18 research outputs found
Quality of life, sexual function, and bariatric surgery: a systematic review
BACKGROUND: Obesity is associated with numerous comorbidities and affects various aspects of life, including quality of life (QOL) and sexual function (SF). Bariatric surgery (BS) is an effective treatment for obese people. Also QOL and SF after BS in the people are not well known. AIMS: To provide insight in the available prospective evidence regarding the short and long-term effects of BS on QOL and SF. MATERIALS AND METHODS: A systematic multi-database search was conducted for ‘quality of life’, ‘Sexual function’ and ‘Bariatric surgery’. Only prospective studies with QOL or SF before and after BS were included. The ‘quality assessment tool for before–after studies with no control group’ was used to assess the methodological quality. RESULTS: Twenty-four studies met the inclusion criteria. Most studies were assessed to be of ‘fair’ to ‘good’ methodological quality. Seven different questionnaires were used to measure both QOL and SF. A significant increase in QOL after BS and light increase in SF were found in all studies (P≤0.05). CONCLUSIONS: Both QOL and SF are increased after BS on both the short and long term. However, due to the heterogeneity of the studies and the generality of the questionnaires are them hard to make a distinction among different BS and difficult to see a relation with medical profit. Therefore, designing QOL and SF measurements to the post BS population are recommended as the focus of future studies
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4
While the increasing availability of global databases on ecological communities has advanced our knowledge
of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In
the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of
Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus
crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced
environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian
Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by
2050. This means that unless we take immediate action, we will not be able to establish their current status,
much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio
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
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost
Effects of feeding with different live preys on the lipid composition, growth and survival of Octopus vulgaris paralarvae
To move forward in the farming of Octopus vulgaris paralarvae, it is necessary to
search for a live prey easy to obtain and maintain in the laboratory that meets the nutritional requirements of the octopus paralarvae and adapts to its predatory behaviour. Grapsus adscensionis zoeae (Crustacea, Decapoda) seems to fulfil most of these
targets, and it was herein used to deepen knowledge of paralarvae lipid requirements
and composition, growth and survival. To this purpose, the effects of feeding with
Grapsus zoeae as sole prey were compared with Artemia at two different stages (nauplii and juveniles), which also differed in their lipid profiles. After 15 days of feeding,
the best growth and survival of paralarvae was obtained in the Grapsus group, and no
differences were observed between both Artemia groups. Triacylglycerides storage
in paralarvae seemed to be co-related with a lower growth and survival, but not with
its prey levels. Contrarily, sterol ester levels were higher in paralarvae fed Grapsus,
reflecting its content in the prey. The best paralarval viability was related to higher
levels of 22:6n-3 (DHA) and 20:4n-6 (ARA), also reflecting its higher content in the
prey. On the other hand, neither the 20:5n-3 (EPA) levels in the prey nor in paralarvae
were related to growth or survival. The implications of these results are discussed
considering the lipid requirements of O. vulgaris paralarvae.Artemia, Grapsus adscensionis zoeae, growth, lipid requirements, Octopus vulgaris paralarvae,
surviva
Effects of feeding with different live preys on the lipid composition, growth and survival of Octopus vulgaris paralarvae
To move forward in the farming of Octopus vulgaris paralarvae, it is necessary to
search for a live prey easy to obtain and maintain in the laboratory that meets the nutritional requirements of the octopus paralarvae and adapts to its predatory behaviour. Grapsus adscensionis zoeae (Crustacea, Decapoda) seems to fulfil most of these
targets, and it was herein used to deepen knowledge of paralarvae lipid requirements
and composition, growth and survival. To this purpose, the effects of feeding with
Grapsus zoeae as sole prey were compared with Artemia at two different stages (nauplii and juveniles), which also differed in their lipid profiles. After 15 days of feeding,
the best growth and survival of paralarvae was obtained in the Grapsus group, and no
differences were observed between both Artemia groups. Triacylglycerides storage
in paralarvae seemed to be co-related with a lower growth and survival, but not with
its prey levels. Contrarily, sterol ester levels were higher in paralarvae fed Grapsus,
reflecting its content in the prey. The best paralarval viability was related to higher
levels of 22:6n-3 (DHA) and 20:4n-6 (ARA), also reflecting its higher content in the
prey. On the other hand, neither the 20:5n-3 (EPA) levels in the prey nor in paralarvae
were related to growth or survival. The implications of these results are discussed
considering the lipid requirements of O. vulgaris paralarvae.En prens