Potentiality of phosphide-based nanotubes for breast cancer detection: A DFT investigation.

Breast cancer is one of the most basilisk cancers for women due to its high mortality rate which can be prevented drastically with early-stage detection. In this work, the adsorption mechanism of two volatile organic compounds that are present in the breath of breast cancer patients, 2-Methyloctane and 3, 3-Dimethylpentane, has been investigated on aluminum phosphide nanotubes (AlPNT) and gallium phosphide nanotubes (GaPNT) in order to understand their feasibility as sensor materials to diagnosis breast cancer at early stage. We have used the quantum mechanical approach by employing density functional theory using B3LYP-D3 hybrid potential for noncovalent interaction along with the LanL2DZ basis in the Gaussian 09 software package. The adsorption properties analyses suggest that GaPNT exhibits better sensing behavior as well as proclaims 12.6% greater adsorption energy for 2-Methyloctane and 9.4% greater adsorption energy for 3, 3-Dimethylpentane than AlPNT. Other structural and electric properties analyses satisfy this conclusion and suggest that GaPNT exhibits higher stability than AlPNT and could possibly be a potential candidate for developing biosensors to detect breast cancer at the preliminary stages.

Skin Cancer Segmentation and Classification Using Vision Transformer for Automatic Analysis in Dermatoscopy-Based Noninvasive Digital System.

Skin cancer is a significant health concern worldwide, and early and accurate diagnosis plays a crucial role in improving patient outcomes. In recent years, deep learning models have shown remarkable success in various computer vision tasks, including image classification. In this research study, we introduce an approach for skin cancer classification using vision transformer, a state-of-the-art deep learning architecture that has demonstrated exceptional performance in diverse image analysis tasks. The study utilizes the HAM10000 dataset; a publicly available dataset comprising 10,015 skin lesion images classified into two categories: benign (6705 images) and malignant (3310 images). This dataset consists of high-resolution images captured using dermatoscopes and carefully annotated by expert dermatologists. Preprocessing techniques, such as normalization and augmentation, are applied to enhance the robustness and generalization of the model. The vision transformer architecture is adapted to the skin cancer classification task. The model leverages the self-attention mechanism to capture intricate spatial dependencies and long-range dependencies within the images, enabling it to effectively learn relevant features for accurate classification. Segment Anything Model (SAM) is employed to segment the cancerous areas from the images; achieving an IOU of 96.01% and Dice coefficient of 98.14% and then various pretrained models are used for classification using vision transformer architecture. Extensive experiments and evaluations are conducted to assess the performance of our approach. The results demonstrate the superiority of the vision transformer model over traditional deep learning architectures in skin cancer classification in general with some exceptions. Upon experimenting on six different models, ViT-Google, ViT-MAE, ViT-ResNet50, ViT-VAN, ViT-BEiT, and ViT-DiT, we found out that the ML approach achieves 96.15% accuracy using Google's ViT patch-32 model with a low false negative ratio on the test dataset, showcasing its potential as an effective tool for aiding dermatologists in the diagnosis of skin cancer.

Laminin coated diamond electrodes for neural stimulation.

The performance of many implantable neural stimulation devices is degraded due to the loss of neurons around the electrodes by the body's natural biological responses to a foreign material. Coating of electrodes with biomolecules such as extracellular matrix proteins is one potential route to suppress the adverse responses that lead to loss of implant functionality. Concurrently, however, the electrochemical performance of the stimulating electrode must remain optimal to continue to safely provide sufficient charge for neural stimulation. We have previously found that oxygen plasma treated nitrogen included ultrananocrystalline diamond coated platinum electrodes exhibit superior charge injection capacity and electrochemical stability for neural stimulation (Sikder et al., 2019). To fabricate bioactive diamond electrodes, in this work, laminin, an extracellular matrix protein known to be involved in inter-neuron adhesion and recognition, was used as an example biomolecule. Here, laminin was covalently coupled to diamond electrodes. Electrochemical analysis found that the covalently coupled films were robust and resulted in minimal change to the charge injection capacity of diamond electrodes. The successful binding of laminin and its biological activity was further confirmed using primary rat cortical neuron cultures, and the coated electrodes showed enhanced cell attachment densities and neurite outgrowth. The method proposed in this work is versatile and adaptable to many other biomolecules for producing bioactive diamond electrodes, which are expected to show reduced the inflammatory responses in vivo.

Wireless induction coils embedded in diamond for power transfer in medical implants.

Wireless power and data transfer to medical implants is a research area where improvements in current state-of-the-art technologies are needed owing to the continuing efforts for miniaturization. At present, lithographical patterning of evaporated metals is widely used for miniature coil fabrication. This method produces coils that are limited to low micron or nanometer thicknesses leading to high impedance values and thus limiting their potential quality. In the present work we describe a novel technique, whereby trenches were milled into a diamond substrate and filled with silver active braze alloy, enabling the manufacture of small, high cross-section, low impedance microcoils capable of transferring up to 10 mW of power up to a distance of 6 mm. As a substitute for a metallic braze line used for hermetic sealing, a continuous metal loop when placed parallel and close to the coil surface reduced power transfer efficiency by 43%, but not significantly, when placed perpendicular to the microcoil surface. Encapsulation of the coil by growth of a further layer of diamond reduced the quality factor by an average of 38%, which can be largely avoided by prior oxygen plasma treatment. Furthermore, an accelerated ageing test after encapsulation showed that these coils are long lasting. Our results thus collectively highlight the feasibility of fabricating a high-cross section, biocompatible and long lasting miniaturized microcoil that could be used in either a neural recording or neuromuscular stimulation device.

Combined effect of cortical cytoskeleton and transmembrane proteins on domain formation in biomembranes.

We investigate the combined effects of transmembrane proteins and the subjacent cytoskeleton on the dynamics of phase separation in multicomponent lipid bilayers using computer simulations of a particle-based implicit solvent model for lipid membranes with soft-core interactions. We find that microphase separation can be achieved by the protein confinement by the cytoskeleton. Our results have relevance to the finite size of lipid rafts in the plasma membrane of mammalian cells.