Probiotic could be a promising alternative to antibiotics for the prevention of enteric infections; however, further information on the dose effects is required. In this study, weanling piglets were orally administered low- or high-dose Lactobacillus rhamnosus ACTT 7469 (1010 CFU/d or 1012 CFU/d) for 1 week before F4 (K88)-positive Escherichia coli challenge. The compositions of faecal and gastrointestinal microbiota were recorded; gene expression in the intestines was assessed by real-time PCR; serum tumour necrosis factor-α (TNF-α) concentrations and intestinal Toll-like receptor 4 (TLR4) were detected by ELISA and immunohistochemistry, respectively. Unexpectedly, high-dose administration increased the incidence of diarrhoea before F4+ETEC challenge, despite the fact that both doses ameliorated F4+ETEC-induced diarrhoea with increased Lactobacillus and Bifidobacterium counts accompanied by reduced coliform shedding in faeces. Interestingly, L. rhamnosus administration reduced Lactobacillus and Bifidobacterium counts in the colonic contents, and the high-dose piglets also had lower Lactobacillius and Bacteroides counts in the ileal contents. An increase in the concentration of serum TNF-α induced by F4+ETEC was observed, but the increase was delayed by L. rhamnosus. In piglets exposed to F4+ETEC, jejunal TLR4 expression increased at the mRNA and protein levels, while jejunal interleukin (IL)-8 and ileal porcine β-defensins 2 (pBD2) mRNA expression increased; however, these increases were attenuated by administration of L. rhamnosus. Notably, expression of jejunal TLR2, ileal TLR9, Nod-like receptor NOD1 and TNF-α mRNA was upregulated in the low-dose piglets after F4+ETEC challenge, but not in the high-dose piglets. These findings indicate that pretreatment with a low dose of L. rhamnosus might be more effective than a high dose at ameliorating diarrhoea. There is a risk that high-dose L. rhamnosus pretreatment may negate the preventative effects, thus decreasing the prophylactic benefits against potential enteric pathogens. Our data suggest a safe threshold for preventative use of probiotics in clinical practice.

We report the results of our systematic survey for Galactic 6.7 GHz Class II CH 3 OH maser emission toward a sample of young stellar objects. The survey was conducted with the Shanghai Tianma Radio Telescope (TMRT). The sample consists of 3348 sources selected from the all-sky Wide-Field Infrared Survey Explorer (WISE) point source catalog. We have discussed the selection criteria in detail and the detection results of those at high Galactic latitudes (i.e. |b| > 2 • ) in a previous paper (paper I). Here, we present the results from the survey of those at low Galactic latitudes, i.e. |b| < 2 • . Of 1875 selected WISE point sources, 291 positions that were actually associated with 224 sources were detected with CH 3 OH maser emission. Among them, 32 are newly detected. Majority of the newly detected sources are associated with bright WISE sources. The majority of the detected sources (209/224 = 93.3%) are quite close to the Galactic Plane (|b| < 1 • ) and lie on the inner spiral arms with positive LSR velocities. Detection rate and the color-color distribution of our detection are all matched with our anticipation. Combining with detections from previous surveys, we compile a catalogue of 1085 sources with 6.7 GHz CH 3 OH maser emission in our Galaxy.

The mechanism underlying the dose effect of probiotics on ameliorating diarrhea has not been fully elucidated. Here, low (1 ؋ 10 9 CFU/ml) or high (

We present a comprehensive analysis of the submissions to the first edition of the Endoscopy Artefact Detection challenge (EAD). Using crowd-sourcing, this initiative is a step towards understanding the limitations of existing state-of-the-art computer vision methods applied to endoscopy and promoting the development of new approaches suitable for clinical translation. Endoscopy is a routine imaging technique for the detection, diagnosis and treatment of diseases in hollow-organs; the esophagus, stomach, colon, uterus and the bladder. However the nature of these organs prevent imaged tissues to be free of imaging artefacts such as bubbles, pixel saturation, organ specularity and debris, all of which pose substantial challenges for any quantitative analysis. Consequently, the potential for improved clinical outcomes through quantitative assessment of abnormal mucosal surface observed in endoscopy videos is presently not realized accurately. The EAD challenge promotes awareness of and addresses this key bottleneck problem by investigating methods that can accurately classify, localize and segment artefacts in endoscopy frames as critical prerequisite tasks. Using a diverse curated multi-institutional, multi-modality, multi-organ dataset of video frames, the accuracy and performance of 23 algorithms were objectively ranked for artefact detection and segmentation. The ability of methods to generalize to unseen datasets was also evaluated. The best performing methods (top 15%) propose deep learning strategies to reconcile variabilities in artefact appearance with respect to size, modality, occurrence and organ type. However, no single method outperformed across all tasks. Detailed analyses reveal the