scholarly journals Ultra-rapid somatic variant detection via real-time threshold sequencing

2021 ◽  
Author(s):  
Jack Wadden ◽  
Brandon Newell ◽  
Joshua Bugbee ◽  
Robert P Dickson ◽  
Carl Koschmann ◽  
...  

Molecular markers are becoming increasingly important for cancer diagnosis, proper clinical trial enrollment, and even surgical decision making, motivating ultra-rapid, intraoperative variant detection. Sequencing-based detection is considered the gold standard approach, but typically takes hours to perform. In this work, we present Threshold Sequencing, a methodology for designing protocols for targeted variant detection on real-time sequencers with a minimal time to result. Threshold Sequencing analytically identifies a time-optimal threshold to stop target amplification and begin sequencing. To further reduce diagnostic time, we explore targeted Loop-mediated Isothermal Amplification (LAMP) and design a LAMP-specific bioinformatics tool--LAMPrey--to process sequenced LAMP product. LAMPrey's concatemer aware alignment algorithm is designed to maximize recovery of diagnostically relevant information leading to a more rapid detection versus standard read alignment approaches. Coupled with time-optimized DNA extraction and library preparation, we demonstrate confirmation of a hot-spot mutation (250x support) from tumor tissue in less than 30 minutes.

2020 ◽  
pp. 1-19
Author(s):  
Fernando Cantú-Bazaldúa

World economic aggregates are compiled infrequently and released after considerable lags. There are, however, many potentially relevant series released in a timely manner and at a higher frequency that could provide significant information about the evolution of global aggregates. The challenge is then to extract the relevant information from this multitude of indicators and combine it to track the real-time evolution of the target variables. We develop a methodology based on dynamic factor models adapted for variables with heterogeneous frequencies, ragged ends and missing data. We apply this methodology to nowcast global trade in goods in goods and services. In addition to monitoring these variables in real time, this method can also be used to obtain short-term forecasts based on the most up-to-date values of the underlying indicators.


Author(s):  
Zhiyao Zhong ◽  
Danji Huang ◽  
Kewei Hu ◽  
Xiaomeng Ai ◽  
Jiakun Fang

Processes ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 522
Author(s):  
Qiu-Yun Huang ◽  
Ai-Peng Jiang ◽  
Han-Yu Zhang ◽  
Jian Wang ◽  
Yu-Dong Xia ◽  
...  

As the leading thermal desalination method, multistage flash (MSF) desalination plays an important role in obtaining freshwater. Its dynamic modeling and dynamic performance prediction are quite important for the optimal control, real-time optimal operation, maintenance, and fault diagnosis of MSF plants. In this study, a detailed mathematical model of the MSF system, based on the first principle and its treatment strategy, was established to obtain transient performance change quickly. Firstly, the whole MSF system was divided into four parts, which are brine heat exchanger, flashing stage room, mixed and split modulate, and physical parameter modulate. Secondly, based on mass, energy, and momentum conservation laws, the dynamic correlation equations were formulated and then put together for a simultaneous solution. Next, with the established model, the performance of a brine-recirculation (BR)-MSF plant with 16-stage flash chambers was simulated and compared for validation. Finally, with the validated model and the simultaneous solution method, dynamic simulation and analysis were carried out to respond to the dynamic change of feed seawater temperature, feed seawater concentration, recycle stream mass flow rate, and steam temperature. The dynamic response curves of TBT (top brine temperature), BBT (bottom brine temperature), the temperature of flashing brine at previous stages, and distillate mass flow rate at previous stages were obtained, which specifically reflect the dynamic characteristics of the system. The presented dynamic model and its treatment can provide better analysis for the real-time optimal operation and control of the MSF system to achieve lower operational cost and more stable freshwater quality.


Electronics ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 943 ◽  
Author(s):  
Il Bae ◽  
Jaeyoung Moon ◽  
Jeongseok Seo

The convergence of mechanical, electrical, and advanced ICT technologies, driven by artificial intelligence and 5G vehicle-to-everything (5G-V2X) connectivity, will help to develop high-performance autonomous driving vehicles and services that are usable and convenient for self-driving passengers. Despite widespread research on self-driving, user acceptance remains an essential part of successful market penetration; this forms the motivation behind studies on human factors associated with autonomous shuttle services. We address this by providing a comfortable driving experience while not compromising safety. We focus on the accelerations and jerks of vehicles to reduce the risk of motion sickness and to improve the driving experience for passengers. Furthermore, this study proposes a time-optimal velocity planning method for guaranteeing comfort criteria when an explicit reference path is given. The overall controller and planning method were verified using real-time, software-in-the-loop (SIL) environments for a real-time vehicle dynamics simulation; the performance was then compared with a typical planning approach. The proposed optimized planning shows a relatively better performance and enables a comfortable passenger experience in a self-driving shuttle bus according to the recommended criteria.


Neurosurgery ◽  
2004 ◽  
Vol 55 (3) ◽  
pp. 551-561 ◽  
Author(s):  
Ali H. Mesiwala ◽  
Louis D. Scampavia ◽  
Peter S. Rabinovitch ◽  
Jaromir Ruzicka ◽  
Robert C. Rostomily

Abstract OBJECTIVE: This study tests the feasibility of using on-line analysis of tissue during surgical resection of brain tumors to provide biologically relevant information in a clinically relevant time frame to augment surgical decision making. For the purposes of establishing feasibility, we used measurement of deoxyribonucleic acid (DNA) content as the end point for analysis. METHODS: We investigated the feasibility of interfacing an ultrasonic aspiration (USA) system with a flow cytometer (FC) capable of analyzing DNA content (DNA-FC). The sampling system design, tissue preparation requirements, and time requirements for each step of the on-line analysis system were determined using fresh beef brain tissue samples. We also compared DNA-FC measurements in 28 nonneoplastic human brain samples with DNA-FC measurements in specimens of 11 glioma patients obtained from central tumor regions and surgical margins after macroscopically gross total tumor removal to estimate the potential for analysis of a biological marker to influence surgical decision making. RESULTS: With minimal modification, modern FC systems are fully capable of real-time, intraoperative analysis of USA specimens. The total time required for on-line analysis of USA specimens varies between 36 and 63 seconds; this time includes delivery from the tip of the USA to complete analysis of the specimen. Approximately 60% of this time is required for equilibration of the DNA stain. When compared with values for nonneoplastic human brain samples, 50% of samples (10 of 20) from macroscopically normal glioma surgical margins contained DNA-FC abnormalities potentially indicating residual tumor. CONCLUSION: With an interface of existing technologies, DNA content of brain tissue samples can be analyzed in a meaningful time frame that has the potential to provide real-time information for surgical guidance. The identification of DNA content abnormalities in macroscopically normal tumor resection margins by DNA-FC supports the practical potential for on-line analysis of a tumor marker to guide surgical resections. The development of such a device would provide neurosurgeons with an objective method for intraoperative analysis of a clinically relevant biological parameter that can be measured in real time.


2020 ◽  
Vol 10 (24) ◽  
pp. 9154
Author(s):  
Paula Morella ◽  
María Pilar Lambán ◽  
Jesús Royo ◽  
Juan Carlos Sánchez ◽  
Jaime Latapia

The purpose of this work is to develop a new Key Performance Indicator (KPI) that can quantify the cost of Six Big Losses developed by Nakajima and implements it in a Cyber Physical System (CPS), achieving a real-time monitorization of the KPI. This paper follows the methodology explained below. A cost model has been used to accurately develop this indicator together with the Six Big Losses description. At the same time, the machine tool has been integrated into a CPS, enhancing the real-time data acquisition, using the Industry 4.0 technologies. Once the KPI has been defined, we have developed the software that can turn these real-time data into relevant information (using Python) through the calculation of our indicator. Finally, we have carried out a case of study showing our new KPI results and comparing them to other indicators related with the Six Big Losses but in different dimensions. As a result, our research quantifies economically the Six Big Losses, enhances the detection of the bigger ones to improve them, and enlightens the importance of paying attention to different dimensions, mainly, the productive, sustainable, and economic at the same time.


2018 ◽  
Vol 15 (8) ◽  
pp. 750-759 ◽  
Author(s):  
Fatemeh Jafari ◽  
S. Jamshid Mousavi ◽  
Jafar Yazdi ◽  
Joong Hoon Kim

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