CCL4 as a potential serum factor in differential diagnosis of central nervous system inflammatory diseases and gliomas.

Computed tomography (CT) scans and magnetic resonance imaging (MRI) are commonly utilized to detect brain gliomas and central nervous system inflammation diseases. However, there are instances where depending solely on medical imaging for a precise diagnosis may result in unsuitable medications or treatments. Pathological analysis is regarded as the definitive method for diagnosing brain gliomas or central nervous system inflammation diseases. To achieve this, a craniotomy or stereotaxic biopsy is necessary to collect brain tissue, which can lead to complications such as cerebral hemorrhage, neurological deficits, cerebrospinal fluid leaks, and cerebral edema. Consequently, the advancement of non-invasive or minimally invasive diagnostic techniques is currently a high priority. This study included samples from four glioma patients and five patients with central nervous system inflammatory diseases, comprising both serum and paired cerebrospinal fluid (CSF). A total of 40 human cytokines were identified in these samples. We utilized a receiver operating characteristic (ROC) analysis to assess the sensitivity and specificity for distinguishing central nervous system inflammation diseases and gliomas. Additionally, we examined the correlation of these factors between serum and CSF in the patients. Ultimately, the identified factors were validated using serum from patients with clinically confirmed gliomas and central nervous system inflammation diseases followed by detection and statistical analysis through ELISA. The levels of serum factors IL-4, IFN-α, IFN-γ, IL-6, TNF-α, CCL4, CCL11, and VEGF were found to be significantly higher in gliomas compared with inflammatory diseases of the central nervous system (p < 0.05). Furthermore, a strong correlation was observed between the levels of CCL4 in serum and CSF, with a correlation coefficient of r = 0.92 (95% CI = 0.20-0.99, p = 0.027). We gathered more clinical samples to provide further validation of the abundance of CCL4 expression. A clinical study analyzing serum samples from 19 glioma patients and 22 patients with central nervous system inflammation diseases revealed that CCL4 levels were notably elevated in the inflammatory group compared with the glioma group (p < 0.001). These results suggest that assessing serum CCL4 levels may be useful in distinguishing those patients for clinical diagnostic purposes.

Exploring the Gut Microbiota Landscape in Cow Milk Protein Allergy: Clinical Insights and Diagnostic Implications in Pediatric Patients.

Cow milk protein allergy (CMPA) is a significant health concern characterized by adverse immune reactions to cow milk proteins. Biomarkers for the accurate diagnosis and prognosis of CMPA are lacking. This study analyzed the clinical features of CMPA, and 16S RNA sequencing was used to investigate potential biomarkers through fecal microbiota profiling. Children with CMPA exhibit a range of clinical symptoms, including gastrointestinal (83% of patients), skin (53% of patients), and respiratory manifestations (26% of patients), highlighting the complexity of this condition. Laboratory analysis revealed significant differences in red cell distribution width (RDW) and inflammatory markers between the CMPA and control groups, suggesting immune activation and inflammatory responses in CMPA. Microbial diversity analysis revealed higher specific diversity indices in the CMPA group compared with those in control group, with significant differences at the genus and species levels. Bacteroides were more abundant in the CMPA group, whereas Bifidobacterium, Ruminococcus, Faecalibacterium, and Parabacteroides were less abundant. The control group exhibited a balanced microbial profile, with a predominant presence of Bifidobacterium bifidum and Akkermansia muciniphila. The significant abundance of Bifidobacterium in the control group (23.19% vs 9.89% in CMPA) was associated with improved growth metrics such as height and weight, suggesting its potential as a probiotic to prevent CMPA and enhance gut health. Correlation analysis linked specific microbial taxa such as Coprococcus and Bifidobacterium to clinical parameters such as family allergy history, weight and height, providing insights into CMPA pathogenesis. Significant differences in bacterial abundance suggested diagnostic potential, with a panel of 6 bacteria achieving high predictive accuracy (area under curve (AUC) = 0.8708). This study emphasizes the complex relationship between the gut microbiota and CMPA, offering valuable insights into disease mechanisms and diagnostic strategies.

Metabolomics study of Shenling Baizhu Powder in the treatment of multiple organ dysfunction syndrome in the elderly (MODSE) with malnutrition.

Malnutrition is an important risk factor for multiple organ dysfunction syndrome in the elderly (MODSE) and seriously affects the occurrence, progression and prognosis of MODSE. Shenling Baizhu Power (SBP), a classic formula from traditional Chinese medicine (TCM), when integrated with enteral nutrition, has been proven to be an effective clinical strategy for treating the patients of MODSE with malnutrition. This study aimed to investigate the metabolic changes during disease occurrence and SBP treatment, and to discover potential metabolic biomarkers for the diagnosis and efficacy evaluation. An untargeted metabolomics strategy based on UHPLC-Q-Orbitrap-HRMS was performed to reveal the differential serum metabolites between MODSE patients with malnutrition (n=59) and healthy controls (n=33), and those between patients treated with enteral nutrition (n=31) and SBP combined with enteral nutrition (n=28). Significantly different metabolites were identified and mapped onto the network of metabolic pathways to explore the metabolic disorders caused by the disease and the metabolic regulatory mechanism of SBP. Additionally, the area under the curve (AUC) of the potential biomarkers was investigated for predicting the disease and the efficacy of SBP. Sixty differential metabolites were identified between the disease and control groups, which were mainly related to amino acid metabolism, energy metabolism and carbohydrate metabolism. In the same way, 50 differential metabolites associated with SBP treatment were identified, which improved metabolic abnormalities in vivo mainly by regulating the above-mentioned metabolic pathways. Finally, 13 differential metabolites in common were selected as the potential biomarkers and the AUC value of each biomarker was within the range of 0.8-1.0, indicating that these biomarkers had high prediction accuracy for the diagnosis and efficacy evaluation of MODSE with malnutrition. This study demonstrates that serum metabolomics approaches based on the UHPLC-Q-Orbitrap-HRMS platform can be applied as a tool to reveal the metabolic changes induced by MODSE with malnutrition and SBP can play an important role in the clinical application.

Integrated single-cell and bulk RNA sequencing identifies POSTN as a potential biomarker and therapeutic target for rheumatoid arthritis.

BACKGROUND: This study aimed to integrate single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data to identify potential biomarkers and therapeutic targets for rheumatoid arthritis (RA). METHOD: Firstly, we obtained the synovial scRNA-seq data from the Immport database and bulk RNA-seq data from the Gene Expression Omnibus (GEO) database. Then, we used weighted gene correlation network analysis (WGCNA) to screen for module genes most relevant to RA and intersected them with the differentially expressed genes (DEGs) obtained from scRNA-seq and bulk RNA-seq to obtain intersecting genes. Next, we constructed a protein-protein interaction (PPI) network of hub genes using the STRING database and Cytoscape software and validated its expression using external validation cohorts. Finally, we performed immune cell infiltration analysis using CIBERSORT and explored the expression and drug binding activity of key gene using clinical samples and molecular docking, respectively. RESULT: We identified six cellular subgroups through dimensionality reduction and clustering, and fibroblasts may be the most important cell cluster in RA based on pseudotime and cell-cell communication analyses. Subsequently, we intersected module genes with DEGs obtained from scRNA-seq and bulk RNA-seq and constructed a PPI network of hub genes (BGN, COL11A1, COL1A1, GUCY1A1, POSTN). In external validation cohorts, POSTN was highly expressed and demonstrated the highest diagnostic performance (AUC = 0.716). In subsequent analyses, we defined POSTN as a key gene and found that its expression level was positively correlated with M2 macrophages in immune cell infiltration analysis. Additionally, POSTN was upregulated in clinical samples and exhibited favorable binding activity with nine anti-rheumatoid arthritis drugs (affinity ≤ -6.0 kcal/mol). CONCLUSION: Through bioinformatics analysis, clinical sample validation, and molecular docking, we found that POSTN was highly expressed in RA and stably bound to common anti-rheumatoid arthritis drugs, which will provide new insights into potential biomarkers and therapeutic targets for RA.

Exploratory screening for micro-RNA biomarkers in canine multicentric lymphoma.

Lymphoma is one of the most frequent hematopoietic tumors in dogs and shares similar features with human counterparts. MicroRNAs (miRNA, small non-coding RNAs) are pivotal in gene regulation fine tuning and cancer hallmarks are influenced by their aberrant expression. Consequently, miRNA biomarkers may assist predicting therapeutic response and clinical outcome by providing less-invasive novel diagnostics tools. The aim of this study was to detect dysregulated miRNAs in lymphomatous lymph node tissues in comparison to lymph node material or PBMCs from healthy control dogs. Potential significant differences in miRNA expression profiles between four lymphoma entities were evaluated. A customized PCR array was utilized to profile 89 canine target miRNAs. Quantification was performed using qPCR, relative expression was determined by the delta-delta Ct method, and p-values were calculated with student's t-test. In the 14 diffuse large B-cell lymphoma (DLBCL) patients, 28 and 24 different miRNAs were significantly dysregulated compared to lymph node material or PBMCs. Sixteen miRNAs occurred in both control groups, with 12 miRNAs being down- and four miRNAs being upregulated. The six peripheral T-cell lymphoma (PTCL) samples showed 24 and 25 dysregulated miRNAs when compared to the healthy controls. A combined analysis of DLBCL and PTCL samples revealed seven shared and 19 differently expressed miRNAs. Potential biomarkers in T- and B-cell lymphoma could be the miRNA-17/92 cluster and miRNA-181-family together with miRNA-34a and miRNA-150. Diagnostic utility of potential biomarkers must be validated in larger, prospective cohorts of canine lymphoma cases and in higher numbers of physiological patient material.

Identification of the Expression of TIE1 and Its Mediated Immunosuppression in Gastric Cancer.

Background: Recently, various evidence has confirmed that Tyrosine Kinase with Immunoglobulin-like and EGF-like domains 1 (TIE1) promotes tumor growth in many cancers. However, the precise mechanism underlying TIE1's involvement in Gastric Cancer (GC) remains elusive. This research aimed to investigate the biological function of TIE1 in regulating GC progression. Methods: The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), GEPIA2.0, Sangerbox3.0 and TIMER databases were used to analyze the TIE1 expression. Immunohistochemistry (IHC) was used to demonstrate the expression of TIE1. TCGA, GEPIA2.0 and Kaplan-Meier were utilized for survival analysis and to explore the association of TIE1 with clinicopathological features. Protein-Protein Interaction (PPI) networks were constructed using Cytoscape. The potential molecular mechanism of TIE1 was investigated by Gene Ontology (GO), Kyoto Encyclopedia of Gene Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA). We studied the relationships between TIE1 and mutations, immune checkpoints (ICs), tumor mutational burden (TMB), as well as microsatellite instability (MSI) to explore the underlying mechanism of immunity in GC. Results: Compared with normal tissue, TIE1 was significantly overexpressed in GC tissues (p = 0.0072) and was associated with poor survival (P < 0.05). According to GO and KEGG enrichment analyses, TIE1 was enriched in signal pathways related to the occurrence, invasion, and migration of malignant tumors (i.e., PI3K-Akt signaling pathway, Calcium signaling pathway, etc.). Immune infiltration analysis suggested that TIE1 is positively correlated with macrophages M2 and negatively correlated with Mast cells, naive B cells and Follicular helper T cells (TFH), which may be a contributing factor to tumor progression. Furthermore, the research on the tumor microenvironment (TME) and tumor purity also proved that TIE1 may be an oncogene. Mutation analysis showed that the high expression group of TIE1 had a higher frequency of mutations in TP53 and ARID1, while the TMB score was lower. Conclusion: TIE1 might be an oncogene via regulating dysregulated immune infiltration to cause immunosuppression in GC and could be identified as a biomarker for prognosis and a therapeutic target for GC.

A signature of seven hypoxia-related lncRNAs is a potential biomarker for predicting the prognosis of melanoma.

Melanoma is the most aggressive type of skin cancer and has a high mortality rate once metastasis occurs. Hypoxia is a universal characteristic of the microenvironment of cancer and a driver of melanoma progression. In recent years, long noncoding RNAs (lncRNAs) have attracted widespread attention in oncology research. In this study, screening was performed and revealed seven hypoxia-related lncRNAs AC008687.3, AC009495.1, AC245128.3, AL512363.1, LINC00518, LINC02416 and MCCC1-AS1 as predictive biomarkers. A predictive risk model was constructed via univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses. Patients were grouped according to the model risk score, and Kaplan-Meier analysis was performed to compare survival between groups. Functional and pathway enrichment analyses were performed to compare gene set enrichment between groups. Moreover, a nomogram was constructed with the risk score as a variable. In both the training and validation sets, patients in the low-risk group had better overall survival than did those in the high-risk group (P<0.001). The 3-, 5- and 10-year area under the curve (AUC) values for the nomogram model were 0.821, 0.795 and 0.820, respectively. Analyses of immune checkpoints, immunotherapy response, drug sensitivity, and mutation landscape were also performed. The results suggested that the low-risk group had a better response to immunotherapeutic. In addition, the nomogram can effectively predict the prognosis and immunotherapy response of melanoma patients. The signature of seven hypoxia-related lncRNAs showed great potential value as an immunotherapy response biomarker, and these lncRNAs might be treatment targets for melanoma patients.

Calcium-sensing Receptor, a Potential Biomarker Revealed by Large-scale Public Databases and Experimental Verification in Metastatic Breast Cancer.

INTRODUCTION: Breast cancer (BC) is a common cancer characterized by a high molecular heterogeneity. Therefore, understanding its biological properties and developing effective treatments for patients with different molecular features is imperative. Calcium-sensing receptor (CaSR) has been implicated in several regulatory functions in various types of human cancers. However, its underlying pathological mechanism in BC progression remains elusive. METHODS: We utilized The Cancer Genome Atlas and Gene Expression Omnibus databases to explore the function of CaSR in the metastasis of BC. Gene ontology analysis, Kyoto Encyclopedia of Genes and Genomes analysis, and Gene Set Enrichment Analysis of biological processes and cell signaling pathways revealed that CaSR could be activated or inhibited. Importantly, quantitative reverse transcriptase-polymerase chain reaction and western blotting were used to verify the gene expression of the CaSR. Wound healing and transwell assays were conducted to assess the effect of CaSR on the migration of BC cells. RESULTS: We demonstrated that CaSR expression in metastatic BC was higher than that in non-metastatic BC. It is the first time that database information has been used to reveal the biological process and molecular mechanism of CaSR in BC. Moreover, the CaSR expression in normal breast epithelial cells was notably less compared to that in BC cells. The activation of CaSR by Cinacalcet (a CaSR agonist) significantly enhanced the migration of BC cells, whereas NPS-2143 (a CaSR antagonist) treatment dramatically inhibited these effects. CONCLUSION AND FUTURE PERSPECTIVE: Bioinformatics techniques and experiments demonstrated the involvement of CaSR in BC metastasis. Our findings shed new light on the receptor therapy and molecular pathogenesis of BC, and emphasize the crucial function of CaSR, facilitating the metastasis of BC.

EnsemBic: An effective ensemble of biclustering to identify potential biomarkers of esophageal squamous cell carcinoma.

The development of functionally enriched and biologically competent biclustering algorithm is essential for extracting hidden information from massive biological datasets. This paper presents a novel biclustering ensemble called EnsemBic based on p-value, which calculates the functional similarity of genetic associations. To validate the effectiveness and robustness of EnsemBic, we apply three well-known biclustering techniques, viz. Laplace Prior, iBBiG, and xMotif to implement EnsemBic and have been compared using different leading parameters. It is observed that the EnsemBic outperforms its competing algorithms in several prominent functional and biological measures. Next, the biclusters obtained from EnsemBic are used to identify potential biomarkers of Esophageal Squamous Cell Carcinoma (ESCC) by exploring topological and biological relevance with reference to the elite genes, attained from genecards. Finally, we discover that the genes F2RL3, APPL1, CALM1, IFNGR1, LPAR1, ANGPT2, ARPC2, CGN, CLDN7, ATP6V1C2, CEACAM1, FTL, PLAU,PSMB4, and EPHB2 carry both the topological and biological significance of previously established ESCC elite genes. Therefore, we declare the aforementioned genes as potential biomarkers of ESCC.

Comparison of the Pathological Complete Response Rate and Survival Between HER2-Low and HER2-Zero Breast Cancer in Neoadjuvant Chemotherapy Setting: A Systematic Review and Meta-Analysis.

Although HER2-low breast cancer (BC) constitutes almost 50% of all BC types, its impact on the pathological complete response (pCR) rate and survival in early BC is uncertain. As a result, a systematic review was conducted to compare the pCR rate and survival of HER2-low and HER2-zero BC in the neoadjuvant chemotherapy (NACT) setting. Two reviewers independently performed literature searches using EMBASE, PubMed, and Cochrane Libraries internet databases up to June 2023. Finally, 29 studies with 178,294 patients were included. HER2-low BC had a considerably lower pCR rate compared to HER2-zero BC in the entire population (Risk Ratio [RR] = 0.68, P < .001) and in the hormone receptor (HR)-positive subgroup (RR = 0.73, P = .009), but not in the HR-negative subgroup (RR = 0.99, P = .755). Furthermore, patients with HER2-low BC exhibited prolonged disease-free survival (DFS) and overall survival (OS) compared to those with HER2-zero BC, observed in both the entire cohort (DFS: P = .004; OS: P = .008) and the HR-negative subgroup (DFS: P = .009; OS: P < .001). In the HR-positive population, OS was superior in HER2-low BC patients (P < .001), whereas no significant differences in DFS were observed (P = .064). Our findings imply that the pCR rate and prognosis of HER2-low BC are distinguished from those of HER2-zero BC in early BC treated with NACT, which contributes to a better knowledge of the BC subgroup.

Quantitative proteomic analysis to identify potential biomarkers linked to quality traits of beef tripe from different sources.

In this work, the 4D data-independent acquisition (DIA) quantitative strategy was used for differential proteomic analysis of four beef tripe samples from different sources to explore the associations between differentially expressed proteins (DEPs) and meat quality traits. A total of 68 shared DEPs were identified in all comparison groups, which were mainly involved in phosphorylation signaling pathway, peroxisome proliferator-activated receptor (PPAR) signaling pathway, and glucuronic acid pathway. In the correlation analysis between DEPs and quality traits of beef tripe, it was found that 21 proteins were significantly associated with the quality traits in beef tripe, which could be considered as the potential biomarkers of beef tripe quality. This study has successfully uncovered the protein composition of beef tripe for the very first time, which helps to understand the key proteins and biological processes associated with the quality traits of beef tripe from different sources and improve the quality control of beef tripe.

Neuropeptides as Potential Biomarkers in Vascular Dementia.

Neuropeptides are endogenous active substances within the central and peripheral nervous systems that play important roles in a wide range of brain functions, including metabolism, food intake, social behavior, reproduction, learning, sleep, and wakefulness. This article reviews recent advances in the involvement of neuropeptides in vascular dementia. Neuropeptides are present in the brain as chemical signals and last for nearly 50 years. Peptide hormones are chemical signals of the endocrine system. Thus, neuropeptides are the most diverse class of signaling molecules in the brain, involving the genomes of many mammals, encoding neuropeptide precursors and many bioactive neuropeptides. Here the aim is to describe the recent advances in classical neuropeptides, as well as putative neuropeptides from other families, in the control of or as diagnostic tools for vascular dementia. Additionally, its molecular mechanisms are described to explore new avenues of treatment and early diagnosis, as there is increasing evidence that dysregulation of vascular processes is associated with different pathological conditions.

miR-16-5p aggravates sepsis-associated acute kidney injury by inducing apoptosis.

Sepsis-associated acute kidney injury (S-AKI) is a common disease in pediatric intensive care units (ICU) with high morbidity and mortality. The newly discovered results indicate that microRNAs (miRNAs) play an important role in the diagnosis and treatment of S-AKI and can be used as markers for early diagnosis. In this study, the expression level of miR-16-5p was found to be significantly upregulated about 20-fold in S-AKI patients, and it also increased by 1.9 times in the renal tissue of S-AKI mice. Receiver operating characteristic (ROC) curve analysis showed that miR-16-5p had the highest predictive accuracy in the diagnosis of S-AKI (AUC = 0.9188). In vitro, the expression level of miR-16-5p in HK-2 cells treated with 10 µg/mL lipopolysaccharide (LPS) increased by more than 2 times. In addition, LPS-exposed renal tissue and HK-2 cells lead to upregulation of inflammatory cytokines IL-6, IL-1ß, TNF-a, and kidney damage molecules kidney injury molecule-1 (KIM-1), neutrophil gelatinase-associated lipocalin (NGAL). However, inhibition of miR-16-5p significantly mitigated LPS expose-mediated kidney injury and inflammation. Furthermore, LPS-exposed HK-2 cells increased more than 1.7-fold the expression levels of Bax and caspase-3, decreased 3.2-fold the expression level of B-cell lymphoma-2 (Bcl-2), and significantly promoted the occurrence of apoptosis. MiR-16-5p mimic further increased LPS-induced apoptosis in HK-2 cells. Nevertheless, inhibition of miR-16-5p significantly attenuated this effect. In summary, up-regulation of miR-16-5p expression can significantly aggravate renal injury and apoptosis in S-AKI, which also proves that miR-16-5p can be used as a potential biomarker to promote early identification of S-AKI.

SEL1L3 as a link molecular between renal cell carcinoma and atherosclerosis based on bioinformatics analysis and experimental verification.

BACKGROUND: Renal cancer, the most common type of kidney cancer, develops in the renal tubular epithelium. Atherosclerosis of the aorta is the primary cause of atherosclerosis. However, the underlying mechanisms remain unclear. METHODS: The renal clear cell carcinoma RNA sequence profile was obtained from The Cancer Genome Atlas (TCGA) database, and the atherosclerosis datasets GSE28829 and GSE43292 based on GPL570 and GPL6244 was obtained from the Gene Expression Omnibus (GEO) database. The difference and hub genes were identified by the Limma protein-protein interaction (PPI) network in R software. Functional enrichment, survival, and immunoinfiltration analyses were performed. The role of SEL1L3 in the ErbB/PI3K/mTOR signaling pathway, apoptosis, invasion, cell cycle, and inflammation was analyzed using western blotting. RESULTS: 764 DEGs were identified from TCGA Kidney Renal Clear Cell Carcinoma (KIRC) dataset. A total of 344 and 117 DEGs were screened from the GSE14762 and GSE53757 datasets, respectively. Functional enrichment analysis results primarily indicated enrichment in the transporter complex, DNA-binding transcription activator activity, morphogenesis of the embryonic epithelium, stem cell proliferation, adrenal overactivity and so on. Fifteen common DEGs overlapped among the three datasets. The PPI network revealed that SEL1L3 was the core gene. Survival analysis showed that lower SEL1L3 expression levels led to a worse prognosis. Immune cell infiltration analysis showed that SEL1L3 expression was significantly correlated with antibody-drug conjugates (aDC), B cells, eosinophils, interstitial dendritic cells (iDC), macrophages, and more. CONCLUSIONS: SEL1L3 plays an important role in renal clear cell carcinoma and atherosclerosis and may be a potential link between them.

KIF20A as a potential biomarker of renal and bladder cancers based on bioinformatics and experimental verification.

BACKGROUND: Bladder cancer (BC) is a malignant tumor that occurs in the bladder wall and often appears in elderly individuals. Renal cancer (RC) arises from the renal tubular epithelium, but its molecular mechanism remains unclear. METHODS: We downloaded RC datasets (GSE14762 and GSE53757) and a BC dataset (GSE121711) to screen differentially expressed genes (DEGs). We also performed weighted gene coexpression network analysis (WGCNA). We created a protein-protein interaction (PPI) network and performed functional enrichment analysis, such as gene set enrichment analysis (GSEA). Heatmaps were made for gene expression. Survival analysis and immunoinfiltration analysis were performed. Comparative toxicogenomics database (CTD) analysis was performed to find the relationship between disease and hub genes. Western blotting was performed to verify the role of KIF20A in apoptosis. RESULTS: A total of 764 DEGs were identified. The GSEA showed that the DEGs were mainly enriched in organic acid metabolism, drug metabolism, mitochondria, and metabolism of cysteine and methionine. The PPI network in GSE121711 showed that KIF20A was a hub gene of renal clear cell carcinoma. Where the expression level of KIF20A was higher, the prognosis of patients was worse. CTD analysis showed that KIF20A was associated with inflammation, proliferation, and apoptosis. KIF20A expression in the RC group was upregulated, as shown by western blotting. The core proteins (including pRB Ser 780, CyclinA, E2F1, CCNE1, and CCNE2) in the pRB Ser 780/CyclinA signaling pathway were also upregulated in the RC group. CONCLUSIONS: KIF20A might be a novel biomarker for researching renal and bladder cancers.

Screening biomarkers for Sjogren's Syndrome by computer analysis and evaluating the expression correlations with the levels of immune cells.

Background: Sjögren's syndrome (SS) is a systemic autoimmune disease that affects about 0.04-0.1% of the general population. SS diagnosis depends on symptoms, clinical signs, autoimmune serology, and even invasive histopathological examination. This study explored biomarkers for SS diagnosis. Methods: We downloaded three datasets of SS patients' and healthy pepole's whole blood (GSE51092, GSE66795, and GSE140161) from the Gene Expression Omnibus (GEO) database. We used machine learning algorithm to mine possible diagnostic biomarkers for SS patients. Additionally, we assessed the biomarkers' diagnostic value using the receiver operating characteristic (ROC) curve. Moreover, we confirmed the expression of the biomarkers through the reverse transcription quantitative polymerase chain reaction (RT-qPCR) using our own Chinese cohort. Eventually, the proportions of 22 immune cells in SS patients were calculated by CIBERSORT, and connections between the expression of the biomarkers and immune cell ratios were studied. Results: We obtained 43 DEGs that were mainly involved in immune-related pathways. Next, 11 candidate biomarkers were selected and validated by the validation cohort data set. Besides, the area under curves (AUC) of XAF1, STAT1, IFI27, HES4, TTC21A, and OTOF in the discovery and validation datasets were 0.903 and 0.877, respectively. Subsequently, eight genes, including HES4, IFI27, LY6E, OTOF, STAT1, TTC21A, XAF1, and ZCCHC2, were selected as prospective biomarkers and verified by RT-qPCR. Finally, we revealed the most relevant immune cells with the expression of HES4, IFI27, LY6E, OTOF, TTC21A, XAF1, and ZCCHC2. Conclusion: In this paper, we identified seven key biomarkers that have potential value for diagnosing Chinese SS patients.

Altered DNA methylome profiles of blood leukocytes in Chinese patients with mild cognitive impairment and Alzheimer's disease.

Objective: DNA methylation plays a potential role in the pathogenesis of Alzheimer's disease (AD). However, little is known about the global changes of blood leukocyte DNA methylome profiles from Chinese patients with mild cognitive impairment (MCI) and with AD, or the specific DNA methylation-based signatures associated with MCI and AD. In this study, we sought to dissect the characteristics of blood DNA methylome profiles in MCI- and AD-affected Chinese patients with the aim of identifying novel DNA methylation biomarkers for AD. Methods: In this study, we profiled the DNA methylome of peripheral blood leukocytes from 20 MCI- and 20 AD-affected Chinese patients and 20 cognitively healthy controls (CHCs) with the Infinium Methylation EPIC BeadChip array. Results: We identified significant alterations of the methylome profiles in MCI and AD blood leukocytes. A total of 2,582 and 20,829 CpG sites were significantly and differentially methylated in AD and MCI compared with CHCs (adjusted p < 0.05), respectively. Furthermore, 441 differentially methylated positions (DMPs), aligning to 213 unique genes, were overlapped by the three comparative groups of AD versus CHCs, MCI versus CHCs, and AD versus MCI, of which 6 and 5 DMPs were continuously hypermethylated and hypomethylated in MCI and AD relative to CHCs (adjusted p < 0.05), respectively, such as FLNC cg20186636 and AFAP1 cg06758191. The DMPs with an area under the curve >0.900, such as cg18771300, showed high potency for predicting MCI and AD. In addition, gene ontology and pathway enrichment results showed that these overlapping genes were mainly involved in neurotransmitter transport, GABAergic synaptic transmission, signal release from synapse, neurotransmitter secretion, and the regulation of neurotransmitter levels. Furthermore, tissue expression enrichment analysis revealed a subset of potentially cerebral cortex-enriched genes associated with MCI and AD, including SYT7, SYN3, and KCNT1. Conclusion: This study revealed a number of potential biomarkers for MCI and AD, also highlighted the presence of epigenetically dysregulated gene networks that may engage in the underlying pathological events resulting in the onset of cognitive impairment and AD progression. Collectively, this study provides prospective cues for developing therapeutic strategies to improve cognitive impairment and AD course.

[Mechanism of famous classical formula Huaihua Powder in treatment of ulcerative colitis based on metabonomics].

Ultra-high performance liquid chromatography-quadrupole-time of flight tandem mass spectrometry(UHPLC-Q-TOF-MS) was employed in this study to observe the effect of Huaihua Powder on the serum metabolites of mice with ulcerative colitis and reveal the mechanism of Huaihua Powder in the treatment of ulcerative colitis. The mouse model of ulcerative colitis was established by dextran sodium sulfate salt(DSS). The therapeutic effect of Huaihua Powder on ulcerative colitis was preliminarily evaluated based on the disease activity index(DAI), colon appearance, colon tissue morphology, and the content of inflammatory cytokines such as tumor necrosis factor-α(TNF-α), interleukin-6(IL-6), and interleukin-1ß(IL-1ß). UHPLC-Q-TOF-MS was employed to profile the endogenous metabolites of serum samples in blank control group, model group, and low-, medium-, and high-dose Huaihua Powder groups. Multivariate analyses such as principal component analysis(PCA), partial least squares discriminant analysis(PLS-DA), and orthogonal partial least squares discriminant analysis(OPLS-DA) were performed for pattern recognition. Potential biomarkers were screened by Mass Profiler Professional(MPP) B.14.00 with the thresholds of fold change≥2 and P<0.05. The metabolic pathways were enriched by MetaboAnalyst 5.0. The results showed that Huaihua Powder significantly improved the general state and colon tissue morphology of mice with ulcerative colitis, reduced DAI, and lowered the levels of TNF-α, IL-6, and IL-1ß in serum. A total of 38 potential biomarkers were predicted to be related to the regulatory effect of Huaihua Powder, which were mainly involved in glycerophospholipid metabolism, glycine, serine, and threonine metabolism, mutual transformation of glucuronic acid, and glutathione metabolism. This study employed metabolomics to analyze the mechanism of Huaihua Powder in the treatment of ulcerative colitis, laying a foundation for the further research.

The brain-specific upregulation of CARD11 in response to avian brain-neurotropic virus infection serves as a potential biomarker.

Avian neurotropic viruses are critical problems in poultry industry causing severe central nervous system (CNS) damage with neuroinvasive and neurovirulence properties. Biomarker of neurotropic viral intracranial invasion is of great application value for the diagnosis, but that of avian neurotropic viruses remains elusive. Previously, we found that chicken caspase recruitment domain family, member 11 (CARD11) was only upregulated in virulent Newcastle disease virus-infected chickens and in chicken primary neuronal cells. In this study, CARD11 was systemically expressed in chickens and pigeons detected by absolute qPCR and immunohistochemical (IHC) assay. After virus challenging, only avian neurotropic viruses (avian encephalomyelitis virus [AEV] and pigeon paramyxovirus type 1 [PPMV-1]) except Marek's disease virus (MDV) can invade brain and cause pathological changes. The relative mRNA expression of CARD11 was brain-upregulated in AEV- or PPMV-1-infected animals, rather than MDV and non-neurotropic viruses (fowl adenovirus serotype 4 [FAdV-4] and infectious bronchitis virus [IBV]). Similarly, the protein expression of CARD11 was only upregulated in the cerebra and cerebella infected by avian brain-neurotropic virus using IHC assay. And there were no correlations between the change level of CARD11 and viral load. Our preliminary data suggested that avian CARD11 may be a potential brain biomarker for avian brain-neurotropic virus invasion.