Diseases (Basel, Switzerland)最新文献

Background/objectives: Colorectal cancer (CRC) is a leading cause of cancer morbidity and mortality worldwide. Despite therapeutic advances, prevention through dietary bioactives remains a promising strategy. The Annurca apple (Malus pumila Miller cv. Annurca), a Mediterranean food rich in chlorogenic acid, exhibits antioxidant and anti-inflammatory effects. This study evaluated, via molecular docking, the multi-target interaction profile of chlorogenic acid against key CRC-related proteins.

Methods: The optimized 3D structure of chlorogenic acid was docked to ten protein targets implicated in CRC pathogenesis, using the GOLD v.2022.3.0 software. Validation of the docking protocol was achieved by re-docking native ligands (RMSD ≤ 2.0 Å). Binding affinities were assessed by ChemPLP scoring, and interaction networks were visualized in Maestro Schrödinger.

Results: Chlorogenic acid displayed consistent binding across all evaluated targets (ChemPLP 57.12-69.66), showing the highest affinity for nAChR (69.66), CXCR2 (65.13), ERβ (63.18) and TGFBR2 (62.94). The ligand formed multiple hydrogen bonds and π-π stacking interactions involving Asp1040 (VEGFR-1), Cys919 (VEGFR-2), Lys320 (CXCR2), and Tyr195 residues (nAChR), contributing to strong complex stabilization. Interaction patterns in CYP19A1, ERβ, and ERRγ suggested potential modulation of hormonal and metabolic signaling. The compound also demonstrated stable binding to mTOR (60.01), indicating a possible inhibitory role in proliferative pathways. Collectively, these findings reveal a broad, polypharmacological binding profile involving angiogenic, inflammatory, and hormonal regulators.

Conclusions: Chlorogenic acid acts as a promising multi-target ligand in CRC prevention, with our in silico evidence supporting its ability to modulate diverse oncogenic pathways. Further experimental studies are warranted to confirm its efficacy and translational potential.

Background/Objectives: Accurate and reproducible grading of lumbar spinal stenosis (LSS) is clinically critical for guiding treatment decisions and patient management, yet manual assessment remains challenging due to imaging variability and inter-observer subjectivity. To address these limitations, this study aimed to evaluate the generalizability of deep learning-based feature extraction methods-VGG19, ConvNeXt-Tiny, and DINOv2-combined with classical machine learning classifiers for automated multi-grade LSS assessment. Automated grading enables objective, reproducible, and scalable assessment of lumbar spinal stenosis severity, addressing key limitations of manual interpretation. Methods: Axial MRI images were processed using pretrained VGG19, ConvNeXt-Tiny, and DINOv2 models to extract deep features. Logistic Regression, Support Vector Machine (SVM), and LightGBM were trained on internal datasets and externally validated using MRI data from the University of Phayao Hospital. Performance was assessed using accuracy, precision, recall, F1-score, confusion matrices, and multi-class ROC curves. Results: VGG19-based features yielded the strongest external performance, with Logistic Regression achieving the highest accuracy (0.9556) and F1-score (0.9558). External validation further demonstrated excellent discrimination, with AUC values ranging from 0.994 to 1.000 across all severity grades. SVM (0.9333 accuracy) and LightGBM (0.9222 accuracy) also performed well. ConvNeXt-Tiny showed stable cross-model performance, while DINOv2 features exhibited reduced generalizability, especially with LightGBM (accuracy 0.6222). Most classification errors occurred between adjacent grades. Conclusions: Deep convolutional features-particularly VGG19-combined with classical machine learning classifiers provide robust and generalizable LSS grading across external MRI data. Despite advances in modern architectures, CNN-based feature extraction remains highly effective for spinal imaging and represents a practical pathway for clinical decision support.

Background/objectives: Cardiovascular diseases (CVDs) remain the leading cause of morbidity and mortality worldwide and increasingly are recognized as a continuum of interconnected conditions rather than isolated entities.

Methods: A structured narrative literature search was performed in PubMed, Scopus, and Google Scholar for publications from 2015 to 2025 using combinations of different keywords: "cardiovascular disease spectrum", "multi-omics", "precision cardiology", "machine learning", and "artificial intelligence in cardiology".

Results: Evidence was synthesized across seven major clusters of cardiovascular conditions, and across these domains, common biological pathways were mapped onto heterogeneous clinical phenotypes, and we summarize how multi-omics integration, AI-enabled imaging and digital tools contribute to improved risk prediction and more informed clinical decision-making within this spectrum.

Conclusions: Interpreting cardiovascular conditions as components of a shared disease spectrum clarifies cross-disease interactions and supports a shift from organ- and syndrome-based classifications toward mechanism- and data-driven precision cardiology. The convergence of multi-omics, and AI offers substantial opportunities for earlier detection, individualized prevention, and tailored therapy, but requires careful attention to data quality, equity, interpretability, and practical implementation in routine care.

Background: High residual platelet reactivity (HRPR) and persistent dyslipidemia remain important unmet needs in cardiovascular risk management, particularly in patients undergoing coronary revascularization. Despite intensive lipid-lowering and antiplatelet therapy, a substantial proportion of patients fail to reach recommended low-density lipoprotein cholesterol (LDL-C) targets or exhibit inadequate platelet inhibition. Inclisiran, a PCSK9-targeting small interfering RNA, represents an emerging approach for long-term LDL-C reduction.

Methods: A narrative review of the literature published between 2009 and 2025 was performed using PubMed, Scopus, Web of Science, and MEDLINE. Studies evaluating the addition of inclisiran to standard lipid-lowering therapy in patients with dyslipidemia and HRPR, assessed using the VerifyNow assay, were included. Illustrative clinical cases from Kazakhstan were analyzed to demonstrate real-world changes in LDL-C levels and platelet reactivity following insufficient response to conventional treatment. The review had a descriptive design.

Results: Available evidence indicates that a significant proportion of high- and very-high-risk patients do not achieve LDL-C targets or are unable to tolerate high-intensity statin therapy. Inclisiran consistently induces sustained reductions in LDL-C and circulating PCSK9 levels. Emerging data suggest a potential indirect modulation of platelet reactivity associated with intensive lipid lowering. In patients at extreme cardiovascular risk-including those after coronary artery bypass grafting (CABG) and with long-standing multivessel coronary artery disease-inclisiran therapy was associated with marked LDL-C reduction and a trend toward normalization of platelet reactivity.

Conclusions: Assessment of platelet function using the VerifyNow assay may improve identification of residual thrombotic risk in patients with advanced atherosclerotic disease. Inclisiran appears to be a promising adjunctive therapy for dyslipidemic patients with persistently elevated cardiovascular risk and HRPR despite standard treatment. Further prospective studies are warranted to clarify the relationship between intensive LDL-C lowering, platelet reactivity, and clinical outcomes, and to optimize integrated lipid-lowering and antiplatelet strategies.

Background/Objectives: The objective was to analyze the effects of Dipeptidyl Peptidase-4 (DPP-4) inhibitors on glycemic control, insulin dose, and preservation of β-pancreatic function (C-peptide) in patients with type 1 diabetes mellitus (T1DM). Methods: A systematic review was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, with a search in the PubMed database. Five randomized clinical trials evaluating the use of different DPP-4 inhibitors in patients with T1DM were selected, measuring parameters including glycated hemoglobin (HbA1c), C-peptide, time in glycemic target/range (TIR), and daily insulin dose. Results: HbA1c showed significant reduction in some studies and no significant alterations in others. TIR increased in one study (~77.87% → ~84.40%). C-peptide showed variable effects across studies. The insulin dose did not show a substantial reduction. Conclusions: DPP-4 inhibitors demonstrated modest benefits for glycemic control and preservation of β-cell function in T1DM, but these effects were inconsistent due to methodological heterogeneity. Standardized studies are needed to define beneficial subgroups and long-term efficacy.

Background: Respiratory Syncytial Virus is a predominant source of morbidity and mortality, particularly among babies, the elderly, and immunocompromised patients. Recent developments in RSV vaccines, approved by the FDA for high-risk groups, have highlighted the necessity for post-marketing surveillance to evaluate their real-world safety and efficacy. Method: This study utilized data from the Vaccine Adverse Event Reporting System (VAERS) covering RSV vaccine administration between 2023 and May 2025. The VAERS database reported data on vaccine types, including Arexvy^®, Abrysvo^®, and mRESVIA^® was analyzed for adverse events and vaccination errors. The demographic information, vaccination trends, and hospitalizations post-vaccination among the vaccinated individuals were accessed. Results: The analysis revealed that the most common adverse events were mild, such as injection site pain, erythema, fatigue, and extremity pain. The data also showed a gradual increase in hospitalization rates from 4.8% in 2023 to 7.5% in 2025. Vaccination errors, including inappropriate administration during pregnancy and excess doses, were also observed. A notable trend was the growing proportion of patients who experienced no adverse events, with the highest rate of symptom-free reports seen in 2025 (25.9%). Conclusions: RSV vaccines demonstrate a generally acceptable safety profile based on post-marketing surveillance data. However, the observed increase in hospitalization rates, vaccination errors, and pregnancy-related outcomes warrants continued active surveillance and cautious interpretation.

Objectives: This study investigated sleeping problems in the Swedish population based on the Swedish National Board of Health and Welfare's national patient register on numbers of patients in specialized outpatient care diagnosed with codes for sleeping problems.

Methods: Numbers of patients per year and per 100,000 inhabitants in various age groups: 0-4, 5-19, 20-39, 40-59, and 60+ years diagnosed each year between 2001 and 2024 with the ICD codes G47 (sleep disorders) or F51 (non-organic sleep disorders) as main diagnosis were assessed.

Results: The highest increase for sleep disorders was seen among children, adolescents, and young adults. All results are given per 100,000 persons. In the age group 0-4 years, the numbers of sleep disorders (G47) increased from 41.5 in 2001 to 215.8 in 2024. The corresponding results in the age group 5-19 years were 13.8 and 235.6, respectively. In the age group 20-39 years, 40.4 were diagnosed in 2001 and 220.9 in 2024. For subjects aged 40-59 years, 169.5 were diagnosed in 2001 and 362.8 in 2024, and for persons aged 60+ years, 116.4 were diagnosed in 2001 and 322.9 in 2024. No major changes in the numbers of persons with F51, non-organic sleep disorders, were observed.

Conclusions: Sleeping problems can be caused by several factors; however, the rapid increase in recent years has temporally coincided with an increase in the public's exposure to microwave radiofrequency (RF) radiation and increasing use of screens. RF radiation and use of screens may negatively impact sleep.

Background: Herpes zoster (HZ) represents a substantial public health concern among aging populations, yet regional variability in clinical patterns and risk determinants remains insufficiently documented. In southeastern Romania, epidemiological data are limited, and the combined influence of demographic, behavioral, and metabolic factors on disease severity has not been systematically evaluated.

Methods: We performed a retrospective observational study including 100 consecutive patients diagnosed with HZ between 2019 and 2023 in a dermatology department in southeastern Romania. Demographic characteristics, lifestyle behaviors, anthropometric status, clinical manifestations, and outcomes were extracted from medical records. Associations between categorical variables were assessed using Chi-square tests and Cramer's V, while interaction patterns were explored through log-linear modeling. Heatmaps were generated in Python (version 3.10) using the Matplotlib library (version 3.7.1) to visualize distribution patterns and subgroup relationships.

Results: The cohort showed a marked age dependence, with 77% of cases occurring in individuals ≥ 60 years, consistent with immunosenescence-driven reactivation. Women represented 59% of cases, and 84.7% of female patients were postmenopausal. Urban residents predominated (91%). Vesicular eruption (84%) and acute pain (79%) were the most frequent symptoms. Localized HZ was observed in 81% of cases, while ophthalmic involvement (11%) and disseminated forms (8%) were less common. Lifestyle factors significantly influenced clinical severity: smokers, alcohol consumers, and sedentary individuals exhibited higher proportions of postherpetic neuralgia (PHN) and ocular complications (p < 0.001). Overweight and obese patients demonstrated a higher burden of PHN, suggesting a role for metabolic inflammation, although BMI was not associated with incidence. No significant association between age category and complication type was detected, likely due to small subgroup sizes despite a clear descriptive trend toward increased severity with advanced age.

Conclusions: These findings support a multifactorial model of HZ severity in southeastern Romania, shaped by age, lifestyle behaviors, hormonal status, and metabolic risk. While incidence patterns align with international data, the strong impact of modifiable factors on complication rates highlights the need for targeted prevention and individualized risk assessment. Results offer a regional perspective that may inform future multicenter investigations.

Background: Chronically non-healing thoracic wounds after cardiac and non-cardiac thoracotomy, including cases when coronary artery bypass grafting (CABG) is performed, represent a great clinical challenge. It is often that a conservative treatment of the wounds does not provide effective regeneration of the damaged tissues. It is especially critical in patients with infected wounds, in patients owning a systemic infection, and in elderly people. Methods: The article presents a case report of successful treatment of a 63-year-old man with refractory chronic osteomyelitis of the sternum and mediastinitis four years after CABG, complicated by COVID-19 at the time of reconstructive surgery. Due to the low effectiveness of conservative treatment methods, a two-stage approach was applied: radical surgical wound debridement followed by infiltration of the wound with allogenic mesenchymal stromal cells (MSCs) of Wharton's jelly (WJ-MSCs). Results: This double-stage therapy successfully modulated the inflammatory environment and stimulated granulation, facilitating final thoracoplasty and osteosynthesis. The patient achieved complete healing of the sternum, demonstrating benefits of WJ-MSCs in treating conservative treatment-resistant infections in the surgical wound. Conclusions: The advantages of using perinatal mesenchymal stem cells, with WJ-MSCs as a type of this class of MSCs, were demonstrated in treating chronically infected sternal surgical wounds. We also compared their regenerative properties to other stem cell types like bone marrow MSCs.

Background: Early identification of patients at risk for severe acute pancreatitis (SAP) remains a major clinical challenge. Circulating biomarkers reflecting systemic inflammation (IL-6) and endothelial dysfunction (Ang-2) have emerged as promising tools for improving early prediction of persistent organ failure and other adverse outcomes.

Objective: To systematically synthesize and compare the diagnostic and prognostic performance of IL-6 and Ang-2 as early biomarkers of severity in adult patients with acute pancreatitis.

Methods: This systematic review was conducted in accordance with PRISMA 2020 guidelines and prospectively registered in PROSPERO (CRD420251177279). PubMed, Scopus, and Web of Science were searched for studies published between 2000 and August 2025. Studies included adult patients (≥18 years) in whom IL-6 and/or Ang-2 levels were measured within 72 h of symptom onset or hospital admission, and where indices of diagnostic accuracy (AUC, sensitivity, specificity, or threshold values) were reported.

Results: Fifteen cohort studies met the inclusion criteria. IL-6 demonstrated a consistent association with SAP and persistent organ failure, with AUC values ranging from 0.69 to 0.99; the highest accuracy was observed within the first 24 h. Specificity varied substantially across studies. Ang-2 showed uniformly high prognostic accuracy (AUC 0.79-0.98), reliably predicting persistent organ failure, multiorgan dysfunction, infected necrosis, and mortality.

Conclusions: IL-6 exhibits high but heterogeneous diagnostic performance (AUC 0.69-0.99), whereas Ang-2 demonstrates consistently high accuracy (AUC 0.79-0.98) across study designs. Combined evaluation of inflammatory and endothelial pathways appears to offer the most robust strategy for early prediction of persistent organ failure in acute pancreatitis.