Search Results (142)

Background: This study aimed to evaluate the prognostic value of some novel laboratory indices in intensive care unit (ICU)-hospitalized sepsis patients. Methods: This retrospective, observational study included 400 patients with sepsis. The indices studied were the C-reactive protein/albumin ratio (CAR), hemoglobin, albumin lymphocyte, and platelet (HALP) score, lymphocyte/monocyte ratio (LMR), prognostic nutritional index (PNI), systemic immune inflammatory index (SII), vitamin B12xC-reactive protein index (BCI), systemic inflammatory response index (SIRI), and platelet/lymphocyte ratio (PLR). The predicting effects of these indices in ICU mortality, along with other clinical outcomes, were investigated. Results: The median age of the study population was 73 (18–95) years and 51.6% were males. The ICU mortality rate was 51.7%. Deceased patients with sepsis had an increased age and high APACHE II and SOFA scores compared to the survivors (p < 0.05 for all). In the multivariate logistic regression analysis, age (HR = 1.069, p = 0.038 in Model 1 vs. HR = 1.053, p = 0.001 in Model 2), SOFA score (HR = 2.145, p < 0.001 in Model 1 vs. HR = 1.740, p < 0.001 in Model 2), phosphorus levels (in Model 1, HR = 0.608, p = 0.037), and CAR (in Model 2, HR = 1.012, p = 0.023) were independent associated factors for ICU mortality. According to the ROC analyses, the SOFA (AUC = 0.879, p < 0.001) and APACHE II (AUC = 0.769, p < 0.001) scores showed high accuracy in predicting ICU mortality, while the PNI (AUC = 0.675, p < 0.001), CAR (AUC = 0.609, p < 0.001), and the BCI (AUC = 0.648, p < 0.001) showed limited accuracy. However, the HALP score did not reach a significant level in predicting ICU mortality (p = 0.067). Conclusions: Excluding the HALP score, the new laboratory indices mentioned above may be prognostic markers for predicting clinical outcomes in intensive care units for patients with sepsis. However, these indices need to be supported by larger patient populations. Full article

Background and Objectives: The evaluation of the haemostatic mechanism in premature neonates remains particularly challenging, due to their immature haemostatic system, the influence of inflammation and the variety of clinical factors. This prospective study aimed at (a) assessing the haemostatic profile of clinically stable preterm neonates by Rotational Thromboelastometry [ROTEM; (EXTEM, INTEM, FIBTEM assays)], (b) establishing reference ranges, and (c) investigating potential differences in comparison to healthy term neonates. We also evaluated the impact of clinical and perinatal factors on the haemostatic status of this vulnerable population. Materials and Methods: 69 premature neonates with no underlying morbidity and 226 healthy term neonates were the study subjects. In term neonates, blood was collected on the 2nd-3rd day of life, if sampling was required for any other reason (hyperbilirubinemia, ABO blood group incompatibility screening, maternal thyroid antibodies, or insufficient prenatal care), whereas in premature neonates, blood was collected between the 4nd-10th day after stabilisation. The parameters measured for each ROTEM assay included Clotting Time (CT), Clot Formation Time (CFT), Alpha angle (α, degrees), Clot Amplitude at 5 and 10 min (A5, A10), Maximal Clot Firmness (MCF), and Lysis Index at 30, 45 and 60 min (Li30, Li45, and Li60 respectively). Results: The data analysis demonstrated a prothrombotic profile in preterm neonates, characterized by increased values of A5, A10, (MCF), and α-angle, and shortened CT and CFT across all assays (EXTEM, INTEM, FIBTEM), when compared to term neonates. A statistically significant inverse correlation was observed between gestational age and clot lysis parameters (INTEM Li45, Li60). Additionally, hematocrit levels were negatively correlated with clot amplitude and kinetics of clot development, while platelet count was positively associated with clot firmness parameters (A5, A10, MCF) and α-angle. Mode of delivery and the presence of gestational diabetes did not significantly affect ROTEM assay values. Preterm neonates with a history of respiratory distress syndrome (RDS) exhibited a more pronounced hypercoagulable profile compared to those without RDS, as reflected by the enhanced clot strength and reduced CT, findings that may be attributed to postnatal pulmonary inflammation and its systemic effects on coagulation. Conclusions: This study introduces for the first time reference values for the parameters of ROTEM assays (EXTEM, INTEM, FIBTEM) in clinically stable preterm neonates—a highly vulnerable patient group with a distinct need for accurate and individualized monitoring of their haemostatic status. The combined assessment of these assays enhances diagnostic precision, and offers a more comprehensive evaluation of neonatal haemostasis. By defining reference ranges in whole blood, this work provides novel data that support the integration of ROTEM into clinical transfusion algorithms. Full article

Background: Pediatric sepsis is a life-threatening disease that is associated with the progression of acute lymphoblastic leukemia (ALL) and the recurrence of B-cell ALL (B-ALL). Although previous studies have reported a partial association between sepsis and ALL, there is limited research on the shared genes between pediatric sepsis and relapsed B-ALL. This study aims to further elucidate the more comprehensive and novel common genetic factors and molecular pathways between the two diseases. Methods: Gene expression datasets pertaining to pediatric sepsis (GSE13904, GSE80496) and relapsed B-ALL (GSE3910, GSE28460) were retrieved from the Gene Expression Omnibus database for this retrospective analysis. The initial analysis identified differentially expressed genes common to both pediatric sepsis and relapsed B-ALL. Subsequent investigations employed three complementary approaches: protein–protein interaction networks, molecular complex detection (MCODE) clustering functions, and support vector machine recursive feature elimination model to separately identify the diagnostic biomarkers for each condition. Importantly, key common genes were identified by overlapping the diagnostic genes for pediatric sepsis and relapsed B-ALL. Further characterization involved comprehensive functional analysis through the Metascape platform, construction of transcription factor (TF)-mRNA-microRNA (miRNA) networks, drug prediction, and molecular docking to explore their biological significance and potential therapeutic targets. Results: Comparative analysis of pediatric sepsis-related and relapsed B-ALL-related datasets revealed two shared genetic markers, lactotransferrin (LTF) and matrix metallopeptidase 9 (MMP9), exhibiting diagnostic significance and consistent upregulation in both disease groups. Transcriptional regulatory network analysis identified specificity protein 1 (SP1) as the principal transcription factor capable of coregulating LTF and MMP9 expression. In addition, molecular docking demonstrated high-affinity interactions between curcumin and MMP9 (−7.18 kcal/mol) as well as reserpine and LTF (−5.4 kcal/mol), suggesting their potential therapeutic utility for clinical evaluation. Conclusions: These findings elucidate the molecular pathogenesis involving LTF and MMP9 in pediatric sepsis and relapsed B-ALL, providing novel insights for clinical diagnosis and therapeutic development. Full article

Background/Objectives: Benign prostatic hyperplasia (BPH) is a prevalent urological disorder in aging men, characterized by the enlargement of prostate epithelial and stromal cells, which leads to lower urinary tract symptoms. Paeonol, a bioactive compound derived from Moutan Cortex (Paeonia suffruticosa), exhibits multiple pharmacological properties; however, its therapeutic potential in BPH remains unclear. This study aimed to elucidate the mechanisms of paeonol in BPH treatment using network pharmacology and in vivo experiments. Methods: Network pharmacology and molecular docking were conducted to identify potential targets of paeonol against BPH. For the in vivo study, testosterone-induced BPH rat models were employed, and efficacy was evaluated through prostate weight assessment, histological examination, and the quantitative real-time polymerase chain reaction (qRT-PCR) analysis of prostate tissues. Results: In silico analysis revealed key signaling pathways involved in apoptosis, proliferation, phosphatidylinositol 3-kinase (PI3K)–protein kinase B (Akt), and inflammation. Paeonol administration significantly reduced prostate weight, volume, and histological hyperplasia in BPH rats. qRT-PCR analysis demonstrated that paeonol may suppress dihydrotestosterone production by inhibiting 5α-reductase 2 (5AR2) and the androgen receptor (AR), while also downregulating local growth factors, alpha serine/threonine-protein kinase (Akt1), nuclear factor-κB (NF-κB), and glutathione reductase (GR) expression. Conclusions: These findings provide novel insights into the multitargeted therapeutic potential of paeonol in BPH by inhibiting 5AR and AR and suppressing proliferation via NF-κB and Akt pathway modulation. Full article

In order to enhance the performance of 112 Gb/s polarization-multiplexed quadrature phase-shift keying (PM-QPSK) coherent optical receivers, a novel digital signal processing (DSP) framework is presented in this study. The suggested method combines cutting-edge signal processing techniques to address important constraints in long-distance, high data rate coherent systems. The framework uses overlap frequency domain equalization (OFDE) for chromatic dispersion (CD) compensation, which offers a cheaper computational cost and higher dispersion control precision than traditional time-domain equalization. An adaptive carrier phase recovery (CPR) technique based on mean-squared differential phase (MSDP) estimation is incorporated to manage phase noise induced by cross-phase modulation (XPM), providing dependable correction under a variety of operating situations. When combined, these techniques significantly increase Q factor performance, and optimum systems can handle transmission distances of up to 2400 km. The suggested DSP approach improves phase stability and dispersion tolerance even in the presence of nonlinear impairments, making it a viable and effective choice for contemporary coherent optical networks. The framework’s competitiveness was evaluated by comparing it against the most recent, cutting-edge DSP methods that were released after 2021. These included CPR systems that were based on kernels, transformers, and machine learning. The findings show that although AI-driven approaches had the highest absolute Q factors, they also required a large amount of computing power. On the other hand, the suggested OFDE in conjunction with adaptive CPR achieved Q factors of up to 11.7 dB over extended distances with a significantly reduced DSP effort, striking a good balance between performance and complexity. Its appropriateness for scalable, long-haul 112 Gb/s PM-QPSK systems is confirmed by a complexity versus performance trade-off analysis, providing a workable and efficient substitute for more resource-intensive alternatives. Full article

Background: Breast cancer (BC) is the most common cancer and the leading cause of cancer death in women. Hereditary BC risk accounts for 25% of all cases. Pathological variants in known BC precursor genes explain only about 30% of hereditary BC cases, while the underlying genetic factors in most families remain unknown. Identifying hereditary cancer risk factors will help improve genetic counseling, cancer prevention, and cancer care. Methods: Here, we used whole-exome sequencing (WES) to identify genetic variants in 105 Vietnamese patients with BC and 50 healthy women. BC-associated variants were screened by the Franklin software and the criteria of the American College of Medical Genetics and Genomics (ACMG) and evaluated based on in silico analysis. Results: In total, 56 variants were identified in 37 genes associated with BC, including ACVR1B, APC, AR, ARFGEF1, ATM, ATR, BARD1, BLM, BRCA1, BRCA2, CASP8, CASR, CHD8, CTNNB1, ESR1, FAN1, FGFR2, HMMR, KLLN, LZTR1, MCPH1, MLH1, MSH2, MSH3, MSH6, NF1, PMS2, PRKN, RAD54L, RB1CC1, RECQL, SLC22A18, SLX4, SPTBN1, TP53, WRN, and XRCC3 in 41 patients. Among them, 12 variants were novel, and 10 variants were assessed as pathogenic/likely pathogenic by ACMG and ClinVar. Variants of uncertain significance (VUS) were evaluated using in silico prediction software to predict whether they are likely to cause the disease in patients. Conclusions: This is the first WES study to identify BC-associated genetic variants in Vietnamese patients, providing a comprehensive database of BC susceptibility gene variants. We suggest using WES as a tool to identify genetic variants in BC patients for risk prediction and treatment guidance. Full article

In this study, we present a novel, six-dimensional, multistable, memristive, hyperchaotic system model demonstrating two positive Lyapunov exponents. With the maximum Lyapunov exponents surpassing 21, the developed system shows pronounced hyperchaotic behavior. The dynamical behavior was analyzed through phase portraits, bifurcation diagrams, and Lyapunov exponent spectra. Parameter b was a key factor in regulating the dynamical behavior of the system, mainly affecting the strength and direction of the influence of $z_1$ on $z_2$. It was found that when the system parameter b was within a wide range of $[13,300]$, the system remained hyperchaotic throughout. Analytical establishment of multistability mechanisms was achieved through invariance analysis of the state variables under specific coordinate transformations. Furthermore, offset boosting control was realized by strategically modulating the fifth state variable, $z_5$. The FPGA-based experimental results demonstrated that attractors observed via an oscilloscope were in close agreement with numerical simulations. To validate the system’s reliability for cybersecurity applications, we designed a novel image encryption method utilizing this hyperchaotic model. The information entropy of the proposed encryption algorithm was closer to the theoretical maximum value of 8. This indicated that the system can effectively disrupt statistical patterns. Experimental outcomes confirmed that the proposed image encryption method based on the hyperchaotic system exhibits both efficiency and reliability. Full article

Background: Previously, we established gemcitabine (Gem)-resistant pancreatic cancer (PaCa) cell lines and showed that the acquisition of Gem resistance is accompanied by enhanced activation of the inflammatory transcription factor nuclear factor-κB (NF-κB). In this study, we focus on CalebinA, a natural compound derived from the rhizomes of turmeric, known for its potent anti-inflammatory properties. It has been suggested that this compound may exert anticancer effects by downregulating the NF-κB signaling cascade. Therefore, we collaborated with Sabinsa Corporation, Japan, to explore its potential application in pancreatic cancer therapy. Methods: We used gemcitabine-resistant pancreatic cell lines to demonstrate the effect of CalebinA on cell toxicity, invasiveness, cytokine levels, NF-κB p65 activity, and tube formation in angiogenesis. Tumor volume and histopathological analysis were used to analyze the effects of CalebinA on tumors induced by the subcutaneous injection of pancreatic cell lines in mice. Results: Treatment with 10 μM CalebinA significantly inhibited NF-κB activity. Gem-resistant PaCa cells exhibited higher invasive and angiogenic capacities than non-resistant parental cells; however, these capacities were markedly suppressed by CalebinA. In vivo, intraperitoneal CalebinA administration every 3 days led to a significant reduction in tumor volume in mice bearing subcutaneous xenografts of the AsPC-1 pancreatic cancer cell line. Immunohistochemical analysis revealed that CalebinA suppressed the expression of Ki-67, CD31-positive microvessel density, and NF-κB p65. Conclusions: These findings suggest that CalebinA holds promise as a novel therapeutic agent for Gem-resistant pancreatic cancer and may be a strong candidate for clinical application. Full article

This study pioneers the integration of Sentinel-2 satellite imagery with Kolmogorov–Arnold networks (KAN) for the evaluation of chlorophyll-a (Chl-a) concentrations in inland lakes. Using Baiyangdian Lake in Hebei Province, China, as a case study, a specialized KAN architecture was designed to extract spectral features from Sentinel-2 data, and a robust algorithm was developed for Chl-a estimation. The results demonstrate that the KAN model outperformed traditional feature-engineering-based machine learning (ML) methods and standard multilayer perceptron (MLP) deep learning approaches, achieving an R² of 0.8451, with MAE and RMSE as low as 1.1920 μg/L and 1.6705 μg/L, respectively. Furthermore, attribution analysis was conducted to quantify the importance of individual features, highlighting the pivotal role of bands B3 and B5 in Chl-a retrieval. Furthermore, spatio-temporal distributions of Chl-a concentrations in Baiyangdian Lake from 2020 to 2024 were generated leveraging the KAN model, further elucidating the underlying causes of water quality changes and examining the driving factors. Compared to previous studies, the proposed approach leverages the high spatial resolution of Sentinel-2 imagery and the accuracy and interpretability of the KAN model, offering a novel framework for monitoring water quality parameters in inland lakes. These findings may guide similar research endeavors and provide valuable decision-making support for environmental agencies. Full article

Background: Blue light (BL) irradiation has been shown to induce photobiomodulation (PBM) in cells. Here, we investigate its influence on cell types involved in wound healing. Methods: Cellular responses of immortalized human keratinocytes (HaCaTs), normal human dermal fibroblasts (NHDFs), and human umbilical vein endothelial cells (HUVECs) after light treatment at 450 nm were analyzed by kinetic assays on cell viability, proliferation, ATP quantification, migration assay, and apoptosis assay. Gene expression was evaluated by transcriptome analysis. Results: A biphasic effect was observed on HaCaTs, NHDFs, and HUVECs. Low-fluence (4.5 J/cm²) irradiation stimulated cell viability, proliferation, and migration. mRNA sequencing indicated involvement of transforming growth factor beta (TGF-β), ErbB, and vascular endothelial growth factor (VEGF) pathways. High-fluence (18 J/cm²) irradiation inhibited these cellular activities by downregulating DNA replication, the cell cycle, and mismatch repair pathways. Conclusions: HaCaTs, NHDFs, and HUVECs exhibited a dose-dependent pattern after BL irradiation. These findings broaden the view of PBM following BL irradiation of these three cell types, thereby promoting their potential application in wound healing and angiogenesis. Our data on low-fluence BL at 450 nm indicates clinical potential for a novel modality in wound therapy. Full article

The increasing deployment of turbines installed offshore is critical for sustainable energy development, yet accurate performance assessment remains challenging due to complex environmental influences, diverse turbine control strategies, and issues with data quality. Traditional performance metrics and power curve models often fail to provide reliable cross-turbine comparisons because they neglect multivariate environmental factors and turbine-specific biases. To address these limitations, this study develops a novel multivariate environmental factor-driven power assessment framework employing segmented long short-term memory (LSTM) models. A hybrid data cleaning method, combining bidirectional quartile analysis with the power curtailment detection, is proposed to effectively identify outliers, including subtle anomalies within typical data ranges. Samples are segmented based on rated wind speed to reflect differences in control strategies, and turbine-specific operational parameters are excluded to ensure unbiased comparisons among turbines. The proposed method achieves substantial improvements in predictive accuracy, with decreases of 9.39% in mean absolute error (MAE) and 11.75% in root mean square error (RMSE), compared to conventional binning approaches. When applied to three 5.5 MW offshore wind turbines, the proposed method reveals significant differences among the units. Turbine A demonstrates the highest performance, while turbines B and C exhibit reductions of 14.35% and 8.29%, respectively. Operational state analysis shows that turbine B experiences substantially longer maintenance durations, indicating severe faults that adversely affect its operational reliability and power output. These findings provide valuable insights for maintenance prioritization and performance benchmarking among wind turbines. 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

Background: Colorectal cancer (CRC) remains one of the most prevalent and fatal malignancies globally, with radiotherapy playing a crucial role in the treatment of locally advanced rectal cancer (LARC). However, the efficacy of radiotherapy is limited by significant resistance, with only a small proportion of patients achieving a pathologic complete response (PCR) to neoadjuvant chemoradiotherapy (nCRT). This study aims to uncover the genetic and molecular factors contributing to radiotherapy resistance in CRC through an integrated analysis of germline mutations, transcriptomic data, and immune microenvironment characteristics. Methods: Whole-exome sequencing (WES) was performed on tumor samples from 12 LARC patients. Transcriptomic data from the TCGA-READ and GSE150082 (LARC with chemoradiotherapy) cohorts were integrated with WES findings. The independent cohort GSE190826 (neoadjuvant therapy in rectal cancer) dataset was utilized to validate the WES data. Single-cell RNA sequencing (scRNA-seq) analysis of GSE132465 (primary CRC) resolved cellular heterogeneity. A random forest algorithm was employed to develop a predictive gene signature. Results: Our findings reveal a mutational landscape associated with radiotherapy resistance, identifying specific germline mutations linked to treatment outcomes. Differential gene expression analysis highlighted pathways involved in DNA replication, DNA repair, and immune regulation, with a focus on the tumor immune microenvironment (TIME). A gene signature, including CDCA4, FANCA, PBRM1, RPL13, and C12orf43, was developed to predict radiotherapy response. Notably, CDCA4 expression was significantly associated with tumor mutation burden (TMB) and microsatellite instability (MSI), and it plays a crucial role in regulating B cell infiltration in the tumor microenvironment. Conclusions: Our study provides novel insights into the molecular mechanisms of radiotherapy resistance in CRC and proposes CDCA4 and B cell-related immune features as potential biomarkers for patient stratification and personalized treatment strategies. Full article

This study looked into the underlying mechanisms and causal relationship between alcoholic liver disease (ALD) and the blood metabolite uridine using a variety of analytical methods, such as Mendelian randomization and molecular dynamics simulations. We discovered uridine to be a possible hepatotoxic agent aggravating ALD by using Mendelian randomization (MR) analysis with genome-wide association study (GWAS) data from 1416 ALD cases and 217,376 controls, as well as with 1091 blood metabolites and 309 metabolite concentration ratios as exposure factors. According to network toxicology analysis, uridine interacts with important targets such as SRC, FYN, LYN, ADRB2, and GSK3B. The single-cell RNA sequencing analysis of ALD tissues revealed that SRC was upregulated in hepatocytes and activated hepatic stellate cells. Subsequently, we determined the stable binding between uridine and SRC through molecular docking and molecular dynamics simulation (RMSD = 1.5 ± 0.3 Å, binding energy < −5.0 kcal/mol). These targets were connected to tyrosine kinase activity, metabolic reprogramming, and GPCR signaling by Gene Ontology (GO) and KEGG studies. These findings elucidate uridine’s role in ALD progression via immunometabolic pathways, offering novel therapeutic targets for precision intervention. These findings highlight the necessity of systems biology frameworks in drug safety evaluation, particularly for metabolites with dual therapeutic and toxicological roles. Full article

Background/Objectives: Chronic craniofacial inflammation is recognized as a factor in anxiety-like behaviors, yet effective therapeutic options remain limited. Agmatine, a dietary bioactive compound found in fermented foods such as sake lees, exhibits modulatory effects on neural functions, alleviating psychological distress like anxiety associated with local inflammation. Methods: We investigated both the therapeutic and preventive effects of agmatine on anxiety-like behaviors and the related neural basis in a mouse model of persistent craniofacial inflammation induced by complete Freund’s adjuvant (CFA). Results: Comprehensive behavioral assessments, including the elevated plus maze, open field, dark–light box, social interaction, and novel object recognition tests, revealed that therapeutic agmatine administration (1.0 and 30 mg/kg) significantly reduced CFA-induced anxiety-like behaviors, with the higher dose showing more robust and sustained effects across multiple time points. These behavioral improvements were paralleled by reductions in acetylated histone H3, FosB, and c-Fos expression in key anxiety-related brain regions, suggesting a reversal of craniofacial inflammation-associated neural changes. In contrast, preventive agmatine treatment exerted modest and time-dependent behavioral benefits with minimal molecular normalization. Notably, preventive agmatine did not affect general locomotor activity (indicated by total movement distance), indicating that its anxiolytic effects were not confounded by altered locomotor activity. Metabolomic analysis confirmed the presence of agmatine in sake lees (~0.37 mM), supporting the hypothesis that fermented food products might offer dietary routes to emotional resilience. Conclusions: These findings underscore agmatine’s promise as a context-specific epigenetic modulator capable of mitigating anxiety-like behaviors by normalizing inflammation-driven molecular dysregulation in the brain. Full article