Background and aim The protective effects of aqueous extract of Pistacia lentiscus leaves (AELPL) against gastric and duodenal ulcers induced by alcohol oral gavage administration in Wistar rats were investigated in this study. Methods The rats were divided into six groups control, ethanol single, ethanol + AEPL (25–50–100) and famotidine + ethanol. Results HPLC-MS analysis allowed the identification of numerous phenolic compounds in P. lentiscus leaves such as flavonoids (isoquercetin and luteolin), flavonols (catechin, rutin and kaempferol), phenolic acids (ellagic and dicaffeoylquinic) and tannins. Ethanol administration induced significant gastric and duodenal ulcerative lesions, while AELPL pretreatment (25, 50 and 100 mg/kg) provided a dose-dependent mucosal protection comparable to famotidine, a widely used drug for the treatment of gastric ulcers. AELPL like famotidine also restored gastric pH and volume, counteracting ethanol-induced acidity. Biochemical analyses demonstrated that AELPL like famotidine mitigated oxidative stress by reducing lipid peroxidation, carbonylated proteins and hydrogen peroxide levels, whereas it restored non-protein thiols content in the stomach, duodenum and plasma in a dose-dependent manner. Additionally, AELPL restored antioxidant enzyme activities including catalase, superoxide dismutase, glutathione peroxidase and glutathione-S-transferase. AELPL also reduced ethanol-induced increase in free iron, ionized calcium and interleukin-6 levels, indicating its anti-inflammatory potential. Conclusion These findings suggest that AELPL exhibits gastroduodenal protective effects against ethanol-induced damage, with efficacy comparable to famotidine. Protective mechanisms likely involve modulation of oxidative stress and inflammation, supporting AELPL’s potential as a therapeutic agent for gastroduodenal injuries.

Background: Adrenocortical carcinoma (ACC) is a rare and extremely lethal endocrine malignancy emerging from adrenal cortex, characterized by a poor prognosis. This study, performed integrated bioinformatics to elucidate the underlying molecular mechanisms and identify novel biomarkers, validating them as therapeutic targets for ACC prognosis. Methods and results: The RNA-seq data across five gene expression profiles identified 79 DEGs through a comparative analysis of normal and ACC specimens. Functional enrichment and pathway analyses using the DAVID database revealed the most significant GO terms and enriched KEGG pathways. PPI network was constructed utilizing the STRING database, followed by module analysis in Cytoscape. Finally, 10 hub genes were identified including TAGLN, LUM, PDGFRA, FBLN5, MMP2, LAMA2, DCN, IGF1, FBLN1, and CXCL12 as potential biomarkers. Subsequent survival analysis confirmed that TAGLN, LUM, LAMA2, FBLN5, and FBLN1 are significantly associated with poor patient survivability. Furthermore, TFs-DEGs and miRNAs-DEGs network analyses, identified 10 transcriptional and post-translational regulators. Finally, gene-disease and gene-drug association highlighted correlated diseases and their promising inhibitors. Conclusion In conclusion, the identified novel biomarkers and associated pathways, provides a comprehensive insight into the molecular mechanisms, prognosis, and potential clinical applications for the diagnosis and therapeutic interventions of ACC.

Purpose Multiple myeloma (MM) is a terminally differentiated plasma cell hematological malignancy. The revised international staging system (RISS) is commonly used in patients with de novo MM, but it has limitations in predicting prognosis. Better biomarkers need to added to the staging system. Results This retrospective study included a total of 302 patients. Smooth curve fitting analysis showed that serum ferritin levels were associated with relapse and all-cause death. The K-M curve analysis indicated that MM patients with higher ferritin levels had shorter PFS (p < 0.0056) and OS (p = 0.0014). Multivariate Cox regression analysis also showed MM patients with high serum ferritin had poor PFS (p = 0.0012) and OS (p = 0.0258), with independent correlation. The prediction model of ROC analysis based on Cox regression validated ferritin had a predictive value for PFS and OS, and increased the predictive value of ISS and RISS for OS. Conclusion We revealed that baseline serum ferritin levels were associated with prognosis in patients with MM, and patients with higher serum ferritin have poorer PFS and OS. Serum ferritin could increase the prediction value. The study provided a new evidence for searching for prognostic biomarkers in MM patients.

Background and Objective Waterpipe smoking (WPS) has increased globally and may lead to various metabolic disorders. However, its long-term effects and cessation impact on metabolic biomarkers and omentin-1 remain unclear. This study aims to evaluate the impact of WPS and its cessation on metabolic biomarkers and omentin-1 levels and explore their correlations. Materials and Methods 90 individuals were categorized into three groups (non-smokers, waterpipe smokers and cessation of waterpipe smokers). FBS and lipid profiles including TC, TG and HDL were measured using the Cobas 6000 c501 system, while FI was analyzed with the Cobas 6000 c601 system. Omentin-1 concentrations were determined using the enzyme-linked immunosorbent assay (ELISA) with a human omentin ELISA kit. Results FI, HOMA-IR and lipid profiles were significantly elevated in WPS and cessation groups. Omentin-1 and DBP levels significantly decreased in both groups compared to non-smokers. Increased WPS duration leads to reduced BMI, WC and DBP, while cessation duration decreases FBS and SBP. A negative association was identified among omentin-1 with FBS and O2. Conclusion WPS and its cessation adversely affect metabolic health, reducing omentin-1 levels and increasing the risk of metabolic disorders. Over time, cessation improves specific biochemical markers, highlighting the need for public health awareness.

Background: Preterm prelabor rupture of the fetal membranes (PPROM) increases the risk of neonatal mortality and morbidity. The etiology behind the condition is multifactorial but believed to result from an overactivation of inflammatory pathways. This systematic review aimed to synthesize the literature behind first-trimester biomarkers associated with PPROM and compare it to literature within the same area for preterm birth. Methods: A search strategy was performed in PubMed, Embase, and CINAHL from 1993 to 2024 resulting in 14,889 articles screened by two independent authors and presented according to PRISMA guidelines. The biomarkers from the included articles were categorized into four medical headings: The immune system, metabolism and endocrinology, hematology, and reproduction. Results: Biomarkers associated with PPROM were primarily related to the immune system. C-reactive protein (CRP) and white blood cells (WBC) were often investigated for an association with PPROM but displayed divergent results of varying quality. Decreased concentrations of placental growth factor (PlGF) were associated with PPROM and spontaneous preterm birth, potentially highlighting a shared etiology, making soluble fms-like tyrosine kinase-1 (sFlt-1) interesting to investigate as well. Conclusion: Most biomarkers were examined in single studies, providing limited data to make significant conclusions about each biomarker. This review encourages further investigation of CRP, WBC, PlGF, and sFlt-1.

Blood biomarkers can provide objective insight into a player’s physiological state of recovery. Individualised approaches to biomarker monitoring may be of higher potential value in assessing player health and recovery compared to population-based reference ranges. We aimed to explore the application of individualised adaptive reference ranges (IARR) in English Premier League (EPL) soccer players using a POC biomarker for C-Reactive Protein (CRP) as a marker of inflammation. Using historical data collected from players’ CRP values during the 2019–2020 season, we evaluated the effectiveness of static and IARR in identifying abnormal values and reported sensitivity and specificity at a 5% significance level. Our analysis confirmed that monitoring with IARR is more effective in identifying true abnormalities compared to population-based static reference ranges, particularly when the intra-individual variability is considerably lower than inter-individual variability. The application of IARR for blood monitoring data could assist the practitioner in identifying periods where a player may require performance (e.g. workload management and recovery practices) or medical support from the multi-disciplinary team. However, IARR serve more as an early warning system than a diagnostic tool. Thus, significant care is needed to prevent misuse and misinterpretation when implementing this strategy in real-world settings.

Background Ischemia and associated hypoxemia-induced oxidative stress play an important role in hyperemesis gravidarum (HG) pathogenesis. Objective The aim was to investigate the role of ischemia-modified albumin (IMA) in predicting HG. Methods A prospective cohort study was conducted with 138 participants with singleton pregnancies who had experienced HG in previous pregnancies. Blood samples were taken at or before 5 weeks, provided they had no symptoms of nausea and vomiting at that time. The samples were stored under appropriate conditions to be analyzed for IMA. All participants were then followed to determine whether they would develop HG. Results HG occurred in 42 participants (HG group), while the remaining 96 participants did not develop HG (control group). Baseline characteristics showed no significant differences. IMA levels were significantly higher in the HG group (p < 0.001). IMA levels did not correlate with body mass index or maternal age. IMA with a cut-off of >74.74 ng/mL (95% sensitivity, 67% specificity) had a discriminatory power with an AUC value of 0.791 (95% CI: 0.714–0.856; p < 0.001) for predicting HG. Conclusion Our results show an association between high IMA levels in early pregnancy and an increased risk of HG. IMA can be used as a predictive tool for HG.

Background and objectives Prior studies have shown that small non-coding RNAs (sncRNAs) are associated with cancer occurrence or development. Recently, a newly discovered class of small ncRNAs known as PIWI-interacting RNAs (piRNAs) have been found to play a vital role in physiological processes and cancer initiation. This study aims to utilize piRNAs as innovative, noninvasive diagnostic biomarkers for breast cancer. Our objective is to develop computational methods that leverage piRNA attributes for breast cancer prediction and its application in diagnostics. Methods We created a set of piRNA sequence descriptors using information extracted from the piRNA sequences. To ensure accuracy, we found a path to convert non-standard piRNA names to standard ones to enable precise identification of these sequences. Using these descriptors, we applied machine-learning (ML) techniques in WEKA (Waikato Environment for Knowledge Analysis) to a dataset of piRNA to assess the predictive accuracy of the following classifiers: Logistic Regression model, Sequential Minimal Optimization (SMO), Random Forest classifier, and Logistic Model Tree (LMT). Furthermore, we performed Shapley additive explanations (SHAP) Analysis to understand which descriptors were the most relevant to the prediction accuracy. The ML models were then validated on an independent dataset to evaluate their effectiveness in predicting breast cancer. Results The top three performing classifiers in WEKA were Logistic Regression, SMO, and LMT. The Logistic Regression model achieved an accuracy of 90.7% in predicting breast cancer, while SMO and LMT attained 89.7% and 85.65%, respectively. Conclusions Our study demonstrates the effectiveness of using ML-based piRNA classifiers in diagnosing breast cancer and contributes to the growing body of evidence supporting piRNAs as biomarkers in cancer diagnosis. However, additional research is needed to validate these findings and further assess the clinical applicability of this approach.