Consecutive renal biopsy in a cohort of patients with lupus nephritis of the Colombian Caribbean

Background: Renal biopsy is the gold standard for the diagnosis and classification of lupus nephritis (LN). However, a consecutive biopsy can predict the clinical course and optimize the therapeutic strategies. Objectives: To compare the histopathological findings with clinical responses. Patients and Methods: Thirty patients with active LN were included. Renal biopsies were performed at the time of diagnosis and subsequently under clinical criteria according to consensus of Spanish Society of Nephrology. The response to treatment was defined as complete response, partial responder or non-responder. The histological change in second biopsy towards LN classes I, II or III/IV-C was defined as histological response (HR). Results: In initial renal biopsy, 28 (93%) patients showed proliferative LN; III-A or A/C (n; 7), IV-A or A/C (n: 19) and mixed; III+IV/V (n; 2). LN class V was presented in two cases. The clinical response was; complete response (10%), partial response (20%), and non-response (70%). HR was manifested in 37% and non-histologic response in 63% of patients. Around 33% of patients with complete response/partial response showed active lesions in the consecutive renal biopsy. Conclusions: In Colombian Caribbean, LN is aggressive and refractory to treatment. The consecutive renal biopsy allowed to demonstrate the persistence of the activity of the lesion in almost half of the patients, which may provide additional information to create better response criteria. The consecutive renal biopsy is a tool that allows improving the evaluation of the response to treatment in the LN

El impacto de la pandemia del COVID-19 en la educación médica: adaptabilidad y experiencia con enseñanza a distancia de la Sociedad Médica Peruano Americana

The COVID-19 pandemic had a significant impact on medical care and medical education in Peru.  In response, the Peruvian American Medical Society (PAMS), a charitable medical organization based in the USA, pursued its medical and educational missions in Peru by adopting virtual learning technology. We developed closer collaborative relationships with several medical schools and the Peruvian Association of Medical Schools (ASPEFAM) while offering a faculty panel of twenty-four members to provide lectures and multidisciplinary webinars in Spanish. We conducted 19 webinars including COVID -19 and non-COVID-19 related topics that over the last two years attracted 14,489 participants from 23 countries. They were the foundation for twenty publications in Peruvian medical journals. Our clinical investigations competition was positively received as was our pilot project on research mentorship. The COVID -19 pandemic had a positive effect on the educational mission of PAMS in Peru.La pandemia del COVID-19 tuvo un impacto significativo en el cuidado y la educación médicos en el Perú. En respuesta, la Sociedad Médica Peruano Americana (PAMS), una organización médica benéfica con sede en los EE. UU., adoptó sus misiones médicas y educativas en Perú usando estrategias virtuales. Desarrollamos colaboración con varias facultades de medicina y la Asociación Peruana de Facultades de Medicina (ASPEFAM) y ofrecimos un panel de veinte y cuatro miembros para brindar conferencias y seminarios multidisciplinarios en español. Hicimos 19 seminarios, incluyendo temas relacionados y no relacionados al COVID-19, que en los últimos dos años atrajo a 14 489 participantes de 23 países. Ellas fueron la base de 20 publicaciones en revistas médicas peruanas. Nuestro concurso de investigaciones clínicas y nuestro proyecto piloto de mentoría de investigación fueron recibidos positivamente. La pandemia del COVID-19 tuvo un efecto positivo en la misión educativa de PAMS en Perú

The Tree Biodiversity Network (BIOTREE-NET): prospects for biodiversity research and conservation in the Neotropics

Biodiversity research and conservation efforts in the tropics are hindered by the lack of knowledge of the assemblages found there, with many species undescribed or poorly known. Our initiative, the Tree Biodiversity Network (BIOTREE-NET), aims to address this problem by assembling georeferenced data from a wide range of sources, making these data easily accessible and easily queried, and promoting data sharing. The database (GIVD ID NA-00-002) currently comprises ca. 50,000 tree records of ca. 5,000 species (230 in the IUCN Red List) from \u3e2,000 forest plots in 11 countries. The focus is on trees because of their pivotal role in tropical forest ecosystems (which contain most of the world\u27s biodiversity) in terms of ecosystem function, carbon storage and effects on other species. BIOTREE-NET currently focuses on southern Mexico and Central America, but we aim to expand coverage to other parts of tropical America. The database is relational, comprising 12 linked data tables. We summarise its structure and contents. Key tables contain data on forest plots (including size, location and date(s) sampled), individual trees (including diameter, when available, and both recorded and standardised species name), species (including biological traits of each species) and the researchers who collected the data. Many types of queries are facilitated and species distribution modelling is enabled. Examining the data in BIOTREE-NET to date, we found an uneven distribution of data in space and across biomes, reflecting the general state of knowledge of the tropics. More than 90% of the data were collected since 1990 and plot size varies widely, but with most less than one hectare in size. A wide range of minimum sizes is used to define a \u27tree\u27. The database helps to identify gaps that need filling by further data collection and collation. The data can be publicly accessed through a web application at http://portal.biotreenet.com. Researchers are invited and encouraged to contribute data to BIOTREE-NET

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

La Red Internacional de Inventarios Forestales (BIOTREE-NET) en Mesoamérica: avances, retos y perspectivas futuras

Conservation efforts in Neotropical regions are often hindered by lack of data, since for many species there is a vacuum of information, and many species have not even been described yet. The International Network of Forest Inventory Plots (BIOTREE-NET) gathers and facilitates access to tree data from forest inventory plots in Mesoamerica, while encouraging data exchange between researchers, managers and conservationists. The information is organised and standardised into a single database that includes spatially explicit data. This article describes the scope and objectives of the network, its progress, and the challenges and future perspectives. The database includes above 50000 tree records of over 5000 species from more than 2000 plots distributed from southern Mexico through to Panama. Information is heterogeneous, both in nature and shape, as well as in the geographical coverage of inventory plots. The database has a relational structure, with 12 inter-connected tables that include information about plots, species names, dbh, and functional attributes of trees. A new system that corrects typographical errors and achieves taxonomic and nomenclatural standardization was developed using The Plant List (http://theplantlist.org/) as reference. Species distribution models have been computed for around 1700 species using different methods, and they will be publicly accessible through the web site in the future (http://portal.biotreenet.com). Although BIOTREE-NET has contributed to the development of improved species distribution models, its main potential lies, in our opinion, in studies at the community level. Finally, we emphasise the need to expand the network and encourage researchers willing to share data and to join the network and contribute to the generation of further knowledge about forest biodiversity in Neotropical regions

Mobile Stress Interventions: Mechanisms and Implications

According to the American Psychological Association, 49% of the U.S. population suffers from chronic, daily stress. Chronic stress also has significant long-term behavioral and physical health consequences, including an increased risk of cardiovascular disease, cancer, anxiety and depression. In this work, we examine how smartphones and mobile sensing can help address the short and long-term consequences of stress. First, we define a conceptual framework for thinking about the interaction between real-time pervasive devices and the real-time physiology of stress. Second, using this framework, we propose a set of guidelines or requirements for pervasive just-in-time intervention (JITI) systems. Third, based on these guidelines, we specify a three-layer software/hardware architecture to support just-in-time interventions for stress. Several themes emerge from this discussion, including the need for robust and accurate context-sensitive forecasting of future stress. Fourthly we describe our experiments and results demonstrating the feasibility of forecasting future stress from current measurements and the effectiveness of the intervention management approach. Finally we discuss the broader implications of mobile-based stress interventions. Whilst this work focuses on chronic stress, we believe the ideas presented are generalizable to other types of just-in-time pervasive interventions

Preventer, A Selection Mechanism For Just-In-Time Preventive Interventions

This paper examines just-in-time adaptive interventions (JITAIs) for stress, a pervasive and affective computing application with significant implications for long-term health and quality of life. We discuss fundamental components needed to enabling JITAIs based for one kind of affect data stress. Chronic stress has significant long-term behavioral and physical health consequences, including an increased risk of cardiovascular disease, cancer, anxiety and depression. This paper conducts post-hoc experiments and simulations to demonstrate feasibility of both real-time stress forecasting and stress intervention adaptation and optimization. Using physiological data collected by ten individuals in the natural environment for one week, we show 1) that simple Hidden Markov Models (HMMs) can be used to forecast physiological measures of stress with up to 3 minutes in advance; and 2) Q-Learning (QL) combined with eligibility traces could be used by an affective computing system to adapt and deliver any number and type of interventions in response to changes in affect. Our hope is that this work will take us one step closer to using pervasive devices to assist in the daily management of chronic stress and other affect-related challenges

A Vehicular Crowdsensing Market for AVs

The rapid adoption of the vehicles and their on-board sensors as a primary means of transportation make them natural candidates for the outsourcing of data collection. However, vehicles mobility patterns tend to cluster into specific regions such as highways and popular roads, that makes their utilization difficult for data collection in isolated regions with low density traffic. We tackle this problem by proposing a probabilistic incentive mechanism for Vehicular Crowdsensing (VCS) that encourages vehicles to deviate from their pre-planned trajectories in order to visit and collect data from the isolated places. Our proposed framework is able to handle asynchronous vehicles. Also, vehicles consider the traffic holistically to find more profitable routes. By using a realistic vehicular movement data set (UBER movement), open-street maps (OSM) and SUMO vehicular traffic simulator, we show our algorithm significantly outperforms traditional approaches for trajectory generation in terms of spatial and temporal coverage, road utilization, and average participant utility

A Location-Based Incentive Algorithm For Consecutive Crowd Sensing Tasks

Crowd Sensing (CS) is a sensing paradigm that takes advantage from the increasing use of mobile smart devices and their capabilities for sensing and computation. In this paper, we present an incentive mechanism for encourage user participation in schemes of sensing that requires consecutive and regular sampling. The proposed mechanism uses a recurrent reverse auction that no only takes into account the sample price, but also the participants location. We show that our mechanism achieves an optimal budget utilization while guarantees area coverage and a sufficient number of participants in every round