Human bone has an innate capacity for self-repair, but it is insufficient to heal critical-sized bone defects. While current scaffolds have the potential to promote the repair of critical-sized defects, this capacity is hindered by their inadequate bioactivity and osteoconductivity. Therefore, a nano-/micro-hierarchical scaffold with a tunable surface architecture was developed to enhance bone regeneration. The resulting biointerface markedly promoted osteogenic differentiation of bone marrow mesenchymal stem cells in a non-linear, roughness-dependent manner. Furthermore, in vivo results displayed that scaffolds with a fiber roughness of approximately 400 nm exhibited the highest potency on bone defect repair. The promising performance of the hierarchical scaffold was found to result from enhanced cellular mechanotransduction by its nano-/micro-hierarchical architectures at the scaffold's biointerface. The present study offers an interesting strategy to address the challenge of critical-sized bone defect repair based on mechanobiology.

Soft electronic sensors based on conductive polymer hydrogels have been increasingly studied toward such applications as healthcare, human-machine interactions, and soft robotics. Correspondingly, the pursuit of high sensing performance often involves the regulation of multifaceted structural and functional properties of the hydrogels. Among various hydrogel types, poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) and poly(vinyl alcohol) (PVA) hybrid structures obtained via the 3D printing technology and the freezing-thawing method have exhibited notable potential for developing soft, high-performance electronic sensors. However, the tuning of micromorphological and functional characteristics of PEDOT:PSS/PVA structures via such approaches for electronic sensing performance has yet to be further explored. Here we show a strategy for modulating the multifaceted characteristics of PEDOT:PSS/PVA hydrogel structures via the combination of direct ink writing and freezing-thawing. The influence of material composition ratio on different properties of PEDOT: PSS/PVA hydrogel was examined. The internal microscale morphologies and the mechanical properties of PEDOT:PSS/PVA hydrogels prepared by freezing-thawing cycles at different freezing temperatures were characterized to reveal the correlation. Subsequently, direct ink writing followed by freezing-thawing was employed to generate PEDOT:PSS/PVA hydrogel structures with tunable characteristics. Eventually, electrophysiological sensing capability of PEDOT:PSS/PVA hydrogel structures obtained with the proposed fabrication method was demonstrated. The findings in this study may be utilized to generate conductive polymer hydrogel structures with specific properties for different sensing applications.

Understanding the in-membrane behaviors of membrane proteins requires precise control over lipid bilayers, yet such precision remains challenging due to their dynamic and amphiphilic nature. Here, a universal strategy is developed to construct open lipid membranes, which are defined as lipid bilayers confined within open DNA nanobarrels based on DNA origami, exhibiting programmable geometry and lateral fluidity. The open membranes exhibit high stability by optimizing the spatial distribution of the leading cholesterols and the lipid ratio. Through the engineering of complementary DNA interactions and shape-matching features, spatially defined membrane fusion can be achieved. Compared with the traditional closed scaffold systems, this strategy has allowed lipid diffusion across adjacent compartments within the same membrane. Such a membrane fusion process brings membrane-associated model proteins into proximity, thereby enhancing confined enzymatic reactions and benefiting the understanding of the dynamic interaction of the membrane proteins within the lipid bilayer. This platform provides a versatile system for investigating membrane protein organization, interaction dynamics, and functional coordination in controlled lipid contexts.

Epidermal sensors can offer continuous and noninvasive measurement of health indicators from the human body, therefore playing an increasingly important role in modern healthcare and human-machine interactions. In particular, soft and lightweight textile-based sensors can closely conform to the human epidermis, enhancing monitoring capability while improving wearing comfort. In the development of epidermal textile-based sensors, nanomaterials are widely used to augment sensing functionalities. However, the existing methods for incorporating nanomaterials into textile-based sensors typically involve different procedures for preparing, transferring, and patterning nanomaterials to customize sensing structures. Here we show that a laser-based approach can be utilized to convert textiles into 3-D graphenic sensing structures, achieving both in situ induction and facile customization. The material properties and microscale/nanoscale morphologies of laser-induced textile-based graphene were characterized, revealing the effect of varying laser power. Further, the electrical and mechanical characteristics of textile-based graphene were examined, laying the foundation for choosing appropriate lasing parameters to meet the requirements in epidermal sensing. To demonstrate the sensing potential of laser-induced textile-based graphene, epidermal sensors for measuring electrophysiological signals and humidity were developed respectively, and their performance was tuned with laser power. The presented approach may facilitate the generation of textile-based sensing devices for various epidermal monitoring applications.

In this paper, we review recent developments and the role of Graph Neural Networks (GNNs) in computational drug discovery, including molecule generation, molecular property prediction, and drug-drug interaction prediction. By summarizing the most recent developments in this area, we underscore the capabilities of GNNs to comprehend intricate molecular patterns, while exploring both their current and prospective applications. We initiate our discussion by examining various molecular representations, followed by detailed discussions and categorization of existing GNN models based on their input types and downstream application tasks. We also collect a list of commonly used benchmark datasets for a variety of applications. We conclude the paper with brief discussions and summarize common trends in this important research area.

Porous metals fabricated via three-dimensional (3D) printing have attracted extensive attention in many fields owing to their open pores and customization potential. However, dense internal structures produced by the powder bed fusion technique fails to meet the feature of porous materials in scenarios that demand large specific surface areas. Herein, we propose a strategy for 3D printing of titanium scaffolds featuring multiscale porous internal structures via powder modification and digital light processing (DLP). After modification, the titanium powders were composited with acrylic resin and maintained spherical shapes. Compared with the raw powder slurries, the modified powder slurries exhibited higher stability and preferable curing characteristics, and the depth sensitivity of the modified powder slurries with 45 vol% solid loading increased by approximately 72%. Green scaffolds were subsequently printed from the slurries with a solid loading reaching 45 vol% via DLP 3D printing. The scaffolds had macropores (pore diameters of approximately 1 mm) and internal open micropores (pore diameters of approximately 5.7–13.0 μ m) after sintering. Additionally, these small-featured (approximately 320 μ m) scaffolds retained sufficient compressive strength ((70.01 ± 3.53) MPa) even with high porosity (approximately 73.95%). This work can facilitate the fabrication of multiscale porous metal scaffolds with high solid loading slurries, offering potential for applications requiring high specific surface area ratios.

Micro/nanoscale 3D bioelectrodes gain increasing interest for electrophysiological recording of electroactive cells. Although 3D printing has shown promise to flexibly fabricate 3D bioelectronics compared with conventional microfabrication, relatively-low resolution limits the printed bioelectrode for high-quality signal monitoring. Here, a novel multi-material electrohydrodynamic printing (EHDP) strategy is proposed to fabricate bioelectronics with sub-microscale 3D gold pillars for in vitro electrophysiological recordings. EHDP is employed to fabricate conductive circuits for signal transmission, which are passivated by polyimide via extrusion-based printing. Laser-assisted EHDP is developed to produce 3D gold pillars featuring a diameter of 0.64 ± 0.04 µm. The 3D gold pillars demonstrate stable conductivity under the cell-culture environment. Living cells can conformally grow onto these sub-microscale 3D pillars with a height below 5 µm, which facilitates the highly-sensitive recording of extracellular signals with amplitudes <15 µV. The 3D pillars can apply electroporation currents to reversibly open the cellular membrane for intracellular recording, facilitating the measurement of subtle cellular electrophysiological activities. As a proof-of-concept demonstration, fully-printed chips with multiple culturing chambers and sensing bioelectronics are fabricated for zone-specific electrophysiological recording in drug testing. The proposed multi-material EHDP strategy enables rapid prototyping of organ-on-a-chip systems with 3D bioelectronics for high-quality electrophysiological recordings.

Functional conductive hydrogels with customizable shapes and structures facilitate seamless integration between biological and electronic interfaces. However, the current capacity to adjust the properties of conductive gels is constrained, frequently requiring complex post-processing methods to ensure gel formation and achieve a balance between mechanical and electrical properties. This significantly limits the flexibility in fabricating gel-based sensing interfaces. In this study, a 3D-printable, photo-crosslinked, carbon-based conductive nanocomposite hydrogel (FPCH) comprising poly(ether) F127 diacrylate (F127DA), Single-Walled carbon nanotubes (SWCNT), and poly(3,4-ethylenedioxythiophene)-polystyrene sulfonic acid (PEDOT:PSS) is developed. By optimizing the proportion of conductive fillers, the hydrogel achieves tunable modulus (as low as 90 kPa), high stretchability (up to 520% strain), conductivity (440 S m-1), and 3D printability. The conductive gel can be rapidly cured on demand via UV-induced crosslinking and demonstrates good biocompatibility. It functions not only as a "skin electronic tattoo" for multimodal applications, such as strain and humidity sensing and thermal compensation but also effectively stimulates the sciatic nerve in vivo at low voltage. Furthermore, electrodes fabricated using 3D printing technology offer conformal contact with brain tissue and enable real-time monitoring of electrophysiological signals, providing a versatile bioelectronic sensing interface for multi-modal applications adaptable for both the in vivo and in vitro environments.

Background:Hepatocellular carcinoma (HCC) is the most prevalent primary liver cancer, characterized by a poor prognosis. Many HCC patients are diagnosed at an advanced stage due to the lack of reliable prognostic biomarkers. G6PC1 (Glucose-6-Phosphatase Catalytic Subunit 1) is abnormally expressed in various cancers, including HCC. This study aimed to investigate the biomarker potential and biological functions of G6PC1 to elucidate its impact on HCC pathogenesis. Methods:G6PC1 expression levels were assessed using TCGA and GEO datasets. Prognostic implications were explored through Kaplan-Meier survival analysis. Potential regulatory transcription factors (TFs) were identified using four prediction tools, and functional mechanisms were investigated via GO and KEGG enrichment analyses. Associations between G6PC1 and HCC metabolic reprogramming, as well as the tumor microenvironment were analyzed. Results:G6PC1 exhibited low expression levels in HCC, which correlated with poor patient prognosis. HNF4A may act as a regulatory factor for G6PC1 in HCC. Functional analysis identified co-expressed genes associated with metabolism-related pathways. Furthermore, G6PC1 was implicated in metabolic reprogramming, immune infiltration, and immunotherapy response. Conclusion:Low G6PC1 expression, associated with poor HCC prognosis, is a potential prognostic biomarker. Integrated multi-omics analyses underscore its clinical significance, involvement in metabolic reprogramming, and immunomodulatory functions, providing a foundation for further investigation into its prognostic potential and mechanistic contributions in HCC.

Additive manufacturing (3D printing) technology aligns with the direction of precision and customization in future medicine, presenting a significant opportunity for innovative development in high-end medical devices. Currently, research and industrialization of 3D printed medical devices mainly focus on nondegradable implants and degradable implants. Primary areas including metallic orthopaedic implants, polyether-ether-ketone (PEEK) bone implants, and biodegradable implants have been developed for clinical and industrial application. Recent research achievements in these areas are reviewed, with a discussion on the additive manufacturing technologies and applications for customized implants. Challenges faced by different types of implants are analyzed from technological, application, and regulatory perspectives. Furthermore, prospects and suggestions for future development are outlined.

Pesticide residues in agri-foods have risk to human health and one solution is to develop simple and accurate methods for rapid detection. We developed a SERS sensor composed of gold nanoparticles (AuNPs) and bacterial cellulose nanocrystal (BCNC) to detect thiram in fruit juice. BCNC-SO3H was used as a stabilizer to support AuNPs via electrostatic repulsion, fabricating a BCNC-AuNPs SERS substrate with uniformly distributed AuNPs. This BCNC-AuNPs SERS substrate was applied to determine thiram residues in peach juice, apple juice, and grape juice with the limits of detection of 0.036 ppm, 0.044 ppm, and 0.044 ppm, respectively. The whole test took 12 min including sample preparation and analysis. The detection limits meet the maximum residue levels of thiram in fruit juices required by China, Europe and North America, indicating that this BCNC-based substrate could serve as a satisfactory SERS sensor for pesticide residue monitoring in the food supply chain.

Total phenolic content (TPC) and antioxidant capacity of maple syrup were determined using Raman spectroscopy and deep learning. TPC was determined by Folin-Ciocalteu assay, while the antioxidant capacity was measured by 2,2-diphenyl-1picrylhydrazyl (DPPH) assay, oxygen radical absorbance capacity (ORAC) assay, and ferric reducing antioxidant power (FRAP) assay. A total of 360 spectra were collected from 36 maple syrup samples of different colours (dark, amber, light) by both benchtop and portable Raman spectrometers. These spectra were used to establish predictive models for assessing the antioxidant profiles of maple syrup. Deep learning models developed along with portable Raman spectroscopy exhibited comparable predictive performance to those developed along with benchtop Raman spectroscopy. Base on the spectral dataset collected using portable Raman spectroscopy, the developed deep learning models exhibited low RMSEs (root mean square errors, 7.2-17.9 % of mean reference values), low MAEs (mean absolute errors, 5.2-13.1 % of mean reference values) and high R2 values (>0.88). The results showed a great goodness of fit and accuracy for predicting the antioxidant profiles of maple syrup, indicating the potential of using portable Raman spectrometer for on-site analysis of antioxidant profiles of maple syrup.

Continuous monitoring of physiological health status and effective protection against external hazards is an indispensable aspect of healthcare management for critically vulnerable populations, particularly for infants or babies. So, the exploration of all-in-one devices remains critical to avoiding their injury and illness. The integration of multiple properties such as sensing, electromagnetic protection, warming/cooling, and water/bacterial repellence into a common fabric is no doubt a promising solution to coping with diverse application scenarios. However, achieving simultaneous integration in an effective and durable fashion faces huge challenges. Herein, multifunctional fabric was achieved by sequentially coating MXene, carbon nanotubes (CNTs), and self-healing polyurethane (PU) onto cotton fabric. The outstanding conductivity of MXene and CNTs as well as the self-healing ability of PU synergistically enable a flexible, breathable, protective, and sensing fabric with a good durability. It could detect the body motions like bending of the finger, elbow, wrist, and knee, with a high gauge factor of 8.78 and fast response. Moreover, this sensing fabric could protect the wearers against electromagnetic waves and bacteria, delivering a minimum reflection loss of -57.6 dB at 7.6 GHz and high bacterial inhibition efficiency due to the incorporation of MXene and polyethylenimine. Besides, the electrothermal performance of carbonaceous materials enables them to act as a heater for body warmth. The synergistic design of this multifunctional textile offers a promising strategy for producing advanced smart textiles, holding great promise in infant or baby healthcare.

In vitro models are essential to a broad range of biomedical research, such as pathological studies, drug development, and personalized medicine. As a potentially transformative paradigm for 3D in vitro models, organ-on-a-chip (OOC) technology has been extensively developed to recapitulate sophisticated architectures and dynamic microenvironments of human organs by applying the principles of life sciences and leveraging micro- and nanoscale engineering capabilities. A pivotal function of OOC devices is to support multifaceted and timely characterization of cultured cells and their microenvironments. However, in-depth analysis of OOC models typically requires biomedical assay procedures that are labor-intensive and interruptive. Herein, the latest advances toward intelligent OOC (iOOC) systems, where sensors integrated with OOC devices continuously report cellular and microenvironmental information for comprehensive in situ bioanalysis, are examined. It is proposed that the multimodal data in iOOC systems can support closed-loop control of the in vitro models and offer holistic biomedical insights for diverse applications. Essential techniques for establishing iOOC systems are surveyed, encompassing in situ sensing, data processing, and dynamic modulation. Eventually, the future development of iOOC systems featuring cross-disciplinary strategies is discussed.

Active materials are capable of responding to external stimuli, as observed in both natural and synthetic systems, from sensitive plants to temperature-responsive hydrogels. Extrusion-based 3D printing of soft active materials facilitates the fabrication of intricate geometries with spatially programmed compositions and architectures at various scales, further enhancing the functionality of materials. This Feature Article summarizes recent advances in extrusion-based 3D printing of active materials in both non-living (i.e., synthetic) and living systems. It highlights emerging ink formulations and architectural designs that enable programmable properties, with a focus on complex shape morphing and controllable light-emitting patterns. The article also spotlights strategies for engineering living materials that can produce genetically encoded material responses and react to a variety of environmental stimuli. Lastly, it discusses the challenges and prospects for advancements in both synthetic and living composite materials from the perspectives of chemistry, modeling, and integration.

Cellular agriculture is an emerging biotechnology that employs animal, bacterial, or plant cell tissues to manufacture agricultural products. Bacterial cellulose (BC) is an exocellular polysaccharide produced by certain aerobic bacteria that has many applications in the food industry. The unique physicochemical properties of BC, such as crystallinity, degree of polymerization, water absorbing and holding capacity, and biocompatibility, make it a promising material to be applied in different fields. It is used as a thickener to maintain viscosity in foods, as a stabilizing agent, and can be added as a dietary fiber. The objective of this chapter is to review and summarize the current studies regarding BC from synthesis to its applications in agri-foods. The production methods including static culture, agitated culture, and culture in bioreactors are discussed. Finally, we review its use in food, food packaging, and biosensors.

There is an increasing demand for epidermal sensors that can adapt to the contours and the movements of the human body, but the fabrication of prevalent polymer-based epidermal sensors often involves costly materials and complex procedures. Paper has emerged as a cost-effective substrate for next-generation epidermal sensors, featuring such advantages as bendability, breathability, biocompatibility, and environment-friendliness. However, transducing materials are commonly introduced to paper substrates in post hoc manners or through timeconsuming syntheses, in addition to the direct manufacturing of paper. Here we report an integrative method to fabricate epidermal paper-based graphene sensors, where graphene induction and paper cutting can be achieved in a single lasing procedure to generate both transducing components and overall sensor formats. Lasing conditions are systematically explored, mainly to control the multifaceted properties of the obtained graphene transducers. The resultant paper-based graphene structures exhibit sufficient reliability in various scenarios regarding storage, lighting, and deformation. Paper-based graphene sensors are strategically designed in terms of overall formats, geometric patterns, hydrophilicity/hydrophobicity, surface functionalization, and readouts for measuring biophysical and biochemical information relevant to human health. The sensor performance can be optimized by adjusting laser power, and the calibrated sensitivities for mechanical strain, temperature, humidity, pH, and glucose are 76.93, -0.15% degrees C-1, 37.06 mu A %-1, 28.13 mV pH-1, and 1.26 mu A mM-1, respectively. Multimodal health monitoring is demonstrated with paper-based graphene sensors. Our approach can facilitate the generation of epidermal paper-based sensors and meet diverse requirements of health monitoring.

Bacteria infections pose a serious threat to public health, and it is urgent to develop facile and accurate detection methods. To meet the important need, a potable and high-sensitive surface enhanced Raman scattering (SERS) biosensor based on aptamer recognition and catalytic hairpin assembly (CHA) signal amplification was proposed for point-of-care detection of Staphylococcus aureus ( S. aureus ). The SERS biosensor contains three parts: recognition probes, SERS sensing chip, and SERS tags. The feasibility of the strategy was verified by gel electrophoresis, and the one-step test route was optimized. The bacteria SERS biosensor has a good linear relationship ranging from 10 to 10 7 CFU mL- 1 with high sensitivity low to 5 CFU mL- 1 , and shows excellent specificity, uniformity, and repeatability on S. aureus identification and enumeration, which can distinguish S. aureus from other bacteria. The SERS biosensor shows a good recovery rate (95.73 % -109.65 %) for testing S. aureus spiked in milk, and has good practicability for detecting S. aureus infected mouse wound, which provides a facile and reliable approach for detection of trace bacteria in the real samples.

The development of biomaterials capable of regulating cellular processes and guiding cell fate decisions has broad implications in tissue engineering, regenerative medicine, and cell-based assays for drug development and disease modeling. Recent studies have shown that three-dimensional (3D) nanoscale physical cues such as nanotopography can modulate various cellular processes like adhesion and endocytosis by inducing nanoscale curvature on the plasma and nuclear membranes. Two-dimensional (2D) biochemical cues such as protein micropatterns can also regulate cell function and fate by controlling cellular geometries. Development of biomaterials with precise control over nanoscale physical and biochemical cues can significantly influence programming cell function and fate. In this study, we utilized a laser-assisted micropatterning technique to manipulate the 2D architectures of cells on 3D nanopillar platforms. We performed a comprehensive analysis of cellular and nuclear morphology and deformation on both nanopillar and flat substrates. Our findings demonstrate the precise engineering of single cell architectures through 2D micropatterning on nanopillar platforms. We show that the coupling between the nuclear and cell shape is disrupted on nanopillar surfaces compared to flat surfaces. Furthermore, our results suggest that cell elongation on nanopillars enhances nanopillar-induced endocytosis. We believe our platform serves as a versatile tool for further explorations into programming cell function and fate through combined physical cues that create nanoscale curvature on cell membranes and biochemical cues that control the geometry of the cell.

Determination of pesticide residues remains a challenge in traditional Chinese medicines in which complex compounds may interfere with analysis signals. This study reports the development of a simple, effective, and high-throughput method combining gas chromatography-tandem mass spectrometry (GC-MS/MS) with either QuEChERS or solid phase extraction (SPE) to determine 147 pesticide residues in traditional Chinese medicines simultaneously. In SPE, the mixture of n-hexane and ethyl acetate (1:1, v/v) was selected to extract 147 pesticides in honeysuckle, and the extracted pesticides were determined by GC-MS/MS. The limits of detection for all pesticides were within 0.01-0.05 mg/kg. The recoveries were within 70-120% and the relative standard deviations were below 20% for over 90% pesticides. The coefficients of determination were up to 0.999 for the linearity between MS signals and different concentrations of pesticides (20-200 ng/mL). The analytical performance was confirmed in determining pesticide residues in dried tangerine peel. SPE achieved comparable recoveries for all pesticides compared to the QuEChERS method.