Serum Samples Of Patients Research Articles

Association of neutrophil extracellular trap levels with Raynaud’s phenomenon, glomerulonephritis and disease index score in SLE patients from Brazil

Neutrophil extracellular traps (NETs) are cell-extruded DNA strands coated with neutrophils' nuclear proteins and enzymes from cytotoxic granules, produced by NETosis, a cell death pathway. They perform an important defensive role in innate immunity, but their increased production and/or inefficient degradation expose new antigens, such as DNA or citrullinated histone peptides, triggering autoimmunity. This study aimed to access possible associations between serum NETs levels with epidemiological, clinical, and serological data from a well-characterized SLE Brazilian patients’ cohort. NET levels were evaluated in one hundred seventy serum samples of patients with Systemic Lupus Erythematosus (SLE) using an Immunoassay. Univariate and multivariate binary logistic regression used clinical patients' data as independent variables. Parametric and non-parametric tests compared log10 base serum NET levels transformed between patients' groups. SLE patients were also dichotomized into “High serum NET levels” and “Low serum NET levels” groups. All analyses were performed in R language 4.1.2, and p < 0.05 were considered significant. Increased susceptibility for high serum NET levels was observed in SLE patients with Raynaud's phenomenon (OR = 2.30, 95 % CI = 1.06–5.21 and p = 0.039), independently of any other risk factor. Also, SLE patients with Raynaud's phenomenon presented higher mean NET serum levels (mean = −0.13 vs. −0.51, p = 0.01). In addition, higher mean NET serum levels were associated with glomerulonephritis (mean = -0.45 vs. −0.12, p = 0.03). Ultimately, the SLEDAI index scored higher in the high NETs serum levels group (median = 2.0 vs. 0.0, p = 6 × 10−3). The formation of NETs might be implicated in Raynaud's phenomenon, glomerulonephritis, and disease index score in SLE patients. Our results highlight the importance of serum NET levels as a possible therapeutical target to modulate the clinical course of SLE.

Protein glycosylation in lung cancer from a mass spectrometry perspective.

Lung cancer is a severe disease for which better diagnostic and therapeutic approaches are urgently needed. Increasing evidence implies that aberrant protein glycosylation plays a crucial role in the pathogenesis and progression of lung cancer. Differences in glycosylation patterns have been previously observed between healthy and cancerous samples as well as between different lung cancer subtypes, which suggests untapped diagnostic potential. In addition, understanding the changes mediated by glycosylation may shed light on possible novel therapeutic targets and personalized treatment strategies for lung cancer patients. Mass spectrometry based glycomics and glycoproteomics have emerged as powerful tools for in-depth characterization of changes in protein glycosylation, providing valuable insights into the molecular basis of lung cancer. This paper reviews the literature on the analysis of protein glycosylation in lung cancer using mass spectrometry, which is dominated by manuscripts published over the past 5 years. Studies analyzing N-glycosylation, O-glycosylation, and glycosaminoglycan patterns in tissue, serum, plasma, and rare biological samples of lung cancer patients are highlighted. The current knowledge on the potential utility of glycan and glycoprotein biomarkers is also discussed.

Increased CX3CL1 in cerebrospinal fluid and ictal serum t-tau elevations in migraine: results from a cross-sectional exploratory case-control study

BackgroundTo date, migraine is diagnosed exclusively based on clinical criteria, but fluid biomarkers are desirable to gain insight into pathophysiological processes and inform clinical management. We investigated the state-dependent profile of fluid biomarkers for neuroaxonal damage and microglial activation as two potentially relevant aspects in human migraine pathophysiology.MethodsThis exploratory study included serum and cerebrospinal fluid (CSF) samples of patients with migraine during the headache phase (ictally) (n = 23), between attacks (interictally) (n = 16), and age/sex-matched controls (n = 19). Total Tau (t-Tau) protein, glial fibrillary acidic protein (GFAP), ubiquitin carboxy-terminal hydrolase L1 (UCH-L1), and neurofilament light chain (NfL) were measured with the Neurology 4-plex kit on a Single Molecule Array SR-X Analyzer (Simoa® SR-X, Quanterix Corp., Lexington, MA). Markers of microglial activation, C-X3-C motif chemokine ligand 1 (CX3CL1) and soluble triggering receptor expressed on myeloid cells 2 (sTREM2), were assessed using an immunoassay.ResultsConcentrations of CX3CL1 but not sTREM2 were significantly increased both ictally and interictally in CSF but not in serum in comparison to the control cohort (p = 0.039). ROC curve analysis provided an AUC of 0.699 (95% CI 0.563 to 0.813, p = 0.007). T-Tau in serum but not in CSF was significantly increased in samples from patients taken during the headache phase, but not interictally (effect size: η2 = 0.121, p = 0.038). ROC analysis of t-Tau protein in serum between ictal and interictal collected samples provided an AUC of 0.729 (95% CI 0.558 to 0.861, p = 0.006). The other determined biomarkers for axonal damage were not significantly different between the cohorts in either serum or CSF.DiscussionCX3CL1 in CSF is a novel potential fluid biomarker of migraine that is unrelated to the headache status. Serum t-Tau is linked to the headache phase but not interictal migraine. These data need to be confirmed in a larger hypothesis-driven prospective study.

Microbiome profiling and Co-metabolism pathway analysis in cervical cancer patients with acute radiation enteritis

BackgroundIntestinal bacteria significantly contribute to the metabolism of intestinal epithelial tissues. As the occurrence and development of radiation enteritis (RE) depend on the “co-metabolism” microenvironment formed by the host and intestinal microbiota, which involves complex influencing factors and strong correlations, ordinary techniques struggle to fully explain the underlying mechanisms. However, given that it is based on systems biology, metabolomics analysis is well-suited to address these issues. This study aimed to analyze the metabolomic changes in urine, serum, and fecal samples during volumetric modulated arc therapy (VMAT) for cervical cancer and screen for characteristic metabolites of severe acute radiation enteritis (SARE) and RE. MethodsWe enrolled 50 patients who received radiotherapy for cervical cancer. Urine, serum, and fecal samples of patients were collected at one day before radiotherapy and the second week, fourth week, and sixth week after the start of radiotherapy. Control group samples were collected during the baseline period. Differential metabolites were identified by metabolomics analysis; co-metabolic pathways were clarified. We used the mini-SOM library for incorporating characteristic metabolites, and established metabolite classification models for predicting SARE and RE. ResultsUrine and serum sample data showed remarkable clustering effect; metabolomics data of the fecal supernatant were evidently disturbed. Patient sample analyses during VMAT revealed the following. Urine samples: Downregulation of the pyrimidine and riboflavin metabolism pathways as well as initial upregulation followed by downregulation of arginine and proline metabolism pathways and the arginine biosynthesis pathway. Fecal samples: Upregulation of linoleic acid and phenylalanine metabolic pathways and initial downregulation followed by upregulation of arachidonic acid (AA) metabolic pathways. Serum samples: Initial upregulation followed by downregulation of the arginine biosynthesis pathway and downregulation of glutathione, AA, and arginine and proline metabolic pathways. ConclusionPatients with cervical cancer exhibited characteristic metabolic pathways and characteristic metabolites predicting RE and SARE were screened out. An effective RE mini-SOM classification model was successfully established.

Frequency shift Raman-based sensing of serum MicroRNA for ultrasensitive cervical cancer diagnosis

Cervical cancer is the most common gynaecological tumor. The development of a sensor for the ultrasensitive detection of cervical cancer is significant in guaranteeing its prognosis. Herein, we proposed a novel surface-enhanced Raman scattering (SERS) analysis platform using a frequency shifts-based sensing model for rapid and ultrasensitive microRNA (miRNA) assay. During the analysis process, miR-21 can be captured by the single-stranded DNA (ssDNA) modified on the platform which is complementary pairing with miR-21. The connection of miR-21 can lead to the variation of the molecular weight and result in the deformation extent of the Raman report molecule 6Thioguanine (6TG); thus, the peak at 1301 cm−1 due to the ring C–N stretches of 6TG shifts to lower frequency. The detection limit (LOD) of the proposed SERS analysis platform is as low as 8.32 aM. Moreover, the platform also has excellent specificity and repeatability, with the relative standard deviation (RSD) value of 6.53 %. Serum samples of cervical cancer patients and healthy subjects were analyzed via the platform and the accuracy of the detection results was verified by qRT-PCR, revealing that SERS results and qRT-PCR results have high homogeneity. Thus, the platform can serve as a potential tool for clinical diagnosis of cervical cancer.

Relationship of Endometriosis with Cortisol and Thyroid Function in Young Working Females

Objective: The study was focused to evaluate the role of endometriosis in development of hypothyroidism in working females subjected to chronic stress. Study Design: cross sectional study. Settings: This research was conducted at department of Gynecology &amp; Obstetrics, The University of Lahore Teaching Hospital, Lahore. Duration: The research was completed in from February 2023 to February 2024. Methods: Serum samples of fifty-five endometriosis patients and fifteen controls were analyzed for T3, T4, TSH, cortisol and estrogen levels by using ELISA kits. Results: The levels of TSH in patient’s serum is (1.02±0.168mIU/L) as related to control (3.08±1.090 mIU/L) were lower in females with endometriosis. Serum estrogen levels in endometriosis patients (67.07±5.54 pg/ml) were higher than normal controls (21.07±3.66pg/ml). Elevated levels of serum cortisol (27.25±3.27) than normal values (11.19±4.18) in endometriosis patients were observed. Thyroid problems may result from this imbalance. Furthermore, there is a change in the quantity of thyroid hormones (T3 and T4) in endometriotic cells. Production of T4 rose whereas that of T3 fell. Thus, our research shows that endometriosis increases the risk of thyroid malfunction and hormone imbalance in women. Conclusion: We came to the conclusion that thyroid hormone contributes to endometriosis because endometrial cells are sensitive to changes in TSH. The thyroid gland and its related hormone concentrations described a varied picture between healthy subjects and patients of endometriosis. Moreover, thyroid hormones and estrogen are found to play their significant roles in the disease.

Whole Blood as a Sample Matrix in Homogeneous Time-Resolved Assay-Förster Resonance Energy Transfer-Based Antibody Detection.

The protein-L-utilizing Förster resonance energy transfer (LFRET) assay enables mix-and-read antibody detection, as demonstrated for sera from patients with, e.g., severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Zika virus, and orthohantavirus infections. In this study, we compared paired serum and whole blood (WB) samples of COVID-19 patients and SARS-CoV-2 vaccine recipients. We found that LFRET also detects specific antibodies in WB samples. In 44 serum-WB pairs from patients with laboratory-confirmed COVID-19, LFRET showed a strong correlation between the sample materials. By analyzing 89 additional WB samples, totaling 133 WB samples, we found that LFRET results were moderately correlated with enzyme-linked immunosorbent assay results for samples collected 2 to 14 months after receiving COVID-19 diagnosis. However, the correlation decreased for samples >14 months after receiving a diagnosis. When comparing the WB LFRET results to neutralizing antibody titers, a strong correlation emerged for samples collected 1 to 14 months after receiving a diagnosis. This study also highlights the versatility of LFRET in detecting antibodies directly from WB samples and suggests that it could be employed for rapidly assessing antibody responses to infectious agents or vaccines.

Serum Fusion Transcripts to Assess the Risk of Hepatocellular Carcinoma and the Impact of Cancer Treatment through Machine Learning

Hepatocellular carcinoma (HCC) is one of the most fatal malignancies. Early diagnosis of HCC is crucial in reducing the risk for mortality. This study analyzed a panel of nine fusion transcripts in serum samples from 61 patients with HCC and 75 patients with non-HCC conditions, using TaqMan real-time quantitative RT-PCR. Seven of the nine fusions frequently detected in patients with HCC included: MAN2A1-FER (100%), SLC45A2-AMACR (62.3%), ZMPSTE24-ZMYM4 (62.3%), PTEN-NOLC1 (57.4%), CCNH-C5orf30 (55.7%), STAMBPL1-FAS (26.2%), and PCMTD1-SNTG1 (16.4%). Machine-learning models were constructed based on serum fusion-gene levels to predict HCC in the training cohort, using the leave-one-out cross-validation approach. One machine-learning model, called the four fusion genes logistic regression model (MAN2A1-FER≤40, CCNH-C5orf30≤38, SLC45A2-AMACR≤41, and PTEN-NOLC1≤40), produced accuracies of 91.5% and 83.3% in the training and testing cohorts, respectively. When serum α-fetal protein level was incorporated into the machine-learning model, a two fusion gene (MAN2A1-FER≤40, CCNH-C5orf30≤38) + α-fetal protein logistic regression model was found to generate an accuracy of 94.8% in the training cohort. The same model resulted in 95% accuracy in both the testing and combined cohorts. Cancer treatment was associated with reduced levels of most of the serum fusion transcripts. Serum fusion-gene machine-learning models may serve as important tools in screening for HCC and in monitoring the impact of HCC treatment.

Abstract 7293: Serum fusion gene transcripts to predict liver cancer

Abstract Hepatocellular carcinoma (HCC) is the most common type of liver cancers and one of the most lethal malignancies for human. Early diagnosis of HCC is crucial in reducing the mortality of the disease. In this report, we analyzed a panel of 9 fusion transcripts in the serum samples from 136 individuals (61 HCC patients and 75 individuals without HCC) using TaqMan qRT-PCR. Our results showed that 7 fusion genes were frequently detected in the serum samples of HCC patients, including MAN2A1-FER (100%), SLC45A2-AMACR (62.3%), ZMPSTE24-ZMYM4 (62.3%), Pten-NOLC1 (57.4%), CCNH-C5orf30 (55.7%), STAMBPL1-FAS (26.2%) and PCMTD1-SNTG1 (16.4%). We then divided the samples into training and testing cohorts based on the sample collection time: 82 individuals with samples collected before 2016 as the training cohort while 54 individuals with sample collected after 2015 as the testing cohort. Machine learning models was constructed based on the combination of different fusion genes with various cutoffs to predict the occurrence of HCC in the training cohort using leave-one-out-cross-validation approach. One of the machine learning models called 4-fusion genes logistic regression model (MAN2A1-FER&amp;lt;40, CCNH-C5orf30&amp;lt;38, SLC45A2-AMACR&amp;lt;41, Pten-NOLC1&amp;lt;40) produced a 91.5% accuracy, with a sensitivity of 87.1% and specificity of 94.1% in the training cohort. The same model generated an accuracy of 83.3%, with a sensitivity of 73.3% and specificity of 95.8% in testing cohort. When the training and testing cohorts were combined, the model produced an accuracy of 86%. When serum α-fetal protein (AFP) level was incorporated into the machine learning model, we found a 2-fusion gene+AFP logistic regression model (MAN2A1-FER&amp;lt;40, CCNH-C5orf30&amp;lt;38, AFP) generated an accuracy of 94.8% in the training cohort with a sensitivity of 93.5% and specificity of 96.3%. The same model generated 95% accuracy in both the testing cohort and the combined cohorts in the validation. Cancer treatment reduced most of the serum fusion transcript levels, reflecting the reduction of the tumor load. As a result, serum fusion gene machine learning models may serve as important tools in screening HCC and monitoring the impact of HCC treatment. Citation Format: Jian-Hua Luo, Yan-Ping Yu, Silvia Liu, David Geller. Serum fusion gene transcripts to predict liver cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7293.

Abstract 7469: Inflammation plays an important role in the progression of chronic myeloid leukemia

Abstract The development of Tyrosine Kinase Inhibitors (TKIs) resulted in a significant increase in the life expectancy of patients with chronic myeloid leukemia (CML). Nevertheless, TKIs still fail in a significant proportion of therapy-naïve patients, or their effectiveness is hampered by secondary resistance. It is therefore urgent to explore the underlying mechanisms in order to develop new therapeutic approaches to cure CML instead of controlling the disease with a lifelong TKI therapy. Using the ScltTA/TRE-BCR::ABL1 mouse model for chronic phase CML we show that BCR::ABL1 leads to the elevation of pro-inflammatory cytokines, known to be important in disease initiation and progression. This is supported by our data from CML patients, where we also observe higher levels of pro-inflammatory cytokines in the serum compared to healthy individuals. Furthermore, we demonstrate that BCR::ABL1 drives the expansion of bone marrow derived mast cells (BMMCs) and sensitizes them for FcεRI triggered degranulation. Interestingly, these BMMCs show differences in their lipid metabolism. Hence, sphingomyelin and lysophosphatidylcholine, both known to be involved in inflammation and cancer progression, are upregulated in BCR::ABL1-positive mast cells compared to their negative counterparts. By crossing in the Cpa3Cre mediated model for mast cell deficiency, we demonstrate for the first time that the lack of mast cells prevents the BCR::ABL1 induced upregulation of pro-inflammatory cytokines and also the development of splenomegaly. In addition, we were able to show that splenomegaly in CML patients is associated with high bone marrow mast cell counts and that an upregulation of pro-inflammatory cytokines in patient serum samples correlated with tryptase levels. In summary, our study identifies mast cells and their inflammatory cytokines as important factors in disease progression and suggests considering them as additional targets in CML therapy. Citation Format: Melanie Langhammer, Julia Schöpf, Timo Jaquet, Katharina Horn, Moritz Angel, Daniel Mohl, Simon Lagies, Corinna Spohr, Daniel Christen, Franziska Maria Uhl, Tiago Maié, Henrike Jacobi, Thorsten B. Feyerabend, Julia Huber, Marcus Panning, Cassian Sitaru, Ivan Costa, Robert Zeiser, Konrad Aumann, Heiko Becker, Till Braunschweig, Steffen Koschmieder, Bernd Kammerer, Khalid Shoumariyeh, Michael Huber, Mirle Schemionek-Reinders, Tilman Brummer, Sebastian Halbach. Inflammation plays an important role in the progression of chronic myeloid leukemia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7469.

Quantitative Proteomic Analysis Identifying and Evaluating TRAF6 and IL-8 as Potential Diagnostic Biomarkers in Neonatal Patients with Necrotizing Enterocolitis.

Necrotizing enterocolitis (NEC) is a common gastrointestinal complication in premature infants, resulting in high morbidity and mortality, and its early detection is crucial for accurate treatment and outcome prediction. Extensive research has demonstrated a clear correlation between NEC and extremely low birth weight, degree of preterm, formula feeding, infection, hypoxic/ischemic damage, and intestinal dysbiosis. The development of noninvasive biomarkers of NEC from stool, urine, and serum has attracted a great deal of interest because to these clinical connections and the quest for a deeper knowledge of disease pathophysiology. Therefore, this study aims to identify protein expression patterns in NEC and discover innovative diagnostic biomarkers. In this study, we recruited five patients diagnosed with NEC and paired necrotic segments of intestinal tissue with adjacent normal segments of intestine to form experimental and control groups. Quantitative proteomics tandem mass tagging (TMT) labeling technique was used to detect and quantify the proteins, and the expression levels of the candidate biomarkers in the intestinal tissues were further determined by quantitative polymerase chain reaction (RT-qPCR), Western blot analysis, Immunofluorescence methods and enzyme-linked immunosorbent assay (ELISA). A total of 6880 proteins were identified and quantified in patients with NEC. A significant disparity in protein expression was observed between necrotic and normal segments of intestinal tissue in NEC patients. A total of 55 proteins were found to be upregulated, and 40 proteins were found to be downregulated in NEC patients when using a p-value of < 0.05, and an absolute fold change of > 1.2 for analysis. GO function enrichment analysis showed the positive regulation of significant biological processes such as mitochondrial organization, vasoconstriction, rRNA catabolism, fluid shear stress response, and glycerol ether biosynthesis processes. Enrichment analysis also revealed essential functions such as ligand-gated ion channel activity, potassium channel activity, ligand-gated cation channel activity, ligand-gated ion channel activity, and ligand-gated channel activity, including molecular functions such as ligand-gated ion channel activity and mitotic events in this comparative group. Significant changes were found in endomembrane protein complex, membrane fraction, mitochondrial membrane fraction, membrane components, membrane intrinsic components, and other localized proteins. Additional validation of intestinal tissue and serum revealed a substantial increase in TRAF6 (tumor necrosis factor receptor-associated factor 6) and IL-8(Interleukin-8, CXCL8). The quantitative proteomic TMT method can effectively detect proteins with differential expression in the intestinal tissues of NEC patients. Proteins TRAF6 and CXCL8/IL-8 are significantly upregulated in the intestinal tissues and serum samples of patients and may serve as valuable predictor factors for NEC's early diagnosis.

Simultaneous SERS Sensing of Cysteine and Homocysteine in Blood Based on the CBT-Cys Click Reaction: Toward Precisive Diagnosis of Schizophrenia.

At present, there is a lack of sufficiently specific laboratory diagnostic indicators for schizophrenia. Serum homocysteine (Hcy) levels have been found to be related to schizophrenia. Cysteine (Cys) is a demethylation product in the metabolism of Hcy, and they always coexist with highly similar structures in vivo. There are few reports on the use of Cys as a diagnostic biomarker for schizophrenia in collaboration with Hcy, mainly because the rapid, economical, accurate, and high-throughput simultaneous detection of Cys and Hcy in serum is highly challenging. Herein, a click reaction-based surface-enhanced Raman spectroscopy (SERS) sensor was developed for simultaneous and selective detection of Cys and Hcy. Through the efficient and specific CBT-Cys click reaction between the probe containing cyan benzothiazole and Cys/Hcy, the tiny methylene difference between the molecular structures of Cys and Hcy was converted into the difference between the ring skeletons of the corresponding products that could be identified by plasmonic silver nanoparticle enhanced molecular fingerprint spectroscopy to realize discriminative detection. Furthermore, the SERS sensor was successfully applied to the detection in related patient serum samples, and it was found that the combined analysis of Cys and Hcy can improve the diagnostic accuracy of schizophrenia compared to a single indicator.

Assessing the sensitivity and specificity of myositis-specific and associated autoantibodies: a sub-study from the MyoCite cohort.

Myositis-specific and associated autoantibodies are important biomarkers in routine clinical use. We assessed local testing performance for myositis autoantibodies by comparing line immunoassay (LIA) to protein radio-immunoprecipitation and identifying clinical characteristics associated with each myositis autoantibody in the MyoCite cohort. Serum samples from patients within the MyoCite cohort, a well-characterized retro-prospective dataset of adult and juvenile idiopathic inflammatory myopathy (IIM) patients in Lucknow, India (2017-2020), underwent LIA at Sanjay Gandhi Postgraduate Institute of Medical Science (SGPGIMS), Lucknow. Immunoprecipitation of 147 IIM patients' serum samples (125 adult-onset, 22 juvenile-onset) was conducted at the University of Bath, with researchers blind to LIA results. LIA performance was assessed against immunoprecipitation as the reference standard, measuring sensitivity, specificity and inter-rater agreement. Univariate and multivariate logistic regression determined clinical associations for specific myositis-specific autoantibodies. Immunoprecipitation identified myositis autoantibodies in 56.5% (n = 83) of patient samples, with anti-Jo1 (n = 16; 10.9%) as the most common, followed by anti-MDA5 (n = 14, 9.5%). While LIA showed good agreement for anti-Jo1, anti-PL7 and anti-PL12 (Cohen's κ 0.79, 0.83 and 1, respectively), poor agreement was observed in other subgroups, notably anti-TIF1γ (Cohen's κ 0.21). Strongly positive samples, especially in myositis-specific autoantibodies, correlated more with immunoprecipitation results. Overall, 59 (40.1%) samples exhibited non-congruence on LIA and immunoprecipitation, and κ values for LIAs for anti-TIF1γ, anti-Ku, anti-PmScl, anti-Mi2 and anti-SAE ranged between 0.21 and 0.60. While LIA reliably detected anti-Jo1, anti-PL7, anti-PL12, anti-MDA5 and anti-NXP-2, it also displayed false positives and negatives. Its effectiveness in detecting other autoantibodies, such as anti-TIF1γ, was poor.

Cyclin A1 (CCNA1) inhibits osteoporosis by suppressing transforming growth factor-beta (TGF-beta) pathway in osteoblasts

BackgroundOsteoporosis is a genetic disease caused by the imbalance between osteoblast-led bone formation and osteoclast-induced bone resorption. However, further gene-related pathogenesis remains to be elucidated.MethodsThe aberrant expressed genes in osteoporosis was identified by analyzing the microarray profile GSE100609. Serum samples of patients with osteoporosis and normal group were collected, and the mRNA expression of candidate genes was detected by quantitative real-time polymerase chain reaction (qRT-PCR). The mouse cranial osteoblast MC3T3-E1 cells were treated with dexamethasone (DEX) to mimic osteoporosis in vitro. Alizarin Red staining and alkaline phosphatase (ALP) staining methods were combined to measure matrix mineralization deposition of MC3T3-E1 cells. Meanwhile, the expression of osteogenesis related genes including alkaline phosphatase (ALP), osteocalcin (OCN), osteopontin (OPN), Osterix, and bone morphogenetic protein 2 (BMP2) were evaluated by qRT-PCR and western blotting methods. Then the effects of candidate genes on regulating impede bone loss caused by ovariectomy (OVX) in mice were studied.ResultsCyclin A1 (CCNA1) was found to be significantly upregulated in serum of osteoporosis patients and the osteoporosis model cells, which was in line with the bioinformatic analysis. The osteogenic differentiation ability of MC3T3-E1 cells was inhibited by DEX treatment, which was manifested by decreased Alizarin Red staining intensity, ALP staining intensity, and expression levels of ALP, OCN, OPN, Osterix, and BMP2. The effects of CCNA1 inhibition on regulating osteogenesis were opposite to that of DEX. Then, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis demonstrated that genes negatively associated with CCNA1 were enriched in the TGF-beta signaling pathway. Inhibitor of TGF-beta signaling pathway partly reversed osteogenesis induced by suppressed CCNA1. Furthermore, suppressed CCNA1 relieved bone mass of OVX mice in vivo.ConclusionDownregulation of CCNA1 could activate TGF-beta signaling pathway and promote bone formation, thus playing a role in treatment of osteoporosis.

A Study on the Immunoregulatory Role of the PD1 Pathway in Juvenile Idiopathic Arthritis.

To investigate the immunoregulatory role of the Programmed-cell-Death-protein-1 (PD1) pathway, an inhibitory immune checkpoint, in Juvenile Idiopathic Arthritis (JIA). The PD1 expression on CD4+ and CD8+ T-cells was determined by flow cytometry and the PD1 soluble form (sPD1) levels by ELISA, in peripheral blood (PB)/serum and synovial fluid (SF) samples of JIA patients and healthy controls (HCs). We searched for any association in-between the biomarkers and with JIA activity. 101 Caucasian patients (69 female), aged 12 (8-15) years, and 20 HCs participated in this study. The PB PD1 expression on T-cells was higher in: a. JIA patients vs HCs (CD4: 1.24% vs 0.32%, p=0.007, CD8: 1.6% vs 0.4%, p=0.002). b. active vs inactive JIA (CD4: 1.44% vs 0.87%, p=0.072, CD8: 2.1% vs 0.93%, p=0.005). The SF PD1 expression on T-cells correlated strongly and positively with the disease activity (CD4: ρ=0.55, p=0.022, CD8: ρ=0.555, p=0.026). The SF PD1 expression on CD8 T-cells was higher in patients on-treatment vs those off-treatment (21.3% vs 5.83% p=0.004). The sPD1 levels were higher in the SF vs the serum (801pg/ml vs 367.2, p=0.013), without an association with disease activity. These results indicate an up-regulation of the PD1-pathway in JIA, at least quantitatively, especially in active disease. sPD1 is compartmentally produced at the inflamed joints. Further investigation in a larger sample of JIA patients may verify these observations and contribute to unravelling the precise role of the PD1 pathway in the pathogenesis and persistence of the joint inflammation.

Immunoassay Testing of Alpha-Gal Specific Immunoglobulin-E: Data from a National Reference Laboratory.

Immunoassay measurements of serum alpha-gal (AG) specific IgE (sIgE) enable antibody detection and quantification with high sensitivity and specificity and are essential for AG syndrome diagnosis and patient management. We here present and analyze results from over 15 000 patient serum samples tested using the ImmunoCAP (Thermo/Phadia) assay. AG-sIgE levels and positivity rates were correlated to patient age, gender, geographic location, repeat testing results, sIgE levels to co-tested red meat whole allergen extracts, and Rocky Mountain spotted fever (RMSF) serology performed on a subset of patient samples. Of the tested samples, 36.7% contained detectable (>0.1 KUA/L) AG-sIgE. Antibody levels were higher in patients of older age, in samples submitted from lower midwestern and southern states, and during the June-December period of the year. Specific IgE to co-tested red meat whole allergens showed moderate to strong correlation to AG-sIgE and were of lower levels. Samples with positive RMSF IgG titers (≥1:64) were of overall higher AG-IgE levels. Findings are consistent with the role of lone star ticks in AG syndrome pathogenesis. Levels of measured sIgE to AG are higher than co-tested sIgE to red meat whole allergen, consistent with the improved diagnostic performance of component-resolved testing.

Glypican-4 serum levels are associated with cognitive dysfunction and vascular risk factors in Parkinson’s disease

Glypicans are biomarkers for various pathologies, including cardiovascular disease, cancer and diabetes. Increasing evidence suggests that glypicans also play a role in the context of neurodegenerative disorders. Initially described as supporting functionality of synapses via glutamate receptors during CNS development, Glypican 4 (GPC-4) also plays a role in the context of dementia via tau hyperphosphorylation in Alzheimer’s disease, which is also a co-pathology in Parkinson’s disease dementia. However, clinical evidence of circulating GPC-4 in Parkinson’s disease (PD) is missing so far. We therefore investigated GPC-4 in biofluids of PD patients. We analyzed GPC-4 levels in cerebrospinal fluid (CSF, n = 140), serum (n = 80), and tear fluid samples (n = 70) of PD patients and control subjects in a similar age range by ELISA (serum, CSF) and western blot (tear fluid). Expression of circulating GPC-4 was confirmed in all three biofluids, with highest levels in serum. Interestingly, GPC-4 levels were age-dependent, and multiple regression analysis revealed a significant association between GPC-4 serum levels and MoCA score, suggesting an involvement of GPC-4 in PD-associated cognitive decline. Furthermore, stratification of PD patients for vascular risk factors revealed a significant increase of GPC-4 serum levels in PD patients with vascular risk factors. Our results suggest GPC-4 as a clinical biomarker for vascular risk stratification in order to identify PD patients with increased risk of developing dementia.

Transcriptomic Signatures of Neuronally Derived Extracellular Vesicles Reveal the Presence of Olfactory Receptors in Clinical Samples from Traumatic Brain Injury Patients.

Traumatic brain injury (TBI) is defined as an injury to the brain by external forces which can lead to cellular damage and the disruption of normal central nervous system functions. The recently approved blood-based biomarkers GFAP and UCH-L1 can only detect injuries which are detectable on CT, and are not sensitive enough to diagnose milder injuries or concussion. Exosomes are small microvesicles which are released from the cell as a part of extracellular communication in normal as well as diseased states. The objective of this study was to identify the messenger RNA content of the exosomes released by injured neurons to identify new potential blood-based biomarkers for TBI. Human severe traumatic brain injury samples were used for this study. RNA was isolated from neuronal exosomes and total transcriptomic sequencing was performed. RNA sequencing data from neuronal exosomes isolated from serum showed mRNA transcripts of several neuronal genes. In particular, mRNAs of several olfactory receptor genes were present at elevated concentrations in the neuronal exosomes. Some of these genes were OR10A6, OR14A2, OR6F1, OR1B1, and OR1L1. RNA sequencing data from exosomes isolated from CSF showed a similar elevation of these olfactory receptors. We further validated the expression of these samples in serum samples of mild TBI patients, and a similar up-regulation of these olfactory receptors was observed. The data from these experiments suggest that damage to the neurons in the olfactory neuroepithelium as well as in the brain following a TBI may cause the release of mRNA from these receptors in the exosomes. Hence, olfactory receptors can be further explored as biomarkers for the diagnosis of TBI.

Photo-sensitive peptide inducing targeted cross-linking in a one-step and reagent-, enzyme- and antibody-free detection of SARS-Cov-2 marker protein

Modern biosensing technology plays a crucial role in combating the spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). However, the associated assays remain costly, considering their extensive daily use. In response, we developed a simplified one-step SARS-CoV-2 protease assay that reduces both time and financial expenses. This approach eliminates the need for extra reagents, enzymes, or antibodies. The simplification involves a photo-sensitive Bengal red-tagged substrate peptide, allowing specific cross-linking upon protease-substrate recognition. This process forms a di-tyrosine product with a distinctive fluorescence signal readout, enabling the detection of SARS-CoV-2 in patient serum samples. This method anticipates a major reduction in assay costs in the near future.

Development of Drug Efficacy Testing Platform for Glomerulonephritis.

We developed a 3D glomeruli tissue chip for glomerulonephritis (GN) testing, featuring a gravity-driven glomerular filtration barrier (GFB) with human podocytes and endothelial cells with a bidirectional flow in the bottom channel. Using puromycin-induced GN, we observed decreased cell viability, increased albumin permeability, and reduced WT1 and nephrin compared to the normal GFB. Tacrolimus restored cell viability, reduced albumin permeability, and increased WT1 expression. Using serum from five membranous nephropathy (MN) patients, we created MN models using a GFB-mimicking chip. A notable decline in cell viability was observed in the serum-induced MN1 and MN2 models. However, tacrolimus restored it. Albumin permeability was reduced in the MN1, MN2, and MN5 models by tacrolimus treatment. MN1 displayed the best clinical response to tacrolimus, exhibiting increased expression of WT1 in chip-based evaluations after tacrolimus treatment. We successfully evaluated the efficacy of tacrolimus using puromycin-induced and serum-induced GN models on a chip that mimicked the structure and function of the GFB. The GFB-mimicking chip holds promise as a personalized platform for assessing drug efficacy using patient serum samples.