Spiking Neural Membrane Systems with Adaptive Synaptic Time Delay.

Spiking neural membrane systems (or spiking neural P systems, SNP systems) are a new type of computation model which have attracted the attention of plentiful scholars for parallelism, time encoding, interpretability and extensibility. The original SNP systems only consider the time delay caused by the execution of rules within neurons, but not caused by the transmission of spikes via synapses between neurons and its adaptive adjustment. In view of the importance of time delay for SNP systems, which are a time encoding computation model, this study proposes SNP systems with adaptive synaptic time delay (ADSNP systems) based on the dynamic regulation mechanism of synaptic transmission delay in neural systems. In ADSNP systems, besides neurons, astrocytes that can generate adenosine triphosphate (ATP) are introduced. After receiving spikes, astrocytes convert spikes into ATP and send ATP to the synapses controlled by them to change the synaptic time delays. The Turing universality of ADSNP systems in number generating and accepting modes is proved. In addition, a small universal ADSNP system using 93 neurons and astrocytes is given. The superiority of the ADSNP system is demonstrated by comparison with the six variants. Finally, an ADSNP system is constructed for credit card fraud detection, which verifies the feasibility of the ADSNP system for solving real-world problems. By considering the adaptive synaptic delay, ADSNP systems better restore the process of information transmission in biological neural networks, and enhance the adaptability of SNP systems, making the control of time more accurate.

Lung Microbiota and Pulmonary Inflammatory Cytokines Expression Vary in Children With Tracheomalacia and Adenoviral or Mycoplasma pneumoniae Pneumonia.

Community-acquired pneumonia (CAP) is a worldwide infectious disease caused by bacteria, viruses, or a combination of these infectious agents. Mycoplasma pneumoniae is an atypical pneumonia pathogen that causes high morbidity and mortality in children, and adenovirus can lead to severe pneumonia. However, the etiology of different types of pneumonia is still unclear. In this study, we selected a total of 52 inpatients with M. pneumoniae pneumonia (MPP) (n = 21), adenovirus pneumonia (AVP) (n = 16), or tracheomalacia (n = 15) to serve as a disease control. Bronchoalveolar lavage fluid (BALF) samples that had been obtained for clinical use were analyzed. We compared the differences in microbiota and the expression of 10 inflammatory cytokines in samples between MPP, AVP, and tracheomalacia. We found that the bacterial diversity in MPP was lower than that in AVP and tracheomalacia. Mycoplasma, Streptococcus, and Pseudomonas were predominant in samples of MPP, AVP, and tracheomalacia, respectively. The expression levels of IL-6, IL-8, and IL-10 were significantly higher in inpatients with AVP compared to children hospitalized with tracheomalacia or MPP. The lung microbiota in MPP was remarkably correlated with IL-2, IL-4, IL-5, IL-6, TNF-α, and IL-1α expressions, while this was not found in tracheomalacia and AVP. Microbiota analysis identified a high load of multi-drug resistant Acinetobacter baumannii in the lung microbiota of several inpatients, which might be associated with the long hospitalization length and intra-group differences at the individual level. This study will help to understand the microbial etiology of tracheomalacia, AVP, and MPP and to identify effective therapies for these diseases.