A one-pot set-up for real-time reaction monitoring by FTIR spectroscopy

2016 ◽  
Vol 50 (3) ◽  
pp. 567-580 ◽  
Author(s):  
Thomas Gillgren ◽  
András Gorzsás
Keyword(s):  
Ftir Spectroscopy ◽  
Real Time ◽  
Reaction Monitoring ◽  
One Pot ◽  
Set Up

scholarly journals On the fly multi-modal observation of ligand synthesis and complexation of Cu complexes in flow with ‘benchtop’ NMR and mass spectrometry

2016 ◽  
Vol 3 (7) ◽  
pp. 919-923 ◽  
Author(s):  
Luzian Porwol ◽  
Alon Henson ◽  
Philip J. Kitson ◽  
De-Liang Long ◽  
Leroy Cronin
Keyword(s):  
Mass Spectrometry ◽  
Real Time ◽  
Self Assembly ◽  
Coordination Compounds ◽  
The Self ◽  
One Pot ◽  
Time Observation ◽  
Set Up ◽  
Cu Complexes ◽  
Real Time Observation

The transfer of one-pot reactions to a continuous non-equilibrium set-up for real-time observation of the self-assembly of new coordination compounds is presented.

DEVELOPMENT OF MULTIPLEX REAL-TIME PCR ASSAY FOR SIX PATHOGENS: RAPID TOOL FOR DIAGNOSIS OF BACTERIAL MENINGITIS

2019 ◽  
pp. 60-66
Author(s):  
Viet Quynh Tram Ngo ◽  
Thi Ti Na Nguyen ◽  
Hoang Bach Nguyen ◽  
Thi Tuyet Ngoc Tran ◽  
Thi Nam Lien Nguyen ◽  
...  
Keyword(s):  
Bacterial Meningitis ◽  
Real Time ◽  
Real Time Pcr ◽  
Diagnostic Methods ◽  
Type B ◽  
E Coli ◽  
Pcr Assays ◽  
Set Up ◽  
Etiological Agents ◽  
Suis Serotype

Introduction: Bacterial meningitis is an acute central nervous infection with high mortality or permanent neurological sequelae if remained undiagnosed. However, traditional diagnostic methods for bacterial meningitis pose challenge in prompt and precise identification of causative agents. Aims: The present study will therefore aim to set up in-house PCR assays for diagnosis of six pathogens causing the disease including H. influenzae type b, S. pneumoniae, N. meningitidis, S. suis serotype 2, E. coli and S. aureus. Methods: inhouse PCR assays for detecting six above-mentioned bacteria were optimized after specific pairs of primers and probes collected from the reliable literature resources and then were performed for cerebrospinal fluid (CSF) samples from patients with suspected meningitis in Hue Hospitals. Results: The set of four PCR assays was developed including a multiplex real-time PCR for S. suis serotype 2, H. influenzae type b and N. meningitides; three monoplex real-time PCRs for E. coli, S. aureus and S. pneumoniae. Application of the in-house PCRs for 116 CSF samples, the results indicated that 48 (39.7%) cases were positive with S. suis serotype 2; one case was positive with H. influenzae type b; 4 cases were positive with E. coli; pneumococcal meningitis were 19 (16.4%) cases, meningitis with S. aureus and N. meningitidis were not observed in any CSF samples in this study. Conclusion: our in-house real-time PCR assays are rapid, sensitive and specific tools for routine diagnosis to detect six mentioned above meningitis etiological agents. Key words: Bacterial meningitis, etiological agents, multiplex real-time PCR

scholarly journals Implementation of a deep learning model for automated classification of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) in real time

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Song-Quan Ong ◽  
Hamdan Ahmad ◽  
Gomesh Nair ◽  
Pradeep Isawasan ◽  
Abdul Hafiz Ab Majid
Keyword(s):  
Deep Learning ◽  
Aedes Aegypti ◽  
Real Time ◽  
Aedes Albopictus ◽  
Automated Classification ◽  
Expert Performance ◽  
Deep Convolutional Neural Networks ◽  
Significant Difference ◽  
Set Up

AbstractClassification of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) by humans remains challenging. We proposed a highly accessible method to develop a deep learning (DL) model and implement the model for mosquito image classification by using hardware that could regulate the development process. In particular, we constructed a dataset with 4120 images of Aedes mosquitoes that were older than 12 days old and had common morphological features that disappeared, and we illustrated how to set up supervised deep convolutional neural networks (DCNNs) with hyperparameter adjustment. The model application was first conducted by deploying the model externally in real time on three different generations of mosquitoes, and the accuracy was compared with human expert performance. Our results showed that both the learning rate and epochs significantly affected the accuracy, and the best-performing hyperparameters achieved an accuracy of more than 98% at classifying mosquitoes, which showed no significant difference from human-level performance. We demonstrated the feasibility of the method to construct a model with the DCNN when deployed externally on mosquitoes in real time.

scholarly journals Operational Research to Assess the Real-Time Impact of COVID-19 on TB and HIV Services: The Experience and Response from Health Facilities in Harare, Zimbabwe

2021 ◽  
Vol 6 (2) ◽  
pp. 94
Author(s):  
Pruthu Thekkur ◽  
Kudakwashe C. Takarinda ◽  
Collins Timire ◽  
Charles Sandy ◽  
Tsitsi Apollo ◽  
...  
Keyword(s):  
Hiv Testing ◽  
Treatment Outcomes ◽  
Real Time ◽  
Treatment Success ◽  
Health Facilities ◽  
Case Detection ◽  
Monthly Data ◽  
Hiv Services ◽  
Tb Treatment ◽  
Set Up

When COVID-19 was declared a pandemic, there was concern that TB and HIV services in Zimbabwe would be severely affected. We set up real-time monthly surveillance of TB and HIV activities in 10 health facilities in Harare to capture trends in TB case detection, TB treatment outcomes and HIV testing and use these data to facilitate corrective action. Aggregate data were collected monthly during the COVID-19 period (March 2020–February 2021) using EpiCollect5 and compared with monthly data extracted for the pre-COVID-19 period (March 2019–February 2020). Monthly reports were sent to program directors. During the COVID-19 period, there was a decrease in persons with presumptive pulmonary TB (40.6%), in patients registered for TB treatment (33.7%) and in individuals tested for HIV (62.8%). The HIV testing decline improved in the second 6 months of the COVID-19 period. However, TB case finding deteriorated further, associated with expiry of diagnostic reagents. During the COVID-19 period, TB treatment success decreased from 80.9 to 69.3%, and referral of HIV-positive persons to antiretroviral therapy decreased from 95.7 to 91.7%. Declining trends in TB and HIV case detection and TB treatment outcomes were not fully redressed despite real-time monthly surveillance. More support is needed to transform this useful information into action.

scholarly journals Real time surveillance of COVID-19 space and time clusters during the summer 2020 in Spain

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Nicolás Rosillo ◽  
Javier Del-Águila-Mejía ◽  
Ayelén Rojas-Benedicto ◽  
María Guerrero-Vadillo ◽  
Marina Peñuelas ◽  
...  
Keyword(s):  
Real Time ◽  
Scan Statistic ◽  
Cluster Aggregation ◽  
Space And Time ◽  
Spatial Trends ◽  
Community Transmission ◽  
Low Incidence ◽  
Set Up ◽  
And Control ◽  
Time Scan

Abstract Background On June 21st de-escalation measures and state-of-alarm ended in Spain after the COVID-19 first wave. New surveillance and control strategy was set up to detect emerging outbreaks. Aim To detect and describe the evolution of COVID-19 clusters and cases during the 2020 summer in Spain. Methods A near-real time surveillance system to detect active clusters of COVID-19 was developed based on Kulldorf’s prospective space-time scan statistic (STSS) to detect daily emerging active clusters. Results Analyses were performed daily during the summer 2020 (June 21st – August 31st) in Spain, showing an increase of active clusters and municipalities affected. Spread happened in the study period from a few, low-cases, regional-located clusters in June to a nationwide distribution of bigger clusters encompassing a higher average number of municipalities and total cases by end-August. Conclusion STSS-based surveillance of COVID-19 can be of utility in a low-incidence scenario to help tackle emerging outbreaks that could potentially drive a widespread transmission. If that happens, spatial trends and disease distribution can be followed with this method. Finally, cluster aggregation in space and time, as observed in our results, could suggest the occurrence of community transmission.

Reducing Culture Reporting Errors in the Microbiology Laboratory

2019 ◽  
Vol 152 (Supplement_1) ◽  
pp. S131-S132
Author(s):  
Kathryn Hogan ◽  
Beena Umar ◽  
Mohamed Alhamar ◽  
Kathleen Callahan ◽  
Linoj Samuel
Keyword(s):  
Real Time ◽  
Error Rate ◽  
Reporting System ◽  
Error Rates ◽  
Tracking Errors ◽  
Corrective Measures ◽  
Safety Awareness ◽  
Before And After ◽  
Set Up ◽  
System Errors

Abstract Objectives There are few papers that characterize types of errors in microbiology laboratories and scant research demonstrating the effects of interventions on microbiology lab errors. This study aims to categorize types of culture reporting errors found in microbiology labs and to document the error rates before and after interventions designed to reduce errors and improve overall laboratory quality. Methods To improve documentation of error incidence, a self-reporting system was changed to an automatic reporting system. Errors were categorized into five types Gram stain (misinterpretations), identification (incorrect analysis), set up labeling (incorrect patient labels), procedures (not followed), and miscellaneous. Error rates were tracked according to technologist, and technologists were given real-time feedback by a manager. Error rates were also monitored in the daily quality meeting and frequently detected errors were discussed at staff meetings. Technologists attended a year-end review with a manager to improve their performance. To maintain these changes, policies were developed to monitor technologist error rate and to define corrective measures. If a certain number of errors per month was reached, technologists were required to undergo retraining by a manager. If a technologist failed to correct any error according to protocol, they were also potentially subject to corrective measures. Results In 2013, we recorded 0.5 errors per 1,000 tests. By 2018, we recorded only 0.1 errors per 1,000 tests, an 80% decrease. The yearly culture volume from 2013 to 2018 increased by 32%, while the yearly error rate went from 0.05% per year to 0.01% per year, a statistically significant decrease (P = .0007). Conclusion This study supports the effectiveness of the changes implemented to decrease errors in culture reporting. By tracking errors in real time and using a standardized process that involved timely follow-up, technologists were educated on error prevention. This practice increased safety awareness in our micro lab.

scholarly journals Broccoli Fluorets: Split Aptamers as a User-Friendly Fluorescent Toolkit for Dynamic RNA Nanotechnology

Molecules ◽  
2018 ◽  
Vol 23 (12) ◽  
pp. 3178 ◽  
Author(s):  
Morgan Chandler ◽  
Tatiana Lyalina ◽  
Justin Halman ◽  
Lauren Rackley ◽  
Lauren Lee ◽  
...  
Keyword(s):  
Real Time ◽  
Logic Gates ◽  
Rna Aptamers ◽  
One Pot ◽  
Rna Nanotechnology ◽  
Close Proximity ◽  
Direct Tracking ◽  
Displacement Approach ◽  
User Friendly ◽  
In Cells

RNA aptamers selected to bind fluorophores and activate their fluorescence offer a simple and modular way to visualize native RNAs in cells. Split aptamers which are inactive until the halves are brought within close proximity can become useful for visualizing the dynamic actions of RNA assemblies and their interactions in real time with low background noise and eliminated necessity for covalently attached dyes. Here, we design and test several sets of F30 Broccoli aptamer splits, that we call fluorets, to compare their relative fluorescence and physicochemical stabilities. We show that the splits can be simply assembled either through one-pot thermal annealing or co-transcriptionally, thus allowing for direct tracking of transcription reactions via the fluorescent response. We suggest a set of rules that enable for the construction of responsive biomaterials that readily change their fluorescent behavior when various stimuli such as the presence of divalent ions, exposure to various nucleases, or changes in temperature are applied. We also show that the strand displacement approach can be used to program the controllable fluorescent responses in isothermal conditions. Overall, this work lays a foundation for the future development of dynamic systems for molecular computing which can be used to monitor real-time processes in cells and construct biocompatible logic gates.

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