Liquid biopsy genotyping in lung cancer: ready for clinical utility?

Liquid biopsy is a blood test that detects evidence of cancer cells or tumor DNA in the circulation. Despite complicated collection methods and the requirement for technique-dependent platforms, it has generated substantial interest due, in part, to its potential to detect driver oncogenes such as epidermal growth factor receptor (EGFR) mutants in lung cancer. This technology is advancing rapidly and is being incorporated into numerous EGFR tyrosine kinase inhibitor (EGFR-TKI) development programs. It appears ready for integration into clinical care. Recent studies have demonstrated that biological fluids such as saliva and urine can also be used for detecting EGFR mutant DNA through application other user-friendly techniques. This review focuses on the clinical application of liquid biopsies to lung cancer genotyping, including EGFR and other targets of genotype-directed therapy and compares multiple platforms used for liquid biopsy

Regulation of Skp2 Expression and Activity and Its Role in Cancer Progression

The regulation of cell cycle entry is critical for cell proliferation and tumorigenesis. One of the key players regulating cell cycle progression is the F-box protein Skp2. Skp2 forms a SCF complex with Skp1, Cul-1, and Rbx1 to constitute E3 ligase through its F-box domain. Skp2 protein levels are regulated during the cell cycle, and recent studies reveal that Skp2 stability, subcellular localization, and activity are regulated by its phosphorylation. Overexpression of Skp2 is associated with a variety of human cancers, indicating that Skp2 may contribute to the development of human cancers. The notion is supported by various genetic mouse models that demonstrate an oncogenic activity of Skp2 and its requirement in cancer progression, suggesting that Skp2 may be a novel and attractive therapeutic target for cancers

Outcome of lung cancer patients with acute respiratory failure requiring mechanical ventilation

AbstractTo assess the weaning outcome of lung cancer patients with acute respiratory failure (ARF) requiring mechanical ventilation, we retrospectively analyzed the database of the respiratory intensive care unit at a university-affiliated tertiary care hospital.Charts were reviewed for cancer status, biochemistries before respiratory failure, causes of respiratory failure, acute physiology and chronic health evaluation (APACHE) III score, ventilatory settings, data recorded during spontaneous breathing, duration of ventilator days, and weaning outcome. Ninety-five consecutive respiratory failure events in 81 patients were recorded from January 1, 1995 through June 30, 1999.Twenty-six episodes ended with successful weaning (27.4%). Age, gender, and cancer status did not affect the weaning outcome. Serum albumin level, APACHE III score, highest fractional inspired O2 (FiO2) and highest positive end-expiratory pressure, organ failure, ability to shift to partial ventilatory support, and duration of mechanical ventilation could significantly influence the weaning outcome statistically. The overall hospital mortality rate was 85.2%.Our results suggested that lung cancer patients with ARF will have a better chance to wean if the initial APACHE III score was less than 70, use of FiO2 never exceeded 0.6, or less than 2 additional organ systems failed during the treatment course

Tooth Position Determination by Automatic Cutting and Marking of Dental Panoramic X-ray Film in Medical Image Processing

This paper presents a novel method for automatic segmentation of dental X-ray images into single tooth sections and for placing every segmented tooth onto a precise corresponding position table. Moreover, the proposed method automatically determines the tooth’s position in a panoramic X-ray film. The image-processing step incorporates a variety of image-enhancement techniques, including sharpening, histogram equalization, and flat-field correction. Moreover, image processing was implemented iteratively to achieve higher pixel value contrast between the teeth and cavity. The next image-enhancement step is aimed at detecting the teeth cavity and involves determining the segment and points separating the upper and lower jaw, using the difference in pixel values to cut the image into several equal sections and then connecting each cavity feature point to extend a curve that completes the description of the separated jaw. The curve is shifted up and down to look for the gap between the teeth, to identify and address missing teeth and overlapping. Under FDI World Dental Federation notation, the left and right sides receive eight-code sequences to mark each tooth, which provides improved convenience in clinical use. According to the literature, X-ray film cannot be marked correctly when a tooth is missing. This paper utilizes artificial center positioning and sets the teeth gap feature points to have the same count. Then, the gap feature points are connected as a curve with the curve of the jaw to illustrate the dental segmentation. In addition, we incorporate different image-processing methods to sequentially strengthen the X-ray film. The proposed procedure had an 89.95% accuracy rate for tooth positioning. As for the tooth cutting, where the edge of the cutting box is used to determine the position of each tooth number, the accuracy of the tooth positioning method in this proposed study is 92.78%

Arsenic exposure and lung fibrotic changes-evidence from a longitudinal cohort study and experimental models

IntroductionArsenic (As) exposure is associated with lung toxicity and we aim to investigate the effects of arsenic exposure on lung fibrotic changes.MethodsParticipants (n= 976) enrolled via a general health survey underwent chest low-dose computed tomography (LDCT), spirometry forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), and urinary arsenic examination during 2016 and 2018. Lung fibrotic changes from LDCT were defined. AsLtoL, low arsenic levels in both 2016 and 2018; AsLtoH, low arsenic in 2016 but high levels in 2018; AsHtoL, high arsenic in 2016 but low levels in 2018; AsHtoH, high arsenic levels in both 2016 and 2018. Mice exposed to 0. 0.2mg/L, 2 mg/L, 50 mg/L of sodium arsenite (NaAsO2) through drinking water for 12 weeks and 24 weeks were applied for histological analysis. Cultured lung epithelial cells were exposed to NaAsO2 and the mesenchymal changes were examined.ResultsAsHtoH increased the risk (OR= 1.65, 95% CI 1.10, 2.49) of Lung fibrotic positive to positive (reference: Lung fibrotic negative to negative) compared with AsLtoL. Moreover, the predicted mean of FVC and FEV1 in AsHtoH (−0.09 units, 95% CI: −0.27, −0.09; −0.09 units, 95% CI: −0.17, −0.01) and AsLtoH (−0.13 units, 95% CI: −0.30, −0.10; −0.13 units, 95% CI: −0.22, −0.04) was significantly lower than ASLtoL. Significant lung fibrotic changes including the increase of the alveolar septum thickness and collagen fiber deposition were observed upon 2 mg/L NaAsO2 treatment for 12 weeks, and the damage was dose- and time-dependent. In vitro, sodium arsenite treatment promotes the epithelial-mesenchymal transition (EMT)-like changes of the normal human bronchial epithelial cells, including upregulation of several fibrotic and mesenchymal markers (fibronectin, MMP-2, and Snail) and cell migration. Inhibition of reactive oxygen species (ROS) and MMP-2 impaired the arsenic-induced EMT changes. Administration of a flavonoid, apigenin, inhibited EMT in vitro and pulmonary damages in vivo with the reduction of mesenchymal markers.Discussionwe demonstrated that continued exposure to arsenic causes lung fibrosis in humans and mice. Targeting lung epithelial cells EMT is effective on the development of therapeutic strategy. Apigenin is effective in the inhibition of arsenic-induced pulmonary fibrosis and EMT

Caries and Restoration Detection Using Bitewing Film Based on Transfer Learning with CNNs

Caries is a dental disease caused by bacterial infection. If the cause of the caries is detected early; the treatment will be relatively easy; which in turn prevents caries from spreading. The current common procedure of dentists is to first perform radiographic examination on the patient and mark the lesions manually. However; the work of judging lesions and markings requires professional experience and is very time-consuming and repetitive. Taking advantage of the rapid development of artificial intelligence imaging research and technical methods will help dentists make accurate markings and improve medical treatments. It can also shorten the judgment time of professionals. In addition to the use of Gaussian high-pass filter and Otsu’s threshold image enhancement technology; this research solves the problem that the original cutting technology cannot extract certain single teeth; and it proposes a caries and lesions area analysis model based on convolutional neural networks (CNN); which can identify caries and restorations from the bitewing images. Moreover; it provides dentists with more accurate objective judgment data to achieve the purpose of automatic diagnosis and treatment planning as a technology for assisting precision medicine. A standardized database established following a defined set of steps is also proposed in this study. There are three main steps to generate the image of a single tooth from a bitewing image; which can increase the accuracy of the analysis model. The steps include (1) preprocessing of the dental image to obtain a high-quality binarization; (2) a dental image cropping procedure to obtain individually separated tooth samples; and (3) a dental image masking step which masks the fine broken teeth from the sample and enhances the quality of the training. Among the current four common neural networks; namely; AlexNet; GoogleNet; Vgg19; and ResNet50; experimental results show that the proposed AlexNet model in this study for restoration and caries judgments has an accuracy as high as 95.56% and 90.30%; respectively. These are promising results that lead to the possibility of developing an automatic judgment method of bitewing film