Performance and egg quality of Embrapa 051 laying hens subjected to different feeding programs.

Abstract: This study aimed to evaluate the productive performance and egg quality of Embrapa 051 lineage laying hens compared to a commercial line (Lohmann Brown) when subjected to different feeding programs. Trial consisted of a randomized complete block design, with four treatments: T1 - Lohmann Brown Line receiving 100% basal diet; T2 - Embrapa 051 Line receiving 93% basal diet; T3 - Embrapa 051 line receiving 100% basal diet; and T4 - Embrapa 051 lineage receiving 107% basal diet. The treatments had five replicates each. The basal diet was that recommended by the Lohmann Brown line manual. Variables of bird performance (egg weight, egg production rate, feed conversion per dozen eggs, energy conversion and egg mass) were analyzed, as well as internal egg quality (Haugh unit, yolk color, yolk percentage, and albumen percentage) and external egg quality (specific gravity, shell percentage, and shell thickness). All performance variables presented significant differences (P <0.05) in the three evaluated cycles, comparing lineages. Egg produced by the Embrapa 051 line had the highest percentages of yolk and those of the Lohmann Brown line had the highest percentage of albumen. In conclusion, Embrapa 051 lineage has the potential to produce good quality eggs, as long as it receives the same feeding program of the genetically established lineage. Resumo: O objetivo deste estudo foi avaliar o desempenho produtivo e a qualidade dos ovos da poedeira Embrapa 051, em comparação com uma linhagem comercial (Lohmann Brown), sujeita a diferentes programas alimentares. O delineamento experimental utilizado foi o de blocos completamente casualizados, e os tratamentos foram: T1 ? Linhagem Lohmann Brown recebendo 100% da dieta base; T2 ? Linhagem Embrapa 051 recebendo 93% da dieta base; T3 ? Linhagem Embrapa 051 recebendo 100% da dieta base; e T4 - Linhagem Embrapa 051 recebendo 107% da dieta base. Os tratamentos tiveram cinco repetições cada. A dieta base foi a recomendada pelo manual da linhagem Lohmann Brown. Foram analisadas variáveis de desempenho zootécnico (peso dos ovos, taxa de produção de ovos, conversão alimentar por dúzia de ovo, conversão energética e massa de ovo); qualidade interna (unidade Haugh, coloração da gema, porcentagem de gema e porcentagem de albúmen) e qualidade externa de ovos (gravidade específica, porcentagem de casca e espessura de casca). Todas as variáveis de desempenho apresentaram diferenças significativas (P<0,05) nos três ciclos avaliados, sendo que as aves da linhagem Lohmann Brown apresentaram os maiores valores para essas variáveis. Em relação às variáveis de qualidade interna e externa dos ovos, apenas as porcentagens de gema e de albúmen apresentaram diferença significativa (P<0,05) entre os tratamentos nos três ciclos avaliados. Os ovos produzidos pela linhagem Embrapa 051 apresentaram as maiores porcentagens de gema e os da linhagem Lohmann Brown a maior porcentagem de albúmen. Com o presente trabalho pode-se concluir que a linhagem Embrapa 051 tem potencial para produzir ovos de boa qualidade, desde que receba o mesmo programa alimentar da linhagem geneticamente estabelecida

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

ITALIAN CANCER FIGURES - REPORT 2015: The burden of rare cancers in Italy = I TUMORI IN ITALIA - RAPPORTO 2015: I tumori rari in Italia

OBJECTIVES: This collaborative study, based on data collected by the network of Italian Cancer Registries (AIRTUM), describes the burden of rare cancers in Italy. Estimated number of new rare cancer cases yearly diagnosed (incidence), proportion of patients alive after diagnosis (survival), and estimated number of people still alive after a new cancer diagnosis (prevalence) are provided for about 200 different cancer entities. MATERIALS AND METHODS: Data herein presented were provided by AIRTUM population- based cancer registries (CRs), covering nowadays 52% of the Italian population. This monograph uses the AIRTUM database (January 2015), which includes all malignant cancer cases diagnosed between 1976 and 2010. All cases are coded according to the International Classification of Diseases for Oncology (ICD-O-3). Data underwent standard quality checks (described in the AIRTUM data management protocol) and were checked against rare-cancer specific quality indicators proposed and published by RARECARE and HAEMACARE (www.rarecarenet.eu; www.haemacare.eu). The definition and list of rare cancers proposed by the RARECAREnet "Information Network on Rare Cancers" project were adopted: rare cancers are entities (defined as a combination of topographical and morphological codes of the ICD-O-3) having an incidence rate of less than 6 per 100,000 per year in the European population. This monograph presents 198 rare cancers grouped in 14 major groups. Crude incidence rates were estimated as the number of all new cancers occurring in 2000-2010 divided by the overall population at risk, for males and females (also for gender-specific tumours).The proportion of rare cancers out of the total cancers (rare and common) by site was also calculated. Incidence rates by sex and age are reported. The expected number of new cases in 2015 in Italy was estimated assuming the incidence in Italy to be the same as in the AIRTUM area. One- and 5-year relative survival estimates of cases aged 0-99 years diagnosed between 2000 and 2008 in the AIRTUM database, and followed up to 31 December 2009, were calculated using complete cohort survival analysis. To estimate the observed prevalence in Italy, incidence and follow-up data from 11 CRs for the period 1992-2006 were used, with a prevalence index date of 1 January 2007. Observed prevalence in the general population was disentangled by time prior to the reference date (≤2 years, 2-5 years, ≤15 years). To calculate the complete prevalence proportion at 1 January 2007 in Italy, the 15-year observed prevalence was corrected by the completeness index, in order to account for those cancer survivors diagnosed before the cancer registry activity started. The completeness index by cancer and age was obtained by means of statistical regression models, using incidence and survival data available in the European RARECAREnet data. RESULTS: In total, 339,403 tumours were included in the incidence analysis. The annual incidence rate (IR) of all 198 rare cancers in the period 2000-2010 was 147 per 100,000 per year, corresponding to about 89,000 new diagnoses in Italy each year, accounting for 25% of all cancer. Five cancers, rare at European level, were not rare in Italy because their IR was higher than 6 per 100,000; these tumours were: diffuse large B-cell lymphoma and squamous cell carcinoma of larynx (whose IRs in Italy were 7 per 100,000), multiple myeloma (IR: 8 per 100,000), hepatocellular carcinoma (IR: 9 per 100,000) and carcinoma of thyroid gland (IR: 14 per 100,000). Among the remaining 193 rare cancers, more than two thirds (No. 139) had an annual IR &lt;0.5 per 100,000, accounting for about 7,100 new cancers cases; for 25 cancer types, the IR ranged between 0.5 and 1 per 100,000, accounting for about 10,000 new diagnoses; while for 29 cancer types the IR was between 1 and 6 per 100,000, accounting for about 41,000 new cancer cases. Among all rare cancers diagnosed in Italy, 7% were rare haematological diseases (IR: 41 per 100,000), 18% were solid rare cancers. Among the latter, the rare epithelial tumours of the digestive system were the most common (23%, IR: 26 per 100,000), followed by epithelial tumours of head and neck (17%, IR: 19) and rare cancers of the female genital system (17%, IR: 17), endocrine tumours (13% including thyroid carcinomas and less than 1% with an IR of 0.4 excluding thyroid carcinomas), sarcomas (8%, IR: 9 per 100,000), central nervous system tumours and rare epithelial tumours of the thoracic cavity (5%with an IR equal to 6 and 5 per 100,000, respectively). The remaining (rare male genital tumours, IR: 4 per 100,000; tumours of eye, IR: 0.7 per 100,000; neuroendocrine tumours, IR: 4 per 100,000; embryonal tumours, IR: 0.4 per 100,000; rare skin tumours and malignant melanoma of mucosae, IR: 0.8 per 100,000) each constituted &lt;4% of all solid rare cancers. Patients with rare cancers were on average younger than those with common cancers. Essentially, all childhood cancers were rare, while after age 40 years, the common cancers (breast, prostate, colon, rectum, and lung) became increasingly more frequent. For 254,821 rare cancers diagnosed in 2000-2008, 5-year RS was on average 55%, lower than the corresponding figures for patients with common cancers (68%). RS was lower for rare cancers than for common cancers at 1 year and continued to diverge up to 3 years, while the gap remained constant from 3 to 5 years after diagnosis. For rare and common cancers, survival decreased with increasing age. Five-year RS was similar and high for both rare and common cancers up to 54 years; it decreased with age, especially after 54 years, with the elderly (75+ years) having a 37% and 20% lower survival than those aged 55-64 years for rare and common cancers, respectively. We estimated that about 900,000 people were alive in Italy with a previous diagnosis of a rare cancer in 2010 (prevalence). The highest prevalence was observed for rare haematological diseases (278 per 100,000) and rare tumours of the female genital system (265 per 100,000). Very low prevalence (&lt;10 prt 100,000) was observed for rare epithelial skin cancers, for rare epithelial tumours of the digestive system and rare epithelial tumours of the thoracic cavity. COMMENTS: One in four cancers cases diagnosed in Italy is a rare cancer, in agreement with estimates of 24% calculated in Europe overall. In Italy, the group of all rare cancers combined, include 5 cancer types with an IR&gt;6 per 100,000 in Italy, in particular thyroid cancer (IR: 14 per 100,000).The exclusion of thyroid carcinoma from rare cancers reduces the proportion of them in Italy in 2010 to 22%. Differences in incidence across population can be due to the different distribution of risk factors (whether environmental, lifestyle, occupational, or genetic), heterogeneous diagnostic intensity activity, as well as different diagnostic capacity; moreover heterogeneity in accuracy of registration may determine some minor differences in the account of rare cancers. Rare cancers had worse prognosis than common cancers at 1, 3, and 5 years from diagnosis. Differences between rare and common cancers were small 1 year after diagnosis, but survival for rare cancers declined more markedly thereafter, consistent with the idea that treatments for rare cancers are less effective than those for common cancers. However, differences in stage at diagnosis could not be excluded, as 1- and 3-year RS for rare cancers was lower than the corresponding figures for common cancers. Moreover, rare cancers include many cancer entities with a bad prognosis (5-year RS &lt;50%): cancer of head and neck, oesophagus, small intestine, ovary, brain, biliary tract, liver, pleura, multiple myeloma, acute myeloid and lymphatic leukaemia; in contrast, most common cancer cases are breast, prostate, and colorectal cancers, which have a good prognosis. The high prevalence observed for rare haematological diseases and rare tumours of the female genital system is due to their high incidence (the majority of haematological diseases are rare and gynaecological cancers added up to fairly high incidence rates) and relatively good prognosis. The low prevalence of rare epithelial tumours of the digestive system was due to the low survival rates of the majority of tumours included in this group (oesophagus, stomach, small intestine, pancreas, and liver), regardless of the high incidence rate of rare epithelial cancers of these sites. This AIRTUM study confirms that rare cancers are a major public health problem in Italy and provides quantitative estimations, for the first time in Italy, to a problem long known to exist. This monograph provides detailed epidemiologic indicators for almost 200 rare cancers, the majority of which (72%) are very rare (IR&lt;0.5 per 100,000). These data are of major interest for different stakeholders. Health care planners can find useful information herein to properly plan and think of how to reorganise health care services. Researchers now have numbers to design clinical trials considering alternative study designs and statistical approaches. Population-based cancer registries with good quality data are the best source of information to describe the rare cancer burden in a population

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.Peer reviewe