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Functional differentiation of human dental pulp stem cells into neuron-like cells exhibiting electrophysiological activity
No full textBackground and aim:
Human dental pulp stem cells (hDPSCs) constitute a promising alternative for central nervous system (CNS) cell therapy. Unlike other human stem cells, hDPSCs can be differentiated, without genetic modification, to neural cells that secrete neuroprotective factors. However, a better understanding of their real capacity to give rise to functional neurons and integrate into synaptic networks is still needed. For that, ex vivo differentiation protocols must be refined, especially to avoid the use of fetal animal serum. The aim of our study is to improve existing differentiation protocols of hDPSCs into neuron-like cells.
Methods:
We compared the effects of the (1) absence or presence of fetal serum during the initial expansion phase as a step prior to switching cultures to neurodifferentiation media. We (2) improved hDPSC neurodifferentiation by adding retinoic acid (RA) and potassium chloride (KCl) pulses for 21 or 60 days and characterized the results by immunofluorescence, digital morphometric analysis, RT-qPCR and electrophysiology.
Results:
We found that neural markers like Nestin, GFAP, S100β and p75NTR were expressed differently in neurodifferentiated hDPSC cultures depending on the presence or absence of serum during the initial cell expansion phase. In addition, hDPSCs previously grown as spheroids in serum-free medium exhibited in vitro expression of neuronal markers such as doublecortin (DCX), neuronal nuclear antigen (NeuN), Ankyrin-G and MAP2 after neurodifferentiation. Presynaptic vGLUT2, Synapsin-I, and excitatory glutamatergic and inhibitory GABAergic postsynaptic scaffold proteins and receptor subunits were also present in these neurodifferentiated hDPSCs. Treatment with KCl and RA increased the amount of both voltage-gated Na+ and K+ channel subunits in neurodifferentiated hDPSCs at the transcript level. Consistently, these cells displayed voltage-dependent K+ and TTX-sensitive Na+ currents as well as spontaneous electrophysiological activity and repetitive neuronal action potentials with a full baseline potential recovery.
Conclusion:
Our study demonstrates that hDPSCs can be differentiated to neuronal-like cells that display functional excitability and thus evidence the potential of these easily accessible human stem cells for nerve tissue engineering. These results highlight the importance of choosing an appropriate culture protocol to successfully neurodifferentiate hDPSCs.University of the Basque Country UPV/EHU (grant COLAB22/07 to J.R.P.).
Basque Government (IT1751-22; to G.I.; IT1473-22, to S.M.; ELKARTEK program MYOZET KK-2024/00111 to G.I.; PIBA_2023_1_0046 to S.M.; “Strengthening strategic health research” program No. 2023333035 to J.R.P.; 2023111031 to S.M.).
MCIN/AEI/https://doi.org/10.13039/501100011033 and by the European Union (NextGenerationEU) “Plan de Recuperación Transformación y Resiliencia” (PID2019-104766RB-C21 to J.R.P. and PID2023-152704OB-I00 to J.R.P. and G.I.).
Instituto de Salud Carlos III and co-founded by the European Union (PI21/00629 to S.M.)
POLIMERBIO SL (UPV/EHU contract 2023.0012 to J.R.P.)
ARSEP Foundation (ARSEP-1310 to S.M.
Residual-based attention Physics-informed Neural Networks for spatio-temporal ageing assessment of transformers operated in renewable power plants
No full textTransformers are crucial for reliable and efficient power system operations, particularly in supporting the integration of renewable energy. Effective monitoring of transformer health is critical to maintain grid stability and performance. Thermal insulation ageing is a key transformer failure mode, which is generally tracked by monitoring the hotspot temperature (HST). However, HST measurement is complex, costly, and often estimated from indirect measurements. Existing HST models focus on space-agnostic thermal models, providing worst-case HST estimates. This article introduces a spatio-temporal model for transformer winding temperature and ageing estimation, which leverages physics-based partial differential equations (PDEs) with data-driven Neural Networks (NN) in a Physics Informed Neural Networks (PINNs) configuration to improve prediction accuracy and acquire spatio-temporal resolution. The computational accuracy of the PINN model is improved through the implementation of the Residual-Based Attention (PINN-RBA) scheme that accelerates the PINN model convergence. The PINN-RBA model is benchmarked against self-adaptive attention schemes and classical vanilla PINN configurations. For the first time, PINN based oil temperature predictions are used to estimate spatio-temporal transformer winding temperature values, validated through PDE numerical solution and fiber optic sensor measurements. Furthermore, the spatio-temporal transformer ageing model is inferred, which supports transformer health management decision-making. Results are validated with a distribution transformer operating on a floating photovoltaic power plant.This research was funded by the Department of Education of the Basque Government (EJ-GV), IKUR Strategy and by the EU NextGenerationEU/PRTR and Spanish State Research Agency (AEI) (grant No. CPP2021-008580). J. I. A. acknowledges financial support (FS) from AEI, Ramón y Cajal Fellowship (grant number RYC2022-037300-I), co-funded by MCIU/AEI/10.13039/501100011033 and FSE+; and from the EJ-GV through the Elkartek (grant number KK-2024/00030) and Consolidated Research Group (grant No. IT1504-22) programs. KM acknowledges FS from Vinnova (grant No. 2021-03748 & 2023-00241). DP acknowledges FS from PID2023-146678OB-I00 funded by MICIU/AEI/10.13039/501100011033 and by the EU NextGenerationEU/PRTR; “BCAM Severo Ochoa” accreditation of excellence CEX2021-001142-S funded by MICIU/AEI/10.13039/501100011033; EJ-GV through the BERC 2022–2025; Elkartek (grant No. KK-2023/00012 & KK-2024/00086); and Consolidated Research Group MATHMODE (IT1456-22) programs. MS acknowledges FS from HORIZON-CL4-2022-QUANTUM01-SGA project 101113946 OpenSuperQPlus100 EU Flagship on Quantum Tech., AEI grants RYC-2020-030503-I & PID2021-125823NA-I00 MCIN/AEI/10.13039/501100011033, “ERDF A way of making EU”, “ERDF Invest in your Future”, and EJ-GV (grant No. IT1470-22). The authors would like to thank Iker Lasa at Tecnalia Research & Innovation for his comments and useful discussions
CNN-aided self-interference estimation for in-band full-duplex systems
No full textModern radio access technologies approach Shannon’s limit, necessitating innovative methods for enhanced spectral efficiency. In-band full-duplex (IBFD) can double the spectral efficiency, enabling simultaneous transmission and reception over the same time-frequency resource. IBFD faces the challenge of self-interference, which has to be canceled by up to 100 dB. This paper estimates the loopback channel through convolutional neural networks (CNNs), which leverage the natural signal structure of wireless channels, effectively mapping time-frequency features. We test the method via simulations in two measured channels, showing cancellations of up to 52 dB
Resting state BOLD-perfusion coupling patterns using multiband multi-echo pseudo-continuous arterial spin label imaging
No full textPublished: 15 January 2025The alteration of neurovascular coupling (NVC), where acute localized blood flow increases
following neural activity, plays a key role in several neurovascular processes including aging and
neurodegeneration. While not equivalent to NVC, the coupling between simultaneously measured
cerebral blood flow (CBF) with arterial spin labeling (ASL) and blood oxygenation dependent (BOLD)
signals, can also be affected. Moreover, the acquisition of BOLD data allows the assessment of resting
state (RS) fMRI metrics. In this study a multiband, multi-echo (MBME) pseudo-continuous ASL (pCASL)
sequence was used to collect simultaneous BOLD and ASL data in a group of healthy control subjects,
and the patterns of BOLD-CBF coupling were evaluated. Coupling was also correlated with the BOLD
RS measures. The variability, reproducibility, and reliability of the metrics were also computed in a
multi-session subgroup. Areas of higher coupling were observed in the visual, motor, parietal, and
frontal cortices and corresponded to major brain networks. Areas of significant correlation between
coupling and BOLD RS measures corresponded to areas of heightened coupling. Higher variability and
lower reliability were found for coupling metrics compared to BOLD RS metrics. These results indicate
BOLD-CBF coupling metrics may be useful for studying neurovascular physiology.This work was funded by a research grant from GE Healthcare to Yang Wang
On the analysis of adapting deep learning methods to hyperspectral imaging. Use case for WEEE recycling and dataset
No full textHyperspectral imaging, a rapidly evolving field, has witnessed the ascendancy of deep learning techniques, supplanting classical feature extraction and classification methods in various applications. However, many researchers employ arbitrary architectures for hyperspectral image processing, often without rigorous analysis of the interplay between spectral and spatial information. This oversight neglects the implications of combining these two modalities on model performance, consumption, and inference time.
This paper evaluates the impact of including different spatial (visual texture) and spectral (captured spectral information) features on deep learning architectures for hyperspectral image segmentation. To this end, it presents different architectural configurations with varying levels of spectral and spatial information and are evaluated in terms of identification performance, energy consumption, and inference time. Additionally, the transferability of knowledge from large pre-trained image foundation models, originally designed for RGB images, to the hyperspectral domain is explored.
Results show that incorporating spatial information alongside spectral data leads to improved segmentation results. However, not all spectral wavelengths are necessary to obtain the optimal performance/energy consumption ratio, which is required for faster and more carbon-neutral models. Training foundation models from the RGB domain leads to lower performance and higher energy consumption models with longer inference times. It is also essential to further develop novel architectures that integrate spectral and spatial information and adapt RGB foundation models to the hyperspectral domain.
Furthermore, this paper contributes to the field by cleaning and publicly releasing the Tecnalia WEEE Hyperspectral dataset. This dataset contains different non-ferrous fractions of Waste Electrical and Electronic Equipment (WEEE), including Copper, Brass, Aluminum, Stainless Steel, and White Copper, spanning the range of 400 to 1000 nm.Some authors have received support by the Elkartek Programme, Basque Government (Spain) (SMART-EYE (KK-2023/00021) )
Mujeres, nobleza y herencia. La pervivencia de la discriminación de género por encima de la ley y el derecho. Mallorca (1760-1930)
No full textSe analizan los principales roles hereditarios asumidos por las mujeres de la nobleza desde la etapa final del Antiguo Régimen hasta la década de 1930. Por un lado, el de herederas usufructuarias y garantes de los linajes y los patrimonios de sus maridos e hijos/as menores de edad. Por otra parte, el de herederas propietarias de sus respectivas Casas por razones de incompatibilidad de linajes o falta de sucesión agnaticia La perspectiva de género permite constatar su relegación generalizada en las sucesiones hereditarias anteriores y posteriores a las reformas legislativas aprobadas durante los siglos XIX y XX. En cualquier caso, su exclusión resulta clave para entender la pervivencia en el tiempo de los patrimonios nobiliarios y la preservación de los códigos de conducta utilizados por la nobleza para perpetuarse como clase dominant
Early Childhood Preservice teachers’ understanding of the infection model and its application in diaper changing.
No full textThis study explores the understanding and application of the infection
model, specifically focusing on cystitis caused by Escherichia coli
(E. coli) in a diaper-changing context, among preservice teachers
(PSTs). Fifty-four PSTs participated in a modeling sequence including
experimentation. The PSTs’ comprehension of infection mechanisms
and the human body’s response to bacterial infections were analyzed
using a framework that addressed components, mechanisms, and
phenomena related to the infection model. Data consisted of six
tasks (two initial, two intermediate, two final). Findings show that
PSTs improved the understanding of the infection model, especially
in the components and mechanisms dimension. The experimentation
mainly facilitated a deeper knowledge about E. coli. Nevertheless,
although the PSTs learned the proper diaper-changing techniques to
prevent infections, in some cases they failed to justify their actions
using the infection model.This study was developed within the KOMATZI (GIU21/031) research group and the research
project PID2022–137010OB–I00 funded by MCIN/AEI/10.13039/501100011033/ FEDER
What Predicts Early Math in Autism? A Study of Cognitive and Linguistic Factors
No full textThis study aimed to examine early mathematical abilities in young children with autism aged four to seven without intellectual disabilities and their connection with autism severity, non-verbal intelligence, and linguistic abilities (receptive vocabulary and grammar). The study involved 42 children with autism. We assessed participants’ cognitive, mathematical, and linguistic abilities. Their mathematical performance was compared with that of typically developing children using standardized measures. Statistical analyses were conducted to identify potential cognitive or linguistic differences across groups based on mathematical performance, and to determine predictive factors for mathematical abilities in children with autism. The findings indicated a higher prevalence of mathematical difficulties among the participants compared to typically developing children. A classification based on mathematical performance revealed statistically significant differences in cognitive and linguistic variables across groups, particularly in the low-performance group. However, no significant differences were found according to autism severity between the groups. The analysis further identified that a combination of visuo-spatial and linguistic abilities was the most predictive factor for mathematical performance. The study suggests that young children with autism without intellectual disabilities may be more likely to experience mathematical difficulties compared to typically developing children. Assessing cognitive and linguistic abilities could serve as a predictive measure for mathematical difficulties of children with autism, even without a formal diagnosis. Future research, with larger samples or longitudinal approaches, could validate these findings or explore which specific mathematical abilities are more related to non-verbal intelligence and which ones to structural languageThis work was supported by the projects PID2022-136246NB-I00, funded by MICIU/AEI/10.13039/501100011033 https://doi.org/10.13039/501100011033 and FEDER, UE; SUBVTC-2023-0014, funded by the Government of Cantabria; and Grant IT1537-22 to the Theoretical Linguistics Group, funded by the Basque Government
Nazioarteko egitate ez-zilegia burutzeko laguntza edo sostengua ematetik eratortzen den nazioarteko erantzukizuna: 2001eko Artikuluen Proiektuko 16. artikuluaren azterketa gaurkotua
No full textAzterlan honetan, nazioarteko egitate ez-zilegiak burutzen direnean hirugarren estatuek ematen duten laguntza eta sostenguak duten ondorioak aztertu dira nazioarteko erantzukizunaren ikuspuntutik. Horretarako, estatuak nazioarteko egitate ez-zilegiengatik duen erantzukizunari buruzko 2001eko Artikuluen Proiektuaren 16. artikuluaren azterketa gaurkotua egin da, nazioarteko doktrina eta jurisprudentzian oinarrituz, eta gaurkotasuna duten adibideak eztabaidara ekarriz. 16. artikuluak, izan ere, funtsezko marko juridikoa ekarri du berekin nazioarteko konplizitatearen eremuan. Baita ere, dena den, eztabaida juridiko ugarien objektua izan da.
Hizkuntza: euskara
Análisis del reciente contexto inflacionista y de la política monetaria desde el modelo IS-LM-PC
No full textRecientemente, en el último cuatrienio post-pandémico ha tenido lugar un periodo inflacionista a nivel internacional y, en particular, en la zona del euro, que ha conducido a los diferentes bancos centrales y, concretamente, al Banco Central Europeo a desplegar medidas de política monetaria de carácter restrictivo a fin de contener la escalada de precios y doblegar la inflación. Ello ha tenido como correlato, no sólo la neutralización del episodio inflacionista, sino también el encarecimiento de las condiciones de financiación, tanto para las empresas como las familias e inclusive para los Estados, con todo lo que ello supone. El presente trabajo pretende analizar esta experiencia desde el prisma del modelo macroeconómico IS-LM-PC