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Studies of acoustic communication often focus on the categories and units of vocalizations, but subtle variation also occurs in how these signals are uttered. In human speech, it is not only phonemes and words that carry information but also the timbre, intonation, and stress of how speech sounds are delivered (often referred to as "paralinguistic content"). In non-human animals, variation across utterances of vocal signals also carries behaviorally relevant information across taxa. However, the discriminability of these cues has been rarely tested in a psychophysical paradigm. Here, we focus on acoustic communication in the zebra finch (Taeniopygia guttata), a songbird species in which the male produces a single stereotyped motif repeatedly in song bouts. These motif renditions, like the song repetitions of many birds, sound very similar to the casual human listener. In this study, we show that zebra finches can easily discriminate between the renditions, even at the level of single song syllables, much as humans can discriminate renditions of speech sounds. These results support the notion that sensitivity to fine acoustic details may be a primary channel of information in zebra finch song, as well as a shared, foundational property of vocal communication systems across species.The present study used 16S rRNA gene amplicon sequencing to assess the impact on salivary microbiome of different grades of dental and periodontal disease and the combination of both (hereinafter referred to as oral disease), in terms of bacterial diversity, co-occurrence network patterns and predictive models. Our scale of overall oral health was used to produce a convenience sample of 81 patients from 270 who were initially recruited. Saliva samples were collected from each participant. Sequencing was performed in Illumina MiSeq with 2 × 300 bp reads, while the raw reads were processed according to the Mothur pipeline. The statistical analysis of the 16S rDNA sequencing data at the species level was conducted using the phyloseq, DESeq2, Microbiome, SpiecEasi, igraph, MixOmics packages. The simultaneous presence of dental and periodontal pathology has a potentiating effect on the richness and diversity of the salivary microbiota. The structure of the bacterial community in oral health differs from that present in dental, periodontal or oral disease, especially in high grades. Supragingival dental parameters influence the microbiota's abundance more than subgingival periodontal parameters, with the former making a greater contribution to the impact that oral health has on the salivary microbiome. The possible keystone OTUs are different in the oral health and disease, and even these vary between dental and periodontal disease half of them belongs to the core microbiome and are independent of the abundance parameters. find more The salivary microbiome, involving a considerable number of OTUs, shows an excellent discriminatory potential for distinguishing different grades of dental, periodontal or oral disease; considering the number of predictive OTUs, the best model is that which predicts the combined dental and periodontal status.There are several reports in the literature on the association between non-arteritic retinal artery occlusion (NA-RAO) and acute ischemic stroke. We investigated the burden of small vessel disease (SVD) and cerebral coincident infarction observed on cerebral magnetic resonance imaging (MRI) in patients with newly diagnosed NA-RAO. In this retrospective, observational, case-series study, consecutive patients with NA-RAO who underwent cerebral MRI within one month of diagnosis between September 2003 and October 2018 were included. The classification of NA-RAO was based on ophthalmologic and systemic examinations. We also investigated the co-incident infarction and burden of underlying SVD, which were categorized as white matter hyperintensity lesion (WMH), cerebral microbleeds (CMB), and silent lacunar infarction (SLI). Among the 272 patients enrolled in the study, 18% presented co-incident infarction and 73% had SVD, which included WMH (70%), CMB (14%), and SLI (30%). Co-incident infarction, WMH, and SLI significantly increased with age co-incident infarction was observed in 8% of young ( less then  50 years) patients and 30% of old (≥ 70 years) patients. The embolic etiology of RAO (large artery atherosclerosis, cardioembolism, and undetermined etiology) was significantly associated with the prevalence of SVD (82% 70% 64%, P = 0.002) and co-incident infarction (30% 19% 8%; P = 0.009). Therefore, high co-incidence of acute cerebral infarction and underlying SVD burden warrant careful neurologic examination and appropriate brain imaging, followed by management of NA-RAO. Urgent brain imaging is particularly pertinent in elderly patients with NA-RAO.The acquired resistance of the first generation epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) is a main factor leading to poor prognosis of non-small cell lung cancer (NSCLC), so we researched whether the high expression of hypoxia-inducible factor-1α (HIF-1α) in EGFR-TKIs sensitive NSCLC tissue tends to induce the acquired resistance. We detected the HIF-1α in normal lung tissue, EGFR-TKIs sensitive NSCLC tissue, the first generation EGFR-TKIs acquired resistant NSCLC tissue and acquired EGFR T790M mutation NSCLC tissue with the method of immunohistochemistry. Then, we compared the expression of HIF-1α in these tissues, and evaluate the effect of HIF-1α expression to the occurrence of acquired resistance. The expression of HIF-1α was much higher in the EGFR-TKIs sensitive NSCLC tissue than that in normal lung tissue. HIF-1α level became higher after the occurrence acquired resistance. There was negative correlation between HIF-1α level before receiving treatment and the time of acquired resistance occurring as well as the acquired EGFR T790M mutation occurring. As the treatment going on, EGFR-TKIs sensitivity rate of low HIF-1α level group was much higher than that of high level group. The high expression of HIF-1α related with the acquired resistance of the first generation EGFR-TKIs, and HIF-1α can be a biomarker to predict the early occurrence of acquired resistance.

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