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Mycetoma is a chronic infection of the skin and underlying tissues caused by fungi or bacteria. It is endemic to tropical regions, mainly affecting men, peasants, between the third and fourth decade of life. The clinical picture is characterized by increased volume, deformity of the anatomical area, and fistulas that drain a stringy exudate with the presence of "pimples." The diagnosis and determination of the etiological agent is carried out by direct analysis and culture of the secretion.

Cutaneous larva migrans is a skin infection caused by the subcutaneous migration of larvae of different species of nematodes. Also called Creeping eruption or serpiginous eruption, it is an endemic skin parasitosis of tropical and subtropical areas with hot and humid climate. In our environment it is unusual, predominating in individuals who have come to these areas, although there are rare cases of acquisition in European countries. It was first described by Lee in 1874 and since then its prevalence has been increasing, affecting millions of people each year. It is an endemic process in tropical and subtropical areas. Due to growing immigration and booming travel to these geographical areas, its prevalence in developed countries has increased in recent decades. For all these reasons, we believe it appropriate to disclose the existence of this parasitic dermatosis among dermatologists and primary care physicians.

Until four years ago, regulations of the drinking water consumption in Colombia did not consider climate change variables and national and international water-urban guidelines in its rate policy. In this sense, it is proposed to determine the scenario of the basic water consumption through a normative revision implemented to guarantee the supply, considering the six socioeconomic strata and classifying three types of cities according to the water endowment and geographic location. It was found, that the Bogotá city shows an initial increase of 58% for stratum 1, which can be considered as high, compared with Medellín and Cali cities (53% and 43%). Hence, changes presented in resolution CRA/750/2016, according to a new consumption of household public services of the Aqueduct, have a large impact on the economy of families, especially for strata 1, 2, and 3.

BACKGROUND Personalized nutrition and protective diets and lifestyles represent a key cancer research priority. The association between consumption of specific dietary components and colorectal cancer (CRC) incidence has been evaluated by a number of population-based studies, which have identified certain food items as having protective potential, though the findings have been inconsistent. Herein we present a systematic review and meta-analysis on the potential protective role of five common phytochemically rich dietary components (nuts, cruciferous vegetables, citrus fruits, garlic and tomatoes) in reducing CRC risk. AIM To investigate the independent impact of increased intake of specific dietary constituents on CRC risk in the general population. METHODS Medline and Embase were systematically searched, from time of database inception to January 31, 2020, for observational studies reporting CRC incidence relative to intake of one or more of nuts, cruciferous vegetables, citrus fruits, garlic and/or tomatoes in the general population. Data were extracted by two independent reviewers and analyzed in accordance with the Meta-analysis of Observational Studies in Epidemiology (MOOSE) and Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) reporting guidelines and according to predefined inclusion/exclusion criteria. Effect sizes of studies were pooled using a random-effects model. RESULTS Forty-six studies were identified. CRC risk was significantly reduced in patients with higher vs lower consumption of cruciferous vegetables [odds ratio (OR) = 0.90; 95% confidence interval (CI): 0.85-0.95; P < 0.005], citrus fruits (OR = 0.90; 95%CI: 0.84-0.96; P < 0.005), garlic (OR = 0.83; 95%CI: 0.76-0.91; P < 0.005) and tomatoes (OR = 0.89; 95%CI: 0.84-0.95; P < 0.005). Subgroup analysis showed that this association sustained when looking at case-control studies alone, for all of these four food items, but no significant difference was found in analysis of cohort studies alone. Nut consumption exhibited a similar trend, but overall results were not significant (OR = 0.72; 95%CI: 0.50-1.03; P < 0.07; I2 = 90.70%). Putative anticarcinogenic mechanisms are proposed using gene-set enrichment analysis of gene/protein perturbations caused by active compounds within each food item. CONCLUSION Increased cruciferous vegetable, garlic, citrus fruit and tomato consumption are all inversely associated with CRC risk. These findings highlight the potential for developing precision nutrition strategies for CRC prevention. Borgas P, Gonzalez G, Veselkov K, Mirnezami R. Phytochemically rich dietary components and the risk of colorectal cancer: A systematic review and meta-analysis of observational studies. World J Clin Oncol 2021; 12(6): 482-499 [PMID: 34189071 DOI: 10.5306/wjco.v12.i6.482]

Background Recent efforts in the field of nutritional science have allowed the discovery of disease-beating molecules within foods based on the commonality of bioactive food molecules to FDA-approved drugs. The pioneering work in this field used an unsupervised network propagation algorithm to learn the systemic-wide effect on the human interactome of 1962 FDA-approved drugs and a supervised algorithm to predict anticancer therapeutics using the learned representations. Then, a set of bioactive molecules within foods was fed into the model, which predicted molecules with cancer-beating potential.The employed methodology consisted of disjoint unsupervised feature generation and classification tasks, which can result in sub-optimal learned drug representations with respect to the classification task. Additionally, due to the disjoint nature of the tasks, the employed approach proved cumbersome to optimize, requiring testing of thousands of hyperparameter combinations and significant computational resources.To overcome the technical limitations highlighted above, we represent each drug as a graph (human interactome) with its targets as binary node features on the graph and formulate the problem as a graph classification task. To solve this task, inspired by the success of graph neural networks in graph classification problems, we use an end-to-end graph neural network model operating directly on the graphs, which learns drug representations to optimize model performance in the prediction of anticancer therapeutics. Results The proposed model outperforms the baseline approach in the anticancer therapeutic prediction task, achieving an F1 score of 67.99%±2.52% and an AUPR of 73.91%±3.49%. It is also shown that the model is able to capture knowledge of biological pathways to predict anticancer molecules based on the molecules’ effects on cancer-related pathways. Conclusions We introduce an end-to-end graph convolutional model to predict cancer-beating molecules within food. The introduced model outperforms the existing baseline approach, and shows interpretability, paving the way to the future of a personalized nutritional science approach allowing the development of nutrition strategies for cancer prevention and/or therapeutics.

In this paper, we introduce a network machine learning method to identify potential bioactive anti-COVID-19 molecules in foods based on their capacity to target the SARS-CoV-2-host gene-gene (protein-protein) interactome. Our analyses were performed using a supercomputing DreamLab App platform, harnessing the idle computational power of thousands of smartphones. Machine learning models were initially calibrated by demonstrating that the proposed method can predict anti-COVID-19 candidates among experimental and clinically approved drugs (5658 in total) targeting COVID-19 interactomics with the balanced classification accuracy of 80–85% in 5-fold cross-validated settings. This identified the most promising drug candidates that can be potentially “repurposed” against COVID-19 including common drugs used to combat cardiovascular and metabolic disorders, such as simvastatin, atorvastatin and metformin. A database of 7694 bioactive food-based molecules was run through the calibrated machine learning algorithm, which identified 52 biologically active molecules, from varied chemical classes, including flavonoids, terpenoids, coumarins and indoles predicted to target SARS-CoV-2-host interactome networks. This in turn was used to construct a “food map” with the theoretical anti-COVID-19 potential of each ingredient estimated based on the diversity and relative levels of candidate compounds with antiviral properties. We expect this in silico predicted food map to play an important role in future clinical studies of precision nutrition interventions against COVID-19 and other viral diseases. Supplementary Information The online version contains supplementary material available at 10.1186/s40246-020-00297-x.

In this paper, we introduce a network machine learning method to identify potential bioactive anti-COVID-19 molecules in foods based on their capacity to target the SARS-CoV-2-host gene-gene (protein-protein) interactome. Our experiments were run using a supercomputing DreamLab App platform, harnessing the idle computational power of thousands of smartphones. Machine learning models were initially calibrated by demonstrating that the proposed method can predict anti-COVID-19 candidates among experimental and clinically approved drugs (5658 in total) targeting COVID-19 interactomics with the balanced classification accuracy of 80-85% in 5-fold cross-validated settings. This identified the most promising drug candidates that can be potentially “repurposed” against COVID-19 including common drugs used to combat cardiovascular and metabolic disorders, such as simvastatin, atorvastatin and metformin. A database of 7694 bioactive food-based molecules was run through the calibrated machine-learning algorithm, which identified 52 biologically active molecules, from varied chemical classes, including flavonoids, terpenoids, coumarins and indoles predicted to target SARS-CoV-2-host interactome networks. This in turn was used to construct a “food map” with the theoretical anti-COVID-19 potential of each ingredient estimated based on the diversity and relative levels of candidate compounds with antiviral properties. We expect this in-silico predicted food map to play an important role in future clinical studies of precision nutrition interventions against COVID-19 and other viral diseases.

Context: The recent increase in accidents, mishaps or road accidents in urban systems with metropolitan characteristics has caused concern in the authorities responsible for planning the issue of mobility and transport subsystems. Indeed, there is convergence that the occurrence of this type of events is away from purely stochastic factors, but are the result of anomalies associated with the intrasystemic interaction of the vehicle, the user and the road. In this sense, the objective of this work is to determine through systemic analysis the components that are causing entropy in the second most important metropolis in Mexico. Method: In this analysis the precepts of systems theory are used; in such a way that through the tringulation of data obtained in situ and solved documentarily the causal components of intrasystemic entropy are determined. To do this, a modified derivation of the Pressure-State-Response model that identifies homeostasis in the urban system is elaborated. Results: The high exposure rates force the user to occupy the road subsystem for long periods of time, which triggers voluntary and involuntary human errors complemented by the lax requirements for obtaining driving licenses. From here, the components that produce accidents include in the road part the pavements in poor condition, absence of signaling, poor design of intersections, among others; in the vehicle part, mechanical failures due to the useful life of the internal components, flexible regulatory frameworks, and other; in the part of the user for breach of the regulations, physiological factors among others. Conclusions: From the systemic analysis, mobility is a subject of valuable study to detect the imbalances in the trinomial Vehicle-User-Road (V-C-U), which lead us to generate preventive and corrective measures that suppress metropolitan accidents, morbidity and mortality in the metropolis; or in our terms to reduce entropy levels in the system.

Introduction The only curative treatment for severe aplastic anemia in children is allogenic stem cell transplantation, but only few patients have a matched related or unrelated donor. Haploidentical stem cell transplantation (haplo-SCT) using bone marrow (BM) and peripheral blood stem cells (PBSC) has been recently described as effective and safe. In this study, we retrospectively describe the outcome of nine pediatric patients who underwent haplo-SCT using only PBSC. Patients and methods The father was the selected donor for seven of the nine patients. Donor specific anti-HLA antibodies were ruled out. Stem cells mobilization was performed with filgrastim 10 mcg/kg/d for five days, and CD34+ were recollected by peripheral blood apheresis on day 0. The conditioning regimen consisted on rabbit anti-thymocyte globulin 2.5 mg/kg/d on days -7, -6, -5, and -4, and cyclophosphamide 50 mg/kg/d on days -3 and -2. We used cyclophosphamide 50 mg/kg/d on days +3 and +4, tacrolimus and mycophenolic acid as graft versus host disease prophylaxis. Results The median follow up was 253 days (range 45-765 days). The median infused CD34+ was 10 × 10^6/kg (range 2.7 to 43 × 10^6/kg). The median myeloid engraftment was day +15 (range 11-30 days), and median platelet engraftment was day +16 (range 12-30 days). In eight of the nine patients, a sustained graft was achieved. One patient never achieved platelet engraftment and died because of cytomegalovirus infection. There was not treatment related toxicity reported. None of the patients had GVHD. The overall survival up to date is 88.8%. The eight surviving patients remain free of transfusions. Conclusions Haplo-SCT could be established as first line treatment when there is no matched related or unrelated donor. According to this short sample and previous reports, PBSC is a feasible option to be effectively used as only source of stem cells.

Recent data indicate that up-to 30–40% of cancers can be prevented by dietary and lifestyle measures alone. Herein, we introduce a unique network-based machine learning platform to identify putative food-based cancer-beating molecules. These have been identified through their molecular biological network commonality with clinically approved anti-cancer therapies. A machine-learning algorithm of random walks on graphs (operating within the supercomputing DreamLab platform) was used to simulate drug actions on human interactome networks to obtain genome-wide activity profiles of 1962 approved drugs (199 of which were classified as “anti-cancer” with their primary indications). A supervised approach was employed to predict cancer-beating molecules using these ‘learned’ interactome activity profiles. The validated model performance predicted anti-cancer therapeutics with classification accuracy of 84–90%. A comprehensive database of 7962 bioactive molecules within foods was fed into the model, which predicted 110 cancer-beating molecules (defined by anti-cancer drug likeness threshold of >70%) with expected capacity comparable to clinically approved anti-cancer drugs from a variety of chemical classes including flavonoids, terpenoids, and polyphenols. This in turn was used to construct a ‘food map’ with anti-cancer potential of each ingredient defined by the number of cancer-beating molecules found therein. Our analysis underpins the design of next-generation cancer preventative and therapeutic nutrition strategies.

El manejo eficiente de carga es un elemento clave para un puerto marítimo pueda competir y proveer adecuados niveles de servicio a sus usuarios. El desempeño de un puerto depende del tiempo de permanencia de la nave, que está condicionado por la eficiencia en las operaciones de carga y descarga de las naves. En el patio, los contenedores son almacenados temporalmente para ser cargados a la nave o despachados a los usuarios externos con un alto impacto en los tiempos de atención de las naves. Este artículo propone una política para stacking de contenedores, considerando las características particulares de un terminal de contenedores en Chile. Para medir el desempeño de este procedimiento, se propone una cota superior para el número de despejes de un contenedor en función de la capacidad de los bloques. Se presentan resultados numéricos en comparación con la cota superior, mostrando un buen desempeño del procedimiento propuesto. Efficient cargo handling is a key element for a maritime port to compete and provide good service levels to its users. The performance of a port is related to ship-turnaround, which is conditioned by the ships loading and unloading operational efficiency. At the yard, containers are temporarily stacked in order to later either load them onto a ship or dispatch them to external users. Stacking has a strong impact on ships’ service times. This paper proposes a container stacking policy, considering the particular characteristics of a container terminal in Chile. In order to measure the performance of the procedure, an upper bound for the number of re-handles of containers is estimated as a function of the block’s capacity. Numerical results are provided in comparison to an upper bound, and a good performance by the proposed procedure is demonstrated.

El uso de medios electrónicos en casi todas las esferas de la vida, ha llevado a los individuos a cambiar la percepción de la realidad, lo que implica la creación de nuevos conceptos y formas de explicar los procesos de comunicación y su impacto en las organizaciones. La presente investigación explora el uso racional y ético del Internet y cómo impacta en la competitividad de las organizaciones, utilizando cuestionarios aplicados a universitarios. Esta investigación arroja una ligera correlación entre el uso racional y la ética con respecto a la competitividad, por lo que no se descarta realizar una investigación posterior que dé continuidad para saber concluyentemente si existe tal correlación.

Background The aim of this study was to evaluate the results of video-assisted mediastinoscopic lymphadenectomy (VAMLA) for staging of non-small cell lung cancer (NSCLC). Methods This was a prospective observational study of all consecutive VAMLAs performed from January 2010 to April 2015 for staging NSCLC. For left lung cancers, extended cervical videomediastinoscopy was added to explore the subaortic and paraaortic nodes. Patients with negative VAMLA results underwent tumor resection and lymphadenectomy of the remaining nodes. Those with N2–3 disease underwent chemoradiation. The rate of unsuspected pathologic (p)N2–3 was analyzed in the global series and in the subgroups of patients according to their nodal status diagnosed by imaging and metabolic techniques. Results One hundred sixty VAMLAs were performed for staging NSCLC (138 tumors were clinical (c)N0-1 based on imaging techniques). The rate of unsuspected N2–3 disease was 18% for the whole series: 40.7% for cN1, 22.2% for cN0 and tumor size greater than or equal to 3 cm, and 6.4% for cN0 and tumor size less than 3 cm. Staging values were sensitivity, 0.96 (95% confidence interval [CI], 0.81–99.3); specificity, 1 (95% CI, 0.97–1); positive predictive value, 1 (95% CI, 0.87–1); negative predictive value, 0.99 (95% CI, 0.95–0.99); and diagnostic accuracy, 0.99 (95% CI, 0.96–0.99). The complication rate was 5.9%. Conclusions VAMLA is a feasible and highly accurate technique. The high rate of unsuspected mediastinal node disease diagnosed by VAMLA in patients with cN1 or cN0 disease and tumor size larger than 3 cm suggests that preresection lymphadenectomies should be included in the current staging algorithms.

Melting gels are hybrid gels that have the ability to soften and flow at around 100°C for some combinations of mono- and di-substituted alkoxysiloxanes, where substitutions are either all aromatic or all aliphatic. In this study, melting gels were prepared using phenyltriethoxysilane (PhTES) and dimethyldiethoxysilane (DMDES), meaning both an aromatic and aliphatic substitution. Differential scanning calorimetry was performed to identify glass-transition temperatures, and thermal gravimetric analysis coupled with differential thermal analysis (TGA-DTA) was performed to measure weight loss. The glass-transition temperatures (Tg) ranged from −61°C to +5.6°C, which are between the values in the methyl only system, where all Tg values are less than 0°C, and those values in the phenyl only system, where Tg values are greater than 0°C. The Tg decreased with an increase in the DMDES fraction. Below 450°C, the gels lost little weight, but around 600°C there was a drop in weight. This temperature is lower than the temperature for gels prepared with only aromatic substitutions, but higher than that for gels prepared with only aliphatic substitutions. Final heat treatment was carried out at 150°C for the gel with 80%PhTES-20%DMDES (in mol%), and the consolidation temperature increased with increasing DMDES content to 205°C for the gel with 50%PhTES-50%DMDES. After this heat treatment, the melting gels no longer soften.

Bone disease in rheumatoid arthritis (RA) is a complex phenomenon where genetic risk factors have been partially evaluated. The system formed by receptor activator for nuclear factor-κB (RANK), receptor activator for nuclear factor-κB ligand (RANKL), and osteoprotegerin (OPG): RANK/RANKL/OPG is a crucial molecular pathway for coupling between osteoblasts and osteoclasts, since OPG is able to inhibit osteoclast differentiation and activation. We aim to evaluate the association between SNPs C950T (rs2073617), C209T (rs3134069), T245G (rs3134070) in theTNFRSF11B(OPG) gene, and osteoporosis in RA. We included 81 women with RA and 52 healthy subjects in a cross-sectional study, genotyped them, and measured bone mineral density (BMD) at the lumbar spine and the femoral neck. Mean age in RA was50±12with disease duration of12±8years. According to BMD results, 23 (33.3%) were normal and 46 (66.7%) had osteopenia/osteoporosis. We found a higher prevalence of C allele for C950T SNP in RA. Polymorphisms C209T and T245G did not reach statistical significance in allele distribution. Further studies including patients from other regions of Latin America with a multicenter design to increase the sample size are required to confirm our findings and elucidate if C950T SNP could be associated with osteoporosis in RA.

Objectives The objectives of this study were to analyse the frequency of gene mutations associated with antitubercular drug resistance in clinical samples from the population of Jalisco State (Mexico) and to evaluate the genetic variability of Mycobacterium tuberculosis and multidrug-resistant (MDR) M. tuberculosis strains to describe the frequency of various families. Methods Clinical isolates of M. tuberculosis obtained from Jalisco State were analysed. Isolates were subjected to drug susceptibility testing, and mutations were characterised by sequencing, followed by genotyping using spoligotyping and mycobacterial interspersed repetitive units–variable-number of tandem repeats (MIRU-VNTR). Moreover, the prevalence of mutations was analysed by phylogenetic lineages. Results Resistant strains were analysed by sequencing of katG , inhA and rpoB genes to determine the presence of mutations associated with isoniazid and rifampicin resistance. In MDR, monoresistant and polyresistant isolates, mutations were found in 17 (54.84%) of 31 strains. Spoligotyping identified six different strain lineages [T1 (25.40%), H3 (7.94%), MANU (4.76%), X1 (3.17%), EAI5 (1.59%) and LAM1 (1.59%)], with the remaining strains identified as orphans. In additional tree-based identification, a dendrogram of spoligotype patterns generated five different similarity clusters. When combining 24-loci MIRU-VNTR and spoligotyping approaches, the results shows that there is no cluster formation, indicating low transmission of the samples. Conclusions This study using spoligotyping and MIRU-VNTR showed that the analysed strains were not related to each other since no two identical strains were found. Families with the highest prevalence in the study were orphans followed by T family.

Objective. There is a lack of information about the genotype frequencies of IL-6 −174G/C and −572G/C polymorphisms in Mexicans with rheumatoid arthritis (RA). Therefore, the aim of this study was to evaluate the association of the IL-6 −174G/C and −572G/C polymorphisms in Mexican mestizo with RA.Methods. We included 137 patients with RA and 102 healthy controls. Patients were assessed for clinical characteristics. IL-6 −174G/C and −572G/C polymorphisms were genotyped using PCR-RFLP analysis. Allele and genotype frequencies and the Hardy-Weinberg equilibrium were computed. Odds ratios (ORs) were computed to identify the risk for RA associated with the presence of GG genotype in comparison with the GC or CC genotypes.Results. The genotype −174GG occurred at a higher frequency in cases and controls (77.4% versus 78.4%,P=0.845). We found similar results for the genotype −572GG (54% in patients versus 60.8% in controls,P=0.295).Conclusions. This is the first study to evaluate the association of −174G/C and −572G/C polymorphisms of the IL-6 gene with RA in Mexican mestizo patients. These two polymorphisms were not associated with RA in the studied sample. Additional studies are required to evaluate if these IL-6 polymorphisms have relevance to the development of more severe disease.

The increase in the number of renewable energy generating facilities has transformed the electricity distribution network into a Distributed Generation (DG) system. This has given rise to a new monitoring scenario for protective devices already installed across radial distribution networks, which may execute unexpected and inappropriate protective actions that cause loss of supply to consumers. These devices are affected by the new condition of the electricity distribution network, as network currents vary. A common practice is to use electrical impedance-based fault localizers. This work describes a novel method for fault detection in radial networks with DG, which does not require knowing the electrical impedances of the lines that compose the network. The method only requires input data regarding the short circuit currents provided by the main feeder and the DG units in the area in which a fault has occurred. This information is sufficient to allow the area where the fault lies to be identified. The underlying idea is that the measurement of the current at two points provides a binocular view of the fault, thus allowing its location to be pinpointed. The method was tested using the IEEE 13-node test feeder system, locating different types of faults in different areas of a simulated radial network. DOI: http://dx.doi.org/10.5755/j01.eie.22.2.7226