A rapid antibiotic susceptibility test (AST) is desperately needed in clinical settings for fast and appropriate antibiotic administration. Traditional ASTs, which rely on cell culture, are not suitable for urgent cases of bacterial infection and antibiotic resistance owing to their relatively long test times. We describe a novel AST called single-cell morphological analysis (SCMA) that can determine antimicrobial susceptibility by automatically analyzing and categorizing morphological changes in single bacterial cells under various antimicrobial conditions. The SCMA was tested with four Clinical and Laboratory Standards Institute standard bacterial strains and 189 clinical samples, including extended-spectrum β-lactamase–positive Escherichia coli and Klebsiella pneumoniae, imipenem-resistant Pseudomonas aeruginosa, methicillin-resistant Staphylococcus aureus, and vancomycin-resistant Enterococci from hospitals. The results were compared with the gold standard broth microdilution test. The SCMA results were obtained in less than 4 hours, with 91.5% categorical agreement and 6.51% minor, 2.56% major, and 1.49% very major discrepancies. Thus, SCMA provides rapid and accurate antimicrobial susceptibility data that satisfy the recommended performance of the U.S. Food and Drug Administration.

The purpose of the study was to investigate the influence of the chin-tuck maneuver on the movements of swallowing-related structures in healthy subjects and formulate standard instructions for the maneuver. A total of 40 healthy volunteers (20 men and 20 women) swallowed 10 mL of diluted barium solution in a “normal and comfortable” position (NEUT), a comfortable chin-down position (DOWN), and a strict chin-tuck position (TUCK). Resting state anatomy and kinematic changes were analyzed and compared between postures. Although angles of anterior cervical flexion were comparable between DOWN (46.65 ± 9.69 degrees) and TUCK (43.27 ± 12.20), the chin-to-spine distance was significantly shorter in TUCK than in other positions. Only TUCK showed a significantly shorter anteroposterior diameter of the laryngeal inlet (TUCK vs. NEUT, 14.0 ± 4.3 vs. 16.3 ± 5.0 mm) and the oropharynx (18.8 ± 3.1 vs. 20.5 ± 2.8 mm) at rest. The maximal horizontal displacement of the hyoid bone was significantly less in TUCK (9.6 ± 3.0 mm) than in NEUT (12.6 ± 2.6 mm; p < 0.01) or DOWN (12.1 ± 3.0 mm; p < 0.01). TUCK facilitated movement of the epiglottic base upward (TUCK vs. NEUT, 15.8 ± 4.7 vs. 13.3 ± 4.5 mm; p < 0.01). In contrast, DOWN increased the horizontal excursion of the epiglottic base and reduced movement of the vocal cords. These results quantitatively elucidated the biomechanical influences of the chin-tuck maneuver including reduced horizontal movement of the hyoid bone, facilitation of vertical movement of the epiglottic base, and narrowing of the airway entrance. Comparing DOWN and TUCK, only TUCK induced significant changes in the airway entrance, hyoid movement, and epiglottic base retraction.

The objective of this study was to compare the quantitative and qualitative shear-wave elastographic (SWE) features of breast cancers with mechanical elasticity and histopathologic characteristics. This prospective study was conducted with institutional review board approval, and written informed consent was obtained. Shear-wave elastography was performed for 30 invasive breast cancers in 30 women before surgery. The mechanical elasticity of a fresh breast tissue section, correlated with the ultrasound image, was measured using an indentation system. Quantitative (maximum, mean, minimum, and standard deviation of elasticity in kilopascals) and qualitative (color heterogeneity and presence of signal void areas in the mass) SWE features were compared with mechanical elasticity and histopathologic characteristics using the Pearson correlation coefficient and the Wilcoxon signed rank test. Maximum SWE values showed a moderate correlation with maximum mechanical elasticity (r = 0.530, P = 0.003). There were no significant differences between SWE values and mechanical elasticity in histologic grade I or II cancers (P = 0.268). However, SWE values were significantly higher than mechanical elasticity in histologic grade III cancers (P < 0.001), which have low amounts of fibrosis, high tumor cellularity, and intratumoral necrosis. In addition, color heterogeneity was correlated with intratumoral heterogeneity of mechanical elasticity (r = 0.469, P = 0.009). Signal void areas in the masses were present in 43% of breast cancers (13 of 30) and were correlated with dense collagen depositions (n = 11) or intratumoral necrosis (n = 2). Quantitative and qualitative SWE features reflect both the mechanical elasticity and histopathologic characteristics of breast cancers.

Detection and diagnosis based on extracting features and classification using electroencephalography (EEG) signals are being studied vigorously. A network analysis of time series EEG signal data is one of many techniques that could help study brain functions. In this study, we analyze EEG to diagnose alcoholism. We propose a novel methodology to estimate the differences in the status of the brain based on EEG data of normal subjects and data from alcoholics by computing many parameters stemming from effective network using Granger causality. Among many parameters, only ten parameters were chosen as final candidates. By the combination of ten graph-based parameters, our results demonstrate predictable differences between alcoholics and normal subjects. A support vector machine classifier with best performance had 90% accuracy with sensitivity of 95.3%, and specificity of 82.4% for differentiating between the two groups.