The osteogenesis of Ginsenoside Rb1 incorporated silk/micro-nano hydroxyapatite/sodium alginate composite scaffolds for calvarial defect

Ginsenoside Rb1, the effective constituent of ginseng, has been demonstrated to play favorable roles in improving the immunity system. However, there is little study on the osteogenesis and angiogenesis effect of Ginsenoside Rb1. Moreover, how to establish a delivery system of Ginsenoside Rb1 and its repairment ability in bone defect remains elusive. In this study, the role of Ginsenoside Rb1 in cell viability, proliferation, apoptosis, osteogenic genes expression, ALP activity of rat BMSCs were evaluated firstly. Then,micro-nano HAp granules combined with silk were prepared to establish a delivery system of Ginsenoside Rb1, and the osteogenic and angiogenic effect of Ginsenoside Rb1 loaded on micro-nano HAp/silk in rat calvarial defect models were assessed by sequential fluorescence labeling, and histology analysis, respectively. It revealed that Ginsenoside Rb1 could maintain cell viability, significantly increased ALP activity, osteogenic and angiogenic genes expression. Meanwhile, micro-nano HAp granules combined with silk were fabricated smoothly and were a delivery carrier for Ginsenoside Rb1. Significantly, Ginsenoside Rb1 loaded on micro-nano HAp/silk could facilitate osteogenesis and angiogenesis. All the outcomes hint that Ginsenoside Rb1 could reinforce the osteogenesis differentiation and angiogenesis factor’s expression of BMSCs. Moreover, micro-nano HAp combined with silk could act as a carrier for Ginsenoside Rb1 to repair bone defect.

Bio-integrated scaffold facilitates large bone regeneration dominated by endochondral ossification

Repair of large bone defects caused by severe trauma,non-union fractures,or tumor resection remains challenging because of limited regenerative ability.Typically,these defects heal through mixed routines,including intramembranous ossification(IMO)and endochondral ossification(ECO),with ECO considered more efficient.Current strategies to promote large bone healing via ECO are unstable and require high-dose growth factors or complex cell therapy that cause side effects and raise expense while providing only limited benefit.Herein,we report a bio-integrated scaffold capable of initiating an early hypoxia microenvironment with controllable release of low-dose recombinant bone morphogenetic protein-2(rhBMP-2),aiming to induce ECO-dominated repair.Specifically,we apply a mesoporous structure to accelerate iron chelation,this promoting early chondrogenesis via deferoxamine(DFO)-induced hypoxia-inducible factor-1α(HIF-1α).Through the delicate segmentation of click-crosslinked PEGylated Poly(glycerol sebacate)(PEGS)layers,we achieve programmed release of low-dose rhBMP-2,which can facilitate cartilage-to-bone transformation while reducing side effect risks.We demonstrate this system can strengthen the ECO healing and convert mixed or mixed or IMO-guided routes to ECO-dominated approach in large-size models with clinical relevance.Collectively,these findings demonstrate a biomaterial-based strategy for driving ECO-dominated healing,paving a promising pave towards its clinical use in addressing large bone defects.

Uncertainty and explainable analysis of machine learning model for reconstruction of sonic slowness logs

Logs are valuable information for oil and gas fields as they help to determine the lithology of the formations surrounding the borehole and the location and reserves of subsurface oil and gas reservoirs.However,important logs are often missing in horizontal or old wells,which poses a challenge in field applications.To address this issue,conventional methods involve supplementing the missing logs by either combining geological experience and referring data from nearby boreholes or reconstructing them directly using the remaining logs in the same borehole.Nevertheless,there is currently no quantitative evaluation for the quality and rationality of the constructed log.In this paper,we utilize data from the 2020 machine learning competition of the Society of Petrophysicists and Logging Analysts(SPWLA),which aims to predict the missing compressional wave slowness(DTC)and shear wave slowness(DTS)logs using other logs in the same borehole.We employ the natural gradient boosting(NGBoost)algorithm to construct an Ensemble Learning model that can predicate the results as well as their uncertainty.Furthermore,we combine the SHAP(SHapley Additive exPlanations)method to investigate the interpretability of the machine learning model.We compare the performance of the NGBosst model with four other commonly used Ensemble Learning methods,including Random Forest,GBDT,XGBoost,LightGBM.The results show that the NGBoost model performs well in the testing set and can provide a probability distribution for the prediction results.This distribution allows petrophysicists to quantitatively analyze the confidence interval of the constructed log.In addition,the variance of the probability distribution of the predicted log can be used to justify the quality of the constructed log.Using the SHAP explainable machine learning model,we calculate the importance of each input log to the predicted results as well as the coupling relationship among input logs.Our findings reveal that the NGBoost model tends to provide greater slowness prediction results when the neutron porosity(CNC)and gamma ray(GR)are large,which is consistent with the cognition of petrophysical models.Furthermore,the machine learning model can capture the influence of the changing borehole caliper on slowness,where the influence of borehole caliper on slowness is complex and not easy to establish a direct relationship.These findings are in line with the physical principle of borehole acoustics.Finally,by using the explainable machine learning model,we observe that although we did not correct the effect of borehole caliper on the neutron porosity log through preprocessing,the machine learning model assigned a greater importance to the influence of the caliper,achieving the same effect as caliper correction.

Exposure to low-level metalaxyl impacts the cardiac development and function of zebrafish embryos

Metalaxyl is an anilide pesticide that is widely used to control plant diseases caused by Peronosporales species.In order to study the toxic effects,zebrafish embryos were exposed to metalaxyl at nominal concentrations of 5,50 and 500 ng/L for 72 hr,and the cardiac development and functioning of larvae were observed.The results showed that metalaxyl exposure resulted in increased rates of pericardial edema,heart hemorrhage and cardiac malformation.The distance between the sinus venosus and bulbus arteriosus,stroke volume,cardiac output and heart rate were significantly increased in larvae exposed to 50 and 500 ng/L metalaxyl compared to solvent control larvae.Significant upregulation in the transcription of tbx5,gata4 and myh6 was observed in the 50 and 500 ng/L treatments,and that of nkx2.5 and myl7 was observed in the 5,50 and 500 ng/L groups.These disturbances may be related to cardiac developmental and functional defects in the larvae.The activity of Na+/K+-ATPase and Ca2+-ATPase was significantly increased in zebrafish embryos exposed to 500 ng/L metalaxyl,and the mRNA levels of genes related to ATPase (atp2a11,atp1b2b,and atp1a3b)(in the 50 and 500 ng/L groups) and calcium channels (cacna1ab)(in the 500 ng/L group) were significantly downregulated;these changes might be associated with heart arrhythmia and functional failure.