Protein Signaling Networks from Single Cell Fluctuations and Information Theory Profiling

Protein signaling networks among cells play critical roles in a host of pathophysiological processes, from inflammation to tumorigenesis. We report on an approach that integrates microfluidic cell handling, in situ protein secretion profiling, and information theory to determine an extracellular protein-signaling network and the role of perturbations. We assayed 12 proteins secreted from human macrophages that were subjected to lipopolysaccharide challenge, which emulates the macrophage-based innate immune responses against Gram-negative bacteria. We characterize the fluctuations in protein secretion of single cells, and of small cell colonies (n = 2, 3,···), as a function of colony size. Measuring the fluctuations permits a validation of the conditions required for the application of a quantitative version of the Le Chatelier's principle, as derived using information theory. This principle provides a quantitative prediction of the role of perturbations and allows a characterization of a protein-protein interaction network

Clinical application of S-Detect to breast masses on ultrasonography: a study evaluating the diagnostic performance and agreement with a dedicated breast radiologist

Purpose The purpose of this study was to evaluate the diagnostic performance of S-Detect when applied to breast ultrasonography (US), and the agreement with an experienced radiologist specializing in breast imaging. Methods From June to August 2015, 192 breast masses in 175 women were included. US features of the breast masses were retrospectively analyzed by a radiologist who specializes in breast imaging and S-Detect, according to the fourth edition of the American College of Radiology Breast Imaging Reporting and Data System lexicon and final assessment categories. Final assessments from S-Detect were in dichotomized form: possibly benign and possibly malignant. Kappa statistics were used to analyze the agreement between the radiologist and S-Detect. Diagnostic performance of the radiologist and S-Detect was calculated, including sensitivity, specificity, positive predictive value (PPV), negative predictive value, accuracy, and area under the receiving operator characteristics curve. Results Of the 192 breast masses, 72 (37.5%) were malignant, and 120 (62.5%) were benign. Benign masses among category 4a had higher rates of possibly benign assessment on S-Detect for the radiologist, 63.5% to 36.5%, respectively (P=0.797). When the cutoff was set at category 4a, the specificity, PPV, and accuracy was significantly higher in S-Detect compared to the radiologist (all P<0.05), with a higher area under the receiver operator characteristics curve of 0.725 compared to 0.653 (P=0.038). Moderate agreement (k=0.58) was seen in the final assessment between the radiologist and S-Detect. Conclusion S-Detect may be used as an additional diagnostic tool to improve the specificity of breast US in clinical practice, and guide in decision making for breast masses detected on US

An effective procedure for sensor variable selection and utilization in plasma etching for semiconductor manufacturing

a b s t r a c t Plasma etching processes have a potentially large number of sensor variables to be utilized, and the number of the sensor variables is growing due to advances in real-time sensors. In addition, the sensor variables from plasma sensors require additional knowledge about plasmas, which becomes a big burden for engineers to utilize them in this filed. Thus an effective procedure for sensor variable selection with minimum plasma knowledge is needed to develop in plasma etching. The integrated squared response (ISR) based sensor variable selection method which facilitates collecting and analyzing sensor data at one time with regard to manipulated variables (MVs) is suggested in this paper. The reference sensor library as well as sensor ranking tables constructed on the basis of ISR can give insight into plasma sensors. The ISR based sensor variable selection method is incorporated with relative gain array (RGA) or nonsquare relative gain array (NRGA) for effective variable selection in building a virtual metrology (VM) system to predict critical dimension (CD) in plasma etching. The application of the technique introduced in this paper is shown to be effective in the CD prediction in plasma etching for a dynamic random access memory (DRAM) manufacturing. The procedure for sensor variable selection introduced in this paper can be a starting point for various sensor-related applications in semiconductor manufacturing

Serum spectrin breakdown product and neurofilament heavy in predicting outcome after cardiac arrest: A diagnostic accuracy study

Objectives: Spectrin breakdown products 145 kDa (SBDP145) and neurofilament heavy chain (Nf-H) have been identified as potential biomarkers of neuronal injury. However, their ability to predict hypoxic-ischemic brain injury following cardiac arrest in humans is not well understood. This study aimed to investigate whether SBDP145 and Nf-H could be used as biomarkers to predict neurological outcomes after cardiac arrest. Methods: This prospective study was conducted at two academic hospitals and included adults who survived after cardiac arrest. Blood samples were collected at 0, 24, and 48 h after the return of spontaneous circulation, and biomarker analyses were performed to measure SBDP145 and Nf-H. Poor neurological outcome was defined as a modified Rankin Score of 4–6, and diagnostic performance was determined by receiver-operating characteristics analysis. Results: A total of 56 patients were included in this study. There were no significant differences in levels of SBDP145 or Nf-H between the poor and good outcome groups at any time point. Areas under the receiver-operating characteristics curve of SBDP145 and Nf-H were small, ranging from 0.51 to 0.7. At 0, 24, and 48 h, SBDP145 showed very low sensitivity (18.61 %, 13.89 %, and 13.79 %, respectively) and accuracy (33.93 %, 36.74 %, and 39.02 %, respectively) at a cut-off value for 100 % specificity. Nf-H also showed very low sensitivity (9.30 %, 16.67 %, and 0 %, respectively) and accuracy (29.09 %, 36.74 %, and 30.95 %, respectively). Conclusions: SBDP145 and Nf-H were found to be poor predictors of poor neurological outcomes six months after cardiac arrest

Systematic Regeneration of Waste Sulfuric Acid in Semiconductor Manufacturing Using Batch Vacuum Distillation

We describe herein a systematic regeneration of waste sulfuric acid produced in semiconductor manufacturing, using batch vacuum distillation (BVD). During the recycling process, dilute sulfuric acid feed was continuously concentrated and fed back to the original wafer washing step. It consisted of a batch tank to charge the feed solution, condenser to capture generated vapor, receiving tank to receive condensed distillate liquid, and vacuum pump to reduce the system pressure. The improper control of the vacuum operation led to incomplete condensation; consequently, the vacuum pump became dysfunctional. The goal of this study was to prevent such mishap. After the feed condition was defined, a basic design was conceived, and the main characteristics of the BVD were determined. The results of sensitivity analyses on the feed and operating conditions have been discussed. The strategies for designing the vacuum pump’s capacity should be changed depending on phase equilibria at the target pressure