Skin Tone Analysis for Representation in Educational Materials (STAR-ED) using machine learning.

Images depicting dark skin tones are significantly underrepresented in the educational materials used to teach primary care physicians and dermatologists to recognize skin diseases. This could contribute to disparities in skin disease diagnosis across different racial groups. Previously, domain experts have manually assessed textbooks to estimate the diversity in skin images. Manual assessment does not scale to many educational materials and introduces human errors. To automate this process, we present the Skin Tone Analysis for Representation in EDucational materials (STAR-ED) framework, which assesses skin tone representation in medical education materials using machine learning. Given a document (e.g., a textbook in .pdf), STAR-ED applies content parsing to extract text, images, and table entities in a structured format. Next, it identifies images containing skin, segments the skin-containing portions of those images, and estimates the skin tone using machine learning. STAR-ED was developed using the Fitzpatrick17k dataset. We then externally tested STAR-ED on four commonly used medical textbooks. Results show strong performance in detecting skin images (0.96 ± 0.02 AUROC and 0.90 ± 0.06 F1 score) and classifying skin tones (0.87 ± 0.01 AUROC and 0.91 ± 0.00 F1 score). STAR-ED quantifies the imbalanced representation of skin tones in four medical textbooks: brown and black skin tones (Fitzpatrick V-VI) images constitute only 10.5% of all skin images. We envision this technology as a tool for medical educators, publishers, and practitioners to assess skin tone diversity in their educational materials.

A causal inference approach for estimating effects of non-pharmaceutical interventions during Covid-19 pandemic.

In response to the outbreak of the coronavirus disease 2019 (Covid-19), governments worldwide have introduced multiple restriction policies, known as non-pharmaceutical interventions (NPIs). However, the relative impact of control measures and the long-term causal contribution of each NPI are still a topic of debate. We present a method to rigorously study the effectiveness of interventions on the rate of the time-varying reproduction number Rt and on human mobility, considered here as a proxy measure of policy adherence and social distancing. We frame our model using a causal inference approach to quantify the impact of five governmental interventions introduced until June 2020 to control the outbreak in 113 countries: confinement, school closure, mask wearing, cultural closure, and work restrictions. Our results indicate that mobility changes are more accurately predicted when compared to reproduction number. All NPIs, except for mask wearing, significantly affected human mobility trends. From these, schools and cultural closure mandates showed the largest effect on social distancing. We also found that closing schools, issuing face mask usage, and work-from-home mandates also caused a persistent reduction on Rt after their initiation, which was not observed with the other social distancing measures. Our results are robust and consistent across different model specifications and can shed more light on the impact of individual NPIs.

Reconstruction of Iberian ceramic potteries using generative adversarial networks.

Several aspects of past culture, including historical trends, are inferred from time-based patterns observed in archaeological artifacts belonging to different periods. The presence and variation of these objects provides important clues about the Neolithic revolution and given their relative abundance in most archaeological sites, ceramic potteries are significantly helpful in this purpose. Nonetheless, most available pottery is fragmented, leading to missing morphological information. Currently, the reassembly of fragmented objects from a collection of thousands of mixed fragments is a daunting and time-consuming task done almost exclusively by hand, which requires the physical manipulation of the fragments. To overcome the challenges of manual reconstruction and improve the quality of reconstructed samples, we present IberianGAN, a customized Generative Adversarial Network (GAN) tested on an extensive database with complete and fragmented references. We trained the model with 1072 samples corresponding to Iberian wheel-made pottery profiles belonging to archaeological sites located in the upper valley of the Guadalquivir River (Spain). Furthermore, we provide quantitative and qualitative assessments to measure the quality of the reconstructed samples, along with domain expert evaluation with archaeologists. The resulting framework is a possible way to facilitate pottery reconstruction from partial fragments of an original piece.

Bulsarapp: Interactive Visual Analysis for Surname Trend Exploration.

The study of surnames for a given population, together with their distribution and spatial patterns identification, has been a long-standing problem in the fields of human biology, public health, and social sciences. The ancestry inferred from surname information can be a useful means to understand the dynamics of human populations. This knowledge allows us to characterize geographically the ethnicity of populations, and to understand the complex relationships between identity, migration, and health issues in a demographic view. However, in most cases, a detailed geolocalization of this data can be a daunting task. We propose a visual analytic tool that summarizes the heterogeneous surname and geographic information collected from Argentinean electoral rolls. This tool allows a massive data analysis, and facilitates interdisciplinary studies about population dynamics related to ancestry, migration, and health. It also offers an easy-to-use interface that allows interactive exploration of isonymy and surname origins, their distribution, and spatial trends in a high population density context.

A microenvironment-inspired synthetic three-dimensional model for pancreatic ductal adenocarcinoma organoids.

Experimental in vitro models that capture pathophysiological characteristics of human tumours are essential for basic and translational cancer biology. Here, we describe a fully synthetic hydrogel extracellular matrix designed to elicit key phenotypic traits of the pancreatic environment in culture. To enable the growth of normal and cancerous pancreatic organoids from genetically engineered murine models and human patients, essential adhesive cues were empirically defined and replicated in the hydrogel scaffold, revealing a functional role of laminin-integrin α3/α6 signalling in establishment and survival of pancreatic organoids. Altered tissue stiffness-a hallmark of pancreatic cancer-was recapitulated in culture by adjusting the hydrogel properties to engage mechano-sensing pathways and alter organoid growth. Pancreatic stromal cells were readily incorporated into the hydrogels and replicated phenotypic traits characteristic of the tumour environment in vivo. This model therefore recapitulates a pathologically remodelled tumour microenvironment for studies of normal and pancreatic cancer cells in vitro.

Phosphoproteomics Identifies PI3K Inhibitor-selective Adaptive Responses in Pancreatic Cancer Cell Therapy and Resistance.

The PI3K pathway is highly active in human cancers. The four class I isoforms of PI3K are activated by distinct mechanisms leading to a common downstream signaling. Their downstream redundancy is thought to be responsible for treatment failures of PI3K inhibitors. We challenged this concept, by mapping the differential phosphoproteome evolution in response to PI3K inhibitors with different isoform-selectivity patterns in pancreatic cancer, a disease currently without effective therapy. In this cancer, the PI3K signal was shown to control cell proliferation. We compared the effects of LY294002 that inhibit with equal potency all class I isoenzymes and downstream mTOR with the action of inhibitors with higher isoform selectivity toward PI3Kα, PI3Kß, or PI3Kγ (namely, A66, TGX-221 and AS-252424). A bioinformatics global pathway analysis of phosphoproteomics data allowed us to identify common and specific signals activated by PI3K inhibitors supported by the biological data. AS-252424 was the most effective treatment and induced apoptotic pathway activation as well as the highest changes in global phosphorylation-regulated cell signal. However, AS-252424 treatment induced reactivation of Akt, therefore decreasing the treatment outcome on cell survival. Reversely, AS-252424 and A66 combination treatment prevented p-Akt reactivation and led to synergistic action in cell lines and patient organoids. The combination of clinically approved α-selective BYL-719 with γ-selective IPI-549 was more efficient than single-molecule treatment on xenograft growth. Mapping unique adaptive signaling responses to isoform-selective PI3K inhibition will help to design better combinative treatments that prevent the induction of selective compensatory signals.

Data-level Linkage of Multiple Surveys for Improved Understanding of Global Health Challenges.

Data-driven approaches can provide more enhanced insights for domain experts in addressing critical global health challenges, such as newborn and child health, using surveys (e.g., Demographic Health Survey). Though there are multiple surveys on the topic, data-driven insight extraction and analysis are often applied on these surveys separately, with limited efforts to exploit them jointly, and hence results in poor prediction performance of critical events, such as neonatal death. Existing machine learning approaches to utilise multiple data sources are not directly applicable to surveys that are disjoint on collection time and locations. In this paper, we propose, to the best of our knowledge, the first detailed work that automatically links multiple surveys for the improved predictive performance of newborn and child mortality and achieves cross-study impact analysis of covariates.

The impact of socioeconomic and phenotypic traits on self-perception of ethnicity in Latin America.

Self-perception of ethnicity is a complex social trait shaped by both, biological and non-biological factors. We developed a comprehensive analysis of ethnic self-perception (ESP) on a large sample of Latin American mestizos from five countries, differing in age, socio-economic and education context, external phenotypic attributes and genetic background. We measured the correlation of ESP against genomic ancestry, and the influence of physical appearance, socio-economic context, and education on the distortion observed between both. Here we show that genomic ancestry is correlated to aspects of physical appearance, which in turn affect the individual ethnic self-perceived ancestry. Also, we observe that, besides the significant correlation among genomic ancestry and ESP, specific physical or socio-economic attributes have a strong impact on self-perception. In addition, the distortion among ESP and genomic ancestry differs across age ranks/countries, probably suggesting the underlying effect of past public policies regarding identity. Our results indicate that individuals' own ideas about its origins should be taken with caution, especially in aspects of modern life, including access to work, social policies, and public health key decisions such as drug administration, therapy design, and clinical trials, among others.

Pancreatic cancer intrinsic PI3Kα activity accelerates metastasis and rewires macrophage component.

Pancreatic ductal adenocarcinoma (PDAC) patients frequently suffer from undetected micro-metastatic disease. This clinical situation would greatly benefit from additional investigation. Therefore, we set out to identify key signalling events that drive metastatic evolution from the pancreas. We searched for a gene signature that discriminate localised PDAC from confirmed metastatic PDAC and devised a preclinical protocol using circulating cell-free DNA (cfDNA) as an early biomarker of micro-metastatic disease to validate the identification of key signalling events. An unbiased approach identified, amongst actionable markers of disease progression, the PI3K pathway and a distinctive PI3Kα activation signature as predictive of PDAC aggressiveness and prognosis. Pharmacological or tumour-restricted genetic PI3Kα-selective inhibition prevented macro-metastatic evolution by hindering tumoural cell migratory behaviour independently of genetic alterations. We found that PI3Kα inhibition altered the quantity and the species composition of the produced lipid second messenger PIP3 , with a selective decrease of C36:2 PI-3,4,5-P3 . Tumoural PI3Kα inactivation prevented the accumulation of pro-tumoural CD206-positive macrophages in the tumour-adjacent tissue. Tumour cell-intrinsic PI3Kα promotes pro-metastatic features that could be pharmacologically targeted to delay macro-metastatic evolution.

Data-Driven Sequential Uptake Pattern Discovery for Family Planning Studies.

Family planning is a crucial component of sustainable global development and is essential for achieving universal health coverage. Specifically, contraceptive use improves the health of women and children in several ways, including reducing maternal mortality risks, increasing child survival rates through birth spacing, and improving the nutritional status of both mother and children. This paper presents a data-driven approach to study the dynamics of contraceptive use and discontinuation in Sub-Saharan African (SSA) countries. We aim to provide policymakers with discriminating contraceptive use patterns under different discontinuation reasons, contraceptive uptake distributions, and transition information across contraceptive types. We used Demographic Health Survey (DHS) Calendar data from five SSA countries. One recurrent pattern found was that continuous usage of injectables resulted in discontinuation due to health concerns in four out of five countries studied. This type of temporal analysis can aid intervention development to support sustainable development goals in Family Planning.

Body shape: Implications in the study of obesity and related traits.

OBJECTIVES: The diagnosis and treatment of obesity are usually based on traditional anthropometric variables including weight, height, and several body perimeters. Here we present a three-dimensional (3D) image-based computational approach aimed to capture the distribution of abdominal adipose tissue as an aspect of shape rather than a relationship among classical anthropometric measures. METHODS: A morphometric approach based on landmarks and semilandmarks placed upon the 3D torso surface was performed in order to quantify abdominal adiposity shape variation and its relation to classical indices. Specifically, we analyzed sets of body cross-sectional circumferences, collectively defining each, along with anthropometric data taken on 112 volunteers. Principal Component Analysis (PCA) was performed on 250 circumferences located along the abdominal region of each volunteer. An analysis of covariance model was used to compare shape variables (PCs) against anthropometric data (weight, height, and waist and hip circumferences). RESULTS: The observed shape patterns were mainly related to nutritional status, followed by sexual dimorphism. PC1 (12.5%) and PC2 (7.5%) represented 20% of the total variation. In PCAs calculated independently by sex, linear regression analyses provide statistically significant associations between PC1 and the three classical indexes: body mass index, waist-to-height ratio, and waist-hip ratio. CONCLUSION: Shape indicators predict well the behavior of classical markers, but also evaluate 3D and geometric features with more accuracy as related to the body shape under study. This approach also facilitates diagnosis and follow-up of therapies by using accessible 3D technology.

Signal-Targeted Therapies and Resistance Mechanisms in Pancreatic Cancer: Future Developments Reside in Proteomics.

For patients with metastatic pancreatic cancer that are not eligible for surgery, signal-targeted therapies have so far failed to significantly improve survival. These therapeutic options have been tested in phase II/III clinical trials mostly in combination with the reference treatment gemcitabine. Innovative therapies aim to annihilate oncogenic dependency, or to normalize the tumoural stroma to allow immune cells to function and/or re-vascularisation to occur. Large scale transcriptomic and genomic analysis revealed that pancreatic cancers display great heterogeneity but failed to clearly delineate specific oncogene dependency, besides oncogenic Kras. Beyond these approaches, proteomics appears to be an appropriate approach to classify signal dependency and to identify specific alterations at the targetable level. However, due to difficulties in sampling, proteomic data for this pathology are scarce. In this review, we will discuss the current state of clinical trials for targeted therapies against pancreatic cancer. We will then highlight the most recent proteomic data for pancreatic tumours and their metastasis, which could help to identify major oncogenic signalling dependencies, as well as provide future leads to explain why pancreatic tumours are intrinsically resistant to signal-targeted therapies. We will finally discuss how studies on phosphatidylinositol-3-kinase (PI3K) signalling, as the paradigmatic pro-tumoural signal downstream of oncogenic Kras in pancreatic cancer, would benefit from exploratory proteomics to increase the efficiency of targeted therapies.

Developmental pathways inferred from modularity, morphological integration and fluctuating asymmetry patterns in the human face.

Facial asymmetries are usually measured and interpreted as proxies to developmental noise. However, analyses focused on its developmental and genetic architecture are scarce. To advance on this topic, studies based on a comprehensive and simultaneous analysis of modularity, morphological integration and facial asymmetries including both phenotypic and genomic information are needed. Here we explore several modularity hypotheses on a sample of Latin American mestizos, in order to test if modularity and integration patterns differ across several genomic ancestry backgrounds. To do so, 4104 individuals were analyzed using 3D photogrammetry reconstructions and a set of 34 facial landmarks placed on each individual. We found a pattern of modularity and integration that is conserved across sub-samples differing in their genomic ancestry background. Specifically, a signal of modularity based on functional demands and organization of the face is regularly observed across the whole sample. Our results shed more light on previous evidence obtained from Genome Wide Association Studies performed on the same samples, indicating the action of different genomic regions contributing to the expression of the nose and mouth facial phenotypes. Our results also indicate that large samples including phenotypic and genomic metadata enable a better understanding of the developmental and genetic architecture of craniofacial phenotypes.

Acinar-to-Ductal Metaplasia Induced by Transforming Growth Factor Beta Facilitates KRASG12D-driven Pancreatic Tumorigenesis.

BACKGROUND & AIMS: Transforming growth factor beta (TGFß) acts either as a tumor suppressor or as an oncogene, depending on the cellular context and time of activation. TGFß activates the canonical SMAD pathway through its interaction with the serine/threonine kinase type I and II heterotetrameric receptors. Previous studies investigating TGFß-mediated signaling in the pancreas relied either on loss-of-function approaches or on ligand overexpression, and its effects on acinar cells have so far remained elusive. METHODS: We developed a transgenic mouse model allowing tamoxifen-inducible and Cre-mediated conditional activation of a constitutively active type I TGFß receptor (TßRICA) in the pancreatic acinar compartment. RESULTS: We observed that TßRICA expression induced acinar-to-ductal metaplasia (ADM) reprogramming, eventually facilitating the onset of KRASG12D-induced pre-cancerous pancreatic intraepithelial neoplasia. This phenotype was characterized by the cellular activation of apoptosis and dedifferentiation, two hallmarks of ADM, whereas at the molecular level, we evidenced a modulation in the expression of transcription factors such as Hnf1ß, Sox9, and Hes1. CONCLUSIONS: We demonstrate that TGFß pathway activation plays a crucial role in pancreatic tumor initiation through its capacity to induce ADM, providing a favorable environment for KRASG12D-dependent carcinogenesis. Such findings are highly relevant for the development of early detection markers and of potentially novel treatments for pancreatic cancer patients.

Correction: Socioeconomic Status Is Not Related with Facial Fluctuating Asymmetry: Evidence from Latin-American Populations.

[This corrects the article DOI: 10.1371/journal.pone.0169287.].

Socioeconomic Status Is Not Related with Facial Fluctuating Asymmetry: Evidence from Latin-American Populations.

The expression of facial asymmetries has been recurrently related with poverty and/or disadvantaged socioeconomic status. Departing from the developmental instability theory, previous approaches attempted to test the statistical relationship between the stress experienced by individuals grown in poor conditions and an increase in facial and corporal asymmetry. Here we aim to further evaluate such hypothesis on a large sample of admixed Latin Americans individuals by exploring if low socioeconomic status individuals tend to exhibit greater facial fluctuating asymmetry values. To do so, we implement Procrustes analysis of variance and Hierarchical Linear Modelling (HLM) to estimate potential associations between facial fluctuating asymmetry values and socioeconomic status. We report significant relationships between facial fluctuating asymmetry values and age, sex, and genetic ancestry, while socioeconomic status failed to exhibit any strong statistical relationship with facial asymmetry. These results are persistent after the effect of heterozygosity (a proxy for genetic ancestry) is controlled in the model. Our results indicate that, at least on the studied sample, there is no relationship between socioeconomic stress (as intended as low socioeconomic status) and facial asymmetries.

Shifts in subsistence type and its impact on the human skull's morphological integration.

OBJECTIVE: Here we evaluate morphological integration patterns and magnitudes in different skull regions to detect if shifts in morphological integration are correlated to the appearance of more processed (softer) diets. METHODS: To do so, three transitional populations were analyzed, including samples from groups that inhabited the same geographical region and for which the evidence shows that major changes occurred in their subsistence mode. Ninety three-dimensional landmarks were digitized on 357 skulls and used as the raw data to develop geometric morphometric analyses. The landmark coordinates were divided into several different regions of biomechanical interest, following a three-level hierarchically nested scheme: the whole skull, further subdivided into neurocranium (divided into the vault and basicranium), the facial (divided into the lower and upper facial), and the masticatory apparatus (divided into alveolar, temporal, and temporo-mandibular joint). RESULTS: Our results indicate that the morphological integration and variability patterns significantly vary across skull regions but are maintained across the transitions. The alveolar border and the lower facial are the regions manifesting greater value of morphological integration and variability, while the upper facial, the temporo-mandibular joint, and the basicranium are highly integrated and poorly variable. CONCLUSIONS: The transition to softer diets increased morphological variation across cranial regions that are more exposed to masticatory strains effects.

Implication of PI3K/Akt pathway in pancreatic cancer: When PI3K isoforms matter?

Pancreatic cancer belongs to the incurable family of solid cancers. Despite of a recent better understanding its molecular biology, and an increased number of clinical trials, there is still a lack for innovative targeted therapies to fight this deadly malignancy. PI3K/Akt signalling is one of the most commonly deregulated signalling pathways in cancer, which explains the massive attention from many pharmaceutical companies over the ten past years on these signalling molecules. The already developed small molecule inhibitors are currently under clinical trial in various cancer types. Class I PI3Ks have 4 isoforms for which the role in physiology starts to be well described in the literature. Data are more unclear for their differential involvement in oncogenesis. In this review, we will discuss about the cognitive and therapeutic potential of targeting this signalling pathway and in particular Class I PI3K isoforms for pancreatic cancer treatment. Isoform-specificity of PI3K inhibitors are currently designed to achieve the same goal as pan-PI3K inhibitors but without potential adverse effects. We will discuss if such strategy is relevant in pancreatic adenocarcinoma.

Facial asymmetry and genetic ancestry in Latin American admixed populations.

Fluctuating and directional asymmetry are aspects of morphological variation widely used to infer environmental and genetic factors affecting facial phenotypes. However, the genetic basis and environmental determinants of both asymmetry types is far from being completely known. The analysis of facial asymmetries in admixed individuals can be of help to characterize the impact of a genome's heterozygosity on the developmental basis of both fluctuating and directional asymmetries. Here we characterize the association between genetic ancestry and individual asymmetry on a sample of Latin-American admixed populations. To do so, three-dimensional (3D) facial shape attributes were explored on a sample of 4,104 volunteers aged between 18 and 85 years. Individual ancestry and heterozygosity was estimated using more than 730,000 genome-wide markers. Multivariate techniques applied to geometric morphometric data were used to evaluate the magnitude and significance of directional and fluctuating asymmetry (FA), as well as correlations and multiple regressions aimed to estimate the relationship between facial FA scores and heterozygosity and a set of covariates. Results indicate that directional and FA are both significant, the former being the strongest expression of asymmetry in this sample. In addition, our analyses suggest that there are some specific patterns of facial asymmetries characterizing the different ancestry groups. Finally, we find that more heterozygous individuals exhibit lower levels of asymmetry. Our results highlight the importance of including ancestry-admixture estimators, especially when the analyses are aimed to compare levels of asymmetries on groups differing on socioeconomic levels, as a proxy to estimate developmental noise.