In vitro fermentation of broiler cecal content : the role of oactobacilli and pH value on the composition of microbiota and end products fermentation.

Aim: To assess the probiotic effects of Lactobacillus agilis JCM 1048 and L. sali-varius ssp. salicinius JCM 1230 and the pH on the cecal microflora of chicken and metabolic end products. Methods and Results: An in vitro system, operated with batch bioreactor, was used for this assessment. Selected bacterial species were monitored at two pH values, over 24 h of batch culture incubation. The concentration of short chain fatty acids (SCFA) and lactate in the fermented material was also determined. The addition of L. agilis JCM 1048 and L. salivarius ssp. salicinius JCM 1230 into vessel 2 (Cc + P) increased the total anaerobes, lactobacilli and bifidobacteria after 24 h incubation. Moreover, lactobacilli supplementation decreased the total aerobes and streptococci, but it did not have any effects on coliforms. The supplementation of lactobacilli in vessel 2 (Cc + P) was found to significantly increase the production of lactate, propionate and butyrate. Further- more, pH did not alter the formation of butyrate, whereas the production of acetate and propionate was significantly decreased at pH = 5Æ 8.Conclusions:L. agilis JCM 1048 and L. salivarius ssp. salicinius JCM 1230, as probiotic bacteria, have the ability to re-establish proper microbial balance by the formation of lactate as well as propionate, and stimulate butyrate-producing bacteria to produce butyrate in the chicken cecum. Significance and Impact of the Study: This study was the first to report this under in vitro conditions, highlighting the probiotic roles of the two Lactobacillus strains in broiler cecal fermentation at different initial pH. These useful data can be helpful in improving the fermentation process in chicken cecum

Reducible Dictionaries for Single Image Super-Resolution based on Patch Matching and Mean Shifting

A single-image super-resolution (SR) method is proposed. The proposed method uses a generated dictionary from pairs of high resolution (HR) images and their corresponding low resolution (LR) representations. First, HR images and the corresponding LR ones are divided into patches of HR and LR, respectively, and then they are collected into separate dictionaries. Afterward, when performing SR, the distance between every patch of the input LR image and those of available LR patches in the LR dictionary is calculated. The minimum distance between the input LR patch and those in the LR dictionary is taken, and its counterpart from the HR dictionary is passed through an illumination enhancement process. By this technique, the noticeable change of illumination between neighbor patches in the super-resolved image is significantly reduced. The enhanced HR patch represents the HR patch of the super-resolved image. Finally, to remove the blocking effect caused by merging the patches, an average of the obtained HR image and the interpolated image obtained using bicubic interpolation is calculated. The quantitative and qualitative analyses show the superiority of the proposed technique over the conventional and state-of-art methods

The risk of nosocomial infection with multidrug-resistant corynebacterium urealyticum after prostate cancer surgery

Corynebacterium urealyticum is a Gram-positive, lipophilic, multidrug resistant, and urease positive microorganism with diph-theroid morphology. C. urealyticum causes several diseases such as urinary tract infection, chronic urological disease, urinary tract infections, and bacteremia in immunocompromised individuals. This study reports a rare case with nosocomial infection and hematuria caused by multidrug-resistant C. urealyticum after prostate cancer surgery. © 2019, Archives of Clinical Infectious Diseases

Efficacy of lactobacilli to normalize production of corticosterone induced by unpleasant handling of broilers

A study was conducted to investigate the effect of two Lactobacillus strains on hypothalamus pituitary adrenal (HPA) axis activity induced by supposedly unpleasant handling (UH) of broiler chickens. The three treatments were: (1) non-handled chicks fed basal diet (control); (2) unpleasantly handled-chicks fed basal diet (UH-BD) and (3) unpleasantly handled-chicks fed basal diet supplemented with the probiotic, lactobacilli (UH-BDL). Chicks were exposed to UH from days 1 to 21. Treatment UH-BDL received probiotics in their diet for the whole experimental period. Blood corticosterone (CS) concentrations were monitored at 14, 28, 35 and 42 days of age and selected caecal bacterial groups were enumerated in 14-day old birds. Unpleasant handling significantly increased blood CS concentrations at 14 and 28 days of age. Blood CS concentration decreased with age over the course of the experimental period. Lactobacillus supplementation did not reduce blood CS concentration in broilers in the UH-BDL treatment. Moreover, the UH treatment did not alter caecal bacterial numbers in the 14-day old broilers while the probiotic numerically increased total anaerobes and lactobacilli. Overall, it seems as if the efficacy of lactobacilli to modulate stress-related high HPA-axis activity depends on gastrointestinal tract microbial alteration. However, Lactobacillus salivarius subsp. salicinius JCM 1230 and L. agilis JCM 1048 were able to re-establish a proper microbial balance in the caecum of the chicken

A haystack full of needles: scalable detection of IoT devices in the wild

Consumer Internet of Things (IoT) devices are extremely popular, providing users with rich and diverse functionalities, from voice assistants to home appliances. These functionalities often come with significant privacy and security risks, with notable recent large scale coordinated global attacks disrupting large service providers. Thus, an important first step to address these risks is to know what IoT devices are where in a network. While some limited solutions exist, a key question is whether device discovery can be done by Internet service providers that only see sampled flow statistics. In particular, it is challenging for an ISP to efficiently and effectively track and trace activity from IoT devices deployed by its millions of subscribers --all with sampled network data. In this paper, we develop and evaluate a scalable methodology to accurately detect and monitor IoT devices at subscriber lines with limited, highly sampled data in-the-wild. Our findings indicate that millions of IoT devices are detectable and identifiable within hours, both at a major ISP as well as an IXP, using passive, sparsely sampled network flow headers. Our methodology is able to detect devices from more than 77% of the studied IoT manufacturers, including popular devices such as smart speakers. While our methodology is effective for providing network analytics, it also highlights significant privacy consequences

Multisource and multitemporal data fusion in remote sensing:A comprehensive review of the state of the art

The recent, sharp increase in the availability of data captured by different sensors, combined with their considerable heterogeneity, poses a serious challenge for the effective and efficient processing of remotely sensed data. Such an increase in remote sensing and ancillary data sets, however, opens up the possibility of utilizing multimodal data sets in a joint manner to further improve the performance of the processing approaches with respect to applications at hand. Multisource data fusion has, therefore, received enormous attention from researchers worldwide for a wide variety of applications. Moreover, thanks to the revisit capability of several

Cross-Attention in Coupled Unmixing Nets for Unsupervised Hyperspectral Super-Resolution

The recent advancement of deep learning techniques has made great progress on hyperspectral image super-resolution (HSI-SR). Yet the development of unsupervised deep networks remains challenging for this task. To this end, we propose a novel coupled unmixing network with a cross-attention mechanism, CUCaNet for short, to enhance the spatial resolution of HSI by means of higher-spatial-resolution multispectral image (MSI). Inspired by coupled spectral unmixing, a two-stream convolutional autoencoder framework is taken as backbone to jointly decompose MS and HS data into a spectrally meaningful basis and corresponding coefficients. CUCaNet is capable of adaptively learning spectral and spatial response functions from HS-MS correspondences by enforcing reasonable consistency assumptions on the networks. Moreover, a cross-attention module is devised to yield more effective spatial-spectral information transfer in networks. Extensive experiments are conducted on three widely-used HS-MS datasets in comparison with state-of-the-art HSI-SR models, demonstrating the superiority of the CUCaNet in the HSI-SR application. Furthermore, the codes and datasets will be available at: https://github.com/danfenghong/ECCV2020_CUCaNet

Default Pathway of var2csa Switching and Translational Repression in Plasmodium falciparum

Antigenic variation is a subtle process of fundamental importance to the survival of a microbial pathogen. In Plasmodium falciparum malaria, PfEMP1 is the major variable antigen and adhesin expressed at the surface of the infected erythrocyte, which is encoded for by members of a family of 60 var-genes. Peri-nuclear repositioning and epigenetic mechanisms control their mono-allelic expression. The switching of PfEMP1 depends in part on variable transition rates and short-lived immune responses to shared minor epitopes. Here we show var-genes to switch to a common gene that is highly transcribed, but sparsely translated into PfEMP1 and not expressed at the erythrocyte surface. Highly clonal and adhesive P. falciparum, which expressed distinct var-genes and the corresponding PfEMP1s at onset, were propagated without enrichment or panning. The parasites successively and spontaneously switched to transcribe a shared var-gene (var2csa) matched by the loss of PfEMP1 surface expression and host cell-binding. The var2csa gene repositioned in the peri-nuclear area upon activation, away from the telomeric clusters and heterochromatin to transcribe spliced, full-length RNA. Despite abundant transcripts, the level of intracellular PfEMP1 was low suggesting post-transcriptional mechanisms to partake in protein expression. In vivo, off-switching and translational repression may constitute one pathway, among others, coordinating PfEMP1 expression