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Activated eosinophil plays a role in promoting fibrosis in endometriotic lesion
Profiling of the microRNA transcriptome in feline whole blood
Abstract Circulating microRNAs (miRNAs) are potential biomarkers for numerous diseases. Characterization of the whole blood (WB) miRNA-transcriptome (miRNome) in cats is lacking, which limits the potential use of miRNAs as biomarkers for diseases such as feline cardiovascular disease. The aims of the present study were to profile and evaluate circulating miRNAs in feline WB by high-throughput sequencing of the total miRNome in WB from twelve domestic mixed breed (DOM) and Norwegian Forest (NFO) cats stringently diagnosed with or without preclinical hypertrophic cardiomyopathy (HCM). A total of 459 mature miRNAs were identified in feline WB, of which 40 were potential novel feline miRNAs. A majority, 85.3%, of the miRNAs showed sequence similarity with human miRNAs. An effect of breed was found, with up to thirteen WB miRNAs being differentially abundant between breeds. The majority of the significant breed-specific miRNAs in feline WB could be associated with regulation of haematopoietic cells. One miRNA, miR-204-5p, was potentially associated with preclinical HCM in NFO cats, but the results need to be confirmed in a larger and sex-unbiased cohort. In conclusion, here we used miRNome-sequencing to identify hundreds of circulating miRNAs in feline WB. Breed should be considered when evaluating the miRNome in feline WB.
BSVA: blockchain-enabled secured vertical aggregation algorithm for transactions management in drug traceability framework
Abstract The pharmaceutical supply chain has a critical component, the Drug Traceability System, which tracks drugs from manufacturers for further processing and distribution. The integration of blockchain technology yields a secure solution for monitoring drugs throughout the supply chain management process. The paper proposes a novel Blockchain-enabled Secured Vertical Aggregation Algorithm (BSVA) by leveraging the Hyperledger model. The proposed model minimizes the requirement for a centralized authority to ensure privacy while also enhancing scalability to reduce response time in the process of managing transactions on the Blockchain. The Certificate Authority is used to maintain a secure data-sharing process. The robust aggregation is used for the local models to process the chain code, ensuring the successful execution of the secured transaction. The smart contract is deployed into a blockchain model as the block is stored and linked to the distributed Ledger. The decentralized framework is used by chain code, which guarantees that transactions are highly transparency. The performance parameters demonstrate the efficiency of the proposed model by enhancing the overall performance of the drug traceability system, as the proposed algorithm ensures the integrity of pharmaceutical products throughout the supply chain.
Dual prompt personalized federated learning in foundation models
Deciphering anti-colorectal cancer potential of Avicennia alba bioactives via network pharmacology and in vitro validation
Publisher Correction: Targeting GRPR for sex hormone-dependent cancer after loss of E-cadherin
Temperature and AC electrical properties effects on phosphate natural mixture, Abu Tartur plateau, Western Desert, Egypt
Abstract The research is focused on examining electrical properties (conductivity and dielectric constant), mineralogy, and geochemical behaviors of natural phosphate mixtures, Abu Tartur plateau, Western Desert Egypt. Abu Tartur plateau has a rich supply of phosphorus deposits. Phosphate deposits mostly consist of fluorapatite (Ca 5 (PO 4 ) 3 F). Our objective is to evaluate the changes in AC electrical properties, emphasizing the effects of temperature, and frequency variations. Electrical properties expand with temperature due to greater mobility of charge carriers at higher frequencies and at higher temperatures. Electrical characteristics were subjected to a temperature range of 60–700 0 C and frequencies of 42 Hz–5 MHz. Electrical properties of phosphate mixtures have a non-linear association with temperature and are highly dependent on frequency. As temperature rises, the conductivity of the mixture also increases, as evidenced by the temperature coefficient. The completion of these investigations will lead to a greater understanding of the geological and geochemical processes that lead to phosphate formation deposits, as well as the development of more effective industrial methods and material attributes. Temperature and conductivity are connected because dissolved ions increase both temperature and conductivity. Both conductivity and temperature are influenced by dissolved ions, hence they are coupled. Heterogeneity fluctuation can have a significant impact on the electrical characteristics of materials. Due to heterogeneity, the change in electrical characteristics is not monotonically affected by increasing conductor concentration. Presence of electrical features becomes more noticeable as temperature concentration increases. AC electrical conductivity of a phosphate natural combination from Abu Tartur and its fluctuation with temperature is inadequate and this work seeks to close this information gap.
Predicting pathological response of resectable esophageal squamous cell carcinoma to neoadjuvant anti-PD-1 with chemotherapy using serum inflammation indexes
Abstract Background Inflammatory indexes are increasingly being considered to predict treatment response in tumors. This study aimed to investigate the efficacy of serum inflammatory indexes in predicting pathological response in patients with esophageal squamous cell carcinoma (ESCC) receiving anti-PD-1 neoadjuvant immunochemotherapy (NICT). Methods We retrospectively collected clinical and laboratory data from 116 ESCC patients who received NICT. We set three outcome variables: pathologic complete response (PCR), good response (GR), and response (R). We assessed between-group differences in inflammation indexes and their diagnostic efficacy. Independent diagnostic markers were filtered using least absolute shrinkage and selection operator (LASSO) logistic regression and multivariable analysis, and the corresponding nomograms for PCR and GR were constructed, respectively. Receiver operating characteristic curves (ROC) and calibration curves assessed the efficiency and accuracy of the models. Decision curve analysis (DCA) and clinical impact curves (CIC) evaluated the clinical value. Moreover, we internally validated the predictive model with a random sample of 30% of patients. Results The prognostic nutritional index (PNI) predicted a cutoff value of 53.585 for PCR with an area under curve (AUC) value of 0.720, a cutoff value of 47.85 for GR with an AUC of 0.723, a cutoff value of 47.85 for R with an AUC of 0.629. Smoking and PNI were independent predictors of PCR, platelet-to-lymphocyte ratio (PLR) and PNI were independent predictors of GR, and PNI was an independent predictor of R. We built PNI-based nomograms to predict PCR and GR with AUC values of 0.795 and 0.763 for the training cohort and 0.907 and 0.757 for the validation cohort, respectively. The predicted and actual results of the calibration curves for both the training and validation groups showed good agreement, with Brier scores below 0.25. Conclusion High PNI value is a shared independent predictor of achieving PCR, GR, and R in ESCC patients receiving anti-PD1 NICT. PNI-based diagnostic models can be used as a practical tool to identify ideal patients for personalized clinical decisions.
Biochemical characterization of a novel purified lectin extracted from Pleurotus ostreatus mushroom for its antiviral activity
Abstract Viruses are responsible for numerous serious outbreaks and pandemics worldwide. In this context, lectins, which are carbohydrate-binding proteins, have garnered attention due to their antiviral properties against RNA and DNA viruses. The antiviral potential of the purified and well-characterized lectin from Pleurotus ostreatus (POL) was assessed against various viruses. POL showed potent antiviral activity against HCV with IC50 values of 68.75 nM and 52.13 nM for determining the blocking and neutralizing infectivity, respectively. POL exhibited IC50 values of 42.75 and 14.88 nM against HBV through treatment and blocking mechanisms, respectively. Notably, POL demonstrated a 58.80% binding capacity to cell-surface CD81, while the IC50 values for targeting the scavenger receptor class B-type I (SR-B1), HCV-NS3/4A protease inhibition, and anti-HBV polymerase activity were established at 10.08, 10.98, and 4.22 nM, respectively. The outcomes of this investigation offer crucial insights into the mechanisms through which POL effectively inhibits infection caused by different viruses. These findings have the potential to inform the development of antiviral strategies and therapeutic interventions.
Assessment of salt-affected soil extent and spatial variability using GIS and remote sensing in Asaita district, Northeastern Ethiopia
DNA lipid nanoparticles as alcohol-sensitive surrogates to trace microbial transmission and monitor hand hygiene
Abstract Understanding the transmission routes of microbial pathogens is essential for infection prevention and control in healthcare settings. However, using infectious microorganisms to this end is challenging and poses potential risks. We explored alcohol-sensitive DNA-encapsulating lipid nanoparticles (LNP) as surrogate tracers to investigate microbial transmission, including the effect of hand hygiene. LNPs embedded in various synthetic matrices were evaluated under controlled laboratory conditions to identify the optimal formulation. The chosen LNP glycerine and sucrose formulation was subsequently tested in patient care experiments, both with and without hand hygiene conducted according to established standards using alcohol-based hand rub (ABHR). Predefined contact surfaces and body sites were sampled and analysed for LNP integrity through quantitative polymerase chain reaction. The study revealed that the LNP formulation remained stable when dried on a surface. Hand hygiene using ABHR reduced LNP integrity to ≤ 1%. Without hand hygiene, LNPs transferred between surfaces maintained nearly 100% integrity. However, stability decreased during skin-to-skin transfer. In a typical patient care interaction, the study LNP formulation demonstrated a rapid, low-risk, and reliable approach for evaluating short pathogen transmission pathways, including the impact of hand hygiene. It shows promise as a diagnostic tool for assessing the effectiveness of transmission prevention measures in real-life clinical settings.
Marginal adaptation of heat and non-heat compatible bioceramic sealers in warm obturation: an in vitro SEM study
Reduced butyrate-producing bacteria and altered metabolic pathways in the gut microbiome of immunoglobulin A nephropathy patients
Abstract Gut-associated lymphoid tissue is central to the production of galactose-deficient IgA1 (Gd-IgA1), a key factor in immunoglobulin A nephropathy (IgAN). Although no major differences in gut microbiome diversity have been reported across IgAN cohorts, functional alterations in microbial composition may contribute to disease pathogenesis. The study was designed as a cross-sectional study with an embedded prospective cohort component. Forty-eight adults with biopsy-confirmed IgAN—categorized as progressors (eGFR decline > 5 ml/min/1.73 m²/year, n = 23) or nonprogressors (n = 23)—and 23 healthy controls (HC) were recruited. Stool samples underwent metagenomic and functional profiling. Alpha diversity did not differ significantly between IgAN patients and HC. However, butyrate-producing bacteria (Butyrococcus, Agathobacter rectalis) were less abundant in IgAN patients. The sulfoquinovose degradation I pathway, associated with these bacteria, was also reduced. Nucleotide- and nucleoside-biosynthesis pathways were elevated in IgAN. Gd-IgA1 levels correlated with variations in metabolic pathways. Progressors demonstrated enhanced activity in isopropanol biosynthesis, biotin biosynthesis II, and phospholipid biosynthesis pathways. IgAN patients show reduced butyrate-producing bacteria and distinct functional changes in the gut microbiome suggestive of immune activation and inflammation. Progressors exhibit additional metabolic shifts linked to bacterial membrane stabilization.
Temperature analysis and ampacity evaluation of HV cable joints based on thermal flow coupling and measurable data
Graph theoretic and machine learning approaches in molecular property prediction of bladder cancer therapeutics
Abstract This work introduces a hybrid computational approach in which degree-based topological descriptors are harnessed with the aid of advanced regression models and artificial neural networks (ANNs) to predict the crucial physicochemical properties of 17 drugs for the treatment of bladder cancer. Each molecule is assigned a molecular graph, from which a series of topological descriptors such as Zagreb indices, Randic index, Atom Bond Connectivity (ABC), and Symmetric Division Degree (SSD)are computed. These indices are used as input features by various regression models along with linear, cubic, and feedforward ANNs. The performance of the models is analyzed using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and the coefficient of determination $$(R^2)$$ . ANNs showed the best predictive performance with the $$R^2$$ value achieving 0.99. Moreover, SHAP (SHapley Additive exPlanations) analysis was used to explain the contribution of each descriptor toward the models’ predictions. The findings validate the promise of the combination of graph-theoretic descriptors with the tools of machine learning to achieve solid and interpretable models of molecular property prediction, which hold the potential for drug discovery and optimization in oncologic applications.