MutSα expression predicts a lower disease-free survival in malignant salivary gland tumors: an immunohistochemical study

Background: Appropriate DNA replication is vital to maintain cell integrity at the genomic level. Malfunction on DNA repair mechanisms can have implications related to tumor behavior. Our aim was to evaluate the expression of key complexes of the DNA mismatch-repair system MutSα (hMSH2-hMSH6) and MutSβ (hMSH2-hMSH3) in a panel comprising the most common benign and malignant salivary gland tumors (SGT), and to determine their association with disease-free survival. Material and Methods: Ten cases of normal salivary gland (NSG) and 92 of SGT (54 benign and 38 malignant) were retrieved. Immunohistochemistry was performed for hMSH2, hMSH3, hMSH6. Scanned slides were digitally analyzed based on the percentage of positive cells with nuclear staining. Cases were further classified in MutSαhigh and MutSβhigh based on hMSH2-hMSH6 and hMSH3-hMSH6 expression, respectively. Results: hMSH3 expression was lower in malignant SGT compared to NSG and benign cases. Adenoid cystic carcinoma (ACC) cases with perineural invasion presented a lower percentage of hMSH3 positive cells. hMSH6 was downregulated in both benign and malignant SGT compared to NSG. Malignant SGT cases with MutSαhigh expression had lower disease-free survival compared to MutSαlow cases. A 10.26-fold increased risk of presenting local recurrence was observed. Conclusions: Our findings suggest that a lack of hMSH3 protein function is associated with a more aggressive phenotype (malignancy and perineural invasion) and that MutSα overexpression predicts a poor clinical outcome in malignant SGT

NEOTROPICAL XENARTHRANS: a data set of occurrence of xenarthran species in the Neotropics

Xenarthrans – anteaters, sloths, and armadillos – have essential functions for ecosystem maintenance, such as insect control and nutrient cycling, playing key roles as ecosystem engineers. Because of habitat loss and fragmentation, hunting pressure, and conflicts with 24 domestic dogs, these species have been threatened locally, regionally, or even across their full distribution ranges. The Neotropics harbor 21 species of armadillos, ten anteaters, and six sloths. Our dataset includes the families Chlamyphoridae (13), Dasypodidae (7), Myrmecophagidae (3), Bradypodidae (4), and Megalonychidae (2). We have no occurrence data on Dasypus pilosus (Dasypodidae). Regarding Cyclopedidae, until recently, only one species was recognized, but new genetic studies have revealed that the group is represented by seven species. In this data-paper, we compiled a total of 42,528 records of 31 species, represented by occurrence and quantitative data, totaling 24,847 unique georeferenced records. The geographic range is from the south of the USA, Mexico, and Caribbean countries at the northern portion of the Neotropics, to its austral distribution in Argentina, Paraguay, Chile, and Uruguay. Regarding anteaters, Myrmecophaga tridactyla has the most records (n=5,941), and Cyclopes sp. has the fewest (n=240). The armadillo species with the most data is Dasypus novemcinctus (n=11,588), and the least recorded for Calyptophractus retusus (n=33). With regards to sloth species, Bradypus variegatus has the most records (n=962), and Bradypus pygmaeus has the fewest (n=12). Our main objective with Neotropical Xenarthrans is to make occurrence and quantitative data available to facilitate more ecological research, particularly if we integrate the xenarthran data with other datasets of Neotropical Series which will become available very soon (i.e. Neotropical Carnivores, Neotropical Invasive Mammals, and Neotropical Hunters and Dogs). Therefore, studies on trophic cascades, hunting pressure, habitat loss, fragmentation effects, species invasion, and climate change effects will be possible with the Neotropical Xenarthrans dataset

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications 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, 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