Using ultrasonographic features to predict the outcomes of patients with small papillary thyroid carcinomas: a retrospective study implementing the 2015 ATA patterns and ACR TI-RADS categories.

BACKGROUND: The aim of this study was to evaluate whether risk stratification systems using ultrasonographic (US) features show associations with the outcomes of patients with small papillary thyroid carcinomas (PTCs). METHODS: This retrospective study received institutional review board approval. From March 2007 to February 2010, 775 patients who underwent surgery for small PTCs (10-20 mm) were included. Based on preoperative US features, PTCs were categorized according to the 2015 American Thyroid Association (ATA) guideline and the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS). The associations of clinicopathological and US features with postoperative patient outcomes were evaluated. RESULTS: In total, 61 patients had high-volume central lymph node metastasis (CLNM, 7.9%) and 100 patients had lateral lymph node metastasis (LLNM, 12.9%). In univariable analyses, a high number of suspicious US features and higher ACR TI-RADS point totals were significantly associated with both high-volume CLNM (P=0.001, each) and LLNM (P<0.001, each). In multivariable analyses of preoperative features, a higher number of suspicious US features and higher ACR TI-RADS point totals were independently associated with high-volume CLNM (odds ratio [OR], 1.516 and 1.201; P=0.002 and P=0.001, respectively) and LLNM (OR, 1.763 and 1.293; all P<0.001). Individual US features, ATA categories, and ACR TI-RADS point totals were not significantly associated with recurrence or distant metastasis. CONCLUSION: The number of suspicious US features and the ACR TI-RADS point total are potential risk factors for cervical lymph node metastasis in patients with small PTCs.

Artificial intelligence based real-time microcirculation analysis system for laparoscopic colorectal surgery.

BACKGROUND: Colonic perfusion status can be assessed easily by indocyanine green (ICG) angiography to predict ischemia related anastomotic complications during laparoscopic colorectal surgery. Recently, various parameter-based perfusion analysis have been studied for quantitative evaluation, but the analysis results differ depending on the use of quantitative parameters due to differences in vascular anatomical structure. Therefore, it can help improve the accuracy and consistency by artificial intelligence (AI) based real-time analysis microperfusion (AIRAM). AIM: To evaluate the feasibility of AIRAM to predict the risk of anastomotic complication in the patient with laparoscopic colorectal cancer surgery. METHODS: The ICG curve was extracted from the region of interest (ROI) set in the ICG fluorescence video of the laparoscopic colorectal surgery. Pre-processing was performed to reduce AI performance degradation caused by external environment such as background, light source reflection, and camera shaking using MATLAB 2019 on an I7-8700k Intel central processing unit (CPU) PC. AI learning and evaluation were performed by dividing into a training patient group (n = 50) and a test patient group (n = 15). Training ICG curve data sets were classified and machine learned into 25 ICG curve patterns using a self-organizing map (SOM) network. The predictive reliability of anastomotic complications in a trained SOM network is verified using test set. RESULTS: AI-based risk and the conventional quantitative parameters including T 1/2max , time ratio (TR), and rising slope (RS) were consistent when colonic perfusion was favorable as steep increasing ICG curve pattern. When the ICG graph pattern showed stepped rise, the accuracy of conventional quantitative parameters decreased, but the AI-based classification maintained accuracy consistently. The receiver operating characteristic curves for conventional parameters and AI-based classification were comparable for predicting the anastomotic complication risks. Statistical performance verifications were improved in the AI-based analysis. AI analysis was evaluated as the most accurate parameter to predict the risk of anastomotic complications. The F1 score of the AI-based method increased by 31% for T 1/2max , 8% for TR, and 8% for RS. The processing time of AIRAM was measured as 48.03 s, which was suitable for real-time processing. CONCLUSION: In conclusion, AI-based real-time microcirculation analysis had more accurate and consistent performance than the conventional parameter-based method.

Risk of Primary Spontaneous Pneumothorax According to Chest Configuration.

BACKGROUND: We compared the chest configurations of patients with primary spontaneous pneumothorax (PSP) and age-sex-matched controls to determine the presence of chest wall deformities in patients with PSP. METHODS: We retrospectively enrolled 166 male patients with PSP (age, 18-19 years) and 85 age-sex-matched controls without PSP, who simultaneously underwent chest computed tomography (CT) and radiography at one of two institutes. After correcting for height, the following thoracic parameters were comparatively evaluated between the two groups: maximal internal transverse (T) and anteroposterior (W) diameters of the chest, maximal internal lung height (H), Haller index (T/W), and T/Height, T/H, W/Height, W/H, and H/Height ratios. RESULTS: Patients were taller than the control subjects (176.5 cm ± 5.9 cm versus 174.4 cm ± 5.6 cm; p = 0.007). After controlling for height, the patient group exhibited lower T and W and greater H and Haller index values than the control group (T: 95% confidence interval [CI], 24.8-25.2 cm versus 25.9-26.5; W: 95% CI, 8.9-9.2 cm versus 10.1-10.6 cm; H: 95% CI, 25.2-25.9 cm versus 23.4-24.4 cm; and Haller index, 95% CI, 2.7-2.9 versus 2.4-2.6; all, p < 0.001). The patient group also exhibited lower T/Height, T/H, W/Height, and W/H ratios and greater H/Height ratio than the control group. CONCLUSIONS: Patients with PSP have an anteroposteriorly flatter, laterally narrower, and craniocaudally taller thorax than subjects without PSP, suggesting that chest configuration is associated with the development of pneumothorax.

Decreased muscle mass is independently associated with knee pain in female patients with radiographically mild osteoarthritis: a nationwide cross-sectional study (KNHANES 2010-2011).

To evaluate the association between muscle mass and knee pain in relation to radiographic severity of knee osteoarthritis. We consulted nationwide health examination and survey records collected from 2010 to 2011 and extracted data regarding female patients aged > 50 years and diagnosed with knee osteoarthritis. Radiographic severity was assessed on plain radiographs using the Kellgren-Lawrence system, whereas appendicular skeletal mass was obtained from dual-energy X-ray absorptiometry data. We performed multivariate logistic regression to evaluate the association between knee pain and muscle mass index (appendicular skeletal muscle mass divided by body weight in percentile) in patient groups stratified by radiographic severity of knee osteoarthritis. Among 17,476 participants of the national survey, 2013 female knee osteoarthritis patients were identified and stratified by radiographic severity (grade ≤ 1, n = 1136; grade 2, n = 240; grade 3, n = 379; and grade 4, n = 258). For mild osteoarthritis (Kellgren-Lawrence grade 2), muscle mass index was significantly lower in patients with knee pain than in those without knee pain (24.9 ± 3.9 vs 26.5 ± 6.3%, P = 0.023), whereas no such difference was noted for severe osteoarthritis (Kellgren-Lawrence grade > 2). After adjusting for clinical variables by multivariate logistic regression, decreased muscle mass index remained significantly associated with knee pain in patients with mild osteoarthritis but not in those with severe osteoarthritis (regression coefficient 0.915, 95% confidence interval 0.854-0.981, P = 0.012). Lower muscle mass may be a risk factor for knee pain in patients with radiographically mild knee osteoarthritis but not in those with radiographically severe osteoarthritis.

Topological modification of the electronic structure by Bi-bilayers lying deep inside bulk Bi2Se3.

We observe the modified surface states of an epitaxial thin film of a homologous series of (Bi2)m(Bi2Se3)n, as a topological insulator (TI), by angle-resolved photoemission spectroscopy measurements. A thin film with m : n = 1 : 3 (Bi8Se9) has been grown with Bi2 bilayers embedded every other three quintuple layers (QLs) of Bi2Se3. Despite the reduced dimension of continuous QLs due to the Bi2 heterolayers, we find that the topological surface states stem from the inverted Bi and Se states and the topologically nontrivial structures are mainly based on the prototype of 3D TI Bi2Se3 without affecting the overall topological order.

Proximity Effect Induced Electronic Properties of Graphene on Bi2Te2Se.

We report that the π-electrons of graphene can be spin-polarized to create a phase with a significant spin-orbit gap at the Dirac point (DP) using a graphene-interfaced topological insulator hybrid material. We have grown epitaxial Bi2Te2Se (BTS) films on a chemical vapor deposition (CVD) graphene. We observe two linear surface bands from both the CVD graphene notably flattened and BTS coexisting with their DPs separated by 0.53 eV in the photoemission data measured with synchrotron photons. We further demonstrate that the separation between the two DPs, Δ(D-D), can be artificially fine-tuned by adjusting the amount of Cs atoms adsorbed on the graphene to a value as small as Δ(D-D) = 0.12 eV to find any proximity effect induced by the DPs. Our density functional theory calculation shows the opening of a spin-orbit gap of ∼20 meV in the π-band, enhanced by 3 orders of magnitude from that of a pristine graphene, and a concomitant phase transition from a semimetallic to a quantum spin Hall phase when Δ(D-D) ≤ 0.20 eV. We thus present a practical means of spin-polarizing the π-band of graphene, which can be pivotal to advance graphene-based spintronics.

In vitro apoptotic effects of methanol extracts of Dianthus chinensis and Acalypha australis L. targeting specificity protein 1 in human oral cancer cells.

BACKGROUND: The aims of this study were to evaluate the apoptotic activities and molecular mechanisms of methanol extracts of Dianthus chinensis (MEDC) and Acalypha australis L. (MEAL) in human oral cancer cells. METHODS: The apoptotic effects and related molecular mechanisms of MEDC and MEAL on oral cancer cells were evaluated using MTS assay, DAPI staining, immunostaining, Western blotting, and reverse transcriptase-polymerase chain reaction. RESULTS: Sp1 was overexpressed in oral tumor tissues compared with normal oral mucosa. Downregulation of Sp1 inhibited the growth of SCC-15 and YD-15 oral cancer cells. MEDC and MEAL inhibited cell growth and induced apoptosis in both cell lines by decreasing the expression of Sp1. In addition, treatment of cells with MEDC and MEAL decreased Mcl-1 expression, which is a downstream target of Sp1. CONCLUSION: Our results indicate that MEDC and MEAL are bioactive natural products that can potentially induce apoptosis of tumor cells that overexpress the Sp1 protein.