Assay for interferon gamma release as a novel marker in pediatric patients with systemic lupus erythematosus.

BACKGROUND: The interferon-gamma (IFN-γ) release assay (IGRA) is an important laboratory diagnosis for latent Mycobacterium tuberculosis (TB) infection. The TB-IGRA measures the release of IFN-γ from peripheral blood cells, who are exposed to TB antigen (Ag), mitogen (MT), or negative/nil control (NL) in vitro. While, an exceptional higher TB Ag-NL level will reflect an elevation of peripheral lymphocytes released IFN-γ in a same condition. Therefore, we found that the elevated levels of TB Ag-NL could become a new biomarker for the diagnosis and treatment of pediatric systemic lupus erythematosus (SLE) patients. METHODS: We have analyzed the clinical data of 776 children who are underwent TB-IGRA testing in the Department of Allergy and Rheumatology of Guangzhou Women and Children's Medical Center from 2018 to 2020. To investigate the association between TB Ag-NL and SLE, we have analyzed the clinical data of 47 SLE patients and TB Ag-NL testing results, and then evaluated the association between TB Ag-NL and SLE disease activity. RESULTS: The TB Ag-NL levels were significantly higher in patients with active SLE than those in inactive SLE (p = 0.0002). The TB Ag-NL levels were positively correlated with the SLE disease activity index (SLEDAI) and laboratory diagnosis parameters. The mean value of TB Ag-NL in SLE patients (0.04191 ± 0.07955, IU/mL) were significantly higher than those in patients with juvenile dermatomyositis (JDM) (0.0158 ± 0.0337, IU/mL, p = 0.036), juvenile idiopathic arthritis (JIA) (0.0162 ± 0.0388, IU/mL, p = 0.001), and healthy controls (HC) (0.0001 ± 0.0027, IU/mL, p = 0.0003). Therefore, the elevated TB Ag-NL levels could serve as a potential diagnostic biomarker of SLE, especially for the active SLE. CONCLUSION: The detection of IFN-γ release levels by the TB-IGRA may be useful to assess SLE disease activity in pediatric patients with active SLE.

Comprehensive pan-cancer analysis of ZNF337 as a potential diagnostic, immunological, and prognostic biomarker.

BACKGROUND: Zinc Finger Protein 337 (ZNF337) is a novel Zinc Finger (ZNF) protein family member. However, the roles of ZNF337 in human cancers have not yet been investigated. METHODS: In this study, with the aid of TCGA databases, GTEx databases, and online websites, we determined the expression levels of ZNF337 in pan-cancer and its potential value as a diagnostic and prognostic marker for pan-cancer and analyzed the relationship between ZNF337 expression and immune cell infiltration and immune checkpoint genes. We then focused our research on the potential of ZNF337 as a biomarker for diagnostic and prognostic in KIRC (kidney renal clear cell carcinoma) and validated in the E-MTAB-1980 database. Moreover, the expression of ZNF337 was detected through qRT-PCR and Western blotting (WB). CCK-8 experiment, colony formation experiment, and EDU experiment were performed to evaluate cell proliferation ability. Wound healing assay and transwell assay were used to analyze its migration ability. The qRT-PCR and WB were used to detect the expression of ZNF337 in tumor tissues and paracancerous tissues of KIRC patients. RESULTS: The pan-cancer analysis revealed that abnormal ZNF337 expression was found in multiple human cancer types. ZNF337 had a high diagnostic value in pan-cancer and a significant association with the prognosis of certain cancers, indicating that ZNF337 may be a valuable prognostic biomarker for multiple cancers. Further analysis demonstrated that the expression level of ZNF337 displayed significant correlations with cancer-associated fibroblasts, immune cell infiltration, and immune checkpoint genes in many tumors. Additionally, ZNF337 was observed to have a high expression in KIRC. Its expression was significantly associated with poor prognosis [overall survival (OS), disease-specific survival (DSS)], age, TNM stage, histologic grade, and pathologic stage. The high ZNF337 expression was associated with poor prognosis in the E-MTAB-1980 validation cohort. The in vitro experiments suggested that the expression of ZNF337 in KIRC tumor tissues was higher than in adjacent tissues, and ZNF337 knockdown inhibited the proliferation and migration of KIRC cells, whereas overexpression of ZNF337 had the opposite effects. CONCLUSIONS: ZNF337 might be an important prognostic and immunotherapeutic biomarker for pan-cancer, especially in KIRC.

Navigating Disease Management: A Comprehensive Review of the De Ritis Ratio in Clinical Medicine.

The De Ritis ratio, defined as the serum aspartate aminotransferase (AST) to alanine aminotransferase (ALT) ratio, is a widely recognized biochemical marker with significant applications in diagnosing and managing various diseases, particularly liver disorders. This comprehensive review synthesizes current knowledge surrounding the clinical relevance of the De Ritis ratio, examining its historical development, diagnostic utility, and prognostic significance across various medical conditions, including liver diseases, cardiovascular disorders, and muscular pathologies. Through an in-depth analysis of literature spanning several decades, this review highlights the role of the De Ritis ratio not only in differential diagnosis but also as a prognostic indicator for disease progression and patient outcomes. The ratio's ability to distinguish between different types of liver pathology, aid in early disease detection, and its potential use in monitoring treatment response are discussed. Additionally, the review addresses the methodological considerations, such as confounding factors and interpretation challenges, that impact the clinical utility of the De Ritis ratio. Given the evolving landscape of clinical diagnostics and the push toward more personalized medicine, the review concludes with recommendations for further research. These include longitudinal studies to explore the ratio's changes over time, comparative research across diverse populations, and technological integration to enhance diagnostic accuracy and patient care. This review aims to reaffirm the importance of the De Ritis ratio in modern clinical practice and encourages continued exploration into its potential applications and benefits in healthcare.

BRD4 expression and its regulatory interaction with miR-26a-3p, DLG5-AS1, and JMJD1C-AS1 lncRNAs in gastric cancer progression.

Gastric cancer remains a significant health challenge despite advancements in diagnosis and treatment. Early detection is critical to reducing mortality, necessitating the investigation of molecular mechanisms underlying gastric cancer progression. This study focuses on BRD4 expression and its correlation with miR-26a-3p, DLG5-AS1, and JMJD1C-AS1 lncRNAs in gastric cancer. Analysis of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets revealed significant upregulation of BRD4 in gastric cancer tissues compared to normal tissues, correlating negatively with miR-26a-3p and positively with DLG5-AS1 and JMJD1C-AS1 lncRNAs. Quantitative RT-PCR confirmed these findings in 25 gastric cancer tissue samples and 25 normal samples. BRD4's overexpression was associated with reduced survival rates and older patient age. MiR-26a-3p, a known tumor suppressor, showed decreased expression in gastric cancer tissues, with ROC analysis suggesting it, alongside BRD4, as a potential diagnostic biomarker. Additionally, bioinformatics predicted miR-26a-3p's interaction with BRD4 mRNA. Upregulated lncRNAs DLG5-AS1 and JMJD1C-AS1 likely act as competing endogenous RNAs, sponging miR-26a-3p, thus promoting BRD4 dysregulation. These lncRNAs have not been previously studied in gastric cancer. The findings propose a novel BRD4/lncRNA/miRNA regulatory axis in gastric cancer, highlighting the potential of BRD4, DLG5-AS1, and JMJD1C-AS1 as biomarkers for early diagnosis. Further studies with larger sample sizes and in vivo and in vitro experiments are needed to elucidate this regulatory mechanism's role in gastric cancer progression.

Integrating machine learning algorithms and multiple immunohistochemistry validation to unveil novel diagnostic markers based on costimulatory molecules for predicting immune microenvironment status in triple-negative breast cancer.

Introduction: Costimulatory molecules are putative novel targets or potential additions to current available immunotherapy, but their expression patterns and clinical value in triple-negative breast cancer (TNBC) are to be clarified. Methods: The gene expression profiles datasets of TNBC patients were obtained from The Cancer Genome Atlas and the Gene Expression Omnibus databases. Diagnostic biomarkers for stratifying individualized tumor immune microenvironment (TIME) were identified using the Least Absolute Shrinkage and Selection Operator (LASSO) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) algorithms. Additionally, we explored their associations with response to immunotherapy via the multiplex immunohistochemistry (mIHC). Results: A total of 60 costimulatory molecule genes (CMGs) were obtained, and we determined two different TIME subclasses ("hot" and "cold") through the K-means clustering method. The "hot" tumors presented a higher infiltration of activated immune cells, i.e., CD4 memory-activated T cells, resting NK cells, M1 macrophages, and CD8 T cells, thereby enriched in the B cell and T cell receptor signaling pathways. LASSO and SVM-RFE algorithms identified three CMGs (CD86, TNFRSF17 and TNFRSF1B) as diagnostic biomarkers. Following, a novel diagnostic nomogram was constructed for predicting individualized TIME status and was validated with good predictive accuracy in TCGA, GSE76250 and GSE58812 databases. Further mIHC conformed that TNBC patients with high CD86, TNFRSF17 and TNFRSF1B levels tended to respond to immunotherapy. Conclusion: This study supplemented evidence about the value of CMGs in TNBC. In addition, CD86, TNFRSF17 and TNFRSF1B were found as potential biomarkers, significantly promoting TNBC patient selection for immunotherapeutic guidance.

Alanine, a potential amino acid biomarker of pediatric sepsis: a pilot study in PICU.

Sepsis is characterized by a metabolic disorder of amino acid occurs in the early stage; however, the profile of serum amino acids and their alterations associated with the onset of sepsis remain unclear. Thus, our objective is to identify the specific kinds of amino acids as diagnostic biomarkers in pediatric patients with sepsis. Serum samples were collected from patients with sepsis admitted to the pediatric intensive care unit (PICU) between January 2019 and December 2019 on the 1st, 3rd and 7th day following admission. Demographic and laboratory variables were also retrieved from the medical records specified times. Serum amino acid concentrations were detected by UPLC-MS/MS system. PLS-DA (VIP > 1.0) and Kruskal-Wallis test (p < 0.05) were employed to identify potential biomarkers. Spearman's rank correlation analysis was conducted to find the potential association between amino acid levels and clinical features. The diagnostic utility for pediatric sepsis was assessed using receiver operating characteristic (ROC) curve analysis. Most of amino acid contents in serum were significantly decreased in patients with sepsis, but approached normal levels by the seventh day post-diagnosis. Threonine (THR), lysine (LYS), valine (VAL) and alanine (ALA) emerged as potential biomarkers related for sepsis occurrence, though they were not associated with PELOD/PELOD-2 scores. Moreover, alterations in serum THR, LYS and ALA were linked to complications of brain injury, and serum ALA levels were also related to sepsis-associated acute kidney injury. Further analysis revealed that ALA was significantly correlated with the Glasgow score, serum lactate and glucose levels, C-reactive protein (CRP), and other indicators for liver or kidney dysfunction. Notably, the area under the ROC curve (AUC) for ALA in distinguishing sepsis from healthy controls was 0.977 (95% CI: 0.925-1.000). The serum amino acid profile of children with sepsis is significantly altered compared to that of healthy controls. Notably, ALA shows promise as a potential biomarker for the early diagnosis in septic children.

Kallistatin as a Potential Biomarker in Polycystic Ovary Syndrome: A Prospective Cohort Study.

BACKGROUND: Polycystic Ovary Syndrome (PCOS) is a prevalent endocrine disorder with significant metabolic implications, including an increased risk of cardiovascular diseases and diabetes. Kallistatin, a serine proteinase inhibitor with anti-inflammatory and antioxidative properties, has been identified as a potential biomarker for PCOS due to its role in modulating inflammation and oxidative stress. METHODS: This prospective cohort study was conducted at a university hospital's gynecology clinic. It included 220 women diagnosed with PCOS and 220 healthy controls matched for age and body mass index. Kallistatin levels were quantitatively assessed using enzyme-linked immunosorbent assay (ELISA) techniques. Associations between kallistatin levels and clinical manifestations of PCOS, including hyperandrogenism and metabolic profiles, were examined. RESULTS: Kallistatin levels were significantly lower in patients with PCOS (2.65 ± 1.84 ng/mL) compared to controls (6.12 ± 4.17 ng/mL; p < 0.001). A strong negative correlation existed between kallistatin levels and androgen concentrations (r = -0.782, p = 0.035). No significant associations were found between kallistatin levels and insulin resistance or lipid profiles. CONCLUSIONS: The findings indicate that reduced kallistatin levels are closely associated with PCOS and could serve as a promising biomarker for its diagnosis. The specific correlation with hyperandrogenism suggests that kallistatin could be particularly effective for identifying PCOS subtypes characterized by elevated androgen levels. This study supports the potential of kallistatin in improving diagnostic protocols for PCOS, facilitating earlier and more accurate detection, which is crucial for effective management and treatment.

Hereditary tyrosinaemia type 1 in the absence of succinylacetone: 4-oxo 6-hydroxyhepanoate (4OHHA), a putative diagnostic biomarker.

Hereditary tyrosinemia type 1 (HT1) is a rare metabolic disease resulting in acute liver failure in early infancy, hypophosphataemic rickets, neurological crises, liver cirrhosis and risk of hepatocellular carcinoma later on in life. It is caused by the deficiency of the enzyme fumarylacetoacetate hydrolase which is involved in the terminal step of the catabolic pathway of tyrosine. Diagnosis is made through clinical suspicion supported by biochemical abnormalities that result from accumulation of upstream metabolites. Detection of succinylacetone (SA) in dried blood spot or urine remains pathognomonic, however it is not always detectable. Here we describe three cases of HT1 presenting with atypical biochemistry, where SA was not always detectable, highlighting the importance of an additional disease biomarker, 4-oxo-6-hydroxyheptanoate.

Integrated Assessment of GFAP and UCH-L1 for their utility in severity assessment and outcome prediction in Traumatic Brain Injury.

OBJECTIVES: This study aimed to explore the potential of glial fibrillary acidic protein (GFAP) and ubiquitin C-terminal hydrolase-L1 (UCH-L1) as biomarkers for diagnosis and prognosis in mild and severe TBI cases, including TBI-related deaths. METHODS: This prospective cohort study includes 40 cases each of mild, severe, fatal TBI cases, and 40 healthy controls. Serum samples were collected from live patients at 8 and 20 h post injury for UCH-L1 and GFAP respectively, and from deceased patients within 6 h of death. RESULTS: Elevated levels of both GFAP and UCH-L1 were observed in patients with severe and fatal TBI cases. These biomarkers exhibited promising potential for predicting various Glasgow Outcome Scale Extended (GOSE) categories. Combining GFAP and UCH-L1 yielded higher predictive accuracy both for diagnosis and prognosis in TBI cases. The study additionally established specific cut-off levels for GFAP and UCH-L1 stratified according to the severity and prognosis. CONCLUSION: GFAP and UCH-L1 individually demonstrated moderate to good discrimination capacity in predicting TBI severity and functional outcomes. However, combining these biomarkers is recommended for improved diagnostic and prognostic utility. This precision tool can enhance patient care, enabling tailored treatment plans, ultimately reducing morbidity and mortality rates in TBI cases.

Multi-Omics Analysis by Machine Learning Identified Lysophosphatidic Acid as a Biomarker and Therapeutic Target for Porcine Reproductive and Respiratory Syndrome.

As a significant infectious disease in livestock, porcine reproductive and respiratory syndrome (PRRS) imposes substantial economic losses on the swine industry. Identification of diagnostic markers and therapeutic targets has been a focal challenge in PPRS prevention and control. By integrating metabolomic and lipidomic serum analyses of clinical pig cohorts through a machine learning approach with in vivo and in vitro infection models, lysophosphatidic acid (LPA) is discovered as a serum metabolic biomarker for PRRS virus (PRRSV) clinical diagnosis. PRRSV promoted LPA synthesis by upregulating the autotaxin expression, which causes innate immunosuppression by dampening the retinoic acid-inducible gene I (RIG-I) and type I interferon responses, leading to enhanced virus replication. Targeting LPA demonstrated protection against virus infection and associated disease outcomes in infected pigs, indicating that LPA is a novel antiviral target against PRRSV. This study lays a foundation for clinical prevention and control of PRRSV infections.

Multiplex plasma protein assays as a diagnostic tool for lung cancer.

Lack of the established noninvasive diagnostic biomarkers causes delay in diagnosis of lung cancer (LC). The aim of this study was to explore the association between inflammatory and cancer-associated plasma proteins and LC and thereby discover potential biomarkers. Patients referred for suspected LC and later diagnosed with primary LC, other cancers, or no cancer (NC) were included in this study. Demographic information and plasma samples were collected, and diagnostic information was later retrieved from medical records. Relative quantification of 92 plasma proteins was carried out using the Olink Immuno-Onc-I panel. Association between expression levels of panel of proteins with different diagnoses was assessed using generalized linear model (GLM) with the binomial family and a logit-link function, considering confounder effects of age, gender, smoking, and pulmonary diseases. The analysis showed that the combination of five plasma proteins (CD83, GZMA, GZMB, CD8A, and MMP12) has higher diagnostic performance for primary LC in both early and advanced stages compared with NC. This panel demonstrated lower diagnostic performance for other cancer types. Moreover, inclusion of four proteins (GAL9, PDCD1, CD4, and HO1) to the aforementioned panel significantly increased the diagnostic performance for primary LC in advanced stage as well as for other cancers. Consequently, the collective expression profiles of select plasma proteins, especially when analyzed in conjunction, might have the potential to distinguish individuals with LC from NC. This suggests their utility as predictive biomarkers for identification of LC patients. The synergistic application of these proteins as biomarkers could pave the way for the development of diagnostic tools for early-stage LC detection.

Oral microbiota distinguishes patients with osteosarcoma from healthy controls.

Objective: The human microbiota plays a key role in cancer diagnosis, pathogenesis, and treatment. However, osteosarcoma-associated oral microbiota alterations have not yet been unraveled. The aim of this study was to explore the characteristics of oral microbiota in osteosarcoma patients compared to healthy controls, and to identify potential microbiota as a diagnostic tool for osteosarcoma. Methods: The oral microbiota was analyzed in osteosarcoma patients (n = 45) and matched healthy controls (n = 90) using 16S rRNA MiSeq sequencing technology. Results: The microbial richness and diversity of the tongue coat were increased in osteosarcoma patients as estimated by the abundance-based coverage estimator indices, the Chao, and observed operational taxonomy units (OTUs). Principal component analysis delineated that the oral microbial community was significant differences between osteosarcoma patients and healthy controls. 14 genera including Rothia, Halomonas, Rhodococcus, and Granulicatella were remarkably reduced, whereas Alloprevotella, Prevotella, Selenomonas, and Campylobacter were enriched in osteosarcoma. Eventually, the optimal four OTUs were identified to construct a microbial classifier by the random forest model via a fivefold cross-validation, which achieved an area under the curve of 99.44% in the training group (30 osteosarcoma patients versus 60 healthy controls) and 87.33% in the test group (15 osteosarcoma patients versus 30 healthy controls), respectively. Notably, oral microbial markers validated strong diagnostic potential distinguishing osteosarcoma patients from healthy controls. Conclusion: This study comprehensively characterizes the oral microbiota in osteosarcoma and reveals the potential efficacy of oral microbiota-targeted biomarkers as a noninvasive biological diagnostic tool for osteosarcoma.

Exploration of effective biomarkers for venous thrombosis embolism in Behçet's disease based on comprehensive bioinformatics analysis.

Behçet's disease (BD) is a multifaceted autoimmune disorder affecting multiple organ systems. Vascular complications, such as venous thromboembolism (VTE), are highly prevalent, affecting around 50% of individuals diagnosed with BD. This study aimed to identify potential biomarkers for VTE in BD patients. Three microarray datasets (GSE209567, GSE48000, GSE19151) were retrieved for analysis. Differentially expressed genes (DEGs) associated with VTE in BD were identified using the Limma package and weighted gene co-expression network analysis (WGCNA). Subsequently, potential diagnostic genes were explored through protein-protein interaction (PPI) network analysis and machine learning algorithms. A receiver operating characteristic (ROC) curve and a nomogram were constructed to evaluate the diagnostic performance for VTE in BD patients. Furthermore, immune cell infiltration analyses and single-sample gene set enrichment analysis (ssGSEA) were performed to investigate potential underlying mechanisms. Finally, the efficacy of listed drugs was assessed based on the identified signature genes. The limma package and WGCNA identified 117 DEGs related to VTE in BD. A PPI network analysis then selected 23 candidate hub genes. Four DEGs (E2F1, GATA3, HDAC5, and MSH2) were identified by intersecting gene sets from three machine learning algorithms. ROC analysis and nomogram construction demonstrated high diagnostic accuracy for these four genes (AUC: 0.816, 95% CI: 0.723-0.909). Immune cell infiltration analysis revealed a positive correlation between dysregulated immune cells and the four hub genes. ssGSEA provided insights into potential mechanisms underlying VTE development and progression in BD patients. Additionally, therapeutic agent screening identified potential drugs targeting the four hub genes. This study employed a systematic approach to identify four potential hub genes (E2F1, GATA3, HDAC5, and MSH2) and construct a nomogram for VTE diagnosis in BD. Immune cell infiltration analysis revealed dysregulation, suggesting potential macrophage involvement in VTE development. ssGSEA provided insights into potential mechanisms underlying BD-induced VTE, and potential therapeutic agents were identified.

Spatial and Single-Cell Investigations Illuminate Theragnostic value and Immune Landscape of Mitochondrial Dynamin-Like GTPase in Breast Cancer.

Background: As we delve into the intricate world of mitochondrial inner membrane proteins, particularly Optic Atrophy types 1 and 3 (OPA1/3), we uncover their pivotal role in maintaining mitochondrial dynamic equilibrium and fusion, crucial for cellular energy production and synthesis. Despite extensive scrutiny, the significance of OPA1/3 in breast cancer (BRCA) and its interplay with the immune microenvironment remain elusive. Materials and Methods: We meticulously sourced BRCA data from renowned repositories such as The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Gene Expression Omnibus (GEO), and the Human Protein Atlas (HPA), leveraging cutting-edge techniques including single-cell RNA-sequencing (scRNA-seq), spatial transcriptomics, and pharmacogenomics. Through multifaceted data analysis, we endeavored to unravel the intricate role and potential value of OPA1/3 in BRCA tumorigenesis and progression. Results: Our investigation reveals a conspicuous upregulation of OPA1/3 expression in BRCA, correlating with dismal prognoses. Kaplan-Meier plot analysis underscores that heightened OPA1/3 levels are associated with poor survival rates. Both clinical specimens and biobank biopsies corroborate the elevated expression of OPA1/3 in breast cancer patients. Moreover, scRNA-seq unveils a strong correlation between OPA1/3 and macrophage infiltration in the BRCA immune milieu, alongside its association with the cellular communication network involving CXCL, TGFb, VEGF, and IL16. Conclusion: In light of these findings, OPA1/3 emerges as a promising contender for therapeutic targeting and as a potential diagnostic, prognostic, and survival biomarker in BRCA. The implications of our study underscore the pressing need to explore these novel biomarkers to enhance patient outcomes.

Long non-coding RNAs as pathophysiological regulators, therapeutic targets and novel extracellular vesicle biomarkers for the diagnosis of inflammatory bowel disease.

Inflammatory bowel disease (IBD) is a chronic relapsing disease of the gastrointestinal (GI) system that includes two groups, Crohn's disease (CD) and ulcerative colitis (UC). To cope with these two classes of IBD, the investigation of pathogenic mechanisms and the discovery of new diagnostic and therapeutic approaches are crucial. Long non-coding RNAs (lncRNAs) which are non-coding RNAs with a length of longer than 200 nucleotides have indicated significant association with the pathology of IBD and strong potential to be used as accurate biomarkers in diagnosing and predicting responses to the IBD treatment. In the current review, we aim to investigate the role of lncRNAs in the pathology and development of IBD. We first describe recent advances in research on dysregulated lncRNAs in the pathogenesis of IBD from the perspective of epithelial barrier function, intestinal immunity, mitochondrial function, and intestinal autophagy. Then, we highlight the possible translational role of lncRNAs as therapeutic targets, diagnostic biomarkers, and predictors of therapeutic response in colon tissues and plasma samples. Finally, we discuss the potential of extracellular vesicles and their lncRNA cargo in the pathophysiology, diagnosis, and treatment of IBD.

I-FABP protein/mRNA and IL-6 as biomarkers of intestinal barrier dysfunction in neonates with necrotizing enterocolitis and SPF BALB/c mouse models.

OBJECTIVE: Neonatal necrotizing enterocolitis (NEC) is a serious intestinal inflammatory disease. We investigated intestinal fatty acid binding protein (I-FABP), I-FABP mRNA, and interleukin-6 (IL-6) as potential diagnostic biomarkers in NEC. METHODS: Forty mice were subjected to hypoxic-ischemic intestinal injury, and then serum I-FABP protein and mRNA levels were quantified. Ileal tissue pathological scores were determined by hematoxylin and eosin staining. I-FABP expression levels and translocation in these tissues were detected using western blotting and immunofluorescence, respectively. Samples from 30 human neonates with NEC and 30 healthy neonates had serum I-FABP protein/mRNA and IL-6 levels measured. RESULTS: The mouse ileal tissue pathological score and I-FABP levels, as well as serum I-FABP and I-FABP mRNA levels, were significantly higher in the model group than in the control group. Serum I-FABP, I-FABP mRNA, and IL-6 levels were significantly higher in human neonates with NEC than in the healthy group. Logistic regression and receiver operating curve analyses revealed that I-FABP protein/mRNA and IL-6 levels could be diagnostic biomarkers for NEC. CONCLUSIONS: I-FABP protein/mRNA and IL-6 levels are useful biomarkers of intestinal ischemic injury in neonates with NEC. The combined detection of I-FABP protein/mRNA and IL-6 is recommended rather than using a single biomarker.

Identification and diagnostic potential of hsa_circ_101303 in colorectal cancer: unraveling a regulatory network.

BACKGROUND: The role of novel circular RNAs (circRNAs) in colorectal cancer (CRC) remains to be determined. This study aimed to identify a novel circRNA involved in CRC pathogenesis, assess its diagnostic value, and construct a regulatory network. METHODS: Differential expression analysis was conducted using circRNA datasets to screen for differentially expressed circRNAs. The expression of selected circRNAs was validated in external datasets and clinical samples. Diagnostic value of plasma circRNA levels in CRC was assessed. A competing endogenous RNA (ceRNA) network was constructed for the circRNA using TCGA dataset. RESULTS: Analysis of datasets revealed that hsa_circ_101303 was significantly overexpressed in CRC tissues compared to normal tissues. The upregulation of hsa_circ_101303 in CRC tissues was further confirmed through the GSE138589 dataset and clinical samples. High expression of hsa_circ_101303 was associated with advanced N stage, M stage, and tumor stage in CRC. Plasma levels of hsa_circ_101303 were markedly elevated in CRC patients and exhibited moderate diagnostic ability for CRC (AUC = 0.738). The host gene of hsa_circ_101303 was also found to be related to the TNM stage of CRC. Nine miRNAs were identified as target miRNAs for hsa_circ_101303, and 27 genes were identified as targets of these miRNAs. Subsequently, a ceRNA network for hsa_circ_101303 was constructed to illustrate the interactions between the nine miRNAs and 27 genes. CONCLUSIONS: The study identifies hsa_circ_101303 as a highly expressed circRNA in CRC, which is associated with the progression of the disease. Plasma levels of hsa_circ_101303 show promising diagnostic potential for CRC. The ceRNA network for hsa_circ_101303 provides valuable insights into the regulatory mechanisms underlying CRC.

Unveiling the role of interleukin-6 in pancreatic cancer occurrence and progression.

Pancreatic cancer is difficult to diagnose early and progresses rapidly. Researchers have found that a cytokine called Interleukin-6 (IL-6) is involved in the entire course of pancreatic cancer, promoting its occurrence and development. From the earliest stages of pancreatic intraepithelial neoplasia to the invasion and metastasis of pancreatic cancer cells and the appearance of tumor cachexia, IL-6 drives oncogenic signal transduction pathways and immune escape that accelerate disease progression. IL-6 is considered a biomarker for pancreatic cancer diagnosis and prognosis, as well as a potential target for treatment. IL-6 antibodies are currently being explored as a hot topic in oncology. This article aims to systematically explain how IL-6 induces the deterioration of normal pancreatic cells, with the goal of finding a breakthrough in pancreatic cancer diagnosis and treatment.

Identification of nicotinamide N-methyltransferase as a promising therapeutic target for sarcopenia.

Sarcopenia is a significant geriatric syndrome that involves the loss of skeletal muscle mass and strength. Due to its substantial endocrine role, the metabolic microenvironment of skeletal muscle undergoes changes with age. Examining the pathogenesis of sarcopenia through focusing on metabolic dysregulation could offer insights for developing more effective intervention strategies. In this study, we analyzed the transcriptomics data to identify specific genes involved in the regulation of metabolism in skeletal muscle during the development of sarcopenia. Three machine learning algorithms were employed to screen key target genes exhibiting strong correlations with metabolism, which were further validated using RNA-sequencing data and publicly accessible datasets. Among them, the metabolic enzyme nicotinamide N-methyltransferase (NNMT) was elevated in sarcopenia, and predicted sarcopenia with an area under the curve exceeding 0.7, suggesting it as a potential therapeutic target for sarcopenia. As expected, inhibition of NNMT improved the grip strength in aging mice and alleviated age-related decline in the mass index of the quadriceps femoris muscles and whole-body lean mass index. Additionally, the NNMTi treatment increased the levels of nicotinamide adenine dinucleotide (NAD+) content, as well as PGC1α and p-AMPK expression in the muscles of both the D-galactose-treated mouse model and naturally aging mouse model. Overall, this work demonstrates NNMT as a promising target for preventing age-related decline in muscle mass and strength.

Diagnostic value of carbohydrate antigen 50 in biliary tract cancer: A large-scale multicenter study.

BACKGROUND: To date, carbohydrate antigen 19-9 (CA19-9) and carcinoembryonic antigen (CEA) have been widely used for the screening, diagnosis and prediction of biliary tract cancer (BTC) patients. However, few studies with large sample sizes of carbohydrate antigen 50 (CA50) were reported in BTC patients. METHODS: A total of 1121 patients from the Liver Cancer Clin-Bio Databank of Anhui Hepatobiliary Surgery Union between January 2017 and December 2022 were included in this study (673 in the training cohort and 448 in the validation cohort): among them, 458 with BTC, 178 with hepatocellular carcinoma (HCC), 23 with combined hepatocellular-cholangiocarcinoma, and 462 with nontumor patients. Receiver operating characteristic (ROC) curves and decision curve analysis (DCA) were used to evaluate the diagnostic efficacy and clinical usefulness. RESULTS: ROC curves obtained by combining CA50, CA19-9, and AFP showed that the AUC value of the diagnostic MODEL 1 was 0.885 (95% CI 0.856-0.885, specificity 70.3%, and sensitivity 84.0%) in the training cohort and 0.879 (0.841-0.917, 76.7%, and 84.3%) in the validation cohort. In addition, comparing iCCA and HCC (235 in the training cohort, 157 in the validation cohort), the AUC values of the diagnostic MODEL 2 were 0.893 (95% CI 0.853-0.933, specificity 96%, and sensitivity 68.6%) in the training cohort and 0.872 (95% CI 0.818-0.927, 94.2%, and 64.6%) in the validation cohort. CONCLUSION: The model combining CA50, CA19-9, and AFP not only has good diagnostic value for BTC but also has good diagnostic value for distinguishing iCCA and HCC.