Identification of autism spectrum disorder using deep learning and the ABIDE dataset

The research was supported by CAPES, Brazilian Ministry of Education (Projeto ACERTA CAPES/OBEDUC 0898/2013; number 23038.002530/2013-93Peer reviewe

Genome-Wide Analysis in Brazilian Xavante Indians Reveals Low Degree of Admixture

Characterization of population genetic variation and structure can be used as tools for research in human genetics and population isolates are of great interest. the aim of the present study was to characterize the genetic structure of Xavante Indians and compare it with other populations. the Xavante, an indigenous population living in Brazilian Central Plateau, is one of the largest native groups in Brazil. A subset of 53 unrelated subjects was selected from the initial sample of 300 Xavante Indians. Using 86,197 markers, Xavante were compared with all populations of HapMap Phase III and HGDP-CEPH projects and with a Southeast Brazilian population sample to establish its population structure. Principal Components Analysis showed that the Xavante Indians are concentrated in the Amerindian axis near other populations of known Amerindian ancestry such as Karitiana, Pima, Surui and Maya and a low degree of genetic admixture was observed. This is consistent with the historical records of bottlenecks experience and cultural isolation. By calculating pair-wise F-st statistics we characterized the genetic differentiation between Xavante Indians and representative populations of the HapMap and from HGDP-CEPH project. We found that the genetic differentiation between Xavante Indians and populations of Ameridian, Asian, European, and African ancestry increased progressively. Our results indicate that the Xavante is a population that remained genetically isolated over the past decades and can offer advantages for genome-wide mapping studies of inherited disorders.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)INCT- Obesidade e DiabetesUniversidade Federal de São Paulo, Disciplina Endocrinol, Escola Paulista Med, São Paulo, BrazilUniv São Paulo, Sch Med, Lab Genet & Mol Cardiol, Inst Heart, São Paulo, BrazilUniv São Paulo, Fac Med Ribeirao Preto, Dept Social Med, Ribeirao Preto, BrazilUniversidade Federal de São Paulo, Disciplina Endocrinol, Escola Paulista Med, São Paulo, BrazilWeb of Scienc

Aerocyte specification and lung adaptation to breathing is dependent on alternative splicing changes

© 2022 Fidalgo et al. This article is available under a Creative Commons License (Attribution 4.0 International, as described at https://creativecommons.org/licenses/by/4.0/).Adaptation to breathing is a critical step in lung function and it is crucial for organismal survival. Alveoli are the lung gas exchange units and their development, from late embryonic to early postnatal stages, requires feedbacks between multiple cell types. However, how the crosstalk between the alveolar cell types is modulated to anticipate lung adaptation to breathing is still unclear. Here, we uncovered a synchronous alternative splicing switch in multiple genes in the developing mouse lungs at the transition to birth, and we identified hnRNP A1, Cpeb4, and Elavl2/HuB as putative splicing regulators of this transition. Notably, we found that Vegfa switches from the Vegfa 164 isoform to the longer Vegfa 188 isoform exclusively in lung alveolar epithelial AT1 cells. Functional analysis revealed that VEGFA 188 (and not VEGFA 164) drives the specification of Car4-positive aerocytes, a subtype of alveolar endothelial cells specialized in gas exchanges. Our results reveal that the cell type-specific regulation of Vegfa alternative splicing just before birth modulates the epithelial-endothelial crosstalk in the developing alveoli to promote lung adaptation to breathing.This work was supported by European Research Council (ERC starting grant [679368]), the European Union (H2020-TWINN-2015 – Twinning [692322]), Fundação para a Ciência e Tecnologia (FCT) (PTDC/MED-PAT/31639/2017, and UIDP/04378/2020 of the Research Unit on Applied Molecular Biosciences - UCIBIO), and Fondation Leducq (17CVD03). CG Fonseca was supported by a PhD fellowship from the doctoral program Bioengineering: Cellular Therapies and Regenerative Medicine funded by Fundação para a Ciência e Tecnologia (FCT) (PD/BD/128375/2017). T Balboni was supported by a PhD fellowship from the doctoral program “Oncology, Hematology and Pathology - 30th Cycle” funded by University of Bologna, Italy. P Caldas was supported by a postdoctoral researcher fellowship from FCT (PTDC/MED-ONC/28660/2017). AASF Raposo was supported by FCT and Fundo Europeu de Desenvolvimento Regional (FEDER) PAC-PRECISE-LISBOA-01-0145-FEDER-016394 and by an assistant researcher contract from FCT (CEECIND/01474/2017). AR Grosso was supported by a principal investigator contract from FCT (CEECIND/02699/2017). FF Vasconcelos was supported by a postdoctoral researcher contract from FCT (CEECIND/04251/2017). CA Franco was supported by a principal investigator contract from FCT (CEECIND/02589/2018).info:eu-repo/semantics/publishedVersio

Clinical factors influencing long-term survival in a real-life cohort of early stage non-small-cell lung cancer patients in Spain

Funding Information: This work was supported in part by Centro de Matematica e Aplicaçoes, UID (MAT/00297/2020), Portuguese Foundation of Science and Technology. Acknowledgments Publisher Copyright: Copyright © 2023 Torrente, Sousa, Guerreiro, Franco, Hernández, Parejo, Sousa, Campo-Cañaveral, Pimentão and Provencio.Background: Current prognosis in oncology is reduced to the tumour stage and performance status, leaving out many other factors that may impact the patient´s management. Prognostic stratification of early stage non-small-cell lung cancer (NSCLC) patients with poor prognosis after surgery is of considerable clinical relevance. The objective of this study was to identify clinical factors associated with long-term overall survival in a real-life cohort of patients with stage I-II NSCLC and develop a prognostic model that identifies features associated with poor prognosis and stratifies patients by risk. Methods: This is a cohort study including 505 patients, diagnosed with stage I-II NSCLC, who underwent curative surgical procedures at a tertiary hospital in Madrid, Spain. Results: Median OS (in months) was 63.7 (95% CI, 58.7-68.7) for the whole cohort, 62.4 in patients submitted to surgery and 65 in patients submitted to surgery and adjuvant treatment. The univariate analysis estimated that a female diagnosed with NSCLC has a 0.967 (95% CI 0.936 - 0.999) probability of survival one year after diagnosis and a 0.784 (95% CI 0.712 - 0.863) five years after diagnosis. For males, these probabilities drop to 0.904 (95% CI 0.875 - 0.934) and 0.613 (95% CI 0.566 - 0.665), respectively. Multivariable analysis shows that sex, age at diagnosis, type of treatment, ECOG-PS, and stage are statistically significant variables (p1) while adjuvant chemotherapy is a good prognostic variable (HR<1). The prognostic model identified a high-risk profile defined by males over 71 years old, former smokers, treated with surgery, ECOG-PS 2. Conclusions: The results of the present study found that, overall, adjuvant chemotherapy was associated with the best long-term OS in patients with resected NSCLC. Age, stage and ECOG-PS were also significant factors to take into account when making decisions regarding adjuvant therapy.publishersversionpublishe

Enhancing collaborative neuroimaging research: introducing COINSTAC Vaults for federated analysis and reproducibility

Collaborative neuroimaging research is often hindered by technological, policy, administrative, and methodological barriers, despite the abundance of available data. COINSTAC (The Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation) is a platform that successfully tackles these challenges through federated analysis, allowing researchers to analyze datasets without publicly sharing their data. This paper presents a significant enhancement to the COINSTAC platform: COINSTAC Vaults (CVs). CVs are designed to further reduce barriers by hosting standardized, persistent, and highly-available datasets, while seamlessly integrating with COINSTAC's federated analysis capabilities. CVs offer a user-friendly interface for self-service analysis, streamlining collaboration, and eliminating the need for manual coordination with data owners. Importantly, CVs can also be used in conjunction with open data as well, by simply creating a CV hosting the open data one would like to include in the analysis, thus filling an important gap in the data sharing ecosystem. We demonstrate the impact of CVs through several functional and structural neuroimaging studies utilizing federated analysis showcasing their potential to improve the reproducibility of research and increase sample sizes in neuroimaging studies

Tunable magnetocaloric effect around room temperature by Fe doping in Mn0.98Cr(0.02-x)FexAs compound

In this work, we present an investigation of the magnetic and magnetocaloric properties of Mn0.98Cr(0.02-x)FexAs compounds with x = 0.002, 0.005 and 0.010. Our findings show that as Fe content increases the unit cell volume decreases, which indicates that Fe doping emulates the pressure effect on the crystalline structure. The transition temperature TC decreases as x increases and it can be set at approximate value of room temperature by changing the doping level. In addition, the magnetic entropy change ΔSM was determined using a discontinuous measurement protocol, and realistic values from the magnetocaloric effect presented by MnAs-type compounds under pressure (emulated pressure) could be obtained. The values of ΔSMMAX are very large, around −11 Jkg−1K−1 with ΔH = 15 kOe, which is higher than that observed for most compounds with TC around room temperature. However, ΔSM is confined to a narrow temperature range of 11 K. To overcome this drawback, the composition of a theoretical composite formed by our samples was calculated in order to obtain a table-shaped ΔSM curve. The simulated composite showed a high value of full width at half maximum δTFWHM of 33 K, which is much higher than that of single sample.Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro - FAPERJ E-26/110.393/2014, E-16/210.263/2014Coordenação de aperfeiçoamento de pessoal de nivel superior - CAPES 485200/2013-9Fundación de Apoyo a la Investigación del Estado de São Paulo - FAPESP 2012/03480-0Ministerio de Economía y Competitividad MAT2013-45165-

Observation of time-invariant coherence in a nuclear magnetic resonance quantum simulator

The ability to live in coherent superpositions is a signature trait of quantum systems and constitutes an irreplaceable resource for quantum-enhanced technologies. However, decoherence effects usually destroy quantum superpositions. It has been recently predicted that, in a composite quantum system exposed to dephasing noise, quantum coherence in a transversal reference basis can stay protected for indefinite time. This can occur for a class of quantum states independently of the measure used to quantify coherence, and requires no control on the system during the dynamics. Here, such an invariant coherence phenomenon is observed experimentally in two different setups based on nuclear magnetic resonance at room temperature, realising an effective quantum simulator of two- and four-qubit spin systems. Our study further reveals a novel interplay between coherence and various forms of correlations, and highlights the natural resilience of quantum effects in complex systems

Is the expansion of sugarcane over pasturelands a sustainable strategy for Brazil's bioenergy industry?

The authors gratefully thank the São Paulo Research Foundation (FAPESP) (grants # 2014/08632-9 # 2015/14122-6, # 2013/17581-6, # 2014/16612-8 and 2018/09845-7) for the scholarship granted while this research was carried out, and CNPq (grants # 402992/2013-0 and # 311661/2014-9) for the financial support of the present research. Anonymous reviewers are also thanked for their valuable criticisms and comments, which led to substantial improvements of this manuscript.Peer reviewedPostprintPostprin

Genome-Wide Analysis in Brazilian Xavante Indians Reveals Low Degree of Admixture

Characterization of population genetic variation and structure can be used as tools for research in human genetics and population isolates are of great interest. The aim of the present study was to characterize the genetic structure of Xavante Indians and compare it with other populations. The Xavante, an indigenous population living in Brazilian Central Plateau, is one of the largest native groups in Brazil. A subset of 53 unrelated subjects was selected from the initial sample of 300 Xavante Indians. Using 86,197 markers, Xavante were compared with all populations of HapMap Phase III and HGDP-CEPH projects and with a Southeast Brazilian population sample to establish its population structure. Principal Components Analysis showed that the Xavante Indians are concentrated in the Amerindian axis near other populations of known Amerindian ancestry such as Karitiana, Pima, Surui and Maya and a low degree of genetic admixture was observed. This is consistent with the historical records of bottlenecks experience and cultural isolation. By calculating pair-wise F-st statistics we characterized the genetic differentiation between Xavante Indians and representative populations of the HapMap and from HGDP-CEPH project. We found that the genetic differentiation between Xavante Indians and populations of Ameridian, Asian, European, and African ancestry increased progressively. Our results indicate that the Xavante is a population that remained genetically isolated over the past decades and can offer advantages for genome-wide mapping studies of inherited disorders.Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (Fapesp)Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq)Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq)INCT Obesidade e DiabetesINCT- Obesidade e Diabete

A large, curated, open-source stroke neuroimaging dataset to improve lesion segmentation algorithms.

Accurate lesion segmentation is critical in stroke rehabilitation research for the quantification of lesion burden and accurate image processing. Current automated lesion segmentation methods for T1-weighted (T1w) MRIs, commonly used in stroke research, lack accuracy and reliability. Manual segmentation remains the gold standard, but it is time-consuming, subjective, and requires neuroanatomical expertise. We previously released an open-source dataset of stroke T1w MRIs and manually-segmented lesion masks (ATLAS v1.2, N = 304) to encourage the development of better algorithms. However, many methods developed with ATLAS v1.2 report low accuracy, are not publicly accessible or are improperly validated, limiting their utility to the field. Here we present ATLAS v2.0 (N = 1271), a larger dataset of T1w MRIs and manually segmented lesion masks that includes training (n = 655), test (hidden masks, n = 300), and generalizability (hidden MRIs and masks, n = 316) datasets. Algorithm development using this larger sample should lead to more robust solutions; the hidden datasets allow for unbiased performance evaluation via segmentation challenges. We anticipate that ATLAS v2.0 will lead to improved algorithms, facilitating large-scale stroke research