Search Results (100)

Background/Objectives: Abdominal sepsis remains a major contributor to morbidity and mortality among surgical and critically ill patients worldwide. Timely diagnosis is frequently hindered by the overlapping clinical and biochemical features of postoperative inflammatory responses and evolving intra-abdominal infections, which may resemble systemic sepsis. Conventional biomarkers, including C-reactive protein (CRP) and procalcitonin (PCT), are widely implemented in clinical practice but demonstrate suboptimal specificity in differentiating infectious from sterile inflammatory conditions in the early postoperative phase. Presepsin (soluble CD14 subtype, sCD14-ST), a circulating fragment released during monocyte–macrophage activation in response to bacterial endotoxins, has emerged as a biomarker reflecting innate immune engagement. This review aims to critically evaluate the current evidence regarding the diagnostic accuracy, prognostic relevance, and potential clinical role of presepsin in abdominal sepsis. Methods: A comprehensive narrative review of the biomedical literature was performed using MEDLINE (via PubMed) and supplementary academic sources. Studies assessing the diagnostic performance, prognostic associations, and clinical applicability of presepsin in abdominal infections, postoperative infectious complications, and sepsis were systematically examined. Where available, comparative analyses with established biomarkers such as CRP and PCT were evaluated to contextualize its incremental value within existing diagnostic frameworks. Results: The accumulated evidence indicates that presepsin concentrations increase early during bacterial infections and correlate with validated severity indices, organ dysfunction scores, and mortality outcomes. Across multiple surgical and intensive care settings, presepsin demonstrated moderate-to-high diagnostic performance, frequently comparable to and occasionally exceeding that of traditional inflammatory biomarkers, particularly in distinguishing septic from non-septic inflammatory states. Moreover, dynamic changes in circulating levels appear to provide additional prognostic information and may support longitudinal clinical assessment. Nonetheless, substantial heterogeneity in study design, patient populations, sampling strategies, and reported cut-off values limits direct cross-study comparability and constrains definitive clinical recommendations. Conclusions: Presepsin represents a biologically plausible and clinically promising biomarker for the early identification and risk stratification of abdominal sepsis. Although current findings are encouraging, further large-scale, methodologically standardized prospective investigations are required to define optimal diagnostic thresholds and to clarify their role within multimodal biomarker strategies in contemporary sepsis management. Full article

Background and Objectives: Serum biomarker discovery in resectable pancreatic ductal adenocarcinoma (PDAC) remains a critical unmet need, as over 80% of patients present with unresectable disease. Serum proteomics offers a promising approach for identifying circulating biomarkers associated with early-stage disease; however, clinical translation has been limited by inconsistent validation and the absence of clinically relevant comparator populations. Materials and Methods: We performed a discovery-phase study using data-independent acquisition mass spectrometry-based serum proteomics in 35 patients with resectable, non-metastatic PDAC and 34 non-cancer controls without hepato-biliary-pancreatic disease. Following quality filtering (≥80% detection threshold), 407 proteins were retained for analysis. Differential abundance was assessed using Welch’s t-test with Benjamini–Hochberg correction (FDR < 0.01, |FC| ≥ 1.5). Diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis and logistic regression with repeated stratified 5-fold cross-validation (100 repetitions) and bootstrap resampling (1000 iterations). Functional enrichment analysis was performed using g:Profiler. Results: Ninety proteins were significantly altered in PDAC (50 increased, 40 decreased). Inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3) demonstrated the highest individual diagnostic performance (AUC = 0.90), followed by coagulation factor XIII A chain (F13A1; AUC = 0.89) and ferritin light chain (FTL; AUC = 0.86). Functional enrichment revealed significant overrepresentation of secretory granule lumen components (adjusted p = 0.001) and complement/coagulation pathways (adjusted p < 0.001). An enrichment-guided three-protein panel (ITIH3, F13A1, and FTL) achieved an AUC of 0.98 (95% CI: 0.95–1.00), with a cross-validated mean AUC of 0.96, sensitivity of 83% (95% CI: 66.4–93.4%), and specificity of 100% (95% CI: 89.7–100%) within the discovery cohort. Conclusions: This discovery-phase study identifies a biologically coherent serum protein signature enriched for secretory granule lumen components in resectable PDAC. The three-protein panel demonstrates strong internal validation performance; however, these estimates may be optimistic due to feature selection performed prior to cross-validation. External validation in independent cohorts—including chronic pancreatitis controls and parallel CA19-9 assessment—will be essential to determine clinical applicability. Full article

Human metapneumovirus (hMPV) is an important cause of acute respiratory tract infections. This study aimed to describe the clinical characteristics, outcomes, and molecular features of hMPV infection among hospitalized patients in Romania. We performed an analysis of prospectively collected surveillance data from patients hospitalized with influenza-like illness or severe acute respiratory infection and tested by RT-PCR for the presence of respiratory viruses between November 2023 and May 2025. Only cases of hMPV monoinfection were analyzed. Clinical, laboratory, and outcome data were analyzed, and a subset of samples with high viral load underwent genetic sequencing of the hMPV fusion (F) gene. A total of 71 patients met the criteria. Children accounted for 62.0% of cases. The clinical features were nonspecific, dominated by cough (87.3%), fever (80.3%), and nasal congestion (47.9%). Adults were significantly more likely to develop dyspnea and respiratory failure requiring oxygen supplementation (51.9% vs. 6.8%, p < 0.001). The median length of hospital stay was 5 days (interquartile range: 2, 7 days), and dyspnea at admission was the strongest factor associated with prolongation of hospitalization. The rate of intensive care unit admission was 4.2%, and overall outcomes were favorable, with no deaths recorded. Molecular analysis revealed the circulation of different hMPV subclades across consecutive seasons, with A2b1 predominating in 2023–2024 and A2b2 in 2024–2025. hMPV infection in hospitalized patients presents with nonspecific clinical features and shows distinct age-related patterns of severity and complications. Early identification of respiratory involvement, particularly dyspnea at presentation, may support risk stratification and optimized clinical management. Preliminary molecular data indicate dynamic circulation of hMPV subclades, underscoring the value of integrated clinical and molecular surveillance. These findings support the inclusion of hMPV in the differential diagnosis of severe acute respiratory infections and highlight the importance of continued monitoring in the post-pandemic period. Full article

Dengue and chikungunya are endemic arboviral diseases in many low- and middle-income countries, often co-circulating and presenting with overlapping symptoms that hinder early diagnosis. Timely differentiation is critical, especially in resource-limited settings where laboratory testing is unavailable. We developed and evaluated machine-learning (ML)- and deep-learning (DL) models to classify dengue, chikungunya, and discarded cases using a large-scale, real-world dataset of over 6.7 million entries from Brazil (2013–2020). After applying the Synthetic Minority Oversampling Technique (SMOTE) to address class imbalance, we trained six ML models and one artificial neural network (ANN) using only demographic, clinical, and comorbidity features. The Random Forest model achieved strong multi-class classification performance (Recall: 0.9288, the Area Under the Curve (AUC): 0.9865). The ANN model excelled in identifying chikungunya cases (Recall: 0.9986, AUC: 0.9283), suggesting its suitability for rapid screening. External validation confirmed the generalizability of our models, particularly for distinguishing discarded cases. Our models demonstrate high-accuracy in differentiating dengue and chikungunya using routinely collected clinical and epidemiological data. This work supports the development of Artificial Intelligence-powered decision-support tools to assist frontline healthcare workers in under-resourced settings and aligns with the One Health approach to improving surveillance and diagnosis of neglected tropical diseases. Full article

Background and Objectives: Radiomics and artificial intelligence (AI) offer emerging quantitative tools for enhancing the diagnostic evaluation of testicular cancer. Conventional imaging—ultrasound (US), magnetic resonance imaging (MRI), and computed tomography (CT)—remains central to management but has limited ability to characterize tumor subtypes, detect occult nodal disease, or differentiate necrosis, teratoma, and viable tumor in post-chemotherapy residual masses. This systematic review summarizes current advances in radiomics and AI for both primary tumors and retroperitoneal disease. Materials and Methods: A systematic search of PubMed, Scopus, and Web of Science identified studies applying radiomics or AI to testicular tumors, retroperitoneal lymph nodes and post-chemotherapy residual masses. Eligible studies included quantitative imaging analyses performed on ultrasound, MRI, and CT, with optional integration of clinical or molecular biomarkers. Eighteen studies met inclusion criteria and were evaluated with respect to methodological design, diagnostic performance, and translational readiness. Results: Across modalities, radiomics demonstrated encouraging discriminatory capacity, with accuracies of 74–82% for ultrasound, 80.7–97.9% for MRI, and 71.7–85.3% for CT. CT-based radiomics for post-chemotherapy residual masses showed moderate ability to distinguish necrosis/fibrosis, teratoma, and viable germ-cell tumor, though heterogeneous methodologies and limited external validation constrained generalizability. The strongest performance was observed in multimodal approaches: integrating radiomics with clinical variables or circulating microRNAs improved accuracy by up to 12% and 15%, respectively, mirroring gains reported in other oncologic radiomics applications. Persisting variability in segmentation practices, acquisition protocols, feature extraction, and machine-learning methods highlights ongoing barriers to reproducibility. Conclusions: Radiomics and AI-enhanced frameworks represent promising adjuncts for improving the noninvasive evaluation of testicular cancer, particularly when combined with clinical or molecular biomarkers. Future progress will depend on standardized imaging protocols, harmonized radiomics pipelines, and multicenter prospective validation. With continued methodological refinement and clinical integration, radiomics may support more precise risk stratification and reduce unnecessary interventions in testicular cancer. Full article

Background/Objectives: HER2-low breast cancer has emerged as a clinically meaningful category that challenges the historical HER2-positive versus HER2-negative classification. Although not defined as a distinct biological subtype, HER2-low tumors exhibit unique clinicopathological features and differential sensitivity to novel antibody–drug conjugates. Accurate identification remains difficult due to limitations in immunohistochemistry performance, inter-observer variability, intratumoral heterogeneity, and dynamic shifts in HER2 expression over time. This review synthesizes current evidence on the biological and clinical characteristics of HER2-low breast cancer and evaluates emerging diagnostic innovations, with emphasis on liquid biopsy approaches and evolving technologies that may enhance diagnostic accuracy and monitoring. Methods: A narrative literature review was conducted, examining tissue-based HER2 testing, liquid biopsy modalities, including circulating tumor cells, circulating nucleic acids, extracellular vesicles, and soluble HER2 extracellular domains, and applications of artificial intelligence (AI) across histopathology and multimodal diagnostic systems. Results: Liquid biopsy technologies offer minimally invasive, real-time assessment of HER2 dynamics and may overcome fundamental limitations of tissue-based assays. However, these platforms require rigorous analytical validation and face regulatory and standardization challenges before widespread clinical adoption. Concurrently, AI-enhanced histopathology and multimodal diagnostic systems improve reproducibility, refine HER2 classification, and enable more accurate prediction of treatment response. Emerging biosensor- and AI-enabled monitoring frameworks further support continuous disease evaluation. Conclusions: HER2-low breast cancer sits at the intersection of evolving pathology and technological innovation. Integrating liquid biopsy platforms with AI-driven diagnostics has the potential to advance precision stratification and guide personalized therapeutic strategies for this expanding patient subgroup. Full article

This study investigates a typical ozone pollution episode in Hong Kong from May 29 to 31, 2023. Based on the observations of a Differential Absorption Lidar (DIAL) system, both ozone and aerosols accumulated below 1.5 km during the pollution episode. Ozone exhibited distinct formation and accumulation characteristics, with concentrations exceeding 200 μg m⁻³. Aerosols presented evident features of regional transport and local coupling, with extinction coefficients surpassing 1.1 km⁻¹. During late spring to early summer, the northward extension of the Western Pacific Subtropical High (WPSH) established favorable conditions for ozone production. This background was amplified by Typhoon Mawar, whose peripheral circulation channeled pollutants from the Pearl River Delta into Hong Kong through horizontal and vertical pathways, significantly worsening near-surface air quality. The episode was eventually mitigated, as enhanced vertical mixing facilitated the dispersion and removal of accumulated pollutants. These results highlight the critical role of meteorological–chemical interactions in shaping this ozone pollution episode. Full article

Uterine leiomyosarcoma (uLMS) is a rare, highly aggressive malignancy of uterine smooth muscle, associated with early metastasis, frequent recurrence, and poor prognosis. Accurate preoperative diagnosis remains difficult given that clinical and radiologic features often overlap with benign leiomyomas, and no reliable biomarkers are currently available. This review summarizes recent evidence on the role of microRNAs (miRNAs) in the biology and clinical management of uLMS. Literature from molecular and translational studies was examined to identify dysregulated miRNAs, their target pathways, and potential diagnostic and therapeutic applications. uLMS displays a characteristic miRNA profile, including downregulation of tumor-suppressive miRNAs such as the miR-29 and miR-200 families and upregulation of oncogenic miRNAs including miR-21 and the miR-183~96~182 cluster, leading to activation of PI3K/AKT/mTOR signaling and epithelial–mesenchymal transition (EMT). Circulating and tissue miRNAs show promise as minimally invasive biomarkers for differentiating uLMS from leiomyomas, predicting prognosis, and guiding therapy. Emerging therapeutic approaches aim to restore the tumor-suppressive miRNAs or inhibit oncogenic ones using mimics or antagomiRs. Overall miRNAs represent critical regulators of uLMS pathogenesis and hold significant potential for precision diagnosis, prognostication, and targeted therapy, though larger validation studies and improved delivery systems are required before clinical translation. Full article

While syncope is characterized by a sudden and temporary loss of consciousness caused by decreased blood flow to the brain and is easily recognized by its clinical features, presyncope involves a sensation of impending fainting, often accompanied by autonomic symptoms. Presyncope is less characterized and studied than syncope, presenting a particular diagnostic challenge in neurology clinics. Neurologists commonly encounter patients with presyncope in outpatient settings or during consultation at the emergency department after cardiopulmonary causes have been excluded. Differential diagnosis of recurrent presyncope is broad but from a neurologic standpoint falls into multiple neurologic categories, including complex partial seizures, basilar or vestibular migraine, dysautonomia, cataplexy, alteration in cerebrospinal fluid flow, Meniere’s disease, posterior circulation transient ischemic attacks and others. Here, we review presyncope as a feature of dysautonomia and common autonomic disorders, such as neurocardiogenic syncope, postural orthostatic tachycardia syndrome, orthostatic hypotension and orthostatic intolerance. We discuss clinical and neurologic exam findings, diagnostic tests, differential diagnosis and treatment of presyncope as a manifestation of common autonomic disorders. Full article

Background/Objectives: Ovarian adnexal masses present diagnostic challenges due to their heterogeneous etiologies. Accurately differentiating these conditions is critical for timely and effective clinical intervention. This study evaluated circulating molecules and serum-induced apoptosis as complementary tools to conventional diagnostic methods (CA125, HE4, and the ROMA index) for distinguishing benign masses from malignant masses. Methods: A cohort of 136 participants (9 healthy controls, 87 women with benign ovarian adnexal masses and 40 with malignant ovarian adnexal masses) was analyzed. The induction of apoptosis in Jurkat cells by patient serum was assessed using flow cytometry. Serum concentrations of sFas/CD95, HE4, CA125, and additional molecules were measured by ELISA and LEGENDplex™. Clinical, ultrasonographic, and histopathological data were correlated with tumor malignancy. To improve diagnostic performance beyond individual biomarkers, we developed two multiparametric classifiers that integrate the dominant parameters identified through group divergence analysis and ROC evaluation across multiple clinical comparisons. Results: Malignant tumors were associated with older age (51.45 ± 8.35 years, p = 0.0002), postmenopausal status (61.1%, p = 0.0013), and larger tumor size (>10 cm). Ultrasonographic features of complexity were observed exclusively in malignant masses. Functional assays revealed reduced apoptosis in Jurkat cells exposed to malignant sera, suggesting tumor-mediated immune evasion. Although higher sFas levels were observed in tumors, no significant differences were identified between the groups. Among the circulating biomarkers, CA125, HE4, MRP8/14, OPN, and SAA levels were significantly higher in malignant tumors than in benign tumors and controls. Conclusions: The evaluation of CA125, HE4, MRP8/14, and apoptosis (Classifier 1) and, more prominently, the measurement of additional molecules: OPN, SAA, IL-6, IL-8, and IGFBP-4 (Classifier 2), systematically outperformed the ROMA. Both achieved superior specificity and balanced accuracy (Youden’s J index) across all clinical comparisons by capturing the biological diversity of malignancies. Full article

Pulmonary neuroendocrine tumors (PULMONARY NETs) are heterogeneous tumors ranging from well-differentiated to highly aggressive neoplasms. The aim of this study is to prospectively test pre-operative circulating free DNA (cfDNA) in PULMONARY NET patients undergoing surgery and evaluate its relationship to clinicopathological features. From February to December 2024, 136 patients with suspected primary lung cancer underwent pre-operative blood sampling, of whom 21 were diagnosed with PULMONARY NETs. Total cell-free nucleic acid extraction was performed using the Genexus Purification System (Thermofisher). cfDNA was quantified using a fluorometric assay with the Qubit dsDNA HS Assay kit (Thermofisher) and a capillary electrophoresis-based assay (cell-free DNA ScreenTape kit) on the Tape Station 4200 systems (Agilent). A cfDNA quality assessment was also obtained (cfDNA sizing and % cfDNA). Most patients had Stage I (18/21.85.7%) typical carcinoids (16/21.76.2%). Nodal involvement was detected in one patient (0.5%). Six months after surgery, all patients were alive without recurrence. Larger tumors presented higher levels of cfDNA. The mean tumor size in patients with cfDNA > 40 ng was 266 mm (±16.7 mm), compared to 13.2 mm (±7.3 mm) for cfDNA < 40 ng (p-value = 0.018). Higher levels of cfDNA were observed in patients with pStages greater than IA (p-value = 0.007). Although limited by a small sample group and biases of a surgical series, we observed that larger/advanced PULMONARY NETs presented higher cfDNA levels pre-operatively. Full article

Objectives: Angelica sinensis is a type of traditional Chinese medicine (TCM) used primarily as a blood tonic. The chemical components that exert their efficacy are mainly bioactive metabolites, such as ferulic acid, flavonoids, and volatile oils. The resources of wild Angelica sinensis (WA) are very scarce, and almost all the market circulation of TCM formulations relies on cultivated Angelica sinensis (CA). Some studies have shown that WA and CA differ in morphological features and chemical composition, but the reasons and mechanisms behind the differences have not been studied deeply. Methods: Herein, metabolomics analysis (MA) and transcriptomics analysis (TA) were used to reveal the differences in bioactive metabolites and genes between WA and CA. Expression of key genes was verified by real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Results: Results showed that 12,580 differential metabolites (DMs) and 1837 differentially expressed genes (DEGs) were identified between WA and CA. Fourteen DMs (e.g., cinnamic acid, caffeic acid, ferulic acid, p-coumaroylquinic acid, and phlorizin) and 27 DEGs (e.g., cinnamic acid 4-hydroxylase (C4H), 4-coumarate-CoA ligase (4CL), shikimate O-hydroxycinnamoyltransferase (HCT), caffeic acid-O-methyltransferase (COMT), cinnamyl-alcohol dehydrogenase (CAD), flavonol synthase (FLS)) were screened in phenylpropanoid biosynthesis and flavonoid biosynthesis. A combined analysis of MA and TA was performed, and a network map of DMs regulated by DEGs was plotted. The results of real-time RT-qPCR showed that the transcriptome data were reliable. Conclusions: These findings provide a reference for further optimization of the development of WA cultivation and breeding of CA varieties. Full article

Background/Objectives: Despite the significant advancements made in the diagnosis of lung cancer, the traditional diagnostic methods remain limited because they are often invasive, expensive, and not suitable for regular screening, creating a need for more accessible and non-invasive alternatives. In this context, the analysis of miRNAs in EVs and free circulating microRNA may be used as liquid biopsies in lung cancer to identify individuals at risk. This study aimed to compare miRNA profiles in the serum and EVs derived from lung cancer patients by focusing on Let-7a-5p and miR-21-3p. Materials and Methods: Serum and EVs were isolated from lung cancer patients and healthy controls. EVs were characterized using nanoparticle tracking analysis, electron microscopy, and Western blotting for surface markers (CD63, CD81, TSG101). Total miRNA levels were quantified in the serum and EVs, and specific miRNAs (hsa-let-7a-5p and hsa-miR-21-3p) were analyzed using RT-qPCR. Statistical analysis evaluated miRNA expression across clinicopathological features, including age, gender, smoking status, tumor stage, cancer type, and EGFR mutation status. Results: Total miRNA levels were significantly enriched in EVs compared to the serum. Let-7a-5p was downregulated in EVs from patients with advanced-stage lung cancer (Stage III–IV) compared to those with early-stage cancer and controls (p < 0.05), while no differences were observed in the serum. Conversely, miR-21-3p was significantly upregulated in EVs and serum from advanced-stage patients (p < 0.01) and in adenocarcinoma compared to squamous cell carcinoma (p < 0.05). No significant differences were observed for age, gender, or smoking status. Conclusions: Our findings highlight the differential expression of miRNAs in EVs and the serum, emphasizing the diagnostic potential of EV-associated Let-7a-5p and miR-21-3p in lung cancer. These results suggest that EVs are a more robust source for miRNA biomarkers compared to the serum. Full article

Increasing evidence underlines the role of B-cells in the development of hepatic fibrogenesis following viral infections and metabolic dysfunction, through different mechanisms depending on the etiology. Circulating biomarkers of B-cell activation—such as B-cell activating factor (BAFF), immunoglobulin G (IgG) subclasses, and free light chains (FLCs)—may be associated with different results between viral and metabolic hepatic fibrosis, supporting their use as diagnostic tools. We conducted a case-control study including 100 patients with liver fibrosis, 50/100 of metabolic etiology and 50/100 of viral etiology. A reference group of 30 healthy donors was included as control. Serum levels of BAFF were measured using ELISA, while IgG subclasses (IgG1, IgG2, IgG3, IgG4), κ-FLC, λ-FLC, and the κ/λ ratio were quantified by turbidimetric methods. In univariate analysis, κ-FLC, λ-FLC, and BAFF levels were significantly elevated in both patient groups, with the highest concentrations consistently observed in metabolic fibrosis. IgG2 was selectively increased in metabolic fibrosis, whereas IgG3 was specifically elevated in viral fibrosis. Multivariate analysis confirmed these findings, showing a clear clustering of the three groups and identifying increased BAFF and κ-FLC as key features of metabolic fibrosis, while elevated IgG3 emerged as the most distinctive marker of viral etiology. These results reveal distinct B-cell-related immunological signatures in metabolic and viral hepatic fibrosis supporting the role of BAFF, FLCs, and IgG subclasses as biomarkers of etiological differentiation, and provide novel insights into the immune mechanisms driving fibrosis progression, potentially contributing to the identification of new therapeutic targets. Full article

Coronary artery disease (CAD) remains a major cause of cardiovascular morbidity and mortality, with growing evidence linking immune dysregulation to its pathogenesis. Aortic stenosis often coexists with CAD (ASCAD), representing an advanced disease form. This study investigates immune pathways in isolated CAD (iCAD) and ASCAD. For this purpose, peripheral blood from 72 individuals (healthy donors, iCAD, and ASCAD patients) was analysed via flow cytometry to assess immune populations. Circulating cytokine levels were measured, and machine learning models identified predictive immune biomarkers. Our data showed that both iCAD and ASCAD patients exhibited immune dysregulation, with reduced dendritic cells, basophils, NK cells, B cells, and T cells, alongside lower frequencies of DCs, lymphocytes, CD8+CD28+ T cells, and CD57+ T cells. Elevated IL-15 and fractalkine, but reduced IL-8 and MCP-1, suggest impaired monocyte and neutrophil mobilisation due to immune cell sequestration in vascular lesions. Distinct immune features emerged between iCAD and ASCAD. iCAD patients showed heightened immune activation, with increased inflammatory CD14+CD16+ monocytes, higher Treg frequencies, and greater CD4+ T cell differentiation into TEM and TEMRA phenotypes. In contrast, ASCAD patients exhibited pronounced immunosenescence, with higher neutrophil counts, lymphopenia, and increased NK and T cell cytotoxicity. Our predictive model distinguished iCAD from ASCAD with high accuracy, identifying CD4+ T cell memory subsets and CD57 expression as key discriminators. This study reveals iCAD as being driven by immune activation and ASCAD by immunosenescence and cytotoxicity. These insights advance CAD immunopathology understanding and support immune-based classification, particularly for ASCAD, where treatment remains limited to surgical intervention. Full article