Boron neutron capture therapy: a promising radiation treatment modality.

Boron neutron capture therapy (BNCT) is a progressive medical technique that combines the use of boron compounds and neutron radiation to preferentially destroy cancer cells while minimizing, but not entirely eliminating, damage to surrounding healthy tissues. This therapy relies on B, delivered via specific compounds, capturing neutrons and undergoing a nuclear reaction. This capture leads to the emission of high-energy alpha particles and lithium ions, which selectively damage the boron-loaded tumour cells, ultimately leading to their destruction.

Automated confidence estimation in deep learning auto-segmentation for brain organs at risk on MRI for radiotherapy.

Purpose: We have built a novel AI-driven QA method called AutoConfidence (ACo), to estimate segmentation confidence on a per-voxel basis without gold standard segmentations, enabling robust, efficient review of automated segmentation (AS). We have demonstrated this method in brain OAR AS on MRI, using internal and external (third-party) AS models.

Methods: Thirty-two retrospectives, MRI planned, glioma cases were randomly selected from a local clinical cohort for ACo training.

Dosimetric impact of contour editing on CT and MRI deep-learning autosegmentation for brain OARs.

Purpose: To establish the clinical applicability of deep-learning organ-at-risk autocontouring models (DL-AC) for brain radiotherapy. The dosimetric impact of contour editing, prior to model training, on performance was evaluated for both CT and MRI-based models. The correlation between geometric and dosimetric measures was also investigated to establish whether dosimetric assessment is required for clinical validation.

GL67 lipid-based liposomal formulation for efficient siRNA delivery into human lung cancer cells.

The efficient delivery of small interfering RNA (siRNA) to the targeted cells significantly affects the regulation of the overexpressed proteins involved in the progression of several genetic diseases. SiRNA molecules in naked form suffer from low internalization across the cell membrane, high susceptibility to degradation by nuclease enzyme and low stability, which hinder their efficacy. Therefore, there is an urge to develop a delivery system that can protect siRNA from degradation and facilitate their uptake across the cell membrane.

Liposome-Encapsulated Tobramycin and IDR-1018 Peptide Mediated Biofilm Disruption and Enhanced Antimicrobial Activity against .

The inadequate eradication of pulmonary infections and chronic inflammation are significant complications in cystic fibrosis (CF) patients, who usually suffer from persistent and frequent lung infections caused by several pathogens, particularly Pseudomonas aeruginosa (P. aeruginosa). The ability of pathogenic microbes to protect themselves from biofilms leads to the development of an innate immune response and antibiotic resistance.

An Efficient Framework for Securing the Smart City Communication Networks.

Recently, smart cities have increasingly been experiencing an evolution to improve the lifestyle of citizens and society. These emerge from the innovation of information and communication technologies (ICT) which are able to create a new economic and social opportunities. However, there are several challenges regarding our security and expectation of privacy.

Facial Features Detection System To Identify Children With Autism Spectrum Disorder: Deep Learning Models.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder associated with brain development that subsequently affects the physical appearance of the face. Autistic children have different patterns of facial features, which set them distinctively apart from typically developed (TD) children. This study is aimed at helping families and psychiatrists diagnose autism using an easy technique, viz.

Augmented Reality (AR) and Cyber-Security for Smart Cities-A Systematic Literature Review.

Augmented Reality (AR) and cyber-security technologies have existed for several decades, but their growth and progress in recent years have increased exponentially. The areas of application for these technologies are clearly heterogeneous, most especially in purchase and sales, production, tourism, education, as well as social interaction (games, entertainment, communication). Essentially, these technologies are recognized worldwide as some of the pillars of the new industrial revolution envisaged by the industry 4.

Chest X-ray Classification for the Detection of COVID-19 Using Deep Learning Techniques.

Recent technological developments pave the path for deep learning-based techniques to be used in almost every domain of life. The precision of deep learning techniques make it possible for these to be used in the medical field for the classification and detection of various diseases. Recently, the coronavirus (COVID-19) pandemic has put a lot of pressure on the health system all around the world.

Phytosomes as an Emerging Nanotechnology Platform for the Topical Delivery of Bioactive Phytochemicals.

The emergence of phytosome nanotechnology has a potential impact in the field of drug delivery and could revolutionize the current state of topical bioactive phytochemicals delivery. The main challenge facing the translation of the therapeutic activity of phytochemicals to a clinical setting is the extremely low absorption rate and poor penetration across biological barriers (i.e.