The global abundance of tree palms

Aim Palms are an iconic, diverse and often abundant component of tropical ecosystems that provide many ecosystem services. Being monocots, tree palms are evolutionarily, morphologically and physiologically distinct from other trees, and these differences have important consequences for ecosystem services (e.g., carbon sequestration and storage) and in terms of responses to climate change. We quantified global patterns of tree palm relative abundance to help improve understanding of tropical forests and reduce uncertainty about these ecosystems under climate change. Location Tropical and subtropical moist forests. Time period Current. Major taxa studied Palms (Arecaceae). Methods We assembled a pantropical dataset of 2,548 forest plots (covering 1,191 ha) and quantified tree palm (i.e., ≥10 cm diameter at breast height) abundance relative to co‐occurring non‐palm trees. We compared the relative abundance of tree palms across biogeographical realms and tested for associations with palaeoclimate stability, current climate, edaphic conditions and metrics of forest structure. Results On average, the relative abundance of tree palms was more than five times larger between Neotropical locations and other biogeographical realms. Tree palms were absent in most locations outside the Neotropics but present in >80% of Neotropical locations. The relative abundance of tree palms was more strongly associated with local conditions (e.g., higher mean annual precipitation, lower soil fertility, shallower water table and lower plot mean wood density) than metrics of long‐term climate stability. Life‐form diversity also influenced the patterns; palm assemblages outside the Neotropics comprise many non‐tree (e.g., climbing) palms. Finally, we show that tree palms can influence estimates of above‐ground biomass, but the magnitude and direction of the effect require additional work. Conclusions Tree palms are not only quintessentially tropical, but they are also overwhelmingly Neotropical. Future work to understand the contributions of tree palms to biomass estimates and carbon cycling will be particularly crucial in Neotropical forests

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

Epitope-based vaccines with the Anaplasma marginale MSP1a functional motif induce a balanced humoral and cellular immune response in mice.

Bovine anaplasmosis is a hemoparasitic disease that causes considerable economic loss to the dairy and beef industries. Cattle immunized with the Anaplasma marginale MSP1 outer membrane protein complex presents a protective humoral immune response; however, its efficacy is variable. Immunodominant epitopes seem to be a key-limiting factor for the adaptive immunity. We have successfully demonstrated that critical motifs of the MSP1a functional epitope are essential for antibody recognition of infected animal sera, but its protective immunity is yet to be tested. We have evaluated two synthetic vaccine formulations against A. marginale, using epitope-based approach in mice. Mice infection with bovine anaplasmosis was demonstrated by qPCR analysis of erythrocytes after 15-day exposure. A proof-of-concept was obtained in this murine model, in which peptides conjugated to bovine serum albumin were used for immunization in three 15-day intervals by intraperitoneal injections before challenging with live bacteria. Blood samples were analyzed for the presence of specific IgG2a and IgG1 antibodies, as well as for the rickettsemia analysis. A panel containing the cytokines' transcriptional profile for innate and adaptive immune responses was carried out through qPCR. Immunized BALB/c mice challenged with A. marginale presented stable body weight, reduced number of infected erythrocytes, and no mortality; and among control groups mortality rates ranged from 15% to 29%. Additionally, vaccines have significantly induced higher IgG2a than IgG1 response, followed by increased expression of pro-inflammatory cytokines. This is a successful demonstration of epitope-based vaccines, and protection against anaplasmosis may be associated with elicitation of effector functions of humoral and cellular immune responses in murine model

Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) Spectroscopy Analysis of Saliva for Breast Cancer Diagnosis

Saliva biomarkers using reagent-free biophotonic technology have not been investigated as a strategy for early detection of breast cancer (BC). The attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy has been proposed as a promising tool for disease diagnosis. However, its utilization in cancer is still incipient, and currently saliva has not been used for BC screening. We have applied ATR-FTIR onto saliva from patients with breast cancer, benign breast disease, and healthy matched controls to investigate its potential use in BC diagnosis. Several salivary vibrational modes have been identified in original and second-derivative spectra. The absorbance levels at wavenumber 1041 cm−1 were significantly higher (p<0.05) in saliva of breast cancer patients compared with those of benign patients, and the ROC curve analysis of this peak showed a reasonable accuracy to discriminate breast cancer from benign and control patients. The 1433–1302.9 cm−1 band area was significantly higher (p<0.05) in saliva of breast cancer patients than in control and benign patients. This salivary ATR-FTIR spectral area was prevalidated as a potential diagnostic biomarker of BC. This spectral biomarker was able to discriminate human BC from controls with sensitivity and specificity of 90% and 80%, respectively. Besides, it was able to differentiate BC from benign disease with sensitivity and specificity of 90% and 70%, respectively. Briefly, for the first time, saliva analysis by ATR-FTIR spectroscopy has demonstrated the potential use of salivary spectral biomarkers (1041 cm−1 and 1433–1302.9 cm−1) as a novel alternative for noninvasive BC diagnosis, which could be used for screening purposes

A Novel Detection Method of Breast Cancer through a Simple Panel of Biomarkers

Circulating tumor cells (CTCs) have been identified as responsible for the spread of tumors to other organs of the body. In this sense, the development of sensitive and specific assays for their detection is important to reduce the number of deaths due to metastases. Here, we assessed whether the detection of CTCs in peripheral blood can serve in the construction of a panel of diagnosis and monitoring treatments of breast cancer (BC), focusing on the expression of markers of epithelial–mesenchymal transition. Through analyzing the blood from women without breast alterations (control), women with benign alterations, women with breast cancer without chemotherapy, and women with breast cancer with chemotherapy, we identified the best markers by transcriptional levels and determined three profiles of CTCs (mesenchymal, intermediate, and epithelial) by flow cytometry which, combined, can be used for diagnosis and therapy monitoring with sensitivity and specificity between 80% and 100%. Therefore, we have developed a method for detecting breast cancer based on the analysis of CTC profiles by epithelial–mesenchymal transition markers which, combined, can be used for the diagnosis and monitoring of therapy

Ethanolic Extracts from Azadirachta indica Leaves Modulate Transcriptional Levels of Hormone Receptor Variant in Breast Cancer Cell Lines

Breast Cancer (BC) encompasses numerous entities with different biological and behavioral characteristics, favored by tumor molecular complexity. Azadirachta indica (neem) presents phenolic compounds, indicating its potential as an antineoplastic compound. The present study aimed to evaluate the cellular response of MCF10, MCF7, and MDA-MB-231 breast cell lines to ethanolic extracts of neem leaves (EENL) obtained by dichloromethane (DCM) and ethyl acetate (EA) solvent. Extracts&rsquo; antiproliferative activities were evaluated against MCF 10A, MCF7, and MDA-MB-231 for 24 and 48 h using MTT assay. ESR1, ESR2, AR, AR-V1, AR-V4, and AR-V7 transcripts were quantified through qPCR for 0.03125 &mu;g/mL of DCM and 1.0 &mu;g/mL for EA for 48 h. The EENL was tested on Drosophila melanogaster as a sole treatment and then also together with doxorubicin. Antiproliferative effect on tumor cell lines without affecting MCF 10A were 1.0 &micro;g/mL (P &lt; 0.001) for EA, and 0.03125 &micro;g/mL (P &lt; 0.0001) for DCM, both after 48 h. Transcriptional levels of AR-V7 increased after treatment. In vivo assays demonstrated that EENL induced fewer tumors at a higher concentration with doxorubicin (DXR). The behavior of AR-V7 in the MDA-MB-231 tumor lineage indicates new pathways involved in tumor biology and this may have therapeutic value for cancer

New Insights into the Role of Polybromo-1 in Prostate Cancer

The human protein Polybromo-1 (PBMR1/BAF180) is a component of the SWI/SNF chromatin-remodeling complex that has been reported to be deregulated in tumors. However, its role in prostate cancer (PCa) is largely unknown. In this study, we described the PBRM1 transcriptional levels and the protein expression/localization in tissues of PCa patients and in prostatic cell lines. Increased PBRM1 mRNA levels were found in PCa samples, when compared to benign disease, and were correlated with higher Gleason score. We also verified that only the nuclear localization of PBRM1 protein is correlated with a more aggressive disease and high Prostate-Specific Antigen (PSA) levels in tissue microarrays. Intriguing expression patterns of mRNA and protein were identified in the cell lines. Although PBRM1 protein was restricted to the nuclei, in tumor cell lines in non-neoplastic cells, it was also present in vesicular-like structures that were dispersed within the cytoplasm. We knocked-down PBRM1 in the castration-resistant PCa (CRPC) cell line PC-3 and we verified that PBRM1 promotes the expression of several markers of aggressiveness, including EpCAM, TGF-&beta;, and N-Cadherin. Therefore, our data supported the hypothesis that PBRM1 displays a pivotal role in the promotion and maintenance of the malignant behavior of PCa, especially in CRPC

Effects of immunization on cytokine expression of mice splenocytes.

<p>The Cytokine expression was quantified before challenge (A) and after <i>A. marginale</i> challenge (B) by real-time PCR with focus on mRNA expression of IL-12, IL-18, IFN-γ, TNF-α, IL-10 and TGF-β. Results are presented as the mean ± SE of the fold-change of mRNA in peptides, ALA or FrA immunized mice (n = 3, A; n = 7, B) compared to negative control (PBS-immunized mice). Animals were challenged with 3×10⁵ rickettsia after 45th day. *Statistically significant differences (p<0.05); **p<0.01; ***p<0.0001.</p