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Gastric cancer (GC) is a highly heterogeneous and aggressive malignant tumor that seriously affects the life safety of people all over the world. Its early manifestations are subtle. The present study aimed to investigate the clinical significance of serum lipid profiles, insulin resistance markers including the triglyceride-glucose (TyG) index and the atherosclerotic index (AI), in GC patients. A retrospective analysis encompassed 215 GC patients and 827 healthy individuals. The study results show that the total cholesterol, triglycerides, low-density lipoprotein, high-density lipoprotein levels, and the TyG index of GC patients were significantly lower than those of the control group before and after propensity score matching analysis. In the GC group, the levels of CEA, CA199, CA125, and CA724 tumor markers were higher than those in the healthy control group. Patients in advanced stages exhibited lower serum levels of serum lipids and TyG index compared to those in early stages. ROC analysis revealed that the TyG index, CA125, and CA199 combination yielded the highest positive prediction rate for GC at 98.6%. TyG index is significantly associated with the risk of adverse reactions after chemotherapy (OR = 1.104, 95% CI 1.028–1.186, P < 0.01). Multiple tumor markers and the TyG index combined detection showed correlations with five adverse reactions caused by chemotherapy (r < 0.6, P < 0.05). Preoperative lipid profiles in the serum show a strong correlation with patients diagnosed with GC. Evaluating a combination of various serum lipids and cancer markers significantly improves diagnostic precision for GC and the ability to predict chemotherapy side effects. [ABSTRACT FROM AUTHOR]

Background: Copeptin is an immediate biomarker of individual stress response; many life-threatening diseases are causing a high elevation of its concentration in plasma, such as myocardial infarction and cardiovascular shock. Moreover, copeptin is a promising marker in sepsis. We aimed to evaluate copeptin as a diagnostic and prognostic marker in neonatal sepsis for the early initiation of appropriate therapy and the prediction of mortality. A prospective case-control study involved 237 neonates (165 cases had neonatal sepsis, and 72 served as controls). Cases were admitted to the neonatal intensive care unit (NICU) and followed up for symptoms and signs of sepsis confirmed by laboratory data: complete blood count (CBC), c-reactive protein (CRP), and cultures. Serum copeptin level by the enzyme-linked immunosorbent assay (ELISA) was measured for all included neonates. We observed that the copeptin level was significantly higher in cases than control (3.51 ± 1.4, 1.61 ± 0.51 pmol/liter, respectively). The cut-off value of copeptin at which we can discriminate between cases and controls was above 2.065 pmol/liter. Among cases, copeptin was higher in early-onset sepsis (EOS) than late-onset sepsis (LOS) neonates, and there was a significant correlation between its level and all the following: age at admission, birth weight, gestational age, history of perinatal asphyxia, maternal chorioamnionitis, and premature rupture of membrane (PROM). Also, copeptin was strongly associated with CRP level and the poor prognosis of patients. Copeptin can predict the death of cases at a cut-off value above 2.995 pmol/liter. Conclusion: Serum copeptin level can be used as a diagnostic and prognostic marker in neonatal sepsis. [ABSTRACT FROM AUTHOR]

We investigated the potential diagnostic and prognostic role of maternally expressed 3 (MEG-3), a type of long non-coding RNA, in epithelial ovarian carcinoma (EOC) by comparing long non-coding RNA (LNCRNA-MEG-3) expression in EOC and normal ovarian tissues and exploring clinical correlations. The study included 126 patients diagnosed with stage III EOC, confirmed by histopathological examination. We used quantitative polymerase chain reaction (qPCR) to quantify levels of the long noncoding RNA MEG-3. The long non-coding RNA MEG-3 expression in EOC tissues was significantly lower than in normal ovarian tissues, indicating its potential as a diagnostic marker. Receiver operating characteristic curve (ROC) analysis demonstrated an Area under the ROC Curve (AUC) of 0.831, signifying its high sensitivity (100%) and specificity (97.04%) in distinguishing malignant ovarian tissues from normal ones. LNCRNA-MEG-3 expression varied significantly across different EOC stages (p < 0.0001) and tumor grades (p < 0.0001), correlating with aggressive behavior and serous tumor types. Low LNCRNA-MEG-3 expression associated with adverse prognostic factors such as ascites (p < 0.0001) and poor treatment response (p < 0.0001). High LNCRNA-MEG-3 expression predicted better treatment response. It also correlates with the size of residual disease after debulking surgery, which is an important prognostic factor. Compared to those with low LNCRNA-MEG-3 expression, patients with high expression had significantly longer overall and disease-free survival (p = 0.0004 and p = 0.0002, respectively). The study highlights LNCRNA-MEG-3 as a valuable diagnostic and prognostic marker for EOC. Low expression of the long non-coding RNA MEG-3 is linked to aggressive tumor features and unfavorable clinical outcomes, stressing the importance of MEG-3 in managing EOC and tailoring the treatment to the individual patient. [ABSTRACT FROM AUTHOR]

Hepatic ischemia-reperfusion injury (HIRI) may cause severe hepatic impairment, acute hepatic insufficiency, and multiorgan system collapse. Exosomes can alleviate HIRI. Therefore, this study explored the role of exosomal-related genes (ERGs) in HIRI using bioinformatics to determine the underlying molecular mechanisms and novel diagnostic markers for HIRI. We merged the GSE12720, GSE14951, and GSE15480 datasets obtained from the Gene Expression Omnibus (GEO) database into a combined gene dataset (CGD). CGD was used to identify differentially expressed genes (DEGs) based on a comparison of the HIRI and healthy control cohorts. The impact of these DEGs on HIRI was assessed through gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA). ERGs were retrieved from the GeneCards database and prior studies, and overlapped with the identified DEGs to yield the set of exosome-related differentially expressed genes (ERDEGs). Functional annotations and enrichment pathways of these genes were determined using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Diagnostic models for HIRI were developed using least absolute shrinkage and selection operator (LASSO) regression and support vector machine (SVM) algorithms. Key genes with diagnostic value were identified from the overlap, and single-sample gene-set enrichment analysis (ssGSEA) was conducted to evaluate the immune infiltration characteristics. A molecular regulatory interaction network was established using Cytoscape software to elucidate the intricate regulatory mechanisms of key genes in HIRI. Finally, exosome score (Es) was obtained using ssGSEA and the HIRI group was divided into the Es_High and Es_Low groups based on the median Es. Gene expression was analyzed to understand the impact of all genes in the CGD on HIRI. Finally, the relative expression levels of the five key genes in the hypoxia-reoxygenation (H/R) model were determined using quantitative real-time PCR (qRT-PCR). A total of 3810 DEGs were identified through differential expression analysis of the CGD, and 61 of these ERDEGs were screened. Based on GO and KEGG enrichment analyses, the ERDEGs were mainly enriched in wound healing, MAPK, protein kinase B signaling, and other pathways. GSEA and GSVA revealed that these genes were mainly enriched in the TP53, MAPK, TGF , JAK-STAT, MAPK, and NFKB pathways. Five key genes (ANXA1, HNRNPA2B1, ICAM1, PTEN, and THBS1) with diagnostic value were screened using the LASSO regression and SVM algorithms and their molecular interaction network was established using Cytoscape software. Based on ssGSEA, substantial variations were found in the expression of 18 immune cell types among the groups (p < 0.05). Finally, the Es of each HIRI patient was calculated. ERDEGs in the Es_High and Es_Low groups were enriched in the IL18, TP53, MAPK, TGF , and JAK-STAT pathways. The differential expression of these five key genes in the H/R model was verified using qRT-PCR. Herein, five key genes were identified as potential diagnostic markers. Moreover, the potential impact of these genes on pathways and the regulatory mechanisms of their interaction network in HIRI were revealed. Altogether, our findings may serve as a theoretical foundation for enhancing clinical diagnosis and elucidating underlying pathogeneses. [ABSTRACT FROM AUTHOR]

Background: This study aimed to investigate the differential expression levels of the cGAS-STING pathway in peripheral blood mononuclear cells (PBMCs) of spinal tuberculosis (TB) patients with different progression and its feasibility as a diagnostic marker. Methods: Peripheral blood and medical records of 25 patients with spinal TB and 10 healthy individuals, were prospectively collected and analyzed. PBMCs and serum were extracted from peripheral blood and the expression levels of the cGAS-STING pathway in PBMCs were measured by real-time PCR (RT-PCR) and serum interferon β (IFN-β) expression levels were measured by enzyme-linked immunosorbent assay (ELISA). The expression of Interferon regulatory Factor 3 (IRF3) in PBMCs was measured using western blot. Statistical analysis was performed using the SPSS 26.0 statistical package. Results: The results showed that the expression level of the TANK-binding kinase 1 (TBK1) and IRF3 was significantly higher in PBMCs (P < 0.05), in patients with active lesions than in patients with stable lesions. The serum concentration of IFN-β was significantly higher in patients with active lesions (P = 0.028). Compared with healthy individuals, the expression level of the cGAS-STING pathway was elevated in PBMCs of TB patients (P < 0.05), and the difference in the expression level of IFN-β was not statistically significant (P > 0.05), and the serum IFN-β concentration was elevated (P < 0.05). The calculated AUC values for TBK1 and IRF3 in PBMCs, IFN-β in serum and erythrocyte sedimentation rate (ESR) to distinguish between patients with active and stable lesions were 0.732, 0.714, 0.839, and 0.714 respectively. Conclusions: The expression level of TBK1 and IRF3 in PBMCs, and IFN-β in the serum of patients with spinal TB is positively correlated with disease activity. TBK1 has higher specificity and IFN-β in serum has higher sensitivity when used to differentiate between patients with active and stable lesions. [ABSTRACT FROM AUTHOR]

The translocator protein (TSPO) is predominately localized on the outer mitochondrial membrane in steroidogenic cells. In the brain, TSPO expression, low under normal conditions, results upregulated in response to glial cell activation, that occurs in neuroinflammation. As a consequence, TSPO has been extensively studied as a biomarker of such conditions by means of TSPO-targeted radiotracers. Although [11C]-PK11195, the prototypical TSPO radioligand, is still widely used for in vivo studies, it is endowed with severe limitations, mainly low sensitivity and poor amenability to quantification. Consequently, several efforts have been focused on the design of new radiotracers for the in vivo imaging of TSPO. The present review will provide an outlook on the latest advances in TSPO radioligands for neuroinflammation imaging. The final goal is to pave the way for (radio)chemists in the future design and development of novel effective and sensitive radiopharmaceuticals targeting TSPO. [ABSTRACT FROM AUTHOR]

Personality traits have been associated with eating disorders (EDs) and comorbidities. However, it is unclear which personality profiles are premorbid risk rather than diagnostic markers. We explored associations between personality and ED-related mental health symptoms using canonical correlation analyses. We investigated personality risk profiles in a longitudinal sample, associating personality at age 14 with onset of mental health symptoms at ages 16 or 19. Diagnostic markers were identified in a sample of young adults with anorexia nervosa (AN, n = 58) or bulimia nervosa (BN, n = 63) and healthy controls (n = 47). Two significant premorbid risk profiles were identified, successively explaining 7.93 % and 5.60 % of shared variance (R c 2 ). The first combined neuroticism (canonical loading, r s = 0.68), openness (r s = 0.32), impulsivity (r s = 0.29), and conscientiousness (r s = 0.27), with future onset of anxiety symptoms (r s = 0.87) and dieting (r s = 0.58). The other, combined lower agreeableness (r s = −0.60) and lower anxiety sensitivity (r s = −0.47), with future deliberate self-harm (r s = 0.76) and purging (r s = 0.55). Personality profiles associated with "core psychopathology" in both AN (R c 2 = 80.56 %) and BN diagnoses (R c 2 = 64.38 %) comprised hopelessness (r s = 0.95, 0.87) and neuroticism (r s = 0.93, 0.94). For BN, this profile also included impulsivity (r s = 0.60). Additionally, extraversion (r s = 0.41) was associated with lower depressive risk in BN. The samples were not ethnically diverse. The clinical cohort included only females. There was non-random attrition in the longitudinal sample. The results suggest neuroticism and impulsivity as risk and diagnostic markers for EDs, with neuroticism and hopelessness as shared diagnostic markers. They may inform the design of more personalised prevention and intervention strategies. • Analyses identify personality risk and diagnostic markers for eating disorders. • Neuroticism and impulsivity are both risk and diagnostic markers. • Neuroticism and hopelessness are shared diagnostic markers. • Extraversion is associated with lower depressive risk in bulimia nervosa. • Interventions targeting these personality traits may improve clinical outcomes. [ABSTRACT FROM AUTHOR]

PAX8 plays a role in development of the thyroid, kidney, and the Wolffian and Mullerian tract. In surgical pathology, PAX8 immunohistochemistry is used to determine tumors of renal and ovarian origin, but data on its expression in other tumors are conflicting. To evaluate PAX8 expression in normal and tumor tissues, a tissue microarray containing 17,386 samples from 149 different tumor types and 608 samples of 76 different normal tissue types was analyzed by immunohistochemistry. PAX8 results were compared with previously collected data on cadherin 16 (CDH16). PAX8 positivity was found in 40 different tumor types. The highest rate of PAX8 positivity was found in thyroidal neoplasms of follicular origin (98.6–100%), gynecological carcinomas (up to 100%), renal tumors (82.6–97.8%), and urothelial neoplasms (2.3–23.7%). Important tumors with near complete absence of PAX8 staining (< 1%) included all subtypes of breast cancers, hepatocellular carcinomas, gastric, prostatic, pancreatic, and pulmonary adenocarcinomas, neuroendocrine neoplasms, small cell carcinomas of various sites, and lymphomas. High PAX8 expression was associated with low tumor grade in 365 non-invasive papillary urothelial carcinomas (p < 0.0001) but unrelated to patient outcome and/or tumor phenotype in clear cell renal cell carcinoma, high-grade serous ovarian cancer, and endometrioid endometrial carcinoma. For determining a renal tumor origin, sensitivity was 88.1% and specificity 87.2% for PAX8, while sensitivity was 85.3% and specificity 95.7% for CDH16. The combination of PAX8 and CDH16 increased specificity to 96.8%. In conclusion, PAX8 immunohistochemistry is a suitable diagnostic tool. The combination of PAX8 and CDH16 positivity has high specificity for renal cell carcinoma. [ABSTRACT FROM AUTHOR]

Background & aims: Perilipin 1 (PLIN1) is an essential lipid droplet surface protein that participates in cell life activities by regulating energy balance and lipid metabolism. PLIN1 has been shown to be closely related to the development of numerous tumor types. The purpose of this work was to elucidate the clinicopathologic significance of PLIN1 in hepatocellular carcinoma (HCC), as well as its impact on the biological functions of HCC cells, and to investigate the underlying mechanisms involved. Methods: Public high-throughput RNA microarray and RNA sequencing data were collected to examine PLIN1 levels and clinical significance in patients with HCC. Immunohistochemistry (IHC) and real-time quantitative reverse transcription polymerase chain reaction (RT‒qPCR) were conducted to assess the expression levels and the clinicopathological relevance of PLIN1 in HCC. Then, SK and Huh7 cells were transfected with a lentivirus overexpressing PLIN1. CCK8 assay, wound healing assay, transwell assay, and flow cytometric analysis were conducted to explore the effects of PLIN1 overexpression on HCC cell proliferation, migration, invasion, and cell cycle distribution. Ultimately, Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to investigate the underlying mechanisms of PLIN1 in HCC progression based on HCC differentially expressed genes and PLIN1 co-expressed genes. Results: PLIN1 was markedly downregulated in HCC tissues, which correlated with a noticeably worse prognosis for HCC patients. Additionally, PLIN1 overexpression inhibited the proliferation, migration, and invasion of SK and Huh7 cells in vitro, as well as arresting the HCC cell cycle at the G0/G1 phase. More significantly, energy conversion-related biological processes, lipid metabolism, and cell cycle signalling pathways were the three most enriched molecular mechanisms. Conclusion: The present study revealed that PLIN1 downregulation is associated with poor prognosis in HCC patients and accelerated HCC progression by promoting cellular proliferation, migration, and metastasis, as well as the mechanisms underlying the regulation of lipid metabolism-related pathways in HCC. [ABSTRACT FROM AUTHOR]

Diabetic foot （DF）， a primary chronic complication of diabetes mellitus， contributes to a major disability and mortality in diabetic patients. DF is diagnosed mainly depending not only on clinical manifestations， signs， and related inspection， but also on recently emerging diagnostic means: biological markers. Inflammatory biomarkers are preferably used for its superiority in DF early diagnosis. In recently years， thanks to advancements of biological technologies， biomarkers such as procalcitonin （PCT）， C-reactive protein （CRP）， interleukins （ILs）， and tumor necrosis factor-alpha （TNF-α） have been comprehensively used in DF diagnosis. Moreover， biomarkers of genomics， proteomics， metabolomics， and metagenomics have been employed as well. In this review， we aim to comprehensively review the role of serum biomarkers in DF diagnosis and risk stratification， elaborating on the current research status in applying serum biomarkers for DF prevention， diagnosis， and prognosis assessment. [ABSTRACT FROM AUTHOR]

Simple Summary: Inflammatory bowel disease (IBD) has become more common among humans and awareness of its prevalence in animals, including horses, has also increased during the past few decades. Equine IBD is problematic as it decreases the performance of horses and causes diarrhea, weight loss, and pain-related behaviors. Apart from high levels of uncertainty in diagnosing IBD, it is stressful for the horse and expensive for the owner as it typically requires transportation to the horse hospital, fasting, endoscopy, and biopsy assessment. Therefore, there is a need for a non-invasive and affordable method to screen for IBD. Fecal microbiota composition has been shown to change in humans and other animals with IBD; therefore, we used fecal samples to study whether equine IBD is also reflected by changes in the composition of gut microbiota. We show that gut microbiota composition was different and that the abundances of certain bacterial groups were significantly increased or decreased in horses with IBD compared to healthy horses. We further used a machine learning model to predict IBD based on the microbiota composition of the fecal samples. The model produced correct predictions with 100% accuracy in our dataset. We conclude that, in the future, studying the microbiota composition of fecal samples could become an accurate, cheap, and non-invasive method in screening for equine IBD. Gastrointestinal disorders are common and debilitating in horses, but their diagnosis is often difficult and invasive. Fecal samples offer a non-invasive alternative to assessing the gastrointestinal health of horses by providing information about the gut microbiota and inflammation. In this study, we used 16S sequencing to compare the fecal bacterial diversity and composition of 27 healthy horses and 49 horses diagnosed with inflammatory bowel disease (IBD). We also measured fecal calprotectin concentration, a marker of intestinal inflammation, in healthy horses and horses with IBD. We found that microbiota composition differed between healthy horses and horses with IBD, although less than five percent of the variation in microbiota composition was explained by individual health status and age. Several differentially abundant bacterial taxa associated with IBD, age, or body condition were depleted from the most dominant Firmicutes phylum and enriched with the Bacteroidota phylum. An artificial neural network model predicted the probability of IBD among the test samples with 100% accuracy. Our study is the first to demonstrate the association between gut microbiota composition and chronic forms of IBD in horses and highlights the potential of using fecal samples as a non-invasive source of biomarkers for equine IBD. [ABSTRACT FROM AUTHOR]

Cancer markers are measurable molecules in blood or tissues that are produced by tumor cells or immune cells in response to cancer progression. They play an important role in clinical diagnosis, prognosis, and therapy monitoring. Splicing factor proline- and glutamine-rich (SFPQ) plays an important role in cancer growth and metastasis. SFPQ is not only more highly expressed in non-small-cell lung cancer (NSCLC) cells than it is in controls, but also highly expressed in cancer cells in patients with other solid cancers. Thus, a new enzyme-linked immunosorbent assay (ELISA) for detecting SFPQ was developed, in which the SFPQ protein is trapped by the first specific mAb coated on a microplate, and then recognized by a second specific mAb. This assay allows for the specific detection of SFPQ in the serum of patients with solid cancer. Regarding NSCLC, the serum SFPQ levels distinguished the non-cancer controls from the patients with NSCLC, with an area under the curve of 0.876, a sensitivity of 87%, and a specificity of 94%. The serum SFPQ levels were significantly elevated in the patients with NSCLC or other solid cancers. In conclusion, serum SFPQ could be a promising novel diagnostic biomarker for NSCLC and other malignancies. [ABSTRACT FROM AUTHOR]

Deep venous thrombosis (DVT) is the third leading cause of death in cardiovascular disease, following heart attacks and strokes. Early diagnosis and intervention are crucial for effective DVT therapy. We aim to investigate whether endothelin-1 (ET-1) could serve as an early diagnostic marker or a potential therapeutic target in a DVT rat model. CCK8 assay, invasion assay, and flow cytometry were used to detect the proliferation, migration and apoptosis of HUVECs, respectively. Elisa assay was used to detect ET-1 and coagulation factor VII in cell supernatant and rat?s plasma. Western blot was used to detect antioxidant signaling protein. Inferior vena cava stenosis was used to construct the DVT rat model. Lentivirus mediated overexpression of ET-1 in HUVECs impaired the cell proliferation and migration, increased cell apoptosis, inhibited the antioxidant signaling pathway proteins expression (e.g., NQO1, GCLC, Nrf-2), and upregulated coagulation factor VII. Furthermore, overexpression of ET-1 further impaired antioxidant signaling pathway protein in response to H2O2 treatment. However, lentivirus mediated ET-1 knockdown and BQ123 (an ET-1 inhibitor), showed the opposite results with ET-1 overexpression. We then established a DVT rat model by inferior vena cava stenosis. The stenosis induced early expression of ET-1 and coagulation factor VII in plasma at day 1 and restore their level at day 10. BQ123 could downregulate the coagulation factor VII to ameliorate the stenosis effects. Our findings suggest that ET-1 might serve as an early diagnostic marker for DVT rat model and a potential therapeutic target for treating DVT. [ABSTRACT FROM AUTHOR]

Abstract Gastric cancer (GC) is a highly heterogeneous and aggressive malignant tumor that seriously affects the life safety of people all over the world. Its early manifestations are subtle. The present study aimed to investigate the clinical significance of serum lipid profiles, insulin resistance markers including the triglyceride-glucose (TyG) index and the atherosclerotic index (AI), in GC patients. A retrospective analysis encompassed 215 GC patients and 827 healthy individuals. The study results show that the total cholesterol, triglycerides, low-density lipoprotein, high-density lipoprotein levels, and the TyG index of GC patients were significantly lower than those of the control group before and after propensity score matching analysis. In the GC group, the levels of CEA, CA199, CA125, and CA724 tumor markers were higher than those in the healthy control group. Patients in advanced stages exhibited lower serum levels of serum lipids and TyG index compared to those in early stages. ROC analysis revealed that the TyG index, CA125, and CA199 combination yielded the highest positive prediction rate for GC at 98.6%. TyG index is significantly associated with the risk of adverse reactions after chemotherapy (OR = 1.104, 95% CI 1.028–1.186, P

Abstract Background Copeptin is an immediate biomarker of individual stress response; many life-threatening diseases are causing a high elevation of its concentration in plasma, such as myocardial infarction and cardiovascular shock. Moreover, copeptin is a promising marker in sepsis. We aimed to evaluate copeptin as a diagnostic and prognostic marker in neonatal sepsis for the early initiation of appropriate therapy and the prediction of mortality. A prospective case-control study involved 237 neonates (165 cases had neonatal sepsis, and 72 served as controls). Cases were admitted to the neonatal intensive care unit (NICU) and followed up for symptoms and signs of sepsis confirmed by laboratory data: complete blood count (CBC), c-reactive protein (CRP), and cultures. Serum copeptin level by the enzyme-linked immunosorbent assay (ELISA) was measured for all included neonates. We observed that the copeptin level was significantly higher in cases than control (3.51 ± 1.4, 1.61 ± 0.51 pmol/liter, respectively). The cut-off value of copeptin at which we can discriminate between cases and controls was above 2.065 pmol/liter. Among cases, copeptin was higher in early-onset sepsis (EOS) than late-onset sepsis (LOS) neonates, and there was a significant correlation between its level and all the following: age at admission, birth weight, gestational age, history of perinatal asphyxia, maternal chorioamnionitis, and premature rupture of membrane (PROM). Also, copeptin was strongly associated with CRP level and the poor prognosis of patients. Copeptin can predict the death of cases at a cut-off value above 2.995 pmol/liter. Conclusion Serum copeptin level can be used as a diagnostic and prognostic marker in neonatal sepsis.

Abstract Hepatic ischemia-reperfusion injury (HIRI) may cause severe hepatic impairment, acute hepatic insufficiency, and multiorgan system collapse. Exosomes can alleviate HIRI. Therefore, this study explored the role of exosomal-related genes (ERGs) in HIRI using bioinformatics to determine the underlying molecular mechanisms and novel diagnostic markers for HIRI. We merged the GSE12720, GSE14951, and GSE15480 datasets obtained from the Gene Expression Omnibus (GEO) database into a combined gene dataset (CGD). CGD was used to identify differentially expressed genes (DEGs) based on a comparison of the HIRI and healthy control cohorts. The impact of these DEGs on HIRI was assessed through gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA). ERGs were retrieved from the GeneCards database and prior studies, and overlapped with the identified DEGs to yield the set of exosome-related differentially expressed genes (ERDEGs). Functional annotations and enrichment pathways of these genes were determined using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Diagnostic models for HIRI were developed using least absolute shrinkage and selection operator (LASSO) regression and support vector machine (SVM) algorithms. Key genes with diagnostic value were identified from the overlap, and single-sample gene-set enrichment analysis (ssGSEA) was conducted to evaluate the immune infiltration characteristics. A molecular regulatory interaction network was established using Cytoscape software to elucidate the intricate regulatory mechanisms of key genes in HIRI. Finally, exosome score (Es) was obtained using ssGSEA and the HIRI group was divided into the Es_High and Es_Low groups based on the median Es. Gene expression was analyzed to understand the impact of all genes in the CGD on HIRI. Finally, the relative expression levels of the five key genes in the hypoxia-reoxygenation (H/R) model were determined using quantitative real-time PCR (qRT-PCR). A total of 3810 DEGs were identified through differential expression analysis of the CGD, and 61 of these ERDEGs were screened. Based on GO and KEGG enrichment analyses, the ERDEGs were mainly enriched in wound healing, MAPK, protein kinase B signaling, and other pathways. GSEA and GSVA revealed that these genes were mainly enriched in the TP53, MAPK, TGF $$\:\beta\:$$ , JAK-STAT, MAPK, and NFKB pathways. Five key genes (ANXA1, HNRNPA2B1, ICAM1, PTEN, and THBS1) with diagnostic value were screened using the LASSO regression and SVM algorithms and their molecular interaction network was established using Cytoscape software. Based on ssGSEA, substantial variations were found in the expression of 18 immune cell types among the groups (p

Abstract Background This study aimed to investigate the differential expression levels of the cGAS-STING pathway in peripheral blood mononuclear cells (PBMCs) of spinal tuberculosis (TB) patients with different progression and its feasibility as a diagnostic marker. Methods Peripheral blood and medical records of 25 patients with spinal TB and 10 healthy individuals, were prospectively collected and analyzed. PBMCs and serum were extracted from peripheral blood and the expression levels of the cGAS-STING pathway in PBMCs were measured by real-time PCR (RT-PCR) and serum interferon β (IFN-β) expression levels were measured by enzyme-linked immunosorbent assay (ELISA). The expression of Interferon regulatory Factor 3 (IRF3) in PBMCs was measured using western blot. Statistical analysis was performed using the SPSS 26.0 statistical package. Results The results showed that the expression level of the TANK-binding kinase 1 (TBK1) and IRF3 was significantly higher in PBMCs (P 0.05), and the serum IFN-β concentration was elevated (P < 0.05). The calculated AUC values for TBK1 and IRF3 in PBMCs, IFN-β in serum and erythrocyte sedimentation rate (ESR) to distinguish between patients with active and stable lesions were 0.732, 0.714, 0.839, and 0.714 respectively. Conclusions The expression level of TBK1 and IRF3 in PBMCs, and IFN-β in the serum of patients with spinal TB is positively correlated with disease activity. TBK1 has higher specificity and IFN-β in serum has higher sensitivity when used to differentiate between patients with active and stable lesions.

Abstract Background & aims Perilipin 1 (PLIN1) is an essential lipid droplet surface protein that participates in cell life activities by regulating energy balance and lipid metabolism. PLIN1 has been shown to be closely related to the development of numerous tumor types. The purpose of this work was to elucidate the clinicopathologic significance of PLIN1 in hepatocellular carcinoma (HCC), as well as its impact on the biological functions of HCC cells, and to investigate the underlying mechanisms involved. Methods Public high-throughput RNA microarray and RNA sequencing data were collected to examine PLIN1 levels and clinical significance in patients with HCC. Immunohistochemistry (IHC) and real-time quantitative reverse transcription polymerase chain reaction (RT‒qPCR) were conducted to assess the expression levels and the clinicopathological relevance of PLIN1 in HCC. Then, SK and Huh7 cells were transfected with a lentivirus overexpressing PLIN1. CCK8 assay, wound healing assay, transwell assay, and flow cytometric analysis were conducted to explore the effects of PLIN1 overexpression on HCC cell proliferation, migration, invasion, and cell cycle distribution. Ultimately, Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to investigate the underlying mechanisms of PLIN1 in HCC progression based on HCC differentially expressed genes and PLIN1 co-expressed genes. Results PLIN1 was markedly downregulated in HCC tissues, which correlated with a noticeably worse prognosis for HCC patients. Additionally, PLIN1 overexpression inhibited the proliferation, migration, and invasion of SK and Huh7 cells in vitro, as well as arresting the HCC cell cycle at the G0/G1 phase. More significantly, energy conversion-related biological processes, lipid metabolism, and cell cycle signalling pathways were the three most enriched molecular mechanisms. Conclusion The present study revealed that PLIN1 downregulation is associated with poor prognosis in HCC patients and accelerated HCC progression by promoting cellular proliferation, migration, and metastasis, as well as the mechanisms underlying the regulation of lipid metabolism-related pathways in HCC.

Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease, pathologically characterized by TDP‐43 aggregates. Recent evidence has been indicated that phosphorylated TDP‐43 (pTDP‐43) is present not only in motor neurons but also in muscle tissues. However, it is unclear whether testing pTDP‐43 aggregation in muscle tissue would assist in the diagnosis of ALS. We propose three key questions: (i) Is aggregation of pTDP‐43 detectable in routine biopsied muscles? (ii) Can detection of pTDP‐43 aggregation discriminate between ALS and non‐ALS patients? (iii) Can pTDP‐43 aggregation be observed in the early stages of ALS? We conducted a diagnostic study comprising 2 groups: an ALS group in which 18 cases underwent muscle biopsy screened from a registered ALS cohort consisting of 802 patients and a non‐ALS control group, in which we randomly selected 54 muscle samples from a biospecimen bank of 684 patients. Among the 18 ALS patients, 3 patients carried pathological GGGGCC repeats in the C9ORF72 gene, 2 patients carried SOD1 mutations, and 7 patients were at an early stage with only one body region clinically affected. The pTDP‐43 accumulation could be detected in routine biopsied muscles, including biceps brachii, deltoid, tibialis anterior, and quadriceps. Abnormal aggregation of pTDP‐43 was present in 94.4% of ALS patients (17/18) compared to 29.6% of non‐ALS controls (16/54; p < 0.001). The pTDP‐43 aggregates were mainly close to the sarcolemma. Using a semi‐quantified pTDP‐43 aggregates score, we applied a cut‐off value of 3 as a diagnostic biomarker, resulting in a sensitivity of 94.4% and a specificity of 83.3%. Moreover, we observed that accumulation of pTDP‐43 occurred in muscle tissues prior to clinical symptoms and electromyographic lesions. Our study provides proof‐of‐concept for the detection of pTDP‐43 accumulation via routine muscle biopsy which may serve as a novel biomarker for diagnosis of ALS. [ABSTRACT FROM AUTHOR]

Diet for many years has been considered a general health determinant. Recent research shows a connection between gut microbiota composition that is shaped by our diet and lifestyle diseases. Plasma trimethylamine N-oxide (TMAO) originates from gut bacteria metabolism of dietary l-carnitine, betaine, and choline. A number of studies suggest a positive correlation between elevated plasma trimethylamine N-oxide levels and a risk for cardiovascular diseases, diabetes, and cancer. Recent experimental and clinical evidence shows that TMAO may serve as a diagnostic and prognostic marker of many pathologic conditions. Therefore, rapid determination of serum TMAO concentration is of clinical interest. [ABSTRACT FROM AUTHOR]

Abstract Objective Early diagnosis and prediction of organ dysfunction are critical for intervening and improving the outcomes of septic patients. The study aimed to find novel diagnostic and predictive biomarkers of organ dysfunction for perioperative septic patients. Method This is a prospective, controlled, preliminary, and single-center study of emergency surgery patients. Mass spectrometry, Gene Ontology (GO) functional analysis, and the protein-protein interaction (PPI) network were performed to identify the differentially expressed proteins (DEPs) from sepsis patients, which were selected for further verification via enzyme-linked immunosorbent assay (ELISA). Logistic regression analysis was used to estimate the relative correlation of selected serum protein levels and clinical outcomes of septic patients. Calibration curves were plotted to assess the calibration of the models. Results Five randomized serum samples per group were analyzed via mass spectrometry, and 146 DEPs were identified. GO functional analysis and the PPI network were performed to evaluate the molecular mechanisms of the DEPs. Six DEPs were selected for further verification via ELISA. Cathepsin B (CatB), vascular cell adhesion protein 1 (VCAM-1), neutrophil gelatinase-associated lipocalin (NGAL), protein S100-A9, prosaposin, and thrombospondin-1 levels were significantly increased in the patients with sepsis compared with those of the controls (p

Objective: Early diagnosis and prediction of organ dysfunction are critical for intervening and improving the outcomes of septic patients. The study aimed to find novel diagnostic and predictive biomarkers of organ dysfunction for perioperative septic patients. Method: This is a prospective, controlled, preliminary, and single-center study of emergency surgery patients. Mass spectrometry, Gene Ontology (GO) functional analysis, and the protein-protein interaction (PPI) network were performed to identify the differentially expressed proteins (DEPs) from sepsis patients, which were selected for further verification via enzyme-linked immunosorbent assay (ELISA). Logistic regression analysis was used to estimate the relative correlation of selected serum protein levels and clinical outcomes of septic patients. Calibration curves were plotted to assess the calibration of the models. Results: Five randomized serum samples per group were analyzed via mass spectrometry, and 146 DEPs were identified. GO functional analysis and the PPI network were performed to evaluate the molecular mechanisms of the DEPs. Six DEPs were selected for further verification via ELISA. Cathepsin B (CatB), vascular cell adhesion protein 1 (VCAM-1), neutrophil gelatinase-associated lipocalin (NGAL), protein S100-A9, prosaposin, and thrombospondin-1 levels were significantly increased in the patients with sepsis compared with those of the controls (p < 0.001). Logistic regression analysis showed that CatB, S100-A9, VCAM-1, prosaposin, and NGAL could be used for preoperative diagnosis and postoperative prediction of organ dysfunction. CatB and S100-A9 were possible predictive factors for preoperative diagnosis of renal failure in septic patients. Internal validation was assessed using the bootstrapping validation. The preoperative diagnosis of renal failure model displayed good discrimination with a C-index of 0.898 (95% confidence interval 0.843–0.954) and good calibration. Conclusion: Serum CatB, S100-A9, VCAM-1, prosaposin, and NGAL may be novel markers for preoperative diagnosis and postoperative prediction of organ dysfunction. Specifically, S100-A9 and CatB were indicators of preoperative renal dysfunction in septic patients. Combining these two biomarkers may improve the accuracy of predicting preoperative septic renal dysfunction. Trial registration: The study was registered at the Chinese Clinical Trials Registry (ChiCTR2200060418) on June 1, 2022. [ABSTRACT FROM AUTHOR]

Introduction: Echinococcosis is a chronic zoonotic disease caused by tapeworms of the genus Echinococcus. The World Health Organization (WHO) has identified encapsulated disease as one of 17 neglected diseases to be controlled or eliminated by 2050. There is no accurate, early, non-invasive molecular diagnostic method to detect echinococcosis. The feasibility of circulating free DNA as a diagnostic method for echinococcosis has yielded inconclusive results in a number of published studies. However, there has been no systematic evaluation to date assessing the overall performance of these assays. We report here the first meta-analysis assessing the diagnostic accuracy of cfDNA in plasma, serum, and urine for echinococcosis. Methods: We systematically searched PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), and WeiPu databases up to 17 January 2024, for relevant studies. All analyses were performed using RevMan 5.3, Meta-DiSc 1.4, Stata 17.0, and R 4.3.1 software. The sensitivity, specificity, and other accuracy indicators of circulating free DNA for the diagnosis of echinococcosis were summarized. Subgroup analyses and meta-regression were performed to identify sources of heterogeneity. Results: A total of 7 studies included 218 patients with echinococcosis and 214 controls (156 healthy controls, 32 other disease controls (non-hydatid patients), and 26 non-study-targeted echinococcosis controls were included). Summary estimates of the diagnostic accuracy of cfDNA in the diagnosis of echinococcosis were as follows: sensitivity (SEN) of 0.51 (95% CI: 0.45-0.56); specificity (SPE) of 0.99 (95% CI: 0.97-0.99); positive likelihood ratio (PLR) of 11.82 (95% CI: 6.74-20.74); negative likelihood ratio (NLR) of 0.57 (95% CI: 0.41-0.80); diagnostic ratio (DOR) of 36.63 (95% CI: 13.75-97.59); and area under the curve (AUC) value of 0.98 (95% CI: 0.96-1.00). Conclusion: Existing evidence indicates that the combined specificity of circulating cfDNA for echinococcosis is high. However, the combined sensitivity performance is unsatisfactory due to significant inter-study heterogeneity. To strengthen the validity and accuracy of our findings, further large-scale prospective studies are required. [ABSTRACT FROM AUTHOR]

Cell-free DNA (cfDNA) has been found to be elevated in patients with schizophrenia (SZ), potentially derived from activated apoptosis, but the underlying mechanisms remain unknown. Moreover, whether the concentrations of cfDNA are altered with disease stage has not been investigated, which limits its clinical application as an auxiliary diagnostic marker for SZ. Using an improved fluorescence correlation spectroscopy (FCS) method that does not require DNA extraction, we measured the molar concentrations of cfDNA in plasma samples of 191 patients with SZ, 78 patients with mood disorders (MD) and 65 healthy controls (HC). We also analyzed the cfDNA composition from either the nucleus or mitochondria, oxidation markers and biochemical indexes to explore the potential mechanistic associations of the increased cfDNA levels. We found that in SZ patients, the cfDNA levels were significantly increased (P = 0.003) regardless of the different disease stages or antipsychotic medication use. Furthermore, qPCR revealed that cell-free nuclear DNA (cf-nDNA) (P = 0.041) but not cell-free mitochondrial DNA (cf-mtDNA) was elevated in SZ patients. Moreover, decreased SOD activity in SZ patients (P = 0.005) was negatively correlated with cfDNA levels (P = 0.047), and fasting blood glucose was positively correlated with cfDNA levels in SZ patients (P = 0.013). Our study provides evidence to support that the elevated cfDNA may be a convenient, effective and stable trait indicator of SZ. Further analysis showed that it mainly came from nucleus, suggesting increased apoptosis, and potentially related to oxidative stress and high blood glucose levels in patients. • We support using cfDNA as a convenient, effective and stable biomarker for SZ. • We found elevated cfDNA levels in SZ patients by improved FCS without DNA extraction. • The cfDNA levels were unrelated to disease stages or antipsychotic medication use. • We found higher cell-free nuclear DNA but unchanged mitochondrial DNA in SZ patients. • The cfDNA levels were correlated with SOD activity and blood glucose in SZ patients. [ABSTRACT FROM AUTHOR]

Delayed therapy escape (DTE) is frequent after thalamic deep brain stimulation for essential tremor, leading to reduced quality of life, often with ataxic symptoms, and early recognition is challenging. Our goal was to examine whether a low-frequency rebound tremor of the left hand after switching off stimulation is useful as a diagnostic marker for DTE. In this cross-sectional study with additional retrospective analysis, we examined 31 patients with bilateral thalamic DBS ≥ 12 months for essential tremor, using quantitative assessments including video-based motion capture, Fahn–Tolosa–Marin Tremor Rating Scale (FTMTRS), and scale for the assessment and rating of ataxia (SARA). If available, preoperative (preOP) and 12-month postoperative assessments were included in the analysis. Evaluations occurred with DBS activated (ON) and deactivated (OFF). A higher ratio FTMTRS nowON/preOP indicated DTE. Preoperative FTMTRS scores were available for 16 patients, including 5 patients with DTE. The receiver operating characteristic analysis found an area under the curve of 0.86 (p = 0.024) for identification of DTE by low-frequency rebound tremor (i.e., OFF) on the left. In conclusion, it could serve as a potential diagnostic marker. [ABSTRACT FROM AUTHOR]

Several lines of evidence point to an interaction between genetic predisposition and environmental factors in the onset of major depressive disorder (MDD). This study is aimed to investigate the pathogenesis of MDD by identifying key biomarkers, associated immune infiltration using bioinformatic analysis and human postmortem sample. The Gene Expression Omnibus (GEO) database of GSE98793 was adopted to identify hub genes linked to endoplasmic reticulum (ER) stress-related genes (ERGs) in MDD. Another GEO database of GSE76826 was employed to validate the novel target associated with ERGs and immune infiltration in MDD. Moreover, human postmortem sample from MDD patients was utilized to confirm the differential expression analysis of hub genes. We discovered 12 ER stress-related differentially expressed genes (ERDEGs). A LASSO Cox regression analysis helped construct a diagnostic model for these ERDEGs, incorporating immune infiltration analysis revealed that three hub genes (ERLIN1 , SEC61B , and USP13) show the significant and consistent expression differences between the two groups. Western blot analysis of postmortem brain samples indicated notably higher expression levels of ERLIN1 and SEC61B in the MDD group, with USP13 also tending to increase compared to control group. The utilization of the MDD gene chip in this analysis was sourced from the GEO database, which possesses a restricted number of pertinent gene chip samples. These findings indicate that ERDEGs especially including ERLIN1 , SEC61B , and USP13 associated the infiltration of immune cells may be potential diagnostic indicators for MDD. • The Gene Expression Omnibus (GEO) databases were used to identify risk genes for depression. • Twelve ER stress-related genes were identified. • ER stress-related genes associated with infiltration of immune system play a role in depression. [ABSTRACT FROM AUTHOR]

Objective: This study aims to develop and validate machine learning models to predict proliferative lupus nephritis (PLN) occurrence, offering a reliable diagnostic alternative when renal biopsy is not feasible or safe. Methods: This study retrospectively analyzed clinical and laboratory data from patients diagnosed with SLE and renal involvement who underwent renal biopsy at West China Hospital of Sichuan University between 2011 and 2021. We randomly assigned 70% of the patients to a training cohort and the remaining 30% to a test cohort. Various machine learning models were constructed on the training cohort, including generalized linear models (e.g., logistic regression, least absolute shrinkage and selection operator, ridge regression, and elastic net), support vector machines (linear and radial basis kernel functions), and decision tree models (e.g., classical decision tree, conditional inference tree, and random forest). Diagnostic performance was evaluated using ROC curves, calibration curves, and DCA for both cohorts. Furthermore, different machine learning models were compared to identify key and shared features, aiming to screen for potential PLN diagnostic markers. Results: Involving 1312 LN patients, with 780 PLN/NPLN cases analyzed. They were randomly divided into a training group (547 cases) and a testing group (233 cases). we developed nine machine learning models in the training group. Seven models demonstrated excellent discriminatory abilities in the testing cohort, random forest model showed the highest discriminatory ability (AUC: 0.880, 95% confidence interval(CI): 0.835-0.926). Logistic regression had the best calibration, while random forest exhibited the greatest clinical net benefit. By comparing features across various models, we confirmed the efficacy of traditional indicators like anti-dsDNA antibodies, complement levels, serum creatinine, and urinary red and white blood cells in predicting and distinguishing PLN. Additionally, we uncovered the potential value of previously controversial or underutilized indicators such as serum chloride, neutrophil percentage, serum cystatin C, hematocrit, urinary pH, blood routine red blood cells, and immunoglobulin M in predicting PLN. Conclusion: This study provides a comprehensive perspective on incorporating a broader range of biomarkers for diagnosing and predicting PLN. Additionally, it offers an ideal non-invasive diagnostic tool for SLE patients unable to undergo renal biopsy. [ABSTRACT FROM AUTHOR]

As a structural protein, keratin is mainly expressed in epithelial cells and skin appendages to provide mechanical support and external resistance. The keratin family has a total of 54 members, which are divided into type I and type II. Two types of keratins connect to each other to form keratin intermediate filaments and participate in the construction of the cytoskeleton. K18 is a non-hair keratin, which is widely expressed in simple epithelial tissues with its partner, K8. Compared with mechanical support, K8/K18 pairs play more important roles in biological regulation, such as mediating anti-apoptosis, regulating cell cycle progression, and transmitting signals. Mutations in K18 can cause a variety of non-neoplastic diseases of the visceral epithelium. In addition, the expression levels of K18 are frequently altered in various epithelial-derived tumors, especially adenocarcinomas, which suggests that K18 may be involved in tumorigenesis. Due to the specific expression pattern of K18 in tumor tissues and its serum level reflecting tumor cell death, apply K18 to diagnose tumors and predict its prognosis have the potential to be simple and effective alternative methods. However, these potential roles of K18 in tumors have not been fully summarized. In this review, we focus on the relationship between K18 and epithelial-derived tumors, discuss the value of K18 as a diagnostic and prognostic marker, and summarize the interactions of K18 with various related proteins in tumorigenesis, with examples of simple epithelial tumors such as lung, breast, liver, and gastrointestinal cancers.

Diquat (DQ) is a commonly used bipyridine herbicide known for its toxic properties and adverse effects on individuals. However, the mechanism underlying DQ-induced damage remain elusive. Our research aimed to uncover the regulatory network involved in DQ-induced damage. We analyzed publicly accessible gene expression patterns and performed research using a DQ-induced damage animal model. The GSE153959 dataset from the Gene Expression Omnibus collection and the animal model of DQ-induced kidney injury were used to identify differentially expressed genes (DEGs). Pathways including the regulation of DNA-templated transcription in response to stress, RNA polymerase II transcription regulator complex and transcription coregulatory activity were shown to be enriched in 21 DEGs. We used least absolute shrinkage and selection operator (LASSO) regression analysis to find possible diagnostic biomarkers for DQ-induced damage. Then, we used an HK-2 cell model to confirm these results. Additionally, we confirmed that 3-hydroxy-3-methylglutaryl-CoA synthase 2 (HMGCS2) was the major gene associated with DQ-induced damage using multi-omics screening. The sample validation strongly suggested that HMGCS2 has promise as a diagnostic marker and may provide new targets for therapy in the context of DQ-induced damage.

Abstract The purpose of this study was to identify novel autoantibodies against tumor-associated antigens (TAAs) and explore a diagnostic panel for Ovarian cancer (OC). Enzyme-linked immunosorbent assay was used to detect the expression of five anti-TAA autoantibodies in the discovery (70 OC and 70 normal controls) and validation cohorts (128 OC and 128 normal controls). Machine learning methods were used to construct a diagnostic panel. Serum samples from 81 patients with benign ovarian disease were used to identify the specificity of anti-TAA autoantibodies for OC. In both the discovery and validation cohorts, the expression of anti-CFL1, anti-EZR, anti-CYPA, and anti-PFN1 was higher in patients with OC than that in normal controls. The area under the receiver operating characteristic curve, sensitivity, and specificity of the panel containing anti-CFL1, anti-EZR, and anti-CYPA were 0.762, 55.56%, and 81.31%. The panel identified 53.06%, 53.33%, and 51.11% of CA125 negative, HE4 negative and the Risk of Ovarian Malignancy Algorithm negative OC patients, respectively. The combination of the three anti-TAA autoantibodies can serve as a favorable diagnostic tool for OC and has the potential to be a complementary biomarker for CA125 and HE4 in the diagnosis of ovarian cancer.

Hypersensitivity pneumonitis (HP) is a complex interstitial pulmonary syndrome. This clinical entity is characterized by sensitization to a specific antigen. Early detection of this antigen is associated with an increased likelihood of a favorable outcome. Increased mortality in hypersensitivity pneumonitis is associated with the development of lung fibrosis. At the same time, clinical interventions do not significantly improve the prognosis of the disease due to a lack of understanding the mechanisms underlying the development of this type of fibrosis. Using reliable biomarkers that objectively reflect biological processes in lung fibrosis may improve clinical decisionmaking. Various biomarkers are now beginning to play a critical role in diagnosing and treating a variety of human diseases. Unfortunately, hypersensitivity pneumonitis is an exception to this general trend. There is still a great deal of research to be done in this area in the search for diagnostic biomarkers. The aim of this study was to identify biomarkers of lung fibrosis development in patients with hypersensitivity pneumonitis. We used mature serum microRNAs, which may regulate inflammation and fibrosis, as such diagnostic markers. Patients with a diagnosis of hypersensitivity pneumonitis (with and without lung fibrosis) as well as healthy individuals without chronic diseases (control group) were included into the study. Clinical and laboratory parameters were assessed in all patients. The miScript miRNA PCR Array Kit (QIAGEN) was used for gene expression profiling of mature serum miRNAs. The data obtained were verified using real-time PCR. Our research has identified a number of mature microRNAs that are likely to be involved in lung fibrosis and inflammation (miR-22, miR-150 and miR-106b). Following an extended study, including monitoring of disease progression over time, the applied diagnostic kit may be used in clinical practice to determine disease activity and development of fibrosis formation in lung tissue in patients with different variants of hypersensitivity pneumonitis.

Dual immunoglobulin domain-containing cell adhesion molecule (DICAM) is a type I transmembrane protein that presents in various cells including renal tubular cells. This study evaluated the expression and protective role of DICAM in renal tubular cell injury. HK-2 cells were incubated and treated with lipopolysaccharide (LPS, 30 μg/mL) or hydrogen peroxide (H2O2, 100 μM) for 24 h. To investigate the effect of the gene silencing of DICAM, small interfering RNA of DICAM was used. Additionally, to explain its role in cellular response to injury, DICAM was overexpressed using an adenoviral vector. DICAM protein expression levels significantly increased following treatment with LPS or H2O2 in HK-2 cells. In response to oxidative stress, DICAM showed an earlier increase (2–4 h following treatment) than neutrophil gelatinase-associated lipocalin (NGAL) (24 h following treatment). DICAM gene silencing increased the protein expression of inflammation-related markers, including IL-1β, TNF-α, NOX4, integrin β1, and integrin β3, in H2O2-induced HK-2 cell injury. Likewise, in the LPS-induced HK-2 cell injury, DICAM knockdown led to a decrease in occludin levels and an increase in integrin β3, IL-1β, and IL-6 levels. Furthermore, DICAM overexpression followed by LPS-induced HK-2 cell injury resulted in an increase in occludin levels and a decrease in integrin β1, integrin β3, TNF-α, IL-1β, and IL-6 levels, suggesting an alleviating effect on inflammatory responses. DICAM was elevated in the early stage of regular tubular cell injury and may protect against renal tubular injury through its anti-inflammatory properties. DICAM has a potential as an early diagnostic marker and therapeutic target for renal cell injury.

Colorectal cancer (CRC) is a complex disease driven by intricate mechanisms, making it challenging to understand and manage. The miR-17-92 cluster has gained significant attention in CRC research due to its diverse functions and crucial role in various aspects of the disease. This cluster, consisting of multiple individual miRNAs, influences critical processes like tumor initiation, angiogenesis, metastasis, and the epithelial–mesenchymal transition (EMT). Beyond its roles in tumorigenesis and progression, miR-17-92′s dysregulation in CRC has substantial implications for diagnosis, prognosis, and treatment, including chemotherapy responsiveness. It also shows promise as a diagnostic and prognostic biomarker, offering insights into treatment responses and disease progression. This review provides a comprehensive overview of recent advancements and the context-dependent role of the miR-17-92 cluster in colorectal cancer, drawing from the latest high-quality published data. It summarizes the established mechanisms governing miR-17-92 expression and the molecular pathways under its influence. Furthermore, it examines instances where it functions as an oncogene or a tumor suppressor, elucidating how cellular contexts dictate its biological effects. Ultimately, miR-17-92 holds promise as a biomarker for prognosis and therapy response, as well as a potential target for cancer prevention and therapeutic interventions. In essence, this review underscores the multifaceted nature of miR-17-92 in CRC research, offering promising avenues for enhancing the management of CRC patients.

Background Rheumatoid arthritis (RA) is an autoimmune, inflammatory joint disease. There is growing evidence that ferroptosis is involved in the pathogenesis of RA. This study aimed to search for diagnostic markers of ferroptosis in RA and to analyse the potential mechanisms and clinical value.Materials and methods RA-associated datasets were used from the publicly available GEO database. Three methods of machine learning were applied to screen biomarkers. The diagnostic efficacy of the results was also verified by receiver operating characteristic (ROC) curve, external dataset, qRT-PCR and Western blot. Enrichment analysis was performed in this process, while protein–protein interaction (PPI) analysis and immune infiltration correlation analysis were performed using biomarkers, and competing endogenous RNA (ceRNA) networks were constructed to search for prospective therapeutic targets.Results MMP13 and GABARAPL1 can be used as ferroptosis diagnostic genes in RA. The ROC curve and PPI result demonstrated that MMP13 and GABARAPL1 had an excellent diagnostic value. The results of signature genes in the external dataset, qRT-PCR and Western blot further confirm our findings. The enrichment analysis showed that p53, MAPK and NOD-like receptor signalling pathways may be involved in the process of ferroptosis in RA. In addition, two ferroptosis diagnostic genes in RA participate in the occurrence of ferroptosis in RA via oxidative stress, metabolism and immune response. Immune infiltration analysis showed that RA extensively infiltrated B cells, T cells, macrophages and other immune cells. Persistent immune activation may be an essential reason for the progression of ferroptosis in RA. We also obtained five potential therapeutic agents for RA and some long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) regulating ferroptosis diagnostic genes.Conclusions Our study suggests that MMP13 and GABARAPL1, which are closely linked with oxidative stress and immunological modulation, can be used as ferroptosis-related potential diagnostic markers in RA and provide new clues regarding the diagnostic and therapeutic targets of ferroptosis in RA.

The purpose of this study was to identify novel autoantibodies against tumor-associated antigens (TAAs) and explore a diagnostic panel for Ovarian cancer (OC). Enzyme-linked immunosorbent assay was used to detect the expression of five anti-TAA autoantibodies in the discovery (70 OC and 70 normal controls) and validation cohorts (128 OC and 128 normal controls). Machine learning methods were used to construct a diagnostic panel. Serum samples from 81 patients with benign ovarian disease were used to identify the specificity of anti-TAA autoantibodies for OC. In both the discovery and validation cohorts, the expression of anti-CFL1, anti-EZR, anti-CYPA, and anti-PFN1 was higher in patients with OC than that in normal controls. The area under the receiver operating characteristic curve, sensitivity, and specificity of the panel containing anti-CFL1, anti-EZR, and anti-CYPA were 0.762, 55.56%, and 81.31%. The panel identified 53.06%, 53.33%, and 51.11% of CA125 negative, HE4 negative and the Risk of Ovarian Malignancy Algorithm negative OC patients, respectively. The combination of the three anti-TAA autoantibodies can serve as a favorable diagnostic tool for OC and has the potential to be a complementary biomarker for CA125 and HE4 in the diagnosis of ovarian cancer. [ABSTRACT FROM AUTHOR]

For the development of a competitive ELISA (cELISA) to detect serum antibodies against the Mycoplasma mycoides subsp. Mycoides (Mmm) (strain PG1), the causative agent of contagious bovine pleuropneumonia (CBPP), all the proteins of this pathogen were analyzed. Then, a specific extracellular region of a transmembrane protein with the potential for diagnosis was identified. After that, a monoclonal antibody (Mab) named 3A8 was obtained using this extracellular region as an immunogen. Finally, a cELISA was established with the extracellular domain of this transmembrane protein as the coating antigen, Mab 3A8 as the competitive antibody, and HRP-labeled goat anti-mouse IgG as the enzyme-labeled antibody. This established method was used to detect the antibody dynamic regularity of goats which are artificially immunized Mmm and was also compared with a commercial ELISA kit. Further, the sera of 1011 different cattle from border provinces of China were monitored using a candidate Mab 3A8 cELISA. The detection results of known background sera used in this study indicate that a candidate diagnostic marker was successfully identified by analyzing all the coding proteins of Mmm in this research, and the cELISA established based on the Mab 3A8 against this protein can detect CBPP-positive serum with specificity and has no cross-reaction with other related epidemic disease-positive sera. In addition, we tested the sera collected from the border areas of China using the established ELISA, and no positive sample was detected. The research protocol of the CBPP cELISA established in this study is different from the traditional method, which can greatly reduce the investment of manpower and capital and save development time. We believe that this study's protocol could serve as a reference for the development of detection methods for mycoplasma and other complex pathogens. Key points: • A Mmm-specific diagnostic marker was obtained based on protein characteristics. • A cELISA was established for CBPP serum antibody detection. • The serological investigation was conducted for CBPP in the border areas of China. [ABSTRACT FROM AUTHOR]

Background: Ulcerative colitis (UC) is a common and progressive inflammatory bowel disease primarily affecting the colon and rectum. Prolonged inflammation can lead to colitis-associated colorectal cancer (CAC). While the exact cause of UC remains unknown, this study aims to investigate the role of the TWIST1 gene in UC. Methods: Second-generation sequencing data from adult UC patients were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified, and characteristic genes were selected using machine learning and Lasso regression. The Receiver Operating Characteristic (ROC) curve assessed TWIST1’s potential as a diagnostic factor (AUC score). Enriched pathways were analyzed, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Variation Analysis (GSVA). Functional mechanisms of marker genes were predicted, considering immune cell infiltration and the competing endogenous RNA (ceRNA) network. Results: We found 530 DEGs, with 341 upregulated and 189 downregulated genes. TWIST1 emerged as one of four potential UC biomarkers via machine learning. TWIST1 expression significantly differed in two datasets, GSE193677 and GSE83687, suggesting its diagnostic potential (AUC = 0.717 in GSE193677, AUC = 0.897 in GSE83687). Enrichment analysis indicated DEGs associated with TWIST1 were involved in processes like leukocyte migration, humoral immune response, and cell chemotaxis. Immune cell infiltration analysis revealed higher rates of M0 macrophages and resting NK cells in the high TWIST1 expression group, while TWIST1 expression correlated positively with M2 macrophages and resting NK cell infiltration. We constructed a ceRNA regulatory network involving 1 mRNA, 7 miRNAs, and 32 long non-coding RNAs (lncRNAs) to explore TWIST1’s regulatory mechanism. Conclusion: TWIST1 plays a significant role in UC and has potential as a diagnostic marker. This study sheds light on UC’s molecular mechanisms and underscores TWIST1’s importance in its progression. Further research is needed to validate these findings in diverse populations and investigate TWIST1 as a therapeutic target in UC. [ABSTRACT FROM AUTHOR]

Simple Summary: Long-chain Acyl-CoA synthetase (ACSL) family members are involved in long-chain fatty acid activation, a crucial step for cells to utilize fatty acids (FAs) in the regulation of FA homeostasis. Cancer cells utilize the limited environmental FAs via the dysregulation of ACSL isoforms to adapt to an altered lipid metabolism. Dysregulated ACSLs are associated with either cancer promotion or inhibition, dependent on the cellular context. The role of ACSLs in different cancer types has not yet been fully elucidated, and, particularly, their role in lung cancer is unclear. In this study, we analyzed the expression pattern of ACSLs, evaluated their diagnostic values, and explored the therapeutic potential of the ACSL inhibitor Triacsin C in human lung cancer cells. Abnormal expression of ACSL members 1, 3, 4, 5, and 6 is frequently seen in human cancer; however, their clinical relevance is unclear. In this study, we analyzed the expression of ACSLs and investigated the effects of the ACSL inhibitor Triacsin C (TC) in lung cancer. We found that, compared to normal human bronchial epithelial (NHBE) cells, ACSL1, ACSL4, and ACSL6 were highly expressed, while ACSL3 and ACSL5 were lost in the majority of lung cancer cell lines. ACSL activity was associated with the expression levels of the ACSLs. In primary lung tumors, a higher expression of ACSL1, ACSL4, and ACSL5 was significantly correlated with adenocarcinoma (ADC). Moreover, ACSL5 was significantly reversely related to the proliferation marker Ki67 in low-grade tumors, while ACSL3 was positively associated with Ki67 in high-grade tumors. Combination therapy with TC and Gemcitabine enhanced the growth-inhibitory effect in EGFR wild-type cells, while TC combined with EGFR-TKIs sensitized the EGFR-mutant cells to EGFR-TKI treatment. Taken together, the data suggest that ACSL1 may be a biomarker for lung ADC, and ACSL1, ACSL4, and ACSL5 may be involved in lung cancer differentiation, and TC, in combination with chemotherapy or EGFR-TKIs, may help patients overcome drug resistance. [ABSTRACT FROM AUTHOR]

Early diagnosis is essential for the safer perinatal management of placenta accreta spectrum (PAS). We used transcriptome analysis to investigate diagnostic maternal serum biomarkers and the mechanisms of PAS development. We analyzed eight formalin-fixed paraffin-embedded placental specimens from two placenta increta and three placenta percreta cases who underwent cesarean hysterectomy at Sapporo Medical University Hospital between 2013 and 2019. Invaded placental regions were isolated from the uterine myometrium and RNA was extracted. The transcriptome difference between normal placenta and PAS was analyzed by microarray analysis. The PAS group showed markedly decreased expression of placenta-specific genes such as LGALS13 and the pregnancy-specific beta-1-glycoprotein (PSG) family. Term enrichment analysis revealed changes in genes related to cellular protein catabolic process, female pregnancy, autophagy, and metabolism of lipids. From the highly dysregulated genes in the PAS group, we investigated the expression of PSG family members, which are secreted into the intervillous space and can be detected in maternal serum from the early stage of pregnancy. The gene expression level of PSG6 in particular was progressively decreased from placenta increta to percreta. The PSG family, especially PSG6, is a potential biomarker for PAS diagnosis. [ABSTRACT FROM AUTHOR]

Background: Leptospirosis is a zoonotic disease caused by pathogenic Leptospira spp., posing a significant public health threat globally. Understanding the clinicopathological profile of leptospirosis and identifying reliable diagnostic markers are crucial for effective disease management. Objective: This study aimed to investigate the clinicopathological profile of human leptospirosis in a tertiary care center in Kerala, India, and evaluate the utility of serum albumin as a diagnostic marker. Methods: A retrospective analysis of medical records was conducted for patients diagnosed with leptospirosis. Demographic data, clinical symptoms, laboratory findings, and outcomes were collected and analyzed. Serum albumin levels were compared between leptospirosis patients and controls. Statistical analyses were performed to assess correlations and associations. Results: A total of 41 patients with confirmed leptospirosis were included in the study. Fever (90.2%), myalgia (82.9%), and headache (70.7%) were common clinical manifestations. Thrombocytopenia (82.9%) and hypoalbuminemia (97.6%) were prevalent laboratory findings. Serum albumin levels were significantly lower in leptospirosis patients compared to controls (p < 0.05). Lower serum albumin levels were associated with increased disease severity and complications, including acute kidney injury. Conclusion: This study provides insights into the clinicopathological characteristics of leptospirosis in Kerala and highlights the potential diagnostic utility of serum albumin. Incorporating serum albumin levels into the diagnostic workup of leptospirosis patients could aid in early detection and risk stratification, ultimately improving clinical outcomes. Further prospective studies are warranted to validate these findings and explore the clinical implications of serum albumin as a prognostic marker for leptospirosis. [ABSTRACT FROM AUTHOR]

Introduction: Diabetic nephropathy (DN), distinguished by detrimental changes in the renal glomeruli, is regarded as the leading cause of death from end-stage renal disease among diabetics. Cellular senescence plays a paramount role, profoundly affecting the onset and progression of chronic kidney disease (CKD) and acute kidney injuries. This study was designed to delve deeply into the pathological mechanisms between glomerulus-associated DN and cellular senescence. Methods: Glomerulus-associated DN datasets and cellular senescence-related genes were acquired from the Gene Expression Omnibus (GEO) and CellAge database respectively. By integrating bioinformatics and machine learning methodologies including the LASSO regression analysis and Random Forest, we screened out four signature genes. The receiver operating characteristic (ROC) curve was performed to evaluate the diagnostic performance of the selected genes. Rigorous experimental validations were subsequently conducted in the mouse model to corroborate the identification of three signature genes, namely LOX, FOXD1 and GJA1. Molecular docking with chlorogenic acids (CGA) was further established not only to validate LOX, FOXD1 and GJA1 as diagnostic markers but also reveal their potential therapeutic effects. Results and discussion: In conclusion, our findings pinpointed three diagnostic markers of glomerulus-associated DN on the basis of cellular senescence. These markers could not only predict an increased risk of DN progression but also present promising therapeutic targets, potentially ushering in innovative treatments for DN in the elderly population. [ABSTRACT FROM AUTHOR]

Background: Uroplakin-1a (Upk1a) and uroplakin-1b (Upk1b) have recently been identified as diagnostic markers for the distinction of urothelial carcinomas from other solid tumor entities. Both proteins play an important role in the stabilization and strengthening of epithelial cells that line the bladder. Methods: To evaluate the prognostic role of uroplakin expression in urothelial carcinomas, more than 2700 urothelial neoplasms were analyzed in a tissue microarray format by immunohistochemistry. To further assess the diagnostic role of uroplakin immunohistochemistry, results were compared with preexisting GATA3 data. Result: The fraction of Upk1a/Upk1b positive cases decreased slightly from pTaG2 low-grade (88% positive for Upk1a/87% positive for Upk1b) and pTaG2 high-grade (92%/89%) to pTaG3 (83%/88%; p > 0.05) and was lower in muscle-invasive (pT2-4) carcinomas (42%/64%; p < 0.0001/p < 0.0001 for pTa vs. pT2-4). Within pT2-4 carcinomas, high expression of Upk1a and Upk1b was linked to nodal metastasis and lymphatic vessel infiltration (p < 0.05) but unrelated to patient outcome. There were significant associations between Upk1a, Upk1b and GATA3 immunostaining (p < 0.0001 each), but 11% of GATA3 negative cancers were Upk1a/b positive and 8% of Upk1a/b negative cancers were GATA3 positive. Absence of GATA3/Upk1a/b staining was significantly linked to poor patient survival in the subgroup of 126 pT4 carcinomas (p = 0.0004) but not in pT2 and pT3 cancers. Conclusions: In summary, the results of our study demonstrate that Upk1a and/or Upk1b immunohistochemistry can complement GATA3 for the distinction of urothelial carcinomas. Furthermore, a progressive loss of Upk1a/b expression during stage progression and a prognostic role of the combination GATA3/Upk1a/Upk1b in pT4 carcinomas is evident. [ABSTRACT FROM AUTHOR]

Abstract The field of neuropsychiatry is considered a middle ground between neurological and psychiatric disorders, thereby bridging the conventional boundaries between matter and mind, consciousness, and function. Neuropsychiatry aims to evaluate and treat cognitive, behavioral, and emotional disorders in individuals with neurological conditions. However, the pathophysiology of these disorders is not yet fully understood, and objective biological indicators for these conditions are currently lacking. Treatment options are also limited due to the blood–brain barrier, which results in poor treatment effects. Additionally, many drugs, particularly antipsychotic drugs, have adverse reactions, which make them difficult to tolerate for patients. As a result, patients often abandon treatment owing to these adverse reactions. Since the discovery of exosomes in 1983, they have been extensively studied in various diseases owing to their potential as nanocellulators for information exchange between cells. Because exosomes can freely travel between the center and periphery, brain-derived exosomes can reflect the state of the brain, which has considerable advantages in diagnosis and treatment. In addition, administration of engineered exosomes can improve therapeutic efficacy, allow lesion targeting, ensure drug stability, and prevent systemic adverse effects. Therefore, this article reviews the source and biological function of exosomes, relationship between exosomes and the blood–brain barrier, relationship between exosomes and the pathological mechanism of neuropsychiatric disorders, exosomes in the diagnosis and treatment of neuropsychiatric disorders, and application of engineered exosomes in neuropsychiatric disorders.

Abstract Background There has been a gradual increase in the occurrence of cardiovascular and cerebrovascular ischemic diseases, particularly as comorbidities. Yet, the mechanisms underlying these diseases remain unclear. Ferroptosis has emerged as a potential contributor to cardio-cerebral ischemic processes. Therefore, this study investigated the shared biological mechanisms between the two processes, as well as the role of ferroptosis genes in cardio-cerebral ischemic damage, by constructing co-expression modules for myocardial ischemia (MI) and ischemic stroke (IS) and a network of protein–protein interactions, mRNA-miRNA, mRNA-transcription factors (TFs), mRNA-RNA-binding proteins (RBPs), and mRNA-drug interactions. Results The study identified seven key genes, specifically ACSL1, TLR4, ADIPOR1, G0S2, PDK4, HP, PTGS2, and subjected them to functional enrichment analysis during ischemia. The predicted miRNAs were found to interact with 35 hub genes, and interactions were observed between 11 hub genes and 30 TF transcription factors. Additionally, 10 RBPs corresponding to 16 hub genes and 163 molecular compounds corresponding to 30 hub genes were identified. This study also clarified the levels of immune infiltration between MI and IS and different subtypes. Finally, we identified four hub genes, including TLR4, by using a diagnostic model constructed by Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis; ADIPOR1, G0S2, and HP were shown to have diagnostic value for the co-pathogenesis of MI and cerebral ischemia by both validation test data and RT-qPCR assay. Conclusions To the best our knowledge, this study is the first to utilize multiple algorithms to comprehensively analyze the biological processes of MI and IS from various perspectives. The four hub genes, TLR4, ADIPOR1, G0S2, and HP, have proven valuable in offering insights for the investigation of shared injury pathways in cardio-cerebral injuries. Therefore, these genes may serve as diagnostic markers for cardio-cerebral ischemic diseases.

The genetic disorder Prader-Willi syndrome (PWS) is mainly caused by the loss of multiple paternally expressed genes in chromosome 15q11-q13 (the PWS region). Early diagnosis of PWS is essential for timely treatment, leading to effectively easing some clinical symptoms. Molecular approaches for PWS diagnosis at the DNA level are available, but the diagnosis of PWS at the RNA level has been limited. Here, we show that a cluster of paternally transcribed snoRNA-ended long noncoding RNAs (sno-lncRNAs, sno-lncRNA1–5) derived from the SNORD116 locus in the PWS region can serve as diagnostic markers. In particular, quantification analysis has revealed that 6,000 copies of sno-lncRNA3 are present in 1 μL whole blood samples from non-PWS individuals. sno-lncRNA3 is absent in all examined whole blood samples of 8 PWS individuals compared to 42 non-PWS individuals and dried blood samples of 35 PWS individuals compared to 24 non-PWS individuals. Further developing a new CRISPR-MhdCas13c system for RNA detection with a sensitivity of 10 molecules per μL has ensured sno-lncRNA3 detection in non-PWS, but not PWS individuals. Together, we suggest that the absence of sno-lncRNA3 represents a potential marker for PWS diagnosis that can be detected by both RT-qPCR and CRISPR-MhdCas13c systems with only microlitre amount of blood samples. Such an RNA-based sensitive and convenient approach may facilitate the early detection of PWS.

Yang Yang,1 Genhao Zhang2 1Department of Nuclear Medicine, Henan Provincial People’s Hospital, People’s Hospital of Zhengzhou University, People’s Hospital of Henan University, Zhengzhou, Henan, 450003, People’s Republic of China; 2Department of Blood Transfusion, Zhengzhou University First Affiliated Hospital, Zhengzhou, Henan, 450052, People’s Republic of ChinaCorrespondence: Genhao Zhang, Email smilegenhao@163.comBackground: There is currently no biomarker that can reliably identify sepsis, despite recent scientific advancements. We systematically evaluated the value of lysosomal genes for the diagnosis of pediatric sepsis.Methods: Three datasets (GSE13904, GSE26378, and GSE26440) were obtained from the gene expression omnibus (GEO) database. LASSO regression analysis and random forest analysis were employed for screening pivotal genes to construct a diagnostic model between the differentially expressed genes (DEGs) and lysosomal genes. The efficacy of the diagnostic model for pediatric sepsis identification in the three datasets was validated through receiver operating characteristic curve (ROC) analysis. Furthermore, a total of 30 normal samples and 35 pediatric sepsis samples were gathered to detect the expression levels of crucial genes and assess the diagnostic model’s efficacy in diagnosing pediatric sepsis in real clinical samples through real-time quantitative PCR (qRT-PCR).Results: Among the 83 differentially expressed genes (DEGs) related to lysosomes, four key genes (STOM, VNN1, SORT1, and RETN) were identified to develop a diagnostic model for pediatric sepsis. The expression levels of these four key genes were consistently higher in the sepsis group compared to the normal group across all three cohorts. The diagnostic model exhibited excellent diagnostic performance, as evidenced by area under the curve (AUC) values of 1, 0.971, and 0.989. Notably, the diagnostic model also demonstrated strong diagnostic ability with an AUC of 0.917 when applied to the 65 clinical samples, surpassing the efficacy of conventional inflammatory indicators such as procalcitonin (PCT), white blood cell (WBC) count, C-reactive protein (CRP), and neutrophil percentage (NEU%).Conclusion: A four-gene diagnostic model of lysosomal function was devised and validated, aiming to accurately detect pediatric sepsis cases and propose potential target genes for lysosomal intervention in affected children.Keywords: pediatric sepsis, diagnostic marker, ROC curves, lysosomal, GSEA

Coronary microvascular dysfunction (CMD) represents a principal etiological factor in ischemic heart disease. Nonetheless, a considerable subset of CMD patients experiences diagnostic delays attributable to the inadequacy of current diagnostic methodologies; which in turn results in deferred therapeutic interventions and elevated mortality rates. This study seeks to elucidate the distinct metabolic profile associated with CMD in rat models and to identify specific diagnostic markers that could enhance the diagnostic accuracy for CMD. In this study, 18 Wistar rats were randomly allocated into two groups: the sham group and the CMD group. The CMD group received injections of embolic microspheres into the left ventricle to establish a CMD model. Subsequently, non-targeted metabolomics and acetylated proteomics analyses were conducted. Machine-learning techniques were employed to identify the co-diagnostic markers of the disease. This study identified 53 key proteins through differential expression proteins (DEPs) and modular proteins analysis. Subsequently, four core proteins (Emc1; Ank1; Fbln2; and Hp) were determined as diagnostic markers for CMD using lasso regression, support vector machine, and random forest methodologies. Receiver operating characteristic curve analysis further demonstrated robust diagnostic performance. Gene ontology and kyoto encyclopedia of genes and genome enrichment analyses indicated that the DEPs were predominantly associated with metabolic pathways. Ultimately, the integrative analysis of proteomics and metabolomics suggested that the central metabolic mechanism underlying CMD pathogenesis may be linked to the tricarboxylic acid cycle. This study revealed specific changes in the proteomic and metabolic profiles of CMD rats and identified four diagnostic markers, which are proteins and metabolites that could be potential diagnostic biomarkers for CMD.

(Background) Cancer-associated fibroblasts (CAFs) are major cancer stromal components. CAFs have diverse functions and cell origins. Podoplanin (PDPN), a lymphatic vessel marker, is also a CAF marker in certain cancers. On daily diagnosis of early colorectal carcinoma (CRC), PDPN upregulation in the stroma is often encountered, suggesting PDPN-positive CAFs have emerged. However, PDPN-positive CAFs in early CRC have not been studied well. (Methods) On immunohistochemistry, PDPN expression in the lamina propria or stroma of adenomas, early CRCs, and neuroendocrine tumors, their normal neighbors, and non-neoplastic colorectal lesions were compared. Single-cell RNA sequencing (scRNA-seq) of CRC was used to explore PDPNhigh CAFs’ cell origins. (Results) Reticular cells or pericryptal fibroblasts in the lamina propria of adenomas and early CRCs showed higher PDPN expression than did normal mucosae and non-neoplastic lesions (p < 0.01). Pericryptal PDPN expression was a diagnostic feature of adenomas and early CRCs. scRNA-seq of CRCs highlighted that PDPNhigh CAFs had distinctly higher COL4A1, COL4A2, and WNT5A expression, unlike well-known CAFs characterized by high FAP, POSTN, or ACTA2 expression. (Conclusions) We demonstrated that pericryptal fibroblasts and reticular cells in the lamina propria are origins of early-stage CRC CAFs and thus have potential as a diagnostic marker for distinguishing colorectal non-neoplastic from neoplastic lesions.

The translocator protein (TSPO) is predominately localized on the outer mitochondrial membrane in steroidogenic cells. In the brain, TSPO expression, low under normal conditions, results upregulated in response to glial cell activation, that occurs in neuroinflammation. As a consequence, TSPO has been extensively studied as a biomarker of such conditions by means of TSPO-targeted radiotracers. Although [11C]-PK11195, the prototypical TSPO radioligand, is still widely used for in vivo studies, it is endowed with severe limitations, mainly low sensitivity and poor amenability to quantification. Consequently, several efforts have been focused on the design of new radiotracers for the in vivo imaging of TSPO. The present review will provide an outlook on the latest advances in TSPO radioligands for neuroinflammation imaging. The final goal is to pave the way for (radio)chemists in the future design and development of novel effective and sensitive radiopharmaceuticals targeting TSPO.

Background: Intracranial aneurysm (IA) is a localized abnormal dilation of the cerebral vascular wall, the degeneration of which is closely related to high oxidative stress. Methods: Clinical information and RNA-seq data from five public datasets were downloaded from the Gene Expression Omnibus (GEO). Using the “GSVA” package, enrichment analysis was performed on the gene sets of the oxidative stress, reactive oxygen species (ROS), metabolism, and inflammatory pathways retrieved from the MsigDB and Kyoto encyclopedia of genes and genomes (KEGG) databases. Weighted gene co-expression network analysis (WGCNA) was conducted using the “WGCNA” package, followed by using the “limma” R package to select differentially expressed genes (DEGs). Key genes were determined by applying three machine learning algorithms (random forest, Lasso, and SVM-RFE). The expression levels of the key genes were verified by the quantitative real-time polymerase chain reaction (qRT-PCR) in IA. Finally, ESTIMATE and CIBERPSORT algorithms were used for immune infiltration analysis. Results: The enrichment score of the oxidative stress, ROS, metabolism, and inflammatory pathways was calculated, and we found that these pathways were significantly activated in IA samples with higher immune infiltration. The intersection between the blue module related to oxidative stress (610 genes identified by WGCNA) and 380 upregulated DEGs contained a total of 209 key genes, which were further processed by machine learning algorithms to obtain four crucial diagnostic markers (FLVCR2, SDSL, TBC1D2, and SLC31A1) for IA. These key genes are highly expressed in human brain vascular smooth muscle cells. The expressions of the four markers were significantly positively correlated with the abnormal activation phenotypes of oxidative stress, the ROS and glucometabolic pathways, and suppressive immune infiltration. Conclusion: This study employed WGCNA combined with three machine learning algorithms to identify four oxidative stress-related signature markers for IA, providing novel insights into the clinical management of IA patients.