Colon cancer arises due to the conversion of precancerous polyps (benign) found in the inner lining of the colon. Prevention is better than cure, and this is very true with respect to colon cancer. Various epidemiologic studies have linked colorectal cancer with food intake. Apple and berry juices are widely consumed among various ethnicities because of their nutritious values. In this review article, chemopreventive effects of these fruit juices against colon cancer are discussed. Studies dealing with bioavailability, in vitro and in vivo effects of apple and berry juices are emphasized in this article. A thorough literature survey indicated that various phenolic phytochemicals present in these fruit juices have the innate potential to inhibit colon cancer cell lines. This review proposes the need for more preclinical evidence for the effects of fruit juices against different colon cancer cells, and also strives to facilitate clinical studies using these juices in humans in large trials. The conclusion of the review is that these apple and berry juices will be possible candidates in the campaign against colon cancer.
We propose a new Hole-filling algorithm by improving the Olympic operator, and we also apply it to generate the volume in our freehand 3D ultrasound reconstruction of the spine. First, the ultrasound frames and position information are compounded into a 3D volume using the Bin-filling method. Then, the Hole-filling method is used to repair gaps in the volume. The conventional Olympic operator defines the empty voxels by sorting the neighboring voxels, removing the n% of the upper and lower values, and averaging them to attain the value to fill the empty voxels. The empty voxel estimation can be improved by thresholding the range width of its neighboring voxels and adjusting it to the average values. The method is tested on a holemanipulated volume derived from a cropped 3D ultrasound volume of a part of the spine. Our MAE calculation on the proposed technique shows improved result compared to all tested existing methods.
Over recent years, the reseach in the field of soft actuation has been extensively increased for achieving more complex motion path with smooth, high flexible movement and high generated force at minimum operating pressure. This paper presents the study on gripping force capability of soft actuators applied on glove-type finger exoskeleton, developed in motivation to assist individuals having weak finger gripping ability in their rehabilitation exercise towards hand function restoration. The exoskeleton utilizes five cylindrical shaped pneumatic bending actuators developed in the lab, which use fiber reinforcement as a cause of bending motion that drive finger’s flexion movement. Four right-handed healthy volunteers simulated paralysis participated in the study. At 200kPa safe operating pressure, the soft exoskeleton worn by the subjects demonstrates the ability to provide adequate grip force. The grip force generated from exoskeleton worn on passive right hand is 4.66 ± 0.2 N and 3.61± 0.2 N from passive left hand, both higher than the minimum grip forces measured to hold the Hand Dynamometer of 240 g. It shows good potential to be used as a finger rehabilitation assist device.
Unreliable spinal X-ray radiography measurement due to standing postural variability can be minimized by using positional supports. In this study, we introduce a balancing device, named BalancAid, to position the patients in a reproducible position during spinal X-ray radiography. This study aimed to investigate the performance of healthy young subjects’ standing posture on the BalancAid compared to standing on the ground mimicking the standard X-rays posture in producing a reproducible posture for the spinal X-ray radiography. A study on the posture reproducibility measurement was performed by taking photographs of 20 healthy young subjects with good balance control standing on the BalancAid and the ground repeatedly within two consecutive days. We analyzed nine posterior–anterior (PA) and three lateral (LA) angles between lines through body marks placed in the positions of T3, T7, T12, L4 of the spine to confirm any translocations and movements between the first and second day measurements. No body marks repositioning was performed to avoid any error. Lin’s CCC test on all angles comparing both standing postures demonstrated that seven out of nine angles in PA view, and two out of three angles in LA view gave better reproducibility for standing on the BalancAid compared to standing on the ground. The PA angles concordance is on average better than that of the LA angles.
This paper presents a cell nucleus segmentation and area measurement of Pap smear images by means of modification of color canals with Canny edge detection and morphological reconstruction methods. Cell nucleus characterization plays an important role for classifying the degree of abnormality in cervical cancer. The aim of this work is to find the matched measurement method with the manual nucleus area measurement. In this work, we utilized pap smear single cell images from Herlev data bank in RGB mode. The cell images were selected from 90 normal class subjects that include: Normal Superficial, Normal Intermediate, and Normal Columnar classes. The nucleus of each cell image was cropped manually to localize from the cytoplasm. The color canals modification was performed on each cropped nucleus image by, first, separating each R, G, B, and grayscale canals, then implementing addition operation based on color canals (R+G+B, R+G, R+B, G+B, and grayscale). The Canny edge detection was applied on those modifications resulting in binary edge images. The nucleus segmentation was implemented on the edge images by performing region filling based on morphological reconstruction. The area property was calculated based on the segmented nucleus area. The nucleus area from the proposed method was verified to the existing manual measurement (ground truth) of the Herlev data bank. Based on thorough observation upon the selected color canals and Canny edge detection. It can be concluded that Canny edge detection with R+G+B canal is the most significant for all Normal classes (r 0,305, p-value 0.05). While for Normal Superficial and Normal Intermediate, Canny edge detection is significant for all RGB modifications with (r 0.414 -0.817 range, , p-value 0.05), and for Normal Columnar, Canny edge detection is significant for R+B canal (r 0.505, p-value 0.05).
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