scholarly journals Therapy of Pediatric-Onset Multiple Sclerosis: State of the Art, Challenges, and Opportunities

2021 ◽  
Vol 12 ◽  
Author(s):  
Monica Margoni ◽  
Francesca Rinaldi ◽  
Paola Perini ◽  
Paolo Gallo
Keyword(s):  
Multiple Sclerosis ◽  
Observational Studies ◽  
State Of The Art ◽  
Therapeutic Agents ◽  
Efficacy And Safety ◽  
Disease Modifying Drugs ◽  
Current State ◽  
Challenges And Opportunities ◽  
Children And Young Adults ◽  
Pediatric Onset

Treatment of pediatric-onset multiple sclerosis (POMS) has been tailored after observational studies and data obtained from clinical trials in adult-onset multiple sclerosis (AOMS) patients. There are an increasing number of new therapeutic agents for AOMS, and many will be formally studied for use also in POMS. However, there are important efficacy and safety concerns regarding the use of these therapies in children and young adults. This review will discuss the current state of the art of POMS therapy and will focus on the newer therapies (oral and infusion disease-modifying drugs) and on those still currently under investigation.

scholarly journals Biohorology and biomarkers of aging: Current state-of-the-art, challenges and opportunities

2020 ◽  
Vol 60 ◽  
pp. 101050 ◽  
Author(s):  
Fedor Galkin ◽  
Polina Mamoshina ◽  
Alex Aliper ◽  
João Pedro de Magalhães ◽  
Vadim N. Gladyshev ◽  
...  
Keyword(s):  
State Of The Art ◽  
Biomarkers Of Aging ◽  
Current State ◽  
Challenges And Opportunities

scholarly journals Survey of Flight Anomaly Detection Methods: Challenges and Opportunities

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Vivian Rowoli Igenewari ◽  
Zakwan Skaf ◽  
Ian K. Jennions
Keyword(s):  
Anomaly Detection ◽  
State Of The Art ◽  
Detection Methods ◽  
Aviation Industry ◽  
Contributing Factors ◽  
Current State ◽  
Challenges And Opportunities ◽  
Proactive Measures ◽  
Component Faults ◽  
Safety Enhancement

Safety enhancement is a major goal of the aviation industry owing to the predicted increase in air travel. There is also the need to prevent fatalities, increase reliability and reduce monetary costs suffered as a result of delays and accidents that still occur. Accidents today are complex as a result of many causal factors acting alone but more often as a combination with other contributing factors. In tackling this trend, proactive measures have been put in place to find hazardous combinations that occur during flights in order to mitigate them before accidents occur. Flight Anomaly Detection (AD) methods are aimed at highlighting abnormal occurrences of a flight, that are different from the norm. As an improvement on the current state-of-the-art method, previous works have proposed different AD techniques for detection of previously unknown flight risks such as component faults, aircraft operational inefficiencies and some abnormal crew behaviour. However, current AD methods individually have limitations that prevent them from detecting certain significant anomalies in flight data. This paper surveys current flight AD approaches, their strengths and limitations as well as brings to light the benefits of a hybrid AD method to extend previous work and find safety-critical events, particularly those related to abnormal crew activity: a class of events known to amount for a substantial number of accidents/incidents today. It also highlights another emerging AD application opportunity, its challenges and how AD is beneficial in addressing them.

In silico approaches for the prediction and analysis of antiviral peptides: a review

2020 ◽  
Vol 26 ◽  
Author(s):  
Phasit Charoenkwan ◽  
Nuttapat Anuwongcharoen ◽  
Chanin Nantasenamat ◽  
Md. Mehedi Hasan ◽  
Watshara Shoombuatong
Keyword(s):  
State Of The Art ◽  
Therapeutic Agents ◽  
Support Vector ◽  
Sequence Information ◽  
Accurate Identification ◽  
Robust Learning ◽  
Current State ◽  
Pharmacokinetic Properties ◽  
Feature Encoding ◽  
Antiviral Peptides

: In light of the growing resistance toward current antiviral drugs, efforts to discover novel and effective antiviral therapeutic agents remain a pressing scientific effort. Antiviral peptides (AVPs) represents promising therapeutic agents due to their extraordinary advantages in terms of potency, efficacy and pharmacokinetic properties. The growing volume of newly discovered peptide sequences in the post-genomic era requires computational approaches for timely and accurate identification of AVPs. Machine learning (ML) methods such as random forest and support vector machine represents robust learning algorithms that are instrumental in successful peptide-based drug discovery. Therefore, this review summarizes the current state-of-the-art on the application of ML methods for identifying AVPs directly from the sequence information. We compare the efficiency of these methods in terms of the underlying characteristics of the dataset used along with feature encoding methods, ML algorithms, cross-validation methods and prediction performance. Finally, guidelines for development of robust AVP models are also discussed. It is anticipated that this review will be serve as a useful guide for the design and development of robust AVP and related therapeutic peptide predictors in the future.

Integrative Approaches to Multiple Sclerosis

2020 ◽  
pp. 219-242
Author(s):  
Marco Vespignani
Keyword(s):  
Multiple Sclerosis ◽  
Central Nervous System ◽  
Autoimmune Disorder ◽  
The United States ◽  
Integrative Approach ◽  
Current Standard ◽  
Disease Modifying Drugs ◽  
Current State ◽  
The Central Nervous System ◽  
Disease Modifying

Multiple sclerosis (MS) is a chronic progressive autoimmune disorder specific to the central nervous system. The incidence of MS in the United States is roughly 400,000 cases, and worldwide there are approximately 2.5 million cases. It is one of the more common neurodegenerative disease and is thought to be autoimmune, although an antibody has not yet been identified. The current standard of treatment consists of disease-modifying drugs, which have their own toxicity profiles that can inflict further harm to a patient. Indeed, many patients are wary of initiating or continuing this type of treatment. Many patients include alternative treatment approaches. This chapter reviews an integrative approach based on our understanding of the disease and the current state of evidence.

A Perspective on Incentive Design: Challenges and Opportunities

2019 ◽  
Vol 2 (1) ◽  
pp. 305-338
Author(s):  
Lillian J. Ratliff ◽  
Roy Dong ◽  
Shreyas Sekar ◽  
Tanner Fiez
Keyword(s):  
Resource Constraints ◽  
State Of The Art ◽  
Future Research ◽  
Tight Coupling ◽  
Incentive Design ◽  
New Class ◽  
Current State ◽  
Challenges And Opportunities ◽  
The Face ◽  
Unexpected Outcomes

The increasingly tight coupling between humans and system operations in domains ranging from intelligent infrastructure to e-commerce has led to a challenging new class of problems founded on a well-established area of research: incentive design. There is a clear need for a new tool kit for designing mechanisms that help coordinate self-interested parties while avoiding unexpected outcomes in the face of information asymmetries, exogenous uncertainties from dynamic environments, and resource constraints. This article provides a perspective on the current state of the art in incentive design from three core communities—economics, control theory, and machine learning—and highlights interesting avenues for future research at the interface of these domains.

scholarly journals Patients’ satisfaction with and views about treatment with disease-modifying drugs in multiple sclerosis

2016 ◽  
Vol 74 (8) ◽  
pp. 617-620 ◽  
Author(s):  
Caroline Vieira Spessotto ◽  
Hanaie Cavalli ◽  
Audred Cristina Biondo Eboni ◽  
Rafael Berlezi Machado ◽  
Analara Munardi Mousquer ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Patient Satisfaction ◽  
New Drugs ◽  
Individual Interview ◽  
Efficacy And Safety ◽  
Disease Modifying Drugs ◽  
Patients Satisfaction ◽  
Disease Modifying ◽  
Points Of View ◽  
The Given

ABSTRACT Objective The treatment of multiple sclerosis (MS) with disease-modifying-drugs (DMDs) is evolving and new drugs are reaching the market. Efficacy and safety aspects of the drugs are crucial, but the patients’ satisfaction with the treatment must be taken into consideration. Methods Individual interview with patients with MS regarding their satisfaction and points of view on the treatment with DMDs. Results One hundred and twenty eight patients attending specialized MS Units in five different cities were interviewed. Over 80% of patients were very satisfied with the drugs in use regarding convenience and perceived benefits. The only aspect scoring lesser values was tolerability. Conclusion Parameters for improving treatment in MS must include efficacy, safety, and patient satisfaction with the given DMD.

scholarly journals Highlights from Faraday Discussion on Designing Nanoparticle Systems for Catalysis, London, UK, May 2018

2018 ◽  
Vol 54 (68) ◽  
pp. 9385-9393
Author(s):  
Rosa Arrigo ◽  
Andrew J. Logsdail ◽  
Laura Torrente-Murciano
Keyword(s):  
Computational Chemistry ◽  
State Of The Art ◽  
Catalyst Design ◽  
Characterization Techniques ◽  
Nanomaterial Synthesis ◽  
Current State ◽  
Challenges And Opportunities ◽  
Rational Catalyst Design

The 2018 Faraday Discussion on “Designing Nanoparticle Systems for Catalysis” brought together leading scientists to discuss the current state-of-the-art in the fields of computational chemistry, characterization techniques, and nanomaterial synthesis, and to debate the challenges and opportunities going forward for rational catalyst design.

scholarly journals Challenges in Application of Petri Nets in Manufacturing Systems

Electronics ◽  
2021 ◽  
Vol 10 (18) ◽  
pp. 2305
Author(s):  
Iwona Grobelna ◽  
Andrei Karatkevich
Keyword(s):  
Petri Nets ◽  
Control Systems ◽  
Manufacturing Systems ◽  
State Of The Art ◽  
Deadlock Prevention ◽  
Current State ◽  
Verification Methods ◽  
Challenges And Opportunities ◽  
University Level ◽  
Made In

Petri nets are a useful mathematical formalism for specification of manufacturing systems, supported by various analysis and verification methods. The progress made in automating control systems and the widespread use of Industry 4.0 pose a number of challenges to their application, starting from the education at university level and ending with modelling of real case studies. The paper aims to present and analyse the most relevant challenges and opportunities related to the use of Petri nets as a modelling technique of manufacturing systems. The review of the literature is primarily based on the years 2019–2020 to reflect the current state of the art. The newest approaches to deadlock prevention and recovering, but also other important analysis problems and difficulties in modelling real industrial processes are discussed. Trends for the future are also identified.

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