237 research outputs found
Type Iax Supernovae
Type Iax supernovae (SN Iax), also called SN 2002cx-like supernovae, are the
largest class of peculiar white dwarf (thermonuclear) supernovae, with over
fifty members known. SN Iax have lower ejecta velocity and lower luminosities,
and these parameters span a much wider range, than normal type Ia supernovae
(SN Ia). SN Iax are spectroscopically similar to some SN Ia near maximum light,
but are unique among all supernovae in their late-time spectra, which never
become fully nebular. SN Iax overwhelmingly occur in late-type host galaxies,
implying a relatively young population. The SN Iax 2012Z is the only white
dwarf supernova for which a pre-explosion progenitor system has been detected.
A variety of models have been proposed, but one leading scenario has emerged: a
type Iax supernova may be a pure-deflagration explosion of a carbon-oxygen (or
hybrid carbon-oxygen-neon) white dwarf, triggered by helium accretion to the
Chandrasekhar mass, that does not necessarily fully disrupt the star.Comment: Author version of a chapter in the 'Handbook of Supernovae', edited
by A. Alsabti and P. Murdin, Springer. 31 pages, 6 figure
Health Diplomacy the Adaptation of Global Health Interventions to Local Needs in sub-Saharan Africa and Thailand: Evaluating Findings from Project Accept (HPTN 043).
Study-based global health interventions, especially those that are conducted on an international or multi-site basis, frequently require site-specific adaptations in order to (1) respond to socio-cultural differences in risk determinants, (2) to make interventions more relevant to target population needs, and (3) in recognition of 'global health diplomacy' issues. We report on the adaptations development, approval and implementation process from the Project Accept voluntary counseling and testing, community mobilization and post-test support services intervention. We reviewed all relevant documentation collected during the study intervention period (e.g. monthly progress reports; bi-annual steering committee presentations) and conducted a series of semi-structured interviews with project directors and between 12 and 23 field staff at each study site in South Africa, Zimbabwe, Thailand and Tanzania during 2009. Respondents were asked to describe (1) the adaptations development and approval process and (2) the most successful site-specific adaptations from the perspective of facilitating intervention implementation. Across sites, proposed adaptations were identified by field staff and submitted to project directors for review on a formally planned basis. The cross-site intervention sub-committee then ensured fidelity to the study protocol before approval. Successfully-implemented adaptations included: intervention delivery adaptations (e.g. development of tailored counseling messages for immigrant labour groups in South Africa) political, environmental and infrastructural adaptations (e.g. use of local community centers as VCT venues in Zimbabwe); religious adaptations (e.g. dividing clients by gender in Muslim areas of Tanzania); economic adaptations (e.g. co-provision of income generating skills classes in Zimbabwe); epidemiological adaptations (e.g. provision of 'youth-friendly' services in South Africa, Zimbabwe and Tanzania), and social adaptations (e.g. modification of terminology to local dialects in Thailand: and adjustment of service delivery schedules to suit seasonal and daily work schedules across sites). Adaptation selection, development and approval during multi-site global health research studies should be a planned process that maintains fidelity to the study protocol. The successful implementation of appropriate site-specific adaptations may have important implications for intervention implementation, from both a service uptake and a global health diplomacy perspective
Multi-messenger observations of a binary neutron star merger
On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta
Exploring cancer register data to find risk factors for recurrence of breast cancer – application of Canonical Correlation Analysis
BACKGROUND: A common approach in exploring register data is to find relationships between outcomes and predictors by using multiple regression analysis (MRA). If there is more than one outcome variable, the analysis must then be repeated, and the results combined in some arbitrary fashion. In contrast, Canonical Correlation Analysis (CCA) has the ability to analyze multiple outcomes at the same time. One essential outcome after breast cancer treatment is recurrence of the disease. It is important to understand the relationship between different predictors and recurrence, including the time interval until recurrence. This study describes the application of CCA to find important predictors for two different outcomes for breast cancer patients, loco-regional recurrence and occurrence of distant metastasis and to decrease the number of variables in the sets of predictors and outcomes without decreasing the predictive strength of the model. METHODS: Data for 637 malignant breast cancer patients admitted in the south-east region of Sweden were analyzed. By using CCA and looking at the structure coefficients (loadings), relationships between tumor specifications and the two outcomes during different time intervals were analyzed and a correlation model was built. RESULTS: The analysis successfully detected known predictors for breast cancer recurrence during the first two years and distant metastasis 2–4 years after diagnosis. Nottingham Histologic Grading (NHG) was the most important predictor, while age of the patient at the time of diagnosis was not an important predictor. CONCLUSION: In cancer registers with high dimensionality, CCA can be used for identifying the importance of risk factors for breast cancer recurrence. This technique can result in a model ready for further processing by data mining methods through reducing the number of variables to important ones
Prevention of febrile neutropenia: use of prophylactic antibiotics
Febrile neutropenia (FN) causes significant morbidity and mortality in patients receiving cytotoxic chemotherapy and can lead to reduced chemotherapy dose intensity and increased overall treatment costs. Antibiotic prophylaxis reduces the incidence of FN. Recent research and meta-analyses confirm that prophylactic fluoroquinolones decrease FN and infection-related mortality in patients with acute leukaemia and those receiving high-dose chemotherapy. Fluoroquinolone prophylaxis also lowers the incidence of FN and all-cause mortality following the first cycle of myelosuppressive chemotherapy for solid tumours. Levofloxacin has been the agent studied most thoroughly in this context. Although there is no convincing evidence that colonisation of individuals with resistant organisms due to antibiotic prophylaxis increases FN or mortality, such concerns must be taken seriously and the use of prophylaxis should be limited responsibly for patients with the greatest chance of benefit. Fluoroquinolone prophylaxis is well tolerated and cost-effective and should be offered to patients receiving chemotherapy for haematological malignancies and high-dose chemotherapy for solid tumours in which prolonged (>7 days) neutropenia is expected. It should also be considered for those receiving chemotherapy for solid tumours and lymphomas during the first cycle of chemotherapy when grade 4 neutropenia is anticipated
Molecular Subtype Classification Is a Determinant of Non-Sentinel Lymph Node Metastasis in Breast Cancer Patients with Positive Sentinel Lymph Nodes
Background: Previous studies suggested that the molecular subtypes were strongly associated with sentinel lymph node (SLN) status. The purpose of this study was to determine whether molecular subtype classification was associated with nonsentinel lymph nodes (NSLN) metastasis in patients with a positive SLN. Methodology and Principal Findings: Between January 2001 and March 2011, a total of 130 patients with a positive SLN were recruited. All these patients underwent a complete axillary lymph node dissection. The univariate and multivariate analyses of NSLN metastasis were performed. In univariate and multivariate analyses, large tumor size, macrometastasis and high tumor grade were all significant risk factors of NSLN metastasis in patients with a positive SLN. In univariate analysis, luminal B subgroup showed higher rate of NSLN metastasis than other subgroup (P = 0.027). When other variables were adjusted in multivariate analysis, the molecular subtype classification was a determinant of NSLN metastasis. Relative to triple negative subgroup, both luminal A (P = 0.047) and luminal B (P = 0.010) subgroups showed a higher risk of NSLN metastasis. Otherwise, HER2 over-expression subgroup did not have a higher risk than triple negative subgroup (P = 0.183). The area under the curve (AUC) value was 0.8095 for the Cambridge model. When molecular subtype classification was added to the Cambridge model, the AUC value was 0.8475. Conclusions: Except for other factors, molecular subtype classification was a determinant of NSLN metastasis in patient
Transmission of MRSA between Companion Animals and Infected Human Patients Presenting to Outpatient Medical Care Facilities
Methicillin-resistant Staphylococcus aureus (MRSA) is a significant pathogen in both human and veterinary medicine. The importance of companion animals as reservoirs of human infections is currently unknown. The companion animals of 49 MRSA-infected outpatients (cases) were screened for MRSA carriage, and their bacterial isolates were compared with those of the infected patients using Pulsed-Field Gel Electrophoresis (PFGE). Rates of MRSA among the companion animals of MRSA-infected patients were compared to rates of MRSA among companion animals of pet guardians attending a “veterinary wellness clinic” (controls). MRSA was isolated from at least one companion animal in 4/49 (8.2%) households of MRSA-infected outpatients vs. none of the pets of the 50 uninfected human controls. Using PFGE, patient-pets MRSA isolates were identical for three pairs and discordant for one pair (suggested MRSA inter-specie transmission p-value = 0.1175). These results suggest that companion animals of MRSA-infected patients can be culture-positive for MRSA, representing a potential source of infection or re-infection for humans. Further studies are required to better understand the epidemiology of MRSA human-animal inter-specie transmission
Does chemotherapy-induced neutropaenia result in a postponement of adjuvant or neoadjuvant regimens in breast cancer patients? Results of a retrospective analysis
In 2005, 224 patients received adjuvant/neoadjuvant chemotherapy for breast cancer in a single institution according to daily practices. Regimens consisted of epirubicin-based chemotherapy (FEC100, four or six cycles), or three cycles of FEC100 followed by three cycles of docetaxel. An absolute blood count was carried out every 3 weeks, 1–3 days before planned chemotherapy cycle. Overall, 1238 cycles were delivered. An absolute neutrophil count (ANC) <1.5 × 109 l−1 before planned chemotherapy was found in 171 cycles. Of these, 130 cycles (76%) were delivered as planned regardless of whether ANC levels recovered, and 41 (24%) were delayed. None of these patients developed a febrile neutropaenia. Haematopoietic support (granulocyte colony-stimulating factor (G-CSF)) was required in 12 cycles. We found that the majority of patients with an ANC <1.5 × 109 l−1 before planned chemotherapy received planned doses, without complications and need for G-CSF
Can Survival Prediction Be Improved By Merging Gene Expression Data Sets?
BACKGROUND:High-throughput gene expression profiling technologies generating a wealth of data, are increasingly used for characterization of tumor biopsies for clinical trials. By applying machine learning algorithms to such clinically documented data sets, one hopes to improve tumor diagnosis, prognosis, as well as prediction of treatment response. However, the limited number of patients enrolled in a single trial study limits the power of machine learning approaches due to over-fitting. One could partially overcome this limitation by merging data from different studies. Nevertheless, such data sets differ from each other with regard to technical biases, patient selection criteria and follow-up treatment. It is therefore not clear at all whether the advantage of increased sample size outweighs the disadvantage of higher heterogeneity of merged data sets. Here, we present a systematic study to answer this question specifically for breast cancer data sets. We use survival prediction based on Cox regression as an assay to measure the added value of merged data sets. RESULTS:Using time-dependent Receiver Operating Characteristic-Area Under the Curve (ROC-AUC) and hazard ratio as performance measures, we see in overall no significant improvement or deterioration of survival prediction with merged data sets as compared to individual data sets. This apparently was due to the fact that a few genes with strong prognostic power were not available on all microarray platforms and thus were not retained in the merged data sets. Surprisingly, we found that the overall best performance was achieved with a single-gene predictor consisting of CYB5D1. CONCLUSIONS:Merging did not deteriorate performance on average despite (a) The diversity of microarray platforms used. (b) The heterogeneity of patients cohorts. (c) The heterogeneity of breast cancer disease. (d) Substantial variation of time to death or relapse. (e) The reduced number of genes in the merged data sets. Predictors derived from the merged data sets were more robust, consistent and reproducible across microarray platforms. Moreover, merging data sets from different studies helps to better understand the biases of individual studies and can lead to the identification of strong survival factors like CYB5D1 expression
Two Distinct Triatoma dimidiata (Latreille, 1811) Taxa Are Found in Sympatry in Guatemala and Mexico
Approximately 10 million people are infected with Trypanosoma cruzi, the causative agent of Chagas disease, which remains the most serious parasitic disease in the Americas. Most people are infected via triatomine vectors. Transmission has been largely halted in South America in areas with predominantly domestic vectors. However, one of the main Chagas vectors in Mesoamerica, Triatoma dimidiata, poses special challenges to control due to its diversity across its large geographic range (from Mexico into northern South America), and peridomestic and sylvatic populations that repopulate houses following pesticide treatment. Recent evidence suggests T. dimidiata may be a complex of species, perhaps including cryptic species; taxonomic ambiguity which confounds control. The nuclear sequence of the internal transcribed spacer 2 (ITS2) of the ribosomal DNA and the mitochondrial cytochrome b (mt cyt b) gene were used to analyze the taxonomy of T. dimidiata from southern Mexico throughout Central America. ITS2 sequence divides T. dimidiata into four taxa. The first three are found mostly localized to specific geographic regions with some overlap: (1) southern Mexico and Guatemala (Group 2); (2) Guatemala, Honduras, El Salvador, Nicaragua, and Costa Rica (Group 1A); (3) and Panama (Group 1B). We extend ITS2 Group 1A south into Costa Rica, Group 2 into southern Guatemala and show the first information on isolates in Belize, identifying Groups 2 and 3 in that country. The fourth group (Group 3), a potential cryptic species, is dispersed across parts of Mexico, Guatemala, and Belize. We show it exists in sympatry with other groups in Peten, Guatemala, and Yucatan, Mexico. Mitochondrial cyt b data supports this putative cryptic species in sympatry with others. However, unlike the clear distinction of the remaining groups by ITS2, the remaining groups are not separated by mt cyt b. This work contributes to an understanding of the taxonomy and population subdivision of T. dimidiata, essential for designing effective control strategies
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