Understanding of Wetting Mechanism Toward the Sticky Powder and Machine Learning in Predicting Granule Size Distribution Under High Shear Wet Granulation.

The granulation of traditional Chinese medicine (TCM) has attracted widespread attention, there is limited research on the high shear wet granulation (HSWG) and wetting mechanisms of sticky TCM powders, which profoundly impact the granule size distribution (GSD). Here we investigate the wetting mechanism of binders and the influence of various parameters on the GSD of HSWG and establish a GSD prediction model. Permeability and contact angle experiments combined with molecular dynamics (MD) simulations were used to explore the wetting mechanism of hydroalcoholic solutions with TCM powder. Machine learning (ML) was employed to build a GSD prediction model, feature importance explained the influence of features on the predictive performance of the model, and correlation analysis was used to assess the influence of various parameters on GSD. The results show that water increases powder viscosity, forming high-viscosity aggregates, while ethanol primarily acted as a wetting agent. The contact angle of water on the powder bed was the largest and decreased with an increase in ethanol concentration. Extreme Gradient Boosting (XGBoost) outperformed other models in overall prediction accuracy in GSD prediction, the binder had the greatest impact on the predictions and GSD, adjusting the amount and concentration of adhesive can control the adhesion and growth of granules while the impeller speed had the least influence on granulation. The study elucidates the wetting mechanism and provides a GSD prediction model, along with the impact of material properties, formulation, and process parameters obtained, aiding the intelligent manufacturing and formulation development of TMC.

Cocrystal Prediction of Nifedipine Based on the Graph Neural Network and Molecular Electrostatic Potential Surface.

Nifedipine (NIF) is a dihydropyridine calcium channel blocker primarily used to treat conditions such as hypertension and angina. However, its low solubility and low bioavailability limit its effectiveness in clinical practice. Here, we developed a cocrystal prediction model based on Graph Neural Networks (CocrystalGNN) for the screening of cocrystals with NIF. And scoring 50 coformers using CocrystalGNN. To validate the reliability of the model, we used another prediction method, Molecular Electrostatic Potential Surface (MEPS), to verify the prediction results. Subsequently, we performed a second validation using experiments. The results indicate that our model achieved high performance. Ultimately, cocrystals of NIF were successfully obtained and all cocrystals exhibited better solubility and dissolution characteristics compared to the parent drug. This study lays a solid foundation for combining virtual prediction with experimental screening to discover novel water-insoluble drug cocrystals.

Evolution characteristics of micromechanics provides insights into the microstructure of pharmaceutical tablets fabricated by bimodal mixtures.

This research focuses on the evolution of mechanical behavior of bimodal mixtures undergoing compaction and diametrical compression. The clusters were built and discrete element method (DEM) was used to investigate the densification process and micromechanics of bimodal mixtures. Additionally, a more comprehensive investigate of the respective breakage of the bimodal mixtures has been carried out. On this basis, qualitative and quantitative analysis of the compressive force, force chain, contact bonds and density field evolution characteristics of the clusters are investigated during the compression process. The entire loading process of the clusters is divided into three stages: rearrangement, breakage and elastic-plastic deformation. Additionally, there are differences in the evolution of micromechanics behavior of different particles in the bimodal mixture, with pregelatinized starch breakage and deformation occurring before microcrystalline cellulose. With the tablet deformation, the fragmentation process of the tablet started at the point of contact and extended toward the center, and the curvature of the force chain increased. This approach may potentially hold a valuable new information relevant to important transformation forms batch manufacturing to advanced manufacturing for the oral solid dosage form.

A new methodology of understanding the mechanism of high shear wet granulation based on experiment and molecular dynamics simulation.

In high shear wet granulation (HSWG), the interaction mechanism between binder and powder with different sugar content is still unclear. Herein, the law and mechanism of the interaction between binder and powder were studied on the molecular level by combining experiment analysis through the Kriging model and molecular dynamics (MD) simulation. For the sticky powder with high sugar content, the ethanol in the binder played a pivotal role in dispersing water into powders, and the amount of water determined the growth of granules. In the saturating stage, the reduction of sugar content facilitates the penetration of ethanol molecules. The concentration of ethanol determines whether the mixture is blended uniformly in the merging stage. The simulation results are consistent with the actual situation and explain the competition mechanism of interaction with binder and powder. Therefore, this research offers an efficient strategy for the in-depth understanding of the HSWG process where the powder is sticky, as well as providing guidelines for the practical application of preparation for Traditional Chinese Medicine (TCM) granules.

Transforming growth factor-ß-Expressing Mesenchymal Stem Cells Induce Local Tolerance in a Rat Liver Transplantation Model of Acute Rejection.

Acute rejection is commonly encountered for long-term survival in liver transplant (LT) recipients and may impact their long-term survival if rejection is severe or recurrent. The aim of this study is to examine the therapeutic potential of transforming growth factor (TGF-ß)-overexpressing mesenchymal stem cells (MSCs) in inducing a local immunosuppression in liver grafts after transplantation. MSCs were transduced with a lentiviral vector expressing the human TGF-ß1 gene; TGF-ß1-overexpressing MSCs (designated as TGF/MSCs) were then transfused into the liver grafts via the portal vein of a rat LT model of acute rejection. Rejection severity was assessed by clinical and histologic analysis. The immunity suppression effects and mechanism of TGF/MSCs were tested, focusing on their ability to induce generation of regulatory T cells (Tregs) in the liver grafts. Our findings demonstrate that transfusion of TGF/MSCs prevented rejection, reduced mortality, and improved survival of rats after LT. The therapeutic effects were associated with the immunosuppressive effects of MSCs and TGF-ß1. Their reciprocal effects on Tregs induction and function resulted in more CD4 + Foxp3 + Helios- induced Tregs, fewer Th17 cells, and improved immunosuppressive effects in local liver grafts. Thus, TGF/MSCs can induce a local immunosuppressive effect in liver grafts after transplantation. The immunomodulatory activity of TGF-ß1 modified MSCs may be a gateway to new therapeutic approaches to prevent organ rejection in clinical transplantation. Stem Cells 2016;34:2681-2692.

Remote ischemic preconditioning promotes early liver cell proliferation in a rat model of small-for-size liver transplantation.

BACKGROUND: The size of the liver donor graft is a major concern in living donor liver transplantation. Rapid regeneration is essential for the survival of these grafts. The purpose of this study was to investigate the effect of remote ischemic preconditioning (RIPC) on liver regeneration in a rat small-for-size liver transplantation model. METHODS: We established rat models of small-for-size liver transplantation (30%) in the presence or absence (control) of remote ischemic preconditioning. We observed liver mass regeneration, serum alanine aminotransferase, hepatic pathologic alterations, flow cytometry, and Ki-67 antigen immunohistochemistry. In addition, using Western blotting and reverse-transcriptase-polymerase chain reaction, we assessed the activation of cell cycle progression as well as tumor necrosis factor-α and interleukin-6 expression. RESULTS: Compared with the control group, serum alanine aminotransferase activity was significantly lower and histopathology changes were significantly attenuated in the RIPC group. Remote ischemic preconditioning induced a high level of interleukin-6 mRNA in small grafts, but suppressed the expression of tumor necrosis factor-α. The proliferation index, indicated by the S-phase and G2/M-phase ratio [(S+G2/M)/(G0/G1+S+G2/M)], was significantly increased in the RIPC group at 24 h (58.25% ± 0.506% versus 53.405% ± 1.25%; P = .007). Meanwhile, cell cycle progression and regeneration (Ki-67) were initiated early in liver grafts treated with RIPC. CONCLUSIONS: These results suggest that RIPC can protect liver cells against ischemia reperfusion injury in the small grafts and enhance liver regeneration. Interleukin-6 may be a critical mediator in the stimulatory effect on liver cell regeneration, which may make RIPC valuable as a hepatoprotective modality.

Comparative proteomic profiling of human bile reveals SSP411 as a novel biomarker of cholangiocarcinoma.

BACKGROUND: Cholangiocarcinoma (CC) is an intractable cancer, arising from biliary epithelial cells, which has a poor prognosis and is increasing in incidence. Early diagnosis of CC is essential as surgical resection remains the only effective therapy. The purpose of this study was to identify improved biomarkers to facilitate early diagnosis and prognostication in CC. METHODS: A comparative expression profile of human bile samples from patients with cholangitis and CC was constructed using a classic 2D/MS/MS strategy and the expression of selected proteins was confirmed by Western blotting. Immunohistochemistry was performed to determine the expression levels of selected candidate biomarkers in CC and matched normal tissues. Finally, spermatogenesis associated 20 (SSP411; also named SPATA20) was quantified in serum samples using an ELISA. RESULTS: We identified 97 differentially expressed protein spots, corresponding to 49 different genes, of which 38 were upregulated in bile from CC patients. Western blotting confirmed that phosphoglycerate mutase 1 (brain) (PGAM-1), protein disulfide isomerase family A, member 3 (PDIA3), heat shock 60 kDa protein 1 (chaperonin) (HSPD1) and SSP411 were significantly upregulated in individual bile samples from CC patients. Immunohistochemistry demonstrated these proteins were also overexpressed in CC, relative to normal tissues. SSP411 displayed value as a potential serum diagnostic biomarker for CC, with a sensitivity of 90.0% and specificity of 83.3% at a cutoff value of 0.63. CONCLUSIONS: We successfully constructed a proteomic profile of CC bile proteins, providing a valuable pool novel of candidate biomarkers. SSP411 has potential as a biomarker for the diagnosis of CC.