic peoples.

Lipid biomarker profile of the Permian organic-rich shales (Irati Formation) in the northernmost of Parana Basin, Brazil.

The Irati Formation (Paraná Basin) is a mixed carbonate and organic-rich shale sequence intruded by Jurassic-Cretaceous basic rocks, featuring Brazil's most important oil shale deposits with different maturity levels. For the first time, the distribution of oil shale biomarkers from an outcrop section (quarry) of the Irati Formation in the northernmost Paraná Basin was analyzed by GC-MS and GC-MS/MS to determine the thermal evolution, organic matter origin and the depositional paleoenvironment. The organic-rich shale at the northernmost border of the basin has high similarity with the central and southernmost areas, indicating a primary control able to induce cyclic sedimentation in a broad (106 km2) and restricted environment. PCA and HCA analysis of bulk and molecular parameters showed changes in the organic matter composition and paleoenvironmental conditions throughout the stratigraphic column. Nonetheless, there are significant differences compared to the central-eastern and southern areas of the basin. Contrasting with the southern region, the north, predominates biphytane, low and medium gammacerane index. Pr/n-C17, Ph/n-C18, HI and OI values suggest type II/III kerogen from marine organic matter with freshwater input. Among the steranes, those of stereochemistry ααα 20R predominate over ααα 20S, and the presence of ßTm indicates the shales are less thermally evolved.

Sample size calculation for comparing two ROC curves.

Biomarkers are key components of personalized medicine. In this paper, we consider biomarkers taking continuous values that are associated with disease status, called case and control. The performance of such a biomarker is evaluated by the area under the curve (AUC) of its receiver operating characteristic curve. Oftentimes, two biomarkers are collected from each subject to test if one has a larger AUC than the other. We propose a simple non-parametric statistical test for comparing the performance of two biomarkers. We also present a simple sample size calculation method for this test statistic. Our sample size formula requires specification of AUC values (or the standardized effect size of each biomarker between cases and controls together with the correlation coefficient between two biomarkers), prevalence of cases in the study population, type I error rate, and power. Through simulations, we show that the testing on two biomarkers controls type I error rate accurately and the proposed sample size closely maintains specified statistical power.

Nonparametric receiver operating characteristic curve analysis with an imperfect gold standard.

This article addresses the challenge of estimating receiver operating characteristic (ROC) curves and the areas under these curves (AUC) in the context of an imperfect gold standard, a common issue in diagnostic accuracy studies. We delve into the nonparametric identification and estimation of ROC curves and AUCs when the reference standard for disease status is prone to error. Our approach hinges on the known or estimable accuracy of this imperfect reference standard and the conditional independent assumption, under which we demonstrate the identifiability of ROC curves and propose a nonparametric estimation method. In cases where the accuracy of the imperfect reference standard remains unknown, we establish that while ROC curves are unidentifiable, the sign of the difference between two AUCs is identifiable. This insight leads us to develop a hypothesis-testing method for assessing the relative superiority of AUCs. Compared to the existing methods, the proposed methods are nonparametric so that they do not rely on the parametric model assumptions. In addition, they are applicable to both the ROC/AUC analysis of continuous biomarkers and the AUC analysis of ordinal biomarkers. Our theoretical results and simulation studies validate the proposed methods, which we further illustrate through application in two real-world diagnostic studies.

Efficacy and Accuracy of Diagnosing Septic Arthritis: How Effective are Current Methods for Timely Diagnosis of Septic Arthritis?

The diagnosis of septic arthritis requires a reliance on ancillary tests, including synovial fluid white blood cell count (jWBC), percentage of polymorphonuclear leukocytes (%PMN), erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP). This study evaluated these tests to determine their diagnostic utility in suspected septic arthritis. A retrospective chart review was performed on patients admitted to an urban hospital who underwent arthrocentesis. The authors evaluated the jWBC, %PMN, ESR, and CRP with receiver operating characteristic (ROC) curve analyses. Two hundred sixty-five patients met inclusion criteria. Sixty-three had a culture-positive aspirate. ROC curve analysis resulted in an area under the curve (AUC) of 0.80 for jWBC with cutoff point of 22,563 cells/mm3 and an AUC of 0.71 for %PMN with cutoff point of 90.5%. CRP and ESR had AUC values of 0.62 and 0.61, respectively. The culture-positive cohort had higher elevations in all assessed diagnostic tests. However, AUC data for ESR and CRP showed little diagnostic utility. Additionally, sensitivities and specificities of jWBC and %PMN were too low. Associated cutoff points would result in excessive unnecessary operative intervention. Further studies should incorporate synovial fluid biomarkers into the workup of a suspected septic joint. (Journal of Surgical Orthopaedic Advances 33(2):108-111, 2024).

Weakly ionized gold nanoparticles amplify immunoassays for ultrasensitive point-of-care sensors.

Gold nanoparticle-based lateral flow immunoassays (AuNP LFIAs) are widely used point-of-care (POC) sensors for in vitro diagnostics. However, the sensitivity limitation of conventional AuNP LFIAs impedes the detection of trace biomarkers. Several studies have explored the size and shape factors of AuNPs and derivative nanohybrids, showing limited improvements or enhanced sensitivity at the cost of convenience and affordability. Here, we investigated surface chemistry on the sensitivity of AuNP LFIAs. By modifying surface ligands, a surface chemistry strategy involving weakly ionized AuNPs enables ultrasensitive naked-eye LFIAs (~100-fold enhanced sensitivity). We demonstrated how this surface chemistry-amplified immunoassay approach modulates nanointerfacial bindings to promote antibody adsorption and higher activity of adsorbed antibodies. This surface chemistry design eliminates complex nanosynthesis, auxiliary devices, or additional reagents while efficiently improving sensitivity with advantages: simplified fabrication process, excellent reproducibility and reliability, and ultrasensitivity toward various biomarkers. The surface chemistry using weakly ionized AuNPs represents a versatile approach for sensitizing POC sensors.

Identification of ibuprofen targeting CXCR family members to alleviate metabolic disturbance in lipodystrophy based on bioinformatics and in vivo experimental verification.

Background: Lipodystrophy is a rare disease that is poorly diagnosed due to its low prevalence and frequent phenotypic heterogeneity. The main therapeutic measures for patients with clinical lipodystrophy are aimed at improving general metabolic complications such as diabetes mellitus, insulin resistance, and hypertriglyceridemia. Therefore, there is an urgent need to find new biomarkers to aid in the diagnosis and targeted treatment of patients with congenital generalized lipodystrophy (CGL). Methods: Dataset GSE159337 was obtained via the Gene Expression Omnibus database. First, differentially expressed genes (DEGs) between CGL and control samples were yielded via differential expression analysis and were analyzed for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment to explore the functional pathways. Next, protein-protein interaction analysis and the MCC algorithm were implemented to yield candidate genes, which were then subjected to receiver operating characteristic (ROC) analysis to identify biomarkers with an area under the curve value exceeding 0.8. Moreover, random forest (RF), logistic regression, and support vector machine (SVM) analyses were carried out to assess the diagnostic ability of biomarkers for CGL. Finally, the small-molecule drugs targeting biomarkers were predicted, and ibuprofen was further validated in lipodystrophy mice. Results: A total of 71 DEGs in GSE159337 were sifted out and were involved in immune receptor activity, immune response-regulating signaling pathway, and secretory granule membrane. Moreover, CXCR2, TNFSF10, NLRC4, CCR2, CEACAM3, TLR10, TNFAIP3, and JUN were considered as biomarkers by performing ROC analysis on 10 candidate genes. Meanwhile, RF, logistic regression, and SVM analyses further described that those biomarkers had an excellent diagnosis capability for CGL. Eventually, the drug-gene network included ibuprofen-CXCR1, ibuprofen-CXCR1, cenicriviroc-CCR2, fenofibrate-JUN, and other relationship pairs. Ibuprofen treatment was also validated to downregulate CXCR1 and CXCR2 in peripheral blood mononuclear cells (PBMCs) and improve glucose tolerance, hypertriglyceridemia, hepatic steatosis, and liver inflammation in lipodystrophy mice. Conclusion: Eight biomarkers, namely, CXCR2, TNFSF10, NLRC4, CCR2, CEACAM3, TLR10, TNFAIP3, and JUN, were identified through bioinformatic analyses, and ibuprofen targeting CXCR1 and CXCR2 in PBMCs was shown to improve metabolic disturbance in lipodystrophy, contributing to studies related to the diagnosis and treatment of lipodystrophy.

Low HDL-C/ApoA-I index is associated with cardiometabolic risk factors and coronary artery calcium: a sub-analysis of the genetics of atherosclerotic disease (GEA) study.

BACKGROUND: The high-density lipoprotein cholesterol to apolipoprotein A-I index (HDL-C/ApoA-I) may be practical and useful in clinical practice as a marker of atherosclerosis. This study aimed to investigate the association between the HDL-C/ApoA-I index with cardiometabolic risk factors and subclinical atherosclerosis. METHODS: In this cross-sectional sub-analysis of the GEA study, 1,363 individuals, women (51.3%) and men (48.7%) between 20 and 75 years old, without coronary heart disease or diabetes mellitus were included. We defined an adverse cardiometabolic profile as excess adipose tissue metrics, non-alcoholic liver fat measured by non-contrasted tomography, metabolic syndrome, dyslipidemias, and insulin resistance. The population was stratified by quartiles of the HDL-C/Apo-AI index, and its dose-relationship associations were analysed using Tobit regression, binomial, and multinomial logistic regression analysis. RESULTS: Body mass index, visceral and pericardial fat, metabolic syndrome, fatty liver, high blood pressure, and CAC were inversely associated with the HDL-C/ApoA-I index. The CAC > 0 prevalence was higher in quartile 1 (29.2%) than in the last quartile (22%) of HDL-C/ApoA-I index (p = 0.035). The probability of having CAC > 0 was higher when the HDL-C/ApoA-I index was less than 0.28 (p < 0.001). This association was independent of classical coronary risk factors, visceral and pericardial fat measurements. CONCLUSION: The HDL-C/ApoA-I index is inversely associated with an adverse cardiometabolic profile and CAC score, making it a potentially useful and practical biomarker of coronary atherosclerosis. Overall, these findings suggest that the HDL-C/ApoA-I index could be useful for evaluating the probability of having higher cardiometabolic risk factors and subclinical atherosclerosis in adults without CAD.

Pathohistomorphometric and Immuno-Histologic Changes in Early Arteriovenous Fistula Failure in Patients with Chronic Kidney Disease.

BACKGROUND: Hemodialysis is a prevalent treatment for the end-stage chronic kidney disease (CKD) worldwide. The primary arteriovenous fistula (AVF), widely considered the optimal hemodialysis access method, fails to mature in up to two-thirds of the cases. The etiology of the early AVF failure, defined as thrombosis or inability to use within three months post-creation remains less understood, and is influenced by various factors including patient demographics, surgical techniques, and genetic predispositions. Neointimal hyperplasia is a primary histological finding in stenotic lesions leading to the AVF failure. However, there are insufficient data on the cellular phenotypes and the impact of the preexisting CKD-related factors. This study aims to investigate the histological, morphometric, and immunohistochemical alterations in the fistula vein, pre-, peri-, and post-early failure. MATERIALS AND METHODS: Eighty-nine stage 4-5 CKD patients underwent standard preoperative assessment, including the Doppler ultrasound, before a typical radio-cephalic AVF creation. Post-failure, a new AVF was created proximally. The vein specimens were collected during the surgery, processed, and analyzed for morphometric analyses and various cellular markers, including Vimentin, TGF, and Ki 67. RESULTS: The study enrolled 89 CKD patients, analyzing various aspects of their condition and AVF failures. The histomorphometric analysis revealed substantial venous luminal stenosis and varied endothelial changes. The immunohistologic analysis showed differential marker expressions pre- and post-AVF creation. CONCLUSION: This study highlights the complexity of the early AVF failures in CKD patients. The medial hypertrophy emerged as a significant preexisting lesion, while the postoperative analyses indicated a shift towards neointimal hyperplasia. The research underscores the nuanced interplay of vascular remodeling, endothelial damage, and cellular proliferation in the AVF outcomes.

Gold nanoparticles-based biosensors: pioneering solutions for bacterial and viral pathogen detection-a comprehensive review.

Gold Nanoparticles (AuNPs) have gained significant attention in biosensor development due to their unique physical, chemical, and optical properties. When incorporated into biosensors, AuNPs offer several advantages, including a high surface area-to-volume ratio, excellent biocompatibility, ease of functionalization, and tunable optical properties. These properties make them ideal for the detection of various biomolecules, including proteins, nucleic acids, and bacterial and viral biomarkers. Traditional methods for detecting bacteria and viruses, such as RT-PCR and ELISA, often suffer from complexities, time consumption, and labor intensiveness. Consequently, researchers are continuously exploring novel devices to address these limitations and effectively detect a diverse array of infectious pathogenic microorganisms. In light of these challenges, nanotechnology has been instrumental in refining the architecture and performance of biosensors. By leveraging advancements in nanomaterials and strategies of biosensor fabrication the sensitivity and specificity of biosensors can be enhanced, enabling more precise detection of pathogenic bacteria and viruses. This review explores the versatility of AuNPs in detecting a variety of biomolecules, including proteins, nucleic acids, and bacterial and viral biomarkers. Furthermore, it evaluates recent advancements in AuNPs-based biosensors for the detection of pathogens, utilizing techniques such as optical biosensors, lateral flow immunoassays, colorimetric immunosensors, electrochemical biosensors, and fluorescence nanobiosensors. Additionally, the study discusses the existing challenges in the field and proposes future directions to improve AuNPs-based biosensors, with a focus on enhancing sensitivity, selectivity, and their utility in clinical and diagnostic applications.

Enhancing sepsis biomarker development: key considerations from public and private perspectives.

Implementation of biomarkers in sepsis and septic shock in emergency situations, remains highly challenging. This viewpoint arose from a public-private 3-day workshop aiming to facilitate the transition of sepsis biomarkers into clinical practice. The authors consist of international academic researchers and clinician-scientists and industry experts who gathered (i) to identify current obstacles impeding biomarker research in sepsis, (ii) to outline the important milestones of the critical path of biomarker development and (iii) to discuss novel avenues in biomarker discovery and implementation. To define more appropriately the potential place of biomarkers in sepsis, a better understanding of sepsis pathophysiology is mandatory, in particular the sepsis patient's trajectory from the early inflammatory onset to the late persisting immunosuppression phase. This time-varying host response urges to develop time-resolved test to characterize persistence of immunological dysfunctions. Furthermore, age-related difference has to be considered between adult and paediatric septic patients. In this context, numerous barriers to biomarker adoption in practice, such as lack of consensus about diagnostic performances, the absence of strict recommendations for sepsis biomarker development, cost and resources implications, methodological validation challenges or limited awareness and education have been identified. Biomarker-guided interventions for sepsis to identify patients that would benefit more from therapy, such as sTREM-1-guided Nangibotide treatment or Adrenomedullin-guided Enibarcimab treatment, appear promising but require further evaluation. Artificial intelligence also has great potential in the sepsis biomarker discovery field through capability to analyse high volume complex data and identify complex multiparametric patient endotypes or trajectories. To conclude, biomarker development in sepsis requires (i) a comprehensive and multidisciplinary approach employing the most advanced analytical tools, (ii) the creation of a platform that collaboratively merges scientific and commercial needs and (iii) the support of an expedited regulatory approval process.

Follicular fluid lipidomics analysis reveals altered lipid signatures in patients with polycystic ovary syndrome.

BACKGROUND: This research investigates the metabolic profiles of follicular fluid (FF) samples from patients with polycystic ovary syndrome (PCOS) undergoing in vitro fertilisation and aims to identify diagnostic and therapeutic biomarkers for PCOS through lipidomic analysis. METHODS: We performed non-targeted lipid analysis of FF samples from women with PCOS (n = 6) and normal controls (n = 6) using ultra-high-performance liquid chromatography-tandem mass spectrometry. Differential lipids between the two groups were screened using multidimensional statistical analysis, followed by fold change analysis and t-tests to identify potential PCOS biomarkers. RESULTS: Multivariate statistical analysis revealed significant differences in FF lipid levels between the PCOS and control groups. Five different lipids were selected as standards, with p < .05. Phosphatidylcholine (PC), the main differentially expressed lipid, was significantly increased in the FF of the POCS group and was closely related to other lipids. CONCLUSIONS: Using ultra-high-performance liquid chromatography-tandem mass spectrometry, we investigated lipid biomarkers based on FF lipidomics to provide useful information for the discovery of diagnostic markers for PCOS. Our study identified five distinct lipids as potential markers of PCOS, with PC being the primary aberrant lipid found in the FF of patients with PCOS.

Follicular fluid (FF) is a complex microenvironment involved in oocyte growth, follicular maturation and germ cell­somatic cell communication. All metabolites during oocyte growth are collected from the FF. This study used lipidomic analysis to identify differences in FF lipids between normal women and those diagnosed with polycystic ovary syndrome (PCOS). The pathogenesis of PCOS is associated with abnormal metabolism of glyceroglycolipids and sphingomyelin. Here, we found that phosphatidylcholine is the main abnormal lipid in FF in patients with PCOS. Our study informs the future research into the development of diagnostic markers for PCOS to be used in clinical practice.