Formulation and Characterization of Triamcinolone Acetonide Acetate-Loaded Microspheres Prepared by a Static Mixing Technique.

PURPOSE: Reproducibility and scale-up production of microspheres through spray drying present significant challenges. In this study, biodegradable microspheres of Triamcinolone Acetonide Acetate (TAA) were prepared using a novel static mixing method by employing poly( lactic-co-glycolic acid) (PLGA) as the sustained-release carrier. METHODS: TAA-loaded microspheres (TAA-MSs) were prepared using a static mixing technique. The PLGA concentration, polyvinyl alcohol concentration (PVA), phase ratio of oil/water, and phase ratio of water/solidification were optimized in terms of the particle size, drug loading (DL), and encapsulation efficiency (EE) of TAA-MSs. The morphology of TAA-MSs was examined using Scanning Electron Microscopy (SEM), while the physicochemical properties were evaluated through X-ray diffraction (XRD), Differential Scanning Calorimetry (DSC), and Fourier Transform Infrared Spectroscopy (FT-IR). The in vitro release of TAA-MSs was compared to that of the pure drug (TAA) using a water-bath vibration method in the medium of pH 7.4 at 37°C. RESULTS: The formulation composition and preparation condition for the preparation of TAA-MSs were optimized as follows: the PLGA concentration was 1%, the phase ratio of oil(dichloromethane) /water (PVA solution) was 1:3, the phase ratio of water (PVA solution)/solidification was 1:2. The optimized TAA-MSs displayed spherical particles with a size range of 30-70 µm, and DL and EE values of 27.09% and 98.67%, respectively. Moreover, the drug-loaded microspheres exhibited a significant, sustained release, with 20% of the drug released over a period of 28 days. The XRD result indicated that the crystalline form of TAA in microspheres had been partly converted into the amorphous form. DSC and FT-IR results revealed that some interactions between TAA and PLGA occurred, indicating that the drug was effectively encapsulated into PLGA microspheres. CONCLUSION: TAA-loaded PLGA microspheres have been successfully prepared via the static mixing technique with enhanced EE and sustained-release manner.

Crafting Docetaxel-Loaded Albumin Nanoparticles Through a Novel Thermal-Driven Self-Assembly/Microfluidic Combination Technology: Formulation, Process Optimization, Stability, and Bioavailability.

Background: The commercial docetaxel (DTX) formulation causes severe side effects due to polysorbate 80 and ethanol. Novel surfactant-free nanoparticle (NP) systems are needed to improve bioavailability and reduce side effects. However, controlling the particle size and stability of NPs and improving the batch-to-batch variation are the major challenges. Methods: DTX-loaded bovine serum albumin nanoparticles (DTX-BSA-NPs) were prepared by a novel thermal-driven self-assembly/microfluidic technology. Single-factor analysis and orthogonal test were conducted to obtain the optimal formulation of DTX-BSA-NPs in terms of particle size, encapsulation efficiency (EE), and drug loading (DL). The effects of oil/water flow rate and pump pressure on the particle size, EE, and DL were investigated to optimize the preparation process of DTX-BSA-NPs. The drug release, physicochemical properties, stability, and pharmacokinetics of NPs were evaluated. Results: The optimized DTX-BSA-NPs were uniform, with a particle size of 118.30 nm, EE of 89.04%, and DL of 8.27%. They showed a sustained release of 70% over 96 hours and an increased stability. There were some interactions between the drug and excipients in DTX-BSA-NPs. The half-life, mean residence time, and area under the curve (AUC) of DTX-BSA-NPs increased, but plasma clearance decreased when compared with DTX. Conclusion: The thermal-driven self-assembly/microfluidic combination method effectively produces BSA-based NPs that improve the bioavailability and stability of DTX, offering a promising alternative to traditional formulations.

Development of Polyvinyl Alcohol/Polyethylene Glycol Copolymer-based Orodispersible Films Loaded with Entecavir: Formulation and In vitro Characterization.

PURPOSE: The aim of the study is to prepare entecavir (ETV)-loaded orodispersible films (ODFs) using polyvinyl alcohol (PVA)/polyethylene glycol (PEG) graft copolymer (Kollicoat® IR) as a film-forming agent, and further to evaluate the dissolution rate, mechanical and physicochemical properties of films. METHODS: ETV-ODFs were prepared by a solvent casting method. The amount of film-forming agent, plasticizer, and disintegrating agent was optimized in terms of the appearance, thickness, disintegration time and mechanical properties of ODFs. The compatibility between the drug and each excipient was conducted under high temperature (60 °C), high humidity (RH 92.5%), and strong light (4500 Lx) for 10 days. The dissolution study of optimal ODFs compared with the original commercial tablet (Baraclude®) was performed using a paddle method in pH 1.0, pH 4.5, pH 6.8, and pH 7.4 media at 37 °C. The morphology of ODFs was observed via scanning electron microscopy (SEM). The mechanical properties such as tensile strength (TS), elastic modulus (EM), and percentage elongation (E%) of ODFs were evaluated using the universal testing machine. The physicochemical properties of ODFs investigated using X-ray diffraction (XRD), differential scanning calorimetry (DSC), and Fourier transform infrared spectroscopy (FT-IR). RESULTS: The related substances were less than 0.5% under high temperature, high humidity, and strong light for 10 days when ETV was mixed with excipients. The optimal formulation of ODFs was set as the quality ratio of Kollicoat® IR, glycerol, sodium alginate (ALG-Na): TiO2: MCC+CMC-Na: ETV was 60:9:12:1:1:1. The drug-loaded ODFs were white and translucent with excellent stripping property. The thickness, disintegration time, EM, TS, and E% were 103.33±7.02 µm, 25.31±1.95 s, 25.34±8.69 Mpa, 2.14±0.26 Mpa, and 65.45±19.41 %, respectively. The cumulative drug release from ODFs was more than 90% in four different media at 10 min. The SEM showed that the drug was highly dispersible in ODFs, and the XRD, DSC, and FT-IR results showed that there occurred some interactions between the drug and excipients. CONCLUSION: In conclusion, the developed ETV-loaded ODFs showed relatively short disintegration time, rapid drug dissolution, and excellent mechanical properties. This might be an alternative to conventional ETV Tablets for the treatment of chronic hepatitis B.

Deep learning-based solution for smart contract vulnerabilities detection.

This paper aims to explore the application of deep learning in smart contract vulnerabilities detection. Smart contracts are an essential part of blockchain technology and are crucial for developing decentralized applications. However, smart contract vulnerabilities can cause financial losses and system crashes. Static analysis tools are frequently used to detect vulnerabilities in smart contracts, but they often result in false positives and false negatives because of their high reliance on predefined rules and lack of semantic analysis capabilities. Furthermore, these predefined rules quickly become obsolete and fail to adapt or generalize to new data. In contrast, deep learning methods do not require predefined detection rules and can learn the features of vulnerabilities during the training process. In this paper, we introduce a solution called Lightning Cat which is based on deep learning techniques. We train three deep learning models for detecting vulnerabilities in smart contract: Optimized-CodeBERT, Optimized-LSTM, and Optimized-CNN. Experimental results show that, in the Lightning Cat we propose, Optimized-CodeBERT model surpasses other methods, achieving an f1-score of 93.53%. To precisely extract vulnerability features, we acquire segments of vulnerable code functions to retain critical vulnerability features. Using the CodeBERT pre-training model for data preprocessing, we could capture the syntax and semantics of the code more accurately. To demonstrate the feasibility of our proposed solution, we evaluate its performance using the SolidiFI-benchmark dataset, which consists of 9369 vulnerable contracts injected with vulnerabilities from seven different types.

Machine Learning-Based Prognostic Model for Patients After Lung Transplantation.

Importance: Although numerous prognostic factors have been found for patients after lung transplantation (LTx) over the years, an accurate prognostic tool for LTx recipients remains unavailable. Objective: To develop and validate a prognostic model for predicting overall survival in patients after LTx using random survival forests (RSF), a machine learning algorithm. Design, Setting, and Participants: This retrospective prognostic study included patients who underwent LTx between January 2017 and December 2020. The LTx recipients were randomly assigned to training and test sets in accordance with a ratio of 7:3. Feature selection was performed using variable importance with bootstrapping resampling. The prognostic model was fitted using the RSF algorithm, and a Cox regression model was set as a benchmark. The integrated area under the curve (iAUC) and integrated Brier score (iBS) were applied to assess model performance in the test set. Data were analyzed from January 2017 to December 2019. Main Outcomes And Measures: Overall survival in patients after LTx. Results: A total of 504 patients were eligible for this study, consisting of 353 patients in the training set (mean [SD] age, 55.03 [12.78] years; 235 [66.6%] male patients) and 151 patients in the test set (mean [SD] age, 56.79 [10.95] years; 99 [65.6%] male patients). According to the variable importance of each factor, 16 were selected for the final RSF model, and postoperative extracorporeal membrane oxygenation time was identified as the most valuable factor. The RSF model had excellent performance with an iAUC of 0.879 (95% CI, 0.832-0.921) and an iBS of 0.130 (95% CI, 0.106-0.154). The Cox regression model fitted by the same modeling factors to the RSF model was significantly inferior to the RSF model with an iAUC of 0.658 (95% CI, 0.572-0.747; P < .001) and an iBS of 0.205 (95% CI, 0.176-0.233; P < .001). According to the RSF model predictions, the patients after LTx were stratified into 2 prognostic groups displaying significant difference, with mean overall survival of 52.91 months (95% CI, 48.51-57.32) and 14.83 months (95% CI, 9.44-20.22; log-rank P < .001), respectively. Conclusions and relevance: In this prognostic study, the findings first demonstrated that RSF could provide more accurate overall survival prediction and remarkable prognostic stratification than the Cox regression model for patients after LTx.

Diagnosis of complication in lung transplantation by TBLB + ROSE + mNGS.

Lung transplantation is a potentially life-saving therapy for patients with terminal respiratory illnesses. Long-term survival is limited by the development of a variety of opportunistic infections and rejection. Optimal means of differential diagnosis of infection and rejection have not been established. With these challenges in mind, we tried to use transbronchial lung biopsy (TBLB) rapid on-site cytological evaluation (ROSE), metagenomic next-generation sequencing (mNGS), and routine histologic examination to timely distinguish infection and rejection, and accurately detect etiologic pathogens. We reviewed the medical records of all patients diagnosed with infection or rejection by these means from December 2017 to September 2018 in our center. We identified seven recipients whose clinical course was complicated by infection or rejection. Three patients were diagnosed with acute rejection, organizing pneumonia, and acute fibrinoid organizing pneumonia, respectively. Four of the seven patients were diagnosed with infections, including Pneumocystis carinii pneumonia, cytomegalovirus, Aspergillus, and bacterial pneumonia. These patients recovered after proper treatment. TBLB + ROSE + mNGS might be a good method to accurately detect etiologic pathogens, which may help us to facilitate the use of targeted and precision medicine therapy in postoperative complications and avoid unnecessary potential adverse effects of drugs.

Population pharmacokinetics and dosing regimen optimization of tacrolimus in Chinese lung transplant recipients.

We aimed to (i) develop a population pharmacokinetic model of tacrolimus in Chinese lung transplant recipients and (ii) propose model-based dosing regimens for individualized treatment. We obtained 807 tacrolimus steady-state whole blood concentrations from 52 lung transplant patients and genotyped CYP3A5*3. Population pharmacokinetic analysis was performed using nonlinear mixed-effects modeling. Monte Carlo simulations were employed to determine the initial dosing regimens. Tacrolimus pharmacokinetics was described by a one-compartment model with first-order absorption and elimination processes. In CYP3A5*3/*3 70-kg patients with 30% hematocrit and voriconazole-free therapy, the mean estimated apparent clearance was 13.1 l h-1 with 20.1% between-subject variability, which was lower than that in Caucasian lung transplant patients (17.5-36.5 l h-1). Hematocrit, postoperative days, tacrolimus daily dose, voriconazole concomitant therapy, and CYP3A5*3 genotype were identified as significant covariates for tacrolimus clearance. To achieve target trough concentration (10-15 ng ml-1) on the 8th day post-transplant, a higher initial dosage than the current regimen of 0.04 mg kg-1 every 12 h is recommended for CYP3A5*1/*3 patients without voriconazole concomitant therapy. Given the nonlinear kinetics of tacrolimus and large variability, population pharmacokinetic model should be combined with therapeutic drug monitoring to optimize individualized therapy.

Intrabronchial display of hilar-mediastinal lymph nodes by virtual bronchoscopic navigation system.

The description of precise intrabronchial positions for the sampling of mediastinal-hilar lymph nodes is critical to successfully perform conventional transbronchial needle aspiration. Previously published maps of mediastinal-hilar lymph nodes were primarily drawn based on experts' experience. We generated a virtual map of the most frequently sampled intrathoracic lymph nodes from an intrabronchial perspective using a virtual bronchoscopic navigation system, to assist with training in conventional transbronchial needle aspiration.

NOGO-B promotes EMT in lung fibrosis via MMP14 mediates free TGF-beta1 formation.

Idiopathic pulmonary fibrosis (IPF) is a lung disease with an extremely poor prognosis. Epithelial mesenchymal transition (EMT) appearing on the airway epithelial cell plays an essential role in the formation and development of Idiopathic pulmonary fibrosis. In this paper, Bleomycin (BLM)-induced mice model combined with bioinformatics analysis were employed to elucidate the potential mechanism of EMT in pulmonary fibrosis. The obtained results showed that endoplasmic reticulum protein Nogo-b may promote MMP14-mediated proprotein maturation of TGF-ß1, accelerating the release of free TGF-ß1 in type II airway epithelial cells A549, subsquently, induce the epithelial-mesenchymal transition (EMT) of the cell. In all, the overexpression of Nogo-b play a role in the course of pulmonary fibrosis by influencing the EMT ability of cells.

Protective effects of astragaloside IV against ovalbumin-induced lung inflammation are regulated/mediated by T-bet/GATA-3.

Bronchial asthma is characterized by chronic lung inflammation, airway hyperresponsiveness, and airway remodelling. Astragaloside IV (3-O-ß-D-xylopyranosyl-6-O-ß-D-glucopyranosyl-cycloastragenol, AST), the primary pure saponin isolated from the root of Astragalus membranaceus, is an effective compound with distinct pharmacological effects including anti-inflammation, immunoregulation, and antifibrosis. However, the effect of AST on asthma remains unclear. In the present study, in the murine model of asthma, the airway hyperresponsiveness was relieved after treatment with AST, accompanied by a reduction of inflammatory cells. In addition, the levels of IL-4 and IL-5 decreased, while the IFN-γ level increased, in bronchoalveolar lavage fluid. The compound also significantly inhibited the synthesis of GATA-3-encoding mRNA and protein in addition to increasing the synthesis of T-bet-encoding mRNA and protein in both lung tissues and CD4+ T cells. Our findings indicate that AST treatment inhibits ovalbumin-induced airway inflammation by modulating the key master switches GATA-3 and T-bet, which results in committing T helper cells to a Th1 phenotype.