Impacto del crecimiento urbano en la transformación de los espacios públicos en el distrito de San Borja

A lo largo de los años se les ha atribuido a los espacios públicos transformaciones de acuerdo con el crecimiento de su población y como este agente ha sido el factor principal de la sostenibilidad de estos lugares. Por consiguiente, esta investigación tiene como objeto principal determinar de qué manera el impacta el crecimiento urbano sobre transformación de los espacios públicos en San Borja, que apuesta por el desarrollo de grandes espacios verdes para el bienestar de su población. Con ello evaluar la disponibilidad y uso de estos grandes espacios destinados para su población y ver como el crecimiento urbano ha cambiado las funciones principales de estos mismos para que junto a las perspectivas de los especialistas mostrar un plan de criterios para la recuperación del verdadero concepto de espacios públicos. Esta investigación parte de una teoría general “Teoría de la Performance” de Víctor Turner, que analiza el naturalismo la actividad humana orgánica y la experiencia vivida en los espacios urbanos tomando en cuenta que cada participante tiene un rol y este altera a los escenarios de manera conjunta. La “Teoría de la esfera Pública” de Arendt referido a la noción como ámbito abierto de debate. El planteamiento teórico empleado se sostiene en una perspectiva a partir del usuario, desde el ordenamiento espacial y los patrones sociales estudiando el espacio vivencial, la construcción de lo social y la calidad de vida urbana. Se realizaron recorridos de observación de interacción/integración/calidad de vida durante 2 días para poder analizar cada espacio uno de los 5 espacios públicos, se entrevistaron a 2 especialistas urbanistas. La validación de los instrumentos se elaboró por medio de juicio de expertos. La recopilación de datos se obtuvo a través una ficha documentaria basada en datos de la INEI y el IMP, fichas de observación por cada muestra y las guías de entrevistas con 12 ítems, llegando a evidenciar que si existe impacto del crecimiento urbano en la transformación de los espacios públicos en el aspecto social. Los resultados alcanzados posibilitan comprender cómo los espacios públicos están siendo empleados desde una perspectiva social. Se pudo encontrar que la calidad de vida urbana de la población puede ser mejorada a través de diversos vínculos entre dimensiones del ecosistema y aspectos de la calidad de vida urbana tales como: disfrute del espacio, distracción, diversión, civismo

G protein-coupled kisspeptin receptor induces metabolic reprograming and tumorigenesis in estrogen receptor-negative breast cancer

Triple-negative breast cancer (TNBC) is a highly metastatic and deadly disease. TNBC tumors lack estrogen receptor (ERα), progesterone receptor (PR), and HER2 (ErbB2) and exhibit increased glutamine metabolism, a requirement for tumor growth. The G protein-coupled kisspeptin receptor (KISS1R) is highly expressed in patient TNBC tumors and promotes malignant transformation of breast epithelial cells. This study found that TNBC patients displayed elevated plasma kisspeptin levels compared with healthy subjects. It also provides the first evidence that in addition to promoting tumor growth and metastasis in vivo, KISS1R-induced glutamine dependence of tumors. In addition, tracer-based metabolomics analyses revealed that KISS1R promoted glutaminolysis and nucleotide biosynthesis by increasing c-Myc and glutaminase levels, key regulators of glutamine metabolism. Overall, this study establishes KISS1R as a novel regulator of TNBC metabolism and metastasis, suggesting that targeting KISS1R could have therapeutic potential in the treatment of TNBC

A Machine Learning Approach for Using the Postmortem Skin Microbiome to Estimate the Postmortem Interval

Research on the human microbiome, the microbiota that live in, on, and around the human person, has revolutionized our understanding of the complex interactions between microbial life and human health and disease. The microbiome may also provide a valuable tool in forensic death investigations by helping to reveal the postmortem interval (PMI) of a decedent that is discovered after an unknown amount of time since death. Current methods of estimating PMI for cadavers discovered in uncontrolled, unstudied environments have substantial limitations, some of which may be overcome through the use of microbial indicators. In this project, we sampled the microbiomes of decomposing human cadavers, focusing on the skin microbiota found in the nasal and ear canals. We then developed several models of statistical regression to establish an algorithm for predicting the PMI of microbial samples. We found that the complete data set, rather than a curated list of indicator species, was preferred for training the regressor. We further found that genus and family, rather than species, are the most informative taxonomic levels. Finally, we developed a k-nearest- neighbor regressor, tuned with the entire data set from all nasal and ear samples, that predicts the PMI of unknown samples with an average error of ±55 accumulated degree days (ADD). This study outlines a machine learning approach for the use of necrobiome data in the prediction of the PMI and thereby provides a successful proof-of- concept that skin microbiota is a promising tool in forensic death investigations

Marketing sensorial y el comportamiento de compra de los clientes de la tienda Tamisis ante el COVID-19 Trujillo, 2020

La presente tesis buscó determinar si existe relación entre el marketing sensorial y comportamiento de compra de los clientes de la tienda Tamisis ante el COVID-19 Trujillo, 2020. Entonces, se desarrolló una investigación que no es experimental, de estudio transversal y enfocado cuantitativamente, considerando a 420 clientes como población a partir de su reapertura en agosto hasta tres meses después del 2020, donde se obtuvo 201 individuos como muestra, los cuales contestaron la encuesta en escala de Likert que sirvió para medir las variables, obteniendo como resultados un coeficiente de Spearman de 0.622, afirmando así que se relacionan las variables. Por último, se concluye aceptando la hipótesis alterna, existiendo una relación entre la variable independiente y dependiente, siendo esta positiva y significativa. Además, hay relación entre la dimensión táctil y comportamiento de compra, con una significancia de .000 < 0.05 y un coeficiente de correlación 0.686. Por lo que, los clientes están a gusto con la experiencia táctil que les brinda la tienda, permitiéndoles sentir las prendas y saber su buena calidad para decidir comprar en esta.This thesis sought to determine whether there is a relationship between sensory marketing and consumer buying behavior among Tamisis' store customers in the face of COVID 19, in Trujillo, 2020. Hence, a non-experimental, cross-sectional and quantitatively focused research was developed, considering 420 customers as population from its reopening in August until three months after 2020, where 201 individuals were obtained as a sample, who answered the survey in Lickert scale that served to measure the variables, obtaining as results a Spearman coefficient of 0.622, thus affirming that the variables are related. Finally, we conclude by accepting the alternative hypothesis, that there is a relationship between the independent and dependent variables, which is positive and significant. In addition, there is a relationship between the tactile dimension and consumer buying behavior, with a significance of .000 < 0.05 and a correlation coefficient of 0.686. Therefore, customers are comfortable with the tactile experience provided by the store, allowing them to feel the garments and know their good quality in order to decide to purchase from the store

KISS1/KISS1R in Cancer: Friend or Foe?

The KISS1 gene encodes KISS1, a protein that is rapidly processed in serum into smaller but biologically active peptides called kisspeptins (KPs). KISS1 and the KPs signal via the G-protein coupled receptor KISS1R. While KISS1 and KPs are recognized as potent positive regulators of the reproductive neuroendocrine axis in mammals, the first reported role for KISS1 was that of metastasis suppression in melanoma. Since then, it has become apparent that KISS1, KPs, and KISS1R regulate the development and progression of several cancers but interestingly, while these molecules act as suppressors of tumorigenesis and metastasis in many cancers, in breast and liver cancer they function as promoters. Thus, they join a small but growing number of molecules that exhibit dual roles in cancer highlighting the importance of studying cancer in context. Given their roles, KISS1, KPs and KISS1R represent important molecules in the development of novel therapies and/or as prognostic markers in treating cancer. However, getting to that point requires a detailed understanding of the relationship between these molecules and different cancers. The purpose of this review is therefore to highlight and discuss the clinical studies that have begun describing this relationship in varying cancer types including breast, liver, pancreatic, colorectal, bladder, and ovarian. An emerging theme from the reviewed studies is that the relationship between these molecules and a given cancer is complex and affected by many factors such as the micro-environment and steroid receptor status of the cancer cell. Our review and discussion of these important clinical studies should serve as a valuable resource in the successful development of future clinical studies

A Machine Learning Approach for Using the Postmortem Skin Microbiome to Estimate the Postmortem Interval.

Research on the human microbiome, the microbiota that live in, on, and around the human person, has revolutionized our understanding of the complex interactions between microbial life and human health and disease. The microbiome may also provide a valuable tool in forensic death investigations by helping to reveal the postmortem interval (PMI) of a decedent that is discovered after an unknown amount of time since death. Current methods of estimating PMI for cadavers discovered in uncontrolled, unstudied environments have substantial limitations, some of which may be overcome through the use of microbial indicators. In this project, we sampled the microbiomes of decomposing human cadavers, focusing on the skin microbiota found in the nasal and ear canals. We then developed several models of statistical regression to establish an algorithm for predicting the PMI of microbial samples. We found that the complete data set, rather than a curated list of indicator species, was preferred for training the regressor. We further found that genus and family, rather than species, are the most informative taxonomic levels. Finally, we developed a k-nearest- neighbor regressor, tuned with the entire data set from all nasal and ear samples, that predicts the PMI of unknown samples with an average error of ±55 accumulated degree days (ADD). This study outlines a machine learning approach for the use of necrobiome data in the prediction of the PMI and thereby provides a successful proof-of- concept that skin microbiota is a promising tool in forensic death investigations

The ear equivalent of Table 3.

<p>The ear equivalent of <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0167370#pone.0167370.t003" target="_blank">Table 3</a>.</p

Summary of data matrix dimensions for joint data (swabs for both ear and nose).

<p>The number of rows in each table is 67 for all data, and the number of columns is the number of organisms, as shown. We also provide the logarithm of the number of columns in each dataset, for later reference.</p

Some select high performing organisms from several taxa, with ADD plotted against abundance.

<p>The vertical axis is normalized for each organism so that the relative abundances are on a similar scale.</p