Acne is one of the most common skin disorders, and its occurrence is closely related to many factors, including sebum secretion, hormone levels, bacterial infection, and inflammatory reactions. Among these, changes in sebum secretion are believed to be one important factor of acne. Increased sebum secretion can induce acne occurrence, and increasing evidence indicates sebum component changes are also strongly related to acne occurrence. Recently, developments in lipidomics have provided effective lipid analysis methods. These can help elucidate the effects of different types of sebum on acne occurrence and provide a theoretical basis for research on the mechanisms of acne pathogenesis and treatment.

IntroductionOn July 1, 2011, the Chinese government launched a national Action Plan for antibiotic stewardship targeting antibiotic misuse in public hospitals. The aim of this study was to evaluate the impacts of the Action Plan in terms of frequency and intensity of antibiotic utilization and patients costs in public general hospitals.MethodsAdministrative pharmacy data from July 2010 to June 2014 were sampled from 65 public general hospitals and divided into three segments: (1) July 2010 to June 2011 as the preparation period; (2) July 2011 to June 2012 as the intervention period; and (3) July 2012 to June 2014 as the assessment period. The outcome measures included (1) antibiotic prescribing rates; (2) intensity of antibiotic consumption; (3) patients costs; and (4) duration of peri-operative antibiotic treatment in clean surgeries of thyroidectomy, breast, hernia, and orthopedic procedures. Longitudinal and cross-sectional analyses were conducted.ResultsLongitudinal analyses showed significant trend changes in the frequency and intensity of antibiotic consumption, the patients’ costs on antibiotics, and the duration of antibiotic treatment received by surgical patients undergoing the 4 clean procedures during the intervention period. Cross-sectional analyses showed that the antibiotic prescribing rates were reduced to 35.3% and 12.9% in inpatient and outpatient settings, that the intensity of antibiotic consumption was reduced to 35.9 DDD/100 bed-days, that patients’ costs on antibiotics were reduced significantly, and that the duration of peri-operative antibiotic treatment received by surgical patients undergoing the 4 types of clean procedures decreased to less than 24 hour during the assessment period.ConclusionThe Action Plan, as a combination of managerial and professional strategies, was effective in reducing the frequency and intensity of antibiotic consumption, patients’ costs on antibiotics, and the duration of peri-operative antibiotic treatment in the 4 clean surgeries.

Larch bark procyanidins (LBPCs) have not only antioxidant and antitumor properties, but also strong bacteriostatic effects. However, it is not clear about the antibacterial mechanisms of LBPC. In this work, the antibacterial effects and mechanisms of LBPC on Staphylococcus aureus were studied in the aspects of morphological structure, cell wall and membrane, essential proteins, and genetic material. The results showed that LBPC effectively inhibited bacterial growth at a minimum inhibitory concentration of 1.75 mg/ml. Bacterial morphology was significantly altered by LBPC treatment, with the cell walls and membranes being destroyed. Extracellular alkaline phosphatase content, bacterial fluid conductivity, and Na+/K+-ATPase and Ca2+-ATPase activities in the membrane system were all increased. In the energy metabolic systems, the activities of succinate dehydrogenase, malate dehydrogenase, and adenosine triphosphatase (ATPase) were all decreased, resulting in a slowdown of metabolism and bacterial growth inhibition. Changes of protein content and composition in the bacteria suggested that the protein expression system was affected. In addition, LBPC was found to bind to DNA grooves to form complexes. Thus, LBPC has a very strong inhibitory effect on S. aureus and can kill S. aureus by destroying the integrity and permeability of the cell wall and cell membrane, affecting protein synthesis, and binding to DNA.

Predicting geographic location using exclusively the visual content of images holds the promise of greatly benefiting users' access to media collections. In this paper, we present a visual-content-based approach that predicts where in the world a social image was taken. We employ a ranking method that assigns a query photo the geo-location of its most likely geo-visual neighbor in the social image collection. The novelty of the approach is that ranking makes use not only of the photos themselves, but also their geo-visual neighbors. In contrast to other approaches, we do not restrict the locations we predict to landmarks or specific cities. The approach is evaluated on a set of 3 million geo-tagged photos from Flickr, released by MediaEval 2012. Experiments show that the proposed system delivers a substantive performance improvement compared with previously proposed, related visual content-based approaches. The discussion illustrates how photo densities, geo-visual redundancy and uploader patterns characteristic of social image collections impacts the performance.

We propose an automatic method that addresses the challenge of predicting the geo-location of social images using only the visual content of those images. Our method is able to generate a geo-location prediction for an image globally. In this respect, it contrasts with other existing approaches, specifically with those that generate predictions restricted to specific cities, landmarks, or an otherwise pre-defined set of locations. The essence and the main novelty of our ranking-based method is that for a given query image a geo-location is recommended based on the evidence collected from images that are not only geographically close to this geo-location, but also have sufficient visual similarity to the query image within the considered image collection. Our method is evaluated experimentally on a public dataset of 8.8 million geo-tagged images from Flickr, released by the MediaEval 2013 evaluation benchmark. Experiments show that the proposed method delivers a substantial performance improvement compared to the existing related approaches, particularly for queries with high numbers of neighbors. In addition, a detailed analysis of the method's performance reveals the impact of different visual feature extraction and image matching strategies, as well as the densities and types of images found at different locations, on the prediction accuracy.

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