Biomarkers For Early Diagnosis Research Articles

Evaluation of diagnostic accuracy of urine neutrophil gelatinase-associated lipocalin in patients with symptoms of urinary tract infections: a meta-analysis.

Early and accurate diagnosis of urinary tract infection (UTI) can prevent serious sequelae including chronic kidney disease. Multiple individual studies have identified urine neutrophil gelatinase-associated lipocalin (uNGAL) as a promising biomarker for early diagnosis of UTI. We sought to understand the distribution and diagnostic accuracy of uNGAL values in patients presenting with UTI symptoms. Our systematic literature reviews in PubMed, Embase, and Cochrane Reviews up to March 2024, identified 25 studies reporting mean/median, standard deviation/quartiles, and detection limits of uNGAL in symptomatic patients with and without culture-confirmed UTI. Seventeen studies were in children. Meta-analyses were performed using the quantile estimation (QE) method estimating the distributions of uNGAL, which were then compared between the UTI and non-UTI groups for identifying the best cut-off points maximizing the Youden index. Sensitivity analyses were performed on all 25 studies including adult patients. We found that uNGAL levels were significantly higher in samples with confirmed UTI compared to those without. In pediatric studies, median and 95% confidence interval (CI) of uNGAL values were 22.41 (95% CI of 9.94, 50.54) ng/mL in non-UTI group vs. 118.85 (95% CI of 43.07, 327.97) ng/mL in UTI group. We estimated the cut-off point of 48.43 ng/mL with highest sensitivity (96%) and specificity (97%) in children. Sensitivity analysis including both pediatric and adult studies yielded similar results. The level of uNGAL in symptomatic patients with confirmed UTI is much higher than that reported in patients without UTI. It may be used as a diagnostic tool to identify UTI early among symptomatic patients. The range of uNGAL concentrations and cut-off points reported in subjects with UTI is much lower than that reported in patients with acute intrinsic kidney injury. https://www.crd.york.ac.uk/, PROSPERO (CRD42023370451).

EEG entropy insights in the context of physiological aging and Alzheimer's and Parkinson's diseases: a comprehensive review.

In recent decades, entropy measures have gained prominence in neuroscience due to the nonlinear behaviour exhibited by neural systems. This rationale justifies the application of methods from the theory of nonlinear dynamics to cerebral activity, aiming to detect and quantify its variability more effectively. In the context of electroencephalogram (EEG) signals, entropy analysis offers valuable insights into the complexity and irregularity of electromagnetic brain activity. By moving beyond linear analyses, entropy measures provide a deeper understanding of neural dynamics, particularly pertinent in elucidating the mechanisms underlying brain aging and various acute/chronic-progressive neurological disorders. Indeed, various pathologies can disrupt nonlinear structuring in neural activity, which may remain undetected by linear methods such as power spectral analysis. Consequently, the utilization of nonlinear tools, including entropy analysis, becomes crucial for capturing these alterations. To establish the relevance of entropy analysis and its potential to discern between physiological and pathological conditions, this review discusses its diverse applications in studying healthy brain aging and neurodegenerative diseases, including Alzheimer's disease (AD) and Parkinson's disease (PD). Various entropy parameters, such as approximate entropy (ApEn), sample entropy (SampEn), multiscale entropy (MSE), and permutation entropy (PermEn), are analysed within this context. By quantifying the complexity and irregularity of EEG signals, entropy analysis may serve as a valuable biomarker for early diagnosis, treatment monitoring, and disease management. Such insights offer clinicians crucial information for devising personalized treatment and rehabilitation plans tailored to individual patients.

Patients With Type 2 Diabetes Mellitus and Early Diabetic Kidney Disease Exhibit Lower Computed Tomography-measured Skeletal Muscle Attenuation Values: A Propensity Score-matched Study

ObjectiveTo investigate the association between computed tomography (CT)-measured quality characteristics of skeletal muscle (SM) and early diagnosis of diabetic kidney disease (DKD) in patients with type 2 diabetes mellitus (T2DM). MethodsThis retrospective study included patients diagnosed with T2DM, with and without early DKD, between January 2019 and December 2021. To reduce potential bias, propensity score matching (PSM) was performed. The area and CT attenuation values for SM and different abdominal adipose depots were measured. After PSM, logistic and multiple linear regression analyse were performed to analyse risk factors for early DKD. ResultsA total of 267 patients were enrolled (mean age, 61.67 years ±10.87; 155 men) and divided into two groups: T2DM with early DKD (n=133); and T2DM without DKD (n=134). After PSM, 230 patients were matched (T2DM with early DKD [n=115]; and T2DM without DKD [n=115]), with no statistical differences in general characteristics between the two groups (P>0.05). In multivariate logistic regression analysis, high-density lipoprotein cholesterol (odds ratio [OR] 0.14; 95% confidence interval [CI] 0.04–0.49; P=0.002), uric acid (OR 1.01; 95% CI 1.00–1.01; P=0.006), and SM attenuation value (OR 0.94; 95% CI 0.90–0.98; P=0.003) were independent risk factors for early DKD. Multiple linear regression analysis revealed significant correlations between SM attenuation value and cystatin C (β=-0.39, P=0.004), urine albumin-to-creatinine ratio (β=-0.26, P=0.026), and estimated glomerular filtration rate (β=0.31 P=0.009) after adjustment for confounders. ConclusionT2DM patients with lower SM attenuation values may exhibit a higher risk for early DKD than those with higher values, which provides a potential imaging biomarker for early DKD diagnosis.

Mendelian randomization analysis reveals causal associations of serum metabolites with sepsis and 28-day mortality

Metabolic disorder has been found to be an important factor in the pathogenesis and progression of sepsis. However, the causation of such an association between serum metabolites and sepsis has not been established. We conducted a two-sample Mendelian randomization (MR) study. A genome-wide association study of 486 human serum metabolites was used as the exposure, whereas sepsis and sepsis mortality within 28 days were set as the outcomes. In MR analysis, 6 serum metabolites were identified to be associated with an increased risk of sepsis, and 6 serum metabolites were found to be related to a reduced risk of sepsis. Furthermore, there were 9 metabolites positively associated with sepsis-related mortality, and 8 metabolites were negatively correlated with sepsis mortality. In addition, “glycolysis/gluconeogenesis” (p = 0.001), and “pyruvate metabolism” (p = 0.042) two metabolic pathways were associated with the incidence of sepsis. This MR study suggested that serum metabolites played significant roles in the pathogenesis of sepsis, which may provide helpful biomarkers for early disease diagnosis, therapeutic interventions, and prognostic assessments for sepsis.

Identifying potential breath biomarkers for early diagnosis of papillary thyroid cancer based on solid-phase microextraction gas chromatography-high resolution mass spectrometry with metabolomics.

Thyroid cancer incidence rate has increased substantially worldwide in recent years. Fine needle aspiration biopsy (FNAB) is currently the golden standard of thyroid cancer diagnosis, which however, is invasive and costly. In contrast, breath analysis is a non-invasive, safe and simple sampling method combined with a promising metabolomics approach, which is suitable for early cancer diagnosis in high volume population. This study aims to achieve a more comprehensive and definitive exhaled breath metabolism profile in papillary thyroid cancer patients (PTCs). We studied both end-tidal and mixed expiratory breath, solid-phase microextraction gas chromatography coupled with high resolution mass spectrometry (SPME-GC-HRMS) was used to analyze the breath samples. Multivariate combined univariate analysis was applied to identify potential breath biomarkers. The biomarkers identified in end-tidal and mixed expiratory breath mainly included alkanes, olefins, enols, enones, esters, aromatic compounds, and fluorine and chlorine containing organic compounds. The area under the curve (AUC) values of combined biomarkers were 0.974 (sensitivity: 96.1%, specificity: 90.2%) and 0.909 (sensitivity: 98.0%, specificity: 74.5%), respectively, for the end-tidal and mixed expiratory breath, indicating of reliability of the sampling and analysis method CONCLUSION: This work not only successfully established a standard metabolomic approach for early diagnosis of PTC, but also revealed the necessity of using both the two breath types for comprehensive analysis of the biomarkers.

Cardiovascular autonomic failure in hereditary transthyretin amyloidosis and TTR carriers is an early and progressive disease marker.

The cardiomyopathic and neuropathic phenotype of hereditary transthyretin amyloidosis are well recognized. Cardiovascular autonomic dysfunction is less systematically and objectively assessed. Autonomic and clinical features, quantitative cardiovascular autonomic function, and potential autonomic prognostic markers of disease progression were recorded in a cohort of individuals with hereditary transthyretin amyloidosis and in asymptomatic carriers of TTR variants at disease onset (T0) and at the time of the first quantitative autonomic assessment (T1). The severity of peripheral neuropathy and its progression was stratified with the polyneuropathy disability score. A total of 124 individuals were included (111 with a confirmed diagnosis of hereditary transthyretin amyloidosis, and 13 asymptomatic carriers of TTR variants). Symptoms of autonomic dysfunction were reported by 27% individuals at T0. Disease duration was 4.5 ± 4.0years [mean ± standard deviation (SD)] at autonomic testing (T1). Symptoms of autonomic dysfunction were reported by 78% individuals at T1. Cardiovascular autonomic failure was detected by functional testing in 75% individuals and in 64% of TTR carriers. Progression rate from polyneuropathy disability stages I/II to III/IV seemed to be shorter for individuals with autonomic symptoms at onset [2.33 ± 0.56 versus 4.00 ± 0.69years (mean ± SD)]. Cardiovascular autonomic dysfunction occurs early and frequently in individuals with hereditary transthyretin amyloidosis within 4.5years from disease onset. Cardiovascular autonomic failure can be subclinical in individuals and asymptomatic carriers, and only detected with autonomic function testing, which should be considered a potential biomarker for early diagnosis and disease progression.

Aqueous humor proteomics analyzed by bioinformatics and machine learning in PDR cases versus controls

BackgroundTo comprehend the complexities of pathophysiological mechanisms and molecular events that contribute to proliferative diabetic retinopathy (PDR) and evaluate the diagnostic value of aqueous humor (AH) in monitoring the onset of PDR.MethodsA cohort containing 16 PDR and 10 cataract patients and another validation cohort containing 8 PDR and 4 cataract patients were studied. AH was collected and subjected to proteomics analyses. Bioinformatics analysis and a machine learning-based pipeline called inference of biomolecular combinations with minimal bias were used to explore the functional relevance, hub proteins, and biomarkers.ResultsDeep profiling of AH proteomes revealed several insights. First, the combination of SIAE, SEMA7A, GNS, and IGKV3D-15 and the combination of ATP6AP1, SPARCL1, and SERPINA7 could serve as surrogate protein biomarkers for monitoring PDR progression. Second, ALB, FN1, ACTB, SERPINA1, C3, and VTN acted as hub proteins in the profiling of AH proteomes. SERPINA1 was the protein with the highest correlation coefficient not only for BCVA but also for the duration of diabetes. Third, “Complement and coagulation cascades” was an important pathway for PDR development.ConclusionsAH proteomics provides stable and accurate biomarkers for early warning and diagnosis of PDR. This study provides a deep understanding of the molecular mechanisms of PDR and a rich resource for optimizing PDR management.

Stage-Specific Alteration and Prognostic Relationship of Serum Fumarate Hydratase Autoantibodies in Gastric Cancer.

The relationship between energy production and cancer is attracting attention. This study aimed to investigate the clinicopathological significance of fumarate hydratase (FH), a tricarboxylic acid cycle enzyme, in gastric cancer using autoantibodies as biomarkers. The study analyzed 116 patients who underwent gastric cancer surgery and 96 healthy controls. Preoperative serum FH autoantibody (s-FH-Ab) titers were analyzed using an immunosorbent assay with an amplified luminescent proximity homogeneous assay. Receiver operating characteristic analysis was used to determine the cutoff s-FH-Ab titer. Clinicopathological factors and prognosis were compared between the high and low s-FH-Ab groups. The s-FH-Ab levels were significantly higher in the gastric cancer group than in the control group (p = 0.01). Levels were elevated even in patients with stage I gastric cancer compared with healthy controls (p = 0.02). A low s-FH-Ab level was significantly associated with distant metastasis (p = 0.01), peritoneal dissemination (p < 0.05), and poor overall survival (p < 0.01). Multivariate analysis revealed that low s-FH-Ab levels were an independent risk factor for poor prognosis (p < 0.01). Therefore, s-FH-Ab levels may be a useful biomarker for early diagnosis and the prediction of prognosis in patients with gastric cancer.

Association between lipid accumulation product and psoriasis among adults: a nationally representative cross-sectional study

BackgroundLipid accumulation product (LAP) is an accessible and relatively comprehensive assessment of obesity that represents both anatomical and physiological lipid accumulation. Obesity and psoriasis are potentially related, according to previous research. Investigating the relationship between adult psoriasis and the LAP index was the goal of this study.MethodsThis is a cross-sectional study based on data from the National Health and Nutrition Examination Survey (NHANES) 2003–2006 and 2009–2014. The association between LAP and psoriasis was examined using multivariate logistic regression and smoothed curve fitting. To verify whether this relationship was stable across populations, subgroup analyses and interaction tests were performed.ResultsThe LAP index showed a positive correlation with psoriasis in 9,781 adult participants who were 20 years of age or older. A 27% elevated probability of psoriasis was linked to every unit increase in ln LAP in the fully adjusted model (Model 3: OR 1.27, 95% CI 1.06–1.52). In comparison with participants in the lowest ln LAP quartile, those in the highest quartile had an 83% greater likelihood of psoriasis (Model 3: OR 1.83, 95% CI 1.08–3.11). This positive correlation was more pronounced for young males, participants who had never smoked, non-drinkers, participants who exercised little, as well as non-hypertensive and non-diabetic participants.ConclusionsThis study found that the LAP index and adult psoriasis were positively correlated, especially in young males without comorbidities. Therefore, it is proposed that LAP may serve as a biomarker for early diagnosis of psoriasis and tracking the effectiveness of treatment.

The role of miRNAs as biomarkers in breast cancer.

Breast cancer (BC) is the second most common cause of deaths reported in women worldwide, and therefore there is a need to identify BC patients at an early stage as timely diagnosis would help in effective management and appropriate monitoring of patients. This will allow for proper patient monitoring and effective care. However, the absence of a particular biomarker for BC early diagnosis and surveillance makes it difficult to accomplish these objectives. miRNAs have been identified as master regulators of the molecular pathways that are emphasized in various tumors and that lead to the advancement of malignancies. Small, non-coding RNA molecules known as miRNAs target particular mRNAs to control the expression of genes. miRNAs dysregulation has been linked to the start and development of a number of human malignancies, including BC, since there is compelling evidence that miRNAs can function as tumor suppressor genes or oncogenes. The current level of knowledge on the role of miRNAs in BC diagnosis, prognosis, and treatment is presented in this review. miRNAs can regulate the tumorigenesis of BC through targeting PI3K pathway and can be used as prognostic or diagnostic biomarkers for BC therapy. Some miRNAs, like miR-9, miR-10b, and miR-17-5p, are becoming known as biomarkers of BC for diagnosis, prognosis, and therapeutic outcome prediction. Other miRNAs, like miR-30c, miR-187, and miR-339-5p, play significant roles in the regulation of hallmark functions of BC, including invasion, metastasis, proliferation, resting death, apoptosis, and genomic instability. Other miRNAs, such as miR-155 and miR-210, are circulating in bodily fluids and are therefore of interest as novel, conveniently accessible, reasonably priced, non-invasive methods for the customized care of patients with BC.

A comprehensive analysis of the oncogenic and prognostic role of TBC1Ds in human hepatocellular carcinoma.

TBC1D family members (TBC1Ds) are a group of proteins that contain the Tre2-Bub2-Cdc16 (TBC) domain. Recent studies have shown that TBC1Ds are involved in tumor growth, but no analysis has been done of expression patterns and prognostic values of TBC1Ds in hepatocellular carcinoma (HCC). The expression levels of TBC1Ds were evaluated in HCC using the TIMER, UALCN and Protein Atlas databases. The correlation between the mRNA levels of TBC1Ds and the prognosis of patients with HCC in the GEPIA database was then analyzed. An enrichment analysis then revealed genes that potentially interact with TBC1Ds. The correlation between levels of TBC1Ds and tumor-infiltrating immune cells (TIICs) in HCC were studied using the TIMER 2.0 database. Finally, a series of in vitro assays verified the role of TBC1Ds in HCC progression. This study revealed the upregulated expression of TBC1Ds in HCC and the strong positive correlation between the mRNA levels of TBC1Ds and poor prognosis of patients with HCC. The functions of TBC1Ds were mainly related to autophagy and the AMPK pathway. There was also a significant correlation between level of TBC1Ds and tumor-infiltrating immune cells (TIICs) in HCC. The promoting role of TBC1Ds in HCC progression was verified in vitro assays. The results of this analysis indicate that TBC1Ds may serve as new biomarkers for early diagnosis and treatment of HCC.

MicroRNA mmu-miR-511-5p: A promising Diagnostic Biomarker in Experimental Toxoplasmosis Using Different Strains and Infective Doses in Mice with Different Immune States Before and After Treatment

PurposeSearching for a novel early diagnostic biomarker for toxoplasmosis, real-time-PCR was currently used to measure the serum mmu-miR-511-5p level in male Swiss-albino mice infected with either; ME49 or RH Toxoplasma gondii (T. gondii) strains.MethodsThree mice groups were used; (GI) constituted the non-infected control group, while (GII) and (GIII) were experimentally infected with ME49 or RH strains, respectively. GII mice were orally infected using 10 or 20 ME49 cysts (ME-10 and ME-20), both were subdivided into; non-treated (ME-10-NT and ME-20-NT) and were further subdivided into; immunocompetent (ME-10-IC and ME-20-IC) [euthanized 3-days, 1, 2, 6 or 8-weeks post-infection (PI)], and immunosuppressed using two Endoxan® injections (ME-10-IS and ME-20-IS) [euthanized 6- or 8-weeks PI], and spiramycin-treated (ME-10-SP and ME-20-SP) that received daily spiramycin, for one-week before euthanasia. GIII mice individually received 2500 intraperitoneal RH strain tachyzoites, then, were subdivided into; non-treated (RH-NT) [euthanized 3 or 5-days PI], and spiramycin-treated (RH-SP) that were euthanized 5 or 10-days PI (refer to the graphical abstract).ResultsRevealed significant upregulation of mmu-miR-511-5p in GII, one-week PI, with gradually increased expression, reaching its maximum 8-weeks PI, especially in ME-20-NT group that received the higher infective dose. Immunosuppression increased the upregulation. Contrarily, treatment caused significant downregulation. GIII recorded significant upregulation 3-days PI, yet, treatment significantly decreased this expression.ConclusionSerum mmu-miR-511-5p is a sensitive biomarker for early diagnosis of ME49 and RH infection (as early as one-week and 3-days, respectively), and its expression varies according to T. gondii infective dose, duration of infection, spiramycin-treatment and host immune status.Graphical abstract

Construction of a 3D Quantum Dot Nanoassembly with Two-Step FRET for One-Step Sensing of Human Telomerase RNA in Breast Cancer Cells and Tissues.

Telomerase is an important biomarker for early diagnosis of cancers, but current telomerase assays usually rely on measuring the extension products of telomerase substrates, which increases the assay complexity. More evidence indicates that human telomerase RNA (hTR), as a core component of telomerase, is positively correlated with the telomerase activity. Herein, we demonstrate the development of a duplex-specific nuclease (DSN)-propelled 3D quantum dot (QD) nanoassembly with two-step Föster resonance energy transfer (FRET) for the one-step sensing of hTR in breast cancer cells and tissues. This assay involves only one hairpin probe modified with a Cy5 at the sixth base from the 5'-biotin end and a BHQ2 at the 3'-terminus, which integrates three functions of target recognition, target recycling amplification, and signal readout. The anchoring of the hairpin probe on the 605QD surface results in the formation of a 3D 605QD-Cy5-probe-BHQ2 nanoassembly in which two-step FRET occurs among the 605QD, Cy5, and BHQ2 quencher. Notably, the formation of 605QD-Cy5-probe-BHQ2 nanoassembly facilitates the reduction of background signal and the increase of signal-to-background ratio due to its dense, highly oriented nucleic acid shell-induced steric hindrance effect. This assay can achieve one-step and rapid detection of hTR with a detection limit of 2.10 fM, which is the simplest and most rapid hTR assay reported so far. Moreover, this assay can efficiently distinguish single-base mismatched sequences, and it can discriminate the hTR level between breast cancer patients and healthy donors with a high accuracy of 100%, with great prospects for early diagnosis of cancers.

Potential Exosome Biomarkers for Parkinson's Disease Diagnosis: A Systematic Review and Meta-Analysis.

Parkinson's disease (PD) is the second most common neurodegenerative disease worldwide. Given its prevalence, reliable biomarkers for early diagnosis are required. Exosomal proteins within extracellular nanovesicles are promising candidates for diagnostic, screening, prognostic, and disease monitoring purposes in neurological diseases such as PD. This review aims to evaluate the potential of extracellular vesicle proteins or miRNAs as biomarkers for PD. A comprehensive literature search until January 2024 was conducted across multiple databases, including PubMed, EMBASE, Web of Science, and Cochrane Library, to identify relevant studies reporting exosome biomarkers in blood samples from PD patients. Out of 417 articles screened, 47 studies were selected for analysis. Among exosomal protein biomarkers, α-synuclein, tau, Amyloid β 1-42, and C-X-C motif chemokine ligand 12 (CXCL12) were identified as significant markers for PD. Concerning miRNA biomarkers, miRNA-24, miR-23b-3p, miR-195-3p, miR-29c, and mir-331-5p are promising across studies. α-synuclein exhibited increased levels in PD patients compared to control groups in twenty-one studies, while a decrease was observed in three studies. Our meta-analysis revealed a significant difference in total exosomal α-synuclein levels between PD patients and healthy controls (standardized mean difference [SMD] = 1.369, 95% confidence interval [CI] = 0.893 to 1.846, p < 0.001), although these results are limited by data availability. Furthermore, α-synuclein levels significantly differ between PD patients and healthy controls (SMD = 1.471, 95% CI = 0.941 to 2.002, p < 0.001). In conclusion, certain exosomal proteins and multiple miRNAs could serve as potential biomarkers for diagnosis, prognosis prediction, and assessment of disease progression in PD.

Small extracellular vesicles detection using dielectrophoresis-based microfluidic chip for diagnosis of breast cancer

Small extracellular vesicles (sEVs) reflect the genotype and phenotype of original cells and are biomarkers for early diagnosis and treatment monitoring of tumors. Yet, their small size and low density make them difficult to isolate and detect in body fluid samples. This study proposes a novel acDEP-Exo chip filled with transparent micro-beads, which formed a non-uniform electrical field, and finally achieved rapid, sensitive, and tunable sEVs capture and detection. The method requires only 20–50 μL of sample, achieved a limit of detection (LOD) of 161 particles/μL, and can detect biomarkers within 13 min. We applied the chip to analyze the two markers of sEV's EpCAM and MUC1 in clinical plasma samples from breast cancer (BC) patients and healthy volunteers and found that the combined evaluation of sEV's biomarkers has extremely high sensitivity, specificity and accuracy. The present study introduces an alternative approach to sEVs isolation and detection, has a great potential in real-time sEVs-based liquid biopsy.

Potential clinical applications of extracellular vesicles in pancreatic cancer: exploring untapped opportunities from biomarkers to novel therapeutic approaches

Pancreatic cancer is a highly lethal and metastatic malignancy, mainly because it often remains undetected until advanced stages due to the limitations of current diagnostic methods, rendering currently available therapies ineffective. Therefore, it is imperative to identify useful biomarkers for early diagnosis and new therapeutic targets for pancreatic cancer. Recently, extracellular vesicles have emerged as promising biomarkers for the diagnosis and prognosis of pancreatic cancer. Given their presence in various bodily fluids, extracellular vesicles offer a non-invasive approach through liquid biopsy to detect and monitor cancer progression. In this review, we comprehensively examine the multifaceted roles of extracellular vesicles in the progression of cancer, while also exploring their potential as diagnostic, prognostic, and therapeutic biomarkers in the context of pancreatic cancer.

Greatly isolated heterogeneous circulating tumor cells using hybrid engineered cell membrane-camouflaged magnetic nanoparticles

BackgroundCirculating tumor cells (CTCs) are considered as a useful biomarker for early cancer diagnosis, which play a crucial role in metastatic process. Unfortunately, the tumor heterogeneity and extremely rare occurrence rate of CTCs among billions of interfering leukocytes seriously hamper the sensitivity and purity of CTCs isolation.MethodsTo address these, we firstly used microfluidic chips to detect the broad-spectrum of triple target combination biomarkers in CTCs of 10 types of cancer patients, including EpCAM, EGFR and Her2. Then, we constructed hybrid engineered cell membrane-camouflaged magnetic nanoparticles (HE-CM-MNs) for efficient capture of heterogeneous CTCs with high-purity, which was enabled by inheriting the recognition ability of HE-CM for various CTCs and reducing homologous cell interaction with leukocytes. Compared with single E-CM-MNs, HE-CM-MNs showed a significant improvement in the capture efficiency for a cell mixture, with an efficiency of 90%. And the capture efficiency of HE-CM-MNs toward 12 subpopulations of tumor cells was ranged from 70 to 85%. Furthermore, by using HE-CM-MNs, we successfully isolated heterogeneous CTCs with high purity from clinical blood samples. Finally, the captured CTCs by HE-CM-MNs could be used for gene mutation analysis.ConclusionsThis study demonstrated the promising potential of HE-CM-MNs for heterogeneous CTCs detection and downstream analysis.Graphical abstract

Seminal plasma S100A8/A9 as a potential biomarker of genital tract inflammation.

Infections and inflammatory reactions in the male genital tract are the leading causes of male infertility with a prevalence of 6%-10%, primarily affecting testicular and epididymal function and ultimately compromising sperm quality. However, most infertile patients with genital infection/inflammation are asymptomatic and easily overlooked. Traditional indicators, including white blood cells, elastase, and other components in semen, can reflect inflammation of the genital tract, but there is still a lack of a uniform standard method of detection. Therefore, it is necessary to explore reliable markers in semen that reflect the inflammatory status of the genital tract. Using the experimental autoimmune orchitis (EAO) model to simulate noninfectious chronic orchitis, we successfully collected ejaculated seminal fluid from EAO rats using optimized electrical stimulation devices. Proteomic analysis was performed using isobaric tags for relative and absolute quantification (iTRAQ). Compared to the control group, 55 upregulated and 105 downregulated proteins were identified in seminal plasma samples from the EAO group. In a preliminary screening, the inflammation-related protein S100A8/A9 was upregulated. We further verified that S100A8/A9 was increased in seminal plasma and highly expressed in testicular macrophages of the EAO model. In patients with oligoasthenospermia and genital tract infections, we also found that S100A8/A9 levels were remarkably increased in seminal plasma and testicular macrophages. S100A8/A9 in semen may be a potential biomarker for chronic genital inflammation. Our study provides a new potential biomarker for early diagnosis and further understanding of male infertility caused by genital inflammation.

Homocystein, Vitamin B12 and Folic Acid as Screening Biomarkers in Early Diagnosis and Gastric Cancer Monitoring.

Gastric cancer has been demonstrating a reduction in the number of cases over the past decades, largely attributed to advancements in public health practices and increased accessibility to educational initiatives for the general population. Nevertheless, it persists as the third leading cause of mortality globally among both men and women. These fatalities are typically associated with delayed disease detection. The current study assessed the levels of homocysteine, vitamin B12, and folic acid as a means of establishing a screening biomarker profile that could be integrated into routine testing protocols to facilitate swift diagnosis of the illness. A total of 207 control subjects and 207 individuals with gastric cancer were scrutinized, with biochemical measurements conducted using chemiluminescence for homocysteine, folic acid, and vitamin B12. The two groups were matched based on age, tumor location, subtype, tumor classification, presence of Epstein-Barr Virus infection (EBV), and Helicobacter pylori (H. pylori). Significant statistical variances were identified in the mean levels of the triad of substances among cancer patients when compared to the control group for all corresponding variables. In conclusion, our study indicated that analyzing the triad of homocysteine, vitamin B12, and folic acid holds diagnostic value for gastric cancer and could potentially serve as an effective screening marker for this type of cancer in the future.

Targeted metabolomics combined with machine learning to identify and validate new biomarkers for early SLE diagnosis and disease activity

BackgroundThe early diagnosis of systemic lupus erythematosus (SLE) and the assessment of disease activity progression remain a great challenge. Targeted metabolomics has great potential to identify new biomarkers of SLE. MethodsSerum from 44 healthy participants and 89 SLE patients were analyzed using HM400 high-throughput targeted metabolomics. Machine learning (ML) with seven learning models and trained the model several times iteratively selected the two best prediction model in a competitive way, which were independent validated by enzyme-linked immunosorbent (ELISA) with 90 SLE patients. ResultsIn this study, 146 differential metabolites, most of them organic acids, amino acids, and bile acids, were detected between patients with initial SLE and healthy participants, and 8 potential biomarkers were found by intersection of ML and statistics (area under the curve [AUC] > 0.95) showing a significant positive correlation with clinical indicators. In addition, we identified and validated 2 potential biomarkers for SLE classification (P < 0.05, AUC > 0.775; N-Methyl-L-glutamic acid, L-2-aminobutyric acid) showing a significant correlation with the SLE Disease Activity Index. These differential metabolites were mainly involved in metabolic pathways, amino acid biosynthesis, 2-oxocarboxylic acid metabolism and other pathways. ConclusionThis study indicated that the tricarboxylic acid cycle might be associated with SLE drug therapy. We identified 8 diagnostic models biomarkers and 2 biomarkers that could be used to identify initial SLE and distinguish different activity degree, which will promote the development of new tools for the diagnosis and evaluation of SLE.