Integration in the C-band between quantum key distribution and the classical channel of 25 dBm launch power over multicore fiber media.

The quantum-classical coexistence can be implemented based on wavelength division multiplexing (WDM), but due to Raman noise, the wavelength spacing between quantum and classical signals and launch power from classical channels are restricted. Space division multiplexing (SDM) can now be availably achieved by multicore fiber (MCF) to reduce Raman noise, thereby loosening the restriction for coexistence in the same band and obtaining a high communication capacity. In this paper, we realize the quantum-classical coexistence over a 7-core MCF. Based on the SDM, the highest launch power of 25 dBm is achieved which has been extended nearly 19 times in previous work. Moreover, both the quantum and classical channels are allocated in the C-band and the minimum wavelength spacing between them is only 1.6 nm. The coexistence system eliminates the need for adding a narrowband filter.

Dysbiosis of lower respiratory tract microbiome are associated with inflammation and microbial function variety.

BACKGROUND: Lower respiratory tract (LRT) microbiome has been reported to associate with pulmonary diseases. Unregulated inflammation is an underlying cause of variable lung diseases. The lung microbiome may play an important role in the smoking-induced inflammatory lung diseases. What's more, the function of microbiome may be more important for understanding how microbes interact with host. Our study aims to explore the effects of smoking on the lower respiratory tract microbiome, the association between variation of lower respiratory tract microbiome and inflammation and whether smoking exposure changes the function of lower respiratory tract microbime. METHODS: Forty male mice were randomly divided into smoking group and non-smoking group, and the smoking group was exposed to cigarette smoke for 2 h per day for 90 days. After experiment, the blood samples were collected to measure the concentration of interleukin-6 (IL-6) and C reactive protein (CRP) by ELISA. Lung tissue samples were used to detect the community and diversity of lower respiratory tract microbiome through 16S rRNA gene quantification and sequencing technology. ANOSIM and STAMP were performed to analyze the differences of the microbial community structure between smoking group and non-smoking group. SPSS 24.0 software was used to analyze the correlations between microbiome and inflammation mediators through scatter plots and Spearman correlation coefficient. Microbial metabolic function was predicted by PICRUSt based on the 16 s rRNA gene quantification and sequencing results. PATRIC database was searched for the potential pathogenic bacteria in lower respiratory tract. RESULTS: Our results suggested that smoking had markedly effects on the microbiota structure of lower respiratory tract based on Bray-Curtis distance (R2 = 0.084, p = 0.005) and on unweighted uniFrac distance (R2 = 0.131, p = 0.002). Smoking mainly affected the abundance of microbiome which belong to Proteobacteria phyla and Firmicutes phyla. Moreover, our results also found that smoking increased the abundance of Acinetobacter, Bacillus and Staphylococcus, which were defined as pathogenic bacteria. Inflammatory mediators were observed to associate with certain microbiome at every level. Most of microbiome which were associated with inflammation belonged to Proteobacteria phyla or Firmicutes phyla. Moreover, we found that the decreased microbiome in smoking group, including Oceanospirillales, Desulfuromonadales, Nesterenkonia, and Lactobacillaceae, all were negatively correlated with IL-6 or CRP. Based on the level of inflammation, the abundance of microbiome differs. At genus level, Lactobacillus, Pelagibacterium, Geobacter and Zoogloea were significantly higher in smoking group with lower IL-6 concentration. The abundance of microbiome was not observed any statistical difference in subgroups with different weight. Three dominant genus, defined as pathogen, were found higher in the smoking group. The microbial functional prediction analysis revealed that ABC-type transport systems, transcription factors, amino acide transport and metabolism, arginine and proline metabolism et al. were distinctively decreased in smoking group, while the proportions of replication, recombination and repair, ribosome, DNA repair and recombination proteins were increased in smoking group (q < 0.05). CONCLUSIONS: Members of Proteobacteria phyla and Firmicutes phyla played an important role in the microbial community composition and keeping a relatively balanced homeostasis. Microbiome dysbiosis might break the balance of immune system to drive lung inflammation. There might exist potential probiotics in lower respiratory tract, such as Lactobacillaceae. The altered function of Lower respiratory tract microbiome under smoking exposure may affect the physiological homeostasis of host.

Association between duration of dialysis and Helicobacter pylori infection in dialysis patients: a meta-analysis.

PURPOSE: The association between Helicobacter pylori (HP) infection and duration of dialysis in dialysis patients is conflicting, this meta-analysis was conducted to elucidate the association between duration of dialysis and HP infection status in dialysis patients, and subgroup study was conducted to explore its influencing factors. Furthermore, our study aims to provide advice on the treatment of dialysis patients. METHODS: Articles published up to 30 September 2018 were searched from PubMed, Embase, Sinomed, Medline, China Knowledge Resource Integrated Database (CNKI) and Wang fang database. Two researchers independently identified whether studies met the eligibility criteria. The adjusted relative risk (RR) or the weighted mean difference (WMD) and their 95% CI were estimated. I2 was performed to evaluate the statistical heterogeneity. Publication bias was evaluated using Egger's test and a funnel plot. RESULTS: Fourteen studies were included involving 2087 dialysis patients, 815 of them were HP positive, 1272 of them were HP negative. Quantitative data and qualitative data were analyzed, respectively. For quantitative data, statistical differences were observed in the association between HP infection and duration of dialysis (P = 0.008), also in the hemodialysis subgroup (P = 0.006). After stratifying by detection methods, differences still existed in groups with different detection methods (P = 0.001, P = 0.033). For qualitative data, there was no statistical difference in the association between HP infection rate and duration of dialysis (P = 0.295). Furthermore, we found that the age was higher in HP positive patients than in HP negative patients (P < 0.001). CONCLUSION: Our meta-analysis found that HP infection rate was negatively correlated with accumulative dialysis time, and methods of HP detection did not influence the association between HP infection and accumulative dialysis time. We also found that age was the risk factor of HP infection in dialysis patients. Further studies need to be performed to elucidate the mechanism of the correlation between HP infection and duration of dialysis, to explore which timing period of dialysis is most susceptible to HP infection, then, improve the prognosis of patients with renal diseases.

Effects of smoking on the lower respiratory tract microbiome in mice.

BACKGROUND: Recent studies break with traditional opinion that the lower respiratory tract is sterile, and increasingly focus on the lung microbiome and disease. Smoking, as an important etiology of inflammatory lung disease, was considered as a factor influencing lung microbiome variations in our study, and we aimed to study the effect of smoking on inflammation and microbial diversity and community. METHODS: Forty male mice were selected and randomly divided into a smoking and a non-smoking group. Mice in the smoking group were exposed to smoke smog for 2 h/day for 90 days. Blood and lung tissues were obtained after the experiment, and ELISA was used to measure interleukin-6 and C reactive protein concentrations. 16S rRNA gene quantification and sequencing technology were used to compare microbial diversity and community between the two groups. SAS 9.1 and R software were used to analyze the data. RESULTS: Thirty-six mice survived, and the weight of the smoking group increased more slowly than that of the non-smoking group. Denser inflammation and congestion were observed in the lungs of the smoking mice compared with the non-smoking group Higher microbial diversity was observed in the smoking group, and Enterobacter, Acidimicrobiales_norank, and Caulobacteraceae_Unclassified genus were significantly more abundant in the non-smoking group (P < 0.001). CONCLUSIONS: Smoking altered microbial diversities and communities in the lower respiratory tract of mice. Microbial variation should be considered in future studies focusing on smoking-induced inflammatory disease.

Cellular transplantation-based evolving treatment options in spinal cord injury.

Spinal cord injury (SCI) often represents a condition of permanent neurologic deficit. It has been possible to understand and delineate the mechanisms contributing to loss of function following primary injury. The clinicians might hope to improve the outcome in SCI injury by designing treatment strategies that could target these secondary mechanisms of response to injury. However, the approaches like molecular targeting of the neurons or surgical interventions have yielded very limited success till date. In recent times, a great thrust is put on to the cellular transplantation mode of treatment strategies to combat SCI problems so as to gain maximum functional recovery. In this review, we discuss about the various cellular transplantation strategies that could be employed in the treatment of SCI. The success of such cellular approaches involving Schwann cells, olfactory ensheathing cells, peripheral nerve, embryonic CNS tissue and activated macrophage has been supported by a number of reports and has been detailed here. Many of these cell transplantation strategies have reached the clinical trial stages. Also, the evolving field of stem cell therapy has made it possible to contemplate the role of both embryonic stem cells and induced pluripotent stem cells to stimulate the differentiation of neurons when transplanted in SCI models. Moreover, the roles of tissue engineering techniques and synthetic biomaterials have also been explained with their beneficial and deleterious effects. Many of these cell-based therapeutic approaches have been able to cause only a little change in recovery and a combinatorial approach involving more than one strategy are now being tried out to successfully treat SCI and improve functional recovery.