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1.
J Nanobiotechnology ; 21(1): 58, 2023 Feb 21.
Artigo em Inglês | MEDLINE | ID: mdl-36810201

RESUMO

Over the past decade, a proliferation of research has used nanoparticles to deliver gaseous signaling molecules for medical purposes. The discovery and revelation of the role of gaseous signaling molecules have been accompanied by nanoparticle therapies for their local delivery. While most of them have been applied in oncology, recent advances have demonstrated their considerable potential in diagnosing and treating orthopedic diseases. Three of the currently recognized gaseous signaling molecules, nitric oxide (NO), carbon monoxide (CO), and hydrogen sulfide (H2S), are highlighted in this review along with their distinctive biological functions and roles in orthopedic diseases. Moreover, this review summarizes the progress in therapeutic development over the past ten years with a deeper discussion of unresolved issues and potential clinical applications.


Assuntos
Gases , Sulfeto de Hidrogênio , Transdução de Sinais , Sulfeto de Hidrogênio/uso terapêutico , Monóxido de Carbono , Óxido Nítrico
2.
Front Cell Infect Microbiol ; 12: 1003033, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-36211965

RESUMO

Biofilms are colonies of bacteria embedded inside a complicated self-generating intercellular. The formation and scatter of a biofilm is an extremely complex and progressive process in constant cycles. Once formed, it can protect the inside bacteria to exist and reproduce under hostile conditions by establishing tolerance and resistance to antibiotics as well as immunological responses. In this article, we reviewed a series of innovative studies focused on inhibiting the development of biofilm and summarized a range of corresponding therapeutic methods for biological evolving stages of biofilm. Traditionally, there are four stages in the biofilm formation, while we systematize the therapeutic strategies into three main periods precisely:(i) period of preventing biofilm formation: interfering the colony effect, mass transport, chemical bonds and signaling pathway of plankton in the initial adhesion stage; (ii) period of curbing biofilm formation:targeting several pivotal molecules, for instance, polysaccharides, proteins, and extracellular DNA (eDNA) via polysaccharide hydrolases, proteases, and DNases respectively in the second stage before developing into irreversible biofilm; (iii) period of eliminating biofilm formation: applying novel multifunctional composite drugs or nanoparticle materials cooperated with ultrasonic (US), photodynamic, photothermal and even immune therapy, such as adaptive immune activated by stimulated dendritic cells (DCs), neutrophils and even immunological memory aroused by plasmocytes. The multitargeted or combinational therapies aim to prevent it from developing to the stage of maturation and dispersion and eliminate biofilms and planktonic bacteria simultaneously.


Assuntos
Antibacterianos , Biofilmes , Animais , Antibacterianos/metabolismo , Antibacterianos/farmacologia , Bactérias/metabolismo , Desoxirribonuclease I , Estágios do Ciclo de Vida , Peptídeo Hidrolases
3.
Entropy (Basel) ; 22(3)2020 Mar 12.
Artigo em Inglês | MEDLINE | ID: mdl-33286098

RESUMO

With the emergence of network security issues, various security devices that generate a large number of logs and alerts are widely used. This paper proposes an alert aggregation scheme that is based on conditional rough entropy and knowledge granularity to solve the problem of repetitive and redundant alert information in network security devices. Firstly, we use conditional rough entropy and knowledge granularity to determine the attribute weights. This method can determine the different important attributes and their weights for different types of attacks. We can calculate the similarity value of two alerts by weighting based on the results of attribute weighting. Subsequently, the sliding time window method is used to aggregate the alerts whose similarity value is larger than a threshold, which is set to reduce the redundant alerts. Finally, the proposed scheme is applied to the CIC-IDS 2018 dataset and the DARPA 98 dataset. The experimental results show that this method can effectively reduce the redundant alerts and improve the efficiency of data processing, thus providing accurate and concise data for the next stage of alert fusion and analysis.

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