Background
Computer‐aided methods have been widely applied to diagnose lesions detected on breast MRI, but fully‐automatic diagnosis using deep learning is rarely reported.
Purpose
To evaluate the ...diagnostic accuracy of mass lesions using region of interest (ROI)‐based, radiomics and deep‐learning methods, by taking peritumor tissues into consideration.
Study Type
Retrospective.
Population
In all, 133 patients with histologically confirmed 91 malignant and 62 benign mass lesions for training (74 patients with 48 malignant and 26 benign lesions for testing).
Field Strength/Sequence
3T, using the volume imaging for breast assessment (VIBRANT) dynamic contrast‐enhanced (DCE) sequence.
Assessment
3D tumor segmentation was done automatically by using fuzzy‐C‐means algorithm with connected‐component labeling. A total of 99 texture and histogram parameters were calculated for each case, and 15 were selected using random forest to build a radiomics model. Deep learning was implemented using ResNet50, evaluated with 10‐fold crossvalidation. The tumor alone, smallest bounding box, and 1.2, 1.5, 2.0 times enlarged boxes were used as inputs.
Statistical Tests
The malignancy probability was calculated using each model, and the threshold of 0.5 was used to make a diagnosis.
Results
In the training dataset, the diagnostic accuracy was 76% using three ROI‐based parameters, 84% using the radiomics model, and 86% using ROI + radiomics model. In deep learning using the per‐slice basis, the area under the receiver operating characteristic (ROC) was comparable for tumor alone, smallest and 1.2 times box (AUC = 0.97‐0.99), which were significantly higher than 1.5 and 2.0 times box (AUC = 0.86 and 0.71, respectively). For per‐lesion diagnosis, the highest accuracy of 91% was achieved when using the smallest bounding box, and that decreased to 84% for tumor alone and 1.2 times box, and further to 73% for 1.5 times box and 69% for 2.0 times box. In the independent testing dataset, the per‐lesion diagnostic accuracy was also the highest when using the smallest bounding box, 89%.
Data Conclusion
Deep learning using ResNet50 achieved a high diagnostic accuracy. Using the smallest bounding box containing proximal peritumor tissue as input had higher accuracy compared to using tumor alone or larger boxes.
Level of Evidence: 3
Technical Efficacy: Stage 2
To identify whether or not immediate loading yields different clinical outcomes from conventional loading of single-tooth implants in the esthetic zone.
Various databases (MEDLINE/PubMed, Cochrane ...CENTRAL, and Embase) were searched electronically to find articles published in the English language from January 2000 to April 2018. Only randomized controlled clinical trials (RCTs) that compared conventional and immediate implant loading with a minimum follow-up period of 1 year or more were considered. Available data were pooled for meta-analysis using the Review Manager software.
Seven RCTs were included. There was no significant difference between immediate and conventional loading protocols on implant survival at the 1-year follow-up (risk ratio RR = 0.99; 95% confidence interval CI: 0.95 to 1.02). The differences regarding marginal bone loss between the two protocols were statistically insignificant (mean difference MD = 0.03 mm; 95% CI: -0.09 to 0.15 mm at the 1-year follow-up, and MD = -0.01 mm; 95% CI: -0.16 to 0.15 mm at the 2-year follow-up). Soft tissue changes following different loading protocols revealed no significant differences in the mesial papillae (MD = 0.30 mm; 95% CI: -0.25 to 0.85 mm), the distal papillae (MD = -0.00 mm; 95% CI: -0.42 to 0.42 mm), and the midfacial mucosa (MD = -0.33 mm; 95% CI: -1.17 to 0.50 mm) at the 1-year follow-up. The esthetic outcomes and patient satisfaction were reported in two and three RCTs, respectively.
A short-term follow-up of single-tooth implants in the esthetic zone showed that the loading protocols (conventional or immediate loading) are not likely to influence the clinical outcomes, including implant survival and peri-implant stability of soft and hard tissues.
Tinospora sinensis (T. sinensis), whose Tibetan name is “Lezhe”, as a traditional medicine, is widely distributed in China, India and Sri Lanka. It is used for the treatment of rheumatic arthralgia, ...sciatica, lumbar muscle strain and bruises. Research over the previous decades indicated that T. sinensis mainly contains terpenes, lignans, alkaloids, phenol glycosides and other chemical components. A wide range of pharmacologic activities such as anti‐inflammatory, analgesic, immunosuppressive, anti‐aging, anti‐radiation, anti‐leishmania and liver protection have been reported. However, the scholar's research on the pharmacodynamic material basis of T. sinensis is relatively weak. Data regarding many aspects such as links between the traditional uses and bioactivities, pharmacokinetics, and quality control standard of active compositions is still limited and need more attention. This review reports a total of 241 compounds, the ethnopharmacology and clinical application of T. sinensis, covering the literature which were searched by multiple databases including Web of Science, PubMed, Google Scholar, Science Direct, CNKI and other literature sources from 1996 to date, with a view to provide a systematic and insightful reference and lays a foundation and inspiration for the application and further in‐depth research of T. sinensis resources.
Two-dimensional (2D) materials are well-known to exhibit interesting phenomena due to quantum confinement. Here, we show that quantum confinement, together with structural anisotropy, result in an ...electric-field-tunable Dirac cone in 2D black phosphorus. Using density functional theory calculations, we find that an electric field, E ext, applied normal to a 2D black phosphorus thin film, can reduce the direct band gap of few-layer black phosphorus, resulting in an insulator-to-metal transition at a critical field, Ec. Increasing E ext beyond Ec can induce a Dirac cone in the system, provided the black phosphorus film is sufficiently thin. The electric field strength can tune the position of the Dirac cone and the Dirac-Fermi velocities, the latter being similar in magnitude to that in graphene. We show that the Dirac cone arises from an anisotropic interaction term between the frontier orbitals that are spatially separated due to the applied field, on different halves of the 2D slab. When this interaction term becomes vanishingly small for thicker films, the Dirac cone can no longer be induced. Spin-orbit coupling can gap out the Dirac cone at certain electric fields; however, a further increase in field strength reduces the spin-orbit-induced gap, eventually resulting in a topological-insulator-to-Dirac-semimetal transition.
This was a longitudinal study of perinatal depressive symptoms among females employed in a large electronics manufacturer in Taiwan, conducted from August 2015 through October 2016. We used ...questionnaires to collect data on perceived job strain, social support, and the Edinburgh Postnatal Depression Scale (EPDS) scores at three perinatal time-points (pregnancy, delivery, and return to the workplace). Of the 153 employees who agreed to participate, 82 completed the three stages. The prevalence of perinatal depressive symptoms for the three stages was 13.7%, 16.8%, and 15.9%, respectively. The incidence at 3 weeks after childbirth and 1 month after returning to the workplace was 11.0% and 6.8%, respectively. During the third trimester of pregnancy, sleep problems (odds ratio OR = 6.2, 95% confidence Interval 95% CI = 2.1-19.3), perceived job strain (OR = 4.4, 95% CI = 1.5-14.3), and lack of support from family or friends (OR = 7.0, 95% CI = 1.3-40.8) were significant risk factors. Sleep problems (OR = 6.0, 95% CI = 1.7-23.5) and lack of support from family or friends (OR = 27.6, 95% CI = 4.1-322.3) were associated with an increased risk of perinatal depressive symptoms at 3 weeks after childbirth. After returning to the workplace, perceived job strain (OR = 18.2, 95% CI = 2.2-435.7) was a significant risk factor. These findings could provide insight about early symptom detection, and more studies to clarify the association would be worthwhile.
Cancer progression is commonly segregated into processes of primary tumour growth and secondary metastasis. Recent evidence suggests that a subpopulation of cancer cells, cancer stem cells (CSCs), is ...responsible for tumour growth in cancer. However, the role of CSCs in cancer metastasis is unclear. In this study, we found that the C terminus of CD44 contributes to sphere formation and survival in vitro via the CD44–SRC–integrin axis. In addition, nuclear CD44/acetylated‐STAT3 is required for clonal formation in vitro and tumourigenicity in vivo. Nuclear CD44 binds to various promoters identified by chromatin immunoprecipitation‐seq, including that of c‐myc and Twist1, leading to cell fate change through transcriptional reprogramming. We propose that nuclear CD44/acetylated‐STAT3 performs an unexpected tumour‐progressing function by enhancing cell outgrowth into structures where cells with properties of CSCs can be generated from differentiated somatic cells in suspension culture, and then exhibit attributes of cells that have undergone an epithelial–mesenchymal transition, leading to tumour metastasis, and a resulting worse prognosis.
CD44 is a known marker for cancer stem cells (CSCs) and had functionally been associated with cancer metastasis. This paper highlights the functional contribution of CD44 in determining cellular features of CSCs that include the definition of underlying molecular mechanisms.
•The study explores the supervisor-related antecedents of FSSB.•When workaholic supervisors perceived their subordinates experienced FWC, they engaged in FSSB.•FSSB predicted subordinates’ OCB toward ...supervisor and subordinate’s withdrawal behaviors at work.•A moderated mediation model was supported.
Drawing from role identity theory and social exchange theory, the current study presents a moderated mediation model which I use to examine how supervisor workaholism and the perception of subordinate’s family-work conflict affect family supportive behavior. This supervisor behavior further influences subordinate’s organizational citizenship behavior toward the supervisor and withdrawal behavior at work. Using a sample of supervisor-subordinate dyads in hotels, I found that (1) supervisor’s perception of subordinate’s family-work conflict enhanced the positive relationship between supervisor workaholism and family supportive supervisor behavior, (2) family supportive supervisor behavior was positively related to subordinate’s organizational citizenship behavior toward the supervisor and negatively related to subordinate’s withdrawal behavior at work, and (3) only when supervisor’s perception of subordinate’s family-work conflict was high did I find a significant indirect effect of supervisor workaholism on subordinate’s organizational citizenship behavior toward the supervisor and withdrawal behavior at work via family supportive supervisor behavior.
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