Assessing the impact of transcriptomics data analysis pipelines on downstream functional enrichment results.

Transcriptomics is widely used to assess the state of biological systems. There are many tools for the different steps, such as normalization, differential expression, and enrichment. While numerous studies have examined the impact of method choices on differential expression results, little attention has been paid to their effects on further downstream functional analysis, which typically provides the basis for interpretation and follow-up experiments. To address this, we introduce FLOP, a comprehensive nextflow-based workflow combining methods to perform end-to-end analyses of transcriptomics data. We illustrate FLOP on datasets ranging from end-stage heart failure patients to cancer cell lines. We discovered effects not noticeable at the gene-level, and observed that not filtering the data had the highest impact on the correlation between pipelines in the gene set space. Moreover, we performed three benchmarks to evaluate the 12 pipelines included in FLOP, and confirmed that filtering is essential in scenarios of expected moderate-to-low biological signal. Overall, our results underscore the impact of carefully evaluating the consequences of the choice of preprocessing methods on downstream enrichment analyses. We envision FLOP as a valuable tool to measure the robustness of functional analyses, ultimately leading to more reliable and conclusive biological findings.

Development of a crowdsourcing- and gamification-based mobile application to collect epidemiological information and promote healthy lifestyles in Mexico.

We developed a mobile application to promote healthy lifestyles and collect non-communicable disease (NCD) data in Mexico. Its theoretical foundations are supported by a framework-guided literature review. With design sprints, Scrum, Model-View-Controller, and Representational State Transfer architecture, we operationalized evidence-based nutrition/physical activity information into a crowdsourcing- and gamification-based application. The application was piloted for three months to monitor the response of 520 adults. Potential improvements were characterized, considering benchmarking, expert guidance, and standards. Salud Activa (English: Active Health) has two crowdsourcing modules: Nutritional scanner, scanning products' bar codes, providing nutritional data, and allowing new product registry feeding our databases; Surveys, comprising gradually-released NCD questions. Three intervention modules were generated: Drinks diary, a beverage assessment component to receive hydration recommendations; Step counter, monitoring users' steps via Google Fit/Health-iOS; Metabolic Avatar, interconnecting modules and changing as a function of beverage and step records. The 3-month median of Salud Activa use was seven days (IQR = 3-12), up to 35% of participants completed a Survey section, and 157 food products were registered through Nutritional scanner. Better customization might benefit usability and user engagement. Quantitative and qualitative data will enhance Salud Activa's design, user uptake, and efficacy in interventions delivered through this platform.

Complementing Cell Taxonomies with a Multicellular Analysis of Tissues.

The application of single-cell molecular profiling coupled with spatial technologies has enabled charting of cellular heterogeneity in reference tissues and in disease. This new wave of molecular data has highlighted the expected diversity of single-cell dynamics upon shared external queues and spatial organizations. However, little is known about the relationship between single-cell heterogeneity and the emergence and maintenance of robust multicellular processes in developed tissues and its role in (patho)physiology. Here, we present emerging computational modeling strategies that use increasingly available large-scale cross-condition single-cell and spatial datasets to study multicellular organization in tissues and complement cell taxonomies. This perspective should enable us to better understand how cells within tissues collectively process information and adapt synchronized responses in disease contexts and to bridge the gap between structural changes and functions in tissues.

Multicellular factor analysis of single-cell data for a tissue-centric understanding of disease.

Biomedical single-cell atlases describe disease at the cellular level. However, analysis of this data commonly focuses on cell-type-centric pairwise cross-condition comparisons, disregarding the multicellular nature of disease processes. Here, we propose multicellular factor analysis for the unsupervised analysis of samples from cross-condition single-cell atlases and the identification of multicellular programs associated with disease. Our strategy, which repurposes group factor analysis as implemented in multi-omics factor analysis, incorporates the variation of patient samples across cell-types or other tissue-centric features, such as cell compositions or spatial relationships, and enables the joint analysis of multiple patient cohorts, facilitating the integration of atlases. We applied our framework to a collection of acute and chronic human heart failure atlases and described multicellular processes of cardiac remodeling, independent to cellular compositions and their local organization, that were conserved in independent spatial and bulk transcriptomics datasets. In sum, our framework serves as an exploratory tool for unsupervised analysis of cross-condition single-cell atlases and allows for the integration of the measurements of patient cohorts across distinct data modalities.

Application of a Simplex-Centroid Mixture Design to Evaluate the Phenolic Compound Content and Antioxidant Potential of Plants Grown in Mexico.

Nowadays, the food and health industries are generating new products with antioxidant potential; among them are those rich in phenolic compounds that have a beneficial impact on human health. Therefore, the aim of this research was to obtain different types of mixtures from Portulaca oleraceae (P), Chenopodium album (C), Opuntia oligacantha Förster var. Ulapa (O), and Amaranthus tricolor (A) and evaluate the content of total phenols, total flavonoids, and antioxidant potential in order to select the mixture with the highest content of phenolic compounds. An experimental simplex-centroid mixture design with 15 experimental treatments was used; the data were analyzed and adjusted to a quadratic model that allowed for the prediction of the content of phenols, flavonoids, and antioxidant activity using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2'-Azino-bis (3-ethylbenz-thiazoline-6-sulfonic acid) (ABTS) of different experimental mixtures. The results show that the individual components of C and P had the highest content of phenols and antioxidant potential. It was observed that the binary mixtures P-C and P-A presented values of total phenols greater than 11 mg of gallic acid equivalents g-1 DW and values of flavonoids greater than 13 mg of quercetin equivalents g-1 DW. These values were higher than those found in the individual components. The P-C mixture with an antioxidant potential of 66.0 ± 0.07 Trolox equivalents g-1 DW could be used as an additive in food or to obtain a functional food that improves the intake of antioxidant compounds in the population.

Development and applications of a CRISPR activation system for facile genetic overexpression in Candida albicans.

For the fungal pathogen Candida albicans, genetic overexpression readily occurs via a diversity of genomic alterations, such as aneuploidy and gain-of-function mutations, with important consequences for host adaptation, virulence, and evolution of antifungal drug resistance. Given the important role of overexpression on C. albicans biology, it is critical to develop and harness tools that enable the analysis of genes expressed at high levels in the fungal cell. Here, we describe the development, optimization, and application of a novel, single-plasmid-based CRISPR activation (CRISPRa) platform for targeted genetic overexpression in C. albicans, which employs a guide RNA to target an activator complex to the promoter region of a gene of interest, thus driving transcriptional expression of that gene. Using this system, we demonstrate the ability of CRISPRa to drive high levels of gene expression in C. albicans, and we assess optimal guide RNA targeting for robust and constitutive overexpression. We further demonstrate the specificity of the system via RNA sequencing. We highlight the application of CRISPR activation to overexpress genes involved in pathogenesis and drug susceptibility, and contribute toward the identification of novel phenotypes. Consequently, this tool will facilitate a broad range of applications for the study of C. albicans genetic overexpression.

Association between SNPs in Leptin Pathway Genes and Anthropometric, Biochemical, and Dietary Markers Related to Obesity.

Obesity is one of the main public health problems in Mexico and the world and one from which a large number of pathologies derive. Single nucleotide polymorphisms (SNPs) of various genes have been studied and proven to contribute to the development of multiple diseases. SNPs of the leptin pathway have been associated with the control of hunger and energy expenditure as well as with obesity and type 2 diabetes mellitus. Therefore, the present work focused on determining the association between anthropometric markers and biochemical and dietary factors related to obesity and SNPs of leptin pathway genes, such as the leptin gene (LEP), the leptin receptor (LEPR), proopiomelanocortin (POMC), prohormone convertase 1 (PCSK1), and the melanocortin 4 receptor (MC4R). A population of 574 young Mexican adults of both sexes, aged 19 years old on average and without metabolic disorders previously diagnosed, underwent a complete medical and nutritional evaluation, biochemical determination, and DNA extraction from the blood; DNA samples were subsequently genotyped. Association analyses between anthropometric, biochemical, and dietary variables with SNPs were performed using binary logistic regressions (p-value = 0.05). Although the sampled population did not have previously diagnosed diseases, the evaluation results showed that 33% were overweight or obese according to BMI and 64% had non-clinically elevated levels of body fat. From the 74 SNP markers analyzed from the five previously mentioned genes, 62 showed polymorphisms within the sampled population, and only 35 of these had significant associations with clinical variables. The risk associations (OR > 1) occurred between clinical markers with elevated values for waist circumference, waist−height index, BMI, body fat percentage, glucose levels, insulin levels, HOMA-IR, triglyceride levels, cholesterol levels, LDL-c, low HDL-c, carbohydrate intake, and protein intake and SNPs of the LEP, LEPR, PCSK1, and MC4R genes. On the other hand, the protective associations (OR < 1) were associated with markers including elevated values for insulin, HOMA-IR, cholesterol, c-LDL, energy intake > 2440 Kcal/day, and lipid intake and SNPs of the LEP and LEPR genes and POMC. The present study describes associations between SNPs in leptin pathway genes, revealing positive and negative interactions between reported SNPs and the clinical markers related to obesity in a sampled Mexican population. Hence, our results open the door for the further study of new genetic variants and their influence on obesity.

Explainable multiview framework for dissecting spatial relationships from highly multiplexed data.

The advancement of highly multiplexed spatial technologies requires scalable methods that can leverage spatial information. We present MISTy, a flexible, scalable, and explainable machine learning framework for extracting relationships from any spatial omics data, from dozens to thousands of measured markers. MISTy builds multiple views focusing on different spatial or functional contexts to dissect different effects. We evaluated MISTy on in silico and breast cancer datasets measured by imaging mass cytometry and spatial transcriptomics. We estimated structural and functional interactions coming from different spatial contexts in breast cancer and demonstrated how to relate MISTy's results to clinical features.

Affordance Equivalences in Robotics: A Formalism.

Automatic knowledge grounding is still an open problem in cognitive robotics. Recent research in developmental robotics suggests that a robot's interaction with its environment is a valuable source for collecting such knowledge about the effects of robot's actions. A useful concept for this process is that of an affordance, defined as a relationship between an actor, an action performed by this actor, an object on which the action is performed, and the resulting effect. This paper proposes a formalism for defining and identifying affordance equivalence. By comparing the elements of two affordances, we can identify equivalences between affordances, and thus acquire grounded knowledge for the robot. This is useful when changes occur in the set of actions or objects available to the robot, allowing to find alternative paths to reach goals. In the experimental validation phase we verify if the recorded interaction data is coherent with the identified affordance equivalences. This is done by querying a Bayesian Network that serves as container for the collected interaction data, and verifying that both affordances considered equivalent yield the same effect with a high probability.

Toward Self-Aware Robots.

Despite major progress in Robotics and AI, robots are still basically "zombies" repeatedly achieving actions and tasks without understanding what they are doing. Deep-Learning AI programs classify tremendous amounts of data without grasping the meaning of their inputs or outputs. We still lack a genuine theory of the underlying principles and methods that would enable robots to understand their environment, to be cognizant of what they do, to take appropriate and timely initiatives, to learn from their own experience and to show that they know that they have learned and how. The rationale of this paper is that the understanding of its environment by an agent (the agent itself and its effects on the environment included) requires its self-awareness, which actually is itself emerging as a result of this understanding and the distinction that the agent is capable to make between its own mind-body and its environment. The paper develops along five issues: agent perception and interaction with the environment; learning actions; agent interaction with other agents-specifically humans; decision-making; and the cognitive architecture integrating these capacities.

Sobrediagnóstico de amebiasis en niños con disentería / Overdiagnosis of amebiasis in children with dysentery

Existen dos amebas, morfológicamente idénticas, cuyas diferencias determinanque una de ellas, Entamoeba histolytica, pueda ser patógena. La otra, Entamoeba dispar, es inocua.Surgió la presunción de que casos tratados como amebiasis, no lo fueran. Objetivo. Identificar E. histolytica en niños con disenterías supuestamente amebianas. Métodos. Estudio transversal y observacional realizado en Santa Fe, entre marzo de 2005 y noviembre de 2007. En niños de 2 meses a 15 años con disentería y exámenes directos con E. histolytica/dispar, se realizó ELISA para detectar la adhesina de E. histolytica (adhesina Eh) en heces.Se efectuaron coloraciones para amebas, coprocultivos y se registraron datos clínicos.Resultados. De 75 casos estudiados, 35 fueron varones y 40 mujeres, con edad (mediana) de 3 años. Todos presentaron diarreas agudas con leucocitos;73 por ciento en sangre visible microcópicamente y 27 por ciento en el estudio microscópico. Tuvieron adhesina Eh positiva, 21. En 3 de ellos se detectaron trofozoítos hematófagos.Se realizaron 15 coprocultivos, en 5 desarrolló S. flexneri de tipo S2. Otros parásitos: 6 (Blastocystis homini 5).Tuvieron adhesina Eh negativa, 54. El 19 por ciento de las coloraciones demostró E. dispar.A 44 se les realizaron coprocultivos; desarrollaron bacterias invasivas 12 casos: S. flexneri de tipo S2 (13), Shigella sp (1), C. jejuni (5), otros (3). Otros parásitos: 12 (Blastocystis hominis 9).Conclusión. En este grupo de niños con disenterías amebianas, en la mitad de los casos seidentificaron bacterias invasivas y sólo en el 28 por ciento se detectó E. histolytica en heces, con lo cual cabría esperar una prevalencia de 18-38 por ciento de casos positivos en la población [IC 95 por ciento (0,179; 0,381)].

Sobrediagnóstico de amebiasis en niños con disentería / Overdiagnosis of amebiasis in children with dysentery

Existen dos amebas, morfológicamente idénticas, cuyas diferencias determinanque una de ellas, Entamoeba histolytica, pueda ser patógena. La otra, Entamoeba dispar, es inocua.Surgió la presunción de que casos tratados como amebiasis, no lo fueran. Objetivo. Identificar E. histolytica en niños con disenterías supuestamente amebianas. Métodos. Estudio transversal y observacional realizado en Santa Fe, entre marzo de 2005 y noviembre de 2007. En niños de 2 meses a 15 años con disentería y exámenes directos con E. histolytica/dispar, se realizó ELISA para detectar la adhesina de E. histolytica (adhesina Eh) en heces.Se efectuaron coloraciones para amebas, coprocultivos y se registraron datos clínicos.Resultados. De 75 casos estudiados, 35 fueron varones y 40 mujeres, con edad (mediana) de 3 años. Todos presentaron diarreas agudas con leucocitos;73 por ciento en sangre visible microcópicamente y 27 por ciento en el estudio microscópico. Tuvieron adhesina Eh positiva, 21. En 3 de ellos se detectaron trofozoítos hematófagos.Se realizaron 15 coprocultivos, en 5 desarrolló S. flexneri de tipo S2. Otros parásitos: 6 (Blastocystis homini 5).Tuvieron adhesina Eh negativa, 54. El 19 por ciento de las coloraciones demostró E. dispar.A 44 se les realizaron coprocultivos; desarrollaron bacterias invasivas 12 casos: S. flexneri de tipo S2 (13), Shigella sp (1), C. jejuni (5), otros (3). Otros parásitos: 12 (Blastocystis hominis 9).Conclusión. En este grupo de niños con disenterías amebianas, en la mitad de los casos seidentificaron bacterias invasivas y sólo en el 28 por ciento se detectó E. histolytica en heces, con lo cual cabría esperar una prevalencia de 18-38 por ciento de casos positivos en la población [IC 95 por ciento (0,179; 0,381)].(AU)

[Overdiagnosis of amebiasis in children with dysentery]. / Sobrediagnóstico de amebiasis en niños con disentería.

INTRODUCTION: There are morphologically identical amebaes, but with differences that can distinguish them; one as pathogenic: Entamoeba histolytica, and the other: Entamoeba dispar, as inoffensive. That brought the new hypothesis that many of the cases treated as amebiasis, weren't so. OBJECTIVE: To identify E. hystolitica in patients with dysentery, supposed to be caused by amebae. METHODS: Transversal and observational study performed between March 2005 and November 2007 in the city of Santa Fe, Argentina. Stools from children aged 2 months to 15 years-old with dysentery and direct exams with E. hystolitica/ dispar, were studied with ELISA to detect the adhesin of E. histolytica (adhesin Eh). Permanent stains for amebae were done as well as stool cultures. Clinical data were charted. RESULTS: 75 children were studied; 35 were male and 40, female, with a median age of 3 years-old. All of them presented diarrhea with leucocyte, 73% macroscopic blood on stool and 27% detectable on the microscope. Elisa Eh was positive in 21; 3 cases had hematophagous trophozoites. In 15 stool cultures were found: S. flexneri S2 type in 5 cases. Other parasites: 6 (Blastocystis homini 5). In 54 adhesin Eh was negative, 19% of the coulouring detected E. dispar. From 44 stool cultures: S. flexneri S2 type was detected in 13, Shigella sp in 1, C jejuni 5, other: 3. Other parasites: 12 (Blastocystis homini 9). CONCLUSION: In this group of children with "amebic dysentery", half of them developed invasive bacteriae and only 28% had E. histolytica on stools; that means that the prevalence of positive cases in the population could be 18% to 38% [CI 95% (0.179; 0.381)].