Study on 3D printed MXene-berberine-integrated scaffold for photo-activated antibacterial activity and bone regeneration.

The repair of mandibular defects is a challenging clinical problem, and associated infections often hinder the treatment, leading to failure in bone regeneration. Herein, a multifunctional platform is designed against the shortages of existing therapies for infected bone deficiency. 2D Ti3C2 MXene and berberine (BBR) are effectively loaded into 3D printing biphasic calcium phosphate (BCP) scaffolds. The prepared composite scaffolds take the feature of the excellent photothermal capacity of Ti3C2 as an antibacterial, mediating NIR-responsive BBR release under laser stimuli. Meanwhile, the sustained release of BBR enhances its antibacterial effect and further accelerates the bone healing process. Importantly, the integration of Ti3C2 improves the mechanical properties of the 3D scaffolds, which are beneficial for new bone formation. Their remarkable biomedical performances in vitro and in vivo present the outstanding antibacterial and osteogenic properties of the Ti3C2-BBR functionalized BCP scaffolds. The synergistic therapy makes it highly promising for repairing infected bone defects and provides insights into a wide range of applications of 2D nanosheets in biomedicine.

Identification of 12 hub genes associated to the pathogenesis of osteoporosis based on microarray and single-cell RNA sequencing data.

Osteoporosis is a common disease, especially among the elderly. This study aimed to comprehensively examine the roles of immune microenvironment in osteoporosis pathogenesis. Expression profiles of GSE35959, GSE7158, and GSE13850 datasets were used to analyze differential expression and identify hub genes related to immune features. Based on the single-cell RNA sequencing (scRNA-seq) data of an osteoporosis patient, different cell types were classified and the relation between immune environment and osteoporosis was explored. Twelve hub genes significantly associated with immune features were selected and 11 subgroups were defined using scRNA-seq data. The expression of two hub genes (CDKN1A and TEFM) was greatly altered during the transformation from mesenchymal stem cells (MSCs) to osteoblasts. Chemokines and chemokine receptors were differentially enriched in different cell types. CXCL12 was high-expressed in MSCs. This study emphasized that immune microenvironment played a critical role in the pathogenesis of osteoporosis. Chemokines and chemokine receptors can modify cell development and affect the interactions among different cell types, leading to unbalanced bone remodeling.

Recent advances in 2D material-based phototherapy.

Phototherapy, which generally refers to photothermal therapy (PTT) and photodynamic therapy (PDT), has received significant attention over the past few years since it is non-invasive, has effective selectivity, and has few side effects. As a result, it has become a promising alternative to traditional clinical treatments. At present, two-dimensional materials (2D materials) have proven to be at the forefront of the development of advanced nanomaterials due to their ultrathin structures and fascinating optical properties. As a result, much work has been put into developing phototherapy platforms based on 2D materials. This review summarizes the current developments in 2D materials beyond graphene for phototherapy, focusing on the novel approaches of PTT and PDT. New methods are being developed to go above and beyond conventional treatment to fully use the potential of 2D materials. Additionally, the efficacy of cutting-edge phototherapy is assessed, and the existing difficulties and future prospects of 2D materials for phototherapy are covered.

Smart biomaterials and their potential applications in tissue engineering.

Smart biomaterials have been rapidly advancing ever since the concept of tissue engineering was proposed. Interacting with human cells, smart biomaterials can play a key role in novel tissue morphogenesis. Various aspects of biomaterials utilized in or being sought for the goal of encouraging bone regeneration, skin graft engineering, and nerve conduits are discussed in this review. Beginning with bone, this study summarizes all the available bioceramics and materials along with their properties used singly or in conjunction with each other to create scaffolds for bone tissue engineering. A quick overview of the skin-based nanocomposite biomaterials possessing antibacterial properties for wound healing is outlined along with skin regeneration therapies using infrared radiation, electrospinning, and piezoelectricity, which aid in wound healing. Furthermore, a brief overview of bioengineered artificial skin grafts made of various natural and synthetic polymers has been presented. Finally, by examining the interactions between natural and synthetic-based biomaterials and the biological environment, their strengths and drawbacks for constructing peripheral nerve conduits are highlighted. The description of the preclinical outcome of nerve regeneration in injury healed with various natural-based conduits receives special attention. The organic and synthetic worlds collide at the interface of nanomaterials and biological systems, producing a new scientific field including nanomaterial design for tissue engineering.

An Effective and Lightweight Deep Electrocardiography Arrhythmia Recognition Model Using Novel Special and Native Structural Regularization Techniques on Cardiac Signal.

Recently, cardiac arrhythmia recognition from electrocardiography (ECG) with deep learning approaches is becoming popular in clinical diagnosis systems due to its good prognosis findings, where expert data preprocessing and feature engineering are not usually required. But a lightweight and effective deep model is highly demanded to face the challenges of deploying the model in real-life applications and diagnosis accurately. In this work, two effective and lightweight deep learning models named Deep-SR and Deep-NSR are proposed to recognize ECG beats, which are based on two-dimensional convolution neural networks (2D CNNs) while using different structural regularizations. First, 97720 ECG beats extracted from all records of a benchmark MIT-BIH arrhythmia dataset have been transformed into 2D RGB (red, green, and blue) images that act as the inputs to the proposed 2D CNN models. Then, the optimization of the proposed models is performed through the proper initialization of model layers, on-the-fly augmentation, regularization techniques, Adam optimizer, and weighted random sampler. Finally, the performance of the proposed models is evaluated by a stratified 5-fold cross-validation strategy along with callback features. The obtained overall accuracy of recognizing normal beat and three arrhythmias (V-ventricular ectopic, S-supraventricular ectopic, and F-fusion) based on the Association for the Advancement of Medical Instrumentation (AAMI) is 99.93%, and 99.96% for the proposed Deep-SR model and Deep-NSR model, which demonstrate that the effectiveness of the proposed models has surpassed the state-of-the-art models and also expresses the higher model generalization. The received results with model size suggest that the proposed CNN models especially Deep-NSR could be more useful in wearable devices such as medical vests, bracelets for long-term monitoring of cardiac conditions, and in telemedicine to accurate diagnose the arrhythmia from ECG automatically. As a result, medical costs of patients and work pressure on physicians in medicals and clinics would be reduced effectively.