Highly selective and sensitive chromogenic detection of nerve agents (sarin, tabun and VX): a multianalyte detection approach

2017 ◽  
Vol 53 (96) ◽  
pp. 12954-12957 ◽  
Author(s):  
Vinod Kumar ◽  
G. Raviraju ◽  
Hemlata Rana ◽  
Vepa Kameswara Rao ◽  
Arvind K. Gupta
Keyword(s):  
Nerve Agents ◽  
Detection Approach ◽  
Multianalyte Detection ◽  
Novel Strategy

A novel strategy using ferrocenyl dye (1) was developed for highly selective chromogenic detection of all nerve agents.

A noise reduction method for semi-supervised community detection based on harmonic function

2018 ◽  
Vol 32 (14) ◽  
pp. 1850166 ◽  
Author(s):  
Lilin Fan ◽  
Kaiyuan Song ◽  
Dong Liu
Keyword(s):  
Harmonic Function ◽  
Prior Knowledge ◽  
Community Detection ◽  
Detection Methods ◽  
Detection Process ◽  
Knowledge Based ◽  
Detection Approach ◽  
Series Of Experiments ◽  
Novel Strategy ◽  
The Impact

Semi-supervised community detection is an important research topic in the field of complex network, which incorporates prior knowledge and topology to guide the community detection process. However, most of the previous work ignores the impact of the noise from prior knowledge during the community detection process. This paper proposes a novel strategy to identify and remove the noise from prior knowledge based on harmonic function, so as to make use of prior knowledge more efficiently. Finally, this strategy is applied to three state-of-the-art semi-supervised community detection methods. A series of experiments on both real and artificial networks demonstrate that the accuracy of semi-supervised community detection approach can be further improved.

Chromogenic and fluorogenic multianalyte detection with a tuned receptor: refining selectivity for toxic anions and nerve agents

RSC Advances ◽  
2016 ◽  
Vol 6 (64) ◽  
pp. 59648-59656 ◽  
Author(s):  
Vinod Kumar ◽  
Hemlata Rana ◽  
G. Raviraju ◽  
Prabhat Garg ◽  
Anuradha Baghel ◽  
...  
Keyword(s):  
Nerve Agents ◽  
Nerve Agent ◽  
Chemical Probe ◽  
Multianalyte Detection

In the present study, a chemical probe was finely tuned for the highly selective and sensitive chromogenic and fluorogenic detection of toxic anions and a nerve agent.

The Collaborative Network Approach: a model for advancing patient-centric research for Castleman disease and other rare diseases

2019 ◽  
Vol 3 (1) ◽  
pp. 97-105
Author(s):  
Mary Zuccato ◽  
Dustin Shilling ◽  
David C. Fajgenbaum
Keyword(s):  
Rare Diseases ◽  
Treatment Options ◽  
Castleman Disease ◽  
High Impact ◽  
Collaborative Network ◽  
Network Approach ◽  
Grant Applications ◽  
Research Questions ◽  
Novel Strategy ◽  
Patient Centric

Abstract There are ∼7000 rare diseases affecting 30 000 000 individuals in the U.S.A. 95% of these rare diseases do not have a single Food and Drug Administration-approved therapy. Relatively, limited progress has been made to develop new or repurpose existing therapies for these disorders, in part because traditional funding models are not as effective when applied to rare diseases. Due to the suboptimal research infrastructure and treatment options for Castleman disease, the Castleman Disease Collaborative Network (CDCN), founded in 2012, spearheaded a novel strategy for advancing biomedical research, the ‘Collaborative Network Approach’. At its heart, the Collaborative Network Approach leverages and integrates the entire community of stakeholders — patients, physicians and researchers — to identify and prioritize high-impact research questions. It then recruits the most qualified researchers to conduct these studies. In parallel, patients are empowered to fight back by supporting research through fundraising and providing their biospecimens and clinical data. This approach democratizes research, allowing the entire community to identify the most clinically relevant and pressing questions; any idea can be translated into a study rather than limiting research to the ideas proposed by researchers in grant applications. Preliminary results from the CDCN and other organizations that have followed its Collaborative Network Approach suggest that this model is generalizable across rare diseases.

Design and Optimization of a Novel Strategy for the Local Treatment of Helicobacter pylori Infections

2020 ◽  
Author(s):  
Taddese Mekonnen Ambay ◽  
Philipp Schick ◽  
Michael Grimm ◽  
Maximilian Sager ◽  
Felix Schneider ◽  
...  
Keyword(s):  
Helicobacter Pylori ◽  
Local Treatment ◽  
Design And Optimization ◽  
Novel Strategy

L cell stimulation: a novel strategy for oral peptide delivery in incretin-based diabetes treatment

2020 ◽  
Author(s):  
Ana Beloqui ◽  
Francesco Suriano ◽  
Matthias Hul ◽  
Yining Xu ◽  
Véronique Préat ◽  
...  
Keyword(s):  
Peptide Delivery ◽  
Diabetes Treatment ◽  
Cell Stimulation ◽  
Oral Peptide Delivery ◽  
L Cell ◽  
Novel Strategy

Evaluating Performance Effects of Low-Level Inhalation Exposure to Nerve Agents in Rats

2004 ◽  
Author(s):  
Raymond F. Genovese ◽  
◽  
Sara J. Shippee ◽  
Jessica Bonnell ◽  
Bernard J. Benton ◽  
...  
Keyword(s):  
Inhalation Exposure ◽  
Nerve Agents ◽  
Low Level ◽  
Performance Effects

A Fault Detection Approach Based on Sound Signal Analysis for Equipment Monitoring

2020 ◽  
pp. 129-139
Author(s):  
Weihai Sun ◽  
Lemei Han
Keyword(s):  
Fault Detection ◽  
Signal Analysis ◽  
Energy Analysis ◽  
Detection Method ◽  
Sound Signal ◽  
Practical Significance ◽  
Time Frequency ◽  
Detection Approach ◽  
Machine Fault ◽  
Learning Data

Machine fault detection has great practical significance. Compared with the detection method that requires external sensors, the detection of machine fault by sound signal does not need to destroy its structure. The current popular audio-based fault detection often needs a lot of learning data and complex learning process, and needs the support of known fault database. The fault detection method based on audio proposed in this paper only needs to ensure that the machine works normally in the first second. Through the correlation coefficient calculation, energy analysis, EMD and other methods to carry out time-frequency analysis of the subsequent collected sound signals, we can detect whether the machine has fault.

Melatonin: a novel strategy for prevention of obesity and fat accumulation in peripheral organs through the improvements of circadian rhythms and antioxidative capacity

2020 ◽  
Vol 3 (1) ◽  
pp. 58-76 ◽  
Author(s):  
Bohan Rong ◽  
Qiong Wu ◽  
Chao Sun
Keyword(s):  
Oxidative Stress ◽  
Skeletal Muscle ◽  
Circadian Rhythms ◽  
Regulatory Mechanisms ◽  
Antioxidative Capacity ◽  
Unicellular Alga ◽  
Peripheral Tissues ◽  
Peripheral Organs ◽  
Regulatory Effects ◽  
Novel Strategy

Melatonin is a well-known molecule for its involvement in circadian rhythm regulation and its contribution to protection against oxidative stress in organisms including unicellular alga, animals and plants. Currently, the bio-regulatory effects of melatonin on the physiology of various peripheral tissues have drawn a great attention of scientists. Although melatonin was previously defined as a neurohormone secreted from pineal gland, recently it has been identified that virtually, every cell has the capacity to synthesize melatonin and the locally generated melatonin has multiple pathophysiological functions, including regulations of obesity and metabolic syndromes. Herein, we focus on the effects of melatonin on fat deposition in various peripheral organs/tissues. The two important regulatory mechanisms related to the topic, i.e., the improvements of circadian rhythms and antioxidative capacity will be thoroughly discussed since they are linked to several biomarkers involved in obesity and energy imbalance, including metabolism and immunity. Furthermore, several other functions of melatonin which may serve to prevent or promote obesity and energy dysmetabolism-induced pathological states are also addressed. The organs of special interest include liver, pancreas, skeletal muscle, adipose tissue and the gut microbiota.

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