123 research outputs found
Anguilliform larvae collected off North Carolina
The distinctive larval stage of eels (leptocephalus) facilitates dispersal through prolonged life in the open ocean. Leptocephali are abundant and diverse off North Carolina, yet data on distributions and biology are lacking. The water column (from surface to 1,293 m) was sampled in or near the Gulf Stream off Cape Hatteras, Cape Lookout, and Cape Fear, North Carolina during summer through fall of 1999â2005, and leptocephali were collected by neuston net, plankton net, Tucker trawl, and dip net. Additional samples were collected nearly monthly from a transect across southern Onslow Bay, North Carolina (from surface to 91 m) from April 2000 to December 2001 by bongo and neuston nets, Methot frame trawl, and Tucker trawl. Overall, 584 tows were completed, and 224 of these yielded larval eels. The 1,295 eel leptocephali collected (combining all methods and areas) represented at least 63 species (nine families). Thirteen species were not known previously from the area. Dominant families for all areas were Congridae (44% of individuals, 11 species), Ophichthidae (30% of individuals, 27 species), and Muraenidae (22% of individuals, ten species). Nine taxa accounted for 70% of the overall leptocephalus catches (in order of decreasing abundance): Paraconger caudilimbatus (Poey), Gymnothorax ocellatus Agassiz complex, Ariosoma balearicum (Delaroche), Ophichthus gomesii (Castelnau), Callechelys muraena Jordan and Evermann, Letharchus aliculatus McCosker, Rhynchoconger flavus (Goode and Bean), Ophichthus cruentifer (Goode and Bean), Rhynchoconger gracilior (Ginsburg). The top three species represented 52% of the total eel larvae collected. Most leptocephali were collected at night (79%) and at depths \u3e 45 m. Eighty percent of the eels collected in discrete depth Tucker trawls at night ranged from mean depths of 59â353 m. A substantial number (38% of discrete depth sample total) of larval eels were also collected at the surface (neuston net) at night. Daytime leptocephalus distributions were less clear partly due to low catches and lower Tucker trawl sampling effort. While net avoidance may account for some of the low daytime catches, an alternative explanation is that many species of larval eels occur during the day at depths \u3e 350 m. Larvae of 21 taxa of typically shallow water eels were collected at depths \u3e 350 m, but additional discrete depth diel sampling is needed to resolve leptocephalus vertical distributions. The North Carolina adult eel fauna (estuary to at least 2,000 m) consists of 51 species, 41% of which were represented in these collections. Many species of leptocephali collected are not yet known to have juveniles or adults established in the South Atlantic Bight or north of Cape Hatteras. Despite Gulf Stream transport and a prolonged larval stage, many of these eel leptocephali may not contribute to their respective populations
Deoxygenation of non-edible vegetable oil to produce hydrocarbons over Mg-Al mixed oxides
none7noopenRomero, Max; Pizzi, Andrea; Toscano, Giuseppe; Casazza, Alessandro Alberto; Busca, Guido; Bosio, Barbara; Arato, ElisabettaRomero, Max; Pizzi, Andrea; Toscano, Giuseppe; Casazza, Alessandro Alberto; Busca, Guido; Bosio, Barbara; Arato, Elisabett
Machine learned daily life history classification using low frequency tracking data and automated modelling pipelines: application to North American waterfowl
Background: Identifying animal behaviors, life history states, and movement patterns is a prerequisite for many animal behavior analyses and effective management of wildlife and habitats. Most approaches classify short-term movement patterns with high frequency location or accelerometry data. However, patterns reflecting life history across longer time scales can have greater relevance to species biology or management needs, especially when available in near real-time. Given limitations in collecting and using such data to accurately classify complex behaviors in the long-term, we used hourly GPS data from 5 waterfowl species to produce daily activity classifications with machine-learned models using âautomated modelling pipelinesâ. Methods: Automated pipelines are computer-generated code that complete many tasks including feature engineering, multi-framework model development, training, validation, and hyperparameter tuning to produce daily classifications from eight activity patterns reflecting waterfowl life history or movement states. We developed several input features for modeling grouped into three broad categories, hereafter âfeature setsâ: GPS locations, habitat information, and movement history. Each feature set used different data sources or data collected across different time intervals to develop the âfeaturesâ (independent variables) used in models. Results: Automated modelling pipelines rapidly developed easily reproducible data preprocessing and analysis steps, identification and optimization of the best performing model and provided outputs for interpreting feature importance. Unequal expression of life history states caused unbalanced classes, so we evaluated feature set importance using a weighted F1-score to balance model recall and precision among individual classes. Although the best model using the least restrictive feature set (only 24 hourly relocations in a day) produced effective classifications (weighted F1 = 0.887), models using all feature sets performed substantially better (weighted F1 = 0.95), particularly for rarer but demographically more impactful life history states (i.e., nesting). Conclusions: Automated pipelines generated models producing highly accurate classifications of complex daily activity patterns using relatively low frequency GPS and incorporating more classes than previous GPS studies. Near real-time classification is possible which is ideal for time-sensitive needs such as identifying reproduction. Including habitat and longer sequences of spatial information produced more accurate classifications but incurred slight delays in processing
The tumor suppressor semaphorin 3B triggers a prometastatic program mediated by interleukin 8 and the tumor microenvironment
Semaphorins are a large family of evolutionarily conserved morphogenetic molecules originally identified for their repelling role in axonal guidance. Intriguingly, semaphorins have recently been implicated in cancer progression (Neufeld, G., T. Lange, A. Varshavsky, and O. Kessler. 2007. Adv. Exp. Med. Biol. 600:118â131). In particular, semaphorin 3B (SEMA3B) is considered a putative tumor suppressor, and yet we found that it is expressed at high levels in many invasive and metastatic human cancers. By investigating experimental tumor models, we confirmed that SEMA3B expression inhibited tumor growth, whereas metastatic dissemination was surprisingly increased. We found that SEMA3B induced the production of interleukin (IL) 8 by tumor cells by activating the p38âmitogen-activated protein kinase pathway in a neuropilin 1âdependent manner. Silencing the expression of endogenous SEMA3B in tumor cells impaired IL-8 transcription. The release of IL-8, in turn, induced the recruitment of tumor-associated macrophages and metastatic dissemination to the lung, which could be rescued by blocking IL-8 with neutralizing antibodies. In conclusion, we report that SEMA3B exerts unexpected functions in cancer progression by fostering a prometastatic environment through elevated IL-8 secretion and recruitment of macrophages coupled to the suppression of tumor growth
Feasibility, acceptability, and characteristics associated with adherence and completion of a culturally relevant internet-enhanced physical activity pilot intervention for overweight and obese young adult African American women enrolled in college
BACKGROUND: African American women are one of the least active demographic groups in the US, with only 36% meeting the national physical activity recommendations in comparison to 46% of White women. Physical activity begins to decline in African American women in adolescence and continues to decline into young adulthood. Yet, few interventions have been developed to promote physical activity in African American women during this critical period of life. The purpose of this article was to evaluate the acceptability and feasibility of a culturally-relevant Internet-enhanced physical activity pilot intervention for overweight/obese African American college females and to examine psychosocial and behavioral characteristics associated with intervention adherence and completion.
METHODS: A 6-month single group pre-posttest design was used. Participants (n = 27) accessed a culturally-relevant Social Cognitive Theory-based physical activity promotion website while engaging in a minimum of four moderate-intensity physical activity sessions each week. Acceptability and feasibility of the intervention was assessed by participant retention and a consumer satisfaction survey completed by participants.
RESULTS: Fifty-six percent of participants (n = 15) completed the intervention. Study completers were more physically active at baseline (P = 0.05) and had greater social support for exercise from family members (P = 0.04). Sixty percent of study completers (n = 9) reported the website as enjoyable or very enjoyable to use and 60% (n = 9) reported increased motivation from participation in the physical activity program. Moreover, 87% (n = 13) reported they would recommend the website to a friend.
CONCLUSIONS: Results provide some preliminary support for the acceptability and feasibility of an Internet-enhanced physical activity program for overweight/obese African American women, while highlighting important limitations of the approach. Successful promotion of physical activity in college aged African American women as they emerge into adulthood may result in the development of life-long healthy physical activity patterns which may ultimately reduce physical activity-related health disparities in this high risk underserved population. Future studies with larger samples are needed to further explore the use of Internet-based programs to promote physical activity in this population
Treatment of high-risk relapsed Wilms tumor with dose-intensive chemotherapy, marrow-ablative chemotherapy, and autologous hematopoietic stem cell support: Experience by the Italian Association of Pediatric Hematology and Oncology
Foreign children with cancer in Italy
<p>Abstract</p> <p>Background</p> <p>There has been a noticeable annual increase in the number of children coming to Italy for medical treatment, just like it has happened in the rest of the European Union. In Italy, the assistance to children suffering from cancer is assured by the current network of 54 centres members of the Italian Association of Paediatric Haematology and Oncology (AIEOP), which has kept records of all demographic and clinical data in the database of Mod.1.01 Registry since 1989.</p> <p>Methods</p> <p>We used the information stored in the already mentioned database to assess the impact of immigration of foreign children with cancer on centres' activity, with the scope of drawing a map of the assistance to these cases.</p> <p>Results</p> <p>Out of 14,738 cases recorded by all centres in the period from 1999 to 2008, 92.2% were born and resident in Italy, 4.1% (608) were born abroad and living abroad and 3.7% (538) were born abroad and living in Italy. Foreign children cases have increased over the years from 2.5% in 1999 to. 8.1% in 2008.</p> <p>Most immigrant children came from Europe (65.7%), whereas patients who came from America, Asia and Oceania amounted to 13.2%, 10.1%, 0.2%, respectively. The immigrant survival rate was lower compared to that of children who were born in Italy. This is especially true for acute lymphoblastic leukaemia patients entered an AIEOP protocol, who showed a 10-years survival rate of 71.0% vs. 80.7% (p < 0.001) for immigrants and patients born in Italy, respectively.</p> <p>Conclusions</p> <p>Children and adolescents are an increasingly important part of the immigration phenomenon, which occurs in many parts of the world. In Italy the vast majority of children affected by malignancies are treated in AIEOP centres. Since immigrant children are predominantly treated in northern Italy, these centres have developed a special expertise in treating immigrant patients, which is certainly very useful for the entire AIEOP network.</p
An Exploratory Study of Field Failures
Field failures, that is, failures caused by faults that escape the testing
phase leading to failures in the field, are unavoidable. Improving verification
and validation activities before deployment can identify and timely remove many
but not all faults, and users may still experience a number of annoying
problems while using their software systems. This paper investigates the nature
of field failures, to understand to what extent further improving in-house
verification and validation activities can reduce the number of failures in the
field, and frames the need of new approaches that operate in the field. We
report the results of the analysis of the bug reports of five applications
belonging to three different ecosystems, propose a taxonomy of field failures,
and discuss the reasons why failures belonging to the identified classes cannot
be detected at design time but shall be addressed at runtime. We observe that
many faults (70%) are intrinsically hard to detect at design-time
Secreted CLIC3 drives cancer progression through its glutathione-dependent oxidoreductase activity
The secretome of cancer and stromal cells generates a microenvironment that contributes to tumour cell invasion and angiogenesis. Here we compare the secretome of human mammary normal and cancer-associated fibroblasts (CAFs). We discover that the chloride intracellular channel protein 3 (CLIC3) is an abundant component of the CAF secretome. Secreted CLIC3 promotes invasive behaviour of endothelial cells to drive angiogenesis and increases invasiveness of cancer cells both in vivo and in 3D cell culture models, and this requires active transglutaminase-2 (TGM2). CLIC3 acts as a glutathione-dependent oxidoreductase that reduces TGM2 and regulates TGM2 binding to its cofactors. Finally, CLIC3 is also secreted by cancer cells, is abundant in the stromal and tumour compartments of aggressive ovarian cancers and its levels correlate with poor clinical outcome. This work reveals a previously undescribed invasive mechanism whereby the secretion of a glutathione-dependent oxidoreductase drives angiogenesis and cancer progression by promoting TGM2-dependent invasion
Personalized risk stratification through attribute matching for clinical decision making in clinical conditions with aspecific symptoms: the example of syncope
Background Risk stratification is challenging in conditions, such as chest pain, shortness of breath and syncope, which can be the manifestation of many possible underlying diseases. In these cases, decision tools are unlikely to accurately identify all the different adverse events related to the possible etiologies. Attribute matching is a prediction method that matches an individual patient to a group of previously observed patients with identical characteristics and known outcome. We used syncope as a paradigm of clinical conditions presenting with aspecific symptoms to test the attribute matching method for the prediction of the personalized risk of adverse events. Methods We selected the 8 predictor variables common to the individual-patient dataset of 5 prospective emergency department studies enrolling 3388 syncope patients. We calculated all possible combinations and the number of patients in each combination. We compared the predictive accuracy of attribute matching and logistic regression. We then classified ten random patients according to clinical judgment and attribute matching. Results Attribute matching provided 253 of the 384 possible combinations in the dataset. Twelve (4.7%), 35 (13.8%), 50 (19.8%) and 160 (63.2%) combinations had a match size 6550, 6530, 6520 and <10 patients, respectively. The AUC for the attribute matching and the multivariate model were 0.59 and 0.74, respectively. Conclusions Attribute matching is a promising tool for personalized and flexible risk prediction. Large databases will need to be used in future studies to test and apply the method in different conditions
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