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Vascular smooth muscle cell dysfunction contribute to neuroinflammation and Tau hyperphosphorylation in Alzheimer disease
No full textThis research was funded by Consejo Nacional de Ciencia, Tecnologia e Innovacion Tecnologica de Peru (grant N~ 024-2019-Fondecyt-BM-INC.INV and CONCYTEC-FONDECYT-E038-01).Despite the emerging evidence implying early vascular contributions to neurode-generative syndromes, the role of vascular smooth muscle cells (VSMCs) in the pathogenesis of Alzheimer disease (AD) is still not well understood. Herein, we show that VSMCs in brains of patients with AD and animal models of the disease are deficient in multiple VSMC contractile markers which correlated with Tau accumulation in brain arterioles. Ex vivo and in vitro experiments demonstrated that VSMCs undergo dramatic phenotypic transitions under AD-like conditions, adopting pro-inflammatory phenotypes. Notably, these changes coincided with Tau hyperphosphorylation at residues Y18, T205, and S262. We also observed that VSMC dysfunction occurred in an age-dependent manner and that expression of Sm22a protein was inversely correlated with CD68 and Tau expression in brain arterioles of the 3xTg-AD and 5xFAD mice. Together, these findings further support the contribution of dysfunctional VSMCs in AD pathogenesis and nominate VSMCs as a potential therapeutic target in AD.Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - Concyte
“Masato de Yuca” and “Chicha de Siete Semillas” Two Traditional Vegetable Fermented Beverages from Peru as Source for the Isolation of Potential Probiotic Bacteria
No full textOpen Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This research was funded by the Ibero-American Programme on Science and Technology for Development (CYTED), grant number 917PTE0537. The Spanish team was funded by the “Agencia Estatal de Investigación” and the “Fondo Europeo de Desarrollo Regional” (AEI/FEDER, UE), grant number PCIN2017-075″. The Peruvian team was funded by the National Council of Science and Technology and Innovation of Peru through its execution unit National Fund for Scientific, Technological and Technological Innovation (CONCYTEC/FONDECYT), grant No. 001–2017.In this work, two Peruvian beverages “Masato de Yuca,” typical of the Amazonian communities made from cassava (Manihot esculenta), and “Chicha de Siete Semillas,” made from different cereal, pseudo-cereal, and legume flours, were explored for the isolation of lactic acid bacteria after obtaining the permission of local authorities following Nagoya protocol. From an initial number of 33 isolates, 16 strains with different RAPD- and REP-PCR genetic profiles were obtained. In Chicha, all strains were Lactiplantibacillus plantarum (formerly Lactobacillus plantarum), whereas in Masato, in addition to this species, Limosilactobacillus fermentum (formerly Lactobacillus fermentum), Pediococcus acidilactici, and Weissella confusa were also identified. Correlation analysis carried out with their carbohydrate fermentation patterns and enzymatic profiles allowed a clustering of the lactobacilli separated from the other genera. Finally, the 16 strains were submitted to a static in vitro digestion (INFOGEST model) that simulated the gastrointestinal transit. Besides, their ability to adhere to the human epithelial intestinal cell line HT29 was also determined. Following both procedures, the best probiotic candidate was Lac. plantarum Ch13, a robust strain able to better face the challenging conditions of the gastrointestinal tract and showing higher adhesion ability to the intestinal epithelium in comparison with the commercial probiotic strain 299v. In order to characterize its benefit for human health, this Ch13 strain will be deeply studied in further works. © 2021, The Author(s).Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - Concyte
An Evaluation of Physiological Public Datasets for Emotion Recognition Systems
No full textAcknowledgment. A. Mendoza, A. Cuno, N. Condori-Fernandez and W. Ramos acknowledge financial support from the “Proyecto Concytec - Banco Mundial, Mejo-ramiento y Ampliación de los Servicios del Sistema Nacional de Ciencia Tecnología e Innovación Tecnológica” 8682-PE, through its executing unit FONDECYT [Contract N? 014-2019-FONDECYT-BM-INC.INV]. Also, this work has been partially supported by Datos 4.0 (TIN2016-78011-C4-1-R) funded by MINECO-AEI/FEDER-UE.[Background] The performance of emotion recognition systems depends heavily on datasets used in their training, validation, or testing stages. [Aims] This research aims to evaluate the extent to which public available physiological datasets created for emotion recognition systems meet a set of reference requirements. [Method] Firstly, we analyze the applicability of some reference requirements proposed for stress datasets and adjust the corresponding evaluation criteria. Secondly, nine public physiological datasets were identified from a previous survey. [Results] None of the evaluated datasets satisfy all the reference requirements in order to be considered as a reference dataset for being used in the construction of reliable emotion recognition systems. [Conclusion] Although the evaluated datasets do not support the whole reference requirements, they provide a baseline for further development. Also, a greater effort is needed to establish specific reference requirements that can appropriately guide the creation of physiological datasets for emotion recognition systems. © 2021, Springer Nature Switzerland AG.Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - Concyte
Bending collapse analysis for thin and medium-thin-walled square and rectangular hollow shapes
No full textD. Lavayen would like to recognize the financial support provided by CONCYTEC (Peru) and The World Bank, through the Pontifical Catholic University of Peru and FONDECYT (Peru): ?Funding Contract N?10-2018-FONDECYT/WB PhD programs in strategic and general areas?. Part of this work has also been supported by Comunidad de Madrid - multiannual agreement with UC3M (?Excelencia para el Profesorado Universitario? - EPUC3M21) - Fifth regional research plan 2016-2020, The authors would also like to thank Dr. M. A. Martinez-Casanova from the Materials Science and Engineering and Chemical Engineering Department at UC3M for his help during testing. All authors approved the version of the manuscript to be published.Thin-walled hollow shapes are of great interest in many industries with weight constraints due to their availability, low price, and strength to weight ratio. However, they are also prone to localized bending collapse, which can be used as an energy absorption mechanism during deformation. Up until now, industrial applications have relied on numerical simulations, non-standardized tests, and a handful of theories to address the bending collapse behavior. In this paper, a modification to the most widely used theory is presented and adapted for hollow shapes with greater thickness that cannot be considered “thick”. To verify the accuracy of the proposed modification, a comparison with a detailed FEM model, validated through various three-point bending collapse experimental tests, has been performed. The results seem to show that the proposed modifications can predict the maximum load and collapse stage behavior of hollow shapes with more accuracy than the original analytical model. Thus, the proposed modification may be used to predict the collapse behavior of commercially available square and rectangular hollow shapes in different fields of application. © 2021 Elsevier LtdConsejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - Concyte
Comparative Study of Spatial Prediction Models for Estimating PM2.5 Concentration Level in Urban Areas
No full textAcknowledgment. The authors gratefully acknowledge financial support by Fondo Nacional de Desarrollo Científico, Tecnológico y de Innovación Tecnológica (Fondecyt) -Mundial Bank (Grant: 50-2018-FONDECYT-BM-IADT-MU).Having accurate spatial prediction models of air pollutant concentrations can be very helpful to alleviate the shortage of monitoring stations, specially in low-to-middle income countries. However, given the large diversity of model types, both statistical, numerical and machine learning (ML) based, it is not clear which of them are most suitable for this task. In this paper we study the predictive capabilities of common machine learning methods for the spatial prediction of PM2.5 concentration level. Three relevant factors were scrutinized: the extent to which meteorological variables impact the prediction performance; the effect of variable normalization by inverse distance weighting (IDW); and the number of neighborhood stations needed to maximize predictive performance. Results in a dataset from Beijing monitoring network show that simple models like Linear Regresors trained on IDW normalized variables can cope with this task. Some knowledge have been derived to guide the construction of competent models for spatial prediction of PM2.5 concentrations with ML-based methods. © 2021, Springer Nature Switzerland AG.Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - Concyte
Convective drying of cambuci, a native fruit from the Brazilian Atlantic Forest: Effect of pretreatments with ethanol and freezing
No full textThe authors are grateful to the S?o Paulo Research foundation (FAPESP, Brazil): projects n? 2014/12606-3 and 2019/05043-6; GR Carvalho post-doctoral fellowship (2018/17844-0); the ?Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior?Brasil (CAPES)?: BO Gomes (88887.485030/2020-00), JS Guedes (88887.513566/2020-00) and KC Santos (88882.378385/2019-01) M.Sc. and Ph.D. Scholarships; the National Council for Scientific and Technological Development (CNPq, Brazil): BS Bitencourt (132297/2019-1) M.Sc. Scholarship and PED Augusto productivity grant (310839/2020-3); the Fondo Nacional de Desarrollo Cient?fico, Tecnol?gico y de Innovaci?n Tecnol?gica (FONDECYT, Peru) from the ?Consejo Nacional de Ciencia, Tecnolog?a e Innovaci?n Tecnol?gica? (CONCYTEC, Peru): project n? 409-2019-FONDECYT; the Universidad Privada del Norte (UPN, Peru): project n? 20201005. The authors are also grateful for the valuable help of B.Sc. Isabela Silveira and N?colas Gon?alves Borrego, as well as Mr. Paulo Nakanishi from ?Sitio Recanto dos P?ssaros? for providing the fruits.Cambuci is a native fruit from the Brazilian Atlantic Forest, with high sensorial and nutritional potential. However, this fruit is very perishable, which impairs its exploration and study. This work reported the convective drying of cambuci for the first time, as an approach to achieve stability. Moreover, it also evaluated for the first time the combination of ethanol and freezing pretreatments to convective drying. Pretreatments were performed by immersion of fresh and previously frozen and thawed cambuci slices in ethanol (5 min at 25°C). Pretreated samples were then convectively dried (50°C, 1 m/s). Drying time was reduced up to ~36% by combining the pretreatments, which was associated with the reduction in the external resistance to mass transfer, once the convective mass transfer coefficient increased up to 94%. In contrast, pretreatments that include freezing had a greater influence on reducing the internal resistance to mass transfer, increasing the effective diffusive coefficient. In addition, the thermal surface profile evidenced the temperature increased faster and reached high levels in pretreatments that include freezing, which could be correlated to their higher drying rates and structure modifications. The obtained results corroborate the modifications produced by freezing and the effects of ethanol on the surface of samples significantly accelerate the convective drying of cambuci. Practical Applications: The present investigation shows that convective drying is a feasible alternative for cambuci processing. Further, being this fruit very perishable, with short harvest and production far from the markets, freezing is a common practice to preserve them in the farms. Consequently, the impact of this unit operation was also evaluated. In addition, the proposed pretreatments (freezing and ethanol) have great application potential to improve the conventional convective drying of fruits. It has been shown that the combination of pretreatments accelerated drying, reducing the processing time by 36%. © 2021 Wiley Periodicals LLC.Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - Concyte
Emerging contaminants, SARS-COV-2 and wastewater treatment plants, new challenges to confront: A short review
No full textThis study was supported by the Consejo Nacional de Ciencia, Tecnolog?a e Innovaci?n Tecnol?gica (CONCYTEC) and the Fondo Nacional de Desarrollo Cient?fico, Tecnol?gico y de Innovaci?n Tecnol?gica (FONDECYT) - Peru. Grant N? 06-2019-FONDECYT-BM-INC.INV.The current pandemic caused by SARS-CoV-2 has put public health at risk, being wastewater-based epidemiology (WBE) a potential tool in the detection, prevention, and treatment of present and possible future outbreaks, since this virus enters wastewater through various sources such as feces, vomit, and sputum. Thus, advanced technologies such as advanced oxidation processes (AOP), membrane technology (MT) are identified through a systematic literature review as an alternative option for the destruction and removal of emerging contaminants (drugs and personal care products) released mainly by infected patients. The objectives of this review are to know the implications that the new COVID-19 outbreak is generating and will generate in water compartments, as well as the new challenges faced by wastewater treatment plants due to the change in a load of contaminants and the solutions proposed based on the aforementioned technologies to be applied to preserve public health and the environment. © 2021 Elsevier LtdConsejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - Concyte
Global high-risk clone of extended-spectrum ?-lactamase (ESBL)-producing Klebsiella pneumoniae ST307 emerging in livestock in Peru
No full textDGS and JAB were funded by a Sir Henry Dale Fellowship, jointly funded by the Wellcome Trust and Royal Society [Grant 102507/Z/13/Z]. DGS was funded by a Wellcome Trust Senior Research Fellowship [217221/Z/19/Z]. CS, JAB, NF and DGS were also funded by a CONCYTEC-UK Embassy grant [No. 003-2016-FONDECYT]. JAB was funded by the National Fund for Scientific and Technological development of Chile [FONDECYT-Iniciación, grant number 11181017]. DF-C receives a doctoral fellowship from the National Agency for Research and Development (ANID) [process number BCH 72170436]. NL is a research fellow of CNPq [312249/2017-9].Presents a letter about the global high-risk clone of extended-spectrum β-lactamase (ESBL)-producing Klebsiella pneumoniae ST307 emerging in livestock in Peru.Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - Concyte
Model-based analysis of multi-UAV path planning for surveying postdisaster building damage
No full textThis study was partly funded by the Japan Society for the Promotion of Science (JSPS) Kakenhi Program (17H06108 and 21H05001); the Core Research Cluster of Disaster Science; the Tough Cyberphysical AI Research Center at Tohoku University, and the National Program for Scientic Research and Advanced Studies (PROCIEN-CIA/CONCYTEC - PERU) [contract number 038-2019 FONDECYT-BM-INC-INV].Emergency responders require accurate and comprehensive data to make informed decisions. Moreover, the data should be acquired and analyzed swiftly to ensure an efficient response. One of the tasks at hand post-disaster is damage assessment within the impacted areas. In particular, building damage should be assessed to account for possible casualties, and displaced populations, to estimate long-term shelter capacities, and to assess the damage to services that depend on essential infrastructure (e.g. hospitals, schools, etc.). Remote sensing techniques, including satellite imagery, can be used to gathering such information so that the overall damage can be assessed. However, specific points of interest among the damaged buildings need higher resolution images and detailed information to assess the damage situation. These areas can be further assessed through unmanned aerial vehicles and 3D model reconstruction. This paper presents a multi-UAV coverage path planning method for the 3D reconstruction of postdisaster damaged buildings. The methodology has been implemented in NetLogo3D, a multi-agent model environment, and tested in a virtual built environment in Unity3D. The proposed method generates camera location points surrounding targeted damaged buildings. These camera location points are filtered to avoid collision and then sorted using the K-means or the Fuzzy C-means methods. After clustering camera location points and allocating these to each UAV unit, a route optimization process is conducted as a multiple traveling salesman problem. Final corrections are made to paths to avoid obstacles and give a resulting path for each UAV that balances the flight distance and time. The paper presents the details of the model and methodologies, and an examination of the texture resolution obtained from the proposed method and the conventional overhead flight with the nadir-looking method used in 3D mappings. The algorithm outperforms the conventional method in terms of the quality of the generated 3D model. © 2021, The Author(s).Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - Concyte
Optimization of a natural low-calorie antioxidant tea prepared from purple corn (Zea mays L.) cobs and stevia (Stevia rebaudiana Bert.)
No full textThe authors acknowledge INNOVATE-PERU for funding the project “Development of purple corn filters with quince and stevia leaves as a proposal for a fruit infusion with high antioxidant capacity, naturally sweetened and with a high level of pleasure in LECOLE PRODUITS S.A.C.'': contract 027-INNOVATEPERU-PIEC1-2019. Also, A. DÍAZ-GARCÍA recognizes the scholarship from the Concytec-Banco Mundial project (Funds Award Agreement No. 02-2018-FONDECYT-BM), through its executing unit, Fondo Nacional de Desarrollo Científico, Tecnológico y de Innovación Tecnológica (Fondecyt).Purple corn (Zea mays L.) is a crop native to Peru and also widely cultivated in some countries around the world. It contains anthocyanins and other phenolic compounds that help reduce the incidence of a variety of chronic diseases. Here, a natural low-calorie antioxidant purple corn cob and stevia-based tea was optimized after being developed from five ingredients: purple corn cob (PCc), quince (Q), stevia (S), cinnamon (C) and cloves (Cv). A corn fiber filtration bag was selected to package single doses of the tea mixtures, based on the porosity, solid leakage during preparation and infusion absorption spectrum of four different types of bag. The tea was then optimized using an I-optimal mixture design to maximize the antioxidant capacity (AC) and total monomeric anthocyanin (TMA) content of the infusions. The optimum formulation given by the regression model consisted of decimal fractions of 0.8672 for PCc, 0.0464 for Q and 0.0864 for S, with a desirability of 91.2%, AC of 9.51 ± 1.21 μmol TE/mL and TMAs of 98.49 ± 6.00 mg C3GE/L, which were validated. The C and Cv contents were set at 0.0333 and 0.0025 of the total mixture, respectively. © 2021Fondo Nacional de Desarrollo Científico y Tecnológico - Fondecy