Multi-Scale 3D Cephalometric Landmark Detection Based on Direct Regression with 3D CNN Architectures.

Background: Cephalometric analysis is important in diagnosing and planning treatments for patients, traditionally relying on 2D cephalometric radiographs. With advancements in 3D imaging, automated landmark detection using deep learning has gained prominence. However, 3D imaging introduces challenges due to increased network complexity and computational demands.

Poly(HEMA-co-MMA) Hydrogel Scaffold for Tissue Engineering with Controllable Morphology and Mechanical Properties Through Self-Assembly.

Poly(2-hydroxyethyl methacrylate) (PHEMA) has been widely used in medical materials for several decades. However, the poor mechanical properties of this material have limited its application in the field of tissue engineering. The purpose of this study was to fabricate a scaffold with suitable mechanical properties and in vitro cell responses for soft tissue by using poly(HEMA-co-MMA) with various concentration ratios of hydroxyethyl methacrylate (HEMA) and methyl methacrylate (MMA).

Biomechanical Evaluation of Hydroxyapatite/poly-l-lactide Fixation in Mandibular Body Reconstruction with Fibula Free Flap: A Finite Element Analysis Incorporating Material Properties and Masticatory Function Evaluation.

In reconstructive surgery following partial mandibulectomy, the biomechanical integrity of the fibula free flap applied to the remaining mandibular region directly influences the prognosis of the surgery. The purpose of this study is to evaluate the biomechanical integrity of two fixation materials [titanium (Ti) and hydroxyapatite/poly-L-lactide (HA-PLLA)]. In this study, we simulated the mechanical properties of miniplate and screw fixations in two different systems by finite element analysis.

For a clinical application of optical triangulation to assess respiratory rate using an RGB camera and a line laser.

This paper presents a non-contact and unrestrained respiration monitoring system based on the optical triangulation technique. The proposed system consists of a red-green-blue (RGB) camera and a line laser installed to face the frontal thorax of a human body. The underlying idea of the work is that the camera and line laser are mounted in opposite directions, unlike other research.

Nucleic Acid Amplification Circuit-Based Hydrogel (NACH) Assay for One-Step Detection of Metastatic Gastric Cancer-Derived Exosomal miRNA.

Gastric cancer (GC) is recognized as the fifth most prevalent malignant tumor worldwide. It is characterized by diverse clinical symptoms, treatment responses, and prognoses. In GC prognosis, the promotion of epithelial-mesenchymal transition (EMT) fosters cancer cell invasion and metastasis, thereby triggering the dissemination of tumor cells.

High-Intensity Focused Ultrasound Increases Facial Adipogenesis in a Swine Model via Modulation of Adipose-Derived Stem Cell Cilia.

Decreased medial cheek fat volume during aging leads to loss of a youthful facial shape. Increasing facial volume by methods such as adipose-derived stem cell (ASC) injection can produce facial rejuvenation. High-intensity focused ultrasound (HIFU) can increase adipogenesis in subcutaneous fat by modulating cilia on ASCs, which is accompanied by increased HSP70 and decreased NF-κB expression.

Unraveling the Potential of Attentive Bi-LSTM for Accurate Obesity Prognosis: Advancing Public Health towards Sustainable Cities.

The global prevalence of obesity presents a pressing challenge to public health and healthcare systems, necessitating accurate prediction and understanding for effective prevention and management strategies. This article addresses the need for improved obesity prediction models by conducting a comprehensive analysis of existing machine learning (ML) and deep learning (DL) approaches. This study introduces a novel hybrid model, Attention-based Bi-LSTM (ABi-LSTM), which integrates attention mechanisms with bidirectional Long Short-Term Memory (Bi-LSTM) networks to enhance interpretability and performance in obesity prediction.

Dual structure-switching aptamer-mediated signal amplification cascade for SARS-CoV-2 detection.

Since the outbreak of the novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) at the end of 2019, the spread of the virus has posed a significant threat to public health and the global economy. This work proposed a one-step, dual-structure-switching aptamer-mediated signal amplification cascade for rapid and sensitive detection of the SARS-CoV-2 nucleocapsid protein. This system consisted of two DNA aptamers with structure-switching functionality and fuel DNA, where a cascade of strand hybridization and displacement triggered fluorescence generation and signal amplification.

Genetically engineered bacteriophages as novel nanomaterials: applications beyond antimicrobial agents.

Bacteriophages, also known as phages, are viruses that replicate in bacteria and archaea. Phages were initially discovered as antimicrobial agents, and they have been used as therapeutic agents for bacterial infection in a process known as "phage therapy." Recently, phages have been investigated as functional nanomaterials in a variety of areas, as they can function not only as therapeutic agents but also as biosensors and tissue regenerative materials.

Extraction of γ-chitosan from insects and fabrication of PVA/γ-chitosan/kaolin nanofiber wound dressings with hemostatic properties.

A nanofiber-based composite nonwoven fabric was fabricated for hemostatic wound dressing, integrating polyvinyl alcohol (PVA), kaolin, and γ-chitosan extracted from three type of insects. The γ-chitosan extracted from Protaetia brevitarsis seulensis exhibited the highest yield at 21.5%, and demonstrated the highest moisture-binding capacity at 535.

Numerical Investigation of Layered Homogeneous Skull Model for Simulations of Transcranial Focused Ultrasound.

Background And Objectives: The influence of the intracranial pressure field must be discussed with the development of a single-element transducer for low-intensity transcranial focused ultrasound because the skull plays a significant role in blocking and dispersing ultrasound wave propagation. Ultrasound propagation is mainly affected by the structure and acoustic properties of the skull; thus, we aimed to investigate the impact of simplifying the acoustic properties of the skull on the simulation of the transcranial pressure field to present guidance for efficient skull modeling in full-wave simulations.

Materials And Methods: We constructed a three-dimensional computational model for ultrasound transmission with the same structure but varying acoustic properties of the skull.

On-site detection of methicillin-resistant Staphylococcus aureus (MRSA) utilizing G-quadruplex based isothermal exponential amplification reaction (GQ-EXPAR).

Methicillin-resistant Staphylococcus aureus (MRSA) has a high incidence in infectious hospitals and communities, highlighting the need for early on-site detection due to its resistance to methicillin antibiotics. The present study introduces a highly sensitive detection system for mecA, a crucial methicillin marker, utilizing an RCA-based isothermal exponential amplification reaction. The G-quadruplex-based isothermal exponential amplification reaction (GQ-EXPAR) method designs probes to establish G-quadruplex secondary structures incorporating thioflavin T for fluorescence.

Surface Modification of Polyetheretherketone (PEEK) Intervertebral Fusion Implant Using Polydopamine Coating for Improved Bioactivity.

The occurrence of bone diseases has been increasing rapidly, in line with the aging population. A representative spinal fusion material, polyetheretherketone (PEEK), is advantageous in this regard as it can work in close proximity to the elastic modulus of cancellous bone. However, if it is used without surface modification, the initial osseointegration will be low due to lack of bioactivity, resulting in limitations in surgical treatment.

A Finite Element Analysis Study of Edentulous Model with Complete Denture to Simulate Masticatory Movement.

The purposes of this study are to establish and validate a finite element (FE) model using finite element analysis methods and to identify optimal loading conditions to simulate masticatory movement. A three-dimensional FE model of the maxillary and mandibular cortical bone, cancellous bone, and gingiva was constructed based on edentulous cone-beam-computed tomography data. Dental computer-aided design software was used to design the denture base and artificial teeth to produce a complete denture.

Camera sheath with transformable head for minimally invasive surgical instruments.

Introduction: This paper presents a camera sheath that can be assembled to various minimally invasive surgical instruments and provide the localized view of the instrument tip.

Material And Methods: The advanced transformable head structure (ATHS) that overcomes the trade-off between the camera resolution and the instrument size is designed for the sheath. Design solutions to maintain the alignment between the camera's line of sight and the instrument tip direction during the transformation of the ATHS are derived and applied to the prototype of the sheath.

Ionizing radiation‑induced modification of nialamide as an anti‑inflammatory agent against lipopolysaccharide‑induced RAW 264.7 and DH82 cells.

Nialamide is a non-selective monoamine oxidase inhibitor that was widely used as an antidepressant. However, it has been prohibited for decades in the depressive medicine market due to the adverse hepatotoxic side effects. The re-use of drugs that have been withdrawn from the market represents a promising approach for the development of novel incrementally modified drugs and, in this context, ionizing radiation can serve as a powerful tool for producing new drug candidates.

deepPGSegNet: MRI-based pituitary gland segmentation using deep learning.

Introduction: In clinical research on pituitary disorders, pituitary gland (PG) segmentation plays a pivotal role, which impacts the diagnosis and treatment of conditions such as endocrine dysfunctions and visual impairments. Manual segmentation, which is the traditional method, is tedious and susceptible to inter-observer differences. Thus, this study introduces an automated solution, utilizing deep learning, for PG segmentation from magnetic resonance imaging (MRI).

Automated Quantification of Total Cerebral Blood Flow from Phase-Contrast MRI and Deep Learning.

Knowledge of input blood to the brain, which is represented as total cerebral blood flow (tCBF), is important in evaluating brain health. Phase-contrast (PC) magnetic resonance imaging (MRI) enables blood velocity mapping, allowing for noninvasive measurements of tCBF. In the procedure, manual selection of brain-feeding arteries is an essential step, but is time-consuming and often subjective.