3D Architecture Research Articles

Silencing NlFAR7 destroyed the pore canals and related structures of the brown planthopper.

Fatty acyl-CoA reductase (FAR) is one of the key enzymes, which catalyses the conversion of fatty acyl-CoA to the corresponding alcohols. Among the FAR family members in the brown planthopper (Nilaparvata lugens), NlFAR7 plays a pivotal role in both the synthesis of cuticular hydrocarbons and the waterproofing of the cuticle. However, the precise mechanism by which NlFAR7 influences the formation of the cuticle structure in N. lugens remains unclear. Therefore, this paper aims to investigate the impact of NlFAR7 through RNA interference, transmission electron microscope, focused ion beam scanning electron microscopy (FIB-SEM) and lipidomics analysis. FIB-SEM is employed to reconstruct the three-dimensional (3D) architecture of the pore canals and related cuticle structures in N. lugens subjected to dsNlFAR7 and dsGFP treatments, enabling a comprehensive assessment of changes in the cuticle structures. The results reveal a reduction in the thickness of the cuticle and disruptions in the spiral structure of pore canals, accompanied by widened base and middle diameters. Furthermore, the lipidomics comparison analysis between dsNlFAR7- and dsGFP-treated N. lugens demonstrated that there were 25 metabolites involved in cuticular lipid layer synthesis, including 7 triacylglycerols (TGs), 5 phosphatidylcholines (PCs), 3 phosphatidylethanolamines (PEs) and 2 diacylglycerols (DGs) decreased, and 4 triacylglycerols (TGs) and 4 PEs increased. In conclusion, silencing NlFAR7 disrupts the synthesis of overall lipids and destroys the cuticular pore canals and related structures, thereby disrupting the secretion of cuticular lipids, thus affecting the cuticular waterproofing of N. lugens. These findings give significant attention with reference to further biochemical researches on the substrate specificity of FAR protein, and the molecular regulation mechanisms during N. lugens life cycle.

A 3D coordination polymer of Cd(II) with conformationally flexible mixed ligands as an active filler for silicone elastomers

The electronic configuration of d10 metals enables for a wide range of coordination numbers and geometries which, together with the use of mixtures of ligands for their coordination, allows fine-tuning of the properties of the complexes formed. By treating Cd(ClO4)2 with 1,3-bis(carboxypropyl)tetramethyldisiloxane (H2Cx) and 4,4′-azopyridyne (AzPy) in solution, a 3D coordination polymer, [Cd(Cx)(AzPy)·1.85H2O]n (1), was mostly formed. The compound was investigated by elemental and spectral analysis, as well as by powder and single crystal X-ray diffraction. Thermal behavior of compound 1 was evaluated by TGA and DSC, while the moisture behavior was studied by dynamic vapor sorption (DVS) analysis. Compound 1 contains a five-dentate Cx2− ligand with Cd atoms in a pentagonal-bipyramidal geometry, as determined by X-ray analysis. The conformational flexibility of the ligands allows the establishment of all possible intermolecular interactions in a very dense packing, the resulting structure having an extremely low free volume (14.8%). The compound is hydrophobic, adsorbing up to 2.4 wt% water vapor, thermally stable up to 160 °C, and has a phase transition around 6 °C, which, based on analysis by polarized optical microscopy (POM), is considered as a second-order crystal-to-crystal transition, facilitated by the mobility of the siloxane fragment. Due to the constraints imposed by the covalent 3D architecture, the conformational photoisomerization of 1 is extremely limited, as indicated by UV–Vis spectroscopy studies on solutions with solvents of different polarities as well as dielectric spectroscopy studies on silicone composites in which it is in solid state with 5 and 20 wt% loading. Instead, it was found that compound 1 significantly increases the dielectric strength of the resulting materials (up to 46 V/μm compared to 18 V/μm in the empty matrix) by incorporating it as a filler, making them suitable for dielectric elastomer generators, as the results of theoretical calculations indicate. In the purification process, a 2D coordination polymer, [Cd(Cx)(AzPy)·H2Cx]n (2), was also identified in traces.

Optomechanically induced transparency/absorption in a 3D microwave cavity architecture at ambient temperature

Leveraging advancements in cavity optomechanics, we explore Optomechanically Induced Transparency/Absorption (OMIT/OMIA) in the microwave domain at ambient temperature. Contrary to previous studies employing cryogenic temperatures, this work exploits a 3D microwave cavity architecture to observe these effects at ambient temperature, broadening the scope of possible applications. The work successfully enhances the optomechanical coupling strength, enabling observable and robust OMIT/OMIA effects, and demonstrating up to 25 dB in signal amplification and 20 dB in attenuation. Operating in the unresolved sideband regime enables tunability across a wider frequency range, enhancing the system’s applicability in signal processing and sensing. The findings herein highlight the potential of optomechanical systems, presenting a simplified, cost-effective, and more feasible approach for applications at ambient temperature.

Design and Construction of a Multi-Tiered Minimal Actin Cortex for Structural Support in Lipid Bilayer Applications.

Artificial lipid bilayers have revolutionized biochemical and biophysical research by providing a versatile interface to study aspects of cell membranes and membrane-bound processes in a controlled environment. Artificial bilayers also play a central role in numerous biosensing applications, form the foundational interface for liposomal drug delivery, and provide a vital structure for the development of synthetic cells. But unlike the envelope in many living cells, artificial bilayers can be mechanically fragile. Here, we develop prototype scaffolds for artificial bilayers made from multiple chemically linked tiers of actin filaments that can be bonded to lipid headgroups. We call the interlinked and layered assembly a multiple minimal actin cortex (multi-MAC). Construction of multi-MACs has the potential to significantly increase the bilayer's resistance to applied stress while retaining many desirable physical and chemical properties that are characteristic of lipid bilayers. Furthermore, the linking chemistry of multi-MACs is generalizable and can be applied almost anywhere lipid bilayers are important. This work describes a filament-by-filament approach to multi-MAC assembly that produces distinct 2D and 3D architectures. The nature of the structure depends on a combination of the underlying chemical conditions. Using fluorescence imaging techniques in model planar bilayers, we explore how multi-MACs vary with electrostatic charge, assembly time, ionic strength, and type of chemical linker. We also assess how the presence of a multi-MAC alters the underlying lateral diffusion of lipids and investigate the ability of multi-MACs to withstand exposure to shear stress.

Correlative cryo-soft X-ray tomography and cryo-structured illumination microscopy reveal changes to lysosomes in amyloid-β-treated neurons

Protein misfolding is common to neurodegenerative diseases (NDs) including Alzheimer's disease (AD), which is partly characterized by the self-assembly and accumulation of amyloid-beta in the brain. Lysosomes are a critical component of the proteostasis network required to degrade and recycle material from outside and within the cell and impaired proteostatic mechanisms have been implicated in NDs. We have previously established that toxic amyloid-beta oligomers are endocytosed, accumulate in lysosomes, and disrupt the endo-lysosomal system in neurons. Here, we use pioneering correlative cryo-structured illumination microscopy and cryo-soft X-ray tomography imaging techniques to reconstruct 3D cellular architecture in the native state revealing reduced X-ray density in lysosomes and increased carbon dense vesicles in oligomer treated neurons compared with untreated cells. This work provides unprecedented visual information on the changes to neuronal lysosomes inflicted by amyloid beta oligomers using advanced methods in structural cell biology.

3D Host Design Strategies Guiding “Bottom–Up” Lithium Deposition: A Review

AbstractLithium metal batteries (LMBs) have the potential to be the next‐generation rechargeable batteries due to the high theoretical specific capacity and the lowest redox potential of lithium metal. However, the practical application of LMBs is hindered by challenges such as the uncontrolled growth of lithium dendrites, unstable solid electrolyte interphase (SEI), and excessive volume change of Li metal. To solve these issues, the design of high‐performance lithium metal anodes (LMAs) with various 3D structures is critical. Targeting at realizing the “bottom–up” Li deposition to fully utilize the 3D architecture, in recent years, strategies such as gradient host materials construction, magnetic field modulation, SEI component design, and so on have attracted intensive attention. This review begins with a fundamental discussion of the Li nucleation and deposition mechanism. The recent advances in the aspects of construction strategies and modification methods that enable the “bottom–up” Li deposition within advanced 3D host materials, with a particular emphasize on their design principles are comprehensively overviewed. Finally, future challenges and perspectives on the design of advanced hosts toward practical LMAs are proposed.

Dimensional advantage: How 3D organoids are re-shaping the oncology research

Traditional in-vitro 2D cell culture-based models have limitations in cancer research, as they do not accurately reflect the complex 3D architecture and interactions we find in tumors. Cell-cell communications are vital for cancer growth and proliferation. Cancer cells communicate with each other and surrounding cells through various pathways, sending signals that promote their growth, survival, and proliferation through autocrine, paracrine, and endocrine. Fundamentally, this communication forms the basis of cancer survival. This can involve growth factors, cytokines, and other molecules that activate essential signaling pathways for tumor growth. Cancer cells need constant blood and nutrients to sustain such massive growth. This is again achieved by communication with endothelial cells to stimulate the formation of new blood vessels to sustain their energy and metabolic needs. The conventional 2D and 3D cultures play a role in oncology research, but each has its strengths and weaknesses when it comes to studying cancer. While 2D culture systems are simple, easier, and inexpensive to set up and maintain, 3D cultures are more realistic representations of actual tumors due to their 3D structure and cell-cell interactions. They can capture the genetic and functional heterogeneity of patient-derived tumors, thereby allowing for modeling the tumor microenvironment with various cell types and signaling and immune molecules. 2D culture fails to accurately reflect the complex 3D architecture and interactions of cells as seen in vivo due to their limited ability to model cell-cell interactions and the tumor microenvironment. 3D culture-derived organoids behave like miniature, simplified organs in vitro, which can be used for drug testing, disease modeling, and regenerative medicine applications. By creating conditions mimicking embryonic development, 3D culture can be used to study organogenesis and tissue morphogenesis.3D culture models can also be used to study the interaction between pathogens and host cells, providing a more accurate representation of in vivo conditions than traditional 2D cultures.
 Therefore, the use of 3D culture is multidimensional and spans multiple avenues, contributing to our advancements in understanding biology, disease mechanisms, oncology research, and the development of novel therapeutic strategies.

Chromone-Based Cd(II) Fluorescent Coordination Polymer Fabricated to Study Optoelectronic and Explosive Sensing Properties.

Here, electrical conductivity and explosive sensing properties of multifunctional chromone-Cd(II)-based coordination polymers (CPs) (1-4) have been explored. The presence of different pseudohalide linkers, thiocyanate ions, and dicyanamide ions resulted in 1D and 3D architecture in the CPs. Thin film devices developed from CPs 1-4 (complex-based Schottky devices, CSD1, CSD2, CSD3, and CSD4, respectively) showed semiconductor behavior. Their conductivity values increased under photo illumination (1.37 × 10-5, 1.85 × 10-5, 1.61 × 10-5, and 2.01 × 10-5 S m-1 under dark conditions and 5.06 × 10-5, 8.78 × 10-5, 7.26 × 10-5, and 10.21 × 10-5 S m-1 under light). The nature of the I-V plots of these thin film devices under light irradiation and dark are nonlinear rectifying, which has been observed in Schottky barrier diodes (SBDs). All four CPs (1-4) exhibited highly selective fluorescence quenching-based sensing properties toward well-known explosives, 2,4-dinitrophenol (DNP) and 2,4,6-trinitrophenol (TNP). The limit of detection (LOD) values are 55, 28, 27, and 31 μM for TNP and 78, 44, 32, and 41 μM for DNP for complexes 1-4, respectively. A structure property correlation has been established to explain optoelectronic and explosive sensing properties.

FeNi nanoalloy-carbon nanotubes on defected graphene as an excellent electrocatalyst for lithium-oxygen batteries

Lithium-oxygen batteries (LOBs) promise high energy density but suffer from catalyst-related issues. We've developed FeNi-NCNT/DrGO, a novel catalyst, by integrating iron-nickel nanoalloys (FeNi) embedded in nitrogen-doped carbon nanotubes (NCNTs) grafted onto defect-rich reduced graphene oxide (DrGO). The fabrication involved freeze-drying, defect engineering, and thermal treatments. The FeNi nanoalloy within the catalyst demonstrates outstanding bifunctional activity, while the NCNTs serve as an excellent electronic conduction medium and DrGO enables favorable ion transport. The 3D open-space architecture of this catalyst provides a rapid diffusion path for the electrolyte and room for accommodating discharge products. As a result, the LOBs with FeNi-NCNT/DrGO exhibits exceptional electrochemical performance, achieving a deep discharge capacity of 21,153.6 mAh g−1 and a high round-trip efficiency of 98.7% at 200 mA g−1. Moreover, it demonstrates excellent cycling stability, exceeding 100 cycles at 200 mA g−1 with a cut-off capacity of 500 mAh g−1.

A multi-layer fabric for high-efficiency solar-driven seawater desalination

Fiber-based photothermal materials for seawater desalination usage have garnered significant attention owing to their outstanding properties. However, traditional monolayer fabrics are prone to possess inherent inefficiencies such as high thermal dissipation and salt crystallization within the evaporation zone, especially reducing the evaporation efficiency during the long-term seawater desalination. Herein, a novel three-layered three-dimensional (3D) spacer carbon/polyester cotton spacer woven fabric (SWF) evaporator is designed. This SWF material was delineated into three distinct layers: an upper evaporate layer, a foundational water absorption layer, and a central water dedicated to water transition, thermal insulation, and salt crystallization. The rational three-layered 3D architecture guarantees the swift aqueous transition within SWF evaporator, simultaneously curtailing thermal losses from the top layer. The evaporation rate of 3D SWF, with 6 mm interval space, registered at 1.6721 kg · m−2·h−1 under a solar intensity of 1 kW · m−2. Furthermore, under conditions with a solar power of 1 kW · m−2 and a wind velocity of 2 m · s−1, the evaporation efficiency of liquid water from SWF, with a central layer height of 12 mm, culminated at 3.9742 kg · m−2·h−1, which validated its adeptness for the seawater desalination applications. The results of our research are helping to provide for efficient and stable methods of wastewater treatment, desalination, and drinking water collection.

Co-axial hydrogel spinning for facile biofabrication of prostate cancer-like 3D models

Glandular cancers are amongst the most prevalent types of cancer, which can develop in many different organs, presenting challenges in their detection as well as high treatment variability and failure rates. For that purpose, anticancer drugs are commonly tested in cancer cell lines grown in 2D tissue culture on plastic dishes in vitro, or in animal models in vivo. However, 2D culture models diverge significantly from the 3D characteristics of living tissues and animal models require extensive animal use and time. Glandular cancers, such as prostate cancer—the second leading cause of male cancer death—typically exist in co-centrical architectures where a cell layer surrounds an acellular lumen. Herein, this spatial cellular position and 3D architecture, containing dual compartments with different hydrogel materials, is engineered using a simple co-axial nozzle setup, in a single step utilizing prostate as a model of glandular cancer. The resulting hydrogel soft structures support viable prostate cancer cells of different cell lines and enable over-time maturation into cancer-mimicking aggregates surrounding the acellular core. The biofabricated cancer mimicking structures are then used as a model to predict the inhibitory efficacy of the poly ADP ribose polymerase inhibitor, Talazoparib, and the antiandrogen drug, Enzalutamide, in the growth of the cancer cell layer. Our results show that the obtained hydrogel constructs can be adapted to quickly obtain 3D cancer models which combine 3D physiological architectures with high-throughput screening to detect and optimize anti-cancer drugs in prostate and potentially other glandular cancer types.

Effect of CVI-induced porosity on elastic properties and mechanical behaviour of 2.5D and 3D Cf/SiC composites with multilayered interphase

The effect of CVI-induced porosity on mechanical behaviour of Cf/SiC composites possessing 2.5D (woven) and 3D (NOOBed) architectures with multilayered (PyC/SiC)n=4 interphase has been investigated. X-ray computed micro-tomography has shown that inter-bundle and inter-fibre pore distribution is influenced by fibre architecture. Elastic constants measured by ultrasound phase spectroscopy have revealed greater anisotropy in 2.5D Cf/SiC composite than 3D Cf/SiC composite. Owing to negligible Cf fraction and flattened inter-bundle pores distributed in thickness direction of 2.5D Cf/SiC composite, the elastic constant, C11 (∼15±0.03 GPa) is <1/6th of C22 and C33 obtained along fibre directions. Despite the flexural strength of 2.5D Cf/SiC composite (∼335±8 MPa) being ∼24% higher than 3D Cf/SiC composite, a more equitable distribution of Cf along three mutually orthogonal directions leads to higher fracture toughness of 3D Cf/SiC composites (∼19±1 MPa-m1/2) and greater damage tolerance. Porosity distributions having influence on crack paths, also affect both strength and fracture behaviour.

A Convolutional Neural Network-Based Auto-Segmentation Pipeline for Breast Cancer Imaging

Medical imaging is crucial for the detection and diagnosis of breast cancer. Artificial intelligence and computer vision have rapidly become popular in medical image analyses thanks to technological advancements. To improve the effectiveness and efficiency of medical diagnosis and treatment, significant efforts have been made in the literature on medical image processing, segmentation, volumetric analysis, and prediction. This paper is interested in the development of a prediction pipeline for breast cancer studies based on 3D computed tomography (CT) scans. Several algorithms were designed and integrated to classify the suitability of the CT slices. The selected slices from patients were then further processed in the pipeline. This was followed by data generalization and volume segmentation to reduce the computation complexity. The selected input data were fed into a 3D U-Net architecture in the pipeline for analysis and volumetric predictions of cancer tumors. Three types of U-Net models were designed and compared. The experimental results show that Model 1 of U-Net obtained the highest accuracy at 91.44% with the highest memory usage; Model 2 had the lowest memory usage with the lowest accuracy at 85.18%; and Model 3 achieved a balanced performance in accuracy and memory usage, which is a more suitable configuration for the developed pipeline.

Nanozyme-based Clusterphene for Enhanced Electrically Catalytic Cancer Therapy.

Nanozyme mediated catalytic therapy is an attractive strategy for cancer therapy. However, the nanozymes are tended to assemble into 3D architectures, resulting in poor catalytic efficiency for therapy. This study designs the assembly of nanozymes and natural enzymes into the layered structures featuring hexagonal pores as nanozyme clusterphene and investigates their catalytic therapy with the assistance of electric field. The nanozyme-based clusterphene consists of polyoxometalate (POM) and natural glucose oxidase (GOx), named POMG-based clusterphene, which facilitate multi-enzyme activities including peroxidase (POD), catalase (CAT), and glutathione oxidase (GPx). The highly ordered layers with hexagonal pores of POMG units significantly improve the peroxidase-like (POD-like) activity of the nanozyme and thus the sustained production of reactive oxygen species (ROS). At the same time, GOx can increase endogenous H2O2 and produce gluconic acid while consuming glucose, the nutrient of tumor cell growth. The results indicate that the POD-like activity of POMG-based clusterphene increase approximately sevenfold under electrical stimulation compared with Nd-substituted keggin type POM cluster (NdPW11). The experiments both in vitro and in vivo show that the proposed POMG-based clusterphene mediated cascade catalytic therapy is capable of efficient tumor inhibiting and preventing tumor proliferation in tumor-bearing mice model, promising as an excellent candidate for catalytic therapy.

3DUV-NetR+: A 3D hybrid semantic architecture using transformers for brain tumor segmentation with MultiModal MR images

Brain tumor segmentation plays a substantial role in Medical Image Analysis (MIS). In this regard, automatic segmentation methods facilitate precise and efficient segmentation, significantly contributing to diagnosis and treatment planning in medical applications. Recently, several Deep Learning-based architectures have been proposed to revolutionize the MIS field. Particularly, the combination of Convolution Neural Networks (CNNs) and Transformers has greatly enhanced and developed segmentation results. Moreover, the Attention mechanism in Transformers allows the modeling of long-range contextual features extracted from CNNs' encoder part. This paper proposes a hybrid advanced 3D model for brain tumor segmentation using multi-modal magnetic resonance images. The model benefits from the features extracted from the encoder of 3DU-Net and V-Net architectures at each depth. Then, a concatenation between these features and their fusion is carried out at each decoder depth to build new significant features followed by a 3D convolution layer and Transformers block for more contextual information. In addition, a final convolution block is applied to get the segmented tumor. To this end, the model is evaluated on the BraTS 2020 dataset to segment different sub-regions of brain tumors. The obtained results demonstrate the effectiveness of the proposed model in terms of dice similarity coefficient (DSC) and Hausdorff Distance (HD). For DSC, 91.95% and 82.80% and 81.70% for Whole Tumor(WT), Tumor Core (TC), and Enhancing Tumor(ET), respectively are archived, while for HD, 4.9 mm, 6.0 mm and 3.8 mm for WT, TC and ET are accomplished.

Three novel mononuclear 4‐vinylpyridine‐based Fe(III) complexes displaying various spin‐crossover behaviour

AbstractThree novel mononuclear 4‐vinylpyridine‐based Fe(III) complexes [FeL(4‐VP)]BPh4 (4‐VP=4‐vinylpyridine; H2L=bis(salicylicdeneaminopropyl)amine, H2salten, 1; H2L=bis(salicylicdeneaminopropyl)methylamine, H2saltenMe, 2; H2L=bis(3‐methoxysalicylideneaminopropyl)methylamine, 3‐OMeH2saltenMe, 3) were synthesized and characterized. Single‐crystal X‐ray diffraction analyses revealed that 1–3 both present the mononuclear structure based on 4‐VP coordinated with bis(salicylicdeneaminopropyl)amine and its derivatives, which give 2D architectures by various interactions among cations and counter‐ions. Magnetic studies showed that both 1 and 2 exhibit one‐step complete spin‐crossover (SCO) behaviours with critical transition temperatures (T1/2) of 178 and 87 K respectively, while 3 exhibits one‐step incomplete spin crossover behaviour (T1/2,3=93 K). The introduction of methyl groups on the amine nitrogen of the Schiff base ligands in 2 and 3 give the bigger repulsive effect, further decrease the cooperation of spin centres, resulting in their spin transition occurring at lower temperatures. In addition, the presence of C−H⋯O weak interactions in 1 and 3 with synergistic effect, led to their spin transition temperatures being higher than that of 2.

Fabrication of gelatin-heparin based cartilage models: enhancing spatial complexity through refinement of stiffness properties and oxygen availability

The intricate nature of native cartilage, characterized by zonal variations in oxygen levels and ECM composition, poses a challenge for existing hydrogel-based tissue models. Consequently, these 3D models often present simplified renditions of the native tissue, failing to fully capture its heterogenous nature. The combined effects of hydrogel components, network properties, and structural designs on cellular responses are often overlooked. In this work, we aim to establish more physiological cartilage models through biofabrication of photopolymerizable allylated-gelatin (GelAGE) and Thiolated Heparin (HepSH) constructs with tailorable matrix stiffness and customized architectures. This involves systematically studying how the native glycosaminoglycan Heparin together with hydrogel stiffness, and oxygen availability within 3D structures influence chondrogenic differentiation and regional heterogeneity. A comprehensive library of 3D hydrogel constructs was successfully developed, encompassing GelAGE-HepSH hydrogels with three distinct stiffness levels: 12, 55 and 121 kPa, and three unique geometries: spheres, discs, and square lattices. In soft GelAGE-HepSH hydrogels, the localization of differentiating cells was observed to be irregular, while stiff hydrogels restricted the overall secretion of ECM components. The medium-stiff hydrogels were found to be most applicable, supporting both uniform tissue formation and maintained shape fidelity. Three different 3D architectures were explored, where biofabrication of smaller GelAGE-HepSH spheres without oxygen gradients induced homogenous, hyaline cartilage tissue formation. Conversely, fabrication of larger constructs (discs and lattices) with oxygen gradients could be utilized to design heterogenous cartilage tissue models. Similarly, temporal oxygen gradients were observed to drive interconnected deposition of glycosaminoglycans (GAGs). Control samples of GelAGE without HepSH did not exhibit any notable changes in chondrogenesis as a function of stiffness, architectures, or oxygen concentrations. Overall, the incorporation of HepSH within GelAGE hydrogels was observed to serve as an amplifier for the biological effects from both stiffness and oxygen cues. In conclusion, fabrication of GelAGE-HepSH constructs designed to impose limitations on oxygen availability induce more zone-specific cartilage tissue alignment. This systematic study of matrix components, network stiffness, and oxygen levels in 3D biofabricated structures contributes to the development of more physiologically relevant cartilage models while further enhancing our overall understanding of cartilage tissue engineering.

AI-Enabled Materials Design of Non-Periodic 3D Architectures With Predictable Direction-Dependent Elastic Properties.

Natural porous materials have exceptional properties-for example, light weight, mechanical resilience, and multi-functionality. Efforts to imitate their properties in engineered structures have limited success. This, in part, is caused by the complexity of multi-phase materials composites and by the lack of quantified understandingof each component's role in overall hierarchy. This challenge is twofold: 1) computational. because non-periodicity and defects render constructing design guidelines between geometries and mechanical properties complex and expensive and 2) experimental. because the fabrication and characterization of complex, often hierarchical and non-periodic 3D architectures is non-trivial.

Influence of the 3D architecture and surface roughness of SiOC anodes on bioelectrochemical system performance: a comparative study of freeze-cast, 3D-printed, and tape-cast materials with uniform composition

3D-printed anodes for bioelectrochemical systems are increasingly being reported. However, comparisons between 3D-printed anodes and their non-3D-printed counterparts with the same material composition are still lacking. In addition, surface roughness parameters that could be correlated with bioelectrochemical performance are rarely determined. To fill these gaps, slurries with identical composition but different mass fractions were processed into SiOC anodes by tape-casting, freeze-casting, or direct-ink writing. The current generation was investigated using electroactive biofilms enriched with Geobacter spp. Freeze-cast anodes showed more surface pores and the highest surface kurtosis of 5.7 ± 0.5, whereas tape-cast and 3D-printed anodes showed a closed surface porosity. 3D-printing was only possible using slurries 85 wt% of mass fraction. The surface pores of the freeze-cast anodes improved bacterial adhesion and resulted in a high initial (first cycle) maximum current density per geometric surface area of 9.2 ± 2.1 A m−2. The larger surface area of the 3D-printed anodes prevented pore clogging and produced the highest current density per geometric surface area of 12.0 ± 1.2 A m−2. The current density values of all anodes are similar when the current density is normalized over the entire geometric surface as determined by CT-scans. This study highlights the role of geometric surface area in normalizing current generation and the need to use more surface roughness parameters to correlate anode properties, bacterial adhesion, and current generation.

Auto-segmentation of pelvic organs at risk on 0.35T MRI using 2D and 3D Generative Adversarial Network models

PurposeManual recontouring of targets and Organs At Risk (OARs) is a time-consuming and operator-dependent task. We explored the potential of Generative Adversarial Networks (GAN) to auto-segment the rectum, bladder and femoral heads on 0.35T MRIs to accelerate the online MRI-guided-Radiotherapy (MRIgRT) workflow. Methods3D planning MRIs from 60 prostate cancer patients treated with 0.35T MR-Linac were collected. A 3D GAN architecture and its equivalent 2D version were trained, validated and tested on 40, 10 and 10 patients respectively. The volumetric Dice Similarity Coefficient (DSC) and 95th percentile Hausdorff Distance (HD95th) were computed against expert drawn ground-truth delineations. The networks were also validated on an independent external dataset of 16 patients. ResultsIn the internal test set, the 3D and 2D GANs showed DSC/HD95th of 0.83/9.72 mm and 0.81/10.65 mm for the rectum, 0.92/5.91 mm and 0.85/15.72 mm for the bladder, and 0.94/3.62 mm and 0.90/9.49 mm for the femoral heads. In the external test set, the performance was 0.74/31.13 mm and 0.72/25.07 mm for the rectum, 0.92/9.46 mm and 0.88/11.28 mm for the bladder, and 0.89/7.00 mm and 0.88/10.06 mm for the femoral heads. The 3D and 2D GANs required on average 1.44 s and 6.59 s respectively to generate the OARs’ volumetric segmentation for a single patient. ConclusionsThe proposed 3D GAN auto-segments pelvic OARs with high accuracy on 0.35T, in both the internal and the external test sets, outperforming its 2D equivalent in both segmentation robustness and volume generation time.