Preeclampsia (PE) occurs in approximately 2–8% of all pregnancies worldwide and represents one of the primary causes of maternal and fetal morbidity and mortality. Angiogenic growth factors such as placental growth factor (PlGF) and vascular endothelial growth factor (VEGF), along with their tyrosine kinase receptor (Flt-1), play a central role in placental and fetal development. Impaired placentation results in the excessive release of the antiangiogenic soluble fms-like tyrosine kinase-1 (sFlt-1) which is pivotal in the pathogenesis of PE. By binding to and neutralizing angiogenic factors, sFlt-1 disrupts normal angiogenic signaling, creating an imbalance that is often detectable before clinical symptoms of PE appear. Recent studies have highlighted the prognostic potential of the sFlt-1/PlGf ratio as an early indicator of PE risk, since this ratio has demonstrated value in both confirming and excluding PE in the high-risk population. Its incorporation into routine medical care has the potential to reduce unnecessary hospital admissions, intensive management, and premature deliveries, ultimately lowering healthcare costs. The objective of this review is to highlight the clinical utility of the sFlt-1/PlGf ratio in the prediction, diagnosis, and management of preeclampsia and to emphasize the cost-effectiveness of implementing sFlt-1/PlGF ratio measurement in the care of women at risk of developing PE.

Kawasaki disease (KD) is a systematic inflammatory condition that results in vasculitis and possible progression to the development of coronary artery lesions if left untreated. Disease pathogenesis is not fully understood, and diagnosis is based on clinical symptoms, with limited reliability considering that KD progression is time sensitive. This is further complicated by the shared clinical characteristics with other febrile diseases. Early diagnosis and prompt treatment start are associated with good prognosis in most patients. However, up to 20% of patients are resistant to available therapeutic agents and would benefit from alternative regimens. Therefore, identification of biomarkers that can provide insights on disease pathogenesis are necessary to enable early diagnosis and initiation of treatment, as well as to predict treatment responses. To this end, immunophenotyping, most commonly by flow cytometry, has been crucial in identifying central factors in KD pathogenesis. The available literature on such factors is vast and may include contradictory findings. Therefore, we aimed to summarize the available literature of the last decade on the immunophenotype of KD, focusing on biomarkers associated with disease pathogenesis and those associated with treatment response. Our review highlights the role of cells of both the innate and adaptive immune system in disease pathogenesis, as well as the role of various secreted and cell surface proteins, including inflammatory cytokines, chemokines, complement receptors, and chemoattractants both in KD pathogenesis and in treatment response.

Mechanobiology plays a pivotal role in skeletal development and bone remodeling. Mechanical signals such as matrix stiffness, fluid shear stress, and hydrostatic pressure activate the Runt-related transcription factor 2 (RUNX2) bone-specific transcription factor through pathways including the mitogen-activated protein kinase (MAPK) signaling cascade and yes-associated protein (YAP)/transcriptional co-activator with PDZ-binding motif (TAZ) effectors. RUNX2 itself affects chromatin remodeling and nuclear architecture via Lamin A/C and Nesprin 1, thereby directing osteogenic differentiation. Thus, RUNX2 acts both as a mechanosensor and mechanoregulator, whereas RUNX2’s mechanosensitivity has been leveraged as a target to achieve bone regeneration. Notably, post-translational modifications and epigenetic alterations can orchestrate this regulation, integrating metabolic and circadian signals. However, due to RUNX2’s nuclear localization, its targeting remains a challenging issue. To this end, indirect targeting, through mammalian/mechanistic target of rapamycin complex 1 (mTORC1) or microRNAs (miRNAs), offers new strategies to employ biomechanics in an attempt to intervene with bone diseases driven by mechanical cues or degeneration, and ultimately repair and regenerate the damaged tissues. Herein we critically elaborate upon molecular aspects of RUNX2 regulation towards exploitation at the clinical level.

Background: HER2-positive breast cancer patients receiving chemotherapy and targeted therapy (including anthracyclines and trastuzumab) face an elevated risk of cardiotoxicity, which can lead to long-term cardiovascular complications. Identifying predictive biomarkers is essential for early intervention. Circulating microRNAs (miRNAs), known regulators of gene expression and cardiovascular function, have emerged as potential indicators of cardiotoxicity. This study aims to evaluate the differential expression of circulating miRNAs in HER2-positive breast cancer patients undergoing chemotherapy and to assess their prognostic ability for therapy-induced cardiotoxicity using machine learning models. Methods: Forty-seven patients were assessed for cardiac toxicity at baseline and every 3 months, up to 15 months. Blood samples were collected at baseline. MiRNA expression profiling for 84 microRNAs was performed using the miRCURY LNA miRNA PCR Panel. Differential expression was calculated via the 2^−∆∆Ct method. The five most upregulated and five most downregulated miRNAs were further assessed using univariate logistic regression and receiver operating characteristic (ROC) analysis. Five machine learning models (Decision Tree, Random Forest (RF), Support Vector Machine (SVM), Gradient Boosting Machine (GBM), k-Nearest Neighbors (KNN)) were developed to classify cardiotoxicity based on miRNA expression. Results: Forty-five miRNAs showed significant differential expression between cardiac toxic and non-toxic groups. ROC analysis identified hsa-miR-155-5p (AUC 0.76, p = 0.006) and hsa-miR-124-3p (AUC 0.75, p = 0.007) as the strongest predictors. kNN, SVM, and RF models demonstrated high prognostic accuracy. The decision tree model identified hsa-miR-17-5p and hsa-miR-185-5p as key classifiers. SVM and RF highlighted additional miRNAs associated with cardiotoxicity (SVM: hsa-miR-143-3p, hsa-miR-133b, hsa-miR-145-5p, hsa-miR-185-5p, hsa-miR-199a-5p, RF: hsa-miR-185-5p, hsa-miR-145-5p, hsa-miR-17-5p, hsa-miR-144-3p, and hsa-miR-133a-3p). Performance metrics revealed that SVM, kNN, and RF models outperformed the decision tree in overall prognostic accuracy. Pathway enrichment analysis of top-ranked miRNAs demonstrated significant involvement in apoptosis, p53, MAPK, and focal adhesion pathways, all known to be implicated in chemotherapy-induced cardiac stress and remodeling. Conclusions: Circulating miRNAs show promise as biomarkers for predicting cardiotoxicity in breast cancer patients. Machine learning approaches may enhance miRNA-based risk stratification, enabling personalized monitoring and early cardioprotective interventions.

Kawasaki disease (KD) is a systematic inflammatory condition that results in vasculitis and possible progression to the development of coronary artery lesions if left untreated. Disease pathogenesis is not fully understood, and diagnosis is based on clinical symp-toms, with limited reliability considering that KD progression is time sensitive. This is further complicated by the shared clinical characteristics with other febrile diseases. Early diagnosis and prompt treatment start are associated with good prognosis in most patients. However, up to 20% of patients are resistant to available therapeutic agents and would benefit from alternative regimens. Therefore, identification of biomarkers that can pro-vide insights on disease pathogenesis are necessary to enable early diagnosis and initi-ation of treatment, as well as to predict treatment responses. To this end, immunophe-notyping, most commonly by flow cytometry, has been crucial in identifying central factors in KD pathogenesis. The available literature on such factors is vast and may in-clude contradictory findings. Therefore, we aimed to summarize the available literature of the last decade on the immunophenotype of KD, focusing on biomarkers associated with disease pathogenesis and those associated with treatment response. Our review high-lights the role of cells of both the innate and adaptive immune system in disease path-ogenesis, as well as the role of various secreted and cell surface proteins, including in-flammatory cytokines, chemokines, complement receptors, and chemoattractants both in KD pathogenesis and in treatment response.

Central nervous system (CNS) tumors consist of a diverse set of malignancies that remain clinically challenging due to their biological complexity, high morbidity, and limited responsiveness to current therapies. A growing body of genomic evidence has revealed that dysregulation of the mitogen-activated protein kinase (MAPK) signaling pathway is a recurrent and unifying characteristic across many pediatric and adult CNS tumor entities. Alterations affecting upstream receptor tyrosine kinases (RTKs), RAS GTPases, RAF kinases, and other associated regulators contribute to MAPK signaling pathway hyperactivation, shaping tumor behavior, therapy response and resistance. These aberrations ranging from hotspot mutations such as BRAF V600E and oncogenic fusions like BRAF–KIAA1549 are particularly enriched in gliomas and glioneuronal tumors, highlighting MAPK signaling as a key oncogenic driver. The expanding availability of molecularly targeted compounds, including selective inhibitors of RAF, MEK and ERK, has begun to transform treatment approaches for specific molecular subtypes. However, the clinical benefit of MAPK-directed therapies is frequently limited by restricted blood–brain barrier (BBB) penetration, intratumoral heterogeneity, parallel pathway reactivation, and an immunosuppressive tumor microenvironment (TME). In this review, we synthesize current knowledge on MAPK pathway alterations in CNS tumors and evaluate the therapeutic landscape of MAPK inhibition, with emphasis on approved agents, emerging compounds, combination strategies, and novel drug-delivery technologies. We also discuss mechanisms that undermine treatment efficacy and highlight future directions aimed at integrating MAPK-targeted therapy into precision-based management of brain tumors.