Synthetic whole-slide image tile generation with gene expression profile-infused deep generative models

In this work, we propose an approach to generate whole-slide image (WSI) tiles by using deep generative models infused with matched gene expression profiles. First, we train a variational autoencoder (VAE) that learns a latent, lower-dimensional representation of multi-tissue gene expression profiles. Then, we use this representation to infuse generative adversarial networks (GANs) that generate lung and brain cortex tissue tiles, resulting in a new model that we call RNA-GAN. Tiles generated by RNA-GAN were preferred by expert pathologists compared with tiles generated using traditional GANs, and in addition, RNA-GAN needs fewer training epochs to generate high-quality tiles. Finally, RNA-GAN was able to generalize to gene expression profiles outside of the training set, showing imputation capabilities. A web-based quiz is available for users to play a game distinguishing real and synthetic tiles: https://rna-gan.stanford.edu/, and the code for RNA-GAN is available here: https://github.com/gevaertlab/RNA-GAN.Grants PID2021- 128317OB-I00MCIN/AEI/10.13039/501100011033Project P20-00163, funded by Consejerı´a de Universidad, Investigacio´ n e InnovacioERDF A way of making Europ

Coupling Noble Metals and Carbon Supports in the Development of Combustion Catalysts for the Abatement of BTX Compounds in Air Streams

The catalytic combustion of volatile organic compounds (VOCs) is one of the most important techniques to remove these pollutants from the air stream, but it should be carried out at the lowest possible temperature, saving energy and avoiding the simultaneous formation of nitrogen oxides (NOx). Under these experimental conditions, the chemisorption of water generated from VOCs combustion may inhibit hydrophilic catalysts. Nowadays, a wide variety of carbon materials is available to be used in catalysis. The behavior of these hydrophobic materials in the development of highly active and selective combustion catalysts is analyzed in this manuscript. The support characteristics (porosity, hydrophobicity, structure, surface chemistry, etc.) and the active phase nature (noble metals: Pt, Pd) and dispersion were analyzed by several techniques and the results correlated with the dual adsorptive and/or catalytic performance of the corresponding catalysts. The coupling of highly active phases and carbon materials (activated carbons, honeycomb coated monoliths, carbon aerogels, etc.) with tuneable physicochemical properties leads to the complete abatement of benzene, toluene and xylenes (BTX) from dilute air streams, being selectively oxidized to CO2 at low temperatures

Methods for autonomous wristband placement with a search-and-rescue aerial manipulator

A new robotic system for Search And Rescue (SAR) operations based on the automatic wristband placement on the victims’ arm, which may provide identification, beaconing and remote sensor readings for continuous health monitoring. This paper focuses on the development of the automatic target localization and the device placement using an unmanned aerial manipulator. The automatic wrist detection and localization system uses an RGB-D camera and a convolutional neural network based on the region faster method (Faster R-CNN). A lightweight parallel delta manipulator with a large workspace has been built, and a new design of a wristband in the form of a passive detachable gripper, is presented, which under contact, automatically attaches to the human, while disengages from the manipulator. A new trajectory planning method has been used to minimize the torques caused by the external forces during contact, which cause attitude perturbations. Experiments have been done to evaluate the machine learning method for detection and location, and for the assessment of the performance of the trajectory planning method. The results show how the VGG-16 neural network provides a detection accuracy of 67.99%. Moreover, simulation experiments have been done to show that the new trajectories minimize the perturbations to the aerial platform.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Electrodes Based on Carbon Aerogels Partially Graphitized by Doping with Transition Metals for Oxygen Reduction Reaction

A series of carbon aerogels doped with iron, cobalt and nickel have been prepared. Metal nanoparticles very well dispersed into the carbon matrix catalyze the formation of graphitic clusters around them. Samples with different Ni content are obtained to test the influence of the metal loading. All aerogels have been characterized to analyze their textural properties, surface chemistry and crystal structures. These metal-doped aerogels have a very well-developed porosity, making their mesoporosity remarkable. Ni-doped aerogels are the ones with the largest surface area and the smallest graphitization. They also present larger mesopore volumes than Co- and Fe-doped aerogels. These materials are tested as electro-catalysts for the oxygen reduction reaction. Results show a clear and strong influence of the carbonaceous structure on the whole electro-catalytic behavior of the aerogels. Regarding the type of metal doping, aerogel doped with Co is the most active one, followed by Ni- and Fe-doped aerogels, respectively. As the Ni content is larger, the kinetic current densities increase. Comparatively, among the different doping metals, the results obtained with Ni are especially remarkable.This research is supported by the FEDER and Spanish projects CTQ2013-44789-R (MINECO) and P12-RNM-2892 (Junta de Andalucía). A.A. is grateful to the European Union for his Erasmus Mundus fellowship, Program ELEMENT. J. C.-Q. is grateful to the Junta de Andalucía for her research contract (P12-RNM-2892). We thank the “Unidad de Excelencia Química Aplicada a Biomedicina y Medioambiente” (UGR) for its technical assistance

Metal-Carbon-CNF Composites Obtained by Catalytic Pyrolysis of Urban Plastic Residues as Electro-Catalysts for the Reduction of CO2

Metal–carbon–carbon nanofibers composites obtained by catalytic pyrolysis of urban plastic residues have been prepared using Fe, Co or Ni as pyrolitic catalysts. The composite materials have been fully characterized from a textural and chemical point of view. The proportion of carbon nanofibers and the final content of carbon phases depend on the used pyrolitic metal with Ni being the most active pyrolitic catalysts. The composites show the electro-catalyst activity in the CO2 reduction to hydrocarbons, favoring all the formation of C1 to C4 hydrocarbons. The tendency of this activity is in accordance with the apparent faradaic efficiencies and the linear sweep voltammetries. The cobalt-based composite shows high selectivity to C3 hydrocarbons within this group of compounds.This research is supported by the FEDER and Spanish projects CTQ2013-44789-R (MINECO) and P12-RNM-2892 (Junta de Andalucía). J.C.-Q. is grateful to the Junta de Andalucía for her research contract (P12-RNM-2892). A.E. acknowledges a predoctoral fellowship from Erasmus Mundus, Al-Idrissi, programme

Performance comparison between multi‑center histopathology datasets of a weakly‑supervised deep learning model for pancreatic ductal adenocarcinoma detection

Background Pancreatic ductal carcinoma patients have a really poor prognosis given its difficult early detection and the lack of early symptoms. Digital pathology is routinely used by pathologists to diagnose the disease. However, visually inspecting the tissue is a time-consuming task, which slows down the diagnostic procedure. With the advances occurred in the area of artificial intelligence, specifically with deep learning models, and the growing availability of public histology data, clinical decision support systems are being created. However, the generalization capabilities of these systems are not always tested, nor the integration of publicly available datasets for pancreatic ductal carcinoma detection (PDAC). Methods In this work, we explored the performace of two weakly-supervised deep learning models using the two more widely available datasets with pancreatic ductal carcinoma histology images, The Cancer Genome Atlas Project (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC). In order to have sufficient training data, the TCGA dataset was integrated with the Genotype-Tissue Expression (GTEx) project dataset, which contains healthy pancreatic samples. Results We showed how the model trained on CPTAC generalizes better than the one trained on the integrated dataset, obtaining an inter-dataset accuracy of 90.62% ± 2.32 and an outer-dataset accuracy of 92.17% when evaluated on TCGA + GTEx. Furthermore, we tested the performance on another dataset formed by tissue micro-arrays, obtaining an accuracy of 98.59%. We showed how the features learned in an integrated dataset do not differentiate between the classes, but between the datasets, noticing that a stronger normalization might be needed when creating clinical decision support systems with datasets obtained from different sources. To mitigate this effect, we proposed to train on the three available datasets, improving the detection performance and generalization capabilities of a model trained only on TCGA + GTEx and achieving a similar performance to the model trained only on CPTAC. Conclusions The integration of datasets where both classes are present can mitigate the batch effect present when integrating datasets, improving the classification performance, and accurately detecting PDAC across different datasets.Spanish Ministry of Sciences, Innovation and Universities under Project PID2021-128317OB-I00Junta de Andalucia P20-0016

Functionalized Cellulose for the Controlled Synthesis of Novel Carbon–Ti Nanocomposites: Physicochemical and Photocatalytic Properties

H.H. gratefully thanks a predoctoral fellowship from Erasmus Mundus (Al-Idrisi II). E.B.-G. is grateful to MINECO for her postdoctoral fellowship (FJCI-2015-23769). S.M.-T. acknowledges the financial support from the University of Granada (Reincorporación Plan Propio). “Unidad de Excelencia Química Aplicada a Biomedicina y Medioambiente” of the University of Granada (UEQ - UGR) is gratefully acknowledged for the technical assistance.Carbon–Ti nanocomposites were prepared by a controlled two-step method using microcrystalline cellulose as a raw material. The synthesis procedure involves the solubilization of cellulose by an acid treatment (H3PO4 or HNO3) and the impregnation with the Ti precursor followed of a carbonization step at 500 or 800 ◦C. The type of acid treatment leads to a different functionalization of cellulose with phosphorus- or oxygen-containing surface groups, which are able to control the load, dispersion and crystalline phase of Ti during the composite preparation. Thus, phosphorus functionalities lead to amorphous carbon–Ti composites at 500 ◦C, while TiP2O7 crystals are formed when prepared at 800 ◦C. On the contrary, oxygenated groups induce the formation of TiO2 rutile at an unusually low temperature (500 ◦C), while an increase of carbonization temperature promotes a progressive crystal growth. The removal of Orange G (OG) azo dye in aqueous solution, as target pollutant, was used to determine the adsorptive and photocatalytic efficiencies, with all composites being more active than the benchmark TiO2 material (Degussa P25). Carbon–Ti nanocomposites with a developed micro-mesoporosity, reduced band gap and TiO2 rutile phase were the most active in the photodegradation of OG under ultraviolet irradiation.This work was financially supported by the Spanish Projects ref. RTI2018-099224-B-I00 from ERDF/Ministry of Science, Innovation and Universities—State Research Agency and Junta de Andalucía - Grant ref. RMN-172

On the Interactions and Synergism between Phases of Carbon–Phosphorus–Titanium Composites Synthetized from Cellulose for the Removal of the Orange-G Dye

Carbon–phosphorus–titanium composites (CPT) were synthesized by Ti-impregnation and carbonization of cellulose. Microcrystalline cellulose used as carbon precursor was initially dissolved by phosphoric acid (H3PO4) to favor the Ti-dispersion and the simultaneous functionalization of the cellulose chains with phosphorus-containing groups, namely phosphates and polyphosphates. These groups interacted with the Ti-precursor during impregnation and determined the interface transformations during carbonization as a function of the Ti-content and carbonization temperature. Amorphous composites with high surface area and mesoporosity were obtained at low Ti-content (Ti:cellulose ratio = 1) and carbonization temperature (500ºC), while in composites with Ti:cellulose ratio = 12 and 800ºC, Ti-particles reacted with the cellulose groups leading to different Ti-crystalline polyphosphates and a marked loss of the porosity. The efficiency of composites in the removal of the Orange G dye in solution by adsorption and photocatalysis was discussed based on their physicochemical properties. These materials were more active than the benchmark TiO2 material (Degussa P25), showing a clear synergism between phases.This research is supported by the FEDER and Spanish projects CTQ2013-44789-R (MINECO) and P12-RNM-2892 (Junta de Andalucía). H.H. gratefully thanks the support of Erasmus-Mundus (Al-Idrisi II) project for PhD scholarship. S.M.-T. acknowledges the financial support from University of Granada (Reincorporación Plan Propio). J.C.-Q. is grateful to the Junta de Andalucía for her research contract (P12-RNM-2892)

Photodegradation of cytostatic drugs by g-C3N4: Synthesis, properties and performance fitted by selecting the appropriate precursor

Graphitic carbon nitride (g-C3N4) was synthetized by a one-step thermal method from different N-rich precursors, namely melamine, dicyandiamide, urea, thiourea and cyanamide. The structure, optical and physicochemical properties of g-C3N4 materials were studied by transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS) and Raman spectroscopy, among others. Both melamine and dicyandiamide provided a less porous structure composed by large flake sheets, whereas urea and thiourea favoured g-C3N4 composed by small flat sheets and wrinkles with a larger porosity. The establishment of more condensed g-C3N4 networks with a reduced band gap was also evidenced for melamine and dicyandiamide precursors, while urea favoured less condensed melem or melon structures. The photoactivity of the different g-C3N4 was assessed for the removal of an aqueous solution containing 5-fluorouracil (5-FU), cyclophosphamide (CP) or a mixture of both cytostatic drugs, under near UV-Vis and solar-LED irradiations. The best performing photocatalysts under near UV-Vis irradiation, were those prepared from melamine (kapp = 14.6 × 10–2 min–1 for 5-FU) and thiourea (kapp = 2.5 × 10–2 min–1 for CP), while urea was the most active under solar-LED irradiation (kapp = 0.183 × 10–2 min–1 for 5-FU). In addition, CP was more resistant to be degraded than 5-FU, and a competitive effect for the generated hydroxyl radicals was evidenced when both pollutant molecules were in the same solution. The photoactivity of g-C3N4 materials was justified by the combination of various effects: (i) surface area, (ii) well-connected and condensed g-C3N4 structures and (iii) high surface C/N ratios with nitrogen vacanciesSpanish Projects from MCIN/AEI/FEDER "Una manera de hacer Europa" RTI2018-099224-B-I00FEDER/Junta de Andalucia-Consejeria de Transformacion Economica, Industria, Conocimiento y Universidades B-RNM-486-UGR20Junta de Andalucia-Consejeria de Universidad, Investigacion e Innovacion -Proyecto P21_00208MICIN/AEIEuropean Social Found (FSE) PRE2019-087946MICIN/AEI RYC-2019-026634-IFSE "El FSE invierte en tu futuro"Universidad de Granada/CBU

Functionalized Graphene Derivatives and TiO2 for High Visible Light Photodegradation of Azo Dyes

Functionalized graphene derivatives including graphene oxide (GO), reduced graphene oxide (rGO), and heteroatom (nitrogen/sulphur (N/S) or boron (B))-doped graphene were used to synthesize composites with TiO2 (T). The photocatalytic performance of composites was assessed for the degradation of Orange G dye (OG) under simulated solar light. All the prepared graphene derivatives—TiO2 composites showed better photocatalytic performance than bare TiO2. A higher photocatalytic activity was found for the composites containing GO and N/S co-doped rGO (kapp = 109.2 × 10−3 and 48.4 × 10−3 min−1 , for GO-T and rGONS-T, respectively). The influence of both initial solution pH and the reactive species involved in the OG degradation pathway were studied. The photocatalytic activity of the samples decreased with the increase of the initial pH (from 3.0 to 10.0) due to the occurrence of electrostatic repulsive forces between the photocatalysts surface and the molecules of OG, both negatively charged. The use of selective scavengers showed that although the photogenerated holes dominate the degradation mechanism, radicals and singlet oxygen also participate in the OG degradation pathway. In addition, reutilization experiments indicated that the samples were stable under the reaction conditions used.ERDF/Ministry of Science, Innovation and Universities-State Research Agency RTI2018-099224-B-I0