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Article ; Online: In Vitro Growth of Human Follicles: Current and Future Perspectives.

Malo, Clara / Oliván, Sara / Ochoa, Ignacio / Shikanov, Ariella

International journal of molecular sciences

2024 Volume 25, Issue 3

Abstract: Ovarian tissue cryopreservation is gaining importance as a successful method to restore fertility to girls and young women at high risk of sterility. However, there are concerns regarding the safety of transplantation after ovarian tissue ... ...

Abstract	Ovarian tissue cryopreservation is gaining importance as a successful method to restore fertility to girls and young women at high risk of sterility. However, there are concerns regarding the safety of transplantation after ovarian tissue cryopreservation due to the high risk of reintroducing cancer cells and causing disease recurrence. In these cases, the development of culture systems that support oocyte development from the primordial follicle stage is required. Notable achievements have been reached in human follicle in vitro growth in the past decade. Currently, systems for the in vitro culture of ovarian tissue are based on two-dimensional substrates that do not support the survival of follicles or recapitulate the mechanical heterogenicity in the mammalian ovary. Recognition of the importance of special arrangements between cells has spurred research in three-dimensional culture systems, and the provision of a precise culture system that maximizes the diffusion of nutrients and gases through the follicles has raised interest in advanced biomimetic models. The current review critically examines various culture systems employed for the in vitro development of follicles, with a particular focus on solutions utilizing Organ-on-a-Chip (OOC) technology. The emphasis on OOC technology underscores its role as a promising avenue in ensuring the successful cultivation and maintenance of follicular structures during the culture period.
MeSH term(s)	Animals ; Humans ; Female ; Ovary ; Ovarian Follicle ; Cryopreservation/methods ; Oogenesis ; Mammals
Language	English
Publishing date	2024-01-26
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2019364-6
ISSN	1422-0067 ; 1422-0067 ; 1661-6596
ISSN (online)	1422-0067
ISSN	1422-0067 ; 1661-6596
DOI	10.3390/ijms25031510
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Evaluation of gelatin-based hydrogels for colon and pancreas studies using 3D

Pamplona, Regina / González-Lana, Sandra / Ochoa, Ignacio / Martín-Rapún, Rafael / Sánchez-Somolinos, Carlos

Journal of materials chemistry. B

2024 Volume 12, Issue 12, Page(s) 3144–3160

Abstract: Biomimetic 3D models emerged some decades ago to address 2D cell culture limitations in the field of replicating biological phenomena, structures or functions found in nature. The fabrication of hydrogels for cancer disease research enables the study of ... ...

Abstract	Biomimetic 3D models emerged some decades ago to address 2D cell culture limitations in the field of replicating biological phenomena, structures or functions found in nature. The fabrication of hydrogels for cancer disease research enables the study of cell processes including growth, proliferation and migration and their 3D design is based on the encapsulation of tumoral cells within a tunable matrix. In this work, a platform of gelatin methacrylamide (GelMA)-based photocrosslinked scaffolds with embedded colorectal (HCT-116) or pancreatic (MIA PaCa-2) cancer cells is presented. Prior to cell culture, the mechanical characterization of hydrogels was assessed in terms of stiffness and swelling behavior. Modifications of the UV curing time enabled a fine tuning of the mechanical properties, which at the same time, showed susceptibility to the chemical composition and crosslinking mechanism. All scaffolds displayed excellent cytocompatibility with both tumoral cells while eliciting various cell responses depending on the microenvironment features. Individual and collective cell migration were observed for HCT-116 and MIA PaCa-2 cell lines, highlighting the ability of the colorectal cancer cells to cluster into aggregates of different sizes governed by the surrounding matrix. Additionally, metabolic activity results pointed out to the development of a more proliferative phenotype within stiffer networks. These findings confirm the suitability of the presented platform of GelMA-based hydrogels to conduct 3D cell culture experiments and explore biological processes associated with colorectal and pancreatic cancer.
MeSH term(s)	Humans ; Gelatin/chemistry ; Hydrogels/chemistry ; Cell Culture Techniques ; Pancreas ; Cell Culture Techniques, Three Dimensional ; Colorectal Neoplasms ; Tumor Microenvironment
Chemical Substances	Gelatin (9000-70-8) ; Hydrogels
Language	English
Publishing date	2024-03-20
Publishing country	England
Document type	Journal Article
ZDB-ID	2702241-9
ISSN	2050-7518 ; 2050-750X
ISSN (online)	2050-7518
ISSN	2050-750X
DOI	10.1039/d3tb02640j
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Article ; Online: Performance in Kahoot! activities as predictive of exam performance.

Garza, M C / Olivan, S / Monleón, E / Cisneros, Ana Isabel / García-Barrios, A / Ochoa, I / Whyte, J / Lamiquiz-Moneo, I

BMC medical education

2023 Volume 23, Issue 1, Page(s) 413

Abstract: Background: Game-based learning (GBL) is effective for increasing participation, creativity, and student motivation. However, the discriminative value of GBL for knowledge acquisition has not yet been proven. The aim of this study is to assess the value ...

Abstract	Background: Game-based learning (GBL) is effective for increasing participation, creativity, and student motivation. However, the discriminative value of GBL for knowledge acquisition has not yet been proven. The aim of this study is to assess the value of Kahoot! as a discriminative tool for formative assessment in medical education in two different subjects. Methods: A prospective experimental study was conducted on a sample of 173 students enrolled in neuroanatomy (2021-2022). One hundred twenty-five students individually completed the Kahoot! prior to the final exam. In addition, students enrolled in human histology during two academic courses were included in the study. The control group course (2018-2019) received a traditional teaching methodology (N = 211), while Kahoot! was implemented during 2020-2021 (N = 200). All students completed similar final exams for neuroanatomy and human histology based on theory tests and image exams. Results: The correlation between the Kahoot score and the final grade was analyzed for all students enrolled in neuroanatomy who completed both exercises. The correlation between the Kahoot exercise and the theory test, image exam and final grade was significantly positive in all cases (r = 0.334 p < 0.001, r = 0.278 p = 0.002 and r = 0.355 p < 0.001, respectively). Moreover, students who completed the Kahoot! exercise obtained significantly higher grades in all parts of the exam. Regarding human histology, the theory tests, image exams and final grades were significantly higher when using Kahoot! versus the "traditional" methodology (p < 0.001, p < 0.001 and p = 0.014, respectively). Conclusions: Our study demonstrates for the first time that Kahoot! can be used to improve and predict the final grade in medical education subjects.
MeSH term(s)	Humans ; Educational Measurement/methods ; Prospective Studies ; Students ; Curriculum ; Motivation
Language	English
Publishing date	2023-06-06
Publishing country	England
Document type	Journal Article
ZDB-ID	2044473-4
ISSN	1472-6920 ; 1472-6920
ISSN (online)	1472-6920
ISSN	1472-6920
DOI	10.1186/s12909-023-04379-x
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Article ; Online: Phertilizer: Growing a clonal tree from ultra-low coverage single-cell DNA sequencing of tumors.

Weber, Leah L / Zhang, Chuanyi / Ochoa, Idoia / El-Kebir, Mohammed

PLoS computational biology

2023 Volume 19, Issue 10, Page(s) e1011544

Abstract: Emerging ultra-low coverage single-cell DNA sequencing (scDNA-seq) technologies have enabled high resolution evolutionary studies of copy number aberrations (CNAs) within tumors. While these sequencing technologies are well suited for identifying CNAs ... ...

Abstract	Emerging ultra-low coverage single-cell DNA sequencing (scDNA-seq) technologies have enabled high resolution evolutionary studies of copy number aberrations (CNAs) within tumors. While these sequencing technologies are well suited for identifying CNAs due to the uniformity of sequencing coverage, the sparsity of coverage poses challenges for the study of single-nucleotide variants (SNVs). In order to maximize the utility of increasingly available ultra-low coverage scDNA-seq data and obtain a comprehensive understanding of tumor evolution, it is important to also analyze the evolution of SNVs from the same set of tumor cells. We present Phertilizer, a method to infer a clonal tree from ultra-low coverage scDNA-seq data of a tumor. Based on a probabilistic model, our method recursively partitions the data by identifying key evolutionary events in the history of the tumor. We demonstrate the performance of Phertilizer on simulated data as well as on two real datasets, finding that Phertilizer effectively utilizes the copy-number signal inherent in the data to more accurately uncover clonal structure and genotypes compared to previous methods.
MeSH term(s)	Humans ; Trees ; DNA Copy Number Variations/genetics ; Neoplasms/genetics ; Sequence Analysis, DNA ; High-Throughput Nucleotide Sequencing/methods ; Single-Cell Analysis
Language	English
Publishing date	2023-10-11
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2193340-6
ISSN	1553-7358 ; 1553-734X
ISSN (online)	1553-7358
ISSN	1553-734X
DOI	10.1371/journal.pcbi.1011544
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Article: Effects of Strategic Supplementation with

Castellaro, Giorgio / Ochoa, Isaí / Borie, Consuelo / Parraguez, Víctor H

Animals : an open access journal from MDPI

2022 Volume 12, Issue 22

Abstract: The aim of the present study was to evaluate the effect of two types of nutritional supplementation during late gestation on the chemical composition, energy value, and IgG concentration in the colostrum and the IgG concentration in the blood serum of ... ...

Abstract	The aim of the present study was to evaluate the effect of two types of nutritional supplementation during late gestation on the chemical composition, energy value, and IgG concentration in the colostrum and the IgG concentration in the blood serum of lambs. Pregnant Merino Precoz ewes (
Language	English
Publishing date	2022-11-16
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2606558-7
ISSN	2076-2615
ISSN	2076-2615
DOI	10.3390/ani12223159
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Article ; Online: Moss enables high sensitivity single-nucleotide variant calling from multiple bulk DNA tumor samples.

Zhang, Chuanyi / El-Kebir, Mohammed / Ochoa, Idoia

Nature communications

2021 Volume 12, Issue 1, Page(s) 2204

Abstract: Intra-tumor heterogeneity renders the identification of somatic single-nucleotide variants (SNVs) a challenging problem. In particular, low-frequency SNVs are hard to distinguish from sequencing artifacts. While the increasing availability of multi- ... ...

Abstract	Intra-tumor heterogeneity renders the identification of somatic single-nucleotide variants (SNVs) a challenging problem. In particular, low-frequency SNVs are hard to distinguish from sequencing artifacts. While the increasing availability of multi-sample tumor DNA sequencing data holds the potential for more accurate variant calling, there is a lack of high-sensitivity multi-sample SNV callers that utilize these data. Here we report Moss, a method to identify low-frequency SNVs that recur in multiple sequencing samples from the same tumor. Moss provides any existing single-sample SNV caller the ability to support multiple samples with little additional time overhead. We demonstrate that Moss improves recall while maintaining high precision in a simulated dataset. On multi-sample hepatocellular carcinoma, acute myeloid leukemia and colorectal cancer datasets, Moss identifies new low-frequency variants that meet manual review criteria and are consistent with the tumor's mutational signature profile. In addition, Moss detects the presence of variants in more samples of the same tumor than reported by the single-sample caller. Moss' improved sensitivity in SNV calling will enable more detailed downstream analyses in cancer genomics.
MeSH term(s)	Algorithms ; Carcinoma, Hepatocellular ; Colorectal Neoplasms/genetics ; DNA, Neoplasm/genetics ; Gene Frequency ; Genomics/methods ; Humans ; Leukemia, Myeloid, Acute/genetics ; Liver Neoplasms/genetics ; Mutation ; Nucleotides ; Polymorphism, Single Nucleotide
Chemical Substances	DNA, Neoplasm ; Nucleotides
Language	English
Publishing date	2021-04-13
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-021-22466-9
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Article ; Online: mspack: efficient lossless and lossy mass spectrometry data compression.

Hanau, Felix / Röst, Hannes / Ochoa, Idoia

Bioinformatics (Oxford, England)

2021 Volume 37, Issue 21, Page(s) 3923–3925

Abstract: Motivation: Mass spectrometry (MS) data, used for proteomics and metabolomics analyses, have seen considerable growth in the last years. Aiming at reducing the associated storage costs, dedicated compression algorithms for MS data have been proposed, ... ...

Abstract	Motivation: Mass spectrometry (MS) data, used for proteomics and metabolomics analyses, have seen considerable growth in the last years. Aiming at reducing the associated storage costs, dedicated compression algorithms for MS data have been proposed, such as MassComp and MSNumpress. However, these algorithms focus on either lossless or lossy compression, respectively, and do not exploit the additional redundancy existing across scans contained in a single file. We introduce mspack, a compression algorithm for MS data that exploits this additional redundancy and that supports both lossless and lossy compression, as well as the mzML and the legacy mzXML formats. mspack applies several preprocessing lossless transforms and optional lossy transforms with a configurable error, followed by the general purpose compressors gzip or bsc to achieve a higher compression ratio. Results: We tested mspack on several datasets generated by commonly used MS instruments. When used with the bsc compression backend, mspack achieves on average 76% smaller file sizes for lossless compression and 94% smaller file sizes for lossy compression, as compared with the original files. Lossless mspack achieves 10-60% lower file sizes than MassComp, and lossy mspack compresses 36-60% better than the lossy MSNumpress, for the same error, while exhibiting comparable accuracy and running time. Availability and implementation: mspack is implemented in C++ and freely available at https://github.com/fhanau/mspack under the Apache license. Supplementary information: Supplementary data are available at Bioinformatics online.
MeSH term(s)	Data Compression/methods ; Software ; High-Throughput Nucleotide Sequencing/methods ; Algorithms ; Mass Spectrometry
Language	English
Publishing date	2021-09-01
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btab636
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Article ; Online: Exposure to Zinc Oxide Nanoparticles Increases Estradiol Levels and Induces an Antioxidant Response in Antral Ovarian Follicles In Vitro.

Santacruz-Márquez, Ramsés / Flaws, Jodi A / Sánchez-Peña, Luz Del Carmen / Hernández-Ochoa, Isabel

Toxics

2023 Volume 11, Issue 7

Abstract: The use of zinc oxide nanoparticles (ZnO NP) in consumer products is increasing, raising concern about their potential toxicity to human health. Nanoparticles have endocrine disrupting effects and can induce oxidative stress, leading to biomolecule ... ...

Abstract	The use of zinc oxide nanoparticles (ZnO NP) in consumer products is increasing, raising concern about their potential toxicity to human health. Nanoparticles have endocrine disrupting effects and can induce oxidative stress, leading to biomolecule oxidation and cell dysfunction. The ovary is one of the most important endocrine organs in female reproduction. Nanoparticles accumulate in the ovary, but it is unknown whether and how exposure to these materials disrupts antral follicle functions. Thus, this study tested the hypothesis that the in vitro exposure to ZnO NPs affects the steroidogenic pathway and induces oxidative stress in ovarian antral follicles. Antral follicles from CD-1 mice were cultured with ZnO NPs (5, 10, and 15 µg/mL) for 96 h. ZnO NP exposure did not affect apoptosis and cell cycle regulators at any of the tested concentrations. ZnO NP exposure at low levels (5 µg/mL) increased aromatase levels, leading to increased estradiol levels and decreased estrogen receptor alpha (
Language	English
Publishing date	2023-07-12
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2733883-6
ISSN	2305-6304 ; 2305-6304
ISSN (online)	2305-6304
ISSN	2305-6304
DOI	10.3390/toxics11070602
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Article ; Online: Fitting a collider in a quantum computer: tackling the challenges of quantum machine learning for big datasets.

Peixoto, Miguel Caçador / Castro, Nuno Filipe / Crispim Romão, Miguel / Oliveira, Maria Gabriela Jordão / Ochoa, Inês

Frontiers in artificial intelligence

2023 Volume 6, Page(s) 1268852

Abstract: Current quantum systems have significant limitations affecting the processing of large datasets with high dimensionality, typical of high energy physics. In the present paper, feature and data prototype selection techniques were studied to tackle this ... ...

Abstract	Current quantum systems have significant limitations affecting the processing of large datasets with high dimensionality, typical of high energy physics. In the present paper, feature and data prototype selection techniques were studied to tackle this challenge. A grid search was performed and quantum machine learning models were trained and benchmarked against classical shallow machine learning methods, trained both in the reduced and the complete datasets. The performance of the quantum algorithms was found to be comparable to the classical ones, even when using large datasets. Sequential Backward Selection and Principal Component Analysis techniques were used for feature's selection and while the former can produce the better quantum machine learning models in specific cases, it is more unstable. Additionally, we show that such variability in the results is caused by the use of discrete variables, highlighting the suitability of Principal Component analysis transformed data for quantum machine learning applications in the high energy physics context.
Language	English
Publishing date	2023-12-15
Publishing country	Switzerland
Document type	Journal Article
ISSN	2624-8212
ISSN (online)	2624-8212
DOI	10.3389/frai.2023.1268852
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Article ; Online: NetActivity enhances transcriptional signals by combining gene expression into robust gene set activity scores through interpretable autoencoders.

Ruiz-Arenas, Carlos / Marín-Goñi, Irene / Wang, Liewei / Ochoa, Idoia / Pérez-Jurado, Luis A / Hernaez, Mikel

Nucleic acids research

2024

Abstract: Grouping gene expression into gene set activity scores (GSAS) provides better biological insights than studying individual genes. However, existing gene set projection methods cannot return representative, robust, and interpretable GSAS. We developed ... ...

Abstract	Grouping gene expression into gene set activity scores (GSAS) provides better biological insights than studying individual genes. However, existing gene set projection methods cannot return representative, robust, and interpretable GSAS. We developed NetActivity, a machine learning framework that generates GSAS based on a sparsely-connected autoencoder, where each neuron in the inner layer represents a gene set. We proposed a three-tier training that yielded representative, robust, and interpretable GSAS. NetActivity model was trained with 1518 GO biological processes terms and KEGG pathways and all GTEx samples. NetActivity generates GSAS robust to the initialization parameters and representative of the original transcriptome, and assigned higher importance to more biologically relevant genes. Moreover, NetActivity returns GSAS with a more consistent definition and higher interpretability than GSVA and hipathia, state-of-the-art gene set projection methods. Finally, NetActivity enables combining bulk RNA-seq and microarray datasets in a meta-analysis of prostate cancer progression, highlighting gene sets related to cell division, key for disease progression. When applied to metastatic prostate cancer, gene sets associated with cancer progression were also altered due to drug resistance, while a classical enrichment analysis identified gene sets irrelevant to the phenotype. NetActivity is publicly available in Bioconductor and GitHub.
Language	English
Publishing date	2024-04-10
Publishing country	England
Document type	Journal Article
ZDB-ID	186809-3
ISSN	1362-4962 ; 1362-4954 ; 0301-5610 ; 0305-1048
ISSN (online)	1362-4962 ; 1362-4954
ISSN	0301-5610 ; 0305-1048
DOI	10.1093/nar/gkae197
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Zs.A 1067: Show issues

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