Dermoscopy is the visual examination of the skin under a polarized or non-polarized light source. By using dermoscopic equipment, many lesion patterns that are invisible under visible light can be clearly distinguished. Thus, more accurate decisions can be made regarding the treatment of skin lesions. The use of images collected from a dermoscope has both increased the performance of human examiners and allowed the development of deep learning models. The availability of large-scale dermoscopic datasets has allowed the development of deep learning models that can classify skin lesions with high accuracy. However, most dermoscopic datasets contain images that were collected from digital dermoscopic devices, as these devices are frequently used for clinical examination. However, dermatologists also often use non-digital hand-held (optomechanical) dermoscopes. This study presents a dataset consisting of dermoscopic images taken using a mobile phone-attached hand-held dermoscope. Four deep learning models based on the MobileNetV1, MobileNetV2, NASNetMobile, and Xception architectures have been developed to classify eight different lesion types using this dataset. The number of images in the dataset was increased with different data augmentation methods. The models were initialized with weights that were pre-trained on the ImageNet dataset, and then they were further fine-tuned using the presented dataset. The most successful models on the unseen test data, MobileNetV2 and Xception, had performances of 89.18% and 89.64%. The results were evaluated with the 5-fold cross-validation method and compared. Our method allows for automated examination of dermoscopic images taken with mobile phone-attached hand-held dermoscopes.

Accurate assessment of cell stiffness distribution is essential due to the critical role of cell mechanobiology in regulation of vital cellular processes like proliferation, adhesion, migration, and motility. Stiffness provides critical information in understanding onset and progress of various diseases, including metastasis and differentiation of cancer. Atomic force microscopy and optical trapping set the gold standard in stiffness measurements. However, their widespread use has been hampered with long processing times, unreliable contact point determination, physical damage to cells, and unsuitability for multiple cell analysis. Here, we demonstrate a simple, fast, label-free, and high-resolution technique using acoustic stimulation and holographic imaging to reconstruct stiffness maps of single cells. We used this acousto-holographic method to determine stiffness maps of HCT116 and CTC-mimicking HCT116 cells and differentiate between them. Our system would enable widespread use of whole-cell stiffness measurements in clinical and research settings for cancer studies, disease modeling, drug testing, and diagnostics.

A new microrobot manipulation technique with high precision (nano level) positional accuracy to move in a liquid environment with diamagnetic levitation is presented. Untethered manipulation of microrobots by means of externally applied magnetic forces has been emerging as a promising field of research, particularly due to its potential for medical and biological applications. The purpose of the presented method is to eliminate friction force between the surface of the substrate and microrobot. In an effort to achieve high accuracy motion, required magnetic force for the levitation of the microrobot was determined by finite element method (FEM) simulations in COMSOL (version 5.3, COMSOL Inc., Stockholm, Sweden) and verified by experimental results. According to position of the lifter magnet, the levitation height of the microrobot in the liquid was found analytically, and compared with the experimental results head-to-head. The stable working range of the microrobot is between 30 µm to 330 µm, and it was confirmed in both simulations and experimental results. It can follow the given trajectory with high accuracy (<1 µm error avg.) at varied speeds and levitation heights. Due to the nano-level positioning accuracy, desired locomotion can be achieved in pre-specified trajectories (sinusoidal or circular). During its locomotion, phase difference between lifter magnet and carrier magnet has been observed, and relation with drag force effect has been discussed. Without using strong electromagnets or bulky permanent magnets, our manipulation approach can move the microrobot in three dimensions in a liquid environment.

Graphene has become a prominent material in cancer research in recent years. Graphene and its derivatives also attract attention as carriers in drug delivery systems. In this study, we designed a graphene oxide (GO)-based methotrexate (MTX)-loaded and folic acid (FA)-linked drug delivery system. MTX and FA were bound to GO synthesized from graphite. MTX/FA/GO drug delivery system and system components were characterized using Fourier transform infrared spectroscopy (FTIR), differential calorimetric analysis (DSC), scanning electron microscopy (SEM), transmission electron microscopy (TEM), zeta potential analysis, and dimension measurement (DLS) studies. SEM and TEM images confirmed the nanosheet structure of GO synthesized from graphite, and it was shown that MTX/FA binding to GO transformed the two-dimensional GO into a three-dimensional structure. FTIR and DSC graphs confirmed that oxygen atoms were bound to GO with the formation of carboxylic, hydroxyl, epoxide, and carbonyl groups as a result of the oxidation of graphite, and GO was successfully synthesized. Additionally, these analyses showed that MTX and FA bind physicochemically to the structure of GO. The in vitro Franz diffusion test was performed as a release kinetic test. The release kinetics mathematical model and correlation coefficient (R2) of MTX-loaded GO/FA nanomaterials were found to be the Higuchi model and 0.9785, respectively. Stiffness analyses showed that adding FA to this release system facilitated the entry of the drug into the cell by directing the system to target cells. As a result of the stiffness analyses, the stiffness values of the control cell group, free MTX, and MTX/FA/GO applied cells were measured as 2.34 kPa, 1.87 kPa, and 1.56 kPa, respectively. According to these results, it was seen that MTX/FA/GO weakened the cancer cells. Combined use of the MTX/FA/GO drug delivery system had a higher cytotoxic effect than free MTX on the MDA-MB-231 breast cancer cell line. The results showed that the synthesized MTX/FA/GO material has promising potential in cancer cell-specific targeted therapy for MTX as a drug delivery system.

This article presents an untethered magnetic manipulation technique for controlling a microrobot position under high rate laminar flows up to 4.5 mL/min. An increase in flow rate exponentially increases the drag force on the microrobot and negatively impacts its positioning accuracy. Increasing the longitudinal force generated by the microrobot’s driving apparatus helps in overcoming the disruptive effects of the fluid flow and increases longitudinal motion stability. To this end, we propose a magnetic configuration with two ring-shaped magnets, one above and the other below the microfluidic channel. This configuration causes the magnetic field lines emanating from the ring-shaped magnets to converge on both sides of the microrobot. Thus, the magnetic trapping forces that hold the microrobot in position are increased. To the best of our knowledge, no prior study exists on investigating the longitudinal motion for high flow velocities ( $>$ 5 mm/s). Investigating the longitudinal forces (along the x -axis) that affect a magnetically driven microrobot is a novel research topic that has many potential application areas, such as cell research, micromanipulation, and lab-on-a-chip systems. The microrobot’s dynamical motion is modeled as a second-order system, and using this model as a guideline, we demonstrate the ability of a microrobot in a square-shaped microfluidic channel ( $900$ $\times 900\,{\mu \text{m}}^{2}$ ) to follow a linear trajectory with a relative velocity up to 132.6 ${\text{mm/s}}$ . A straight and longitudinal trajectory of 4000 $\mu \text{m}$ has been successfully followed in the same and opposite directions to the flow for different flow rates (1–4.5 mL/min) and different robot speeds (10–50 mm/s).