3D bioprinting of in vitro porous hepatoma models:establishment,evaluation,and anticancer drug testing

Traditional tumor models do not tend to accurately simulate tumor growth in vitro or enable personalized treatment and are particularly unable to discover more beneficial targeted drugs.To address this,this study describes the use of threedimensional(3D)bioprinting technology to construct a 3D model with human hepatocarcinoma SMMC-7721 cells(3DP-7721)by combining gelatin methacrylate(GelMA)and poly(ethylene oxide)(PEO)as two immiscible aqueous phases to form a bioink and innovatively applying fluorescent carbon quantum dots for long-term tracking of cells.The GelMA(10%,mass fraction)and PEO(1.6%,mass fraction)hydrogel with 3:1 volume ratio offered distinct pore-forming characteristics,satisfactorymechanical properties,and biocompatibility for the creation of the 3DP-7721 model.Immunofluorescence analysis and quantitative real-time fluorescence polymerase chain reaction(PCR)were used to evaluate the biological properties of the model.Compared with the two-dimensional culture cell model(2D-7721)and the 3D mixed culture cell model(3DM-7721),3DP-7721 significantly improved the proliferation of cells and expression of tumor-related proteins and genes.Moreover,we evaluated the differences between the three culture models and the effectiveness of antitumor drugs in the three models and discovered that the efficacy of antitumor drugs varied because of significant differences in resistance proteins and genes between the three models.In addition,the comparison of tumor formation in the three models found that the cells cultured by the 3DP-7721 model had strong tumorigenicity in nude mice.Immunohistochemical evaluation of the levels of biochemical indicators related to the formation of solid tumors showed that the 3DP-7721 model group exhibited pathological characteristics of malignant tumors,the generated solid tumors were similar to actual tumors,and the deterioration was higher.This research therefore acts as a foundation for the application of 3DP-7721 models in drug development research.

Bearing Fault Diagnosis with DDCNN Based on Intelligent Feature Fusion Strategy in Strong Noise

Intelligent fault diagnosis in modern mechanical equipment maintenance is increasingly adopting deep learning technology.However,conventional bearing fault diagnosis models often suffer from low accuracy and unstable performance in noisy environments due to their reliance on a single input data.Therefore,this paper proposes a dual-channel convolutional neural network(DDCNN)model that leverages dual data inputs.The DDCNN model introduces two key improvements.Firstly,one of the channels substitutes its convolution with a larger kernel,simplifying the structure while addressing the lack of global information and shallow features.Secondly,the feature layer combines data from different sensors based on their primary and secondary importance,extracting details through small kernel convolution for primary data and obtaining global information through large kernel convolution for secondary data.Extensive experiments conducted on two-bearing fault datasets demonstrate the superiority of the two-channel convolution model,exhibiting high accuracy and robustness even in strong noise environments.Notably,it achieved an impressive 98.84%accuracy at a Signal to Noise Ratio(SNR)of−4 dB,outperforming other advanced convolutional models.

Dynamic Compressive Deformation and Fracture of a Hollow Bulk Metallic Glass

The dynamic mechanical behaviors of hollow Zr41.2Ti13.8Cu12.5Ni10.0Be22.5 bulk metal glass (BMG) are investigated using a splitting Hopkinson pressure bar (SHPB) in this study. Upon dynamic compressive loading, the hollow specimen exhibit lower strength and poor ductility, caused by the higher stress concentration for the hollow one through FEM modeling. The different strain-rate responses for the hollow specimen are compared and explained. On the fracture surface of the hollow samples, there are highly dense vein patterns, many liquid drops and fishbone-like patterns.

Pulse electrochemical synaptic transistor for supersensitive and ultrafast biosensors

High sensitivity and fast response are the figures of merit for benchmarking commercial sensors.Due to the advantages of intrinsic signal amplification,bionic ability,and mechanical flexibility,electrochemical transistors(ECTs)have recently gained increasing popularity in constructing various sensors.In the current work,we have proposed a pulse-driven synaptic ECT for supersensitive and ultrafast biosensors.By pulsing the presynaptic input(drain bias,VD)and setting the modulation potential(gate bias)near transconductance intersection(VG,i),the synaptic ECT-based pH sensor can achieve a record high sensitivity up to 124 mV pH^(-1)(almost twice the Nernstian limit,59.2 mV pH^(-1))and an ultrafast response time as low as 8.75 ms(7169 times faster than the potentiostatic sensors,62.73 s).The proposed synaptic sensing strategy can effectively eliminate the transconductance fluctuation issue during the calibration process of the pH sensor and significantly reduce power consumption.Besides,the most sensitive working point at VG,i has been elaborately figured out through a series of detailed mathematical derivations,which is of great significance to provide higher sensitivity with quasi-nonfluctuating amplification capability.The proposed electrochemical synaptic transistor paired with an optimized operating gate offers a new paradigm for standardizing and commercializing high-performance biosensors.

3D printed-electrospun PCL/hydroxyapatite/MWCNTs scaffolds for the repair of subchondral bone

Osteochondral defect caused by trauma or osteoarthritis exhibits a major challenge in clinical treatment with limited symptomatic effects at present.The regeneration and remodeling of subchondral bone play a positive effect on cartilage regeneration and further promotes the repair of osteochondral defects.Making use of the strengths of each preparation method,the combination of 3D printing and electrospinning is a promising method for designing and constructing multi-scale scaffolds that mimic the complexity and hierarchical structure of subchondral bone at the microscale and nanoscale,respectively.In this study,the 3D printed-electrospun poly(ɛ-caprolactone)/nano-hydroxyapatites/multi-walled carbon nanotubes(PCL/nHA/MWCNTs)scaffolds were successfully constructed by the combination of electrospinning and layer-by-layer 3D printing.The resulting dual-scale scaffold consisted of a dense layer of disordered nanospun fibers and a porous microscale 3D scaffold layer to support and promote the ingrowth of subchondral bone.Herein,the biomimetic PCL/nHA/MWCNTs scaffolds enhanced cell seeding efficiency and allowed for higher cell-cell interactions that supported the adhesion,proliferation,activity,morphology and subsequently improved the osteogenic differentiation of bone marrow mesenchymal stem cells in vitro.Together,this study elucidates that the construction of 3D printed-electrospun PCL/nHA/MWCNTs scaffolds provides an alternative strategy for the regeneration of subchondral bone and lays a foundation for subsequent in vivo studies.

In situ fabrication of organic electrochemical transistors on a microfluidic chip

Microfluid chips integrating with organic electrochemical transistors (OECTs) are useful for manufacturing biosensors with high throughput and large-scale analyses. We report here the utilization of alternating current (AC) electrodeposition to fabricate OECTs in situ on a microfiuid chip. With this method, the organic semiconductor (OS) layer with a channel length of 8μm was readily prepared without requiring the postbonding process in the conventional construction of microfluidic chips. Poly(3,4-ethylenedioxythiophene):poly(4-styrenesulfonate)/graphene quantum dots (PEDOT:PSS/GQDs) composites with different morphologies, such as microfilms, nanodendrites and nanowires were electropolymerized. The mass transfer process of the electropolymerization reaction was evidenced to be diffusion limited. Morphologies, growth directions, and chemical structures of OS layers could be tuned by the amplitude and the frequency of the AC voltage. Transfer and output characteristic curves of OECTs were measured on the microfluidic chip. The maximum transconductance, on/off current ratio and threshold voltage measured in the experiment was 1.58 mS, 246, and 0.120 V, respectively.

Mesenchymal stem cells loaded on 3D-printed gradient poly(e-caprolactone)/methacrylated alginate composite scaffolds for cartilage tissue engineering

Cartilage has limited self-repair ability due to its avascular,alymphatic and aneural features.The combination of three-dimensional(3D)printing and tissue engineering provides an up-and-coming approach to address this issue.Here,we designed and fabricated a tri-layered(superficial layer(SL),middle layer(ML)and deep layer(DL))stratified scaffold,inspired by the architecture of collagen fibers in native cartilage tissue.The scaffold was composed of 3D printed depth-dependent gradient poly(e-caprolactone)(PCL)impregnated with methacrylated alginate(ALMA),and its morphological analysis and mechanical properties were tested.To prove the feasibility of the composite scaffolds for cartilage regeneration,the viability,proliferation,collagen deposition and chondrogenic differentiation of embedded rat bone marrow mesenchymal stem cells(BMSCs)in the scaffolds were assessed by Live/dead assay,CCK-8,DNA content,cell morphology,immunofluorescence and real-time reverse transcription polymerase chain reaction.BMSCs-loaded gradient PCL/ALMA scaffolds showed excellent cell survival,cell proliferation,cell morphology,collagen II deposition and hopeful chondrogenic differentiation compared with three individual-layer scaffolds.Hence,our study demonstrates the potential use of the gradient PCL/ALMA construct for enhanced cartilage tissue engineering.

Biocompatible chitosan/polyethylene glycol/multi-walled carbon nanotube composite scaffolds for neural tissue engineering

Carbon nanotube(CNT)composite materials are very attractive for use in neural tissue engineering and biosensor coatings.CNT scaffolds are excellent mimics of extracellular matrix due to their hydrophilicity,viscosity,and biocompatibility.CNTs can also impart conductivity to other insulating materials improve mechanical stability guide neuronal cell behavior and trigger axon regeneration.The performance of chitosan(CS)/polyethylene glycol(PEG)composite scaffolds could be optimized by introducing multi-walled CNTs(MWCNTs).CS/PEG/CNT composite scaffolds with CNT content of 1%,3%,and 5%(1%=0.01 g/mL)were prepared by freeze-drying.Their physical and chemical properties and biocompatibility were evaluated.Scanning electron microscopy(SEM)showed that the composite scaffolds had a highly connected porous structure.Transmission electron microscope(TEM)and Raman spectroscopy proved that the CNTs were well dispersed in the CS/PEG matrix and combined with the CS/PEG nanofiber bundles.MWCNTs enhanced the elastic modulus of the scaffold.The porosity of the scaffolds ranged from 83%to 96%.They reached a stable water swelling state within 24 h,and swelling decreased with increasing MWCNT concentration.The electrical conductivity and cell adhesion rate of the scaffolds increased with increasing MWCNT content.Immunofluorescence showed that rat pheochromocytoma(PC12)cells grown in the scaffolds had characteristics similar to nerve cells.We measured changes in the expression of nerve cell markers by quantitative real-time polymerase chain reaction(qRT-PCR),and found that PC12 cells cultured in the scaffolds expressed growth-associated protein 43(GAP43),nerve growth factor receptor(NGFR),and class IIIβ-tubulin(TUBB3)proteins.Preliminary research showed that the prepared CS/PEG/CNT scaffold has good biocompatibility and can be further applied to neural tissue engineering research.

Effects of incident energy and angle on carbon cluster ions implantation on silicon substrate:a molecular dynamics study

Carbon cluster ion implantation is an important technique in fabricating functional devices at mi- cro/nanoscale. In this work, a numerical model is constructed for implantation and implemented with a cutting- edge molecular dynamics method. A series of simulations with varying incident energies and incident angles is performed for incidence on silicon substrate and correlated effects are compared in detail. Meanwhile, the behav- ior of the cluster during implantation is also examined under elevated temperatures. By mapping the nanoscopic morphology with variable parameters, numerical formalism is proposed to explain the different impacts on phrase transition and surface pattern formation. Particularly, implantation efficiency （IE） is computed and further used to evaluate the performance of the overall process. The calculated results could be properly adopted as the theoretical basis for designing nano-structures and adjusting devices＇ properties.