Direct ink writing of vancomycin-loaded polycaprolactone/ polyethylene oxide/ hydroxyapatite 3D scaffolds

Novel inks were formulated by dissolving polycaprolactone (PCL), a hydrophobic polymer, in organic solvent systems; polyethylene oxide (PEO) was incorporated to extend the range of hydrophilicity of the system. Hydroxyapatite (HAp) with a weight ratio of 55–85% was added to the polymer-based solution to mimic the material composition of natural bone tissue. The direct ink writing (DIW) technique was applied to extrude the formulated inks to fabricate the predesigned tissue scaffold structures; the influence of HAp concentration was investigated. The results indicate that in comparison to other inks containing HAp (55%, 75%, and 85%w/w), the ink containing 65% w/w HAp had faster ink recovery behavior; the fabricated scaffold had a rougher surface as well as better mechanical properties and wettability. It is noted that the 65% w/w HAp concentration is similar to the inorganic composition of natural bone tissue. The elastic modulus values of PCL/PEO/HAp scaffolds were in the range of 4–12 MPa; the values were dependent on the HAp concentration. Furthermore, vancomycin as a model drug was successfully encapsulated in the PCL/PEO/HAp composite scaffold for drug release applications. This paper presents novel drug-loaded PCL/PEO/HAp inks for 3D scaffold fabrication using the DIW printing technique for potential bone scaffold applications.     

A Smart Deep Convolutional Neural Network for Real-Time Surface Inspection

A proper detection and classification of defects in steel sheets in real time have become a requirement for manufacturing these products, largely used in many industrial sectors. However, computers used in the production line of small to medium size companies, in general, lack performance to attend real-time inspection with high processing demands. In this paper, a smart deep convolutional neural network for using in real-time surface inspection of steel rolling sheets is proposed. The architecture is based on the state-of-the-art SqueezeNet approach, which was originally developed for usage with autonomous vehicles. The main features of the proposed model are: small size and low computational burden. The model is 10 to 20 times smaller when compared to other networks designed for the same task, and more than 700 times smaller than general networks. Also, the number of floating-point operations for a prediction is about 50 times lower than the ones used for similar tasks. Despite its small size, the proposed model achieved near-perfect accuracy on a public dataset of 1800 images of six types of steel rolling defects.     

Capsiate Intake with Exercise Training Additively Reduces Fat Deposition in Mice on a High-Fat Diet,but Not without Exercise Training

While exercise training (ET) is an efficient strategy to manage obesity, it is recommended with a dietary plan to maximize the antiobesity functions owing to a compensational increase in energy intake. Capsiate is a notable bioactive compound for managing obesity owing to its capacity to increase energy expenditure. We aimed to examine whether the antiobesity effects of ET can be further enhanced by capsiate intake (CI) and determine its effects on resting energy expenditure and metabolic molecules. Mice were randomly divided into four groups (n = 8 per group) and fed high-fat diet. Mild-intensity treadmill ET was conducted five times/week; capsiate (10 mg/kg) was orally administered daily. After 8 weeks, resting metabolic rate and metabolic molecules were analyzed. ET with CI additively reduced the abdominal fat rate by 18% and solely upregulated beta-3-adrenoceptors in adipose tissue (p = 0.013) but did not affect the metabolic molecules in skeletal muscles. Surprisingly, CI without ET significantly increased the abdominal fat rate (p = 0.001) and reduced energy expenditure by 9%. Therefore, capsiate could be a candidate compound for maximizing the antiobesity effects of ET by upregulating beta-3-adrenoceptors in adipose tissue, but CI without ET may not be beneficial in managing obesity.     

A Distinct Cytokine Profile and Stromal Vascular Fraction Metabolic Status without Significant Changes in the Lipid Composition Characterizes Lipedema

Lipedema is an adipose tissue disorder characterized by the disproportionate increase of subcutaneous fat tissue in the lower and/or upper extremities. The underlying pathomechanism remains unclear and no molecular biomarkers to distinguish the disease exist, leading to a large number of undiagnosed and misdiagnosed patients. To unravel the distinct molecular characteristic of lipedema we performed lipidomic analysis of the adipose tissue and serum of lipedema versus anatomically- and body mass index (BMI)-matched control patients. Both tissue groups showed no significant changes regarding lipid composition. As hyperplastic adipose tissue represents low-grade inflammation, the potential systemic effects on circulating cytokines were evaluated in lipedema and control patients using the Multiplex immunoassay system. Interestingly, increased systemic levels of interleukin 11 (p = 0.03), interleukin 28A (p = 0.04) and interleukin 29 (p = 0.04) were observed. As cytokines can influence metabolic activity, the metabolic phenotype of the stromal vascular fraction was examined, revealing significantly increased mitochondrial respiration in lipedema. In conclusion, despite sharing a comparable lipid profile with healthy adipose tissue, lipedema is characterized by a distinct systemic cytokine profile and metabolic activity of the stromal vascular fraction.     

Sequential alignment attention model for scene text recognition

Scene text recognition has been a hot research topic in computer vision due to its various applications. The state-of-the-art solutions usually depend on the attention-based encoder-decoder framework that learns the mapping between input images and output sequences in a purely data-driven way. Unfortunately, there often exists severe misalignment between feature areas and text labels in real-world scenarios. To address this problem, this paper proposes a sequential alignment attention model to enhance the alignment between input images and output character sequences. In this model, an attention gated recurrent unit (AGRU) is first devised to distinguish the text and background regions, and further extract the localized features focusing on sequential text regions. Furthermore, CTC guided decoding strategy is integrated into the popular attention-based decoder, which not only helps to boost the convergence of the training but also enhances the well-aligned sequence recognition. Extensive experiments on various benchmarks, including the IIIT5k, SVT, and ICDAR datasets, show that our method substantially outperforms the state-of-the-art methods.     

Recent Advances in Design of Functional Biocompatible Hydrogels for Bone Tissue Engineering

Bone related diseases have caused serious threats to human health owing to their complexity and specificity. Fortunately, owing to the unique 3D network structure with high aqueous content and functional properties, emerging hydrogels are regarded as one of the most promising candidates for bone tissue engineering, such as repairing cartilage injury, skull defect, and arthritis. Herein, various design strategies and synthesis methods (e.g., 3D-printing technology and nanoparticle composite strategy) are introduced to prepare implanted hydrogel scaffolds with tunable mechanical strength, favorable biocompatibility, and excellent bioactivity for applying in bone regeneration. Injectable hydrogels based on biocompatible materials (e.g., collagen, hyaluronic acid, chitosan, polyethylene glycol, etc.) possess many advantages in minimally invasive surgery, including adjustable physicochemical properties, filling irregular shapes of defect sites, and on-demand release drugs or growth factors in response to different stimuli (e.g., pH, temperature, redox, enzyme, light, magnetic, etc.). In addition, drug delivery systems based on micro/nanogels are discussed, and its numerous promising designs used in the application of bone diseases (e.g., rheumatoid arthritis, osteoarthritis, cartilage defect) are also briefed in this review. Particularly, several key factors of hydrogel scaffolds (e.g., mechanical property, pore size, and release behavior of active factors) that can induce bone tissue regeneration are also summarized in this review. It is anticipated that advanced approaches and innovative ideas of bioactive hydrogels will be exploited in the clinical field and increase the life quality of patients with the bone injury.     

Single Cell Bioprinting with Ultrashort Laser Pulses

Tissue engineering requires the precise positioning of mammalian cells and biomaterials on substrate surfaces or in preprocessed scaffolds. Although the development of 2D and 3D bioprinting technologies has made substantial progress in recent years, precise, cell-friendly, easy to use, and fast technologies for selecting and positioning mammalian cells with single cell precision are still in need. A new laser-based bioprinting approach is therefore presented, which allows the selection of individual cells from complex cell mixtures based on morphology or fluorescence and their transfer onto a 2D target substrate or a preprocessed 3D scaffold with single cell precision and high cell viability (93–99% cell survival, depending on cell type and substrate). In addition to precise cell positioning, this approach can also be used for the generation of 3D structures by transferring and depositing multiple hydrogel droplets. By further automating and combining this approach with other 3D printing technologies, such as two-photon stereolithography, it has a high potential of becoming a fast and versatile technology for the 2D and 3D bioprinting of mammalian cells with single cell resolution.     

Amyloid-Beta Induces Different Expression Pattern of Tissue Transglutaminase and Its Isoforms on Olfactory Ensheathing Cells: Modulatory Effect of Indicaxanthin

Herein, we assessed the effect of full native peptide of amyloid-beta (Aβ) (1-42) and its fragments (25-35 and 35-25) on tissue transglutaminase (TG2) and its isoforms (TG2-Long and TG2-Short) expression levels on olfactory ensheathing cells (OECs). Vimentin and glial fibrillary acid protein (GFAP) were also studied. The effect of the pre-treatment with indicaxanthin from Opuntia ficus-indica fruit on TG2 expression levels and its isoforms, cell viability, total reactive oxygen species (ROS), superoxide anion (O₂⁻), and apoptotic pathway activation was assessed. The levels of Nestin and cyclin D1 were also evaluated. Our findings highlight that OECs exposure to Aβ(1-42) and its fragments induced an increase in TG2 expression levels and a different expression pattern of its isoforms. Indicaxanthin pre-treatment reduced TG2 overexpression, modulating the expression of TG2 isoforms. It reduced total ROS and O₂⁻ production, GFAP and Vimentin levels, inhibiting apoptotic pathway activation. It also induced an increase in the Nestin and cyclin D1 expression levels. Our data demonstrated that indicaxanthin pre-treatment stimulated OECs self-renewal through the reparative activity played by TG2. They also suggest that Aβ might modify TG2 conformation in OECs and that indicaxanthin pre-treatment might modulate TG2 conformation, stimulating neural regeneration in Alzheimer’s disease.