Development Of A Balb/c Mouse Model Of Helicobacter Pylori Infection With Fresh And Frozen Bacteria.

An experimental model for H. pylori infection was established by intragastrically challenging BALB/c mice with 1 ml (10(8) CFU/ml) of suspension for two consecutive days. Animals were divided into three groups. GA: mice inoculated with fresh bacteria; GB: mice inoculated with frozen bacteria, and GC: mice inoculated with brucella broth (control group). Animals were killed at 7, 14, 21, 28, 35 and 60 days pi and fragments of stomach and duodenum were collected, paraffin embedded and stained by hematoxylin-eosin and Giemsa. The results showed that challenged mice exhibited mild duodenitis and gastritis. In group GA, infiltration in the duodenum was lymphoplasmacytic until day 35; in group GB, it was lymphomonocytic for 60 days pi. In the stomach, H. pylori induced lymphomonocytic infiltration that was present from days 7 to 60 in group GA. In group GB, it was only present from days 14 to 35. In conclusion, our data suggested that freezing altered pathogenic properties of H. pylori and probably inhibited expression of bacterial antigens and consequently the establishment and maintenance of infection. Although the animals developed mild duodenitis and gastritis, the BALB/c mouse is not susceptible to developing peptic ulcers during H. pylori infection.38101-

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

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

Development of a BALB/c mouse model of Helicobacter pylori infection with fresh and frozen bacteria

An experimental model for H. pylori infection was established by intragastrically challenging BALB/c mice with 1 ml (10(8) CFU/ml) of suspension for two consecutive days. Animals were divided into three groups. GA: mice inoculated with fresh bacteria; GB: mice inoculated with frozen bacteria, and GC: mice inoculated with brucella broth (control group). Animals were killed at 7, 14, 21, 28, 35 and 60 days pi and fragments of stomach and duodenum were collected, paraffin embedded and stained by hematoxylin-eosin and Giemsa. The results showed that challenged mice exhibited mild duodenitis and gastritis. In group GA, infiltration in the duodenum was lymphoplasmacytic until day 35; in group GB, it was lymphomonocytic for 60 days pi. In the stomach, H. pylori induced lymphomonocytic infiltration that was present from days 7 to 60 in group GA. In group GB, it was only present from days 14 to 35. In conclusion, our data suggested that freezing altered pathogenic properties of H. pylori and probably inhibited expression of bacterial antigens and consequently the establishment and maintenance of infection. Although the animals developed mild duodenitis and gastritis, the BALB/c mouse is not susceptible to developing peptic ulcers during H. pylori infectio

Comparative Analysis Of Two-dimensional Electrophoresis Maps (2-de) Of Helicobacter Pylori From Brazilian Patients With Chronic Gastritis And Duodenal Ulcer: A Preliminary Report.

Helicobacter pylori is a bacterium recognized as the major cause of peptic ulcer and chronic gastritis. Recently, a proteome-based approach was developed to investigate pathogenic factors related to H. pylori. In this preliminary study, H. pylori strains were isolated from gastric biopsies of patients with chronic gastritis and duodenal ulcers. A partial proteomic analysis of H. pylori strains was performed by bacterial lyses and proteins were separated by two-dimensional gel electrophoresis (2-DE). A comparative analysis was performed to verify a differential protein expression between these two 2-DE maps. These data should be useful to clarify the role of different proteins related to bacterial pathogenesis. This study will be completed using a larger number of samples and protein identification of H. pylori by MALDI-TOF mass spectrometry.48175-

NEOTROPICAL ALIEN MAMMALS: a data set of occurrence and abundance of alien mammals in the Neotropics

Biological invasion is one of the main threats to native biodiversity. For a species to become invasive, it must be voluntarily or involuntarily introduced by humans into a nonnative habitat. Mammals were among first taxa to be introduced worldwide for game, meat, and labor, yet the number of species introduced in the Neotropics remains unknown. In this data set, we make available occurrence and abundance data on mammal species that (1) transposed a geographical barrier and (2) were voluntarily or involuntarily introduced by humans into the Neotropics. Our data set is composed of 73,738 historical and current georeferenced records on alien mammal species of which around 96% correspond to occurrence data on 77 species belonging to eight orders and 26 families. Data cover 26 continental countries in the Neotropics, ranging from Mexico and its frontier regions (southern Florida and coastal-central Florida in the southeast United States) to Argentina, Paraguay, Chile, and Uruguay, and the 13 countries of Caribbean islands. Our data set also includes neotropical species (e.g., Callithrix sp., Myocastor coypus, Nasua nasua) considered alien in particular areas of Neotropics. The most numerous species in terms of records are from Bos sp. (n = 37,782), Sus scrofa (n = 6,730), and Canis familiaris (n = 10,084); 17 species were represented by only one record (e.g., Syncerus caffer, Cervus timorensis, Cervus unicolor, Canis latrans). Primates have the highest number of species in the data set (n = 20 species), partly because of uncertainties regarding taxonomic identification of the genera Callithrix, which includes the species Callithrix aurita, Callithrix flaviceps, Callithrix geoffroyi, Callithrix jacchus, Callithrix kuhlii, Callithrix penicillata, and their hybrids. This unique data set will be a valuable source of information on invasion risk assessments, biodiversity redistribution and conservation-related research. There are no copyright restrictions. Please cite this data paper when using the data in publications. We also request that researchers and teachers inform us on how they are using the data