Human Pleural Fluid Elicits Pyruvate and Phenylalanine Metabolism in Acinetobacter baumannii to Enhance Cytotoxicity and Immune Evasion

The CCAAT box-harboring proteins represent a family of heterotrimeric transcription factors which is highly conserved in eukaryotes. In fungi, one of the particularly important homologs of this family is the Hap complex that separates the DNA-binding domain from the activation domain and imposes essential impacts on regulation of a wide range of cellular functions. So far, a comprehensive summary of this complex has been described in filamentous fungi but not in the yeast. In this review, we summarize a number of studies related to the structure and assembly mode of the Hap complex in a list of representative yeasts. Furthermore, we emphasize recent advances in understanding the regulatory functions of this complex, with a special focus on its role in regulating respiration, production of reactive oxygen species (ROS) and iron homeostasis.Fil: Nyah, Rodman. California State University; Estados UnidosFil: Martinez, Jasmine. California State University; Estados UnidosFil: Fung, Sammie. California State University; Estados UnidosFil: Nakanouchi, Jun. California State University; Estados UnidosFil: Myers, Amber L.. California State University; Estados UnidosFil: Harris, Caitlin M.. California State University; Estados UnidosFil: Dang, Emily. California State University; Estados UnidosFil: Fernandez, Jennifer. California State University; Estados UnidosFil: Liu, Christine. California State University; Estados UnidosFil: Mendoza, Anthony M.. California State University; Estados UnidosFil: Jimenez, Verónica. California State University; Estados UnidosFil: Nikolaidis, Nikolas. California State University; Estados UnidosFil: Brennan, Catherine A.. California State University; Estados UnidosFil: Bonomo, Robert A.. Louis Stokes Cleveland Department of Veterans Affairs Medical Cente; Estados Unidos. Center for Antimicrobial Resistance and Epidemiology; Estados Unidos. Case Western Reserve University School of Medicine; Estados UnidosFil: Sieira, Rodrigo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Ramirez, Maria Soledad. California State University; Estados Unido

The Digital Life of Walkable Streets

Walkability has many health, environmental, and economic benefits. That is why web and mobile services have been offering ways of computing walkability scores of individual street segments. Those scores are generally computed from survey data and manual counting (of even trees). However, that is costly, owing to the high time, effort, and financial costs. To partly automate the computation of those scores, we explore the possibility of using the social media data of Flickr and Foursquare to automatically identify safe and walkable streets. We find that unsafe streets tend to be photographed during the day, while walkable streets are tagged with walkability-related keywords. These results open up practical opportunities (for, e.g., room booking services, urban route recommenders, and real-estate sites) and have theoretical implications for researchers who might resort to the use social media data to tackle previously unanswered questions in the area of walkability.Comment: 10 pages, 7 figures, Proceedings of International World Wide Web Conference (WWW 2015

First Detector Guide to Invasive Insects

This is a guide to help first detectors identify invasive insects, including biology, identification, and monitoring

Pediatric Non-Rhabdomyosarcoma Soft Tissue Sarcomas:Standard of Care and Treatment Recommendations from the European Paediatric Soft Tissue Sarcoma Study Group (EpSSG)

This paper describes the standard of care for patients with non-rhabdomyosarcoma soft tissue sarcomas (NRSTS) and the therapeutic recommendations developed by the European paediatric Soft tissue sarcoma Study Group (EpSSG). NRSTS form a very mixed group of mesenchymal extraskeletal malignancies. Their rarity, heterogeneity, and aggressiveness make the management of children and adolescents with these tumors complex and challenging. The overall cure rate for patients with NRSTS is around 70%, but survival depends on several prognostic variables, such as histotype and tumor grade, extent of disease and stage, tumor size, and tumor site. While surgery remains the mainstay of treatment for most of these tumors, a multimodal therapeutic approach including radiotherapy and chemotherapy is required in many cases. The EpSSG NRSTS 2005 study was the first prospective protocol tailored specifically to NRSTS. Together with the ARST0332 study developed by the North-American Soft Tissue Sarcoma Committee of the Children’s Oncology Group (COG), the EpSSG NRSTS 2005 study currently represents the benchmark for these tumors, establishing risk-adapted standards of care. The EpSSG has developed common treatment recommendations for the large group of adult-type NRSTS (including synovial sarcoma), and specific treatment recommendations for other particular adult-type histologies (ie, alveolar soft-part sarcoma, clear cell sarcoma and dermatofibrosarcoma protuberans); other highly malignant tumors with a biology and clinical behavior differing from those of adult-type NRSTS (ie, rhabdoid tumors and desmoplastic small round cell tumor); and soft tissue tumors of intermediate malignancy (ie desmoid-type fibromatosis, inflammatory myofibroblastic tumors, and infantile fibrosarcoma). New effective drugs are needed for patients whose NRSTS carries the worst prognosis, ie, those with unresectable tumors, metastases at diagnosis, or relapsing disease. Progress in this area relies on our ability to develop international integrated prospective collaborations, both within existing pediatric oncology networks and, importantly, between the communities of specialists treating pediatric and adult sarcoma.</p

Incorporating statistical uncertainty in the use of physician cost profiles

<p>Abstract</p> <p>Background</p> <p>Physician cost profiles (also called efficiency or economic profiles) compare the costs of care provided by a physician to his or her peers. These profiles are increasingly being used as the basis for policy applications such as tiered physician networks. Tiers (low, average, high cost) are currently defined by health plans based on percentile cut-offs which do not account for statistical uncertainty. In this paper we compare the percentile cut-off method to another method, using statistical testing, for identifying high-cost or low-cost physicians.</p> <p>Methods</p> <p>We created a claims dataset of 2004-2005 data from four Massachusetts health plans. We employed commercial software to create episodes of care and assigned responsibility for each episode to the physician with the highest proportion of professional costs. A physicians' cost profile was the ratio of the sum of observed costs divided by the sum of expected costs across all assigned episodes. We discuss a new method of measuring standard errors of physician cost profiles which can be used in statistical testing. We then assigned each physician to one of three cost categories (low, average, or high cost) using two methods, percentile cut-offs and a t-test (p-value ≤ 0.05), and assessed the level of disagreement between the two methods.</p> <p>Results</p> <p>Across the 8689 physicians in our sample, 29.5% of physicians were assigned a different cost category when comparing the percentile cut-off method and the t-test. This level of disagreement varied across specialties (17.4% gastroenterology to 45.8% vascular surgery).</p> <p>Conclusions</p> <p>Health plans and other payers should incorporate statistical uncertainty when they use physician cost-profiles to categorize physicians into low or high-cost tiers.</p

Heart Rate Variability Dynamics for the Prognosis of Cardiovascular Risk

Statistical, spectral, multi-resolution and non-linear methods were applied to heart rate variability (HRV) series linked with classification schemes for the prognosis of cardiovascular risk. A total of 90 HRV records were analyzed: 45 from healthy subjects and 45 from cardiovascular risk patients. A total of 52 features from all the analysis methods were evaluated using standard two-sample Kolmogorov-Smirnov test (KS-test). The results of the statistical procedure provided input to multi-layer perceptron (MLP) neural networks, radial basis function (RBF) neural networks and support vector machines (SVM) for data classification. These schemes showed high performances with both training and test sets and many combinations of features (with a maximum accuracy of 96.67%). Additionally, there was a strong consideration for breathing frequency as a relevant feature in the HRV analysis

Histone acetylation-independent transcription stimulation by a histone chaperone

Histone chaperones are thought to be important for maintaining the physiological activity of histones; however, their exact roles are not fully understood. The physiological function of template activating factor (TAF)-I, one of the histone chaperones, also remains unclear; however, its biochemical properties have been well studied. By performing microarray analyses, we found that TAF-I stimulates the transcription of a sub-set of genes. The transcription of endogenous genes that was up-regulated by TAF-I was found to be additively stimulated by histone acetylation. On performing an experiment with a cell line containing a model gene integrated into the chromosome, TAF-I was found to stimulate the model gene transcription in a histone chaperone activity-dependent manner additively with histone acetylation. TAF-I bound to the core histones and remodeled the chromatin structure independent of the N-terminal histone tail and its acetylation level in vitro. These results suggest that TAF-I remodel the chromatin structure through its interaction with the core domain of the histones, including the histone fold, and this mechanism is independent of the histone acetylation status

Heart Rate Variability Dynamics for the Prognosis of Cardiovascular Risk

Statistical, spectral, multi-resolution and non-linear methods were applied to heart rate variability (HRV) series linked with classification schemes for the prognosis of cardiovascular risk. A total of 90 HRV records were analyzed: 45 from healthy subjects and 45 from cardiovascular risk patients. A total of 52 features from all the analysis methods were evaluated using standard two-sample Kolmogorov-Smirnov test (KS-test). The results of the statistical procedure provided input to multi-layer perceptron (MLP) neural networks, radial basis function (RBF) neural networks and support vector machines (SVM) for data classification. These schemes showed high performances with both training and test sets and many combinations of features (with a maximum accuracy of 96.67%). Additionally, there was a strong consideration for breathing frequency as a relevant feature in the HRV analysis