Search Results (45)

This study introduces an enhanced Intrusion Detection System (IDS) framework for Denial-of-Service (DoS) attacks, utilizing network traffic inter-arrival time (IAT) analysis. By examining the timing between packets and other statistical features, we detected patterns of malicious activity, allowing early and effective DoS threat mitigation. We generate real DoS traffic, including normal, Internet Control Message Protocol (ICMP), Smurf attack, and Transmission Control Protocol (TCP) classes, and develop nine predictive algorithms, combining traditional machine learning and advanced deep learning techniques with optimization methods, including the synthetic minority sampling technique (SMOTE) and grid search (GS). Our findings reveal that while traditional machine learning achieved moderate accuracy, it struggled with imbalanced datasets. In contrast, Deep Neural Network (DNN) models showed significant improvements with optimization, with DNN combined with GS (DNN-GS) reaching 89% accuracy. However, we also used Recurrent Neural Networks (RNNs) combined with SMOTE and GS (RNN-SMOTE-GS), which emerged as the best-performing with a precision of 97%, demonstrating the effectiveness of combining SMOTE and GS and highlighting the critical role of advanced optimization techniques in enhancing the detection capabilities of IDS models for the accurate classification of various types of network traffic and attacks. Full article

E3 ubiquitin ligases and deubiquitinating enzymes (DUBs) are pivotal regulators of bone homeostasis, orchestrating osteoblast differentiation, proliferation, and osteoclast activity by controlling protein degradation and stability. This review delineates the roles of key E3 ligases (e.g., Smurf1, Smurf2, TRIM family) and DUBs (e.g., USP family) in bone formation and resorption. E3 ligases such as Smurf1/2 inhibit osteogenesis by degrading BMP/Smad signaling components, while TRIM proteins and HERC ligases promote osteoblast differentiation. Conversely, DUBs like USP2 and USP34 stabilize β-catenin and Smad1/RUNX2, enhancing osteogenic pathways, whereas USP10 and USP12 suppress differentiation. Dysregulation of these enzymes contributes to osteoporosis, fracture non-union, and other bone disorders. The interplay between ubiquitination and deubiquitination, alongside the regulatory role of miRNA and environmental factors, underscores their therapeutic potential. Future research should focus on developing therapies targeting E3 ubiquitin ligases, deubiquitinases, miRNA regulators, and small-molecule inhibitors to restore bone homeostasis in osteoporosis and fracture healing disorders. Full article

Background: The etiology of acute myocardial infarction (AMI) in patients without history of standard modifiable risk factors (SMuRFs) remains unclear. Simultaneously, evidence suggests that mental health status (MHS) contributes to the pathogenesis of AMI and worsens its outcomes. Methods: This analysis of the prospective “Beyond-SMuRFs” (NCT05535582) study included 650 consecutive patients with AMI who had available data on self-reported MHS before AMI, calculated by the SF36-Questionnaire mental component summary (MCS). Poor MHS was defined as MCS ≤ 50. Multivariable logistic-regression and Cox-regression analyses were implemented to investigate poor MHS as a potential predictor of SMuRF-less AMIs and compare all-cause mortality based on SMuRF-less and MH status, respectively. Results: Of 650 patients with AMI (mean age 62.6 ± 12.1 years), 288 (44.3%) had MCS ≤ 50 and 128 (19.7%) were SMuRF-less patients. Three out of four SMuRF-less patients reported an MCS ≤ 50 (n = 96, 75%), a significantly higher percentage than the corresponding percentage in patients with SMuRFs (n = 192, 36.8%; p < 0.01). The multivariable logistic regression model showed that MCS ≤ 50 was an independent predictor of SMuRF-less AMI [aOR = 0.95; 95% CI (0.94–0.96)]. Time-to-event analysis for all-cause mortality showed that patients with MCS > 50 had lower mortality rates than those with poor MHS (aHR, 3.61 [95% CI, 2.02 to 6.43], p < 0.01). Higher risk for all-cause mortality was also observed in SMuRF-less patients with poor MHS compared to patients with at least one SMuRF and good MHS [aHR, 4.52 (95% CI, 0.94–21.73)]. Conclusions: Poor MHS was an independent predictor of the occurrence of SMuRF-less AMI and predictive of higher mortality in patients with and without SMuRFs. Full article

Integrin β4 (ITGB4) mediates lung endothelial cell (EC) inflammation attenuated by simvastatin, an HMG CoA-reductase inhibitor. The cytoplasmic domain of ITGB4 is predicted to bind kindlin-2. Kindlin-2 expression is mediated by SMURF1, an E3 ubiquitin ligase that promotes kindlin-2 ubiquitination and degradation. We hypothesized that increased kindlin-2 expression via the inhibition of SMURF1 mediates EC inflammatory responses relevant to acute lung injury (ALI). To investigate this, human lung ECs were treated with simvastatin (5 µM, 16 h) prior to the immunoprecipitation of kindlin-2 and Western blotting for ITGB4. Next, ECs were treated with a SMURF1 inhibitor, A01, and increased kindlin-2 expression was confirmed. In assays of barrier function, kindlin-2 was silenced (siRNA) in ECs prior to thrombin and measurements of transendothelial resistance (TER) and FITC-dextran transwell flux. Repeat assessments of barrier function were performed in A01-treated ECs. Finally, mice were pretreated with A01 prior to LPS; bronchoalveolar lavage (BAL) fluid was collected, and their lungs were used for histology. Simvastatin increased ITGB4:kindlin-2 association, while A01 increased kindlin-2 expression. Thrombin-induced EC barrier disruption was both increased after kindlin-2 silencing and decreased by A01. Finally, murine ALI was significantly attenuated by A01. Our findings suggest that the augmentation of kindlin-2 may serve as a novel ALI therapeutic strategy. Full article

Ferritin heavy chain 1 (FTH1) is pivotal in the storage, release, and utilization of iron, plays a crucial role in the ferroptosis pathway, and exerts significant impacts on various diseases. Iron influences skeletal muscle development and health by promoting cell growth, ensuring energy metabolism and ATP synthesis, maintaining oxygen supply, and facilitating protein synthesis. However, the precise molecular mechanisms underlying iron’s regulation of skeletal muscle growth and development remain elusive. In this study, we demonstrated that the conditional knockout (cKO) of FTH1 in skeletal muscle results in muscle atrophy and impaired exercise endurance. In vitro studies using FTH1 cKO myoblasts revealed notable decreases in GSH concentrations, elevated levels of lipid peroxidation, and the substantial accumulation of Fe²⁺, collectively implying the induction of ferroptosis. Mechanistically, E3 ubiquitin-protein ligase SMURF1 (SMURF1) acts as an E3 ubiquitin ligase for FTH1, thereby facilitating the ubiquitination and subsequent degradation of FTH1. Consequently, this activation of the ferroptosis pathway by SMURF1 impedes myoblast differentiation into myotubes. This study identifies FTH1 as a novel regulator of muscle cell differentiation and skeletal muscle development, implicating its potential significance in maintaining skeletal muscle health through the regulation of iron homeostasis. Full article

The Internet of Medical Things (IoMT) is revolutionizing healthcare by enabling advanced patient care through interconnected medical devices and systems. However, its critical role and sensitive data make it a prime target for cyber threats, requiring the implementation of effective security solutions. This paper presents a novel intrusion detection system (IDS) specifically designed for IoMT networks. The proposed IDS leverages machine learning (ML) and deep learning (DL) techniques, employing a stacking ensemble method to enhance detection accuracy by integrating the strengths of multiple classifiers. To ensure real-time performance, the IDS is implemented within a Kappa Architecture framework, enabling continuous processing of IoMT data streams. The system effectively detects and classifies a wide range of cyberattacks, including ARP spoofing, DoS, Smurf, and Port Scan, achieving an outstanding detection accuracy of 0.991 in binary classification and 0.993 in multi-class classification. This research highlights the potential of combining advanced ML and DL methods with ensemble learning to address the unique cybersecurity challenges of IoMT systems, providing a reliable and scalable solution for safeguarding healthcare services. Full article

The E3 ubiquitin ligase Smurf1 catalyzes the ubiquitination and proteasomal degradation of several protein substrates related to inflammatory responses and antiviral signaling. This study investigated the role of Smurf1 in modulating inflammation induced by Betacoronavirus infection. Bone marrow-derived macrophages (BMDMs) from C57BL/6 (wild-type) or Smurf1-deficient (Smurf1^−/−) mice were infected with MHV-A59 to evaluate the inflammatory response in vitro. Smurf1 was found to be required to downregulate the macrophage production of pro-inflammatory mediators, including TNF, and CXCL1; to control viral release from infected cells; and to increase cell viability. To assess the impact of Smurf 1 in vivo, we evaluated the infection of mice with MHV-A59 through the intranasal route. Smurf1^−/− mice infected with a lethal inoculum of MHV-A59 succumbed earlier to infection. Intranasal inoculation with a 10-fold lower dose of MHV-A59 resulted in hematological parameter alterations in Smurf1^−/− mice suggestive of exacerbated systemic inflammation. In the lung parenchyma, Smurf1 expression was essential to promote viral clearance, downregulating IFN-β mRNA and controlling the inflammatory profile of macrophages and neutrophils. Conversely, Smurf1 did not affect IFN-β mRNA regulation in the liver, but it was required to increase TNF and iNOS expression in neutrophils and decrease TNF expression in macrophages. In addition, Smurf1^−/− mice exhibited augmented liver injuries, accompanied by high serum levels of alanine aminotransferase (ALT). These findings suggest that Smurf1 plays a critical role in regulating the inflammatory response in macrophages and attenuating systemic inflammation during Betacoronavirus infection. Full article

Angiogenesis is essential for remodeling and repairing existing vessels, and this process requires signaling pathways including those controlled by transforming growth factor beta (TGF-β). We have previously reported crosstalk between TGF-β and the protein kinase With No lysine (K) 1 (WNK1). Homozygous disruption of the gene encoding WNK1 results in lethality in mice near embryonic day E12 due to impaired angiogenesis, and this defect can be rescued by the endothelial-specific expression of an activated form of the WNK1 substrate kinase Oxidative Stress-Responsive 1 (OSR1). However, molecular processes regulated via a collaboration between TGF-β and WNK1/OSR1 are not well understood. Here, we show that WNK1 interacts with the E3 ubiquitin ligases SMURF1/2. In addition, we discovered that WNK1 regulates SMURF1/2 protein stability and vice versa. We also demonstrate that WNK1 activity regulates TGF-β receptor levels, in turn, controlling TGF-β signaling. Full article

The risk-factor-based prediction of atherosclerotic coronary artery disease (CAD) remains suboptimal, particularly in the absence of any of the standard modifiable cardiovascular risk factors (SMuRFs), making the discovery of biomarkers that correlate with atherosclerosis burden critically important. We hypothesized that cytokines and receptors associated with inflammation in CAD—tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), interleukin-18 (IL-18), and osteoprotegerin (OPG)—would be independently associated with CAD. To determine this, we measured the serum biomarker levels of 993 participants from the BioHEART study who had CT coronary angiograms that were scored for severity of stenosis and plaque composition. We found that the quartiles of TRAIL, OPG, and IL-18 were significantly associated with disease scores, and that the IL-18/TRAIL and OPG/TRAIL ratios demonstrated significant differences between no CAD vs. STEMI whereas only the OPG/TRAIL ratio showed differences between no CAD and obstructive CAD (stenosis > 50%). However, these associations did not persist after adjustment for age, sex, SMuRFs, and a family history of CAD. In conclusion, TRAIL, IL-18, and OPG and the derived ratios of IL-18/TRAIL and OPG/TRAIL demonstrate significant associations with raw disease scores and risk factors, but these markers are not discriminatory biomarkers for the prediction of CAD when incorporated into multi-variable risk models. Full article

Code smells are early warning signs of potential issues in software quality. Various techniques are used in code smell detection, including the Bayesian approach, rule-based automatic antipattern detection, antipattern identification utilizing B-splines, Support Vector Machine direct, SMURF (Support Vector Machines for design smell detection using relevant feedback), and immune-based detection strategy. Machine learning (ML) has taken a great stride in this area. This study includes relevant studies applying ML algorithms from 2005 to 2024 in a comprehensive manner for the survey to provide insight regarding code smell, ML algorithms frequently applied, and software metrics. Forty-two pertinent studies allow us to assess the efficacy of ML algorithms on selected datasets. After evaluating various studies based on open-source and project datasets, this study evaluated additional threats and obstacles to code smell detection, such as the lack of standardized code smell definitions, the difficulty of feature selection, and the challenges of handling large-scale datasets. The current studies only considered a few factors in identifying code smells, while in this study, several potential contributing factors to code smells are included. Several ML algorithms are examined, and various approaches, datasets, dataset languages, and software metrics are presented. This study provides the potential of ML algorithms to produce better results and fills a gap in the body of knowledge by providing class-wise distributions of the ML algorithms. Support Vector Machine, J48, Naive Bayes, and Random Forest models are the most common for detecting code smells. Researchers can find this study helpful in better anticipating and taking care of software development design and implementation issues. The findings from this study, which highlight the practical implications of ML algorithms in software quality improvement, will help software engineers fix problems during software design and development to ensure software quality. Full article

Screening and identifying the active compounds in foods are important for the development and utilization of functional foods. In this study, the anti-enteritis activity of ethanol extract from Camellia oleifera oil (PECS) was quickly evaluated using a Smurf Drosophila model and the metabolomics approach, combined with molecular docking techniques, were performed to rapidly screen and identify compounds with potential anti-enteritis activity in PECS. PECS showed good anti-enteritis activity and inhibited the activity of 5-lipoxygenase (LOX), cyclooxygenase 2 (COX-2) and inducible nitric oxide synthase (iNOS). In particular, wighteone and p-octopamine were newly identified in C. oleifera oil and were proven to have good anti-enteritis activity. The inhibitory activity of kaempferitrin (IC₅₀ = 0.365 mmol L⁻¹) was higher than that of wighteone (IC₅₀ = 0.424 mmol L⁻¹) and p-octopamine (IC₅₀ = 0.402 mmol L⁻¹). Of note, the IC₅₀ value of salazosulfapyridine was 0.810 mmol L⁻¹. Inhibition of LOX activity is likely one of the anti-enteritis mechanisms of PECS. These new findings lay the foundation for further investigations into the underlying mechanisms of anti-enteritis activity in C. oleifera oil. Full article

Risk-factor-based scoring systems for atherosclerotic coronary artery disease (CAD) remain concerningly inaccurate at the level of the individual and would benefit from the addition of biomarkers that correlate with atherosclerosis burden directly. We hypothesized that serum soluble lectin-like oxidized low-density lipoprotein receptor-1 (sLOX-1) would be independently associated with CAD and investigated this in the BioHEART study using 968 participants with CT coronary angiograms, which were scored for disease burden in the form of coronary artery calcium scores (CACS), Gensini scores, and a semi-quantitative soft-plaque score (SPS). Serum sLOX-1 was assessed by ELISA and was incorporated into regression models for disease severity and incidence. We demonstrate that sLOX-1 is associated with an improvement in the prediction of CAD severity when scored by Gensini or SPS, but not CACS. sLOX-1 also significantly improved the prediction of the incidence of obstructive CAD, defined as stenosis in any vessel >75%. The predictive value of sLOX-1 was significantly greater in the subgroup of patients who did not have any of the standard modifiable cardiovascular risk factors (SMuRFs). sLOX-1 is associated with CAD severity and is the first biomarker shown to have utility for risk prediction in the SMuRFless population. Full article

Patients with ST-elevation myocardial infarction (STEMI), but without standard modifiable risk factors (SMuRF-less), are surprisingly common and appear to have a worse, or at best similar, short-term prognosis. However, relatively little attention has been paid to the prevalence and prognosis of SMuRF-less patients with non-STEMI (NSTEMI). The aim of our study was to identify the proportion and outcomes of SMuRF-less NSTEMI patients in a large US healthcare population. Patients with NSTEMI between 2001–2021 presenting to Intermountain Healthcare hospitals and catheterization laboratories were included. SMuRF-less status was defined as no clinical diagnosis of, or treatment for, hypertension, hyperlipidemia, diabetes, and smoking. Outcomes were assessed at 60 days and long-term for major adverse cardiovascular events (MACE: death, myocardial infarction, and heart failure hospitalization). Multivariable Cox proportional hazard regression was used to determine MACE hazard ratios (HR) for SMuRF-less versus patients with SMuRF. NSTEMI patients totaled 8196, of which 1458 (17.8%) were SMuRF-less. SMuRF-less patients were younger, more frequently male, had fewer comorbidities, and were slightly less likely to have revascularization. For SMuRF-less patients, 60-day MACE outcomes were lower (adj HR = 0.55, p < 0.0001), and this persisted for long-term MACE outcomes (adj HR = 0.64, p < 0.0001) and for each of its components. In this large US healthcare population, SMuRF-less NSTEMI presentation, as with STEMI presentation, was found to be common (17.8%). However, unlike STEMI reports, short- and long-term outcomes were better for SMuRF-less patients. Further studies to increase understanding of risk factors and preventive measures for NSTEMI in SMuRF-less patients are indicated. Full article

The purpose of this investigation was to examine mutations and mRNA levels of potential genes linked to diarrhea susceptibility in order to assess the health status of diarrheic kids of Baladi goats. One hundred female Baladi kids (35 diarrheic and 65 apparently healthy) were used. PCR-DNA sequencing was conducted for TMED1, CALR, FBXW9, HS6ST3, SMURF1, KPNA7, FBXL2, PIN1, S1PR5, ICAM1, EDN1, MAPK11, CSF1R, LRRK1, and CFH markers revealed nucleotide sequence variants in the frequency of distribution of all detected SNPs (p ˂ 0.05) between healthy and affected kids. Chi-square analysis showed a significant difference between resistant and affected animals. Gene expression profile revealed that TMED1, CALR, FBXW9, HS6ST3, SMURF1, KPNA7, FBXL2, PIN1, S1PR5, ICAM1, EDN1, MAPK11, CSF1R and LRRK1 were significantly up-regulated in diarrheic kids than resistant ones. Meanwhile, CFH gene elicited an opposite trend. On the mRNA levels of the examined indicators, there was a substantial interaction between the type of gene and diarrhea resistance/susceptibility. The findings could support the importance of nucleotide variations and the expression pattern of the examined genes as biomarkers for diarrhea resistance/susceptibility and offer a useful management strategy for Baladi goats. Full article