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Three-dimensional (3D) bioprinting is an advanced technology to fabricate artificial 3D tissue constructs containing cells and hydrogels for tissue engineering and regenerative medicine. Nanocomposite reinforcement endows hydrogels with superior properties and tailored functionalities. A broad range of nanomaterials, including silicon-based, ceramic-based, cellulose-based, metal-based, and carbon-based nanomaterials, have been incorporated into hydrogel networks with encapsulated cells for improved performances. This review emphasizes the recent developments of cell-laden nanocomposite bioinks for 3D bioprinting, focusing on their reinforcement effects and mechanisms, including viscosity, shear-thinning property, printability, mechanical properties, structural integrity, and biocompatibility. The cell-material interactions are discussed to elaborate on the underlying mechanisms between the cells and the nanomaterials. The biomedical applications of cell-laden nanocomposite bioinks are summarized with a focus on bone and cartilage tissue engineering. Finally, the limitations and challenges of current cell-laden nanocomposite bioinks are identified. The prospects are concluded in designing multi-component bioinks with multi-functionality for various biomedical applications. STATEMENT OF SIGNIFICANCE: 3D bioprinting, an emerging technology of additive manufacturing, has been one of the most innovative tools for tissue engineering and regenerative medicine. Recent developments of cell-laden nanocomposite bioinks for 3D bioprinting, and cell-materials interactions are the subject of this review paper. The reinforcement effects and mechanisms of nanocomposites on viscosity, printability and biocompatibility of bioinks and 3D printed scaffolds are addressed mainly for bone and cartilage tissue engineering. It provides detailed information for further designing and optimizing multi-component bioinks with multi-functionality for specialized biomedical applications.

Laparoscopic liver resection (LLR) for hepatocellular carcinoma (HCC) remains controversial, especially for tumors larger than 5 cm. We compared the short- and long-term outcomes of laparoscopic and open liver resection (OLR) for large HCC.Patients with large HCC after curative hepatectomy were enrolled. To compare the short-term outcomes, propensity score matching (PSM) and inverse probability treatment weighting (IPTW) were performed to reduce the effect of confounding factors, respectively. Subsequently, Cox-regression analyses were conducted to identify the independent risk factors associated with decreased recurrence-free survival (RFS) and poor overall survival (OS).There were 265 patients enrolled in the final analysis: 146 who underwent OLR and 119 who underwent LLR. There was no significant difference between the OLR and LLR groups according to PSM and IPTW analysis (all P 0.05). Multivariable analysis revealed that LLR was not independently associated with poorer OS (HR 1.15, 95% CI 0.80-1.67, P = 0.448) or RFS (HR 1.22, 95% CI 0.88-1.70, P = 0.238).There were no significant differences in perioperative complications or long-term prognosis between LLR and OLR for large HCC, which provides evidence for standard laparoscopic surgical practice with adequate surgeon experience and careful patient selection.

The role of angiogenesis in health and disease have gained considerable momentum in recent years. Visualizing angiogenic patterns and associated events of surrounding vascular beds in response to therapeutic and laboratory-grade biomolecules have become a commonplace in regenerative medicine and the biosciences. To aid imaging investigations in angiogenesis, the two-photon excitation fluorescence microscopy (2PEF), or multiphoton fluorescence microscopy is increasingly utilized in scientific investigations. The 2PEF microscope confers several distinct imaging advantages over other fluorescence excitation microscopy techniques - for the observation of in-depth, three-dimensional vascularity in a variety of tissue formats, including fixed tissue specimens and in vivo vasculature in live specimens. Understanding morphological and subcellular changes that occur in cells and tissues during angiogenesis will provide insights to behavioral responses in diseased states, advance the engineering of physiologically-relevant tissue models and provide biochemical clues for the design of therapeutic strategies. We review the applicability and limitations of the 2PEF microscope on the biophysical and molecular-level signatures of angiogenesis in various tissue models. Imaging techniques and strategies for best practices in 2PEF microscopy will be reviewed.

Purpose This paper aims to detect the printing failures (such as warpage and collapse) in material extrusion (MEX) process effectively and timely to reduce the waste of printing time, energy and material. Design/methodology/approach The approach is designed based on the frequently observed fact that printing failures are accompanied by abnormal material phenomena occurring close to the nozzle. To effectively and timely capture the phenomena near the nozzle, a camera is delicately installed on a typical MEX printer. Then, aided by the captured phenomena (images), a smart printing failure predictor is built based on the artificial neural network (ANN). Finally, based on the predictor, the printing failures, as well as their types, can be effectively detected from the images captured by the camera in real-time. Findings Experiments show that printing failures can be detected timely with an accuracy of more than 98% on average. Comparisons in methodology demonstrate that this approach has advantages in real-time printing failure detection in MEX. Originality/value A novel real-time approach for failure detection is proposed based on ANN. The following characteristics make the approach have a great potential to be implemented easily and widely: (1) the scheme designed to capture the phenomena near the nozzle is simple, low-cost, and effective; and (2) the predictor can be conveniently extended to detect more types of failures by using more abnormal material phenomena that are occurring close to the nozzle.

Background and Aims Preoperative prediction of microvascular invasion (MVI) using a noninvasive method remain unresolved, especially in HBV-related in intrahepatic cholangiocarcinoma (ICC). This study aimed to build and validate a preoperative prediction model for MVI in HBV-related ICC.Methods Patients with HBV-associated ICC undergoing curative surgical resection were identified. Univariate and multivariate logistic regression analyses were performed to determine the independent risk factors of MVI in the training cohort. Then, a prediction model was built by enrolling the independent risk factors. The predictive performance was validated by receiver operator characteristic curve (ROC) and calibration in the validation cohort.Results Consecutive 626 patients were identified and randomly divided into the training (418, 67%) and validation (208, 33%) cohorts. Multivariate analysis showed that TBIL, CA19-9, tumor size, tumor number, and preoperative image lymph node metastasis were independently associated with MVI. Then, a model was built by enrolling former fiver risk factors. In the validation cohort, the performance of this model showed good calibration. The area under the curve was 0.874 (95% CI: 0.765–0.894) and 0.729 (95%CI: 0.706–0.751) in the training and validation cohort, respectively. Decision curve analysis showed an obvious net benefit from the model.Conclusion Based on clinical data, an easy model was built for the preoperative prediction of MVI, which can assist clinicians in surgical decision-making and adjuvant therapy.

The impact of diabetes mellitus (DM) on the survival of patients with hepatocellular carcinoma (HCC) is still unclear. The present study aims to draw a firm conclusion in terms of evaluating the impact of DM on the prognosis of HCC after hepatectomy.The pattern of recurrence for HCC was often stratified into early-stage (2 years) and late-stage (≥2 years) recurrence. Because the early-stage recurrence was mainly attributed to aggressive tumor pathological characteristics, patients who recurrence or die within 2 years were excluded. Cumulative overall survival (OS) and recurrence-free survival (RFS) were determined by the method of Kaplan-Meier, and the independent risk factors of OS/RFS were determined by Cox regression analysis.A total of 426 patients were eventually included. The 3- and 5-year OS in patients with and without DM was 83.7%, 55.1%; and 90.9%, 77.4%, respectively. Multivariate analysis showed that DM was an independent risk factor for OS (HR 1.166, 95% CI 1.056-2.036,DM is an independent risk factor for long-term prognosis in patients with HCC. Patients with DM after hepatectomy for HCC, thus, need to actively control DM and closer follow-up.

PurposeWe evaluated he effects of molecular guided-targeted therapy for intractable cancer. Also, the epidemiology of druggable gene alterations in Chinese population was investigated.Materials and methodsThe Long March Pathway (ClinicalTrials.gov identifier: NCT03239015) is a non-randomized, open-label, phase II trial consisting of several basket studies examining the molecular profiles of intractable cancers in the Chinese population. The trial aimed to 1) evaluate the efficacy of targeted therapy for intractable cancer and 2) identify the molecular epidemiology of the tier II gene alterations among Chinese pan-cancer patients.ResultsIn the first stage, molecular profiles of 520 intractable pan-cancer patients were identified, and 115 patients were identified to have tier II gene alterations. Then, 27 of these 115 patients received targeted therapy based on molecular profiles. The overall response rate (ORR) was 29.6% (8/27), and the disease control rate (DCR) was 44.4% (12/27). The median duration of response (DOR) was 4.80 months (95% CI, 3.33−27.2), and median progression-free survival (PFS) was 4.67 months (95% CI, 2.33−9.50). In the second stage, molecular epidemiology of 17,841 Chinese pan-cancer patients demonstrated that the frequency of tier II gene alterations across cancer types is 17.7%. Bladder cancer had the most tier-II alterations (26.1%), followed by breast cancer (22.4%), and non-small cell lung cancer (NSCLC; 20.2%).ConclusionThe Long March Pathway trial demonstrated a significant clinical benefit for intractable cancer from molecular-guided targeted therapy in the Chinese population. The frequency of tier II gene alterations across cancer types supports the feasibility of molecular-guided targeted therapy under basket trials.

Wound healing is a dynamic process that involves a series of molecular and cellular events aimed at replacing devitalized and missing cellular components and/or tissue layers. Recently, extracellular vesicles (EVs), naturally cell-secreted lipid membrane-bound vesicles laden with biological cargos including proteins, lipids, and nucleic acids, have drawn wide attention due to their ability to promote wound healing and tissue regeneration. However, current exploitation of EVs as therapeutic agents is limited by their low isolation yields and tedious isolation processes. To circumvent these challenges, bioinspired cell-derived nanovesicles (CDNs) that mimic EVs were obtained by shearing mesenchymal stem cells (MSCs) through membranes with different pore sizes. Physical characterisations and high-throughput proteomics confirmed that MSC-CDNs mimicked MSC-EVs. Moreover, these MSC-CDNs were efficiently uptaken by human dermal fibroblasts and demonstrated a dose-dependent activation of MAPK signalling pathway, resulting in enhancement of cell proliferation, cell migration, secretion of growth factors and extracellular matrix proteins, which all promoted tissue regeneration. Of note, MSC-CDNs enhanced angiogenesis in human dermal microvascular endothelial cells in a 3D PEG-fibrin scaffold and animal model, accelerating wound healing in vitro and in vivo. These findings suggest that MSC-CDNs could replace both whole cells and EVs in promoting wound healing and tissue regeneration. Agency for Science, Technology and Research (A*STAR) Ministry of Education (MOE) Nanyang Technological University Published version This work was supported by the National University of Singapore (NanoNash Program A-0004336-00-00 & A-0008504- 00-00, Singapore), and Nanyang Technological University, Singapore (grant number 001487-00001). Giorgia Pastorin. would also like to thank the Industry Alignment FunddPre-Positioning (IAF-PP) grant (A20G1a0046 and R-148-000-307-305/A0004345-00-00). This work was also supported by the Singapore Ministry of Education, under its Singapore Ministry of Education Academic Research Fund Tier 1 (10051 - MOE AcRF Tier 1: Thematic Call 2020) from Bertrand Czarny. Jiong-Wei Wang would like to thank the National University of Singapore NanoNASH Program (NUHSRO/2020/002/NanoNash/LOA) and the National University of Singapore Yong Loo Lin School of Medicine Nanomedicine Translational Research Program (NUHSRO/ 2021/034/TRP/09/Nanomedicine). Authors would also like to thank for the financial supports from Agency for Science, Technology, and Research (A*STAR, Singapore) Advanced Manufacturing and Engineering Individual Research Grant (AME IRG) (Project ID: A1883c0013, Singapore).

Although anatomical hepatectomy (AH) is widely used in the treatment of hepatocellular carcinoma (HCC), the prognosis is still unsatisfactory. The present study aimed to evaluate the survival benefit of adjuvant transcatheter arterial chemoembolization (TACE) for patients with HCC after AH. A total of 832 patients were stratified into with adjuvant TACE (443, 53.2%) and without adjuvant TACE group (389, 46.8%) AH. Propensity score matching (PSM) was performed to control for confounding factors, and multivariable Cox regression was performed to determine the independent risk factors. After PSM, the results showed that the adjuvant TACE group had better overall survival (OS) and recurrence-free survival (RFS). Among the patients with tumor recurrence, adjuvant TACE was associated with a high rate of early-stage tumor at recurrence, a lower recurrence rate around the frontal margin and extrahepatic metastases, and a higher rate of receiving curative treatment. Multivariable Cox regression analysis showed that adjuvant TACE was an independent prognostic factor for OS (HR 0.673, P = 0.001) and RFS (HR 0.650, P = 0.001). Patients with HCC after AH can benefit from postoperative adjuvant TACE. Therefore, adjuvant TACE should be considered for patients with a high risk of recurrence.

Product appearance is one of the crucial factors that influence consumers’ purchase decisions. The attractiveness of product appearance is mainly determined by the inherent aesthetics of the design composition related to the arrangement of visual design elements. Hence, it is critical to study and improve the arrangement of visual design elements for product appearance design. Strategies that apply aesthetic design principles to assist designers in effectively arranging visual design elements are widely acknowledged in both academia and industry. However, applying aesthetic design principles relies heavily on the designer’s perception and experience, while it is rather challenging for novice designers. Meanwhile, it is hard to measure and quantify design aesthetics in designing artefacts when designers refer to existing successful designs. In this regard, this study aims to introduce a method that assists designers in applying aesthetic design principles to improve the attractiveness of product appearance. Furthermore, formulas for aesthetic measurement based on aesthetic design principles are also developed, and it makes an early attempt to provide quantified aesthetic measurements of design artefacts. A case study on camera design was conducted to demonstrate the merits of the proposed method where the improved strategies for the camera appearance design offer insights for concept generation in product appearance design based on aesthetic design principles.

Battery/Ultracapacitor (UC) Hybrid Energy Storage Systems (HESS) for Electric Vehicles (EVs) have been frequently proposed in the literature to increase battery cycle life. The HESS consists of a Power Management Strategy (PMS) and an Energy Management Strategy (EMS). Existing EMS are quite empirical, such as setting constant target UC energy levels regardless of load. This work presents an improved complete HESS management strategy. The EMS involves a more comprehensive method of setting the target UC energy level using a speed-dependent band. This allows the UC to achieve two goals – contain sufficient energy for future accelerations and have sufficient space for capturing energy from future regenerative braking – without knowledge of the future drive profile. The PMS involves a speed-dependent battery power limit, which also achieves two goals – better UC utilization and allowing the battery to supply the steady state power. Simulations show existing works cannot achieve the four goals simultaneously unless their UCs are sized twice as large compared to the proposed rule-based HESS. In addition, the proposed HESS extends battery cycle life by up to 42% compared to a battery-only system. Lastly, a reduced-scale experiment was built to show that the proposed HESS is able to run in real-time.

This chapter presents the basic concepts of aesthetic needs and product specifications in conceptual design. The user aesthetics needs are considered one of the significant determinants in increasing user satisfaction. In this regard, the importance of establishing product appearance specifications to identify user aesthetic needs is discussed. A method is introduced to demonstrate the significance of considering aesthetic and emotional needs when establishing product appearance specifications in product conceptual design. To improve appearance specifications based on aesthetic experiences collected from users and designers, an approach using fuzzy logic is proposed and illustrated by a case study of digital camera design.

The representation and archiving of design information play an essential role in product conceptual design by enabling the design teams to reuse existing solutions. However, most existing studies on information management of conceptual design focus mainly on the systematization of function-related design knowledge, while few studies are related to the aesthetic aspect of design information. The challenge lies in acquiring and quantifying the aesthetic information involved in conceptual design activities. It is also difficult to represent and archive the relationships and hierarchies of aesthetic information in conceptual design. In this context, this study proposes a method to facilitate the searching and retrieval of existing design solutions with effective representation and archiving of both functional and aesthetic information in conceptual design. First, to address the challenge of acquiring and quantifying the aesthetic information, Kansei adjectives and aesthetic design principles were applied to quantify the aesthetic design information. Second, a model using knowledge-based information representation and an approach for archiving conceptual design information was proposed to represent and archive the aesthetic information in hierarchal relationships. The proposed approach was illustrated by a case study of digital camera design. A system prototype with a domain-driven vocabulary to represent and archive aesthetic information for digital camera design was successfully developed to show the feasibility of the proposed approach.

The growth behavior of stress corrosion cracking (SCC) of Alloy 600 with different cold-work levels was investigated in simulated boiling water reactors water environments. In addition, a correlation of cold-work levels, grain boundary characteristic, and the SCC growth behavior of Alloy 600 were studied. The results show that grains with high residual strain caused by cold work provide transgranular crack growth paths. The SCC growth rates of the specimens also increase with an increase in the degree of cold work and decrease remarkably after switching to the hydrogen water chemistry environment. Grain boundary character proves to be a factor more important than the localized strain concentration at the grain boundary in terms of its role in the intergranular crack growth rate of the Alloy 600 with a cold-work degree from 20% to 30%.

Multi-label learning methods can be categorised into algorithm adaptation, problem transformation and ensemble methods. Some of these methods depend on a base classifier and the relationship is not well understood. In this paper the sensitivity of five problem transformation and two ensemble methods to four types of classifiers is studied. Their performance across 11 benchmark datasets is measured using 16 evaluation metrics. The best classifier is shown to depend on the method: Support Vector Machines (SVM) for binary relevance, classifier chains, calibrated label ranking, quick weighted multi-label learning and RAndom k-labELsets; k-Nearest Neighbours (k-NN) and Naive Bayes (NB) for Hierarchy Of Multilabel classifiERs; and Decision Trees (DT) for ensemble of classifier chains. The statistical performance of a classifier is also found to be generally consistent across the metrics for any given method. Overall, DT and SVM have the best performance–computational time trade-off followed by k-NN and NB.

Orthopedic bone plates are most commonly used for bone fracture fixation for more than 100 years. The bone plate design had evolved over time overcoming many challenges such as insufficient strength and excessive plate–bone contact affecting the blood circulation. However, it is only made of two materials, either stainless steel (AISI 316L) or titanium (Ti–6Al–4V). There are two main limitations of metallic bone implants, namely stress shielding and the problem of malocclusion caused by the displacement of the fracture site during healing. To overcome the two problems, a new bone plate design with the incorporation of auxetic structures is proposed in this work. This study aims to use auxetic structure section in the bone plate that would decrease the stiffness of the region, thereby mitigating the stress-shielding effect and at the same time act as a deformable section to enable intra-operative bending for effective alignment while having enough bending strength and stiffness. Two different auxetic structures namely re-entrant honeycomb and missing rib structures were considered. The auxetic structure incorporated bone plates were designed, finite element analysis was done, fabricated using direct metal laser sintering technique, and tested. The results indicate that the re-entrant honeycomb structure incorporated bone plates serve as an effective bone design compared to the conventional bone plate design, in terms of stress shielding and intra-operative bending while offering similar mechanical and bending strength.

Recently, many methods have been proposed to deal with the problem of cross-domain semantic segmentation. Most of them choose to conduct domain adversarial training either on the high-level convolutional neural network (CNN) features or on the output segmentation maps. Typically, a relatively small weight is given to the adversarial training loss to avoid the problem of mode collapse. However, one potential weakness of these methods is that low-level CNN layers may receive little gradients for domain adaptation, especially when the network is deep. To address this problem, we propose to conduct an auxiliary adversarial training on the fused multi-level CNN features. Gradients for domain adaptation can thus flow into low-level CNN layers more easily along a shorter path. Experiments are conducted on the dataset of Cityscapes with using the source datasets of GTA5 and SYNTHIA, respectively. Quantitative and qualitative results certify the efficacy of the proposed method.

Additive manufacturing enables the fabrication of periodic ceramic lattices with controllable micro-architectures. Many studies reported their catastrophic brittle fracture behaviour. However, ceramic lattices may fail by a layer-by-layer pseudo-ductile fracture mode, by controlling micro-architectures and porosities. Moreover, their fracture behaviour can be optimised by introducing strut/wall thickness gradients. This paper investigates the fracture behaviour and the fracture mode transition of ceramic triply periodic minimal surface (TPMS) structures. Alumina TPMS structures with relative densities of 0.14-0.37 are fabricated by ceramic stereolithography. Quasi-static compression tests validate a transition density range for non-graded samples: low ( 0.25) relative density samples show layer-by-layer pseudo-ductile and catastrophic brittle fracture modes, respectively. The pseudo-ductile failure mode increases the energy absorption performance, enabling load-bearing capacity for a compressive strain up to 50%. With appropriate thickness gradients, graded structures exhibit significant increase of energy absorption without a decrease of fracture strength compared to their non-graded counterparts.

Energy-efficient manufacturing is playing an important role in addressing worldwide problems like air pollution, climate change, and energy crisis. Despite of the close relationship between process planning and scheduling, existing research efforts often consider energy efficiency-related issues by treating them separately and sequentially. This may cause various problems such as unbalanced resource allocation and infeasible production solutions, thus limiting their potential application. To advance the current state of the art in this area, this paper investigates energy-efficient integration of process planning and scheduling. Specifically, a mixed-integer linear programming model is firstly developed to formulate this problem mathematically. Subsequently, to solve more realistic large-sized problems, a heuristic-based two-stage approach is proposed. Stage 1 and Stage 2 aim at minimizing the total tardiness and reducing the total energy consumption, respectively. A realistic case study shows that the proposed two-stage approach works more efficiently and effectively than a modified genetic algorithm from existing literature. Through instructive modification of the solution space, the proposed approach can effectively reduce the total tardiness and total energy consumption; meanwhile the machining cost of individual process plans can also be kept at low level throughout the searching process. Results show that the proposed approach can allocate the machining resources in a more reasonable manner. As such, this paper may be a valuable supplement to existing efforts aiming at developing energy-efficient manufacturing techniques.

Multiple common databases were integrated to analyze the expression status and prognostic meaning ofThe transcription of

Chromia-forming ferritic stainless steel (FSS) is a highly promising interconnect material for application in solid oxide fuel cells. In this study, initial oxidation of chromium oxides was performed at 500–800 °C to understand the evolution of materials at an early stage. The structural variations in oxide scales were analyzed through scanning electron microscopy, energy dispersive spectroscopy (EDS), transmission electron microscopy (TEM), X-ray diffractometry (XRD), laser confocal microscopy (LSCM), X-ray photoelectron spectroscopy (XPS), and Raman spectroscopy. Surface electrochemical properties were investigated through electrochemical impedance spectroscopy to understand how the heat treatment temperature affected surface impedance. Treatment temperatures higher than 700 °C facilitate the diffusion of Cr and Mn, thus allowing ferritic spinels to form on the surface and leading to high electrical conductivity.

ObjectiveThis study aimed to investigate the role and potential regulatory mechanism of citron kinase (CIT) in esophageal squamous cell carcinoma (ESCC).MethodsCitron kinase (CIT) expression in ESCC tissues was analyzed based on the microarray dataset GSE20347, and CIT expression in ESCC cell lines was analyzed. Eca-109 cells were lentivirally transfected with shRNA-CIT (LV-shCIT) to knock down CIT, followed by investigation of cell proliferation and apoptosis. Nude mouse xenograft experiments were performed to evaluate the tumorigenicity of CIT-knockdown Eca-109 cells. Microarray analysis of Eca-109 cells transfected with LV-shCIT or LV-shNC and subsequent Ingenuity Pathway Analysis (IPA) were performed to identify CIT-related differentially expressed genes (DEGs) and signaling pathways. Furthermore, the expression of key DEGs was validated using the clinical samples of ESCC.ResultsCitron kinase (CIT) was highly expressed in ESCC tissues and cell lines. Knockdown of CIT suppressed Eca-109 cell proliferation and promoted apoptosis in vitro. Moreover, CIT knockdown significantly reduced tumorigenicity of Eca-109 cells in vivo. Microarray and IPA analysis showed that signaling by the Rho family GTPases pathway was significantly activated, and CIT intrinsically interacted with the protein kinase AMP-activated catalytic subunit alpha 1 (PRKAA1), sequestosome 1 (SQSTM1), and interleukin 6 (IL6). Notably, the expression levels of PRKAA1 and SQSTM1 were upregulated in ESCC tissues, while the IL6 expression was downregulated.ConclusionOur findings confirm that CIT functions as an oncogene in ESCC. CIT may contribute to ESCC development by upregulating PRKAA1 and SQSTM1 as well as downregulating IL6. Citron kinase may serve as a promising therapeutic target for ESCC.

Annotating large-scale datasets to train modern convolutional neural networks is prohibitively expensive and time-consuming for many real tasks. One alternative is to train the model on labeled synthetic datasets and apply it in the real scenes. However, this straightforward method often fails to generalize well mainly due to the domain bias between the synthetic and real datasets. Many unsupervised domain adaptation (UDA) methods were introduced to address this problem but most of them only focused on the simple classification task. This paper presents a novel UDA model which integrates both image and feature level based adaptations to solve the cross-domain object detection problem. We employ objectives of the generative adversarial network and the cycle consistency loss for image translation. Furthermore, region proposal based feature adversarial training and classification are proposed to further minimize the domain shifts and preserve the semantics of the target objects. Extensive experiments are conducted on several different adaptation scenarios, and the results demonstrate the robustness and superiority of the proposed method.

Modern manufacturing enterprises are consuming a considerable amount of energy every year. Improving energy efficiency will not only benefit the enterprises economically, but also help the world to overcome various problems such as energy crisis and air pollution. To achieve this, an accurate energy consumption model is essential. The main objective of this paper is to develop an improved cutting power-based energy consumption model for general end milling process. The proposed model consists of an idle part due to auxiliary components and spindle rotation, and an additional part due to cutting workpiece materials. The first part is modelled as a function of spindle rotation speed, and the other part is considered proportional to the cutting power. Experiments under various milling conditions have demonstrated the effectiveness and efficacy of the proposed model. Comparative studies show that the proposed model is more accurate than other models. Although calibrated from slotting experiments when cutting aluminium alloy, the proposed model is applicable for general milling process. Partial-immersion milling experiments show that the prediction error of the proposed model is as low as 1.74%. When workpiece material changes to titanium alloy, its performance remains decent, with low prediction error of 2.81%. This reveals its capability to provide reliable estimation for different workpiece materials. As such, it could help avoid tedious model calibration, thus saving time, material, and energy. Finally, the energy efficiency of general end milling process is investigated through numerical experiments with the proposed model. By revealing the relationship between energy consumption and various cutting parameters, the proposed model could serve as an excellent platform towards energy-efficient manufacturing/cleaner production.

Additively manufactured lattice structures enable the realisation of light-weight, multi-functional, structures. For example, lattices can be used for high stiffness and buckling resistance in sandwich structures or as support material for additive manufacturing. Topology optimisation and additive manufacturing are two technologies that allow the design, optimisation and manufacture of complex lattice designs. In this work, a new lattice optimisation methodology is presented that tailors the size, shape and orientation of individual lattice trusses in three-dimensional space by using principal strain fields obtained from topology optimisation. This new method of generating functionally graded lattices is shown both numerically and experimentally to be capable of generating lattice structures with greatly improved stiffness and strength when compared to lattice structures with a uniform lattice infill. Upper and lower relative density thresholds and minimum truss member sizes are included in the optimisation workflow to ensure that the optimised lattice designs are compatible with additive manufacturing process constraints. The functional grading method is also shown to be capable of generating conformal lattice structures in three dimensions, even for complex loading conditions and arbitrary volume boundaries.

3D printing and particularly fused deposition modelling (FDM) is widely used for prototyping and fabricating low-cost customised parts. However, present fused deposition modelling 3D printers have limited nozzle condition monitoring techniques to minimize nozzle clogging errors. Nozzle clogging is one of the significant process errors in fused deposition modelling 3D printers, and it affects the quality of prototyped parts in terms of mechanical properties and geometrical accuracy. This paper proposes a dynamic model for current-based nozzle condition monitoring in fused deposition modelling, which is briefly described as follows. First, all the process forces in filament extrusion of the fused deposition modelling were identified and derived theoretically, and theoretical equations of the feed rolling forces and flow-through-nozzle forces were derived. In addition, the effect of the nozzle clogging on the current of extruding motor were identified. Second, based on the proposed dynamic model, current-based nozzle condition monitoring method was proposed. Next, sets of experiments on FDM machine using polylactic acid (PLA) material were carried out to verify the proposed theoretical model, and the results were analysed and evaluated. Findings of the present study indicate that nozzle clogging in FDM 3D printing can be monitored by sensing the current of the filament extruding motor. The proposed model can be used efficiently for monitoring nozzle clogging conditions in fused deposition modelling 3D printers as it is based on the fundamental process modelling.

Drop-on-demand (DOD) bioprinting has been widely used in tissue engineering due to its high-throughput efficiency and cost effectiveness. However, this type of bioprinting involves challenges such as satellite generation, too-large droplet generation, and too-low droplet speed. These challenges reduce the stability and precision of DOD printing, disorder cell arrays, and hence generate further structural errors. In this paper, a multi-objective optimization (MOO) design method for DOD printing parameters through fully connected neural networks (FCNNs) is proposed in order to solve these challenges. The MOO problem comprises two objective functions: to develop the satellite formation model with FCNNs; and to decrease droplet diameter and increase droplet speed. A hybrid multi-subgradient descent bundle method with an adaptive learning rate algorithm (HMSGDBA), which combines the multi-subgradient descent bundle (MSGDB) method with Adam algorithm, is introduced in order to search for the Pareto-optimal set for the MOO problem. The superiority of HMSGDBA is demonstrated through comparative studies with the MSGDB method. The experimental results show that a single droplet can be printed stably and the droplet speed can be increased from 0.88 to 2.08 m·s−1 after optimization with the proposed method. The proposed method can improve both printing precision and stability, and is useful in realizing precise cell arrays and complex biological functions. Furthermore, it can be used to obtain guidelines for the setup of cell-printing experimental platforms. Keywords: Drop-on-demand printing, Inkjet printing, Gradient descent multi-objective optimization, Fully connected neural networks

Background Mesenchymal stem cells (MSCs) can migrate to tissue injury sites where they can induce multipotential differentiation and anti-inflammation effects to treat tissue injury. When traditional therapeutic methods do not work, MSCs are considered to be one of the best candidates for cell therapy. MSCs have been used for treating several injury- and inflammation-associated diseases, including liver cirrhosis. However, the therapeutic effect of MSCs is limited. In some cases, the anti-inflammatory function of naïve MSCs is not enough to rescue tissue injury. Methods Carbon tetrachloride (CCl4) was used to establish a mouse liver cirrhosis model. Enhanced green fluorescence protein (EGFP) and hepatocyte nuclear factor-4α (HNF-4α) overexpression adenoviruses were used to modify MSCs. Three weeks after liver injury induction, mice were injected with bone marrow MSCs via their tail vein. The mice were then sacrificed 3 weeks after MSC injection. Liver injury was evaluated by measuring glutamic-pyruvic transaminase (ALT) and glutamic oxalacetic transaminase (AST) levels. Histological and molecular evaluations were performed to study the mechanisms. Results We found that HNF-4α-overexpressing MSCs had a better treatment effect than unmodified MSCs on liver cirrhosis. In the CCl4-induced mouse liver injury model, we found that HNF-4α-MSCs reduced inflammation in the liver and alleviated liver injury. In addition, we found that HNF-4α promoted the anti-inflammatory effect of MSCs by enhancing nitric oxide synthase (iNOS) expression, which was dependent on the nuclear factor kappa B (NF-κB) signalling pathway. Conclusions MSCs overexpressing HNF-4α exerted good therapeutic effects against mouse liver cirrhosis due to an enhanced anti-inflammatory effect. Gene modification is likely a promising method for improving the effects of cell therapy. Electronic supplementary material The online version of this article (10.1186/s13287-019-1260-7) contains supplementary material, which is available to authorized users.

Specific structures of esophagus play an important role in specific functions. However, current esophageal tissue engineering scaffolds replicate them poorly. To address this issue, the objective of this study is to fabricate a hierarchical PCL/F127 scaffold inspired by the natural esophageal structure. The hierarchical scaffold consists of aligned fibers in micro-size and thin film with nano-sized pores through combining E-jetting and E-spraying. The aligned fibers of scaffold guide the orientation and induce the elongation of fibroblasts, mimicking the uniformly oriented esophageal muscles. Furthermore, the film functioned as a protective barrier to replicate the esophageal mucosa. Meanwhile, the film also increases cell adhesion area, hence, improving cell proliferation. These two features of the fabricated hierarchical scaffold mimic the structure of natural esophagus. Moreover, fabricated hierarchical scaffold possesses comparable mechanical properties to natural esophagus. These results prove the potential of fabricated scaffold for esophagus tissue repair.

Improving energy efficiency has been one of main objectives in modern manufacturing enterprises. Various approaches aiming at efficient energy management have been proposed/developed, among which minimizing energy consumption by energy-sensible production scheduling techniques has emerged as a promising one. However, reported workshop models are quite simple and unrealistic. This paper studies a more realistic workshop model called ultra-flexible job shop (uFJS). In an uFJS, the sequence among operations for a job can be changed within certain constraints. To formulate this energy-efficient scheduling problem, a mixed-integer linear programming model was developed. To deal with large-sized problems, a specially designed genetic algorithm (GA) was subsequently proposed and implemented. Numerical results showed the proposed GA worked with decent effectiveness and efficiency. Finally, several comparative studies are carried out to further demonstrate its efficacy in terms of energy efficiency improvement. The advantage of the uFJS as compared to other relative simple workshop models is also shown. By considering the flexibility in operation sequencing in each job, the uFJS effectively integrates process planning and scheduling in discrete parts manufacturing system, thus providing a much larger solution space for more energy-efficient solutions. It therefore provides an excellent platform for decision-makers when developing energy-efficient techniques and strategies

NGCs are considered as an alternative treatment method for treating peripheral nerve injuries in place of nerve autografts. Biomimicry, conductivity, and biodegradability are the properties expected of an ideal NGC. PCL/PAA NGCs with three different concentrations of PAA (2.5, 5 and 7.5%) were fabricated using EHD-jet 3D printing. The mechanical properties of the PCL/PAA NGCs mimic the native human nerve properties (ultimate tensile strength of 6.5 to 11.7 MPa) and the conductivity match that of the amphibian motor nerve fiber myelin sheath (10−6 S/cm). The in vitro degradation studies reveal that they are biodegradable and injury/site-specific biodegradability can be obtained by tuning the PCL/PAA concentration ratio. In addition, PAA being a polyanionic polymer has the potential to act as a cation-exchanger, mimicking the functions of the nerve cortical gel layer, thereby influencing the electrophysiological phenomena called nerve excitation and conduction. Neural differentiation studies with PC12 cells assessed by the Reverse Transcription-Polymerase Chain Reaction (RT-PCR) and immunocytochemistry showed enhanced gene expression with the presence of PAA. Our results suggest that the EHD-jet 3D printed porous conductive PCL/PAA NGCs has the potential to be used in the treatment of peripheral nerve injuries. Keywords: 3D printing, Tissue engineering scaffolds, Peripheral nerve injury, Nerve guide conduits, Electrohydrodynamic jet, Conductive scaffolds

3D printing and particularly fused filament fabrication is widely used for prototyping and fabricating low-cost customized parts. However, current fused filament fabrication 3D printers have limited nozzle condition monitoring techniques to minimize nozzle clogging errors. Nozzle clogging is one of the most significant process errors in current fused filament fabrication 3D printers, and it affects the quality of the prototyped parts in terms of geometry tolerance, surface roughness, and mechanical properties. This paper proposes a nozzle condition monitoring technique in fused filament fabrication 3D printing using a vibration sensor, which is briefly described as follows. First, a bar mount that supports the liquefier in fused filament fabrication extruder was modeled as a beam excited by a system of process forces. The boundary conditions were identified, and the applied forces were analyzed for Direct and Bowden types of fused filament fabrication extruders. Second, a new 3D printer with a fixed extruder and a moving platform was designed and built for conducting nozzle condition monitoring experiments. Third, nozzle clogging was simulated by reducing the nozzle extrusion temperature, which caused partial solidification of the filament around inner walls of the nozzle. Fourth, sets of experiments were performed by measuring the vibrations of a bar mount during extrusion of polylactic acid, acrylonitrile butadiene styrene, and SemiFlex filaments via Direct and Bowden types of fused filament fabrication extruders. Findings of the current study show that nozzle clogging in fused filament fabrication 3D printers can be monitored using an accelerometer sensor by measuring extruder’s bar mount vibrations. The proposed technique can be used efficiently for monitoring nozzle clogging in fused filament fabrication 3D printers as it is based on the fundamental process modeling.

The resection margin (RM) status and microscopic vascular invasion (MVI) are known prognostic factors for intrahepatic cholangiocarcinoma (ICC). An enhanced understanding of their impact on long-term prognosis is required to improve oncological outcomes.A total of 711 consecutive patients who underwent curative liver resection for hepatitis B virus-related ICC were retrospectively analyzed. The different impact of the RM status (narrow,1 cm, or wide, ≥1 cm) and MVI (positive, +, or negative, -) on overall survival (OS) and recurrence-free survival (RFS) were analyzed.The 1-, 3-, and 5-year OS rates were 67.6%, 42.5%, and 33.2% in wide RMMVI (-), 58.0%, 36.1%, and 26.5% in narrow RMMVI (-), 51.0%, 27.0%, and 24.3% in wide RMMVI (+), and 39.0%, 20.4% and 14.3% in narrow RMMVI (+) (Combined analysis of RM and MVI can better stratify the risks of postoperative death and recurrence in patients with HBV-related ICC, which may help subsequent adjuvant therapy and closer follow-up.

Bioprinting three-dimensional (3D) tissue equivalents have progressed tremendously over the last decade. 3D bioprinting is currently being employed to develop larger and more physiologic tissues, and it is of particular interest to generate vasculature in biofabricated tissues to aid better perfusion and transport of nutrition. Having an advantage over manual culture systems by bringing together biological scaffold materials and cells in precise 3D spatial orientation, bioprinting could assist in placing endothelial cells in specific spatial locations within a 3D matrix to promote vessel formation at these predefined areas. Hence, in the present study, we investigated the use of bioprinting to generate tissue-level capillary-like networks in biofabricated tissue constructs. First, we developed a bioink using collagen type-1 supplemented with xanthan gum (XG) as a thickening agent. Using a commercial extrusion-based multi-head bioprinter and collagen-XG bioink, the component cells were spatially assembled, wherein the endothelial cells were bioprinted in a lattice pattern and sandwiched between bioprinted fibroblasts layers. 3D bioprinted constructs thus generated were stable, and maintained structural shape and form. Post-print culture of the bioprinted tissues resulted in endothelial sprouting and formation of interconnected capillary-like networks within the lattice pattern and between the fibroblast layers. Bioprinter-assisted spatial placement of endothelial cells resulted in fabrication of patterned prevascularized constructs that enable potential regenerative applications in the future.

Background Patients with lung adenocarcinoma (LUAD) have high mortality rate and poor prognosis. The LUAD cells display increased aerobic glycolysis, which generates energy required for their survival and proliferation. Deregulation of Wnt/β-catenin signaling pathway induces the metabolism switching and oncogenesis in tumor cells. RING finger protein 115 (RNF115) is an E3 ligase for ubiquitin-mediated degradation. Although the oncogenic functions of RNF115 have been revealed in breast tumor cells, the effect of RNF115 on lung cancer is still not clear. Methods RNF115 expression and its correlation with the features of LUAD patients were analyzed by using public database and our own cohort. The functions of RNF115 in proliferation and energy metabolism in LUAD cells were explored by downregulating or upregulating RNF115 expression. Results We demonstrated that RNF115 was overexpressed in LUAD tissues and its expression was positively correlated with the poor overall survival of LUAD patients. Moreover, RNF115 overexpression inhibited LUAD cell apoptosis and promoted cellular proliferation and metabolism in LUAD cells. On the contrary, RNF115 knockdown displayed reverse effects. Furthermore, the underlying mechanism of the biological function of RNF115 in LUAD was through regulating Wnt/β-catenin pathway via ubiquitination of adenomatous polyposis coli (APC). Conclusion The current study reveals a close association between RNF115 expression and prognostic conditions in LUAD patients and the oncogenic roles of RNF115 in LUAD at the first time. These findings may help establish the foundation for the development of therapeutics strategies and clinical management for lung cancer in future.

Background and Aim: The resection margin (RM) status and microscopic vascular invasion (MVI) are known prognostic factors for intrahepatic cholangiocarcinoma (ICC). An enhanced understanding of their impact on long-term prognosis is required to improve oncological outcomes.Methods: We reviewed data on 711 consecutive patients who underwent curative liver resection for hepatitis B virus–related ICC. The different impact of the RM status (narrow, Results: The 1-, 3-, and 5-year OS rates were 67.6%, 42.5% and 33.2% in wide RM & & MVI (-), 58.0%, 36.1% and 26.5% in narrow RM & MVI (-), 51.0%, 27.0% and 24.3% in wide RM & MVI (+), and 39.0%, 20.4% and 14.3% in narrow RM & MVI (+) (p < 0.001).The 1-, 3-, and 5-year RFS rates were 60.0%, 40.2% and 28.7% in wide RM & MVI (-), 45.2%, 34.3% and 24.2% in narrow RM & MVI (-), 40.0%, 18.5% and 12.3% in wide RM & MVI (+), and 28.2%, 11.5% and 9.8% in narrow RM & MVI (+) (p < 0.001). Multivariate analysis showed that RM & MVI were independent risk factors for the OS and RFS. Conclusions: Combined analysis of RM and MVI can better stratify the risks of postoperative death and recurrence in patients with HBV-related ICC, which may help subsequent adjuvant therapy and follow-up.