Search Results (339)

Porcine epidemic diarrhea virus (PEDV) infection induces severe, often fatal, watery diarrhea and vomiting in neonatal piglets, characterized by profound dehydration, villus atrophy, and catastrophic mortality rates approaching 100% in unprotected herds. This study developed a composite probiotic from Min-pig-derived Lactobacillus crispatus LCM233, Ligilactobacillus salivarius LSM231, and Lactiplantibacillus plantarum LPM239, which exhibited synergistic growth, potent acid/bile salt tolerance, and broad-spectrum antimicrobial activity against pathogens. In vitro, the probiotic combination disrupted pathogen ultrastructure and inhibited PEDV replication in IPI-2I cells. In vivo, PEDV-infected piglets administered with the multi-strain probiotic exhibited decreased viral loads in anal and nasal swabs, as well as in intestinal tissues. This intervention was associated with the alleviation of diarrhea symptoms and improved weight gain. Furthermore, the multi-strain probiotic facilitated the repair of intestinal villi and tight junctions, increased the number of goblet cells, downregulated pro-inflammatory cytokines, enhanced the expression of barrier proteins, and upregulated antiviral interferon-stimulated genes. These findings demonstrate that the multi-strain probiotic mitigates PEDV-induced damage by restoring intestinal barrier homeostasis and modulating immune responses, providing a novel strategy for controlling PEDV infections. Full article

Background: Several blood biomarkers have shown a major role in predicting major adverse complications (MACs) in patients who have undergone cardiac surgery. Here, we aimed to investigate the possible role of the blood urea nitrogen (BUN) to serum albumin ratio (BAR) and the inflammatory prognostic index (IPI) in predicting major adverse complication after surgical aorta valve replacement (SAVR). Methods: The clinical, echocardiographic, and clinical-chemistry laboratory data of 195 patients who underwent SAVR were evaluated. The post-surgical MACs (death, surgical re-exploration, myocardial infarction and cerebral ischemia) during the hospitalization were recorded. Univariate and multivariate logistic regression analyses were studied by comparing the basic clinical features, echocardiographic parameters, and patients’ hematological indices between patients with or without MACs. Results: The mean age was 66.1 years, and 62.5% were males. Logistic regression analysis showed that the left atrium volume (LAV), BAR, and IPI as either continuous or categorical variables were independently associated with MACs. Moreover, we found a combined effect of higher LAV with a higher value of BAR or IPI. Combined higher levels of LAV and BAR increased the risk of developing MACs by 9.8 (CI 95% = 2.8–34.3, p = 0.0003), while higher values of LAV and IPI increased the risk of developing MACs by 4.5. Conclusions: Higher levels of BAR and IPI, alone or in combination with higher LAVs, showed an independent predictive value of MACs after SAVR. These findings strongly support the importance of evaluating easily available biomarkers of the pre-operative status of patients in order to predict adverse outcomes. Full article

Power quality is a key issue in cold ironing (CI) systems, where a stable, clean power supply is essential to meet the needs of moored vessels. According to IEC/ISO/IEEE 80005-1, these systems must deliver high power at standardized voltages (6.6 kV or 11 kV) with minimal harmonic distortion in the presence of vessel load variability. This study proposes a model-free control strategy based on an intelligent proportional–integral (iPI) corrector with adaptive gain, applied to a three-phase modular multilevel converter (MMC) equipped with an LC filter. This architecture, adapted to distributed infrastructures, reduces the number of transformers required while guaranteeing high output voltages. The iPI strategy improves system robustness, dynamically compensates for disturbances, and ensures better power quality. A comparative analysis of three control strategies, proportional–integral (PI), intelligent proportional–integral (iPI), and intelligent proportional–integral adaptive (iPIa), performed in MATLAB/Simulink and complemented by experimental tests on the OPAL-RT platform, revealed a significant THD reduction of 1.18%, in accordance with the IEC/ISO/IEEE 80005-1 standard. These results confirm the effectiveness of the proposed method in meeting the requirements of CI systems. Full article

Swine acute diarrhea syndrome coronavirus (SADS-CoV), initially identified in China in February 2017, severely impacts the swine industry by causing lethal watery diarrhea in neonatal piglets. Understanding the molecular mechanism employed by SADS-CoV to evade the host’s immune defenses is of utmost importance. In this study, using the porcine ileum epithelial cell line IPI-FX as an in vitro model, we investigated the highly pathogenic SADS-CoV GDS04 strain and its nonstructural protein 5 (nsp5) for their roles in inhibiting interferon-beta (IFN-β) production. Our findings indicated that GDS04 inhibited poly(I:C)-induced IFN-β production by impeding the promoter activities of IRF3 and NF-κB. As a 3C-like protease, SADS-CoV nsp5 functioned as an interferon inhibitor by interacting with IKKε, reducing its protein abundance, and inhibiting its phosphorylation. This study enhances our understanding of the interaction between coronaviruses and their hosts, providing novel insights into the evasion of the immune system by coronaviruses. Full article

Background/Objectives: To evaluate the prognostic role of the inflammatory prognostic index (IPI) value at admission in major adverse cardiovascular and cerebrovascular events (MACCEs) in individuals with non-ST elevation myocardial infarction (NSTEMI) undergoing percutaneous coronary intervention (PCI). Methods: A total of 1142 NSTEMI patients with a mean age of 61.9 ± 12.5 years were included. Admission C-reactive protein level, serum albumin level, and complete blood counts of participants were collected from hospital records. The IPI was calculated based on the following formula: C-reactive protein/albumin ratio (CAR) x neutrophil-to-lymphocyte ratio (NLR). An aggregate index of systemic inflammation (AISI) value was calculated using the ‘‘neutrophil count x monocyte count x platelet/lymphocyte count’’ formula. The study cohort was divided into two groups according to the median IPI value. Results: Patients with higher IPI values were statistically more likely to suffer from MACCEs within one year (p < 0.001), thus the admission IPI value was found to be associated with future development of MACCEs. Furthermore, it had sufficient discrimination power (AUC = 0.70) and predictive accuracy in identifying MACCEs compared to other inflammatory parameters such as the CAR (AUC = 0.64), the NLR (AUC = 0.64), and the AISI (AUC = 0.59). Adding the IPI to the baseline multivariable logistic regression model significantly improved the model’s discrimination and net clinical benefit effect for identifying patients who would suffer from MACCEs, with a C-index of 0.84 (95% CI: 0.82–0.86) and explanatory power of 23.2% (R² = 0.232, DeLong test p = 0.001). High-risk patients with an IPI value greater than 2.43 had significantly more adverse events (p < 0.001). Conclusions: The IPI may be a promising inflammatory index for use in clinical practice to determine the risk prediction of MACCEs in NSTEMI patients undergoing PCI. Full article

This paper proposes an improved random projection-based method for testing high-dimensional two-sample mean vectors and covariance matrices. For mean testing, the proposed approach incorporates training data to guide the construction of projection matrices toward the estimated mean difference, thereby substantially enhancing the power of the projected Hotelling’s $T^2$ statistic. We introduce three aggregation strategies—maximum, average, and percentile-based—to ensure stable performance across multiple projections. For covariance testing, the method employs data-driven projections aligned with the leading eigenvector of the sample covariance matrix to amplify the differences between matrices. Aggregation strategies—maximum-, average-, and percentile-based for the mean problem and minimum and average p-values for the covariance problem—are developed to further stabilize performance across repeated projections. An application to gene expression data is provided to illustrate the method. Extensive simulation studies show that the proposed method performs favorably compared to a recent state-of-the-art technique, particularly in detecting sparse signals, while maintaining control of the Type-I error rate. Full article

Quantitative ¹⁸F-FDG PET/CT-derived metabolic metrics are strongly associated with patient outcomes in diffuse large B-cell lymphoma (DLBCL), but the lack of consensus on optimal segmentation thresholds limits standardization. This study evaluated the prognostic value of various metabolic tumor volume (MTV) segmentation approaches in 140 stage II–IV DLBCL patients treated with standard immunochemotherapy. MTV was derived using fixed SUV (≥2.5, ≥4.0), relative (>41% SUVmax), and adaptive (liver-to-background) thresholds. Baseline MTV metrics significantly correlated with 3-year overall survival (OS3) in univariate analysis in overall cohort, with MTV41 showing the strongest association (HR: 1.27; p = 0.003). MTV25 and MTV41 remained significant in the stage 4 patient subgroup. However, in multivariate analysis, no MTV metric independently predicted OS3 when adjusted for the International Prognostic Index (IPI), which remained the dominant predictor (HR: 1.95; p < 0.0001). ROC analysis confirmed superior AUC for IPI (0.76) over PET-based metrics (0.64–0.69). Predictive models integrating IPI with PET metrics were robust but failed to improve prognostic accuracy beyond IPI alone. Although PET-derived MTV metrics provide prognostic value in univariate analysis, threshold selection has minimal impact, and their added value is limited when combined with IPI, reinforcing its role as the most reliable survival predictor in DLBCL. Full article

This article presents a comprehensive study of the (2+1)-dimensional Zakharov–Kuznetsov (ZK) $(q,p,r)$ equation with time fractional derivativeUtilizing the fractional Lie group method, we derive several results, including the symmetries, similarity reductions and conservation laws for this equation. Our findings not only correct previous errors in the literature but also introduce new results, such as the Lie transformation group and optimal system for this model. The study provides a rigorous mathematical framework for analyzing this fundamental model, which describes nonlinear ion-acoustic wave evolution in magnetized plasmas. Full article

Background and Objectives: The comparative efficacy and safety of nivolumab plus ipilimumab (Nivo-Ipi) combination therapy between patients with either postoperative recurrent non-small cell lung cancer (NSCLC) or inoperable stage III/IV NSCLC have yet to be conclusively determined. Materials and Methods: This retrospective study reviewed the medical records of consecutive patients diagnosed with either postoperative recurrent NSCLC or inoperable stage III/IV NSCLC. Both groups, referred to as the postoperative and inoperable cohorts respectively, underwent Nivo-Ipi therapy at four Japanese medical institutions between December 2020 and November 2022. The study’s primary aim was to evaluate and compare the efficacy and safety outcomes across these two groups. Results: A total of 161 patients received Nivo-Ipi therapy (postoperative group, n = 30; inoperable group, n = 131). The objective response rate was comparable between the postoperative and inoperable groups (36.7% vs. 32.1%, p = 0.67). Median progression-free survival did not differ significantly between groups (8.9 months vs. 6.5 months, p = 0.14). However, median overall survival was significantly longer in the postoperative group (not reached vs. 13.0 months, p = 0.012). The incidence of grade ≥ 3 adverse events in the postoperative group included lung injury (13.3%), liver dysfunction (10.0%), adrenal insufficiency (6.7%), and colitis (6.7%). No significant difference was observed in the frequency of grade ≥ 3 treatment-related adverse events between the groups, and no treatment-related deaths occurred in the postoperative group. Conclusions: Patients with postoperative recurrent NSCLC treated with Nivo-Ipi demonstrated significantly longer overall survival compared to those with inoperable NSCLC. Given its favorable efficacy and acceptable toxicity profile, postoperative recurrent disease may warrant consideration as a stratification factor in clinical trials for advanced NSCLC. Nivo-Ipi therapy could serve as a preferred first-line treatment option for patients with postoperative recurrent NSCLC. Full article

The virus-induced gene silencing (VIGS) technique can effectively inhibit systemic viral infection by down-regulating plant endogenous gene expression, and it has become an important tool to study plant gene function. However, few studies have reported that wheat dwarf virus (WDV), which enables high-throughput gene silencing, could be used in a rice VIGS system. In this study, a VIGS vector system was constructed based on WDV, and successfully silenced the Phytoene desaturase gene and the rice blast resistance gene Pi21 in rice. Pi21-silenced plants showed significantly increased resistance to rice blast, significantly reduced lesion area, and did not show high disease symptoms (grade 8–9). In addition, the WDV vector has the advantages of rapid infection, high proliferation, and an unconformity genome, and has little influence on rice growth and development. This study validates the effectiveness of the WDV-VIGS system in rice gene function studies and provides a new gene silencing tool for blast resistance breeding. Full article

Background/Objectives: Circulating tumor DNA (ctDNA) has emerged as a promising biomarker for non-invasive tumor monitoring in diffuse large B-cell lymphoma (DLBCL). Methods: In this study, 52 patients with newly diagnosed advanced-stage DLBCL treated with R-CHOP underwent serial ctDNA analysis at baseline, interim (after three cycles), and end of treatment. The prognostic significance of ctDNA dynamics was evaluated, and its predictive value was compared with the PET/CT response. Results: Targeted next-generation sequencing revealed baseline ctDNA in 98.1% of patients, with 74.7% concordance to tumor tissue genotyping. Higher baseline ctDNA levels correlated with elevated LDH, older age, and high IPI scores. A ≥2-log reduction in ctDNA at interim was significantly associated with improved overall survival (p = 0.004), though not with progression-free survival. Notably, combining interim ctDNA dynamics with PET/CT results enhanced the predictive accuracy for treatment outcomes, particularly among patients with partial metabolic responses. Conclusions: These findings support the clinical utility of ctDNA for dynamic risk assessment in DLBCL, and suggest that integrating ctDNA with imaging biomarkers may guide more personalized therapeutic strategies. Further validation using highly sensitive ctDNA assays is warranted to optimize its role in routine clinical practice. Full article

Quasi-two-dimensional (quasi-2D) perovskites have emerged as a transformative platform for high-efficiency perovskite light-emitting diodes (PeLEDs), benefiting from their tunable quantum confinement, high photoluminescence quantum yields (PLQYs), and self-assembled energy funneling mechanisms. This review systematically explores interfacial energy transfer engineering strategies that underpin advancements in device performance. By tailoring phase composition distributions, passivating defects via additive engineering, and optimizing charge transport layers, researchers have achieved external quantum efficiencies (EQEs) exceeding 20% in green and red PeLEDs. However, challenges persist in blue emission stability, efficiency roll-off at high currents, and long-term operational durability driven by spectral redshift, Auger recombination, and interfacial ion migration. Emerging solutions include dual-cation/halogen alloying for bandgap control, microcavity photon management, and insulator–perovskite–insulator (IPI) architectures to suppress leakage currents. Future progress hinges on interdisciplinary efforts in multifunctional material design, scalable fabrication, and mechanistic studies of carrier–photon interactions. Through these innovations, quasi-2D PeLEDs hold promise for next-generation displays and solid-state lighting, offering a cost-effective and efficient alternative to conventional technologies. Full article

This study incorporates the comprehensively observed proxies of in situ geotechnical, geophysical, petrophysical, and lithological datasets to estimate groundwater presence. Two machine-learning approaches, random forest regression (RFR) and deep neural network (DNN), are applied. The constructed RFR and DNN models are validated using observed depths of groundwater levels at 772 K-NET sites in Japan. The RFR model exhibited effectiveness and robust performance compared to the poor-fitting performance of the DNN model and previous groundwater detection physical-based approaches. The RFR and DNN models yielded a remarkable 1:1 agreement between the observed and predicted groundwater levels at 733 and 470 K-NET sites, respectively. During the RFR training process, all datasets at the 772 K-NET sites were split into training, validating, and unseen testing datasets with the ratio set at 1:1:11. This k-fold cross-validation strategy demonstrates better-fitting performance for the RFR model. The contributions and interactions among the in situ observed proxies utilizing the variance-based global sensitivity analyses can be understood. The P-wave velocity and the standard penetration test values have exhibited prominent contributions among other proxies at groundwater depths. To apply the RFR model at any given site, reliable and detailed P- and S-wave velocity structures are crucial to building the needed source datasets. Full article

Background: Limited data exist on primary palatine tonsil Non-Hodgkin lymphoma (NHL) from regions with constrained healthcare access. This study investigated this malignancy in Western and South-Western Romania, comparing lower-stage (Ann-Arbor I-III) and advanced-stage (IV) disease. Methods: A retrospective cohort study (2010–2019) at a tertiary referral hospital included 59 patients with primary palatine tonsil NHL. Data on demographics, clinical presentation, comorbidities (including viral hepatitis B/C), histology, International Prognostic Index (IPI) score, treatment, and outcomes were collected. Statistical comparisons between lower-stage (n = 26) and advanced-stage (n = 33) groups were performed. Results: A high proportion presented with advanced-stage disease (55.9%). The advanced-stage group had significantly more B symptoms (90.9% vs. 69.2%, p = 0.038) and elevated LDH levels (93.9% vs. 57.7%, p = 0.013). Viral hepatitis B and/or C infection was more frequent in advanced-stage disease (30.3% vs. 15.4%, p = 0.44). Combined chemoradiotherapy was more commonly used in lower-stage disease (38.46% vs. 12.12%, p = 0.019). There was no statistically significant difference in relapse rates between the groups. Conclusions: This study highlights the substantial burden of advanced-stage primary palatine tonsil NHL in Western Romania, suggesting a need for improved early detection. The association between viral hepatitis and advanced-stage, although not statistically significant, warrants further investigation. These findings may inform tailored management approaches in resource-constrained settings. Full article

The aim of almost every production firm is to gain maximum profit along with customer satisfaction. The formation of imperfect products is an obvious process in a production system, which is not a good thing from a business point of view. This paper considers an inventory model for an imperfect production system. All the imperfect products are assumed to be reworkable. An investment occurs for in-process inspection to reduce the rate of formation of imperfect items. A comparison is performed with a production system without in-process inspection to demonstrate the effectiveness of the model. The study shows that the implementation of in-process inspection significantly reduces the total cost of the system as compared to a production system without in-process inspection. The results obtained show that the use of in-process inspection can reduce the total cost by up to 9.3%. Moreover, reducing the formation of defective items saves energy as well as resources. In addition, to reduce carbon emissions, a penalty is implemented on carbon emissions caused by manufacturing, reworking, disposal, and indirect emissions caused by the transportation of disposed items to the treatment facility. As everyone should now be concerned about the environment, green technology is implemented to reduce the amount of carbon emissions to some extent. A classical optimization technique is used to achieve decision variables, i.e., optimal production quantity (Q), fraction of profit invested in in-process inspection ($P_f$), and green technology investment (G), such that the total cost of the system is minimized. A sensitivity analysis is performed to determine the effects of various parameters on the decision variables and total cost. Maple 18 and Mathematica 11 software are used for mathematical work and graphical representation. Full article