Alterations of CD8+CD28- T cells in systemic lupus erythematosus and rheumatoid arthritis

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Antrodia cinnamomea reduces obesity and modulates the gut microbiota in high-fat diet-fed mice.

BackgroundObesity is associated with gut microbiota dysbiosis, disrupted intestinal barrier and chronic inflammation. Given the high and increasing prevalence of obesity worldwide, anti-obesity treatments that are safe, effective and widely available would be beneficial. We examined whether the medicinal mushroom Antrodia cinnamomea may reduce obesity in mice fed with a high-fat diet (HFD).MethodsMale C57BL/6J mice were fed a HFD for 8 weeks to induce obesity and chronic inflammation. The mice were treated with a water extract of A. cinnamomea (WEAC), and body weight, fat accumulation, inflammation markers, insulin sensitivity and the gut microbiota were monitored.ResultsAfter 8 weeks, the mean body weight of HFD-fed mice was 39.8±1.2 g compared with 35.8±1.3 g for the HFD+1% WEAC group, corresponding to a reduction of 4 g or 10% of body weight (P<0.0001). WEAC supplementation reduced fat accumulation and serum triglycerides in a statistically significant manner in HFD-fed mice. WEAC also reversed the effects of HFD on inflammation markers (interleukin-1β, interleukin-6, tumor necrosis factor-α), insulin resistance and adipokine production (leptin and adiponectin). Notably, WEAC increased the expression of intestinal tight junctions (zonula occludens-1 and occludin) and antimicrobial proteins (Reg3g and lysozyme C) in the small intestine, leading to reduced blood endotoxemia. Finally, WEAC modulated the composition of the gut microbiota, reducing the Firmicutes/Bacteroidetes ratio and increasing the level of Akkermansia muciniphila and other bacterial species associated with anti-inflammatory properties.ConclusionsSupplementation with A. cinnamomea produces anti-obesogenic, anti-inflammatory and antidiabetic effects in HFD-fed mice by maintaining intestinal integrity and modulating the gut microbiota

The pharmaceutical use of permethrin: Sources and behavior during municipal sewage treatment

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2010 Springer Science+Business Media, LLC.Permethrin entered use in the 1970s as an insecticide in a wide range of applications, including agriculture, horticultural, and forestry, and has since been restricted. In the 21st century, the presence of permethrin in the aquatic environment has been attributed to its use as a human and veterinary pharmaceutical, in particular as a pedeculicide, in addition to other uses, such as a moth-proofing agent. However, as a consequence of its toxicity to fish, sources of permethrin and its fate and behavior during wastewater treatment are topics of concern. This study has established that high overall removal of permethrin (approximately 90%) was achieved during wastewater treatment and that this was strongly dependent on the extent of biological degradation in secondary treatment, with more limited subsequent removal in tertiary treatment processes. Sources of permethrin in the catchment matched well with measured values in crude sewage and indicated that domestic use accounted for more than half of the load to the treatment works. However, removal may not be consistent enough to achieve the environmental quality standards now being derived in many countries even where tertiary treatment processes are applied.United Utilities PL

Developmental white matter microstructure in autism phenotype and corresponding endophenotype during adolescence.

During adolescence, white matter microstructure undergoes an important stage of development. It is hypothesized that the alterations of brain connectivity that have a key role in autism spectrum conditions (ASCs) may interact with the development of white matter microstructure. This interaction may be present beyond the phenotype of autism in siblings of individuals with ASC, who are 10 to 20 times more likely to develop certain forms of ASC. We use diffusion tensor imaging to examine how white matter microstructure measurements correlate with age in typically developing individuals, and how this correlation differs in n=43 adolescents with ASC and their n=38 siblings. Correlations observed in n=40 typically developing individuals match developmental changes noted in previous longitudinal studies. In comparison, individuals with ASC display weaker negative correlation between age and mean diffusivity in a broad area centred in the right superior longitudinal fasciculus. These differences may be caused either by increased heterogeneity in ASC or by temporal alterations in the group's developmental pattern. Siblings of individuals with ASC also show diminished negative correlation between age and one component of mean diffusivity-second diffusion eigenvalue-in the right superior longitudinal fasciculus. As the observed differences match for location and correlation directionality in our comparison of typically developing individuals to those with ASC and their siblings, we propose that these alterations constitute a part of the endophenotype of autism.This research was funded by an MRC Clinician Scientist Fellowship to MDS from the UK Medical Research Council (G0701919). LRC was supported by the Gates Cambridge Scholarship Trust. SB-C was supported by the Wellcome Trust, the MRC and the Autism Research Trust, during the period of this work.This is the final published version. It first appeared at http://www.nature.com/tp/journal/v5/n3/full/tp201523a.html

Learning Joint Spatial-Temporal Transformations for Video Inpainting

High-quality video inpainting that completes missing regions in video frames is a promising yet challenging task. State-of-the-art approaches adopt attention models to complete a frame by searching missing contents from reference frames, and further complete whole videos frame by frame. However, these approaches can suffer from inconsistent attention results along spatial and temporal dimensions, which often leads to blurriness and temporal artifacts in videos. In this paper, we propose to learn a joint Spatial-Temporal Transformer Network (STTN) for video inpainting. Specifically, we simultaneously fill missing regions in all input frames by self-attention, and propose to optimize STTN by a spatial-temporal adversarial loss. To show the superiority of the proposed model, we conduct both quantitative and qualitative evaluations by using standard stationary masks and more realistic moving object masks. Demo videos are available at https://github.com/researchmm/STTN.Comment: Accepted by ECCV202

The effect of providing a USB syllabus on resident reading of landmark articles

Background: The acquisition of new knowledge is a primary goal of residency training. Retrieving and retaining influential primary and secondary medical literature can be challenging for house officers. We set out to investigate the effect of a Universal Serial Bus (USB) drive loaded with landmark scientific articles on housestaff education in a pilot study. Methods: We created a USB syllabus that contains 187 primary scientific research articles. The electronic syllabus had links to the full-text articles and was organized using an html webpage with a table of contents according to medical subspecialties. We performed a prospective cohort study of 53 house officers in the internal medicine residency program who received the USB syllabus. We evaluated the impact of the USB syllabus on resident education with surveys at the beginning and conclusion of the nine-month study period. Results: All 50 respondents (100%) reported to have used the USB syllabus. The self-reported number of original articles read each month was higher at the end of the nine-month study period compared to baseline. Housestaff rated original articles as being a more valuable educational resource after the intervention. Conclusions: An electronic syllabus with landmark scientific articles placed on a USB drive was widely utilized by housestaff, increased the self-reported reading of original scientific articles and seemed to have positively influenced residents’ attitude toward original medical literature

Otalgia and eschar in the external auditory canal in scrub typhus complicated by acute respiratory distress syndrome and multiple organ failure

<p>Abstract</p> <p>Background</p> <p>Scrub typhus, a mite-transmitted zoonosis caused by <it>Orientia tsutsugamushi</it>, is an endemic disease in Taiwan and may be potentially fatal if diagnosis is delayed.</p> <p>Case presentations</p> <p>We encountered a 23-year-old previously healthy Taiwanese male soldier presenting with the right ear pain after training in the jungle and an eleven-day history of intermittent high fever up to 39°C. Amoxicillin/clavulanate was prescribed for otitis media at a local clinic. Skin rash over whole body and abdominal cramping pain with watery diarrhea appeared on the sixth day of fever. He was referred due to progressive dyspnea and cough for 4 days prior to admission in our institution. On physical examination, there were cardiopulmonary distress, icteric sclera, an eschar in the right external auditory canal and bilateral basal rales. Laboratory evaluation revealed thrombocytopenia, elevation of liver function and acute renal failure. Chest x-ray revealed bilateral diffuse infiltration. Doxycycline was prescribed for scrub typhus with acute respiratory distress syndrome and multiple organ failure. Fever subsided dramatically the next day and he was discharged on day 7 with oral tetracycline for 7 days.</p> <p>Conclusion</p> <p>Scrub typhus should be considered in acutely febrile patients with multiple organ involvement, particularly if there is an eschar or a history of environmental exposure in endemic areas. Rapid and accurate diagnosis, timely administration of antibiotics and intensive supportive care are necessary to decrease mortality of serious complications of scrub typhus.</p

The identification of informative genes from multiple datasets with increasing complexity

Background In microarray data analysis, factors such as data quality, biological variation, and the increasingly multi-layered nature of more complex biological systems complicates the modelling of regulatory networks that can represent and capture the interactions among genes. We believe that the use of multiple datasets derived from related biological systems leads to more robust models. Therefore, we developed a novel framework for modelling regulatory networks that involves training and evaluation on independent datasets. Our approach includes the following steps: (1) ordering the datasets based on their level of noise and informativeness; (2) selection of a Bayesian classifier with an appropriate level of complexity by evaluation of predictive performance on independent data sets; (3) comparing the different gene selections and the influence of increasing the model complexity; (4) functional analysis of the informative genes. Results In this paper, we identify the most appropriate model complexity using cross-validation and independent test set validation for predicting gene expression in three published datasets related to myogenesis and muscle differentiation. Furthermore, we demonstrate that models trained on simpler datasets can be used to identify interactions among genes and select the most informative. We also show that these models can explain the myogenesis-related genes (genes of interest) significantly better than others (P < 0.004) since the improvement in their rankings is much more pronounced. Finally, after further evaluating our results on synthetic datasets, we show that our approach outperforms a concordance method by Lai et al. in identifying informative genes from multiple datasets with increasing complexity whilst additionally modelling the interaction between genes. Conclusions We show that Bayesian networks derived from simpler controlled systems have better performance than those trained on datasets from more complex biological systems. Further, we present that highly predictive and consistent genes, from the pool of differentially expressed genes, across independent datasets are more likely to be fundamentally involved in the biological process under study. We conclude that networks trained on simpler controlled systems, such as in vitro experiments, can be used to model and capture interactions among genes in more complex datasets, such as in vivo experiments, where these interactions would otherwise be concealed by a multitude of other ongoing events