Corrections to "Micropositioning and Control of an Underactuated Platform for Microscopic Applications".

[This corrects the article PMC5110010.].

Soft Multi-Directional Force Sensor for Underwater Robotic Application.

Tactile information is crucial for recognizing physical interactions, manipulation of an object, and motion planning for a robotic gripper; however, concurrent tactile technologies have certain limitations over directional force sensing. In particular, they are expensive, difficult to fabricate, and mostly unsuitable for underwater use. Here, we present a facile and cost-effective synthesis technique of a flexible multi-directional force sensing system, which is also favorable to be utilized in underwater environments. We made use of four flex sensors within a silicone-made hemispherical shell structure. Each sensor was placed 90° apart and aligned with the curve of the hemispherical shape. If the force is applied on the top of the hemisphere, all the flex sensors would bend uniformly and yield nearly identical readings. When force is applied from a different direction, a set of flex sensors would characterize distinctive output patterns to localize the point of contact as well as the direction and magnitude of the force. The deformation of the fabricated soft sensor due to applied force was simulated numerically and compared with the experimental results. The fabricated sensor was experimentally calibrated and tested for characterization including an underwater demonstration. This study would widen the scope of identification of multi-directional force sensing, especially for underwater soft robotic applications.

Micropositioning and Control of an Underactuated Platform for Microscopic Applications.

For automation of biological experiments at the micro-scale, highly precise manipulator equipped with a microscope is required. However, current micropositioning stages have several limitations, such as: 1) manual operation, 2) lack of rotational capability, 3) incompatibility with a microscope, and 4) small range of motion (RoM). This research aims to develop a microscope compatible XYθ micropositioning stage with large RoM for phenotyping multiple biological samples rapidly for various microscopic applications. An underactuated planar mechanism, kinematic analysis, and control of the XYθ stage are presented in this paper. The planar mechanism consists of two piezoelectric linear actuators for translational motion capability and two passive revolute joints at the tip of each linear actuator for rotational capability. Based on the kinematic analysis of the stage, controllability and control strategy of the underactuated stage is described. Finally, the feasibility of the micropositioning stage for a general positioning and orienting task is verified by both simulation and tissue core experiments.

Design and fabrication of a flexible MEMS-based electromechanical sensor array for breast cancer diagnosis.

The use of flexible micro-electro-mechanical systems (MEMS) based device provides a unique opportunity in bio-medical robotics such as characterization of normal and malignant tissues. This paper reports on design and development of a flexible MEMS-based sensor array integrating mechanical and electrical sensors on the same platform to enable the study of the change in electro-mechanical properties of the benign and cancerous breast tissues. In this work, we present the analysis for the electrical characterization of the tissue specimens and also demonstrate the feasibility of using the sensor for mechanical characterization of the tissue specimens. Eight strain gauges acting as mechanical sensors were fabricated using poly(3,4-ethylenedioxythiophene) poly(styrenesulfonate) (PEDOT:PSS) conducting polymer on poly(dimethylsiloxane) (PDMS) as the substrate material. Eight electrical sensors were fabricated using SU-8 pillars on gold (Au) pads which were patterned on the strain gauges separated by a thin insulator (SiO2 1.0µm). These pillars were coated with gold to make it conducting. The electromechanical sensors are integrated on the same substrate. The sensor array covers 180µm × 180µm area and the size of the complete device is 20mm in diameter. The diameter of each breast tissue core used in the present study was 1mm and the thickness was 8µm. The region of interest was 200µm × 200µm. Microindentation technique was used to characterize the mechanical properties of the breast tissues. The sensor is integrated with conducting SU-8 pillars to study the electrical property of the tissue. Through electro-mechanical characterization studies using this MEMS-based sensor, we were able to measure the accuracy of the fabricated device and ascertain the difference between benign and cancer breast tissue specimens.

State-of-the-Art of Breast Cancer Diagnosis in Medical Images via Convolutional Neural Networks (CNNs).

Early detection of breast cancer is crucial for a better prognosis. Various studies have been conducted where tumor lesions are detected and localized on images. This is a narrative review where the studies reviewed are related to five different image modalities: histopathological, mammogram, magnetic resonance imaging (MRI), ultrasound, and computed tomography (CT) images, making it different from other review studies where fewer image modalities are reviewed. The goal is to have the necessary information, such as pre-processing techniques and CNN-based diagnosis techniques for the five modalities, readily available in one place for future studies. Each modality has pros and cons, such as mammograms might give a high false positive rate for radiographically dense breasts, while ultrasounds with low soft tissue contrast result in early-stage false detection, and MRI provides a three-dimensional volumetric image, but it is expensive and cannot be used as a routine test. Various studies were manually reviewed using particular inclusion and exclusion criteria; as a result, 91 recent studies that classify and detect tumor lesions on breast cancer images from 2017 to 2022 related to the five image modalities were included. For histopathological images, the maximum accuracy achieved was around 99 %, and the maximum sensitivity achieved was 97.29 % by using DenseNet, ResNet34, and ResNet50 architecture. For mammogram images, the maximum accuracy achieved was 96.52 % using a customized CNN architecture. For MRI, the maximum accuracy achieved was 98.33 % using customized CNN architecture. For ultrasound, the maximum accuracy achieved was around 99 % by using DarkNet-53, ResNet-50, G-CNN, and VGG. For CT, the maximum sensitivity achieved was 96 % by using Xception architecture. Histopathological and ultrasound images achieved higher accuracy of around 99 % by using ResNet34, ResNet50, DarkNet-53, G-CNN, and VGG compared to other modalities for either of the following reasons: use of pre-trained architectures with pre-processing techniques, use of modified architectures with pre-processing techniques, use of two-stage CNN, and higher number of studies available for Artificial Intelligence (AI)/machine learning (ML) researchers to reference. One of the gaps we found is that only a single image modality is used for CNN-based diagnosis; in the future, a multiple image modality approach can be used to design a CNN architecture with higher accuracy.

Light mediated drug delivery systems: a review.

Achieving a novel drug delivery system needs site-specificity along with dosage control. Many physical, chemical, mechanical, and biological signals are used for developing these systems, out of which light has been used predominantly in the past decade. Light responsive drug delivery systems have tremendous potential, and their exploration is crucial in developing a precise and controlled delivery system. Spatio-temporal and intensity control of light allows better manipulation of drug delivery vehicles than mechanical, chemical, and biological signals. The use of ultraviolet (UV) and near-infrared (NIR) light has helped in upgrading therapeutic functionalities, while the use of up-conversion nanoparticles (UCNPs) has delivered an extension into theranostic tools. Biomaterials incorporated with photosensitizers can readily respond to changes in light and are vital in achieving clinical success via translational research. Further, the inclusion of biological macromolecules for the transportation of drugs, genes, and proteins has seen a broader application of light-controlled systems. The key objective of this review paper is to summarise the evolution of light-activated targeted drug delivery systems and the importance of biomaterials in developing one.

Electromechanical Coupling Factor of Breast Tissue as a Biomarker for Breast Cancer.

GOAL: This research aims to validate a new biomarker of breast cancer by introducing electromechanical coupling factor of breast tissue samples as a possible additional indicator of breast cancer. Since collagen fibril exhibits a structural organization that gives rise to a piezoelectric effect, the difference in collagen density between normal and cancerous tissue can be captured by identifying the corresponding electromechanical coupling factor. METHODS: The design of a portable diagnostic tool and a microelectromechanical systems (MEMS)-based biochip, which is integrated with a piezoresistive sensing layer for measuring the reaction force as well as a microheater for temperature control, is introduced. To verify that electromechanical coupling factor can be used as a biomarker for breast cancer, the piezoelectric model for breast tissue is described with preliminary experimental results on five sets of normal and invasive ductal carcinoma (IDC) samples in the 25-45 temperature range. CONCLUSION: While the stiffness of breast tissues can be captured as a representative mechanical signature which allows one to discriminate among tissue types especially in the higher strain region, the electromechanical coupling factor shows more distinct differences between the normal and IDC groups over the entire strain region than the mechanical signature. From the two-sample -test, the electromechanical coupling factor under compression shows statistically significant differences ( 0.0039) between the two groups. SIGNIFICANCE: The increase in collagen density in breast tissue is an objective and reproducible characteristic of breast cancer. Although characterization of mechanical tissue property has been shown to be useful for differentiating cancerous tissue from normal tissue, using a single parameter may not be sufficient for practical usage due to inherent variation among biological samples. The portable breast cancer diagnostic tool reported in this manuscript shows the feasibility of measuring multiple parameters of breast tissue allowing for practical application.

Toward a Portable Cancer Diagnostic Tool Using a Disposable MEMS-Based Biochip.

GOAL: The objective of this study is to design and develop a portable tool consisting of a disposable biochip for measuring electrothermomechanical (ETM) properties of breast tissue. METHODS: A biochip integrated with a microheater, force sensors, and electrical sensors is fabricated using microtechnology. The sensor covers the area of 2 mm and the biochip is 10 mm in diameter. A portable tool capable of holding tissue and biochip is fabricated using 3-D printing. Invasive ductal carcinoma and normal tissue blocks are selected from cancer tissue bank in Biospecimen Repository Service at Rutgers Cancer Institute of New Jersey. The ETM properties of the normal and cancerous breast tissues (3-mm thickness and 2-mm diameter) are measured by indenting the tissue placed on the biochip integrated inside the 3-D printed tool. RESULTS: Integrating microengineered biochip and 3-D printing, we have developed a portable cancer diagnosis device. Using this device, we have shown a statistically significant difference between cancerous and normal breast tissues in mechanical stiffness, electrical resistivity, and thermal conductivity. CONCLUSION: The developed cancer diagnosis device is capable of simultaneous ETM measurements of breast tissue specimens and can be a potential candidate for delineating normal and cancerous breast tissue cores. SIGNIFICANCE: The portable cancer diagnosis tool could potentially provide a deterministic and quantitative information about the breast tissue characteristics, as well as the onset and disease progression of the tissues. The tool can be potentially used for other tissue-related cancers.

Simultaneous MEMS-based electro-mechanical phenotyping of breast cancer.

Carcinomas are the most commonly diagnosed cancers originating in the skin, lungs, breasts, pancreas, and other organs and glands. In most of the cases, the microenvironment within the tissue changes with the progression of disease. A key challenge is to develop a device capable of providing quantitative indicators in diagnosing cancer by measuring alteration in electrical and mechanical property of the tissues from the onset of malignancy. We demonstrate micro-electro-mechanical-systems (MEMS) based flexible polymer microsensor array capable of simultaneously measuring electro-mechanical properties of the breast tissues cores (1 mm in diameter and 10 µm in thickness) from onset through progression of the cancer. The electrical and mechanical signatures obtained from the tissue cores shows the capability of the device to clearly demarcate the specific stages of cancer in epithelial and stromal regions providing quantitative indicators facilitating the diagnosis of breast cancer. The present study shows that electro-mechanical properties of the breast tissue core at the micro-level are different than those at the macro-level.

Bimanual shoulder flexion system with surface electromyography for hemiplegic patients after stroke: A preliminary study.

A robot-assisted bimanual shoulder flexion rehabilitation system with surface electromyography (sEMG) for hemiplegic patients after stroke is presented as a preliminary study before clinical test. The assistive system driven by combination of bimanual mirror imaging motion and sEMG in order to induce continuous voluntary stimulation to muscle and nerve of the patients. In this paper, hardware design, controller with impedance compensation of actuator using disturbance observer (DOB) for back-drivable operation, and sEMG signal processing to obtain desired assistive torque are also reported. The performance of impedance compensation and assistive operation of the system with sEMG were verified by experiments with a healthy participant. This system is expected to help to recover functionality of neural/musculoskeletal system to hemiplegic patients.

Prognostic value of CT before thrombolytic therapy in iliofemoral deep venous thrombosis.

PURPOSE: To prospectively assess the computed tomographic (CT) findings of iliofemoral deep venous thrombosis (DVT) and evaluate their relevance to the treatment of DVT with catheter-directed thrombolysis. MATERIALS AND METHODS: Twenty-four consecutive patients with symptomatic iliofemoral DVT were studied with both nonenhanced and contrast-enhanced CT before thrombolytic therapy. Mean duration of clinical symptom was 15.8 days +/- 20.8 (range, 1-90 d). Selected CT findings were prospectively evaluated and correlated with duration of symptoms and outcome of thrombolytic therapy, including attenuation number of the thrombus on nonenhanced CT (in HU), presence of venous distention (distention ratio: vein diameter divided by the diameter of corresponding normal contralateral vein), and poor venous wall demarcation. The following threshold variables were also evaluated: attenuation > or =60 HU and distention ratio > or =1.5. RESULTS: CT was suggestive of DVT in all patients, although different patterns were present. Higher attenuation on noncontrast CT was seen in patients who had favorable outcome of thrombolytic therapy compared to poor responders (66.1 +/- 8.7 vs 45.9 +/- 9.6; P <.0001). Distention ratio was also significantly higher in the good response group (2.6 +/- 1.4 vs 1.4 +/- 0.7; P <.05). Recent onset of clinical symptoms was associated with better outcome (9.4 d +/- 8.9 vs 28.6 d +/- 31.2; P <.03). Multiple-stepwise regression analysis of these variable produce the results of "attenuation >60" as the most predictive variable of favorable outcome of thrombolysis, followed by "distention ratio >1.5" and poor demarcation. CONCLUSION: Selected CT findings are better predictors of a favorable outcome of thrombolytic therapy than duration of clinical symptoms alone.